In this article we compute many topological indices for the family of Möbius ladder. At first we give general closed form of M-polynomial of this family and recover many degree based topological indices out of it. We also compute Zagreb indices and Zagreb polynomials of this family.

In this paper we report a new development on the numerical model for aluminum-steam combustion. This model is based on diffusion flame of continuum regime and the thermal equilibrium between the particle and the flow field, which can be used to calculate the aluminum particle combustion model for two phase calculation conditions. The model prediction is in good agreement with the experimental data. A new type of vortex combustor was proposed for the combustion of aluminum and steam, and the mathematical model of the two phase reacting flow with in this combustor was established. The turbulence effects are modeled using the Reynolds Stress Model (RSM) with Linear Pressure-Strain approach, and the Eddy-Dissipation model is used to simulate the gas phase combustion. Aluminum particles are injected into the vortex combustor and form a swirling flow around the chamber and their trajectories are traced using the Discrete Phase Model (DPM). The simulation results show that the vortex combustor can achieve high efficient combustion of aluminum and steam. The influencing factors, such as the eccentric distance of the inlet of aluminum particles, particle size and steam inlet diameter, etc., are studied. The work described in this paper represents an attempt to the design of a vortex combustor in order to increase aluminum combustion efficiency.

In this work model of mirror elements equilibrium of the micromechanical components is developed, the behavior analysis of the mirror element of micromechanical mirrors in case changing of control voltages of electrostatic actuators is carried out, an expression for determining the maximum value of deflection voltage at which the snap-down effect will take the following form is obtained in case of the influence of the coefficient of the electrostatic rigidity of electrostatic actuators. The developed equilibrium model of mirror elements and the obtained results of modeling can be used at design of micromechanical mirrors with internal suspensions.

The viticulture sector, spanning over 7.3 million hectares worldwide, plays a crucial economic role but faces challenges such as labor shortages, rising production costs, market competition, and climate change stresses. Addressing these issues requires monitoring the spatial and temporal variability in vineyard productivity. Traditional ground-based observations, though accurate, are time-consuming and limited in scope. Precision viticulture, leveraging technologies like GPS, remote sensing, and artificial intelligence, offers efficient, non-destructive monitoring tools. This study aims to develop and test a technological workflow using the mobile app Digivit, integrated with the AgroSat platform, to estimate yield variability in vineyards. The workflow was performed during the 2023 growing season in a series of vineyards near Siena (Italy) and involved two main steps: spatial variability characterization using AgroSat and yield estimation using the mobile Digivit app. AgroSat processed Sentinel-2 NDVI data to identify homogeneous zones, while Digivit used smartphone images of grape clusters to estimate yields. The field campaign, performed three weeks before harvest, involved monitoring representative vines within identified zones and uploading georeferenced images for cluster segmentation analysis. Yield estimates were validated against measured weights, showing a strong linear correlation (R²=0.85, RMSE=43.74g). Excluding one outlier improved correlation to R²=0.95, RMSE=14.58g. Vineyard-level yield predictions were compared with harvest data, achieving an overall error of approximately 7%, in agreement with other methods in the literature. The study demonstrates that the Digivit app provides accurate, timely yield prediction, supporting farmers in harvest planning and winemaking management. The user-friendly mobile app approach facilitates a broader adoption of precision viticulture technologies among farmers, overcoming barriers related to technical expertise.

Formaldehyde (HCHO), an indoor volatile organic compound, is seriously harmful to human health. Therefore, green and effective decomposition of HCHO is essential. TiO₂ has been employed for the degradation of HCHO via photocatalytic generation of reactive oxygen species (ROS) (O^2-, ·OH), yet the low specific surface area of crystalline TiO₂ depressed the catalytic performance. Herein, we prepared TiO₂ aerogels with high specific surface area and high porosity by sol-gel method, and added PVA to introduce flexible molecular chains for pore size regulation. The photocatalytic performance test verifies that the pore size of TiO₂ aerogel is one of the important factors for HCHO decomposition. Notably, through the establishment of theoretical model and calculation, we validated that the efficiency of HCHO decomposition is related to the oxygen pressure in the pores of TiO₂ aerogel, and the oxygen pressure is inversely proportional to the pore size. Accordingly, the optimal pore size of TiO₂ aerogel for the photocatalytic HCHO decomposition is 2 nm~10 nm. This study provides a theoretical idea for TiO₂ aerogels in the decomposition reaction of HCHO, which is expected to inspire more breakthroughs in the study of TiO₂ aerogels for green chemistry.

: Climate change necessitates urgent actions to mitigate carbon dioxide (CO2) emissions from fossil fuel-based energy generation. Among various strategies, the deployment of carbon capture and storage (CCS) solutions are critical for reducing emissions from point sources such as power plants and heavy industries. In this context, cryogenic carbon capture (CCC) via desublimation has emerged as a promising technology. While CCC offers high separation efficiency, minimal downstream compression work, and integration potential with existing industrial processes, challenges such as low operating temperatures and equipment costs persist. Ongoing research aims to address these hurdles in order to optimize the desublimation processes for widespread implementation. This review consolidates diverse literature works, providing insights into the strengths and limitations of CCC technology, including the latest pilot plant scale demonstrations. The transformative potential of CCC is first assessed on a theoretical basis, such as thermodynamic aspects and mass transfer phenomena. Then, recent advancements in the proposed process configurations are critically assessed and compared through key performance indicators. Furthermore, future research directions for this technology are clearly highlighted.

During the last two decades several cases of venous thrombosis (VTE) after a prolonged period at a computer has been described, denominated “eThrombosis”. Video gaming on a computer has become very popular and can be a social activity where several players are gathered to play against each other or in a virtual environment for several days (“LAN (i.e., Local Area Network) parties”) where the participants are sedentary and consuming calorie-rich food items. The aim of this study was to investigate a potential coagulation activation during a 42 hour LAN party. Nine male gamers volunteered for the LAN party. Citrated blood was sampled before and every 6 hours, and plasma was analyzed for thrombin generation, and Thrombin-antithrombin-complexes (TAT), prothrombin Fragment 1+2 (F1+2), and D-dimer. Thrombin generation increased slightly but not significantly during the LAN party, whereas the coagulation activation markers were unchanged. These results do not indicate that the coagulation system is activated significantly during 42 h gaming with minimal physical activity. Although an increased activity cannot be excluded, it does not directly indicate a risk of VTE in general. It may be specific and particularly susceptible in-dividuals who are prone to thrombosis and, therefore, are at risk of developing e-thrombosis.

The late diagnosis of Type 2 Diabetes Mellitus can occur due to lack of access to the primary health care system and the non-manifestation of symptoms. Faced with this problem, this work presents the creation of a mobile application, called DiabetesCheck, for predicting the risk of Type 2 Diabetes Mellitus. A mathematical model is used, which classifies the risk of Type 2 Diabetes Mellitus for a group of patients with intervention and for a comparative group, using Fuzzy Classification and Decision Trees. The proposed application allows the health professional to monitor patients through the history stored in a database, allowing a representation of the evolution of patients and indication of medications. Therefore, this proposal aims to carry out the diagnosis in the initial phase of the disease and help in the prescription of more effective treatments and in the proposition of public policy strategies in epidemiology and screening.

This report provides a comprehensive overview of occupational asthma and respiratory hypersensitivity, focusing on some chemicals used in the workplace Includes numerous case studies and research papers related to occupational exposure methacrylates, such as HEMA-HPMA, and respiratory hypersensitivity are discussed And the relationship is explored The book also examines asthma pathophysiology, emerging drug delivery systems used to treat asthma, and the potential of nanoparticles , dendrimers and micellar systems have to improve pulmonary drug delivery in detail The worldwide prevalence of asthma is highlighted, with higher rates in high-GDP countries. The book highlights the need to improve asthma diagnosis, treatment and biomarkers, particularly in rural and low-income countries where the disease is often underdiagnosed and inadequately treated, and discusses the role of inflammation in asthma, in particular secondary inflammation characterized by specific cytokines and inflammation cells In addition, the paper explores various drug delivery methods, such as parenteral and parenteral drugs, pressurized inhalers (pMDIs), dry powder inhalers ( DPIs), nebulizers, nanoparticles, liposomes, micellar systems, microparticles , dendrimers, and gene therapy . These systems aim to increase pulmonary delivery of drugs and improve clinical outcomes. The potential of dendrimer bilirubin-based nanoparticles and micellar systems in the treatment of asthma and lung inflammatory diseases, including asthma, has been discussed in summary, this paper provides an overview of occupational asthma and respiratory hypersensitivity, and this discussion highlights the association between methacrylate exposure and respiratory hypersensitivity.

Type II pneumocytes are the target of SARS-CoV-2 which alters their redox homeostasis to increase reactive oxygen species (ROS). Melatonin (MT) has antioxidant proprieties and protects mitochondrial function. Here we evaluated whether the treatment with MT compensated for the redox homeostasis alteration in serum from COVID-19 patients. We determined oxidative stress (OS) markers such as carbonyls, glutathione (GSH), total antioxidant capacity (TAC), thiols, nitrites (NO2–), lipid peroxidation (LPO), and thiols groups in serum. We also studied the enzymatic activities of glutathione peroxidase (GPx), -S-transferase (GST), reductase (GR), thioredoxin reductase (TrxR), extracellular superoxide dismutase (ecSOD) and peroxidases. There was a significant increase in LPO and carbonyls (p≤0.03) and a decrease in TAC, NO2–, thiols, GSH, (p<0.001) in COVID-19 patients. The activities of the ecSOD, TrxR, GPx, GST, GR and peroxidases were decreased (p≤ 0.04). The treatment with MT favored the activity of the antioxidant enzymes which contributed to increase TAC and restored the lost redox homeostasis. MT also modulated glucose homeostasis functioning as a glycolytic agent and inhibited the Warburg effect. Thus, MT restores the redox homeostasis which is altered in COVID-19 patients and can be used as adjuvant therapy in the SARS-CoV-2 infection.

The possible future emergence of new SARS-CoV-2 virus variants pushes the development of new chemoprophylaxis protocols complementary to the unspecific and specific immune-prophylaxis measures currently used. The SARS-CoV-2 virus is particularly sensitive to oxidation due to the relevant positive electrical charge of its spike protein used as a ligand for target cells. The present study evaluated the safety and efficacy of a new oxidant preparation, liquid hyperoxygen (IOL), to neutralize the SARS-CoV-2 virus. IOL was incubated with throat swabs containing a human wild-type virus. The samples were then incubated with cells expressing the ACE2 receptor and therefore very sensitive to SARS-CoV-2 infection. The ability to neutralize SARS-CoV-2 was determined by assessing the amount of viral nucleic acid inside cells by PCR. The results obtained indicate that IOL, even at considerable dilutions, is capable, after incubation times of less than 30 min and even equal to 5 min, to completely inhibit SARS-CoV-2 infection. This inhibitory effect has been shown to be due to the oxidizing capacity of the IOL. This oxidizing capacity is exerted towards the virus but does not damage eukaryotic cells either in the in vitro or in the in vivo skin model. Obtained results indicate that the use of IOL, a hydrophilic liquid mixture saturated with highly reactive oxygen and nitrogen species, is a new powerful, safe, and effective tool for preventing possible future outbreaks of COVID-19 disease.

Nowadays, it is highly desired to develop highly active and humidity resistive ozone decomposition catalyst to eliminate the ozone contaminant, one of the primary pollutants in air. In this work, a series of Cu2S hollow structured materials are rapidly synthesized using different structured Cu2O templates. The Cu2S from porous Cu2O shows the highest ozone catalytic decomposition efficiency of >95% to 400 ppm ozone with a weight hourly space velocity of 480,000 cm3g-1h-1 in dry air. Importantly, the conversion still keeps >85% in a high relative humidity of 90%. The mechanism is explored by diffusive reflectance infrared spectroscopy which shows the decomposition intermediate of O22-, and the X-ray photoelectron spectroscopy reveals the dual active site of both Cu and S. All these results show the effective decomposition of ozone by Cu2S especially in harsh environments, promising for active ozone elimination.

As humans age, aberrancies in several signaling pathways occur. In the aging population, some patients display abnormal bone morphogenetic protein (BMP) signaling. This can lead to osteoporosis (OP), a debilitating bone disorder caused by an imbalance between osteoblasts and osteoclasts. In 2002, the Food and Drug Administration (FDA) approved usage of recombinant human BMP-2 (rhBMP-2) during spinal fusion surgery as it is crucial for bone formation. However, complications have been reported with rhBMP-2 and primary osteoblasts isolated from OP patients are unresponsive to BMP-2. While patient samples are available, previous medical history may alter results. Therefore, C57BL/6 mice, an aging model that displays aberrant BMP-signaling, can be utilized to investigate OP and aging. We show that BMP receptor type Ia (BMPRIa) is upregulated in the bone marrow stromal cells (BMSCs) of 15-month mice similar to previous data. We show that a conjugation between BMP-2 and Quantum Dots (QDot®s) effectively binds to BMPRIa and can investigate BMP-2 activity. After incubating BMSCs with methyl-β-cyclodextrin (MβCD), BMP-signaling is restored in 15-month mice as shown by western blotting and the von Kossa assay. MβCD may be used to rescue BMPRIa and the BMP-signaling pathway can be utilized by future therapeutics to treat OP.

