Journal of Dental Research

Aim: Cross-sectional summaries of periodontitis based on clinical attachment loss (CAL) are, by definition, conditioned on surviving teeth. Because the most severely affected teeth are more likely to have been lost, these measures may underestimate cumulative disease burden and show an artificial flattening (attenuation) of severity with age. We hypothesised that measures more sensitive to severe attachment loss would show greater attenuation at older ages than measures defined across a broader range of sites. Materials and Methods: Using nationally representative data from adults aged 30+ years in NHANES 2009-2014, we examined age-specific trajectories across multiple continuous measures of periodontal severity and assessed whether divergence between measures followed the pattern predicted under severity-dependent tooth loss. Results: The proportion of observable sites declined from 93% at ages 30-34 to 68% at 80+ years, establishing the structural basis for the divergence observed across severity measures. All severity measures showed nonlinear attenuation with age, with distortion increasing with severity threshold. Higher-threshold measures exhibited the greatest attenuation, while lower-threshold measures showed more stable trajectories. Conclusions: Cross-sectional summaries of periodontitis reflect disease among surviving teeth rather than cumulative damage across teeth originally at risk. Attenuation at older ages is consistent with depletion of the most severely affected teeth rather than biological slowing. Distortion varies by measure, with higher-threshold and mean-based indices most affected, whereas the CAL 3+ mm threshold provides a more stable basis for age comparisons.

Background: Periodontitis is defined by cumulative, irreversible tissue destruction, yet population-based measurement typically relies on cross-sectional indicators derived from retained teeth. Destruction that occurred earlier in life, particularly disease severe enough to result in tooth loss, is structurally excluded from these measures, potentially leading to systematic underestimation of lifetime periodontal burden. Objective: To develop and evaluate a measurement framework that estimates lifetime periodontal burden from cross-sectional data by explicitly incorporating informative tooth loss under etiological uncertainty. Methods: Data were drawn from 10,324 adults aged [≥]30 years participating in the 20090-2016 National Health and Nutrition Examination Survey (NHANES) who completed full-mouth periodontal examination and glycated hemoglobin (HbA1c) testing. Lifetime periodontal burden was estimated by combining observed clinical attachment loss in retained teeth with probabilistic contributions from missing teeth, using three alternative age-stratified attribution schedules derived from epidemiological studies of periodontal extraction. Performance was compared with conventional measures of periodontal severity and extent using distributional analyses, correlations with HbA1c, discrimination of diabetes status, and relative importance analysis. Age-adjusted models were treated as sensitivity analyses. Results: Estimated lifetime periodontal burden exhibited strong, monotonic age gradients across glycemic categories, in contrast to more attenuated patterns observed for severity and extent. Across attribution schedules, lifetime burden showed stronger correlations with HbA1c ({rho} = 0.30-0.32) than conventional measures. In multivariable models including all indices, lifetime burden retained an independent association with HbA1c, whereas severity and extent contributed little unique information. Discriminative performance for diabetes status was consistently higher for lifetime burden than for conventional measures and remained stable across attribution schedules. Conclusions: Lifetime periodontal burden can be estimated from cross-sectional data by explicitly modelling informative tooth loss rather than restricting measurement to retained teeth. Incorporating historical tissue loss under uncertainty yields a more coherent representation of cumulative periodontal destruction than snapshot-based measures and provides a methodological basis for life-course-oriented periodontal epidemiology.

