Journal of Hematology & Oncology

Curative-intent immunochemotherapy fails in ~30% of patients with large B-cell lymphoma (LBCL), yet no validated molecular tool enables early identification of high-risk individuals to guide treatment intensification. Using shallow whole genome sequencing (sWGS) of plasma cell-free DNA from 190 LBCL patients, we developed and validated the ACT score (Aberrations, fragment Composition, Terminal motifs), a composite classifier integrating genomic and fragmentomic features from a single post-cycle-1 sample. ACT-positive patients had worse 2-year outcomes versus ACT-negative patients: time-to-progression 29% vs. 83% (HR 4.4, 95% CI 1.9 - 10.0; P = 1.5 x 10 - 4) and overall survival 47% vs. 93% (HR 8.7, 95% CI 3.0 - 25.4; P = 1.8 x 10-6). ACT score was independently prognostic of the International Prognostic Index, and their combination identified the highest-risk patients. Unlike mutation-based approaches, this assay requires neither tumor tissue, germline control nor a baseline plasma sample. Built on open-source tools and sWGS, the ACT score offers a feasible scalable strategy for early risk stratification in aggressive LBCL.

Background: Severe cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) are major dose-limiting toxicities of chimeric antigen receptor (CAR) T-cell therapy. Existing pre-infusion biomarkers offer modest discrimination, motivating non-invasive alternatives. Methods: We prospectively enrolled 26 patients with relapsed/refractory large B-cell lymphoma receiving axicabtagene ciloleucel. Pre-infusion (day -1) exhaled breath samples were analyzed by gas chromatography-mass spectrometry for 40 volatile organic compounds (VOCs). Candidates with univariate AUC > 0.65 for severe (grade >=2) CRS or ICANS were carried forward to sensitivity-maximization-at-given-specificity with LASSO regularization (SMAGS-LASSO), which selected separate panels for each outcome. Model performance was assessed by leave-one-out cross-validation with permutation p-values and Harrell bootstrap optimism correction. Results: The 4-VOC CRS panel (heptanal, benzaldehyde, 2-butanone, ethylbenzene) achieved LOOCV AUC 82.5% (80% sensitivity at 88% specificity) and the 3-VOC ICANS panel (nonanal, allyl methyl sulfide, levomenthol) achieved AUC 86.3% (67% sensitivity at 86% specificity). By tertile, severe CRS occurred in 8/9 (89%) high-risk versus 2/9 (22%) low-risk patients (Cox HR 6.82, 95% CI 1.41-32.9, p=0.017) and severe ICANS occurred in 8/9 (89%) versus 2/9 (22%) (HR 8.28, 95% CI 1.73-39.6, p=0.008). Each 1-SD score increase corresponded to a 3.80-fold higher hazard of severe CRS (p<0.001) and 4.36-fold higher hazard of severe ICANS (p<0.001). In head-to-head comparison, the 3-VOC ICANS panel outperformed the modified Endothelial Activation and Stress Index (mEASIX) (delta-AUC +0.36, DeLong 1-sided p=0.008). The 4-VOC CRS panel had numerically higher AUC than mEASIX (delta-AUC +0.19, p=0.150). Conclusions: Pre-infusion exhaled breath VOC panels stratify CAR T-cell recipients by severity and timing of severe CRS and ICANS, providing a non-invasive complement to existing serum biomarkers. Multi-institutional validation is warranted.