Cognitive reserve is the adaptability of cognitive processes in the face of brain aging and pathology. This study aimed to validate the Arabic version of the Cognitive Reserve Index Questionnaire (CRIq) in a healthy Lebanese sample. CRIq assesses cognitive reserve through three domains: education, working activity, and leisure time. Statistical measures, including descriptive and regression analysis along with structural equation modeling, were utilized to investigate the convergent and discriminant validity of CRIq, incorporating fluid intelligence (Gf) and measures of cognitive function, long-term memory encoding and retrieval (Glr), and processing speed (Gs). Results from 174 participants revealed that the activities assessed by CRIq-Arabic were comparable to the original CRIq study, with slight cultural differences. The internal consistency of CRIq-Arabic was good (Cronbach's α = 0.88), indicating reliability. Convergent validity was confirmed, with moderate to high loadings on the cognitive reserve latent construct. Discriminant validity was supported as correlations between cognitive reserve variables and non-target constructs (Gf, Glr, Gs) were less than 1. The findings provide an initial psychometric validation of the CRIq-Arabic. Further research in clinical samples is needed to enhance its utility in neuropsychological practice.

Optimal detection strategies for effective convalescent immunity after SARS-CoV-2 infection and vaccination remain unclear. The objective of this study was to characterize convalescent immunity targeting the SARS-CoV-2 spike protein using a multiparametric approach. At the beginning of the pandemic, we recruited 30 COVID-19 unvaccinated convalescent donors and 7 unexposed asymptomatic controls. Peripheral blood mononuclear cells (PBMCs) were obtained from leukapheresis cones. The humoral immune response was assessed by measuring serum anti-SARS-CoV-2 spike S1 subunit IgG semiquantitative ELISA and T cell immunity against S1 and S2 subunits were studied by IFN-γ Enzyme-Linked Immune absorbent Spot (ELISpot), flow cytometric (FC) activation-induced marker (AIM) assays and the assessment of cytotoxic CD8+ T-cell function (in the subset of HLA-A2 positive patients). No single immunoassay was sufficient in identifying anti-spike convalescent immunity among all patients. There was no consistent correlation between adaptive humoral and cellular anti-spike responses. Our data indicate that the magnitude of anti-spike convalescent humoral and cellular immunity is highly heterogeneous and highlights the need for using multiple assays to comprehensively measure SARS-CoV-2 convalescent immunity. These observations might have implications for COVID-19 surveillance, and optimal vaccination strategies for emerging variants. Further studies are needed to determine the optimal assessment of adaptive humoral and cellular immunity following SARS-CoV-2 infection, especially in the context of emerging variants and unclear vaccination schedules.

COVID-19 has rapidly spread worldwide since December 2019. During the pandemic, SARS-CoV-2 repeatedly mutated from Alpha to Omicron. The severity and mortality are related to age, sex, and underlying diseases (respiratory, cerebrovascular, cardiovascular, metabolic, cancer, and immune diseases). We retrospectively studied 44 hospitalized stroke patients infected with the SARS-CoV-2 Omicron variant. The mortality rate of hospitalized stroke patients with COVID-19 was 6 (13.6%). The cause of death was coagulopathy in 3 cases of ischemic stroke. High modified Rankin Scale score（mRS）of stroke patient was correlated with severity of COVID-19. The timing of vaccination is inversely correlated with COVID-19 severity. In conclusion, stroke patients with COVID-19 have high mortality rates attributed to coagulopathy. Stroke patients with high mRS scores are more likely to develop severe COVID-19. In high mRS scores, therapy for severe COVID-19 should be administered.

Type 2 diabetes mellitus (T2DM) is a common metabolic disease characterised by insulin resistance and elevated blood glucose levels, affecting millions of people worldwide. T2DM patients with dyslipidaemia have an increased risk of cardiovascular disease (CVD). A complex interplay of risk factors such as hyperglycaemia, dyslipidaemia, hypertension, obesity, inflammation and oxidative stress favour the development of atherosclerosis, a central mechanism in the pathogenesis of cardiovascular disease. Dyslipidaemia, a hallmark of T2DM, is characterised by elevated triglycerides, decreased high-density lipoprotein (HDL) cholesterol and the presence of small, dense low-density lipoprotein (LDL) particles, all of which promote atherosclerosis. In this article, we have attempted to present various treatment strategies that include pharmacological interventions such as statins, ezetimibe, PCSK9 inhibitors, fibrates and omega-3 fatty acids. We have also tried to highlight the pivotal role of lifestyle modifications, including physical activity and dietary changes, in improving lipid profiles and overall cardiovascular health in T2DM patients. We have also tried to present the latest clinical guidelines for the management of dyslipidaemia in T2DM patients. In conclusion, the treatment of dyslipidaemia in T2DM patients is of great importance as it lowers lipid particle levels, slows the progression of atherosclerosis and ultimately reduces susceptibility to cardiovascular disease.

The Main Protease (Mpro) plays a pivotal role in the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is considered a highly conserved viral target. Disruption of the catalytic activity of Mpro produces a detrimental effect on the course of the infection, making this target one of the most attractive for the treatment of COVID-19. The current success of the SARS-CoV-2 Mpro inhibitor Nirmatrelvir, the first oral drug for the treatment of severe forms of COVID-19, has further focused the attention of researchers on this important viral target, making the search for new Mpro inhibitors a thriving and exciting field for the development of antiviral drugs active against SARS-CoV-2 and related coronaviruses.

The SARS-CoV-2 virus, causative agent of COVID-19, is known for its genetic diversity. Virus variants of concern (VOCs) as well as variants of interest (VOIs) are classified by the World Health Organization (WHO) according to their potential risk to global health. This study seeks to enhance the identification and classification of such variants by developing a novel bioinformatics criterion centered on the virus's spike protein (SP1), a key player in host cell entry, immune response, and a mutational hotspot. To achieve this, we pioneered a unique phylogenetic algorithm which calculates EIIP-entropy as a distance measure based on the distribution of the Electron-Ion Interaction Potential (EIIP) of amino acids in SP1. This method offers a comprehensive, scalable, and rapid approach to analyze large genomic data sets and predict the impact of specific mutations. This innovative approach provides a robust tool for classifying emergent SARS-CoV-2 variants into potential VOCs or VOIs. It could significantly augment surveillance efforts and understanding of variant characteristics, while also offering potential applicability to the analysis and classification of other emerging viral pathogens and enhancing global readiness against emerging and re-emerging viral pathogens.

D-Glucaric acid is an important bio-based building block of polymers and is a high value-added chemical that can be used in a variety of applications. In the present study, the Udh target genes from Pseudomonas putida and Pseudomonas syringae were used together to construct the expression vector pETDuet-2×Udh. The transformants of BL21(DE3) with vector pETDuet-2×Udh was applied to produce glucaric acid from glucuronic acid. After optimization of induction conditions, the highest Udh expression were achieved when 0.4 mmol L-1 isopropyl-β-d–thiogalactoside (IPTG) was added to cell cultures at an OD600 value of 0.6 followed by culture at 26℃ for 6 hours. The production of glucaric acid substantially reached 5.24 ± 0.015 g L-1 in fed-batch cultures in a 30 L tank. In the present study, a new system for glucaric acid production was established, which was more economic and friendly to environment.

N'-(5-bromofuran-2-carbonyl)isonicotinohydrazide (1) was obtained as a white solid in 83% yield by 2-methyl-6-nitrobenzoic anhydride (MNBA)/4-dimethylaminopyridine (DMAP)-catalyzed reaction of 5-bromofuran-2-carboxylic acid and isoniazid in dichloromethane at room temperature. The structure of N'-(5-bromofuran-2-carbonyl)isonicotinohydrazide (1) was elucidated by 1H NMR, 13C NMR, FTIR, and the high resolution mass spectrometers. Molecular docking screening of the title compound (1) on the cyclooxygenase-2 (COX-2) protein (PDB ID: 5IKR) exhibited that compound (1) has a good binding affinity, suggesting that it is very interesting for further structure optimization and in-depth research as a potential COX-2 inhibitor.

Keywords: Marine sulfated glycans; SARS-CoV-2; Omicron XBB.1.5, Spike protein; Heparin

Recent studies have confirmed that lung microvascular endothelial injury plays a critical role in the pathophysiology of COVID-19. Our group and others have demonstrated the beneficial effects of H2S in several pathological processes and provided a rationale for considering the therapeutic implications of H2S in COVID-19 therapy. Here, we evaluated the effect of the slow-releasing H2S donor, GYY4137, on the barrier function of a lung endothelial cell monolayer in vitro, after challenging the cells with plasma samples from COVID-19 patients or inactivated SARS-CoV-2 virus. We also assessed how the cytokine/chemokine profile of patients’ plasma, endothelial barrier permeability, and disease severity correlated with each other. Alterations of barrier permeability after treatments with patient plasma, inactivated virus, and GYY4137 were monitored and assessed by electrical impedance measurements in real-time. We present evidence that GYY4137 treatment reduced endothelial barrier permeability after plasma challenge and completely reversed the endothelial barrier disruption caused by inactivated SARS-CoV-2 virus. We also showed that disease severity correlated with the cytokine/chemokine profile of the plasma but not with barrier permeability changes in our assay. Overall, these data demonstrate that treatment with H2S-releasing compounds has the potential to ameliorate SARS-CoV-2–associated lung endothelial barrier disruption.

The mRNA vaccines for SARS-CoV-2 have demonstrated efficacy and immunogenicity in the re-al-world setting. However, most of the research on vaccine immunogenicity has been centered on characterizing the antibody response, with limited exploration into the persistence of spike-specific memory B cell response. Here we monitored the durability of the memory B cell response and characterize the trajectory of spike-specific B cell phenotypes in healthy individuals who have received two doses of the BNT162b2 vaccine up to 9 months post-vaccination. To profile the spike-specific B cell response we applied the tSNE and Cytotree automated approaches. Our data showed the induction of spike-specific IgA+ and IgG+ plasmablasts and IgA+ activated cells 7 days after the second dose which disappeared 3 months later, while subsets of spike-specific IgG+ resting memory B cells became predominant 9 months after vaccination, and they were capable to differentiate into spike-specific IgG secreting cells when in vitro restimulated. Other subsets of spike-specific B cells, such as IgM+ or unswitched IgM+IgD+ or IgG+ double negative/atypical cells, were also elicited by the BNT162b2 vaccine and persisted up to month 9. The analysis of circulating spike-specific IgG, IgA and IgM was in line with the plasmablasts observed. The longitudinal analysis of the antigen-specific B cell response elicited by mRNA-based vaccines provides valuable insights into our understanding of the immunogenicity of this novel vaccine platform destined to a future widespread use, and it is crucial in guiding future decisions and vaccination schedules.

Erectile dysfunction (ED) is a common and feared complication of radical prostatectomy (RP) for prostate cancer. Recently, tissue engineering is being attempted for post-prostatectomy ED, with controlled interactions between cells, growth factors, and extracellular matrix (ECM) being important for nerve regeneration's structural integrity. In this study, we evaluated the effects of biomechanical ECM patch on human bone marrow-derived mesenchymal stem cells (hBMSCs) morphology and behavior in bilateral cavernous nerve injury (BCNI) rat model. The ECM patch, made of decellularized human fibroblast-derived ECM (hFDM) and a biocompatible polyvinyl alcohol (PVA) hydrogel, was tested with human bone marrow-derived mesenchymal stem cells (hBMSCs) on a bilateral cavernous nerve injury (BCNI) rat model. In vitro analysis showed that the hFDM/PVA + hBMSCs patches significantly increased neural development markers. In vivo experiments demonstrated that the rats treated with the hFDM/PVA patch had higher ICP/MAP ratio, a higher ratio of smooth muscle to collagen, increased content of nNOS, higher levels of eNOS protein expression, and a higher cGMP level compared to the BCNI group. These results indicate that the hFDM/PVA patch is effective in promoting angiogenesis, smooth muscle regeneration, and nitrergic nerve regeneration, which could contribute to improved erectile function in post-prostatectomy ED.

Natural herbs and functional foods contain bioactive molecules capable of augmenting the immune system and mediating anti-viral functions. Functional foods, such as prebiotics, probiotics, and dietary fibers, have been shown to have positive effects on gut microbiota diversity and immune function. The use of functional foods has been linked with en-hanced immunity, regeneration, improved cognitive function, maintenance of gut mi-crobiota, and significant improvement in overall health. The gut microbiota plays a critical role in maintaining overall health and immune function, and disruptions to its balance have been linked to various health problems. SARS-CoV-2 infection has been shown to affect gut microbiota diversity, and the emergence of variants poses new challenges to combat the virus. SARS-CoV-2 recognizes and infects human cells through ACE2 receptors prevalent in lung and gut epithelial cells. Humans are prone to SARS-CoV-2 infection because the respiratory and gastrointestinal tracts are rich in microbial diversity and contain high ACE2 and TMPRSS2. This review article explores the potential use of functional foods in mitigating the impact of SARS-CoV-2 variants on gut microbiota diversity and the potential use of functional foods as a strategy to combat these effects.

