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Results for “Scoring framework”

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PubMed1998

Attention-deficit disorder. A paradigm for psychotropic medication intervention in pediatrics.

Pediatricians frequently encounter patients with behavioral or academic problems in clinical practice. Assessing and managing these patients requires awareness of the numerous physical, emotional, and psychological causes. Because of their limited contact with these patients during a routine visit, pediatricians as a minimum, should rely on careful parental and social history, teachers' evaluations by checklist, achievement test scores and grades, and the clinicians' own gestalt regarding patients' behavior. This article provides a framework that practitioners can incorporate into their routine office practices. Practitioners must also be knowledgeable about different forms of ADD and learning disabilities, differential diagnosis, and frequently encountered comorbidities. A modest armamentarium of psychotropic drugs potentially useful in the treatment of ADD are available; however, they must be aware of indications, subtle differences in pharmacokinetics, rates of efficacy, and adverse effects for these medications. Appropriate behavioral intervention, educational assessment, and placement when necessary are also essential for optimal management. Enabling the child or adolescent to achieve successfully in school, to experience positive social interactions, and to regain self-esteem are the more rewarding facets of pediatric care.

Adolescent↗

PubMedDate not supplied

"Bayes affinity fingerprints" improve retrieval rates in virtual screening and define orthogonal bioactivity space: when are multitarget drugs a feasible concept?

Conventional similarity searching of molecules compares single (or multiple) active query structures to each other in a relative framework, by means of a structural descriptor and a similarity measure. While this often works well, depending on the target, we show here that retrieval rates can be improved considerably by incorporating an external framework describing ligand bioactivity space for comparisons ("Bayes affinity fingerprints"). Structures are described by Bayes scores for a ligand panel comprising about 1000 activity classes extracted from the WOMBAT database. The comparison of structures is performed via the Pearson correlation coefficient of activity classes, that is, the order in which two structures are similar to the panel activity classes. Compound retrieval on a recently published data set could be improved by as much as 24% relative (9% absolute). Knowledge about the shape of the "bioactive chemical universe" is thus beneficial to identifying similar bioactivities. Principal component analysis was employed to further analyze activity space with the objective to define orthogonal ligand bioactive chemical space, leading to nine major (roughly orthogonal) activity axes. Employing only those nine activity classes, retrieval rates are still comparable to original Bayes affinity fingerprints; thus, the concept of orthogonal bioactive ligand chemical space was validated as being an information-rich but low-dimensional representation of bioactivity space. Correlations between activity classes are a major determinant to gauge whether the desired multitarget activity of drugs is (on the basis of current knowledge) a feasible concept because it measures the extent to which activities can be optimized independently, or only by strongly influencing one another.

Algorithms↗

PubMed1998

Empirical scoring functions. II. The testing of an empirical scoring function for the prediction of ligand-receptor binding affinities and the use of Bayesian regression to improve the quality of the model.

This paper tests the performance of a simple empirical scoring function on a set of candidate designs produced by a de novo design package. The scoring function calculates approximate ligand-receptor binding affinities given a putative binding geometry. To our knowledge this is the first substantial test of an empirical scoring function of this type on a set of molecular designs which were then subsequently synthesised and assayed. The performance illustrates that the methods used to construct the scoring function and the reliance on plausible, yet potentially false, binding modes can lead to significant over-prediction of binding affinity in bad cases. This is anticipated on theoretical grounds and provides caveats on the reliance which can be placed when using the scoring function as a screen in the choice of molecular designs. To improve the predictability of the scoring function and to understand experimental results, it is important to perform subsequent Quantitative Structure-Activity Relationship (QSAR) studies. In this paper, Bayesian regression is performed to improve the predictability of the scoring function in the light of the assay results. Bayesian regression provides a rigorous mathematical framework for the incorporation of prior information, in this case information from the original training set, into a regression on the assay results of the candidate molecular designs. The results indicate that Bayesian regression is a useful and practical technique when relevant prior knowledge is available and that the constraints embodied in the prior information can be used to improve the robustness and accuracy of regression models. We believe this to be the first application of Bayesian regression to QSAR analysis in chemistry.

Bayes Theorem↗

PubMed1999

Reconstruction of acquired sub-total ear defects with autologous costal cartilage.