Background: Non-invasive diagnosis, reliable recurrence surveillance remain critical unmet needs in gliomas. Glioma induces profound systemic immune alterations despite its anatomical confinement to the central nervous system. Circulating immune cells, particularly monocytes, are key mediators of tumor-host crosstalk and may retain tumor-induced transcriptional imprints. However, their potential clinical utility as blood-based biomarkers for detection and monitoring, remain largely unexplored. Methods and findings: In this study, we performed integrated single-cell RNA sequencing of blood immune cells and demonstrated that circulating CD14+ monocytes are significantly expanded in glioma patients, exhibiting features of differentiation arrest and increased transcriptional plasticity. These cells harbor glioma-specific molecular signatures distinct from those observed in healthy controls and patients with other tumors. Leveraging these findings, we developed an ensemble machine learning diagnostic model based on transcriptomic profiles of circulating CD14+ monocytes (training cohort, n=107), which achieved a mean area under the receiver operating characteristic curve (AUC) of 0.971 during cross-validation. In an independent cohort of 567 participants, the model maintained high diagnostic accuracy, yielding an AUC of 0.877 for distinguishing glioma from controls and other tumors. And it achieved a recurrence detection AUC of 0.969 in 51 postoperative samples. Moreover, in a prospective follow-up study involving 30 glioma patients, lower model-derived scores of postoperation were significantly associated with prolonged progression-free survival (log-rank test, P=0.043), supporting its prognostic utility. Conclusion: We demonstrate circulating CD14+ monocytes undergo glioma-specific transcriptional reprogramming, generating systemic tumor-associated signal captured via transcriptomic profiling. This blood-based diagnostic model provides non-invasive, scalable approach for glioma detection, recurrence surveillance, outcome prediction.

While prostate cancer (PC) is defined as immunologically cold, limiting the efficacy of immune checkpoint inhibitors, therapeutic vaccination targeting tumor-associated antigens represents an attractive strategy to promote disease control in low volume metastatic patients. The UV1 cancer vaccine is based on immunization with tripeptide fragments from human telomerase reverse transcriptase (hTERT) and a phase II clinical trial demonstrated induction of robust T cell response in men with de novo metastatic castration-sensitive prostate cancer (mCSPC). Comparison with long-term survival data of non-metastatic CSPC patients as reference showed that despite metastatic disease at diagnosis, UV1-treated patients who mounted an early vaccine-induced immune response achieved progression-free and overall survival comparable to non-metastatic patients. We examined biological determinants of clinical benefit following UV1 vaccination including tumor transcriptome and T cell receptor (TCR) profiling from circulating and tissue resident T-cells of the 22 men enrolled. Analysis of diagnostic and post-UV1 treatment biopsies revealed that low baseline exhaustion of T cells and higher CD8+ T cell abundance are associated with early immune response to the vaccine and longer survival. Moreover, we identified specific TCR motifs relative to early responders, that can indicate potential benefit from UV1 vaccination. These findings indicate that baseline intratumoral T cell exhaustion state and repertoire shape responsiveness to hTERT vaccination and long-term outcome. Overall, our study underlines how baseline immune profiling may be used as a companion biomarker to predict mCSPC patients most likely to benefit from therapeutic vaccination.

Importance: While gut dysbiosis is known to impair response to immune checkpoint inhibitors (ICIs), the relative clinical impact of antibiotic timing (pre- vs. post-ICI initiation) remains unclear. Objective: To evaluate whether antibiotic timing differentially influences overall survival (OS) in a large, multi-institutional pan-cancer cohort. Design, Setting, and Participants: This retrospective cohort study utilized deidentified electronic health record data from six academic medical centers within the University of California Health system. We included 21,108 adults with any malignancy who received PD-1, PD-L1, or CTLA-4 inhibitors between January 2014 and December 2024. Exposures: Antibiotic exposure windows were categorized as pre-only (-60 to -1 days), post-only (+1 to +60 days), both windows, or none. Main Outcomes and Measures: The primary outcome was overall survival (OS) calculated from the first ICI dose. Multivariable Cox proportional hazards models adjusted for demographics, tumor type, line of therapy, and baseline health indicators (albumin, NLR, and recent hospitalization). Results: Among 21,108 patients, 17.3% had pre-only exposure, 13.3% had post-only exposure, and 60.6% had no exposure. In the multivariable model, post-only exposure (HR, 1.27; 95% CI, 1.20-1.35) and combined pre- and post- exposure (HR, 1.31; 95% CI, 1.23-1.40) were significantly associated with higher mortality. Pre-only exposure was not significantly associated with OS (HR, 1.04; 95% CI, 0.99-1.10). Subgroup analyses by tumor type showed consistent trends across major malignancies, including head and neck (Post HR, 1.46) and renal cell carcinoma (Post HR, 1.26). Conclusions and Relevance: In contrast to some smaller studies, this large-scale analysis indicates that antibiotic exposure after ICI initiation carries a greater risk than exposure prior to treatment. These findings highlight the need for rigorous antibiotic stewardship strategies specifically during the early phases of immunotherapy treatment.

