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PubMed1990

Simulation of mechanisms of viral interference in influenza.

Biological interference among viral agents might have significant implications for disease prevention and therapy. Field data for influenza yield conflicting evidence concerning the independence of infection rates, or disease severity, for two co-circulating viruses. To examine the effects of several assumed modes of interference for influenza, simulations of a Monte Carlo micropopulation model of influenza epidemics have been performed. Model parameters were selected so that the simulated attack rates for each of two different viral strains matched actual field data. Rates of infection were compared for single agents and for two viruses with only behavioural interference. Other simulations included temporary immunity to the other virus for the duration of the infection, and/or reduced shedding of viral particles for dual infections. Simulated viral competition had little impact on epidemic severity, duration, or size distribution. Under the conditions studied, viral interference in natural populations would be difficult to infer from field observations of attack rates. Other simulations extended a partial immunity and/or reduced viral shedding during an infection with a second virus. These indicated that interference might be suggested by field data, but it could not be demonstrated conclusively. Still other simulations showed that for epidemics with much higher attack rates for both viruses, it would be relatively easy to demonstrate interference. However, in order to observe interference between influenza strains, it would be necessary to monitor on an almost daily basis, using a method of viral detection which would have to be both highly specific and also very sensitive.

Adolescent↗

PubMed1991

Computer simulations of chondrocytic clone behaviour in rabbit growth plates.

The growth behaviour of chondrocytic clones in the cell columns of the proximal tibial growth plates of young rabbits was modelled in computer simulations. Simulations were performed, modelling either clones in large groups of columns or clones in one single column. The former were based on morphological data and measurements of cell columns from an earlier study while the latter utilised previous findings of cellular kinetics in rabbit growth plates. Simulation results that resembled most closely the actual observations on rabbit growth plates were those in which a distribution of values was assumed both for clone length (ranging from 1000 to 2000 microns) and for the lengths of the discontinuities between clones. When the assumption was made in the models that the disappearing (metaphyseal) end of an 'old' clone moved more rapidly than the developing (epiphyseal) end of a 'new' clone, replacing the former, the length of the discontinuity between these two clones increased with time. This assumption, which could be modelled in the simulations of clones in a single column based on cell growth behaviour, was found to provide an explanation for an earlier finding that there are more short columns at the epiphyseal side than at the metaphyseal side of a growth plate.

Animals↗

PubMed1991

Quality of laboratory performance in testing for human immunodeficiency virus type 1 antibody. Variables associated in multivariate analyses.

In May 1988, the Centers for Disease Control's Model Performance Evaluation Program (Atlanta, Ga) surveyed 1092 laboratories that performed enzyme immunoassays and Western blot tests for human immunodeficiency virus type 1 antibody on mailed plasma samples of known human immunodeficiency virus type 1 antibody reactivity and that described their laboratory characteristics and testing practices. The study objective was to evaluate the quality of laboratory performance in testing for human immunodeficiency virus type 1 antibody. After identifying relevant variables in univariate analyses, multivariate analyses were performed using stepwise logistic models. Human immunodeficiency virus type 1 antibody test performance was independently associated with analytic variables such as commercial test kit used and with nonanalytic variables such as experience, training, and degree requirements of laboratory personnel. These results validate the importance of nonanalytic variables to the quality of outcomes in laboratory testing.

AIDS Serodiagnosis↗

PubMed2026

Machine learning-based clinical tool for identifying factors associated with symptomatic knee osteoarthritis: the Nagahama study.

