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PubMed2026

Evaluating the Efficacy of Electronic Screening, Brief Intervention, and Referral to Treatment (e-SBIRT) for Gambling: An Online Pilot Randomised Trial.

OBJECTIVES: To investigate the efficacy of electronic screening, brief intervention, and referral to treatment (e-SBIRT) at improving gambling outcomes and increasing help-seeking. METHODS: We conducted a two-arm, randomised online pilot trial (n = 83) comparing an e-SBIRT intervention with an active control over 12 weeks. The brief intervention was informed by motivational interviewing and incorporated personalised normative feedback, information provision, and relapse-prevention components. Eligible participants were aged 18 or older, resided in the UK and had scores indicating at least moderate severity gambling. RESULTS: Participants (54 [65.1%] male; mean [SD] age = 40.58 [12.75] years, mean [SD] PGSI = 7.16 [5.58]) in the e-SBIRT and control conditions showed improvements in gambling harms (p = 0.033) and perceived ability to control gambling (p = 0.029). No significant effects of condition assignment or condition x time interactions were observed. However, exploratory analyses of individual model coefficients suggested greater improvement in perceived ability to control gambling among participants receiving e-SBIRT at 12 weeks (p = 0.043). Exploratory analyses also suggested higher rates of help-seeking at 12-week follow-up among participants receiving e-SBIRT. CONCLUSION: Overall, e-SBIRT did not demonstrate clear advantages over assessment and information provision alone. Further research should prioritise refining intervention components and evaluating SBIRT approaches in settings that better reflect its opportunistic delivery model.

Humans↗

PubMed2026

The identification of growth-promoting lncRNAs in oral cavity squamous cell carcinoma.

Oral Cavity Squamous Cell Carcinoma (OCSCC) is an aggressive tumor that develops within the mouth of patients. Tumor-suppressor gene loss and genomic arrangements fuel tumorigenesis and transcriptional reprogramming. Understanding how these alterations contribute to OCSCC growth and cell survival may identify new therapeutic vulnerabilities or biomarkers. We profiled the role of long non-coding RNAs (lncRNAs) in the growth of three OCSCC cell lines using a CRISPRi-screen and identified 19 lncRNAs that contribute to OCSCC proliferation. By comparing these lncRNAs to other screens, we find that these lncRNAs are uniquely required in OCSCC and not other malignancies. We show that these lncRNAs are abundantly expressed in OCSCC cells and tumors. Independent testing of candidate lncRNAs confirms their role in supporting OCSCC growth. Our results show that a novel subset of lncRNAs are required for the growth of OCSCC cancer cells and that these lncRNAs are cell lineage specific.

CRISPRi↗

PubMed2026

Systematic multi-domain screening of lead-specific electrocardiographic features associated with sudden cardiac death.

UNLABELLED: Electrocardiogram (ECG) provides four-dimensional view to the electrical properties of the heart. We performed a comprehensive multi-domain screening to find the most significant lead-specific ECG features associated with sudden cardiac death (SCD). METHODS: We analyzed retrospective data from 21,176 consecutive patients undergoing coronary angiography in Tampere University Hospital between 2007 and 2018. 937 ECG variables provided by the 12SL algorithm were used for the analysis. From those, the significant lead-specific ECG variables were categorized into three subgroups: P-wave, QRS complex, and ST-segment/T-wave. The most significant (i.e., lowest P-value) independent lead-specific ECG variables were tested in multivariate analysis after filtering correlating variables with weaker associations with SCD. RESULTS: Among ventricular depolarization (QRS complex) variables, the strongest associations with SCD were observed for QRS intrinsicoid deflection (lead I) (p = 4.6 × 10-8), QRS peak-to-peak amplitude (lead aVR) (p = 1.9 × 10-5), and Q-wave amplitude (lead V1) (p = 7.6 × 10-6). Among repolarization (ST-segment and T-wave) variables, the strongest predictors of SCD were T-wave amplitude (lead aVR) (p = 3.5 × 10-7) and ST-segment end amplitude (lead aVL) (p = 8.1 × 10-5). The strongest associations with SCD among atrial depolarization (P-wave) variables were P-wave onset amplitude (lead V6) (p = 3.1 × 10-6), P'-wave amplitude (lead V2) (p = 2.1 × 10-5), and P-wave duration (lead V2) (p = 2.4 × 10-3). These variables remained significant in multivariate analysis alongside global ECG variables (e.g., heart rate, QRS duration, and LVH). CONCLUSION: Systematic screening and utilizing the full prognostic potential of the 12‑lead ECG reveal several key elements of the electrical properties of the heart that associate with SCD.

