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PubMed2026

Exploratory proteomic and metabolomic profiling of pleural effusions identifies histone H4 and alanine as promising complementary markers for pleural tuberculosis.

The diagnosis of pleural tuberculosis (Pl-TB) remains challenging. Histopathological analysis and pathogen detection in pleural biopsies are informative but limited. We investigated differentially expressed proteins and metabolites in pleural effusions from patients with Pl-TB, malignancies, and other pathologies. A proteomic analysis of pooled pleural effusions identified 45 proteins exclusively detected or upregulated in Pl-TB samples, many linked to infectious processes. Conversely, 18 proteins were uniquely found or upregulated in malignant pleural effusions, mainly associated with detoxification and hemostasis. To validate these findings, we employed targeted proteomics in individual samples. Eight proteins were validated: S100-A9, histone H4, insulin-like growth factor-binding protein 2, fibrinogen beta chain, ficolin-3, immunoglobulin heavy constant alpha 1, sulfhydryl oxidase 1, and histidine-rich glycoprotein. Additionally, NMR-based metabolomics identified 13 metabolites with differential abundance between Pl-TB and non-TB samples. Notably, N-acetyl-glycoprotein and the branched-chain amino acids, alanine and lysine differed between groups. Proteomic and metabolomic analyses revealed distinct molecular profiles between Pl-TB and non-TB patients, despite intra-group variability. To address this, we applied classification models. Histone H4 and alanine consistently emerged as discriminative features. Overall, this study provides novel insights into the molecular landscape of Pl-TB. The combined quantification of proteins and metabolites may improve differential diagnosis, although should be further validated in larger, independent cohorts before clinical application.

Humans↗

PubMed2026

Epidemiological status of bovine viral diarrhea virus in water buffalo (Bubalus bubalis): A global systematic review and meta-analysis.

Bovine viral diarrhea virus (BVDV) remains a neglected viral disease in water buffalo despite its significant economic impact in production systems. Although limited epidemiological studies have been reported worldwide, the serostatus and active infection in buffalo have not been systematically reviewed. A systematic review and meta-analysis were conducted to estimate BVDV prevalence in water buffalo and identify associated epidemiological factors. Relevant studies published up to January 31, 2026, were retrieved from five electronic databases. A total of 49 studies were identified from 15 different countries were found for inclusion. A random-effects model was used to estimate pooled-prevalence and assess heterogeneity among studies. A meta-analysis of 37 studies (9270 buffalo) estimated a pooled BVDV seroprevalence of 30.5%, while analysis of 16 studies (7189 animals) indicated an antigen prevalence of 16.5%. Continent-wise analysis revealed the highest BVDV seroprevalence in South-America (44.0%), while antigen prevalence was highest in Africa (21.2%) followed by Asia at 12.2%, and no BVDV data reported from North-America. Among the different countries, the highest BVDV seroprevalence was detected in Turkey (61.6%) and Argentina (59.0%), while antigen prevalence was highest in Egypt (21.2%), with lower estimates in Brazil (11.8%) and Iraq (11.3%). Notably, high heterogeneity (I2 > 90%) was observed in the all-pooled estimates, indicating variations in sampling period, age, sex, sample source and types, diagnostic methods, production-system, and study quality. These findings demonstrate the widespread presence of BVDV in water buffalo populations and indicate the need for targeted control strategies to mitigate its impact on health and productivity.

Animals↗

PubMed2026

Anabolic androgen therapy in critically ill adults: A systematic review and meta-analysis.

