Introduction Medical science must be based on sound and scientific evidence and requires continuous research. Engaging in research allows students and faculty to explore new frontiers, question existing paradigms, and discover innovative solutions to medical challenges. As a specialty, community medicine plays a pivotal role in addressing public health issues. However, the engagement of community medicine residents in biomedical research remains suboptimal, which may impede the generation of evidence-based practices tailored to the Indian context. This study was conducted to find the interest and engagement of community medicine residents, and factors influencing their interest in biomedical research. Methods An online survey was conducted among community medicine residents of Uttar Pradesh, from February to April 2024, using Google Forms having a semi-structured, pretested questionnaire. Results One hundred and ninety-six residents participated in the study, where females (52.6%; 103/196) outnumbered males (47.4%; 93/196). The majority of participants were third-year residents (40.8%). Most participants seemed interested in biomedical research (83.2%) and thought that Basic Course in Biomedical Research (BCBR) helps conduct research projects (75%). Around half had previous experience in research projects, with cross-sectional studies being the most common (75.9%) study design. Enhancing research skills and a desire to contribute to medical knowledge emerged as primary motivators. On the other hand, the lack of time due to being overburdened with academic and educational activities was seen as the most common barrier to conducting research. Conclusions The majority of participants were found interested in research activities. The opportunity to improve research skills, desire to serve the medical fraternity, and a positive impact on resumes were the leading motivating factors for conducting research. Difficulty in sparing time, little knowledge, and poor support from mentors were found as important barriers.

CONCLUSIONS: Recent methodology advances in computational signal deconvolution have enabled bulk transcriptome data analysis at a finer cell-type level. Through deconvolution, identifying cell-type-specific differentially expressed (csDE) genes is drawing increasing attention in clinical applications. However, researchers still face a number of difficulties in adopting csDE detection methods in practice, especially in their experimental design. Here we present cypress, the first experimental design and statistical power analysis tool in csDE identification. This tool can reliably model purified cell-type-specific (CTS) profiles, cell-type compositions, biological and technical variations, offering a high-fidelity simulator for bulk RNA-seq convolution and deconvolution. cypress conducts simulation and evaluates the impact of multiple influencing factors, by various biostatistical metrics, to help researchers optimize experimental design and conduct power analysis.
METHODS: cypress is an open-source R/Bioconductor package at https://bioconductor.org/packages/cypress/.
BACKGROUND: Supplementary data are available at Bioinformatics online.

Psychosocial properties of oral health have been reported. The present study aimed to investigate the causal effect of complete loss of natural teeth on loneliness by using fixed-effects analysis to control for confounding factors, including unmeasured time-invariant factors. Data from older adults participating in at least 2 consecutive waves of the English Longitudinal Study of Ageing in waves 3 (2006/2007), 5 (2010/2011), and 7 (2014/2015) were analyzed (N = 18,682 observations from 7,298 individuals). The association between complete loss of natural teeth and loneliness score (ranging from 3 to 9) was examined using fixed-effect linear regression analysis adjusting for time-varying confounders, including sociodemographic and health characteristics. The prevalence of complete tooth loss was 12.7%, 12.8%, and 10.6% in waves 3, 5, and 7, respectively. Individuals who transitioned to complete tooth loss during any 2 consecutive waves had an increase in loneliness score by 0.27 (95% confidence interval [CI] 0.03, 0.52), which was greater than those who maintained natural teeth (-0.03; 95% CI -0.05, -0.01). Fixed-effects analysis adjusting for time-varying confounders revealed a significant association between complete loss of natural teeth and an increase in loneliness score by 0.31 (95% CI 0.17, 0.46). Complete loss of natural teeth among older adults in England was associated with loneliness, even after accounting for measured time-varying and (un)measured time-invariant confounders. Retaining natural teeth may reduce the risk of loneliness.

BACKGROUND: Adjusting for confounding variables is critical for objective comparison of outcomes. The explanatory power of variables used in adjusted models for injury and their relative utility across age groups has not been well-defined. This study aimed to assess the explanatory power of covariates commonly adjusted in injury research and their relative performance across age groups.
METHODS: Inpatients 18-100 y (2017-2022) were selected from 90 hospital trauma registries. Patients were grouped into sequential 5-y age blocks. Mortality was defined as the proportion of patients \"expired + hospice\". Dominance analysis was used to determine the average contribution (McFadden\'s R2) for covariates commonly included in multivariable logistic regressions.
RESULTS: Three hundred seventeen-thousand one hundred thirty-six patients were included (51.1% male, mean age: 63, mean injury severity score [ISS]: 9.8, mean Glasgow Coma Scale: 14.3, 93.5% blunt). Total explanatory power (McFadden\'s R2) for mortality was highest in youngest age group (52.7% in 18-24 group) and decreased with age, with the lowest R2 (19.6%) in 95-100 group. Regardless of age, the Glasgow Coma Scale was the most important covariate (R2 ranging from 9.0% to 20.4%). At age 18-24 y, ISS was a more dominant contributor than Elixhauser Score, but beyond 55 y, Elixhauser Score became more dominant than ISS.
CONCLUSIONS: The explanatory power of adjustment models including common covariates is limited and varies significantly across age groups, decreasing linearly with age. Adjusting for outcomes using these covariates may limit objective comparisons especially for older adults. Additional research is needed to identify covariates that enhance the explanatory power of adjustment models to allow for more objective comparisons across all ages.

