Ecological Applications

Military aviation training noise remains understudied despite its widespread impacts across urban, rural, and wilderness areas. The predominance of low-frequency noise and repetitive training can create pervasive noise pollution, yet past research often fails to capture the full range of health and quality-of-life effects. This study analyzed two complaint datasets related to Whidbey Island Naval Air Station noise: U.S. Navy records (2017-2020) and Quiet Skies Over San Juan County data (2021-2023). We analyzed and mapped sentiment intensity from noise complaints relative to modeled annual noise exposure, developed a typology to classify impacts, and modeled the environmental and operational factors influencing complaints. Findings revealed widespread negative sentiment and anger, often beyond the bounds of estimated noise contours, suggesting that annual cumulative noise models inadequately estimate community impacts. Complaints consistently highlighted sleep disturbance, hearing and health concerns, and compromised home environments due to shaking, vibration, and disruption of daily life. Residents also reported significant social, recreational, and work disruptions, along with feelings of fear, helplessness, and concern for children's well-being. The number of complaints were strongly associated with training schedules, with late-night sessions being the strongest predictor. A delayed response pattern suggests residents reach a frustration threshold before filing complaints. Overall, our findings demonstrate persistent negative sentiment and diverse impacts from military aviation noise. Results highlight the need for improved noise metrics, modeling and operational adjustments to mitigate the most disruptive effects.

Neurodegenerative diseases such as Mild Cognitive Impairment (MCI), Multiple Sclerosis (MS), Parkinson s Disease (PD), and Amyotrophic Lateral Sclerosis (ALS) are becoming more prevalent. Each of these diseases, despite its specific pathophysiological mechanisms, leads to widespread reorganization of brain activity. However, the corresponding neurophysiological signatures of these changes have been elusive. As a consequence, to date, it is not possible to effectively distinguish these diseases from neurophysiological data alone. This work uses Magnetoencephalography (MEG) resting-state data, combined with interpretable machine learning techniques, to support differential diagnosis. We expand on previous work and design a Riemannian geometry-based classification pipeline. The pipeline is fed with typical connectivity metrics, such as covariance or correlation matrices. To maintain interpretability while reducing feature dimensionality, we introduce a classifier-independent feature selection procedure that uses effect sizes derived from the Kruskal-Wallis test. The ensemble classification pipeline, called REDDI, achieved a mean balanced accuracy of 0.81 (+/-0.04) across five folds, representing a 13% improvement over the state-of-the-art, while remaining clinically transparent. As such, our approach achieves reliable, interpretable, data-driven, operator-independent decision-support tools in Neurology.

The modern Western diet (MWD) provides high linoleic acid (LA) exposure, typically contributing 6-9% of total caloric intake. These high LA levels have fueled a longstanding debate regarding whether this dietary pattern confers benefit or risk. Importantly, LA intake is disproportionately elevated among lower socioeconomic populations due to greater reliance on industrial seed oils and ultra-processed foods. Despite decades of research, controlled dietary intervention studies directly evaluating the biological consequences of varying LA exposure remain limited. The current randomized, double-blind intervention compared the effects of a 12-week Low LA diet (2.5% energy) versus a High LA diet (10.0% energy) in healthy adults. Primary outcomes included plasma highly unsaturated fatty acid (HUFA) concentrations and ex vivo zymosan-stimulated whole-blood oxylipin generation. Fifty- two participants completed the intervention. High LA exposure resulted in a marked reduction in plasma n-3 eicosapentaenoic acid (EPA) concentrations compared with the LowLA arm. In contrast, levels of arachidonic acid (ARA), dihomo-gamma-linolenic acid (DGLA) and docosahexaenoic acid (DHA) did not differ by dietary LA exposure. Analysis of oxylipin species revealed that levels of EPA-derived relative to ARA-derived mediators were significantly reduced in the High LA arm. These findings reveal that higher dietary LA selectively suppresses EPA pools and EPA-derived oxylipins without altering ARA, shifting the lipid mediator balance toward a more n-6-dominant profile.