Acquired sub-total ear defects are common and challenging to reconstruct. We report the use of an autologous costal cartilage framework to reconstruct sub-total defects involving all anatomical regions of the ear. Twenty-eight partially damaged ears in 27 patients were reconstructed with this technique. The defects resulted from bites (14), road traffic accidents (five), burns (four), iatrogenic causes (four) and chondritis following minor trauma (one). Computerised image analysis revealed a median of 31% (range 13-72%) ear loss. An autologous costal cartilage framework was fashioned in all cases. If adequate local skin was available, this was draped over the framework, but in nine cases preliminary tissue expansion was used and in a further three cases with significant scarring, the framework was covered with a temporoparietal fascial flap. Clinical assessment after ear reconstruction was undertaken, scoring for symmetry, the helical rim, the antihelical fold, the lobe position and a 'natural look' to produce a four-point scale; 11 were excellent, 12 were good, two were fair and three were poor. Our experience suggests that formal delayed reconstruction with autologous costal cartilage is to be recommended when managing acquired, sub-total ear deformity.

Adolescent↗

PubMed2025

Sex as a modifier of genetic risk for type 1 diabetes.

Sex differences influence the pathogenesis of type 1 diabetes (T1D), yet most genetic studies have treated sex as a control covariate rather than a dynamic effect modifier. Sex influences immune cell behaviour, including CD4+ and CD8+ T cell activation, regulatory T cell stability, B cell autoantibody production, dendritic cell priming and monocyte/macrophage inflammation. Underlying mechanisms include hormone-responsive enhancers, X-escape gene dosage and sex-biassed chromatin states, intersecting with T1D-associated variants to produce sex-specific immune phenotypes. These insights help explain regional variation in sex ratios of T1D incidence, such as male predominance in high-risk populations and female excess in low-risk populations. Biological sex shapes T1D risk across multiple layers, including polygenic load; environmental exposures such as vitamin D deficiency and enteroviral infection; and sex-specific hormonal, chromosomal and epigenetic influences. An integrative G × E × S (genetic × environmental × sex-specific) liability-threshold framework is thus supported. Clinical and translational implications include developing sex-specific polygenic risk scores, biomarker panels and interventional strategies targeting pathways such as hormone signalling, vitamin D metabolism and the microbiome. Future multi-omic, longitudinal studies are warranted to test genotype-sex interactions, integrate sex as a core effect modifier and enable precision prevention and treatment of T1D in both males and females.

Humans↗

PubMed2004

Cognitive reorganization and stigmatization among persons with HIV.

BACKGROUND: A diagnosis of human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) is a life-changing event, where persons must deal with a life-threatening, debilitating disease and its associated stigma and isolation. Studies over the past decade have shown that writing and talking about stressful and traumatic experiences, such as a life-threatening illness, causes emotions surrounding the trauma to change and to become cognitively reorganized. The result is a reduction in inhibition and change in basic cognitive and linguistic processes, which have contributed to meaningful behavioural, psychological, and physical health benefits across a variety of populations. AIMS: To describe the construction of the Integrated Model of Health Promotion for persons with HIV/AIDS, and present initial empirical support of the model from a feasibility pilot study of women with HIV/AIDS. APPROACH: The Integrated Model of Health Promotion is described and relevant literature in the field is reviewed. The model is implemented in a feasibility pilot study utilizing the emotional writing disclosure intervention. RESULTS: Participants in the experimental condition demonstrated a promising pattern of cognitive reorganization, a reduced perception of stigma, and an improvement in mental health scores compared with the control condition. CONCLUSION: Implications of these findings are discussed within the framework of the Integrated Model of Health Promotion. The model explores health and behavioural benefits associated with emotional writing in individuals with HIV/AIDS. The limited sample size of this pilot study precludes testing for significance. Further studies are required prior to the development of practice guidelines.