Metabolomic analysis has been explored to search for disease biomarkers in humans for some time. The application to animal species, including fish, however, is still at the beginning. In the present study, we have used targeted and untargeted metabolomics to identify metabolites in the plasma of Atlantic salmon (Salmo salar) challenged with Piscine orthoreovirus (PRV-1), aiming to find metabolites associated with the progression of PRV-1 infection into heart and skeletal muscle inflammation (HSMI). The metabolomes of control and PRV-1-infected salmon were compared at three time points during disease development by employing different biostatistical approaches. Targeted metabolomics resulted in the determination of affected metabolites and metabolic pathways, revealing a substantial impact of PRV-1 infection on lipid homeostasis, especially on several (lyso)phosphatidylcholines, ceramides, and triglycerides. Untargeted metabolomics showed a clear separation of the treatment groups at later study time points, mainly due to effects on lipid metabolism pathways. In a subsequent multi-omics approach, we combined both metabolomics datasets with previously reported proteomics data generated from the same salmon plasma samples. Data processing with DIABLO software resulted in the identification of significant metabolites and proteins that were representative of the HSMI development in the salmon.

OBJECTIVE: Utility values enable relative comparisons across various health conditions, providing information for efficient allocation of healthcare resources. This study aimed to (1) quantify the utility values attributable to oral health-related quality of life (OHRQoL) in Japanese adults and (2) develop models for converting the 14-item Oral Health Impact Profile (OHIP-14) scores into EuroQoL 5-dimension 5-level (EQ-5D-5L)-based utility values.
METHODS: This was a cross-sectional study. Data from a large-scale Internet survey of Japanese adults conducted in 2022 (n = 28 405; mean age 48.2 years) were analysed. Multiple linear regression models were fitted to investigate the association between OHIP-14 scores and EQ-5D-5L-based utility values, adjusting for confounders. Conversion models were developed using a random half of the participants, and the observed and predicted utility values in the other half were compared to evaluate the model performance.
RESULTS: Among the participants, 55.2% scored 0, 20.9% scored 1-5 and 23.9% scored 6-56 on the OHIP-14, corresponding mean utility values of 0.93, 0.90 and 0.84, respectively. A one-point increase in the OHIP-14 score was associated with a lower utility value (coefficient: -0.0053; 95% confidence interval:health-related quality of life -0.0056, -0.0051). The estimated utility value attributable to OHIP-14 was -23.3 per 1000 individuals, greater than that for other prevalent chronic conditions, including hypertension and diabetes (-2.9 and -7.1 per 1000 individuals, respectively). The conversion model incorporated the OHIP-14 total score, age, sex and self-rated health, predicted utility scores on average and captured differences according to the number of teeth lost. However, there was a discrepancy between predicted and observed utility values in the lower utility value groups.
CONCLUSIONS: OHRQoL substantially impacted utility values at the population level. The OHIP-14 holds the potential as a valuable tool for predicting average utility values based on oral health conditions; however, the prediction performance was relatively low for individuals with a lower health-related quality of life.

Rapid advances in high-throughput DNA sequencing technologies have enabled large-scale whole genome sequencing (WGS) studies. Before performing association analysis between phenotypes and genotypes, preprocessing and quality control (QC) of the raw sequence data need to be performed. Because many biostatisticians have not been working with WGS data so far, we first sketch Illumina\'s short-read sequencing technology. Second, we explain the general preprocessing pipeline for WGS studies. Third, we provide an overview of important QC metrics, which are applied to WGS data: on the raw data, after mapping and alignment, after variant calling, and after multisample variant calling. Fourth, we illustrate the QC with the data from the GENEtic SequencIng Study Hamburg-Davos (GENESIS-HD), a study involving more than 9000 human whole genomes. All samples were sequenced on an Illumina NovaSeq 6000 with an average coverage of 35× using a PCR-free protocol. For QC, one genome in a bottle (GIAB) trio was sequenced in four replicates, and one GIAB sample was successfully sequenced 70 times in different runs. Fifth, we provide empirical data on the compression of raw data using the DRAGEN original read archive (ORA). The most important quality metrics in the application were genetic similarity, sample cross-contamination, deviations from the expected Het/Hom ratio, relatedness, and coverage. The compression ratio of the raw files using DRAGEN ORA was 5.6:1, and compression time was linear by genome coverage. In summary, the preprocessing, joint calling, and QC of large WGS studies are feasible within a reasonable time, and efficient QC procedures are readily available.