Abstract: The SARS-CoV-2 pandemic has significantly impacted world health and economic status. In response, much work has been undertaken to provide effective, safe vaccines, antibodies and antiviral drugs with which to address this pandemic. Treatment of a pandemic population presents multiple challenges in addition to the primary issue of drug efficacy and safety, such as large scale drug manufacture and distribution, drug stability, oral dosing and pharmacoeconomic considerations. Ideally, these factors must be addressed if new candidate drugs are to be advanced for treatment of large (pandemic) populations. Subsequently, new antivirals have reached the market but choices are few. According to the NIH Covid Treatment Guidelines, only three small molecule antiviral drugs are available to treat COVID-19 disease. As such, a significant part of the research towards discovery of new antiviral drugs has focused on screening and evaluation of ‘repurposed drugs’ or previously approved or clinical stage drugs. Yet, in spite of this increased research activity, one promising clinical stage candidate drug has received little attention regarding its potential as a monotherapy or component of combination therapy for treatment of COVID-19 disease. Tucaresol, with documented human safety and pharmacokinetic data, is an orally active, stable, small molecule amenable to large scale manufacture by a proprietary two-step synthesis developed by us. Tucaresol functions as a host-targeted antiviral by selective protection/reconstitution of CD4+ T helper cells as demonstrated in HIV patients and SIV macaques. In view of similarities between HIV and SARS-CoV-2, especially with respect to host CD4+ T helper cells, and the suitability of Tucaresol for facile treatment of pandemic populations, Tucaresol is presented herein for treatment of mild-to-moderate COVID-19 patients but may also be useful for treatment of advanced disease accompanied by lymphopenia.

This research intended to report amine-functionalized multiwall carbon nanotubes (MWCNTs) prepared by a simple method for efficient and rapid removal of Reactive Yellow 2 (RY2) from water. EDS analysis showed that the N content increased from 0 to 2.42% and from 2.42 to 8.66% after modification by APTES and PEI, respectively. BET analysis displayed that the specific surface area, average pore size, and total pore volume were reduced from 405.22 to 176.16 m2/g, 39.67 to 6.30 nm, and 4.02 to 0.28 cm3/g, respectively. These results proved that the PEI/APTES-MWCNTs were successfully prepared. pH edge experiment indicated that pH 2 was optimal for RY2 removal. At pH 2 and 25 °C, the time required for adsorption equilibrium was 10, 15, and 180 min at initial concentrations of 50, 100, and 200 mg/L, respectively; and the maximum RY2 uptake calculated by the Langmuir model was 714.29 mg/g. Thermodynamic studies revealed that the adsorption process was spontaneous and endothermic. 0-0.1 mol/L of NaCl showed negligible effect on RY2 removal by PEI/APTES-MWCNTs. Five adsorption/desorption cycles confirmed the good reusability of PEI/APTES-MWCNTs in RY2 removal. Overall, the PEI/APTES-MWCNTs are a potential and efficient adsorbent for reactive dye wastewater treatment.

The global threat of COVID-19 has led to the increasing use of metabolomics to study SARS-CoV-2 infection in humans and animals. Despite this, understanding SARS-CoV-2's metabolome during infection remains difficult and incomplete. Here, metabolic responses were characterized from sampled nasal washes collected from an asymptomatic ferret model (n = 20) at different time points before and after the SARS-CoV-2 challenge using an LC-MS-based metabolomics approach. Multivariate analysis of the nasal wash metabolome data resulted in several statistically significant features being observed. Despite no effects of gender or interaction between gender and time on the time course of SARS-CoV-2 infection, 16 metabolites were significantly different at every time point post-infection. Among these altered metabolites, the relative abundance of taurine was elevated post infection which could be an indication of hepatotoxicity, while the accumulation of sialic acids could indicate SARS-CoV-2 invasion. The pathway analysis identified several pathways influenced by SARS-CoV-2 infection. Of these, sugar, glycan, and amino acid metabolisms were the key altered pathways in the upper respiratory channel during infection. These findings provide some new insights into the progression of SARS-CoV-2 infection in ferrets at the metabolic level which could be useful for the development of early clinical diagnosis tools and new or repurposed drug therapies.

Vehicle HVAC systems can accumulate and recirculate highly infectious respiratory diseases via aerosols. Integrating UVC to complement automobile HVAC systems can protect occupants from developing allergies, experiencing inflammatory problems, or acquiring respiratory infectious diseases by inactivating pathogenic organisms. UVC can add little to no static pressure with minimal space, unlike mercury lamps which are larger and heavier. Additionally, UVC LEDs are effective at low voltage and have no mercury or glass. While previous experiments have shown UVC LED technology can reduce bacteriophage Phi6 concentrations by 1 log in 5 minutes (selected as the average time to clean the cabin air), those studies had not positioned LED within the HVAC itself or studied the susceptibility of the surrogate at the specific wavelength. This study aimed to assess the disinfection performance of UVC LEDs in automotive HVAC systems and determine the dose-response curve for bacteriophage Phi6, a SARS-CoV-2 surrogate. To achieve this, UVC LEDs were installed in a car HVAC system. To determine inactivation efficacy, a model chamber of 3.5 m3, replicating the typical volume of a car, containing the modified automobile HVAC system was filled with bacteriophage Phi6, and the HVAC was turned on with and without the UVC LEDs being turned on. The results revealed that HVAC complemented with UVC reduced bacteriophage Phi6 levels significantly more than the HVAC alone and reduced the viral concentration in the cabin by more than 1 LRV (90% viral reduction) in less than 5 minutes. The performance after 5 minutes is expected to be significantly better against SARS-CoV-2 because of its higher sensitivity to UVC, especially at lower wavelengths (below 270 nm). HVAC alone could not achieve a 90% viral reduction of bacteriophage Phi6 in 15 minutes. Applying UVC LEDs inside an HVAC system is an effective means of quickly reducing the number of aerosolized viral particles in the chamber, by inactivating microorganisms leading to improved cabin air quality.

Low back pain is a clinically highly relevant musculoskeletal burden and is associated with inflammatory as well as degenerative processes of the intervertebral disc. However, the pathophysiology and cellular pathways contributing to this devastating condition are still poorly understood. Based on previous evidence, we hypothesize that tissue renin-angiotensin system (tRAS) components, including the SARS-CoV-2 entry receptor angiotensin-converting enzyme 2 (ACE2), are present in human nucleus pulposus (NP) cells and associated with inflammatory and degenerative processes. Experiments were performed with NP cells from 4 human donors. The existence of angiotensin II, angiotensin II type 1 receptor (AGTR1), AGTR2, MAS-receptor (MasR), and ACE2 in human NP cells was validated with immunofluorescent staining and gene expression analysis. Hereafter the cell viability was assessed after adding agonists and antagonists of the target receptors as well as angiotensin II in different concentrations for up to 48 hours of exposure. A TNF-α-induced inflammatory in vitro model was employed to assess the impact of angiotensin II addition and the stimulation or inhibition of the tRAS receptors on inflammation, tissue remodeling, expression of tRAS markers, and the release of nitric oxide (NO) into the medium. Further, protein levels of IL-6, IL-8, IL-10, and intracellular as well as secreted angiotensin II were assessed after exposing the cells to the substances, and inducible nitric oxide synthase (iNOS) levels were evaluated utilizing Western Blot. The existence of tRAS receptors and angiotensin II were validated in human NP cells. Cell viability analysis revealed no cytotoxic effects of angiotensin II. The AGTR1 inhibitor Candesartan and the MAS receptors AVE0991 showed cytotoxic effects at high concentrations (100 µM). The addition of angiotensin II only showed a mild impact on gene expression markers. However, there was a significant increase in NO secreted by the cells. The gene expression ratios of pro-inflammatory/anti-inflammatory cytokines IL-6/IL--10, IL-8/IL-10, and TNF-α /IL-10 were positively correlated with the AGTR1/AGTR2 and AGTR1/MAS1 ratios, respectively. The stimulation of the AGTR2 MAS-receptor and the inhibition of the AGTR1 receptor revealed beneficial effects on the gene expression of inflammatory and tissue remodeling markers. This finding was also present at the protein level. We did not find alterations in iNOS protein concentrations after adding the drugs. The current data showed that tRAS components are expressed in human NP cells and are associated with inflammatory and degenerative processes. Further characterization of the associated pathways is warranted. The findings indicate that tRAS modulation might be a novel therapeutic approach to intervertebral disc disease.

One of the models that could be used to understand the adoption of vaccine uptake is the Health Belief Model (HBM). The aim of this study is to assess the role of HBM constructs and perceived health status (PHS) on vaccination status of individuals and to understand the role of socio-demographic variables on HBM scoring. A comparative cross-sectional telephone survey was conducted among 1,325 vaccinated (60.0%) and non-vaccinated (40.0%) vaccinated individuals aged 40 years and above in July 2021 in Punjab province, Pakistan. A higher level of education was the strongest predictor of positive HBM. All constructs of HBM, PHS and cues-to-action were significant predictors of COVID-19 vaccination uptake with perceived benefits as the strongest predictor. In order to expand the vaccination coverage, doubled pronged interventions utilizing both ICT and human resources should be designed that address each barrier perceived by individuals and understandably communicate the benefits of COVID-19 vaccine to the broader population.

During the SARS-CoV-2 vaccination campaign, people with CF (pwCF) were considered a clinically vulnerable population. However, data on immunogenicity of anti-SARS-CoV-2 vaccines in pwCF are lacking. We conducted a prospective study enrolling all patients aged >12 and followed-up in our CF centre, who received two doses of the BNT162b2 vaccine in March-­­­October 2021. They underwent a blood sample for quantification of antibodies to the SARS-CoV-2 spike protein receptor binding domain immediately before receiving the first dose and after 3 and 6 months from the second dose. We enrolled 143 patients (median age: 21 years, range: 13-38); of whom 16 had a previous infection. Median antibody titer (interquartile range) after 3 months from vaccination was 1288 U/mL (730-2115) and decreased to 918 U/mL (534-1488) after 6 months (P<0.0001). Median values were higher among previously infected patients as compared to those naïve to SARS-CoV-2 (9107 vs 1229 U/mL at 3 months and 4810 vs 829 U/mL at 6 months, P<0.0001) with no significant differences in the rate of decline over time (P=0.135). All pwCF mounted an antibody response after two-doses of BNT162b2 vaccine that waned at 6 months from vaccination. Age ≥30 years and use of inhaled corticosteroids were associated with a lower humoral response.

Conventional methods of crop mapping need ground truth information to train the classifier. Thanks to the frequent acquisition allowed by recent satellite missions (Sentinel 2), we can identify temporal patterns that depend on both phenology and crop management. Some of these patterns are specific to a given crop and thus can be used to map it. Thus, we can substitute ground truth information used in conventional methods with agronomic knowledge. This approach was applied to identify irrigated permanent grasslands (IPG) in the Crau area (Southern France) which play a crucial role in groundwater recharge. The grassland is managed by making three mows during the May-October period which leads to a specific temporal pattern of leaf area index (LAI). The mowing detection algorithm was designed using the temporal LAI signal derived from Sentinel 2 observations. The algorithm includes some filtering to remove noise in the signal that might lead to false mowing detection. A pixel is considered a grassland if the number of detected mows is greater than 1. A data set covering five years (2016-2020) was used. The detection mowing number was done at the pixel level and then results are aggregated at the plot level. A validation data set including 780 plots was used to assess the performances of the classification. We obtained a Kappa index ranging between 0.94-0.99 according to the year. These results were better than other supervised classification methods that include training data sets. The analysis of land-use changes shows that misclassified plots concern grasslands managed less intensively with strong intra-parcel heterogeneity due to irrigation defects or year-round grazing. Time series analysis, therefore, allows us to understand different management practices. Real land-use change in use can be observed, but long time series are needed to confirm the change and remove ambiguities with heterogeneous grasslands.

In this paper, the phases in the Mg-Ti-O system using the 1:1 formulation of MgO:TiO2 mixing synthetic brucite of Mexican origin with TiO2 microparticles of high purity and with a heat treatment at 1100°C for 1 h were studied. The raw materials and formulation by XPS and DRX techniques were characterized. The results demonstrate the presence of different oxidation states in titania and the formation of different oxides in the Mg-Ti-O system when mixed and calcined at 1100°C; additionally, the formation of vacancies in the crystal lattice during the transformation from hexagonal brucite to magnesia with a cubic structure centered on the faces is estimated. With the results, its thermal behavior is warned based on the MgO-TiO2 phase diagram.

During the novel coronavirus disease (COVID-19) pandemic, several environmental factors have influenced the activities and the protection policy measures. This has had a major effect on climate change and global environmental catastrophe. In many countries, the strategy of closing various activities such as tourism, industrial production, stopped normal life, transportation, among others. This closure has a positive impact on the environment. However, the massive use of masks and personal protection could significantly increase pollution worldwide. The impact on the environment needs to be calculated to have information for public health actions. In this study, we present a first overview of the potential impacts of COVID-19 on some environmental matrices in Bogota, Colombia.

The purpose of the current study was directed to investigate the effectiveness of docosahexaenoic acid (DHA) as a chemopreventive agent on experimentally induced hamster buccal pouch (HBP) carcinogenesis; Material and methods: 40 Syrian male hamsters, five weeks old, were divided into 4 groups of 10 animals in each as follows, GI: Topical application of liquid paraffin alone (thrice a week for 14 weeks), GII: Topical application of 7, 12 dimethyl benz[a]anthracene (DMBA) alone (0.5 % in liquid paraffin, thrice a week for 14 weeks), GIII: Topical application of DMBA (0.5 % in liquid paraffin, thrice a week for 14 weeks) + Oral administration of DHA (125 mg/kg b.w. in 1 ml distilled water by oral gavage, thrice a week for 14 weeks on alternative days of DMBA application), GIV : Oral administration of DHA alone (125 mg/kg b.w. in 1 ml distilled water by oral gavage, thrice a week for 14 weeks); Results: Gross observations and histopathological findings revealed a-GI: normal stratified squamous epithelium b- GII: well and moderately differentiated squamous cell carcinoma (SCC) c-: GIII: showed variable results ranges from hyperkeratosis, hyperkeratosis and focal hyperplasia, mild dysplasia, and well differentiated SCC with superficial invasion of tumor cells not extended to deeper areas d: GIV: normal similar to GI. Immunohistochemical results revealed that oral DHA treatment to DMBA treated hamsters restored the normal expression of bcl-2; Conclusion: DHA has the potential to be a dietary chemopreventive agent due to its capacity to improve carcinogen detoxification and to block/suppress the initiation and promotion stages of experimentally produced HBP carcinogenesis.