BACKGROUND: A clinical tool that evaluates factors associated with symptomatic knee osteoarthritis (OA) based on modifiable factors is lacking. This study aimed to develop a machine learning-based clinical assessment tool using modifiable factors to identify factors associated with symptomatic knee OA and to determine its accuracy. METHODS: This study included 429 participants (81.8% women; age, 69.0 ± 5.3 years) from the Nagahama Study who were ≥60 years old and had radiographically confirmed knee OA. A Knee Society Knee Scoring System 2011 symptom score of <23 points defined symptomatic knee OA. Participants were randomly assigned to training (70%) and test (30%) datasets. A machine learning model was developed using Extreme Gradient Boosting with 27 variables, and the SHapley Additive exPlanation (SHAP) values were used to assess feature importance. The top 8 features were translated into a 100-point clinical scoring tool weighted by their SHAP contributions. The cutoff value indicating symptomatic knee OA in the clinical assessment tool was determined using receiver operating characteristic analysis, and model performance was evaluated in both datasets. RESULTS: The clinical assessment tool consisted of low back pain, OA severity, depressive tendencies, knee flexion/extension range of motion, knee extension and hip abduction strength, and lower limb muscle quality. The model showed moderate discriminative performance (AUC 0.771 and 0.773 in the training and test datasets, respectively), with a cutoff point of 47. CONCLUSION: The proposed clinical assessment tool may provide a structured framework for assessing modifiable factors associated with symptomatic knee OA, reflecting their contribution to current symptom status.

Humans↗

PubMed2026

Externally validated risk prediction models for gestational diabetes mellitus: A systematic review and meta-analysis.

INTRODUCTION: Risk prediction models for gestational diabetes mellitus (GDM) offer potential for early identification and targeted prevention. External validation is crucial to assess model performance across diverse populations. Despite the availability of numerous GDM prediction models, limited evidence exists on their external validation frequency, methodological quality, and clinical applicability. This systematic review evaluated externally validated GDM prediction models, focusing on methodological rigor, reporting standards, and clinical relevance to inform future research and implementation. MATERIAL AND METHODS: Databases including Ovid MEDLINE, Embase, Scopus, Emcare, and CINAHL were searched up to May 1, 2025. Studies reporting external validation of GDM risk prediction models were included. Two reviewers independently screened studies. Data were extracted using the CHARMS framework, and risk of bias and applicability were assessed using PROBAST+AI. The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO; CRD420251125758). RESULTS: Twenty-six studies validated 33 models, with validation sample sizes ranging from 50 to 75 161. Over half used the IADPSG criteria to define GDM. Discrimination metrics were commonly reported, but calibration, overall performance, and clinical utility were often lacking. Meta-analysis was feasible for only four models: Teede et al., Nanda et al., Naylor et al., and Van Leeuwen et al., each showing fair discrimination. The Teede et al. model was the most widely validated, with 11 external validations across six continents and a pooled AUC of 0.72 (95% CI: 0.67-0.76). Despite fewer validations, the Nanda et al. model achieved the highest pooled discrimination (5 validations; pooled AUC 0.77, 95% CI: 0.74-0.80). The Naylor et al. and van Leeuwen et al. models also underwent meta-analysis, as sufficient external validation studies were available to support comparative performance assessment. Notably, 69.23% of studies had a high risk of bias. CONCLUSIONS: While many models showed acceptable predictive performance, most validations were methodologically weak. Future studies should follow best-practice guidelines and promote scalable validation strategies, such as algorithm sharing, to enhance clinical utility.

Humans↗

PubMed1976

Toward a metatheoretical model of cognitive development.

Recently Piaget's model of cognitive development has been seriously questioned. This questioning was due partially to the inadequacy of the model in explaining creative, scientific and mature thought in adulthood. Various proposals have suggested the existence of a fifth stage in cognitive to represent adult thought. A second tradition has focused on the Piagetian model as a competence model. This has initiated a search for an appropriate performance model to describe the processes by which knowledge is actively constructed and applied. The present work reviews the theoretical positions and the research relevant to issue and proposes a synthesis through which cognitive development can be viewed as being both product and process, competence and performance, structure and function simultaneously.

Adult↗

PubMed1991

Mean square error of estimates of HIV prevalence and short-term AIDS projections derived by backcalculation.

