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At least 235 records · Page 13Linked to original sources
PubMed2026

Evolving Role of Immunotherapy in Advanced Esophageal Squamous Cell Carcinoma: Are Programmed Death-Ligand 1 (PD-L1) Cutoffs Still Relevant?

Immune checkpoint inhibitors have transformed the management of advanced esophageal squamous cell carcinoma (ESCC) across first-line, second-line, and perioperative settings. Programmed death-ligand 1 (PD-L1) expression has served as the principal biomarker guiding patient selection for these agents, yet it is measured inconsistently across trials and antibody platforms, and its predictive value has come under renewed scrutiny as follow-up data have matured. This review synthesizes the pivotal randomized trials that established anti-programmed cell death protein-1 therapy in ESCC, critically appraises the pooled and patient-level meta-analyses that have re-examined outcomes across biomarker subgroups, and situates recent regulatory reassessment of PD-L1 thresholds within this broader evidence base. Assay heterogeneity between scoring systems, discordance across antibody clones, and the biological distinction between PD-L1 as a prognostic versus a predictive marker are examined as sources of continued uncertainty. The review concludes by considering emerging genomic and microenvironmental biomarkers that may eventually complement or refine PD-L1-based patient selection, and offers a framework for interpreting a single expression threshold as an approximate, assay-dependent stratifier rather than a precise biological boundary.

combined positive score↗
PubMed2025

vcfgl: a flexible genotype likelihood simulator for VCF/BCF files.

MOTIVATION: Accurate quantification of genotype uncertainty is pivotal in ensuring the reliability of genetic inferences drawn from NGS data. Genotype uncertainty is typically modeled using Genotype Likelihoods (GLs), which can help propagate measures of statistical uncertainty in base calls to downstream analyses. However, the effects of errors and biases in the estimation of GLs, introduced by biases in the original base call quality scores or the discretization of quality scores, as well as the choice of the GL model, remain under-explored. RESULTS: We present vcfgl, a versatile tool for simulating genotype likelihoods associated with simulated read data. It offers a framework for researchers to simulate and investigate the uncertainties and biases associated with the quantification of uncertainty, thereby facilitating a deeper understanding of their impacts on downstream analytical methods. Through simulations, we demonstrate the utility of vcfgl in benchmarking GL-based methods. The program can calculate GLs using various widely used genotype likelihood models and can simulate the errors in quality scores using a Beta distribution. It is compatible with modern simulators such as msprime and SLiM, and can output data in pileup, Variant Call Format (VCF)/BCF, and genomic VCF file formats, supporting a wide range of applications. The vcfgl program is freely available as an efficient and user-friendly software written in C/C++. AVAILABILITY AND IMPLEMENTATION: vcfgl is freely available at https://github.com/isinaltinkaya/vcfgl.

Software↗
PubMed2000

RHO--radiation hybrid ordering.

Radiation hybrid (RH) mapping is a somatic cell technique that is used for ordering markers along a chromosome and estimating the physical distances between them. With the advent of this mapping technique, analyzing the experimental data is becoming a challenging and demanding computational task. In this paper we present the software package RHO (radiation hybrid ordering). The package implements a number of heuristics that attempt to order genomic markers along a chromosome, given as input the results of an RH experiment. The heuristics are based on reducing an appropriate optimization problem to the traveling salesman problem (TSP). The reduced optimization problem is either the nonparametric obligate chromosome breaks (OCBs) or the parametric maximum likelihood estimation (MLE). We tested our package on both simulated and publicly available RH data. For synthetic RH data, the reconstructed markers' permutation is very close to the original permutation, even with fairly high error rates. For real data we used the framework markers' data from the Whitehead Institute maps. For most of the chromosomes (18 out of 23), there is a perfect agreement or nearly perfect agreement (reversal of chromosome arm or arms) between our maps and the Whitehead framework maps. For the remaining five chromosomes, our maps improve on the Whitehead framework maps with respect to both optimization criteria, having higher likelihood and fewer breakpoints. For three chromosomes, the results differ significantly (lod score >1.75), with chromosome 2 having the largest improvement (lod score 3.776).