BackgroundPreterm birth is one of the most significant etiologies for neonatal morbidity and mortality. Preterm delivery is classified as iatrogenic preterm delivery and spontaneous preterm delivery. The role of placental pathology is studied. Materials and methodsWe have previously collected placental pathology data with maternal pregnancy and neonatal birth data, and we investigated the role of placental pathology in preterm delivery. Preterm delivery was categorized as late preterm (34-36 weeks), moderate preterm (32 to 33 weeks), and extreme preterm (less than 32 weeks). Neonatal, maternal, placental gross and histologic features, and laboratory parameters were compared across groups using chi-square tests for categorical variables and Kruskal-Wallis tests for continuous variables using various programs in R-package. ResultsTotally 3723 singleton placentas including 3307 term (88.8%) and 416 preterm placentas (11.2%) were examined with maternal pregnancy data and neonatal birth data. There were 614 placentas from patients with preeclampsia/pregnancy induced hypertension (PRE/PIH) (16.5%). Preterm delivery showed significantly lower fetal birth weight, placental weight, and fetal-placental ratio (all p<0.01). Maternal Black race was more prevalent in preterm groups (up to 50.8% in extreme preterm vs. 33.2% in term, p<0.01). Preterm delivery was statistically associated with PRE/PIH and maternal vascular malperfusion (MVM), maternal and fetal inflammatory response (MIR and FIR), and increased pre-delivery white blood count (WBC). Extreme preterm deliveries were markedly associated with intrauterine fetal death (27.5%, p<0.01) and MIR/FIR (56.7%, p<0.01). After excluding PRE/PIH patients, preterm delivery was statistically associated with MIR/FIR and increased WBC. ConclusionsDistinct clinicopathologic profiles exist across preterm subcategories, with MVM predominating in late/moderate preterm and severe pathologic features (including fetal demise and acute inflammation) in extreme preterm. These findings highlight heterogeneous etiologies of preterm delivery.

Background and aims: Pancreatic ductal adenocarcinoma (PDAC) surveillance is limited to individuals with familial or genetic risk although most future cases arise outside these groups. In a retrospective study, PRISM, an electronic health record (EHR)-based PDAC risk model, identified individuals in the general population at elevated near-term risk of PDAC. We aimed to prospectively evaluate whether PRISM can identify high-risk individuals beyond current surveillance groups across U.S. health systems. Methods: We performed a prospective multicenter cohort study after deployment of PRISM in April 2023 across 44 U.S. health care organizations. Eligible adults aged [&ge;]40 years without prior PDAC received a single baseline risk score and were assigned to prespecified risk tiers. Patients were followed for incident PDAC for 30 months. We estimated tier-specific 30-month cumulative incidence (positive predictive value, PPV), number needed to screen (NNS), standardized incidence ratios (SIRs), and time from deployment and first high-risk flag to diagnosis. Results: Among 6,282,123 adults assigned a PRISM score, 5,058,067 had follow-up; 3,609 developed PDAC. The highest-risk tier had 30-fold higher PDAC incidence than the study population. At the SIR 5 threshold, 30-month cumulative incidence was 0.35% (NNS, 284.2); at SIR 16, 1.14% (NNS, 87.4); and at SIR 30, 2.19% (NNS, 45.7). Median time from deployment to PDAC diagnosis was 9.5 months, and median time from first high-risk flag to diagnosis at SIR 5 was 3.5 years. Shapley additive explanations (SHAP) analyses supported patient- and tier-level interpretability. Conclusions: Prospective deployment of PRISM across multiple U.S. health care organizations identified individuals at elevated near-term risk for PDAC, with substantial risk enrichment and lead time before diagnosis. These findings support the real-world scalability and generalizability of EHRbased risk stratification for risk-adapted early detection. ClinicalTrials.gov identifier NCT05973331

