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PubMed2026

The Role of Artificial Intelligence Combined With Digital Cholangioscopy for Indeterminant and Malignant Biliary Strictures: A Systematic Review and Meta-analysis.

BACKGROUND: Current endoscopic retrograde cholangiopancreatography (ERCP) and cholangioscopic-based diagnostic sampling for indeterminant biliary strictures remain suboptimal. Artificial intelligence (AI)-based algorithms by means of computer vision in machine learning have been applied to cholangioscopy in an effort to improve diagnostic yield. The aim of this study was to perform a systematic review and meta-analysis to evaluate the diagnostic performance of AI-based diagnostic performance of AI-associated cholangioscopic diagnosis of indeterminant or malignant biliary strictures. METHODS: Individualized searches were developed in accordance with PRISMA and MOOSE guidelines, and meta-analysis according to Cochrane Diagnostic Test Accuracy working group methodology. A bivariate model was used to compute pooled sensitivity and specificity, likelihood ratio, diagnostic odds ratio, and summary receiver operating characteristics curve (SROC). RESULTS: Five studies (n=675 lesions; a total of 2,685,674 cholangioscopic images) were included. All but one study analyzed a deep learning AI-based system using a convoluted neural network (CNN) with an average image processing speed of 30 to 60 frames per second. The pooled sensitivity and specificity were 95% (95% CI: 85-98) and 88% (95% CI: 76-94), with a diagnostic accuracy (SROC) of 97% (95% CI: 95-98). Sensitivity analysis of CNN studies (4 studies, 538 patients) demonstrated a pooled sensitivity, specificity, and accuracy (SROC) of 95% (95% CI: 82-99), 88% (95% CI: 72-95), and 97% (95% CI: 95-98), respectively. CONCLUSIONS: Artificial intelligence-based machine learning of cholangioscopy images appears to be a promising modality for the diagnosis of indeterminant and malignant biliary strictures.

Humans↗

PubMed2026

Diagnostic performance of panfungal PCR on tissue specimens for the diagnosis of invasive fungal diseases: a systematic review and meta-analysis of the Fungal PCR Initiative (FPCRI).

UNLABELLED: Invasive fungal diseases are difficult to diagnose because of the limited sensitivity of culture. Panfungal PCR amplicon sequencing assays (targeting ribosomal RNA, such as 18S, 28S, ITS) are recommended for fungal identification in histopathology samples showing fungal elements. However, data describing its overall performance and consistency are lacking. This systematic literature review and meta-analysis assessed the performance of panfungal PCR on formalin-fixed paraffin-embedded (FFPE) and non-fixed (fresh or frozen) tissue samples. A systematic literature search was performed to include studies reporting the use of panfungal PCR for fungal identification in FFPE or non-fixed tissue samples. PCR sensitivity and specificity were assessed using the reference standard of histopathology showing fungal elements. Quality assessment was performed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Pooled estimates were obtained using random-effects meta-analysis. Twenty-eight studies were included. In FFPE samples (18 studies, 852 samples), sensitivity and specificity were 75.4% (95% confidence interval [CI], 59.2-86.6) and 93.5% (70.2-98.9), respectively. Sensitivity in non-fixed samples (13 studies, 207 samples) was 86.5% (74.7-93.3), while specificity could not be assessed (insufficient data). Comparative analyses showed a significantly higher sensitivity of panfungal PCR over culture (88.2%; 76-94.7 vs 52.2%; 39-65, P = 0.001). Sub-analyses could not demonstrate the superiority of one PCR target over another due to limited data. Panfungal PCR exhibited adequate sensitivity and good specificity in FFPE samples. Sensitivity was even higher in non-fixed samples and largely superior to culture. Nevertheless, large interstudy variability was observed, warranting interlaboratory studies to define the optimal PCR target and standardized protocols. IMPORTANCE: Invasive fungal diseases are difficult to diagnose because of the low sensitivity of culture. Panfungal PCRs are widely used for fungal identification in tissue specimens but suffer from heterogeneous procedures and performance. This meta-analysis shows an acceptable sensitivity (75.4% and 86.5% in fixed and non-fixed samples, respectively) and good specificity (93.5%) of panfungal PCR, supporting its use, not only on histopathology-positive fixed samples but also in non-fixed samples concomitantly with other diagnostic tools (cultures and fungal-specific PCRs if available). These results provide a strong basis for further standardization of panfungal PCR techniques via interlaboratory assays to assess reproducibility and optimize analytical protocols. CLINICAL TRIALS: This study is registered with PROSPERO as CRD42023461148.

