Biology

Diabetes Mellitus (DM) is a metabolic disorder characterized by hyperglycemia, with type 1 characterized as an autoimmune destruction of pancreatic beta cells and type 2 characterized by insulin resistance with progressive beta cell dysfunction. This study applied an existing binary classification algorithm (ALTARN) to accurately predict DM. ALTARN, as a tabular attention residual neural network, uses residual connection to find complex patterns present in tabular columns. We achieved an average training accuracy of 75.22%. Furthermore, a robust set of validation metrics was obtained via five-fold stratified cross-validation, yielding an average accuracy of 74.61%, an average precision of 72.36%, a mean recall of 79.69%, and a mean F1 score of 75.83%.

Neural tube defects (NTDs) represent frequent and severe congenital anomalies of the central nervous system, including anencephaly, spina bifida, and encephalocele. This retrospective study evaluates the occurrence, prenatal diagnosis, and sex distribution of NTDs in the Czech Republic during the period 1961-2020. Data were obtained from the National Registry of Congenital Anomalies within the National Registry of Reproductive Health. Both prenatally and postnatally diagnosed cases of anencephaly, spina bifida, and encephalocele were analyzed. A total of 2,521 cases of anencephaly, 3,391 cases of spina bifida, and 704 cases of encephalocele were recorded. Prenatal diagnosis with subsequent termination of pregnancy accounted for a substantial proportion of cases, particularly in anencephaly. The mean total incidence per 10,000 live births was 2.91 for anencephaly, 4.38 for spina bifida, and 1.24 for encephalocele. Sex distribution analysis across six consecutive decades demonstrated a persistent predominance of affected females in spina bifida, with statistically significant differences in selected periods. In contrast, anencephaly and encephalocele showed a female predominance only in earlier decades, whereas a higher proportion of affected males has been observed in recent years. Although advances in prenatal diagnostics have markedly reduced the incidence of NTDs among live-born children, the overall population incidence of these defects has remained stable.

To characterize tuberculosis transmission and assess the impact of important interventions, a data-driven SEITR TB model is created. The potential for disease persistence has been calculated using the basic reproduction number. To determine the factors most significantly affecting the spread of tuberculosis, stability and sensitivity analyses are conducted. Strengthened treatment measures and optimized distancing significantly lower infection levels, according to numerical simulations. The Least Squares Fitting technique is used to validate real epidemiological data with a model solution. And the results emphasize that the best combinations of social distancing and treatment not only reduce the number of infections but also provide a cost-effective strategy for public health planning. Additionally, two numerical techniques, namely Pearson correlation and Partial Rank Correlation Coefficients (PRCC), are utilized to assess the sensitivity of model parameters. It is noted that the outcomes of these two methods are in agreeable comparison with one another regarding sensitivity analysis.

Background/ObjectivesOur objective was to understand the role of clinical and continuous glucose monitoring (CGM) parameters in predicting the risk of hypoglycemia in type 1 diabetes pediatric patients. MethodsPediatric patients with type 1 diabetes (n=71) at the Oradea County Clinical Emergency Hospital, Romania, underwentCGM during their initial visit and were followed for at least 6 months, with in-clinic visits every 3 months. Age, body mass index, time in range, mean daily glucose(MDG) concentration, coefficient of variation(%CV)were considered as potential predictors of the risk of hypoglycemia (presented as the percentage of time spent below two glycemic thresholds: 3.9 and 3.0 mmol/L, corresponding to mild, respectively clinically significant hypoglycemia). ResultsLooking at a total of 142 glycemic profiles, MDG was significantly lower in those with hypoglycemia compared to those without, while %CV was significantly higher(p<0.0001). Regression tree models identified %CV as the dominant variable for both thresholds, while classification tree models identified %CV for clinically significant hypoglycemia and MDG for mild hypoglycemia. It was observed that in profiles with a %CV below 36.15% and MDG above 7.16 mmol/L, the mean percentage of time spent below the 3.9 mmol/L threshold was 4.8%--a value close to that recommended in American Diabetes Association guidelines. Patients younger than 7 years presented the highest frequency of both mild and clinically significant hypoglycemic episodes. ConclusionsOur study supports %CV and MDG concentration as key factors in predicting hypoglycemia risk. Minimizing the risk of hypoglycemia in pediatric patients requires a %CV below 36%.