We simulated multinomial AIDS incidence counts from 27 'representative' AIDS epidemics that spanned a period corresponding to previous applications of backcalculation (1 January 1977 to 1 July 1987) and assessed mean square error for several back-calculated estimators of HIV prevalence and short-term AIDS projections. Estimators were based on flexible model selection procedures that chose the best-fitting non-negatively constrained model of the infection curve from a family of possible step-function models. Selection of the best-fitting model from a family of four-step models each with a long last step of width of 4 or 4.5 years offered a favourable tradeoff between bias and variance when compared with selection from families of models with three steps or from families with a short last step. Five-step models performed as well as four-step models. Three-step models had substantially larger mean square error in some epidemic situations. Percentage root mean square error (PRMSE) for estimates of cumulative HIV prevalence as of 1 January 1985 was less than 14 per cent over a range of hypothetical epidemics of N = 50,000 infected individuals. PRMSE for short-term projections was less than 18 per cent. Estimates of cumulative HIV prevalence as of 1 July 1987 were substantially more uncertain and had a PRMSE of 33 per cent in the unfavourable case of a rapidly rising HIV epidemic. Estimates of cumulative HIV prevalence as of 1 July 1987 were positively biased in HIV epidemics with a rapidly decreasing recent HIV incidence rate and negatively biased in rapidly increasing HIV epidemics. Despite these uncertainties, we obtained useful estimates even for HIV epidemics with as few as 5000 infected individuals.

Acquired Immunodeficiency Syndrome↗

PubMed1987

Human sleep and circadian rhythms: a simple model based on two coupled oscillators.

We propose a model of the human circadian system. The sleep-wake and body temperature rhythms are assumed to be driven by a pair of coupled nonlinear oscillators described by phase variables alone. The novel aspect of the model is that its equations may be solved analytically. Computer simulations are used to test the model against sleep-wake data pooled from 15 studies of subjects living for weeks in unscheduled, time-free environments. On these tests the model performs about as well as the existing models, although its mathematical structure is far simpler.

Body Temperature↗

PubMed1990

Long QT syndrome. New electrocardiographic characteristics.

The long QT syndrome is electrocardiographically characterized by a prolonged QT interval and by several other, more subtle, ST-T-U wave abnormalities, most of which have not been quantified. To determine the possible usefulness of several new electrocardiographic characteristics in identifying patients with known long QT syndrome, logistic regression models were applied to a data base of seven new, relatively independent, electrocardiographic repolarization variables. These were measured on digitized 12-lead electrocardiograms of 315 normal subjects and 37 patients with the long QT syndrome (members of well-identified long QT syndrome families, QTc greater than 0.44 second, 27% symptomatic), who ranged in age from 17 to 60 years. Electrocardiographic variables that independently differentiated (p less than 0.001) patients with long QT syndrome from normal subjects included quantitative measures of repolarization: early duration, rate, T wave symmetry, late phenomena, and heterogeneity. All selected repolarization variables except the early duration variable were essentially independent of the QTc (r2 less than 0.15), and all contributed significantly to the identification of patients with long QT syndrome. A classification model of five electrocardiographic predictor variables resulted in an estimated sensitivity (95% confidence interval) of 92.6% (81.6-100%) and an estimated specificity (95% confidence interval) of 95.8% (93.6-98.1%). This model performed significantly better than an alternative classification model that was based on the early duration variable as a single predictor variable. The symptomatic status of patients with long QT syndrome could not be predicted by any combination of the electrocardiographic variables in the investigated model.

Adolescent↗

PubMed1986

Gaseous homeostasis and the circle system. Validation of a model.

The performance of a model of a subject breathing from a circle system has been examined in relation to nitrogen and helium. The ability of the model to maintain a nitrogen steady-state breathing air, the attainment of a new steady-state after perturbation of an existing nitrogen equilibrium, the washout of nitrogen from the subject model on breathing oxygen, and the estimation of functional residual capacity using a rebreathing method with helium as an indicator have been assessed. The predictable and accurate performance of the model in these studies, together with its ability to reproduce the results of a number of previously published studies in man, suggest that the model can be used to predict the behaviour of circle systems when used with inhaled anaesthetic agents.