(1) Background: Mouse-mammary tumor virus (MMTV) might play a role in the etiology of some breast cancers in humans. The purpose of our study was to identify MMTV DNA sequences in breast tissue samples from breast cancer patients operated in our regional center from Romania. (2) Methods: We have selected 75 patients with non-metastatic breast cancer treated with curative intent and searched with PCR the MMTV-like DNA sequence in the breast cancer tissue and normal breast tissue obtained from the same patients. (3) Results: None of the examined samples was positive for MMTV-like target sequences on PCR. (4) Conclusions: We could not prove that MMTV plays a role in the etiology of breast cancer in our patient group. This finding is similar to findings of other geographically related research groups and might be due to the fact that only the Mus musculus domesticus mouse species was proven to carry infectious MMTV, but not the Mus musculus musculus species, which is specific to South-Eastern Europe and some parts of Asia.

Several hypotheses have been presented on the origin of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from its identification as the agent causing the current coronavirus disease 19 (COVID-19) pandemic. So far, no hypothesis has managed to identify the origin, and the issue has resurfaced. Here we have unfolded a pattern of distribution of several mutations in the SARS-CoV-2 proteins across different continents comprising 24 geo-locations. The results showed an evenly uneven distribution of unique protein variants, distinct mutations, unique frequency of common conserved residues, and mutational residues across the 24 geo-locations. Furthermore, ample mutations were identified in the evolutionarily conserved invariant regions in the SARS-CoV-2 proteins across almost all geo-locations we have considered. This pattern of mutations potentially breaches the law of evolutionary conserved functional units of the beta-coronavirus genus. These mutations may lead to several novel SARS-CoV-2 variants with a high degree of transmissibility and virulence. A thorough investigation on the origin and characteristics of SARS-CoV-2 needs to be conducted in the interest of science and to be prepared to meet the challenges of potential future pandemics.

It has been more than a year since the first case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was found. This coronavirus has infected more than 110 million people worldwide by the end of February, 2021, and several virulent as well as more spreadable mutant forms of SARS-CoV-2 have emerged subsequently. In the latter group, three variants B.1.1.7, B.1.351, and P1 lineages, have been reported. Using computer simulation, the present paper investigates the structural differences between the wild type SARS-CoV-2 spike protein and its Asn501Tyr (N501Y) mutant variant. Time-based structural changes between the receptor binding domains of these two species are also examined. The N501Y mutation is common to all the three aforesaid mutant variants.

COVID-19 is a contagious respiratory disease that is causing significant global morbidity and mortality. Understanding the impact of a SARS-CoV-2 infection on the host metabolism is still in its infancy but of great importance. Herein, we investigated the metabolic response during viral shedding and post-shedding in an asymptomatic SARS-CoV-2 ferret model (n=6) challenged with two SARS-CoV-2 isolates. Virological and metabolic analyses were performed on (minimally invasive) collected oral swabs, rectal swabs, and nasal washes. Fragments of SARS-CoV-2 RNA were only found in the nasal wash samples in four of the six ferrets, and in the samples collected 3 to 9 days post-infection (referred to as viral shedding). Central carbon metabolism metabolites were analyzed during viral shedding and post-shedding periods using a dynamic MRM (dMRM) database and method. Subsequent untargeted metabolomics and lipidomics of the same samples were performed using an LC-QToF-MS methodology, building upon the identified differentiated central carbon metabolism metabolites. Multivariate analysis of the acquired data identified 29 significant metabolites and three lipids that were subjected to pathway enrichment and impact analysis. The presence of viral shedding coincided with the challenge dose administered and significant changes in the citric acid cycle, purine metabolism, and pentose phosphate pathways, amongst others, in the host nasal wash samples. An elevated immune response in the host was also observed between the two isolates studied. These results support other reported metabolomic-based findings found in clinical observational studies and indicate the utility of metabolomics applied to ferrets for further COVID-19 research that advances early diagnosis of asymptomatic and mild clinical COVID-19 infections, in addition to assessing the effectiveness of new or re-purposed drug therapies.

This article analyses the environmental impact of the measures imposed during the SARS-CoV-2 pandemic. We compare the evolution of atmospheric pollution levels in recent years and during lockdown, and assess the effects of the decrease in mobility and changes in patterns and lifestyles during the latter period. Thus, the reduction in the risk to human health brought about by the improvement of air quality during the months of confinement through the use of dose-response functions is estimated. The focus of the case study is the island of Tenerife. The island of Tenerife has been selected because it can serve as an example for other sites in Europe. We distinguish between the three areas with the highest population concentrations: the Metropolitan, Southern, and Northern areas. The impacts of air pollution and its relationship with changes in consumption and activity patterns are clearly distinguishable. Therefore, the lessons learned can be easily extrapolated to other areas, in both island and mainland contexts.

In the context of the COVID-19 pandemic, thousands of healthcare workers (HCWs) infected with COVID-19 have lost their lives worldwide. At the early stage of the epidemic, when COVID-19 was still not considered as a pandemic, a large number of Chinese HCWs were infected. Officials reported that more than 3,000 HCWs in Hubei contracted the virus at the early stage of the outbreak due to limited knowledge of the virus. Following reports of overloaded local hospitals, more than 42,000 medical staff, including those from the military, were dispatched to Hubei from across the country. At the peak of the fight, one in 10 intensive care medics in China were working in Wuhan. During fighting against COVID-19 in China, although a large number of HCWs were infected by SARS-CoV-2 in the early stages of the epidemic, the timely adoption of measures indicated that, a faster rate of diagnosis could be achieved, patients were isolated in-time, HCWs’ safety was prioritized, training on basic protective knowledge and unified management of HCWs was strengthened, and effective protective measures were implemented. This resulted in the accomplishment of zero SARS-CoV-2 infection among the 42,632 members of the national medical teams sent to Hubei, and the number of COVID-19 cases among HCWs in local hospitals also significantly decreased, thereby indicating that hospital-acquired infections of SARS-CoV-2 among HCWs are fully preventable.

Four new zoonotic coronaviruses outbreak occurred in the past two decades. The first coronavirus outbreak happened in 2003 and was named Severe Acute Respiratory Syndrome Coronavirus-1 (SARS-CoV-1), followed by Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in 2013, and by Swine Acute Diarrhoea Syndrome (SADS) in 2017. In late December 2019, a patient from Wuhan Seafood Wholesale Market, China, was admitted to Huang's hospital with respiratory distress syndrome (RDS) of apparently unknown etiology, which later was diagnosed with SARS-CoV-2-induced coronavirus disease-19 (COVID-19). SARS-CoV-2 was identified from another clade within the subgenus Sarbecovirus of the genus Betacoronavirus. This new CoV variant showed 96.2% similarity at whole-genome level to bat coronavirus. Based on genetic studies, pangolin, bats, and snakes are suspected to be a possible intermediate host of this virus, but further research is in progress to determine how this virus appeared and what is the exact source of infection. The SARS-CoV-2 outbreak has higher transmissibility, contagiosity and pathogenicity compared to that of SARS-CoV-1 and MERS-CoV. SARS-CoV-2 swiftly spread from continent to continent and is persistently causing a shocking global public health concern albeit the rate of infected cases and mortality is relatively decreasing over time. In this review, we provide an update on the origin, transmissibility, etiology, epidemiology, and evolution of COVID-19. We also highlight the current diagnostics, therapies, and prognostics for SARS-CoV-2. Eventually, we report and provide our humble opinion about the preventive strategies to control the ongoing related pandemic situation at global and individual levels, considering the international public health emergency and possible future epidemics and pandemics.

A signal analysis of the genoma sequenced of coronavirus variants: B.1.1.7, B.1.135, B.1.429-B.1.427, B.1.525 and P1 is presented. We deal with a certain type of finite alternating sum series having independently distributed terms associated with binary (0,1) indicators for the nucleotide bases A,C,G,T. This method provides additional information to conventional Similarity comparisons and Power Spectrum approaches. It leads to uncover distinctive patterns regarding the intrinsic data organization of genomic sequences according to its progression along the nucleotide bases position. Hence, the method could be useful for survelliance of genoma variants.

The novel coronavirus SARS-CoV-2 likely emerged from a wildlife source with transmission to humans followed by rapid geographic spread throughout the globe and severe impacts on both human health and the global economy. Since the onset of the pandemic, there have been many instances of human-to-animal transmission involving companion, farmed and zoo animals, and limited evidence for spread into free-living wildlife. The establishment of reservoirs of infection in wild animals would create significant challenges to infection control in humans and could pose a threat to the welfare and conservation status of wildlife. We discuss the potential for exposure, onward transmission and persistence of SARS-CoV-2 in an initial selection of wild mammals (bats, canids, felids, mustelids, great apes, rodents and cervids). Dynamic risk assessment and targeted surveillance are important tools for the early detection of infection in wildlife, and here we describe a framework for collating and synthesising emerging information to inform targeted surveillance for SARS-CoV-2 in wildlife. Surveillance efforts should be integrated with information from public and veterinary health initiatives to provide insights into the potential role of wild mammals in the epidemiology of SARS-CoV-2.

In this article, the geometry of pseudoparallel, Ricci-generalized pseudoparallel and 2-Ricci-generalized pseudoparallel invariant submanifolds of an almost $\alpha$-cosymplectic $(\kappa,\mu,\nu)$ space has been searched under the some conditions. We also give some characterizations for such submanifolds. I think that obtained new results contribute to differential geometry.

Abstract. The purpose of this review is to investigate the nature of privacy concerns in the context of Smart Local Energy Systems (SLES) to understand how SLES providers can minimize both users’ concern, and cause for concern, around privacy. We conducted a rapid realist review and thematic framework analysis against Bronfrenbrenner’s socio-ecological model to understand privacy concerns in different contexts. A common privacy concern was that sharing detailed energy use data had the potential to reveal information about home life, and to intrude upon people’s sense of autonomy, choice and control. Evidence suggests that people are willing to accept newdata sharing technologies if the benefits of doing so are clear, anticipated, and mutually beneficial. Building trust, through increasing knowledge and understanding was a mechanism for overcoming privacy concerns, but this was mediated by the organization providing the information. Non-profit organizations were more trusted to ensure appropriate safeguards to privacy were in place. One key barrier to participation with good supporting evidence was that people can resist perceived intrusions on their privacy. This could be actively resisted by refusing to install data collection technologies or passively by non-participation in adapting energy use behaviors: both of which are necessary for SLES to achieve their goals of managing energy demand and building resilience in smart grids.

The urgent need to improve performance in the construction industry has led to the adoption of many innovative technologies. 3D laser scanners are amongst the leading technologies being used to capture and process assets or construction project data for use in various applications. Due to its nascent nature, many questions are still unanswered about 3D laser scanning, which in turn contribute to the slow adaptation of the technology. Some of these include the role of 3D laser scanners in capturing and processing raw construction project data. How accurate is the 3D laser scanner or point cloud data? How does laser scanning fit with other wider emerging technologies such as Building Information Modelling (BIM)? This study adopts a proof-of-concept approach, which in addition to answering the afore-mentioned questions, illustrates the application of the technology in practice. The study finds that the quality of the data, commonly referred to as point cloud data is still a major issue as it depends on the distance between the target object and 3D laser scanner’s station. Additionally, the quality of the data is still very dependent on data file sizes and the computational power of the processing machine. Lastly, the connection between laser scanning and BIM approaches is still weak as what can be done with a point cloud data model in a BIM environment is still very limited. The aforementioned findings reinforce existing views on the use of 3D laser scanners in capturing and processing construction project data.

Conventionally, eukaryotic mRNAs were thought to be monocistronic, leading to the translation of a single protein. However, large-scale proteomics has led to a massive identification of proteins translated from mRNAs of alternative ORF (AltORFs), in addition to the predicted proteins issued from the reference ORF or from ncRNAs. These alternative proteins (AltProts) are not represented in the conventional protein databases and this “Ghost proteome” was not considered until recently. Some of these proteins are functional and there is growing evidence that they are involved in central functions in physiological and physiopathological context. Based on our experience with AltProts we have got interested in finding out their involvement in development of the SARS-CoV-2 virus, responsible for the 2020 Covid-19 outbreak. Thus, we have scrutinized the recently published data by Krogan and coworkers (2020) on the SARS-CoV-2 interactome with host cells by co-IP in the perspective of drug repurposing. The initial work has revealed the interaction between 332 human cellular RefProts with the 27 viral proteins. Re-interrogation of this data using 23 viral targets and including AltProts, followed by enrichment of the interaction networks, leads to identify 218 RefProts (in common to initial study) plus 56 AltProts involved in 93 interactions. This demonstrates the necessity to take into account the Ghost proteome for discovering new therapeutic targets and establish new therapeutic strategies. Missing the ghost proteome in the drug metabolism and pharmacokinetic (DMPK) drug development pipeline will certainly be a major limitation to the establishment of efficient therapies.