Humans↗

PubMed2026

Parent-of-origin effects on allelic expression bias in interspecific poplar hybrids.

In hybrid plants, phenotypic outcomes are governed by interactions between the two parental genomes. However, the mechanisms underlying the interplay of divergent regulatory networks from these genomes remain poorly understood. In this study, we compared gene-level and allele-specific expression patterns, as well as differentially enriched pathways between F₁ and complex backcross (CBC) lines derived from a natural interspecific hybrid population of Populus fremontii (Pf) and P. angustifolia (Pa). Metabolic differences between Pf and Pa which exhibit low and high levels respectively of phenylpropanoid-derived condensed tannins were leveraged. Using individualized transcriptome references, differential expression and clustering analyses revealed CBC-biased and F₁-biased expression for genes involved in phenylpropanoid metabolism and photosynthesis, respectively. Biased expression of these genes at the allele level was also observed in F1. At the whole-transcriptome level, Pa-biased genes predominated in F₁ hybrids, and Pa alleles displayed more conserved expression patterns than Pf alleles across examined samples. Further analyses indicated that allelic expression bias was significantly associated with parental origin, which could be driven by sequence variations in cis-regulatory elements and differences in CpG island length. Our findings demonstrate strong parent-of-origin effects on divergent regulatory networks governing gene expression in poplar hybrids and provide clues for strategic parental selection tailored to specific metabolic pathways of interest.

cis-regulation↗

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

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

Cre-loaded integrase-defective lentiviral vectors for targeted cassette exchange in CHO cells.

Genome-modifying enzymes, such as recombinases and CRISPR-associated nucleases, enable targeted gene insertion when delivered transiently to minimize off-target effects. Precise genome engineering requires controlled enzyme activity, as well as efficient donor DNA transfer. Integrase-defective lentiviral vectors (IDLVs) provide a promising platform for transient episomal DNA transfer; however, their integration efficiency depends on complementary genome-targeting strategies. Here, we engineered Cre-loaded IDLVs (Cre-IDLVs) that co-package lentiviral vector genomes together with bioactive Cre recombinase. Cre was inserted into the Gag region of an integrase-defective gag-pol construct, allowing for efficient encapsidation and protease-mediated release during virion maturation without compromising the viral titer. The resulting particles carried donor cassettes flanked by heterospecific loxP sites. When applied to CHO founder cells harboring compatible genomic loxP landing pads, Cre-IDLVs efficiently mediated recombination-mediated cassette exchange, producing the highest number of G418-resistant colonies among the plasmid ratios tested. Genomic PCR and sequencing confirmed precise locus-specific insertion without detectable random integration in the analyzed clones. These findings establish Cre-IDLVs as a streamlined dual-delivery platform that couples transient recombinase activity with episomal donor DNA transfer. This hybrid lentiviral strategy provides a programmable approach for controlled and site-specific genome modification in mammalian cells.

Integrases↗

PubMed2026

Association of galectin-3 in systemic lupus erythematosus: A systematic review and meta-analysis.