Humans↗

PubMed2026

Genetic Screening of Colombian Patients With Early-Onset Parkinson Disease.

BACKGROUND AND OBJECTIVES: Early-onset Parkinson disease (EOPD), defined as symptom onset before 50 years of age, accounts for approximately 10% of patients and is suggested to have a greater genetic component than typical late-onset forms of the disease. Recessive variants in PRKN, PINK1, and DJ-1, are the most common genetic cause of EOPD, however, most studies are in patients of white ancestry. This study aims to analyze genetic variants in PRKN, PINK1, and DJ-1 in Colombian patients to help address the gap in EOPD genetic research of South American populations. METHODS: We analyzed 43 unrelated patients with EOPD using Sanger sequencing for the PRKN, PINK1, and DJ-1 genes and employed multiplex ligation-dependent probe amplification to detect copy number variants. Additionally, long-read whole-genome sequencing was conducted on 3 unresolved patients with age at onset before 30 years of age (long-read sequencing [LRS] patient A-C). RESULTS: We identified known pathogenic single-nucleotide variants and copy number variants in the PRKN gene accounting for 2 patients' disease (4.6% of patients). We observed 2 pathogenic variants in PRKN (c.155delA; p.N52Mfs*29 and c.1083+1G>A) in patient 1, who reported an age at onset of 16 years. We further detected a homozygous duplication of PRKN exons 5-6 in an additional patient, age at onset of 18 years. DISCUSSION: Our study helps characterize genetic contributors to EOPD in Colombian patients, demonstrating genetic forms (PRKN, PINK1, and DJ-1) are rare. Our results highlight a need to include diverse populations in research to improve genetic understanding of disease.

Journal Article↗

PubMed2026

Current Diagnostic Pathways for Rheumatoid Arthritis-Associated Interstitial Lung Disease Result in Substantial Underdiagnosis and Excess Mortality: A Multicenter Norwegian Quality Assurance Audit.

OBJECTIVE: Recent guidelines suggest risk-stratified screening for rheumatoid arthritis-associated interstitial lung disease (RA-ILD). However, the diagnostic gap between current routine care and this screening approach remains unquantified. We assessed currently detected RA-ILD in Norway, benchmarking findings against recent screening-based estimates of the true disease burden. METHODS: This 10-year quality assurance audit across six centers covered 43% of the Norwegian population. RA-ILD cases identified via ICD-10 codes were confirmed by manual chart review. Prevalence was calculated relative to a registry-derived total RA background population and benchmarked against a 10% expected target derived from recent prospective studies. Mortality was compared to a 3:1 frequency-matched RA control group using Cox proportional hazards regression. RESULTS: Among 17,305 RA patients, 188 (1.1%) had verified ILD; when benchmarked against an expected 10% prevalence, this indicates an 89% diagnostic gap in routine clinical care. Mean age at ILD detection was 67.5 years. Most cases (93.6%) possessed ≥2 established risk factors for RA-ILD: 93.6% were seropositive, 76.1% had smoking histories, while RA onset age ≥60 and persistently increased inflammatory laboratory markers were present in over half of patients. RA-ILD was associated with significantly increased mortality; 66 (4.1/100 person-years) deaths occurred in the RA-ILD group vs. 120 (2.3/100 person-years) among RA controls (HR 1.77; 95% CI: 1.31-2.39, p<0.001). CONCLUSION: When comparing to prevalence expectations, current routine care may leave a substantial proportion of cases undetected, primarily capturing a high-risk phenotype with excess mortality. Systematic, risk-stratified screening is needed to bridge this diagnostic gap, aiming to enable earlier intervention.

Interstitial lung disease↗

PubMed2026

Responding to a protracted tuberculosis outbreak: lessons from multiple rounds of investigation in a Chinese boarding school.