Algorithms↗
PubMed1999

Proximal and distal correlates of maternal control style.

Control, as an aspect of maternal interaction, has been found to be an important component to optimal child development. Maternal control style is defined as a mother's tendency to be controlling or supportive of her child's autonomy. The relationship between two types of maternal characteristics, proximal and distal, and maternal control style was investigated in a sample of 184 mothers and their 4-year-old children. Global ratings of videotaped data of two problem-solving tasks were made on a 5-point scale. An optimal maternal control style was associated with higher levels of the distal maternal characteristics of maternal education, age, occupation, and higher levels of the proximal characteristics of maternal responsivity and involvement. A hierarchical regression model explaining 26% of the variance in maternal control style scores supports the importance of both types of maternal characteristics. The results are discussed in relation to the methodology and the theoretical framework of role.

Adult↗
PubMed2026

A machine learning-derived intratumoral heterogeneity-related signature predicts the prognosis for and therapeutic response in patients with skin cutaneous melanoma.

BACKGROUND: Reliable biomarkers for predicting prognosis and therapeutic response in skin cutaneous melanoma (SKCM) remain limited. This study aimed to develop an intratumoral heterogeneity (ITH)-related prognostic signature for SKCM using integrative machine learning. METHODS: RNA sequencing (RNA-seq) data from 472 SKCM patients in The Cancer Genome Atlas (TCGA) and 214 patients in the GSE65904 cohort were analyzed. ITH scores were calculated using the DEPTH2 algorithm. Differentially expressed genes (DEGs) were identified between high- and low-ITH groups [|log2fold change (FC)| &#x2265;1, false discovery rate (FDR) <0.05]. Based on 38 prognostic DEGs identified by univariate Cox regression, we employed an integrative framework of 101 machine learning algorithm combinations to construct prognostic models in the TCGA training cohort. The model with the highest average concordance index (C-index) was validated in the GSE65904 cohort and selected as the prognostic ITH-related signature (PIRS). Associations of the PIRS risk score with tumor mutational burden (TMB), immune cell infiltration, immune checkpoint gene expression, and drug sensitivity were systematically evaluated. Model performance was assessed using receiver operating characteristic (ROC) curves and Cox regression analyses. RESULTS: A 38-gene PIRS was constructed using the plsRcox algorithm. Patients with high PIRS risk scores exhibited significantly poorer overall survival (OS) in both the TCGA and Gene Expression Omnibus (GEO) cohorts. The PIRS was identified as an independent prognostic factor, with area under the curve (AUC) values of 0.779, 0.734, and 0.756 for 1-, 3-, and 5-year survival, respectively. High-risk samples displayed significantly lower TMB (P<0.05), reduced immune and stromal cell infiltration (P<0.001), downregulated immune function, and decreased expression of immune checkpoint genes. Additionally, high- and low-PIRS risk score groups exhibited distinct sensitivity patterns to different classes of targeted agents. CONCLUSIONS: The machine learning-derived PIRS robustly predicts prognosis in SKCM patients. Its clinical application is promising for optimizing patient risk stratification and treatment decisions, though further prospective validation is warranted.

Skin cutaneous melanoma (SKCM)↗
PubMed2001

Assessment of health economics in Alzheimer's disease (AHEAD) based on need for full-time care.