The COVID-19 pandemic has wreaked havoc on the whole world, taking over half a million lives and capsizing the world economy in unprecedented magnitudes. With the world scampering for a vaccine, early detection and containment is the only redress. Existing diagnostic technologies with high accuracy like RT-PCRs are expensive and sophisticated, requiring skilled individuals for specimen collection and screening, resulting in lower outreach. So, methods excluding direct human intervention are much sought after, and artificial intelligence-driven automated diagnosis, especially with radiography images, captured the researchers' interest. This survey marks a detailed inspection of the deep-learning-based automated detection of COVID-19 works done to date, a comparison of the available datasets, methodical challenges like imbalanced datasets, and others, along with probable solutions with different pre-processing methods, and scopes of future exploration in this arena. We also benchmarked the performance of 315 deep models in diagnosing COVID-19, Normal, and Pneumonia from x-ray images of a custom dataset created from four others. The dataset is publicly available at https://github.com/rgbnihal2/COVID-19-X-ray-Dataset. Our results show that DenseNet201 model with Quadratic SVM classifier performs the best (accuracy: 98.16%, sensitivity: 98.93%, specificity: 98.77%) and maintains high accuracies in other similar architectures as well. This proves that even though radiography images might not be conclusive for radiologists, but it is so for deep learning algorithms for detecting COVID-19. We hope this extensive review will provide a comprehensive guideline for researchers in this field.

The regioselectivity in non-polar [3+2] cycloaddition (32CA) reactions has been studied within the Molecular Electron Density Theory (MEDT) at the B3LYP/6-311G(d,p) level. To this end, the 32CA reactions of nine simplest three-atom-components (TACs) with 2-methylpropane were selected. The electronic structure of the reagents has been characterised through the Electron Localisation Function (ELF) and the Conceptual DFT. The energy profiles of the two regioisomeric reaction paths and ELF of the transition state structures are studied to understand the origin of the regioselectivity in these 32CA reactions. This MEDT study permits to conclude that the least electronegative ends X1 atom of these TACs controls the asynchronicity in the C-X (X = C,N,O) single bond formation, and consequently, the regioselectivity. This behaviour is a consequence of the fact that the creation of the non-bonding electron density required for the formation of the new CX single bonds has a lesser energetic cost at the least electronegative X1 atom than that at the Z3 one.

Sun-Induced chlorophyll Fluorescence (SIF) relates directly to photosynthesis yield and stress but there are still uncertainties in its interpretation. Most of these uncertainties concern the influences of the emitting vegetation’s structure (e.g., leaf angles, leaf clumping) and biochemistry (e.g., chlorophyll content, other pigments) on the radiative transfer of fluorescent photons. The Caatinga is a large region at northeast Brazil of semiarid climate and heterogeneous vegetation, where such biochemical and structural characteristics can vary greatly even within a single hectare. With this study we aimed to characterize eleven years of SIF seasonal variation from Caatinga vegetation (2007 to 2017) and to study its responses to a major drought in 2012. Orbital SIF data from the instrument GOME-2 was used along with MODIS MAIAC EVI and NDVI. Environmental data included precipitation rate (TRMM), surface temperature (MODIS) and soil moisture (ESA CCI). To support the interpretation of SIF responses we have used red and far-red SIF adjusted by the Sun’s zenith angle (SIF-SZA) and by daily Photosynthetically Active Radiation (dSIF). Furthermore, we have also adjusted SIF through two contrasting formulations using NDVI data as proxy for structure and biochemistry, based on previous leaf-level and landscape level studies: SIF-Yield and SIF-Prod. Data was tested with time-series decomposition, rank correlation, spatial correlation and Linear Mixed Models (LMM). Results show that GOME-2 SIF and adjusted SIF formulations responded consistently to the observed environmental variation and showed a marked decrease in SIF emissions in response to a 2012 drought, that was generally larger than the corresponding NDVI and EVI decreases. Drought sensitivity of SIF, as inferred from LMM slopes, was correlated to land cover at different regions of the Caatinga. This is the first study to show correlation between landscape-level SIF and an emergent property of ecosystems (i.e., resilience), showcasing the value of remotely sensed fluorescence for ecological studies.

Background: To prioritize the development of antiviral compounds, it is necessary to compare their relative preclinical activity and clinical efficacy. Methods: We reviewed in vitro, animal model, and clinical studies of candidate anti-coronavirus compounds and placed extracted data in an online relational database. Results: As of July 2020, the Coronavirus Antiviral Research Database (CoV-RDB; covdb.stanford.edu) contained &gt;2,400 cell culture, entry assay and biochemical experiments, 240 animal model studies, and 56 clinical studies from &gt;300 published papers. SARS-CoV-2, SARS-CoV, and MERS-CoV account for approximately 85% of the data. Approximately 75% of experiments involved compounds with a known or likely mechanism of action, including receptor binding inhibitors and monoclonal antibodies (20%); viral protease inhibitors (18%); polymerase inhibitors (9%); interferons (8%); fusion inhibitors (8%); host endosomal trafficking inhibitors (7%); and host protease inhibitors (5%). For 724 compounds with a known or likely mechanism, 95 (13%) are licensed in the US for other indications, 72 (10%) are licensed outside the US or are in human trials, and 557 (77%) are pre-clinical investigational compounds. Conclusion: CoV-RDB facilitates comparisons between different candidate antiviral compounds, thereby helping scientists, clinical investigators, public health officials, and funding agencies prioritize the most promising compounds and repurposed drugs for further development.

Objective: To examine the burnout syndrome among the healthcare personnel in Puerto Rico during the COVID-19 pandemic. Methods: Descriptive study that pursues to understand burnout syndrome in the clinical personnel in Puerto Rico. The Maslach Burnout Inventory (MBI) was sent via email to healthcare professionals around the island. Furthermore, open questions were asked to the participants. Results: The overall burnout level on the clinical personnel was found to be moderate. Nonetheless, in physicians, 12.1% had severe burnout levels compared to a 13.1% score in nurses. Additionally, 92.4% of physicians and 100% of nurses had moderate to severe burnout. In the three subscales, nurses scored high levels in all of them, and physicians were high in Emotional Exhaustion and moderate level in Depersonalization and Personal Accomplishment at Work. There were high levels of burnout syndrome of the clinical personnel in Puerto Rico. Conclusion: Since the beginning of the COVID-19 pandemic, over 90% of healthcare professionals in Puerto Rico have been working with moderate to severe burnout syndrome, being the nurses the most affected. Key Words: Burnout syndrome, MBI, Clinical personnel, COVID-19, SARS-CoV-2

In this paper, a solenoid based linearly movable armature system is designed using robust control theory in order to improve the performance of the system. Reference track method is the best performance analysis for position control systems. Among the robust controllers, H infinity mixed-sensitivity and Mixed H 2 /H∞ with Regional Pole Placement Controllers are used to improve the performance of the system. Comparison of the proposed controllers for tracking a reference displacement signals (step and sine wave) and a promising simulation result have been obtained.

The coronavirus disease-2019 (COVID-19) pandemic is an ongoing pandemic caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Although COVID-19 pandemic is not a direct surgical problem, its impact on the surgical units has been substantial. Many operations have been cancelled or deferred due to risk of disease spread and staff shortages. Operating theatres are identified as areas of high risk of disease transmission due to aerosol generation during the surgical procedures and prolonged patient contact. Resource limitations, including lack of personal protective equipment (PPE) and limited availability of testing, continue to expose the surgical community to COVID-19. In this review, evidence and consensus guidelines on surgical practice during the COVID-19 pandemic are summarised and described. Immediate action is deemed essential to ensure unhindered provision of surgical care while optimizing the use of limited resources and ensuring staff safety.

Since the severe acute respiratory syndrome (SARS) outbreak in 2003, human coronaviruses (hCoVs) have been identified as causative agents of severe acute respiratory tract infections. Two more hCoV outbreaks have since occurred, the most recent being SARS-CoV-2, the causative agent of coronavirus disease 2019 (COVID-19). The clinical presentation of SARS and MERS is remarkably similar to COVID-19, with hyperinflammation causing a severe form of the disease in some patients. Previous studies show that the expression of the SARS-CoV E protein is associated with the hyperinflammatory response that could culminate in acute respiratory distress syndrome (ARDS), a potentially fatal complication. This immune-mediated damage is largely caused by a cytokine storm, which is induced by significantly elevated levels of inflammatory cytokines interleukin (IL)-1beta and IL-6, which are partly mediated by the expression of the SARS-CoV E protein. The interaction between the SARS-CoV E protein and the host protein, syntenin, as well as the viroporin function of SARS-CoV E, are linked to this cytokine dysregulation. This review aims to compare the clinical presentation of virulent hCoVs with a specific focus on the cause of the immunopathology. The review also proposes that inhibition of IL-1beta and IL-6 in severe cases can improve patient outcome.

It is unclear why European countries have been more severely affected by COVID-19 than East Asian countries. In this ecological study we compared the COVID-19 epidemics (cumulative incidence and mortality rates), host genetic susceptibility and national responses (testing intensity) in all European versus all Western Pacific/East Asian countries reporting cases in the first month of the epidemic. The host-genetic-susceptibility assessment was limited to the frequency of the D-allele of the angiotensin converting enzyme-1 (ACE-1) which has been found to be positively associated with COVID-19 incidence within European countries. Despite earlier epidemics, countries from the Western Pacific reported lower cumulative numbers of COVID-19 cases/100 000 inhabitants than European countries (P=0.0002). The Western Pacific countries also reported fewer cumulative COVID-19 deaths/100 000 (P=0.0024). Whilst there was little difference in the cumulative number of tests conducted/100 000, the percent of COVID-19 tests reported positive was higher in Europe than the Western Pacific (P=0.0076). The frequency of the ACE-1 D-allele was lower in the Western Pacific than European countries (P=0.0007). Our results suggest that a combination of different testing strategies and host genetic susceptibility contribute to difference in severity of the COVID-19 epidemics in the Western Pacific/East Asia and Europe.

Several epidemiological models are being used around the world to project the number of infected individuals and the mortality rates of the COVID-19 outbreak. Advancing accurate prediction models is of utmost importance to take proper actions. Due to a high level of uncertainty or even lack of essential data, the standard epidemiological models have been challenged regarding the delivery of higher accuracy for long-term prediction. As an alternative to the susceptible-infected-resistant (SIR)-based models, this study proposes a hybrid machine learning approach to predict the COVID-19 and we exemplify its potential using data from Hungary. The hybrid machine learning methods of adaptive network-based fuzzy inference system (ANFIS) and multi-layered perceptron-imperialist competitive algorithm (MLP-ICA) are used to predict time series of infected individuals and mortality rate. The models predict that by late May, the outbreak and the total morality will drop substantially. The validation is performed for nine days with promising results, which confirms the model accuracy. It is expected that the model maintains its accuracy as long as no significant interruption occurs. Based on the results reported here, and due to the complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research.

The fast spread of COVID-19 constitutes a worldwide challenge to the public health, educational, and trade systems, affecting the overall wellbeing of human societies. The high transmission and mortality rates of this virus, and the unavailability of a vaccine or treatment, resulted in the decision of multiple governments to enact measures of social distancing. Thus, it is of general interest to consider the validity of the proposal for keeping a social distancing of at least 2 m from other persons to avoid the spread of COVID-19. The exposure to the bioaerosol can result in the deposition of the pathogen in the respiratory tract of the host causing disease and an immunological response. In the atmospheric context, the work evaluates the effect of aerodynamic diameter (size) of particles in carrying RNA copies of the novel coronavirus. A SARS-CoV-2 carrier person talking, sneezing, or coughing at distance of 2 m can still provide a pathogenic bioaerosol load with submicron particles that remain viable in air for up to 3 hours for exposure of healthy persons near and far from the source in a stagnant environment. The deposited bioaerosol creates contaminated surfaces, which if touched can act as a path to introduce the pathogen by mouth, nose, or eyes and cause disease.

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models need to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak.

Water quality retrieval for small urban waterbodies by remote sensing get used to be difficult due to coarse spatial resolution of the remote sensing imagery. The recently launched Sentinel-2 produces imagery with a spatial resolution of 10 m. It provides an opportunity to solve the problem of retrieving water quality for small waterbodies. Additionally, many water management issues also require fine resolution of imagery, e.g. illegal discharge to an urban waterbody. Since illegal discharges are an important issue for urban water management, chemical oxygen demand (COD), total phosphorous (TP), and total nitrogen (TN) were chosen as the target parameters for water quality retrieval in this study. COD, TP and TN, however, are non-optically active parameters. There were limited studies in the past to retrieve these parameters in comparison with optically active parameters, e.g. Chlorophyll-A etc. This study compared three machine learning models, namely Random Forest (RF), Support Vector Regression (SVR), and Neural Networks (NN), to investigate the opportunity to retrieve the above non-optically active parameters. Results showed that R² of TP, TN, and COD by NN, RF and SVR were 0.94, 0.88, and 0.86, respectively. The performances of water quality retrieval for these non-optically active parameters were significantly improved by the optimized machine learning models. These models hence solved the problem to use remote sensing data to retrieve these non-optically active water quality parameters and provided a new monitoring strategy for small waterbodies. Water quality mapping obtained by Sentinel-2 imagery provided a full spatial coverage of the water quality characterization for the entire water surface. Compared with water samples collecting and testing, it greatly reduced labor cost, reagents cost, and waste treatment cost. It also may help identify illegal discharges to urban waterbodies. The method developed in this research provides a new practical and efficient water quality monitoring strategy in managing water with consideration of environmental sustainability.

