The global pandemic of COVID-19 accounts for more than 14,000 deaths worldwide. However, little is known about the host genetics interaction with infection and COVID-19 progression. To better understand the role of host genetics, we review the current literature, aggregate readily available genetic resources, and provide some updated analysis relevant to COVID-19 and associated phenotypes. Using the unrelated individuals in UK Biobank (total n = 337,579 across 5 populations), we aggregate human leukocyte antigen and ABO blood type frequencies. We find significant and consistent risk reduction of blood group O reported in Zhao et al. and encourage broad sharing of ABO blood type frequencies that are readily accessible across COVID-19 with mild, moderate, and severe/critical symptoms for robust inferences at https://tinyurl.com/abo-covid19. In addition, we generate polygenic risk scores (PRSs) weights for 29 blood measurements, including clinically relevant haematological measurements for COVID-19, such as lymphocyte count and percentage. Focusing on the 8 most COVID-19 clinically relevant blood measurements, we performed PRS-PheWAS analysis across 44 disease antigen measurements (n = 6,643 unrelated individuals in White British group), infectious diseases and acute respiratory infections (n = 20,928 cases and 349,000 controls across 3 population groups) and deaths (n = 1,846 cases and 368,082 controls), recorded in hospital inpatient record and death registry data, respectively, in UK Biobank, and find host genetic PRS associations with disease risk. Taken together, we anticipate these resources (https://github.com/rivas-lab/covid19) will aid in improving our understanding of host genetic risk factors playing a role in SARS-CoV-2 infection and COVID-19 disease severity.

Rodents are known to be reservoir hosts for at least 60 zoonotic diseases and are known to play an important role in their transmission and spreading in different ways. We sampled different rodent communities within and around human settlements in Northern Senegal, an area subjected to major environmental transformations associated with global changes. Herein, we conducted an epidemiological study on their bacterial communities.One hundred and seventy-one (171) invasive and native rodents were captured, 50 from outdoors trapping sites and 121 rodents from indoors habitats, consisting on 5 species. DNA of thirteen pathogens have been successfully screened on the rodent’s spleens. We found: 2.3% of positive spleens to Piroplasmida and amplified one which gives a potentially new species Candidatus “Theileria senegalensis”; 9.35% of Bartonella spp. and amplified 10, giving three genotypes. 3.5% of filariasis species; 18.12% of Anaplasmataceae species and amplified only 5, giving a new potential species Candidatus “Ehrlichia senegalensis”; 2.33 % of Hepatozoon spp.; 3.5% of Kinetoplastidae spp; and 15.2% of Borrelia spp. and amplified 8 belonging all to Borrelia crocidurae.Some of the species of pathogens carried by the rodents of our studied area may be unknown because most of those we have identified are new species. In one bacterial taxon, Anaplasma, a positive correlation between host body mass and infection was found. Overall, male and invasive rodents appeared less infected than female and native ones, respectively.

Cotton is one of the most important economic crops in the world, whereas insect attacks is a prime cause of its losses on yield and quality. Despite it is important, little is known about the mechanism of cotton response to insect. In this study, we simulated insect feeding by applying insect oral secretions (OS) to wounds, and combined transcriptome and metabolome analysis to comprehensively investigate how OS from two major pest species (Helicoverpa armigera and Spodoptera litura) affect cotton defense responses. Obvious differences were observed that 12,668 and 13,379 genes differently expressed respectively in cotton after being treated with different OS when compared with wounding along. Upon the addition of OS, JA-signaling pathway were rapidly and strongly induced, however SA-biosynthesis related gens were significantly down-regulated. By constructing the co-expression gene network, we identified a hub gene which encoding a leucine-rich repeat receptor kinase may play important role in recognition and signal transduction at early stage. We also found that OS from different insect species altered abundance of flavonoid related compound with different patterns. Interestingly, Gossypol which is a well-known anti-insect compound was kept a relative low content after OS application relative to wounding which implied the existence of the suppression effects of OS to cotton defense response. This study illustrated the transcriptional and metabolic changes of cotton in responding to OS from two chewing insect species, identified potential key gene during the interaction process and finds the evidence for OS’s inhibition effects on cotton defense response.

A supramolecular host-guest interaction and sensing between cationic pillar[5]arenes (CP5) and L-carnitine were developed by the competitive host-guest recognition for the first time. The fluorescence sensing platform was constructed by CP5 functionalized Au nanoparticles (PP5@Au-NPs) as receptor and probe (rhodamine 123, R123), which shown a high sensitivity and selectivity to L-carnitine detection. Due to the property of the negative charge and molecular size of L-carnitine, it can be highly captured by the CP5 via electrostatic interactions and hydrophobic interactions. The mechanism of host-guest between PP5 and L-carnitine was studied by ¹H NMR and molecular docking, which indicated more affinity binding force of PP5 with L-carnitine. Therefore, a selective and sensitive fluorescent method was developed. It has a linear response of 0.1–2.0 and 2.0–25.0 μM and a detection limit of 0.067 μM (S/N = 3) for L-carnitine. The fluorescent sensing platform was also used to detect L-carnitine in human serum and milk samples, which provided potential applications of detection drugs of abuse, and had path for guarding a serious food safety issues.

Factors affecting the host-virus interaction must be understood for the effective application of bacteriophages to combat bacterial pathogens. Two novel E. coli phages, the T1-like siphophage LL5 and the rV5-like myophage LL12, were subjected to forward genetic screens against the Keio collection, a library of single non-essential gene deletions in E.coli str. BW25113. These genome-wide screens and subsequent experiments identified eight genes required for efficient propagation of phage LL5 and six genes required for propagation of LL12. The majority of the genes identified were involved in production of the phage receptors. E. coli mutants deficient in heptose II and the phosphoryl substituent of heptose I of the inner core lipopolysaccharide (LPS) were unable to propagate phage LL5, as were mutants deficient in the outer membrane protein TolC. Mutants lacking glucose I of the LPS outer core failed to propagate LL12. Two cytoplasmic chaperones, PpiB and SecB, were found to be required for efficient propagation of phage LL5 but not LL12. This approach may be useful for identifying phage receptors and required host factors in other phages, which would provide valuable information for their potential use as therapeutics and for phage engineering.

Although the parasite Toxoplasma gondii is one of the most pervasive neurotropic pathogens in the world, the host-parasite interactions during CNS infection and consequences of neurological infection are just beginning to be unraveled. The chronic stages of infection have been considered dormant, although several studies have found correlations of infection with an array of host behavioral changes. These may facilitate parasite transmission and impact neurological diseases. During infection, in addition to the presence of the parasites within neurons, host-mediated neuroimmune and hormonal responses to infection are also present. T. gondii induces numerous changes to host neurons during infection and globally alters host neurological signaling pathways, as discussed in this review. Understanding the neurophysiological changes in the host brain is imperative to understanding the parasitic mechanisms and to delineate the effects of this single-celled parasite on health and its contribution to neurological disease.

Trichoderma has been widely studied for its potential as a biocontrol agent against plant pathogenic organisms. Trichoderma's biological control mechanisms include competition, modification of environmental conditions, antibiosis, induction of plant defensive mechanisms, and mycoparasitism. Trichoderma species are known to produce a variety of secondary metabolites that have antifungal activity. These metabolites include peptaibols, gliotoxin, and trichokonins. Trichoderma also produces chitinases and β-1,3-glucanases that can degrade the cell walls of fungal pathogens. In addition to direct antagonism against fungal pathogens, Trichoderma can also induce systemic or localised resistance in plants, which is achieved through the production of elicitors such as chitin oligosaccharides and β-glucans that activate plant defence responses. Trichoderma can also form mutualistic associations with plants. In these associations, Trichoderma colonises the roots of plants and promotes plant growth by increasing nutrient uptake and inducing systemic resistance. Using Trichoderma as a biocontrol agent has several advantages over conventional crop protection techniques based on applying synthetic pesticides.

The mortality rate of women during the gestation period or after delivery is very high worldwide. ToRCH pathogens [Toxoplasma gondii (T.gondii), Rubella Virus (RV), Cytomegalovirus (CMV), and Herpes Simplex Virus (HSV)] are transmitted vertically and are associated with mortality and complications both in the mother and the fetus or children. Therefore, this study is designed to investigate the ToRCH pathogen-induced histopathological changes in placental tissues and associated post-obstetric complications in Pakistani women. Women (N = 68) included in this study were divided into Group A (women with current abortion and bad obstetric history-BOH) and Group B (women with normal delivery and BOH). The venous blood collected was analyzed for ToRCH antibodies through ELISA. A small piece of placenta tissue taken after delivery or abortion was subjected to nucleic acid (NA) detection through PCR using ToRCH pathogen-specific primers. The placental tissue was analyzed for histopathological changes under a microscope. The data obtained were analyzed using percentages and the Chi square test. Overall ToRCH antibody positivity was 64.70% (44/68). Of these, IgM (Immunoglobulin M) was found in 17.65% (12/68), IgG (Immunoglobulin G) in 45.59% (31/68), and one case (1.47%) was seropositive for both IgM and IgG. The NA was detected in 66.18% (45/68) of the placental tissues of the study population. The higher prevalence of antibodies for T.gondii and RV (23.53% each) and NA for RV, CMV, and HSV (17.99% each) was observed in the study population. The ToRCH infection (antibodies and NA) with BOH complications was statistically found to be non-significant (p> 0.05). Overall discrepancies in ToRCH antibodies and NA positivity were found in 86.76% (59/68) of cases, especially for RV (26.47%). Chorionic villitis (CV) in placental tissues was observed in 20.59% (14/68), i.e., 13.23% of Group A and 7.35% of Group B. Of the total, four women with T.gondii, six with RV, and three each with CMV and HSV infection were found with CV. The most common BOH complications observed were recurrent spontaneous abortions (RSAs) (47.05%, 32/68), stillbirth (22.05%, 15/68), congenital abnormalities (14.70%, 10/68), etc. It was observed that RSAs were associated with CV (10.29%) in the study population. The BOH complication and CV were found to be statistically non-significant (p> 0.05). It is concluded that ToRCH pathogens are prevalent in the study population, and CV was the only histopathological change found and associated with BOH complications.

Colletotrichum lini is a flax fungal pathogen, comprising differently virulent strains. In this work, we sequenced the genomes of three C. lini strains of different virulence: high virulent #390-1, medium virulent #757, and low virulent #771. We obtained more than 100× genome coverage with Oxford Nanopore Technologies reads and more than 50× genome coverage with Illumina data. To construct high-quality genomes, several assembly strategies were tested. The final assemblies were obtained using the Canu – Racon ×2 – Medaka – Polca scheme and were 54.0-55.3 Mb in length, contained 26-32 contigs, had an N50 > 5 Mb and the BUSCO completeness > 96%. Comparative analysis of the constructed genomes showed high similarity between mitochondrial and nuclear genomes. However, a rearrangement event and the loss of a 0.9 Mb contig were revealed. The candidate effectors were predicted in sets of proteins received after genome annotation. The obtained genome sequences of C. lini strains extend the knowledge on the genetic diversity of Colletotrichum species and are the basis for establishing molecular mechanisms of pathogenicity of the flax pathogen and effective control of flax anthracnose.

The implementation of One Health/EcoHealth/Planetary Health approaches has been identified as key (i) to address the strong interconnections between risk for pandemics, climate change and biodiversity loss, and (ii) to develop and implement solutions to these interlinked crises. As a response to the multiple calls of scientists in that direction, we have put forward seven long term research questions regarding COVID-19 and emerging infectious diseases (EIDs) that are based on an effective integration of environmental, ecological, evolutionary, and social sciences to better anticipate and mitigate EIDs. Research needs cover the social-ecology of infectious disease agents, their evolution, the determinants of susceptibility of humans and animals to infections, and the human and ecological factors accelerating infectious disease emergence. For comprehensive investigation, they include the development of nature-based solutions to interlinked global planetary crises, addressing ethical and philosophical questions regarding the relationship of humans to nature and regarding transformative changes to safeguard the environment and human health. In support of this research, we propose the implementation of innovative multidisciplinary facilities embedded in social-ecosystems locally: the “ecological health observatories” and the “living laboratories”. This work has been carried out in the frame of the EC project HERA (www.HERAresearchEU.eu) that aims to set the priorities for an environment, climate and health research agenda in the EU by adopting a systemic approach in the face of global environmental change.

