Currently, entire world is crumbled due to COVID-19 caused by novel SARS-CoV-2. Globally, over 5 million people are infected by SARS-CoV-2 with 6% fatality rate. The surface spike (S) protein plays a key role in the pathogenesis of SARS-CoV-2 by mediating viral entry through human angiotensin converting enzyme 2 (hACE2) receptors on the host cell and there is a big global race to find viral neutralizing antibodies and vaccine against S protein of SARS-CoV-2. Since SARS-CoV-2 evolved into 10 different clades in a very short span, a study on sipke protein mutation is essential to have effective vaccine coverage globally. Based on the mutation analysis of S protein from 166 Indian SARS-CoV-2 genome, a total of 40 different SNPs comprising of 14 synonymous and 26 non-synonymous mutations were observed, and notably, Indian S protein diverged into two major clusters, D614 and G614, with 11 different types. Majority of Indian strains fall in A2a and O clusters. Alarmingly, we have observed six SNPs at RBD and notably two of them at RBM (S438F and S494P). S494P SNP, similar to Bat–SARS like-CoV, may indicate a low ACE2 binding affinity. Interestingly 38% of Indian strains harbor a characteristic D614G SNP which was found predominantly in A2a cluster, mostly comprising USA and European strains with high disease severity. The association of disease severity with D614G SNP is well-correlated in states with high death rate except Maharashtra. Notably, more than 50% of D614G mutation were observed in Northern part of India and 14% in Southern part but not in Kerala and Tamil Nadu strains. Highly conserved motif, D614 (608-VAVLYQDVNCT-618) in upstream and also few downstream, of S1/S2 furin cleavage site may indicate specific key role in efficient interaction with host proteases in pathogenesis. Further studies are warranted to clarify the impact of SD614G SNP association to disease severity . Interestingly, C2367T (Y789Y) synonymous SNP is observed in 37% of Indian strains and notably similar SNPs with degeneracy bases were observed which is a key indication for the possibility of misdiagnosis by Real-Time PCR and revised strategies are needed for the precise diagnosis. Circulation of high number of signature SNPs [D614G and C2367T (Y789Y)] in certain states may be an early indication of emergence of community transmission in India. Further large genome sequence data from India will aid in deep understanding on the diversity of circulating SASR-Cov-2 and its impact on disease severity, origin of imported cases to India, community spread, effect on diagnosis and vaccine coverage.

Causative agent of the viral pneumonia outbreak in the World identified as SARS-CoV2 leads to a severe respiratory illness like SARS and MERS. The pathogen spreading has turned into a pandemic dissemination and increased the mortality rate. Therefore, useful information is urgently necessary for effective control of the disease. Our study shows the existence of unvarying sequence with no mutation, including ORF1ab regions in 134 high-quality filtered genome sequences of SARS-CoV2 downloaded from the GISAID database. We have detected this sequence stability by using MAUVE analysis and pairwise alignment with Global Needleman Wunsch algorithm for each two different sequences, reciprocally. They also confirmed all these results were also with the Clustal W analysis. The first 6500 bp including ORF1ab region is an unvarying sequence. According to the highest TM-score of predicted protein structure analysis, the results showed it is very similar to spike protein of feline infectious peritonitis virus strain UU4 (PDB 6JX7) depending on amino acid sequences encoded by this unvarying region, and N-acetyl-D-glucosamine is the ligand of this protein. These results have confirmed that N-acetyl-D-glucosamine could play an important role in controlling of SARS-CoV-2. Also, our molecular docking analysis data supports a strong protein-ligand interaction of N-acetyl-D-glucosamine with spike receptor-binding domain bound with ACE2 (PDB 6M0J) and RNA-binding domain of nucleocapsid phosphoprotein (PDB 6WKP) from SARS CoV-2. Therefore, binding of N-acetyl-D-glucosamine to these proteins could inhibit SARS CoV-2’s replication. In the present work, we have suggested providing a repurposing compound for further in vitro and in vivo studies and new insights for ongoing clinical treatments as a new strategy to control of SARS-CoV-2 infections.

Recent reports suggest that the clinical course of coronavirus disease 2019 (COVID-19) in previously healthy children is usually milder as compared to adults. However, children with comorbid conditions such as diabetes are at increased risk of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as well as morbidity and mortality due to COVID-19. Experience in adults with diabetes shows that they are prone to faster metabolic decompensation, develop diabetes-related complications, and have a poor prognosis when hospitalized with COVID-19. Data on children are limited. The aim of this mini-review is to discuss the possible risks to children and adolescents with diabetes during the current pandemic and the special considerations in management in those affected with COVID-19. The challenges for children who develop new-onset type 1 diabetes during the COVID-19 lockdown, especially in accessing healthcare, are also discussed.

Introduction: Due to the spread of SARS CoV-2 virus responsible for COVID-19 disease, there is an urgent need to analyse COVID-19 epidemic perception in Poland. This study aims to investigate social perception of coronavirus in the Internet media during the epidemic. It is a signal report highlighting the main issues in public perception and medical commutation in real time. Methods: We study the perception of COVID-19 epidemic in Polish society using quantitative analysis of its digital footprints on the Internet on platforms: Google, Twitter, YouTube, Wikipedia and electronic media represented by Event Registry, from January 2020 to 29.04.2020 (before and after official introduction to Poland on 04.03.20). We present trend analysis with a support of natural language processing techniques. Results: We identified seven temporal major clusters of interest on the topic COVID-19: 1) Chinese, 2) Italian, 3) Waiting, 4) Mitigations, 5) Social distancing and Lockdown, 6) Anti-crisis shield, 7) Restrictions releasing. There was an exponential increase of interest when the Polish government “declared war against disease” around 11/12.03.20 with a massive mitigation program. Later on, there was a decay in interest with additional phases related to social distancing and an anti-crisis legislation act with local peaks. We have found that declarations of mitigation strategies by the Polish prime minister or the minister of health gathered the highest attention of Internet users. So enacted or in force events do not affect interest to such extent. Traditional news agencies were ahead of social media (mainly Twitter) in dissemination of information. We have observed very weak or even negative correlations between a colloquial searching term 'antiviral mask' in Google, encyclopaedic definition in Wikipedia “SARS-CoV-2” as well official incidence series, implying different mechanisms governing the search for knowledge, panic related behaviour and actual risk of acquiring infection. Conclusions: Traditional and social media do not only reflect reality, but also create it. Risk perception in Poland is unrelated to actual physical risk of acquiring COVID-19. As traditional media are ahead of social media in time, we advise to choose traditional news media for a quick dissemination of information, however for a greater impact, social media should be used. Otherwise public information campaigns might have less impact on society than expected.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an etiologic agent of the respiratory disease in humans that is known as coronavirus disease 2019 (COVID19). The first outbreak of the disease was initially documented in Wuhan, Hubei Province, China in late December 2019 where people had experienced SARS pneumonia-like symptoms with unknown etiology. Since then it has been observed that COVID-19 positive patients have been showing mild to severe upper respiratory illness symptoms. The type of virus is known to make its transfer from animals to humans and for the concerned virus; researchers have claimed its origin from bat coronavirus at whole-genome level with a 96 % sequence identity. The COVID-19 virus is very contagious and communicable in nature and has been spread throughout the globe since its first outbreak in China. On March 9, 2020, WHO declared it as a Pandemic, and within a month it was already reported to have shown its presence in 213 countries and territories or areas. As of April 29, 2020, this novel virus infected 3,218,183 people and caused 228,029 mortalities worldwide with a variable mortality rate from 3-13 % across the planet and also varied by age and gender. Diagnosis of the disease is a key component in understanding and controlling the spread of the virus and several techniques have been devised including RT-PCR, ELISA, and sequencing-based approaches. To cure COVID-19 patients as of now we do not have proven to be a safe and effective treatment. Therapeutic options currently under investigation in various parts of the world. However, there are various effective therapeutic targets to repurpose the present antiviral therapy for developing potential interventions against SARS-CoV-2. Boosting the immune system can also help to prevent and spread of COVID-19 using various medication and exercises. In this review, our goal to summarize and discussed the present scientific advancements to fight against this novel pandemic.

Covid-19 has given a halt to all the activities in the world. Europe was most affected, followed by the United States of America. It has taken more than 350000 lives until now. In this study, we have assessed the severity of Covid-19 by analyzing the mortality rate of Covid-19 and other chronic diseases. The Covid-19 data and “death rate” data caused by other diseases were downloaded from the world health organization (WHO) website. A normalized method was used to see the mortality rate of Covid-19 in comparison to other diseases. The deaths caused by Covid-19 in April 2020 have overtaken the average number of deaths caused by Cancer, Cardiovascular diseases, and other diseases in Belgium, the United Kingdom (UK), Spain, France, and Ireland. Covid-19 was found to be strongly correlated with non-communicable respiratory diseases and Cancer with correlation coefficients 0.73 and 0.67 respectively. The severity of Covid-19 in the United States of America (USA) was moderate. The severity of Covid-19 in Asian countries was found to be low. Europe showed the highest diversity in the mortality rate of Covid-19. On average, except for a few European countries, Cardiovascular diseases, cancer, and non-communicable respiratory diseases were still more lethal and caused more deaths than Covid-19.

Background: There are no known medicines or vaccines to control the COVID-19 pandemic caused by SARS-CoV-2 (nCoV). Antiviral peptides are superior to conventional drugs and may also be effective against COVID-19. Hence, we investigated the SARS-CoV-2 Spike RBD (nCoV-RBD) that interacts with hACE2 for viral attachment and entry. Methods: Three strategies and bioinformatics approaches were employed to design potential nCoV-RBD - hACE2 interaction-blocking peptides that may restrict viral attachment and entry. Firstly, the key residues interacting with nCoV-RBD - hACE2 are identified and hACE2 sequence based peptides are designed. Second, peptides from five antibacterial peptide databases that block nCoV-RBD are identified; finally, a chimeric peptide design approach is used to design peptides that can bind to key nCoV-RBD residues. The final peptides are selected based on their physiochemical properties, numbers and positions of key residues binding, binding energy, and antiviral properties. Results: We found (i) three amino acid stretches in hACE2 interact with nCoV-RBD; (ii) effective peptides must bind to three key positions of nCoV-RBD: Gly485/Phe486/Asn487, Gln493, and Gln498/Thr500/Asn501; (iii) Phe486, Gln493, and Asn501 are critical residues; (iv) AC20 and AC23 derived from hACE2 may block two key critical positions; (iv) DBP6 identified from databases can block the three sites of the nCoV-RBD interacting with one critical position Gln498; (v) seven chimeric peptides were considered promising among which cnCoVP-3, cnCoVP-4, and cnCoVP-7 are the top three; and (vi) cnCoVP-4 meets all the criteria and is the best peptide. Conclusion: All the ten peptides need experimental validation for their therapeutic efficacy.

Reliable estimates of poplar plantations area are not available at the French national scale due to the unsuitability and low update rate of existing forest databases for this short-rotation species. While supervised classification methods have been shown to be highly accurate in mapping forest cover from remotely sensed images, their performance depends to a great extent on the labelled samples used to build the models. In addition to their high acquisition cost, such samples are often scarce and not fully representative of the variability in class distributions. Consequently, when classification models are applied to large areas with high intra-class variance, they generally yield poor accuracies. In this paper, we propose the use of active learning (AL) to efficiently adapt a classifier trained on a source image to spatially distinct target images with minimal labelling effort and without sacrificing classification performance. The adaptation consists in actively adding to the initial local model, new relevant training samples from other areas, in a cascade that iteratively improves the generalisation capabilities of the classifier, leading to a global model tailored to different areas. This active selection relies on uncertainty sampling to directly focus on the most informative pixels for which the algorithm is the least certain of their class labels. Experiments conducted on Sentinel-2 time series showed that when the same number of training samples was used, active learning outperformed passive learning (random sampling) by up to 5% of overall accuracy and up to 12% of class F-score. In addition, and depending on the class considered, the random sampling required up to 50% more samples to achieve the same performance of an active learning-based model. Moreover, the results demonstrate the suitability of the derived global model to accurately map poplar plantations among other tree species with overall accuracy values up to 14% higher than those obtained with local models. The proposed approach paves the way for national-scale mapping in an operational context.

Outbreaks of coronavirus disease 2019 (COVID-19) have been recorded in different countries across the globe. The virus is highly contagious, hence early detection, isolation, and quarantine of infected patients will play an important role in containing the viral spread. Diagnosis in a mobile lab can aid to find infected patients in time. Here, we develop a field-deployable diagnostic workflow that can reliably detect COVID-19. Instruments used in this workflow could easily fit in a mobile cabin hospital and also be installed in the community. Different steps from sample inactivation to detection were optimized to find the fastest steps and portable instruments in detection of COVID-19. Each step was compared to that of the normal laboratory diagnosis set-up. From the results, our proposed workflow (80 min) was two times faster compared to that of the normal laboratory workflow (183 min) and a maximum of 32 samples could be detected at each run. Additionally, we showed that using 1% Rewocid WK-30 could inactivate the novel coronavirus directly without affecting the overall detection results. Comparison of our workflow using an in-house assay to that of a commercially acquired assay produced highly reliable results. From the 250 hospital samples tested, there was a high concordance 247/250 (98.8%) between the two assays. The in-house assay sensitivity and specificity were 116/116 (100%) and 131/134 (97.8%) compared to that of the commercial assay. Based on these results, we believe that our workflow is fast, reliable, adaptable and most importantly, field deployable.

In the past decades, several new diseases have emerged in new geographical areas, with pathogens including Ebola, Zika, Nipah, and coronaviruses (CoVs). Recently, a new type of viral infection has emerged in Wuhan City, China, and initial genomic sequencing data of this virus does not match with previously sequenced CoVs, suggesting a novel CoV strain (2019-nCoV), which has now been termed as severe acute respiratory syndrome CoV-2 (SARS-CoV-2). Although Coronavirus disease 2019 (COVID-19) is suspected to originate from an animal host (zoonotic origin) followed by human-to-human transmission, the possibility of other routes such as food-borne transmission should not be ruled out. Compared to diseases caused by previously known human CoVs, COVID-19 shows less severe pathogenesis but higher transmission competence, as is evident from the continuously increasing number of confirmed cases globally. Compared to other emerging viruses such as Ebola virus, avian H7N9, SARS-CoV, or MERS-CoV, SARS-CoV-2 has shown relatively low pathogenicity and moderate transmissibility. Codon usage studies suggest that this novel virus may have been transferred from an animal source such as bats. Early diagnosis by real-time PCR and next-generation sequencing has facilitated the identification of the pathogen at an early stage. Since, no antiviral drug or vaccine exists to treat or prevent SARS-CoV-2, potential therapeutic strategies that are currently being evaluated predominantly stem from previous experience with treating SARS-CoV, MERS-CoV, and other emerging viral diseases. In this review, we address epidemiological, diagnostic, clinical, and therapeutic aspects, including perspectives of vaccines and preventive measures that have already been globally recommended.