Background: Current deep learning models in computational pathology, radiology, and digital pathology produce opaque predictions that lack the explainable artificial intelligence (xAI) capabilities required for clinical adoption. Despite achieving radiologist-level performance in tasks from whole-slide image (WSI) classification to mammographic screening, these models function as black boxes: clinicians cannot trace predictions to specific biological features, verify outputs against established morphological criteria, or integrate AI reasoning into precision oncology workflows and tumor board decision-making. Methods: We present Virtual Spectral Decomposition (VSD), a modality-agnostic, interpretable-by-design framework that decomposes medical images into six biologically interpretable tissue composition channels using sigmoid threshold functions - the same mathematical structure as CT windowing. Unlike post-hoc xAI methods (Grad-CAM, SHAP, LIME) applied to black-box deep learning models, VSD channels have pre-defined biological meanings derived from tissue physics, providing inherent explainability without sacrificing quantitative rigor. For whole-slide image (WSI) analysis in digital pathology, we introduce the dendritic tile selection algorithm, a biologically-inspired hierarchical architecture achieving 70-80% computational reduction while preferentially sampling the tumor immune microenvironment. VSD is validated across three cancer types and imaging modalities: pancreatic ductal adenocarcinoma (PDAC) on CT imaging, lung adenocarcinoma (LUAD) on H&E-stained pathology slides using TCGA data, and breast cancer on screening mammography. Composition entropy of the six-channel vector is computed as a visual Biological Entropy Index (vBEI) - an imaging biomarker quantifying the diversity of active biological defense systems. Results: In pancreatic cancer, the fat-to-stroma ratio (a novel CT-derived radiomics biomarker) declines from >5.0 (normal) to <0.5 (advanced PDAC), enabling early detection of desmoplastic invasion before mass formation on standard imaging. In lung cancer, composition entropy from H&E whole-slide images correlates with tumor immune microenvironment markers from RNA-seq (CD3: rho=+0.57, p=0.009; CD8: rho=+0.54, p=0.015; PD-1: rho=+0.54, p=0.013) and predicts overall survival (low entropy immune-desert phenotype: 71% mortality vs 29%, p=0.032; n=20 TCGA-LUAD), providing immune phenotyping for checkpoint immunotherapy patient selection from a $5 H&E slide without molecular assays. In breast cancer, each lesion type produces a characteristic six-channel fingerprint functioning as an interpretable computer-aided diagnosis (CAD) system for quantitative BI-RADS assessment and subtype classification (IDC vs ILC vs DCIS vs IBC). A five-level xAI audit trail provides complete traceability from clinical decision support output to specific biological structures visible on the original images. Conclusion: VSD establishes a unified, interpretable-by-design mathematical framework for explainable tissue composition analysis across imaging modalities and cancer types. Unlike black-box deep learning and post-hoc xAI approaches, VSD provides inherently interpretable, clinically verifiable cancer detection and immune phenotyping from standard clinical imaging at existing costs - without requiring foundation model infrastructure, specialized hardware, or molecular assays. The open-source pipeline (Google Colab, Supplementary Material) enables immediate reproducibility and extension to additional cancer types across the pan-cancer TCGA atlas.

Chimeric antigen receptor T-cell (CAR-T) therapy targeting CD19 has transformed outcomes for children with relapsed or refractory (R/R) B-cell acute lymphoblastic leukemia (B-ALL), yet the influence of molecular subtype on outcomes remains unclear. We evaluated the impact of cytogenetic and molecular signatures on complete response (CR), overall survival (OS), and leukemia-free survival (LFS) after CD19 CAR-T therapy in eighty-six pediatric patients with R/R B-ALL treated with tisagenlecleucel. CR was assessed 30 days after infusion. Cytogenetic data were available for 84 patients and molecular profiling for 62. Survival analyses included 72 patients who received CD19 CAR-T as the sole cellular therapy. Seventy-seven patients achieved CR (89.5%). Pre-infusion bone marrow blasts of [&ge;]20% were associated with lower CR rates (53.8% vs 95.9%, p<0.0001) and significantly reduced OS and LFS (both p<0.0001). Among molecular markers, RAS mutations correlated with inferior OS (p=0.0222) and LFS (0.0402). In multivariate analysis, bone marrow blasts >20% and RAS mutations independently predicted inferior OS. Post CAR-T, CD19 negative relapses showed almost twice higher prevalence of RAS mutations (66% vs 37.5%). These findings highlight RAS mutations as a key molecular predictor of outcome after CD19 CAR-T therapy and suggest emergence of unique risk stratification for patients receiving CD19-targeting therapy.

BackgroundMulticancer early detection tests could be used for cancer screening, but may lead to harms, including false positive results and overdiagnosis of indolent tumours that would not have become clinically evident during that persons lifetime. We assessed the potential for these screening harms in the context of future population-based screening with a multicancer early detection test. MethodsWe used a microsimulation model to assess potential population-level impacts of screening at ages 50-75 years with a multicancer early detection test in Canada. We assumed high test specificity (97-99.1%) and test sensitivity increasing with cancer stage. The model includes latent indolent cancers that would not be diagnosed within that persons lifetime but can be overdiagnosed through screen-detection. We calculated the yearly and cumulative lifetime probabilities of screening overdiagnosis and false positive test results, assuming a range of preclinical screen-detectable periods (2-5 years). ResultsAn estimated 2.1-6.0% of all yearly screen-detected cancers with a multicancer screening test were predicted to be overdiagnoses across scenarios. The proportion of overdiagnosis varied by site, and strongly increased with age, going from 1% at age 50 to over 10% of screen-detected cancers by age 75. The test positive predictive value ranged from 15.9%-77.6%, meaning that there could be 0.3-5.3 false positives with no underlying cancer for every true cancer case detected by the test. ConclusionPopulation-level multicancer screening with a multicancer early detection test would likely not lead to substantial screen-related overdiagnosis. Healthcare systems should consider how screening false positives may increase their diagnostic service caseload.