Microbiome research has gained considerable interest due to the emerging evidence of its impact on human and animal health. Similar to higher organisms, the gut-associated microbiota of mosquitoes affect host fitness and other phenotypes. It is now well established that microbes can alter pathogen transmission in mosquitoes, either positively or negatively, and avenues are being explored to exploit microbes for vector control. However, less attention has been paid to how microbiota affect phenotypes that impact vectorial capacity. Several mosquito and pathogen components, such as vector density, biting rate, survival, vector competence and pathogen extrinsic incubation period all influence pathogen transmission. Interestingly, the mosquito gut-associated microbes can impact each of these components, and therefore ultimately modulate vectorial capacity. Promisingly, this expands the options available to exploit microbes for vector control by also targeting parameters that affect vectorial capacity. However, there are still many knowledge gaps in the biology of the mosquito – microbe symbiosis that need to be addressed in order to understand these interactions more thoroughly and exploit them efficiently. Here, we review current evidence of the impacts of the microbiome on aspects of vectorial capacity highlighting opportunities for novel vector control strategies and areas where further studies are required.

The biotic and abiotic stresses are the main causes of the loss of agricultural crops productivity, their normal growth and development in the environment. It has been calculated that two-thirds of the major crops are frequently lost due to adverse environmental conditions. The productivity of crops under unfavorable environmental stresses is apparently the main challenge to the breeders and farmers where polyamines (PAs) play diverse roles in environmental stimuli. PAs (putrescine, spermidine, and spermine) are low molecular weight positively charge compounds have the active potential power to negative charge molecules (DNA, RNA, and proteins) is widely distributed in all living organisms. Evidence showed that PAs contribute a lot of different physiological and biological functions, such as cell growth and development, controlling the cell cycle, involve in gene expression, cell signaling, replication, transcription, translation, and membrane stabilization. Naturally occurring polyamines activity acuminated to their involvement with different biotic and abiotic stresses and contribute to the survival of the plant in the environment. Here, we have described the potential mechanisms, synthesis, and various roles of PAs during stresses tolerant and disease resistance.

This paper studies the Bondi-Metzner-Sachs group in homogeneous projective coordinates, because it is then possible to write all transformations of such a group in a manifestly linear way. The 2-sphere metric, Bondi-Metzner-Sachs metric, asymptotic Killing vectors, generators of supertranslations, as well as boosts and rotations of Minkowski spacetime, are all re-expressed in homogeneous projective coordinates. Last, the integral curves of vector fields which generate supertranslations are evaluated in detail. This work prepares the ground for more advanced applications of the differential geometry of asymptotically flat spacetimes in projective coordinates.

This study reports new records of eight species of Cicadellini (Hemiptera, Cicadellidae, Cicadellinae), all potential vectors of the bacterium Xylella fastidiosa Wells et al. 1987, which causes citrus variegated chlorosis. The sharpshooters were captured using a sweeping net in citrus orchards across seven municipalities in Amazonas State, Brazil. This research addresses the lack of information on sharpshooter occurrence in the Amazonas region, emphasizing the need for further investigations in this area.

Abstract This study delved into the application of various machine learning (ML) models for the classification of lung cancer levels. Through meticulous monitoring of parameters such as minimum child weight and learning rate, efforts were made to mitigate overfitting while optimizing model performance. The Deep Neural Network (DNN) emerged as a standout performer, showcasing robust performance across training, validation, and testing stages. Ensemble methods like voting and bagging also demonstrated promising results. However, Support Vector Machine (SVM) models with the Sigmoid kernel faced challenges in achieving satisfactory performance. Overall, the investigation sheds light on the efficacy of different ML models in lung cancer level classification and underscores the importance of parameter tuning to address overfitting concerns.

In this project the EEG – electroencephalogram - channel(s) will be characterized to diagnose PTSD – Post-traumatic stress disorder – cases. For this aim, we applied boosting methods including a combination of K-mean and Support Vector Machine (SVM) models to find the feature weights to detect the PTSD cases. We classified 32 channels of 12 subjects including 6 PTSD and 6 healthy controls using a 6-mean classifier. The linear SVM found the weights of distinguished channels within each subject for each cluster. It was found that the significant SVM weights of F4, F8, and Pz are smaller in PTSD than in healthy subjects. This new method can be used as a tool to better understand the interaction of EEG signals and diagnosis.

G4v is a four-vector theory of gravitation proposed by Mead (2015, 2023a,b) which reinterprets several major results commonly celebrated for the tensor-based approach of General Relativity (GR). Here, we show that G4v obeys the correspondence principle, an important test of any relativistic theory. We derive the non-relativistic Lagrangian and Energy expressions at the limit of low speeds and potentials, complete with the correct terms for potential energy (something traditional Special Relativity is incapable of achieving). G4v could represent a new interpretation of the gravitational field with essentially the same mathematics as electromagnetism (Mead 2023a). It is also possible to interpret G4v as a very interesting (and useful) approximation of the Einstein field equations (Mead 2023b).

Sarcopenia becomes more common with age, being most prevalent among elderly individuals. According to the EWGSOP, muscle mass is one of the criteria for the evaluation of sarcopenia. The main methods for evaluating muscle mass are CT, MRI, and DXA, but these methods are difficult to apply in the field due to equipment costs, radioactivity, and lack of portability. BIVA and PhA are alternative approaches for assessing somatic cell mass and volume and do not require predictive equations. These variables are clinically relevant parameters that indicate cell health, especially cell membrane integrity and cell function. This study in sarcopenic and nonsarcopenic elderly volunteers aimed to determine the BIVA distribution pattern among individual sarcopenia patients; to evaluate the relationship between PhA and muscle strength, muscle quality, and physical function; and to find any correlates of PhA. The sample comprised 134 free-living elderly individuals of both sexes aged 69–91 years. Anthropometric parameters, grip strength, DXA findings, BIA results, and physical performance (the 6-meter walk test) were measured. Impedance vector distributions were evaluated in sarcopenia patients and healthy elderly individuals using BIVA. According to the AWGS criteria, sarcopenia was diagnosed according to DXA findings, grip strength and physical performance test results. Group differences were evaluated using the t test, Mann‒Whitney U test, and Hotelling's T2 test. Correlation analysis was performed to identify variables significantly associated with PhA. Linear regression analysis was performed to determine whether PhA was associated with muscle strength, muscle quality and physical function. BIVA detected a significant difference between the sarcopenia and non-sarcopenia groups (both sexes) due to higher R/H values and lower phase angles in a few individuals, whereas Xc/Ht values did not differ between the two groups. The sarcopenia group had a significantly lower PhA than the non-sarcopenia group among both males (p<0.01) and females (p<0.05). PhA was significantly correlated with age, ASM, HGS, and muscle quality in both sexes and significantly correlated with ASM/Ht2 and physical performance in males. PhA was a significant indicator of muscle strength in both males (β = 2.6; p<0.01) and females (β = 3.4; p<0.01), a significant indicator of muscle quality in both males (β = 0.07; p<0.05) and females (β = 0.17; p<0.01), and a significant indicator of physical performance in males (β = 0.3; p<0.01). BIVA can detect changes in muscle mass in individuals with sarcopenia and is a practical method for the assessment of sarcopenia in the field. PhA is a good indicator of muscle strength, muscle quality and physical performance (in males). These methods can help diagnose sarcopenia in elderly individuals with reduced mobility.

The color and NIR spectrum are key to build an oil estimation model, thus it requires individual olives clustering before the Sohlext oil extraction method can be applied. The objective was to analyze an OC estimation model of individual olives, based on cluster of similar color and NIR spectrum in different combination of the first and/or the second season. This study was performed with Chilean Arbequina olives in 2016 and 2017. The descriptor of the cluster consisted of the 3 color channels of c1, c2, c3 color model plus 11 reflectance points between 1710 and 1735 nm of each olive, normalized with the Z-score index. Clusters of similar color and NIR spectrum were formed with the k-means++ algorithm, leaving a sufficient amount of olives to be able to perform the Sohlext analysis of OC, as reference value. The estimation models were based on the Support Vector Machine. The test was carried out with the Leave One-Out Cross Validation in different training-testing combinations. The best model predicted the OC with 6% and 13%deviation respect to the real value in one season by itself and when one season tested with another season, respectively. The use of clustering in estimation model is discussed.

The bacterial genus and species of Bacillus thuringiensis var israelensis (Bti), is entomotoxic, used in the biological control of mosquito vectors of human diseases, such as malaria and dengue. Following the studies carried out in Mexico and Guatemala with ovillantas, in which the presence of larvae of both species of Anopheles albimanus W and Aedes aegypti L were observed, and with the intention of continuing to develop an ecologically friendly mosquito control, Bti was added to the ovillantas, to improve and already efficient method on the elimination of both types of mosquitoes. The objectives of this work were: to analyze the effectiveness of two commercial formulations of Bti, serovar H-14 (Bactimos) wettable powder, 3,500 ITU, from Biochem prods., and Vectobac, 2,000 ITU wettable powder, (Abbot Lab.) on second and third instars larvae of A. albimanus and Ae. aegypti (Diptera Culicidae). The two formulations were effective against A. albimanus W(higher concentrations), while Ae. aegypti L was very susceptible to Bti, therefore it is proposed for the best control of these genus and vector species of malaria and dengue at adequate concentrations.

The study utilizes the energy-flux-vector method to analyze the heat transfer characteristics of natural convection in a wavy-wall porous square cavity with a partially-heated bottom surface. The effects of the modified Darcy number and modified Rayleigh number on the energy-flux-vector distribution and mean Nusselt number are examined. The results show that when a low modified Darcy number with any value of modified Rayleigh number is given, the recirculation regions are not formed in the energy-flux-vector distribution within the porous cavity. Therefore, a low mean Nusselt number is obtained. The recirculation regions do still not form and thus the mean Nusselt number has a low value when a low modified Darcy number with a high modified Rayleigh number is given. However, when the values of the modified Darcy number and modified Rayleigh number are high, the energy flux vectors generate recirculation regions and thus a high mean Nusselt number is obtained.

Machine learning (ML) methodologies have been looked upon recently as a potential candidate for mitigating nonlinearity issues in optical communications. In this paper, we experimentally demonstrate a 40-Gb/s 256-quadrature amplitude modulation (QAM) signal-based Radio over Fiber (RoF) system for 50 km of standard single mode fiber length which utilizes support vector machine (SVM) decision method to indicate an effective nonlinearity mitigation. The influence of different impairments in the system is evaluated that includes the influences of Mach-Zehnder Modulator nonlinearities, in-phase and quadrature phase skew of the modulator. By utilizing SVM, the results demonstrated in terms of bit error rate and eye linearity suggest that impairments are significantly reduced and licit input signal power span of 5dBs is enlarged to 15 dBs.

This paper is devoted to the study of reproducing kernels on 2-inner product Hilbert spaces. We focus on a new structure to produce reproducing kernel Hilbert and Banach spaces. According to multi-variable computing, this structures can be useful in electrocardiographs, machine learning and economy

With the rapid progress of genetic engineering and gene therapy, World Anti-Doping Agency has alerted to gene doping and prohibited its use in sports. However, there is no standard method available yet for detection of transgenes delivered by recombinant adenoviral (rAdV) vectors. Here we aimed to develop a detection method for transgenes delivered by rAdV vectors in a mouse model that mimics gene doping. rAdV vectors containing mCherry gene was delivered in mice through intravenous injection or local muscular injection. After five days, stool and whole blood samples were collected, and total DNA was extracted. As additional experiments, whole blood was also collected from mouse tail tip until 15 days from injection of the rAdv vector. Transgene fragments from different DNA samples were analyzed using semi-quantitative PCR (sqPCR), quantitative PCR (qPCR), and droplet digital PCR (ddPCR). In the results, transgene fragments could directly be detected from blood cell fraction-DNA, plasma-cell free DNA and stool-DNA by qPCR and ddPCR, depending on specimen type and injection methods. We observed that a combination of blood cell fraction-DNA and ddPCR was more sensitive than other combinations used in this model. These results could accelerate the development of detection methods for gene doping.