Based on recent computational and experimental studies, hesperidin, a bioactive flavonoid abundant in citrus peel, stands out for its high binding affinity to the main cellular receptors of SARS-CoV-2, outperforming drugs already recommended for clinical trials. Thus, it is very promising for prophylaxis and treatment of COVID-19, along with other coexistent flavonoids such as naringin, which could help restraining the pro-inflammatory overreaction of the immune system. Controlled hydrodynamic cavitation processes showed the highest speed, effectiveness and efficiency in the integral and green aqueous extraction of flavonoids, essential oils and pectin from citrus peel waste. After freeze-drying, the extracted pectin showed high quality and excellent antioxidant and antibacterial activities, attributed to flavonoids and essential oils adsorbed and concentrated on its surface. This study reviews the recent evidence about hesperidin as a promising molecule, and proposes a feasible and affordable process based on hydrodynamic cavitation for the integral aqueous extraction of citrus peel waste resulting in hesperidin-rich products, either aqueous extracts or pectin tablets. The uptake of this process on a relevant scale is urged, in order to achieve large-scale production and distribution of hesperidin-rich products. Meanwhile, experimental and clinical studies could determine the effective doses either for therapeutic and preventive purposes.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is characterized by a high mortality of elderly men with age-related comorbidities. In most of these patients, uncontrolled local and systemic hyperinflammation induces severe and often lethal outcomes. The aging process is characterized by the gradual development of a chronic subclinical systemic inflammation (inflamm-aging) and by acquired immune system impairment (immune senescence). Here, we advance the hypothesis that some key features of aging contribute to the disproportionate SARS-CoV-2 mortality suffered by elderly men. At least four well-recognized aging-related characteristics that are strongly expressed in older men go some way towards explaining why these patients account for the vast majority of fatalities: i. the presence of subclinical systemic inflammation without overt disease, ii. a blunted acquired immune system and type I interferon response due to the chronic inflammation; iii. the downregulation of ACE2 (SARS-CoV-2 receptor), which triggers inflammation, particularly in patients with age-related comorbid diseases such as type II diabetes; and iv. accelerated biological aging, as measured by epigenetic and senescence markers (e.g. telomere shortening) associated to the chronic inflammatory state. Though typical of the aged, especially of elderly men, it is conceivable that these features are also shared by some subsets of the younger population. The high mortality rate of SARS-CoV-2 infection suggests that clarification of the mechanisms of inflamm-aging and immune senescence can help combat not only age-related disorders but also SARS-CoV-2 infection.

Corona viruses cause extensive SARS epidemics via super spread events (SSE). Due to variation in infection risk and heterogeneity of reproduction numbers specific distinction between SSE’s and typical case events is essential. SARS transmissions unveil a complex scenario in which SSE’s are shaped by multiple factors. Specific screening strategies for infection emergence within potential super spreading groups will help to efficiently control the SARS-2 pandemic and alleviate the partially effective general restriction measures.

This paper investigates whether the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) pandemic – also known as COronaVIrus Disease 19 (COVID-19) – could have been favored by specific weather conditions. It was found that the 2020 winter weather in the region of Wuhan (Hubei, Central China) – where the virus first broke out in December and spread widely from January to February 2020 – was strikingly similar to that of the Northern Italian provinces of Milan, Brescia and Bergamo, where the pandemic has been very severe from February to March. The similarity suggests that this pandemic worsens under weather temperatures between 4°C and 11°C. Based on this result, specific isotherm world maps were generated to locate, month by month, the world regions that share similar temperature ranges. From January to March, this isotherm zone extended mostly from Central China toward Iran, Turkey, West-Mediterranean Europe (Italy, Spain and France) up to the United State of America, coinciding with the geographic regions most affected by the pandemic from January to March. It is predicted that next spring, as the weather gets warm, the pandemic will likely worsen in northern regions (United Kingdom, Germany, East Europe, Russia and North America) while the situation will likely improve in the southern regions (Italy and Spain). However, in autumn, the pandemic could come back and affect the same regions again. The Tropical Zone and the entire Southern Hemisphere, but in restricted southern regions, could avoid a strong pandemic because of the sufficiently warm weather during the entire year. Google-Earth-Pro interactive-maps are provided as supplements.

More than 179,000 individuals have fallen ill of the Coronavirus disease (COVID-19) caused by the SARS-CoV-2 virus, which first emerged in China less than four months ago in December 2019. As of today, there exist no approved treatments against COVID-19. Vaccines are being developed, but they will take time, at least one year, to reach the population. Drug repositioning represents a fast track because already approved medicines have been broadly tested through multiple trials. We developed a repositioning strategy that mostly leads to candidates that are commonly used. The advantages are that they will facilitate proof of concept in humans through a “real-world evidence” approach and should be rapidly available to the population. We focus on the established research results that the unfolded protein response (UPR) and autophagy pathways of the host cells are essential to the life cycle of previously known coronaviruses. We performed the relevant bioinformatics analysis to understand and confirm if SARS-CoV-2 may interact with these druggable pathways. Based on these considerations, we prioritized two additional druggable pathways, which are important to the viral life cycle and tightly connected to UPR/autophagy signaling: the mitochondrial permeability transition pores (MPTP) and NLRP-3 inflammasome pathways. These four important pathways are perturbed in most major common diseases and have therefore been targeted by numerous broadly prescribed drugs. We have identified 97 approved drugs that are known to modulate these four identified pathways, and which represent, therefore, interesting repositioning candidates. Although it is indisputable that these drugs should never be used for immediate self-medication against COVID-19, we notice that some of them could also be prescribed to individuals who have COVID-19 comorbidities (e.g., hypertension). It is debated if these comorbidities are linked to the pathology itself (e.g., hypertension) or the drugs used to treat the pathology (e.g., sartans). Therefore, relevant preclinical tests and massive electronic health records (i.e., real-world evidence) must be used to pre-screen them and check the COVID-19 prognosis of individuals taking these drugs.

A SARS-CoV receptor-binding domain (RBD) recombinant protein was developed and manufactured under current good manufacturing practices in 2016. The protein known as RBD219-N1 when formulated on Alhydrogel®, induced high-level neutralizing antibodies and protective immunity with minimal immunopathology in mice after a homologous virus challenge with SARS-CoV (MA15 strain). In this report, we examined published evidence in support of whether the SARS-CoV RBD219-N1 could be repurposed as a heterologous vaccine against Coronavirus Infectious Disease (COVID)-19. Our findings include evidence that convalescent serum from SARS-CoV patients can neutralize SARS-CoV-2. Additionally, a review of published studies using monoclonal antibodies (mAbs) raised against SARS-CoV RBD and that neutralize the SARS-CoV virus in vitro, finds that some of these mAbs bind to the receptor-binding motif (RBM) within the RBD, while others bind to domains outside this region within RBD. This information is relevant and supports the possibility of developing a heterologous SARS-CoV RBD vaccine against COVID-19, especially due to the finding that the overall high amino acid similarity (82%) between SARS-CoV and SARS-CoV-2 spike and RBD domains is not reflected in RBM region (59%). However, the high similarity (94%) in the region outside of RBM offers the potential of conserved neutralizing epitopes between both viruses.

Almost half of the confirmed COVID-19 cases detected so far in the United Kingdom are part of a large cluster of 13 British nationals who tested positive for SARS-CoV-2 in the UK, Spain, and France. Transmissions among this cluster occurred at a ski resort in France, and originated from a single infected traveller returning from a conference in Singapore where he acquired the virus. At least 21 individuals were exposed to the virus, tested, and quarantined, with 13 of those testing positive between the period of 6th Feb and 15th Feb. Here, all publicly available information about the primarily UK/France cluster is consolidated, providing a complete and accessible summary of the cases and their connections. Notable in this cluster are the number of individuals infected, the apparent absence of any severe illness among those infected, and a case of a `delayed positive' test during isolation after initially testing negative, at least 7 days after last possible contact.

The spike protein of SARS coronavirus (SARS-CoV) attaches the virus to its cellular receptor, angiotensin-converting enzyme 2 (ACE2), which is mediated by the receptor binding domain (RBD) of the spike protein. Recently, an analysis based on decade-long structural studies of SARS was reported to illustrate with atomic-level details receptor recognition by the novel coronavirus from Wuhan, i.e., 2019-nCoV. Here, this article reports a comprehensive set of structural electrostatic analysis of all SARS-CoV spike protein RBD-related structures as of February 13, 2020, aiming at identifying the electrostatic hot spots for SARS-CoV spike protein to be complexed with ACE2 and its neutralizing antibodies. First, this article identified a structural action mechanism of the F26G19 antibody (of SARS-CoV spike protein), where its Asp56 residue binds to the Arg426 of the SARS-CoV spike protein RBD against the formation of the interfacial Arg426-Glu329 salt bridges between ACE2 and the SARS-CoV spike protein RBD. Second, a hypothesis is reported that a pair of electrostatic clips exist at the interface between ACE2 and the SARS-CoV spike protein RBD, including both Arg426-Glu329 and His445-Glu23-Lys447 salt bridges. Last, this article reports a structurally identified interfacial Glu35-Arg479 salt bridge which helps stabilize the complex structure of ACE2 and the SARS-CoV spike protein RBD. Overall, the structurally identified electrostatic hot spots reported here may be useful for the design of SARS-CoV-neutralizing antibodies in future.

Easy to use satellite-based water quality visualizations are needed for monitoring and understanding coastal and inland waters, but to date, no publicly accessible real-time global visualization system was in place. Here we introduce the Ulyssys Water Quality Viewer (UWQV), a Sentinel Hub EO Browser Custom script designed for qualitative views of aquatic chlorophyll and suspended sediment concentrations. The viewer avoids unmixing of the chlorophyll and suspended sediment spectral signal by visualizing these parameters together, with high concentrations of suspended sediment obscuring chlorophyll if present. Cloud masking uses the Hollstein and Braaten algorithms (existing EO Browser custom script code), additionally water surfaces are masked using the Normalized Differential Water Index. Chlorophyll is estimated using reflectance line height-based indicators such as fluorescence line height and maximum chlorophyll index. Suspended sediment is visualized based on single-band reflectances at 620 or 700 nm. Data sources are Sentinel-2 and Sentinel-3 images, allowing either 20 m spatial resolution or up to daily imaging. This visualization system is easy to operate and interpret, and combined with the data service capacity of the Sentinel Hub, it is expected that UWQV will contribute to monitoring of remote water bodies and to our overall understanding of physical limnology and aquatic ecology.

The epithelial cell tight junction structure is the site of the transepithelial movement of solutes and water between epithelial cells (paracellular permeability). Paracellular permeability can be divided into two distinct pathways, the Pore Pathway mediating the movement of small ions and solutes and the Leak Pathway mediating the movement of large solutes. Claudin proteins form the basic paracellular permeability barrier and mediate the movement of small ions and solutes via the Pore Pathway. The Leak Pathway remains less understood. Several proteins have been implicated in mediating the Leak Pathway, including occludin, ZO proteins, tricellulin, and actin filaments, but the proteins comprising the Leak Pathway remain unresolved. The properties of the Leak Pathway, such as its molecular mechanism, its regulation, and whether or not it has a size limit, remain controversial. This review will trace the evolution of the Leak Pathway concept from its origins, will discuss the current information about the properties of the Leak Pathway, and will discuss recent research suggesting a possible molecular basis for the Leak Pathway. Based on these findings, we propose a model for the molecular mechanism underlying the Leak Pathway and its regulation.

Supplier selection is one of the most important multi criteria decision making (MCDM) problems for decision makers in competitive market. Organizations of today’s world are seeking new ways to reduce negative effects of their organizations to the environment and to reach a greener system. At this point, green supplier selection concept has gained great importance with its ability on incorporating environmental or green criteria into the classical supplier selection practices. Therefore, in this study, it is aimed at proposing a multi-phase MCDM model based on Best-Worst Method (BWM) and interval type-2 fuzzy technique for order preference by similarity to ideal solution (TOPSIS). A case study in a plastic injection molding facility in Turkey is performed to show the applicability of the proposed integrated methodology. The paper ensures insights into the decision making, methodology, and managerial implications. Results of the case study are examined and suggestions for future research are provided.

Common genetic variants of the fat mass and obesity associated (FTO) gene are strongly associated with obesity and type 2 diabetes. FTO is ubiquitously expressed, but appears to have tissue-specific roles. Earlier studies have focused on the role of hypothlamic FTO in the regulation of metabolism. However, it appears that FTO plays a role in the regulation of metabolism in a tissue-specific manner. Recent studies suggest that expression of hepatic FTO is regulated by metabolic signals such as nutrients and hormones and altered FTO levels in liver affects glucose and lipid metabolism. This review outlines recent findings on hepatic FTO in the regulation of metabolism, with particular focus on hepatic glucose and lipid metabolism. It is proposed that abnormal activity of hepatic signaling pathways involving FTO links metabolic impairments such as obesity, type 2 diabetes and nonalcoholic fatty liver disease (NAFLD). Therefore, a better understanding of these pathways may lead to therapeutic approaches to treat these metabolic diseases by targeting hepatic FTO. The overall goal of this review is to place FTO within the context of hepatic regulation of metabolism.

Ischemic neuron loss contributes to brain dysfunction in patients with cardiac arrest (CA). Histidine–tryptophan–ketoglutarate (HTK) solution is a preservative used during organ transplantation. Can HTK also protect neurons from severe hypoxia (SH) following CA? We isolated rat primary cortical neurons and induced SH with or without HTK. Changes in caspase-3, hypoxia-inducible factor 1-alpha (HIF-1α), and NADPH oxidase-4 (NOX4) expression were evaluated at different time points till 72 h. Using a rat asphyxia model, we induced CA-mediated brain damage and then completed resuscitation. HTK or sterile saline was administered into the left carotid artery. Neurological deficit scoring and mortality were evaluated for 3 days. Then the rats were sacrificed for evaluating NOX4 and H2O2 level in blood and brain. In the in vitro study, HTK attenuated SH- and H2O2-mediated cytotoxicity in a volume- and time-dependent manner, associated with persisted HIF-1α expression, reductions in procaspase-3 activation and NOX4 expression. The inhibition of HIF-1α abrogated HTK’s effect on NOX4. In the in vivo study, neurological scores were significantly improved by HTK. H2O2 level, NOX4 activity and NOX4 gene expression were all decreased in the brain specimen of HTK-treated rats. Our results suggest that HTK acts as an effective neuroprotective solution.

Hypothesis: Anti-diabetic drugs modulate p-21 activated kinase (PAK) signaling Introduction: Type 2 diabetes mellitus (T2DM) is a chronic inflammatory disease associated with increased cancer risk. PAK signaling is implicated in cellular homeostasis when regulated, and cancer when unrestrained. Recent reports provided a role for PAK signaling in glucose homeostasis, but the role of PAKs in the pathogenesis of T2DM is unknown. Here we performed a mini-meta analysis to explore if anti-diabetic drugs modify PAK signaling pathways, and provide insight regarding modulation of these pathways to potentially reduce diabetes-associated cancer risk. Methods: PAK interacting partners in T2DM were identified using online STRING database. Correlation studies were performed via systematic literature review to understand the effect of anti-diabetic drugs on PAK signaling. Mini meta analysis correlated multiple clinical studies and revealed the overall clinical response rate and percentage of adverse events in piogliazone (n=53) and metformin (n=91) treated patients with PAK-associated diseases. Results: A total of 30 PAK interacting partners were identified (10: reduced beta-cell mass; 10: beta-cell dysfunction; 10: obesity-insulin resistance) which were highly associated with Wnt, and G-protein signaling. Anti-diabetic drug metformin activated signaling pathways upstream; whereas pioglitazone inhibited pathways downstream of PAK. Overall clinical response upon pioglitazone treatment was 53%. 79% of pioglitazone and 75% of metformin treated patients had adverse events. Pioglitazone reduced molecular-PAK biomarkers of proliferation (Ki67 and CyclinD1), and metformin had the opposite effect. Conclusions: PAK signaling in T2DM likely involves Wnt and G-protein signaling which may be altered by anti-diabetic drugs metformin and pioglitazone. Apart from the therapeutic limitations of adverse events, pioglitazone may be promising in chemoprevention, however long-term multi-centered studies, which initiate pioglitazone treatment early will be required to fully assess the full potential of these drugs.