Critical illness is characterized by a catabolic, proinflammatory state. Anabolic agents, such as testosterone, have therefore been proposed as therapeutic targets. Our objectives were to assess the effects of testosterone in critically ill populations on patient-important outcomes and identify design limitations to inform future studies. We searched for randomized control trials (RCTs) through Medline, Embase, and EBM Reviews databases from inception through February 24, 2026, including English language articles enrolling adults (≥18 years) admitted to ICU where anabolic androgen therapies (AAT) were compared with placebo or standard of care. Studies had to report at least one of: mortality, ICU and hospital lengths of stay, or duration of mechanical ventilation. We extracted data independently using a standardized data extraction tool, and feedback was received from all co-authors to ensure agreement. For each outcome, we performed meta-analyses using a random-effects model with inverse variance weighting in RevMan. We used the GRADE approach to assess certainty in pooled estimates of effect. Of 1325 screened articles, we found 4 that fit our inclusion criteria. Together, we judged risk of bias as 'some concerns' in 3 trials and 'high' in the final trial, and ultimately found that the effects of anabolic-androgen therapy on patient-important outcomes uncertain. With the uncertainty of current evidence for the effects of anabolic-androgen therapy in critically ill adults, there is insufficient support for its routine use. Future randomized evidence is needed to determine whether anabolic-androgen therapy improves clinically-important outcomes and better define its safety profile in critically ill adults.

Humans↗

PubMed2026

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗

PubMed2026

MET expression by immunohistochemistry as a biomarker in pancreatic neuroendocrine tumours.

INTRODUCTION: MET (c-MET) is a receptor tyrosine kinase implicated in numerous cancers, including pancreatic neuroendocrine tumours (pNETs), by promoting cell proliferation, survival, invasion and angiogenesis. Recognizing its oncogenic potential, there is significant interest in MET-targeted therapies for malignancies like pNETs, which often develop treatment resistance. Immunohistochemistry (IHC) has become a practical method for detecting MET overexpression in cancers. This study evaluates MET expression in pNETs by IHC and assesses its correlation with prognostic variables and survival outcomes. METHODS AND RESULTS: Tissue microarrays containing well-differentiated neuroendocrine tumours from the gastrointestinal tract were analysed. The study included 125 pNET cores from 112 patients after application of inclusion criteria. MET expression was determined using the H-score system. Different variables were assessed for H-score distribution and cross-tables. Survival analyses were conducted based on progression-free survival and overall survival. Positive MET expression was found in 83.5% of cases. Higher MET H-scores were seen in patients with lymphovascular invasion (LVI), distant metastases and higher tumour grade (P < 0.05). When assessing different variables for higher MET H-scores, a significant association emerged at the 150-cut-off-point for LVI, perineural invasion, radiological evidence of progression and overall survival. For survival analysis, at a MET H-score threshold of 200, high MET expression was significantly associated with shorter progression-free survival (mean 8.7 versus 13.4 years, P < 0.05) and overall survival (mean 3.6 versus 7.7 years, P < 0.05). CONCLUSION: Elevated MET expression is linked to adverse histopathological features and worse clinical outcomes in pNET. Standardizing MET IHC evaluation is critical as anti-MET therapies develop, and identifying patients likely to benefit from these treatments remains essential.

MET protein↗

PubMed2026

The Effect of Pain Catastrophizing on Acupuncture Treatment for Chronic Pain in Cancer Survivors.

CONTEXT: Pain catastrophizing (PC) predicts worse pain outcomes in cancer survivors. However, little is known whether PC influences pain outcomes of nonpharmacological treatments such as acupuncture. OBJECTIVES: This study aimed to assess the impact of PC on acupuncture efficacy for chronic pain in cancer survivors. METHODS: This secondary analysis of PEACE trial used two-sample t-test and Pearson's chi-squared test to analyze the pain outcomes of cancer survivors who received electroacupuncture (EA) or battlefield acupuncture (BFA). PC was measured using Pain Catastrophizing Scale (PCS). The Brief Pain Inventory (BPI) was used to measure pain severity and interference at the primary endpoint (week 12). RESULTS: Among 266 participants, 41 (15.41%) had a high baseline PC. Among those receiving EA, high PC patients had greater reductions in pain severity (-3.9 vs. -2.1, P = 0.006) and pain interference (-3.8 vs. -2.6, P = 0.04) than low PC. PC was not associated with pain outcomes in BFA group (P > 0.05 for both severity and interference). Among patients with high PC, a greater proportion were responders in the EA group than those in BFA group (83.3% vs. 43.5%, P = 0.009). Among low PC patients, there was no significant difference in the proportion of responders between the EA and BFA groups (66.1% vs. 64.5%, P = 0.8). CONCLUSION: We found that cancer survivors with high baseline PC had greater pain reductions with EA than BFA and compared to low PC patients. These findings suggest that EA may serve as a targeted treatment option for vulnerable patients with high PC and further support precision pain management.