Maternal smoking during pregnancy is associated with adverse effects on offspring health through impaired placental structure and function. Nicotine and other tobacco-related compounds readily cross the placental barrier, disrupt metabolic pathways, and increase the risk of long-term developmental disorders in newborn. Here, placental metabolic alterations associated with maternal smoking exposure were examined with metabolomics. We used placental samples from the Kuopio Birth Cohort study from 23 nonsmoking controls pregnancies, 19 pregnancies with early smoking exposure (cotinine detected in first-trimester but not in at-term samples), and 13 pregnancies with continuous smoking-exposure (cotinine detected in both first-trimester and at-term samples). Differences in placental metabolomic profiles were seen between controls and both smoking-exposed groups. For example, increased activity of xenobiotic metabolism pathways showed as elevated CYP1A2-related metabolites, e.g., aminoamide local anesthetic metabolite detected in both smoking-exposure groups (p=0.0042 and 0.0019, respectively). Disruptions in amino acid metabolism were observed, e.g., reduced placental tryptophan levels (p=0.0209 and 0.0237). Placentas from women who quit smoking during showed markers of reduced oxidative stress, lower oxidized glutathione (p=0.0119) and higher ergothioneine (p=0.0426) levels. These findings indicate that many smoking-related effects on the placental metabolome persist beyond acute nicotine exposure, showing long-term biological effects of maternal smoking during pregnancy. Plain language summarySmoking during pregnancy can possibly change how the placenta functions, which also affects the newborns long-term health. In this study, we compared placentas from nonsmokers, women who quit during pregnancy, and those who kept smoking. Clear chemical differences were seen in the placentas of smoking exposed pregnant women. The main changes included lowered levels of tryptophan and glutathione, which are important for growth and protection from stress. These results show that smoking-related changes in the placenta can persist beyond active nicotine exposure.

BackgroundCervical cancer is one of the most common malignant tumors of the female reproductive system. Existing treatments provide limited benefit for patients with advanced, recurrent or metastatic disease, and reliable prognostic markers are lacking. In this study we integrated multi-omic data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database. Protein-coding genes meeting the criteria of an adjusted P value < 0.05 and |log2 fold-change| > 5 were screened; 693 genes were identified. We further focused on three genes related to the tumor microenvironment--interleukin 21 (IL21), C-X-C motif chemokine ligand 9 (CXCL9) and cluster of differentiation 1A (CD1A)--and performed differential expression analysis, survival analysis, clinical stage analysis and immune infiltration correlation analysis to clarify their prognostic value and potential mechanisms in cervical cancer. Results(1) CXCL9 and CD1A were highly expressed in cervical cancer tissues, and all three genes showed high expression across different pathological stages without stage-dependent differences; (2) high expression of IL21, CXCL9 and CD1A improved patient prognosis and was positively associated with overall survival (OS), disease-specific survival (DSS) and progression-free interval (PFI); (3) expression of IL21, CXCL9 and CD1A was closely correlated with infiltration of multiple immune cells: IL21 correlated with total T cells, helper T cells and B cells, CXCL9 correlated with T cells and activated dendritic cells, and CD1A correlated with immature dendritic cells. ConclusionIL21, CXCL9 and CD1A are potential prognostic biomarkers and key immunomodulatory factors in cervical cancer. This study provides a new direction for immunotherapy and individualized precision treatment of cervical cancer.

