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At least 73 records · Page 4Linked to original sources
PubMed2026

Genome-wide association, polygenic risk scores, and machine learning for chronic post-surgical pain risk stratification: A UK biobank study.

Chronic post-surgical pain is a prevalent and debilitating complication following surgery, representing a clinical challenge. Despite the established heritability of pain phenotypes, large-scale genetic studies remain limited. This study aimed to identify genetic variants associated with chronic post-surgical pain, develop polygenic risk scores, and integrate these with clinical features for risk prediction. UK Biobank data from 47,836 participants (2490 cases and 45,346 controls) were split into training (80%; n = 38,268) and validation (20%; n = 9568) sets prior to analysis. A genome-wide association study was conducted on the training set only, across 19 million variants, and polygenic risk scores were constructed and integrated with clinical features in a logistic regression framework. Two close, rare, imputed signals crossed the genome-wide significance threshold but lacked local linkage-disequilibrium support, while 220 variants crossed the suggestive threshold. In the held-out validation set, cases had higher mean polygenic risk scores than controls (0.138 vs. -0.021; Cohen's d = 0.16, p < 0.001). A logistic regression model integrating clinical features and polygenic risk scores achieved an area under the curve of 0.639 (95% CI: 0.583-0.693), higher than models using either feature set alone. The polygenic risk score for chronic post-surgical pain was among the most important predictors. Risk stratification revealed the top quartile had 3.84-fold higher odds of chronic post-surgical pain than the bottom quartile (95% CI: 2.00-7.37). These findings suggest a possible modest genetic contribution to chronic post-surgical pain. Polygenic risk scores may complement clinical factors in surgical risk stratification. PERSPECTIVE: Chronic post-surgical pain may have a modest genetic contribution. This UK Biobank study identified over 220 variants at suggestive significance and constructed a polygenic risk score that was significantly elevated in cases. A combined clinical-genomic model achieved a 3.84-fold difference in odds across predicted-risk quartiles.

Chronic post-surgical pain↗
PubMed1988

Asymmetric stratification. An outline for an efficient method for controlling confounding in cohort studies.

Confounding is usually controlled by either cross-stratification or multivariate modeling. The first approach is simple and intuitive, but it is not practical for controlling many factors. The second approach, although less intuitive, may provide a more efficient means for controlling many confounders, but its ability to control confounding depends on the appropriateness of the chosen model. Hybrid methods based on a multivariate confounder score or a propensity score combine the favorable characteristics of both methods and may be better suited for controlling many confounders. However, the resulting strata are defined by subranges of a multivariate model, and, therefore, may possess little intrinsic meaning. The authors propose the principle of asymmetric stratification to control efficiently a number of confounders in cohort studies while retaining the intuitive appeal and general framework of cross-stratification. The proposed method resembles a propensity score analysis but does not use a multivariate model to define the strata. Instead, strata are defined by the categories of only a subset of the original potential confounders. The authors also demonstrate how our proposed method can be implemented by an application of classification and regression trees (CART) (recursive partitioning), as outlined by Breiman et al. (Classification and Regression Trees. Belmont, CA: Wadsworth, 1984). Computer simulations and an actual example suggest that the proposed method is a potentially simpler alternative to the standard propensity score analysis. Specific recommendations on how the proposed method can be improved are also presented.

Aged↗
PubMed2026

A reinforcement learning-enhanced fuzzy multi-objective equilibrium optimization framework for multiple sequence alignment.