We propose a novel credit risk measurement model for Corporate Default Swap spreads, that combines vector autoregressive regression with correlation networks. We focus on the sovereign CDS spreads of a collection of countries, that can be regarded as idiosyncratic measures of credit risk. We model them by means of a vector autoregressive regression model, composed by a time dependent country specific component, and by a contemporaneous component that describes contagion effects among countries. To disentangle the two components, we employ correlation networks, derived from the correlation matrix between the reduced form residuals. The proposed model is applied to ten countries that are representative of the recent financial crisis: top borrowing/lending countries, and peripheral European countries. The empirical findings show that the proposed model is a good predictor of CDS spreads movements, and that the contemporaneous component decreases prediction errors with respect to a simpler autoregressive model. From an applied viewpoint, core countries appear to import risk, as contagion increases their CDS spread, whereas peripheral countries appear as exporters of risk. Greece is an unfortunate exception, as its spreads seem to increase for both idiosyncratic factors and contagion effects.

In this paper, we present a method for detecting and quantifying pathogens in water samples. The method proposes a portable dark field imaging and analysis system for quantifying E. coli concentrations in water after being labeled with magnetic particles. The system utilizes the tracking of moving micro/nano objects close to or below the optical resolution limit confined in small sample volumes (~ 10 µl). In particular, the system analyzes the effect of volumetric changes due to bacteria conjugation to magnetic microparticles (MP) on their Brownian motion while being suspended in liquid buffer solution. The method allows for a simple inexpensive implementation and the possibility to be used as point-of-need testing system. Indeed, a work-ing prototype is demonstrated with the capacity of quantifying E. coli colony forming units (CFU) at a range of 1x10³ - 6x10³ CFU/mL.

The holistic approach of One Health, which sees human, animal, plant, and environmental health as a unit, rather than discrete parts, requires not only interdisciplinary cooperation, but standardized methods for communicating and archiving data, enabling participants to easily share what they have learned and allow others to build upon their findings.Ongoing work by NCBI and the GenomeTrakr project illustrates how open data platforms can help meet the needs of federal and state regulators, public health laboratories, departments of agriculture, and universities. Here we describe how microbial pathogen surveillance can be transformed by having an open access database along with Best Practices for contributors to follow. First, we describe the open pathogen surveillance framework, hosted on the NCBI platform. We cover the current community standards for WGS quality, provide an SOP for assessing your own sequence quality and recommend QC thresholds for all submitters to follow. We then provide an overview of NCBI data submission along with step by step details. And finally, we provide curation guidance and an SOP for keeping your public data current within the database. These Best Practices can be models for other open data projects, thereby advancing the One Health goals of Findable, Accessible, Interoperable and Re-usable (FAIR) data.

Juvenile Polyposis Syndrome (JPS) is a rare autosomal dominant disorder characterized by multiple juvenile polyps in the gastrointestinal tract, often associated with mutations in genes such as Smad4 and BMPR1A. This study explores the impact of Smad4 knockout on the development of intestinal polyps using Collaborative Cross (CC) mice, a genetically diverse model. Our results reveal a significant increase in intestinal polyps in Smad4 knockout mice across the entire population, emphasizing the broad influence of Smad4 on polyposis. Sex-specific analyses demonstrate higher polyp counts in knockout males and females compared to their WT counterparts, with distinct correlation patterns. Line-specific effects highlight the nuanced response to Smad4 knockout, underscoring the importance of genetic variability. Multimorbidity heat maps offer insights into complex relationships between polyp counts, locations, and sizes. Heritability analysis reveals a significant genetic basis for polyp counts and sizes, while machine learning models, including k-Nearest Neighbours and Linear Regression, identify key predictors, enhancing our understanding of juvenile polyposis genetics. Overall, this study provides a comprehensive understanding of the intricate genetic interplay in the context of Smad4 knockout, offering valuable insights into potential therapeutic targets for juvenile polyposis and related diseases.

Acute and chronic graft versus host disease (a/cGVHD) are major complications of allogeneic stem cell transplantation and a frequent cause of non relapse-mortality. The treatment of a/cGVHD consists of steroid administration at full dose. In the case of aGVHD, around 60 % of patients with grade III/IV fails to respond (steroid-resistant, SR), requiring a second line therapy. Extracorporeal photopheresis (ECP) represents a good option for second line treatment, leading to multiorgan response in several patients. Here, we have evaluated the performances of a cytofluorimetric quality control of the first ECP procedure in 29 patients with severe SR aGVHD who underwent ECP. The quality control represents a check control of in vitro cell apoptosis/death induction in collected and irradiated CD3+ cells by ECP. Our analysis shows that in more than 70 % quality controls a relevant apoptotosis/death of CD3+ cells was observed after cell irradiation, as compared to non-irradiated controls. Albeit observed in a small patients’ series, the occurrence of relevant in vitro effect after ECP relates to less procedures and/or to a better survival on ECP. Age, disease, gender, aGVHD grade and time from transplant to the first ECP had not impact on ECP efficacy in this patients’ series.

Epitranscriptomic RNA modifications play a crucial role in the posttranscriptional regulation of gene expression. N6-methyladenosine (m6A) is the most prevalent internal modification of eukaryotic RNA and plays a pivotal role in RNA fate. RNA m6A modification is regulated by a group of cellular proteins, methyltransferases (writers) and demethylases (erasers), which add and remove the methyl group from adenosine, respectively. m6A modification is recognized by a group of cellular RNA-binding proteins (readers) that specifically bind to m6A-modified RNA, mediating effects on RNA stability, splicing, transport, and translation. The functional significance of m6A modification of viral and cellular RNA is an active area of virology research. In this review, we summarize and analyze current literature on m6A modification of HIV-1 RNA, the multifaceted functions of m6A in regulating HIV-1 replication, and the role of viral RNA m6A modification in evading the innate immune responses to infection. Furthermore, we briefly discuss future directions and therapeutic implications of mechanistic studies of HIV-1 epitranscriptomic modifications.

Human pulmonary paragonimiasis, an emerging concern in North East India, frequently masquerades as pulmonary tuberculosis due to clinical and radiological similarities, leading to diagnostic challenges. This research was aimed to harness the immunoblotting technique to discern immunodiagnostic protein antigens from both adult worm and excretory-secretory (ES) extracts of the prevalent Paragonimus westermani type 1 in Arunachal Pradesh, North East India. We studied the time kinetics of immunoreactive patterns in relation to the duration of infection in rodent models. Immunoblot analyses were also conducted using sera from ELISA positive patients confirmed with paragonimiasis, facilitating the selection of antigenic extracts with diagnostic potential. Further, ES proteins antigens were subjected to 2D- immunoblot analysis and immunoreactive protein spots identified by MALDI-TOF MS. Immunoreactivity patterns of ES antigens with sera of paragonimiasis positive patients were detailed, and specific immunoreactive protein antigens were pinpointed using peptide mass fingerprinting (MALDI-TOF). This work underscores the enhanced diagnostic accuracy when combining ELISA with immunoblotting for pulmonary paragonimiasis in regions like North East India, marked by co-existing helminth infections.

The objective of the present study is to isolate phages targeting multidrug resistant (MDR), extended spectrum beta lactamase (ESBL) positive clinical isolate of E. coli ( U1007), sequence and analyze the phage genome and use machine learning tools to predict host cell surface receptor and finally evaluate the efficiency of monophage and phage cocktail in vitro and in vivo in a zebrafish model. Phage specific for E. coli U1007 was isolated from Ganges River (designated as U1G), Cuoom River (designated as CR) and Hospital waste water (designated as M phage). The obtained phages were triple purified and enriched. U1G phages had a greater burst size of 124 PFU/cell and a latent time of 25 min.M phage had a burst size of 150 PFU/cell with a shortlatent time of 20min. Similarly CR phage has a short latent 20 min and a burst size of 115 PFU/cell. Based on capsid architecture, U1G phage resembles Podoviridae, CR phage is structurally similar to Myoviridae and M phage has morphology that resembles Siphoviridae. Genome sequencing and analysis revealed that the size of the U1G phage genome is 73275 bp Whereas that of CR phage and M phage are 45236 bp and 45294 bp, respectively. All three genomes were marked by the absence of genes encoding tRNA sequence, antibiotic resistant or virulent genes. A machine learning (ML) based multi-class classification model using algorithms such as Random Forest, Logistic Regression, and Decision Tree were employed to predict the host receptor targeted by all 3 phages and the best performing algorithm Random Forest predicted LPS O antigen , LamB or OmpC for U1G FhuA, OmpC for CR phage and FhuA, LamB, TonB or OmpF for the M phage as the host receptor targeted by the receptor binding protein (RBP) of the phages. In vitro time kill assay showed that treatment with monophages alone and along with colistin resulted in regrowth whereas phage combinations significantly reduced the regrowth and by 24h the phage cocktail along with colistin produced a significant 3 log declinein cell counts relative to the untreated control. In vivo intramuscular infection study in zebrafish showed that phages were non toxic and a cocktail of dual (U1G +M) phage along with colsitin resulted in a significant 3.5 log decline in cell counts whereas triple phage combination along with colistin resulted in 3 log decline in cell counts probably due to host receptor competition. Our study highlights the potential of phage cocktail therapy in mitigating MDR clinical isolate of E. coli in vitro and in vivo.

Hosting FIFA World Cup obviously produce immense socio-economic impacts to a nation. Proximal non-host city perception to mega event was frequently explored, while distal non-host city perception has less investigated. This study assessed the socio-economic impacts of FIFA World Cup Qatar 2022 in Chon Buri Sports City residents. Participants were 422 Chon Buri Sports City residents from eleven districts. Perception on socio-economic impacts of hosting FWC Qatar 2022 was measured from the translated Scale of Perceived Social Impacts. Extracted seven dimensions by confirmatory factor analysis is consistent with empirical data. Positive impact dimensions are Community Development, Community Pride, Economic Benefits. Negative impact dimensions are Traffic Problems, Security Risks, Economic Costs, and Environmental Concerns. Chon Buri Sports City residents perceived fewer negative impacts than other non-host city residents. Positive impacts of hosting FWC Qatar 2022 has more influenced on Chon Buri Sports City residents’ perception than negative impacts. These findings advantage for sport stakeholders to deeper understand the impacts of mega event hosting.

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.

The different cell subsets of the immune system express vitamin D receptor (VDR). Through VDR, vitamin D exerts different functions which influences on immune responses, as previously shown in different preclinical models. Based on this background, retrospective studies have explored the impact of vitamin D levels on the outcome of patients undergoing allogeneic hematopoietic stem cell transplantation, showing that vitamin D deficiency is related to an increased risk of complications, especially graft-versus-host disease. These results have been confirmed in a prospective cohorts trial, although further studies are required to confirm this data. In addition, the role of vitamin D on the treatment of hematologic malignancies has also been explored. Considering this dual effect both on the immune system as well as on tumor cells in patients with hematologic malignancies, vitamin D might be useful in this setting both to decrease graft-versus-host disease and relapse rates.

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 paper, we have numerically investigated a metasurface based perfect absorber design established on the impedance matching phenomena. The paper comprises of two parts. In the first part, the device performance of the perfect absorber is studied which is composed of a silicon Nano-cylindrical meta-atoms periodically arranged on the thin gold layer. The device design is unique which works for both x-oriented and y-oriented polarized light, besides independent of the angle of incidence. In the second part of the paper, CO2 gas sensing application is explored by depositing a thin layer of functional host material polyhexamethylene biguanide polymer on the metasurface. The refractive index of the host material decreases due to the absorption of the CO2 gas. As a result, the resonance wavelength of the perfect absorber performs a prominent blueshift. With the help of the proposed sensor design based on metasurface, the CO2 gas concentration range of 0-524 ppm is detected. The maximum sensitivity of ~17.3 pm/ppm is acquired for the gas concentration of 434 ppm. The study presented in this work explores the opportunity of utilizing metasurface perfect absorber for gas sensing applications by employing the functional host materials.