Background: CD8+ tumor-infiltrating lymphocytes (TILs) are established prognostic markers in colorectal cancer, yet the clinical significance of CD103+CD8+ tissue-resident memory-like (TRM-like) T cells in locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (NACRT) remains unknown. Methods: We quantified CD8+ and CD103+CD8+ T-cell densities in stromal and intratumoral compartments of post-NACRT resection specimens from 40 LARC patients using Cu-Cyto, a deep learning-based imaging cytometry platform. Associations with survival, pathological response, and adjuvant chemotherapy (AC) were examined. Treatment-induced T-cell dynamics were assessed in paired pretreatment biopsies and post-NACRT resections (n = 9). Results: High stromal CD103+CD8+ density independently predicted better 5-year RFS (67.4% vs. 12.1%, p < 0.001) and OS (80.0% vs. 26.6%, p = 0.016); intratumoral density showed no prognostic significance. Pathological response correlated with stromal CD8+ but not CD103+CD8+ density. Paired analysis revealed a selective non-expansion of the CD103+ subset: stromal CD8+ T cells increased significantly after NACRT while CD103+CD8+ density remained unchanged. AC may preferentially benefit patients with low stromal CD103+CD8+ density. Conclusions: Stromal CD103+CD8+ T-cell density is a robust independent prognostic biomarker in rectal cancer after NACRT that appears to reflect pre-existing rather than treatment-induced immunity. Given its stability across NACRT, pretreatment biopsy assessment may provide equivalent prognostic information, with potential implications for patient stratification before treatment initiation.

Background: The development of personalised mRNA cancer vaccines holds considerable promise for oncology, yet a significant translational gap persists between neoantigen identification and the selection of therapeutically impactful targets. Current approaches predominantly prioritise human leukocyte antigen (HLA) binding affinity and immunogenicity, often overlooking the systems-level biological context of the target. This can inadvertently favour immunogenic but biologically peripheral peptides that exert limited influence on tumour signalling networks, thereby constraining vaccine efficacy. Furthermore, mRNA therapeutics must satisfy additional design requirements, including favourable codon usage and favourable secondary-structure stability, which directly affect in vivo translation and half-life. A unified computational framework that integrates neoantigen discovery with network biology is therefore critically needed. Results: Here, we present PimRNA, a Priority index (Pi)-centric computational medicine framework that bridges this gap by unifying neoantigen identification, mRNA sequence optimisation, and gene interaction network analysis. First, high-confidence tumour-specific HLA class I and II neoantigenic peptides are identified from paired tumour-normal genomic and tumour transcriptomic data using NeoDisc. Second, the coding sequences of these peptides are optimised for stability and translational efficiency with LinearDesign, yielding a core set of neoantigen-encoding mRNAs. Third, a random walk with restart algorithm is applied to a knowledgebase of gene interactions to identify peripheral genes exhibiting significant network connectivity to core genes, generating a gene-predictor matrix in which each gene is assigned an affinity score reflecting its network proximity to immunogenic neoantigens. These scores are consolidated into a single, unified priority rating (0-5) for each gene, followed by subnetwork analysis that reveals therapeutically relevant gene modules. Application of PimRNA to breast cancer and melanoma datasets demonstrates that it successfully selects high-confidence immunogenic neoantigen candidates embedded within biologically meaningful tumour-specific networks. Conclusion: PimRNA provides a systems biology foundation for mRNA vaccine design, moving beyond isolated immunogenicity to prioritise targets that are both highly presented and central to tumour-relevant biological networks. This framework offers a generalisable strategy for the rational discovery and prioritisation of mRNA therapeutics, significantly advancing the field of computational medicine towards personalised cancer vaccines.

