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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↗

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↗

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↗

PubMed2026

Partitioned blood pressure polygenic risk reveals differential genetic effects of tissue-specific enhancers and their interactions on cardiovascular disease.

Polygenic risk scores (PRS) compress genome-wide associations into a single predictor, but this aggregation obscures the distinct biological mechanisms through which genetic variation shapes complex traits. Here we introduce a framework that additively decomposes a trait's PRS, without loss of SNP heritability, into independent components defined by the tissue-specific and tissue-agnostic cis-regulatory elements (CREs) in which its variants act. Applied to blood pressure (BP) using ~0.5 million CREs across four BP-relevant tissues (adrenal gland, artery, heart, kidney), the framework reveals that regulatory effects are globally additive across tissues yet locally non-additive, and that the resulting partitioned scores carry pronounced, reproducible heterogeneity in their effects on BP and cardiovascular outcomes. We show this heterogeneity reflects gene-environment interactions, and trace one example to its mechanism: a kidney-CRE-partitioned score is protective against coronary artery disease and myocardial infarction through an interaction between ATP2B1 and antihypertensive medication. Explicitly modeling these interactions improves prediction and transferability, and tissue-focused partitioning increases power to resolve causal genes and reveals genes such as ADAMTS8 with antagonistic effects across BP components. Validated in an independent All of Us cohort, these findings recast the PRS from a blunt aggregate predictor into a mechanistic probe of context-dependent genetic architecture.

Journal Article↗

PubMed1985

Preliminary experiences with WHO's ICIDH; a user's report.

A simple feasibility study of the ICIDH was conducted: 1148 patients were classified by their physician, the opinion of the physicians about the feasibility of the ICIDH was recorded, and finally 21 patients were classified twice to assess reliability. The results suggest that the I code is feasible for patients with locomotor disorders. The use of the D code presented several problems. It is very time-consuming and reliability of D code assignments seems to be low. The feasibility of the D code can probably be improved if the numerical framework is reshaped. The H code seems to allow for simple meaningful scorings, although we tended to use it as a substitute for the impractical D code, rather than as an indicator of handicap.

Persons with Disabilities↗

PubMed2026

Pan-Cancer Quantification of Driver Alteration Transmission Across Molecular Layers Reveals Limited Propagation to Protein Abundance.

Precision oncology relies primarily on DNA-level alterations for therapeutic decisions, but the extent to which driver mutations propagate to protein abundance has not been systematically evaluated. Here, I developed a regression-based transmission score (TS_R 2) to quantify driver alteration signal propagation across DNA, mRNA, and protein layers. Applying this framework to matched genomic, transcriptomic, proteomic, and phosphoproteomic data from 754 Clinical Proteomic Tumor Analysis Consortium (CPTAC) tumors across seven cancer types, I analyzed 86 driver gene-cancer type pairs, of which 83 were evaluable for the full two-layer transmission score. I employed covariate-adjusted regression for each molecular transition, assessing significance via permutation testing (n = 1000). Mixed-effects modeling then partitioned gene-intrinsic from cancer-type-dependent effects. Only 5 of 83 evaluable pairs (6%) demonstrated high transmission (TS_R 2 > 0.05), with receptor tyrosine kinases (EGFR, FGFR2) exemplifying this class. The primary bottleneck occurred at the mutation-mRNA transition, not mRNA-protein translation. Gene identity accounted for 49% of transmission efficiency variance, nearly double the contribution of cancer type (29%). Copy number alterations transmitted signals 13.8-fold more efficiently than point mutations, and truncating mutations showed higher transmission than missense variants (Wilcoxon p = 0.005). Microsatellite instability attenuated mRNA-protein transmission in UCEC and COAD. These findings demonstrate that many driver alterations show limited propagation to protein abundance. This challenges DNA-only interpretations in precision oncology and provides a framework for integrated functional driver prioritization.

Humans↗

PubMed1985

Perioperative functions. Classification of knowledge and required skills.

The study results form a beginning framework from which values of resource appropriateness could be developed, which was the original intent of this study. An algorithm could be designed to score an individual's formal and informal training in specific skills as they relate to the O-Types identified. These results could be translated into resource appropriateness scores under each of the four factors. The results also provide a means for simplifying categories of the Operating Room Staffing Model and provide a beginning framework to assess resource appropriateness.

Clinical Competence↗

PubMed2026

Primer design through submodular function estimation.