Objective: To identify Dickkopf-1 (DKK1) as a prognostically relevant candidate in head and neck squamous cell carcinoma and to evaluate whether DKK1 and cytoskeleton-associated protein 4 (CKAP4) expression is associated with cervical lymph node metastasis in tongue squamous cell carcinoma (TSCC). Methods: DKK1 was screened using the Human Protein Atlas Pathology Atlas. Immunohistochemical expression of DKK1 and CKAP4 was examined in 54 patients with primary TSCC (cT1-4N0) treated surgically between 2015 and 2020. Nine cases were excluded because of insufficient tissue blocks or inadequate staining quality, leaving 45 evaluable cases. Associations with delayed cervical lymph node metastasis were assessed together with conventional clinicopathological factors, including infiltrative growth pattern (INF) and pathological depth of invasion (pDOI). Results: In public database analysis, high DKK1 expression was associated with poorer overall survival in head and neck squamous cell carcinoma. In the TSCC cohort, pDOI [≥]5 mm and INF pattern c were significantly associated with cervical lymph node metastasis. Positive DKK1 and CKAP4 expression were also significantly associated with cervical lymph node metastasis. Furthermore, combined DKK1/CKAP4 positivity, when incorporated with INF and pDOI, provided additional risk stratification, and cases with all 3 factors showed a markedly increased likelihood of cervical lymph node metastasis. Conclusions: Expression of DKK1 and CKAP4 was associated with cervical lymph node metastasis in TSCC. Combined assessment of DKK1/CKAP4 expression with INF and pDOI may improve pathological risk stratification and may help identify patients who require closer neck evaluation and postoperative management.

Neuroimaging based pain decoding faces two underappreciated challenges: between subject variability that prevents classifiers from generalizing across patients, and within session cross validation designs that inflate reported accuracy by conflating within person and between person variance. Here we address both using portable functional near infrared spectroscopy (fNIRS) during pharmacologically verified local nerve anesthesia. Twentyfive patients with clinically painful teeth underwent 36 channel bilateral fNIRS during percussion before ("Pre") and after ("Post") local nerve anesthesia. In 13 block-success patients, a paired Pre versus Post comparison with healthy tooth control identified three temporal hemodynamic response function (HRF) features (late slope, mean first derivative, and baseline normalized amplitude) whose analgesia interaction effects (d = 0.63 to 0.79) exceeded that of raw general linear model (GLM) amplitude (d = 0.56), with a significant difference-in-differences interaction (p = 0.011). Per-patient calibration with these features yielded leave one subject out (LOSO) AUC = 0.68 to 0.76 for nonlinear classifiers (permutation p = 0.002), with HbO-specific feature selection achieving the best performance (RF AUC = 0.760); a healthy tooth negative control was non-significant. End to end deep learning on raw time series (CNN LSTM AUC = 0.719) was competitive with feature based classifiers, while linear models did not reach significance. Critically, head to head comparison of within-session CV and LOSO on the same data revealed mean inflation of +0.13 AUC across all model types, including deep learning, demonstrating that high within session accuracy alone does not establish subject-independent validity. Exploratory analyses suggested complementary roles for oxyhemoglobin (HbO; within patient analgesia detection) and deoxyhemoglobin (HbR; cross patient information), and that trial to trial response variability may complement amplitude for cross patient pain detection. These results show that per patient calibration with temporal HRF features supports subject independent analgesic-state detection under strict LOSO evaluation, and that within-session validation (standard in the fNIRS pain- decoding literature) can substantially overestimate performance.

Background: Chronic rhinosinusitis (CRS) is a heterogeneous inflammatory airway disease associated with impaired mucociliary clearance and persistent inflammation. While prior work has focused on inflammatory and molecular pathways, the physicochemical properties of mucus itself remain poorly characterized. This study aimed to define compositional and biophysical features of CRS mucus that may contribute to dysfunction. Methods: A prospective cross-sectional study was conducted in 15 adults undergoing endoscopic sinus surgery (11 CRS, 4 controls). Mucus was collected from the middle meatus. Hydration was measured by lyophilization. Ionic composition was quantified using mass spectrometry. Viscoelasticity was assessed via oscillatory shear rheology. Total protein, total carbohydrate, sialic acid (Sia) and fucose (Fuc) content were quantified using enzymatic and chemical assays. Statistical comparisons were performed using nonparametric tests. Results: CRS mucus exhibited significantly higher Ca2+; and Mg2+; concentrations (approximately two-fold; p<0.05) and increased variability in hydration and ion content compared to controls. Rheology showed greater heterogeneity and a non-significant trend toward increased viscoelasticity in CRS. Total protein and carbohydrate content were not significantly different; however, the carbohydrate-to-protein ratio was significantly reduced in CRS (p=0.04). Sia content and Sia-to-carbohydrate ratio were significantly elevated in CRS (p=0.04 and p=0.002), particularly in CRS with nasal polyps. Fuc content did not differ between groups. Conclusions: CRS mucus demonstrates coordinated alterations in ionic composition and glycosylation, characterized by increased cation content, hypersialylation, and reduced carbohydrate-to-protein ratios. These changes may contribute to altered mucus properties and impaired mucociliary clearance, highlighting mucus composition as a potential therapeutic target in CRS.

