Peptidomic profile of human milk as influenced by fortification with different protein sources: An in vitro dynamic digestion simulation.

Fortification of human milk (HM) is often necessary to meet the nutritional requirements of preterm infants. The present experiment aimed to establish whether the supplementation of HM with either an experimental donkey milk-derived fortifier containing whole donkey milk proteins, or with a commercial bovine milk-derived fortifier containing hydrolyzed bovine whey proteins, affects peptide release differently during digestion. The experiment was conducted using an in vitro dynamic system designed to simulate the preterm infant's digestion followed by digesta analysis by means of LC-MS-MS. The different fortifiers did not appear to influence the cumulative intensity of HM peptides. Fortification had a differential impact on the release of either donkey or bovine bioactive peptides. Donkey milk peptides showed antioxidant/ACE inhibitory activities, while bovine peptides showed opioid, dipeptil- and propyl endo- peptidase inhibitory and antimicrobial activity. A slight delay in peptide release from human lactoferrin and α-lactalbumin was observed when HM was supplemented with donkey milk-derived fortifier.

Fixed-Domain Asymptotics Under Vecchia's Approximation of Spatial Process Likelihoods.

Statistical modeling for massive spatial data sets has generated a substantial literature on scalable spatial processes based upon Vecchia's approximation. Vecchia's approximation for Gaussian process models enables fast evaluation of the likelihood by restricting dependencies at a location to its neighbors. We establish inferential properties of microergodic spatial covariance parameters within the paradigm of fixed-domain asymptotics when they are estimated using Vecchia's approximation. The conditions required to formally establish these properties are explored, theoretically and empirically, and the effectiveness of Vecchia's approximation is further corroborated from the standpoint of fixed-domain asymptotics.

Exploring the equity of distribution of general medical services funding allocations in Wales: a time-series analysis.

BACKGROUND: Good access to quality primary care in high-income countries can improve population health. Access to primary care is however often not equal among socioeconomic groups; our analysis sought to explore whether funding, a determinant of service supply, is equitably distributed among GP practices in Wales. AIM: We sought to explore the relationship between funding and deprivation among GP practices in Wales, to understand the equity of current funding policies. DESIGN & SETTING: We obtained funding data for general practices in Wales between 2014 and 2022 and explored the equity of distribution using the percentage of practice patients living in the 20% most deprived small areas in Wales. We generated a linear regression model exploring the relationship between practice funding and deprivation, with an interaction term with time in years. RESULTS: Practice funding rose for all practices between 2014 and 2022. Practice deprivation and time in years were both associated with practice funding, with increases in practice deprivation associated with reduced funding allocations, and time being associated with a small increase in funding over the study period. Over the period of analysis of 2004-2022, for every 10% increase in patients living in the most deprived LSOAs, funding per patient decreases on average by 1%. CONCLUSION: Primary cares in Wales in more deprived areas receive discernibly less funding per patient than those in less deprived areas. Given the potential and likelihood primary care can affect population health outcomes, this underinvestment may be contributing to existing health inequalities and requires urgent further analysis and action.

How to evaluate local fit (residuals) in large structural equation models.

Consistent with reporting standards for structural equation modelling (SEM), model fit should be evaluated at two different levels, global and local. Global fit concerns the overall or average correspondence between the entire data matrix and the model, given the parameter estimates for the model. Local fit is evaluated at the level of the residuals, or differences between observed and predicted associations for every pair of measured variables in the model. It can happen that models with apparently satisfactory global fit can nevertheless have problematic local fit. This may be especially true for relatively large models with many variables, where serious misspecification is indicated by some larger residuals, but their contribution to global fit is diluted when averaged together with all the other smaller residuals. It can be challenging to evaluate local fit in large models with dozens or even hundreds of variables and corresponding residuals. Thus, the main goal of this tutorial is to offer suggestions about how to efficiently evaluate and describe local fit for large structural equation models. An empirical example is described where all data, syntax and output files are freely available to readers.

Genomic signatures of positive selection in Awarik dromedary camels from southwestern of Saudi Arabia.