ObjectiveThis study aimed to evaluate the efficacy, safety, and optimal strains of probiotics for pediatric allergic rhinitis (AR) using meta-analysis and network meta-analysis. MethodsA systematic search was conducted in databases including PubMed, Web of Science, Cochrane Library, and China National Knowledge Infrastructure up to July 31, 2025, to identify randomized controlled trials (RCTs). Inclusion criteria were pediatric patients with AR, probiotic interventions, control groups receiving placebo or standard treatment, and reported outcomes such as Total Nasal Symptom Score (TNSS), Pediatric Rhinoconjunctivitis Quality of Life Questionnaire (PRQLQ), serum IgE levels, clinical efficacy, or adverse events. Study quality was assessed using the JADAD scale, with meta-analysis and network meta-analysis (NMA) performed via RevMan and R software, calculating standardized mean differences (SMD), relative risks (RR), and surface under the cumulative ranking curve (SUCRA) values. ResultsTwenty-six RCTs were included, involving 3,014 patients (1,565 in the probiotic group and 1,404 in the control group). Meta-analysis showed that probiotics significantly reduced TNSS (SMD = -0.85, 95% CI [-1.25, -0.44], P < 0.05), improved PRQLQ scores (SMD = -3.94, 95% CI [-4.55, -3.33], P < 0.05), enhanced clinical efficacy (RR = 1.16, 95% CI [1.07, 1.25], P < 0.05), and decreased adverse events (RR = 0.22, 95% CI [0.06, 0.82], P < 0.05), but exerted no overall effect on serum IgE (SMD = -0.39, 95% CI [-0.99, 0.09], P = 0.11). Subgroup and NMA analyses indicated that mixed strains performed superiorly across multiple outcomes. ConclusionsProbiotics, particularly mixed strains, are a safe and effective adjunctive therapy for pediatric AR, improving symptoms and quality of life. Large-scale RCTs are required to validate optimal regimens.

We describe a fast, noninvasive, low-cost survey method designed to understand the mode of transmission of an emerging pathogen. It is inspired from the standard household prevalence survey consisting in sampling households and counting the total number of people infected in each household, but refines it with the aim of improving diagnosis and estimating more parameters of the model of intra-household transmission. The survey was carried out in May-June 2020, during part of the first national French lockdown and received responses from more than 6,000 households involving a total of 20,000 people. We explain how we conceived the questionnaire, how we disseminated it, to the public through an open website hosted by CNRS, marketed through media and social media, and to a socially representative panel hosted by two survey institutes (BVA, Bilendi). We used the data obtained from the representative panel to correct for sampling biases in the CNRS survey using a classical raking procedure. Our results indicate that raking correctly canceled statistical biases between the two populations. We obtain the empirical distribution in households of the number and nature of symptoms. The main factors affecting the presence of symptoms are age, gender, body mass index (BMI), household size, but not necessarily in the expected direction. Our study shows that combining self-reporting and representative surveys allows investigators to obtain information on prevalence and household transmission mechanisms on emerging diseases at low cost.

Accurate identification of unknown pathogens is critical for medicine and public health, yet current metagenomic workflows remain heavily dependent on specialized bioinformatics expertise and manual interpretation, creating substantial bottlenecks in time-sensitive diagnostic settings1. The key challenges lie in achieving precise species identification amidst high background noise and translating complex microbial data into clinically actionable insights2,3. Here we present the Global Pathogen Analysis System (GPAS), an integrated computational framework that combines rapid and accurate pathogen identification with large language model (LLM)-based semantic interpretation. Central to GPAS is a dynamic-library alignment mechanism informed by prior probabilities of inter-species misclassification. By integrating a hybrid machine learning model that couples elastic neural networks with Bayesian inference, this approach substantially reduces both false positives and false negatives, achieving species-level accuracy superior to existing state-of-the-art tools. To enable clinical interpretation, we constructed a unified microbial knowledge graph integrating global metagenomic and metaviromic sample repositories, and trained a pathogen-specialized LLM agent. Through end-to-end reinforcement learning, the agent autonomously executes multi-step reasoning workflows extracting pathogen-specific insights from complex data and generating human-readable, evidence-based reports. Application to throat swab samples demonstrates that GPAS not only accurately identifies pathogenic microorganisms but also reveals how SLE-associated immune dysregulation reshapes the respiratory microbiome and promotes pathobiont overgrowth, providing clinically instructive interpretations. By substantially lowering technical barriers to pathogen identification, GPAS offers an accessible yet powerful platform for clinical diagnostics, public health surveillance, and microbiome research. The system is freely available at: https://gpas.nh.ac.cn/.