Background: The use of immune checkpoint inhibitors (ICIs) in the treatment of cancer has rapidly expanded over the last decade. However, there are several knowledge gaps in understanding how tumor cells evade the immune system. There is paucity of data in HPV negative oral cancer, particularly of the gingivobuccal region. Understanding the mechanism of immune system evasion in this cancer is vital for improving patient outcomes. Methods: We characterized the baseline immune milieu of oral cancer using immunohistochemistry (IHC) on whole tumor sections from 124 cases. Tumors were classified as hot or cold and further stratified into high-risk and low-risk groups. High-risk patients included those with lymph node metastasis at diagnosis/recurrence or distant metastasis within 2 years of treatment completion. Patients without these features were categorized as low risk. Validation by RNA-Seq and Joint Enrichment Analysis of Oncogenic and Immunologic Pathways was carried out in a subset of 46 cases. Results: Hot high-risk tumors (by IHC) were distinguished by elevated PD-L1 expression and reduced NK-cell, PD1, and CTLA-4 expression. There was no difference in the expression levels of CD3+, CD8+, granzyme, or perforin compared to hot low-risk tumors, findings that align with the definition of hot tumors. RNA-Seq revealed a gene signature associated with exhausted T-cells in hot high-risk tumors. Gene and pathway analyses identified differential upregulation of isoform-specific TOX, TCF, CXCR, RUNX, IRF, BRD and BCL6 genes, implicating immune cell exhaustion and tumor aggressiveness. Significantly downregulated genes included PDCD1, HAVCR2, ZAP70, and STAT, indicative of a disabled immune microenvironment. These findings support that a state of immune exhaustion in HHR tumors is driven by progenitor exhausted T-cells and terminally exhausted T-cells; independent of PD1-TIM3. Conclusion: These findings suggest that combining TOX/TCF/BCL6 inhibitors with immune checkpoint inhibitors in the adjuvant setting might benefit patients with hot high-risk tumors. Given the results, testing for a targeted exhaustion-related gene panel at diagnosis is recommended for oral cancers to stratify tumors as high-risk or low-risk. Larger validation studies and clinical trials are now warranted.

Objective Memory impairment is a frequent comorbidity of focal epilepsy, incompletely explained by seizure frequency or structural pathology. Ictal and postictal hippocampal dysfunction disrupt memory processes, but their cumulative impact remains poorly quantified. This study introduces cumulative hippocampal seizure-related burden metrics and examines their association with long-term memory consolidation. Methods Twenty consecutive patients undergoing stereo-EEG in Marseille (2016-2018) were prospectively included. Continuous stereo-EEG recordings between two memory assessments (30 minutes and one week post-encoding) were analysed. Hippocampal ictal involvement and durations were assessed using epileptogenicity markers and visual stereo-EEG analysis. The postictal period was quantified using permutation entropy. Cumulative hippocampal seizure-related burden metrics (ictal, postictal and combined: c-HipSZB) were computed across hippocampus-involving ictal events. Verbal and visual memory were assessed using standardized recall and recognition tasks. Associations were examined using univariate and multivariate analyses. Results Higher dominant-hemisphere hippocampal burden was associated with poorer one-week verbal memory (performance and retention), independently of most covariates. Higher c-HipSZB was associated with lower total recall performance (RT; free + cued) and RT retention ({beta} = -25.04 and -23.88; R2 = 0.57 and 0.53; p < 0.05) and accounted for the greatest variance in both outcomes (adjusted R2= 0.59 and 0.53; {beta} = -25.45 and -24.27; p < 0.01), particularly when adjusting for epilepsy duration. No robust associations were observed between non-dominant-hemisphere hippocampal seizure-related burden metrics and visual memory. Effects predominantly involved recall. Interpretation Cumulative ictal-postictal hippocampal dysfunction is a major determinant of impaired long-term verbal memory consolidation in focal epilepsy.