Anesthesia, Inhalation↗

PubMed1986

Perceptual studies on ultrasonic B-scan textures.

A pilot study of the perceptual characteristics of ultrasonic textured images is described. Scans of four models performed on four real-time machines optimised for display of a normal liver were used. A trial with 22 observers indicated that the model that gave images closest to the liver image varied between machines. A second, paired similarity test with five observers using all the model images was performed, with a cluster analysis of a multidimensional scaling procedure. This suggested that the prominent features of the textural images are often more closely related to the machines than to the models. Considerable further work is needed to confirm these pilot results and to identify the visual cues that are most significant in textured images.

Biophysical Phenomena↗

PubMed1975

Modeling static and dynamic human cardiovascular responses to exercise.

A human performance model has been developed and described [9] which portrays the human circulatory, thermo regulatory and energy-exchange systems as an intercoupled set. In this model, steady state or static relationships are used to describe oxygen consumption and blood flow. For example, heart rate (HTRT) is calculated as a function of the oxygen and the thermo-regulatory requirements of each body compartment, using the steady state work values of cardiac output (CO, sum of all compartment blood flows) and stroke volume (SV, assumed maximal after 40% maximal oxygen consumption): HTRT=CO/SV. The steady state model has proven to be an acceptable first approximation, but the inclusion of transient characteristics are essential in describing the overall systems' adjustment to exercise stress. In the present study, the dynamic transient characteristics of heart rate, stroke volume and cardiac output were obtained from experiments utilizing step and sinusoidal forcing of work. The gain and phase relationships reveal a probable first order system with a six minute time constant, and are utilized to model the transient characteristics of these parameters. This approach leads to a more complex model but a more accurate representation of the physiology involved. The instrumentation and programming essential to these experiments are described.

Analog-Digital Conversion↗

PubMed2026

MRI-based radiomics model for predicting VEGFA expression and prognosis in lower-grade glioma.

BACKGROUND: Gliomas are the most common primary tumors of the central nervous system. Their treatment remains highly challenging, with high rates of associated disability and mortality. Conventional prognostic indicators no longer adequately satisfy the clinical demands of precision medicine. Therefore, it is essential to further explore novel prognostic biomarkers to enable accurate risk stratification and to provide new reference indicators for personalized precision therapy. PURPOSES: This study aimed to investigate the prognostic significance of vascular endothelial growth factor A (VEGFA) in patients diag nosed with lower-grade gliomas (LGGs) using an MRI based radiomics model. METHODS: Data regarding VEGFA expression and clinical records of LGG patients were retrieved from The Cancer Genome Atlas (TCGA). Corresponding preoperative MRI data were obtained from The Cancer Imaging Archive (TCIA) for radiomic feature extraction. Patients were stratified into high- and low- VEGFA expression groups based on survival information from the current cohort using the survminer package. The overall survival (OS) was assessed using Kaplan-Meier analysis and Cox proportional hazards regression. Predictive models were developed using logistic regression (LR), and model performance was evaluated via receiver operating characteristic (ROC) curve analysis, with area under the curve (AUC) values reported. An optimized model incorporating the Akaike information criterion (AIC) was also constructed (AIC-LR). RESULTS: VEGFA expression was significantly associated with OS (P = 0.002). Multivariate Cox regression confirmed VEGFA as an independent prognostic factor (hazard ratio [HR] = 2.545, 95% confidence interval: 1.422-4.555). Furthermore, VEGFA expression correlated with immune infiltration levels, particularly of M1 and M2 macrophages and T follicular helper cells, and was associated with enrichment in Wnt signaling and B cell receptor signaling pathways. The LR and AIC-LR models demonstrated acceptable predictive performance, with AUCs of 0.728 (95% CI: 0.612-0.843) and 0.725(95% CI: 0.612-0.839) in the training cohort, and 0.704 (95% CI: 0.562-0.847) and 0.718(95% CI: 0.576-0.861) in the validation cohort, respectively. CONCLUSIONS: The MRI based radiomics model showed potential for noninvasive assessment of VEGFA expression and may provide auxiliary information for prognostic evaluation in LGG. Further validation in larger samples and independent external cohorts is required before clinical application.