ObjectivesThere is currently insufficient evidence linking COVID-19 infection with Graves disease (GD). Following the complete lifting of COVID-19 restrictions on December 13, 2022, widespread infection in Guangzhou provides a basis for this study. This research aims to investigate the correlation between COVID-19 infection and GD onset, explore the epidemiological characteristics of newly diagnosed GD post-infection, and offer a scientific basis for treatment. MethodsThe study population included 494 GD outpatients treated in the Department of Endocrinology at the Second Affiliated Hospital of Guangzhou Medical University from January 1 to June 30 each year between 2021 and 2023. They were divided into two groups: 2023 (N=219) and 2021-2022 (N=275), based on the time node of widespread COVID-19 infection in 2023. The new diagnosis rate, general clinical characteristics, and serological test results of GD patients were analyzed before and after the outbreak of COVID-19. ResultsCompared with the 2021-2022 group, the new diagnosis rate of GD patients in 2023 showed a significant increase (12.8% vs. 8.4%, P<0.001). Furthermore, there was a significant decrease in pre-treatment thyrotropin receptor antibody levels (P=0.01), white blood cell count (P=0.02), and neutrophil proportion (P=0.04), while there was a significant increase in the proportion of patients with a family history (P=0.047). Follow-up until June 30 of that year revealed that the proportion of newly diagnosed GD patients developing hypothyroidism during treatment in 2023 significantly increased compared to the 2021-2022 group (P<0.001). ConclusionsAfter widespread infection of COVID-19, the diagnosis rate of newly diagnosed GD increased, which may influence the epidemiological characteristics of related GD patients before initial treatment and during treatment.

ObjectiveTo identify clusters of high-cost patients in England based on diagnoses and sociodemographic characteristics to inform targeted population health management. DesignA retrospective population-based cohort study using unsupervised machine learning. SettingEnglish primary care electronic health records from the Clinical Practice Research Datalink, linked to Hospital Episode Statistics for hospital records and Office for National Statistics mortality data. Participants10,119,490 adult patients aged 18 years or over registered with 1,397 general practices in England on 1 April 2018. High-cost patients were defined as the top 1% of total healthcare spending (n=101,195). Additional high-cost population were examined, including age-specific subgroups, patients who died during the year and patients in the top 1% of unplanned care costs. Main outcome measuresPrimary and secondary care costs in financial year 2018/19. Clusters of high-cost patients defined using unsupervised machine learning based on age, sex, area-level deprivation, ethnicity, and diagnoses recorded during 2006/07-2018/19. ResultsHigh-cost patients accounted for GBP1.8billion (26.8%) of GBP6.6billion population costs. Mean annual costs per high-cost patients were GBP17,485 (median GBP14,609; interquartile range: GBP12,028 to GBP19,633) compared with GBP653 (GBP103; GBP14 to GBP352) in the overall population. Hierarchical clustering identifying nine clusters was the optimal solution based on evaluation combining multiple validity and stability metrics. Across those clusters, mean age ranged from 56 to 79 years, and mean annual costs ranged from GBP15,792 (95%CI GBP15,629 to GBP15,955) to GBP19,107 (GBP18,784 to GBP19,430). Notable clusters produced across clustering approaches and high-cost populations, including younger people with liver disease and mental health conditions, patients with nodal metastases, patients with prostate cancer and hyperplasia, and older people with cardiovascular disease and dementia. ConclusionHigh-cost patients are a heterogeneous population with distinct clinical and sociodemographic profiles and utilization patterns. Clustering across multiple high-cost populations identified recurrent clusters, highlighting common pathways of high expenditure, while also revealing population-specific patterns of need. Incorporating cluster-based approaches into population health management may improve the targeting of case management programmes, optimise resource allocation, and support more effective and sustainable health system planning. What is already known on this topicO_LIA small proportion of patients account for a large share of healthcare costs, and are a priority for population health management. C_LIO_LIPrevious clustering studies show heterogeneity among high-cost patients, but are often limited by scale, care settings, or lack of robustness assessment C_LI What this study addsO_LIUsing linked English primary and secondary care data for over 10 million adults, the top 1% high-cost patients accounted for more than a quarter of total costs. C_LIO_LIBy comparing multiple clustering methods across several high-cost populations, we identify recurrent, clinically interpretable subgroups, including younger adults with liver disease and mental health conditions, highly deprived, with heavy emergency use; oncology with nodal metastases, intensive planned pathways and high mortality; older men with prostate cancer or hyperplasia, sustained planned care; and older adults with cardiovascular disease and dementia, recurrent emergency admissions and high primary-care contact C_LI How this study might affect research, practice or policyO_LIRobust segmentation can complement risk prediction by supporting more tailored, multidisciplinary care for high-cost patients. C_LIO_LICluster profiles can inform population health management and service planning in universal healthcare systems. C_LI

