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Simple Summary: The journey of discovering melanoma—the most dangerous type of skin cancer—biomarkers is never-ending. Under that assumption, this study attempts to partially fill a gap in that journey by identifying melanoma-related biomarkers. This research paper studied the genetic and molecular profiling of melanoma. A transcriptome-wide association study (TWAS) was conducted to reveal the significant biomarkers associated with melanoma. A molecular network was constructed to represent the significant interactions between genes and microRNAs (miRNAs). The related biological processes, the enriched pathways, and the associated diseases were identified. The hotspot biomarkers were discovered to elucidate further the mechanism of these genes and miRNAs in melanoma pathogenesis. This work reveals the pathogenesis and biologically important molecular interactions of melanoma and provides new insights into the molecular mechanisms of melanoma. A transcriptome-wide association study (TWAS) was conducted on genome-wide association study (GWAS) summary statistics of malignant melanoma of skin (UK Biobank dataset) and The Cancer Genome Atlas-Skin Cutaneous Melanoma (TCGA-SKCM) gene expression weights to identify melanoma susceptibility genes. The GWAS included 2465 cases and 449,799 controls, while the gene expression testing was conducted on 103 cases. Afterward, a gene enrichment analysis was applied to identify significant TWAS associations. The melanoma's gene–microRNA (miRNA) regulatory network was constructed from the TWAS genes and their corresponding miRNAs. At last, a disease enrichment analysis was conducted on the corresponding miRNAs. The TWAS detected 27 genes associated with melanoma with p-values less than 0.05 (the top three genes are LOC389458 (RBAK), C16orf73 (MEIOB), and EIF3CL). After the joint/conditional test, one gene (AMIGO1) was dropped, resulting in 26 significant genes. The Gene Ontology (GO) biological process associated the extended gene set (76 genes) with protein K11-linked ubiquitination and regulation of cell cycle phase transition. K11-linked ubiquitin chains regulate cell division. Interestingly, the extended gene set was related to different skin cancer subtypes. Moreover, the enriched pathways were nsp1 from SARS-CoV-2 that inhibit translation initiation in the host cell, cell cycle, translation factors, and DNA repair pathways full network. The gene-miRNA regulatory network identified 10 hotspot genes with the top three: TP53, BRCA1, and MDM2; and four hotspot miRNAs: mir-16, mir-15a, mir-125b, and mir-146a. Melanoma was among the top ten diseases associated with the corresponding (106) miRNAs. Our results shed light on melanoma pathogenesis and biologically significant molecular interactions. [ABSTRACT FROM AUTHOR]

This paper discusses the use of biomarkers in clinical practice and biomedical research. Biomarkers are measurable characteristics that can be used to indicate the presence or absence of a disease or to track the progression of a disease. They can also be used to predict how a patient will respond to a particular treatment. Biomarkers have enriched clinical practice and disease prognosis by providing measurable characteristics that indicate biological processes. They offer valuable insights into disease susceptibility, progression, and treatment response, aiding drug development and personalized medicine. However, developing and implementing biomarkers come with challenges that must be addressed. Rigorous testing, standardization of assays, and consideration of ethical factors are crucial in ensuring the reliability and validity of biomarkers. Reliability is vital in biomarker research. It ensures accurate measurements by preventing biases and facilitating robust correlations with outcomes. Conversely, validation examines which and how many biomarkers correspond to theoretical constructs and external criteria, establishing their predictive value. Multiple biomarkers are sometimes necessary to represent the complex relationship between exposure and disease outcomes accurately. Susceptibility factors are pivotal in disease states' complex interaction among genetic and environmental factors. Gaining a comprehensive understanding of these factors is essential for effectively interpreting biomarker data and maximizing their clinical usefulness. Using well-validated biomarkers can improve diagnoses, more effective treatment evaluations, and enhanced disease prediction. This, in turn, will contribute to better patient outcomes and drive progress in medicine. [ABSTRACT FROM AUTHOR]

This paper explores the dynamics of COVID-19 transmission, particularly focusing on super-spreaders, through the lens of the SIR model. The model comprises six compartments representing susceptible, exposed, symptomatic infected, super-spreader, asymptomatic infected, and recovered individuals. Utilizing a set of non-linear, interdependent differential equations, we numerically solve for model parameters to examine the influence of super-spreaders on infection spread within the population. We calculate the basic reproduction number (R0) and discuss the stability of disease-free equilibrium. Our findings underscore the significant role played by super-spreaders and asymptomatic individuals in disease dissemination. Drawing on the epidemiological concept of the iceberg phenomenon, we offer insights into super-spreader events (SSEs) in India and their ramifications. [ABSTRACT FROM AUTHOR]

Mitochondrial DNA (mtDNA) exhibits distinct characteristics distinguishing it from the nuclear genome, necessitating specific analytical methods in genetic studies. This comprehensive review explores the complex role of mtDNA in a variety of genetic studies, including genome-wide, epigenome-wide, and phenome-wide association studies, with a focus on its implications for human traits and diseases. Here, we discuss the structure and gene-encoding properties of mtDNA, along with the influence of environmental factors and epigenetic modifications on its function and variability. Particularly significant are the challenges posed by mtDNA's high mutation rate, heteroplasmy, and copy number variations, and their impact on disease susceptibility and population genetic analyses. The review also highlights recent advances in methodological approaches that enhance our understanding of mtDNA associations, advocating for refined genetic research techniques that accommodate its complexities. By providing a comprehensive overview of the intricacies of mtDNA, this paper underscores the need for an integrated approach to genetic studies that considers the unique properties of mitochondrial genetics. Our findings aim to inform future research and encourage the development of innovative methodologies to better interpret the broad implications of mtDNA in human health and disease. [ABSTRACT FROM AUTHOR]

Systemic sclerosis (SSc) is a rare autoimmune connective tissue disorder characterized by massive fibrosis, vascular damage, and immune imbalance. Advances in rheumatology and immunology over the past two decades have led to a redefinition of systemic sclerosis, shifting from its initial perception as primarily a "hyperfibrotic" state towards a recognition of systemic sclerosis as an immune-mediated disease. Consequently, the search for genetic markers has transitioned from focusing on fibrotic mechanisms to exploring immune regulatory pathways. Immunogenetics, an emerging field at the intersection of immunology, molecular biology, and genetics has provided valuable insights into inherited factors that influence immunity. Data from genetic studies conducted thus far indicate that alterations in genetic messages can significantly impact disease risk and progression. While certain genetic variations may confer protective effects, others may exacerbate disease susceptibility. This paper presents a comprehensive review of the most relevant genetic changes that influence both the risk and course of systemic sclerosis. Special emphasis is placed on factors regulating the immune response, recognizing their pivotal role in the pathogenesis of the disease. [ABSTRACT FROM AUTHOR]

Background: Motor neuron disease (MND) (also known as amyotrophic lateral sclerosis) is a life‐limiting neurodegenerative condition. In up to 20% of people with MND, a pathogenic variant associated with autosomal dominant inheritance can be identified. Children of people carrying a pathogenic variant have a 50% chance of inheriting this and a higher, although harder to predict, chance of developing the disease compared to the general adult population. This paper explores the experience of living with the genetic risk of MND. Methods: We undertook a UK‐based interview study with 35 individuals, including: 7 people living with genetically‐mediated forms of MND; 24 asymptomatic relatives, the majority of whom had an increased risk of developing the disease; and 4 unrelated partners. Results: We explore how individuals make sense of genetic risk, unpacking the interplay between genetic knowledge, personal perception, experiences of the disease in the family, age and life stage and the implications that living with risk has for different aspects of their lives. We balance an emphasis on the emotional and psychological impact described by participants, with a recognition that the salience of risk fluctuates over time. Furthermore, we highlight the diverse strategies and approaches people employ to live well in the face of uncertainty and the complex ways they engage with the possibility of developing symptoms in the future. Finally, we outline the need for open‐ended, tailored support and information provision. Conclusions: Drawing on wider literature on genetic risk, we foreground how knowledge of MND risk can disrupt individuals' taken‐for‐granted assumptions on life and perceptions of the future, but also its contextuality, whereby its relevance becomes more prominent at critical junctures. This research has been used in the development of a public‐facing resource on the healthtalk.org website. Patient or Public Contribution: People with experience of living with genetic risk were involved throughout the design and conduct of the study and advised on aspects including the topic guide, sampling and recruitment and the developing analysis. Two patient and public involvement contributors joined a formal advisory panel. [ABSTRACT FROM AUTHOR]

