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During the COVID-19 pandemic, pneumonia was the leading cause of respiratory failure and death. In addition to SARS-COV-2, it can be caused by several other bacterial and viral agents. Even today, variants of SARS-COV-2 are endemic and COVID-19 cases are common in many places. The symptoms of COVID-19 are highly diverse and robust, ranging from invisible to severe respiratory failure. Current detection methods for the disease are time-consuming and expensive with low accuracy and precision. To address such situations, we have designed a framework for COVID-19 and Pneumonia detection using multiple deep learning algorithms further accompanied by a deployment scheme. In this study, we have utilized four prominent deep learning models, which are VGG-19, ResNet-50, Inception V3 and Xception, on two separate datasets of CT scan and X-ray images (COVID/Non-COVID) to identify the best models for the detection of COVID-19. We achieved accuracies ranging from 86% to 99% depending on the model and dataset. To further validate our findings, we have applied the four distinct models on two more supplementary datasets of X-ray images of bacterial pneumonia and viral pneumonia. Additionally, we have implemented a flask app to visualize the outcome of our framework to show the identified COVID and Non-COVID images. The findings of this study will be helpful to develop an AI-driven automated tool for the cost effective and faster detection and better management of COVID-19 patients. [ABSTRACT FROM AUTHOR]

An unbiased, widely accepted estimate of the rate of occurrence of new cases of autism over time would facilitate progress in understanding the causes of autism. The same may also apply to other disorders. While incidence is a widely used measure of occurrence, birth prevalence—the proportion of each birth year cohort with the disorder—is the appropriate measure for disorders and diseases of early childhood. Studies of autism epidemiology commonly speculate that estimates showing strong increases in rate of autism cases result from an increase in diagnosis rates rather than a true increase in cases. Unfortunately, current methods are not sufficient to provide a definitive resolution to this controversy. Prominent experts have written that it is virtually impossible to solve. This paper presents a novel method, time-to-event birth prevalence estimation (TTEPE), to provide accurate estimates of birth prevalence properly adjusted for changing diagnostic factors. It addresses the shortcomings of prior methods. TTEPE is based on well-known time-to-event (survival) analysis techniques. A discrete survival process models the rates of incident diagnoses by birth year and age. Diagnostic factors drive the probability of diagnosis as a function of the year of diagnosis. TTEPE models changes in diagnostic criteria, which can modify the effective birth prevalence when new criteria take effect. TTEPE incorporates the development of diagnosable symptoms with age. General-purpose optimization software estimates all parameters, forming a non-linear regression. The paper specifies all assumptions underlying the analysis and explores potential deviations from assumptions and optional additional analyses. A simulation study shows that TTEPE produces accurate parameter estimates, including trends in both birth prevalence and the probability of diagnosis in the presence of sampling effects from finite populations. TTEPE provides high power to resolve small differences in parameter values by utilizing all available data points. [ABSTRACT FROM AUTHOR]

Background: Syndromic management is widely used to treat symptomatic sexually transmitted infections in settings without aetiologic diagnostics. However, underlying aetiologies and consequent treatment suitability are uncertain without regular assessment. This systematic review estimated the distribution, trends, and determinants of aetiologies for vaginal discharge, urethral discharge, and genital ulcer in sub-Saharan Africa (SSA). Methods and findings: We searched Embase, MEDLINE, Global Health, Web of Science, and grey literature from inception until December 20, 2023, for observational studies reporting aetiologic diagnoses among symptomatic populations in SSA. We adjusted observations for diagnostic test performance, used generalised linear mixed-effects meta-regressions to generate estimates, and critically appraised studies using an adapted Joanna Briggs Institute checklist. Of 4,418 identified records, 206 reports were included from 190 studies in 32 countries conducted between 1969 and 2022. In 2015, estimated primary aetiologies for vaginal discharge were candidiasis (69.4% [95% confidence interval (CI): 44.3% to 86.6%], n = 50), bacterial vaginosis (50.0% [95% CI: 32.3% to 67.8%], n = 39), chlamydia (16.2% [95% CI: 8.6% to 28.5%], n = 50), and trichomoniasis (12.9% [95% CI: 7.7% to 20.7%], n = 80); for urethral discharge were gonorrhoea (77.1% [95% CI: 68.1% to 84.1%], n = 68) and chlamydia (21.9% [95% CI: 15.4% to 30.3%], n = 48); and for genital ulcer were herpes simplex virus type 2 (HSV-2) (48.3% [95% CI: 32.9% to 64.1%], n = 47) and syphilis (9.3% [95% CI: 6.4% to 13.4%], n = 117). Temporal variation was substantial, particularly for genital ulcer where HSV-2 replaced chancroid as the primary cause. Aetiologic distributions for each symptom were largely the same across regions and population strata, despite HIV status and age being significantly associated with several infection diagnoses. Limitations of the review include the absence of studies in 16 of 48 SSA countries, substantial heterogeneity in study observations, and impeded assessment of this variability due to incomplete or inconsistent reporting across studies. Conclusions: In our study, syndrome aetiologies in SSA aligned with World Health Organization guidelines without strong evidence of geographic or demographic variation, supporting broad guideline applicability. Temporal changes underscore the importance of regular aetiologic re-assessment for effective syndromic management. PROSPERO number: CRD42022348045. Julia Michalow and colleagues estimate the aetiologies and aetiologic distributions of vaginal discharge, urethral discharge, and genital ulcer in sub-Saharan Africa. Author summary: Why was this study done?: Symptom-based case management is common for treating sexually transmitted infections (STIs) in sub-Saharan Africa (SSA). Characterising the infectious aetiologies (causes) of each syndrome is crucial to ensure adequate choice of treatment. Recent comprehensive assessments on the aetiologies for vaginal discharge, urethral discharge, and genital ulcer are lacking in SSA. What did the researchers do and find?: We conducted a systematic review that included 190 studies in 32 SSA countries spanning 1969 and 2022. We accounted for the sensitivity and specificity of different diagnostic tests used across studies and used meta-regression models to estimate the distribution of infections causing each symptom. We determined that the main aetiologies for vaginal discharge were candidiasis (69% of cases in 2015), bacterial vaginosis (50%), chlamydia (16%), and trichomoniasis (13%); for urethral discharge were gonorrhoea (77%) and chlamydia (22%); and for genital ulcer were herpes simplex virus type 2 (HSV-2) (48%) and syphilis (9%). Distributions of infectious aetiologies were similar across regions and population subgroups but changed over time. What do these findings mean?: The findings support the applicability and continued use of World Health Organization guidelines for symptomatic STI management across SSA settings. National STI programmes should re-assess aetiologies regularly due to changes over time. Limitations of the review include that no data were available in 16 of 48 SSA countries, there was large variability in results across studies identified in the review, and certain information of interest was missing or inconsistently reported across studies. [ABSTRACT FROM AUTHOR]

Introduction: Gender Incongruence refers to the discordance between biological sex and gender identity. Although it is possible to find literature reviews about the etiology of Gender Incongruence, almost all of these correspond to non-systematic narrative reviews, so they do not make explicit the methodology used in the collection and analysis of sources, even less its levels of evidence. In order to remedy this, we will conduct a scoping review to answer the question: what are the factors associated with gender incongruence and what level of evidence is there for each factor in the scientific literature? Methods and analysis: We will conduct a scoping review according to the methodology specified in the JBI Manual for Evidence Synthesis (Chapter 11) and the PRISMA extension for scoping reviews (PRISMA-ScR). Four databases will be reviewed to identify papers that match our search criteria, followed by a screening of titles and abstracts, the complete reading of those articles that have not been excluded, and the coding of these using the data extraction instrument developed for this research (see S1 Appendix). Data extracted will be analyzed in terms of frequency counts of factors, types of factors and levels of evidence for each factor. Results will be presented in tabular or diagrammatic forms supported by a narrative summary. Findings: The present review will help to map the factors associated with incongruence between biological sex and gender identity, specifying their levels of evidence. This evidence-based knowledge will be useful for clinicians evaluating gender incongruence, especially given that international guidelines recommend careful assessment of factors that may interfere with the clarity of gender identity development and decision making. [ABSTRACT FROM AUTHOR]

Introduction: Hypertension is a widespread condition when the blood's force on the artery walls is extremely high to develop adverse health effects. This paper aimed to jointly model the longitudinal change of blood pressures (systolic and diastolic) and time to the first remission of hypertensive outpatients receiving treatment. Methods: A retrospective study design was used to collect appropriate data on longitudinal changes in blood pressure and time-to-event from the medical charts of 301 hypertensive outpatients under follow-up at Felege Hiwot referral hospital, Ethiopia. The data exploration was done using summary statistics measures, individual profile plots, Kaplan-Meier plots, and log-rank tests. To get wide-ranging information about the progression, joint multivariate models were employed. Results: A total of 301 hypertensive patients who take treatment was taken from Felege Hiwot referral hospital recorded between Sep. 2018 to Feb. 2021. Of this 153 (50.8%) were male, and 124 (49.2%) were residents from rural areas. About 83(27.6%), 58 (19.3%), 82 (27.2%), and 25 (8.3%) have a history of diabetes mellitus, cardiovascular disease, stroke, and HIV respectively. The median time of hypertensive patients to have first remission time was 11 months. The hazard of the patient's first remission time for males was 0.63 times less likely than the hazard for females. The time to attain the first remission for patients who had a history of diabetes mellitus was 46% lower than for those who had no history of diabetes mellitus. Conclusion: Blood pressure dynamics significantly affect the time to the first remission of hypertensive outpatients receiving treatment. The patients who had a good follow-up, lower BUN, lower serum calcium, lower serum sodium, lower hemoglobin, and take the treatment enalapril showed an opportunity in decreasing their blood pressure. This compels patients to experience the first remission early. Besides, age, patient's history of diabetes, patient's history of cardiovascular disease, and treatment type were the joint determinant factors for the longitudinal change of BP and the first remission time. The Bayesian joint model approach provides specific dynamic predictions, wide-ranging information about the disease transitions, and better knowledge of disease etiology. [ABSTRACT FROM AUTHOR]