Radiomics↗

PubMed1988

Observational learning of a left-right behavioral asymmetry in mice (Mus musculus).

B6D2F1 hybrid mice that were allowed to observe a trained female mouse open a pendulum door to the right (or to the left) to enter a food compartment later solved this problem faster than pupils that had been placed behind a visual barrier. Male pupils that had observed a "left-handed" teacher performed sinistrally; males that had observed a "right-handed" model performed dextrally. Female pupils did not exhibit their demonstrator's laterality. Observational learning may provide a means to maintain certain lateralized behaviors. Such social learning may lead to the emergence of local traditions and to the cultural diffusion of behavioral asymmetries.

Animals↗

PubMed2025

Evaluating Language Models for Biomedical Fact-Checking: A Benchmark Dataset for Cancer Variant Interpretation Verification.

Accurate interpretation of genomic variants is critical for precision oncology but remains slow and dependent on specialized expertise. Public knowledgebases such as the Clinical Interpretation of Variants in Cancer (CIViC) help by curating literature-backed variant interpretations in a structured form, yet verification and review have become major bottlenecks. To address this, we developed CIViC-Fact, a benchmark dataset and pipeline for testing automated systems that verify the accuracy of cancer variant claims. CIViC-Fact links structured claims to sentence-level supporting or refuting evidence from full-text articles, and includes expert annotations and explanations. We evaluated multiple language models. Proprietary models performed well without training, but a smaller open-source model, fine-tuned on CIViC-Fact, achieved the highest accuracy (89%). Applying our fact-checking pipeline to real CIViC entries showed that reviewing less than 20% of content, focusing on flagged entries, would be sufficient to catch over half of all errors. This AI-assisted triage greatly accelerates the review process without replacing or reducing expert insight, ensuring that existing careful oversight remains in place while curators can work more efficiently. CIViC-Fact provides a realistic, high-consequence framework for biomedical fact-checking and a path toward more rigorous and efficient knowledgebase curation.

Journal Article↗

PubMed2026

Quality over quantity: biopsy-anchored CT radiogenomics models outperform all-lesion training in a multi-tumour cohort despite a smaller sample size.

OBJECTIVE: Radiogenomics aims to non-invasively predict tumour genotypes from imaging, but most studies assume molecular homogeneity by assigning a single biopsy-derived label to all lesions within a patient. This approach risks substantial label noise given well-documented interlesional heterogeneity. We investigated whether anchoring training to biopsy-confirmed lesions improves radiogenomic model performance and generalisability. MATERIALS AND METHODS: We retrospectively analysed 1646 patients (11473 segmented lesions) with contrast-enhanced CT and EGFR mutation status from next-generation sequencing at the Netherlands Cancer Institute, alongside an external NSCLC radiogenomics cohort (n = 158). All visible lesions were segmented, and the exact biopsy site was matched to its segmentation. Radiomic features were extracted, and machine learning models were trained with three lesion selection strategies: all lesions, non-biopsied lesions only, and biopsy-confirmed lesions only. To disentangle label quality from sample size, we created size-matched variants (one lesion per patient) for all-lesion and non-biopsied strategies. RESULTS: All models achieved significant discrimination of EGFR status on internal validation (AUC = 0.62-0.68). However, performance of the all-lesion and non-biopsied models declined on external validation (AUC = 0.55-0.63), while the biopsy-anchored model maintained stable performance (AUC = 0.62), despite having only 1/10th of the training sample size. When training sets were size-matched, the biopsy-anchored approach significantly outperformed a model trained on all available lesions on external validation (p = 0.037). CONCLUSIONS: Radiogenomic models trained on biopsy-confirmed lesions outperform conventional all-lesion strategies in external validation, despite using an order of magnitude fewer samples. Prioritising lesion-level label fidelity can mitigate heterogeneity-driven noise, enhancing robustness and clinical translation of imaging-based genomic prediction. KEY POINTS: Question Does assigning biopsy-derived molecular labels to all lesions introduce heterogeneity-driven label noise that reduces the generalisability of radiogenomic models? Findings Models trained exclusively on biopsy-confirmed lesions demonstrated superior external generalisability compared with all-lesion approaches, despite being trained on substantially fewer samples. Clinical relevance Biopsy-anchored radiogenomics improves the reliability of non-invasive mutation prediction by accounting for tumour heterogeneity, potentially supporting clinical decision-making when tissue sampling is limited or molecular results are discordant across lesions.