UNASSIGNED: To describe and demonstrate sample size and power calculation for ophthalmic studies with a binary outcome from one or both eyes.
UNASSIGNED: We describe sample size and power calculation for four commonly used eye designs: (1) one-eye design or person-design: one eye per subject or outcome is at person-level; (2) paired design: two eyes per subject and two eyes are in different treatment groups; (3) two-eye design: two eyes per subject and both eyes are in the same treatment group; and (4) mixture design: mixture of one eye and two eyes per subject. For each design, we demonstrate sample size and power calculations in real ophthalmic studies.
UNASSIGNED: Using formulas and commercial or free statistical packages including SAS, STATA, R, and PS, we calculated sample size and power. We demonstrated that different statistical packages require different parameters and provide similar, yet not identical, results. We emphasize that studies using data from two eyes of a subject need to account for the intereye correlation for appropriate sample size and power calculations. We demonstrate the gain in efficiency in designs that include two eyes of a subject compared to one-eye designs.
UNASSIGNED: Ophthalmic studies use different eye designs that include one or both eyes in the same or different treatment groups. Appropriate sample size and power calculations depend on the eye design and should account for intereye correlation when two eyes from some or all subjects are included in a study. Calculations can be executed using formulas and commercial or free statistical packages.

Disability studies have been successfully focusing on individuals\' lived experiences, the personalization of goals, and the constitution of the individual in defining disease and restructuring public understandings of disability. Although they had a strong influence in the policy making and medical modeling of disease, their framework has not been translated to traditional naturalistic accounts of disease. I will argue that, using new developments in evolutionary biology (Extended Evolutionary Synthesis [EES] about questions of proper function) and behavioral ecology (Niche conformance and construction about the questions of reference classes in biostatistics accounts), the main elements of the framework of disability studies can be used to represent life histories at the conceptual level of the two main \"non-normative\" accounts of disease. I chose these accounts since they are related to medicine in a more descriptive way. The success of the practical aspects of disability studies this way will be communicated without causing injustice to the individual since they will represent the individuality of the patient in two main naturalistic accounts of disease: the biostatistical account and the evolutionary functional account. Although most accounts criticizing the concept of disease as value-laden do not supply a positive element, disability studies can supply a good point for descriptive extension of the concept through inclusion of epistemic agency.

BACKGROUND: The extent to which differences in results from Apixaban for Reduction in Stroke and Other Thromboembolic Events in Atrial Fibrillation (ARISTOTLE) and Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial (ROCKET) atrial fibrillation (AF)-the landmark trials for the approval of apixaban and rivaroxaban, respectively, for non-valvular AF-were influenced by differences in their protocols is debated. The potential influence of selection criteria on trial results was assessed by emulating these trials in data from the Global Anticoagulant Registry in the Field (GARFIELD)-AF registry.
METHODS: Vitamin K antagonist (VKA) and non-vitamin K oral antagonist (NOAC) users from GARFIELD-AF were selected according to eligibility for the original ARISTOTLE or ROCKET AF trials. A propensity score overlap weighted Cox model was used to emulate trial randomisation between treatment groups. Adjusted HRs for stroke or systemic embolism (SE) within 2 years of enrolment were calculated for each NOAC versus VKA.
RESULTS: Among patients on apixaban, rivaroxaban and VKA, 2570, 3560 and 8005 were eligible for ARISTOTLE, respectively, and 1612, 2005 and 4368, respectively, for ROCKET AF. When selecting for ARISTOTLE criteria, apixaban users had significantly lower stroke/SE risk versus VKA (HR 0.57; 95% CI 0.34 to 0.94) while no reduction was observed with rivaroxaban (HR 0.98; 95% CI 0.68 to 1.40). When selecting for ROCKET AF criteria, safety and efficacy versus VKA were similar across the NOACs.
CONCLUSIONS: Apixaban and rivaroxaban showed similar results versus VKA in high-risk patients selected according to ROCKET AF criteria, whereas differences emerged when selecting for the more inclusive ARISTOTLE criteria. Our results highlight the importance of trial selection criteria in interpreting trial results and underline the problems faced in comparing treatments across rather than within clinical trials.