Cancer-related casualties are the most common cause of death worldwide. The discovery of biomarkers is of utmost importance for diagnosis and disease monitoring. Herein, we performed a comprehensive metabolomics biomarker discovery effort in plasma from 615 lung, ovarian and colorectal cancer patients at diagnosis and 95 non-cancerous control subjects. This pan-cancer investigation identified specific panels of metabolites in the entire sample cohort with a high discriminating power and demonstrated by combined ROC AUC values of up to 0.95. The identified metabolites are mainly associated with lipid and amino acid metabolism as well as xenobiotic transformation. These metabolite panels of high predictive power provide new metabolic insights in these cancers and demonstrate the potential of metabolomics for improved diagnosis and monitoring disease progression.

Prehabilitation (PRH) is a preoperative process aimed at optimizing patients functional capacity to improve surgical outcomes and overall well-being. While its physical and cognitive benefits are increasingly documented, its emotional impact, particularly in neuro-oncology patients, remains less explored. This study assessed the psychological effects of a PRH program on 29 brain tumor patients. The primary outcome, emotional well-being, was measured using quality of life and emotional distress metrices. Secondary outcomes included perceived stress levels and control attitudes. Additionally, qualitative data from structured interviews provided further insights into the psychological effects of the intervention. The results indicated significant improvements in quality of life and reductions in emotional distress, particularly among women. While perceived stress levels remained stable, control attitudes showed an increase. Qualitative analysis further highlighted the positive changes in the control sense and identified additional factors, such as the importance of social support sources during the PRH process. Overall, these findings suggest that PRH interventions play a significant role in enhancing emotional well-being among neuro-oncological patients in the preoperative phase. These results underscore the importance of implementing comprehensive and personalized PRH approaches to optimize clinical status both before and after surgery, thereby promoting sustained psychological benefits in this population. This study is based on data collected at Institut Guttmann in Barcelona in the context of the Prehabilita project (ClinicalTrials.gov identifier: NCT05844605; registration date: 06/05/2023).

Objective detection of evoked potentials (EPs) is central to digital diagnostics in hearing assessment and clinical neurophysiology, yet current approaches remain time-intensive and sensitive to inter-individual noise variability. Many existing detection methods rely on population-based assumptions or computationally demanding procedures, limiting robustness and efficiency in real-world clinical settings. We present Fmpi, a digital EP detection framework enabling individualised, real-time response detection through analytical modelling of the spectral colour and temporal dynamics of background noise within each recording. Using extensive simulations and large-scale human electroencephalography datasets spanning brainstem, steady-state, and cortical EPs recorded in adults and infants, we demonstrate performance comparable or superior to state-of-the-art bootstrapped methods while operating at a fraction of the computational cost and maintaining well-controlled sensitivity with improved specificity. Importantly, Fmpi incorporates a futility detection mechanism enabling early termination of uninformative recordings, reducing testing time without compromising diagnostic reliability.