Humans↗

PubMed2026

Machine learning-integrated multi-omics risk prediction for pulmonary fungal infection in COPD and lung cancer: a transcriptomic and immune profiling study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) and lung cancer are major risk factors for invasive pulmonary fungal infection (IPFI), carrying an attributable mortality of 30%-80%. Their coexistence further amplifies immunosuppression, while current diagnostic criteria remain inadequate for early risk identification. METHODS: Transcriptomic data from the GEO dataset GSE296912 (scRNA-seq; 12,078 cells from normal and COPD lung tissue) and The Cancer Genome Atlas (TCGA)-lung adenocarcinoma (LUAD) bulk RNA-seq cohort (539 tumor and 59 normal samples) underwent differential expression and cross-omics integration analysis. Five machine learning models were constructed: logistic regression, SVM, random forest, XGBoost, and LASSO. Candidate genes were validated by qRT-PCR in A549 cells and THP-1-derived macrophages stimulated with heat-inactivated Aspergillus fumigatus conidia, a protocol selected to ensure BSL-2 biosafety compliance and isolate PAMP-mediated innate immune signaling. Model performance was evaluated using 5-fold stratified cross-validation with AUC, calibration curves, and decision curve analysis. RESULTS: Single-cell transcriptomic analysis of 12,078 cells identified 14 distinct cell populations, with marked myeloid expansion and immune dysregulation in COPD lung tissue. Cross-omics integration with TCGA-LUAD data identified 1,145 shared genes (79 immune-related), converging on NF-κB, TLR4, and cytokine receptor signaling. The random forest model achieved excellent discriminative performance (5-fold CV AUC = 0.988), with Treg infiltration, TLR4, and MMP9 as the top predictors. qRT-PCR confirmed significant upregulation of all five candidate genes (DEFB4A, S100A8, IL-8, MMP9, and TLR4) in both A549 and THP-1 cells following fungal stimulation. CONCLUSION: This multi-omics machine learning model integrating scRNA-seq and TCGA transcriptomic data demonstrates excellent discriminative performance (AUC = 0.988), with mechanistic convergence of NF-κB, TLR4, and oncogenic signaling pathways identified across shared immune gene signatures. In vitro qRT-PCR validation confirms the biological relevance of five key antifungal immune genes, providing a transcriptomic foundation for future prospective IPFI risk stratification in patients with COPD and lung cancer.

TLR4↗

PubMed1976

Verbalization in EMR children's observational learning.

The effect of descriptive verbalization during observation of a model on mentally retarded boys' retention for what they had observed was examined. Forty 9- to 12-year-old boys in public-school EMR classes were grouped on the basis of relatively high or low IQ scores. One-half of each group observed a videotaped model perform a series of novel acts, while in addition to viewing the tape, the other half described the model's actions. Observational learning was immediately tested through a set of prompts for imitation, with prizes offered commensurate with level of performance. Regardless of IQ group, the boys who were required to verbalize the model's behavior were able to imitate it significantly better than boys who merely watched the model; high and low IQ groups did not significantly differ in observational learning. Further directions for research on mentally retarded children's observational learning were suggested.

Attention↗