There is an unmet need to identify biomarkers of active thyroid eye disease (TED). scRNAseq revealed that orbital fibroblasts from orbital decompressions in people with TED express high levels of thyroid hormone receptors, growth factor receptors, including insulin-like growth factor 1 receptor (IGF1R), and extracellular matrix proteins including SPARC (osteonectin), whereas orbital fat endothelial cells expressed thyroid peroxidase (TPO). SPARC was significantly raised in the serum of people with thyroid disease compared to healthy controls. Furthermore, those with moderate, severe and sight threatening TED had higher SPARC levels than those with thyroid disease but free of TED or mild TED. Free-triiodothyronine (FT3) levels were positively correlated with SPARC in moderate-sight threatening TED. SPARC and IGF1 were positively correlated across people with thyroid disease alone, as well as TED. Thyroid stimulating hormone (TSH) levels were negatively correlated with SPARC in moderate-sight threatening TED. When participants were followed longitudinally, SPARC decreased after the active phase of TED. At the protein level, immunohistochemistry indicated that SPARC was heterogeneously expressed by fibroblasts in both control and TED orbital fat. SPARC is a key mediator of fibrosis and deposition of extracellular matrix and the correlation of SPARC serum levels to TED status and FT3 make it a promising biomarker of active TED.

Background The Hump-nosed pit viper is a recognized but neglected medically significant species causing morbidity and mortality, with non-availability of a specific antivenom. There are many gaps in our understanding of its envenomation, including burden, clinical syndrome, complications and management. Methodology The study is a retrospective sub analysis of the Prospective VENOMS registry and hospital records of Hump Nosed Pit Viper envenomation from a single tertiary care center in coastal Karnataka from May 2018 to March 2024. Epidemiology, syndrome, complications and treatment strategies have been described. A linear mixed model analysis was conducted to study the effect of different therapeutic interventions in combating venom induced consumptive coagulopathy (VICC) Principal Findings Of 46 cases, 24 patients had VICC. The most common complications were AKI (21.7%), TMA (10.9%) and stroke (4.4%). Anaphylaxis to ASV (23.9%) was the most common therapeutic complication. Therapeutic interventions included ASV, administration of blood products and therapeutic plasma exchange along with supportive care. The linear mixed model revealed that administration of blood products (p=<0.001) had the strongest influence on the INR value, however, often resulting in a transient decline in INR value. ASV (p=0.052) caused only marginally significant change in INR. The role of TPE could not be statistically inferred, however, individual cases with severe VICC improved without complications, therefore it required further study but can be considered in critical cases. Conclusions/Significance This study describes the syndrome of hump-nosed pit viper envenomation, while highlighting the urgent need for a species-specific antivenom, recommends treatment strategies that can be used in the interim. Additionally, geo-spatial mapping draws attention to hotspots and the hypothesis that HNPV in coastal Karnataka have regionally distinct toxicity trends.