PURPOSE: This study analysed a multi-semester pulmonary tuberculosis (PTB) cluster outbreak in a Chinese boarding school to provide evidence for future epidemic control. METHODS: Contacts were screened via symptoms, infection tests and chest radiography. Screening expanded progressively from close contacts to same-floor contacts, then all students and staff. Whole-genome sequencing (WGS) with single nucleotide polymorphism (SNP) and bioinformatics analysis was used for lineage classification, transmission clustering (≤12 SNPs defining a cluster) and drug resistance prediction. RESULTS: From 2020 to 2022, 20 students were diagnosed with PTB, half laboratory-confirmed. Most cases clustered in class 16 and were epidemiologically linked to the primary case (case 0), who had household PTB exposure. Case 0 and case 1 had diagnostic delays exceeding 3 and 6 months, respectively. WGS of five isolates (case 1, 3, 4, 9 and 10) collected over three semesters showed all belonged to lineage 2 and differed by ≤12 SNPs, confirming the same transmission chain. The infection rate in class 16 (46.34%) was significantly higher than other case classes (19.05%) and classes without cases (8.27%) (χ2 = 61.169, p < 0.001). No new cases were detected during a one-year follow-up of students involved in the outbreak after the final round of screening, nor among household contacts of all cases followed up to the present. CONCLUSIONS: Lack of entry health examinations facilitated the outbreak. Delayed diagnosis, incomplete contact screening and absence of preventive treatment led to cross-semester persistence. The infection rate disparity confirms class 16 as the outbreak epicentre. Improving community case management, extending contact follow-up and enhancing cluster outbreak measures are recommended to prevent future outbreaks.

Humans↗

PubMed2026

Effects of faba bean-based crisping culture on phenotypic characteristics, muscle quality, and serum metabolome in Nile tilapia: Screening biomarkers to assess the degree of crisping.

Feeding Nile tilapia (Oreochromis niloticus) a faba bean-based crisping diet enhances muscle hardness (crispness) and overall flesh quality. However, the underlying mechanisms and reliable biomarkers remain insufficiently defined. This study integrated phenotypic traits, muscle texture, collagen content, serum antioxidant enzyme activities (SOD, CAT, and GSH-Px), MDA levels, and serum metabolomics to understand the determinants of muscle crisping. Fish were assigned to a crisping diet or a control group for 90 days. Individuals in the crisping group were implanted with passive integrated transponder (PIT) tags to enable correlation analyses among phenotypic traits (body weight/length/frame changes), serum indicators (NAM, FAD, and GSH-Px) and muscle hardness. Compared with controls, the crisping diet significantly increased muscle hardness, gumminess, and chewiness, accompanied by elevated collagen content. Antioxidant profiles were altered, with higher activities of serum SOD and CAT, together with elevated MDA levels and reduced GSH-Px activity (P < 0.05). Metabolomic analysis identified 830 differential metabolites (682 upregulated and 148 downregulated), predominantly comprising carboxylic acids and derivatives, glycerophospholipids, and benzene derivatives. Enrichment analysis indicated significant involvement in general metabolic pathways, ATP-binding cassette (ABC) transporters, amino acid biosynthesis, and glycine, serine, and threonine metabolism (P < 0.05). Notably, acetylpyruvate was upregulated in glutathione metabolism, nicotinate and nicotinamide metabolism, and galactose metabolism; pantothenic acid was upregulated in glycine, serine, and threonine metabolism; whereas δ-tocotrienol was downregulated. Correlation analysis revealed weak negative associations between muscle hardness and phenotypic traits (body weight/length/frame changes D5-7, D5-10, D7-8) (P < 0.05). In contrast, serum NAM and FAD were weakly positively correlated with muscle hardness, whereas GSH-Px showed a weak negative correlation (P < 0.05). Collectively, these findings suggest that body weight, body length, frame measurements (D5-7, D5-10, and D7-8), and serum NAM, FAD, and GSH-Px are associated with the degree of muscle crispness in Nile tilapia fed a faba bean-based crisping diet and may serve as candidate biomarkers under these culture conditions.

Animals↗

PubMed2026

Exploring the mechanism of aroma production in fermented cherry juice by L. brevis LD1.0600 using flavomics and whole genome analysis.

