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Results for “Bayesian modelling”

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PubMedDate not supplied

Bayesian analysis of a dose-response experiment with serial sacrifices.

This paper presents analysis and comments which are believed to be appropriate for certain carcinogenesis studies where sacrifices are performed throughout the experiment. Estimates of the risk probability for each dose level and sacrifice time are found utilizing the sample likelihood as the posterior density. The dose-response relationship is investigated with these estimates as the response. In order to test if the dose is effective and to check the appropriateness of the time-to-incidence model a Bayesian multiple comparisons technique is introduced.

Animals↗

PubMedDate not supplied

How much quality control is enough? A cost-effectiveness model for clinical laboratory quality control procedures (illustrated by its application to a ligand-assay-based screening program).

Quality assurance testing represents a substantial proportion of the clinical laboratory budget, but current guidelines are based on criteria that pertain to analytic error rather than to optimization of the cost-effectiveness of patient care. A general Bayesian mathematical model for the cost-effectiveness of assay quality control has been developed, and is demonstrated using previously published data. The cost-effectiveness of quality assurance as defined here depends upon the prevalence of disease, the shapes of the distributions of test results observed in the non-diseased and diseased populations, the decision limit selected for labeling results positive or negative, the costs and benefits associated with each of the possible therapeutic outcomes, the magnitude of random and systematic analytical errors, the statistical power of the quality control test in use, the costs associated with delays due to re-assay, and the proportion of total test cost attributable to quality control procedures. Given current clinical laboratory practice, much of this information will not be routinely available. The model combines these factors into a simple equation with three terms: one for the cost of the original and any required repeat laboratory analyses, one for the cost of delay entailed by the rejection of an assay batch, and one for the change in total costs consequent to rejection of erroneous assay results.

Clinical Laboratory Techniques↗

PubMed2025

Generative model for the first cell fate bifurcation in mammalian development.

The first cell fate bifurcation in mammalian development directs cells toward either the trophectoderm (TE) or inner cell mass (ICM) compartments in pre-implantation embryos. This decision is regulated by the subcellular localization of a transcriptional co-activator YAP and takes place over several progressively asynchronous cleavage divisions. As a result of this asynchrony and variable arrangement of blastomeres, reconstructing the dynamics of the TE/ICM cell specification from fixed embryos is extremely challenging. To address this, we developed a live-imaging approach and applied it to measure pairwise dynamics of nuclear YAP and its direct target genes, CDX2 and SOX2, which are key transcription factors of the TE and ICM, respectively. Using these datasets, we constructed a generative model of the first cell fate bifurcation, which reveals the time-dependent statistics of the TE and ICM cell allocation. In addition to making testable predictions for the joint dynamics of the full YAP/CDX2/SOX2 motif, the model revealed the stochastic nature of the induction timing of the key cell fate determinants and identified the features of YAP dynamics that are necessary or sufficient for this induction. Notably, temporal heterogeneity was particularly prominent for SOX2 expression among ICM cells. As heterogeneities within the ICM have been linked to the initiation of the second cell fate decision in the embryo, understanding the origins of this variability is of key significance. The presented approach reveals the dynamics of the first cell fate choice and lays the groundwork for dissecting the next cell fate decisions in mouse development.

Animals↗

PubMed1991

Estimation of relative potency with sequential dilution errors in radioimmunoassay.

Sequential dilution is a very common procedure in radioimmunoassay, in which the dilution error will be accumulated from the highest to the lowest concentration. A simulated example in relative potency determination is used to demonstrate the potentially wrong conclusion that can be drawn, when the dilution error is not properly included in the model. A Bayesian method is used and an alternative approximation via maximum likelihood is proposed. An alternative experimental design is recommended to increase the precision of the inference.

Bayes Theorem↗

PubMed2026

Comparative effectiveness of game-based learning modalities in nursing and medical education: a systematic review and Bayesian network meta-analysis.