Background. Pancreatic ductal adenocarcinoma (PDAC) has a five-year survival rate of approximately 12%, largely because it is typically diagnosed at an advanced stage. CT-based computational methods for early detection exist but rely on black-box deep learning or large texture feature sets without tissue-specific interpretability. Methods. We developed Virtual Spectral Decomposition (VSD), which applies six parameterized sigmoid functions S(HU) = 1/(1+exp(-alpha x (HU - mu))) to standard portal-venous CT, decomposing each pixel into tissue-specific response channels for fat (mu=-60), fluid (mu=10), parenchyma (mu=45), stroma (mu=75), vascular (mu=130), and calcification (mu=250). Dendritic Binary Gating identifies structural content per channel using morphological filtering, enabling co-firing analysis and lone firer identification. A 25-feature signature was extracted per patient. Three independent datasets were analyzed: NIH Pancreas-CT (n=78 healthy), Medical Segmentation Decathlon Task07 (n=281 PDAC, paired tumor/adjacent tissue), and CPTAC-PDA from The Cancer Imaging Archive (n=82, multi-institutional, with DICOM time point tags). The same six sigmoid parameters were used across all datasets without retraining. Results. VSD achieved AUC 0.943 for field effect detection (healthy vs cancer-adjacent parenchyma) and AUC 0.931 for patient-stratified tumor specification on MSD. On CPTAC-PDA, VSD achieved AUC 0.961 (6 features) and 0.979 (25 features) for distinguishing healthy from cancer-bearing pancreas on scans obtained prior to pathological diagnosis. All significant features replicated across datasets in the same direction: z_fat (d=-2.10, p=3.5e-27), z_fluid (d=-2.76, p=2.4e-38), fire_fat (d=+2.18, p=1.2e-28). Critically, VSD severity did not correlate with days-from-diagnosis (r=-0.008, p=0.944) across a range of day -1394 to day +249. Patient C3N-01375, scanned 3.8 years before pathological diagnosis, had VSD severity 1.87, well above the healthy mean of 0.94 +/- 0.33. The tissue transformation signature was temporally stable, indicating an early, persistent tissue state rather than a progressively worsening process. Conclusions. VSD with Dendritic Binary Gating detects a stable pancreatic tissue composition signature on standard CT that is present years before clinical diagnosis, validated across three independent datasets without parameter adjustment. The six sigmoid channels map to biologically meaningful tissue components through a fully transparent interpretability chain. The temporal stability of the signal implies a detection window of 3-7 years, consistent with known PanIN-3 microenvironment transformation timelines. VSD functions as a single-scan screening tool applicable to any abdominal CT performed during the pre-clinical window.

Children with acute lymphoblastic leukemia (ALL) are treated with multiagent chemotherapy that causes profound changes to the immune system. There are limited data on how disease and therapy impact antigen-specific immune memory, leading to inconsistent guidelines on best practices for revaccination of this population. Here, to inform vaccine guidance, we investigated whether immunity derived from routine childhood measles and varicella zoster virus (VZV) vaccines is maintained during and after therapy for childhood ALL. We report that antibodies against measles and VZV were significantly reduced in children with ALL (n=45) compared to healthy controls (n=13), particularly in older children in whom a longer time had passed since their most recent vaccine dose. However, the avidity of the measles and VZV-specific antibodies was indistinguishable between groups. Despite changes to the composition of the T cell compartment, both overall and antigen-specific T cell function were preserved in children with ALL. These data provide compelling evidence for revaccination of children following ALL treatment. Intact T cell responses suggest that post-treatment revaccination would be effective.

PurposeAnti-vascular endothelial growth factor (anti-VEGF) therapy is the standard of care for neovascular age-related macular degeneration (AMD), yet many patients exhibit persistent retinal degeneration, fibrosis, and incomplete therapeutic response. The molecular pathways underlying this incomplete response remain poorly understood. We sought to identify VEGF-independent signaling pathways active in the vitreous of anti-VEGF-treated AMD patients. MethodsWe performed multiplex antibody-based proteomic profiling of 1,000 human proteins in vitreous samples from patients with neovascular AMD receiving anti-VEGF therapy (n=8) and comparative controls (n=6). Differential protein expression was assessed using one-way ANOVA, followed by gene ontology and pathway enrichment analyses. Drug-target relationships were evaluated to identify potential opportunities for therapeutic repositioning. ResultsWe identified 107 differentially expressed proteins (p<0.05), including key regulators of immune signaling, angiogenesis, and metabolism. Notably, multiple components of cytotoxic lymphocyte pathways were dysregulated, including IL-21R, SIGLEC-7, CTLA4, and IL-2-associated signaling. Enrichment analyses revealed significant activation of pathways related to T-cell activation, interleukin signaling, and leukocyte-mediated cytotoxicity. These immune signatures persisted despite suppression of VEGF signaling. Several clinically available immunomodulatory agents--including abatacept, sirolimus, and dupilumab--targeted pathways identified in this dataset. ConclusionsAnti-VEGF-treated neovascular AMD exhibits persistent cytotoxic immune signaling in the vitreous, suggesting that VEGF-independent immune mechanisms may contribute to ongoing retinal damage and incomplete therapeutic response. These findings provide a rationale for combination therapeutic strategies targeting both angiogenic and immune pathways in AMD.