INTRODUCTION: Cognitive trajectories may clarify how type 2 diabetes (T2D) and impaired fasting glucose (IFG) relate to dementia risk, but longitudinal associations remain unclear, particularly in the context of stroke. METHODS: Data from 5,631 dementia- and stroke-free older adults (mean age 75 years) from 7 international population-based cohorts were analyzed. Linear mixed-effects models estimated cognitive trajectories during stroke-free and post-stroke follow-up. Glucose status was defined by fasting glucose and prior T2D diagnosis. RESULTS: Over 6.6 years of follow-up (4.5% with incident stroke), T2D was associated with lower baseline cognitive performance compared with normal fasting glucose (-0.14 SD, 95% CI -0.21 to -0.07), but not with faster cognitive decline during stroke-free or post-stroke follow-up. IFG was not associated with lower cognitive performance or faster decline. DISCUSSION: In older adults, T2D was associated with persistently lower cognitive performance but not faster decline, suggesting adverse cognitive effects may be established before late life.

We present a compact pump-and-probe mid-infrared Optothermal Spectrometer (OTHES) equipped with Spatial Probing and Autocorrection (SPAC) optimized for robust intravital application in humans. SPAC-OTHES facilitates alignment stability and spectral comparability across different measurement sessions involving different skin types. Contrary to state-of-the-art, SPAC-OTHES uses camera-based beam detection and an auto-calibration mechanism that enables ca. 73% better spectral reproducibility in intravital measurements in human volunteers than non-calibrated readouts. Moreover, SPAC-OTHES has the potential to lower the glucose quantification error, as demonstrated here in artificial skin phantoms, where an improvement of 52% compared to conventional diode-based detection was observed. The compactness of OTHES, combined with reliable SPAC-readout, has the potential to accelerate commercialization and broad application of biosensors based on mid-infrared spectroscopy.

Background: Antenatal care (ANC) utilization is critical for improving maternal and neonatal health outcomes. Despite the World Health Organization recommendation of at least eight ANC contacts during pregnancy and the implementation of free maternal healthcare policies in Ghana, significant geographic and socioeconomic disparities in ANC utilization persist. This study therefore assessed the spatial distribution and geographically varying determinants of ANC utilization among women in Ghana. Methods: A cross sectional analytical study was conducted using women data from the 2022 Ghana Demographic and Health Survey. The analysis included women aged 15 to 49 years with an index child younger than five years preceding the survey. Descriptive statistics were computed using Stata version 18, while spatial analyses were conducted in QGIS version 3.44. Global Morans I was used to assess spatial autocorrelation, whereas Local Morans I and Getis Ord Gi analyses identified spatial clusters, hotspots, and coldspots of ANC utilization. Ordinary Least Squares (OLS) regression and Geographically Weighted Regression (GWR) models were fitted to assess global and local determinants of ANC utilization. Results: Overall, only 26.0% of women achieved adequate ANC utilization, while 74.0% reported inadequate ANC attendance. Adequate ANC utilization was higher among women with higher education (42.0%) and those from the richest households (41.3%) compared with women without formal education (19.1%) and those from the poorest households (17.6%). Regional disparities were observed, with Western (48.8%), Eastern (48.0%), and Greater Accra (47.3%) regions recording the highest ANC utilization, whereas Savannah (24.7%), Northern (25.8%), and North East (26.8%) regions recorded the lowest utilization levels. Global Morans I demonstrated significant positive spatial autocorrelation (Morans I = 0.457, p = 0.044), indicating geographic clustering of ANC utilization across Ghana. Getis Ord Gi analysis identified significant coldspots within Northern, Savannah, and North East regions, while Central Region demonstrated significant hotspot clustering. OLS regression showed that maternal education (B = 0.284, p = 0.003) and household wealth (B = 0.191, p = 0.011) positively influenced ANC utilization, whereas distance to health facility negatively influenced utilization (B = -0.156, p = 0.019). The GWR model demonstrated improved explanatory performance (Adjusted R-squared = 0.71), confirming substantial spatial heterogeneity in ANC determinants across Ghana. Conclusion: Adequate ANC utilization in Ghana remains low and geographically unequal. Maternal education, household wealth, and geographic accessibility significantly influence ANC utilization, with pronounced disparities concentrated within Northern Ghana. Spatially targeted maternal health interventions aimed at improving education, reducing socioeconomic inequalities, and enhancing healthcare accessibility are required to improve equitable ANC utilization across Ghana.