BACKGROUND: Game-based learning (GBL) is increasingly used in healthcare education, but educators must choose among diverse modalities (e.g., quiz platforms, apps, serious games and metaverse environments). Comparative evidence on which modalities perform best across learning domains (knowledge, attitudes, and practice) remains limited. AIM: To compare the effects of distinct GBL modalities on knowledge, attitudes, and practice outcomes in nursing and medical education and to explore whether comparative effects differ by learner group (pre-licensure students and in-service professionals). DESIGN: PRISMA-NMA-aligned systematic review and Bayesian network meta-analysis. METHODS: We searched eight databases and trial registries through September 2, 2024, for randomized controlled trials comparing GBL with traditional teaching (TT). Outcomes were transformed to a 0-100 scale and analysed as change from baseline in Bayesian consistency models; random-effects models were selected using deviance information criterion (DIC). Risk of bias was assessed using RoB 2. We report mean differences (MDs) with 95% credible intervals (CrIs) versus TT, ranking probabilities, and subgroup NMAs by learner group. RESULTS: Thirty-one RCTs (n = 3439) were included; 15 contributed complete data to the network. Risk of bias was low in 15 trials and raised some concerns in 16. The network was modest for knowledge (11 trials) and sparse for attitudes (3) and practice (4). Compared with TT, metaverse-based learning showed improved attitudes (MD 15; 95% CrI 12 to 18), based on a single trial. For knowledge and practice, Kahoot-based quizzes (MD 9.1; 95% CrI -8.9 to 27) and app-based learning (MD 4.6; 95% CrI -4.4 to 14) had the highest estimated mean improvements, but credible intervals were wide and included the null for most comparisons. Subgroup rankings differed by learner group, but several comparisons were imprecise and uncertainty was substantial, particularly in sparse networks. CONCLUSIONS: GBL modalities may improve learning outcomes compared with TT, but relative effects appear domain-specific and the certainty of rankings is limited by sparse evidence and imprecision. Future trials should prioritise head-to-head comparisons, robust outcome measurement, and longer-term retention and transfer outcomes in both student and in-service populations.

Humans↗

PubMed2026

Minimally invasive versus open abdominoperineal resection and the risk of postoperative perineal hernia: a systematic review and meta-analysis.

BACKGROUND: The impact of minimally invasive surgery on the risk of postoperative perineal hernia after abdominoperineal resection (APR) or extralevator abdominoperineal excision (ELAPE) remains uncertain. This study compares perineal hernia rates and perioperative outcomes between minimally invasive and open approaches. METHODS: PubMed, Scopus, Web of Science, and Cochrane Library were searched through June 2026. Pooled odds ratios (ORs) and mean differences (MDs) with 95% confidence intervals (CIs) were calculated using random-effects models. A Bayesian meta-analysis was additionally performed for the primary outcome. RESULTS: Four comparative observational studies involving 763 patients were included; 249 underwent minimally invasive APR/ELAPE, and 514 underwent open APR/ELAPE. Postoperative perineal hernia was significantly more frequent following minimally invasive surgery (OR 4.13; 95% CI 2.24-7.61; p < 0.001). Intraoperative blood loss was significantly lower in the minimally invasive group (MD - 156.5 mL; 95% CI - 298.4 to - 14.5; p = 0.03), as was operative time (MD - 41.7 min; 95% CI - 60.8 to - 22.5; p < 0.01). No significant differences were observed in hospital stay (MD - 2.5 days; 95% CI - 5.4 to 0.4; p = 0.09) or 30-day readmission rates (OR 1.41; 95% CI 0.82-2.42; p = 0.209). Bayesian analysis yielded a posterior mean OR of 4.04 (95% CrI 1.96-8.36), corresponding to a 99.9% posterior probability that minimally invasive surgery increases the risk of postoperative perineal hernia. CONCLUSION: Minimally invasive APR/ELAPE was associated with an increased risk of postoperative perineal hernia compared with the open approach. Strategies to reduce this complication while preserving the benefits of minimally invasive surgery warrant further investigation.

Humans↗

PubMed1986

The objective interpretation of histopathological data: an application to the ageing of ovine bruises.

Muscle and adipose tissue from a total of 178 experimental bruises inflicted on sheep and aged from 1 to 72 h old were processed for light microscopic examination. Five observed histopathological features of inflammation and repair were scored semiquantitatively on a scale of 1-4 according to their degrees of change from the normal state. These data were evaluated mathematically using a Bayesian probability model designed for the purpose. The model was able to age bruises with an acceptable degree of accuracy only as either 1-20 h or 24-72 h old but within these constraints a degree of confidence in excess of 90% was achieved. The exact performance of the model depended on the nature and number of tissue samples examined but mathematical ageing was superior to interpretative ageing based on personal experience.

Adipose Tissue↗

PubMed1989

Computer-assisted optimization of aminophylline therapy in the emergency department.