Hackathons are collaborative events that bring together diverse groups to solve predefined challenges. The COVID-19 pandemic caused by SARS-CoV-2 has emphasized the need for portable and reproducible genomics analysis pipelines to study the genetic susceptibility of the human host and investigate human-SARS-CoV-2 protein interactions. To build and strengthen institutional capacities in OMICS data analysis applied to host-pathogen interaction (HPI), the PHINDaccess project organized two hackathons in 2020 and 2021. These hackathons are aimed at developing bioinformatics pipelines related to the SARS-CoV-2 viral genome, its phylodynamic transmission, and the identification of human genome host variants, with a focus on addressing global health challenges, particularly in low- and middle-income countries (LMIC). This paper outlines the preparation, proceedings, and lessons learned from these hackathons, including the challenges faced by participants and our recommendations based on our experience for organizing hackathons in LMIC and beyond. [ABSTRACT FROM AUTHOR]

Objective: The Samoan community has a disproportionately higher incidence of gestational diabetes mellitus (GDM). We explored consumer and healthcare providers' insight into perceptions of risk, attitudes to lifestyle behaviour change and experiences of GDM among Australian Samoan women in South Western Sydney. Methods: Semi-structured interviews and a focus group with Samoan women recruited through three churches, a diabetes and pregnancy clinic in South Western Sydney and via social media were conducted. Semi-structured interviews with healthcare providers' were also conducted. Main themes were thematically analysed to identify recurring patterns using Quirkos software. Identified themes were framed against the constructs of the Health Belief Model. Results: One focus group (n=4) and 12 one-to-one interviews were conducted among Samoan women. Eighteen semi-structured interviews with healthcare providers' were also conducted. There was a high concordance between Samoan women and healthcare providers' regarding perception of risk and barriers to maintaining a healthy lifestyle. However, Samoan women reported negative interactions with healthcare providers' that hindered their behaviour change, while healthcare providers' reported that normalisation of diabetes, confusion of GDM with type 2 diabetes and spiritual health beliefs were deterrents to behaviour change among Samoan women. Conclusion: Cross-cultural factors can influence the uptake of a healthy lifestyle. Future research should consider use of culturally tailored strategies when developing educational resources targeting Samoan women. Implications for research, policy and practice: The participants' viewpoints expressed in this study suggest a critical need for the development of culturally-tailored health promotion strategies for Samoan women and cultural training for healthcare providers', to improve GDM care and subsequent pregnancy outcomes. What is already known about the topic? * There is limited data and research on GDM particularly among the Australian-Samoan community though the available data highlight the significant morbidity and mortality due to diabetes in this population. * Samoan women are at an increased risk of gestational diabetes mellitus. What this paper adds: * This paper provides knowledge and understanding on ways to prevent and manage GDM by investigating the perception of risk and experiences of GDM among Australian Samoan women and healthcare professionals in Sydney. * It provides current evidence base for policy makers and researchers to develop health promotion strategies and interventions that are relevant to the Samoan and other culturally and linguistically diverse (CALD) communities in Australia. [ABSTRACT FROM AUTHOR]

In this paper I discuss the possibility of considering periphrastic passive constructions as syntactic Latinisms. To do so, I start from the definition of Latinism and present a gradual conception of it that enables the differentiation of strong and weak syntactic Latinisms. In this sense, I question the characterisation of the periphrastic passive as an inherited form, a problem that requires reflection on the types of linguistic change and the processes of linguistic elaboration that contribute to multiplying the possibilities of variation in languages subjected to scripturalisation processes since the Middle Ages. In the case of the periphrastic passive, this paper presents a brief state of the art and insists on the point of view of translation, which frequently proves how forms with active diathesis have a special prominence as opposed to those with passive diathesis. I also present a general overview of the diachronic research focused on the phenomenon. The examples selected for this paper include fragments of medieval and Renaissance works in which it is possible to discern various Latinising, Anti-Latinising and Hyper-Latinising tendencies. [ABSTRACT FROM AUTHOR]

In this paper, a reaction-diffusion SIRS epidemic model with nonlinear incidence rate and partial immunity in a spatially heterogeneous environment is proposed. The wellposedness of the solution is firstly established. Then the basic reproduction number R0 is defined and a threshold dynamics is obtained. That is, when R0 < 1, the disease-free steady state is locally stable, which implies that the disease is extinct, when R0 > 1, the disease is permanent, and there exists at least one positive steady state solution. Finally, the asymptotic profiles of the positive steady state solution as individuals disperse at small and large rates are investigated. Furthermore, as an application of theoretical analysis, a numerical example involving the spread of influenza is discussed. Based on the numerical simulations, we find that the increase of transmission rate and spatial heterogeneity can enhance the risk of influenza propagation, and the increase of diffusion rate, saturation incidence for susceptible and recovery rate can reduce the risk of influenza propagation. Therefore, we propose to reduce the flow of people to lower the effect of spatial heterogeneity, increase the transfer of infected individuals to hospitals in surrounding areas to increase the diffusion rate, and increase the construction of public medical resources to increase the recovery rate for controlling influenza propagation. [ABSTRACT FROM AUTHOR]

Despite well-documented evidence that structurally disadvantaged populations are disproportionately affected by infectious diseases, our understanding of the pathways that connect structural disadvantage to the burden of infectious diseases is limited. We propose a conceptual framework to facilitate more rigorous examination and testing of hypothesized mechanisms through which social and environmental factors shape the burden of infectious diseases and lead to persistent inequities. Drawing upon the principles laid out by Link and Phelan in their landmark paper on social conditions (J Health Soc Behav. 1995;(spec no.):80–94), we offer an explication of potential pathways through which structural disadvantage (e.g. racism, sexism, and economic deprivation) operates to produce infectious disease inequities. Specifically, we describe how the social environment affects an individual's risk of infectious disease by 1) increasing exposure to infectious pathogens and 2) increasing susceptibility to infection. This framework will facilitate both the systematic examination of the ways in which structural disadvantage shapes the burden of infectious disease and the design of interventions that can disrupt these pathways. [ABSTRACT FROM AUTHOR]

Background: Osteoarthritis of the knee is an irreversible disease that causes great pain, and genetic factors play an important role in its occurrence and development. There have been many studies on the correlation between ADAM12 polymorphisms and genetic susceptibility to osteoarthritis, but the results remain inconclusive. Methods: Papers from PubMed, Web of Science, EMbase, Springer, SCOPUS, Google Scholar and other databases were systematically retrieved with a cut-off of January 2022. All case–control studies on ADAM12 rs3740199, rs1871054, rs1044122, and rs1278279 polymorphisms and osteoarthritis were searched. Fixed or random effects models were used for pooled analysis with OR values and 95% confidence intervals (CI), and publication bias was assessed. In addition, the false-positive reporting probability test was used to assess the confidence of a statistically significant association. Results: Eleven articles were included, which included 3332 patients with osteoarthritis and 5108 healthy controls. Meta-analysis showed that the rs1871054 polymorphism of ADAM12 was associated with osteoarthritis in dominant, recessive, allelic, and homozygote genetic models [C vs. T: OR = 1.34 95% CI (1.05, 1.71), P < 0.001]. Our subgroup analysis revealed an association between the ADAM12 polymorphism rs1871054 in Asians and osteoarthritis [C vs. T: OR = 1.61, 95% CI (1.25, 2.08), P < 0.001], albeit this was only for three studies. In addition, the ADAM12 polymorphism rs1871054 is associated with osteoarthritis in patients younger than 60 years of age [C vs. T: OR = 1.39, 95% CI (1.01, 1.92), P = 0.289]; however, the ADAM12 gene rs3740199, rs1044122, and rs1278279 site polymorphisms were not significantly. Furthermore, when assessing the confidence of the positive results, the positive results were found to be credible (except for Age < 60). Conclusion: Polymorphism at the rs1871054 site of ADAM12 is associated with genetic susceptibility to osteoarthritis, but rs3740199, rs1044122, and rs1278279 site polymorphisms are not. [ABSTRACT FROM AUTHOR]