MOTIVATION: Multiplex PCR-based enrichment is widely used in viral genome sequencing and pathogen surveillance. However, designing large sets of primers that maximize genome coverage while minimizing primer-primer interactions remains a major computational challenge. Existing methods such as SADDLE and Olivar use heuristics to optimize a Badness score for primer dimers but lack theoretical guarantees on solution quality. RESULTS: We introduce PRISM, a new framework that formulates multiplex primer design as a constrained submodular maximization problem. Our method defines an objective that balances genome coverage and dimer risk, and applies a local search algorithm with a constant-factor approximation guarantee. Evaluations on viral genome datasets demonstrate that PRISM consistently achieves lower Badness scores compared to PrimalScheme, Olivar, and primerJinn. These results highlight the scalability and theoretical rigor of submodular optimization in primer design. AVAILABILITY: PRISM is open-source and available at https://github.com/yhhan19/PRISM-new. The experimental data, scripts, and results used in this paper are archived on Figshare at https://doi.org/10.6084/m9.figshare.32806499.

Algorithms↗

PubMed2025

A comprehensive evaluation of candidate genetic polymorphisms in a large histologically characterized MASLD cohort using a novel framework.

BACKGROUND: There is a substantial heritable component to metabolic dysfunction-associated steatotic liver disease (MASLD), and several genetic variants that promote MASLD development or associate with its severity have been reported. These associations vary in terms of their effect size and degree of replication. METHODS: We developed a framework to classify previously identified MASLD genetic polymorphisms into 4 tiers based on effect size and extent of replication in the literature. We tested the association between "tier 1" single-nucleotide polymorphisms (OR ≥1.5, replicated in >2 independent studies) and biopsy measures of MASLD severity in a large, well-characterized histologic cohort of MASLD patients (n=3094). RESULTS: Across 19 "tier 1" variants reflecting 11 genetic loci, only those in the PNPLA3-SAMM50-PARVB locus showed significant associations with biopsy-proven fibrosis severity and NAFLD activity score; the highest risk was for the rs738409 p.I148M variant in PNPLA3. A genetic risk score based on "tier 1" variants, as well as a previously developed genetic risk score based on variants in PNPLA3, TM6SF2, and HSD17B13, were both associated with fibrosis and NAFLD activity score, but these results were driven entirely by PNPLA3 rs738409. CONCLUSIONS: Our study provides a framework to prioritize evaluation of genetic polymorphisms for future replication efforts and demonstrates that in a large case-only cohort, histologic severity of MASLD is only robustly associated with the presence of variation in PNPLA3 among known candidate genes. These findings may have implications for patient risk stratification based on the presence of PNPLA3 rs738409.

Humans↗

PubMed1976

A personality needs profile of some outstanding female athletes.

The Edwards Personal Preference Schedule (EPPS) was administered to 24 outstanding U.S. female athletes who were competitors in the 1972 Olympic Games. The resulting EPPS group profile strongly points to the essential normality of these competitors. Within the framework of a well-balanced needs profile, the two highest group needs scores were in the realm of achievement and autonomy. Thus, these prominent athletes demonstrated the kind of personality profile anticipated from a group of women with seemingly high needs for achievement and self-accomplishment. The EPPS, therefore, appears to be a promising personality measure to assess achievement motivation.

Achievement↗

PubMed1986

Assessment of neurological 'soft signs' in adolescents: reliability studies.

The validity and reliability of a scoring system for 'neurological soft signs' in teenagers was assessed. Six scales were adapted and fitted into the framework of a conventional neurological examination. The following emerged: each of the three multi-item scales had high internal consistency; inter-rater agreement on mirror movements of 'live' subjects was satisfactory; ratings of videotapes agreed among examiners for mirror movements and dysdiadochokinesis but not for choreiform movements; data-based cut-off scores defining present vs. absent were congruent with the ratings of outside neurologists; and each examiner was consistent in rating mirror movements and rapid alternating movements from videotapes over several months.

Adolescent↗

PubMed2026

SeqQC-former: A sequence-quality fusion framework for QC-aware review prioritization of candidate somatic SNVs in cancer genomics.