Adolescent↗

PubMed2026

scRNA-seq and bulk RNA-seq reveal the characteristics of macrophage copper metabolism and establish a risk signature in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a prevalent malignancy with an urgent need for improved prognostic stratification and treatment-response prediction. This study aimed to explore a macrophage copper metabolism-associated prognostic model and to investigate the relationship between this risk model and the tumor immune microenvironment. METHODS: The FindClusters function was used to analyze cell clusters, and CellChat and CellPhoneDB/LIANA were employed for cell-cell communication analysis. Copper metabolism-related genes were sourced from the MSigDB database. A prognostic risk model was established using least absolute shrinkage and selection operator (LASSO) analysis and multivariate Cox regression analysis, and a nomogram was constructed by integrating the prognostic model with clinicopathological factors. Additional analyses were performed to map the seven model genes in single-cell data, assess model uncertainty and robustness, evaluate macrophage/copper/cuproptosis-related transcriptional programs, and examine the correlations between risk score, immune infiltration and predicted drug sensitivity. RESULTS: Using single-cell RNA sequencing (scRNA-seq) data, we identified four macrophage subpopulations. Macrophages with high SPP1 expression showed close interaction with T cell populations and were associated with copper ion metabolism. By incorporating 141 copper metabolism-related genes and using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort, we constructed a seven-gene risk prediction model. Additional single-cell mapping showed that the model genes were detectable in the HCC single-cell dataset and showed a macrophage-associated expression pattern. The model showed moderate prognostic discrimination in TCGA-LIHC, whereas its external performance was heterogeneous and remained evaluable across external cohorts, with performance varying among datasets. Immune and mechanism-related analyses suggested that the risk signature was associated with macrophage-related infiltration, copper metabolism and cuproptosis-related transcriptional programs. Drug sensitivity analysis nominated Daporinad as a computationally predicted candidate compound, supporting Daporinad as a pharmacogenomic candidate for follow-up investigation. CONCLUSIONS: By integrating scRNA-seq and bulk RNA sequencing (RNA-seq) data, we constructed a macrophage copper metabolism-associated prognostic signature for HCC. The risk score was associated with survival, immune microenvironment features and predicted drug response, providing a transcriptomic framework for risk stratification and therapeutic hypothesis generation.

Hepatocellular carcinoma (HCC)↗

PubMed2005

Automatic scoring and quality assessment using accuracy bounds for FP-TDI SNP genotyping data.

BACKGROUND: Human diversity, namely single nucleotide polymorphisms (SNPs), is becoming a focus of biomedical research. Despite the binary nature of SNP determination, the majority of genotyping assay data need a critical evaluation for genotype calling. We applied statistical models to improve the automated analysis of 2-dimensional SNP data. METHODS: We derived several quantities in the framework of Gaussian mixture models that provide figures of merit to objectively measure the data quality. The accuracy of individual observations is scored as the probability of belonging to a certain genotype cluster, while the assay quality is measured by the overlap between the genotype clusters. RESULTS: The approach was extensively tested with a dataset of 438 nonredundant SNP assays comprising >150,000 datapoints. The performance of our automatic scoring method was compared with manual assignments. The agreement for the overall assay quality is remarkably good, and individual observations were scored differently by man and machine in 2.6% of cases, when applying stringent probability threshold values. CONCLUSION: Our definition of bounds for the accuracy for complete assays in terms of misclassification probabilities goes beyond other proposed analysis methods. We expect the scoring method to minimise human intervention and provide a more objective error estimate in genotype calling.

Algorithms↗

PubMed1993

Peer teaching among nursing students in the clinical area: effects on student learning.

Substantial use of clinical peer teaching among students has been reported, but there is limited description of outcomes and no reports of the use of a theoretical framework. The purpose of this study was to investigate the effects of peer teaching on baccalaureate nursing students' clinical performance. It was hypothesized that students who were taught by peers will: (a) achieve significantly higher improvement scores than students taught by teachers alone; and (b) rate their preference for peer teaching equal to or higher than instructor teaching. Bandura's (1971) social learning theory provided the framework for the study. The experimental design involved 50 volunteer subjects on two surgical units, one for peer teaching and one for instructor teaching. Data were collected from pre- and post-psychomotor and cognitive tests of a surgical dressing procedure and from a Clinical Teaching Preference Questionnaire (CTPQ). Experimental subjects achieved significantly higher cognitive improvement scores (t = 1.67; P < 0.05) and moderately higher psychomotor improvement scores in support of hypothesis 1. Responses on the CTPQ showed support for hypothesis 2.

Adult↗

PubMed2026

Meniscal preservation in the age of biologics: toward a quantitative decision algorithm for personalized repair.