Genetic studies of disease progression can be used to identify factors that may influence survival or prognosis, which may differ from factors that influence on disease susceptibility. Studies of disease progression feed directly into therapeutics for disease, whereas studies of incidence inform prevention strategies. However, studies of disease progression are known to be affected by collider (also known as "index event") bias since the disease progression phenotype can only be observed for individuals who have the disease. This applies equally to observational and genetic studies, including genome-wide association studies and Mendelian randomisation (MR) analyses. In this paper, our aim is to review several statistical methods that can be used to detect and adjust for index event bias in studies of disease progression, and how they apply to genetic and MR studies using both individual- and summary-level data. Methods to detect the presence of index event bias include the use of negative controls, a comparison of associations between risk factors for incidence in individuals with and without the disease, and an inspection of Miami plots. Methods to adjust for the bias include inverse probability weighting (with individual-level data), or Slope-Hunter and Dudbridge et al.'s index event bias adjustment (when only summary-level data are available). We also outline two approaches for sensitivity analysis. We then illustrate how three methods to minimise bias can be used in practice with two applied examples. Our first example investigates the effects of blood lipid traits on mortality from coronary heart disease, while our second example investigates genetic associations with breast cancer mortality. [ABSTRACT FROM AUTHOR]

Mathematical models have wide applications in studying COVID-19 epidemic transmission dynamics, however, most mathematical models do not take into account the heterogeneity of susceptible populations and the non-exponential distribution infectious period. This paper attempts to investigate whether non-exponentially distributed infectious period can better characterize the transmission process in heterogeneous susceptible populations and how it impacts the control strategies. For this purpose, we establish two COVID-19 epidemic models with heterogeneous susceptible populations based on different assumptions for infectious period: the first one is an exponential distribution model (EDM), and the other one is a gamma distribution model (GDM); explicit formula of peak time of the EDM is presented via our analytical approach. By data fitting with the COVID-19 (Omicron) epidemic in Spain and Norway, it seems that Spain is more suitable for EDM while Norway is more suitable for GDM. Finally, we use EDM and GDM to evaluate the impaction of control strategies such as reduction of transmission rates, and increase of primary course rate (PCR) and booster dose rate (BDR). [ABSTRACT FROM AUTHOR]

Simple Summary: The coronavirus disease (COVID-19) pandemic has increased morbidity and mortality in the general population. Patients with cancer have immune dysfunction due to the use of immunosuppressive agents, poor nutritional status, or the direct effects of the tumor on the reactivity of the immune system, making oncological patients more susceptible to severe disease and death. In this systematic review and meta-analysis, we evaluated whether lung cancer increases the risk of severe COVID-19 and the risk of dying from the disease. We found that mortality in patients with lung cancer was significantly higher than that in control patients (HR = 2.00 [95%CI 1.52, 2.63], p < 0.01) or with other malignancies (HR = 1.91 [95%CI 1.53, 2.39], p < 0.01). In addition, we also observed a higher risk of severe infection in patients with lung cancer (HR = 1.47 [95%CI 1.06, 2.03], p = 0.02). We suggest that, in this setting, vaccine use may be considered a useful and mandatory measure to save lives. Introduction: The outbreak of COVID-19 poses an unprecedented challenge to global public health. Patients with cancer are at a higher risk during the SARS-CoV-2 pandemic. Patients with lung cancer and COVID-19 were compared to those without cancer and those with other malignancies for the main outcome of this study. The aim of this study was to evaluate the differences in susceptibility, disease severity, and mortality between lung cancer patients and the general population. Methods: Using PRISMA reporting guidelines, we conducted a systematic review and meta-analysis of the published literature. The Cochrane Library database, PubMed, EMBASE, and PubMed Central were comprehensively searched for published papers until 31 May 2022. A pooled risk ratio (OR) with 95% CI was presented as the result of this meta-analysis. Results: We included 29 studies involved 21,257 patients with lung cancer and SARS-CoV-2 infection. Analysis data showed that mortality in patients with lung cancer was significantly higher than that in patients without cancer (HR = 2.00 [95%CI 1.52, 2.63], p < 0.01) or with other malignancies (HR = 1.91 [95%CI 1.53, 2.39], p < 0.01). In addition, we also observed a higher risk of severe infection in terms of life-threatening or required ICU admission/mechanical ventilation for lung cancer patients (HR = 1.47 [95%CI 1.06, 2.03], p = 0.02) than for patients with no cancer or other malignancies. Regarding lung cancer as a risk factor for acquiring SARS-CoV-2 infection, we could not reach statistical significance (hazard ratio [HR] =2.73 [95%CI 0.84, 8.94], p = 0.1). Conclusion: Lung cancer represents an important comorbidity and modifies COVID-19 prognosis in terms of disease severity and mortality. More patients experience severe or even fatal events. Considering their inherent fragility, patients with lung cancer, and generally all oncological populations, should be treated more carefully during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

In this paper, we hypothesize that it is possible to localize image regions of preclinical tumors in a Chest X-ray (CXR) image by a weakly-supervised training of a survival prediction model using a dataset containing CXR images of healthy patients and their time-to-death label. These visual explanations can empower clinicians in early lung cancer detection and increase patient awareness of their susceptibility to the disease. To test this hypothesis, we train a censor-aware multi-class survival prediction deep learning classifier that is robust to imbalanced training, where classes represent quantized number of days for time-to-death prediction. Such multi-class model allows us to use post-hoc interpretability methods, such as Grad-CAM, to localize image regions of preclinical tumors. For the experiments, we propose a new benchmark based on the National Lung Cancer Screening Trial (NLST) dataset to test weakly-supervised preclinical tumor localization and survival prediction models, and results suggest that our proposed method shows state-of-the-art C-index survival prediction and weakly-supervised preclinical tumor localization results. To our knowledge, this constitutes a pioneer approach in the field that is able to produce visual explanations of preclinical events associated with survival prediction results. • First weakly-supervised survival prediction method to localize preclinical tumors. • State-of-the-art survival time prediction results on the NLST dataset. • Innovative explainable censor-aware multi-class survival prediction. • Innovative survival prediction robust to imbalanced time-to-death distribution. • New benchmark for explainable preclinical survival prediction using the NLST dataset. [ABSTRACT FROM AUTHOR]

Context: Migration is one of the most politically pressing issues of the 21st century but migrant health remains an under‐researched area. The International Collaboration for Participatory Health Research (ICPHR) working group on migration developed this position statement to address opportunities and challenges in relation to migrant health. It aims to contribute to a shift from a deficit model that sees migrants as passively affected by policies to their reconceptualization as citizens who are engaged in the co‐creation of solutions. Methods: This paper examines the opportunities and challenges posed by the use of PHR with migrants. It draws on a broad literature to provide examples of successful PHR with migrants and highlights critical issues for consideration. Findings: Successful initiatives illustrate the value of engaging migrants in the definition of the research agenda, the design and implementation of health interventions, the identification of health‐protective factors and the operationalization and validation of indicators to monitor progress. Within increasingly super diverse contexts, fragmented community landscapes that are not necessarily constructed along ethnicity traits, inadequate structures of representation, local tensions and operational barriers can hamper meaningful PHR with migrants. Conclusion: For each research context, it is essential to gauge the 'optimal' level and type of participation that is more likely to leverage migrants' empowerment. The development of Monitoring and Evaluation tools and methodological strategies to manage inter‐stakeholder discrepancies and knowledge translation gaps are steps in this direction. Patient or public contribution: This paper draws from contributions of migrant populations and other stakeholders to policymaking. [ABSTRACT FROM AUTHOR]

