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PubMed2026

Artificial intelligence-based tumour infiltrating lymphocyte quantification in patients with triple-negative breast cancer: an independent validation study.

BACKGROUND: Tumour-infiltrating lymphocytes (TILs) are a robust prognostic marker in patients with triple-negative breast cancer. Artificial intelligence (AI)-derived computational tools assessing TILs could improve efficiency, but require independent validation against clinical outcomes. We aimed to compare the prognostic performance of AI-derived TIL scores with pathologist-scored TILs in a large, prospectively collected dataset pooled from randomised controlled trials. METHODS: CATALINA was an independent, external validation study using prospectively collected long-term clinical outcome data pooled from seven randomised clinical trials conducted at multiple sites. We independently evaluated two previously validated AI pipelines that generate five computationally assessed tumour-infiltrating lymphocyte (cTIL) scores by masked, independent deployment of locked models. cTIL scores were correlated with the mean of the pathologist-scored stromal TILs (sTILs) in 220 digitised haematoxylin and eosin whole slide images in a cohort of patients with early-stage triple-negative or HER-2 positive breast cancer, previously scored by trained pathologists in a TIL-reproducibility study. Prognostic performance was assessed in a separate cohort of patients with early triple-negative breast cancer pooled from seven prospective, randomised adjuvant trials. Multivariable Cox regression models adjusted for clinicopathological factors and study heterogeneity assessed associations of cTIL score and sTIL score with invasive disease-free survival, distant disease-free survival, and overall survival. 5-year discrimination was estimated using time-dependent area under the receiver operating characteristic curve (AUC). FINDINGS: Individual data were collated from 1759 patients, of whom 1356 had complete clinicopathological data, pathologist sTIL scores, and cTIL scores available. Modest correlation (r 0·375-0·473) was observed between cTIL scores and the mean pathologist sTIL score. Both sTIL and cTIL were independently associated with 5-year invasive disease-free survival, distant disease-free survival, and overall survival after adjustment for clinicopathological factors (hazard ratio for invasive disease-free survival was 0·73 [95% CI 0·66-0·82]; q<0·0001, distant disease-free survival was 0·70 [0·61-0·79]; q<0·0001, and overall survival was 0·72 [0·63-0·82]; q<0·0001 for sTIL scores and 0·80 [0·73-0·89]; q<0·0001, 0·77 [0·69-0·86]; q<0·0001, and 0·79 [0·70-0·88]; q=0·0002, respectively, for percentage_lymphocyte scores). In models adjusted for clinicopathological variables and sTIL score, cTIL score did not maintain a statistically significant prognostic association. Both sTIL and cTIL scores improved the 5-year AUC over clinicopathological variables alone, while cTIL score did not significantly further improve AUC when combined with clinicopathological variables and sTIL score. INTERPRETATION: Two cTIL models deployed entirely without retraining or modification provided statistically significant prognostic information and improved risk discrimination compared with clinicopathological variables alone in this large, platform-based, independent validation study. Although cTIL score did not incrementally improve prognostication compared with models combining clinicopathological variables with sTIL score, these findings support the application of cTILs as a reproducible prognostic biomarker, particularly in settings where routine or widespread pathologist assessment is unavailable. FUNDING: Breast Cancer Research Foundation (USA).

Humans↗

PubMed2026

Methods for defining equity-stratifying variables: a systematic review of validation studies.