Bacillary dysentery is an infectious disease caused by Shigella dysenteriae, which has a seasonal distribution. External environmental factors, including climate, play a significant role in its transmission. This paper identifies climate-related risk factors and their role in bacillary dysentery transmission. Harbin, in northeast China, with a temperate climate, and Quzhou, in southern China, with a subtropical climate, are chosen as the study locations. The least absolute shrinkage and selectionator operator is applied to select relevant climate factors involved in the transmission of bacillary dysentery. Based on the selected relevant climate factors and incidence rates, an AutoRegressive Integrated Moving Average (ARIMA) model is established successfully as a time series prediction model. The numerical results demonstrate that the mean water vapour pressure over the previous month results in a high relative risk for bacillary dysentery transmission in both cities, and the ARIMA model can successfully perform such a prediction. These results provide better explanations for the relationship between climate factors and bacillary dysentery transmission than those put forth in other studies that use only correlation coefficients or fitting models. The findings in this paper demonstrate that the mean water vapour pressure over the previous month is an important predictor for the transmission of bacillary dysentery. [ABSTRACT FROM AUTHOR]

Background: Congenital heart defects (CHDs) are the most common congenital malformations. The aetiology of CHDs is complex. Large cohort studies and systematic reviews and meta-analyses based on these have reported an association between higher risk of CHDs in the offspring and individual maternal metabolic disorders such as obesity, diabetes, hypertension, and preeclampsia, all conditions that can be related to insulin resistance or hyperglycaemia. However, the clinical reality is that these conditions often occur simultaneously. The aim of this review is, in consequence, both to evaluate the existing evidence on the association between maternal metabolic disorders, defined as obesity, diabetes, hypertension, preeclampsia, dyslipidaemia and CHDs in the offspring, as well as the significance of combinations, such as metabolic syndrome, as risk factors. Methods: A systematic literature search of papers published between January 1, 1990 and January 14, 2021 was conducted using PubMed and Embase. Studies were eligible if they were published in English and were case-control or cohort studies. The exposures of interest were maternal overweight or obesity, hypertension, preeclampsia, diabetes, dyslipidaemia, and/or metabolic syndrome, and the outcome of interest was CHDs in the offspring. Furthermore, the studies were included according to a quality assessment score. Results: Of the 2,250 identified studies, 32 qualified for inclusion. All but one study investigated only the individual metabolic disorders. Some disorders (obesity, gestational diabetes, and hypertension) increased risk of CHDs marginally whereas pre-gestational diabetes and early-onset preeclampsia were strongly associated with CHDs, without consistent differences between CHD subtypes. A single study suggested a possible additive effect of maternal obesity and gestational diabetes. Conclusions: Future studies of the role of aberrations of the glucose-insulin homeostasis in the common aetiology and mechanisms of metabolic disorders, present during pregnancy, and their association, both as single conditions and–particularly–in combination, with CHDs are needed. [ABSTRACT FROM AUTHOR]

Many studies have demonstrated the clinical utility and importance of epilepsy gene panel testing to confirm the specific aetiology of disease, enable appropriate therapeutic interventions, and inform accurate family counselling. Previously, SCN9A gene variants, in particular a c.1921A>T p.(Asn641Tyr) substitution, have been identified as a likely autosomal dominant cause of febrile seizures/febrile seizures plus and other monogenic seizure phenotypes indistinguishable from those associated with SCN1A, leading to inclusion of SCN9A on epilepsy gene testing panels. Here we present serendipitous findings of genetic studies that identify the SCN9A c.1921A>T p.(Asn641Tyr) variant at high frequency in the Amish community in the absence of such seizure phenotypes. Together with findings in UK Biobank these data refute an association of SCN9A with epilepsy, which has important clinical diagnostic implications. Author summary: Epilepsy is defined as a tendency to have seizures, affecting around 1:100 people worldwide. Some genetic types of epilepsy can be diagnosed using a test that examines genes that have previously been shown to cause epilepsy when affected by genetic alterations. Identifying the genetic cause of a patient's epilepsy can help determine which treatments are likely to be helpful, provide prognostic information and inform accurate family counselling. The genes that are included in diagnostic epilepsy gene testing panels are decided by reviewing published scientific studies. Previous publications have described an association between the SCN9A gene and forms of epilepsy, leading to inclusion of the SCN9A gene in diagnostic testing panels. In this paper we present the results of our genetic findings and follow-up studies of SCN9A gene alterations in the Amish community and UK Biobank, alongside a fresh appraisal of previous studies investigating the role of SCN9A in epilepsy. Together our findings strongly refute an association between SCN9A and epilepsy. This work has important clinical implications and should lead to the revaluation of SCN9A by expert groups and its' removal from genetic testing panels, preventing future genetic misdiagnosis which may have devastating and sometimes lethal consequences. [ABSTRACT FROM AUTHOR]

Konzo (caused by consumption of improperly processed cassava, Manihot esculenta) and neurolathyrism (caused by prolonged overconsumption of grass pea, Lathyrus sativus) are two distinct non-infectious upper motor neurone diseases with identical clinical symptoms of spastic paraparesis of the legs. They affect many thousands of people among the poor in the remote rural areas in the central and southern parts of Africa afflicting them with konzo in Ethiopia and in the Indian sub-continent with neurolathyrism. Both diseases are toxico-nutritional problems due to monotonous consumption of starchy cassava roots or protein-rich grass pea seeds as a staple, especially during drought and famine periods. Both foods contain toxic metabolites (cyanogenic glycosides in cassava and the neuro-excitatory amino acid b-ODAP in grass pea) that are blamed for theses diseases. The etiology is also linked to the deficiency in the essential sulfur amino acids that protect against oxidative stress. The two diseases are not considered reportable by the World Health Organization (WHO) and only estimated numbers can be found. This paper analyzes research performance and determines scientific interest in konzo and neurolathyrism. A literature search of over 21 years (from 1990 to 2010) shows that in terms of scientific publications there is little interest in these neglected motorneurone diseases konzo and neurolathyrism that paralyze the legs. Comparison is made with HTLV-1/TSP, an infectious disease occurring mainly in Latin America of which the clinical manifestation is similar to konzo and neurolathyrism and requires a differential diagnosis. Our findings emphasize the multidisciplinary nature of studies on these neglected diseases, which however have not really captured the attention of decision makers and project planners, especially when compared with the infectious HTLV-1/TSP. Konzo and neurolathyrism can be prevented by a balanced diet. [ABSTRACT FROM AUTHOR]

Background: Blood-based or urinary biomarkers may play a role in quantifying the future risk of type 2 diabetes (T2D) and in understanding possible aetiological pathways to disease. However, no systematic review has been conducted that has identified and provided an overview of available biomarkers for incident T2D. We aimed to systematically review the associations of biomarkers with risk of developing T2D and to highlight evidence gaps in the existing literature regarding the predictive and aetiological value of these biomarkers and to direct future research in this field. Methods and Findings: We systematically searched PubMed MEDLINE (January 2000 until March 2015) and Embase (until January 2016) databases for observational studies of biomarkers and incident T2D according to the 2009 PRISMA guidelines. We also searched availability of meta-analyses, Mendelian randomisation and prediction research for the identified biomarkers. We reviewed 3910 titles (705 abstracts) and 164 full papers and included 139 papers from 69 cohort studies that described the prospective relationships between 167 blood-based or urinary biomarkers and incident T2D. Only 35 biomarkers were reported in large scale studies with more than 1000 T2D cases, and thus the evidence for association was inconclusive for the majority of biomarkers. Fourteen biomarkers have been investigated using Mendelian randomisation approaches. Only for one biomarker was there strong observational evidence of association and evidence from genetic association studies that was compatible with an underlying causal association. In additional search for T2D prediction, we found only half of biomarkers were examined with formal evidence of predictive value for a minority of these biomarkers. Most biomarkers did not enhance the strength of prediction, but the strongest evidence for prediction was for biomarkers that quantify measures of glycaemia. Conclusions: This study presents an extensive review of the current state of the literature to inform the strategy for future interrogation of existing and newly described biomarkers for T2D. Many biomarkers have been reported to be associated with the risk of developing T2D. The evidence of their value in adding to understanding of causal pathways to disease is very limited so far. The utility of most biomarkers remains largely unknown in clinical prediction. Future research should focus on providing good genetic instruments across consortia for possible biomarkers in Mendelian randomisation, prioritising biomarkers for measurement in large-scale cohort studies and examining predictive utility of biomarkers for a given context. [ABSTRACT FROM AUTHOR]

The objective of this study was to explore the potential causalities of fat mass, nonfat mass and height (henceforth, 'anthropometric measures') with sepsis risk and mortality. We conducted the Mendelian randomization (MR) investigation using genome-wide association study (GWAS) summary statistics of anthropometric measures, sepsis, and sepsis mortality. The GWAS summary data from the UK Biobank was used. Firstly, MR analysis was performed to estimate the causal effect of anthropometric measures on the risk of sepsis. The inverse-variance weighted (IVW) method was utilized as the primary analytical approach, together with weighted median-based method. Cochrane's Q test and MR-Egger intercept test were performed to assess heterogeneity and pleiotropy, respectively. Finally, we performed a series of sensitivity analyses to enhance the precision and veracity of our findings. The IVW method showed that genetically predicted weight-related measures were suggestively linked to an increased risk of sepsis. However, height displayed no causal association with sepsis risk and mortality. Furthermore, weight-related measures also displayed significant MR association with the sepsis mortality, except body nonfat mass and right leg nonfat mass. However, MVMR analysis indicated the observed effects for weight-related measures in the univariable MR analyses are more likely a bias caused by the interrelationship between anthropometric measures. According to the MR-Egger intercept assessment, our MR examination was not influenced by horizontal pleiotropy (all p>0.05). Moreover, the reliability of the estimated causal association was confirmed by the sensitivity analyses. In conclusion, these findings provided vital new knowledge on the role of anthropometric-related measures in the sepsis etiology. [ABSTRACT FROM AUTHOR]