Introduction: The Awarik camel population in southwestern Saudi Arabia exhibits unique genetic and phenotypic traits compared to other domestic camel populations. This study aims to explore the genomic signatures of positive selection in Awarik camels to understand their evolutionary history and identify genetic adaptations potentially shared with East African camel populations. Methods: Whole genome sequencing data from nine Awarik camels were analyzed using two robust intra-population haplotype-based statistical methods: integrated haplotype score (iHS) and number of segregating sites by length (nSL). These analyses were conducted to identify candidate regions under positive selection within the Awarik camel genome. Results and discussion: These analyses identified 66 and 53 candidate selection regions, encompassing 185 and 123 genes, respectively. The iHS analysis revealed significant selection signals on chromosomes 15 and 16, including a robust overlap on chromosome 15 (10 regions) involving the TRNAI-AAU gene, suggesting its critical role in adaptive processes. Additionally, chromosome 3 exhibited the highest number of candidate regions totaling 10. The nSL analysis highlighted statistically significant regions on chromosomes 2 and 7, as well as a high concentration of candidate regions on chromosome 14, totaling five regions. Notably, large candidate regions were also identified on chromosome 11 (200 kb: 51.750-51.950 kb) and chromosome 9 (325 kb: 45.825-46.150 kb). Functional annotation of these genes revealed involvement in diverse biological processes including olfactory activity, immune regulation, metabolism, insulin secretion, reproductive performance, kidney function, and cellular signaling, with specific genes like BAG5, septin 7, SLC13A1, PCED1B, BMPR1B, ZAR1, JAKMIP2, and NOTCH2 highlighted. These findings contribute to our understanding of the adaptive mechanisms of Awarik camels and have important implications for breeding and conservation strategies. Further research on these genetic adaptations, particularly those affecting immune response, is crucial to mitigate the impacts of climate change on camel populations.

Altered Brain Structure in Hemifacial Spasm Patients: A Multimodal Brain Structure Study.

Objective: Hemifacial spasm (HFS) is a clinical neurosurgical disease, which brain structural alterations caused by HFS remain a topic of debate. We evaluated changes in brain microstructure associated with HFS and observed their relevance to clinical characteristics. Methods: We enrolled 72 participants. T1-weighted structural and diffusion tensor images were collected from all participants using 3.0T magnetic resonance equipment. Voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) were used to identify changes in gray matter volume (GMV) and disruptions in white matter (WM) integrity. The severity of the spasms was graded using the Cohn scale. Results: VBM analysis revealed that the GMV was significantly reduced in the left Thalamus and increased GMV in the right Cerebellum IV-V of the HFS group. TBSS analysis showed that FA in the left superior longitudinal fasciculus (SLF) of the HFS group was significantly increased. GMV in the thalamus showed a negative correlation with disease duration and Cohn grade, while FA in the left SLF had a positive correlation with both the disease duration and Cohn grade. Conclusion: We identified regions with altered GMV in HFS patients. Additionally, we determined that FA in the left SLF might serve as a significant neural indicator of HFS.

Reconsidering Public Attitudes Toward Deceased Organ Donation Registration.

Background: The aim of the current study is to understand Americans' attitudes toward deceased organ donation and to assess their level of acceptance on positions toward organ donation. Methods: In summer and winter of 2023, 2 national samples completed measures of attitudes toward donation, reported their registration status, rated positions related to donation, and provided demographic information. Results: Data from 2 samples indicated registration estimates between 50% and 57% and a significant proportion of those unregistered reported reluctance to register. The believability of national registry estimates and ratings of acceptability of 9 organ donation positions differed by registration status. Conclusion: Mass media and motor vehicles interventions seeking to increase registration rates should take into consideration individual attitudes and support toward donation may not be as strong as once thought.

Exploring the Link Between Parental Sociodemographic Characteristics and Multiple Births: Insights from National Birth Data in Japan, 1995-2020.