Humans↗

PubMed2026

Lipid metabolism is a key central, systemic and gut microbial feature of the decline in rat hippocampal function during middle age.

Middle age is emerging as a turning point in brain ageing, prognostic of future cognitive health and amenable to intervention. Metabolic and proteomic differences during this period are not yet fully understood and may potentially influence functions of the hippocampus, a brain area that regulates memory and anxiety. While the gut microbiota is implicated in brain ageing, the relationship between the gut microbiota, the metabolic state, and hippocampal proteome in middle age has not been investigated. We hypothesise that peripheral metabolic or protein features are associated with hippocampal vulnerability in middle age. Therefore, young adult and middle-aged rats were assessed for behavioural, proteomic, metabolic, and gut microbiota differences. Proteomic profiling of the hippocampus revealed differential expression of proteins indicative of altered synaptic signalling. Concurrently, adult hippocampal neurogenesis was decreased in middle age. Hippocampal microglia exhibited a lipid rich, inflammatory phenotype in middle age which correlated with poorer memory performance. CSF and serum proteomic and metabolomic analyses identified dysregulated lipid-related pathways potentially contributing to hippocampal vulnerability in middle age. Furthermore, 16S rRNA sequencing revealed reduced abundance of bacteria involved in lipid metabolism regulation. However, faecal microbiota transfer from young to middle aged rats was not sufficient to robustly improve hippocampus-dependent spatial memory. Together, these findings highlight dysfunctional lipid metabolism as a key feature of middle age that may contribute to decline in hippocampal function. Given that the scope for intervention is limited during older age, targeting biomarkers involved in metabolic and lipid homeostasis may be pivotal for the development of pharmacological or lifestyle-based interventions during middle age which could ultimately delay future cognitive ageing.

Animals↗

PubMed2026

Sex differences in sleep and alcohol consumption outcomes following a digital insomnia intervention.

BACKGROUND: Poor sleep is a well-established risk factor for heavy drinking, and evidence suggests that sleep could serve as a potential treatment target for reducing alcohol consumption. The relationship between poor sleep and problematic drinking appears to be stronger among females, but no studies to date have assessed sex differences in alcohol consumption following insomnia treatment. Here, we combine the samples from two clinical trials to investigate sex differences in the effects of a digital cognitive behavioral therapy for insomnia (Sleep Healthy Using the Internet; SHUTi) on sleep and alcohol outcomes. METHODS: 184 heavy drinking individuals with insomnia (weekly binge episodes: 4/5 + drinks in one sitting for females/males; AUDIT score >7; ISI score >14) were randomly assigned to either the SHUTi program (n = 102) or an active control program (n = 82). Participants completed self-report assessments at baseline, immediately following the 9-week intervention period, and at 3 and 6-months post-intervention. RESULTS: Linear mixed effects models showed that SHUTi effects over time were stronger among females than males for improved sleep outcomes and reduced frequency of total and heavy drinking days (ps ≤ 0.038). Follow-up comparisons of within-group effect sizes revealed consistently larger reductions in alcohol consumption among SHUTi females (Cohen's d range = 0.92-2.23) than SHUTi males (Cohen's d range = 0.65-1.95). CONCLUSIONS: Findings suggest that SHUTi may be more efficacious in improving sleep and reducing drinking among females with insomnia compared to males. These results could have important implications for sex-specific prevention and treatment efforts for heavy drinking individuals with insomnia.

Humans↗

PubMed2026

Development and Validation of a Predictive Model for Identification of Cognitive Impairment Risk in Older Adults with Subjective Cognitive Decline：A Longitudinal Study.