Exploring the biological significance of mutations in SARS-CoV-2 coronavirus, causing the COVID–19 pandemic, has recently become an area of paramount interest for many researchers, who are pouring their tremendous efforts, in cracking the COVID–19 pandemic code. One of many such mutations that have occurred in the viral genome is V483A mutation, which is a part of the receptor-binding motif (RBM), present in the S1 domain of the spike protein. V483A mutant virus is becoming popular in North America with 36 cases so far, due to its frequent occurrences in recent days. In this review, we have assembled all information, currently available on V483A mutation, and have made a critical analysis based on the perspectives of many researchers all around the world. Comparison is made between the wild type and the V483A mutants to analyze certain factors like the type of interaction between the virus and host cell interface, binding affinity, stability, partition energy, hydrophobicity, occurrence rate, and transmissibility. Insilico dynamic analysis shows minimal alteration in the receptor-binding domain (RBD) of V483A mutant protein in free-state and no significant change of mutant tertiary structure of RBM upon binding to the ACE2 receptor. Comprehensive details about infectivity and evasion of the immune system by the virus are discussed. This information can in turn be of monumental importance in the field of vaccine and drug development because the mutants are becoming resistant to the vaccines and monoclonal antibodies.

Coronavirus Disease 2019 (COVID-19), caused by SARS-CoV-2 (Severe Acute Respiratory Syndrome - Coronavirus-2) of the family Coronaviridae, appeared in Wuhan, Hubei province, China being its epicenter in December 2019. This disease was declared as posing Public Health International Emergency by World Health Organization on January 30, 2020, attained the status of a very high-risk category on February 29, and now having a pandemic status (March 11, 2020). COVID-19 has presently spread to more than 195 countries/territories while killing nearly 19,600 humans out of cumulative confirmed cases accounting to more than 430,000 within a short period of just a few weeks. The majority of deaths have been reported in Italy and China. Researchers worldwide are pacing with high efforts to counter the spread of this virus and to design effective vaccines and therapeutics/drugs. Few of the studies have shown the potential of animal-human interface and zoonotic links in the origin of SARS-CoV-2. Exploring the possible zoonosis and revealing the factors responsible for its initial transmission from animals to humans will pave ways to design and implement effective preventive and control strategies to counter COVID-19. The present review presents an overview of COVID-19 and the causative virus SARS-CoV-2, with particular emphasis on the role of animals and their jumping the cross-species barriers, experiences learned from SARS- and MERS-CoVs, zoonotic links, and spillover events, transmission to humans and rapid spread., highlighting in very brief the preventive and control measures along with a few of the recent research developments to counter this pandemic virus/disease.

Despite the implementation of control strategies, the invasive parasitic mite Varroa destructor remains one of the principal causes of honey bee (Apis mellifera) colony losses in numerous countries. For this reason, the parasite represents a serious threat to beekeeping and to agro-ecosystems that benefit from the pollination services provided by honey bees. Numerous selection programmes have been initiated over the last three decades with the aim of promoting the establishment of balance in the host–parasite relationship and, thus, helping European honey bees to survive in the presence of the parasite without the need for acaricide treatments. Such programmes have focused on either selective breeding for putative resistance traits or natural selection. To date, no clear overview of these attempts has been available, which has prevented building on past successes or failures and, therefore, hindered the development of a sustainable strategy for solving the V. destructor problem. In the present study, we review past and current selection strategies, report on their outcomes and discuss their limitations. Based on this state-of-the-art knowledge, we propose a strategy for increasing response to selection and colony survival against V. destructor infestations. Developing in-depth knowledge regarding the selected traits, optimising selection programmes and communicating their outcomes are all crucial to our efforts to establish a balanced relationship between the invasive parasite and its new host.

Abstract: With the availability of an increasing number of 3D structures of bacteriophage components, combined with powerful in silico predictive tools, it has become possible to decipher the structural assembly and functionality of phage adhesion devices. In the current study, we examined 113 members of the 936 group of lactococcal siphophages, and identified a number of Carbohydrate Binding Modules (CBMs) in the neck passage structure and major tail protein, on top of evolved Dit proteins as recently reported by us. The binding ability of such CBM-containing proteins was assessed through the construction of green fluorescent protein fusion proteins and subsequent binding assays. Two CBMs, one from the phage tail and another from the neck, demonstrated definite binding to their phage-specific host. Bioinformatic analysis of the structural proteins of 936 phages reveals that they incorporate binding modules which exhibit structural homology to those found in other lactococcal phage groups and beyond, indicating that phages utilize common structural “bricks” to enhance host binding capabilities. The omnipresence of CBMs in Siphophages supports their beneficial role in the infection process, as they can be combined in various ways to form appendages with different shapes and functionalities, ensuring their success in host detection in their respective ecological niches.

Prasinoviruses are large dsDNA viruses commonly found in aquatic systems worldwide, where they can infect and lyse unicellular prasinophyte algae such as Ostreococcus. Host susceptibility is virus strain-specific, but resistance of susceptible Ostreococcus tauri strains to a virulent virus arises frequently. In clonal resistant lines that re-grow, viruses are usually present for many generations, and genes clustered on chromosome 19 show physical rearrangements and differential expression. Here, we investigated changes occurring during the first two weeks after inoculation of viruses. By serial dilutions of cultures at the time of inoculation, we estimated the frequency of resistant cells arising in virus-challenged O. tauri cultures to be 10⁻³–10⁻⁴ of the inoculated population. Re-growing resistant cells were detectable by flow cytometry 3 days post-inoculation (dpi), visible re-greening of cultures occurred by 6 dpi, and karyotypic changes were visually detectable at 8 dpi. Resistant cell lines showed a modified spectrum of host-virus specificities and much lower levels of OtV5 adsorption.

One of the most serious concerns about mega event-related changes to small cities is how to effectively utilize newly developed public attractions after the Olympic Games. Making connections with existing local amenities and forming attraction networks can be effective strategies for continuing a city’s revitalization. However, despite the expected benefits, attraction network research shows that these benefits often fail to materialize. With the case of Gangneung, a 2018 winter Olympic hosting city, this study investigated visitation patterns to nineteen selected attractions using network analysis. The results indicate that the most influential nodes are located on the northern coast, the eastern coast, and in the south downtown area, those nodes being the central locations where the strongest of connections are made. New attractions such as the Olympic Park and Walwha Linear Park were rather isolated. While seasonal and periodic variations, visitors’ residences, and destination choice attitudes had a significant effect on visitation patterns, the attraction networks, modes of transportation, proximity to region, and type similarity were not significant factors in the forming of visitation patterns. The results make a methodological contribution to tourist behavior and network research. In addition, beyond individual attraction development, the results provide practical implications in regard to networking and cooperation between multiple attractions using temporal and spatial strategies such as management/investment prioritizing, travel route development, and program scheduling.

The pennate diatom Phaeodactylum tricornutum is a model organism able to synthesize industrially-relevant molecules. Commercial-scale cultivation currently requires large monocultures, prone to bio-contamination. However, little is known about the identity of the invading organisms. To reduce the complexity of natural systems, we systematically investigated the microbiome of non-axenic P. tricornutum cultures from a culture collection in reproducible experiments. The results revealed a dynamic bacterial community that developed differently in “complete” and “minimal” media conditions. In complete media, we observed an accelerated “culture crash”, indicating a more stable culture in minimal media. The identification of only four bacterial families as major players within the microbiome suggests specific roles depending on environmental conditions. From our results we propose a network of putative interactions between P. tricornutum and these main bacterial factions. We demonstrate that, even with rather sparse data, a mathematical model can be reconstructed that qualitatively reproduces the observed population dynamics, thus indicating that our hypotheses regarding the molecular interactions are in agreement with experimental data. Whereas the model in its current state is only qualitative, we argue that it serves as a starting point to develop quantitative and predictive mathematical models, which may guide experimental efforts to synthetically construct and monitor stable communities required for robust upscaling strategies.

This paper presents an explicit method for constructing tangential and anisotropic bases in quadratic spaces. We will also provide three theorems that allow us to explicitly calculate vectors that are orthogonal or tangent to given vectors or that provide necessary and sufficient conditions for the existence of such vectors. A classical theorem on quadratic space states that every finite-dimensional quadratic space has an orthogonal basis. A result that seems to be unanswered is under what conditions a finite-dimensional quadratic space has a basis consisting of isotropic vectors. A second problem is whether or not every finite-dimensional quadratic space has a basis consisting of mutually tangent vectors, where two vectors v,w are tangent if (u·v)2=(u·u)(v·v). In this paper, we attack these two problems.

We investigate regular damped oscillatory structures appearing in the "effective" form factor of various hadrons. The behavior of this form factor can be extracted from the experimental information on total cross sections, the processes $\sigma_{tot}(e^+e^- \to h \bar h)$, $h=\pi^{\pm}, K^{\pm}, K^0, p, n $ are examined. The apparent oscillations have been observed for the first time for the proton and we show, taking also other hadrons into the consideration, that they are an arbitrary artifact resulting from a very simplistic theoretical description based on an elementary three-parametric model. If the data are described by a more appropriate and well physically funded U\&A model, then the oscillations disappear. In addition, if the simple model is used to describe the data, one observes that the oscillations are opposite for particles which form an isospin dublet. We show, by using the U\&A model, that this feature is explained by the transformation properties of the corresponding states in the isotopic space.

In this paper, a new full-Newton step feasible interior point method for convex quadratic programming is presented and analyzed. The idea behind this method is to replace the complementarity condition with a non-negative variable weight vector and use the algebraic equivalent transformation for the obtained equation. Under the selection of appropriate parameters, the quadratic rate of convergence of the new algorithm is established. In addition, the iteration complexity of the algorithm is obtained. Finally, some numerical results are presented to demonstrate the practical performance of the proposed algorithm.

Lipid nanoparticles (LNPs) have attracted extensive attention in tumor immunotherapy in recent years. The strategy of targeting immune cells in cancer therapy has become a research area of great interest. mRNA vaccines are a potential choice for tumor immunotherapy due to their ability to directly encode antigen proteins and stimulate a strong immune response. However, the mode of delivery and lack of stability of mRNA are key issues limiting its application. LNPs are an excellent mRNA delivery vector, and their structural stability and biocompatibility make them an effective means to deliver mRNA to specific targets. This study summarizes the research progress in LNP delivery vector-assisted targeted controlled release mRNA vaccines in tumor immunity. The role of LNPs in improving mRNA stability, immunogenicity and targeting is discussed. In addition, combined with the cutting-edge research results, the potential mechanisms and application prospects of LNP-mRNA vaccines in tumor immunotherapy were further analyzed. This review aims to systematically summarize the latest research progress in LNP delivery carrier-assisted targeted controlled-release mRNA vaccines in tumor immunity to provide new ideas and strategies for tumor immunotherapy and provide more effective treatment plans for patients.

Every subset S of a Cartesian spaces Rd, endowed with differen- tial structure C∞(S) generated by restrictions to S of functions in C∞(Rd), has a canonical partition M(S) by manifolds, which are or- bits of the family X(S) of all derivations of C∞(S) that generate local one-parameter groups of local diffeomorphisms of S. This partition satisfies the frontier condition, Whitney’s conditions A and B. If M(S) is locally finite, then it satisfies all definitions of stratification of S. This result extends to Hausdorff locally Euclidean differential spaces.

This article explores the relationship between convex functions defined on integers ($\mathbb{Z}$) and their extension to real numbers ($\mathbb{R}$). We introduce key definitions and investigate the hypothesis that there exists a unique convex curve within this family of functions, leading to a proof by contradiction. Our findings highlight the preservation of convexity as functions transition from integers to real numbers.

Duchenne muscular dystrophy (DMD) is a yet incurable rare genetic disease that affects the skeletal and cardiac muscles, leading to progressive muscle wasting and premature death. DMD is caused by the lack of dystrophin, a muscle protein essential for the biochemical support and integrity of muscle fibers. Gene replacement strategies for Duchenne muscular dystrophy (DMD) employing the adeno-associated virus (AAV) face the challenge imposed by the limited packaging capacity of AAV, only allowing the accommodation of a short version of dystrophin (µDys) that is still far removed from correcting human disease. The need to develop strategies leading to the expression of a best performing dystrophin variant led to only few studies reporting on the use of dual vectors, but none reported on a method to assess in vivo transgene reconstitution efficiency, the degree of which directly affects the use of safe AAV dosing. We report here on the generation of a dual AAV vector approach for the expression of a larger dystrophin version (quasidystrophin) based on homologous recombination, and the development of a methodology employing a strategic droplet digital PCR design, to determine the recombination efficiency as well as the occurrence of unwanted concatemerization events or aberrant expression from the single vectors. We demonstrated that, upon systemic delivery in the dystrophic DBA2mdx mice, our dual AAV approach led to high transgene reconstitution efficiency and negligible ITR-dependent concatemerization, with consequent remarkable protein restoration in muscles and improvement of muscle pathology. This evidence supports the suitability of our system for gene therapy application and the potential of this methodology to assess and improve the feasibility for therapeutic translation of multiple vector approaches

We introduce new metric structures on a smooth manifold (called “weak" structures) that generalize the almost contact, Sasakian, cosymplectic, etc. metric structures (φ,ξ,η,g) and allow us to take a fresh look at the classical theory and find new applications. This assertion is illustrated by generalizing several well-known results. It is proved that any Sasakian structure is rigid, i.e., our weak Sasakian structure is homothetically equivalent to a Sasakian structure. It is shown that a weak almost contact structure with parallel tensor φ is a weak cosymplectic structure and an example of such a structure on the product of manifolds is given. Conditions are found under which a vector field is a weak contact vector field.