BACKGROUND AND OBJECTIVE: Disease burden is often disproportionally higher among those who are socially disadvantaged by factors defined in the PROGRESS-Plus framework (ie, Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital, with "Plus" covering features like age and disability). The accuracy and applicability of case definitions to identify these variables from administrative and clinical health data are unknown. We conducted a systematic review to explore how equity-stratifying variables, as categorized by the PROGRESS-Plus framework, have been defined and validated in epidemiologic studies using administrative health, population-level, or electronic health record (EHR) data. METHODS: Medline, EMBASE, CINAHL, Web of Science, and Google Scholar were searched from the inception of the databases to 2024 for validation studies of equity-stratifying variables in adults using administrative health datasets, health registries, or EHR data. Titles and abstracts, followed by relevant full-text articles, were screened in duplicate by two reviewers for eligibility. The data sources utilized, algorithms employed, and their associated performance measures were extracted and synthesized from included studies. Given substantial heterogeneity in study design, equity-stratifying variable definition, and performance metrics, meta-analysis was not possible. RESULTS: Of the 9099 unique citations screened, 188 full texts were reviewed and 116 were included in this review. Most studies were published between 2019 and 2024 (n = 64, 55%) and were validation studies of race/ethnicity definitions that used race/ethnicity codes or surname list algorithms (n = 66, 57%). No studies examined religion. Regarding the reported performance measure estimates, the race/ethnicity/culture/language equity-stratifying variables category had the largest variability across sensitivity, positive predictive value (PPV), and Cohen's Kappa. Occupation validation studies had the lowest variation in sensitivity and PPV. CONCLUSION: Despite an increasing number of publications reporting on the validation of equity-stratifying variables relevant to the PROGRESS-Plus framework, performance measures varied widely across studies. The significant heterogeneity in equity-stratifying variable definitions and methods used to validate them support the need for further rigorous validation of equity-stratifying variables in administrative and clinical health data. PLAIN LANGUAGE SUMMARY: Disease burden is often higher in people who experience financial hardships, lower level of education, discrimination due to race/ethnicity, and unstable housing. These social factors can be considered health equity factors and are important for understanding health inequalities. Health researchers often use large datasets, such as hospital or electronic health records (EHRs), to study these health equity factors. However, it is not clear how accurately these data sources capture information about people's social circumstances and how these factors are defined. In this study, we reviewed existing research to understand how health equity factors have been defined across health data sources and how accurate they are at measuring aspects of health equity and social disadvantage. Of the more than 9000 studies we identified, we included 116 that met our criteria for this systematic review. Most included studies focused on identifying race and ethnicity, often using codes or surname-based methods. We found that the accuracy of these methods varied widely across studies, meaning results may not always be reliable or comparable. Overall, our findings show that there are inconsistencies in how social factors are defined and measured in health data. This makes it difficult to fully understand and address health inequalities using routinely collected health data. More work is needed to develop and validate better quality and more consistent methods for capturing these important social factors.

Humans↗

PubMed2026

Artificial intelligence-assisted histopathological diagnosis of endocervical gastric-type adenocarcinoma: a multicenter model development and validation study.

Endocervical gastric-type adenocarcinoma (GAS) is one of the most aggressive subtypes of cervical cancer and is frequently underdiagnosed due to morphological ambiguity, leading to delayed diagnosis. Despite the availability of molecular and genomic assays, their high cost, complexity, and limited reproducibility restrict clinical use. This study therefore proposes a highly sensitive artificial intelligence (AI)-assisted diagnostic system for GAS based exclusively on H&E-stained histopathological images. We included 309 slides from 96 GAS cases collected at Peking University Third Hospital from January 2018 to January 2025, representing the largest GAS cohort reported to date for AI research. In addition, we incorporated other morphologically analogous diseases, encompassing a total of 1,320 slides sourced from four categories: normal cervical mucosa (NORM), benign endocervical lesion entities (BELE), HPV-associated adenocarcinoma (HPVA), and endometrioid carcinoma with mucinous differentiation (ECMD). We developed GASPath, based on a novel multiple instance learning framework that efficiently captures fine-grained morphological variations from H&E-stained images. Beyond internal validation, GASPath was evaluated across 12 independent retrospective cohorts and further subjected to large-scale real-world validation on more than 7,000 samples from March 2024 to April 2025. Across three stages, GASPath demonstrated high performance. In internal validation (Stage I), it achieved an accuracy of 0.980 (95% CI 0.977-0.983) and an ROC-AUC of 0.995 (95% CI 0.994-0.997). In external validation (Stage II), the sensitivity reached 0.902 and improved to 0.968 with proposed strategies. For biopsy samples, GASPath achieved an ROC-AUC of 0.990 (95% CI 0.984-0.997). In large-scale real-world deployment (Stage III, n = 7,056), GASPath achieved a balanced accuracy of 0.953, with 100% sensitivity for GAS (45/45 cases correctly identified). The heatmaps highlight morphological features of GAS that are easily underestimated, such as irregular, angulated glands, subtle loss of nuclear polarity, and mild cytologic atypia, which show substantial morphological overlap with other diagnostic categories. GASPath enables high-sensitivity detection of GAS in routine H&E-stained slides, obviating the need for extensive auxiliary testing while preventing underdiagnosis and misdiagnosis. This advancement addresses a critical gap by streamlining diagnostic workflows without compromising accuracy. Its implementation could enable cost-effective, scalable AI-assisted diagnostics, potentially transforming the early detection and management of this aggressive cancer subtype.