BACKGROUND: Subjective cognitive decline (SCD) is a transitional state between objective cognitive impairment and cognitively intact mental status, providing a critical window for implementing preventive interventions to delay objective cognitive decline. AIMS: We aimed to develop a predictive model for SCD progression in older adults with mild cognitive impairment (MCI). This model will facilitate the identification of risk factors and establishment of targeted interventions for community-based SCD management. METHODS: Data from the China Health and Retirement Longitudinal Study (CHARLS) was utilized in this study, extracting 18 indicators. Potential predictors selected through univariate Cox regression and LASSO regression analyses were sequentially incorporated into a multivariable Cox regression model. A nomogram was constructed to establish a predictive model. Model validation encompassed Area Under Curve (AUC) metrics for discriminative capacity, complemented by quantitative assessments using calibration curve analysis for precision verification and decision curve analysis (DCA) for clinical utility evaluation. RESULTS: A total of 1099 older adults with SCD were included in the final analysis, of whom 114 (10.3%) developed MCI. Multivariable Cox regression identified residence, marital status, educational level, social participation, gait speed, and baseline cognitive function. The model demonstrated time-dependent AUC values of 0.885, 0.830, 0.839, and 0.836 in the training set when evaluating discriminative capacity at 2-, 4-, 7-, and 9-year, respectively. The predictive model showed excellent predictive ability according to AUC, calibration curve, and DCA. CONCLUSIONS: A predictive model was created to estimate the risk of developing MCI in older individuals with SCD, offering clinician-actionable intervention benchmarks for preventive care.

Humans↗

PubMed2026

Study of prescription-indication of antivirals for herpesviruses in a Colombian population: a cross-sectional study.

BACKGROUND: To describe the utilization patterns and therapeutic indications of antivirals used for herpesvirus infections in Colombian patients. RESEARCH DESIGN/METHODS: A cross-sectional study on the use of antivirals for treating outpatients with herpesviruses between November 2023 and January 2024 in a Colombian population database. The Micromedex® database was used to identify Food and Drug Administration (FDA)-approved indications, off-label uses, and potentially inappropriate indications. RESULTS: A total of 14,816 individuals were included (median age:53.0 years [IQR:35.0-65.0]; 60.5% women). Acyclovir was the most frequently prescribed antiviral (oral:77.3%; topical:43.4%). Overall, 56.1% received oral therapy only, 25.2% combined oral and topical therapy, and 18.7% topical therapy only. FDA-approved indications accounted for 29.1% of use (herpes zoster), off-label use for 26.9% (mainly prophylaxis in immunocompromised patients), and potentially inappropriate use for 25.3% (primarily topical treatment of herpes zoster). Acyclovir use (OR:5.93; 95%CI:4.60-7.64) and specialist care (OR:2.17; 95%CI:1.73-2.71) were associated with off-label use. CONCLUSIONS: Antiviral prescribing for herpesvirus infections in a group of patients in Colombia is largely driven by acyclovir, with a substantial proportion of off-label and potentially inappropriate use, particularly involving topical therapies for herpes zoster. These findings highlight significant gaps in adherence to evidence-based recommendations and underscore the need for targeted interventions to optimize prescribing practices.

Humans↗

PubMed2026

Ten years on, still out of reach: barriers to PrEP access and retention in France according to frontline actors (QualiPrEP Study).

Pre-exposure prophylaxis (PrEP) for HIV has been available in France since 2014, and reimbursed since 2016, with general practitioners allowed to prescribe it since 2021. Despite these policy advances, uptake remains low among some of the most affected populations. This community-based qualitative study explored barriers to PrEP access and retention ten years into its implementation.Interviews were conducted with 28 PrEP frontline actors (healthcare professionals and community-based workers involved in promoting, prescribing, or supporting PrEP). The sample included one group discussion (n = 5), two triads (n = 6), two dyads (n = 4), and nine individual interviews (n = 13). Thematic analysis was inductive, with barriers classified across four main domains.Participants were mostly cisgender men, median age 48, born in France and abroad, and employed by NGOs in Paris. Thirteen barriers and four major themes emerged: (1) Internal psychosocial barriers: lack of knowledge, negative health-related reactions; HIV stigma; STI risk perception, taboos; (2) Internal pragmatic barriers: perceived limits of protection, usage and follow-up constraints; (3) External psychosocial barriers: limited physician knowledge and reluctance; (4) External pragmatic barriers: communication failures; structural constraints, lack of human and financial resources.Findings call for more targeted messaging, simplified care models and provider training. They highlight the need to address social and symbolic dimensions of PrEP, with insights from those supporting users to ensure more equitable implementation.