Hypothesis: Anti-diabetic drugs modulate p-21 activated kinase (PAK) signaling Introduction: Type 2 diabetes mellitus (T2DM) is a chronic inflammatory disease associated with increased cancer risk. PAK signaling is implicated in cellular homeostasis when regulated, and cancer when unrestrained. Recent reports provided a role for PAK signaling in glucose homeostasis, but the role of PAKs in the pathogenesis of T2DM is unknown. Here we explored whether PAK signaling should be targeted via chemoprevention to reduce diabetes-associated cancer risk. Methods: PAK interacting partners in T2DM were identified using online STRING database. Systematic literature review provided the effect of anti-diabetic drugs on PAK signaling. Review of clinical studies revealed the overall clinical response rate and percentage of adverse events in piogliazone (n=53) and metformin (n=91) treated patients with PAK-dependent diseases. Results: A total of 30 PAK interacting partners were identified (10: reduced beta-cell mass; 10: beta-cell dysfunction; 10: obesity-insulin resistance) which were highly associated with Wnt, and G-protein signaling. Anti-diabetic drug metformin activated signaling pathways upstream; whereas pioglitazone inhibited pathways downstream of PAK. Overall clinical response upon pioglitazone treatment was 53%. 79% of pioglitazone and 75% of metformin treated patients had adverse events. Pioglitazone reduced molecular-PAK biomarkers of proliferation (Ki67 and CyclinD1), and metformin had the opposite effect. Conclusions: PAK signaling in T2DM involves Wnt and G-protein signaling which is altered by anti-diabetic drugs metformin and pioglitazone. Apart from the therapeutic limitations of adverse events, pioglitazone is promising in chemoprevention, however long-term multi-centered studies, which initiate pioglitazone treatment early will be required to fully assess the full potential of these drugs.

A timely inventory of agricultural areas and crop types is an essential requirement for ensuring global food security. Satellite remote sensing has proven to be an increasingly more reliable tool to identify crop types. With the Copernicus program and its Sentinel satellites, a growing source of satellite remote sensing data is publicly available at no charge. Here we use joint Sentinel-1 radar and Sentinel-2 optical imagery to create a crop map for Belgium. To ensure homogenous radar and optical input across the country, Sentinel-1 12-day backscatter composites were created after incidence angle normalization, and Sentinel-2 NDVI images were smoothed to yield dekadal cloud-free composites. An optimized random forest classifier predicted the 8 crop types with a maximum accuracy of 82% and a kappa coefficient of 0.77. We found that a combination of radar and optical imagery always outperformed a classification based on single-sensor inputs, and that classification performance increased throughout the season until July, when differences between crop types are largest. Furthermore we showed that the concept of classification confidence derived from the random forest classifier provided insight in the reliability of the predicted class for each pixel, clearly showing that parcel borders have a lower classification confidence. We concluded that the synergistic use of radar and optical data for crop classification led to richer information increasing classification accuracies compared to optical-only classification. Further work should focus on object-level classification and crop monitoring to exploit the rich potential of combined radar and optical observations.

Introduction The authors reviewed the published evidence on the presence of oligosaccharides in human milk (HMO) and their benefits in in vitro and in vivo studies, as well as to evaluate published data on the addition of some of HMOs to infant formula. Method PubMed was searched from inception to April 2018 Results The presence of HMOs is a dynamic process, determined by many factors such as duration of lactation, environmental and genetic factors. HMOs may support immune function development and provide protection against infectious diseases directly through the interaction of the gut epithelial cells or indirectly through the modulation of the gut microbiota, including the stimulation of the bifidobacteria. Only a few of the many HMOs can be made industrially, and are added to infant formula. They have been shown to be safe and well tolerated, including normal growth and a trend towards health benefit. Conclusions HMOs are one of the major differences between cow’s milk and human milk , and evidence indicates that these components do have a health promoting benefit. The addition of one or two of these components to infant formula is safe, and brings infant formula closer to human milk.

The aim of this study was to examine oxidative stress and low level of alpha-1-antitrypsin (A1AT) in primary Sjögren's syndrome (pSS), and evaluate the associated autoreactivity against unmodified and their 4-hydroxy-2-nonenal (HNE)-modified peptides with pSS. Two differentially expressed proteins, alpha-1-acid glycoprotein 1 (A1AG1) and A1AT, exhibited 2-fold differences, and their HNE modifications were identified by depleted-albumin and immunoglobulin G (IgG) serum protein, in-solution digestion, in-gel digestion, and nano-LC-MS/MS from pSS patients and age-matched healthy controls (HCs). Furthermore, levels of proteins, confirmation of HNE modifications, HNE-protein adducts and autoreactivity against unmodified and their HNE-modified peptides were further validated. Levels of the HNE-protein adduct and A1AG1 were significantly higher in pSS patients than HCs, but levels of A1AT were significantly lower in pSS patients compared to HCs. Only the HNE modification of A1AT was confirmed. Further, concentrations of anti-A1AT^50-63 IgG and anti-A1AT^50-63 HNE IgA were significantly lower in pSS patients than HCs. Our study suggests that elevated HNE-protein adduct, oxidative stress, level [odds ratio (OR) 4.877, p = 0.003], lowered A1AT level (OR 3.910, p = 0.010) and a decreased level of anti-A1AT^50-63 IgG (OR 3.360, p = 0.010) showed an increased risk in pSS patients compared to HCs, respectively.

This paper focuses on evaluating airline service quality from the perspective of passengers view. Until now a lot of researches has performed in airline service quality evaluation in the world but a little research has been conducted in Iran, yet. In this research a framework for measuring airline service quality in Iran is proposed. After reviewing airline service quality criteria, SSQAI model was selected because of its comprehensiveness in covering airline service quality dimensions. SSQAI questionnaire items were redesigned to adopt with Iranian airlines requirements and environmental circumstances in the Iran's economic and cultural context. This study includes fuzzy decision-making theory, considering the possible fuzzy subjective judgment of the evaluators during airline service quality evaluation. Fuzzy TOPSIS have been applied for ranking airlines service quality performances. Three major Iranian airlines which have the most passenger transfer volumes in domestic and foreign flights, were chosen for evaluation in this research. Results demonstrated Mahan airline has got the best service quality performance rank in gaining passengers' satisfaction with delivery of high quality services to its passengers, among the three major Iranian airlines. IranAir and Aseman airlines placed in the second and third rank, respectively, according to passenger's evaluation.Statistical analysis have been used in analyzing passenger responses. Due to abnormality of data, Non-parametric tests were applied. To demonstrate airline ranks in every criterion separately, Friedman test was performed. Variance analysis and Tukey test were applied to study the influence of increasing in age and educational level of passengers' on degree of their satisfaction from airline's service quality. Results showed that age has not significant relation with passenger satisfaction of airlines, however increasing in educational level demonstrated a negative impact on passengers' satisfaction from airline's service quality.

Splines and quasi-interpolation operators are important both in approximation theory and applications. In this paper, we construct a family of quasi-interpolation operators for the bivariate quintic spline spaces S₅³ (∆_mn⁽²⁾). Moreover, the properties of the proposed quasi-interpolation operators are studied, as well as its applications for solving two-dimensional Burgers’ equation and image reconstruction. Some numerical examples show that these methods, which are easy to implement, provide accurate results.

The problem of quantifying the vulnerability of graphs has received much attention nowadays, especially in the field of computer or communication networks. In a communication network, the vulnerability measures the resistance of the network to disruption of operation after the failure of certain stations or communication links. If we think of a graph as modeling a network, the average lower 2-domination number of a graph is a measure of the graph vulnerability and it is defined by ${\gamma }_{2av}\left(G\right)=\frac{1}{\left|V\left(G\right)\right|}{\sum }_{v\in V\left(G\right)}{\gamma }_{2v}\left(G\right)$, where the lower 2-domination number, denoted by ${\gamma }_{2v}\left(G\right)$, of the graph G relative to v is the minimum cardinality of 2-domination set in G that contains the vertex v. In this paper, the average lower 2-domination number of wheels and some related networks namely gear graph, friendship graph, helm graph and sun flower graph are calculated. Then, we offer an algorithm for computing the 2-domination number and the average lower 2-domination number of any graph G.

Measures in the SARS-CoV-2 pandemic were based on rough ideas regarding transmission routes of pathogens. Quantified models of physical transmission routes are mostly lacking, a gap to be filled. Vaccines and medicines, important, are not studied here. We first survey main routes, from primary production in the alveoli and intestines to emissions, environmental routes, to exposure and alveolar infection. Next, specific routes are modelled, mostly at a preliminary state, open to systematic improvement. Starting from a standardized emitter, modelling results show extreme differences in potential exposure, in a range covering up to 4 orders of magnitude. The outcomes are pathogen-specific, already different between SARS-CoV-2 and influenza. Extreme exposures may result in smaller spaces; with lower ventilation rates; with a high density of emitting persons per m3; who stay there for several hours; and visitors staying more than a few minutes. In spaces where a build-up of concentrations is low, exposures are low, lowest in open air situations. A main conclusion for the next pandemic is that a quantified model can give strong guidance on where measures are primarily due. For SARS-CoV-2, ventilation can be improved short-term. Longer-term, effective ventilation rules and adaptation of buildings may reduce high exposures substantially.

Cystic echinococcosis (CE), caused by the larval stage of Echinococcus granulosus, is significantly underreported in Mongolia due to geographical remoteness, lack of early diagnostics, and poor clinical management. This study aimed to provide a more accurate estimate of CE in Mongolia by comparing data of surgical (reported) and diagnosed (unreported) cases, and assessing the challenges faced by rural doctors in disease management and surveillance. We collected data on surgical cases hospitalized between 2006-2016 and newly diagnosed CE cases in 2016 from eight provinces. Using a quasi-Poisson regression model of the collected data, we used extrapolation to estimate the number of diagnosed cases for the entire country. Additionally, fourty health professionals from all 21 provinces rated local clinical management for CE through a questionnaire. Results reveal that surgical cases (2.2 per year) represent only one-eighth of diagnosed cases (15.9 per year). The laboratory facilities, disease reporting, and cyst classification usage scored below 2. These results highlight the significant underreporting of CE in Mongolia and urges human and animal health experts, along with policymakers, to invest into combating CE, particularly in remote provincial areas. It also emphasizes the need for standard clinical management involving cyst classification according to WHO-IWGE, seamless integration of CE reporting and monitoring mechanisms, which can significantly contribute to the national and global burden estimation of CE.

Alginate-silver nanocomposites in the form of spherical beads and films were prepared using a green approach by using the aqueous extract of Ajwa dates seeds. The nanocomposites were fabricated by in situ reduction and gelation method by ionotropic crosslinking using calcium ions in solution. The rich phytochemicals of the dates seeds extract played a dual role as reducing and stabilizing agent in the synthesis of silver nanoparticles. The formation of silver nanoparticles was studied using UV-Vis absorption spectroscopy and a distinct surface plasmon resonance (SPR) peak at 421 nm characteristic of silver nanoparticles confirmed the green synthesis of silver nanoparticles. The morphology of the nanocomposite beads and film was compact with even distribution of silver nanoclusters. The catalytic property of the nanocomposite beads was evaluated for the degradation of 2-nitrophenol in the presence of sodium borohydride. The degradation followed pseudo-first order kinetics with a rate constant of 1.40 ´ 10^-3 s^-1 at 23 °C with an activation energy of 18.45 kJ mol^-1. The thermodynamic parameters such as changes in enthalpy and entropy were evaluated to be 15.22 kJ mol^-1 and -197.50 J mol^-1 K^-1, respectively. The nanocomposite exhibited properties against three clinically important pathogens (Gram-positive and Gram-negative bacteria)

In the global carbon cycle, atmospheric carbon emissions, both ‘natural’ and anthropogenic, are balanced by carbon uptake (i.e. sequestration) that mostly occurs via photosynthesis, plus a much smaller proportion via geological processes. Since the formation of the Earth about 4.54 billion years ago the ratio between emitted and sequestered carbon has varied considerably with atmospheric CO₂ levels ranging from 100,000 ppm to a mere 100 ppm. Over this time, a huge amount of carbon has been sequestered due to photosynthesis and essentially removed from the cycle, being buried as fossil deposits of coal, oil and gas. Relatively low atmospheric CO₂ levels were the norm for the past 10 million years, and during the past million years they averaged about 220 ppm. More recently, the Holocene epoch, starting ~11,700 years ago, has been a period of unusual climatic stability with relatively warm, moist conditions and low atmospheric CO₂ levels of between 260 and 280 ppm. During the Holocene, stable conditions facilitated a social revolution with domestication of crops and livestock leading to urbanisation and development of complex technologies. As part of the latter process, immense quantities of sequestered fossil carbon have recently been used as energy sources, resulting in a particularly rapid increase in CO₂ emissions after 1950 CE to the current value of 424 ppm, with further rises to >800 ppm predicted by 2100. This is already perturbing the previously stable Holocene climate and threatening future food production and social stability. Today, the global carbon cycle has been shifted such that carbon sequestration is no longer keeping up with recent anthropogenic emissions. In order to address this imbalance it is important to understand the roles of high-capacity carbon sequestration systems, such as natural forests and tropical croplands, and to devise strategies to facilitate net CO₂ uptake.

This study aimed to develop a laboratory-scale direct air capture unit for evaluating and comparing amine-based adsorbents under temperature vacuum swing adsorption conditions. The experimental campaign conducted with the direct air capture unit allowed for the determination of equilibrium loading, CO2 uptake capacity, and other main performance parameters of the investigated adsorbent Lewatit VP OC 1065®. The investigations also helped to understand the co-adsorption of both CO2 and H2O on the tested material, which is crucial for improving temperature vacuum swing adsorption processes. This was achieved by obtaining pure component isotherms for CO2 and H2O as well as three different co-adsorption isotherm models from literature. It was found that the weighted average dual-site Toth model emerged as the most accurate and reliable model for simulating this co-adsorption behavior. Its predictions closely align with experimental data, particularly in capturing the adsorption equilibrium at various temperatures. It was also observed that this lab-scale unit offers advantages over thermogravimetric analysis when conducting adsorption experiments on the chosen amine. The final aim of this study is to provide a pathway to develop devices for testing and developing efficient and cost-effective adsorbents for direct air capture.

The increased prevalence of obesity worldwide has been implicated for the alarming rise of the incidence of gestational diabetes and preeclampsia as well, both considered as threatening conditions for both mother and fetus. We studied gene polymorphisms of the proinflammatory cytokine Interleukin 6 (IL-6) and the gene expression levels of VEGF and VEGF-receptor all known to be involved in pregnancy complications aiming to identify possible predisposing risk factors in pregnancies with obesity. G allele of IL-6 was found to correspond with an increased risk for gestational diabetes and preeclampsia occurrence. Furthermore, in obese pregnant mothers with either gestational diabetes or pre-existing type 2 diabetes and to those developed preeclampsia it was confirmed that gene expression levels of VEGF were reduced while they were increased for VEGF receptor. We conclude that the genetic profile of the obese pregnant woman shares a common background with that of a pre-existing type 2 diabetes mellitus and therefore predisposes to complications in pregnancy.