Neuromyelitis Optica and Multiple Sclerosis are idiopathic inflammatory demyelinating diseases of the central nervous system that currently are considered distinct autoimmune diseases, so differences in genetic susceptibility would be expected. This study aimed to investigate the HLA association with Neuromyelitis Optica by a systematic review with meta-analysis. The STROBE instrument guided research paper assessments. Thirteen papers published between 2009 and 2020 were eligible. 568 Neuromyelitis Optica patients, 41.4% Asians, 32.4% Latin Americans and 26.2% Europeans were analyzed. Only alleles of the DRB1 locus were genotyped in all studies. Neuromyelitis Optica patients have 2.46 more chances of having the DRB1*03 allelic group than controls. Ethnicity can influence genetic susceptibility. The main HLA association with Neuromyelitis Optica was the DRB1*03:01 allele in Western populations and with the DPB1*05:01 allele in Asia. Differences in the Multiple Sclerosis and Neuromyelitis Optica genetic susceptibility was confirmed in Afro descendants. The DRB1*03 allelic group associated with Neuromyelitis Optica has also been described in other systemic autoimmune diseases. [ABSTRACT FROM AUTHOR]

Background: This paper aims to assess the presence of gender differences in medication use and mortality in a cohort of patients affected exclusively by hypertension, in 193 municipalities in the Lombardy Region (Northern Italy), including Milan's metropolitan area. Methods: A retrospective cohort study was conducted (N = 232,507) querying administrative healthcare data and the Register of Causes of Death. Hypertensive patients (55.4% women; 44.6% men) in 2017 were identified; gender differences in medication use (treatment, 80% compliance) and deaths (from all causes and CVDs) were assessed at two-year follow-ups in logistic regression models adjusted for age class, census-based deprivation index, nationality, and pre-existing health conditions. Models stratified by age, deprivation index, and therapeutic compliance were also tested. Results: Overall, women had higher odds of being treated, but lower odds of therapeutic compliance, death from all causes, and death from CVDs. All the outcomes had clear sex differences across age classes, though not between different levels of deprivation. Comparing patients with medication adherence, women had lower odds of death from all causes than men (with a narrowing protective effect as age increased), while no gender differences emerged in non-compliant patients. Conclusions: Among hypertensive patients, gender differences in medication consumption and mortality have been found, but the extent to which these are attributable to a female socio-cultural disadvantage is questionable. The findings reached, with marked age-dependent effects in the outcomes investigated, suggest a prominent role for innate sex differences in biological susceptibility to the disease, whereby women would take advantage of the protective effects of their innate physiological characteristics, especially prior to the beginning of menopause. [ABSTRACT FROM AUTHOR]

Summary: Background: Infection with Staphylococcus aureus was initially considered a major problem in hospitals, but over the last few decades the incidence of community-acquired infection has also increased. Paper currency has recently been identified as another mode of spread by which community-acquired S. aureus infection may be transmitted, since paper currency is frequently transferred from one person to another. In the present study, S. aureus strains were isolated from paper currency and screened to detect virulence-associated genes. Methods: Paper currency was collected randomly from operators in mutton shops, vegetable shops, hospitals, medical stores, snacks corners, and restaurants in the two cities of India, Dehradun and Delhi. Samples were screened for pathogenic S. aureus by various biochemical assays. Three isolates were used to study the survival of S. aureus on paper currency. Virulence genes were amplified by PCR. Antibiotic susceptibility was determined against nine antibiotics by the disk diffusion method. Results: Sixty-seven isolates of Staphylococcus aureus were isolated from paper currency from the two Indian cities. The maximum number of isolates was recovered from hospitals, followed by mutton shops, and the minimum from restaurants. The test isolates could survive on paper currency for eight days under in vitro conditions (27°C temperature and 30% relative humidity). A set of four virulence genes viz. cna (16 isolates), icaA (19 isolates), hlg (21 isolates), and sdrE (18 isolates) was amplified using gene-specific primers. Only eight isolates possessed all four virulence genes. Antimicrobial susceptibility tests showed that those isolates having all the tested virulence genes were more resistant. Conclusions: This study clearly suggests that paper currency can serve as a carrier for the spread of resistant bacterial pathogens. [Copyright &y& Elsevier]

Structural variation (SV) is an important type of genome variation and confers susceptibility to human cancer diseases. Systematic analysis of SVs has become a crucial step for the exploration of mechanisms and precision diagnosis of cancers. The central point is how to accurately detect SV breakpoints by using next-generation sequencing (NGS) data. Due to the cooccurrence of multiple types of SVs in the human genome and the intrinsic complexity of SVs, the discrimination of SV breakpoint types is a challenging task. In this paper, we propose a convolutional neural network- (CNN-) based approach, called svBreak, for the detection and discrimination of common types of SV breakpoints. The principle of svBreak is that it extracts a set of SV-related features for each genome site from the sequencing reads aligned to the reference genome and establishes a data matrix where each row represents one site and each column represents one feature and then adopts a CNN model to analyze such data matrix for the prediction of SV breakpoints. The performance of the proposed approach is tested via simulation studies and application to a real sequencing sample. The experimental results demonstrate the merits of the proposed approach when compared with existing methods. Thus, svBreak can be expected to be a supplementary approach in the field of SV analysis in human tumor genomes. [ABSTRACT FROM AUTHOR]

Background: As the vector-borne diseases tick-borne encephalitis (TBE) and Lyme borreliosis (LB) are common in Germany and transmitted by tick bites, the aim of this study was to assess differences in the number of tick bites in various professions and regions across southern Germany to evaluate the differences in tick-associated risk.Materials and Methods: The analysis is based on three cross-sectional studies that were conducted in 2016 and 2017 in two real-life settings and in one medical setting in Bavaria. All participants filled in a paper-based questionnaire about their history with tick bites. Only adult participants (≥ 18 years) were included in this study.Results: Overall, 3503 individuals (mean age 50.8 ± 15.2 years, median age 53.0 ± 12.2 years, 54.0% female) were included. Of these, 50% worked in an outdoor profession and 56% lived in environs. Around 70% of participants reported at least one previous tick bite. In comparison to indoor workers, forestry workers (OR = 2.50; 95% CI: 1.10-5.68) had the highest risk for a tick bite followed by farmers (OR = 1.22; 95% CI: 1.01-1.47). Furthermore, people living in rural areas (OR = 1.97, 95% CI:1.49-2.59) and environs (OR = 1.98, 95% CI: 1.54-2.55) were twice as likely to have a previous tick bite than people living in urban areas. In general, slightly more tick bites were reported by people living in eastern Bavaria.Conclusion: Rising numbers of TBE and LB indicate the need for further prevention strategies, which should focus on outdoor professions with a higher risk and people living in environs and rural areas. [ABSTRACT FROM AUTHOR]

Asthma is a chronic inflammatory disease of the respiratory tract that has become a public health problem in various countries. Referring to the Global Initiative for Asthma, the prevalence of asthma continues to increase especially in children. Coronavirus Disease 2019 (COVID-19) is an infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that has declared a pandemic by the world health organization on March 2020. For many years, it has been known that people with asthma have a worse impact on respiratory viral infections. Asthma has been listed by the centers for disease control and prevention as one of the risk factors for COVID-19, although several studies have different results. SARS-CoV-2 utilizes angiotensin-converting enzyme 2 (ACE2) as its cellular receptor, and it has been known that the expression of the ACE2 receptor is reduced in asthma patients. This reduced expression could also be accounted from the therapy of asthma. This paper aims to discuss the pathophysiology of asthma and COVID-19 and the susceptibility of asthma patients in contracting COVID-19. [ABSTRACT FROM AUTHOR]