BackgroundSystemic lupus erythematosus (SLE) is an autoimmune condition showing persistent profiling of inflammation and damage of organs and immune system. Amongst many biomarkers for such autoimmune diseases, Galectin-3 (Gal-3) a β-galactoside-binding lectin responsible for regulation, inflammation, and fibrosis of immune repsonses, has engrossed researchers for further investigations as a potential biomarker. However, correlation has been studied between circulating Galectin-3 levels and SLE but outcomes still remain inconsistent. Therefore, this systematic review and meta-analysis evaluated the association between circulating galectin-3 levels and SLE.Materials and MethodsPubMed, Scopus, ScienceDirect, Web of Science, and Embase databases are extensively used for literature search. The last database search was conducted on September 6, 2025. Eligible studies included case control studies reporting circulating galectin-3 levels in individuals with SLE and healthy controls. Two independent reviewers performed study selection and data extraction. Study quality was evaluated using the Newcastle-Ottawa Scale. Comprehensive Meta-Analysis software was used for statistical analysis. Pooled effect sizes were calculated as mean differences with 95% confidence intervals. Heterogeneity was assessed using the Cochrane Q test and I2 statistics, and publication bias was evaluated using Begg's funnel plot and Egger's regression analysis.ResultsSeven eligible studies were included in the meta-analysis. The pooled results showed that patients with SLE had significantly higher circulating Galectin-3 levels than healthy controls (mean difference = 8.48; 95% CI: 3.84-13.12; p < 0.0001). Substantial heterogeneity was observed across studies (Tau square: 32.57, Q = 196.03; p < 0.0001, I2 = 96.93%). Sensitivity analysis confirmed the stability of the overall findings. Begg's funnel plot and Egger's regression analysis indicated no publication bias among studies. Subgroup analysis supports the results of the overall analysis.ConclusionThis meta-analysis depicts that galectin-3 may serve as a biomarker associated with SLE pathogenesis and inflammatory activity due to significantly elevated levels of circulating galectin-3 levels in patients with systemic lupus erythematosus.

Humans↗

PubMed2026

Comparative Effectiveness of Pharmacogenomics for Treatment of Depression.

PURPOSE/BACKGROUND: Pharmacogenomics (PGx), or the use of genetic information to assess drug-gene interactions, is an important step toward precision medicine. It is unclear if clinician use of PGx yields better outcomes for their patients. This study compared the effectiveness of combinatorial PGx-guided plus guideline-informed treatment (PGx+GIT) with guideline-informed treatment (GIT) alone to improve well-being in individuals with major depressive disorder. METHODS/PROCEDURES: Eligible participants (N=201) were randomized to PGx+GIT or GIT alone. PGx was measured with the proprietary GeneSight combinatorial test. PGx+GIT participant clinicians received test results within 2 business days to inform decisions about medication changes. Participants completed the World Health Organization Well-Being Index (WHO-5), Patient Health Questionnaire (PHQ-9), and PROMIS Profile physical functioning and social roles and activity domains every 2 weeks for 2 months and then every 2 months for the remaining 10 months. Monthly medication changes operationalized as necessary clinical adjustments were tracked with the medication recommendation tracking form. FINDINGS/RESULTS: Both groups improved average well-being over the 12-month study period (model-based change in WHO-5 per log (week) [95% CI]: 4.1 [3.3, 5.0] PGx+GIT and 4.8 [4.0, 5.5] GIT). PGx+GIT did not result in superior improvement in well-being (model-based difference [95% CI]: -0.6 [-1.8, 0.5], P =0.270), or any secondary outcomes. The effect of randomized treatment on well-being was not moderated by depression severity, number of previous failed medications for major depressive disorder, or presence of a comorbid condition. IMPLICATIONS/CONCLUSIONS: These data suggest PGx+GIT was not superior to GIT alone, possibly due to a ceiling effect of GIT, or PGx did not yield better results.

Humans↗

PubMed2026

In Vivo Genome Editing Approach to Disrupt Hydroxyacid Oxidase 1 for the Treatment of Primary Hyperoxaluria Type 1.