Abnormally widened spatial and temporal binding windows (SBW/TBWs; length of space/time whereby stimuli are considered part of the same percept) are observed in schizophrenia. TBW alterations have been associated with altered sense of agency (hereafter referred to as agency), and an associative relationship between embodiment (body ownership) and agency has been proposed. SBWs/TBWs are investigated separately, but no evidence exists of these being separate in mechanism, system or function. The underlying neural substrate of schizophrenia remains unclear. The literature claims either pro-psychotic or anti-psychotic effects of Δ9-Tetrahydrocannabinol (THC) in patients and healthy individuals, but major support for cannabis in the aetiology of schizophrenia is associative, not causal. To clarify if THC is pro- or anti-psychotic, this single-blind, placebo-controlled within-subjects cross-over study tested several hypotheses. 1) Competing hypotheses that a synthetic THC analogue, Nabilone (NAB, 1–2 mg), would alter measures of agency and embodiment in healthy volunteers (n = 32) similarly, or opposite, to that of in patients with schizophrenia. 2) That there would be significant associations between any NAB-induced alterations in individual agency and embodiment measures in the Projected Hand Illusion (PHI). 3) That there is a unitary spatio-temporal binding window (STBW). A large proportion of individuals did not experience the PHI. Multimodal and bi-directional effects of NAB on the PHI were observed. Evidence of a unitary spatio-temporal binding window (STBW) was observed. NAB widened the STBW in some but narrowed it in others as a function of space and delay. No associations were found between agency and embodiment. [ABSTRACT FROM AUTHOR]

Low serum levels of high-density lipoprotein cholesterol (HDL-C) have been shown to be a risk factor for coronary artery disease independent of low-density lipoprotein cholesterol (LDL-C) in different populations. In this study, we investigated genetic variants through genome-wide association studies to determine their association with HDL-C levels in a sample of 2,700 patients. We identified several SNPs associated with HDL-C levels in the Lebanese population using unadjusted and adjusted by biological factors models. We replicated the association of rs3764261 within CETP with HDL-C levels in the study population, and found other previously unidentified SNPs to be significant at the suggestive level, in both previously identified and unidentified genes. This paper reports the first genome-wide analysis of HDL-C in the Lebanese, Middle Eastern, population and supports the importance of genome-wide association studies across different and minor ethnicities to understand better the etiology of complex human diseases. [ABSTRACT FROM AUTHOR]

For studying cancer and genetic diseases, the issue of identifying high correlation genes from high-dimensional data is an important problem. It is a great challenge to select relevant biomarkers from gene expression data that contains some important correlation structures, and some of the genes can be divided into different groups with a common biological function, chromosomal location or regulation. In this paper, we propose a penalized accelerated failure time model CHR-DE using a non-convex regularization (local search) with differential evolution (global search) in a wrapper-embedded memetic framework. The complex harmonic regularization (CHR) can approximate to the combination and ℓq (1 ≤ q < 2) for selecting biomarkers in group. And differential evolution (DE) is utilized to globally optimize the CHR’s hyperparameters, which make CHR-DE achieve strong capability of selecting groups of genes in high-dimensional biological data. We also developed an efficient path seeking algorithm to optimize this penalized model. The proposed method is evaluated on synthetic and three gene expression datasets: breast cancer, hepatocellular carcinoma and colorectal cancer. The experimental results demonstrate that CHR-DE is a more effective tool for feature selection and learning prediction. [ABSTRACT FROM AUTHOR]

Establishing appropriate heatwave thresholds is important in reducing adverse human health consequences as it enables a more effective heatwave warning system and response plan. This paper defined such thresholds by focusing on the non-linear relationship between heatwave outcomes and meteorological variables as part of an inductive approach. Daily data on emergency department visitors who were diagnosed with heat illnesses and information on 19 meteorological variables were obtained for the years 2011 to 2016 from relevant government agencies. A Multivariate Adaptive Regression Splines (MARS) analysis was performed to explore points (referred to as “knots”) where the behaviour of the variables rapidly changed. For all emergency department visitors, two thresholds (a maximum daily temperature ≥ 32.58°C for 2 consecutive days and a heat index ≥ 79.64) were selected based on the dramatic rise of morbidity at these points. Nonetheless, visitors, who included children and outside workers diagnosed in the early summer season, were reported as being sensitive to heatwaves at lower thresholds. The average daytime temperature (from noon to 6 PM) was determined to represent an alternative threshold for heatwaves. The findings have implications for exploring complex heatwave-morbidity relationships and for developing appropriate intervention strategies to prevent and mitigate the health impact of heatwaves. [ABSTRACT FROM AUTHOR]

The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. We define a disease event to be a biological event with focus on the One Health paradigm. These events are characterized by evidence of infection and or disease condition. We reviewed models that attempted to predict a disease event, not merely its transmission dynamics and we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011). We searched commercial and government databases and harvested Google search results for eligible models, using terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche modeling. After removal of duplications and extraneous material, a core collection of 6,524 items was established, and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. As a result, we systematically reviewed 44 papers, and the results are presented in this analysis. We identified 44 models, classified as one or more of the following: event prediction (4), spatial (26), ecological niche (28), diagnostic or clinical (6), spread or response (9), and reviews (3). The model parameters (e.g., etiology, climatic, spatial, cultural) and data sources (e.g., remote sensing, non-governmental organizations, expert opinion, epidemiological) were recorded and reviewed. A component of this review is the identification of verification and validation (V&V) methods applied to each model, if any V&V method was reported. All models were classified as either having undergone Some Verification or Validation method, or No Verification or Validation. We close by outlining an initial set of operational readiness level guidelines for disease prediction models based upon established Technology Readiness Level definitions. [ABSTRACT FROM AUTHOR]

Background: Urinary tract infections (UTI) are common in under-five children, with significant consequences leading to bacteremia, dehydration, kidney scarring, and renal failure. The incidence of UTI varies with patients' demographics and geographic location. Limited studies have addressed UTI issues, particularly in children. We determined the proportion of UTI, bacterial aetiology, and antimicrobial susceptibility patterns and associated factors among under-five children at the district hospital between March and April 2023 Methods: We conducted a cross-sectional study using a convenient non-probability sampling technique to collect urine samples from participants with signs and symptoms of UTI. Written informed consent was obtained from parents or guardians. We collected Participants' information using a pretested structured questionnaire. Urine samples were processed at the Regional Referral Hospital. All analyses were conducted using STATA version 15.0. We determined the factors associated with UTI using a modified Poisson model multivariable analysis of the modified Poisson model. The results were presented as a prevalence ratio and 95% confidence interval. The level of significance was specified at 0.05. Result: The study recruited 368 under-five children; 194 (52.7%) were males, and the median age (interquartile range) was 24 (13–36) months. Of all, 28.8% (95% CI-24.3–33.6) had culture-confirmed UTI. One hundred and six pathogens were isolated, the majority being Escherichia coli (E. coli), 37 (34.9%), and Staphylococcus aureus (S. aureus), 26 (24.5%). The susceptibility of E. coli to cefepime, piperacillin-tazobactam, nitrofurantoin, and meropenem ranged from 81.1% to 97.3%. S. aureus was most susceptible to nitrofurantoin (96.2%) and ciprofloxacin (92.3%). Multidrug resistance was observed in 33.0% of isolates. The proportion of Methicillin-resistant S. aureus and extended-spectrum beta-lactamases was 23.1% and 25%, respectively. UTI was observed more in patients presenting with vomiting, dysuria, and abdominal pain, patients below 24 months of age, nappy users, and uncircumcised males. Conclusion: Our study found a relatively high proportion of UTI among under-five children associated with vomiting, dysuria, abdominal pain, nappy use, and uncircumcision in males. The pathogens were least susceptible to (trimethoprim-sulfamethoxazole, gentamycin, ampicillin, and penicillin) the commonly used antibiotic. We advocate a thorough clinical analysis to detect the predictors of UTI and a periodic review of empirical treatment of UTI based on the antibiotic susceptibility pattern. [ABSTRACT FROM AUTHOR]

Background: An increasing use of point of care diagnostic tests that exclude malaria, coupled with a declining malaria burden in many endemic countries, is highlighting the lack of ability of many health systems to manage other causes of febrile disease. A lack of knowledge of distribution of these pathogens, and a lack of screening and point-of-care diagnostics to identify them, prevents effective management of these generally treatable contributors to disease burden. While prospective data collection is vital, an untapped body of knowledge already exists in the published health literature. Methods: Focusing on the Mekong region of Southeast Asia, published data from 1986 to 2011 was screened to for frequency of isolation of pathogens implicated in aetiology of non-malarial febrile illness. Eligibility criteria included English-language peer-reviewed studies recording major pathogens for which specific management is likely to be warranted. Of 1,252 identified papers, 146 met inclusion criteria and were analyzed and data mapped. Results: Data tended to be clustered around specific areas where research institutions operate, and where resources to conduct studies are greater. The most frequently reported pathogen was dengue virus (n = 70), followed by Orientia tsutsugamushi and Rickettsia species (scrub typhus/murine typhus/spotted fever group n = 58), Leptospira spp. (n = 35), Salmonella enterica serovar Typhi and Paratyphi (enteric fever n = 24), Burkholderia pseudomallei (melioidosis n = 14), and Japanese encephalitis virus (n = 18). Wide tracts with very little published data on aetiology of fever are apparent. Discussion and Conclusions: This mapping demonstrates a very heterogeneous distribution of information on the causes of fever in the Mekong countries. Further directed data collection to address gaps in the evidence-base, and expansion to a global database of pathogen distribution, is readily achievable, and would help define wider priorities for research and development to improve syndromic management of fever, prioritize diagnostic development, and guide empirical therapy. [ABSTRACT FROM AUTHOR]