Wearable digital health technologies may complement traditional gait assessments in amyotrophic lateral sclerosis (ALS) by sensitively capturing real-world mobility changes. In this study, we validated six digital gait metrics derived from ankle-worn sensors in a natural history cohort of 182 individuals with ALS. Investigated metrics correspond to various aspects of gait, including volume, speed, intensity, similarity, variability, and fragmentation. Longitudinal analyses showed significant declines in step count, peak cadence, stride intensity, and stride similarity, with increasing stride duration variability and walking fragmentation over 52 weeks. Many participants exhibited greater relative change in the gait metrics than the self-reported ALS Functional Rating Scale-Revised (ALSFRS-RSE). Stratified analyses revealed that digital metrics captured significant functional decline even in participants with stable walking scores on the ALSFRS-RSE. These findings support the potential utility of these metrics for disease monitoring in ALS clinical care and trials.

Background: The rising prices of cancer medicines have intensified concerns about treatment access and health system sustainability particularly in low- and middle-income settings. Systematic facility level evidence on what medicines is actually available, at what prices, and at what cost to patients remains scarce, constraining evidence-based policy reform. Methods: Using adapted WHO/Health action international methodology, we conducted a cross-sectional survey of 52 cancer medicines across five therapeutic classes at five health facilities in Kisumu County, Kenya. Availability was measured as the proportion of facilities stocking each medicine. Affordability was assessed using days' wages required for the lowest-paid government worker to purchase standard treatment regimens, calculated per one chemotherapy cycle and maximum possible cycles. Results: Overall medicine availability was 48.1%, with marked inter-facility variation. Affordability analysis revealed severe financial barriers. The breast cancer AC regimen required 19.6-47.4 days' wages per full course; cervical cancer cisplatin, 19.8-49.2 days' wages; colorectal FOLFOX, 80.0-303.6 days' wages; and prostate docetaxel reached 437 days' wages at the highest-cost facility. The Social Health Authority's (SHA) KES 550,000 annual ceiling adequately covered cytotoxic regimens for common cancers at competitive prices but was exceeded by 24-116% for HER2-positive breast cancer requiring trastuzumab, with further strain for recurrent cervical and metastatic prostate cancers. Conclusions: Cancer medicines in Kisumu County are inconsistently available and highly variable in price resulting in inequitable access. We call for urgent retail price markup regulation, expanded pooled procurement through KEMSA, inclusion of priority targeted therapies on the Kenya Essential Medicines List, and SHA benefit packages redesigned around full-course regimen costs.