Objective: The study aims to evaluate the real-world effectiveness of Highly Aspherical Lenslets spectacle (HAL; Essilor(R) Stellest(R)) in slowing myopia progression among Indian children and adolescents aged between 4 and 16 years. Methods and analysis: This was a multicentre retrospective study conducted across 10 leading ophthalmic centers. The study participants comprised children aged between 4 and 16 years who were prescribed HAL spectacles (Essilor(R) Stellest(R)). Data were extracted from electronic medical records at three time points: T1: One year prior to intervention; T2: Baseline at HAL spectacle prescription; T3: 6 to 24 months after prescription. The primary endpoint was the myopia progression and axial elongation in the year following prescription, compared with the untreated year and with published meta-regression models. Only data from the right eye were analysed, with the expected physiological progression estimated based on the individual progression trajectory after adjusting for age-related slowing as reported in published meta-regression models. Results: A total of 372 myopic children were included in the study. The annual myopia progression was -0.72 {+/-} 0.47 D/year during the untreated period, reducing to -0.11 {+/-} 0.29 D/year with HAL spectacle wear. The expected progression without treatment was -0.65 D/year, based on trajectory-adjusted modelling, indicating a treatment effect of 0.54 D/years and an estimated 83% slowing in myopia progression compared to expected progression. The expected axial elongation under physiological conditions was 0.29 mm/year, estimated using age-adjusted meta-regression models; with HAL lens wear, axial elongation was 0.11 {+/-} 0.16 mm/year, corresponding to a [~]62% relative slowing of elongation. Conclusion: The present study demonstrates the real-world evidence validating the efficacy of HAL lenses as an effective myopia control intervention in Indian children and adolescents. The retrospective design and limited follow-up period warrant future prospective, long-term studies to validate these findings.

Objectives: For suspected hip fractures, prehospital protocols directing patients to an orthopaedic centre rather than the nearest emergency department (ED) could reduce time-to-surgery but may impact EMS travel burden. This study evaluates the impact of transfer protocols by quantifying transport to hospitals from long term care (LTC) facilities across Ontario. Methods: A retrospective cross-sectional analysis of all Ontario LTC facilities and hospitals was performed. Two protocols were modeled: standard transfer to the nearest ED with subsequent transfer if required, and selective transfer based on Collingwood Hip Fracture Rule prehospital screening1 directly to the nearest orthopaedic services (orthoED). Median one-way travel distances were calculated from Google Maps. Results: In Ontario, 15.4% of LTC residents require hospital destination decisions because their nearest ED lacks orthopaedic services; for these facilities, median distances were 2.7km to the ED and 36.0km to the orthoED. Among the 52 LTC facilities where selective transfer was distance-optimal, it substantially reduced travel for patients with hip fracture (31.1km vs 49.6km; P<.01) while only modestly increasing travel for patients without hip fracture. Where standard transfer was distance-optimal, little travel difference was noted for patients with hip fracture, however false positive screened patients traveled significantly further to an orthoED. Greatest negative consequences of selective transfer lie in the 1.3% of residents living farthest (>100km) from an orthoED. Conclusions: EMS direct transportation to hospitals with orthopaedics may improve hip fracture care but can increase EMS burden due to patients identified falsely as having a hip fracture, particularly in remote communities.

In this study, we investigate gender bias in a Retrieval-Augmented Generation (RAG) based AI assistant developed for Finnish wellbeing services counties. We tested the system using 36 clinically relevant queries, each rendered in three gendered variants (male, female, gender-neutral), and evaluated responses using both an LLM-as-a-judge approach and a human expert panel consisting of a physician and a sociologist specializing in ethics. We observed substantial and clinically significant differences across gendered variants, including differential treatment urgency, inappropriate symptom associations, and misidentification of clinical context. Female variants disproportionately framed responses around childcare and reproductive health regardless of clinical relevance, reflecting societal stereotypes rather than medical reasoning. Bias manifested both at the LLM generation stage and the RAG retrieval stage, in several cases causing the model to hallucinate responses entirely. Some bias patterns were persistent across repeated runs, while others appeared inconsistently, highlighting the challenge of distinguishing systematic bias from stochastic variation.