Background: Chongqing is the largest municipality and located in Southwestern of China, with over 30 million registered inhabitants. There are few reports regarding the epidemiology of influenza in Chongqing. The objective of the paper is to explore the epidemiology of influenza in Chongqing, in order to provide scientific basis for prevention and control of influenza. Methodology /Principal Findings: From 2011 to 2015, we collected information on influenza-like illness (ILI) patients fulfilling the case definition, and took nasalpharyngeal or throat swabs specimens from ILI cases per week at the 7 sentinel hospitals. Specimens were tested by reverse transcription-polymerase chain reaction(RT-PCR) for influenza. Descriptive epidemiology was applied to analyze the epidemiology and etiology of influenza. A total of 9,696,212 cases were enrolled, of which 111,589 were ILI. Of those 24,868 samples from ILI cases, 13.3% (3,314/24,868) tested positive for influenza virus (65.7% influenza A, 34.1% influenza B, and 0.2% influenza A and B co-infection). Among the influenza A viruses, 71.3% were seasonal influenza A(H3N2) and 28.7% were influenza A(H1N1)pdm09. No cases of seasonal A(H1N1) were detected. The isolation rate was highest in children aged 5–14 years old. Influenza activity consistently peaked during January-March in 2011–2015, and June-July in 2012, 2014 and 2015. Conclusions: Influenza is an important public health problem among ILI patients in Chongqing, especially among school-aged children. It might be beneficial to prioritize influenza vaccination for school-aged children and implement the school-based intervention to prevent and mitigating influenza outbreaks in Chongqing, particularly during the seasonal peaks. [ABSTRACT FROM AUTHOR]

Background: Ethiopia is assumed to have the highest burden of podoconiosis globally, but the geographical distribution and environmental limits and correlates are yet to be fully investigated. In this paper we use data from a nationwide survey to address these issues. Methodology: Our analyses are based on data arising from the integrated mapping of podoconiosis and lymphatic filariasis (LF) conducted in 2013, supplemented by data from an earlier mapping of LF in western Ethiopia in 2008–2010. The integrated mapping used woreda (district) health offices’ reports of podoconiosis and LF to guide selection of survey sites. A suite of environmental and climatic data and boosted regression tree (BRT) modelling was used to investigate environmental limits and predict the probability of podoconiosis occurrence. Principal Findings: Data were available for 141,238 individuals from 1,442 communities in 775 districts from all nine regional states and two city administrations of Ethiopia. In 41.9% of surveyed districts no cases of podoconiosis were identified, with all districts in Affar, Dire Dawa, Somali and Gambella regional states lacking the disease. The disease was most common, with lymphoedema positivity rate exceeding 5%, in the central highlands of Ethiopia, in Amhara, Oromia and Southern Nations, Nationalities and Peoples regional states. BRT modelling indicated that the probability of podoconiosis occurrence increased with increasing altitude, precipitation and silt fraction of soil and decreased with population density and clay content. Based on the BRT model, we estimate that in 2010, 34.9 (95% confidence interval [CI]: 20.2–51.7) million people (i.e. 43.8%; 95% CI: 25.3–64.8% of Ethiopia’s national population) lived in areas environmentally suitable for the occurrence of podoconiosis. Conclusions: Podoconiosis is more widespread in Ethiopia than previously estimated, but occurs in distinct geographical regions that are tied to identifiable environmental factors. The resultant maps can be used to guide programme planning and implementation and estimate disease burden in Ethiopia. This work provides a framework with which the geographical limits of podoconiosis could be delineated at a continental scale. [ABSTRACT FROM AUTHOR]

Epizootic haemorrhagic disease virus (EHDV) may cause severe clinical episodes in some species of deer and sometimes in cattle. Laboratory diagnosis provides a basis for the design and timely implementation of disease control measures. There are seven distinct EHDV serotypes, VP2 coding segment 2 being the target for serotype specificity. This paper reports the development and validation of eight duplex real-time RT-PCR assays to simultaneously amplify the EHDV target (S9 for the pan-EHDV real-time RT-PCR assay and S2 for the serotyping assays) and endogenous control gene Beta-actin. Analytical and diagnostic sensitivity and specificity, inter- and intra-assay variation and efficiency were evaluated for each assay. All were shown to be highly specific and sensitive. [ABSTRACT FROM AUTHOR]

Objectives: Fever of unknown origin (FUO) remains a challenge in clinical practice. Fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is helpful in diagnosing the etiology of FUO. This paper aims to develop a completely automatic classification method based on PET/CT data for the computer-assisted diagnosis of FUO. Methods: We retrospectively analyzed the FDG PET/CT scan of 175 FUO patients, 79 males and 96 females. The final diagnosis of all FUO patients was achieved through pathology or clinical evaluation, including 108 normal patients and 67 FUO patients. CT anatomic information was used to acquire bone functional information from PET images. The skeletal system of FUO patients was classified by analyzing the standardized uptake value (SUV) and the PET index of bone glucose metabolism (PIBGM). The SUV distributions in the bone marrow and the bone cortex were also studied in detail. Results: The SUV and PIBGM of the bone marrow only slightly differed between the FUO patients and normal people, whereas the SUV of whole bone structures and the PIBGM of the bone cortex significantly differed between the normal people and FUO patients. The method detected 43 patients from 67 FUO patients, with sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 64.18%, 95%, 93.48%, 72.73%, and 83.33%, respectively. Conclusion: The experimental results demonstrate that the study can achieve automatic classification of FUO patients by the proposed novel biomarker of PIBGM, which has the potential to be utilized in clinical practice. [ABSTRACT FROM AUTHOR]

Alzheimer’s disease (AD) is a progressive degenerating disease of complex etiology. A variety of risk factors contribute to the chance of developing AD. Lifestyle factors, such as physical, mental and social activity, education, and diet all affect the susceptibility to developing AD. These factors are in turn related to the level of personal income. Lower income usually coincides with lower level of education, lesser mental, leisure—social and physical activity, and poorer diet. In the present paper, we have analyzed the correlation of historical (1929–2011) per capita personal income (PCPI) for all states of the USA with corresponding age-adjusted AD death rates (AADR) for years 2000, 2005 and 2008. We found negative correlations in all cases, the highest one (R ≈ -0.65) for the PCPIs in the year 1970 correlated against the AADRs in 2005. From 1929 to 2005 the R value varies in an oscillatory manner, with the strongest correlations in 1929, 1970, 1990 and the weakest in 1950, 1980, 1998. Further analysis indicated that this oscillatory behavior of R is not artificially related to the economic factors but rather to delayed biological consequences associated with personal income. We conclude that the influence of the income level on the AD mortality in 2005 was the highest in the early years of life of the AD victims. Overall, the income had a significant, lifelong, albeit constantly decreasing, influence on the risk of developing AD. We postulate that the susceptibility of a population to late-onset AD (LOAD) is determined to a large extent by the history of income-related modifiable lifestyle risk factors. Among these risk factors, inappropriate diet has a significant contribution. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is a chronic autoimmune rheumatic disease that can cause painful swelling in the joint lining, morning stiffness, and joint deformation/destruction. These symptoms decrease both quality of life and life expectancy. However, if RA can be diagnosed in the early stages, it can be controlled with pharmacotherapy. Although many studies have examined the possibility of early assessment and diagnosis, few have considered the relationship between significant risk factors and the early assessment of RA. In this paper, we present a novel framework for early RA assessment that utilizes data preprocessing, risk pattern mining, validation, and analysis. Under our proposed framework, two risk patterns can be discovered. Type I refers to well-known risk patterns that have been identified by existing studies, whereas Type II denotes unknown relationship risk patterns that have rarely or never been reported in the literature. These Type II patterns are very valuable in supporting novel hypotheses in clinical trials of RA, and constitute the main contribution of this work. To ensure the robustness of our experimental evaluation, we use a nationwide clinical database containing information on 1,314 RA-diagnosed patients over a 12-year follow-up period (1997–2008) and 965,279 non-RA patients. Our proposed framework is employed on this large-scale population-based dataset, and is shown to effectively discover rich RA risk patterns. These patterns may assist physicians in patient assessment, and enhance opportunities for early detection of RA. The proposed framework is broadly applicable to the mining of risk patterns for major disease assessments. This enables the identification of early risk patterns that are significantly associated with a target disease. [ABSTRACT FROM AUTHOR]

Background: Acute patients presenting with hypotension in the prehospital or emergency department (ED) setting are in need of focused management and knowledge of the epidemiology characteristics might help the clinician. The aim of this review was to address prevalence, etiology and mortality of nontraumatic hypotension (SBP ≤ 90 mmHg) with or without the presence of shock in the prehospital and ED setting. Methods: We performed a systematic literature search up to August 2013, using Medline, Embase, Cinahl, Dare and The Cochrane Library. The analysis and eligibility criteria were documented according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-guidelines) and The Cochrane Collaboration. No restrictions on language, publication date, or status were imposed. We used the Newcastle-Ottawa quality assessment scale (NOS-scale) and the Strengthening the Reporting of Observational studies in Epidemiology (STROBE-statement) to assess the quality. Results: Six observational studies were considered eligible for analysis based on the evaluation of 11,880 identified papers. Prehospital prevalence of hypotension was 19.5/1000 emergency medicine service (EMS) contacts, and the prevalence of hypotensive shock was 9.5-19/1000 EMS contacts with an inhospital mortality of shock between 33 to 52%. ED prevalence of hypotension was 4-13/1000 contacts with a mortality of 12%. Information on mortality, prevalence and etiology of shock in the ED was limited. A meta-analysis was not feasible due to substantial heterogeneity between studies. Conclusion: There is inadequate evidence to establish concise estimates of the characteristics of nontraumatic hypotension and shock in the ED or in the prehospital setting. The available studies suggest that 2% of EMS contacts present with nontraumatic hypotension while 1-2% present with shock. The inhospital mortality of prehospital shock is 33-52%. Prevalence of hypotension in the ED is 1% with an inhospital mortality of 12%. Prevalence, etiology and mortality of shock in the ED are not well described. [ABSTRACT FROM AUTHOR]