This study focused on L.brevis LD1.0600 with excellent fermentation traits: it analyzed genome-wide key regulatory genes for micro-metabolites, combined with fermented cherry juice flavor metabolomics data, and used machine learning to explore correlations between gene regulation, metabolite production, and flavor formation. The SVM model screened and verified fermented cherry juice VOCs; through OAV and flavor wheel analysis, LD1.0600 emerged as the top-performing strain, with a sweet, fruity dominant aroma. Key aroma-active components (OAV > 100) included 2-methoxy-4-vinylphenol, benzaldehyde, 2-methyl-butanoic acid and hexanoic acid, and 2-methoxy-4-vinylphenol and hexanoic acid elevated by LD1.0600-regulated genes (Chrom1-001884, Chrom1-000925, fabF and Chrom1-000199). At the same time, through research, a "strain screening-SVM screening of DVCs-OAV screening of key aroma components-whole genome sequencing of flavor regulatory genes" system was established. This system can not only be applied to the screen fermentation strains, but also can be extended to the application of other fermentation products.

Fermentation↗

PubMed2026

Assessment of atypical glandular cell interpretation in Pap tests using the Hologic Genius Digital Diagnostics System.

Atypical glandular cells (AGC) are a diagnostic challenge. The aim of this study was to evaluate the efficacy and diagnostic performance of AGC detection on the Hologic Genius Digital Diagnostics System (HGDDS). A retrospective analysis of 451 ThinPrep Pap cases was conducted, including 207 cases of AGC, 27 cases of high-grade squamous intraepithelial lesion (HSIL), 25 cases of low-grade squamous intraepithelial lesion (LSIL), and 192 benign cases. All AGC cases had follow-up histologic diagnoses, with 66 cases subsequently diagnosed as adenocarcinoma. The slides were randomized, scanned, and analyzed by the HGDDS. Patient age and HPV test results were provided to reviewers, an experienced cytologist, who screened the cases, followed by two cytopathologists who independently examined the cases on the HGDDS. Diagnostic concordance between the two cytopathologists indicated strong agreement (κ = 0.829). Sensitivity of AGC on Papanicolaou (Pap) tests for adenocarcinoma detection on HGDDS was 98.5% and 95.5%, respectively, comparable to the original ThinPrep interpretation (OTPI). Specificity for adenocarcinoma detection was significantly higher (84.6% and 85.6%) with the HGDDS than 27.7% with OTPI. Overall, the diagnostic performance for AGC/HSIL interpretation to detect CIN2/3/adenocarcinoma appeared to have improved with HGDDS compared with OTPI, particularly for specificity and positive predictive value (PPV). This is the first study evaluating AGC diagnosis using the HGDDS. The findings demonstrate that the sensitivity of adenocarcinoma detection as AGC on HGDDS is comparable to the ThinPrep Imaging System, but the specificity and PPV are improved. This suggests the potential of artificial intelligence to augment the performance of cervical cancer screening.

Humans↗

PubMed2026

Innovations in microbial physical mutagenesis for food fermentation: An overview from traditional to emerging technologies.

Microbial strains serve as an important factor affecting fermentation efficiency and product quality. To obtain superior strains, mutation breeding is a classic strategy. Compared to chemical mutagenesis, physical mutagenesis directly induces genomic changes, providing notable advantages such as the elimination of chemical residues and environmental sustainability, hence rendering it a favored method for enhancing food-grade microorganisms. Conventional physical mutagenesis mostly depends on UV, rays, high pressure, or space radiation. As physical technologies advance, emerging methods such as ion implantation, plasma, microwave, ultrasound, and pulsed light are widely utilized for genetic modification. Mutagenesis technologies are progressively transitioning from single-effect to multi-effect synergy. Recent evaluations indicate that emerging technologies can enhance microbial mutation efficiency at the application level relative to established technologies. Nonetheless, the systematic clarification and comparative analysis at the mechanistic level remain inadequate, hindering intuitive comprehension of the qualities and distinctions across techniques. Furthermore, physical mutagenesis encounters several significant obstacles, such as cellular damage, limited rates of advantageous mutations, and laborious screening processes. This review carefully elucidates the mechanisms and properties of physical mutagenesis technology and delineates the distinctions among approaches through comparative analysis. Simultaneously, solutions for optimizing mutagenesis are presented to tackle the principal challenges mentioned above. This review aims to offer a theoretical foundation and practical guidance for the enhanced application of physical mutagenesis technologies in microbial breeding.