The emergency department (ED) is a unique setting for pharmacokinetic-guided drug administration because of the need to rapidly optimize therapy. We compared outcomes in patients receiving intravenous aminophylline according to population-based ED guidelines (group 1) or Bayesian-derived pharmacokinetic estimates (group 2), we determined predictors for admission or discharge in our study group, and we assessed the ability of a Bayesian pharmacokinetic model to estimate theophylline requirements in the ED. The study population was composed of 82 patients (42 males, 40 females) with a mean age of 43 +/- 15.5 years. Fifteen patients were excluded because of protocol violations. Of the 67 cases studied, 30 were assigned to group 1, and 37 were assigned to group 2. Patient demographics, baseline theophylline concentration, and theophylline loading dose did not differ significantly between treatment groups. The aminophylline maintenance infusion was significantly (P less than .001) lower in group 1 (0.4 +/- 0.2 mg/kg/h) than in group 2 (0.6 +/- 0.2 mg/kg/h). Serum theophylline concentrations at one hour post-loading-dose did not differ significantly between treatment groups; however, significant differences were observed at two hours post-load (P less than .002) and four hours post-load (P less than .001). Baseline peak flow rate (PFR) was significantly (P less than .03) higher in group 1 (170 +/- 85 L/min) than in group 2 (132 +/- 62 L/min), but did not differ significantly at any other times throughout the study. The PFR one hour post-load (PFR-1) was the strongest (P less than .003) predictor of outcome.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗

PubMed2026

Precision targeting of teacher burnout using network-informed ecological momentary interventions.

Teacher well-being affects classroom functioning and workforce stability, yet generic digital programs rarely use person-specific affect dynamics to select support. This cluster-randomised trial evaluated whether micro-interventions selected from high expected influence (EI) nodes in teachers' contemporaneous affect networks produced larger changes in burnout-related EI and everyday happiness than content-matched random allocation. The objectives were to estimate allocation effects on changes in estimated network summaries and happiness, evaluate network change as a statistical mediator, examine personality moderation, and benchmark simpler allocation rules. A two-arm cluster randomised platform trial was conducted in 84 public schools across four urban districts in H Province. After a 14 day baseline of ecological momentary assessment (EMA), person specific partial correlation networks were estimated for happiness, exhaustion, detachment, efficacy and rumination. An optimisation engine prioritised three brief micro-intervention types per teacher according to baseline EI, while the active control received the same library without network information. EMA continued for 8 weeks; Bayesian multilevel models, permutation-based mediation, and benchmarking analyses were applied. EI-based targeting produced larger reductions in the composite EI-change index than active control (mean difference 0.11, 95% credible interval 0.08 to 0.14) and higher week 7 EMA happiness (4.4 points on a 0 to 100 scale, 95% credible interval 2.7 to 6.0), with a positive arm by week slope difference of 0.62 points per week (95% credible interval 0.39 to 0.85). Model-based mediation estimates were consistent with approximately one half of the happiness difference being statistically associated with change in the composite EI-change index (average conditional mediation estimate 3.5 points, 95% credible interval 2.0 to 5.2). Benchmarking showed smaller gains under severity, threshold, or group-level centrality rules. Effects were stronger among teachers higher in conscientiousness. The findings indicate that integrating EMA, network modelling, and EI-driven optimisation yields measurable gains beyond content-matched exposure, providing a proof of concept for district-scale precision mental health that requires prospective implementation testing. Replication in additional regions, expanded node sets, and longer follow up are warranted to assess durability and generalisability.

Female↗

PubMed2026

Pneumococcal population structure influences the effects of air pollution on invasive disease risk in South Africa.

Streptococcus pneumoniae is highly diverse, comprising over 100 serotypes and hundreds of genomic lineages amid widespread vaccination. While it can cause invasive pneumococcal disease (IPD) which exhibits pronounced seasonal spikes, the interplay between pneumococcal diversity and environmental drivers remains unexplored. Here we analysed 59,017 IPD cases over 19 years from South Africa, incorporating 4,350 genome-sequenced isolates, using Bayesian spatiotemporal models to link environmental exposure and pneumococcal diversity. Cumulatively, across an 8-week period, moderate relative humidity (33-49%) and cold minimum temperatures (4-10 °C) increased IPD risk by 5% and 4%, respectively. Conversely, warm maximum temperatures (27-38 °C) were associated with up to a 10% increased risk within a week of exposure. There was a positive association between air pollution (PM2.5) and IPD, although it varied by age, disease presentation, and most notably serotype and lineage. Specifically, the lag time between PM2.5 exposure and disease onset varied by serotype, with only serotypes 4, 8 and 23F conferring an immediate IPD risk. High prevalence of GPSC21 lineage (serotype 19F) also modified the pollution response, shifting the lag structure to produce immediate risk of disease following high PM2.5 exposure. Our results demonstrate that pneumococcal population structure shapes air quality risk which in turn can shape the fitness landscape of microbial populations. Integration of these data may inform public health policy.