Humans↗

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

Symptom Burden After Dialysis Initiation and Its Association With Hospitalization.

RATIONALE & OBJECTIVE: Symptom burden is distressing for patients living with kidney failure, but there is limited information about the combination of symptoms and individual symptoms that most strongly predict health care use in this group. We classified and summarized patients' symptom burden levels and changes over time and estimated associations with hospitalizations among patients receiving incident hemodialysis. STUDY DESIGN: Longitudinal, observational. SETTING & PARTICIPANTS: Individuals initiating dialysis in the United States. EXPOSURE: Kidney Disease Quality of Life-36 (KDQOL-36) measure. OUTCOME: First hospitalization after dialysis initiation. ANALYTICAL APPROACH: Latent transition analysis was used to identify symptom burden classes using the KDQOL-36. Cox regression models were used to assess whether individual KDQOL-36 symptoms and symptom burden groups were associated with hospitalization risk after dialysis initiation, independent of demographics and comorbid conditions. RESULTS: 1,818 participants were Black (29%), were aged >65 years (59%), were women (42%), had diabetes (49%), and had hypertension (74%). Latent transition analysis identified the following 3 symptom burden groups: (1) low (low severity of all symptoms and kidney disease impacts), (2) moderate (high physical health impact and overall burden of kidney disease), and (3) high (high levels of all symptoms and kidney disease impact). After adjusting for patient characteristics, all KDQOL-36 scales except the Effects of Kidney Disease scale were associated with a higher hazard of hospitalization. Using the symptom burden groups, a high symptom burden was associated with a 20% increase in the hazard of hospitalization. A 1-category worsening in pain interference and in fatigue was associated with a 12% and an 8% increased hazard of hospitalization, respectively. LIMITATIONS: Findings may not generalize outside the United States. CONCLUSIONS: Pain interference and fatigue, as well as an overall symptom burden, are useful prognostic indicators in patients receiving in-center hemodialysis. Symptom burden should remain a treatment target in hemodialysis.

Hemodialysis↗

PubMed2026

Herd-level heterogeneity of antimicrobial resistance in commensal Escherichia coli: A nationwide high-throughput survey of Australian pig herds.

Antimicrobial resistance in commensal Escherichia coli provides a useful indicator for overall antimicrobial resistance burden. We applied this approach to assess antimicrobial resistance within and between commercial pig herds across Australia. A high-throughput robotic workflow was used to isolate 2730 E. coli colonies from rectal contents collected in 2022 from healthy slaughter pigs (n = 300) representing 30 herds (∼70% of national production). Up to 94 isolates per herd underwent antimicrobial susceptibility testing using the Robotic Antimicrobial Susceptibility Platform. Isolate- and herd-level antimicrobial resistance indices were calculated, weighting antimicrobials by their human health importance. Resistance to first-line agents was widespread: ampicillin 77% and tetracycline 79%. By contrast, resistance to critically important antimicrobials was rare (ciprofloxacin 0.11%; extended-spectrum cephalosporins 0.04%), and no clinical resistance to carbapenems or colistin was detected. Overall, 56.9% of isolates were multi-class resistant. Herd-level antimicrobial resistance within indices ranged from 1.51 to 5.76, revealing substantial between-herd heterogeneity. Three herds carried critically important antimicrobials-resistant isolates that would likely have been missed using conventional, lower-density sampling approaches. Whole-genome sequencing identified fluoroquinolone-resistant isolates belonging to ST10 and ST69 (both qnrS1), and ST744 (Quinolone Resistance Determining Region mutations plus blaCTX-M-27). By testing approximately tenfold more isolates than conventional surveys, we uncovered considerable antimicrobial resistance with heterogeneity within and between animals and herds, including farm-specific variability. This expanded sampling also enabled detection of critically important antimicrobial resistance at very low prevalence. In conclusion, high-throughput, high-density testing offers a practical early-warning system and herd-level benchmark to inform surveillance and targeted interventions.