Identifying similar diseases could potentially provide deeper understanding of their underlying causes, and may even hint at possible treatments. For this purpose, it is necessary to have a similarity measure that reflects the underpinning molecular interactions and biological pathways. We have thus devised a network-based measure that can partially fulfill this goal. Our method assigns weights to all proteins (and consequently their encoding genes) by using information flow from a disease to the protein interaction network and back. Similarity between two diseases is then defined as the cosine of the angle between their corresponding weight vectors. The proposed method also provides a way to suggest disease-pathway associations by using the weights assigned to the genes to perform enrichment analysis for each disease. By calculating pairwise similarities between 2534 diseases, we show that our disease similarity measure is strongly correlated with the probability of finding the diseases in the same disease family and, more importantly, sharing biological pathways. We have also compared our results to those of MimMiner, a text-mining method that assigns pairwise similarity scores to diseases. We find the results of the two methods to be complementary. It is also shown that clustering diseases based on their similarities and performing enrichment analysis for the cluster centers significantly increases the term association rate, suggesting that the cluster centers are better representatives for biological pathways than the diseases themselves. This lends support to the view that our similarity measure is a good indicator of relatedness of biological processes involved in causing the diseases. Although not needed for understanding this paper, the raw results are available for download for further study at . [ABSTRACT FROM AUTHOR]

Background: The prevalence of asthma and allergic diseases is rising worldwide. Evidence on potential causal pathways of asthma and allergies is growing, but findings have been contradictory, particularly on the interplay between allergic diseases and understudied social determinants of health like migration status. This review aimed at providing evidence for the association between migration status and asthma and allergies, and to explore the mechanisms between migration status and the development of asthma and allergies. Methods and Findings: Systematic review on asthma and allergies and immigration status in accordance with the guidelines set by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The pooled odds ratio (OR) of the prevalence of asthma in immigrants compared to the host population was 0.60 (95% CI 0.45–0.84), and the pooled OR for allergies was 1.01 (95% CI 0.62–1.69). The pooled OR for the prevalence of asthma in first generation versus second generation immigrants was 0.37 (95% CI 0.25–0.58). Comparisons between populations in their countries of origin and those that emigrated vary depending on their level of development; more developed countries show higher rates of asthma and allergies. Conclusions: Our findings suggest a strong influence of the environment on the development of asthma and allergic diseases throughout the life course. The prevalence of asthma is generally higher in second generation than first generation immigrants. With length of residence in the host country the prevalence of asthma and allergic diseases increases steadily. These findings are consistent across study populations, host countries, and children as well as adults. Differences have been found to be significant when tested in a linear model, as well as when comparing between early and later age of migration, and between shorter and longer time of residence. [ABSTRACT FROM AUTHOR]

Objective: Chronic Fatigue (CF) still remains unclear about its etiology, pathophysiology, nomenclature and diagnostic criteria in the medical community. Traditional Chinese medicine (TCM) adopts a unique diagnostic method, namely ‘bian zheng lun zhi’ or syndrome differentiation, to diagnose the CF with a set of syndrome factors, which can be regarded as the Multi-Label Learning (MLL) problem in the machine learning literature. To obtain an effective and reliable diagnostic tool, we use Conformal Predictor (CP), Random Forest (RF) and Problem Transformation method (PT) for the syndrome differentiation of CF. Methods and Materials: In this work, using PT method, CP-RF is extended to handle MLL problem. CP-RF applies RF to measure the confidence level (p-value) of each label being the true label, and then selects multiple labels whose p-values are larger than the pre-defined significance level as the region prediction. In this paper, we compare the proposed CP-RF with typical CP-NBC(Naïve Bayes Classifier), CP-KNN(K-Nearest Neighbors) and ML-KNN on CF dataset, which consists of 736 cases. Specifically, 95 symptoms are used to identify CF, and four syndrome factors are employed in the syndrome differentiation, including ‘spleen deficiency’, ‘heart deficiency’, ‘liver stagnation’ and ‘qi deficiency’. The Results: CP-RF demonstrates an outstanding performance beyond CP-NBC, CP-KNN and ML-KNN under the general metrics of subset accuracy, hamming loss, one-error, coverage, ranking loss and average precision. Furthermore, the performance of CP-RF remains steady at the large scale of confidence levels from 80% to 100%, which indicates its robustness to the threshold determination. In addition, the confidence evaluation provided by CP is valid and well-calibrated. Conclusion: CP-RF not only offers outstanding performance but also provides valid confidence evaluation for the CF syndrome differentiation. It would be well applicable to TCM practitioners and facilitate the utilities of objective, effective and reliable computer-based diagnosis tool. [ABSTRACT FROM AUTHOR]

Cortical oscillatory signals of single and double tremor frequencies act together to cause tremor in the peripheral limbs of patients with Parkinson's disease (PD). But the corticospinal pathway that transmits the tremor signals has not been clarified, and how alternating bursts of antagonistic muscle activations are generated from the cortical oscillatory signals is not well understood. This paper investigates the plausible role of propriospinal neurons (PN) in C3–C4 in transmitting the cortical oscillatory signals to peripheral muscles. Kinematics data and surface electromyogram (EMG) of tremor in forearm were collected from PD patients. A PN network model was constructed based on known neurophysiological connections of PN. The cortical efferent signal of double tremor frequencies were integrated at the PN network, whose outputs drove the muscles of a virtual arm (VA) model to simulate tremor behaviors. The cortical efferent signal of single tremor frequency actuated muscle spindles. By comparing tremor data of PD patients and the results of model simulation, we examined two hypotheses regarding the corticospinal transmission of oscillatory signals in Parkinsonian tremor. Hypothesis I stated that the oscillatory cortical signals were transmitted via the mono-synaptic corticospinal pathways bypassing the PN network. The alternative hypothesis II stated that they were transmitted by way of PN multi-synaptic corticospinal pathway. Simulations indicated that without the PN network, the alternating burst patterns of antagonistic muscle EMGs could not be reliably generated, rejecting the first hypothesis. However, with the PN network, the alternating burst patterns of antagonist EMGs were naturally reproduced under all conditions of cortical oscillations. The results suggest that cortical commands of single and double tremor frequencies are further processed at PN to compute the alternating burst patterns in flexor and extensor muscles, and the neuromuscular dynamics demonstrated a frequency dependent damping on tremor, which may prevent tremor above 8 Hz to occur. [ABSTRACT FROM AUTHOR]

Background: Precise effects of albuminuria and low estimated glomerular filtration rate (eGFR) on cardiovascular mortality, all-cause mortality, and renal events in diabetic patients are uncertain. Materials and Methods: A systematic review was conducted of the literature through MEDLINE, EMBASE, and CINHAL from 1950 to December 2010. Cohort studies of diabetic patients providing adjusted relative risk (RR) of albuminuria and eGFR for risks of cardiovascular mortality, all-cause mortality, and renal events were selected. Two reviewers screened abstracts and full papers of each study using standardized protocol. Results: We identified 31 studies fulfilling the criteria from 6546 abstracts. With regard to the risk of cardiovascular mortality, microalbuminuria (RR 1.76, 95%CI 1.38–2.25) and macroalbuminuria (RR 2.96 95%CI 2.44–3.60) were significant risk factors compared to normoalbuminuria. The same trends were seen in microalbuminuria (RR 1.60, 95%CI 1.42–1.81), and macroalbuminuria (RR 2.64, 95%CI 2.13–3.27) for the risk of all-cause mortality, and also in microalbuminuria (RR 3.21, 95%CI 2.05–5.02) and macroalbuminuria (RR 11.63, 95%CI 5.68–23.83) for the risk of renal events. The magnitudes of relative risks associated with low eGFR along with albuminuria were almost equal to multiplying each risk rate of low eGFR and albuminuria. No significant factors were found by investigating potential sources of heterogeneity using subgroup analysis. Conclusions: High albuminuria and low eGFR are relevant risk factors in diabetic patients. Albuminuria and low eGFR may be independent of each other. To evaluate the effects of low eGFR, intervention, or race, appropriately designed studies are needed. [ABSTRACT FROM AUTHOR]

Background: Acute respiratory infections (ARIs) are the leading cause of children and their leading killer. ARIs are responsible for at least six percent of the world's disability and death. Viruses are one of the most common agents causing ARIs. Few studies on the viral etiology and clinical characteristics of ARIs have been performed in the northwest region of China, including Gansu Province. Methods: Clinical and demographic information and throat swabs were collected from 279 patients from January 1st to December 30st, 2011. Multiplex RT-PCR was performed to detect 16 respiratory viral pathogens. Results: 279 patients were admitted for ARIs. The patients aged from 1 month to 12 years, with the median age of 2 years. Of which, 105 (37.6%) were positive for at least one pathogen. A total of 136 respiratory viral pathogens were identified from the 105 patients. Respiratory syncytial virus (RSV) was the most frequently detected pathogen (26.5%, 36/136), followed by parainfluenza virus (PIV) 1–3 (22.1%, 30/136), human rhinovirus (HRV) (21.3%, 29/136), human coronavirus (CoV) (10.3%, 14/136) and human adenovirus (HAdV) (9.6%, 13/136). Influenza A (Flu A), human metapneumovirus (hMPV) and human bocavirus (BoCA) were found 4.4%, 3.7% and 2.2%, respectively. Influenza B (Flu B) and seasonal influenza A H1N1(sH1N1) were not detected. Single-infections were detected in 30.5% (85/279) of cases. RSV was the most common pathogens in patients under 1 year and showed seasonal variation with peaks during winter and spring. Conclusions: This paper presents data on the epidemiology of viral pathogens associated with ARIs among children in Gansu Province, China. RSV is most frequently detected in our study. The findings could serve as a reference for local CDC in drawing up further plans to prevent and control ARIs. [ABSTRACT FROM AUTHOR]