BackgroundConsanguineous unions are defined as the matrimony between individuals who are blood relatives. Researchers in all over the world worked on this issue and they checked the ratio of prevalence and effects of consanguinity in different regions of world. This research was conducted in the District Faisalabad, upper Punjab. ObjectiveTo find rate of consanguinity, coefficient of inbreeding (F) and its impacts. MethodsThe data was collected from six tehsils of District Faisalabad by interviewing the subjects. The data collected within the time span of six months. Total of 2366 subjects were interviewed after their consent approval. ResultsThe rate of consanguinity was noted 41.83% with 0.03053 coefficient of inbreeding. High rate of consanguinity (23.36%) was noted among first cousins. The distantly related and not related unions were 35.64% and 22.56% respectively. The rate of consanguineous unions in six tehsils ranged from 33.99% in Jaranwala to 53.85% in Tandlianwala. Consanguineous marriages were noted high in Punjabi speaking subjects, in housewives, in reciprocal marital types, in grand-parents and one couple family types and Rajpoot castes. There was found no significant differences of consanguinity in rural and urban areas. The rate of still births was noted high (82.25%) in consanguineous unions while neonatal, post neonatal and child mortality was low such less as 6.45%, 8.06% and 3.22% respectively. The prenatal mortality was noted slightly high 44.94% in consanguineous unions as compared to non-consanguineous unions. The congenital malformation rate was 6.29% in all marital unions but this rate was high (59.06%) in consanguineous unions as compared to non-consanguineous unions (40.93%). This is a pilot study to analyze the potential of inbreeding coefficient (F) in the District Faisalabad.

BackgroundImpulse oscillometry is a noninvasive pulmonary function test performed during quiet breathing and requires minimal patient cooperation. It is useful for detecting small airway disease and provides increased sensitivity for diagnosing asthma in younger children who may have difficulty completing standard spirometry. Bronchodilator testing, a standard assessment of airflow obstruction reversibility, is recommended in patients with suspected asthma who present obstructive airflow patterns. ObjectiveTo evaluate impulse oscillometry parameters before and after bronchodilator administration across different age groups and to examine the relationship between age and airway resistance in patients with clinician-diagnosed asthma. MethodsThis retrospective study included patients with clinician-diagnosed asthma who demonstrated obstructive airflow patterns and a positive bronchodilator response. Participants were grouped by age: younger than 6 years, 6 to 20 years, and older than 20 years. Key impulse oscillometry parameters--airway resistance at 5 Hz, airway resistance at 20 Hz, the difference between these values, and resonance frequency--were collected and compared across groups. A positive bronchodilator response was defined as a reduction in airway resistance of more than 30% in individuals younger than 18 years and more than 40% in adults. ResultsA total of 225 patients (123 males and 102 females) were included, with a median age of 6 years. At baseline, the median airway resistance at 5 Hz was 175.34% of the reference value (95% CI, 171.66-178.62), and airway resistance at 20 Hz was 121.68% (95% CI, 118.73-127.12). The median difference between these values was 52.32% (95% CI, 49.89-57.14), and the median resonance frequency was 5.11 Hz (95% CI, 4.62-5.35). After bronchodilator administration, airway resistance at 5 Hz decreased to 123.56% (95% CI, 119.07-126.77), corresponding to a median reduction of 52.8% (95% CI, 49.48-56.08; P < 0.0001). Age demonstrated a moderate positive correlation with airway resistance at 20 Hz (r = 0.51, P < 0.001). ConclusionsProximal airway resistance increases with age among patients with asthma, suggesting age-related differences in airway inflammation. Impulse oscillometry combined with bronchodilator assessment provides a practical approach for evaluating airflow reversibility and enhances diagnostic accuracy in suspected asthma.