OBJECTIVE: To develop a framework for estimating the long-term health and economic consequences of AD based on patient characteristics at a given point in time. METHODS: A pharmacoeconomic model (Assessment of Health Economics in Alzheimer's Disease, AHEAD) was developed based on equations that relate the probability of needing full-time care (FTC) over time to patient characteristics summarized in index scores. These equations were developed from published data on interquartile times until FTC is needed and until death, using nonlinear regressions of the resulting index-specific hazards. These equations were then incorporated into a hidden Markov framework that allows for calculation of expected time to FTC and to death, as well as of the economic consequences of disease progression. There are three major states in the model: not requiring FTC ("pre-FTC"), requiring FTC, and death. RESULTS: Outcomes for five sample patients are derived to illustrate application of the AHEAD model. The impact of altering disease markers in these patients is also considered. CONCLUSION: The need for a generally applicable tool to forecast long-term outcomes based on relatively short-term data is becoming increasingly acute with the advent of new therapies for AD. The AHEAD model provides a relatively simple framework for the prediction of time to FTC requirement based on short-term observed data such as those from clinical trials. Although subject to the uncertainties inherent in modeling, the model nevertheless provides a standard estimation technique that may facilitate comparisons between existing and emerging therapies.

Aged↗
PubMed2000

Assessment of neuropsychologic impairments after head injury: interrater reliability and factorial and criterion validity of the Neurobehavioral Rating Scale-Revised.

OBJECTIVE: To study interrater reliability and factorial and criterion validity of the Neurobehavioral Rating Scale-Revised (NRS-R). DESIGN: Validity study on persons with traumatic brain injury (TBI) and test-retest reliability study on a randomly selected subset of patients. Factor analyses, kappa statistics, intraclass correlation coefficients, and Cronbach's alphas were used. SETTING: Inpatients from 15 French hospitals, mainly rehabilitation units. Other recruitment sites included a neurology hospital unit and a psychiatry hospital specifically devoted to TBI rehabilitation. PATIENTS: Two hundred eighty-six TBI patients ages 16 to 70 years (convenience sample). RESULTS: For the reliability study, the average of percentages of agreement among the items was 74.3% and the average of kappa statistics was .40. Factor analyses disclosed a maximum likelihood extraction of 5 correlated factors (F), explaining 42.2% of total variance: (F1) deficits in intentional behavior and in memory, (F2) lowering of emotional state, (F3) emotional and behavioral hyperactivation, (F4) lowering of arousal state and of attention, and (F5) language and speech problems. Results support the criterion validity of the factors. Reliability of the factor scores and internal consistencies of factors were very good. CONCLUSIONS: Results describe some important properties of the NRS-R and, through an understanding of its underlying structure and relationships with the patients' clinical characteristics, contribute to the conceptual framework of neuropsychologic impairments after TBI.

Adolescent↗
PubMed1984

A scale to measure physician beliefs about psychosocial aspects of patient care.

This report describes the development and initial validation of a self-report instrument designed to measure beliefs about psychosocial aspects of patient care held by primary care physicians. The strategy used was borrowed from psychological measurement: a rational scale was constructed based on an existing theoretical framework concerning the physician's role, what the patient wants and physicians' reactions to their patients as people. The validation step compared scale scores obtained by diverse groups of providers. Psychometric characteristics of the Physician Belief Scale are adequate: scores follow an approximately normal distribution with the mean near the midpoint of possible scores. Lower scores on the Scale represent a more psychosocial approach to patient care. Initial construct validation was successful: physicians from four disciplines obtained scores congruent with expectations about the psychosocial orientations of the disciplines. A reliable and valid measure has been developed to assess physicians' psychosocial beliefs. The instrument may be used to evaluate effectiveness of behavioral science teaching, describing regional or other differences in physician beliefs within and between specialties and estimating changes in provider beliefs.

Attitude of Health Personnel↗
PubMed2003

A radiation hybrid map of bovine chromosome 24 and comparative mapping with human chromosome 18.

We present herein a bovine chromosome 24 (BTA24) radiation hybrid (RH) map using 40 markers scored on a panel of 90 RHs. Of these markers, 29 loci were ordered with odds of at least 1000:1 in a framework map. An average retention frequency of 17.4% was observed, with relatively higher frequencies near the centromere. The length of the comprehensive map was 640 centiray5000 (cR5000) with an average marker interval of approximately 17.3 cR5000. The observed locus order is generally consistent with currently published bovine linkage and physical maps. Nineteen markers were either Type I loci or closely associated with expressed sequences and thus could be used to compare the BTA24 RH map with human mapping information. All genes located on BTA24 were located on human chromosome 18, and previously reported regions of conserved synteny were extended. The comparative data revealed the presence of at least six conserved regions between these chromosomes.

