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PubMed2026

Evaluation of three Aspergillus antibody assays for screening of chronic pulmonary aspergillosis: prospective diagnostic accuracy study.

OBJECTIVES: Chronic pulmonary aspergillosis (CPA) is a frequent complication of pulmonary tuberculosis (PTB), particularly in high-burden settings where access to reliable serological diagnostics remains limited. We evaluated the diagnostic performance of two immunochromatographic technology (ICT) lateral flow assays (LFAs) and an ELISA for CPA screening among patients with active or previously treated PTB. METHODS: In this two-year prospective multicentre diagnostic evaluation, serum from adults with prior or active PTB was tested using the Era Biology Aspergillus IgG ICT LFA, LDBio Aspergillus IgG/IgM ICT LFA, and Bordier Aspergillus fumigatus IgG ELISA. CPA diagnosis was established using a consensus composite reference standard incorporating clinical, immunological, radiological, and microbiological criteria. The Bordier ELISA was used as part of the immunological component of the consensus CPA diagnosis, with a cutoff optical density of ≥1.0. Diagnostic accuracy, agreement statistics, receiver operating characteristic analysis, and latent class analysis (LCA) were performed. RESULTS: Among 340 participants, 24 (7.06%) had CPA. Proportion of participants with positive antibody tests among all tested individuals were 6.76% for LDBio ICT LFA, 20.0% for Era Biology ICT LFA, and 11.47% for Bordier ELISA. Against consensus CPA diagnosis, Bordier ELISA showed 87.50% sensitivity and 94.30% specificity, LDBio ICT LFA 58.33% sensitivity and 97.15% specificity, and Era Biology LFA 66.67% sensitivity and 83.54% specificity. LCA estimated CPA prevalence at 7.72%. LCA-derived sensitivities and specificities were 86.58% and 99.92% for LDBio ICT LFA, 83.39% and 85.31% for Era Biology LFA, and 79.10% and 94.19% for Bordier ELISA. CONCLUSIONS: The Bordier ELISA showed high sensitivity and specificity, while the LDBio ICT LFA demonstrated very high specificity with strong LCA-derived performance. These findings support the use of ELISA for laboratory diagnosis and ICT as a point-of-care screening tool for CPA in resource-limited settings. Era Biology Aspergillus IgG LFA demonstrated moderate sensitivity and acceptable diagnostic performance, indicating its potential utility as a supplementary screening assay for CPA in settings where rapid, point-of-care testing is required.

Humans↗
PubMed2026

Source- and Solubility-specific Choline, Gut Microbiota, and Dyslipidemia Risk: Trimethylamine N-oxide-associated and Non-trimethylamine N-oxide-Associated Patterns in a Prospective Cohort Study.

BACKGROUND: Dietary choline, a major precursor of the gut microbial metabolite trimethylamine N-oxide (TMAO), is implicated in dyslipidemia risk; however, source- and form-specific associations and interactions with gut microbiota remain unclear. OBJECTIVES: The aim of this study was to examine longitudinal associations of source- and form-specific dietary choline with plasma TMAO and dyslipidemia and to identify gut microbiota interactions. METHODS: Using data from the China Health and Nutrition Survey (2018-2023), dietary intake was assessed via 3 consecutive 24-h recalls in this prospective cohort study. Two-level generalized linear mixed-effects models were applied in 4828 adults (mean age: 55.9 ± 12.6 y, 56.6% females) to assess choline-dyslipidemia associations. Choline-TMAO and TMAO-dyslipidemia analyses were conducted in 1091 participants free of dyslipidemia at baseline. Among 7169 adults with gut microbiome data, Least Absolute Selection and Shrinkage Operator and logistic regression identified lipid-associated gut genera; TMAO relationships were examined in a subset of 693 participants. RESULTS: Higher intakes of total [Q4 compared with Q1: odds ratio (OR) = 1.261; 95% confidence interval (CI): 1.007, 1.580], red meat-derived (OR: 1.753; 95% CI: 1.196, 2.568), and lipid-soluble choline (OR: 1.304; 95% CI: 1.047, 1.624) were associated with higher risk of elevated low-density lipoprotein cholesterol (LDL cholesterol), whereas vegetable-derived choline was inversely associated. Egg-derived and lipid-soluble choline were positively associated with plasma TMAO, which was prospectively associated with 5-y incident dyslipidemia (Q4 compared with Q1-OR: 1.620; 95% CI: 1.047, 2.509), elevated LDL cholesterol (Q3 compared with Q1-OR: 2.478; 95% CI: 1.187, 5.174), and hypertriglyceridemia (Q4 compared with Q1-OR: 1.829; 95% CI: 1.028, 3.225). Three TMAO-associated genera were identified: Lachnospiraceae and Phascolarctobacterium as pro-risk taxa and Turicibacter as protective. The adverse LDLcholesterol association of egg-derived choline was observed exclusively in Phascolarctobacterium-enriched individuals. CONCLUSIONS: Dietary choline source and solubility differentially associated with dyslipidemia risk through TMAO-associated and non-TMAO-associated patterns, with gut microbiota as key modulators.