Multiple sequence alignment (MSA) is a fundamental task in bioinformatics, underpinning comparative genomics, structural analysis, and evolutionary inference. However, MSA remains a challenging multi-objective optimization problem due to the need to simultaneously maximize alignment accuracy, preserve conserved regions, and control gap proliferation, particularly in large and heterogeneous sequence collections. In this work, we propose MOFSACEO-MSA, a novel hybrid optimization framework for multiple sequence alignment that integrates a fuzzy multi-objective evaluation scheme with the Equilibrium Optimizer (EO) and a Soft Actor-Critic (SAC)-based adaptive control mechanism. The proposed framework formulates MSA as a dynamic multi-objective optimization problem, in which alignment quality is assessed using complementary residue-level and column-level criteria, including Sum-of-Pairs score, column conservation, entropy, and gap statistics. Fuzzy membership functions are employed to harmonize competing objectives into a unified optimization landscape, while EO provides robust global exploration. To further enhance adaptability, SAC dynamically regulates key EO parameters during the search process, enabling an effective balance between exploration and exploitation across datasets of varying size and heterogeneity. Extensive experiments werew conducted on diverse biological sequence datasets, with a primary focus on RNA benchmarks, including structured families from Rfam, large-scale repositories from RNAcentral and GenBank, and organism-specific tRNA datasets from GtRNAdb. Comparative evaluations against classical alignment tools (ClustalW, MAFFT, MUSCLE, PRANK, KAlign, and T-Coffee), metaheuristic methods (SAGA, Sequoya and EAFSA), and a reinforcement learning-based approach (RLALIGN) demonstrate that MOFSACEO-MSA consistently achieves competitive or superior Sum-of-Pairs scores while significantly reducing gap proportions and maintaining compact alignment lengths. Notably, the proposed framework exhibits improved robustness on large and highly heterogeneous datasets, where existing methods often suffer from excessive gap insertion or unstable convergence. Overall, MOFSACEO-MSA provides a flexible and extensible optimization paradigm that effectively bridges evolutionary search and reinforcement learning for high-quality multiple sequence alignment, with demonstrated effectiveness on challenging RNA alignment tasks.

Sequence Alignment↗
PubMed1996

[Analysis of outcome quality control in intensive care medicine using the Simplified Acute Physiology Score II].

AIM: the main aim of the study was to assess the applicability of the Simplified Acute Physiology Score II (SAPS II) to the evaluation of outcome quality within the framework of quality assurance in patients in a medical intensive care unit. The outcome parameter employed was hospital mortality, measured as mortality index (hospital mortality actually observed/predicted mortality), the predicted mortality being derived from the individual mortality risk calculated for each patient in accordance with SAPS II. METHOD: For the period of one year, the SAPS II score, the individual mortality risk, the mean scores, mortality risk, intensive care and hospital mortality, and the mortality index (99% confidence interval) were calculated with the aid of a specially developed program for all 1,114 patients kept under observation or treated for longer than 4 hours in the intensive care unit. The entries (data) were monitored by random checks for the correctness of the individual entries and overall completeness of patient inclusion. The applicability of the SAPS II for our own patient material was checked with the aid of Receiver Operating Characteristic curves. In compliance with the original SAPS II to include patients of a coronary care unit but not to evaluate them, only the 604 patients with the diseases of medical intensive care were taken into account for quality control. High-risk groups (patients older than 76, critically ill patients with a mortality risk of more than 0,5, patients receiving respiratory support) and individual diagnostic categories were considered separately as subgroups. RESULTS: In the entire group, the mean mortality risk was 21,1% the observed intensive care mortality 11,2%, the hospital mortality 18,0%, and the mortality index 0,86 (0,75 to 1,00). The mortality actually observed, therefore, corresponded to that predicted on the basis of the SAPS prognostic system. Also in the subgroups of elderly patients, and individual diagnostic categories (cerebral, bronchopulmonary cardiovascular, gastrointestinal diseases), the mortality index did not differ significantly from 1,0. A mortality index significantly less than 1,0 (observed mortality significantly lower than predicted mortality) was found in the sub-groups of the seriously ill, of patients receiving respiratory support, and in the diagnostic category of intoxications. The monthly analysis showed fluctuating mortality indices which, however, never differed significantly from 1,0. The surface under the ROC curve for the entire group was 0,89, and 0.81-0.99 for the various diagnostic categories. CONCLUSIONS: The prognostic system SAPS II can be employed to evaluate the quality of outcome measured by hospital mortality in patients of a medical intensive care unit, provided that the applicability of the score is demonstrated for the patient material involved, the outcome of the overall group and of the high-risk groups is referred to the accuracy and completeness of the entered data is checked, and the scoring systems accepted as quality standard.