Water pollution is a common problem for dams situated within an urban or agricultural catchment. This can negatively affect the hydro ecosystem, drinking, recreational and other uses of water. In this study, the drinking water quality class of the Roodeplaat Dam, South Africa which faces pollution problems was modeled using machine learning algorisms in Python Jupyter Notebook 6.0.0. Eleven monthly water quality parameters recorded at five sampling stations from January 1981 to September 2017 were used for training and testing the model. Five machine learning classifiers: Gaussian Naïve Bayes (GNB), K-nearest neighbors (KNN), Decision Tree (DT), Support Vector Machines (SVM), and Linear Regression (LR) at a test size of 20%, 25%, 30%, and 40% were used to classify water into five classes (Excellent to Very bad). It was investigated that the dam water has only three classes good, medium, and bad. The prediction accuracies of machine learning algorithms from the highest to the lowest were 96.39%, 96.17%, 92.25%, 90.20, and 54.19% for KNN, DT, SVM, GNB, and LR, respectively. Therefore, KNN at a test size of 30% was recommended to classify the water quality of Roodeplat Dam accurately. Hence, machine learning algorithms can be used to identify the class of water quality before the water is treated and distributed for drinking use.

This study aimed to assess the physical characteristics of elite international soccer referees, compare them with other referee populations in the literature, and establish reference tolerance ellipses for the bioelectrical impedance vector analysis (BIVA) point graph. Forty-one elite international soccer referees (age 38.8 ± 3.6 years) participated in the study. the participants underwent body composition assessments, including dual-energy X-ray absorptiometry, BIVA, and somatotype. The Somatotype Attitudinal Distance (SAD), the two-sample Hotelling’s T2 test, and the Mahalanobis test were used to determine somatotype and bioelectrical vector differences with the literature. The average somatotype of the referees was a balanced mesomorph (2.8, 6.5, 2.8). Elite international referees significantly differed from other samples in the literature (SAD = 2.1, 2.6, 2.9 with respect to Zimbabwean, Brazilian, and South African referees, respectively). The bioelectrical vector was significantly different from the general population (T2  76.6; F = 38.8; D = 1.44; P < 0.001) and athletes (T2  25.3; F = 12.6; D = 0.8; P < 0.001). Somatotype values and tolerance ellipses from this study may be useful as a reference for developing training programs and improving the selection process of referees in soccer.

Disease control programs need to identify breeding sites of mosquitoes which transmit malaria and other diseases to target interventions and identify environmental risk factors. Increasing availability of very high resolution drone data provides new opportunities to find and characterize these vector breeding sites. Within this study, we identified land cover types associated with malaria vector breeding sites in West Africa. Drone images from two malaria endemic regions in Burkina Faso and Côte d’Ivoire were assembled and labeled using open-source tools. We developed and applied a workflow using region of interest-based and deep learning methods to classify these habitat types from very high resolution natural color imagery. Analysis methods achieved a dice coefficient ranging between 0.68 and 0.88 for different vector habitat types; however, this classifier consistently identified the presence of specific habitat types of interest. This establishes a framework for developing deep learning approaches to identify vector breeding sites and highlights the need to evaluate how results will be used by control programs.

Mosquitoes are widespread arthropods that serve as vectors for a broad spectrum of viruses, many of which pose a substantial threat to humans. Conversely, some viruses may seemingly present with beneficial implications for the health of man whilst impinging on other domains of life, such as the fungi-infecting mycoviruses. This study is only the second one so far to describe the exceptionally scarcely identified Xanthi chryso-like virus (XCLV), member of the mycopathogenic Chrysoviridae family, in a new geographical area and a novel potential arthropod vector, the Culex pipiens mosquito. Interestingly, the XCLV was initially fortuitously detected by West Nile virus-specific primers directed at a conserved part of the NS5 gene, possibly indicative of a genetic resemblance and shared ancestry reflected in the NS5 evolutionary heritage. Detection and characterization of the virus and insect alike was done via PCR and Sanger sequencing. This investigation draws attention to our knowledge of viral pervasiveness – be it topographical or vectorial – and how humble it truly is. Additionally, we would propose that more attention be given to arthropod-borne viral pathogens that might prove advantageous to human health.

Dengue virus infections are a serious public health problem worldwide. Aedes aegypti is the primary vector of dengue in Cuba. Since there is no vaccine or specific treatment, the control efforts are directed to reduce mosquito populations. The indiscriminate use of pesticides can lead to increase insecticide resistance as well as adverse effects on human health. The sterile insect technique is a species-specific and environmental friendly method of insect control based on the release of large numbers of sterile males. The success of this technique in sustainable control of agricultural pests has encouraged its evaluation for mosquito control. Here, we describe an open field trial to evaluate the effect of the release of irradiated males on a wild population of Aedes aegypti. The case-control study was performed in a suburb of Havana, and compared the mosquito population before and after the intervention, in both control and treated areas. The wild population was monitored by an ovitrap network, recording frequency and density of eggs as well as their hatch rate. A significant induced sterility was observed in the field population, compared to the control. The ovitrap index and the mean eggs/ trap declined dramatically after an expected lag period of twelve and five weeks, respectively. For the last three weeks, no egg was collected in the treated area, evidencing a significant suppression of the wild population. We conclude that the sterile males released competed successfully, and induced enough sterility to suppress the local Aedes aegypti population.

Aedes scapularis is a neotropical mosquito known to transmit pathogens of medical and veterinary importance. Its recent establishment in southeastern Florida has potential public health implications. We used an ecological niche modeling approach to predict the abiotic environmental suitability for Ae. scapularis across much of the Americas and Caribbean Islands. Georeferenced occurrence data obtained from the Global Biodiversity Inventory Facility and recent collection records of Ae. scapularis from southern Florida served as input for model calibration. Environmental layers included bioclimatic variables provided in 2000 to 2010 average Modern Era Retrospective-analysis for Research and Applications climatic (MERRAclim) data. Models were run in the software program Maxent. Isothermality values found often in costal environments contributed strongest to model performance. Model projections suggested areas predicted suitable for Ae. scapularis across portions of the Amazon Basin, the Yucatán Peninsula, the Florida Peninsula, and multiple Caribbean Islands. Additionally, model predictions suggested connectivity of highly suitable or relatively suitable environments spanning the United States Gulf Coast, which may facilitate geographic expansion of this species. At least sixteen Florida counties were predicted highly suitable for Ae. scapularis, suggesting vigilance is needed by vector control and public health agencies to recognize further spread of this vector.

In the present work, a novel conductive liquids method of study has been proposed. It is based on the phenomenon of radiofrequency anisotropy of electrolyte solution discovered by us. It arises in response to mechanical or acoustic excitation of the solution. We have observed the phenomenon during the development of an RF polarimetric contactless cardiograph. The electric field vector of the transmitted 433.82 MHz signal rotated after its transition through the pericardial region. That rotation depends on the change of blood acceleration when passing through the chambers of the heart and large vessels. It has also been revealed that rotation occurs after RF wave passage through the physiological saline (0.9% NaCl) subjected to any mechanical excitation inside it like a jet appearing or soundwave passing. No significant difference was detected experimentally between NaCl and KCl solutions behavior. It means that the mechanism of hydrodynamic separation of ions is apparently not suitable to explain the phenomenon. The response we have registered resembles the magnetization process of spin glasses. From the nature of the observed response, we have concluded that a fundamentally new physical effect is discovered. It may provide wide opportunities for remote measurement of the electrolyte solution parameters with polarized radio-frequency signals.

An analysis is presented of the possible existence of a second anomalous dipole moment of Dirac’s particle next to the angular one. It includes a discussion why, in spite of his own derivation, Dirac has doubted about its relevancy. It is shown why since then it has been overlooked and why it has vanished from leading textbooks. A critical survey is given on the reasons of its reject, including the failure of attempts to measure and the perceived violations of time reversal symmetry and chargeparity symmetry. It is emphasized that the anomalous electric dipole moment of the pointlike electron (AEDM) is fundamentally different from the quantum field type electric dipole moment of an electron (eEDM) as defined in the standard model of particle physics and that its measurement requires different instrumentation. A proposal has been described how to prove or disprove its existence by experiment. Moreover, by reference from literature, the possible impact is discussed in the nuclear domain and in the gravitational domain.

The aim of this paper is to obtain Karush-Kuhn-Tucker optimality conditions for weakly efficient solutions to vector equilibrium problems with the addition of constraints in the novel context of Hadamard manifolds as opposed to the classical examples of Banach, normed or Hausdorff spaces. More specifically, classical necessary and sufficient conditions for weakly efficient solutions to the constrained vector optimization problem are presented. As well as some examples. The results presented in this paper generalize results obtained by Gong (2008) and Wei and Gong (2010) and Feng and Qiu (2014) from Hausdorff topological vector spaces, real normed spaces and real Banach spaces to Hadamard manifolds, respectively.

It is shown that a Mueller quaternion can be formulated as a quaternion with matrix coefficients, and this Mueller quaternion transforms the Stokes quaternion for depolarizing process as well as for nondepolarizing process. Mueller quaternion keeps track of the phase acquired by the Stokes quaternion and, in general, quaternion states of optical media comprises all properties of Jones, Mueller-Jones and Mueller matrices.

ARBTools is a Python library containing a Lekien-Marsden type tricubic spline method for interpolating three-dimensional scalar or vector fields presented as a set of discrete data points on a regular cuboid grid. ARBTools was developed for simulations of magnetic molecular traps, in which the magnitude, gradient and vector components of a magnetic field are required. Numerical integrators for solving particle trajectories are included, but the core interpolator can be used for any scalar or vector field. The only additional system requirements are NumPy.

In this present study, we conducted untargeted metabolic profiling using Gas Chromatography-Mass Spectrometry (GC-MS) analysis of ascidian Didemnum bistratum to assess the chemical constituents by searching in NIST library with promising biological properties against anti-bacterial and Zika virus vector mosquitocidal Properties. Metabolites, steroids and fatty acids are abundant in crude compounds of ascidian D. bistratum and showed potential zone growth inhibition against bacterial strains Kluyvera ascorbate (10 mm). The active crude compounds of D. bistratum exhibited prominent larvicidal activity against the Zika vector mosquitoes of Aedes aegypti and Cluex quinquefasciatus (LC₅₀ values of 0.4436 to 2.23 mg/mL). The findings of this study provide a first evidence of the biological properties exhibited by D. bistratum extracts, thus increasing the knowledge about the Zika virus vector mosquitocidal properties of ascidian. Overall, ascidian D. bistratum are promising and biocontrol or eco-friendly tool against A. aegypti and C. quinquefasciatus with prospective toxicity against non-target organisms.

NaoMaiTong (NMT: Radix et Rhi-zoma Rhei, Radix Ginseng, Radix Puerariae, and Rhizoma Ligustici Chuanxiong as 9: 9: 6: 6) is a traditional Chinese medicine prescription for treating ischemia cerebral apoplexy. In this work, four cell injury models of ischemic stroke were establish, namely hypoxic injury, glutamate damage, injury of potassium chloride and hydrogen peroxide damage model. The protective effects of NMT and its single herbs-containing sera of different time points on PC12 cell damage were evaluated respectively, and the corresponding efficacy-time curves were drawn. Cell viability was measured by MTT (3-(4,5)-Dimethylthiahiazo(-z-y1)-3,5-di-phenytetrazoliumromide) assay. Furthermore, an statistical methods of support vector machine (SVM) were used to establish the correlation between concentration-time-efficacy for the first time. These results revealed that NMT-containing serum has obvious protective effect on the four injury models and can significantly improve cell viability. The PK-PD correlation between fifteen ingredients in the NMT compound with four model efficacy indexes indicated that rhein, puerarin, and 3'-methoxy puerarin might be the most important constituents controlling the pharmacological effects of NMT. The study suggested that these fifteen components are likely to be the material basis of NMT and recommended to increase the amounts of Pueraria in the NMT compound. That provided the scientific basis and demonstration for the research of efficacy material base of Traditional Chinese Medicine (TCM).