Humans↗
PubMed2026

Exposure to size-specific particulate matter accelerates DNA methylation aging in people with HIV.

BACKGROUND: People with HIV (PWH) face accelerated aging and increased health risks, with DNA methylation age (DNAmAge) as a critical senescence biomarker. Particulate matter is linked to DNAmAge acceleration (DNAmAA) in general population, but its impact in PWH remains unstudied. METHODS: Thirty-two PWH from Wuhan, China, were enrolled in a prospective panel study with follow-up, and each participant underwent at least two repeated measurements during the study period. Portable air quality monitor measured PM 1 , PM 2.5 , and PM 10 exposures 72 h preblood sampling. We analyzed genome-wide DNA methylation in peripheral blood and calculated six AA metrics. Linear mixed-effects and weighted quantile sum regression models evaluated associations between particulate matter exposure and DNAmAA. RESULTS: Significant associations between particulate matter exposure and DNAmAA were observed at various lag windows. For every 10 μg/m 3 increase in 24-h average PM 2.5 , Hannum DNAmAA, Pheno DNAmAA, Grim DNAmAA, SkinBlood DNAmAA, and Elastic DNAmAA increased by 0.266 years [95% confidence interval (CI): 0.035-0.480], 0.421 years (95% CI: 0.032-0.701), 0.336 years (95% CI: 0.073-0.546), 0.295 years (95% CI: 0.021-0.495), and 0.254 years (95% CI: 0.034-0.445), respectively. PM 10 contributed most substantially to the cumulative PM effect on epigenetic AA in the lag0-24 h window. CONCLUSION: Short-term particulate matter exposure, particularly PM 10 , significantly accelerates epigenetic aging in PWH, highlighting the need to integrate air quality management into healthy aging strategies for this vulnerable population.

China↗
PubMed2026

Fatty acids and breast cancer: Epidemiology, subtype-specific metabolism, immune regulation, and clinical translation.

Fatty acids (FAs) are bioactive dietary and metabolic molecules that participate in membrane architecture, energy homeostasis, inflammatory signaling, gene regulation and immune function, all of which intersect with breast cancer (BC) risk, progression and treatment response. In this narrative review we integrate epidemiological, clinical, translational and mechanistic evidence on the role of FAs in BC. Saturated, monounsaturated, trans- and polyunsaturated FAs (PUFAs) are treated as distinct biological exposures rather than interchangeable measures of total fat intake. Similarly, evidence from dietary assessment, circulating biomarkers, erythrocyte membrane composition, adipose tissue stores and tumor lipid signatures is interpreted separately, because each captures exposure and biology at a different level. BC subtypes differ in FA synthesis, uptake, oxidation, storage and remodeling: luminal tumors are frequently linked to hormone-regulated lipogenesis, human epidermal growth factor receptor 2 (HER2)-positive tumors to growth-factor-driven lipid metabolism, and triple-negative tumors to exogenous FA uptake, inflammatory lipid mediators and ferroptosis-related vulnerabilities. FA-derived mediators also shape immune-cell polarization, cytokine signaling and the tumor microenvironment, and dietary FAs may reshape the gut microbiota; the fiber-derived short-chain FAs it produces, distinct from dietary FAs, likewise help regulate immune and inflammatory tone. Clinical data suggest possible roles for fat-quality modification and selected n-3 PUFA interventions, but findings are heterogeneous and not yet sufficient to support routine biomarker-guided precision onco-nutrition. Candidate biomarkers, such as erythrocyte n-6:n-3 composition, require prospective validation before clinical implementation. FA biology thus represents a modifiable but complex axis in BC prevention, tumor biology and supportive care.

Humans↗
PubMed2026

Diagnostic accuracy of bronchoalveolar lavage fluid-based testing for pulmonary cryptococcosis: A systematic review and meta-analysis.