Adolescent↗
PubMed1996

FASTA-SWAP and FASTA-PAT: pattern database searches using combinations of aligned amino acids, and a novel scoring theory.

We introduce two new pattern database search tools that utilize statistical significance and information theory to improve protein function identification. Both the general pattern scoring theory with the specific matrices introduced here and the low redundancy of pattern databases increase search sensitivity and selectivity. Pattern scoring preferentially rewards matches at conserved positions in a pattern with higher scores than matches at variable positions, and assigns more negative scores to mismatches at conserved positions than to mismatches at variable positions. The theory of pattern scoring can be used to create log-odds pattern scores for patterns derived from any set of multiple alignments. This theoretical framework can be used to adapt existing sequence database search tools to pattern analysis. Our FASTA-SWAP and FASTA-PAT tools are extensions of the FASTA program that search a sequence query against a pattern database. In the first step, FASTA-SWAP searches the diagonals of the query sequence and the library pattern for high-scoring segments, while FASTA-PAT performs an extended version of hashing. In the second step, both methods refine the alignments and the scores using dynamic programming. The tools utilize an extremely compact binary representation of all possible combinations of amino acid residues in aligned positions. Our FASTA-SWAP and FASTA-PAT tools are well suited for functional identification of distant relatives that may be missed by sequence database search methods. FASTA-SWAP and FASTA-PAT searches can be performed using our World-Wide Web Server (http://dot.imgen.bcm.tmc.edu:9331/seq-search/Op tions/fastapat.html).

Algorithms↗
PubMed2026

Beyond antigen matching: compatibility intelligence theory for transfusion as an emergent biological system.

BACKGROUND: Despite major advances in serologic testing, extended phenotyping, and blood group genomics, clinically similar transfusion exposures may result in markedly different immune and clinical outcomes. Existing compatibility strategies do not fully explain this biological variability. OBJECTIVES: To examine transfusion compatibility as an emergent donor-recipient biological state and propose a systems-level conceptual framework that integrates established biological determinants into a testable model for future precision transfusion medicine. METHODS: This narrative review critically synthesizes current evidence from blood group genomics, recipient immunobiology, inflammation, disease-specific biology, transfusion medicine, and computational prediction. The proposed framework distinguishes Compatibility Intelligence Theory (CIT) as a biological interpretation from Precision Transfusion Intelligence (PTI) as its potential clinician-supervised translational application. RESULTS: The review argues that transfusion compatibility is shaped by interactions among donor genetics, recipient immune biology, inflammatory physiology, disease context, transfusion history, and longitudinal adaptation rather than by antigen matching alone. CIT provides an organizational framework for integrating these determinants, whereas PTI describes a possible clinician-supervised translation. To address current feasibility, the revised framework separates variables into routinely measurable, contextually available but incompletely standardized, and research-stage domains, and proposes a staged strategy for deriving rather than assuming their quantitative weights. Any clinical implementation would require comparative validation against current serologic, phenotypic, and genotype-based practice. CONCLUSIONS: Compatibility Intelligence Theory offers a testable systems-level framework for understanding transfusion compatibility without replacing established transfusion practices. The framework is not presented as a ready-to-use score: currently measurable variables can be organized for structured risk review, whereas inflammatory, immunogenetic, and multi-omic inputs require prospective standardization and validation. If future studies demonstrate incremental predictive and patient-centered benefit, CIT-informed PTI could support an adaptive, evidence-based extension of current precision transfusion practice.

Humans↗
PubMed2025

OctopuSV and TentacleSV: a one-stop toolkit for multi-sample, cross-platform structural variant comparison and analysis.