Female↗

PubMed2026

Predicting 5-Year Mortality in Non-Small-Cell Lung Cancer Using the Korean Central Cancer Registry: Model Development and Validation Study.

BACKGROUND: Non-small-cell lung cancer (NSCLC) is one of the most common cancers and a leading cause of cancer-related mortality, making prognostic prediction clinically essential. Machine learning models are increasingly used to assess prognosis; however, developing systems that combine high discrimination with clear, clinically interpretable reasoning remains challenging. OBJECTIVE: This study aimed to develop deep learning models that predict 5-year mortality in NSCLC using data from the Korea Central Cancer Registry and quantify feature importance through permutation testing. METHODS: We identified 3144 patients diagnosed between 2014 and 2017 who had complete clinical data, pulmonary function test results, histological information, genomic data, and staging details. After preprocessing, the cohort was divided into stratified training, validation, and test sets in a 70%-15%-15% ratio. Five models were tuned using Hyperband across 10 predefined feature groups. The primary evaluation metric was the area under the receiver operating characteristic curve (AUC); additional metrics included accuracy, F1-score, precision, and recall. Groupwise permutation importance was calculated for each model, and the concordance of importance rankings was assessed using the Friedman test. RESULTS: All 5 models yielded comparable discrimination values on the test set (AUC=0.875-0.879). Model A was selected as the primary model and achieved an AUC of 0.879, an accuracy of 0.806, an F1-score of 0.824, and a Brier score of 0.142. Permuting the stage resulted in the largest decrease in AUC (0.217), followed by the pulmonary function test (0.016). Gene mutation had a modest overall impact but became more influential within the adenocarcinoma subset. The Friedman test showed no statistically significant differences in importance rankings across the models (P=.93). CONCLUSIONS: A grouped-input deep learning framework achieved discrimination comparable to a conventional Cox proportional hazards model using the same routine clinical variables for 5-year mortality prediction in NSCLC. Group-level permutation importance provided stable and reproducible insights into the clinical factors influencing risk, which may guide future model refinement and clinical decision-making.

Humans↗

PubMed2026

Simultaneous determination of imiquimod and terbinafine in skin permeation studies: Validation of a liquid chromatography method with fluorescence detection.

Chromoblastomycosis is a chronic, neglected subcutaneous mycosis posing significant therapeutic challenges. A topical strategy combining terbinafine (TBF), an antifungal, with imiquimod (IMQ), a TLR-7/8 agonist immunomodulator, has emerged a promising alternative. However, no validated analytical method is currently available to simultaneously quantify both drugs in skin, which is crucial for novel formulation development. This study reports the development and validation of a simple HPLC method with fluorescence detection (excitation 236 nm, emission 340 nm) for the simultaneous determination of TBF and IMQ extracted from porcine skin. Separation was achieved on a C8 reversed-phase column (125 × 4.0 mm, 5 μm) using a mobile phase of methanol and water (60,40, v/v), both containing 0.1% formic acid at a flow rate of 0.8 mL/min. The method showed excellent linearity (r > 0.999) over 0.01-1.0 μg/mL for IMQ and 0.1-2.0 μg/mL for TBF. Intra- and inter-day precision demonstrated coefficients of variation below 5%, and recovery rates from skin (79-105%) confirmed accuracy. Limits of detection were 0.001 μg/mL for IMQ and 0.004 μg/mL for TBF, with quantification limits of 0.02 μg/mL and 0.16 μg/mL, respectively. This selective, sensitive, and reproducible method represents a valuable analytical tool for supporting the development and quality control of topical formulations for chromoblastomycosis and other fungal skin diseases.

Animals↗

PubMed2026

An individualized nomogram for predicting progression-free survival in systemic anaplastic large cell lymphoma: a multicenter, retrospective, and internally validated study.