BACKGROUND: Pulmonary cryptococcosis(PC) presents diagnostic challenges because of its non-specific clinical and radiological manifestations. Bronchoalveolar lavage fluid (BALF)-based testing, which includes latex agglutination (LA) and lateral flow assay (LFA), offers a minimally invasive diagnostic method, yet its pooled diagnostic accuracy remains unclear. METHODS: We systematically searched PubMed, Embase, Cochrane Library, and Scopus from inception to May 2026. Studies evaluating BALF-based testing for PC with extractable 2 × 2 data were included. The methodological quality of relevant studies was assessed by the QUADAS-2 tool. Pooled sensitivity, specificity, likelihood ratios, and diagnostic odds ratio (DOR) were estimated using a bivariate random-effects model. Subgroup analyses were performed by testing method and reference standard type. Heterogeneity was evaluated through paired forest plots, HSROC visualization, and exploratory bivariate meta-regression. RESULTS: The pooled sensitivity was 0.87 (95% CI: 0.81-0.91), and the specificity was 0.99 (95% CI: 0.982 - 0.995). The pooled positive likelihood ratio (PLR) was 88.00 (95% CI: 47.39 - 163.42), the negative likelihood ratio (NLR) was 0.13 (95% CI: 0.09 -0.20), and the DOR was 658.50 (95% CI: 285.36-1519.55). No significant threshold effect or publication bias was detected. Exploratory meta-regression suggested a possible assay-method effect in the joint model (P = 0.03), mainly driven by specificity (P = 0.01). CONCLUSIONS: The study demonstrates the high accuracy of CrAg in BALF for the diagnosis of pulmonary cryptococcosis, supporting its role as an important adjunctive diagnostic tool, particularly when tissue biopsy is not feasible or rapid results are needed. Larger prospective studies with standardized protocols are needed to validate these estimates.

Humans↗
PubMed2026

Diagnostic and prognostic value of fibroblast growth factor 23 in acute kidney injury: systematic review and meta-analysis.

Background: Acute kidney injury (AKI) is associated with high mortality and adverse outcomes. Fibroblast growth factor 23 (FGF23) has emerged as a potential biomarker for AKI; however, its diagnostic and prognostic utility remains inconsistent.Methods: We conducted a systematic review and meta-analysis of studies evaluating circulating intact FGF23 (iFGF23) or C-terminal FGF23 (cFGF23) (PROSPERO: CRD42022302659). PubMed, EMBASE, CNKI, and Wanfang databases were searched through June 9, 2026. QUADAS-2 was used for quality assessment. A random-effects bivariate model pooled sensitivity, specificity, positive/negative likelihood ratio (PLR/NLR), diagnostic odds ratio (DOR), and area under the summary receiver operating characteristic curve (SROC AUC).Results: Twenty-three studies were included: 17 diagnostic, 6 prognostic (one addressing both). For AKI diagnosis, the pooled sensitivity was 0.79 (95% CI 0.73-0.86), specificity 0.82 (95% CI 0.75-0.89), PLR 4.40 (95% CI 2.59-6.21), NLR 0.25 (95% CI 0.16-0.34), DOR 17.49 (95% CI 8.67-35.16), and SROC AUC 0.87 (95% CI 0.81-0.92). Substantial heterogeneity was observed (I2 = 67%), with iFGF23 demonstrating higher accuracy than cFGF23 (AUC 0.91 vs 0.81). For AKI mortality, pooled sensitivity was 0.77 (95% CI 0.69-0.84), specificity 0.76 (95% CI 0.70-0.82), DOR 10.89 (95% CI 6.86-17.30), and SROC AUC 0.77 (95% CI 0.70-0.83). Significant heterogeneity was noted (I2 = 86.2% for sensitivity, 80.4% for specificity). No significant publication bias was detected.Conclusions: Circulating FGF23 exhibits moderate-to-high diagnostic and moderate prognostic performance in AKI, though interpretation is limited by substantial heterogeneity. It may serve as a complementary biomarker for risk stratification, pending further validation with standardized protocols.

Humans↗
PubMed2026

Developmental roles of LSD1/KDM1A-like (LDL) proteins in plants.