MOTIVATION: Structural variants (SVs) influence gene regulation, disease progression, and diagnostics, yet integrating SV calls across platforms remains difficult due to inconsistent annotations, limited merging flexibility, and fragmented workflows. Ambiguous breakend (BND) annotations, which comprise many variant calls, are often discarded or misclassified, hindering variant characterization. Existing tools lack advanced merging operations essential for precise identification of disease-specific or somatic variants across samples or patient groups. Additionally, current SV analysis pipelines require extensive manual intervention and complex parameter tuning, compromising reproducibility and scalability. Addressing these gaps is crucial for improving the accuracy, interpretability, and clinical utility of SV analyses. RESULTS: We developed OctopuSV and TentacleSV to address these long-standing challenges in SV analysis. OctopuSV features a specialized BND correction module that converts ambiguous BND annotations into canonical SV types, recovering important variants that are often overlooked by existing tools. Additionally, it provides advanced set operations (difference, complement, custom-defined) that enable sophisticated variant filtering without programming expertise, critical for identifying tumor-specific SVs or variants unique to specific sample groups. TentacleSV completes our solution by automating the entire SV analysis process from raw sequencing data to high-confidence callsets, ensuring consistency and reproducibility across projects. Benchmarking across short-read and long-read platforms showed superior F1 score, complete SV type consistency compared to existing tools. Our framework enables experimental biologists and clinical researchers to perform sophisticated analyses ranging from cancer subtype-specific SV identification to multi-sample comparative studies without requiring specialized programming skills. AVAILABILITY AND IMPLEMENTATION: All codes are available at https://github.com/ylab-hi/OctopuSV; https://github.com/ylab-hi/TentacleSV.

Software↗
PubMed1979

[Vegetative phenomena in the course of depressive states].

Depressive psychoses are accompanied by vegetative disorders. Third-order blood-pressure waves are an expression of vasomotor rhythms which through diencephalic and limbic structures tend to adjust the blood pressure to the respective overall psychovegetative situation. In the case of depressions with an axious increase of impulse, statistical evidence was obtained, within the framework of clinical improvement, for a correlation between a decreasing score of depression and an increasing frequency of third-order waves. The same central trends of these quantities suggest that both of them are different manifestations of a common functional disorder in the limbic system and diencephalon.

Affective Disorders, Psychotic↗
PubMed1978

Eye movements and a dynamic stimulus situation.

Two experiments were conducted to investigate performance with and without voluntary eye movements in a dynamic stimulus situation. Experiment I used a combined tracking and prediction task. Level of training, complexity of the signal, and visual region sampled were the variables of interest. Experiment II manipulated the same variables in only the prediction task. Thus, the amount of attention allotted to the prediction task was varied between experiments. The d' measure indicated that under peripheral vision instructions accuracy on the prediction task was the same as under foveal vision instructions provided that: (1) the level of task complexity was low, (2) the subjects were well trained, and (3) only the prediction task was performed, or in the dual task situation only visual regions near the fovea were sampled. All other combinations of the variables resulted in a lower performance scores under peripheral vision instructions. Results are interpreted within the framework of current theories of the functional visual field.

Eye Movements↗
PubMed2026

A nucleolar stress gene signature enables quantitative scoring across multi-omics contexts.

The nucleolus is essential for ribosome biogenesis and cellular homeostasis, and its dysfunction can induce nucleolar stress, a process implicated in cancer and other diseases. However, nucleolar stress is commonly inferred from morphological changes or a limited set of functional assays, and quantitative approaches based on gene expression profiles remain lacking. Here, we integrate literature curation with multi-dataset screening to define a nucleolar stress gene signature and develop a nucleolar stress score (NuS) applicable to bulk transcriptomics, single-cell transcriptomics, proteomics, and spatial transcriptomics. Using this framework, we show in colorectal cancer models that oxaliplatin induces nucleolar stress, suppresses nascent rRNA synthesis, and activates p53 signaling, whereas these responses are attenuated in oxaliplatin-resistant cells. Combined with a ribosome biogenesis activity score (RiboSis), NuS captures related but distinct dimensions of nucleolar function and stratifies tumors into functional states associated with clinical outcomes. NuS-based analysis of perturbational transcriptomes further prioritizes compounds with putative nucleolar stress-inducing activity. Collectively, this study provides a quantitative framework for evaluating nucleolar stress and illustrates its applications in disease stratification and drug mechanism discovery.