BACKGROUND: Despite advances in arthroscopic repair and biologic augmentation, surgical indication for meniscal tears remains heterogeneous. No standardized framework currently integrates biomechanical, clinical, and biological determinants to guide repair versus resection. PURPOSE: To develop a quantitative decision model-the Meniscal Preservation Score (MPS)-that unifies biomechanical and biological evidence to stratify reparability potential and standardize treatment selection in meniscal surgery. METHODS: A systematic evidence synthesis conducted in accordance with PRISMA 2020 reporting standards of studies published from 2000 to 2025 in PubMed, Embase, and Scopus identified key determinants of meniscal healing. Five consistent predictors-patient age, vascularity, tear morphology, associated pathology, and activity profile-were weighted through a two-round modified Delphi consensus among ten experienced knee surgeons. The resulting 0-9-point MPS was incorporated into a stepwise decision tree linking lesion morphology, biological context, and surgical strategy. Conceptual validation used 50 simulated cases and a retrospective cohort of 45 patients to test agreement between algorithm recommendations and expert surgical decisions. RESULTS: The MPS achieved 86% concordance with expert judgment in simulation and 84% agreement in clinical validation. In this retrospective exploratory cohort, cases in which surgical management was concordant with MPS recommendations demonstrated higher mean IKDC scores at 24 months and lower observed reoperation rates. These findings should be interpreted as associative rather than causal, as treatment allocation was not controlled and discordant cases may have represented inherently more complex pathology. CONCLUSION: The MPS represents an evidence-informed decision-support framework designed to systematize reparability assessment. While exploratory analyses suggest structural coherence with expert reasoning, prospective implementation and external validation are required before clinical adoption as a predictive tool. LEVEL OF EVIDENCE: conceptual model with exploratory validation.

Humans↗

PubMed2024

A functional genomic framework to elucidate novel causal metabolic dysfunction-associated fatty liver disease genes.

BACKGROUND AND AIMS: Metabolic dysfunction-associated fatty liver disease (MASLD) is the most prevalent chronic liver pathology in western countries, with serious public health consequences. Efforts to identify causal genes for MASLD have been hampered by the relative paucity of human data from gold standard magnetic resonance quantification of hepatic fat. To overcome insufficient sample size, genome-wide association studies using MASLD surrogate phenotypes have been used, but only a small number of loci have been identified to date. In this study, we combined genome-wide association studies of MASLD composite surrogate phenotypes with genetic colocalization studies followed by functional in vitro screens to identify bona fide causal genes for MASLD. APPROACH AND RESULTS: We used the UK Biobank to explore the associations of our novel MASLD score, and genetic colocalization to prioritize putative causal genes for in vitro validation. We created a functional genomic framework to study MASLD genes in vitro using CRISPRi. Our data identify VKORC1 , TNKS , LYPLAL1 , and GPAM as regulators of lipid accumulation in hepatocytes and suggest the involvement of VKORC1 in the lipid storage related to the development of MASLD. CONCLUSIONS: Complementary genetic and genomic approaches are useful for the identification of MASLD genes. Our data supports VKORC1 as a bona fide MASLD gene. We have established a functional genomic framework to study at scale putative novel MASLD genes from human genetic association studies.

Humans↗

PubMed2026

Graph neural network-based risk stratification of prostate cancer using gene expression and SHAP interpretability.

Accurate risk stratification is essential for guiding treatment decisions and preventing over treatment of prostate cancer, which remains one of the most prevalent cancers among adult men. While the Gleason score, obtained from prostate biopsies, is routinely used to assess tumor aggressiveness, the biopsy procedure carries risks such as pain, infection, and, in some cases, serious complications such as sepsis. In this study, we proposed an artificial intelligence-based framework that integrates mRNA expression profiles with functional interaction networks to classify prostate cancer patients into low-, medium-, and high-risk groups defined by Gleason scores. The pipeline comprised five steps: (1) data collection from The Cancer Genome Atlas (TCGA), (2) preprocessing of gene expression data, (3) two-stage feature selection to identify informative biomarkers, (4) risk classification using a dual-branch graph neural network (GNN) that combines gene-gene interaction graphs with sample-level expression features, and (5) model interpretation using SHAP to quantify feature contributions. Differentially expressed genes were identified in the High (ASPN, GMNN, PEBP4, C2, KNCK17), Medium (C2, IGSF1, ASPN, CDKN3, AMH), and Low (TNMD, VWA5B2, ST6GALNAC5, CYP3A5, PHGR1) risk groups, underscoring the molecular heterogeneity of disease progression. On an independent held-out test set, the model achieved AUCs of 0.86, 0.88, and 0.95 for the low-, medium-, and high-risk groups, respectively, with an overall accuracy of 80%. These results suggest that combining GNN-based modeling with explainable AI can capture both global and local molecular patterns relevant to tumor aggressiveness. However, as the model was developed and evaluated solely on the TCGA cohort, the findings should be regarded as exploratory, and external validation will be required to establish generalizability. Within these limitations, the proposed framework highlights the potential of molecular profiling and graph-based deep learning to support more precise, potentially less invasive, risk assessment and individualized treatment planning in prostate cancer.