Dynamic measurement error correction is an effective method to improve the sensor precision. Dynamic measurement error prediction is an important part of error correction, support vector machine (SVM) is often used to predicting the dynamic measurement error of sensors. Traditionally, the parameters of SVM were always set by manual, which can not ensure the model’s performance. In this paper, a method of SVM based on an improved particle swarm optimization (NAPSO) is proposed to predict the dynamic measurement error of sensors. Natural selection and Simulated annealing are added in PSO to raise the ability to avoid local optimum. To verify the performance of NAPSO-SVM, three types of algorithms are selected to optimize the SVM’s parameters, they are the particle swarm optimization algorithm (PSO), the improved PSO optimization algorithm (NAPSO), and the glowworm swarm optimization (GSO). The dynamic measurement error data of two sensors are applied as the test data. The root mean squared error and mean absoluter percentage error are employed to evaluate the prediction models’ performances. The experiment results show that the NAPSO-SVM has a better prediction precision and a less prediction errors among the three algorithms, and it is an effective method in predicting dynamic measurement errors of sensors.

In this paper, a new approach to retrieve semantic images based on shape and geometric features of image in conjunction with multi-class support vector machine is proposed. Zernike moment as shape feature is to verify the invariance of objects for silhouette image. In addition, a set of geometrical features is to explore the objects shape using two features of rectangularity and circularity. Then the extracted features are normalized and employed for multi-class support vector machine either for learning or retrieving processes. The retrieving process relies on three main tasks which namely Query Engine, Matching Module and Ontology Manger, respectively. Query Engine is to build the input text or image query using SPARQL language. The matching module extracts the shape and geometric features of image’s objects and employ them to Ontology Manger which in turn inserts them in ontology knowledge base. Benchmark mammals have been conducted to empirically conclude the outcome of proposed approach. Our experiment on text and image retrieval yields efficient results to problematic phenomena than previously reported.

High-Level Synthesis (HLS) tools have revolutionized FPGA application development by providing a more efficient and streamlined approach, significantly impacting digital design methodologies. Despite the capability of FPGAs to customize numerical representations in data paths, most HLS projects have focused on fixed-point precision, while floating-point representations remain limited to vendor-provided single, double, and half-precision formats. This paper proposes a customized floating-point library compatible with HLS to address these limitations. This library allows programmers to define the number of exponent and mantissa bits at compile time, providing greater flexibility and enabling the use of mixed precision. Moreover, this library includes optimized implementations of common components such as vector summation (VSUM), dot-product (DP), and matrix-vector multiplication (MVM). Results demonstrate that the proposed library reduces latency and resource utilization compared to vendor IP blocks, particularly in VSUM, DP, and MVM operations. For example, the MVM operation involving a 32x32 matrix, using vendor IP requires 22 clock cycles, whereas CuFP completes the same task in just 7 clock cycles, using approximately 60% fewer DSPs, 10% fewer LUTs, and 60% fewer FFs.

Viruses are silent enemies that intrude and take control of the plant cell's machinery for their own multiplication. Infection by viruses and the resulting damage is still a major challenge in the agriculture sector. Plants have the ability to fight back, but the ability of viruses to counteract and mutate at a fast rate helps them to hide from the host response. Therefore, classical approaches for introgressing resistance genes by breeding have obtained limited success in counteracting the virus menace. Genetic modification (GM) based strategies have been successful in engineering artificial resistance in plants. Several different approaches based on pathogen derived resistance, antisense constructs, hairpin RNA, double stranded RNA etc. have been used to enhance plant resistance to the virus. Recently, genome editing (GE) strategies mainly involving the CRISPR/Cas mediated modifications are being used for virus control. In this review, we discuss the developments and advancements in the GM and GE based methods in tackling virus infection in plants.

Listerias of the phylogenetic lineage II (PLII) are common in the European environment, and are hypovirulent. Despite this, they caused more than a third of sporadic cases of listeriosis, and multi-country foodborne outbreaks. L. monocytogenes ST37 is one of them. During the COVID-19 pandemic ST37 appeared in the clinical cases and ranked second in occurrence among food isolates in the Moscow region. The aim of this study was to describe the genomic features of ST37 isolates from different sources. All clinical cases of ST37 were in the cohort of male patients (age, 48-81 years) with meningitis-septicemia manifestation, and COVID-19 or Influenza in the anamnesis. The core genomes of the fish isolates were closely related. The clinical and meat isolates revealed a large diversity. Prophages (2-4/genome) were the source of the unique genes. Two clinical isolates displayed the pseudolysogeny, and excided prophages were A006-like. Absence of the plasmids, the assortment of virulence factors and resistance determinants in chromosome corresponded to the hypovirulent characteristics. However, all clinical isolates caused severe disease with deaths in four cases. Thus, these studies allow us to speculate that a previous viral infection increases a human susceptibility to listeriosis.

Inflammatory bowel disease (IBD) is an incurable, chronic disorder of the gastrointestinal tract, whose incidence increases every year. Scientific research is constantly delivering new information about the disease and its multivariate, complex etiology. Nevertheless, full discovery and understanding of the complete mechanism of IBD pathogenesis still pose a significant challenge to today's science. Recent studies unanimously confirmed the association of gut microbial dysbiosis with IBD, as well as its contribution to the regulation of the inflammatory process. It transpires that not only the altered composition of pathogenic and commensal bacteria is characteristic of disturbed intestinal homeostasis in IBD, but also of viruses, parasites, and fungi, which are active in the intestine. In fact, the crucial function of microbial metabolome in the human body is altered, which causes a wide range of effects in the host, thus providing a basis for the disease. On the other hand, human genomic and functional research revealed more loci that play an essential role in gut homeostasis regulation, immune response, and intestinal epithelial function. This review aims to organize and summarize currently available knowledge concerning the role and interaction of crucial factors associated with IBD pathogenesis, particularly host genetic composition, intestinal microbiota, and metabolome, with immune regulation.

Cholesterol biosynthesis inhibitors (statins) protect hypercholesterolemic patients from developing active tuberculosis, suggesting that these drugs could help the host to control the pathogen at the initial stages of the disease. This work studies the effect of fluvastatin on the early response of healthy peripheral blood mononuclear cells (PBMC) to inactivated Mycobacterium tuberculosis (Mtb) H37Ra. We found that in fluvastatin-treated PBMC, most monocytes/macrophages became foamy cells that overproduce NLRP3 inflammasome components in the absence of immune stimulation, evidencing important cholesterol metabolism/immunity connections. When both fluvastatin-treated and untreated PBMC were exposed to Mtb, a subset of macrophages quickly captured large amounts of bacilli and died, concentrating the bacteria in necrotic areas. In fluvastatin-untreated cultures, most of the remaining macrophages became epithelioid cells that isolated these areas of cell death in granulomatous structures that barely produced IFN-gamma. By contrast, in fluvastatin-treated cultures, foamy macrophages surrounded the accumulated bacteria to degrade them, markedly activated caspase-1 and elicited a potent IFNgamma/cytotoxic response. In rabb-gammaits immunized with the same bacteria, fluvastatin therapy increased the tuberculin test response. We conclude that statins enhance macrophage effectiveness to control Mtb supported by adaptive immunity, offering a promising tool in the design of alternative therapies to fight tuberculosis.

When the zoonotic parasite of rodents that can cause human neuroangiostrongyliasis, i.e., Angiostrongylus cantonensis, is found in its natural definitive hosts, it is usually reported in isolation, as if the rat lungworm were the only component of the within-rat parasite community. In this study we report the coinfections found in rats naturally infected by A. cantonensis in urban populations of Rattus norvegicus and Rattus rattus in Valencia, Spain. In addition to the rat lungworms, which were found in 14 of the 125 rats studied (a prevalence of 11.20%), 18 other parasite infrapopulations (intestinal and tissular protists, microsporidia, and helminths) were found; some of them with high burdens. Fourteen of these 19 species found are potential zoonotic parasites, namely Blastocystis, Giardia duodenalis, Cryptosporidium spp., Enterocytozoon bieneusi, Encephalitozoon hellem, Toxoplasma gondii, Brachylaima spp., Hydatigera taeniaeformis larvae, Hymenolepis nana, Hymenolepis diminuta, Angiostrongylus cantonensis, Calodium hepaticum, Gongylonema neoplasticum and Moniliformis moniliformis. Despite the limited number of rats studied, the total predominance of coinfected rats as well as their high parasite loads seem to indicate a clear trend towards parasite tolerance.

Apicomplexan infections, such as giardiasis and cryptosporidiosis, negatively impact a considerable proportion of human and commercial livestock populations. Despite this, the molecular mecha-nisms of disease, particularly the effect on the body beyond the gastrointestinal tract, are still poorly understood. To highlight host-parasite-microbiome biochemical interactions, we utilised integrated metabolomics-16S rRNA genomics and metabolomics-proteomics approaches in a C57BL/6J mouse model of giardiasis and compared these to Cryptosporidium and uropathogenic Escherichia coli (UPEC) infections. Comprehensive samples (faeces, blood, liver, and luminal contents from duo-denum, jejunum, ileum, caecum and colon) were collected 10 days post infection and subjected to proteome and metabolome analysis by liquid and gas chromatographic mass-spectrometry, re-spectively. Microbial populations in faeces and luminal washes were examined using 16S rRNA metagenomics. Proteome-metabolome analyses indicated that 12 and 16 key pathways were sig-nificantly altered in the gut and liver, respectively, during giardiasis with respect to other infections. Energy pathways including glycolysis and supporting pathways of glyoxylate and dicarboxylate metabolism, and redox pathway of glutathione metabolism, were upregulated in small intestinal luminal contents and the liver during giardiasis. Metabolomics-16S rRNA genetics integration in-dicated that populations of three bacterial families –Autopobiaceae (Up), Desulfovibrionaceae (Up) and Akkermanasiaceae (Down) – were most significantly affected across the gut during giardiasis, causing upregulated glycolysis and short-chained fatty acid (SCFA) metabolism. In particular, the perturbed Akkermanasiaceae population seemed to cause oxidative stress responses along the gut-liver axis. Overall, the systems biology approach applied in this study highlighted that the effects of host-parasite-microbiome biochemical interactions extended beyond the gut ecosystem to the gut-liver axis. These findings form the first steps in a comprehensive comparison to ascertain the major molecular and biochemical contributors of host-parasite interactions and contribute towards the development of biomarker discovery and precision health solutions for apicomplexan infections.

Enterovirus 71 (EV71) is an etiological agent of hand foot and mouth disease and can also cause neurological complications in young children. However, there are no approved drugs to treat EV71 infections. In this study, we conducted an antiviral drug screening by using a Food and Drug Administration (FDA)-approved drug library. We identified five drugs that showed dose-dependent inhibition of viral replication. Sertraline was further characterized because it exhibited the most potent antiviral activity with the highest selectivity index among the five hits. The antiviral activity of sertraline was noted for other EV serotypes. The drug’s antiviral effect is not likely associated with its approved indications as an antidepressant and its mode-of-action as a selective serotonin reuptake inhibitor. The time-of-addition assay revealed that sertraline inhibited an EV71 infection at the entry stage. We also showed that sertraline partitioned into acidic compartments, such as endolysosomes, to neutralize the low pH levels. In agreement with the findings, the antiviral effect of sertraline could be relieved greatly by exposing virus-infected cells to extracellular low-pH culture media. Together, we have identified an FDA-approved antidepressant with the new indication for the broad-spectrum EV inhibition by blocking viral entry through the alkalization of the endolysosomal route.