Background: In follow-up studies, the occurrence of the intermediate event may influence the risk of the outcome of interest. Existing methods estimate the effect of the intermediate event by including a time-varying covariate in the outcome model. However, the insusceptible fraction to the intermediate event in the study population has not been considered in the literature, leading to effect estimation bias due to the inaccurate dataset.Methods: In this paper, we propose a new effect estimation method, in which the susceptible subpopulation is identified firstly so that the estimation could be conducted in the right population. Then, the effect is estimated via the extended Cox regression and landmark methods in the identified susceptible subpopulation. For susceptibility identification, patients with observed intermediate event time are classified as susceptible. Based on the mixture cure model fitted the incidence and time of the intermediate event, the susceptibility of the patient with censored intermediate event time is predicted by the residual intermediate event time imputation. The effect estimation performance of the new method was investigated in various scenarios via Monte-Carlo simulations with the performance of existing methods serving as the comparison. The application of the proposed method to mycosis fungoides data has been reported as an example.Results: The simulation results show that the estimation bias of the proposed method is smaller than that of the existing methods, especially in the case of a large insusceptible fraction. The results hold for small sample sizes. Besides, the estimation bias of the new method decreases with the increase of the covariates, especially continuous covariates, in the mixture cure model. The heterogeneity of the effect of covariates on the outcome in the insusceptible and susceptible subpopulation, as well as the landmark time, does not affect the estimation performance of the new method.Conclusions: Based on the pre-identification of the susceptible, the proposed new method could improve the effect estimation accuracy of the intermediate event on the outcome when there is an insusceptible fraction to the intermediate event in the study population. [ABSTRACT FROM AUTHOR]

Background and Aim: Strangle in the horses is the commonest and the most significant infectious disease. An antibiotic of the first choice, commonly Penicillin, is used for antimicrobial therapy. Due to side effects and resistance against used antibiotics, interest in novel antimicrobial substances from other sources, including herbal medicine as safe agents has been raised. This study evaluated the antibacterial susceptibility profile of Streptococcus equi subsp equi in the confrontation of Trans-cinnamaldehyde, 1, 8 Cineole, and Pulegone on bacterial pathogens isolated from the horse. Materials and Methods: Two hundred clinically isolates were studied by the single disk method to Ampicillin, Ciprofloxacin, Trimethoprim sulfamethoxazole, Gentamicin, Enrofloxacin, Chloramphenicol, Azithromycin, Cefotaxime, Oxytetracycline, Erythromycin, and Penicillin. Paper discs were prepared by impregnation in 10 μL essential oils main compounds (EOMC). The antibacterial activities of Trans-cinnamaldehyde, 1, 8 Cineole, and Pulegone were evaluated by microbroth dilution and disk diffusion methods against isolates of S. equi. Results & Conclusion: All the isolates were resistant to Trimethoprim-sulfamethoxazole and Cefotaxime. The maximum growth inhibition zone was related to Oxytetracycline and Ampicillin. The growth inhibition zone diameter was 30 mm, 20 mm, and 26 mm for Trans-cinnamaldehyde, Pulegone, and 1, 8 Cineole, respectively. The results of the Minimum inhibitory concentrations (MICs) and Minimum Bactericidal Concentrations (MBCs) showed that Trans-cinnamaldehyde had the highest antibacterial activity compared to other EOMC against S. equi. This study indicated that Trans-cinnamaldehyde, 1, 8 Cineole, and Pulegone revealed antibacterial properties; therefore, these main constituents of the medicinal plant could be a safe candidate for the new antibacterial products. [ABSTRACT FROM AUTHOR]

This paper outlines the relationship between Borderline Personality Disorder (BPD) and the traumatic experiences one may face in their life. In doing so, the paper assesses the relationship between trauma and each of the core characteristics of BPD: disturbed emotion and cognition, behaviour dysregulation, and interpersonal turmoil. The goal of this paper is to present a thorough review of the literature detailing how traumatic experiences such as neglect, assault, and abuse, may act as a trigger, activating a predisposition towards the development of BPD. [ABSTRACT FROM AUTHOR]

A vaccination strategy based on the state feedback control theory is proposed. The objective is to fight against the propagation of an infectious disease within a host population. This propagation is modelled by means of a SISV (susceptible-infectious-susceptible-vaccinated) epidemic model with a time-varying whole population and with a mortality directly associated with the disease. The vaccination strategy adds four free-design parameters, with three of them being the feedback gains of the vaccination control law. The other one is used to switch off the vaccination if the proportion of susceptible individuals is smaller than a prescribed threshold. The paper analyses the positivity of such a model under the proposed vaccination strategy as well as the conditions for the existence of the different equilibrium points of its normalized model. The fact that an appropriate adjustment of the control gains avoids the existence of endemic equilibrium points in the normalized SISV model while guaranteeing the existence of a unique disease-free equilibrium point being globally exponentially stable is proved. This is a relevant novelty dealt with in this paper. The persistence of the infectious disease within a host population irrespective of the growing properties of the whole population can be avoided in this way. Such theoretical results are mathematically proved and, also, they are illustrated by means of simulation examples. Moreover, the performance of the proposed vaccination strategy in several real situations is studied in some simulation examples. One of them deals with the presence of uncertainties, which affects the synthesis of the vaccination control law, in the measures of the subpopulations of the model. [ABSTRACT FROM AUTHOR]

The article highlights the study by Paul Elliott and colleagues which investigates the causes of high blood pressure. It relates that Elliott and colleagues have combined information about environmental influences with metabolic profiling, in which they gathered details about diet, alcohol, drug and supplement use from individuals aged between 40 and 59. It notes that the researchers have analysed the amounts of certain urinary constituents and found links between this urinary constituent and a person's diet and blood pressure.

Background: Genetic testing is widely used in evaluating a patient's predisposition to hereditary diseases. In the case of cancer, when a functionally impactful mutation (i.e. genetic variant) is identified in a disease-relevant gene, the patient is at elevated risk of developing a lesion in their lifetime. Unfortunately, as the rate and coverage of genetic testing has accelerated, our ability to assess the functional status of new variants has fallen behind. Therefore, there is an urgent need for more practical, streamlined and cost-effective methods for classifying variants. Results: To directly address this issue, we designed a new approach that uses alterations in protein subcellular localization as a key indicator of loss of function. Thus, new variants can be rapidly functionalized using high-content microscopy (HCM). To facilitate the analysis of the large amounts of imaging data, we developed a new software toolkit, named MAPS for machine-assisted phenotype scoring, that utilizes deep learning to extract and classify cell-level features. MAPS helps users leverage cloud-based deep learning services that are easy to train and deploy to fit their specific experimental conditions. Model training is code-free and can be done with limited training images. Thus, MAPS allows cell biologists to easily incorporate deep learning into their image analysis pipeline. We demonstrated an effective variant functionalization workflow that integrates HCM and MAPS to assess missense variants of PTEN, a tumor suppressor that is frequently mutated in hereditary and somatic cancers. Conclusions: This paper presents a new way to rapidly assess variant function using cloud deep learning. Since most tumor suppressors have well-defined subcellular localizations, our approach could be widely applied to functionalize variants of uncertain significance and help improve the utility of genetic testing. [ABSTRACT FROM AUTHOR]

The article reports on the identification of tetherin, a protein factor that stops human immunodeficiency virus-1 (HIV) stuck to surface of human cells and unable to spread. Virologist Paul Bieniasz at the Aaron Diamond AIDS Research Center and Laboratory of Retrovirology at the Rockefeller University in New York investigated cell-surface proteins that might keep to HIV-1 in the absence of viral protein U (VPU). It is said that there is much to learn about tetherin for there are hints that it has broad antiviral activity. Moreover, there is a need for investigations whether genetic variation in tetherin might affect susceptibility to HIV infection.