Prostatic Neoplasms↗

PubMed1986

Biological nonoptimality and quality of postnatal environment as codeterminants of intellectual development.

The relation of nonoptimal condition at birth to the intellectual development of children reared in 2 different environments was investigated in a 4 1/2-year longitudinal experiment. Subjects were 80 disadvantaged children, half of whom were randomly assigned at birth to a day-care program designed to prevent mild mental retardation and half to an educationally untreated control group. All subjects for this report were full-term and weighed over 2,500 grams at birth; condition at birth was considered nonoptimal if the 1-min Apgar score was less than or equal to 8. Results indicated that nonoptimal perinatal status had significant adverse effects on 4 1/2-year scores on the McCarthy Scales of Children's Abilities in the control group (p less than .01); however, test scores of children with optimal or nonoptimal Apgars did not differ within the group that received educational treatment. The results provide support for a framework stressing initial biological vulnerability and subsequent environmental insufficiency as cumulative risk factors in the development of children from low SES families.

Apgar Score↗

PubMed2004

Quantitative sports and functional classification (QSFC) for disabled people with spasticity.

Although sports classification for cerebral palsy has been in use for several years, it is complicated both for training and for scoring. People with cerebral palsy are difficult to fit into classification systems that are appropriate for other disability groups. The aim of this report is to describe the development of a framework for a simple quantitative classification of cerebral palsy. It was designed to be easily understood by all who are investigating, treating, training, coaching, and working with spastic disabled people. The scoring system is accurate and quick, so long as the definitions of items listed are adhered to.

Activities of Daily Living↗

PubMed1977

The participant-observer: a source of invalidity in measuring motor skills?

Test validity can be defined as the accuracy of a test score. Artifacts, sources of error that affect validity, have been studied in both research design and written test frameworks but have received little attention in the context of tests of motor behavior in an educational setting. One potential source of invalidity in motor skill testing is the presence of participant-observers. The participant-observer effect is defined as the influence of the presence of other subjects who are waiting to be tested or who have already been tested on subjects who are being tested. This study was designed to measure the test performances of 175 college women with participant-observers present and with participant-observers absent. The test was an overarm throw for speed measured by an incident light velocimeter. The data were analyzed using 2 X 4 fixed-effects analysis of variance. The presence of other participant-observers did not elicit performance scores that were different from those of subjects tested alone. Thus testing subjects in groups where one member of the group is tested while the others observe did not adversely affect performance on the overarm throw compared with that of subjects tested alone.

Female↗

PubMed2026

Efficacy and safety of Vertebral Body Sliding Osteotomy (VBSO) versus Anterior Cervical Corpectomy and Fusion (ACCF): A systematic review and meta-analysis.