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.

Importance Prognostic tools beyond staging are needed to guide treatment and counseling in head and neck squamous cell carcinoma (HNSCC). Objective To develop and externally validate a machine learning model predicting survival in advanced HNSCC using routinely collected clinical and biomarker data. Design, Setting, and Participants Retrospective, multi-institutional cohort study including 2,385 patients with stage III-IV HNSCC diagnosed from 2012-2022 in the University of California Health Data Warehouse (UCHDW). Patients were randomly split into training (n = 1,908) and test (n = 477) sets. Partial external validation used 7,749 patients from the Surveillance, Epidemiology, and End Results (SEER) registry (2010-2020). Exposures Demographic, tumor, treatment, comorbidity, and biomarker variables recorded at or before diagnosis. Main Outcomes and Measures The primary outcome was all-cause mortality within 70 months. Cox proportional hazards models included all predictors. Discrimination was assessed with Harrell's concordance index (C-index), calibration with predicted vs observed survival, and stratification with Kaplan-Meier curves. A Random Survival Forest (RSF) was trained for benchmarking and interpretability using Shapley Additive exPlanations (SHAP). Results Among 2,385 patients in UCHDW (median age, 63 years; 29.0% mortality), the Cox model achieved a C-index of 0.735 in the internal test set. Risk quartiles showed clear separation on Kaplan-Meier curves (log-rank p < 0.0001). In the SEER cohort (n = 7,749), where only demographic, staging, subsite, and treatment variables were available, the reduced Cox model achieved a C-index of 0.688, with calibration showing modest underestimation of survival in high-risk groups. Age, T stage, Charlson Comorbidity Index, neutrophil-to-lymphocyte ratio, and platelet count were among the strongest predictors, while surgery was associated with improved survival. The RSF achieved a C-index of 0.758 internally, with SHAP highlighting nonlinear effects of albumin, BMI, and inflammatory markers. Conclusions and Relevance A machine learning model using routine clinical and biomarker data demonstrated good prognostic performance in advanced HNSCC, with partial external validation. Such approaches may support individualized survival estimates, risk stratification, and treatment discussions, but broader validation is required before clinical adoption.

Background: Reirradiation (reRT) is increasingly offered following progression in diffuse intrinsic pontine glioma (DIPG) and diffuse midline glioma (DMG), though optimal patient selection remains a challenge. This study evaluated clinical outcomes after reRT in a contemporary cohort of patients with DIPG/DMG. Methods: Patients <26 years old with DMG/DIPG treated with radiation therapy between 2011-2025 were retrospectively reviewed. Primary endpoints included overall survival (OS2) and progression-free survival (PFS2), measured from first progression, and change in neurologic symptoms after reRT. Survival was estimated using Kaplan Meier methods, with Cox proportional hazards modeling for prognostic factors. Results: Fifty eight patients were included; 37 (63.8%) underwent reRT. Tumors were predominantly pontine (74.1%). ReRT was associated with improvement in motor function (51.4% vs. 9.5%, p=0.002), cranial nerve function (29.7% vs. 4.8%, p=0.044), and gait ataxia (35.1% vs. 9.5%, p=0.059). Median OS2 and PFS2 were improved with reRT (OS2: 9.67 vs. 2.57 months, p<0.001; PFS2: 5.63 vs. 1.57 months, p<0.001). OS2 was independently associated with reRT (HR 0.27, p<0.0001), pontine location (HR 2.94, p=0.004), and steroid use at progression (HR 4.12, p=0.001). PFS2 was independently associated with reRT (HR 0.23, p < .0001) and distant pattern of failure (HR 2.83, p=.037). Among reRT patients, non-pontine location was associated with improved OS2 (p=0.02), and local failure was associated with improved PFS2 (p=0.003). Conclusion: ReRT was associated with neurologic improvement and prolonged survival. Patients with non-pontine tumors or local-only failure might derive the greatest benefit. Prospective studies are warranted to define optimal dose/fractionation and refine patient selection.

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.

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.