This present study investigated the parental characteristics of multiple births using national birth data in Japan. This study included birth data from Vital Statistics: Occupational and Industrial Aspects every five fiscal years from 1995 to 2020. The multiple birth rates were defined as the number of live-birth deliveries with multiple fetuses (e.g., twins, triplets) per total live-birth deliveries. Parental ages, nationalities, occupations and household occupation (occupation of the top earner of the household) were considered as parental characteristics. The multiple birth rates were calculated based on parental characteristics for each year, and a log-binomial regression model was used to assess the association between parental characteristics and multiple births. The multiple birth rate for Japanese mothers consistently exceeded that for non-Japanese mothers over the years, and the rate increased progressively from manual workers to lower non-manual workers and then to upper non-manual workers for both maternal and paternal occupations. The regression results indicated that the risk ratio (RR) for multiple births among non-Japanese mothers was significantly lower than that among Japanese mothers. Moreover, concerning household occupation, the RRs of self-employed individuals, full-time employees at smaller companies, others, and the unemployed were significantly lower than those of full-time employees at larger companies. Furthermore, the RRs of lower non-manual and manual workers were significantly lower than those of upper non-manual workers in maternal and paternal occupations. The results suggested an association between multiple births and parental socioeconomic status in Japan.

Robust and automatic beamstop shadow outlier rejection: combining crystallographic statistics with modern clustering under a semi-supervised learning strategy.

During the automatic processing of crystallographic diffraction experiments, beamstop shadows are often unaccounted for or only partially masked. As a result of this, outlier reflection intensities are integrated, which is a known issue. Traditional statistical diagnostics have only limited effectiveness in identifying these outliers, here termed Not-Excluded-unMasked-Outliers (NEMOs). The diagnostic tool AUSPEX allows visual inspection of NEMOs, where they form a typical pattern: clusters at the low-resolution end of the AUSPEX plots of intensities or amplitudes versus resolution. To automate NEMO detection, a new algorithm was developed by combining data statistics with a density-based clustering method. This approach demonstrates a promising performance in detecting NEMOs in merged data sets without disrupting existing data-reduction pipelines. Re-refinement results indicate that excluding the identified NEMOs can effectively enhance the quality of subsequent structure-determination steps. This method offers a prospective automated means to assess the efficacy of a beamstop mask, as well as highlighting the potential of modern pattern-recognition techniques for automating outlier exclusion during data processing, facilitating future adaptation to evolving experimental strategies.

A Statistical Framework for Assessing the Relationship between Biomarkers and Clinical Endpoints in Alzheimer's Disease.

Changes in biomarker levels of Alzheimer's disease (AD) reflect underlying pathophysiological changes in the brain and can provide evidence of direct and downstream treatment effects linked to disease modification. Recent results from clinical trials of anti-amyloid ß (Aß) treatments have raised the question of how to best characterize the relationship between AD biomarkers and clinical endpoints. Consensus methodology for assessing such relationships is lacking, leading to inconsistent evaluation and reporting. In this review, we provide a statistical framework for reporting treatment effects on early and late accelerating AD biomarkers and assessing their relationship with clinical endpoints at the subject and group levels. Amyloid positron emission tomography (PET), plasma p-tau, and tau PET follow specific trajectories during AD and are used as exemplar cases to contrast biomarkers with early and late progression. Subject-level correlation was assessed using change from baseline in biomarkers versus change from baseline in clinical endpoints, and interpretation of the correlation is dependent on the biomarker and disease stage. Group-level correlation was assessed using the placebo-adjusted treatment effects on biomarkers versus those on clinical endpoints in each trial. This correlation leverages the fundamental advantages of randomized placebo-controlled trials and assesses the predictivity of a treatment effect on a biomarker or clinical benefit. Harmonization in the assessment of treatment effects on biomarkers and their relationship to clinical endpoints will provide a wealth of comparable data across clinical trials and may yield new insights for the treatment of AD.

Space-time scanning statistics in the prediction and evaluation of dengue epidemic clusters.