Introduction Obstructive lung diseases (OLDs) are responsible for high rates of illness and death worldwide. Inflammation, chronic airflow limitation, and bronchial remodeling occur in OLD and eventually result in the unique respiratory sounds. Despite its subjective and having low reproducibility, still traditional auscultation using a manual stethoscope is the main method used to identify the lung sounds. Nevertheless, the combination of recent advancements in digital stethoscopes and AI (Artificial Intelligence) has permitted the objective measurement of lung sounds. Nevertheless, there is a lack of standardized, region-specific databases for AI training and validation. Even though lung sound classification is an emerging aspect in research and telerehabilitation the lobar wise acoustic pattern is still novel due to lack of prevailing database to train AI models. Identifying this gap this study aims to develop an acoustic repository and analyze the data using segmental lung sounds from patients with OLDs and healthy controls through an electronic stethoscope. Methods and analysis This is a cross sectional observational study involving 120 participants (60 OLD patients and 60 healthy controls). Lobar wise acoustic signals will be captured using an electronic stethoscope in healthy and diseases population. The data will be analyzed using Audacity software for annotations and then it will be used for feature extraction and statistical analysis. The acoustic features extracted through Audacity, will include frequency, intensity, pitch, and root mean square (RMS) energy. Repeated measures ANOVA will be applied to compare mean sound intensities across lung segments while Pearson correlation will be used to assess associations with body composition parameters. The data will then be standardized for AI-based diagnostic applications. Ethics and dissemination The study is being reviewed from the Ethics Review Committee, Faculty of Medicine, University of Peradeniya (2025/EC/87) will be sought. Informed consent will be obtained in writing. The dissemination of results will take place through peer-reviewed publications and the creation of a public database containing lung sounds from the region.

Background: Climate mitigation policies can lower air pollutant concentrations and deliver substantial health co-benefits. The French Ecological Transition Agency (ADEME) proposed four contrasting Transitions 2050 net-zero scenarios. We quantified mortality, morbidity, and health-economic co-benefits from projected PM2.5 and NO2 reductions across all four scenarios in continental France. Methods: Emission projections were input to the CHIMERE chemistry-transport model to estimate PM2.5 and NO2 concentrations for 2030 and 2050. Health impacts were assessed using disease-specific cessation-lag assumptions relative to 2019, covering premature mortality, morbidity, DALYs, and economic benefits across nine outcomes (hypertension, lung cancer, ischaemic heart disease, stroke, COPD, type-2 diabetes, acute lower respiratory infections, and asthma in children and adults). Findings: Population exposure is projected to decline by about 40% for PM2.5 and 70% for NO2 by 2050, with health gains remaining substantial and broadly equivalent across all four scenarios and modest differences between sufficiency-oriented and technology-driven pathways. Under delayed-impact assumptions, avoided premature deaths ranged from 21,300 to 22,100 for PM2.5 and 24,500 to 26,200 for NO2. Morbidity and disability-adjusted life year (DALY) reductions, as well as economic savings, spanned similarly; total avoided morbidity cases were 84,000-88,000, direct medical cost reductions were e1.0-1.1 billion/year, and intangible cost savings of e41-43 billion and e36-39 billion, respectively. Interpretation: Health co-benefits are substantial, consistent across contrasting scenarios, and increase markedly from 2030 to 2050. Explicitly incorporating these co-benefits into climate policy appraisals may strengthen the case for ambitious mitigation and improve decision-maker acceptability.

Objectives To examine the acute effects of a single bout of high-intensity interval training (HIIT) on fetal blood flow distribution during the third trimester of pregnancy. Methods Thirty-four healthy pregnant participants (mean age 31.6 years, standard deviation (SD) 4.1; gestational week 33.8 (SD 0.4) completed eight 30-second high-intensity cycling work-bouts interspersed with 2-minute rest periods. Fetal heart rate (FHR), maternal blood pressure, and Doppler-derived blood flow indices in the middle cerebral artery, umbilical artery and vein, and ductus venosus were assessed before and after exercise. We estimated fetal liver blood flow and the ratio of umbilical vein flow to ductus venosus. Maternal heart rate (HR) and FHR were recorded throughout exercise. Paired t-tests compared pre- and post-exercise values. Results No significant changes were observed in fetal blood flow indices or distribution following exercise. Average maternal HR and FHR during the work-bouts were 158 bpm (SD 16) and 152 bpm (SD 12), respectively. Following HIIT, maternal systolic blood pressure increased by 5 mmHg (95% CI 1 to 8, p=.014), maternal HR by 22 bpm (95% CI 15 to 28, p<.001), and FHR by 13 bpm (95% CI 10 to 17, p<.001). We recorded 16 instances of FHR above normal range during HIIT. Conclusion A single HIIT session in late pregnancy increased maternal blood pressure and HR and transiently elevated FHR but did not affect fetal blood flow indices or distribution. Brief episodes of fetal tachycardia were observed but appeared to be clinically insignificant. Future research should investigate the effects of repeated HIIT exposure during pregnancy.