Exploring therapeutic options is crucial in the ongoing COVID-19 pandemic caused by SARS-CoV-2. Nirmatrelvir, a potent inhibitor targeting the SARS-CoV-2 Mpro, shows promise as an antiviral treatment. Additionally, Ivermectin, a broad-spectrum antiparasitic drug, has demonstrated effectiveness against the virus in laboratory settings. However, its clinical implications are still debated. Using computational methods such as molecular docking and 100 ns molecular dynamics simulations, we investigated how Nirmatrelvir and Ivermectin interact with SARS-CoV-2 Mpro(A). Calculations using density functional theory have been instrumental in elucidating the behavior of isolated molecules, primarily by analyzing the frontier molecular orbitals. Our analysis revealed distinct binding patterns: Nirmatrelvir formed strong interactions with amino acids like MET49, MET165, HIS41, HIS163, HIS164, PHE140, CYS145, GLU166, and ASN142, showing stable binding with a root mean square deviation (RMSD) of around 2.0 Å. On the other hand, Ivermectin interacted with THR237, THR239, LEU271, LEU272, and LEU287, displaying an RMSD of 1.87 Å, indicating enduring interactions. Both ligands stabilized Mpro(A), with Ivermectin showing stability and persistent interactions despite forming fewer hydrogen bonds. These findings offer detailed insights into how Nirmatrelvir and Ivermectin bind to the SARS-CoV-2 main protease, providing valuable information for potential therapeutic strategies against COVID-19.

Semenov-Tian-Shansky has introduced the modified classical Yang-Baxter equation, which is called the modified $r$-matrix. Relevant studies have been extensive in recent times. This paper is devoted to study cohomology theory of modified Rota-Baxter pre-Lie algebras and its applications. First we introduce the concept and representations of modified Rota-Baxter pre-Lie algebras. We then develop the cohomology of modified Rota-Baxter pre-Lie algebras with coefficients in a suitable representation. As applications, we consider the infinitesimal deformations, abelian extensions and skeletal modified Rota-Baxter pre-Lie 2-algebra in terms of lower degree cohomology groups.

The quality of healthcare services is a very important indicator of social welfare in developed and emerging countries. Good quality levels are critical to ensuring patient safety, improving health outcomes, increasing patient satisfaction, optimizing resource utilization, and meeting regulatory requirements. The stable and sustainable operation of medical institutions urgently requires the establishment of a reliable and effective medical quality performance evaluation platform. However, the complexity of the evaluation process, involving numerous evaluators and the consideration of different subjective and objective criteria, poses significant challenges and essentially constitutes a group multi-criteria decision-making problem. This article uses the overall medical environment of the institution, medical service attitude, medical security, administrative service measures, etc. as measurement standards to deal with this challenge. It proposes a medical service quality measurement model suitable for both qualitative and quantitative analysis. In view of the heterogeneity of information, the two-tuple fuzzy language calculation method is introduced to enable evaluators to skillfully manage diverse information and effectively avoid potential information omission problems in the subjective evaluation integration process. The effectiveness and feasibility of the model were demonstrated by applying it to the operational framework of a medical institution in central Taiwan.

The sheer number of gene variants and the extent of the observed clinical and molecular heterogeneity recorded in neuropsychiatric disorders (NPDs), could be due to the magnified downstream effects initiated by a smaller group of genomic higher order alterations in response to endogenous or environmental stress. Chromosomal common fragile sites (CFS) are functionally linked with microRNA’s, gene copy number variants (CNVs), sub-microscopic deletions and duplications of DNA, rare single-nucleotide variants (SNVs/SNPs) and small insertions/deletions (indels), as well as chromosomal translocations, gene duplications, altered methylation, microRNA and L1 transposon activity and 3-D chromosomal topology characteristics. These genomic structural features have been linked with various NPDs in mostly isolated reports, and have usually only been viewed as areas harboring potential candidate genes of interest. The suggestion to use a higher level entry point, (the ‘fragilome’ and associated features), activated by a central mechanism (‘stress’) for studying NPD genetics, has the potential to unify the existing vast number of different observations in this field. This approach may explain the continuum of gene findings distributed between affected and unaffected individuals, the clustering of NPD phenotypes and overlapping comorbidities, the extensive clinical and molecular heterogeneity and the association with certain other medical disorders.

(1) Background: In this work, a series of benzimidazole derivatives containing colchicine-like and cathechol-like moieties with methyl group substitution in the benzimidazole ring were evaluated for their in vitro antiproliferative, pro-apoptotic and antioxidative activity against highly invasive breast cancer cell line MDA-MB-231 and related impairment of tubulin dynamics; (2) Methods: MTT assay was used to evaluate the antiproliferative activity. In vitro tubulin polymerization assay as well as docking analysis was applied to prove the alterations in tubulin polymerization. Immunofluorescent and DAPI staining reveal the pro-apoptotic potential of benzimidazole derivatives and the effect on tubulin’s dynamics in living cells. The antioxidant activity was evaluated by scavenging of H2O2 and hypochlorite ion and ortho-phenanthroline tests; (3) Results: The compounds containing colchicine-like moiety displayed significant growth inhibitory effect against cancer cell line as was highlighted the role of methyl functional group on the tubulin aggregation and blockage of mitosis. All compounds showed an ability to scavenge H2O2, while the compounds with cathecol-like moiety were more effective against hypochlorite ion and chelation of iron; (4) Conclusions: The benzimidazole derivative containing colchicine-like moiety and methyl group substitution in benzimidazole ring is a potential antiproliferative and microtubule destabilizing agent.

This study aimed to elucidate the similarities and differences between amyloid-forming corpora amylacea (CA) in the prostate and lung, examine the nature of CAs in cystic tumors of the atrioventricular node (CTAVN), and clarify the distinctions between amyloid-forming CA and spheroid-type amyloid deposition. We conducted proteomics analyses using liquid chromatography–tandem mass spectrometry with laser microdissection and immunohistochemistry to validate the characteristics of CAs in the lung and prostate. Our findings revealed that CAs in these organs primarily consist of common proteins (β2-microglobulin and lysozyme) and locally produced proteins. Moreover, we observed a discrepancy between the histopathological and proteomic analysis results in CTAVN-associated CAs. In addition, while the histopathological appearance of amyloid-forming CAs and spheroid-type amyloid deposits were nearly identical, the latter deposition lacked β2-microglobulin and lysozyme, and exhibited evident destruction of surrounding tissue. A literature review further supported these findings. These results suggest that amyloid-forming CAs in the lung and prostate are formed through a shared mechanism, serving as waste containers (wasteosomes) and/or storage for excess proteins (functional amyloids). In contrast, we hypothesize that while amyloid-forming CA and spheroid-type amyloid deposits are formed, in part, through common mechanisms, the latter are pathological.

Employing remote sensing techniques to evaluate crop residue cover (CRC) enables rapid mapping of tillage practices over large cropland areas, which has significant practical implications for monitoring the implementation of conservation tillage practices. This research utilized Sentinel-2 MSI and Landsat-8 OLI remotely sensed data, various spectral indices were calculated and the datasets were correlated with the field-measured CRC data. Selected spectral indices, highly significantly correlated, were chosen to build a correlation model between the indices and the CRC. Considering Sentinel-2 MSI and Landsat 8 OLI remotely sensed data variations in spectral and spatial scales, the accuracy of CRC models was evaluated using R2 and RMSE values. From the results, it's evident that all six spectral indices, including STI, NDTI, SRNDR, NDI5, NDI7 and NDSVI, registered correlation coefficients with the CRC exceeded 0.3 in the study area. STI and NDTI showed a stronger correlation to CRC, with coefficients of 0.810 and 0.803, respectively. For the Landsat 8 data, the lowest correlation obtained was for NDSVI with the Landsat 8 data with a correlation coefficient of 0.358. Applying the linear regression technique, STI and NDTI obtained higher accuracy compared to other indices in the Sentinel-2 MSI data. For NDTI and STI, The R2 values were 0.650 and 0.665, respectively, while their corresponding RMSE values were 3.96% and 4.03%. The highest model accuracy was obtained for the STI and NDTI constructed from the Landsat 8 OLI data (R2 values 0.41 and 0.40; RMSE values 5.25% and 5.27%, respectively). The CRC model built using partial least squares regression (PLSR) exhibited greater precision when applied to the Sentinel-2 MSI data (R2 value 0.894; RMSE value 2.18%) in comparison to the Landsat 8 OLI data (R2 value 0.695; RMSE value 3.70%). PLSR has the potential to enhance the precision of the model. In addition, the study area shows that the estimation of the CRC is better in the one-dimensional linear regression model and the PLSR model created with the Sentinel-2 MSI optical data compared to the Landsat 8 OLI optical remotely sensed data. The validation suggests that the CRC estimation in the study area is more precise when using the model relying on Sentinel-2 satellite imagery rather than the Landsat 8 OLI imagery.

Alzheimer’s Disease (AD), a progressive and debilitating condition, is reported to be the most common type of dementia, with at least 55 million people believed to be currently affected. Many causation hypotheses of AD exist, yet the intriguing link between viral infection and its possible contribution to the known etiology of AD has become an attractive focal point of research for the field and a challenging study task. In this review, we will explore the historical perspective and milestones that led the field to investigate the viral connection to AD. Specifically, several viruses such as Herpes Simplex Virus 1 (HSV-1), Zika virus (ZIKV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), along with several others mentioned, include the various viruses presently considered within the field. We delve into the strong evidence implicating these viruses in the development of AD. We will also extend beyond these mere associations by carefully analyzing the potential mechanisms by which viruses may contribute to AD pathology. This includes but is not limited to direct neuronal infections, dysregulation of immune responses, and the impact on protein processing. Controversies and challenges of the viral-AD relationship emerge as we tease out these potential mechanisms considered. Looking forward, we emphasize the future directions the field should take to tackle the remaining unanswered questions and the glaring research gaps that persist. Overall, this review aims to provide a comprehensive survey of the past, present, and future of the potential link between viral infections and their association with AD development.

Wastewater-Based Epidemiology (WBE) is currently used to monitor not only the spread of the pandemic virus SARS-CoV-2 but also for other viruses in endemic conditions, particularly in the absence of syndromic surveillance. Continuous monitoring of sewage requires high costs and significant time investment, highlighting the need for standardized methods and structured monitoring strategies. In this context, we conducted weekly wastewater monitoring in northwestern Italy, targeting Human Adenovirus (HAdV), Norovirus Genogroup II (NoVggII), Enterovirus (EV), and SARS-CoV-2. Samples collected at the entrance of treatment plants were concentrated using PEG/NaCl precipitation and viral nucleic acids were extracted and detected by real-time (RT-)qPCR. NoVggII resulted the most identified target (84.4%), followed by HAdV, SARS-CoV-2, and EV. Only HAdV and EV exhibited seasonal peaks in spring and summer. SARS-CoV-2 results compared with data previously collected in the same study area (February 2021 to September 2021) revealed a shift from an epidemic to a pandemic status, likely due to the evolution of variants. In conclusion, WBE, using standardized methods and an efficient monitoring strategy, proves valuable for virus surveillance in pandemic and epidemic scenarios, enabling the identification of temporal-local distribution patterns that are useful for making informed public health decision.

This study investigates the influence of economic growth on CO2 emissions levels in three developed countries—Argentina, Equatorial Guinea, and South Korea—based on their status as high-income countries. We test the environmental Kuznets curve (EKC) hypothesis using the time series approaches to check the relationship and direction of causality among the variables over a sample spanning 1974–2020. The results show an inverted U-shaped short-run relationship in all three countries. In the long run, only South Korea supports the EKC hypothesis. Further, Granger causality results indicate the existence of causality. These long-run causal relationships between economic growth and emissions recommend one policy implication that wealthy governments must expand investments in renewable clean energy projects and R&D, with regulatory measures to suppress harmful environmental procedures and support environmentally friendly development.

Human-to-animal SARS-CoV-2 transmission was observed, including a veterinarian contracting COVID-19 through close contact with an infected cat, suggesting an atypical anthropozoonotic transmission. This study investigated the prevalence of SARS-CoV-2 antibodies in cats during human outbreaks and elucidated the correlation between cat infections and human epidemics. A total of 1,107 cat sera samples were collected and screened for SARS-CoV-2 antibodies using a modified indirect ELISA human SARS-CoV-2 antibodies detection kit. The samples were confirmed using a cPass surrogate viral neutralization assay. The SARS-CoV-2 seropositivity rate was 22.67% (199/878), mirroring the trend observed in concomitant human case numbers. The waves of an epidemic and provinces did not significantly impact ELISA-positive cat. Notably, Chon Buri ex-hibited a strong positive correlation (r = 0.99, P = 0.009) between positive cat sera and reported human case numbers. Additionally, cPass surrogate viral neutralization revealed a 3.99% (35/878) seropositivity rate. While there were significant differences in positive cat numbers and proportions between epidemic waves. In Samut Sakhon, a positive correlation (r = 1, P = 0.042) was noted between the proportion of positive cat sera and reported human cases. The findings emphasize the need for ongoing surveillance to comprehend SARS-CoV-2 dynamics in both human and feline populations.

Research indicates compelling evidence of SARS-CoV-2 vertical transmission as a result of placental pathology. Background: This study offers an approach on histopathological and immunohistochemical placental observations from SARS-CoV-2 positive mothers compared negative ones. Methods: Out of 44 examined placentas, 24 were collected from patients with SARS-CoV-2 infection during pregnancy and 20 without infection. Results: The disease group showed strong SARS-CoV-2 positivity of the membranes, trophoblast and fetal villous macrophages. Most infections occurred during the third trimester of pregnancy (66.6%). Pathology revealed areas consistent with avascular villi (AV), thrombi in the chorionic vessels and umbilical cord in the positive group, suggesting fetal vascular malperfusion (FVM). Other observed features included infarction (17%), perivillous fibrin deposition (29%), intervillous fibrin (25%), delayed placental maturation (8.3%), chorangiosis (13%), chorioamnionitis (8.3%) and meconium (21%). The negative control group revealed only one case of placental infarction (5%), intervillous fibrin (5%), delayed placental maturation (5%), chorioamnionitis (5%) and two cases of meconium (19%). Our results were consistent with literature. Conclusions: This study shows SARS-CoV-2 has an impact on coagulation, demonstrated by fetal thrombotic vasculopathy (p=0.01) and fibrin deposition (p=0.01). Further research is necessary to establish whether SARS-CoV-2 is the cause of vascular pathologies during pregnancy.

This article systematically reviews the research achievements on the MnOx/TiO2 catalyst doped with transition metals or rare earth metals for the catalytic selective catalytic reduction of NH3 (SCR-NH3) reaction. The Methodi Ordinatio systematic literature analysis method was employed to rank relevant articles based on journal impact factors, publication years, and citation counts. The ranking data shows that the undoped MnOx/TiO2 catalysts exhibit a catalytic efficiency of up to approximately 90% for NOx reduction, while the doped MnOx/TiO2 catalysts with transition metals or rare earth metals can achieve a maximum reduction efficiency of 100%. Among all the doped metals, the catalyst doped with nickel demonstrates the best NOx reduction performance. The comprehensive literature research concludes that MnOx/TiO2-based SCR catalysts, especially those doped with transition metals or rare earth metals, have significant catalytic efficiency and development potential in reducing NOx emissions in SCR reactions.