Objectives: To detect clusters of dengue hemorrhagic fever in an urbanized district of Hai Phong City, Vietnam using Poisson space-time retrospective and prospective analysis. Methods: A cross-sectional and retrospective study analyzed dengue surveillance data in the period from January 01, 2018, to December 31, 2022. Spatial-temporal scanning statistics were performed using the free software SatScan v10.1.2. Results: A total of 519 cases were recorded. The cumulative incidence per 100,000 inhabitants was 3.37, 127.36, 10.96, 0, and 296.04 in 2018, 2019, 2020, 2021, and 2022, respectively. By retrospective Poisson model-based analysis, seven clusters were detected. Six of these seven detected outbreaks occurred in November and December 2022. The largest cluster had a relative risk (RR) of 1539.5 (P <0.00001). The smallest cluster has a RR of 316.1 (P = 0.006). Prospective analysis using the Poisson model significantly detected four active case clusters at the time of the study. The largest cluster of cases with RR was 47.7 (P <0.00001) and the smallest cluster with RR was 18.2 (P <0.00001). Conclusions: This study provides a basis for improving the effectiveness of interventions and conducting further investigations into risk factors in the study area, as well as in other urban and suburban areas nationwide.

Overcoming the pitfalls of categorizing continuous variables in ecology, evolution and behaviour.

Many variables in biological research-from body size to life-history timing to environmental characteristics-are measured continuously (e.g. body mass in kilograms) but analysed as categories (e.g. large versus small), which can lower statistical power and change interpretation. We conducted a mini-review of 72 recent publications in six popular ecology, evolution and behaviour journals to quantify the prevalence of categorization. We then summarized commonly categorized metrics and simulated a dataset to demonstrate the drawbacks of categorization using common variables and realistic examples. We show that categorizing continuous variables is common (31% of publications reviewed). We also underscore that predictor variables can and should be collected and analysed continuously. Finally, we provide recommendations on how to keep variables continuous throughout the entire scientific process. Together, these pieces comprise an actionable guide to increasing statistical power and facilitating large synthesis studies by simply leaving continuous variables alone. Overcoming the pitfalls of categorizing continuous variables will allow ecologists, ethologists and evolutionary biologists to continue making trustworthy conclusions about natural processes, along with predictions about their responses to climate change and other environmental contexts.

Association of early statin initiation during COVID-19 admission with inpatient mortality at an academic health system in Illinois, March 2020 to September 2022: a target trial emulation using observational data.

OBJECTIVE: We assessed the association of early statin initiation with inpatient mortality among hospitalised COVID-19 patients. DESIGN, SETTING AND PARTICIPANTS: This observational study emulated a hypothetical target trial using electronic health records data from Northwestern Medicine Health System, Illinois, 2020-2022. We included patients who were ≥40 years, admitted ≥48 hours for COVID-19 from March 2020 to August 2022 and had no evidence of statin use before admission. INTERVENTIONS: Individuals who initiated any statins within 48 hours of admission were compared with individuals who did not initiate statins during this period. PRIMARY OUTCOME MEASURES: Inpatient mortality at hospital days 7, 14, 21 and 28 were determined using hospital records. Risk differences between exposure groups were calculated using augmented inverse propensity weighting (AIPW) with SuperLearner. RESULTS: A total of 8893 individuals (24.5% early statin initiators) were included. Early initiators tended to be older, male and have higher comorbidity burdens. Unadjusted day 28 mortality was higher in early initiators (6.0% vs 3.6%). Adjusted analysis showed slightly higher inpatient mortality risk at days 7 (RD: 0.5%, 95% CI: 0.2 to 0.8) and 21 (RD: 0.6%, 95% CI: 0.04 to 1.1), but not days 14 (RD: 0.4%, 95% CI: -0.03 to 0.9) and 28 (RD: 0.4%, 95% CI: -0.2 to 1.1). Sensitivity analyses using alternative modelling approaches showed no difference between groups. CONCLUSIONS: Early statin initiation was not associated with lower mortality contrasting with findings of previous observational studies. Trial emulation helped in identifying and addressing sources of bias incompletely addressed by previous work. Statin use may be indicated for other conditions but not COVID-19.

An optimized instrument variable selection approach to improve causality estimation in association studies.