Animals↗
PubMed2026

Comprehensive evaluation of AlphaFold/OpenFold prediction of experimentally unresolved proteins through novel metrics.

Predicting accurate protein structures is essential for understanding molecular mechanisms, interpreting the impact of sequence variation, and supporting translational applications ranging from drug discovery to clinical genomics. Recent advances in deep-learning-based predictors such as AlphaFold2, OpenFold, and AlphaFold3 have transformed structural biology, enabling routine in silico modeling even for challenging or previously uncharacterized proteins. However, systematic benchmarking of these tools-especially for novel targets and single amino acid variants-remains limited. Conventional global metrics often fail to capture biologically meaningful discrepancies. By evaluating multiple implementations of AlphaFold2 and OpenFold, together with ColabFold and the AlphaFold3 server, across 10 different proteins and 222 single amino acid protein variants encompassing a wide range of sizes, structures, and functions, we show that although widely used global indicators-like mean pLDDT, pTM-score, and RMSD-frequently suggest comparable performance, substantial local-level differences remain elusive. To address this gap, we introduce a comparative framework leveraging Bland-Altman agreement analysis, to evaluate per-residue C&#x3b1;-confidence differences and Per-Residue profiles (PRPs), complemented by Uniform Manifold Approximation and Projection (UMAP). This approach reveals marked localized divergences, particularly within flexible or intrinsically disordered regions, where both predictor choice and single-residue substitutions trigger the largest conformational shifts. We further demonstrate that using reduced homology databases has minimal impact on predicted structural quality, offering computationally efficient alternatives. Collectively, our findings underscore the importance of integrating global and residue-specific evaluations to more accurately assess robustness, agreement, and practical usability across contemporary protein structure prediction methods.

Proteins↗
PubMed1998

Drug policies and harms: a conceptual framework.

Existing indicators of drug-related policies and harms - official statistics, treatment data, and so on - are difficult to interpret and to compare across jurisdictions. We propose a conceptual framework including key dimensions of policy and harm. The framework is designed to guide creation of a new dataset in which existing empirical data can be used to assign city-specific scores on policy and harm dimensions. By an interpretive process involving local experts and a coordinating body, we believe that existing data can be evaluated and synthesized to derive these scores. We also propose a cumulative case-study method of querying the dataset to test hypotheses regarding relationships between policies and harms.

Crime↗
PubMed2025

A large-scale study across the avian clade identifies ecological drivers of neophobia.

Neophobia, or aversion to novelty, is important for adaptability and survival as it influences the ways in which animals navigate risk and interact with their environments. Across individuals, species and other taxonomic levels, neophobia is known to vary considerably, but our understanding of the wider ecological drivers of neophobia is hampered by a lack of comparative multispecies studies using standardized methods. Here, we utilized the ManyBirds Project, a Big Team Science large-scale collaborative open science framework, to pool efforts and resources of 129 collaborators at 77 institutions from 24 countries worldwide across six continents. We examined both difference scores (between novel object test and control conditions) and raw data of latency to touch familiar food in the presence (test) and absence (control) of a novel object among 1,439 subjects from 136 bird species across 25 taxonomic orders incorporating lab, field, and zoo sites. We first demonstrated that consistent differences in neophobia existed among individuals, among species, and among other taxonomic levels in our dataset, rejecting the null hypothesis that neophobia is highly plastic at all taxonomic levels with no evidence for evolutionary divergence. We then tested for effects of ecological factors on neophobia, including diet, sociality, habitat, and range, while accounting for phylogeny. We found that (i) species with more specialist diets were more neophobic than those with more generalist diets, providing support for the Neophobia Threshold Hypothesis; (ii) migratory species were also more neophobic than nonmigratory species, which supports the Dangerous Niche Hypothesis. Our study shows that the evolution of avian neophobia has been shaped by ecological drivers and demonstrates the potential of Big Team Science to advance our understanding of animal behavior.