The symmetries of a Riemann surface $\Sigma \setminus \{a_i\}$ with $n$ punctures $a_i$ are encoded in its fundamental group $\pi_1(\Sigma)$. Further structure may be described through representations (homomorphisms) of $\pi_1$ over a Lie group $G$ as globalized by the character variety $\mathcal{C}=\mbox{Hom} (\pi_1,G)/G$. Guided by our previous work in the context of topological quantum computing (TQC) and genetics, we specialize on the $4$-punctured Riemann sphere $\Sigma=S_2^{(4)}$ and the \lq space-time-spin' group $G=SL_2(\mathbb{C})$. In such a situation, $\mathcal{C}$ possesses remarkable properties (i) a representation is described by a $3$-dimensional cubic surface $V_{a,b,c,d}(x,y,z)$ with $3$ variables and $4$ parameters, (ii) the automorphisms of the surface satisfy the dynamical (non linear and transcendental) Painlev\'e VI equation (or $P_{VI}$), (iii) there exists a finite set of $1$ (\mbox{Cayley-Picard})+$3$ (\mbox{continuous platonic})+$45$ (\mbox{icosahedral}) solutions of $P_{VI}$. In this paper we feature on the parametric representation of some solutions of $P_{VI}$, (a) solutions corresponding to algebraic surfaces such as the Klein quartic and (b) icosahedral solutions. Applications to the character variety of finitely generated groups $f_p$ encountered in TQC or DNA/RNA sequences are proposed.

The pandemic SARS-CoV-2 continues to evolve to give rise to variants of concern that can escape vaccine-induced immunity. As such, more effective vaccines are urgently needed. In this study, we evaluated virus-like particle (VLP) as a vaccine platform for SAS-CoV-2. The spike, envelope, and membrane proteins of the SARS-CoV-2 Wuhan strain were expressed by a single recombinant baculovirus BacMam and assembled into VLPs in cell culture. The morphology and size of the SARS-CoV-2 VLP as shown by transmission electron microscopy was found to be similar to the authentic SARS-CoV-2 virus particle. In a mouse trial, two intramuscular immunizations of the VLP BacMam with no adjuvant elicited spike-specific binding antibodies in both sera and bronchoalveolar lavage fluids. Importantly, BacMam VLP -vaccinated mouse sera showed neutralization activity against SARS-CoV-2 spike pseudotyped lentivirus. Our results indicated that the SARS-CoV-2 VLP BacMam stimulated spike-specific immune responses with neutralization activity.

As yin and yang, cancer and diabetes are metabolic disorders characterized by deregulated, yet opposing, metabolic alterations. These metabolic shifts reflect a complex network of defective underlying signaling pathways, which ultimately orchestrate both disease pathogenesis and progression. The Warburg effect portrays the chief metabolic phenotype in cancer and is reflected by the dominance of aerobic glycolysis over minimal-to-no viable oxidative phosphorylation in cancer. Conversely, during the pathogenesis of type 2 diabetes (T2D), oxidative phosphorylation is constantly heightened. In advanced insulin resistance and T2D, the metabolic landscape becomes more complex, with exacerbating metabolic alterations affecting oxidative phosphorylation in a tissue-specific manner. Promising nutritional adjuvants, such as alpha-lipoic acid and flavonoids, can reprogram metabolism and exert antitumor and antidiabetic effects. Other pharmacological agents, such as metformin, have therapeutic effects on cancer and T2D. Herein, we discuss the molecular mechanisms and signaling pathways involved in the metabolic shifts in cancer and T2D, and explore the therapeutic strategies under investigation that aim to reverse the metabolic shift in both disease scenarios.

During the COVID-19 pandemic, the circulation of non–SARS-CoV-2 respiratory viruses changed throughout the world. This study aimed to analyze the effect of respiratory syncytial virus (RSV), metapneumovirus (MPV), rhinovirus (RV), and parainfluenza (PIV)-3 single infection, dual co-infection, and viral load on cytokine and chemokine expression in 300 Mexican patients with ARIs negative for SARS-CoV-2. Molecular detection and viral load were performed by RT-qPCR. Cytokine and chemokine expression was determined in samples positive for single RSV, MPV, RV, or PIV-3 infection, and in the most frequent dual co-infections, by a cytokine panel using a magnetic-bead-based multiplex immunoassay. Of the patients positive for viral infection, 91.7% had a single infection and 8.3% had dual co-infections. In this study, RSV was the respiratory virus with the highest prevalence, and the most common dual co-infection was RV+RSV. On the other hand, RV infections had the highest viral loads compared to the other viruses detected. FGF basic, MIP-1α IL-8, IP-10, MCP-1, IFN-γ, and RANTES showed differential expression between single infections and dual co-infections compared to healthy patients. We report, for the first time, the circulation of non-SARS-CoV-2 viruses in the south of Mexico and the cytokine and chemokine profiles associated with these viruses.

The removal of H2S from natural gas and other gases such as biogas, refinery gases, and coal gas is required because H2S is toxic and corrosive, even in traces. Zeolites are widely used in the removal of H2S from the above-mentioned gases. In this work, we prepared an Ag-exchanged 13X molecular sieve by using different concentrations of AgNO3 to increase its adsorption properties. XRD, SEM, and BET techniques were used to characterize samples. When compared to unmodified 13X, the adsorption capacity of AgII-13X increased by about 50 times. The results of this study suggest that the silver-modified 13X molecular sieve is highly effective at extracting H2S from natural gas.

Background: SARS-CoV-2 continues to impact human health globally, with airborne transmission being a significant mode for transmission. In addition to tools like vaccination and testing, counter-measures that reduce viral spread in indoor settings are critical. This study aims to assess the efficacy of UV-C light, utilizing the Violett sterilization device, as a countermeasure against airborne transmission of SARS-CoV-2 in the highly susceptible Golden Syrian hamster model. Methods: Two cohorts of naïve hamsters were subjected to airborne transmission from experimentally infected hamsters; one cohort was exposed to air treated with UV-C sterilization, while the other cohort was exposed to un-treated air. Results: Treatment of air with UV-C light prevented the airborne transmission of SARS-CoV-2 from experimentally exposed hamster to naïve hamsters. Notably, this protection was sustained over a muti-day exposure period during peak viral shedding from hamsters. Conclusion: These findings demonstrate the efficacy of the UV-C light to mitigate airborne SARS-CoV-2 transmission. As variants continue to emerge, UV-C light holds promise as a tool to reduce infections in diverse indoor settings, ranging from healthcare facilities to households. This study reinforces the urgency of implementing innovative methods to reduce airborne disease transmission and safeguard public health against emerging biological threats.

Cadmium (Cd) is a pervasive toxic metal, present in most food types, cigarette smoke, and contaminated air. It has no nutritional or physiological value, but most cells in the body will assimilate Cd, as its charge and ionic radius are similar to the essential metals, iron, zinc, and calcium (Fe, Zn, Ca), which are required for cellular metabolism and functional integrity. The kidney is regarded as the principal site of Cd toxicity as it preferentially accumulates in the proximal tubular epithelium here. As these cells die due to toxic accumulation, Cd complexed with metallothionein are released into tubular lumen and excreted. Excretion of Cd, signifying current renal cell toxicity, is used as a measure of long-term Cd exposure. Approximately 10% of the global population are now living with diabetes and over 80% of these are overweight or obese. This association has fueled an intense search for any exogenous chemicals and life-style factors that could induce excessive weight gain. Whilst epidemiological studies have clearly linked diabetes to Cd exposure, this appears to be independent of obesity. Indeed, obesity may enhance diabetogenic effects of Cd. This review highlights Cd exposure sources and levels associated with diabetes type 2 along with the pathophysiologic mechanisms by which Cd disrupt glucose metabolism. Special emphasis is on roles of the liver and kidney in glucose homeostasis, heme-glucose cross-talk, and the involvement of heme oxygenase-1 and -2 (HO-1 and HO-2). From heme degradation, both HO-1 and HO-2 release Fe, carbon monoxide and a precursor substrate for producing a cytoprotective biochemical, bilirubin, whilst HO-2 appears to have also anti-diabetic and anti-obese actions.

The novel coronavirus disease (COVID-19) pandemic has resulted in over 720 million confirmed cases and 7 million deaths worldwide, with insufficient treatment options. Innumerable efforts are being made around the world for faster identification of therapeutic agents to treat the deadly disease. Postacute sequelae of SARS-CoV-2 infection or COVID-19 (PASC), also called Long COVID, is still being understood and lacks treatment options as well. A growing list of drugs are being suggested by various in silico, in vitro and ex vivo models, however currently only two treatment options are widely used: the RNA-dependent RNA polymerase (RdRp) inhibitor remdesivir, and the main protease inhibitor nirmatrelvir in combination with ritonavir. Computational drug development tools and in silico studies involving molecular docking, molecular dynamics, entropy calculations and pharmacokinetics can be useful to identify new targets to treat COVID-19 and PASC, as shown in this work and our recent paper that identified alendronate as a promising candidate. We have now investigated all bisphosphonates which can bind competitively to nidovirus RdRp-associated nucleotidyl (NiRAN) transferase domain, and systematically down selected seven candidates (CHEMBL608526, CHEMBL196676, CHEMBL164344, CHEMBL4291724, CHEMBL4569308, CHEMBL387132, CHEMBL98211), two of which closely resemble the approved drugs minodronate and zoledronate. This work and our recent paper together provide an in silico mechanistic explanation for alendronate and zoledronate users having dramatically reduced odds of SARS-CoV-2 testing, COVID-19 diagnosis, and COVID-19-related hospitalizations, and indicate that similar observational studies with minodronate could be valuable.

Background: Antibiotic-containing carrier systems are one option that offers the advantage of releasing active ingredients over a longer period of time. In vitro sustained drug release from a carrier system consisting of microporous β-TCP ceramic and alginate has been reported in previous works. Alginate dialdehyde (ADA) gelatin gel showed both better mechanical properties when loaded into a β-TCP ceramic and higher biodegradability than pure alginate. Methods: Dual release of daptomycin and BMP-2 was measured on days 1, 2, 3, 6, 9, 14, 21, and 28 by HPLC and ELISA. After release, the microbial efficacy of the daptomycin was verified and the biocompatibility of the composite was tested in cell culture. Results: Daptomycin and the model compound FITC protein A (n=30) were released from the composite over 28 days. A Daptomycin release above the minimum inhibitory concentration (MIC) by day 9 and a burst release of 71.7 ± 5.9 % were observed in the loaded ceramics. Low concentrations of BMP-2 were released from the loaded ceramics over 28 days.

SARS-CoV-2 infection can lead to life-threatening clinical manifestations. Patients with cardiovascular disease (CVD) are at higher risk for severe courses of COVID-19. However, strategies to predict the course of SARS-CoV-2 infection in CVD patients at the time of hospital admission are still missing. Here, we investigated whether this prediction is achievable by prospectively analysing the blood immunophenotype of 94 participants, including 20 uninfected and 37 acutely SARS-CoV-2-infected CVD patients and 37 healthy donors, using a 36-colour spectral flow cytometry panel. Unsupervised data analysis revealed little differences between healthy donors and CVD patients, whereas the distribution of the cell populations changed dramatically in SARS-CoV-2-infected CVD patients. The latter had more mature NK cells, activated monocyte subsets, central memory CD4+ T cells, and plasmablasts but fewer dendritic cells, CD16+ monocytes, innate lymphoid cells, and CD8+ T cell subsets. Moreover, we identified an immune signature characterised by mucosal-associated invariant T (MAIT) cells, intermediate effector CD8+ T cells, and natural killer T (NKT) cells that is predictive for CVD patients with a severe course of COVID-19. Thus, intensified immunophenotype analyses can help identify patients at risk of severe COVID-19 at hospital admission, improving clinical outcomes through specific treatment.

In this study, we aimed to reveal the proinflammatory effects of serum 25-hydroxyvitamin D3 (Vit D) deficiency and insufficiency in new-onset type 2 diabetes mellitus (T2DM) and prediabe-tes. We recruited 84 prediabetes patients, 94 new-onset T2DM patients and 113 healthy partici-pants. Levels of C-reactive protein (CRP), fibrinogen, ferritin, interleukin-1β (IL-1β), interleu-kin-6 (IL-6), interleukin-8 (IL-8), tumour necrosis factor-α (TNF-α), nuclear factor kappa-B (NF-κB) and mitogen-activated protein kinase (MAPK) were measured in the serum of the par-ticipants. The ANOVA Bonferonni and Kruskal Wallis Dunn tests were used for the comparison of the inflammation markers and vitamin D levels between the groups. Upon covariance analy-sis with age, gender and BMI; Vit D levels of T2DM group were found to be significantly lower (p<0.003). Proinflammatory markers and CRP were found to be significantly higher in predia-betic and diabetic subjects. In the prediabetes group, IL-1β, IL-6, IL-8, TNF-α and MAPK were significantly higher in those with Vit D insufficiency and deficiency groups. In T2DM group, IL-1β, IL-6, IL-8, TNF-α, NF-κB, MAPK and CRP were significantly higher in those with Vit D insufficiency and deficiency. Our study emphasizes the proinflammatory effects of Vit D on the initiation of inflammation in both prediabetes and diabetes mellitus.

This paper presents a new method for the design of separable denominators 2-D IIR filters with nearly linear phase in the passband. The design method is based on a balanced-realization model reduction technique. The nearly linear-phase 2-D IIR filter is designed using 2-D model reduction from a linear-phase 2-D FIR filter, which serves as the initial filter. The structured controllability and observability Gramians $P^s$ and $Q^s$ serve as the foundation for this technique. These Gramians are block diagonal positive-definite matrices that satisfy 2-D Lyapunov equations. An efficient method is used to compute these Gramians by minimizing the traces of $P^s$ and $Q^s$ under linear matrix inequalities (LMI) constraints. The use of these Gramians ensures that the resulting 2-D IIR filter preserves stability and can be implemented using a separable denominator 2-D filter with fewer coefficients than the original 2-D FIR filter. Numerical examples show that the proposed method compares favorably with existing techniques.

Monoclonal antibodies (mAbs) are an important treatment option for COVID-19 caused by SARS-CoV-2, especially in immunosuppressed patients. However, this treatment option can become ineffective due to mutations in the SARS-CoV-2 genome, mainly in the receptor binding domain (RBD) of the spike (S) protein. In the present study 7950 SARS-CoV-2 positive samples from the Uppsala and Örebro regions of central Sweden collected between March 2022 and May 2023 were whole-genome sequenced using next-generation sequencing, mainly with the Nanopore sequencing method. Pango lineages were determined and all single nucleotide polymorphism (SNP) mutations that occurred in these samples were identified. The dominant sublineages changed over time and mutations conferring resistance to currently available mAbs became common. Notable ones are R346T and K444T mutations in the RBD that confer significant resistance against tixagevimab and cilgavimab mAbs. Further, mutations conferring a high-fold resistance to bebtelovimab, such as the K444T and V445P mutations, were also observed in the samples. This study highlights that resistance mutations have over time rendered currently available mAbs ineffective against SARS-CoV-2 in most patients. Therefore, there is a need for continued surveillance of resistance mutations and the development of new mAbs that target more conserved regions of the RBD.

COVID-19, a contagious disease caused by the novel coronavirus SARS-CoV-2, emerged in 2019 and quickly became a pandemic, infecting more than 700 million people worldwide. The disease incidence, morbidity and mortality rates have started to decline since the development of effective vaccines against the virus and the widespread immunization of the population. SARS-CoV-2 vaccines are associated with minor local or systemic adverse reactions, while serious adverse effects are rare. Thyroid-related disorders have been reported after vaccination for COVID-19, and Graves’ disease (GD) is the second most common amongst them. Thyroid eye disease (TED), an extrathyroidal manifestation of GD is rarely observed post COVID-19 vaccination. All TED cases followed mRNA-based vaccinations, but two new onset mild TED cases post viral vector vaccine (ChAdox1nCoV-19) have also been reported. We report the case of a 63-year-old woman who presented with new onset hyperthyroidism and moderate-to-severe and active TED ten days after she received the first dose of a viral vector vaccine against SARS-CoV-2. This is the first case of moderate-to-severe TED after such a vaccine. Our patient was initially treated with intravenous glucocorticoids and subsequently with intravenous rituximab, due to no response. The disease was rendered inactive after rituximab, but constant diplopia persisted, and the patient was referred for rehabilitative surgery.