OBJECTIVES: To develop an individualized nomogram for predicting disease progression risk in systemic anaplastic large cell lymphoma (sALCL). METHODS: Independent predictors of progression-free survival (PFS) were identified using Cox regression in a multicenter retrospective cohort of 109 sALCL patients (2010-2022). These were incorporated into a three-factor nomogram, evaluated via bootstrapped internal validation (1000 resamples), ROC analysis, C-index, decision curve analysis (DCA), and clinical impact curve (CIC). RESULTS: A total of 29 PFS events occurred during a median follow-up of 31 months. Multivariable modelling selected serum β2-microglobulin elevation, extranodal disease, and front-line chemotherapy choice (CHOP versus CHOPE or BV+CHP) as autonomous progression drivers. Upon internal bootstrap validation, the nomogram yielded strong prognostic accuracy, achieving AUCs of 0.81, 0.85 and 0.87 for 1-, 3- and 5-year progression-free survival, alongside a corrected C-index of 0.779 (95% CI: 0.699 - 0.861). Calibration plots showed close agreement between predicted and observed outcomes, while DCA confirmed superior net clinical benefit versus conventional IPI or Ann Arbor stratification across multiple decision thresholds. CONCLUSION: This first sALCL-specific nomogram integrates clinical and treatment variables to provide personalized PFS risk estimation. While internally validated, this exploratory, observation-based tool requires external validation and recalibration in prospective cohorts before clinical implementation.

Humans↗

PubMed2026

PCSK9 as a Key Gene of Metastasis in Lung Adenocarcinoma: A Multi-omics and Experimental Validation Study.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common form of lung cancer. Proprotein convertase subtilisin/kexin type 9 (PCSK9) is abnormally expressed in various tumor tissues and is associated with malignant phenotypes. However, the clinical significance, function, and mechanism of LUAD invasion and metastasis remain unclear. METHODS: We retrospectively enrolled 100 patients with LUAD in this study. Initially, qRT-PCR was performed to detect PCSK9 levels in clinical tissues. Subsequently, bioinformatics analysis of scRNA-seq and The Cancer Genome Atlas Program (TCGA) datasets was performed to predict the role of PCSK9 in tumor cell malignancy and its potential downstream pathways. These predictions were validated experimentally using the CCK-8 assay, TUNEL staining, wound healing, transwell invasion assay, and an in vivo lung metastasis model. Finally, Western blotting and an AKT inhibitor (MK2206) were used to verify the underlying mechanism. RESULTS: PCSK9 was significantly upregulated in LUAD tissues compared to paracancerous tissues and was associated with poorer OS and DFS. Bioinformatics analysis of scRNA-seq data and TCGA analysis predicted that PCSK9 is highly enriched in tumor cells and is involved in EMT, and that the PI3K/AKT pathway plays a significant role in LUAD development. Experiments confirmed that PCSK9 markedly promoted LUAD cell proliferation, migration, and invasion in vitro and lung metastasis in vivo. PCSK9 overexpression significantly upregulated p-AKT, p-PI3K, and p-mTOR levels. Furthermore, the AKT inhibitor, MK2206, reversed the promoting effects of PCSK9. CONCLUSIONS: PCSK9 expression is associated with the prognosis and diagnosis of LUAD. This molecule activates the PI3K/AKT signaling pathway, thereby driving invasion, metastasis, and proliferation in LUAD.

Humans↗

PubMed2026

Exploring the mechanism of the Lianshi Jianpi formula in treating impaired glucose tolerance: a network pharmacology, molecular docking, and experimental validation study.

OBJECTIVE: To explore the bioactive constituents, key targets, signalling pathways, and molecular mechanisms of Lianshi Jianpi formula (, LSJPF) in the treatment of impaired glucose tolerance (IGT) through network pharmacology, molecular docking, and in vivo experiments. METHODS: The active ingredients and targets of LSJPF were identified using the Traditional Chinese Medicine Systems Pharmacology and HERB databases, whereas the IGT-related targets were sourced from GeneCards, DisGeNET, and PubMed. The overlap analysis identified potential targets of LSJPF. Protein-protein interaction networks and core targets were evaluated using the Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape, and molecular docking confirmed the binding affinities. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using Metascape. The therapeutic mechanisms were validated in an animal IGT model. RESULTS: LSJPF contained 229 compounds, with 15 active compounds and 77 potential target proteins. The phosphatidylinositol-3-kinase (PI3K)-protein kinase B (AKT) signalling pathway emerged as a key IGT pathway. The KEGG enrichment analysis revealed the pivotal genes RAC-alpha serine/threonine-protein kinase (AKT1), heat shock protein 90 kDa alpha B1, and B-cell lymphoma 2 family protein, which predominantly interact with beta-sitosterol and beta-carotene, the major constituents of Semen Euryales, Semen lablab Album, Semen sojae Atricolor in LSJPF. Molecular docking revealed strong binding affinities between LSJPF and IGT-related targets. In an animal IGT model, LSJPF treatment prevented weight loss; reduced food and water intake; decreased blood glucose levels; improved insulin resistance; decreased serum triglyceride, cholesterol, and low-density lipoprotein cholesterol levels; alleviated liver pathology; and significantly increased the levels of phosphorylated adenosine 5'-monophosphate-activated protein kinase (AMPK), PI3K, and AKT, suggesting its potential role in regulating glucose and lipid metabolism. CONCLUSIONS: These findings reveal the potential of LSJPF as an IGT intervention that targets the AMPK/PI3K/AKT cascade, validating network pharmacology predictions and highlighting the role of multipathway mechanisms in metabolic diseases.