Animals↗
PubMed1993

A comparison of ICD-10 and DSM-III-R criteria for substance abuse and dependence.

As part of DSM-IV field trials for substance use disorders, 100 inpatients from two psychiatric substance abuse units were interviewed using a modified version of the Substance Abuse Module (SAM) to ascertain substance use diagnoses according to ICD-10 and DSM-III-R criteria. Both criteria sets developed from the theoretical framework presented by Gross and Edwards (1976) and thus, they should demonstrate close concurrence in diagnoses of dependence and abuse/harmful use. The kappa scores obtained in these analyses demonstrate good to excellent agreement on the diagnoses of dependence across substances. There was poor agreement between DSM-III-R and ICD-10 for abuse/harmful use diagnoses. Although there is generally good agreement between DSM-III-R and ICD-10 for substance dependence diagnoses, important differences exist between the two criteria sets both for the diagnoses of abuse and harmful use, and for the diagnosis of marijuana dependence. These differences are primarily due to the inclusion of social problems and repeated use of substances in hazardous situations as DSM-III-R criteria.

Alcoholism↗
PubMed2000

Using the Baldrige management system framework in health care: the Veterans Health Administration experience.

BACKGROUND: In 1998 the Veterans Health Administration (VHA) developed the Quality Achievement Recognition Grant, a competitive grant application open to all Veterans Integrated Service Networks (VISNs) within the VHA system and based on the Baldrige management framework. Eight of the 22 VISNs attended the educational programs and initiated the grant application process; 7 completed applications. Team award experts from VHA and external sources reviewed, scored, and wrote feedback reports to all applicants and conducted four site visits. IDENTIFICATION OF BEST PRACTICES AND RECOMMENDATIONS FOR FUTURE APPLICANTS: Each application was compared to examples of ideal applications to identify areas of excellence and areas for improvement. In general, the best applicants identified and described key processes and articulated the methods used to evaluate and improve processes. For example, they were able to identify the process used to incorporate key constituents into the strategy development process. One applicant developed a series of management advisory committees, the membership of which includes veterans' service organizations, academic affiliates, community members, and congressional delegates, which were tapped to develop a strategic plan. Leading applicants in the future are likely to be able to demonstrate evidence of deployment and constant review of the strategy and to emphasize the human resources plan into the strategic planning and deployment. CONCLUSIONS: The Baldrige management framework is a useful tool for identification of areas of achievement and areas for improvement within the VHA. Potential applicants for the award could benefit from ensuring coherence across the application, placing a greater emphasis on work systems, and incorporating more extensive analysis of market conditions.

Awards and Prizes↗
PubMed2026

Development and Validation of a Clinical Polygenic Risk Report in U.S.-Based Health Systems for 8 Cardiovascular Conditions.