Animals↗

PubMed2026

Molecular diagnostic yield and barriers in inherited retinal diseases: a retrospective cohort study.

OBJECTIVE: To evaluate the diagnostic yield of panel-based genetic testing for inherited retinal diseases (IRDs) and identify barriers to molecular resolution. DESIGN: Retrospective cohort. PARTICIPANTS: A total of 404 patients with clinically confirmed IRDs who were evaluated at the Adult Inherited Retinal Dystrophy Service, Ontario, Canada (October 2021-September 2024). METHODS: Patients underwent targeted massive parallel sequencing panel testing. Diagnostic yield was calculated, and unresolved cases were reviewed. Associations between yield, phenotype, ethnicity, and sex were assessed using χ² analysis. RESULTS: Of 685 referrals, 570 had confirmed IRDs. After we excluded 140 pending results and 26 patients who declined testing, 404 patients were analyzed. At referral, 94 patients (23.2%) had a previous molecular diagnosis, and 138 (34.0%) were diagnosed through clinic-initiated testing, giving an overall yield of 57.4%. Yield varied significantly by phenotype (χ², P = 1.4 × 10⁻⁶), from 94.4% in vitelliform macular dystrophies to 25.0% in vitreoretinopathies, with no sex association (P = 1.0). Disease-causing variants were identified in 83 IRD-associated genes, most frequently ABCA4, USH2A, and BEST1. Of 172 unresolved cases, 62 (36.0%) had negative panels, and 110 (63.9%) were inconclusive, including 30 with unphased pathogenic variants in recessive genes and 10 with high-suspicion variants of uncertain significance. Key barriers included limited family availability for phasing, restricted access to functional assays, and lack of public coverage for whole-exome or whole-genome sequencing. CONCLUSIONS: Massive parallel sequencing-based panel testing achieved a 57% diagnostic yield in this IRD population. Success was strongly phenotype-dependent with substantial heterogeneity. Whole-exome sequencing, whole-genome sequencing, family segregation, and functional genomics could improve diagnostic outcomes and management.

Humans↗

PubMed2026

Metabolomic and structural signatures of pigmented and non-pigmented Himalayan rice landraces.

BACKGROUND: This study investigated the anti-oxidant properties, starch composition, pasting behavior, structural properties, textural properties and non-targeted metabolomic profiles of pigmented and non-pigmented rice landraces as potential next-generation functional food ingredients. RESULTS: Pigmented rice demonstrated 1.34 times more anti-oxidant activity as compared to non-pigmented rice. Pigmented landraces showcased superior nutritional and functional attributes, including higher total dietary fiber and starch content. Fourier-transform infrared (FTIR) analysis revealed distinct molecular signatures with enhanced peak transmittance, while X-ray diffraction (XRD) indicated greater crystallinity ranging from 36-44.3% in pigmented rice compared with 30-40% in non-pigmented rice, suggesting improved digestibility and processing versatility. Pigmented rice recorded less amylose content hence tended to possess increased adhesiveness values whereas non-pigmented rice revealed greater amylose content hence was coupled with greater hardness values. Field-emission scanning electron microscopy (FE-SEM) images revealed that pigmented rice had densely packed and polygonal starch granules whereas non-pigmented rice had loosely packed starch granules with intergranular voids. Untargeted gas chromatography-mass spectrometry (GC-MS) profiling identified 84 metabolites, including unique compounds such as 3,3-dimethylbutanol and ethanoic acid, along with shared metabolites such as sucrose and linoleic acid, highlighting notable biochemical diversity. Multivariate statistical analyses using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway mapping further differentiated the metabolomic landscapes, with variable importance in the projection (VIP) scores identifying key bioactive contributors. CONCLUSION: Pigmented rice landraces exhibited significant functional and nutritional advantages, making them promising candidates for functional food development and nutritional improvement programs. These findings support their potential role in advancing sustainable and health-oriented food systems. © 2026 Society of Chemical Industry.