Worldwide, the COVID-19 pandemic, which was brought on by the brand-new coronavirus SARS-CoV-2, has claimed a sizable number of lives. Despite the urgency, COVID-19 does not have any particular antiviral treatments at this time. As a result, scientists are concentrating on repurposing already existing antiviral medications or creating brand-new ones. The SARS-CoV-2 main protease, which is necessary for viral replication, has been identified as a possible target for a family of medicines called main protease inhibitors (MPIs). Studies of the major proteases from SARS-CoV and MERS-CoV, which have remarkably similar structures and functions to SARS-CoV-2, have provided insight for the creation of MPIs. By analyzing the MPI trials for SARS-CoV and MERS-CoV, this review sheds light on the possible therapeutic uses of MPIs for COVID-19. The review talks about how MPIs work, how effective they are against SARS-CoV and MERS-CoV, and how safe they are. The paper also emphasizes current developments in the creation of MPIs for SARS-CoV-2, including as computational studies, in vitro and in vivo research, and clinical trials. According to the review, there is a lot of hope for MPIs in the treatment of COVID-19, and numerous medications are in the works. Although more research is needed to assess their safety and effectiveness in clinical settings, these medications may offer patients with COVID-19 a much-needed therapeutic option. The review also emphasizes the importance of ongoing research into the structure and function of the SARS-CoV-2 main protease, as this information will be critical for the development of effective MPIs and other antiviral drugs in the future.

Coronavirus disease-2019 (COVID-19) was seen as a respiratory disease, however, an increasing number of reports indicated that the spike protein could also be the cause of the long-term post-infectious conditions known as Long-COVID characterized by a group of unresponsive idiopathic severe neuro, cardio-vascular disorders, including strokes, cardiopathies, neuralgias, fibromyalgia, and Parkinson's like-disease. Different lines of pieces of evidence confirmed that the spike protein that can be found on the surface of the SARS-CoV-2 virus latches onto angiotensin-converting enzyme 2 (ACE2) receptors located on target cells. The RNA genome of coronaviruses, which, has a median length of 29 kb and is the longest among all RNA viruses, is comprised of six to ten open reading frames (ORFs) that are responsible for encoding both the replicase and structural proteins for the virus. Each of the components of the viral genome is packaged into a helical nucleocapsid that is surrounded by a lipid bilayer. The viral envelope of coronaviruses is typically made up of three proteins that include the membrane protein (M), the envelope protein (E), and the spike protein (S). The spike protein not only facilitates the virus entry into healthy cells, which is the first step in infection but also promote profound damage to different organs and tissues leading to severe impairments and long-term disabilities. Here, we discussed the pervasive mechanism that spikes mRNA adopted to alter multipotent and pluripotent stem cell (SCs) genomes and the acquired disability of generating an infinite number of affected clonal cells. This stance is based on the molecular and evolutionary aspects obtained from retrotransposons-retrotransposition in mammalians and humans that documented the frequent integration of mRNA molecules into genomes and thus into DNA. Retrotransposition is the molecular process in which transcribed and spliced mRNAs are accidentally reverse-transcribed and inserted into new genomic positions to form a retrogene. Sequence-specific traits of mRNA clearly showed long interspersed element-1 (LINE-1 or L1) to confirm the retrotransposition, considered the most abundant autonomously active retrotransposons in the human genome. In mammals, L1 retrotransposons drive retrotransposition and are composed of long terminal repeats (LTRs) and non-LTR retrotransposons (mainly long interspersed nuclear elements or LINEs); specifically, the LTR-mediated retrocopies are immediately cotranscribed with their flanking LTR retrotransposons. In response to retrotransposons transposition, stem cells (SCs) employ a number of silencing mechanisms, such as DNA methylation and histone modification. This manuscript theorizes the expression patterns, functions, and regulation of mRNA Spike protein imprinted by SCs retrotransposons which generate unlimited lines of affected cell progenies and tissues as the main condition of untreatable Spike-related inflammatory conditions.

Gene or genome editing (GE) revises, removes, or replaces a mutated gene at the DNA level; it is a tool. Gene therapy (GT) offsets mutations by introducing a "normal" version of the gene into the body while the diseased gene remains in the genome; it is a medicine. So far, no in vivo GE product has been approved, as opposed to 22 GT products approved by the FDA. However, several are under development, and the FDA anticipates their fast entry, as evidenced by the FDA's actions of issuing GE-specific guidelines. The potential of GE in treating diseases far supersedes any other modality due to the recognized role of genes in most human diseases. While GT products add missing genes, GE tools can overcome many aberrations. However, GE presents many safety challenges, including off-target impact, delivery consistency, and long-term effects of gene-fixing. However, most of these concerns will be resolved once the FDA begins approving them, leading to hundreds of products capable of treating untreatable diseases.

New Jersey was among the first states impacted by the COVID-19 pandemic, with one of the highest overall death rates in the nation. Nevertheless, relatively few reports have been published focusing specifically on New Jersey. Here we report on molecular, clinical, and epidemiologic observations from the largest healthcare network in the state, in a cohort of vaccinated and unvaccinated individuals with laboratory-confirmed SARS-CoV-2 infection. We conducted molecular surveillance of SARS-CoV-2-positive nasopharyngeal swabs collected in nine hospitals from December 2020 through June 2022, using both whole genome sequencing (WGS) and a real-time RT-PCR screening assay targeting spike protein mutations found in variants of concern (VOC) within our region. De-identified clinical data were obtained retrospectively, including demographics, COVID-19 vaccination status, ICU admission, ventilator support, mortality, and medical history. Statistical analyses were performed to identify associations between SARS-CoV-2 variants, vaccination status, clinical outcomes, and medical risk factors. A total of 5,007 SARS-CoV-2-positive nasopharyngeal swabs were successfully screened and/or sequenced. Variant screening identified three predominant VOC, including Alpha (n =714), Delta (n =1,877), and Omicron (n =1,802). Omicron isolates were further sub-typed as BA.1 (n =899), BA.2 (n =853), and BA.4/BA.5 (n =50); the remaining 614 isolates were classified as “Other”. Approximately 31.5% (1,577/5,007) of the samples were associated with vaccine breakthrough infections, which increased in frequency following the emergence of Delta and Omicron. Severe clinical outcomes included ICU admission (336/5007 = 6.7%), ventilator support (236/5007 = 4.7%), and mortality (430/5007 = 8.6%), with increasing age being the most significant contributor to each (p &lt;0.001). Unvaccinated individuals accounted for 79.7% (268/336) of ICU admissions, 78.3% (185/236) of ventilator cases, and 74.4% (320/430) of deaths. Highly significant (p &lt;0.001) increases in mortality were observed in individuals with cardiovascular disease, hypertension, cancer, diabetes, and hyperlipidemia, but not with obesity, thyroid disease, or respiratory disease. Significant differences (p &lt;0.001) in clinical outcomes were also noted between SARS-CoV-2 variants, including Delta, Omicron BA.1, and Omicron BA.2. Vaccination was associated with significantly improved clinical outcomes in our study, despite an increase in breakthrough infections associated with waning immunity, greater antigenic variability, or both. Underlying comorbidities contributed significantly to mortality in both vaccinated and unvaccinated individuals, with increasing risk based on the total number of comorbidities. Real-time RT-PCR-based screening facilitated timely identification of predominant variants using a minimal number of spike protein mutations, with faster turnaround time and reduced cost compared to WGS. Continued evolution of SARS-CoV-2 variants will likely require ongoing surveillance for new VOCs, with real-time assessment of clinical impact.

Cancer patients may experience significant distress. The “Emotion Thermometers” (ETs) are a short visual analogue scale used to screen patients for psychosocial risk. This study aimed to assess emotional distress in a large sample of cancer patients attending psychological services at an NGO, and to explore factors that may contribute to it. The ETs were answered by 899 cancer patients. They were, on average, 59.9 years old, the majority were female, had breast cancer, were under treatment or were disease-free survivors, and reported high levels of emotional distress, above the cut-off (≥5). A Generalized Linear Model was used to measure the association between the level of Distress and 33 items of the problem list. Four items - sadness, depression, sleep and breathing - were found to be significantly related to a higher level of Distress. Additionally, women and those who were in the palliative phase also had significantly higher levels of Distress. Conclusions: The results confirm the need for early emotional screening in cancer patients, as well as the relevance of attending to the characteristics of each patient. Additionally, they highlight the utility of the ETs for the clinical practice, allowing to optimize the referral to specialized psy-chosocial services.

Forest damage has become more frequent in Europe in the last decades, and remote sensing offers a powerful tool for monitoring them rapidly and cost-effectively. A novel approach was developed to utilize high-resolution ESA Sentinel-2 satellite imagery and Google Earth Engine cloud computing. The processing, analysing, and visualization of vegetation and water index (NDVI, NDVIch, Z NDVI, EVI, NDWI) maps and charts derived from satellite images took place in the cloud to ensure the detection of forest disturbances in the Hungarian study site for the period 2017-2020. The index maps were classified to reveal forest disturbances, and the cloud-based method successfully showed drought and frost damage in the oak-dominated Nagyerdő forest of Debrecen. Differences in the reaction to damage between tree species were visible in the index values, therefore a Random Forest Machine Learning classifier was applied to show the spatial distribution of dominant species. Accuracy assessment was accomplished with confusion matrices that compared classified index maps to field-surveyed data, demonstrating 71% Total Accuracy for forest damage and 76% for tree species. Based on the results of this study and the resilience of Google Earth Engine, the presented method has the potential to be extended to monitor the entire Hungary.

The spread of SARS-CoV-2 variants of concern (VOCs), is of great importance to the whole community, since their genetic changes may increase transmissibility, disease severity and reduce effectiveness of vaccines. Moreover, these changes may lead to failure of diagnostic measures, thus variant-specific diagnostic methods are essential. To date, genetic sequencing is the gold standard method to discriminate between variants, however it is time consuming (several days) and expensive. Therefore, the development of rapid diagnostic methods for SARS-CoV-2 in accordance with its genetic modification is of great importance. In this study, we introduce a Mass-Spectrometry (MS)-based methodology for the diagnosis of SARS-CoV-2 in clinical specimens, a methodology which enables universal identification, alongside with variant-specific discrimination. The universal identification of SARS-CoV-2 is based on conserved markers shared by all variants, while the identification of the specific variant relies on variant-specific markers. Determining a specific set of peptides for a given variant consists of a multistep procedure, starting with in-silico search for variant-specific tryptic peptides, followed by tryptic digest of a cell-cultured SARS-CoV-2 variant and identification of these markers by HR-LC-MS/MS analysis. As a proof of concept, this approach was demonstrated for four representative VOCs, in comparison with the wild-type Wuhan reference strain. For each variant, at least two unique markers, derived mainly from the spike (S) and nucleocapsid (N) viral proteins, were identified. This methodology is specific, rapid, easy to perform and inexpensive, therefore can be applied as a general diagnostic tool of pathogenic variants.

Steroid-responsive meningitis-arteritis (SRMA) is a predominantly Th-2 immune-mediated dis-ease, but exact pathomechanism remains still unclear. Interleukin-31 (IL-31) is predominantly produced by T cells with a Th-2 phenotype during proinflammatory conditions. We hypothesize, IL-31 might be involved in the pathogenesis of SRMA. IL-31 was measured in archived samples (49 serum and 52 CSF samples) of dogs with SRMA, Meningoencephalitis of unknown origin (MUO), infectious meningoencephalitis, atopic dermatitis and of healthy control dogs using a competitive canine IL-31 ELISA. Mean serum IL-31 level in dogs with SRMA (n=18) was mildly higher compared to dogs with atopic dermatitis (n=3) and MUO (n=15) and markedly higher than in healthy controls (n=10) and dogs with infectious meningoencephalitis (n=3). Dogs with SRMA in the acute stage of the disease and without any pre-treatment had the highest IL-31 levels. The mean CSF IL-31 value of dogs with SRMA (n=23) was quite similar to healthy controls (n=8) and did not differ significantly from dogs with MUO (n=19) and infectious meningoencephalitis (n=2). Based on this study, an involvement of IL-31 in the pathogenesis of the systemic Th-2 im-mune-mediated immune response in SRMA can be assumed as a further component leading to an aberrant immune reaction.

Metabolic-associated fatty liver disease (MAFLD) and its potential impact on the severity of COVID-19 have gained significant attention during the pandemic. This review aimed to explore the genetic determinants associated with MAFLD, previously recognized as non-alcoholic fatty liver disease (NAFLD), and their potential influence on COVID-19 outcomes. Various genetic polymorphisms, including PNPLA3 (rs738409), GCKR (rs780094), TM6SF2 (rs58542926), and LYPLAL1 (rs12137855), have been investigated in relation to MAFLD susceptibility and progression. Genome-wide association studies and meta-analyses have revealed associations between these genetic variants and MAFLD risk, as well as their effects on lipid metabolism, glucose regulation, and liver function. Furthermore, emerging evidence suggests a possible connection between these MAFLD-associated polymorphisms and the severity of COVID-19. Studies exploring the association between indicated genetic variants and COVID-19 outcomes have shown conflicting results. Some studies observed a potential protective effect of certain variants against severe COVID-19, while others reported no significant associations. This review highlights the importance of understanding the genetic determinants of MAFLD and its potential implications for COVID-19 outcomes. Further research is needed to elucidate the precise mechanisms linking these genetic variants to disease severity and to develop gene profiling tools for early prediction of COVID-19 outcomes. If confirmed as determinants of disease severity, these genetic polymorphisms could aid in identifying high-risk individuals and improving the management of COVID-19.

The uneven immunogenicity of the attenuated tetravalent dengue vaccine has created the diffi-culty to achieve a balanced protection against all four serotypes of dengue virus (DENV). To overcome this problem, non-replicative-based vaccines have come into focus as their immuno-genicity is adjustable. This approach is excellent for multivalent vaccines but commonly faces the issue of low immunogenicity. In this present study, we developed a non-replicating dengue vaccine composing of UV-inactivated dengue-2 virus (UV-DENV2) and DENV-2 NS1-279 protein encapsidated within nanoparticles. This vaccine candidate was administered in the presence of BCG cell wall cytoskeleton (BCG-CWS) as an adjuvant. We revealed, here, that encapsidated immunogens with BCG-CWS exerted potent activities on both B and T cells and elicited Th-1/Th-2 responses in mice. This was evidenced by strong neutralizing antibody activity with an unde-tectable antibody enhancing activity in a group of mice receiving encapsidated immunogens with BCG-CWS. Importantly, BCG-CWS significantly augmented antibody-mediated comple-ment-fixing activity, strongly stimulated the antigen-specific polyfunctional T cell responses as well as activated mixed Th-1/Th-2 responses specific to DENV2- and NS1-279 antigens. In conclu-sion, BCG-CWS potently adjuvanted the inactivated DENV-2 and subunit DENV immunogens. The mechanism of adjuvanticity remains unclear. This study revealed the potential use of BCG-CWS in vaccine development.