Anterior cervical corpectomy and fusion (ACCF) is an established treatment for complex cervical myelopathy and ossification of the posterior longitudinal ligament (OPLL), yet it carries risks of dural injury and graft-related failure. Vertebral body sliding osteotomy (VBSO) is a novel technique that avoids direct OPLL manipulation by translating the vertebral body anteriorly to enlarge the spinal canal. Although early studies suggest VBSO may reduce complications, evidence remains limited to retrospective cohorts from the technique's developers, with no high-level synthesis directly comparing it to ACCF. We therefore conducted this meta-analysis to compare clinical outcomes, complications, and radiographic parameters between VBSO and ACCF, while critically evaluating the certainty of the evidence and its generalizability. A systematic search of PubMed, Embase, Scopus, the Cochrane Library, and Web of Science (through June 2025) identified four retrospective cohort studies (449 patients; VBSO n = 209, ACCF n = 240). A critical limitation of the included evidence is that all studies originated from a single institution (Asan Medical Center, Seoul, Korea) with overlapping enrollment periods (2006-2020), increasing the risk of duplicate patient cohorts. Furthermore, the first author (D.-H. Lee) is the same across all included studies, introducing substantial surgeon-expertise bias. Outcomes included neurological recovery, functional outcomes, complications, and radiographic parameters. Certainty of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework. Neurological recovery and functional outcomes were comparable between groups. ACCF showed slightly higher postoperative JOA scores (MD -0.59, 95% CI -0.96 to -0.22; p < 0.01), though the clinical relevance is uncertain. VBSO was associated with reduced risks of graft subsidence (RR 0.23; p < 0.01), pseudarthrosis (RR 0.25; p < 0.01), revision surgery (RR 0.17; p < 0.01), and neurological deterioration (RR 0.17; p = 0.02). CSF leakage appeared to be less frequent with VBSO, but the difference was not statistically significant. VBSO was also associated with greater postoperative cervical lordosis and shorter hospital stays. However, these findings must be interpreted with extreme caution: leave-one-out sensitivity analyses revealed that the results for postoperative JOA score, neurological deterioration, and pseudarthrosis were fragile and driven by a single large study, meaning these apparent advantages may not be robust. In addition, GRADE assessment revealed very low certainty across all assessed outcomes. Given the very low certainty of evidence, the preliminary nature of the available data, the fragility of several key findings, and the critical limitations of the underlying studies (single institution, overlapping patient cohorts, developer bias, and systematic imbalance in follow-up duration), the observed differences should be considered hypothesis-generating rather than definitive. VBSO should not be considered a proven superior alternative to ACCF based on the current evidence. Prospective, multicenter, international studies with balanced follow-up durations conducted by independent surgical teams are required before broader adoption can be recommended.

Humans↗

PubMed2026

Integration of single-cell transcriptomics and genomic mutation analysis identifies an immunotherapy-resistant tumor subcluster and validates ARNTL2 as a malignant driver in lung adenocarcinoma.

BACKGROUND: Immunotherapy resistance in lung adenocarcinoma (LUAD) remains a critical clinical challenge, and the mechanisms underlying resistance-associated intratumoral heterogeneity are poorly characterized. METHODS: We performed single-cell RNA sequencing of LUAD patients receiving neoadjuvant immunotherapy (responders vs. non-responders), integrating inferCNV, GSVA, and differential expression analyses. Cluster-specific genes were validated across seven independent cohorts (TCGA-LUAD, GSE13213, GSE26939, GSE29016, GSE30219, GSE31210, GSE42127). A multi-algorithm machine learning framework was used to construct a prognostic model, and the immune microenvironment was characterized using TCIA scoring, seven infiltration algorithms, and ESTIMATE. ARNTL2 function was assessed by CCK-8 and Transwell assays in A549 and H1299 cells. RESULTS: Non-responders showed significant enrichment of epithelial cells, depletion of cytotoxic T/NK cells, and elevated copy number variation burden versus responders (p < 0.0001). A resistance-enriched malignant subcluster (Cluster 2) exhibited hyperproliferative and metabolic reprogramming signatures with upregulated KRT17, S100A2, and CST6, which showed tumor-specific overexpression, adverse prognostic value, and genomic amplification across cohorts. CoxBoost combined with survivalSVM achieved optimal predictive performance (C-index = 0.686), yielding robust risk stratification (HR: 2.54-10.51, all p < 0.05). Low-risk patients showed greater immune infiltration and higher TCIA immunophenoscores. ARNTL2 was an independent prognostic factor (HR: 2.07-4.64) strongly correlated with risk score (r = 0.69), and its knockdown suppressed proliferation and invasion in both LUAD cell lines (all p < 0.05). CONCLUSION: This study identifies a resistance-associated malignant subcluster in LUAD, constructs a validated CoxBoost + survivalSVM prognostic model with robust immune stratification, and establishes ARNTL2 as a core oncogenic driver and therapeutic target.

ARNTL2↗

PubMed2002

Five-factor model of personality and job satisfaction: a meta-analysis.

This study reports results of a meta-analysis linking traits from the 5-factor model of personality to overall job satisfaction. Using the model as an organizing framework, 334 correlations from 163 independent samples were classified according to the model. The estimated true score correlations with job satisfaction were -.29 for Neuroticism, .25 for Extraversion, .02 for Openness to Experience, .17 for Agreeableness, and .26 for Conscientiousness. Results further indicated that only the relations of Neuroticism and Extraversion with job satisfaction generalized across studies. As a set, the Big Five traits had a multiple correlation of .41 with job satisfaction, indicating support for the validity of the dispositional source of job satisfaction when traits are organized according to the 5-factor model.

Factor Analysis, Statistical↗