Primary hyperoxaluria type 1 (PH1) is a rare autosomal recessive disorder that leads to kidney and liver failure. PH1 is caused by a mutation in the alanine glyoxylate aminotransferase (AGXT) gene, which encodes a key metabolic enzyme that converts glyoxylate to glycine in the liver. Inability to metabolize glyoxylate leads to oxalate overproduction, yielding insoluble calcium oxalate crystals; accumulation of these crystals leads to progressive organ failure. Here, we used a novel, minimally disruptive genome-editing approach to disrupt the mechanism of action of hydroxyacid oxidase 1 (HAO1), an upstream enzyme in the glyoxylate metabolic pathway. Successful gene editing and disruption of the HAO1 gene is expected to increase levels of glycolate, a harmless intermediate of the glycine metabolic pathway, thereby preventing the formation of calcium oxalate crystals. We intravenously administered an adeno-associated virus (AAV) vector expressing the M1HAO1 meganuclease to both wild-type and Agxt-/- mice, a mouse model of PH1. We observed >30% editing of HAO1 in Agxt-/- mice, correlating with a dose-dependent increase in serum glycolate levels. At the highest dose tested, urine glycolate levels increased by 79%, with a concomitant 75% decrease in urine oxalate levels. We also evaluated in vivo targeting in rhesus macaques injected with AAV expressing two different versions of the HAO1 meganuclease. Dose-dependent editing of hepatic DNA and RNA was achieved, and serum glycolate levels changed in a manner consistent with successful liver editing; additionally, the treatment was well tolerated. Our results indicate that AAV-delivered meganucleases can effectively target HAO1 in mice and nonhuman primates to achieve high levels of HAO1 gene editing. Moreover, increased glycolate levels in serum indicate that this intervention significantly impacts the HAO1-mediated glycolate-to-glyoxylate pathway. These data suggest that this approach may represent an effective treatment for PH1.

Hyperoxaluria, Primary↗

PubMed2026

Can ChatGPT Replace Human Clinical Coders? A Comparative Study in Otology Billing.

OBJECTIVE: Evaluate the utility of the large language model (LLM), ChatGPT, for the analysis of operative notes and the generation of Current Procedural Terminology (CPT) codes in comparison to human clinical coders. STUDY DESIGN: CPT billing codes assigned by ChatGPT were compared to existing billing data. Otology practice within a tertiary academic center. METHODS: About 191 operative notes from a single surgeon (9/2022-10/2023) were analyzed. ChatGPT-3.5 and 4 models were prompted for CPT codes based on operative notes. Assessment included determining exact and partial match rates, sensitivity and specificity for targeted procedures, and work Relative Value Units (wRVU) differences between ChatGPT-generated and human-assigned codes. RESULTS: ChatGPT-3.5 achieved exact matches in 22% of cases and partial matches in 32%, while ChatGPT-4 achieved 14% exact and 33% partial matches. When cochlear implantation (CI) was excluded, performance dropped significantly. For CI, ChatGPT-3.5 demonstrated a sensitivity of 94% and specificity of 90%, while ChatGPT-4 showed a sensitivity of 96% and specificity of 92%. In contrast, performance on cartilage grafting was poor, with sensitivities of 4.2% for ChatGPT-3.5 and 0% for ChatGPT-4. ChatGPT-3.5 and 4 showed moderate CPT code matching accuracy among themselves, with slight agreement to human coders. Both models tended to underbill for wRVUs compared to human coders, with significant differences in the values generated. CONCLUSION: This study assessed ChatGPT's effectiveness in automating CPT code assignment for otologic surgeries. While the models achieved high sensitivity values for assigning codes related to cochlear implantation, both models struggled with complex cases, failed to apply modifiers, and often assigned fewer wRVUs. The findings highlight ChatGPT's potential in medical billing but indicate a need for further refinement.

Humans↗

PubMed2026

Short-term psychodynamic psychotherapy for functional neurological disorder: A pilot randomized controlled trial.