ObjectiveOrofacial clefts may involve the complete vertical thickness of the lip (complete) or partial thickness (incomplete). This study evaluates side preference for completeness in nonsyndromic asymmetric bilateral and unilateral cleft lip with or without cleft palate (NSCL/P). DesignWe studied 4 multiethnic cohorts from North and South America, Asia, and Africa, including 3,561 individuals with NSCL/P. Associations between cleft completeness, sex, ethnicity, and race were assessed using Chi-square or Fishers exact test (=0.05). ParticipantsPatients with NSCL/P with complete information on cleft type and completeness were included. Our main goal was to analyze side preference of complete clefting in different demographic groups, sex and race. ResultsAmongst asymmetric bilateral cases, left side completeness was significantly more frequent than the right side (73.7% vs. 26.3%; p<0.001). No associations observed for sex or race with ethnicity showing a trend toward significance (50.0% vs. 25.5%; p=0.088). Amongst symmetric bilateral and unilateral cases, Hispanics exhibited completeness more frequently than non-Hispanics (96.4% vs 89.5%; p<0.001; 84.1% vs. 79.7%; p<0.001). For unilateral cases, completeness showed no side preference. Caucasians were less likely to exhibit complete clefts compared to Asians, Blacks, or other racial groups (68.7% vs 84.9% or 81.2% or 81.7%; p<0.001). Females more frequently presented with completeness than males (81.2% vs 76.6%; p=0.003). ConclusionsIn NSCL/P with bilateral asymmetry, the left side is more often complete than the right side. Although unilateral left-sided clefts are more common overall, completeness shows no side preference. Race and ethnicity demonstrate significant associations with cleft severity patterns.

In this research, we create a new fractional-order SEIHRD framework to examine how the Nipah virus moves from one species to another (zoonotic spillover) and how it later spreads throughout a community (via contact with one another) or in a hospital or isolation situation (via entering into a hospital or being placed under quarantine). We used the fractional-derivative formulation of the SEIHRD model to demonstrate memory-based effects related to the progression of an infection and also reflect time-distributed effects associated with surveillance and control measures placed on an infected patient. We first demonstrated that the basic epidemiologic properties of the model were consistent by showing that the solutions of the SEIHRD differential equations will always yield positive and bounded solutions within biologically relevant parameter ranges. We then established the well-posedness of this model by transforming the SEIHRD differential equations into an equivalent integral operator and applying various fixed-point arguments to demonstrate that there will always be unique solution(s) to the SEIHRD differential equations. To evaluate the threshold parameter for the transmission of Nipah virus within a given population we calculated the threshold level through the next generation method to determine the expected number of secondary infections from a new or chronically infected host. One of the main contributions of this work is to include an analysis of the robustness of a given solution to all potential perturbations (i.e., Ulam-Hyers and generalized Ulam-Hyers stability). In addition, we provide analytic results guaranteeing that small perturbations due to approximate modeling, numerical approximation (discretization), or the lack of data fidelity will produce controlled deviations in the solutions. To finish this project, we perform a global sensitivity analysis on uncertain coefficients to evaluate their contribution to the uncertainty of each coefficient and to find out the coefficients that most strongly influence major outcome metrics. This will allow us to develop a priority order for prioritizing spillover control (reduction of human contact and/or isolation), contact reduction, and expenditure of resources towards isolation-related interventions. The resulting framework converts fractional epidemic modeling from a descriptive simulation to a replicable method with robustly defined behavior and equal response prediction.