We applied a generalized SEIR epidemiological model to the recent SARS-CoV-2 outbreak in the world, with a focus on Italy and its Lombardia, Piemonte, and Veneto regions. We focus on the application of a stochastic approach in fitting the model numerous parameters using a Particle Swarm Optimization (PSO) solver, to improve the reliability of predictions in the medium term (30 days). We analyze the official data and the predicted evolution of the epidemic in the Italian regions, and we compare the results with data and predictions of Spain and South Korea. We link the model equations to the changes in people’s mobility, with reference to Google’s COVID-19 Community Mobility Reports. We discuss the effectiveness of policies taken by different regions and countries and how they have an impact on past and future infection scenarios.

Recent emergence of novel coronavirus (SARS-CoV-2) all over the world has resulted more than 33,106 global deaths. To date well-established therapeutics modules for infected patients are unknown. In this present initiative, molecular interactions between FDA-approved antiviral drugs against the Hepatitis-C virus (HCV) have been investigated theoretically against the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. HCV and SARS-CoV-2 are both +ssRNA viruses. At 25^o C beclabuvir, a non-nucleoside inhibitor of the RdRp_HCV can efficiently bind to RdRp _SARS-CoV-2 (ΔG_AutoDock = -9.95 kcal mol^-1) with an inhibition constant of 51.03 nM. Both the ΔG_London and ΔG_{GBVI / WSA} values were - 9.06 and - 6.67 kcal mol^-1, respectively for binding of beclabuvir to RdRp_SARS-CoV-2. In addition, beclabuvir has also shown better binding free energy with RdRp_SARS-CoV-2 (ΔG_vina = -8.0 kcal mol^-1) than that observed with the Thumb 1 domain of RdRp_HCV (ΔG_vina = -7.1 kcal mol^-1). InterProScan has suggested the RNA-directed 5'-3' polymerase activity exists within 549^th to 776^th amino acid residues of RdRp_SARS-CoV, where the major amino acid residues interacting being I591, Y621, C624, D625, A690, N693, L760, D762, D763, and E813-N817. Molecular interaction suggests occupancy of beclabuvir inside the active site environment of the RdRp_SARS-CoV-2, the enzyme essential for viral RNA synthesis. In conclusion, results suggest beclabuvir may serve as an anti-SARS-CoV-2 drug.

One notable features of the SARS-CoV-2 genome is that the spike protein of SARS-CoV-2 has a functional polybasic (furin) cleavage site (RRAR) at the S1–S2 boundary through the insertion of 12 nucleotides encoding PRRA. To date, the furin cleavage site (FCS) remains an experimentally uncharted territory both structurally and functionally. For instance, whether or not FCS is actually cleaved, before or after viral cell entry or exit, still remains to be experimentally investigated. With currently available structural data, this article presents a computational structural characterization of the FCS inserted into SARS-CoV-2 spike glycoprotein, and puts forward a set of structural hypothesis against the hypothesis of SARS-CoV-2 from purposeful manipulation: (1), the inserted FCS does not alter, neither stabilize nor de-stabilize, the overall structure of SARS-CoV-2 spike glycoprotein; (2), the net structural consequence of FCS is the insertion of a furin cleavage site into SARS-CoV-2 spike glycoprotein, whose S1 and S2 subunits will still be bonded together even if the FCS is actually cleaved by furin protease.

The COVID-19 pandemic is placing unprecedented stress on healthcare systems around the world. Although Radiation Oncology Departments are not at the frontline of fighting this infectious disease, it is important to implement COVID-19 policies to reduce risk of staff and patient exposure, and to limit the risk of department shutdown or downtime. This brief report describes the policy implemented at George Washington University Radiation Oncology to manage the risks of COVID-19. This includes a General Statement related to the priorities of the Radiation Oncology department, a screening procedure for new and follow-up patients, management policies for critical and non-critical patients with COVID-19 or under quarantine, a policy for the management of patients currently under treatment who are diagnosed or placed in quarantine, a clinical escalation action plan, guidelines for staff meetings and travel, and procedure management. This policy was implemented at George Washington University Radiation Oncology after the first case of COVID-19 was reported in Washington DC on March 7, 2020.

The transnational spread of coronavirus (2019-nCoV) first detected in Wuhan is causing global panic; thus, accelerated research into clinical intervention is of high necessity. The spike glycoprotein structure has been resolved, and its affinity to human angiotensin-converting enzyme 2 (ACE-2) has been experimentally validated. Here, using computational methods, a metastable conformation of 2019-nCoV-RBD/ACE-2 complex has been revealed and FDA-database of approved drugs have been docked into the interface. Darunavir has been discovered as high ligand affinity candidate capable of disrupting communication between 2019-nCoV-RBD and ACE-2. Darunavir, in addition to its previously known anti-HIV protease inhibitor is now repurposeable for the treatment 2019-nCoV disease acting via disruption of cellular recognition, binding and invasion.

A novel coronavirus (SARS-CoV-2) that is initially found to trigger human severe respiratory illness in Wuhan City of China in 2019, has killed 2,718 people in China by February 26, 2020, and which has been recognized as a public health emergency of international concern as well. And the virus has spread to more than 38 countries around the world. However, the drug has not yet been officially licensed or approved to treat SARS-Cov-2 infection. NSP12-NSP7-NSP8 complex of SARS-CoV-2, essential for viral replication and transcription, is generally regarded as a potential target to fight against the virus. According to the NSP12-NSP7-NSP8 complex (PDB ID: 6NUR) structure of SARS, two homologous models were established for virtual screening in the present study, namely NSP12-NSP7 interface model and NSP12-NSP8 interface model. Seven compounds (Saquinavir, Tipranavir, Lonafarnib, Tegobuvir, Olysio, Filibuvir, and Cepharanthine) were selected for binding free energy calculations based on virtual screening and docking scores. All seven compounds can combine well with NSP12-NSP7-NSP8 in the homologous model, providing drug candidates for the treatment and prevention of SARS-CoV-2.

The NA61/SHINE experiment studies hadron production in hadron-hadron, hadron-nucleus and nucleus-nucleus collisions. The physics programme includes the study of the onset of deconfinement and search for the critical point as well as reference measurements for neutrino and cosmic ray experiments. For strong interactions, future plans are to extend the programme of study of the onset of deconfinement by measurements of open-charm and possibly other short-lived, exotic particle production in nucleus-nucleus collisions. This new programme is planned to start after 2020 and requires upgrades to the present NA61/SHINE detector setup. Besides the construction of a large acceptance silicon detector, a 10-fold increase of the event recording rate is foreseen, which will necessitate a general upgrade of most detectors.

The Biginelli reaction is a highly versatile reaction, which leads to dihydropyrimidinones/thiones. This scaffold is reported as being a privileged structure due to its ability to interact with biological targets. Synthesis of ethyl 4-(2-fluorophenyl)-6-methyl-2-thioxo-1-(p-tolyl)-1,2,3,4-tetrahydropyrimidine-5-carboxylate was achieved through the Biginelli reaction using a functionalized thiourea. In silico studies demonstrated that the compound title showed good potential for interacting with ecto-5’-nucleotidase, which has been considered as a target in designs for anti-cancer drugs.

Abstract Background: Diabetes mellitus is dramatically increasing in the wide world. The managing of diabetes care emphasized the self-management education and support into patients’ care and family care. Objective: to review and synthesizes the effectiveness of DSME strategies involving family as a key person to provide social support for diabetes mellitus self-management of glycemic uncontrolled patients Method: Three databases through PubMed, CINAHL, and Scopus were reviewed to assess the relevant articles. The following search terms: “type 2 diabetes,” “self-management,” “family support,” and “glycemic uncontrolled.” We summarized details of family support on self-management among glycemic uncontrolled patients for 14 existing studies. Results: A total of 22 intervention studies were identified. Those studies have a heterogeneous of the education strategies, support perceived, follow-ups strategies and outcomes among type 2 DM. Family integration on diabetes self-management education (DSME) has a positive impact on several outcomes including, self-care behaviors, psychological outcomes, self-efficacy and clinical outcomes Conclusions: This systematic review found robust data related to the integration of family support on diabetes self-management among glycemic uncontrolled patients. Consequently, the improvement in outcomes was identified. Implications: The findings suggest model of family engagement is better and needed for sustaining the diabetes care in the long-term care

Glacier dynamics play an important role in the mass balance of many glaciers, ice caps and ice sheets. In this study we exploit Radarsat-2 (RS-2) Wide Fine (WF) data to determine the surface speed of Svalbard glaciers in the winters of 2012/2013 and 2013/2014 using Synthetic Aperture RADAR (SAR) offset and speckle tracking. The RS-2 WF mode combines the advantages of the large spatial coverage of the Wide mode (150 x 150 km) and the high pixel resolution (9m) of the Fine mode and thus has a major potential for glacier velocity monitoring from space through offset and speckle tracking. Faster flowing glaciers (1.95 m d^-1 - 2.55 m d^-1) which are studied in detail are Nathorstbreen, Kronebreen, Kongsbreen and Monacobreen. Using our Radarsat-2 WF dataset, we compare the performance of two SAR tracking algorithms, namely the GAMMA Remote Sensing Software and a custom written MATLAB script (GRAY method) that has primarily been used in the Canadian Arctic. Both algorithms provide comparable results, especially for the faster flowing glaciers and the termini of slower tidewater glaciers. A comparison of the WF data to RS-2 Ultrafine and Wide mode data reveals the superiority of RS-2 WF data over the Wide mode data.

Dietary vitamin A/all-trans retinol/ROL plays a critical role in human vision. ROL circulates bound to the plasma retinol-binding protein (RBP4) as RBP4-ROL. In the eye, the STRA6 membrane receptor binds to circulatory RBP4 and internalizes ROL. STRA6 is however not expressed in systemic tissues, where there is high-affinity RBP4 binding and ROL uptake. We tested the hypothesis, that the second retinol-binding protein 4 receptor 2 (Rbpr2) which is highly expressed in systemic tissues of zebrafish and mouse, contains a functional RBP4 binding domain, critical for ROL transport. As for STRA6, modeling and docking studies confirmed three conserved RBP4 binding residues in zebrafish Rbpr2. In cell culture studies, disruption of the RBP4 binding residues on Rbpr2 almost completely abolished uptake of exogenous vitamin A. CRISPR generated rbpr2-RBP4 domain zebrafish mutants showed microphthalmia, shorter photoreceptor outer segments, and decreased opsins, that were attributed to impaired ocular retinoid content. Injection of WT-Rbpr2 mRNA into rbpr2 mutant or all-trans retinoic acid treatments rescued the mutant eye phenotypes. In conclusion, zebrafish Rbpr2 contains a putative extracellular RBP4-ROL ligand-binding domain, critical for yolk vitamin A transport to the eye for ocular retinoid production and homeostasis, for photoreceptor cell survival.

This study offers an analysis of existing research on sustainability and its link to accounting and management control in the port sector. The existing studies do not provide a comprehensive discussion of management accounting and control tools in this context, despite recognizing the relevance of the issue. The Scoping Review was used as a methodological basis, with reference to the framework of Arksey and O’Malley [1], with the aim of mapping the literature on the role of ac-counting and management control, as well as their relationship with the Triple Bottom Line associated with the various levels of sustainability in this sector. The results point to a diversity of tools used essentially in developed countries, where the interest in efficiency, sustainability and strategic alignment stands out.

For very first time, we report the synthesis of 8-(2-methoxyphenyl)-6-methyl-2-(1-methyl-1H-benzo[d]imidazol-2-yl)quinoline 1. This was achieved in several steps, including usage of Suzuki reaction for functionalization of 2-(1H-benzo[d]imidazol-2-yl)quinoline moiety. The new compound exhibits blue fluorescence. Its structure was confirmed with 1D- and 2D-NMR spectroscopy, IR-spectroscopy, high-resolution mass spectrometry and X-ray analysis.

Survivability is a critical concern in WSNs, heavily influenced by energy efficiency. Addressing severe energy constraints in WSNs requires solutions that meet application goals while prolonging network life. This paper presents an energy optimization approach (EOAMRCL) for WSNs, integrating the Grey Wolf Optimization (GWO) for enhanced performance. EOAMRCL aims to enhance energy efficiency by selecting the optimal duty-cycle schedule, transmission power, and routing paths. The proposed approach employs a centralized strategy using a hierarchical network architecture. During the cluster formation phase, an objective function, augmented with GWO, determines the ideal cluster heads (CHs). The routing protocol then selects routes with minimal energy consumption for data transmission to CHs, using transmission power as a metric. In the transmission phase, the MAC layer forms a duty-cycle schedule based on cross-layer routing information, enabling nodes to switch between active and sleep modes according to their network allocation vectors (NAV). This process is further optimized by an enhanced CSMA/CA mechanism, which incorporates sleep/activate modes and pairing nodes to alternate between active and sleep states. This integration reduces collisions, improves channel assessment accuracy, and lowers energy consumption, thereby enhancing overall network performance. EOAMRCL was evaluated in a MATLAB environment, demonstrating superior performance compared to EEUC, DWEHC, and CGA-GWO protocols, particularly in terms of network lifetime and energy consumption. This highlights the effectiveness of integrating GWO and the updated CSMA/CA mechanism in achieving optimal energy efficiency and network performance.