Dengue fever is a viral mosquito-borne infection, a major international public health concern. With 2.5 billion people at risk of acquiring the infection around the world, disease severity is influenced by the immunological status of the individual, seronegative or seropositive, prior to natural infection. Caused by four antigenically related but distinct serotypes, DENV-1 to DENV-4, infection by one serotype confers life-long immunity to that serotype and a period of temporary cross-immunity (TCI) to other serotypes. The clinical response on exposure to a second serotype is complex with the so-called Antibody-Dependent enhancement (ADE) process, a disease augmentation phenomenon when pre-existing antibodies to previous dengue infection do not neutralize but rather enhance the new infection, used to explain the etiology of severe disease. In this paper, we present a minimalistic mathematical model framework developed to describe qualitatively the dengue immunological response mediated by antibodies. Three models are analyzed and compared: i) primary dengue infection, ii) secondary dengue infection with the same (homologous) dengue virus and iii) secondary dengue infection with a different (heterologous) dengue virus. We explore the features of viral replication, antibody production, and infection clearance over time. The model is developed based on body cells and free virus interactions resulting in infected cells activating antibody production. Our mathematical results are qualitatively similar to the ones described in the empiric immunology literature, providing insights on the immunopathogenesis of severe disease. Results presented here are of use for future research directions to evaluate the impact of dengue vaccines.

Symbioses between animals and bacteria are ubiquitous. To better understand these relationships, it is essential to unravel how bacteria evolve to colonize hosts. Previously, we serially passaged the free-living bacterium, Shewanella oneidensis, through the digestive tracts of germ-free larval zebrafish (Danio rerio) to uncover the evolutionary changes involved in the initiation of a novel symbiosis with a vertebrate host. After 20 passages, we discovered an adaptive missense mutation in the mshL gene of the msh pilus operon, which improved host colonization, increased swimming motility, and reduced surface adhesion. In the present study, we have determined that this mutation was a loss-of-function mutation and found that it improved zebrafish colonization by augmenting S. oneidensis representation in the water column outside larvae through a reduced association with environmental surfaces. Additionally, we found that strains containing the mshL mutation were able to immigrate into host digestive tracts at higher rates per capita. However, mutant and evolved strains exhibited no evidence of a competitive advantage after colonizing hosts. Our results demonstrate that bacterial behaviors outside the host can play a dominant role in facilitating the onset of novel host associations.

Thermal variations affect tri-trophic interactions involving plants, herbivores, and parasitoids, causing a mismatch between their phenological cycles. In the current environmental context of climate change, climatic factors can undergo profound and sudden changes, such as sudden hot or cold snaps. Here we show that episodes of short but sustained low temperatures have increased, mainly in the month of May, in the last two decades. We subjected galls induced by Asian chestnut gall wasp (ACGW) Dryocosmus kuriphilus to cold stress to assess if and how the pest and its parasitoids were affected. Over the course of two years seasonal parasitism, parasitism rates, the relative abundance of each parasitoid species, and mortality of ACGW were calculated. We found that the cold treatment affected both pest and parasitoids, resulting in a reduction in emerging ACGWs and differing ratios of species within the parasitoid community. The striking example was the change in the relative frequency of three species of Eupelmus spp. and of Mesopolobus tibialis, which doubled in thermally-stressed galls in all chestnut fields. The thermal effects on the development of the host and the direct effects of cold temperatures on the surface of galls (i.e., humidity or hardness of the galls) warrant further research in this direction.

The accurate virus detection, strain discrimination, and source attribution of contaminated food items remains a persistent challenge because of the high mutation rates anticipated to occur in foodborne RNA viruses, such as Hepatitis A virus (HAV). This has led to predictions of the existence of more than one sequence variant between the hosts (inter-host) or within an individual host (intra-host). However, there have been no reports of intra-host variants from an infected single individual, and little is known about the accuracy of the single nucleotide variations (SNVs) calling with various methods. In this study, the presence and identity of viral SNVs, either between HAV clinical specimens or among a series of samples derived from HAV clone1-infected FRhK4 cells, were determined following analyses of nucleotide sequences generated using next-generation sequencing (NGS) and pyrosequencing methods. The results demonstrate the co-existence of inter- and intra-host variants both in the clinical specimens and the cultured samples. The discovery and confirmation of multi-viral RNAs in an infected individual is dependent on the strain discrimination at the SNV level, and critical for successful outbreak traceback and source attribution investigations. The detection of SNVs in a time series of HAV infected FRhK4 cells improved our understanding on the mutation dynamics determined probably by different selective pressures. Additionally, it demonstrated that NGS could potentially provide a valuable investigative approach toward SNV detection and identification for other RNA viruses.

Keywords: Artificial Neural Network (ANN), Support Vector Machine (SVM), Support Vector Regression (SVR), Lightweight Gradient Boosting Machines (Light GBM), Machine Learning, Solar Irradiance (SI), Solar forecasting

The combination of encryption and digital watermarking technologies is a trend to achieve full lifecycle data protection. Recently, reversible data hiding in encrypted domain (RDHED) has greatly aroused the interests of many scholars. But the fixed order of first encryption and then watermarking makes this kind of algorithms unsuitable to many applications. Commutative encryption and watermarking (CEW) technology realizes the flexible combination of encryption and watermarking, and suits more applications. However, most existing CEW schemes for vector maps are not reversible and unsuitable to high precision maps. To solve this problem, here we propose a commutative encryption and reversible watermarking (CERW) algorithm for vector maps based on virtual coordinates which are uniformly distributed on the number axis. The CERW algorithm consists of virtual interval step based encryption scheme and coordinate difference based reversible watermarking scheme. In the encryption scheme, the map coordinates are moved randomly by multiples of virtual interval step defined as distance between two adjacent virtual coordinates. In the reversible watermarking scheme, difference expansion (DE) technique is used to embed the watermark bit into the coordinate difference computed based on the relative position of a map coordinate in a virtual interval. Since the relative position of a map coordinate in a virtual interval keeps unchanged during the coordinate scrambling encryption process, the watermarking operation and the encryption operation don’t interfere with each other and the commutativity between encryption and watermarking achieves. Results show that: proposed method has high security, high capacity and good invisibility. In addition, the algorithm is not only applicable to polyline and polygon vector data, but also can be applied to sparsely distributed point data which the traditional DE watermarking algorithm often fails to watermark.

Several studies have already demonstrated the relationship between the loss of natural habitats and the incidence of diseases caused by vectors, such as dengue, which is an acute fever disease, considered a serious public health problem. The aim of the present study was to analyze the relationship between land use changes between 2009 and 2019 and the occurrence of dengue fever in 2015 and 2019 by municipality, using the state of Minas Gerais as a case study. For this, secondary data obtained from openly available sources were used. Natural vegetation cover data were obtained from the MAPBiomas platform and dengue occurrence data from the Ministry of Health, in addition to socioeconomic indicators from the Brazilian Institute for Geography and Statistics. Between 2015 and 2019, 1,255,731 cases of dengue were recorded throughout the state of Minas Gerais, ranging from 0 to 227 per thousand inhabitants between municipalities. The occurrence of dengue was distributed throughout all regions of Minas Gerais, affected by climatic and socioeconomic aspects. In general, municipalities with net loss of natural vegetation, predominantly located in the Cerrado biome, had the highest number of dengue cases in the studied period. Despite the significant positive relationship between these two variables, three of the eight socioeconomic parameters analyzed also affected the occurrence of dengue: population density, human development index (both positively) and Gini inequality index (negatively). These results indicate that, contrary to expectations, municipalities with better social conditions had more dengue cases. Our study indicates that natural vegetation is, directly or indirectly, involved in the ecosystem service of dengue control, despite the occurrence of this disease being affected by multiple factors that interact in a complex way. Thus, policies towards reducing deforestation must be complemented by a continuous investment in public health policies and reduction of social inequalities to efficiently control dengue fever.

The traditional receiver employs scalar tracking loops, resulting in degraded navigation performance in weak signal and high dynamic scenarios. An innovative design of a vector tracking receiver based on nonlinear Kalman filter (KF) tracking loops is proposed in this paper, which combines the strengths of both vector tracking and KF tracking loops. Firstly, a comprehensive description of the vector tracking receiver model is presented, and unscented Kalman filter (UKF) is applied to nonlinear tracking loop. Secondly, to enhance the stability and robustness of the KF tracking loop, we introduce square root filtering and an adaptive mechanism. The tracking loop based on square root UKF (SRUKF) can dynamically adjust its filtering parameters based on signal noise and feedback Doppler error. Finally, the proposed method is implemented on a software-defined receiver (SDR), and the field vehicle experiment demonstrates the superiority of this method over other receivers in complex dynamic environments.

We introduce a special vector field ω on a Riemannian manifold (N^m, g), such that the Lie derivative of the metric g with respect to ω is equal to ρRic, where Ric is the Ricci curvature of (N^m, g) and ρ is a smooth function on N^{m} and call this vector field a ρ-Ricci vector field. We use ρ-Ricci vector field on a Riemannian manifold (N^m, g) and find two characterizations of m-sphere S^m(α). In first result, we show that an m-dimensional compact and connected Riemannian manifold (N^m, g) with nonzero scalar curvature admits a ρ-Ricci vector field ω such that ρ is nonconstant function and the integral of Ric(ω,ω) has a suitable lower bound is necessary and sufficient for (N^m, g) to be isometric to m-sphere S^m(α). In second result, we show that an m-dimensional complete and simply connected Riemannian manifold (N^m, g) of positive scalar curvature admits a ρ-Ricci vector field ω such that ρ is a nontrivial solution of Fischer-Marsden equation and the squared length of the covariant derivative of ω has an appropriate upper bound, if and only if, (N^m, g) to be isometric to m-sphere S^m(α).

Landslide is one of the most common geological disasters in China, which is characterized by suddenness and uncertainty, and it is difficult to realize accurate identification, early warning and forecasting of landslide disaster by conventional means. With the development of high-resolution remote sensing satellites and InSAR surface deformation monitoring technology, the traditional means of landslide monitoring data sources are limited, and there is a lack of effective methods to excavate the characteristics of the spatial distribution of landslide hazards and their triggering factors and other issues. In this paper, the area extending 10 km outside the VII isobar of the Gengma earthquake is taken as the study area, and 13 evaluation factors are screened out by integrating the factors of InSAR surface deformation, topography and geological environment, and the Bayesian Optimized Convolutional Neural Network (BO-CNN) is used for the evaluation of landslide susceptibility, and the BO-RF and PSO-SVM models are selected for the comparative analysis. The model accuracy evaluation was carried out by three indexes: ROC curve, AUC value and FR value, in which the ROC curves of PSO-SVM, BO-RF and BO-CNN were all close to the upper-left corner of the corner, and the AUC values were 0.9388, 0.9529, and 0.9535, respectively, and the FR value of landslide in the high susceptibility area of BO-CNN was as high as 14.9, and was higher than that of PSO-SVM and BO-RF, respectively. SVM and BO-RF model is 4.55 and 3.69 higher, the experimental results show that the BO-CNN model used in this paper has a better effect in landslide susceptibility evaluation, and the research results of the local government's disaster prevention and mitigation measures are of great significance.

Triatoma infestans (Klug) is an insect recognized as not only an important vector of South-American trypanosomiasis (Chagas disease) but also a model of specific cellular morphofunctional organization and epigenetic characteristics. The purpose of the present review is to highlight certain cellular processes that are particularly unveiled in T. infestans, such as 1) somatic polyploidy involving nuclear and cell fusions that generate giant nuclei; 2) diversification of nuclear phenotypes in the Malpighian tubules during insect development; 3) heterochromatin compartmentalization into large bodies with specific spatial distribution and presumed mobility in the cell nuclei; 4) chromatin remodeling and co-occurrence of necrosis and apoptosis in the Malpighian tubules under stress conditions; 5) epigenetic markers; 6) unexplained response of heterochromatin to valproic acid, an epidrug that inhibits histone deacetylases and induces DNA demethylation in other cell systems. These cellular processes and epigenetic characteristics emphasize the role of T. infestans as an attractive model for cellular research.