Depression is a type of complex psychiatric disorder with long-term, recurrent bouts, and its etiology remains largely unknown. Here, an integrated approach utilizing 1H NMR and UPLC-Q-TOF/MS together was firstly used for a comprehensive urinary metabonomics study on chronic unpredictable mild stress (CUMS) treated rats. More than twenty-nine metabolic pathways were disturbed after CUMS treatment and thirty-six potential biomarkers were identified by using two complementary analytical technologies. Among the identified biomarkers, nineteen (10, 11,16, 17, 21–25, and 27–36) were firstly reported as potential biomarkers of CUMS-induced depression. Obviously, this paper presented a comprehensive map of the metabolic pathways perturbed by CUMS and expanded on the multitude of potential biomarkers that have been previously reported in the CUMS model. Four metabolic pathways, including valine, leucine and isoleucine biosynthesis; phenylalanine, tyrosine and tryptophan biosynthesis; tryptophan metabolism; synthesis and degradation of ketone bodies had the deepest influence in the pathophysiologic process of depression. Fifteen potential biomarkers (1–2, 4–6, 15, 18, 20–23, 27, 32, 35–36) involved in the above four metabolic pathways might become the screening criteria in clinical diagnosis and predict the development of depression. Moreover, the results of Western blot analysis of aromatic L-amino acid decarboxylase (DDC) and indoleamine 2, 3-dioxygenase (IDO) in the hippocampus of CUMS-treated rats indicated that depletion of 5-HT and tryptophan, production of 5-MT and altered expression of DDC and IDO together played a key role in the initiation and progression of depression. In addition, none of the potential biomarkers were detected by NMR and LC-MS simultaneously which indicated the complementary of the two kinds of detection technologies. Therefore, the integration of 1H NMR and UPLC-Q-TOF/MS in metabonomics study provided an approach to identify the comprehensive potential depression-related biomarkers and helpful in further understanding the underlying molecular mechanisms of depression through the disturbance of metabolic pathways. [ABSTRACT FROM AUTHOR]

Background: Pastoralists in low-income countries usually live in close proximity to their animals and thus represent an important repository of information about livestock disease. Since wild and domestic animals often mix freely whilst grazing, pastoralists are also able to observe first-hand the diseases that are present in wildlife and as such are key informants in disease outbreaks in sylvatic animals. We report here the findings of the first study of the knowledge and role of Masai pastoralists in mange in wildlife and livestock in Masai Mara, Kenya. Methodology/Principal Findings: In this paper we describe the knowledge of mange accrued by 56 Masai pastoralists in Kenya and how they respond to it in both wildlife and livestock. In total, 52 (93%) pastoralists had a clear idea of the clinical appearance of mange, 13 (23%) understood its aetiology and 37 (66%) knew that mites were the causal agent. Thirty-nine (69%) believed that mange cross-infection between domestic and wild animals occurs, while 48 (85%) had observed mange in domestic animals including sheep (77%), goats (57%), dogs (24%) and cattle (14%). The pastoralists had also observed wild animals infected with mange, above all lions (19%), gazelles (14%), cheetahs (12%) and wildebeests (2%). In 68% of cases Masai pastoralists treat mange infection or apply control measures, most commonly via the topical use of acaricides (29%) and/or the reporting of the outbreak to the veterinary authorities (21%). In the period 2007-2011, Kenya Wildlife Service received 24 warnings of 59 wild animals with mange-like lesions from the Masai Mara pastoralist community. The reported species were cheetah, lion, wild dog, Thomson' gazelle and wildebeest. Conclusion: Masai pastoralists have good knowledge of mange epidemiology and treatment. Their observations and the treatments they apply are valuable in the control of this disease in both wild and domestic animals. [ABSTRACT FROM AUTHOR]

The identification of disease-causing genes is a fundamental challenge in human health and of great importance in improving medical care, and provides a better understanding of gene functions. Recent computational approaches based on the interactions among human proteins and disease similarities have shown their power in tackling the issue. In this paper, a novel systematic and global method that integrates two heterogeneous networks for prioritizing candidate disease-causing genes is provided, based on the observation that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein interactions. In this method, the association score function between a query disease and a candidate gene is defined as the weighted sum of all the association scores between similar diseases and neighbouring genes. Moreover, the topological correlation of these two heterogeneous networks can be incorporated into the definition of the score function, and finally an iterative algorithm is designed for this issue. This method was tested with 10-fold cross-validation on all 1,126 diseases that have at least a known causal gene, and it ranked the correct gene as one of the top ten in 622 of all the 1,428 cases, significantly outperforming a state-of-the-art method called PRINCE. The results brought about by this method were applied to study three multi-factorial disorders: breast cancer, Alzheimer disease and diabetes mellitus type 2, and some suggestions of novel causal genes and candidate disease-causing subnetworks were provided for further investigation. [ABSTRACT FROM AUTHOR]

Background: The aetiological diagnostic of fevers in Laos remains difficult due to limited laboratory diagnostic facilities. However, it has recently become apparent that both scrub and murine typhus are common causes of previous undiagnosed fever. Epidemiological data suggests that scrub typhus would be more common in rural areas and murine typhus in urban areas, but there is very little recent information on factors involved in scrub and murine typhus transmission, especially where they are sympatric - as is the case in Vientiane, the capital of the Lao PDR. Methodology and Principal Findings: We therefore determined the frequency of IgG seropositivity against scrub typhus (Orientia tsutsugamushi) and murine typhus (Rickettsia typhi), as indices of prior exposure to these pathogens, in randomly selected adults in urban and peri-urban Vientiane City (n = 2,002, ⩾35 years). Anti-scrub and murine typhus IgG were detected by ELISA assays using filter paper elutes. We validated the accuracy of ELISA of these elutes against ELISA using serum samples. The overall prevalence of scrub and murine typhus IgG antibodies was 20.3% and 20.6%, respectively. Scrub typhus seropositivity was significantly higher among adults living in the periphery (28.4%) than in the central zone (13.1%) of Vientiane. In contrast, seroprevalence of murine typhus IgG antibodies was significantly higher in the central zone (30.8%) as compared to the periphery (14.4%). In multivariate analysis, adults with a longer residence in Vientiane were at significant greater risk of past infection with murine typhus and at lower risk for scrub typhus. Those with no education, living on low incomes, living on plots of land with poor sanitary conditions, living in large households, and farmers were at higher risk of scrub typhus and those living in neighborhoods with high building density and close to markets were at greater risk for murine typhus and at lower risk of scrub typhus past infection. Conclusions: This study underscores the intense circulation of both scrub and murine typhus in Vientiane city and underlines difference in spatial distribution and risk factors involved in the transmission of these diseases. [ABSTRACT FROM AUTHOR]

Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http:// function.princeton.edu/growthrate. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases are the leading cause of human mortality worldwide. Among the many factors associated with the etiology, incidence, and evolution of such diseases; social and environmental issues constitute an important and often overlooked component. Understanding to a greater extent the scope to which such social determinants of cardiovascular diseases (SDCVD) occur as well as the connections among them would be useful for public health policy making. Here, we will explore the historical trends and associations among the main SDCVD in the published literature. Our aim will be finding meaningful relations among those that will help us to have an integrated view on this complex phenomenon by providing historical context and a relational framework. To uncover such relations, we used a data mining approach to the current literature, followed by network analysis of the interrelationships discovered. To this end, we systematically mined the PubMed/MEDLINE database for references of published studies on the subject, as outlined by the World Health Organization’s framework on social determinants of health. The analyzed structured corpus consisted in circa 1190 articles categorized by means of the Medical Subheadings (MeSH) content-descriptor. The use of data analytics techniques allowed us to find a number of non-trivial connections among SDCVDs. Such relations may be relevant to get a deeper understanding of the social and environmental issues associated with cardiovascular disease and are often overlooked by traditional literature survey approaches, such as systematic reviews and meta-analyses. [ABSTRACT FROM AUTHOR]

Introduction: Coronavirus disease of 2019 (COVID-19) is a global health problem. The impact of chronic liver diseases on the course and outcome of COVID-19 is still the subject of research. The aim of this study was to show the characteristics of COVID-19 patients with chronic liver diseases, and to establish the risk factors for unfavourable outcome. Methods: A retrospective observational study was conducted at the Infectious Disease Clinic in Belgrade, Serbia, and included 80 patients with chronic liver diseases and COVID-19 within a time frame of two years (between 15 March 2020 and 15 March 2022). Characteristics of the affected persons, as well as the risk factors for a fatal outcome, were analyzed. Results: Of the 80 subjects in the study, 23.8% had chronic viral hepatitis, 12.5% autoimmune liver diseases and alcoholic liver disease respectively, 30% had non-alcoholic fatty liver disease, while 11.2% had chronic liver diseases of unknown aetiology. A total of 33.7% had cirrhosis, 6.3% hepatocellular carcinoma and 5% had liver transplants. A total of 92.5% of respondents had pneumonia (21.2% were critically ill). A deterioration of chronic liver disease was registered among 33.7% of patients, and decompensation in 3.8%; 76.3% patients recovered, while 23.7% had a lethal outcome. Risk factors for lethal outcome by univariate analysis were: alcoholic liver disease, cirrhosis, increased transaminases values prior to COVID-19, malignancy, severe pneumonia and dyspnea. In a multivariate analysis, the presence of liver cirrhosis (OR = 69.1, p = 0.001) and severe pneumonia (OR = 22.3, p = 0.006) remained independently predictive for lethal outcome. Conclusion: These findings will help with the evaluation of COVID-19 patients who have chronic liver diseases and will improve their risk stratification. [ABSTRACT FROM AUTHOR]