The existing studies have shown that miRNAs are related to human diseases by regulating gene expression. Identifying miRNA association with diseases will contribute to diagnosis, treatment, and prognosis of diseases. The experimental identification of miRNA-disease associations is time-consuming, tremendously expensive, and of high-failure rate. In recent years, many researchers predicted potential associations between miRNAs and diseases by computational approaches. In this paper, we proposed a novel method using deep collaborative filtering called DCFMDA to predict miRNA-disease potential associations. To improve prediction performance, we integrated neural network matrix factorization (NNMF) and multilayer perceptron (MLP) in a deep collaborative filtering framework. We utilized known miRNA-disease associations to capture miRNA-disease interaction features by NNMF and utilized miRNA similarity and disease similarity to extract miRNA feature vector and disease feature vector, respectively, by MLP. At last, we merged outputs of the NNMF and MLP to obtain the prediction matrix. The experimental results indicate that compared with other existing computational methods, our method can achieve the AUC of 0.9466 based on 10-fold cross-validation. In addition, case studies show that the DCFMDA can effectively predict candidate miRNAs for breast neoplasms, colon neoplasms, kidney neoplasms, leukemia, and lymphoma. [ABSTRACT FROM AUTHOR]

The existing studies have shown that miRNAs are related to human diseases by regulating gene expression. Identifying miRNA association with diseases will contribute to diagnosis, treatment, and prognosis of diseases. The experimental identification of miRNA-disease associations is time-consuming, tremendously expensive, and of high-failure rate. In recent years, many researchers predicted potential associations between miRNAs and diseases by computational approaches. In this paper, we proposed a novel method using deep collaborative filtering called DCFMDA to predict miRNA-disease potential associations. To improve prediction performance, we integrated neural network matrix factorization (NNMF) and multilayer perceptron (MLP) in a deep collaborative filtering framework. We utilized known miRNA-disease associations to capture miRNA-disease interaction features by NNMF and utilized miRNA similarity and disease similarity to extract miRNA feature vector and disease feature vector, respectively, by MLP. At last, we merged outputs of the NNMF and MLP to obtain the prediction matrix. The experimental results indicate that compared with other existing computational methods, our method can achieve the AUC of 0.9466 based on 10-fold cross-validation. In addition, case studies show that the DCFMDA can effectively predict candidate miRNAs for breast neoplasms, colon neoplasms, kidney neoplasms, leukemia, and lymphoma. [ABSTRACT FROM AUTHOR]

Introduction. Human ABO blood type antigens exhibit alternative phenotypes and genetically derived glycoconjugate structures that are located on the red cell surface which play an active role in the cells' physiology and pathology. Associations between the blood type and disease have been studied since the early 1900s when researchers determined that antibodies and antigens are inherited. However, due to lack of antigens of some blood groups, there have been some contentious issues with the association between the ABO blood group and vulnerability to certain infectious and noninfectious diseases. Objective. To review different literatures that show the association between ABO blood groups and different diseases. Method. Original, adequate, and recent articles on the same field were researched, and the researcher conducted a comprehensive review on this topic. Thus, taking out critical discussions, not only a descriptive summary of the topic but also contradictory ideas were fully retrieved and presented in a clear impression. In addition, some relevant scientific papers published in previous years were included. The article search was performed by matching the terms blood types/groups with a group of terms related to different diseases. The articles were screened and selected based on the title and abstract presented. Results. The susceptibility to various diseases, such as cancer, cardiovascular diseases, infections and hematologic disorders, cognitive disorders, circulatory diseases, metabolic diseases, and malaria, has been linked with ABO blood groups. Moreover, blood group AB individuals were found to be susceptible to an increased risk of cognitive impairment which was independent of geographic region, age, race, and gender. Disorders such as hypertension, obesity, dyslipidemia, cardiovascular disease (CVD), and diabetes were also more prevalent in individuals with cognitive impairment. Early etiological studies indicated that blood type O has a connection with increased incidence of cholera, plague, tuberculosis infections, and mumps, whereas blood type A is linked with increased incidence of smallpox and Pseudomonas aeruginosa infection; blood type B is also associated with increased incidence of gonorrhea, tuberculosis, and Streptococcus pneumoniae, E. coli, and salmonella infections; and blood type AB is associated with increased incidence of smallpox and E. coli and salmonella infections. Diabetes mellitus, hypercholesterolemia, arterial hypertension, and family history for ischemic heart disease are the most common risk factors for cardiovascular diseases and can be genetically transmitted to offspring. Higher incidence of cancers in the stomach, ovaries, salivary glands, cervix, uterus, and colon/rectum was common in blood type A people than in O type people. The link between the ABO blood type and thromboembolic diseases and bleeding risk are intervened by the glycosyltransferase activity and plasma levels and biologic activity of vWF (Von Willebrand factor), a carrier protein for coagulation factor VIII which is low in O type. Conclusion. Several studies related to the ABO phenotype show that genetically determined human ABO blood groups were correspondingly linked with an increased risk of various infectious and noninfectious diseases. However, further investigations are needed particularly on the molecular level of ABO blood groups and their association with various diseases. [ABSTRACT FROM AUTHOR]

This paper studies the social acceptability and feasibility of a focused protection strategy against coronavirus disease 2019 (COVID-19). We propose a control scheme to develop herd immunity while satisfying the following two basic requirements for a viable policy option. The first requirement is social acceptability: the overall deaths should be minimized for social acceptance. The second is feasibility: the healthcare system should not be overwhelmed to avoid various adverse effects. To exploit the fact that the disease severity increases considerably with age and comorbidities, we assume that some focused protection measures for those high-risk individuals are implemented and the disease does not spread within the high-risk population. Because the protected population has higher severity ratios than the unprotected population by definition, the protective measure can substantially reduce mortality in the whole population and also avoid the collapse of the healthcare system. Based on a simple susceptible-infected-recovered model, social acceptability and feasibility of the proposed strategy are summarized into two easily computable conditions. The proposed framework can be applied to various populations for studying the viability of herd immunity strategies against COVID-19. For Japan, herd immunity may be developed by the proposed scheme if R 0 ≤ 2.0 and the severity rates of the disease are 1/10 times smaller than the previously reported value, although as high mortality as seasonal influenza is expected. [ABSTRACT FROM AUTHOR]

Objective: This paper reports an Elizabethkingia meningoseptica outbreak on a pediatric intensive care unit with emphasis on investigation of outbreak source, infection control interventions, patient characteristics and comparative antimicrobial susceptibility results. Methods: This was an ambidirectional cohort study conducted in a university hospital 20-bed pediatric intensive care unit. Patient ages ranged from 4 to 11 months, with a median age of 9 months. 83% of the patients had severe underlying conditions. Samples from staff and environmental surfaces were obtained to identify a common source of infection. Antimicrobial susceptibility tests of isolated bacteria were done using the disk diffusion method and the Vitek®2 automated system. Results: Environmental surveillance revealed contamination of the water reservoirs of two different mechanical ventilators. In-vitro antimicrobial susceptibility testing results with two different methods (Vitek®2 and disk diffusion) were coherent for most of the investigated antibiotics, but without coherence for ciprofloxacin and levofloxacin. Resistance was found to the relatively new antibiotics ceftaroline and ceftazidime-avibactam. Conclusions:E. meningoseptica is a significant cause of nosocomial infections, with high mortality especially in children. Investigation of the outbreak source and continuation of intensive infection control precautions are vital to handle E. meningoseptica outbreaks in PICUs. Using quinolones according to testing results of automated AST systems may lead to inadequate treatment and foster the selection of resistant strains. [ABSTRACT FROM AUTHOR]