Mutagenesis↗

PubMed2026

Nutrition and Diet-Related Training and Curriculum in the US Predoctoral Dental Programs.

PURPOSE: Nutrition and diet are vital for oral and systemic health. It is unclear how well US predoctoral dental programs prepare students in nutrition screening and counseling. This study analyzed US dental school curricula on these topics. METHODS: A cross-sectional online survey was sent to the publicly available email addresses of 67 of 72 academic dental deans at US Commission on Dental Accreditation-accredited dental schools. Items assessed availability, modes and hours of instruction, curricular topics, clinical integration, and instructors. Descriptive statistics summarized responses. RESULTS: A total of 21 academic deans responded, for an overall response rate of 29%. Most (85%) of responding academic dental deans reported that nutrition and diet education was mandatory, with none treating it as optional. Of these schools, 83% offered both classroom and clinical training, while 17% provided only didactic teaching. Didactic hours varied; 42% reported 10 or fewer hours. Foundational nutrition topics were common, although dietary guidelines such as MyPlate were reported less often (66%). Oral health-related nutrition content was broadly covered, with all respondents reporting instruction related to caries, erosion, periodontal disease, and oral dysfunction. Counseling content was less consistent, particularly public health nutrition (67%) and the impact of oral dysfunction on diet and nutrition (72%). CONCLUSION(S): Most responding academic dental deans report including nutrition and diet education in their curricula. However, it remains uncertain whether these topics are incorporated at schools that did not participate in the survey. Variability in curricular time, counseling, and teaching highlights the need for clearer competencies and more clinical training. Improving this could better prepare future dentists for common dietary risks affecting oral and systemic health.

dental caries↗

PubMed2026

Age at menopause and subjective cognitive symptoms predict digital cognitive outcomes at the gynecological Well-Woman visit.

INTRODUCTION: Women are at increased risk for Alzheimer's Disease (AD). Growing evidence suggests that the menopausal transition may represent a vulnerable window for development of AD-related pathology. Yet, women are diagnosed with AD later than men. Conducting routine cognitive screenings and integrating information about both cognitive symptoms and age at menopause may help address sex-based disparities in detection and prevention. This study investigated whether subjective cognitive symptoms, in combination with age at menopause, were associated with performance on a digital cognitive task in postmenopausal women. METHODS: 183 postmenopausal women (mean age = 63.8, range = 45-85) were recruited after their Well-Woman visit. Participants completed the Screener for Cognitive Problems in Everyday Life (SCoPE) to assess subjective cognitive symptoms, followed by a sensitive measure of objective cognition: the Linus Health Digital Clock and Recall (DCR™). Information was also collected on age at menopause. We examined associations of subjective cognitive symptoms and age at menopause with digital cognitive performance, adjusting for age, education and depression. Model fit was evaluated using adjusted R2, AIC, and BIC. RESULTS: 48.1% of women reported one or more cognitive symptoms on the SCoPE. On objective testing, 73.2% scored in the normal range, 20.8% in the borderline range, and 6.0% in the impaired range. SCoPE total score was negatively associated with objective cognitive performance in adjusted models (B = -.12, p = .03). Age at menopause showed a significant quadratic association with cognitive performance (B = -0.006, p<.001). SCoPE total was not associated with DCR subtests, while age at menopause predicted both Delayed Recall and Clock Drawing. CONCLUSION: Subjective cognitive symptoms and age at menopause were associated with lower performance on a sensitive, objective cognitive test. Findings support routine cognitive screening and suggest that subjective cognitive symptoms as well as age at menopause are associated with cognitive function.

Humans↗

PubMed2026

Photon-counting detector computed tomography (PCD-CT) in multiple myeloma: a systematic review and trial sequential meta-analysis on image quality and radiation dose.