Background and Objective: Access to real-world electronic health records (EHRs) remains limited by privacy, governance and annotation constraints, hindering the development of clinical natural language processing models. Realistic synthetic progress notes may provide EHR-like corpora that preserve clinically rigorous information on diagnoses, treatments, symptoms, imaging, laboratory findings and therapeutic trajectories without relying directly on sensitive patient records. This study evaluates whether large language models (LLMs) can generate realistic Spanish prostate cancer progress notes from published case reports, preserving clinical content, temporality and hospital-style conventions.

People living with HIV (PLWH) are known to maintain a degree of immune deficiency despite efficient antiretroviral therapy and may exhibit diminished responses to vaccines. In this study, we assessed the immune response to SARS-CoV-2 infection and vaccines in two geographically distinct PLWH populations. PLWH and HIV-negative (HIV-) participants were recruited from Qu&bec City (QC), Canada, and Bobo-Dioulasso (BD), Burkina Faso, for two visits at 24-week intervals during the predominance of the Omicron variant, from May 2022 to September 2023. Blood samples were collected at each visit for the detection of antibodies against spike (anti-S) and nucleocapsid (anti-N) proteins of SARS-CoV-2 in platelet-free plasma. A total of 360 participants were enrolled. We detected anti-S antibodies in 99% of participants, indicating that nearly all had prior exposure to the SARS-CoV-2 spike antigen, either through vaccination or prior infection. Anti-S titers showed no difference between PLWH and HIV& participants in each location, while significantly higher titers were observed in participants from QC compared to BD. In contrast, anti-N antibodies, indicative of prior infection, were detected in 39% and 86% of the participants in QC and BD, respectively, suggesting that the virus circulated largely in the latter population. No difference in anti-N levels was observed between PLWH and HIV& participants in BD. However, participants in QC had significantly lower titers compared to HIV participants. Overall, this study shows that PLWH develop robust antibody responses to SARS-CoV-2 vaccination, comparable to those observed in HIV& participants. Significant geographic differences were observed in anti-S titers, irrespective of HIV status, with participants from QC displaying higher titers. In contrast, participants from BD had higher anti-N antibody prevalence and titers, reflecting more SARS-CoV-2 infections in BD than in QC. Finally, analysis of anti-S antibody titers against several circulating variants revealed significantly lower levels in unvaccinated participants and in those vaccinated with monovalent vaccines in BD. No significant difference was observed between monovalent and bivalent vaccines administered in QC. All authors have seen and approved the manuscript.