Waldenstrom macroglobulinemia (WM) is a rare indolent neoplasm characterized by presence of more than 10% lymphoid cells in BM that exhibit plasmacytoid or plasma cell differentiation that secretes an IgM monoclonal protein. This is a retrospective analysis of 89 patients of WM that describes the clinical and laboratory characteristics, treatment patterns and outcome of patients of WM. The median age of the entire cophort was 66 years with male predominance (67.4%). Most common presentations were symptoms pertaining to anemia (77.5%) and constitutional symptoms (33.7%). Median bone marrow lymphoplasmacytic cells were 41%. Positivity for MYD88 and CXCR4 mutations were seen in 81.8% and 2.4% cases. BR was the most common regimen used (52.8%). Overall response rates were seen at 87.8%. Median overall survival, progression free survival and time to next treatment is 8.49 years, 2.15 years and 3.88 years. BR regimen was associated with highest event free survival.

Background: Metronidazole (MTZ) is a first-line antibiotic for several enteric infections. Its use is common in low-income countries, where most primary-care consultations are conducted by nurses. However, increasing resistance among some enteric pathogens is a growing concern. Using WHO guidelines, we conducted a register-based cross-sectional study to assess MTZ prescribing practices and their determinants in public and private primary healthcare facilities in South Benin. Methods: We performed a register-based cross-sectional study covering the year 2020 in 11 primary healthcare facilities (5 public and 6 private) in Abomey-Calavi, South Benin, following WHO recommendations. In total, 200 visits per facility were selected using systematic random sampling. The primary outcome was the prevalence of MTZ prescription. Determinants of MTZ prescription were identified using multivariable logistic regression analysis. Results: In total, 2,200 medical visits were analyzed. The median age of patients was 19 years, and 57% were female. Antimalarials were prescribed in 52% of visits. Antibacterial agents were prescribed in the majority of visits, with MTZ being the second most frequently prescribed antibiotic (18%), after aminopenicillins (27%). In multivariable analysis, digestive symptoms (adjusted odds ratio [aOR], 8.65; 95% confidence interval [CI], 6.49-11.6), genitourinary symptoms (aOR, 6.84; 95% CI, 3.18-15.0), and skin lesions (aOR, 2.39; 95% CI, 1.58-3.60) were independently associated with increased odds of MTZ prescription. In contrast, fever (aOR, 0.66; 95% CI, 0.49-0.87), respiratory symptoms (aOR, 0.44; 95% CI, 0.26-0.71), and malaria (aOR, 0.21; 95% CI, 0.15-0.28) were associated with decreased odds. Visits in the private sector were also associated with higher odds of MTZ prescription compared with the public sector (aOR, 2.31; 95% CI, 1.78-3.02). Conclusion: MTZ is the second most commonly prescribed antibiotic in primary care in the study area, with its use largely driven by digestive symptoms. Further studies are needed to assess the appropriateness of this prescription. Additionally, research is warranted to understand better the determinants of higher antimicrobial prescribing in the private healthcare sector.

Mpox virus (MPXV) gained increased attention following the declaration of two Public Health Emergencies of International Concern (PHEICs) in 2022 and 2024. The rapid spread of MPXV and the increase in human-to-human transmission highlighted the need for improved diagnostic tools for characterizing infection patterns and transmission dynamics. While PCR is effective for detecting active infections, serological approaches can help identify previous or asymptomatic infections and support retrospective surveillance. However, many serological assays developed during recent outbreaks have not been evaluated in endemic settings such as the Democratic Republic of the Congo (DRC). This study aims to define antigen-specific serological cutoff values to differentiate MPXV-seroreactive individuals from those with other orthopoxvirus (OPXV) exposure or different vaccination histories, specifically for use in the DRC. Here, we analyzed 134 individuals, divided into six distinct cohorts with different exposures. Serum samples were tested using Mesoscale Discovery (MSD) to screen for five MPXV and vaccinia virus (VACV) orthologous antigens: A29L/A27L, A35R/A33R, B6R/B5R, E8L/D8L, and M1R/L1R. Receiver operating characteristic (ROC) analysis identified the best-performing antigens and established seroreactivity cutoff values. A binary composite rule was also evaluated to improve the classification of these results. We identified three MPXV antigens, E8L (cut-off=12.33 AU/mL), A35R (cut-off=5.22 AU/mL), and B6R (cut-off=9.77 AU/mL), that showed the strongest discriminatory performance in the dataset. Collectively, these three antigens form a significant panel that demonstrated clear separation between our mpox survivor cohort and other OPXV-exposed individuals.