BACKGROUND: Polygenic risk scores (PRS) stratify inherited cardiovascular risk, but their path to clinical implementation remains unclear. OBJECTIVES: We aimed to develop and validate integrated PRS for 8 cardiovascular conditions and outline a framework for their clinical reporting. METHODS: We analyzed genotype and clinical data from 245,394 All of Us Research Program participants. Publicly available PRS for 8 traits-coronary artery disease, atrial fibrillation, type 2 diabetes, venous thromboembolism (VTE), thoracic aortic aneurysm (TAA), extreme hypertension, severe hypercholesterolemia, and elevated lipoprotein(a)-were combined using PRSmix, an elastic-net approach. Integrated PRS were externally validated in 53,306 Mass General Brigham Biobank participants using logistic regression, adjusting for age, sex, and ancestry. RESULTS: Of 53,306 genotyped Mass General Brigham Biobank participants (55.6% women, mean age 53 &#xb1; 17 years), integrated PRS demonstrated robust discrimination and appropriate calibration across 8 cardiovascular traits. Comparing high genetic risk (top 10% of PRS distribution, or top 20% for rarer TAA and VTE) vs average risk (26th-75th percentiles, or 21st-80th percentiles for TAA and VTE) yielded ORs: coronary artery disease (3.7 [95% CI: 3.4-4.1]), type 2 diabetes (3.1 [95% CI: 2.8-3.3]), atrial fibrillation (3.0 [95% CI: 2.7-3.3]), VTE (1.9 [95% CI: 1.6-2.0]), TAA (1.7 [95% CI: 1.5-1.9]), hypertension (2.1 [95% CI: 1.8-2.3]), hypercholesterolemia (4.1 [95% CI: 3.7-4.5]), and lipoprotein(a) (41.0 [95% CI: 27.0-62.2]). Incorporating integrated PRS into clinical models improved risk classification, while prospective analyses confirmed significant associations with incident cardiovascular outcomes. CONCLUSIONS: Integrated PRS offer an implementable framework for genetic risk reporting, and are now available as a clinically orderable test. Broader prospective validation studies are needed to further establish clinical utility.

Humans↗
PubMed2000

A cognitive task analysis for dental hygiene.

To be an effective assessment tool, a simulation-based examination must be able to evoke and interpret observable evidence about targeted knowledge, strategies, and skills in a manner that is logical and defensible. Dental Interactive Simulations Corporation's first assessment effort is the development of a scoring algorithm for a simulation-based dental hygiene initial licensure examination. The first phase in developing a scoring system is the completion of a cognitive task analysis (CTA) of the dental hygiene domain. In the first step of the CTA, a specifications map was generated to provide a framework of the tasks and knowledge that are important to the practice of dental hygiene. Using this framework, broad classes of behaviors that would tend to distinguish along the dental hygiene expert-novice continuum were identified. Nine paper-based cases were then designed with the expectation that the solutions of expert, competent, and novice dental hygienists would differ. Interviews were conducted with thirty-one dental hygiene students/practitioners to capture solutions to the paper-based cases. Transcripts of the interviews were analyzed to identify performance features that distinguish among the interviewees on the basis of their expertise. These features were more detailed and empirically grounded than the originating broad classes and better serve to ground the design of a scoring system. The resulting performance features were collapsed into nine major categories: 1) gathering and using information, 2) formulating problems and investigating hypotheses, 3) communication and language, 4) scripting behavior, 5) ethics, 6) patient assessment, 7) treatment planning, 8) treatment, and 9) evaluation. The results of the CTA provide critical information for defining the necessary elements of a simulation-based dental hygiene examination.

Algorithms↗
PubMed2002

Low-probability event-detection and separation via statistical wavelet thresholding: an application to psychophysiological denoising.

OBJECTIVES: The aim of this paper is to introduce and test a general, wavelet-based method for the automatic removal of noise and artefact from psychophysiological data. METHODS: Statistical wavelet thresholding (SWT) performs blind source separation by transforming data to the wavelet domain, and subsequent filtering of wavelet coefficients based on a statistical framework. The observed wavelet coefficients are modelled using a Gaussian distribution, from which low-probability outliers are attenuated based on their z-scores. RESULTS: The technique was applied to both simulated and real event-related potentials (ERP) data. SWT applied to artificial data displayed increased signal-to-noise ratio (SNR) improvements as noise amplitude increased. ERP averages of filtered experimental data displayed a correlation of 0.93 with operator-filtered data, compared with a correlation of 0.56 for unfiltered data. The energy of operator-designated contaminated trials was attenuated by a factor of 7.46 relative to uncontaminated trials. SNR improvement was observed in simulated tests. CONCLUSIONS: Variations of SWT may be useful in situations where one wishes to separate uncommon/uncharacteristic structures from time series data sets. For artefact removal applications, SWT appears to be a valid alternative to expert operator screening.

Artifacts↗