Climate change and globalization have raised the risk of vector-borne disease (VBD) introduction and spread in various European nations in recent years. In Italy, viruses carried by tropical vectors have been shown to cause viral encephalitis, one of the symptoms of arbovirosis, a spectrum of viral disorders spread by arthropods such as mosquitoes and ticks. Arbovirosis are currently causing alarm and attention, and the World Health Organization (WHO) has released recommendations to adopt essential measures, particularly during the hot season, to restrict the spreading of the infectious agents among breeding stocks. In this scenario, rapid analysis systems are required, because they can quickly provide information on potential virus-host interactions, the evolution of the infection, and the onset of disabling clinical symptoms, or serious illnesses. Such systems include bioinformatics approaches integrated with molecular evaluation. Viruses have co-evolved different strategies to transcribe their own genetic material, by changing the host's transcriptional machinery, even in short periods of time. The introduction of genetic alterations, particularly in RNA viruses, results in a continuous adaptive fight against the host's immune system. We suggest an in silico pipeline method to unravel viral sequences that may interact with host RNA binding proteins (RBPs), which play important roles in RNA metabolism and its several related biological processes. Indeed, viral RNA sequences, able to bind host RBPs may compete with cellular RNAs, altering important metabolic processes. Our findings suggest that the proposed in silico approach, could be a useful and promising tool to investigate the complex and multiform clinical manifestations of viral encephalitis, and possibly identify altered metabolic pathways as targets of pharmacological treatments and innovative therapeutic protocols.

Aging kills 100,000 people a day - more than any other cause of death combined. The exact causes of aging have been much discussed, but the most pressing issue with regard to aging appears to me to be lipofuscin accumulation. That is, the accumulation of indigestible cellular garbage that needs to be removed from our cells, then the body. In this piece, I will explain why I think “getting rid of the garbage” should be at least one of our main goals with regard to longevity research for now.

The system identification problem with multiple nonlinearities is relevant. Its decision depends on many factors. These include: feedbacks, the method of connecting nonlinear links, signal properties. They affect the identifiability of the system parameters. We introduced a condition for the excitation constancy for state variables, which considers the S-identifiability of the system. We propose system decomposition by measuring input to identify parameters. Each subsystem has an implicit identification representation. It guarantees obtaining estimates of subsystem parameters based on experimental data. The trajectories boundedness of adaptive system proved in parametric and coordinate spaces. Conditions guaranteeing exponential stability of the system obtained. Systems of self-oscillation generation and nonlinear correction of a nonlinear system consider. Conditions for the trajectories boundedness of the adaptive system obtained for these cases. The influence of nonlinearity and feedback on the system performance estimated.

The synuclein family consists of α-, β-, and γ-Synuclein (α-Syn, β-Syn, and γ-Syn), expressed in the neurons and concentrated in synaptic terminals. While α-Syn is at the center of interest due to its implication in the pathogenesis of Parkinson’s disease (PD) and other synucleinopathies, limited information exists on the other members. The current study aimed at investigating the biological role of γ-Syn controlling the midbrain dopamine (DA) function. We generated two different mouse models with i) γ-Syn overexpression induced by an adeno-associated viral vector and ii) γ-Syn knockdown induced by a ligand-conjugated antisense oligonucleotide, to modify the endogenous γ-Syn transcription levels in midbrain DA neurons. The progressive overexpression of γ-Syn decreased DA neurotransmission in the nigrostriatal and mesocortical pathways. In parallel, mice evoked motor deficits in the rotarod and impaired cognitive performance as assessed by novel object recognition, passive avoidance, and Morris water maze tests. Conversely, acute γ-Syn knockdown selectively in DA neurons facilitated forebrain DA neurotransmission. Importantly, modifications in γ-Syn expression did not induce the loss of DA neurons or changes in α-Syn expression. Collectively, our data strongly suggest that DA re-lease/re-uptake processes in the nigrostriatal and mesocortical pathways are partially dependent on SNc/VTA γ-Syn transcription levels, and are linked to modulation of DA transporter function, similar to α-Syn.

Defect detection and identification from fruits and vegetables are particularly challenging for Indian agriculture. Defect Detection is a process to identify the defects or damages in vegetables and fruits, based on the shapes, colors and textures. The local market finds it difficult to cope with the defects and other infections in fruits and vegetables as quality evaluations and classification of vegetables and fruits have become tedious process. Recently, several approaches based on Image processing, Machine Learning and Artificial Intelligence methods have been proposed for the purpose of defect detection. On the basis of classifying the types of defects, related pathogens, and physical and morphological characteristics descriptors, we review the different approaches based on a corpus of 57 articles between 2016 and 2021. In the process of describing the defect analysis, steps from the target articles, algorithms, and methods including qualitative and quantitative evaluation are mainly summarized. The aim of this current review work is to present-day novel images and collects recent defective area calculation methods to detect surface defects of fruits and vegetables using RGB images and to classify whether the fruit is defected or fresh. A rigorous evaluation of many new algorithms provided for quality assurance by researcher’s probes of vegetables and fruits have been conducted in this work. This review work conveys that using the recent identification features will help to decrease the disadvantages in fruit storeroom owing to storage of the affected vegetables and fruits, ie. Preventing the spread of defects and other infections from the infected fruits and vegetables to the fresh ones.

In this paper we give the improved and new analytical and semi-analytical expression for calcu-lating the magnetic vector potential, magnetic field, magnetic force, mutual inductance, torque, and stiffness between two inclined current-carrying arc segments in air. The expressions are ob-tained either in the analytical form over the incomplete elliptic integrals of the first and the sec-ond time or by the single numerical integration of some elliptical integrals of the first and the second kind. The validity of the presented formulas is proved from the special cases when the inclined circular loops are treated. We mention that all formulas are obtain by the integral ap-proach except the stiffness which is found by the derivative of the magnetic force.

The World Anti-Doping Agency (WADA) has prohibited gene doping in the context of progress in gene therapy. In addition, there is a risk of the EPO gene being applied in gene doping among athletes. Along with this, development of a gene-doping test has been underway in worldwide. Here, we had two purposes: to develop a robust gene doping mouse model using the human EPO gene (hEPO) transferred using recombinant adenovirus (rAdV) as a vector and to develop a detection method to prove gene doping using this model. The rAdV including the hEPO gene were injected intravenously to transfer the gene to the liver. After injection, the mice developed significantly increased red blood cell counts in whole blood and increased gene expressions of hematopoietic markers in the spleen, indicating successful development of the gene doping model. Next, we detected direct and indirect proof of gene doping in whole blood DNA and RNA using qPCR assay and RNA sequencing. Proof was detected in one drop of whole blood DNA and RNA over a long period; furthermore, the overall RNA expression profiles significantly changed. Therefore, we have advanced detection of hEPO gene doping in humans.

Prothrombotic thrombocytopathy mimicking heparin-induced thrombocytopenia has been observed in patients with severe COVID-19 and after immunisation with the Vaxzevria vaccine. Herein, we discuss the pathogenesis of this disorder focusing on the possible involvement of anti-platelet factor 4 (PF4) autoantibodies.

Use of Machine Learning (ML) methodologies in optical communications has paved a new pathway. In this paper, firstly, we discuss the use of ML methodologies for reducing optical fiber nonlinearities, nonlinearity compensation, fault detection and optical performance monitoring. Then we present our recent work where we compare RL-SARSA and SVM based method with conventional method. The results show that RL-SARSA and SVM methods are successful candidates in mitigating the nonlinearities in proposed system as compared to conventional optical communication system.

The ASCE-EWRI reference evapotranspiration (ETo) equation is recommended as a standardized method for reference crop ETo estimation. However, various climate data as input variables to the standardized ETo method are considered limiting factors in most cases and restrict the ETo estimation. This paper assessed the potential of different machine learning (ML) models for ETo estimation using limited meteorological data. The ML models used to estimate daily ETo included Gene Expression Programming (GEP), Support Vector Machine (SVM), Multiple Linear Regression (LR), and Random Forest (RF). Three input combinations of daily maximum and minimum temperature (Tmax and Tmin), wind speed (W) with Tmax and Tmin, and solar radiation (Rs) with Tmax and Tmin were considered using meteorological data during 2003–2016 from six weather stations in the Red River Valley. To understand the performance of the applied models with the various combinations, station, and yearly based tests were assessed with local and spatial approaches. Considering the local and spatial approaches analysis, the LR and RF models illustrated the lowest rate of improvement compared to GEP and SVM. The spatial RF and SVM approaches showed the lowest and highest values of the scatter index as 0.333 and 0.457, respectively. As a result, the radiation-based combination and the RF model showed the best performance with higher accuracy for all stations either locally or spatially, and the spatial SVM and GEP illustrated the lowest performance among models and approaches.

Crowd density estimation is an important task for crowd monitoring. Many efforts have been done to automate the process of estimating crowd density from images and videos. Despite series of efforts, it remains a challenging task. In this paper, we proposes a new texture feature-based approach for the estimation of crowd density based on Completed Local Binary Pattern (CLBP). We first divide the image into blocks and then re-divide the blocks into cells. For each cell, we compute CLBP and then concatenate them to describe the texture of the corresponding block. We then train a multi-class Support Vector Machine (SVM) classifier, which classifies each block of image into one of four categories, i.e. Very Low, Low, Medium, and High. We evaluate our technique on the PETS 2009 dataset, and from the experiments, we show to achieve 95% accuracy for the proposed descriptor. We also compare other state-of-the-art texture descriptors and from the experimental results, we show that our proposed method outperforms other state-of-the-art methods.

Background: Previous papers have developed a statistical mechanics of neocortical interactions (SMNI) fit to short-term memory and EEG data. Adaptive Simulated Annealing (ASA) has been developed to perform fits to such nonlinear stochastic systems. An N-dimensional path-integral algorithm for quantum systems, qPATHINT, has been developed from classical PATHINT. Both fold short-time propagators (distributions or wave functions) over long times. Previous papers applied qPATHINT to two systems, in neocortical interactions and financial options. Objective: In this paper the quantum path-integral for Calcium ions is used to derive a closed-form analytic solution at arbitrary time that is used to calculate interactions with classical-physics SMNI interactions among scales. Using fits of this SMNI model to EEG data, including these effects, will help determine if this is a reasonable approach. Method: Methods of mathematical-physics for optimization and for path integrals in classical and quantum spaces are used for this project. Studies using supercomputer resources tested various dimensions for their scaling limits. In this paper the quantum path-integral is used to derive a closed-form analytic solution at arbitrary time that is used to calculate interactions with classical-physics SMNI interactions among scales. Results: The mathematical-physics and computer parts of the study are successful, in that there is modest improvement of cost/objective functions used to fit EEG data using these models. Conclusions: This project points to directions for more detailed calculations using more EEG data and qPATHINT at each time slice to propagate quantum calcium waves, synchronized with PATHINT propagation of classical SMNI.

The goal of VAR or BVAR is the characterization of the dynamics and endogenous relationships among time series. Also the VAR models are known for their applications to forecasting and policy analysis. This paper compare the performance of VAR and Sims-Zha Bayesian VAR models when the multiple time series are jointly influenced by different levels of collinearity and autocorrelation in the short term (T=16, 32, 64 and 128). Five levels (-0.9,-0.5, 0,+0.5,+0.9) of collinearity and autocorrelation were considered and the results from the simulation study revealed that VAR(2) model dominated for no and moderate levels of autocorrelation (-0.5, 0, +0.5) irrespective of the collinearity level except in few cases when T=16. While the BVAR models dominated for high autocorrelation levels (-0.9 and +0.9) irrespective of the collinearity level except in few cases when T=128. The performance of the models varies at different levels of the collinearity and autocorrelated error, and also varies with the short term periods. Furthermore, the values of the RMSE and MAE criteria decrease as a result of increase in the time series length. In conclusion, the performance of the forecasting models depend on the time series data structure and the time series length. It is therefore recommended that the data structure and series length should be considered in using an appropriate model for forecasting.

Various factors and constraints should be considered when developing a manufacturing production schedule, and such a schedule is often based on rules. This paper develops a composite dispatching rule based on heuristic rules that comprehensively consider various factors in a semiconductor production line. The composite rule is obtained by exploring various states of a semiconductor production line (machine status, queue size, etc.), where such indicators as makespan and equipment efficiency are used to judge performance. A model of the response surface, as a function of key variables, is then developed to find the optimized parameters of a composite rule for various production states. Further, dynamic scheduling of semiconductor manufacturing is studied based on support vector regression (SVR). This approach dynamically obtains a composite dispatching rule (i.e. parameters of the composite dispatching rule) that can be used to optimize production performance according to real-time production line state. Following optimization, the proposed dynamic scheduling approach is tested in a real semiconductor production line to validate the effectiveness of the proposed composite rule set.