BackgroundPrimary aldosteronism(PA) screening is recommended but disease prevalence exceeds the availability of adrenal vein sampling(AVS). MethodsAn AVS optimal allocation tool for health systems was developed using administrative data and AVS registries from Calgary and Taiwan. Four easily-definable phenotypes of PA based on an elevated aldosterone-renin-ratio (ARR), and the presence/absence of hypokalemia or adrenal mass were identified, representing progressively severe PA and stepwise increasing rates of AVS-defined lateralization. Using supply-and-demand principles, a customizable, web-based tool was developed that considers PA referral volume, PA phenotype prevalence, maximum AVS available/year, AVS success rate, and desired rate of finding unilateral disease. ResultsThe most prevalent phenotype of PA was characterized by an elevated ARR and hypokalemia but no adrenal mass (41.9 [39.9-43.9]%); hypokalemia and adrenal mass accounted for (15.6[14.4-16.9]%) of cases. There was a progressive increase in AVS lateralization rate with increasing severity of phenotype observed in both the Calgary and Taiwan data, ranging from (20-39%) in those with PA without hypokalemia or adrenal mass to (70-90%) in those with hypokalemia and adrenal mass. After accounting for institution-specific lateralization rates and allowing for system-level differences in high- and low-volume PA referrals, and high- and low AVS availability, the customizable AVS allocation tool was able to generate individualized strategies ranging from restrictive (exclusive reservation of AVS for cases with hypokalemia and adrenal mass) to more inclusive strategies (assigning a proportion of AVS allocation to less severe PA cases). ConclusionsAn AVS allocation tool that uses common, simple, and globally available PA case data may assist in health system AVS program case allocation for maximum equity and wait-list control. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/26345289v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1c9be00org.highwire.dtl.DTLVardef@1d91e00org.highwire.dtl.DTLVardef@140aa8aorg.highwire.dtl.DTLVardef@7c76c6_HPS_FORMAT_FIGEXP M_FIG C_FIG

Identifying individuals at risk of early onset type 1 diabetes (diagnosed <2 years) would be highly beneficial in reducing risk of severe diabetic ketoacidosis (DKA) for those with extreme autoimmunity. We aimed to investigate whether genetic variation contributes to heterogeneity in age of type 1 diabetes onset, focusing on those diagnosed <2 years and ages previously defined by histological differences. We carried out association testing on 6773 individuals with type 1 diabetes and tested for heterogeneity in Human Leukocyte Antigen (HLA) variants across stratified age groups (594 diagnosed <2 years, 2241 diagnosed 2-7 years, 3094 diagnosed 7-13 years, 844 diagnosed 13+ years). We used a 67 SNP type 1 diabetes genetic risk score (T1D-GRS) to quantify aggregated genetic risk and assessed its utility in screening for type 1 diabetes <2 years. We observed higher T1D-GRSs as age of onset decreased in type 1 diabetes and found that DR3-DQ2 homozygosity was most strongly associated with <2 years onset (log-OR=4.27). The T1D-GRS showed high discriminative ability for <2 years onset type 1 diabetes onset (AUC=0.94) and correctly identified 88% of type 1 diabetes cases at the 85th population centile. We have shown higher genetic risk for very early onset T1D and suggest T1D-GRSs in newborn screening is likely to be particularly sensitive to those with younger type 1 diabetes onset.

BackgroundMillions of people worldwide suffer from thyroid dysfunction, and especially hypothyroidism, which is a prevalent endocrine disorder contributing extensively to systemic and metabolic illness. In hypothyroidism, triiodothyronine (T3) and thyroxine (T4), thyroid hormones that control metabolism in several organ systems, are insufficiently secreted. ObjectivesThe objective of this study was to determine the effect of anti-thyroid antibodies on thyroid function in Bangladeshi newly diagnosed patients with hypothyroidism. MethodsA cross-sectional analysis of adult patients with newly diagnosed hypothyroidism was carried out. Thyroid function tests (FT4, TSH), thyroid autoantibodies (anti-TPO, anti-Tg), symptoms, physical findings, and demographics were obtained and analyzed. ResultsThe average age of the study participants was 36.07{+/-}11.00 years, and 70.1% were female. 72.7% of the cases were rural. 89% of the patients were antibody-positive, 81.8% anti-TPO, 55.2% anti-Tg, and 48.1% both. Enlargement of the thyroid (p<0.001) and gain of weight (p<0.043) were associated with antibody positivity. Grade 1 goitre alone was highly predictive of antibody positivity (AOR 11.766, p<0.001). Neither FT4 nor TSH correlated significantly with antibody titers. A significant correlation, however, was noted between anti-Tg and anti-TPO titers. ConclusionRecently developed hypothyroid patients usually have a condition named especially anti-TPO positive, and it is usually accompanied by goitre and family history. Even if the thyroid function tests are not conclusive, early diagnosis and better understanding of the disease process can be made by screening for thyroid antibodies.