LYSINE-SPECIFIC DEMETHYLASE 1-like (LDL) proteins are conserved FAD-dependent amine oxidases that serve as pivotal regulators in plants. While animal systems typically rely on a single LSD1/KDM1A enzyme, the Arabidopsis thaliana genome encodes an expanded family of LDL homologues (FLD, LDL1, LDL2, and LDL3), resulting in substantial subfunctionalization and specialized recruitment mechanisms. This review explores the diverse developmental roles of plant LDLs, ranging from flowering time and circadian clock regulation to heterochromatin maintenance and epigenetic regulation. We discuss the redundant roles of FLD, LDL1, and LDL2 in repressing the floral repressor FLC and their nonredundant specialized function within the CCA1/LHY-TOC1 circadian feedback loop. A central focus of our review is the emerging mechanism of transcription-coupled demethylation, in which LDLs associate with the phosphorylated C-terminal domain of RNA polymerase II to modify chromatin cotranscriptionally within gene bodies. By integrating findings from Arabidopsis thaliana and crops such as tomato and soybean, we illustrate how the diversified LDL-mediated regulatory toolkit facilitates precise, gene-specific regulation. Ultimately, the LDL family represents a cornerstone of the sophisticated epigenetic strategies that regulate plant phenotypic plasticity in response to developmental and environmental cues.

Circadian clock↗
PubMed2026

Diagnostic performance of machine learning models versus established risk stratification for intracranial aneurysm rupture: a systematic review and bivariate meta-analysis.

BACKGROUND: Machine learning (ML) models have been proposed to improve the discrimination of intracranial aneurysm rupture status beyond established clinical risk stratification tools. However, reported performance is heterogeneous and the relative contribution of model architecture and feature dominance remains unclear. METHODS: We performed a Preferred Reporting Items for Systematic Reviews and Meta-Analyses-diagnostic test accuracy systematic review and diagnostic meta-analysis of studies evaluating ML models for intracranial aneurysm rupture discrimination. PubMed, Embase and CENTRAL were searched to February 2026. Sensitivity and specificity were pooled using a bivariate random-effects model, with summary receiver operating characteristic curves generated across training, internal testing and external validation datasets. Models were compared with regression-based approaches and Population, Hypertension, Age, Size of aneurysm, Earlier subarachnoid haemorrhage, Site of aneurysm (PHASES) scores. Subgroup and meta-regression analyses explored associations between algorithm family and feature domain. RESULTS: Sixty-two retrospective cohorts (29 709 patients 209 models) met the inclusion criteria. In training datasets, pooled sensitivity and specificity for ML were 0.81 (95% CI 0.75 to 0.85) and 0.83 (0.80-0.86), with an area under the curve (AUC) of 0.878, exceeding PHASES (AUC 0.667). In testing datasets, ML retained higher discrimination (AUC 0.837) than regression models (0.806) and PHASES (0.646). In external validation, sensitivity was preserved (0.82), but specificity declined (0.66). Deep learning demonstrated the highest AUCs (training and testing). Incorporation of haemodynamic or radiomic features improved pooled discrimination relative to morphology alone. Evidence of small-study effects and mostly unclear Prediction Model Risk Of Bias Assessment Tool ratings were observed. CONCLUSIONS: ML approaches demonstrate higher pooled discrimination for aneurysm rupture status than conventional risk scores in retrospective datasets, but reduced external validation specificity and heterogeneity limit confidence for clinical translation. Prospective, externally validated, calibrated models are required before integration into routine cerebrovascular risk stratification.

Humans↗
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

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

Tissue-derived extracellular matrix hydrogels instruct epigenetic adaptation in metastatic colonization.

The extracellular matrix (ECM) plays a central role in regulating tumor progression and metastatic colonization by providing biochemical and mechanical signals that shape cancer cell fate. However, most organoid culture systems rely on basement membrane extracts that fail to reproduce the tissue-specific extracellular environments encountered during metastasis. Here, we develop tissue-derived decellularized matrix hydrogels to reconstruct organ-specific microenvironments and investigate epigenetic adaptation to ECM cues during metastatic colonization. Patient-derived colorectal cancer organoids cultured in colon-derived matrices exhibited enhanced maintenance of stem-like phenotypes and colon-specific chromatin accessibility landscapes compared with cultures grown in basement membrane extracts, demonstrating improved physiological relevance for primary tumor modeling. When exposed to matrices derived from secondary organs, the organoids showed distinct growth phenotypes accompanied by rapid, tissue-dependent chromatin accessibility remodeling, indicating that ECM composition alone can reshape regulatory programs governing metastatic adaptation. Notably, liver-derived matrices selectively activated hepatocyte nuclear factor 4 alpha (HNF4A)-associated transcriptional networks and created a context-specific dependence on c-MET signaling for survival. Functional perturbation of HNF4A or c-MET signaling confirmed that both are required for organoid formation specifically within the liver matrix environment. Together, these findings establish tissue-derived matrix hydrogels as instructive bioactive materials that actively regulate cancer cell epigenetic states and reveal microenvironment-specific therapeutic vulnerabilities during early metastatic colonization.

Journal Article↗
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↗