Molecular Docking Simulation↗

PubMed2026

Diagnostic performance of machine learning models for malignant and non-malignant pleural effusion: Systematic review and meta-analysis.

BACKGROUND: Accurately distinguishing malignant pleural effusion (MPE) from non-malignant pleural effusion is clinically important, but the generalisability and methodological quality of machine-learning (ML) models remain uncertain. METHODS: We searched eight databases to 23 April 2026. Diagnostic performance was pooled using random-effects and Reitsma bivariate models, and study quality was assessed using PROBAST+AI. RESULTS: Forty-two studies were included; 17 contributed to the AUC meta-analysis and 14 to the bivariate analysis. The pooled AUC was 0.90 (95 % CI 0.85-0.94; 95 % prediction interval 0.62-0.98), with sensitivity of 0.80 (95 % CI 0.77-0.83) and specificity of 0.87 (95 % CI 0.79-0.92). Only nine studies reported external, temporal or independent validation. Externally validated studies had a lower pooled AUC than studies without external validation (0.83 vs 0.92), with lower specificity observed in the two externally validated studies contributing sensitivity and specificity data. All 42 development assessments had high overall quality concerns, and all 42 model evaluations were judged at high risk of bias. CONCLUSIONS: ML models showed good apparent accuracy for distinguishing MPE from non-MPE, but the evidence was limited by substantial heterogeneity, high risk of bias and scarce external validation. The pooled estimates reflect the average performance of different selected models rather than the expected accuracy of a single clinical test. ML models should be regarded as adjuncts to existing diagnostic pathways until they are confirmed by rigorous multicentre prospective external validation and clinical-impact studies.

Humans↗

PubMed2026

Wearable wrist-watch type cuff oscillometric blood pressure monitors: consensus statement by the European Society of Hypertension Working Group on blood pressure monitoring.

Wearable wristwatch-type cuff oscillometric blood pressure (BP) monitors represent a new category of BP devices and are the first wearable monitors to use established cuff-oscillometric BP measurement technology. This consensus statement by the European Society of Hypertension Working Group on BP Monitoring reviews the published evidence on their design, accuracy, validation, clinical application, and remaining research questions. Of 281 articles identified through a systematic PubMed search, 26 were relevant. Several devices are currently available; however, only two have published validation studies performed according to established standards (Omron HeartGuide and Huawei Watch D/D2). Static validation studies generally showed acceptable accuracy, whereas data on 24-h ambulatory use, in special populations, and clinical applications remain limited. Potential advantages include self-initiated measurement at home, at work, and in other settings and conditions; more convenient and repeatable 24-h ambulatory monitoring; more convenient and accurate assessment of asleep BP; capture of stress-related and other BP-related episodes. However, proper wrist position, user adherence, ambulatory performance, and clinical applications require further investigation. More research is needed to establish the accuracy and clinical utility of these novel devices and their role in improving the diagnosis and management of hypertension.

Humans↗

PubMed2026

Validation of an integrated metagenomic pipeline combining optimized wet-lab processing and tiered reporting for CSF pathogen detection.