BACKGROUND: Evidence-based psychotherapeutic treatments for Functional Neurological Disorder (FND) remain limited. This pilot trial evaluated the preliminary efficacy of Short-term Psychodynamic Psychotherapy (STPP) plus Standard Medical Care (SMC) compared with SMC alone in reducing FND symptom frequency. METHODS: Adults with FND were randomized (1:1) to receive either SMC alone or 12 weekly sessions of STPP plus SMC. The primary outcome was symptom frequency (days with symptoms in the last 4 weeks) assessed at the end of treatment (3 months) and at 6-month follow-up. Secondary outcomes included treatment response (≥50% reduction in symptom frequency) and scores on the Hamilton Depression Rating Scale (HAM-D), Hamilton Anxiety Rating Scale (HAM-A), and World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0). RESULTS: Of 91 randomized patients (mean age 38.2 years, 75.8% female), 81.3% completed follow-up. Intention-to-treat analysis using Linear Mixed Models showed that STPP plus SMC significantly reduced symptom frequency compared with SMC alone (estimated mean difference -5.72 [95% CI -8.68 to -2.77]; Cohen's d = 0.77; p < 0.001).Treatment response was achieved by 65.8% in the intervention group versus 16.7% in controls (OR 8.21 [95% CI 2.79-24.19]; p < 0.001; NNT 2.0).Significant improvements were also observed for depression (HAM-D: estimated mean difference -10.80; d = 1.45), anxiety (HAM-A: -7.94; d = 1.06), and disability (WHODAS 2.0: -5.77; d = 0.74), all p < 0.001. CONCLUSIONS: STPP was associated with clinically meaningful improvements in FND symptom frequency and all secondary outcomes, with large effect sizes and high treatment response rates. These findings support the preliminary efficacy of STPP for FND and justify larger, multicenter confirmatory trials.

Humans↗

PubMed2026

A mechanism-guided framework for prioritizing membrane-interaction anti-Vibrio peptides from peptidomics data.

A mechanism-guided framework for prioritizing membrane-interaction antimicrobial peptide candidates from proteomics-derived peptide mixtures is presented. The framework integrates conservative machine-learning-based antimicrobial peptide (AMP) screening with a literature-derived membrane-interaction plausibility (MAP) assessment and a data-driven membrane-interaction ranking function (AIPx), followed by structural visualization for interpretability. MAP encodes physicochemical characteristics commonly associated with peptide-membrane interaction and provides a graded plausibility assessment. Building upon this physicochemically interpretable framework, AIPx ranks peptides using feature weights calibrated from experimentally characterized anti-Vibrio peptides, where minimum inhibitory concentration (MIC) values are used as a coarse-grained ranking reference rather than a direct prediction target. In a peptidomics-based peptide fractionation study targeting Vibrio spp., AIPx exhibited a consistent relationship with experimentally observed antibacterial activity. Distributional analysis revealed that peptide fractions exhibiting high anti-Vibrio activity are characterized by enrichment of high-ranking peptides rather than by AMP abundance alone. By structuring AMP identification and prioritization as sequential stages, the MAP + AIPx framework enables interpretable and experimentally actionable candidate selection by reducing biologically implausible candidates. The framework facilitates species-oriented prioritization of AMP candidates, addressing a key challenge in antimicrobial peptide discovery where activity may depend on target-specific membrane characteristics. Moreover, the approach is extensible through species-specific calibration and supports interpretable, mechanism-informed prioritization in antimicrobial peptide discovery.

Proteomics↗

PubMed2026

MIC-based tuberculosis drug susceptibility testing using Sensititre MYCOTB: a diagnostic accuracy meta-analysis.

Accurate drug susceptibility testing (DST) is crucial for designing effective regimens for multidrug-resistant (MDR) and pre-extensively drug-resistant tuberculosis (pre-XDR TB). Sensititre MYCOTB enables simultaneous determination of minimum inhibitory concentrations (MICs) for multiple drugs, but its diagnostic performance varies across studies. This meta-analysis evaluated the diagnostic performance of Sensititre MYCOTB for key MDR and pre-XDR TB drugs. The protocol was registered in PROSPERO (CRD420251230599). PubMed, Cochrane, Google Scholar, Scopus, ONOS, Web of Science, ScienceDirect, and registries were systematically searched for studies published between 2010 and 2025. Studies comparing the Sensititre MYCOTB with reference DST for Mycobacterium tuberculosis complex (MTBC) were included. Bias assessment and pooled diagnostic accuracy estimates were generated. Fourteen studies, including 1,728 isolates, were analyzed. Rifampicin and isoniazid demonstrated high sensitivity (0.976 [95% CI: 0.94-0.99] and 0.977 [95% CI: 0.95-0.99]) and specificity (0.958 [95% CI: 0.84-0.98] and 0.957 [95% CI: 0.83-0.99], respectively) with low heterogeneity. Amikacin, kanamycin, and ofloxacin demonstrate good diagnostic accuracy, with high specificity (>0.98 [95% CI]). Moderate diagnostic accuracy was observed for ethambutol, streptomycin, ethionamide, and rifabutin. Cycloserine, moxifloxacin, and para-aminosalicylic acid showed inconsistent performance despite excellent specificity (>0.97 [95% CI]). Sensitivity analysis partially improved pooled sensitivity for moxifloxacin 0.801 (95% CI: 0.585-0.924) and para-aminosalicylic acid 0.76 (95% CI: 0.518-0.894), whereas cycloserine remained at 0.436 (95% CI: 0.190-0.725), although heterogeneity persisted. Sensititre MYCOTB DST demonstrates high diagnostic accuracy for MDR-TB and pre-XDR-TB drugs, while caution is required with cycloserine, moxifloxacin, and para-aminosalicylic acid. These findings support the integration of MIC-based testing into clinical decision-making.