Introduction: SARS-CoV-2 infection was first reported in 2019 and has since spread throughout the world. This is a cross-sectional study in cooperation with 118 Department of Pre-Hospital and Territorial Emergency (118 SET) of Taranto City and the University of Bari, Aldo Moro, and the School of Medicine from Italy. We conducted a study on how the COVID-19 epidemics evolved and how it was contained by different countermeasures by taking into account data showing socio-demographic and that older persons, as well as individuals with comorbidities and poor metabolic health, and people coming from economically depressed areas with lower quality of life in general, are more likely to develop severe COVID-19 infection. Objective: Examine the association between county-level socio-demographic risk factors and COVID-19 incidence and mortality, determining the possible emo-biological markers, ferritin, and lymphocytes, that could be indicative of SARS-CoV-2 infection. Methods: Descriptive cross-sectional study on 600 patients examined and treated at general hospital Ninh Thuan from January to September 2022. Results: 33/600 patients were confirmed to be infected with SARS-CoV-2 (5.5%), males 4.8% and females 5.8%, the median age of infected patients is 36 years. Most infections were mild (75.8%). Our results revealed that the structure and the spatial arrangement of socio-demographic arrangements are important either as epidemiological determinants or as disease markers. Conclusion: Approximately 5.5% of patients infected with SARS-CoV-2 come to examination and treatment at the hospital, these findings suggested that possible infection rate in the burden of the COVID-19 pandemic, the sociodemographic risk factors, and their root causes must be addressed. In addition, lab results obtained from affected patients showed that lymphocytes and ferritin could be considered traits of mild COVID-19 infection.

The objective of the present study is to analyze COVID-19 transmission in specific dampest regions with excess rainfall and recurring fogs. The working hypothesis is that widespread transmission of SARS CoV 2 (leading to COVID-19) and similar viral agents can be explained by specific climate factors having high air humidity. The main case study of the Turkish Black Sea region is investigated. Results reveal that the provinces in region under study have some climate factors and geographical features that foster the accelerated transmission of viral agents, such as SARS-CoV-2, and consequential negative impact on society. In particular, Spearman's Correlation Coefficient shows a statistically significant positive association between the average atmospheric pressure and the spread of the COVID-19 confirmed cases in Samsun province (Spearman’s correlation coefficient rs =0.86, p-value 0.05). A statistically significant positive association between the average precipitation and the spread of COVID-19 confirmed cases in Sinop province (Spearman’s correlation coefficient rs =0.79, p-value 0.05), and finally, a statistically significant negative association between the average sun hour and the spread of the COVID-19 confirmed cases in Samsun province (Spearman’s correlation coefficient rs = 0.89, p-value 0.01). These findings suggest that regions' geographical characteristics, demographic structure, climate and environmental parameters must be considered in the national scale epidemic management plans to design effective anti-pandemic health policies to cope with future waves of the COVID-19 and new airborne diseases and to reduce negative effects on health, social and economic systems.

As the name implies, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA virus and a member of the corona virus family, primarily affecting the upper respiratory system and the lungs. Like many other respiratory viruses, SARS-CoV-2 can spread to other organ systems. Apart from causing diarrhea, another most common but debilitating complication caused by the SARS-CoV-2 is neurological symptoms and cognitive difficulties, which occur in up to two thirds of hospitalized covid patients and ranging from shortness of concentration, overall declined cognitive speed to executive or memory function impairment. Neuro-cognitive dysfunction and “brain fog” are frequently present in COVID-19 cases, which can last several months after the infection, leading to disruption of daily life. Cumulative evidence suggests that SARS-CoV-2 affects vasculature in the extra pulmonary systems directly or indirectly, leading to impairment of endothelial function and even multi-organ damage. The post COVID-19 long-lasting neurocognitive impairments have not been studied fully; and the underlying mechanism remains elusive. In this review, we summarize the current understanding of the effects of COVID-19 on vascular dysfunction and how vascular dysfunction leads to cognitive impairment in patients.

2-(5,6-diphenyl-1,2,4-triazin-3-yl)pyridinium dichloroiodate (I) (1) was synthesized by reacting 3-(2-pyridyl)-5,6-diphenyl-1,2,4-triazine with ICl in dichloromethane solution. The structural characterization of 1 by SC-XRD analysis was accompanied by elemental analysis, FT-IR, and FT-Raman spectroscopy measurements.

Synthetic antivirals and corticosteroids have been used to treat both influenza and the SARS-CoV-2 disease named COVID-19. However, these medications are not always effective, produce several adverse effects, and are associated with high costs. Medicinal plants and their constituents act in several different targets and signaling pathways involved in the pathophysiology of Influenza and COVID-19. This study aimed to perform a review to evaluate the effects of medicinal plants on Influenza and COVID-19 and to investigate the potential delivery systems for new antiviral therapies. EMBASE, PubMed, GOOGLE SCHOLAR, and COCHRANE databases were searched. The studies included in this review showed that medicinal plants, in different formulations, can help decrease viral spread and time of full recovery. Plants reduced the incidence of acute respiratory syndromes and the symptom scores of the illnesses. Moreover, plants are related to few adverse effects and have low costs. In addition to their significance as natural antiviral agents, medicinal plants and their bioactive compounds may exhibit low bioavailability. This highlights the need for alternative delivery systems, such as metal nanoparticles, that can effectively transport these compounds to infected tissues.

In post mortem analyses, SARS-CoV-2 was found in the middle ear of some, but not all patients with COVID-19 disease. It is not clear whether SARS-CoV-2 penetrated the ear passively post mortem, or existed in the middle ear of living patients during, and perhaps also after infection. This study investigates whether SARS-CoV-2 can be found in the middle ear of living patients during ear surgery. Swabs from the nasopharynx, the filter connected to the tracheal tube and secretion from the middle ear were collected during middle ear surgery. All samples were tested for the presence of SARS-CoV-2 with PCR. History of vaccination, COVID-19 and contact with SARS-CoV-2-positive individuals were recorded preoperatively. Postoperative SARS-CoV-2 infection was noted at the follow-up visit. Overall 63 participants (62%) were children and 39 (38%) were adults. SARS-CoV-2 was found in the middle ear and in the nasopharynx of two and four CovEar Study participants, respectively. The filter connected to the tracheal tube was sterile in all cases. Cycle threshold (ct) values of the PCR test were between 25.94 and 37.06. SARS-CoV-2 penetrates into the middle ear of living patients and can be found in asymptomatic patients. The presence of SARS-CoV-2 in the middle ear may have implications for ear surgery and can pose a risk of infection for operating room staff. It may also directly affect the audio-vestibular system.

The COVID-19 pandemic has underscored the importance of swift responses and the necessity of dependable technologies for vaccine development. Our team previously developed a fast cloning system for the modified vaccinia virus Ankara (MVA) vaccine platform. In this study, we report the construction and preclinical testing of a recombinant MVA vaccine obtained using this system. We obtained recombinant MVA expressing the unmodified full-length SARS-CoV-2 spike (S) protein containing the D614G amino acid substitution (MVA-Sdg) and a version expressing a modified S protein containing amino acid substitutions designed to stabilize the protein a in a pre-fusion conformation (MVA-Spf). S protein expressed by MVA-Sdg was found to be expressed and correctly processed and transported to the cell surface, where it efficiently produced cell-cell fusion. Version Spf, however, was not proteolytically processed and despite being transported to the plasma membrane, it failed to induce cell-cell fusion. We assessed both vaccine candidates in prime-boost regimens in the susceptible transgenic K18-human angiotensin converting enzyme 2 (K18-hACE2) mice and in golden Syrian hamsters. Robust immunity and protection from disease was induced with either vaccine in both animal models. Remarkably, the MVA-Spf vaccine candidate produced higher levels of antibodies, a stronger T cell response, and a higher degree of protection from challenge. In addition, the levels of SARS-CoV-2 in the brain of MVA-Spf inoculated mice was decreased to undetectable levels. Those results add to our current experience and range of vaccine vectors and technologies for developing a safe and effective COVID-19 vaccine

In this review, we aimed to understand the relationship between SARS-CoV-2 infection and preeclampsia severity in infected pregnant women. Pregnant women with SARS- CoV-2 infection have been shown to have a significantly increased risk of maternal death, ICU admission, preterm delivery, and stillbirth compared with those without infection. The risk of preeclampsia also increases in pregnant women infected with SARS-CoV-2, particularly in those with severe symptoms. We emphasize the im-portance of specialized clinical management to prevent poor pregnancy outcomes in this situation. The association between COVID-19 and preeclampsia (PE) is likely due to multiple mechanisms, including the direct effects of the virus on trophoblast function and the arterial wall, acute atherosis, local inflammation leading to pla-cental ischemia, exaggerated inflammatory responses in pregnant women, SARS-CoV-2-related myocardial injury, cytokine storm, and thrombotic microan-giopathy. Emphasis has been placed on the potential impact of COVID-19 on pregnant women, specifically in relation to thrombotic complications, placental dysfunction, and cardiovascular dysfunction. Undoubtedly, one of the diagnostic tools to differentiate between COVID-19-induced preeclampsia-like syndrome and true preeclampsia is the use of biomarkers, such as the sFlt-1/PlGF ratio. We wish to highlight the potential for COVID-19-induced myocardial injury in pregnant women and the associated in-crease in maternal mortality rate. Vaccination against COVID-19 in the general population and in pregnant women in particular, drastically reduced the severity of the disease. There is an urgent need to continue the follow-up of these women and their children to detect the appearance of sequelae of the disease or peristent COVID 19

Aim: Aging is companied by deteriorations of insulin resistance (IR) and insulin secretion. However, little is known about the roles of aging on different phases of insulin secretion (ISEC); i.e., the first- and second-phase of insulin secretion (FPIS, SPIS) and glucose effectiveness (GE). Methods: Totally 169 individuals (43 men and 126 women) with the similar fasting plasma glucose (FPG: 90 mg/dL) and BMI (men: 23 kg/m2, women 22 kg/m2) were enrolled. IR, FPIS, SPIS, and GE were estimated using our previously developed equations shown below. Pearson correlation analysis was conducted to assess the correlations between age and four diabetes factors (DFs: IR, FPIS, SPIS and GE). The equations that are used to calculate the DF in the present study were built and published by our group. Results: The age of the participants ranged from 18- to 78-year-old. Men had higher FPIS but lower HDL-C levels than women (2.067±0.159, 1.950±0.186 μU/min and 1.130±0.306, 1.348±0.357 mmol/dl, accordingly). The results of Pearson correlation revealed that age was negatively related to IR and GE in both genders (IR: r = -0.39, p < 0.001 for men, r = -0.24, p < 0.003 for women; GE: r = 0.66, p < 0.001 for men, r = 0.78, p < 0.001 for women). In the meanwhile, FPIS was also only found to be negatively correlated with age in female (r = -0.238, p = 0.003). But there was no different with SPIS and age in both of genders. Conclusions: We have found that in Chinese with normal FPG level (90 mg/dl) and body mass index (men: 23 kg/m2, women: 22: kg/m2), age is negatively related to IR and GE in both genders. At the same time, only FPIS was found to be negatively related to age in women. The tightness of their relationships, from the highest to the lowest are, GE, FPIS and IR accordingly. The importance of GE should be re-evaluated. These results should be interpreted with caution because of the small sample size.

Abstract The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in people in the city of Wuhan at the end of December 2019, and it has since spread to all continents. Global interest has been focused on discovering a treatment and developing a successful coronavirus vaccine as a result of the emergence of this new coronavirus. In this research, we sequenced the whole genome of the SARS-COV-2 virus that were isolated from 40 patients in Duhok, Iraq. 95 different mutations were identified in our isolation when such the whole genome sequence of the SARS-COV-2 isolated from the city of Wuhan, China (Accession number: NC 045512.2) was matched to the virus's sequence using Sequencing technology (Illumina , USA ) and Assembly method (iVar 1.3.1). Sequence analysis revealed that 38 mutations were found at spike glycoprotein (S), 30 of which were found in the ORF1b , 11 mutations were found in ORF1b ,7,3,2,1 mutations were found in ( N,M,ORF6 ,ORF9 /E ) genes which had been linked to structural changes at various places. The conclusion that the cases in Iraq were of different origins of infections and had a close relationship with the isolates from different country and state were further confirmed by phylogenetic analysis and transmission. The whole genome sequence of the SARS-CoV-2 , which were identified from the Iraqi Kurdistan region, and reported as a first study in Kurdistan region.

Smartphone-based point-of-care testing (POCT) is rapidly emerging as an alternative to traditional screening and laboratory testing, particularly in resource-limited settings. In this proof-of-concept study, we present a smartphone- and cloud-based artificial intelligence quantitative analysis system (SCAISY) for relative quantification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific IgG antibody lateral flow assays that enables rapid and accurate evaluation of test strips. By capturing an image with a smartphone camera, SCAISY quantitatively analyzes antibody levels and provides results to the user. We analyzed changes in antibody levels over time in over 248 individuals, including vaccine type, number of doses, and infection status, with a standard deviation of less than 10%. We also tracked antibody levels in six participants before and after SARS-CoV-2 infection. Finally, we examined the effects of lighting conditions, camera angle, and smartphone type to ensure consistency and reproducibility. This study suggests that SCAISY is a simple and powerful tool for real-time public health surveillance, enabling the acceleration of quantifying SARS-CoV-2-specific antibodies generated by either vaccination or infection and tracking of personal immunity levels.

Essential oils have demonstrated antiviral activity, but their toxicity can hinder their use as therapeutic agents. Recently, some essential oil components have been used within safe levels of acceptable daily intake limits without causing toxicity. The "ImmunoDefender," a novel antiviral compound made from a well-known mixture of essential oils, is considered highly effective in treating SARS-CoV-2 infections. The components and doses were chosen based on existing information about their structure and toxicity. Blocking the Main Protease (Mpro) of SARS-CoV-2 with high affinity and capacity is critical for inhibiting the virus's pathogenesis and transmission. In-silico studies were conducted to examine the molecular interactions between the main essential oil components in "ImmunoDefender" and SARS-CoV-2 Mpro. The screening results showed that six key components of ImmunoDefender formed stable complexes with Mpro via its active catalytic site with binding energies ranging from -8.75 to -10.30 kcal/mol, respectively for Cinnamtannin B1, Cinnamtannin B2, Pavetannin C1, Syzyginin B, Procyanidin C1, and Tenuifolin. Furthermore, three essential oil bioactive inhibitors, Cinnamtannin B1, Cinnamtannin B2, and Pavetannin C, have a significant ability to bind to the allosteric site of the main protease with binding energies of -11.12, -10.74, and -10.79 kcal/mol, These results suggest that these essential oil bioactive compounds may play a role in preventing the attachment of the translated polyprotein to Mpro, inhibiting the virus's pathogenesis and transmission. These components also had drug-like characteristics similar to approved and effective drugs, suggesting further pre-clinical and clinical studies are needed to confirm the generated in-silico outcomes.

This paper presents the symmetries of differential equations associated with one-variable and Bivariate Hermite polynomials by proposing a representation of Lie algebra for these differential operators. Applying the Baker-Campbell-Hausdorff formula to these algebras, results in new relations and generating functions in one-variable and Bivariate Hermite polynomials. A general form of representation for other orthogonal polynomials such as Laguerre polynomials is introduced.