UNLABELLED: Metagenomic next-generation sequencing (mNGS) in the infectious disease diagnostic space has been gaining traction and is popular for aiding in the diagnosis of central nervous system infections. However, many challenges and obstacles remain in making this technology a gold standard for infectious disease diagnostic testing. One major challenge is being able to distinguish between the clinically relevant organisms from background contamination. We performed a validation study for mNGS on cerebrospinal fluid (CSF) that utilized positive clinical samples and contrived samples that incorporated a bioinformatics pipeline that can better distinguish between background contamination and clinically relevant organisms and used a three-tiered reporting algorithm meant to decrease the inherent subjectivity that comes with interpreting and reporting data from clinical metagenomic sequencing. The validation of this assay and category-based reporting pipeline revealed an overall concordance of 91.8%, with a sensitivity of 100% and a specificity of 72.4%. In addition, we improved the detection of clinically relevant RNA viruses to almost 100% in the CSF by modifying the wet lab processing of the sample. This bioinformatics pipeline with a category-based reporting algorithm will provide more confidence in reporting microorganisms detected with this technology, mNGS, and improving patient care. IMPORTANCE: Metagenomic next-generation sequencing (mNGS) can offer a broad, unbiased approach for the detection of infectious pathogens and has shown promise in diagnosing central nervous system infections. Despite its potential, clinical implementation remains limited by challenges in distinguishing clinically relevant organisms from background contamination. This study validated an mNGS assay for cerebrospinal fluid that incorporates an optimized bioinformatics pipeline with a three-tiered reporting algorithm designed to reduce subjectivity and enhance diagnostic confidence. The assay also has improved detection of clinically relevant RNA viruses through modified wet-lab processing. These findings support the clinical utility of a structured, category-based reporting approach for mNGS, advancing its reliability as a diagnostic tool in infectious disease testing.

Metagenomics↗

PubMed2026

Pan-cancer Bioinformatics Analysis Combined with Colon Cancer Experimental Validation: A Study on TMED3 as a Diagnostic and Prognostic Biomarker.

Transmembrane Emp24 Protein Transport Domain 3 (TMED3), a member of the p24 protein family, has been implicated in tumor proliferation, invasion, and migration. This study aimed to evaluate the expression patterns, prognostic significance, immune associations, and potential biological functions of TMED3 across multiple cancer types using pan-cancer bioinformatics analysis combined with immunohistochemical (IHC) validation in colon cancer. Multiomics datasets from The Cancer Genome Atlas, Genotype-Tissue Expression, UALCAN, Human Protein Atlas, and cBioPortal databases were analyzed to investigate TMED3 expression and genetic alterations in pan-cancer. Immunohistochemistry was performed to evaluate TMED3 protein expression in colon cancer tissues. Kaplan-Meier survival analysis and Cox regression analysis were used to assess the prognostic value of TMED3. Spearman correlation analysis was conducted to evaluate the associations of TMED3 with tumor mutational burden, microsatellite instability (MSI), immune cell infiltration, and immune checkpoints. Gene Set Enrichment Analysis was performed to investigate potential biological pathways associated with TMED3 in colon cancer. TMED3 expression was elevated in most tumor types and was associated with unfavorable overall survival and disease-specific survival in adrenocortical carcinoma, colon adenocarcinoma, and uveal melanoma. The greatest frequency of TMED3 genetic alterations was identified in mesothelioma, with amplification representing the predominant alteration type. In addition, TMED3 expression showed significant correlations with tumor mutational burden and microsatellite instability in kidney renal clear cell carcinoma, stomach adenocarcinoma, and uterine corpus endometrial carcinoma. TMED3 expression was also associated with immune infiltration and immune checkpoint expression in several tumors. IHC analysis demonstrated increased TMED3 expression in colon cancer tissues compared with normal colon tissues and showed an association with T stage. Functional enrichment analysis identified pathways related to ribosome, antigen processing and presentation, oxidative phosphorylation, and pentose phosphate. These findings indicate that TMED3 may represent a promising biomarker for the diagnosis and prognostic evaluation of colon cancer as well as other tumor types.

Humans↗

PubMed2026

Assessing the Concurrent Validity of the Australian Treatment Outcomes Profile in a Methamphetamine Dependent Treatment-Seeking Population.

INTRODUCTION: The Australian Treatment Outcomes Profile (ATOP) is a brief clinical tool assessing substance use, health and well-being used in Australian alcohol and other drug treatment services. It is validated for use with clients using alcohol, opioids and cannabis, but not yet for clients who primarily use methamphetamine. METHODS: An embedded validation study was undertaken in treatment-seeking adults enrolled in a randomised double-blind placebo-controlled trial of lisdexamfetamine for methamphetamine dependence with sites in New South Wales, South Australia and Victoria. Participant demographics were collected during study screening. The ATOP and comparators (Time Line Follow Back, Opiate Treatment Index, Depression Anxiety Stress Scale, WHOQOL-BREF and Personal Wellbeing Index) were collected at baseline. Continuous ATOP items were analysed using Pearson's correlation coefficient, and dichotomous items were analysed using Fleiss's κ. Agreement was rated as strong where measures were ≥ 0.50, moderate where agreement was 0.30-0.49, and weak where < 0.30. RESULTS: One hundred and eighteen study participants (2018-2020) had data for concurrent validity analysis. Strong validity was demonstrated for physical health, psychological health, quality of life, injecting drug use and crime items, and for days of use for amphetamines, alcohol, cannabis and cocaine. There was weak validity for days of use for benzodiazepines. Heroin use days and other opioid use days were endorsed by fewer than five participants and were therefore unable to be assessed. DISCUSSION AND CONCLUSIONS: The ATOP is valid for use in a treatment-seeking methamphetamine-dependent population, expanding the range of tools for assessment and standardised outcome monitoring across different settings and services.