Cell Nucleolus↗
PubMed1995

Body image disturbances in young adults with cancer. Implications for the oncology clinical nurse specialist.

The impact of the diagnosis of cancer and its treatments on the body image of young adults (18-29 years) diagnosed with cancer is relatively unknown. This descriptive comparative study examined body image scores of young adults diagnosed with cancer and young adults without cancer. The conceptual framework for this study was taken from body image and developmental theory. Secord and Jourard's body cathexis/self-cathexis scales and a demographic sheet were mailed to 162 young adults diagnosed with cancer and to 150 young adults without cancer. A t test was used to compare the mean scores between the two groups. A statistically significant difference was found between the mean scores reported by the young adults diagnosed with cancer for the body cathexis and self-cathexis scales. The self-cathexis and body cathexis scores indicated that the young adults diagnosed with cancer had a more positive body image than the young adults without cancer. The mean scores were also compared in relation to the demographic data collected using t tests and analysis of variance. Within the group diagnosed with cancer, male subjects demonstrated a more secure body-cathexis (p value of 0.012) and married subjects demonstrated a more secure self-cathexis than the single subjects did (p value of 0.04). No statistically significant difference was found within the group without cancer related to demographic variables. Implications for the oncology clinical nurse specialist are explored.

Adolescent↗
PubMed1997

A prospectively planned cumulative meta-analysis applied to a series of concurrent clinical trials.

Sequential designs are now a familiar part of clinical trial methodology. In particular, the triangular test has been used in several individual studies. Methods of combining studies are also well-known from the literature on meta-analysis. However, the combination of the two approaches is new. Consider the situation where a series of studies is to be conducted, following broadly similar protocols comparing a new treatment with a control treatment. In order to obtain an answer as quickly as possible to an efficacy or safety question it may be desirable to perform a cumulative meta-analysis on one particular variable. This could, for example, be the primary efficacy variable, an expensive assessment conducted in only a subgroup of patients, or a serious side-effect. To allow for the size of the treatment difference varying from study to study we might wish to provide a global estimate. Hence a random effects combined analysis, within a sequential framework, would appear to be appropriate. A methodology which utilizes efficient score statistics and Fisher's information is presented. Simulations show that the proposed methodology will achieve the specified error probabilities with reasonable accuracy provided that any random effect is relatively small. Ignoring random effects when they are present can lead to inaccuracies. A simulated example illustrates a number of practical issues.

Clinical Trials as Topic↗
PubMed1996

The assessment of disability with the Groningen Activity Restriction Scale. Conceptual framework and psychometric properties.

The conceptual framework, psychometric properties, descriptive statistics, and the rules for administration and scoring of the Groningen Activity Restriction Scale (GARS) for assessing disability in the area of ADL (Activities of Daily Living including mobility) as well as IADL (Instrumental Activities of Daily Living) are presented. The result show that the GARS, which can be administered both face-to-face and by mail questionnaire, is an easy to administer, comprehensive, reliable, hierarchical, and valid measure for assessing disability in older people. By integrating previously developed scales measuring different domains of disability (ADL, IADL, and mobility) and the use of a four-category response format, an accurate and detailed measure of disability can be obtained and a broader range of needs of subjects can be described. The GARS manual, including detailed procedures for administration and scoring, encourages unambiguous administration and interpretation which results in more comparable research outcomes.

Activities of Daily Living↗
PubMed1985

Effect of gender role identity on patterns of feminine and self-concept scores from late pregnancy to early postpartum.