Microbial Sensitivity Tests↗

PubMed2026

Exploring the experiences, views, and needs of family members of emergency response workers: a systematic review and meta-synthesis.

Background: Emergency responders, including firefighters, police officers, and paramedics, face workplace challenges that may harm their well-being. They typically rely on family members for support, which may have damaging effects on the family system. While the experiences of emergency responders are well established, their families' subsequent struggles are less well explored.Objective: This review explores the experiences, views, and needs of family members, through determining the mental health and well-being issues that they face, and establishing ways in which family members could be supported.Method: We searched five databases (MEDLINE, Embase, PsychINFO, Scopus, and ProQuest) for qualitative papers exploring experiences of family members of emergency responders. Seventeen studies met the inclusion criteria, and data were meta-synthesized using thematic analysis.Results: Six themes and two subthemes were identified from the meta-synthesis. 'Experiences of emotional strain' reflected worry over safety and coping with volatile moods. 'Increased responsibilities' involved safeguarding emergency responders' well-being and managing household duties, at the expense of family members' own needs. Families felt 'devoted yet invisible', with sacrifices overlooked by both emergency responders and society. 'Impacts on the family dynamic' included relational detachment and frustration. 'Support for emergency responder families' from fellow emergency responder families was valued, but organizational support was limited. 'Media portrayal and societal perceptions' varied, as police families faced hostility, while firefighter and paramedic families garnered respect, particularly during the COVID-19 pandemic.Conclusions: This review highlights that family members play a central role in maintaining the well-being of emergency responders, yet simultaneously face hardships associated with their family member's work and feel undervalued despite their support. This lack of recognition extends to limited professional support. There is a critical need for targeted mental health interventions to support family members, alongside family support measures from emergency responder organizations to assist with the practical difficulties faced by families.

Humans↗

PubMed2026

Webcam-Based Real-Time Visual Feedback During Baduanjin Practice in Older Adults: 6-Week Pilot Randomized Study.