Mendelian randomization (MR) is an emerging tool for inferring causality in genetic epidemiology. MR studies suffer bias from weak genetic instrument variables (IVs) and horizontal pleiotropy. We introduce a robust integrative framework strictly adhering with STROBE-MR guidelines to improve causality inference through MR studies. We implemented novel t-statistics-based criteria to improve the reliability of selected IVs followed by various MR methods. Further, we include sensitivity analyses to remove horizontal-pleiotropy bias. For functional validation, we perform enrichment analysis of identified causal SNPs. We demonstrate effectiveness of our proposed approach on 5 different MR datasets selected from diverse populations. Our pipeline outperforms its counterpart MR analyses using default parameters on these datasets. Notably, we found a significant association between total cholesterol and coronary artery disease (P = 1.16 × 10-71) in a single-sample dataset using our pipeline. Contrarily, this same association was deemed ambiguous while using default parameters. Moreover, in a two-sample dataset, we uncover 13 new causal SNPs with enhanced statistical significance (P = 1.06 × 10-11) for liver-iron-content and liver-cell-carcinoma. Likewise, these SNPs remained undetected using the default parameters (P = 7.58 × 10-4). Furthermore, our analysis confirmed previously known pathways, such as hyperlipidemia in heart diseases and gene ME1 in liver cancer. In conclusion, we propose a robust and powerful framework to infer causality across diverse populations and easily adaptable to different diseases.

Summary statistics knockoffs inference with family-wise error rate control.

Testing multiple hypotheses of conditional independence with provable error rate control is a fundamental problem with various applications. To infer conditional independence with family-wise error rate (FWER) control when only summary statistics of marginal dependence are accessible, we adopt GhostKnockoff to directly generate knockoff copies of summary statistics and propose a new filter to select features conditionally dependent on the response. In addition, we develop a computationally efficient algorithm to greatly reduce the computational cost of knockoff copies generation without sacrificing power and FWER control. Experiments on simulated data and a real dataset of Alzheimer's disease genetics demonstrate the advantage of the proposed method over existing alternatives in both statistical power and computational efficiency.

F ST between haploids and diploids in species with discrete ploidy phases.

Many organisms alternate between distinct haploid and diploid phases, which generates population structure according to ploidy level. In this research, we consider a haploid-diploid population using statistical approaches developed for spatially subdivided populations, where haploids represent one "patch" and diploids another "patch". In species with alternating generations, sexual reproduction causes movement from diploids to haploids (by meiosis with recombination) and from haploids to diploids (by syngamy). Thus, an allele in one ploidy phase can be said to "migrate" to the other ploidy phase by sexual reproduction and to "remain" in the same ploidy phase by asexual reproduction. By analyzing a coalescent model of the probability of identity by descent and by state for a haploid-diploid system, we define FST-like measures of differentiation between haploids and diploids and show that these measures can be simplified as a function of the extent of sexuality in each ploidy phase. We conduct simulations with an infinite-alleles model and discuss a method for estimating the degree of effective sexuality from genetic data sets that uses the observed FST measures of haploid-diploid species.

Bayesian identification and estimation of radon-related increased hazard rates of cancer death in the updated French cohort of uranium miners (1946-2014).

OBJECTIVE: A recent update of the French cohort of uranium miners added seven years of follow-up data. We use these new data to look for new possible radon-related increased risks and refine the estimation of the potential association between cumulative radon exposure and four cancer sites: lung cancer, kidney cancer, brain and central nervous system (CNS) cancer and leukemia (excluding chronic lymphocytic leukemia, which is not radiation-induced). METHODS: Several parametric survival models are proposed, fitted and compared under the Bayesian paradigm, to perform new and original exposure-risk analyses. In line with recent UNSCEAR recommendations, we consider time-related effect modifiers and exposure rate as potential effect modifying factors. We use Bayesian model selection criteria to identify radon-related increased hazard rates. RESULTS: Under the assumption of a linear exposure-risk relationship, we found a substantial evidence for a strictly positive effect of cumulative radon exposure on the hazard rate of death by lung cancer among French uranium miners. Given the current available data under the assumptions of a linear or log-linear exposure-risk relationship, it is not possible to conclude in favour of the absence or the existence of a strictly positive effect of chronic exposure to radon on the hazard rate of death by kidney cancer. Regarding death by brain and CNS cancer, there is a substantial evidence for the absence of radon-related effect. Finally, under the assumption of a log-linear exposure-risk relationship, a small positive radon-related effect appears when looking at the risk of death by leukemia (excluding CLL). CONCLUSION: This study investigates the existence of radon-related increased risk of death by lung cancer, kidney cancer, brain and CNS cancer and leukemia under a Bayesian framework and assumptions of linear and log-linear exposure-risk relationships. If there is no doubt in the interpretation of the results for lung cancer and brain and CNS cancer, the conclusion is less clear-cut in the case of kidney cancer and leukemia (excluding CLL). A future update of the French cohort, increasing the follow-up time for miners, may help to reach a clearer conclusion for these two cancer sites.