Background Hydroxychloroquine (HCQ) combined with azithromycin (AZM) has been widely administered to patients with COVID-19 despite scientific controversies. In particular the potential to prolong cardiac repolarisation by using this combination has been discussed. Materials and methods We report a pragmatic and simple safety approach which we implemented in the first patients treated for COVID-19 in our center early 2020. Treatment contraindications were the presence of severe structural or electrical heart disease, baseline corrected QT interval (QTc) >500 ms, hypokalaemia, or other drugs prolonging QTc that could not be interrupted. Electrocardiogram and QTc was evaluated at admission and re-evaluated after 48 hours of the initial prescription. Results Among 424 consecutive adults (mean age 46.3 ± 16.1 years; 216 women). Patients were followed in conventional wards (21.5%) or in a day-care unit (78.5%). A total of 11 patients (2.6%) had contraindications to HCQ-AZ combination. In the remaining 413 treated patients, there were no arrhythmic events in any patient during the 10-day treatment regimen. QTc was slightly but statistically significantly prolonged by 3.75 ± 25.4 ms after two days (p=0.003). Ten patients (2.4%) developed QTc prolongation >60 ms, and none had QTc >500 ms. Conclusions This report do not aim to contribute to knowledge of the efficacy of treating COVID-19 with HCQ-AZ. However, a simple initial assessment of patient medical history, ECG and kalaemia identifies contraindicated patients and enables the safe treatment by HCQ-AZ of COVID-19 patients. QT-prolonging anti-infective drugs can be used safely in acute life-threatening infections, provided that a strict protocol and close collaboration between infectious disease specialists and rhythmologists are followed.

Water quality is the measure of chemical, physical and biological suitability of water in relation to natural effects and intended purpose which may affect human health and aquatic life. Assessment of water quality is very essential for the management of water resources and human health. Traditionally, in-situ measurements have been used to obtain the water quality parameters of the water bodies. However, with the availability of satellite images, researchers have shown that satellite images are a reliable tool that can be used to estimate water quality. Satellite image-derived water quality parameters provide extensive spatial extent and large temporal variations when compared to traditional in situ sample collection and laboratory measurements. The present work estimated several parameters for quality of water in the Kamuzu reservoir of Lilongwe River for the 2013-2020 period using Sentinel-2 and Landsat-8 satellite images. The band ratio algorithms were used to retrieve Chlorophyll a (Chl-a), Turbidity, Total Suspended Matter (TSM), Secchi depth, Coloured Dissolved Organic Matter (CDOM), and Cyanobacteria from the reservoir. Turbidity and TSM were compared with the in-situ data collected over the same period. The comparison indicated R² of 0.9 and 0.69 for TSM and Turbidity respectively from Sentinel-2 images whereas R² of 0.56 and 0.61 was obtained using Landsat 8 images which are quite encouraging. The other set of results included the spatial distribution maps of water quality parameters using Landsat-8 and Sentinel-2 satellite data. It was observed that the spatial distribution of water quality parameters, except for CDOM and Cyanobacteria, showed very good distribution and matches with the theoretical results. However, for CDOM and Cyanobacteria, the distribution was almost similar for the entire study area and the band ratio algorithm may not be able to estimate them quite reasonably. This research reiterates the need for the use of remote sensing in estimating the water quality parameters and may be a substitute to the in-situ data, in terms of spread and frequency, which is very common to most of the water bodies, across the globe.

Due to the fact that to date, the question of the origin of SARS-CoV-2 has not been resolved yet, the author analyzed the main advances in the development of genetic engineering of viruses that took place before the onset of the COVID-19 pandemic. The first artificial genetically modified viruses could appear in nature in the mid-1950s. The technique of nucleic acid hybridization was developed by the end-1960s. In the late 1970s, a method called the "reverse genetics" emerged to synthesize RNA and DNA molecules. In the early 1980-s, it became possible to combine the genes of different viruses and insert the genes of one virus into the genome of another virus. Since that time, the production of vector vaccines began. Currently, by modern technologies one can assemble any virus based on the nucleotide sequence available in the virus database or designed by a computer as a virtual model.Scientists around the world are invited to answer the call of Neil Harrison and Jeffrey Sachs of Columbia University, for a thorough and independent investigation into the origin of SARS-CoV-2. Only a full understanding of the origin of the new virus can minimize the likelihood of a similar pandemic in the future.

The calculation of the exact value of the square root of 2 is requested. In order to obtain its infinite value, A new concept is proposed where the accumulations of the infinitely many of finity is indicated by the change in direction which means that there is a jump from finity to infinity .The meaningless for an infinite number with a decimal point is indicated by this jump because any decimal number only have meanings within a finite range values and there is only an infinite integer quantity that can not be operated by algorithms like operations of multiplication，division,addition, and subtraction . The final result of the change in direction is two quantity where the second quantity and the first quantity extend in parallel line and never intersect and the second quantity represent the size of the first quantity. The first quantity is the infinitely great that can't be talked about anything outside of it and can compress any quantities outside of it to nothing and it is the exact value of the square root of 2 .

The article is devoted to the problem of autoimmune diseases provocation by coronavirus infection and the role of molecular mimicry in this phenomenon. SARS-CoV-2 can disguise its proteins as human ones in order to avoid immune attack. A bioinformatics analysis of the probable pentapeptide sharing between human autoantigens of endocrinocytes and SARS-CoV-2 spike protein, membrane protein and nucleocapsid protein was performed. Antigen mimicry between S-proteins of all other known human Coronaviruses and typical target autoantigens of endocrinocytes was also explored. Six human-identical regions were found in the SARS-CoV-2 membrane and nucleocapsid proteins, all of them in their immunodominant epitopes. All shared epitopes belong to antigens of endocrine cells commonly targeted during autoimmune endocrinopathies. Moreover, samples of the pituitary, adrenal and thyroid from patients who died from coronovirus infection (COVID-19) were studied morphologically using histochemical methods. A high frequency of SARS-CoV-2 caused inflammation of the studied endocrine organs was found in patients who died from severe COVID-19. At the same time, the abundant expression of virus antigens by the cells of the adenohypophysis was combined with the complete absence of its expression by the cells of the neurohypophysis. SARS-CoV-2 infected cells apparently perished by non-apoptotic pathway. The foci of lesions in endocrine organs contained abundant lymphocytic infiltrates which may witness for the impact of autoimmune processes. The facts revealed emphasize the need of endocrinological diagnostic alertness of a physician while observing patients with post-vaccination and post-COVID-19 health disorders. [3 figures, 6 tables, bibliography: 45 references].

Abstract: The SARS-CoV-2 pandemic has reemphasized the urgent need for broad-spectrum antiviral therapies. We developed a computational workflow using scRNA-Seq data to assess cellular metabolism during viral infection. With this workflow we predicted the capacity of cells to sustain SARS-CoV-2 virion production in patients and found a tissue-wide induction of metabolic pathways that support viral replication. Expanding our analysis to influenza A and dengue viruses, we identified metabolic targets and inhibitors for potential broad-45 spectrum antiviral treatment. These targets were highly enriched for known interaction partners of all analyzed viruses. Indeed, phenformin, an NADH:ubiquinone oxidoreductase inhibitor, suppressed SARS-CoV-2 and dengue virus replication. Atpenin A5, blocking succinate dehydrogenase, inhibited SARS-CoV-2, dengue virus, respiratory syncytial virus, and influenza A with high selectivity indices. In vivo, phenformin showed antiviral activity against SARS-CoV-2 in a Syrian hamster model. Our work establishes host metabolism as druggable for broad-spectrum antiviral strategies, providing invaluable tools for pandemic preparedness.

High circulating concentrations of the gut microbiota-derived metabolite trimethylamine N-oxide (TMAO) are significantly associated with the risk of obesity and type 2 diabetes (T2D). We aimed at evaluating the impact of glycemic control and bariatric surgery on circulating concentrations of TMAO and its microbiota-dependent intermediate, γ-butyrobetaine (γBB), in newly diagnosed T2D patients and morbidly obese subjects. An additional experiment was carried out in eight male C57BL/6J mice fed a Western-type diet for twelve weeks. The strategy for glycemic control in the T2D patients significantly improved the HbA1c concentrations without producing changes in the estimated glomerular filtration rate. However, the plasma TMAO and γBB concentrations were significantly increased following the glycemic control in T2D patients. Bariatric surgery was very effective in reducing weight in obese subjects. Nevertheless, the surgery reduced plasma γBB concentrations without affecting TMAO concentrations and the estimated glomerular filtration rate. Neither diet-induced obesity nor insulin resistance were associated with circulating TMAO and γBB concentrations in mice. Our findings do not support that glycemic control or bariatric surgery improve the circulating concentrations of TMAO in newly diagnosed T2D and morbidly obese patients. The contribution of antidiabetic drugs to gut microbiota composition could explain TMAO elevations in treated T2D subjects.

Interferometry Synthetic Aperture Radar (InSAR) is an advanced remote sensing technique for studying the earth's surface topography and deformations. It is used to generate high-quality Digital Elevation Models (DEMs). DEMs are a crucial and primary input to various topographical quantification and modelling applications. The quality of input DEMs can be further improved using fusion methods, which combine multi-sensor or multi-temporal datasets intelligently to retrieve the best information amongst the input data. This research study is based on developing a Neural Network based fusion approach for improving InSAR based DEMs in plain and hilly terrains. The study areas comprise of relatively plain terrain from Ghaziabad and hilly terrain of Dehradun and their surrounding regions. The training dataset consists of DEM elevations and derived topographic attributes like slope, aspect, topographic position index (TPI), terrain ruggedness index (TRI), and vector roughness measure (VRM) in different land use land cover classes of the study areas. The spaceborne altimetry ICESat-2 ATL08 photon data is used as a reference elevation. A Feed Forward Neural Network with backpropagation algorithm is trained based on the prepared training samples. The trained model produces fused DEMs by learning the relationship between the input and target samples. This is used to predict elevations in the test areas. The accuracy of results from the models are assessed with TanDEM-X 90 m DEM. The fused DEMs show significant improvement in terms of RMSE over the input DEMs with improvement factor of 94.65 % in plain area and 82.62 % in hilly area. The study concludes that the ANN with its universal approximation property is able to significantly improve the fused DEM.

With the emergence of COVID-19 pandemic in 2019, the world saw a humungous loss of human life and economic resources globally but also the rapid appearance of SARS-CoV-2 variants which have exhibited a higher transmissibility and/or virulence and which also evade immune system to such an extent that it raises a big question mark on the efficacy of current diagnostics, vaccines and convalescent plasma and mAb therapies. This has been attributed to the emergence of huge spectrum of mutations, especially in the virus’s spike (S) protein, occurring in regions harboring high concentration of B cell epitopes thus allowing neutralizing antibody escape. The mutations resulting in ACE 2 receptor recognition failure (T19R), unfavorable electrostatic interactions (E484K), structural change (∆69-70), disruption of hydrogen bonds, salt bridges or hydrophobic interactions (K417N, N501Y, ∆Y145) and change in orientation (N501Y) cause strong immune evasion by these variants. Further, the recent emergence of Omicron with more than 30 mutations in the S protein VOC allows it to escape and fail diagnosis as well as immune system and the protection generated by different vaccination regimes. Yet Omicron may not be the end of the story. This review presents an insight of the immunity escape and its mechanisms followed by different SARS-CoV-2 variant of concerns.

The coronavirus disease of 2019, COVID-19, is caused by an infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was recognized in late 2019 and has since spread worldwide leading to a pandemic with unprecedented health and financial consequences. There remains an enormous demand for new diagnostic methods that can deliver fast, low-cost, and easy-to-use confirmation of a SARS-CoV-2 infection. We have developed an affordable electrochemical biosensor for the rapid detection of serological immunoglobulin (Ig) G antibody in sera against the Spike protein. Materials and Methods: A previously identified linear B-cell epitope (EP) specific to SARS-CoV-2 spike glycoprotein and recognized by IgG in patient sera was selected for the target molecule. After synthesis, the EP was immobilized onto the surface of the working electrode of a commercially available screen-printed electrode (SPE). The capture of SARS-CoV-2 specific IgGs allowed the formation of an immunocomples that was measured by square wave voltammetry from its generation of hydroquinone (HQ). Results: An evaluation of the performance of the EP-based biosensor presented a selectivity and specificity for COVID-19 of 93% and 100%, respectively. No cross-reaction was observed to antibodies against other diseases that included Chagas disease, Chikungunya, Leishmaniosis, and Dengue. Differentiation of infected and non-infected individuals was possible even at high dilution factor that decreased the required sample volumes to a few microliters. Conclusion: The final device proved suitable for diagnosing COVID-19 assaying actual serum samples and the results displayed good agreement with the molecular biology diagnoses. The flexibility to conjugate other EPs to SPEs suggests that this technology could be rapidly adapted to diagnose new variants of SARS-CoV-2 or other pathogens.

At-home rapid antigen test (RAT) kits for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are valuable public health tools during the present coronavirus disease (COVID-19) pandemic. They provide fast identification of coronavirus infection, which can help to reduce the transmission rates and burden on the healthcare system. However, they have lower sensitivity when compared with the reverse transcription polymerase chain reaction (RT-PCR) tests. One of the reasons for the lower sensitivity is due to the RAT color indicators being indistinct or invisible to the naked eye after the measurements. For this reason, we propose a systematic approach, through which we investigated anonymously provided at-home RAT kit results by using our in-house open source image processing scripts developed for affordable Raspberry Pi computer and Raspberry Pi HQ camera systems (available at https://github.com/kmiikki/ratcv). Therefore, we aimed at minimizing the human-related analysis errors for such kits. We believe that our framework can contribute to reduced the delayed quarantines of infected individuals and spreading of the current infectious disease.

This was a retrospective cohort study, which aimed to investigate the factors associated with hesitancy to receive the third dose of coronavirus disease 2019 (COVID-19) vaccine. A paper-based questionnaire survey was administered to all participants. Accordingly, the study included participants who provided answer in the questionnaire whether they have an intent to receive the third dose of vaccine. Data on sex, age, area of residence, adverse reactions after the second vaccination, whether the third vaccination was desired, and reasons to accept or hesitate booster vaccination were retrieved. Among the 2439 participants with mean (±SD) age of 52.6±18.9 years, and median IgG-S antibody titer of 324.9 (AU/mL), 97.9% of participants indicated their intent to accept a third vaccination dose. The logistic regression revealed that younger age (OR=0.98; 95% CI: 0.96-1.00) and higher antibody level (OR=2.52; 95% CI: 1.27-4.99) are positively associated with the third vaccine hesitancy. The efficacy of the COVID-19 vaccine and concerns about adverse reactions had significant impact on the third vaccination behavior. A rapid increase in the booster dose rate is needed to control the pandemic, and specific approaches should be taken in these groups that are likely to hesitate the third vaccine, subsequently increasing booster contact rate.

Escherichia coli and Shigella are common diarrhea-causing pathogens in children and adults. Enteroinvasive Escherichia coli (EIEC) shares a similar pathogenic mechanism with Shigella. However, EIEC are less virulent than Shigella. The aim of this work was to get a better understanding of the virulence differences between EIEC and S. flexneri. We investigated i) the bacterial gene co-expression networks (GCNs) and ii) the the transcriptional modules (WGCNA) of Caco-2 cells infected with EIEC or with S. flexneri during a three-hour period of bacterial infection. The GCN analysis showed that EIEC and S. flexneri networks presented different topologies. Additionally, the EIEC network revealed that pINV genes are not connected with chromosomal genes. WGCNA and eigengene analysis showed enterocyte gene expression variation along the three-hour bacterial post-infection period. Additionally, at one-hour post-infection EIEC induced a higher number of gene expression changes in Caco-2 cells than S. flexneri. Several of these genes are involved in autophagy. This study showed that the lower virulence of EIEC is associated with a lack of functional cooperation between pINV and chromosomal genes, differently from what was observed in S. flexneri. Consequently, EIEC becomes less efficient in subverting host-cell bacterial recognition as well as defense mechanisms such as autophagy.