Relationships among gender role identity, feminine scores, self-concept, and perception of comfort in the mothering role were examined. Fifty-two primiparous and 21 multiparous women completed study questionnaires during the third trimester, 2 to 3 weeks postpartum, and 4 to 6 weeks postpartum. Low feminine gender role identity groups demonstrated the greatest change in feminine and self-concept scores over time. Differences in patterns emerged among the groups regarding size and significance of correlations between feminine and self-concept scores. Implications of findings for nursing practice and the study conceptual framework, as well as study limitations, are discussed.

Adult↗
PubMedDate not supplied

Indicators for measuring the quality of family planning services in Nigeria.

This article presents the Situation Analysis approach as a means of collecting data that can be used to assess the quality of care provided by family planning service-delivery points (SDPs), and describes the quality of services offered in Nigeria. Elements of the quality of services provided at 181 clinical service-delivery points in six states of Nigeria are described. The substantive results from the study suggest that although most of the 181 service points sampled are functional, the quality of care being provided could be improved. Illustrative scores for these indicators and elements of the Bruce-Jain framework are given. By comparison with contraceptive prevalence surveys, the Situation Analysis approach is still in its early stages. Some methodological issues are raised here and future directions for strengthening the validity and applicability of the approach are discussed.

Bias↗
PubMed1997

Enumerating and ranking discrete motifs.

Discrete motifs that discriminate functional classes of proteins are useful for classifying new sequences, capturing structural constraints, and identifying protein subclasses. Despite the fact that the space of such motifs can grow exponentially with sequence length and number, we show that in practice it usually does not, and we describe a technique that infers motifs from aligned protein sequences by exhaustively searching this space. Our method generates sequence motifs over a wide range of recall and precision, and chooses a representative motif based on a score that we derive from both statistical and information-theoretic frameworks. Finally, we show that the selected motifs perform well in practice, classifying unseen sequences with extremely high precision, and infer protein subclasses that correspond to known biochemical classes.

Algorithms↗
PubMed1997

Ela 1.0--a framework for life-cycle impact assessment developed by the Fraunhofer-Gesellschaft. Part A: The conceptual framework.

The Fraunhofer-Gesellschaft has sponsored the development of a conceptual and flexible, computer aided tool to perform the impact assessment within LCA (life cycle assessment) for technical products and processes. The developed general framework "Ela 1.0" (environmental loads analysis) consists of four elements: the selection of appropriate impact categories, the categorization of emissions and wastes leaving the systems as well as of resource and energy consumption, the characterization and an analysis of the results of the impact assessment. The latter compares the product-based emissions with the total of emissions of a region such as Germany, the EU or OECD countries. The framework Ela 1.0 considers the environmental categories: global warming, ozone depletion, resource and energy consumption, wastes, eutrophication (including COD and BOD as measured parameters), acidification, ecotoxicity, ozone formation and human toxicity. The latter categories are handled by listing of precursors for ozone formation, and by listing of emissions scored according to their human hazard potential. The options, possibilities and limitations of the conceptual framework are presented in part A of a series of publications.

Acid Rain↗
PubMed1988

The Level of Expressed Emotion Scale: a new measure of expressed emotion.

The Level of Expressed Emotion (LEE) scale was developed to provide an index of the perceived emotional climate in a person's influential relationships. Unlike existing measures, the scale was constructed on the basis of a conceptual framework described by expressed emotion theorists. In addition to providing an overall score, the 60-item scale assesses the following four characteristic attitudes or response styles of significant others: Intrusiveness, emotional response, attitude toward illness, and tolerance/expectations. The scale underwent extensive psychometric development procedures: (1) theoretically based item generation; (2) pilot testing with normal and psychiatric populations to select the final items; and (3) construct validation within a schizophrenic population. The results were quite favorable and indicate that the LEE scale has sound psychometric properties of internal consistency; reliability; independence from sex, age, and amount of contacts; and construct validity.

Adaptation, Psychological↗