BACKGROUND: Baduanjin qigong is a traditional mind-body exercise used to support balance and physical health in older adults. Age-related changes in proprioception may make accurate self-directed performance difficult without external guidance. OBJECTIVE: The aim of this study is to explore whether webcam-based real-time visual feedback delivered during supervised laboratory sessions was associated with differences in webcam-derived 2D pose discrepancy and movement consistency during Baduanjin practice in older adults. METHODS: A total of 31 older adults were enrolled, and 28 participants with complete analyzable records were included in this complete-case dataset (feedback group, n=14; nonfeedback group, n=14). All sessions were conducted face-to-face in a supervised motion-analysis laboratory. Weekly 2D pose-discrepancy values were analyzed using a linear mixed-effects model with fixed effects for group, categorical week, and the group-by-week interaction and a participant-specific random intercept. Joint- and movement-specific participant-level 6-week means were analyzed exploratorily using Welch independent-samples t tests. Holm correction was applied across 24 exploratory contrasts (6 week-specific, 8 joint-specific, and 10 movement-specific comparisons), and Hedges g and 95% CIs were reported. Participant-specific weekly slopes and within-participant variability were additionally examined to directly assess longitudinal error drift. RESULTS: The linear mixed-effects model showed no significant group-by-week interaction (Wald χ25=1.09; P=.96) and no significant overall week effect (Wald χ25=6.40; P=.27). Averaged across 6 weeks, the feedback group had an estimated mean 2D pose discrepancy 1.20° lower than the nonfeedback group (95% CI -2.38° to -0.02°; P=.046), although this marginal pilot finding was sensitive to an analytic approach. No week-specific contrast remained significant after Holm adjustment. Nominal right elbow, right shoulder, and right knee differences did not survive global Holm correction. Form 3 showed a lower mean discrepancy in the feedback group (mean difference -3.70°, 95% CI -5.86° to -1.54°; Hedges g=-1.30; unadjusted P=.002; Holm-adjusted P=.04). Direct analyses of participant-specific slopes and within-participant SDs did not support a significant between-group difference in longitudinal error drift. CONCLUSIONS: In this small exploratory pilot study conducted under supervised laboratory conditions, the 6-week trajectories did not differ significantly between groups. A marginally lower average 2D pose discrepancy was observed in the feedback group across the 6 weeks, but no individual week- or joint-specific comparison remained significant after multiplicity adjustment. Form 3 was the only exploratory contrast that remained significant after global Holm correction. Direct longitudinal analyses did not demonstrate prevention of error drift. Larger studies using validated reference measurements, prespecified outcomes, and adequately powered longitudinal designs are required.

Humans↗

PubMed2026

Comparison of black carbon measurements using filter-specific reference transmittance to those using lab blanks or an average of unloaded filters.

Filter-based optical techniques compare light transmission intensities between loaded (I) and unloaded (I0) filters as a measure of light-absorbing mass for subsequent estimations of equivalent black carbon (eBC). We analyzed 5,379 15 mm Teflon filters from the Household Air Pollution Intervention Network (HAPIN) trial to assess the influence that different methods of I0 estimations have on eBC measures. We compared eBC measurements using filter-specific I0 values (Method 1) to those using three other methods of I0 estimation: the lab blank scan from a given session (Method 2), the average of all pre-sample filter scans (Method 3), and the average of all lab blank filter scans (Method 4). We assessed the agreement between Method 1 and the alternative methods using Bland-Altman analysis. We also assessed the relationship between Method 1 and the alternative methods across the complete measurement range and after stratifying exposure data into quartiles according to Method 1 eBC exposures. The mean (SD) personal eBC exposure for Method 1 was 7.8 μg/m3 (5.9), and exposures ranged from 1.3 to 46.8 μg/m3. Compared to Method 1, eBC using Methods 2, 3, and 4 were higher by 0.7 μg/m3, 0.1 μg/m3, and 0.7 μg/m3, respectively. The performances of linear regression models between Method 1 and all other methods were moderate to strong (R2 range: 0.42-0.93) in the second, third, and fourth quartiles; however, the models in the first quartile (eBC range: 1.3-2.9 μg/m3) performed poorly (R2 = 0.25-0.26), with error approximately 25% of the mean. Our findings suggest that, in most instances, conventional methods for obtaining I0 values can be used to sufficiently characterize eBC; however, analyzing filters before sampling adds appreciably to the accuracy of eBC estimations in lower concentration settings.Implications: Filter-based optical techniques compare light transmission intensities between loaded (I) and unloaded (I0) filters as a measure of light-absorbing mass for subsequent estimations of equivalent black carbon (eBC). To assess the influence that different methods of I0 estimations have on eBC measures, we analyzed 5,379 15 mm Teflon filters from the Household Air Pollution Intervention Network (HAPIN) trial. Our findings suggest that, in most instances, conventional methods for obtaining I0 values can be used to sufficiently characterize eBC; however, analyzing filters before sampling adds appreciably to the accuracy of eBC estimations in lower concentration settings.

Soot↗

PubMed2026

A systematic approach to standardizing the visual appearance of endometriotic lesions for artificial intelligence recognition.