Humans↗

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 ± 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↗

PubMed2026

Validation of a national genetic evaluation for methane emission in Holstein cattle.

Lactanet Canada launched a genomic evaluation for methane efficiency for Holsteins in April 2023, utilizing milk mid-infrared-predicted methane (CH4) emissions (CH4MIR) as a proxy. This study validated the methane efficiency genomic evaluation using genotyped cows with CH4MIR and CH4 records from GreenFeed systems (CH4GF), along with relative breeding values (RBV) for methane production and methane efficiency from the April 2023 evaluation. In Lactanet's methane efficiency evaluation, a higher RBV indicates more desirable, lower-emitting animals. For the validation, RBV were categorized into quintiles for the CH4MIR dataset and tertiles for the CH4GF dataset to evaluate trends across the RBV distribution. Mean CH4MIR decreased progressively across RBV quintiles for both traits, with all pairwise comparisons among quintiles significantly different. Similarly, CH4GF emissions declined across RBV tertiles, with significant differences observed between the lowest and highest tertiles. Additional analyses using RBV threshold categories confirmed that cows with the highest RBV consistently exhibited lower methane emissions. Linear regression analyses further demonstrated a negative relationship between RBV and methane emissions, supporting the predictive ability of the genomic evaluation. These findings confirm that Canada's genomic evaluation for methane efficiency effectively differentiates cows by methane emission potential, reinforcing its potential as a tool for genetic selection to reduce methane emissions in dairy cattle.

Journal Article↗

PubMed2026

Characterizing Submental Neuromuscular Activity of Swallowing Rehabilitation: An Electromyographic Evaluation of Rehabilitative Maneuvers in Healthy Adults.

PURPOSE: The effortful swallow (ES), the Mendelsohn maneuver (MM), and isometric tongue presses (TPs) are widely used swallowing maneuvers/exercises to improve elements of swallowing, such as muscle strength and biomechanics. However, the underlying neuromuscular mechanisms of these exercises remain unclear, potentially limiting our ability to specify treatment targets and improve treatment efficacy. This study aimed to compare submental neuromuscular activation patterns during the ES, MM, TPs, and typical swallows in healthy young and older adults. METHOD: As part of a larger randomized crossover validation study, 60 healthy adults (30 young and 30 older) completed typical swallows and three maneuvers using a wearable submental surface electromyographic (sEMG) system (i-Phagia). Outcome variables included (a) normalized mean sEMG amplitude and (b) time to peak sEMG amplitude. Linear mixed models were used to examine effects of task, age, and sex on both outcomes. RESULTS: Normalized mean amplitude was significantly different across tasks. Post hoc pairwise comparisons confirmed that all three maneuvers produced higher normalized mean sEMG amplitude than typical swallows, with the ES eliciting the highest amplitude across age groups. Time to peak amplitude differed significantly across tasks, with typical swallows requiring the shortest time to reach peak amplitude, followed by the ES, MM, and TP. CONCLUSIONS: The ES required the highest neuromuscular effort with the shortest time to reach peak amplitude, suggesting its potential for targeting submental muscle power. Typical swallows required the least neuromuscular effort with the shortest time to reach peak amplitude, suggesting their potential for training submental muscle speed. The MM and TP may also improve submental muscle strength; however, given their temporal requirements (longer durations), they may be more beneficial for targeting coordination and endurance, though more research in this area is warranted. These findings underscore the importance of task-specific neuromuscular profiling to inform mechanism-based swallowing rehabilitation. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.32948549.

Humans↗

PubMed2026

Whole-Genome Analysis of Bacillus Licheniformis Ali5 and Synthesis of Lichenysin via Genome Shuffling.