Lagochilascariasis is a parasitic disease caused by a helminth of the order Ascaroidea, genus Lagochilascaris that comprises 6 species, among which only Lagochilascaris minor Leiper, 1909, is implicated in the human form of the disease. It is remarkable that the majority of cases of human lagochilascariasis in the Americas have been reported in Brazil. The natural definitive hosts of this parasite seem to be wild felines and canines. Lagochilascariasis is mostly a chronic human disease that can persist for several years, in which the parasite burrows into the subcutaneous tissues of the neck, paranasal sinuses, and mastoid. L. minor exhibits remarkable ability to migrate through the tissues of its hosts, destroying even bone tissue. Fatal cases have been described in which the parasite was found in the lungs or central nervous system. Treatment is often palliative, with recurrence of lesions. This paper summarizes the main features of the disease and its etiologic agent, including prevalence, life cycle, clinical course, and treatment. [ABSTRACT FROM AUTHOR]

Lysosomal acid lipase deficiency (LAL-d) is a rare autosomal recessive disease in which LAL activity is almost absent, with consequent massive microvesicular steatosis evolving to cirrhosis and liver failure. We aimed to determine LAL-activity, and to investigate the most common single nucleotide polymorphism (SNP) affecting the LIPA gene and responsible for 50–70% of LAL-d cases (rs116928232 c.894G>A), in patients with cryptogenic cirrhosis. Sixty-three patients with cryptogenic cirrhosis, 88 cirrhotics of known etiology, and 97 healthy subjects were enrolled. LAL-activity was determined in dried-blood-spot (DBS). The c.894G>A mutation was analyzed by pyrosequencing method in SNP mode. LAL-activity was severely reduced in patients with cryptogenic cirrhosis with respect to healthy subjects [0.62 (0.44–0.86) Vs 0.96 (0.75–1.25) nmol/spot/h, p<0.001)], but it was also reduced in known-etiology cirrhotics [0.54 (0.42–0.79) nmol/spot/h, p<0.001 Vs healthy subjects; p = 0.5 Vs cryptogenic cirrhotics]. Fourteen percent of cryptogenic cirrhotics and 20% of known-etiology cirrhotics showed a LAL-activity in the range of heterozygous carriers of LIPA gene mutations (0.15–0.40 nmol/spot/h). However, none of the subjects with reduced LAL-activity carried the c.894G>A SNP except for one patient with HCV cirrhosis. By multivariate analysis, LAL-activity was not associated with age, sex, liver enzymes, liver function or lipid parameters, while it was independently associated with white blood cell (β = 0.2; p<0.01) and platelet (β = 0.4; p<0.001) counts and with the condition of cirrhosis (β = -0.2; p = 0.04). Conclusion: Liver cirrhosis is characterized by a severe acquired reduction of LAL-activity, the precise causes and consequences of which need to be further addressed. DBS-determined lysosomal enzyme activities seem to be affected by white blood cell and platelet counts, and the specificity of these tests can be reduced when applied to determined populations, such as cirrhotics. [ABSTRACT FROM AUTHOR]

Since next-generation sequencing (NGS) has become widely available, large gene panels containing up to several hundred genes can be sequenced cost-efficiently. However, the interpretation of the often large numbers of sequence variants detected when using NGS is laborious, prone to errors and is often difficult to compare across laboratories. To overcome this challenge, the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) have introduced standards and guidelines for the interpretation of sequencing variants. Additionally, disease-specific refinements have been developed that include accurate thresholds for many criteria, enabling highly automated processing. This is of particular interest for common but heterogeneous disorders such as hearing impairment. With more than 200 genes associated with hearing disorders, the manual inspection of possible causative variants is particularly difficult and time-consuming. To this end, we developed the open-source bioinformatics tool GenOtoScope, which automates the analysis of all ACMG/AMP criteria that can be assessed without further individual patient information or human curator investigation, including the refined loss of function criterion ("PVS1"). Two types of interfaces are provided: (i) a command line application to classify sequence variants in batches for a set of patients and (ii) a user-friendly website to classify single variants. We compared the performance of our tool with two other variant classification tools using two hearing loss data sets, which were manually annotated either by the ClinGen Hearing Loss Gene Curation Expert Panel or the diagnostics unit of our human genetics department. GenOtoScope achieved the best average accuracy and precision for both data sets. Compared to the second-best tool, GenOtoScope improved the accuracy metric by 25.75% and 4.57% and precision metric by 52.11% and 12.13% on the two data sets, respectively. The web interface is accessible via: http://genotoscope.mh-hannover.de:5000 and the command line interface via: https://github.com/damianosmel/GenOtoScope. Author summary: New high-throughput sequencing technologies can produce massive amounts of information and are used by laboratories to explain the often complex genetic etiology of hereditary diseases. To use these sequencing technologies effectively, software tools have been developed that can aid researchers interpreting genetic data by semi-automatically classifying the biologic (and, thus, potentially medical) impact of the detected variants (i.e. alterations of the patient's genome compared to the human reference genome). Variant classification itself is a very complex process: various information has to be taken into account and carefully judged, allowing room for interpretation. Over the last decade, the quality of genetic analysis evaluation and the consistency between different laboratories have improved substantially. This is in particular a result of increasing standardization, which extends to gene- or disease-specific considerations. Hereby, a largely uniform variant interpretation is possible even for common but heterogeneous disorders. To design a reliable tool that can accommodate these precise specifications, we chose hearing loss as a model disease because it is the most common sensory disorder, often hereditary and has a high impact on patients every-day lifes. The currently available genetic variant classification tools are either not designed specifically for the interpretation of variants detected in subjects with hearing loss or they do not allow researchers to use them for batch classification of all variants detected, e.g. in a study group. To address this drawback, we developed GenOtoScope, an open-source tool that automates the pathogenicity classification of variants potentially associated with congenital hearing loss. By adjusting specific parameters, the algorithm could also be easily adapted to other medical conditions. GenOtoScope can be applied for the automatic classification of all variants detected in a set of individuals. [ABSTRACT FROM AUTHOR]

Background: Few studies have assessed the burden of Chagas disease in non-endemic countries and most of them are based on prevalence estimates from Latin American (LA) countries that likely differ from the prevalence in migrants living in Europe. The aim of this study was to systematically review the existing data informing current understanding of the prevalence of Chagas disease in LA migrants living in European countries. Methods: We conducted a systematic review and meta-analysis of studies reporting prevalence of Chagas disease in European countries belonging to the European Union (EU) before 2004 in accordance with the MOOSE guidelines and based on the database sources MEDLINE and Global Health. No restrictions were placed on study date, study design or language of publication. The pooled prevalence was estimated using random effect models based on DerSimonian & Laird method. Results: We identified 18 studies conducted in five European countries. The random effect pooled prevalence was 4.2% (95%CI:2.2-6.7%); and the heterogeneity of Chagas disease prevalence among studies was high (I2 = 97%,p<0.001). Migrants from Bolivia had the highest prevalence of Chagas disease (18.1%, 95%CI:13.9–22.7%). Conclusions: Prevalence of Chagas in LA migrants living in Europe is high, particularly in migrants from Bolivia and Paraguay. Data are highly heterogeneous dependent upon country of origin and within studies of migrants from the same country of origin. Country-specific prevalence differs from the estimates available from LA countries. Our meta-analysis provides prevalence estimates of Chagas disease that should be used to estimate the burden of disease in European countries. [ABSTRACT FROM AUTHOR]

Krabbe disease is caused by a deficiency of the lysosomal galactosylceramidase (GALC) enzyme, which results in the accumulation of galactosylceramide (GalCer) and psychosine. In Krabbe disease, the brunt of demyelination and neurodegeneration is believed to result from the dysfunction of myelinating glia. Recent studies have shown that neuronal axons are both structurally and functionally compromised in Krabbe disease, even before demyelination, suggesting a possible neuron-autonomous role of GALC. Using a novel neuron-specific Galc knockout (CKO) model, we show that neuronal Galc deletion is sufficient to cause growth and motor coordination defects and inflammatory gliosis in mice. Furthermore, psychosine accumulates significantly in the nervous system of neuron-specific Galc-CKO. Confocal and electron microscopic analyses show profound neuro-axonal degeneration with a mild effect on myelin structure. Thus, we prove for the first time that neuronal GALC is essential to maintain and protect neuronal function independently of myelin and may directly contribute to the pathogenesis of Krabbe disease. Krabbe disease is a demyelinating neurodegenerative disorder caused by a deficiency of the enzyme lysosomal galactosylceramidase (GALC), which results in the accumulation of galactosylceramide and psychosine. This study uses a novel neuron-specific knockout model in the first in vivo attempt to investigate the role of neuronal GALC in neuronal function and the etiology of Krabbe disease. [ABSTRACT FROM AUTHOR]