INTRODUCTION: Numerous studies have shown that the diagnostic performance and reproducibility of visual recognition of endometriosis during laparoscopy are poor. The use of artificial intelligence (AI) seems relevant for exhaustive lesion recognition. Standardization of the visual classification of lesions, in the form of an ontology, is an essential prerequisite to enable medical experts to annotate surgical data consistently and subsequently allow engineers to train and build an artificial intelligence tool for endometriosis recognition. MATERIAL AND METHODS: A systematic search was conducted in the MEDLINE (via PubMed), EMBASE, and the Cochrane Library databases up to May 2022, aiming to identify studies describing the laparoscopic visual appearance of superficial endometriosis, endometriomas, and deep infiltrating endometriosis. The accumulated data in the literature concerning the visual appearance of the different forms of endometriosis were used to create an ontology that could be used for artificial intelligence applications. RESULTS: Out of 932 articles screened, 35 studies were selected based on the inclusion criteria of human subjects with histologically confirmed endometriosis lesions visualized via laparoscopy. The selected studies were reviewed to develop a visual ontology of endometriosis lesions observed via laparoscopy. The lesions were categorized into 4 classes and further subdivided into 11 subclasses: superficial (black, red, white, or subtle), adhesions (dense or filmy), deep (obliteration, retraction, or deformation), and ovarian (endometrioma or chocolate fluid). The positive predictive value (PPV) varied across lesion types: black lesions (PPV 47%-97%), red lesions (PPV 33%-100%), white lesions (PPV 20%-81%), and ovarian endometriosis (PPV 42%-98%). Nonspecific lesions such as adhesions (PPV 16%-50%) and subtle superficial lesions (PPV 0%-67%) presented lower PPVs. Deep endometriosis lesions, often buried within organs, required indirect signs (obliteration, retraction, deformation) for identification. CONCLUSIONS: The visual ontology proposed in this systematic search could facilitate the detection and classification of endometriosis lesions using artificial intelligence. This study highlights the challenges of reaching a consensus on lesion recognition and classification in AI projects due to the diverse visual presentations of endometriosis.

Humans↗

PubMed2026

Effect of Peer Comparison Feedback and Professional Norms on Vitamin D Testing and Generic Medication Prescribing.

BACKGROUND: Organization for Economic Cooperation and Development (OECD) estimates suggest that 20% of health care spending is wasteful or even harmful. Previous interventions have had limited success in discouraging low-value care in medical practice. METHODS: We conducted a nationwide randomized controlled trial among primary care physicians (PCPs) in Switzerland (November 2020-December 2021). We randomly assigned PCPs to one of three intervention groups related to low-value care (vitamin D testing, generic prescribing, or a cost intervention) or a control group. This article reports results for the vitamin D testing and generic prescribing interventions compared with the common control group. PCPs in the intervention groups received a personalized information letter combining professional norms and peer comparison feedback about the low-value service (either vitamin D testing or prescribing of nongeneric medications). Primary endpoints were (1) the number of vitamin D tests per 100 patients and (2) the share of generic medications prescribed. We estimated average treatment effects using linear regression and assessed effect heterogeneity with a causal forest. RESULTS: A total of 618 PCPs were randomly assigned to the vitamin D intervention, 597 to the generic prescribing intervention and 601 to the common control group. The intervention reduced average vitamin D testing by 3.66 tests per 100 patients (95% confidence interval [CI], -5.42 to -1.89; P<0.001). The intervention did not increase average generic medication prescribing (mean difference, +0.57 percentage points; 95% CI, -0.68 to +1.81 percentage points; P=0.37). Heterogeneity analysis suggested that reductions in vitamin D testing among physician subgroups ranged from one to seven per 100 patients and that higher baseline generic prescribing rates were associated with increases in generic substitution following the intervention. No increases in low-value care were seen among those physicians with low baseline levels. CONCLUSIONS: Peer comparison letters emphasizing professional norms reduced vitamin D testing but did not increase generic medication prescribing. (Funded by the Swiss National Science Foundation; AEA Randomized Controlled Trials Registry no., AEARCTR-0004747.).

Humans↗