Oryza↗

PubMed2026

Temporal Trends and Spatial Variation in Preterm Prelabour Rupture of Membranes: A Population-Based Study.

OBJECTIVE: To describe the temporal trends in Preterm prelabour rupture of membranes (PPROM) in metropolitan France and the geographical distribution at the administrative division level. DESIGN: Exploratory population-based study using administrative data of the French National Health Data System. SETTING: Metropolitan France, 2015 to 2023. POPULATION: Pregnancy with a diagnosis of PROM before 37 SA. METHODS: Annual crude incidence of PPROM was calculated by dividing the number of pregnancies with PPROM diagnosis by the number of live births recorded during the same period. Annual trend was estimated by a binomial negative mixed model. Smoothed standardised incidence ratios were estimated based on a BYM2 model, which accounts for spatial variability between departments. MAIN OUTCOME: PPROM cases, defined as pregnancies with first hospitalizations with a diagnosis of PROM before 37 weeks. RESULTS: Over the study period, we included 150 615 PPROM cases representing 16 735 (±596) per year. Incidence of PPROM cases showed an ascending trend over time (incidence rate ratio 1.023 per year; 95% CI: 1.017-1.030) with an annual crude incidence ranging from 2.2% in 2015 to 2.7% in 2023. A decrease in the incidence was observed in 2020 relative to other years (incidence rate ratio 0.903, 95% CI: 0.887-0.920). A map of smoothed SIRs of PPROM cases at the French administrative division level revealed geographical inequalities. CONCLUSIONS: This first population-based study describing PPROM cases in metropolitan France paves the way for further studies to explore environmental hypotheses. Identifying temporal and geographical disparities in PPROM incidence is relevant to public health policy and practice as such disparities argue for the development of targeted prevention strategies in high-risk areas.

French national health data system↗

PubMed2026

Evidence Gap in Managing Lateral Pelvic Lymph Nodes in Rectal Cancer: a Systematic Review of Radiation Boost Strategies.

PURPOSE: Lateral pelvic lymph node (LPLN) involvement is a significant predictor of local recurrence in patients with locally advanced rectal cancer (LARC). While lateral pelvic lymph node dissection (LPLND) is routinely used in some countries to manage suspicious nodes, it is associated with increased morbidity and is not widely adopted in Western practice. Radiation boost (dose escalation) to involved LPLNs during neoadjuvant chemoradiotherapy (nCRT) has emerged as a potential non-surgical alternative. Despite increasing adoption of radiation boost to clinically involved LPLNs, there remains limited evidence defining its safety, oncologic benefit, and role relative to LPLND. METHODS: A systematic search of MEDLINE, EMBASE, ClinicalTrials.gov, and Cochrane databases was conducted following PRISMA guidelines. Studies were included if they reported outcomes of radiation dose escalation specifically targeting radiologically suspicious LPLNs in the context of nCRT. RESULTS: Ten retrospective cohort studies encompassing 482 radiation boosted patients were included. Boost doses ranged from 35.0 to 60.2 Gy. Rates of Grade 2-3 toxicity ranged from 28.0% to 39.3% across individual studies, with only one study reporting a single Grade 4 adverse event. Across individual studies, reported nodal response rates ranged from 62.3% to 100%. Comparative studies suggest that radiation boost may improve local control and reduce LPLN recurrence. CONCLUSION: Current retrospective evidence suggests that radiation dose escalation to involved LPLNs is a promising treatment strategy; however, the available data are limited by retrospective study designs and substantial clinical heterogeneity. Given the absence of prospective evidence and lack of consensus in current guidelines, an important evidence gap remains. Well-designed prospective trials are warranted to define the role of LPLN boost relative to LPLND.

Humans↗