Background Oropouche virus (OROV) is an emerging vector-borne virus with rapidly expanding geographic range, increasing case counts, and growing evidence of severe outcomes including neuroinvasive disease and vertical transmission. Because OROV infection presents with nonspecific febrile illness that overlaps clinically with other viruses including dengue, zika, and chikungunya, accurate molecular diagnostics are essential for patient care and surveillance. Yet existing assays rely on single genomic targets and are vulnerable to detection failure as the virus evolves and reassorts. Methodology/Principal Findings To support diagnostic capacity, we developed and clinically validated a multiplexed qPCR assay targeting three regions of the OROV S segment, incorporating redundancy to preserve sensitivity across viral diversity while enabling robust clinical interpretation. The multiplex also includes an assay targeting RNaseP as an internal sample control to ensure adequate sample processing. We evaluated assay performance using both historical and contemporary OROV strains and validated the assay on contrived serum, plasma, and cerebrospinal fluid samples, assessing linearity, limit of detection (LOD), accuracy, specificity, precision, and sample stability. The assay met or exceeded all predefined acceptance criteria for clinical testing and achieved an LOD as low as 6 copies per reaction for contemporary outbreak strains. We further implemented a logic-based interpretation matrix that reduced false-positive risk while maintaining sensitivity near the analytical LOD. Conclusions/Significance Our assay sensitively and specifically detects OROV RNA in serum, plasma, and cerebrospinal fluid while incorporating safeguards against viral evolution and reassortment. The assay has been approved for use by CLIA at Nexus Medical Labs in 49 U.S. states, expanding access to timely OROV diagnostics in the United States and providing a durable framework for molecular detection of reassorting, rapidly evolving viruses as OROV continues to spread into new regions.

Rationale: Efficacious dose selection for anti-tuberculosis drugs has traditionally relied on achieving plasma exposures above the minimum inhibitory concentration, but this approach has not consistently aligned with clinical outcomes. Objectives: We sought to identify early pharmacokinetic-pharmacodynamic targets most predictive of clinical efficacious dose. Methods: We conducted a back-translational, pharmacokinetic-pharmacodynamic simulation-based analysis of 15 anti-tuberculosis drugs. Using pharmacokinetic data from multiple biological matrices and a range of pharmacodynamic metrics, we established candidate exposure-response targets for attainment. We systematically evaluated the predictive accuracy of each target pair against established clinical doses to formulate a decision-making framework linking key drug properties to the most predictive targets. Measurements and Main Results: Depending on the target used, projected clinical doses varied widely - both within and across compounds - highlighting the importance of target selection for dose projection and go/no-go decisions. In general, targeting cellular lesion-level drug exposures relative to in vivo preclinical potency provided an effective approach for early dose selection. However, for highly penetrating drugs, targeting site-of-action therapeutic exposures in the caseum was more predictive of clinical dose. Based on these findings, we developed a preliminary dose prediction tool that enables drug developers to estimate clinically relevant dose ranges of compounds using in vitro and early in vivo data. Conclusions: This work establishes and validates a simple, evidence-based framework to standardize early translational decision-making on dose selection of anti-tuberculosis candidates in development.

Background: Regular exercise is a highly effective yet underutilized strategy to reduce cardiometabolic disease burden. Whether brief structured exercise programs confer lasting cardiometabolic benefits remains unclear. The STRRIDE-Prediabetes Reunion study examined legacy effects of exercise training on cardiorespiratory fitness, body composition, and cardiometabolic health. Methods: Seventy-three participants (71.3 {+/-} 7.2 years; 64% women; 77% White) completed Reunion assessments ~11 years after completing one of four 6-month interventions differing in exercise amount, intensity, and inclusion of diet-induced weight loss. Linear mixed effects models evaluated longitudinal trajectories; secondary analyses examined baseline-adjusted associations among short-term intervention response and Reunion outcomes. Results: Abdominal adiposity improved across all groups from baseline to Reunion, with waist circumference decreasing ~3 cm over the follow-up period. In contrast, cardiorespiratory fitness and fat-free mass declined significantly. A significant group by time interaction was observed for total fat mass (p=0.01), with continued fat mass reductions observed in women randomized to high amount exercise. After baseline adjustment, greater short-term intervention response was associated with more favorable Reunion outcomes across fitness, body composition, and cardiometabolic domains; fat-free mass showed the strongest association ({beta}=0.84, p<0.0001). Conclusions: In older adults with prediabetes, the STRRIDE-Prediabetes interventions produced several legacy health effects persisting more than a decade later. Legacy effects differed by sex and exercise dose, and short-term intervention response relative to baseline was associated with long-term outcomes, supporting targeted exercise strategies to preserve cardiometabolic health and functional independence with aging.