The accurate prioritization of candidate somatic single-nucleotide variants (SNVs) remains a challenge due to the substantial variability in sequencing quality across genomic loci. SeqQC-Former is a sequence-quality fusion framework that integrates the local nucleotide context with read-level quality-control (QC) covariates derived from matched tumor-normal sequencing data. This integration generates QC-aware prioritization scores for the downstream review of candidate variants. Unlike conventional variant callers, SeqQC-Former is designed not to infer biological truth but to support post-calling review and prioritization under heterogeneous sequencing conditions. The framework was trained and evaluated on a SEQC2-derived dataset comprising 89,447 candidate loci, including 1378 positive and 88,069 negative loci. In chromosome-held-out validation, which aims to reduce potential genomic-position leakage, SeqQC-Former demonstrated strong discrimination (AUROC = 0.9479; AUPRC = 0.9448), indicating good generalization to previously unseen chromosomes. Given that the SEQC2-derived labels contain QC-associated information; these results should be interpreted as an evaluation of QC-aware prioritization capability rather than an independent validation of biological variant correctness. Ablation analyses revealed that structured QC covariates provided the dominant predictive signal under the current SEQC2-derived labeling regime. SeqQC-Former achieved a significantly higher AUROC than classical machine-learning baselines, as determined by DeLong's test (p < 0.01). Application to 53,164 glioblastoma variants demonstrated that external predictions were sensitive to QC scaling and threshold selection, underscoring that model outputs should be interpreted as QC-dependent prioritization scores rather than calibrated probabilities or definitive biological classifications. Overall, SeqQC-Former offers a reproducible post-calling QC-aware prioritization framework for large-scale somatic SNV review and underscores the importance of explicitly modeling sequencing-quality information when interpreting structured cancer genomics datasets.

Humans↗

PubMed1992

The contribution of constructional accuracy and organizational strategy to nonverbal recall in schizophrenia and chronic alcoholism.

The Rey-Osterrieth complex figure was used to assess the separate influences of the constructional accuracy and the organizational strategy employed while copying the figure on the later, incidental recall of the figure. We tested a model, which hypothesized that subjects who copied the main framework of the figure holistically would be more likely to achieve good copy accuracy scores and to reproduce the figure more accurately at recall than subjects who used a piecemeal approach during copy. Subjects included 68 detoxified, chronic alcoholics (ALC), 28 patients with schizophrenia (SZ), and 69 normal control subjects (NCS). The results showed that the ALC and the SZ groups, on average, had lower accuracy and strategy scores at copy than did the NCS group, and furthermore, that the combined contributions of copy accuracy and copy strategy accounted for group differences at recall. A path analysis revealed that, for all three groups, copy strategy had a significant direct effect on copy accuracy. Moreover, copy accuracy and copy strategy made independent contributions to recall accuracy within the ALC and NCS groups; by contrast, within the SZ group, copy strategy made an independent contribution to recall performance but copy accuracy did not. These results suggest that (1) organizational strategy can influence constructional accuracy at both copy and recall; (2) copy accuracy and strategy have the potential to influence recall independently; and (3) the recall deficit in ALC could be attributed to abnormalities in both accuracy and strategy at copy, whereas in SZ it could be attributed only to strategy abnormalities. The deficits observed on the complex figure test in the ALC and SZ were primarily nonmnemonic and were related to ability in figure construction and organizational strategy.

Adult↗

PubMed2026

LLPS-based classification and a novel prognostic signature reveal NRF1 as a therapeutic target in pancreatic cancer.

BACKGROUND: Aberrant liquid-liquid phase separation (LLPS) can alter biomolecular condensate functions and may influence pancreatic tumorigenesis and progression, but the specific role of LLPS regulators in prognosis and the tumor immune microenvironment (TIME) in pancreatic ductal adenocarcinoma (PDAC) remains unclear. METHODS: We integrated transcriptome data of LLPS regulator-related differentially expressed genes (DEGs; n = 298) in a cohort of 176 PDAC patients from TCGA. Three LLPS regulator subtypes (LS1-LS3) were identified through multi-omics analyses, and a prognostic LLPS subtype-related risk model (LRRPC) was developed and validated. Chromatin immunoprecipitation confirmed NRF1 binding to promoters of key risk genes, and in vitro and in vivo experiments assessed the effects of NRF1 targeting on tumor growth. RESULTS: The three LLPS regulator subtypes exhibited significant differences in prognosis, clinical features, genomic alterations, TIME patterns and predicted immunotherapy response. The LRRPC signature predicted prognosis and immunotherapy efficacy across cohorts and was associated with tumor biomarkers and immune infiltration. Nuclear Respiratory Factor 1 (NRF1) directly regulated hub genes such as FAM83A, RHOV and ITGB6, promoting PDAC cell proliferation, while its inhibition induced apoptosis and reduced tumor growth. CONCLUSIONS: This study proposes an LLPS-based stratification framework for PDAC, and the LRRPC model provides an LLPS subtype-related risk score that may assist personalized prognostic assessment and immunotherapy stratification. NRF1 emerges as a promising therapeutic candidate whose targeting can inhibit tumor progression in PDAC experimental models and warrants further evaluation.

Immunotherapy↗