Asthma is a chronic inflammatory disease of the respiratory tract that has become a public health problem in various countries. Referring to the Global Initiative for Asthma, the prevalence of asthma continues to increase especially in children. Coronavirus Disease 2019 (COVID-19) is an infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that has declared a pandemic by the world health organization on March 2020. For many years, it has been known that people with asthma have a worse impact on respiratory viral infections. Asthma has been listed by the centers for disease control and prevention as one of the risk factors for COVID-19, although several studies have different results. SARS-CoV-2 utilizes angiotensin-converting enzyme 2 (ACE2) as its cellular receptor, and it has been known that the expression of the ACE2 receptor is reduced in asthma patients. This reduced expression could also be accounted from the therapy of asthma. This paper aims to discuss the pathophysiology of asthma and COVID-19 and the susceptibility of asthma patients in contracting COVID-19. [ABSTRACT FROM AUTHOR]

Pharmacological anisocoria is a rare but benign condition. This paper presents an eleven-year-old patient with asthma who developed ipratropium bromide-associated anisocoria during nebulizer treatment. Hypotheses regarding the possible causes of anisocoria are discussed and precautions to be taken during treatment are presented. To prevent the development of anisocoria, it was found that it is important to use the appropriate mask during nebulizer treatment, to place the mask on the face properly, and, if possible, to administer drugs by closing the eyes. Further, it is recommended that patients undergo an ophthalmological examination before discharge and that they and their families be informed that the condition is temporary. [ABSTRACT FROM AUTHOR]

Objectives: Distinct diseases prevent endangered huemul deer (Hippocamelus bisulcus) recovery. Fundamental etiological factors include nutriments, a mayor component of habitat quality. Undernutrition affects growth, skeletal development, osteopathology, reproduction and immunocompetence: this paper amplifies data corroborating micro-nutrient deficiencies among huemul. Results: In Argentina, 57% huemul cadavers exhibited osteopathology, with new cases reported here. Recently, 86% live huemul had osteopathology: cranial lesions involved antemortem tooth loss, reducing feeding efficiency and body condition, with starvation deaths. This population had tissues well deficient compared to other cervids, averaging 0.28 ppm selenium, 4.98 ppm copper, whereas for manganese 55% were deficient (2.52 ppm) and 45% adequate (42.79 ppm). Recently, lesions in one Chilean huemul were interpreted to stem from parapoxvirus. That population also has cases with cranial osteopathologies, high disease susceptibility (parapoxvirus, parasitism, foot lesions), crippled antlers, and low density, indicative of marginal habitat and primary etiological factors like undernutrition and immunosuppression. The reported atypical symptoms attributed to parapoxvirus may relate to probable diagnostic limitations, but does support presence of nutritional deficiencies. Patagonia has selenium deficient plants and livestock, including severe muscular dystrophy, and soil levels in extant huemul areas considered very deficient. Moreover, 73% of Chilean huemul were selenium deficient and 64% severely deficient with concomitant cranial osteopathology. [ABSTRACT FROM AUTHOR]

Some certain genetic polymorphisms have been considered to implicate in the pathogenesis and progression of autoimmune diseases and may predispose to an early stage of general autoimmune susceptibility. Recent studies have been conducted to investigate the association between macrophage migration inhibitory factor- (MIF-) 173G/C gene polymorphism and autoimmune diseases; however, the results were not exactly identical. In the present study, a systematic review and meta-analysis of case-control studies was performed to estimate the relationship. A comprehensive search of PubMed, Ebsco, EMbase, WanFang databases and CNKI was done. Odds ratio (ORs) and corresponding 95% confidence intervals (CIs) were combined to pool the effect size. The publication bias was examined by Begg's funnel plots and Egger's test. RevMan 5.3 and STATA 12.0 software were used for statistical processing. 23 papers were included, and the results revealed that MIF-173G/C was significantly associated with an increased risk of autoimmune diseases in five genetic models (recessive genetic model: OR = 1.95 , 95% CI: 1.52-2.50; dominant genetic model: OR = 1.35 , 95% CI: 1.24-1.46; allele model: OR = 1.32 , 95% CI: 1.23-1.41; homozygote model: OR = 1.92 , 95% CI: 1.57-2.35; heterozygote model: OR = 4.92 , 95% CI: 4.03-6.02), whether in Asia, Europe, or North America. Furthermore, subgroup analysis showed an increasing risk in rheumatoid arthritis (RA), ulcerative colitis (UC), Crohn's disease (CD), atopic dermatitis (AD), Henoch-Schonlein purpura (HSP), and Henoch-Schonlein purpura nephritis (HSPN), but it was not related to the susceptibility of autoimmune hepatitis (AIH). Therefore, it could be considered that MIF-173G/C polymorphism could increase the susceptibility of autoimmune diseases, while there may be the discrepancy of disease entity. [ABSTRACT FROM AUTHOR]

Social insect colonies exhibit colony-level phenotypes such as social immunity and task coordination, which are produced by the individual phenotypes. Mapping the genetic basis of such phenotypes requires associating the colony-level phenotype with the genotypes in the colony. In this paper, we examine alternative approaches to DNA extraction, library construction, and sequencing for genome wide association studies (GWAS) of colony-level traits using a population sample of Cataglyphis niger ants. We evaluate the accuracy of allele frequency estimation from sequencing a pool of individuals (pool-seq) from each colony using either whole-genome sequencing or reduced representation genomic sequencing. Based on empirical measurement of the experimental noise in sequenced DNA pools, we show that reduced representation pool-seq is drastically less accurate than whole-genome pool-seq. Surprisingly, normalized pooling of samples did not result in greater accuracy than un-normalized pooling. Subsequently, we evaluate the power of the alternative approaches for detecting quantitative trait loci (QTL) of colony-level traits by using simulations that account for an environmental effect on the phenotype. Our results can inform experimental designs and enable optimizing the power of GWAS depending on budget, availability of samples and research goals. We conclude that for a given budget, sequencing un-normalized pools of individuals from each colony provides optimal QTL detection power. Author summary: Genomic mapping techniques are used to map phenotypes to genotypes. Mapping is of general interest in any biological system, including fundamental studies of biological traits, clinical studies of genetic predisposition to disease, and agro- and bio-technological studies of domesticated plants and animals. Typically, such studies associate phenotypic measurements of individuals with their genotypes. Here we evaluate methodological approaches for genomic mapping of phenotypes that are expressed at the level of a group rather than that of individuals. We demonstrate that genomic sequencing of a DNA pool from multiple samples provides increased statistical power within a limited budget. Our results facilitate more efficient use of resources in genomic mapping studies that investigate group-level phenotypes. [ABSTRACT FROM AUTHOR]

In this paper, we consider the impact of heterogeneous susceptibility on disease transmission dynamics, using a simple mathematical model formulated by a system of ordinary differential equations. Our model describes a time-varying immunity level, which is enhanced by reinfection and diminished by waning immunity. Through mathematical analysis, we show that unexpected outbreaks, called delayed outbreaks, occur even when the basic reproduction number is less than one. A reallocation of susceptibility at the individual level, by repeated infections, in the host population induces delayed outbreaks. [ABSTRACT FROM AUTHOR]