This study assesses the impact of nurse-originated changes in central venous catheter (CVC) management on the incidence of central line-associated bloodstream infections (CLABSI) and catheter-related bloodstream infections (CRBSI). It is a single-center retrospective cohort study conducted at an urban, tertiary referral, and academic center serving pediatric patients. The study cohort comprised 236 patients and 323 CVCs seen between 2012 and 2022. CLABSI and CRBSI were defined according to the Centers for Disease Control and Prevention definitions. Oncology nurse leaders developed CVC-specific educational modules for CLABSI prevention. All relevant information during the CVC maintenance period was noted in the patient's CVC logbook. 24 (7%) cases of confirmed CLABSI were identified. The incidence of CVC-related infections was 0.32 cases per 1000 catheter days. The incidence decreased by 40% between the first and second three-year study period. Documented exit-site infection was reported in 32 (10%) cases. The correlation between exit-site infection and CLABSI was found in 9 (28%) cases. Our CVC-related infection rates are significantly lower than the incidence reported by the Italian Association of Pediatric Hematology and Oncology, which settles at 3-5 cases per 1000 catheter days. Our data confirm the effectiveness of local CVC management guidelines in preventing CVC-related infectious complications.

Polymeric Intraocular lenses (IOLs) are vital for restoring vision following cataract surgery and for correcting refractive errors. Despite technological and medical advancements, challenges persist in achieving optimal vision and preventing complications. Surface modifications aim to mitigate the risk of posterior capsule opacification (PCO), while pre-operative measurements aid in selecting suitable IOLs. However, individualized solutions are lacking and there is a clear demand for the development of fully customised IOL surfaces. We employ laser micromachining technology for precise modifications via ablation on PMMA and Acrylic IOLs, using femtosecond (fs), nanosecond (ns), and diode continuous wave (CW) lasers, at wavelengths ranging from near-ultraviolet to infrared. Characterization reveals controlled ablation patterning, achieving feature sizes from as small as 400 nm to several micrometers. Regular and confocal Micro-Raman spectroscopy revealed alterations of the IOL materials' structural integrity for some pattering cases, thus affecting the optical properties, while these can be minimised by proper selection of micromachining conditions. The results suggest the feasibility of accurate IOL patterning, which could offer personalized vision correction solutions, based on relevant corneal wavefront data, thus surpassing standard lenses, marking a significant advancement in cataract surgery outcomes.

For the first time to optimize the creation of new neuroprotective agents based on bioflavonoids, we applied information technologies - docking analysis to calculate the binding of candidate molecules to the pharmacological target protein transthyretin, as well as the program of virtual screening of NO scavengers. As a result of this approach, the substance catechin was isolated from candidate molecules - quercetin, catechin, Epicatechin gallate, Epicatechin, Procyanidin B1, Procyanidin B2, Procyanidin B3, Catechin-3-gallate according to docking analysis. As a result of virtual screening, catechin was identified as a potential NO scavenger (55.15% prediction). The results of the prediction were confirmed by in vitro experiments. Course administration of catechin to animals with experimental multiple sclerosis (MS) against the background of methylprednisolone administration completely eliminated lethal cases, reduced the number of diseased animals by 20%, as well as prevented the development of severe neurological symptoms by 20% (compared to the methylprednisolone group) and by 60% compared to the control group. Course administration of catechin with methylprednisolone leads to decrease of neurodegradation markers in the cytosol of rats with EAE: NSE by 37%, and S-100 - by 54.8%. The combined administration of methylprednisolone significantly exceeds the combination of methylprednisolone with the reference drug mexidol by the degree of NSE reduction. The obtained results indicate a significant neuroprotective effect of ocular combinations of methylprednisolone and catechin. The above-mentioned confirms the correctness of bioflavonoid selection with the help of virtual screening program.

When profit-driven renewal is difficult to implement, many historic districts are “frozen protected” in China. In the social context of “building cities for the people” in recent years, the public value-oriented renewal of urban historic areas plays an important role in the transformation of cities. This study investigates the strategies of historic district regeneration in China by integrating spatial form, urban governance, and public value. We propose a novel framework to analyze the regeneration of historic districts, using Taiyuan Bell Tower Street as a case study. The framework distinguishes between two dimensions: spatial and economic-social. In the spatial dimension, we focus on the transformation of spatial form to regenerate public value, emphasizing the attribute of "publicness" as central to urban regeneration efforts. This involves a tiered approach of excavating and upgrading historic districts at macro, meso, and micro levels. In the economic-social dimension, we explore urban governance to strengthen public value, involving government, market, and societal actors in a collaborative renewal process. The analysis highlights that a public value-oriented approach to heritage regeneration offers greater sustainability and could serve as a model for other cities seeking similar outcomes.

Lane detection is a foundational technology for autonomous driving systems. It involves identifying the boundaries of lanes on the road and ensuring the vehicle stays within these boundaries. Accurate lane detection is crucial for safety, navigation and traffic management. This paper presents an artificial intelligent based autonomous road lane detection and navigation system for vehicles. The system can detect and analyze road lanes accurately and efficiently in real-time, with frame rates of up to 17 FPS. By utilizing image processing techniques, the system can identify the location and boundaries of road lanes and obstacles on the road and provide accurate and reliable navigation guidance to the driver. The system is integrated with sensors and actuators to provide comprehensive autonomous navigation. The efficiency of the proposed system is demonstrated using accuracy of lane detection on straight and curve lanes covering frames per second and motor of the speed as parameters for assessment. Results show that the proposed system detects lane as entire lane detection, partial lane detection and no detection status on different settings.

Mangrove ecosystems are one of the most productive on our planet but have declined globally by 30-50%. Many species rely on mangrove habitat and thus their conversion to aquaculture farms has led to a noticeable loss in commodities such as wild fish stocks. This study aimed to assess 1) the influence of the presence of aquaculture and 2) restoration projects on the ecosystems ability to provide resources. We collected data on mangrove vegetation (i.e., biomass, richness and abundance), soil nutrients (i.e. organic carbon, aluminium and nitrogen), crab abundance and fishing pressure in six sites. We set up 15 plots in each site and collected data between May and July 2023. Via generalised linear mixed models we found that the abundance and richness of crabs was significantly higher in aquaculture plots than in no aquaculture plots. Aquaculture plots had higher topsoil aluminium, topsoil and subsoil Nitrogen, and had lower topsoil Carbon than non-aquaculture sites. Restored sites had less Nitrogen in the topsoil than unmanaged sites. Biomass did not change between aquaculture, restored and unmanaged plots. We found a negative correlation between crab abundance and richness and mangrove DBH, suggesting that the species of crabs present preferred areas with propagules for feeding (e.g., Grapsidae crabs). The content of nitrogen in the subsoil was positively correlated with mangrove richness, diversity and height, suggesting the importance of nitrogen availability for mangrove growth. The content of aluminium in the subsoil was negatively correlated with the content of organic carbon both in topsoil and subsoil, suggesting the detrimental effect of aluminium on the carbon cycle. Fishing practices were observed in all sites during the data collection period. Even if most of the vegetation parameters were not significantly affected by presence of aquaculture or management for restoration, it is clear that important variables such as aluminium carbon, and nitrogen content in the soil and crab assemblages were highly variable.

Poultry farming in Slovakia has a tradition and an irreplaceable position to ensure rational nutrition for the population. In terms of a nutritional value, poultrymeat (Galliformes) contains a high amount of proteins, essential amino acids, essential unsaturated fatty acids, minerals, vitamins and a low fat content. Poultrymeat production has a relatively short reproductive cycle and thus allows regulating the demand and supply. The poultry market also influences the development of domestic consumption. According to the Statistical Office of the Slovak Republic, the consumption of meat has witnessed a persistent increase over the last 10 years. [1] According to the 2023 AVEC (The Voice of European Meat Sector) annual report, the consumption of poultrymeat in Slovakia was 20.0 kg per person per year. The average consumption in the EU-27 (2021) was 23.4 kg, with the countries with the highest consumption being Portugal (37.8 kg), Ireland (36.0 kg), Hungary (33.5 kg) and Spain (29.9 kg). On the other hand, the countries with the lowest consumption of poultrymeat, apart from Slovakia, also include Austria and Greece with a consumption of 21.5, resp. 21.0 kg [2]. The breeding of broiler chickens, as well as the production and placing on the market of poultrymeat must comply with the requirements laid down by legislation, while the compliance is regularly checked by the competent authorities.

The open data market is growing, driven by laws requiring governments to make data publicly available. However, the true value of this market lies in the products and services derived from open data. In Slovenia, the open data market has been growing since 2015, especially in the field of mobility. Platforms such as Avtolog.si facilitate the retrieval of vehicle data via vehicle identification numbers, while tocen.si, ojpp.si, and brezavta.si aggregate mobility data, focusing on sustainable and micromobile public transportation services. These platforms use open government data and private sector open data, and are freely accessible. This study examines the use of open data in the Slovenian mobility applications and similar solutions developed in other countries. By mapping these applications, we gain valuable insights into potential advances in the field, and provide a useful resource for future developers worldwide. By focusing on the socio-economic impact of these innovations, the study identifies methods for evaluating such applications. This approach highlights how transforming open data into user-friendly products and services can deepen our understanding of their broader societal and economic benefits. While open data is valuable in its own right, its full transformative potential is realized through innovative products that support sustainable lifestyles and promote environmentally conscious behavior.

Despite the recognized influence of body mass on combat techniques, the relationship between body segment mass (BSM) and combat moves remains unexplored. This study aimed to examine the relationship between striking arm mass (SAM), kicking leg mass (KLM), and body mass (BM) with the dynamic forces of the direct punches (DP), palm strikes (PS), elbow strikes (ES), front kicks (FK), and countermovement jumps (CMJ) performance. Sixteen male military cadets (22.3 ± 1.8 years, 181.4 ± 7.0 cm, 82.1 ± 8.5 kg) performed combat techniques, with performance measured by using a force plate and body segment mass assessed by Dual-energy X-ray absorptiometry. Spearman's correlation analysis, the Wilcoxon test, and Cohen's d were applied. Results indicated the relationship between KLM or BM and FK impulse (r = 0.64, p = 0.01; r = 0.52, p = 0.04, respectively) and CMJ impact force (r = 0.80, p ≤ 0.01; r = 0.70, p ≤ 0.01, respectively). Moreover, FK peak and impact forces were moderately correlated with CMJ jump height (r = 0.74, p ≤ 0.01; r = 0.77, p ≤ 0.01). The highest relationship was found between KLM and FK impulse; however, the difference in variability explained by KLM versus body mass is only 12%. This suggests that knowledge of BSM did not provide a significantly better estimate of the dynamic forces of the punches and FK than BM.

Whey protein was pretreated with multi-frequency ultrasound in mono, dual, and tri-frequency modes. The effect of multi-frequency ultrasound pretreatment on the hardness, chemical forces, and microstructure of acid-induced whey protein gel was investigated. Whey protein gels pretreated with dual and tri-frequency ultrasound showed higher hardness (p3.35 mm) in those samples were resisted to gastric digestion. Moreover, the tri-frequency ultrasound pretreatment of whey protein gel released the least free amino group during gastric digestion. In contrast, whey protein gel with the mono-frequency ultrasound pretreatment released the highest amount of free amino acid group during intestinal digestion. Findings from this study suggested that gel hardness and network density could modulate the digestion behaviors of protein gels.

Microplastic pollution (MP) in marine environments around the globe is severe and enough precautions have not been taken so far for its prevention. The focus of this study is to quantify MPs from beach sediment and seawater samples and to identify their distribution and types along the western coast of Sri Lanka from the Kelani River estuary to the Mahaoya estuary. Nine sites along this 42 km stretch were selected and random sampling was employed to collect a minimum of 8 sediment samples from each site between October and December 2021. Water samples were also collected, parallel to the sediments, from the ocean surface. FTIR analysis revealed that most of the MPs found were polyethylene(PE), polypropylene(PP), polystyrene(PS), polyethylene terephthalate(PET), and phenol formaldehyde resin. The mean abundance of MPs varied from 2.0 ± 0.6 items/L to 161.0 ± 15.7 items/L in water samples and, from 3.0 ± 0.3 items/m2 to 656.0 ± 34.5 items/m2 in sediment samples. The MPs found were identified in different shapes as fragments (80.2%), pellets (14.9%), fibers (2.7%) and foams (2.5%). Analysis revealed that the beach sediments were contaminated with PS, phenol formaldehyde resin, PET, PP and PE, while surface seawater is dominated by phenol formaldehyde resin, PS, PP and PE.

This review examines methodologies studying soil carbon in urban green spaces, a field requiring higher attention as their ecosystem services are valued and urban mitigation plans against climate change are developed. In the growing global urbanization, urban green spaces play a crucial role as nature-based solutions to address climate challenges, demanding efficient carbon accounting and reduction strategies. In this research, a systematic review was conducted assessing publications from 2021 to 2023 in the databases Web of Science and Scopus. Findings expose the lack of standardization in the methodologies used to study soil carbon in urban green spaces, evidencing in situ measurements at different sampling depths and studies without longitudinal monitoring over time. In addition, studies originated primarily in universities from China, United States and Spain, which focused on carbon in the form of Soil Organic Carbon and Total Carbon. Based on these findings, recommendations are made advocating for the combination and standardizing methodologies. This review offers valuable insights that shed light on an ignore and often overseen issue. Further studies and standardized methodology are needed, to help cities efforts in their pursuit of carbon neutrality by acknowledging the influential role of urban soils, especially green spaces.