OBJECTIVES: To systematically review and perform a meta-analysis comparing the effects of PCD-CT versus EID-CT on image quality (sharpness) and radiation dose (CTDIvol) in patients with bone lesions due to multiple myeloma (MM). METHODS: A comprehensive search of PubMed, Embase, Scopus, and Cochrane Central was conducted from inception to October 2025. Studies comparing PCD-CT and EID-CT in MM patients were included. Methodological quality was assessed using ROBINS-I, and the certainty of evidence was assessed using GRADE. RESULTS: A total of 41 studies were identified that matched our search criteria. After duplicate removal and screening, five studies (n = 170 patients) were included in the systematic review, with four contributing to the meta-analysis. PCD-CT showed a significant pooled mean difference in image sharpness (mean difference, + 0.99 points; 95% CI, 0.62-1.37; p < 0.001). PCD-CT also demonstrated a reduction in radiation dose (mean difference, -4.95 milligrays; 95% CI, -8.39 to -1.50; p = 0.005). Trial sequential analysis (TSA) confirmed stability of pooled estimates, with conclusive evidence for image sharpness improvement, and suggestive yet incomplete evidence for radiation dose reduction. CONCLUSION: Compared to EID-CT in MM, PCD-CT significantly improves subjective image sharpness as supported by trial sequential analysis. Conventional meta-analysis suggested a reduction in radiation dose with PCD-CT; however, trial sequential analysis indicated that the cumulative evidence remains inconclusive. Further large-scale studies are suggested to confirm the magnitude of the radiation dose reduction benefit.

Humans↗

PubMed2026

Identifying and Prioritizing Core Components of Relationship Education Programs: a Case Study of an Artificial Intelligence (AI) Assisted Systematic Review.

The field of prevention science seeks to identify and implement effective strategies to address social, emotional, and health challenges. A critical aspect of this endeavor is determining the core components of prevention programs that drive positive outcomes. This article presents a case study utilizing artificial intelligence (AI)-assisted systematic review methods to identify key components of healthy marriage and relationship education programs. Given the growing body of research in this domain, AI tools offer a promising means to enhance the efficiency and accuracy of literature reviews. This study employed AI to screen, code, and validate research articles, demonstrating its effectiveness in expediting systematic reviews while maintaining high accuracy in inclusion screening. This case study involved a systematic review of 22,028 resources (identified from PsycINFO, Academic Search Ultimate, and Google) and a final data set of 268 relevant studies. AI screening was integral in effectively conducting multiple rounds of screening. However, findings also highlight challenges in AI-assisted qualitative data abstraction, underscoring the continued need for human expertise in complex coding tasks. The study contributes to the ongoing discourse on integrating AI into prevention science methodologies and offers insights for optimizing AI applications in systematic reviews.

Artificial Intelligence↗

PubMed2026

Identification Matters: How Data Sharing Affects Pupil Honesty and Engagement in Universal School Well-Being Assessments.

PURPOSE: Universal well-being assessments in schools may support early identification of pupils needing mental health support. However, little is known about how privacy and confidentiality concerns influence pupils' acceptability of assessments and willingness to engage authentically. This study examined how hypothetical identification, where responses are linked to pupils and shared with key stakeholders, affects pupils' anticipated honesty and engagement, and whether known help-seeking barriers predict negative responses. METHODS: Cross-sectional data were collected from 12,377 primary (ages 8-10) and secondary pupils (ages 11-17) across 55 schools in England. Pupils reported whether their responses would change if identifiable and shared with school staff, parents/guardians, or external professionals. Responses indicating reduced honesty or likelihood of disengagement were coded as negative. Predictors were examined using mixed-effects logistic regression models, including demographics, school connectedness, and mental well-being. RESULTS: Identification and data sharing influenced pupils' anticipated engagement, particularly in secondary schools. Identification by school staff elicited the highest proportion of negative responses in both phases, whereas external professionals elicited the fewest. Most primary pupils reported they would respond authentically, while a larger proportion of secondary pupils indicated they would respond less honestly or disengage when responses were identifiable and shared. Across primary and secondary samples, low well-being, low school connectedness, and being female were associated with greater likelihood of negative response. DISCUSSION: Pupils' anticipated engagement with well-being assessments is shaped by who accesses their data, with marked developmental differences. Strengthening trust, privacy, and connectedness, and supporting pupils' autonomy, may improve the acceptability and response accuracy.

Humans↗

PubMed2026

Assessing perinatal depression identifying abilities among maternal and child health workers in rural China using smartphone-based virtual patients: a multi-center cross-sectional study.