Use of emergency departments by children and young people following telephone triage: a large database study.

BACKGROUND: Although one objective of NHS 111 is to ease the strain on urgent and emergency care services, studies suggest the telephone triage service may be contributing to increased demand. Moreover, while parents and caregivers generally find NHS 111 satisfactory, concerns exist about its integration with the healthcare system and the appropriateness of advice. This study aimed to analyse the advice provided in NHS 111 calls, the duration between the call and ED attendance, and the outcomes of such attendances made by children and young people (C&YP). METHODS: A retrospective cohort study was carried out of C&YP (≤17) attending an ED in the Yorkshire and Humber region of the UK following contact with NHS 111 between 1 April 2016 and 31 March 2017. This linked-data study examined NHS 111 calls and ED outcomes. Lognormal mixture distributions were fit to compare the time taken to attend ED following calls. Logistic mixed effects regression models were used to identify predictors of low-acuity NHS 111-related ED attendances. RESULTS: Our study of 348 401 NHS 111 calls found they were primarily concerning children aged 0-4 years. Overall, 13.1% of calls were followed by an ED attendance, with a median arrival time of 51 minutes. Of the 34 664 calls advising ED attendance 41% complied, arriving with a median of 38 minutes-27% of which defined as low-acuity. Although most calls advising primary care were not followed by an ED attendance (93%), those seen in an ED generally attended later (median 102 minutes) with 23% defined as low-acuity. Younger age (<1) was a statistically significant predictor of low-acuity ED attendance following all call dispositions apart from home care. CONCLUSION: More tailored options for unscheduled healthcare may be needed for younger children. Both early low-acuity attendance and late high-acuity attendance following contact with NHS 111 could act as useful entry points for clinical audits of the telephone triage service.

Global, regional, and national burden of acute myeloid leukemia, 1990-2021: a systematic analysis for the global burden of disease study 2021.

BACKGROUND: Acute myeloid leukemia (AML), as the most common subtype of leukemia in adults, is characterised by rapid progression and poor prognosis. In the context of the rapid development of medical technology and the complexity of social factors, a detailed report describing the latest epidemiological patterns of AML is important for decision makers to allocate healthcare resources effectively. METHODS: Our research utilized the latest data sourced from the Global Burden of Disease (GBD) 2021. To delineate the burden of AML, we comprehensively described the incidence, deaths, disability-adjusted life years (DALYs), and the associated age-standardized rates per 100,000 persons (ASR) spanning from 1990 to 2021 stratifies according to age, sex, socio-demographic index (SDI), and nationality. Additionally, we extracted and analyzed data about the risk factors that contribute to AML-related deaths and DALYs. RESULTS: According to our study, the incidence of AML has continued to rise globally from 79,372 in 1990 to 144,645 in 2021 and AML affected the male and the elderly populations disproportionately. Furthermore, there was a significant positive correlation between the burden of AML and the SDI value. Developed nations generally exhibited higher age-standardized incidence rate, age-standardized death rate, and age-standardized disability-adjusted life year rate than the developing nations. We also analyzed the prevalence of smoking, high body mass index, and occupational benzene and formaldehyde exposure in the AML population in different SDI regions. Moreover, smoking and high body mass index were more prevalent in developed countries, whereas occupational exposure to these chemicals was the predominant risk factor in developing countries. CONCLUSION: The global burden of AML has increased over the past 32 years, with rising morbidity and mortality. The incidence of AML is differentially distributed across different SDI countries or regions. AML incidence is higher in the elderly and in men. The proportions of smoking, high body mass index, and occupational exposure to benzene and formaldehyde varied by region. The findings highlight the need for region-specific prevention and call for future research on preventive strategies and new treatments to lower AML incidence and improve patient outcomes.