In the majority of children with growth hormone (GH) deficiency (GHD), normal GH secretion may occur before the attainment of final height. The aim of the study was to assess the incidence of persistent and transient GHD and the effectiveness of recombined human GH (rhGH) therapy in children with isolated idiopathic GHD, with respect to the moment of therapy withdrawal and according to different diagnostic criteria of GHD. Analysis included 260 patients (173 boys, 87 girls) with isolated idiopathic GHD who completed rhGH therapy and have reassessed GH and IGF-1 secretion. The incidence of transient GHD with respect to different pre- and post-treatment criteria was compared together with assessment of GH therapy effectiveness. Incidence of transient GHD, even with respect to pediatric criteria was very high. Normal GH secretion occurred before the attainment of near-final height. Application of more restricted criteria decreased the number of children diagnosed with GHD but not the incidence of transient GHD among them. Poor response to GH therapy was observed mainly in patients with normal IGF-1 before treatment, suggesting that diagnosis of GHD may be false positive. Further efforts should be made to avoid overdiagnosis GHD and overtreatment of the patients.

Background Sarcopenia is a state with progressive and generalized loss of skeletal muscle mass and strength. It is a serious complication occurring in chronic kidney disease (CKD) patients which increases morbidity and mortality rate. Sarcopenia is diagnosed when loss of both compartments - muscle strength and skeletal muscle quality or quantity are present. However, there are still numerous patients, also with CKD, diagnosed as pre-sarcopenic individuals with low muscle strength and normal skeletal muscle quality or quantity and conversely, with correct muscle strength and decreased skeletal muscle mass, who are prone to develop sarcopenia in future life. It is crucial to examine numerous variables possibly associated with changes of skeletal muscle mass and muscle strength in terms of preventing the development of sarcopenia. The aim of the study was to investigate anthropometric and clinical correlates and sources of variation in both skeletal muscle mass and muscle strength in advanced stages of CKD. Methods The study sample consisted of 84 non-dialysis dependent patients of both sexes (including 45.2% of women) with eGFR < 45 ml/min/1.73m²: 26.2% with eGFR 30-44 mL/min/1.73 m², 65.5% with eGFR 15-29 mL/min/1.73 m² and 8.3% with eGFR < 15 mL/min/1.73 m². Muscle strength was estimated by measuring hand grip strength (HGS) with the use of handheld hydraulic dynamometer. Muscle quantity was measured by bioimpedance spectroscopy using Body Composition Monitor. Appendicular skeletal muscle mass (ASM) was calculated according to Lin’s formula. Serum creatinine, urea, uric acid and albumin were measured. Results In bivariate analysis we found that ASM significantly and positively correlated with anthropometric variables such as body mass (r=0.903, p<0.001), NH weight (r=0.882, p<0.001), height (r=0.694, p<0.001), body mass index (BMI) (r=0.701, p<0.001), lean tissue mass (LTM) (r=0.664, p<0.001), lean tissue index (LTI) (r=0.433, p<0.001), fat mass (r=0.614, p<0.001) and fat tissue index (FTI) (r=0.449, p<0.001), and was negatively associated with clinical variable such as hydration status (p<0.001). HGS significantly and positively correlated with anthropometric parameters such as body mass (r=0.319, p=0.003), NH weight (r=0.315, p=0.004), height (r=0.666, p<0.001), LTM (r=0.490, p<0.001), LTI (r=0.238, p=0.029), and ASM (r=0.501, p<0.001), and was negatively associated with clinical variables like uric acid (p=0.039) and urea (p<0.001). After adjustment for age, sex and height, HGS remained significantly and negatively related with uric acid (β=-1.078, p=0.041) and hydration status (β=-0.805, p=0.042). Conclusions In CKD patients, ASM is determined mainly by anthropometric parameters but HGS - both by anthropometric and clinical variables specific for CKD.

MicroRNAs are small non-coding RNAs, which contribute to the regulation of many physiolog-ical and pathological processes. Conventionally, miRNAs perform their activity in the cyto-plasm, where they regulate gene expression by interacting in a sequence-specific manner with mature messenger RNAs. Recent studies point to the presence of mature miRNAs in the nucleus. This review summarizes current findings regarding the molecular activities of nuclear miRNAs. These molecules can regulate gene expression at the transcriptional level by directly binding DNA on the promoter or the enhancer of regulated genes. MiRNAs recruit to these regions dif-ferent protein complexes, resulting both in activation or repression of transcription, through a number of molecular mechanisms. Haematopoiesis is presented as a paradigmatic biological process whereby nuclear miRNAs possess a relevant regulatory role. Nuclear miRNAs may af-fect gene expression also acting on nuclear mRNA processing and on the biogenesis of miRNA themselves by regulating pri-miRNA maturation. Overall, nuclear miRNAs are biologically ac-tive molecules that can be critical for the fine tuning of gene expression and deserve further studies in a number of physiological and pathological conditions

The enterprise software sector is experiencing a significant transformation driven by rapid technological progress and evolving business needs. An effective release management process is crucial for the solution providers and customers, as they incorporate the principles of Industry 4.0 and 5.0. With the growing dependence on software solutions and services, ensuring their quality, reliability, and security is highly necessary. The release management process incorporates strategic planning, regression testing, accurate deployment, and continuous monitoring of software updates. However, the rapid advancements in artificial intelligence (AI) and machine learning (ML) create a unique challenge to the release management process. The existing research needs to address the necessary adaptations for Industry 5.0, mainly in product-based software organizations, to the release management process without a change management system. After working with several software solution stakeholders, based on the responses from SaaS project stakeholders, we have presented a revised software release readiness workflow by incorporating a change management module. The preliminary result based on data over a limited period of time indicates that the revised workflow has the potential to improve the management of slippage, particularly by more effectively addressing NFR-related issues, thereby resulting in more predictable and reliable release cycles.

Background and Objectives Neurofibromatosis 1 (NF1 MIM # 162200), also known as von Recklinghausen disease, is among the most common autosomal dominantly transmitted disorders characterized mainly by neurocutaneous manifestations such as café au lait spots, intertriginous freckling, various types of neurofibromas (cutaneous neurofibromas or plexiform tumors), neurological manifestations, and bone abnormalities. It occurs with an incidence of 1:3000–1:4000 cases. Cone-rod dystrophies belong to the large group of retinal dystrophies, a highly heterogeneous group of disorders clinically manifested mainly by damage to cone and rod cells and have a broad spectrum of clinical manifestations. Many genes are involved in their etiology, with more than 100 currently identified, including the CRX gene responsible for the autosomal dominant form of cone-rod dystrophy (ad CORD). Materials and Methods: The authors present an intriguing case of a patient diagnosed with Neurofibromatosis type 1 (NF1) as an infant and ocular involvement (myopia and astigmatism onset at age 15), which yielded a surprising molecular testing result. Results: Molecular DNA analysis identified a rare occurrence of two mutational variants, including a pathogenic variant in the NF1 gene, c.3871-2A, and a likely pathogenic variant in the CRX gene c.119G>A. Conclusions: The authors present this case to highlight the surprises offered by molecular testing in a condition where the diagnosis is usually based on clinical criteria, thus providing patients with competent genetic advice.

The emotion of disgust protects individuals against pathogens, and it has been found that during pregnancy, it is elevated. Physiological mechanisms discussed in relation to these changes include immune markers and progesterone levels. The aim of this study is to assess the association between steroids and disgust in pregnancy. In a sample of 179 pregnant women, we have analyzed blood serum steroid concentrations and measured disgust sensitivity by text-based questionnaires in the first and third trimester. We found positive correlations between disgust sensitivity and the levels of C19 steroids, including testosterone, but also its precursors in the Δ5 pathway (androstenediol, DHEA, and their sulfates) and the Δ4 pathway (androstenedione). Furthermore, positive correlations between disgust sensitivity and 5α/β-reduced C19 steroid metabolites were consistently present in both trimesters. In the first trimester, we found a positive association between disgust sensitivity and 17-hydroxypregnanolone as well as some estrogens. In the third trimester, we have observed positive associations between disgust sensitivity and cortisol as well as immunoprotective Δ5 C19 7α/β-hydroxy-steroids. Our study has thus shown that disgust sensitivity is positively correlated with immunomodulatory steroids, and in the third trimester, steroids may reflect potential maternal anxiety-related symptoms.

Graphene hybrid-filler polymer composites have emerged as prominent materials that revolutionize heavy industries. This study encapsulates the in-depth analysis of different influential factors such as filler/graphene type, aspect ratios, dispersion methods, filler-matrix compatibility, fiber orientation, synergistic effects, different processing techniques, and post-curing conditions that affect the processing, properties and determine the resultant applications of graphene hybrid polymer composites. Additionally, it discusses the substantial role of graphene collaboration with other fillers such as carbon nanotubes, silica, nano-clays and metal oxides to produce functionalized hybrid polymer composites with synergistically enhanced tailored properties to offer solutions for heavy industries like aerospace, automotive, electronics, and energy harvesting. The review concludes with some suggestions and outlook on the future of these composite materials by emphasizing the need for continued research to fully optimize their potential.

Human Activity Recognition (HAR) technology enables continuous behavior monitoring, particularly valuable in healthcare. This study investigates the viability of using an ear-worn motion sensor for classifying daily activities, including lying, sitting/standing, walking, ascending stairs, descending stairs, and running. Fifty healthy participants (between 20 and 47 years old) engaged in these activities while under monitoring. Various machine learning algorithms, ranging from interpretable shallow models to state-of-the-art deep learning approaches designed for HAR, were employed for classification. Results demonstrate the ear sensor's efficacy, with deep learning models achieving 98% accuracy rate of classification. The obtained classification models are agnostic regarding which ear the sensor is worn and robust against moderate variations in sensor orientation (e.g., due to differences in auricle anatomy), meaning no initial calibration of the sensor orientation is required. The study underscores the ear's efficacy as a suitable site for monitoring human daily activity and suggests its potential for combining HAR with in-ear vital signs monitoring. This approach offers a practical method for comprehensive health monitoring by integrating sensors in a single anatomical location. This integration facilitates individualized health assessments, with potential applications in tele-monitoring, personalized health insights, and optimizing athletic training regimes.

Sensory integration is an essential function of human life, and its decline causes difficulties in the quality of life, especially in older adults. In this study, we proposed an arm-reaching task based on a virtual reality head-mounted display (VR-HMD) system to assess sensory integration in daily life, and examined whether reaching task performance was associated with age and resting-state functional connectivity (rsFC) between the brain regions of interest involved in sensory integration. We hypothesized that performance during a reaching task with multiple cognitive loadings would be affected by aging. The gap angle between the reaching hand and target positions was compared between older and middle-aged adults as a measure of sensory integration function. In addition, rsFC, which was significantly correlated with the gap angles of individual participants in the older adult group, was identified using resting-state functional magnetic resonance imaging data. The mean gap angle was significantly larger in the older adults than in the middle-aged group and was also significantly correlated with connections between the left primary motor area and the left inferior temporal gyrus, temporo-occipital part. Because the connectivity between the areas is known to be related to visuomotor integration, the results suggest the involvement of visuomotor integration in the decline of sensory integration function in old age and the validity of the gap angle during the proposed VR-HMD task as an index for the decline in function.

The regulation of cell death is a fundamental issue in cell biology and continues to be intensely investigated worldwide. The significance of research in this field persists because understanding the determinants of cell lifespan directly impacts the maintenance of multicellular organism homeostasis and, consequently, is crucial for addressing biomedical challenges associated with various diseases. It is recognized that the initiation of cell death can be prompted by both specific signals (such as cytokines or hormones) and nonspecific stimuli, including radiation, temperature increase, or oxidants. When these factors affect a cell, numerous signaling pathways are triggered in the cell, leading to neutralization of the effects of their negative effects or, in case of irreparable damage, to cell elimination. This removal of damaged cells occurs through apoptosis or programmed cell death, a highly regulated process. Numerous signaling molecules participate in orchestrating the apoptotic process, many of which also govern other essential functions within the organism. Physiological factors capable of triggering the apoptotic program in cells include nitric oxide (NO), which serves as one of the key signaling molecules regulating the functions of the cardiovascular, nervous, and immune systems of the organism. The unique chemical nature of NO, along with its numerous intracellular targets and physiologically active redox forms, raises questions about the specific mechanisms through which NO exerts its damaging effects on cells. Utilizing pharmacological preparations- such as sources (donors) of exogenous nitric oxide- represents an approach to investigating the initiation and execution of the apoptotic program in sensitive target cells. Furthermore, this approach holds promise as a direction for discovering new selective drugs.

Background and Objectives: In this current state, Type 2 Diabetes Mellitus (T2DM) is more prevalent in the population, and metformin is used as a first-line medication for treating it. There was up surge in the utilization of alternative therapies in the management of diabetes. Especially in diabetes, Herbal medicines are considered safe and reliable by majority of the population. Aim: The purpose of this research is aimed to estimate the safety and efficacy of Polyherbal Metabolite Compounds (PHMC) capsules in adults with T2DM. Materials and Methods: In this study, 60 T2DM patients aged 18-60 years were randomly assigned to Groups A (30) receiving Metformin 500 mg twice a day after food and Group B (30) receiving PHMC capsule 500 mg twice a day after food in a prospective, randomized and open-label clinical study. The in-silico simulation study was performed to selected plants major compounds on target protein Insulin-like Growth Factor-1 (1K3A). Result: The PHMC is found to be safe and effective in the management of T2DM. The FBS, PPBS and HbA1c were significantly lowered (p