Background: Many classification methods have been proposed based on magnetic resonance images. Most methods rely on measures such as volume, the cerebral cortical thickness and grey matter density. These measures are susceptible to the performance of registration and limited in representation of anatomical structure. This paper proposes a two-stage local feature fusion method, in which deformable registration is not desired and anatomical information is represented from moderate scale. Methods: Keypoints are firstly extracted from scale-space to represent anatomical structure. Then, two kinds of local features are calculated around the keypoints, one for correspondence and the other for representation. Scores are assigned for keypoints to quantify their effect in classification. The sum of scores for all effective keypoints is used to determine which group the test subject belongs to. Results: We apply this method to magnetic resonance images of Alzheimer's disease and Parkinson's disease. The advantage of local feature in correspondence and representation contributes to the final classification. With the help of local feature (Scale Invariant Feature Transform, SIFT) in correspondence, the performance becomes better. Local feature (Histogram of Oriented Gradient, HOG) extracted from 16×16 cell block obtains better results compared with 4×4 and 8×8 cell block. Discussion: This paper presents a method which combines the effect of SIFT descriptor in correspondence and the representation ability of HOG descriptor in anatomical structure. This method has the potential in distinguishing patients with brain disease from controls. [ABSTRACT FROM AUTHOR]

This is the first of 2 review papers on genetics and genomics appearing as part of the series on "omics." Genomics pertains to all components of an organism's genes, whereas genetics involves analysis of a specific gene or genes in the context of heredity. The paper provides introductory comments, describes the basis of human genetic diversity, and addresses the phenotypic consequences of genetic variants. Rare variants with large effect sizes are responsible for single-gene disorders, whereas complex polygenic diseases are typically due to multiple genetic variants, each exerting a modest effect size. To illustrate the clinical implications of genetic variants with large effect sizes, 3 common forms of hereditary cardiomyopathies are discussed as prototypic examples of single-gene disorders, including their genetics, clinical manifestations, pathogenesis, and treatment. The genetic basis of complex traits is discussed in a separate paper. [ABSTRACT FROM AUTHOR]

In this paper we present a mathematical model for the transmission dynamics of Contagious Bovine Pleuropneumonia (CBPP) by considering antibiotic treatment and vaccination. The model is comprised of susceptible, vaccinated, exposed, infectious, persistently infected, and recovered compartments. We analyse the model by deriving a formula for the control reproduction number Rc and prove that, for Rc<1, the disease free equilibrium is globally asymptotically stable; thus CBPP dies out, whereas for Rc>1, the unique endemic equilibrium is globally asymptotically stable and hence the disease persists. Thus, Rc=1 acts as a sharp threshold between the disease dying out or causing an epidemic. As a result, the threshold of antibiotic treatment is αt⁎=0.1049. Thus, without using vaccination, more than 85.45% of the infectious cattle should receive antibiotic treatment or the period of infection should be reduced to less than 8.15 days to control the disease. Similarly, the threshold of vaccination is ρ⁎=0.0084. Therefore, we have to vaccinate at least 80% of susceptible cattle in less than 49.5 days, to control the disease. Using both vaccination and antibiotic treatment, the threshold value of vaccination depends on the rate of antibiotic treatment, αt, and is denoted by ραt. Hence, if 50% of infectious cattle receive antibiotic treatment, then at least 50% of susceptible cattle should get vaccination in less than 73.8 days in order to control the disease. [ABSTRACT FROM AUTHOR]

This paper discusses the concepts of vulnerability and susceptibility and their relevance for understanding and tackling health inequalities. Tackling socioeconomic inequalities in health is based on an understanding of how an individual's social position influences disease risk. Conceptually, there are two possible mechanisms (not mutually exclusive): there is either some cause(s) of disease that are unevenly distributed across socioeconomic groups (differential exposure) or the effect of some cause(s) of disease differs across groups (differential effect). Since differential vulnerability and susceptibility are often used to denote the latter, we discuss these concepts and their current use and suggest an epidemiologically relevant distinction. The effect of social position can thus be mediated by causes that are unevenly distributed across social groups and/or interact with social position. Recent improvements in the methodology to estimate mediation and interaction have made it possible to calculate measures of relevance for setting targets and priorities in policy for health equity which include both mechanisms, i.e. equalize exposure or equalize effects. We finally discuss the importance of differential susceptibility and vulnerability for the choice of preventive strategies, including approaches that target high-risk individuals, whole populations and vulnerable groups. [ABSTRACT FROM AUTHOR]

Using drawings to bridge the communication barriers between adults and children, this article looks at examples of fieldwork with socioeconomically disadvantaged young families in Denmark with a parent who has multiple diagnoses. Studies suggest a link between a disadvantaged socioeconomic childhood and a predisposition to illness and disease in later life and that children of ill parents tend to be ill more often and be lonelier than their peers with healthy parents. These findings are underpinned by other studies showing how children's social relations are vital to how they experience childhood and for their current and future health profile. Based on this knowledge, we wanted to study how children from families without a great deal of resources experience their family life but were faced with the dilemma of how to study this phenomenon. Reflection on these experiences shows that drawing is an effective method to facilitate conversations with children about difficult and taboo issues. The method's strength lies in the way it materializes thoughts and feelings, in the way it generates a sense of "community" between the child and the researcher, which is often challenging in ethnographic research involving children. With their drawings, the children were able to express feelings, sentiments, and experiences that were difficult to articulate in words but not equally difficult to recall as a physical and mental experience or to draw on paper. The drawings illustrated a shared desire among the children who took part in the study for normality, routine, and stability in the family. Please note that we emphasize the importance of including other fieldwork data when interpreting drawings and that it is essential to have a solid contextual understanding of the field. [ABSTRACT FROM AUTHOR]

Background: Mosquitoes, being a nuisance species, are considered as one of the most important species in public health control programs due to their role as a vector in mosquito-borne diseases observed in humans and animals. We evaluated the susceptibility status of Culex pipiens collected from northern Izmir, Turkey in 2011–16. Methods: Mosquito larvae, collected from three different locations in northern İzmir, were reared in the laboratory. Adult susceptibility bioassays were performed using the WHO insecticide-impregnated papers including deltamethrin 0.05%, permethrin 0.75%, α-cypermethrin 0.05% and cyfluthrin 0.15%. In addition, adult bioassays were performed after the pre-exposure to piperonyl butoxide (PBO) to determine the contribution of P450 detoxification enzymes to the phenotypic resistance. Results: In all of the three populations, high levels of resistance were observed (mortalities<63%) to all of the four pyrethroids. Different pyrethroids but with the same mode of action can exhibit significantly different phenotypic resistance in a single population. PBO bioassays also showed that P450 detoxification enzymes can have diverse effects on different pyrethroids. Conclusion: Using just one chemical in a class of insecticide can be misleading for resistance studies. [ABSTRACT FROM AUTHOR]

Predicting the population-level effects of an infectious disease intervention that incorporate multiple modes of intervention is complicated by the joint non-linear dynamics of both infection transmission and the intervention itself. In this paper, we consider the sensitivity of Dynamic Optimal Control Profiles (DOCPs) for the optimal joint investment in both a contagiousness and susceptibility-based control of HIV to bio-behavioral, economic, and programmatic assumptions. The DOCP is calculated using recently developed numerical algorithms that allow controls to be represented by a set of piecewise constant functions that maintain a constant yearly budget. Our transmission model assumes multiple stages of HIV infection corresponding to acute and chronic infection and both within- and between-individual behavioral heterogeneity. We parameterize a baseline scenario from a longitudinal study of sexual behavior in MSM and consider sensitivity of the DOCPs to deviations from that baseline scenario. In the baseline scenario, the primary determinant of the dominant control were programmatic factors, regardless of budget. In sensitivity analyses, the qualitative aspects of the optimal control policy were often robust to significant deviation in assumptions regarding transmission dynamics. In addition, we found several conditions in which long-term joint investment in both interventions was optimal. Our results suggest that modeling in the service of decision support for intervention design can improve population-level effects of a limited set of economic resources. We found that economic and programmatic factors were as important as the inherent transmission dynamics in determining population-level intervention effects. Given our finding that the DOCPs were robust to alternative biological and behavioral assumptions it may be possible to identify DOCPs even when the data are not sufficient to identify a transmission model. [ABSTRACT FROM AUTHOR]