Journal Article↗

PubMed2025

Limited contributions of bacteria and fungi to coral nutrition revealed by amino acid δ13C analysis.

Corals often form reef ecosystems that support diverse marine life, but they are sensitive to environmental fluctuations that can affect their nutrient acquisition. While coral-associated microbes (e.g., Symbiodiniaceae, bacteria and fungi) may supplement nutrients to coral hosts via metabolite translocation and nutrient recycling, the extent to which these microbial partners contribute to coral autotrophy or heterotrophy remains unclear. Here, we seasonally measure the carbon isotopes of amino acids (δ13CAA) in reef-building coral Pocillopora damicornis and its nutrient sources (e.g., Symbiodiniaceae and particulate organic matter). Regional Bayesian mixing models show that P. damicornis increased autotrophy (from 67.1 to 80.5%), but decreased particulate feeding (from 32.9 to 19.5%) from the cool season to the warm season. Stable essential δ13CAA values (valine, leucine and isoleucine) suggest limited seasonal changes in microbial contributions. Linear discriminant analysis, which combines current and published data from basal organisms (e.g., bacteria and fungi) to coral consumers, also reveals limited bacterial and fungal contributions to coral nutrition. Thus, we advocate that coral nutrition is primarily determined by Symbiodiniaceae translocation and particulate feeding. As these nutritional pathways are highly subject to environmental fluctuations, corals lacking trophic flexibility may suffer more from malnutrition and even population decline under global environmental change.

Anthozoa↗

PubMed2025

Detection of cell-type-specific differentially methylated regions in epigenome-wide association studies.

MOTIVATION: DNA methylation at cytosine-phosphate-guanine (CpG) sites is one of the most important epigenetic markers. Therefore, epidemiologists are interested in investigating DNA methylation in large cohorts through epigenome-wide association studies (EWAS). However, the observed EWAS data are bulk data with signals aggregated from distinct cell types. Deconvolution of cell-type-specific signals from EWAS data is challenging because phenotypes can affect both cell-type proportions and cell-type-specific methylation levels. Recently, there has been active research on detecting cell-type-specific risk CpG sites for EWAS data. However, existing methods all assume that the methylation levels of different CpG sites are independent and perform association detection for each CpG site separately. Although these methods significantly improve the detection at the aggregated-level-identifying a CpG site as a risk CpG site as long as it is associated with the phenotype in any cell type, they have low power in detecting cell-type-specific associations for EWAS with typical sample sizes. RESULTS: Here, we develop a new method, Fine-scale inference for Differentially Methylated Regions (FineDMR), to borrow strengths of nearby CpG sites to improve the cell-type-specific association detection. Via a Bayesian hierarchical model built upon Gaussian process functional regression, FineDMR takes advantage of the spatial dependencies between CpG sites. FineDMR can provide cell-type-specific association detection as well as output subject-specific and cell-type-specific methylation profiles for each subject. Simulation studies and real data analysis show that FineDMR substantially improves the power in detecting cell-type-specific associations for EWAS data. AVAILABILITY AND IMPLEMENTATION: FineDMR is freely available at https://github.com/JiaRuofan/Detection-of-Cell-type-specific-DMRs-in-EWAS.

DNA Methylation↗

PubMed2025

Bayesian estimation of allele-specific expression in the presence of phasing uncertainty.

MOTIVATION: Allele-specific expression (ASE) analyses aim to detect imbalanced expression of maternal versus paternal copies of an autosomal gene. Such allelic imbalance can result from a variety of cis-acting causes, including disruptive mutations within one copy of a gene that impact the stability of transcripts, as well as regulatory variants outside the gene that impact transcription initiation. Current methods for ASE estimation suffer from a number of shortcomings, such as relying on only one variant within a gene, assuming perfect phasing information across multiple variants within a gene, or failing to account for alignment biases and possible genotyping errors. RESULTS: We developed BEASTIE, a Bayesian hierarchical model designed for precise ASE quantification at the gene level, based on given genotypes and RNA-Seq data. BEASTIE addresses the complexities of allelic mapping bias, genotyping error, and phasing errors by incorporating empirical phasing error rates derived from Genome-in-a-Bottle individual NA12878. BEASTIE surpasses existing methods in accuracy, especially in scenarios with high phasing errors. This improvement is critical for identifying rare genetic variants often obscured by such errors. Through rigorous validation on simulated data and application to real data from the 1000 Genomes Project, we establish the robustness of BEASTIE. These findings underscore the value of BEASTIE in revealing patterns of ASE across gene sets and pathways. AVAILABILITY AND IMPLEMENTATION: The software is freely available from Github (https://github.com/x811zou/BEASTIE); and Zendo (DOI: 10.5281/zenodo.15062124).