Whole-genome sequencing of Bacillus licheniformis Ali5 was performed via MGI-seq PE150 and Nanopore single-molecule real-time sequencing. The strain has a 4,114,664 bp circular genome encoding 4030 protein-coding genes. Functional annotation across NR, COG, GO, KEGG, CARD, BacMet, and CAZy databases identified 4025, 2812, 988, 1242, 72, 69, and 94 corresponding genes, respectively, and antiSMASH 6.0 revealed multiple antimicrobial biosynthetic gene clusters, including intact lichenysin and lichenicidin VK21 A1/A2 gene clusters. Three rounds of recursive protoplast fusion-based genome shuffling, paired with a dual-index screening system, significantly improved strain growth and lichenysin biosynthesis. Recombinants exhibited shortened lag phase, enhanced proliferation, improved stationary-phase stability, and higher diauxic peak biomass. PP3-176 and PP3-186 showed 4.6%-8.1% higher 12-h shake-flask titer and 3.1%-4.0% higher maximum titer than the parental average, with excellent fermentation stability. 1-L bioreactor validation confirmed strong scale-up potential. PP3-186 achieved 27.2% and 31.6% titer increases at 12 h and 20 h, while PP3-176 yielded 20.4% and 14.6% improvements with robust metabolic performance. This study validates genome shuffling as an effective strategy for enhancing lichenysin production, providing candidate strains and technical support for industrial application.

Bacillus licheniformis↗

PubMed2026

Maternal genetic variants associated with aneuploid conception: a narrative review.

BACKGROUND: Human aneuploid conception, a leading cause of infertility, pregnancy loss, and congenital disorders (e.g. Down's syndrome), arises from errors in chromosome segregation during oocyte meiosis or embryonic mitosis. While advanced maternal age is a well-established risk factor, significant inter-individual variation exists among younger women, suggesting a substantial role for maternal genetic determinants. OBJECTIVE AND RATIONALE: This review summarizes the identified maternal genetic variants associated with aneuploid conceptions and highlights directions for future research. SEARCH METHODS: We systematically searched PubMed, Embase, and the Cochrane Library (up to 12 January 2026), using key terms related to maternal genetics, genetic variants, aneuploidy, and pregnancy. Inclusion criteria were human studies, genetic confirmation of aneuploidy (in oocytes/embryos/products of conception/fetal cells), maternal variants (rare single-nucleotide variations, single-nucleotide polymorphisms, and small indels [≤50 bp]), and English-language publications. Exclusion criteria were non-human studies, structural/non-aneuploid numerical abnormalities, paternal factors, and conference abstracts. Extracted data items included study identifiers, population characteristics, variant details, detection methods, clinical phenotypes, type and origin of aneuploidy, pathogenicity or effect assessment, and gene inclusion in currently commercially available infertility next-generation sequencing (NGS) panels. Rare variants were classified per American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines, whereas common variants were evaluated based on effect estimates and functional validation. Study quality was appraised using a modified Newcastle-Ottawa Scale. Supplementary searches explored associations between the identified genes and a broader range of reproductive phenotypes. OUTCOMES: From 28 studies covering the broad clinical spectrum of aneuploid pregnancies (including embryo arrest, implantation failure, pregnancy loss, hydatidiform mole, and fetal aneuploidy), we identified maternal variants associated with aneuploid conceptions. These were functionally categorized into meiotic recombination, spindle dynamics, checkpoint enforcement, and the maternal-to-zygotic transition. Among them, variants in several genes are supported by higher-quality evidence, including likely pathogenic rare variants in KIF18A, ELL3, and CEP120, as well as common variants in PLK4 and CCDC66. Although some identified genes (HFM1, MCM9, MEI1, BUB1B, NLRP2, NLRP7, and TLE6) are included in commercial infertility NGS panels, their direct association with aneuploidy requires further validation. WIDER IMPLICATIONS: This review proposes that 'aneuploidy predisposition' constitutes a critical, mechanism-driven dimension for the genetic diagnosis of infertility, complementing phenotype-based frameworks. This approach would best serve women with unexplained infertility and a normal karyotype who have either a history of recurrent aneuploidy or heterogeneous reproductive phenotypes across different cycles. Adopting this perspective refines clinical genetic testing paradigms and underscores the need to prioritize artificial intelligence-enhanced clinico-genomic association studies and develop polygenic risk models integrated with clinical factors. PROSPERO REGISTRATION NUMBER: CRD42025636217.

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