OBJECTIVE: To assess rural maternal and child health (MCH) workers' virtual patients (VPs)-assessed performance in identifying perinatal depression (PND) using smartphone-based VPs, and to identify factors associated with this performance in rural Hunan, China. METHODS: A multicentre cross-sectional study was conducted in Hunan Province, China. A standardized questionnaire collected demographic and work-related characteristics of rural MCH workers. Smartphone-based VPs were used to assess PND identification performance in a simulated clinical scenario. An overall score ≥60 was used as a prespecified operational benchmark across consultation, ancillary assessment, diagnosis, management, and health education domains. Data were analyzed using SPSS 26.0. RESULTS: A total of 375 rural MCH workers participated, yielding an effective response rate of 90.4%. Only 25.9% met the prespecified operational benchmark for VP-assessed PND identification performance. The mean accuracy scores for consultation, ancillary assessment, diagnosis, management, and health education were 94%, 48%, 64%, 58%, and 74%, respectively. Complete consultation accuracy was higher among MCH workers from township health centers than among those from county-level MCH hospitals. MCH workers aged 18-39 years showed higher odds of complete diagnostic accuracy for PND than those aged ≥40 years. CONCLUSIONS: Smartphone-based VP assessment was feasible in rural MCH settings and revealed suboptimal PND identification performance. Mobile VPs may help identify frontline performance gaps and inform targeted training, but further validation against real-world clinical performance, or standardized patient encounters is needed before large-scale implementation. These findings may support targeted capacity-building for rural MCH workers and more equitable perinatal mental health care.

Humans↗

PubMed2026

Mining Stored-Specimen Studies for Information about Cancer Natural History.

The advent of new multicancer early detection tests and publication of early diagnostic results have generated expectations of clinical benefit from multicancer screening. The clinical benefit of a cancer screening test depends critically on disease natural history, which is typically learned from prospective screening studies. Retrospective studies of stored blood specimens are important in learning about a test's preclinical diagnostic performance but have rarely been used to infer natural history. The extent to which these studies might be harnessed to also learn natural history is discussed in the context of an article in this issue that infers the combined natural history of a range of cancers targeted by a multicancer early detection test using a case-control subsample of specimens from a large cohort study. The critical question concerns the identifiability of key transition rates in multistate models of natural history alongside state-specific sensitivities. The article suggests that these parameters are estimable within a Bayesian framework that leverages prior information about test sensitivity from diagnostic studies. We offer a heuristic discussion of identifiability in this setting and encourage formal study to determine the extent to which models with varying degrees of complexity may be learned from stored-specimen studies. See related article by Dai et al., p. 1535.

Humans↗

PubMed2025

Artificial Intelligence in Diagnosing Depression Through Behavioural Cues: A Diagnostic Accuracy Systematic Review and Meta-Analysis.

AIM: To synthesise existing evidence concerning the application of AI methods in detecting depression through behavioural cues among adults in healthcare and community settings. DESIGN: This is a diagnostic accuracy systematic review. METHODS: This review included studies examining different AI methods in detecting depression among adults. Two independent reviewers screened, appraised and extracted data. Data were analysed by meta-analysis, narrative synthesis and subgroup analysis. DATA SOURCES: Published studies and grey literature were sought in 11 electronic databases. Hand search was conducted on reference lists and two journals. RESULTS: In total, 30 studies were included in this review. Twenty of which demonstrated that AI models had the potential to detect depression. Speech and facial expression showed better sensitivity, reflecting the ability to detect people with depression. Text and movement had better specificity, indicating the ability to rule out non-depressed individuals. Heterogeneity was initially high. Less heterogeneity was observed within each modality subgroup. CONCLUSIONS: This is the first systematic review examining AI models in detecting depression using all four behavioural cues: speech, texts, movement and facial expressions. IMPLICATIONS: A collaborative effort among healthcare professionals can be initiated to develop an AI-assisted depression detection system in general healthcare or community settings. IMPACT: It is challenging for general healthcare professionals to detect depressive symptoms among people in non-psychiatric settings. Our findings suggested the need for objective screening tools, such as an AI-assisted system, for screening depression. Therefore, people could receive accurate diagnosis and proper treatments for depression. REPORTING METHOD: This review followed the PRISMA checklist. PATIENTS OR PUBLIC CONTRIBUTION: No patients or public contribution.

Humans↗