Bayes Theorem↗

PubMed2025

Bayesian reconstruction and differential testing of excised introns.

MOTIVATION: Characterizing the differential excision of introns is critical for understanding the functional complexity of a cell or tissue, from normal developmental processes to disease pathogenesis. Most transcript reconstruction methods infer full-length transcripts from high-throughput sequencing data. However, this is a challenging task due to incomplete annotations and the heterogeneous expression of transcripts across cell-types, tissues, and experimental conditions. Several recent methods circumvent these difficulties by considering local splicing events, but these methods lose transcript-level splicing information and may conflate similar, but distinct transcripts. RESULTS: In this work, we formalize a new transcript reconstruction problem that interpolates between the full-length and local splicing perspectives by considering sequences of exon-exon junctions (SEEJs) that co-occur in transcripts. We then present a hierarchical Bayesian admixture model and posterior inference algorithms for computing SEEJs (BSEEJ), and a generalized linear model for characterizing differential SEEJ usage based on model parameter estimates. We show that BSEEJ achieves high F1 score for reconstruction tasks and improved accuracy and sensitivity in differential splicing when compared with six transcript and local splicing methods on simulated data. Lastly, we evaluate BSEEJ on experimental data based on transcript reconstruction, novelty of transcripts produced, model sensitivity to hyperparameters, and a functional analysis of differentially expressed SEEJs. AVAILABILITY AND IMPLEMENTATION: BSEEJ is freely available at https://github.com/bayesomicslab/BSEEJ.

Bayes Theorem↗

PubMed1978

Computer-assisted identification of anaerobic bacteria.

A computer program was developed to identify anaerobic bacteria by using simultaneous pattern recognition via a Bayesian probabilistic model. The system is intended for use as a rapid, precise, and reproducible aid in the identification of unknown isolates. The program operates on a data base of 28 genera comprising 238 species of anaerobic bacteria that can be separated by the program. Input to the program consists of biochemical and gas chromatographic test results in binary format. The system is flexible and yields outputs of: (i) most probable species, (ii) significant test results conflicting with established data, and (iii) differential tests of significance for missing test results.

Anaerobiosis↗

PubMed2026

Genomic background of gestation length and calving-related traits in Holstein cattle.

The reproductive success of cows directly influences the profitability of dairy farms. Reproductive traits, particularly calving-related traits, generally have low heritability but sufficient additive genetic variance to enable genetic progress through genomic selection. Thus, the primary objectives of this study were to estimate genetic parameters and perform single-step genome-wide association studies (ssGWAS) for calf size, calving ease, gestation length, and stillbirth in Holstein cattle. Variance components were estimated based on animal models and Bayesian inference using a data set containing 226,717 animals with phenotypic records, 15,761 animals genotyped with 45,101 SNP markers, and 461,819 animals in the pedigree. SNP effects were estimated using the single-step GBLUP method. For direct and maternal genetic effects, heritability estimates (posterior standard deviation) ranged from 0.001 (0.002) for gestation length in heifers to 0.16 (0.001) for gestation length in cows. Genetic correlations ranged from -0.57 (0.01) between calving ease and stillbirth in heifers to 0.74 (0.01) between gestation length evaluated in heifers and cows. The ssGWAS results supported a highly polygenic architecture for calving-related traits, with most genomic signals not reaching genome-wide significance. A genome-wide significant association was detected for calving ease in cows on BTA23, highlighting FARS2 as a positional candidate gene. The strongest GWAS signals for each trait harbored additional biologically important candidate genes, including NPPA, NPPB, BCHE, EPHA4, DLD, and GTF2I. Given the generally low heritability estimates and the predominantly polygenic architecture observed for these traits, genomic selection may contribute to the genetic improvement of calving-related traits in Holstein cattle, with potential benefits for cow welfare, calf survival, and overall dairy production efficiency.

dairy cattle↗

PubMed1987

Empirical Bayesian estimation in the logistic model.

Explore the source record for details and available documents.

Bayes Theorem↗

PubMed1988

Transplantation statistics in the UK--an agenda for the next quinquennium.

Our next quinquennial plan for transplantation studies extends MPI to corneal and unrelated marrow transplantation. It applies Bayesian hierarchical modelling to regional variation in donor procurement and continues a program of special studies to augment national databases with respect to kidney, corneal, heart and liver transplantation. It promotes research collaboration among European and other organ exchange organizations as pioneered in the Council of Europe 1986 Study on High Sensitization, which showed the effectiveness of the network of European organ exchange organizations in liaising with transplant units.

Bayes Theorem↗