Background: Southern China is at risk for arborvirus disease transmission, including Zika virus and dengue. Patients often present to clinical care with non-specific acute febrile illnesses (AFI). To better describe the etiology of AFI, we implemented a two-year AFI surveillance project at five sentinel hospitals in Yunnan and Guangdong Provinces. Methods: Between June 2017 and August 2019, we enrolled patients between 2 and 65 years of age presenting at one sentinel hospital in Mengla County, Yunnan, and four in Jiangmen City, Guangdong, with symptoms of AFI (acute onset of fever ≥ 37.5°C within the past 7 days) without respiratory symptoms or diarrhea. Demographic, epidemiologic, and clinical information was obtained and entered into a web-based AFI surveillance database. A custom TaqMan Array card (TAC) was used to test patients' whole blood specimens for 27 different pathogens using real-time polymerase chain reaction assays. Results: During the two-year project period, 836 patients were enrolled; 443 patients from Mengla County and 393 patients from Jiangmen City. The median age was 33 years [range: 2–65], and most were hospitalized [641, 77%]. Of 796 patients with valid TAC results, 341 (43%) were positive for at least one of the 10 unique pathogens detected. This included 205 (26%) patients positive for dengue virus, 60 (8%) for Orientia tsutsugamushi, and 42 (5%) for Coxiella burnetii. Ten patients (1%) in Jiangmen City tested positive for malaria, 8 of whom reported recent travel outside of China. TAC results were negative for 455 (57%) patients. None of the patients had a positive TAC detection for Zika virus. Conclusions: The project detected variability in the etiology of AFI in Southern China and highlighted the importance of differential diagnosis. Dengue, O. tsutsugamushi, and C. burnetii were the most frequently identified pathogens among enrolled AFI patients. As a non-notifiable disease, the frequent detection of C. burnetii is noteworthy and warrants additional investigation. The project provided a framework for routine surveillance for persons presenting with AFI. [ABSTRACT FROM AUTHOR]

Background: In March 2020, WHO announced the COVID-19 a pandemic and a major global public health emergency. Mortality from COVID-19 is rapidly increasing globally, with acute respiratory failure as the predominant cause of death. Many patients experience severe hypoxia and life-threatening respiratory failure often requiring mechanical ventilation. To increase safety margins during emergency anaesthesia and rapid sequence intubation (RSI), patients are preoxygenated with a closed facemask with high-flow oxygen and positive end-expiratory pressure (PEEP). Due to the high shunt fraction of deoxygenated blood through the lungs frequently described in COVID-19 however, these measures may be insufficient to avoid harmful hypoxemia. Preoxygenation with inhaled nitric oxide (iNO) potentially reduces the shunt fraction and may thus allow for the necessary margins of safety during RSI. Methods and design: The INOCOV protocol describes a phase II pharmacological trial of inhaled nitric oxide (iNO) as an adjunct to standard of care with medical oxygen in initial airway and ventilation management of patients with known or suspected COVID-19 in acute respiratory failure. The trial is parallel two-arm, randomized, controlled, blinded trial. The primary outcome measure is the change in oxygen saturation (SpO2), and the null hypothesis is that there is no difference in the change in SpO2 following initiation of iNO. Trial registration: EudraCT number 2020-001656-18; WHO UTN: U1111-1250-1698. Protocol version: 2.0 (June 25th, 2021). [ABSTRACT FROM AUTHOR]

Background: Meningitis remains an important cause of morbi-mortality in adults in sub-Saharan Africa. Data on the etiological investigation of meningitis in adults in Mozambique is limited and most studies were conducted in southern Mozambique. Identification of the etiology of meningitis in adults are crucial to guide prevention and treatments strategies. In this study, we determine the burden of fungal and bacterial meningitis among adults at the three largest hospitals in Mozambique. Method: We performed analysis of data from the routine sentinel surveillance system for meningitis in Mozambique from January 2016 to December 2017. Cerebrospinal fluid (CSF) samples were collected from eligible adults (≥18 years old) who met World Health Organization (WHO) case definition criteria for Meningitis. All samples were tested by cryptococcal antigen (CrAg) lateral flow assay (LFA), culture and triplex real-time polymerase chain reaction (qPCR) assay and all patients were tested for human immunodeficiency virus (HIV) using the national algorithm for HIV testing. Results: Retrospective analysis of 1501 CSF samples from adults clinically suspected of meningitis revealed that 10.5% (158/1501) were positive for bacterial and fungal meningitis. Of these 158 confirmed cases, the proportion of Cryptococcal meningitis and pneumococcal meningitis was38.6% (95% CI: 31.0% to 46.7%) and 36.7% (95% CI: 29.2% to 44.7%), respectively. The other bacterial agents of meningitis identified include Neisseria meningitidis (8.9%; 14/158), Escherichia coli (6.3%; 10/158), Haemophilus influenzae (5.1%; 8/158) and S. aureus (4.4%; 7/158), which represent (24.7%; 39/158) of the total confirmed cases. Conclusion: Altogether, our findings show a high burden of Cryptococcal meningitis among adults in Mozambique, especially in people living with HIV, followed by pneumococcal meningitis. Our findings suggest that rollout of CrAg Lateral Flow Assay in the health system in Mozambique for early detection of cryptococcus neoformans is necessary to improve overall patient care. [ABSTRACT FROM AUTHOR]

Notch signaling is essential for the development of T cell progenitors through the interaction of NOTCH1 receptor on their surface with the ligand, Delta-like 4 (DLL4), which is expressed by the thymic epithelial cells. Notch signaling is quickly shut down once the cells pass β-selection, and CD4/CD8 double positive (DP) cells are unresponsive to Notch. Over the past two decades a number of papers reported that over-activation of Notch signaling causes T cell acute lymphoblastic leukemia (T-ALL), a cancer that prominently features circulating monoclonal CD4/CD8 double positive T cells in different mouse models. However, the possible outcomes of Notch over-activation at different stages of T cell development are unknown, and the fine timing of Notch signaling that results in T-ALL is poorly understood. Here we report, by using a murine model that ectopically expresses DLL4 on developing T cells, that the T-ALL onset is highly dependent on a sustained Notch activity throughout the DP stage, which induces additional mutations to further boost the signaling. In contrast, a shorter period of Notch activation that terminates at the DP stage causes a polyclonal, non-transmissible lymphoproliferative disorder that is also lethal. These observations resolved the discrepancy of previous papers on DLL4 driven hematological diseases in mice, and show the critical importance of the timing and duration of Notch activity. [ABSTRACT FROM AUTHOR]

Background: Triatomine bugs are the insect vectors of Trypanosoma cruzi, the etiological agent of Chagas disease. These insects are known to aggregate inside shelters during daylight hours and it has been demonstrated that within shelters, the aggregation is induced by volatiles emitted from bug feces. These signals promote inter-species aggregation among most species studied, but the chemical composition is unknown. Methodology/Principal Findings: In the present work, feces from larvae of the three species were obtained and volatile compounds were identified by solid phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS). We identified five compounds, all present in feces of all of the three species: Triatoma infestans, Panstrongylus megistus and Triatoma brasiliensis. These substances were tested for attractivity and ability to recruit insects into shelters. Behaviorally active doses of the five substances were obtained for all three triatomine species. The bugs were significantly attracted to shelters baited with blends of 160 ng or 1.6 µg of each substance. Conclusions/Significance: Common compounds were found in the feces of vectors of Chagas disease that actively recruited insects into shelters, which suggests that this blend of compounds could be used for the development of baits for early detection of reinfestation with triatomine bugs. [ABSTRACT FROM AUTHOR]

Introduction: Remdesivir and Dexamethasone represent the cornerstone of therapy for critically ill patients with acute hypoxemic respiratory failure caused by Coronavirus Disease 2019 (COVID-19). However, clinical efficacy and safety of concomitant administration of Remdesivir and Dexamethasone (Rem-Dexa) in severe COVID-19 patients on high flow oxygen therapy (HFOT) or non-invasive ventilation (NIV) remains unknown. Materials and methods: Prospective cohort study that was performed in two medical Intensive Care Units (ICUs) of a tertiary university hospital. The clinical impact of Rem-Dexa administration in hypoxemic patients with COVID-19, who required NIV or HFOT and selected on the simplified acute physiology score II, the sequential organ failure assessment score and the Charlson Comorbidity Index score, was investigated. The primary outcome was 28-day intubation rate; secondary outcomes were end-of-treatment clinical improvement and PaO2/FiO2 ratio, laboratory abnormalities and clinical complications, ICU and hospital length of stay, 28-day and 90-day mortality. Results: We included 132 patients and found that 28-day intubation rate was significantly lower among Rem-Dexa group (19.7% vs 48.5%, p<0.01). Although the end-of-treatment clinical improvement was larger among Rem-Dexa group (69.7% vs 51.5%, p = 0.05), the 28-day and 90-day mortalities were similar (4.5% and 10.6% vs. 15.2% and 16.7%; p = 0.08 and p = 0.45, respectively). The logistic regression and Cox-regression models showed that concomitant Rem-Dexa therapy was associated with a reduction of 28-day intubation rate (OR 0.22, CI95% 0.05–0.94, p = 0.04), in absence of laboratory abnormalities and clinical complications (p = ns). Conclusions: In COVID-19 critically ill patients receiving HFO or NIV, 28-day intubation rate was lower in patients who received Rem-Dexa and this finding corresponded to lower end-of-treatment clinical improvement. The individual contribution of either Remdesevir or Dexamethasone to the observed clinical effect should be further investigated. [ABSTRACT FROM AUTHOR]

Network medicine has been applied successfully to elicit the structure of large-scale molecular interaction networks. Its main proponents have claimed that this approach to integrative medical investigation should make it possible to identify functional modules of interacting molecular biological units as well as interactions themselves. This paper takes a significant step in this direction. Based on a large-scale analysis of the nervous system molecular medicine literature, this study analyzes and visualizes the complex structure of associations between diseases on the one hand and all types of molecular substances on the other. From this analysis it then identifies functional co-association groups consisting of several types of molecular substances, each consisting of substances that exhibit a pattern of frequent co-association with similar diseases. These groups in turn exhibit interlinking in a complex pattern, suggesting that such complex interactions between functional molecular modules may play a role in disease etiology. We find that the patterns exhibited by the networks of disease – molecular substance associations studied here correspond well to a number of recently published research results, and that the groups of molecular substances identified by statistical analysis of these networks do appear to be interesting groups of molecular substances that are interconnected in identifiable and interpretable ways. Our results not only demonstrate that networks are a convenient framework to analyze and visualize large-scale, complex relationships among molecular networks and diseases, but may also provide a conceptual basis for bridging gaps in experimental and theoretical knowledge. [ABSTRACT FROM AUTHOR]