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PubMed2026

Mortality of Individuals With PRNP Variants Associated With Prion Disease in the United States, 1998-2024.

BACKGROUND AND OBJECTIVES: To characterize the survival of individuals with pathogenic PRNP variants-including to estimate annual hazards, to judge the accuracy of previously reported survival data, and to evaluate the utility of public record searches in determining vital status. METHODS: In this single-center cohort study, we gathered data on individuals who received positive antemortem PRNP genetic tests at the US National Prion Disease Pathology Surveillance Center (NPDPSC), including both diagnostic tests in symptomatic individuals, and predictive tests in asymptomatic individuals. Genetic test and autopsy results were queried from the NPDPSC database, and public record searches were conducted using online tools. RESULTS: Four hundred four individuals received positive genetic test results. Of 206 cases symptomatic at the time of genetic testing, 188 are likely now deceased based on typical disease duration for their genetic variants. Combined autopsy and public record searches in combination confirmed 174 of these deaths, for an estimated 92.6% sensitivity. We evaluated the age-dependent penetrance of the reportedly highly penetrance variants D178N and E200K and the reportedly low-penetrance variant V210I. Among 99 initially asymptomatic individuals with the pathogenic E200K variant, more than 936 person-years of follow-up, 18 deaths were observed, significantly fewer than 27.4 expected according to life tables based on retrospective data. The age-dependent penetrance of E200K calculated from these longitudinal data was significantly lower than that from retrospective data, with 69% penetrance by age 80 and a median age at death of 75. For the pathogenic D178N variant, the median age at death was 57, which was numerically later, but not significantly different from, that seen in retrospective data. For V210I, just 2 deaths occurred, both after age 90, consistent with minimal penetrance. DISCUSSION: Our data support high penetrance of PRNP D178N and E200K variants and low penetrance of V210I. For E200K, the age at onset distribution appears to be shifted slightly later, and lifetime risk slightly lower, than previously reported. Autopsy data and public death records in combination were sensitive and concordant for determining long-term outcomes, but additional prospective data should be gathered to support future preventive trials.

Journal Article↗

PubMed2026

Umbilical Cord-Derived Cell-Based Interventions for Bronchopulmonary Dysplasia and Related Complications in Preterm Infants: A Bayesian Sparse-Data Meta-Analysis.

Bronchopulmonary dysplasia (BPD) is a major complication of prematurity with limited disease-modifying therapies. We evaluated umbilical cord-derived cell-based interventions for BPD and related complications in preterm infants. This Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020-based systematic review and meta-analysis were registered in PROSPERO. PubMed, Cochrane Library, Web of Science, CNKI, and Wanfang were searched from inception to June 14, 2026. Comparative clinical studies of umbilical cord-derived cell-based interventions in preterm infants at risk of or diagnosed with BPD were included. Outcomes included BPD, BPD severity, death, persistent pulmonary hypertension of the newborn (PPHN), patent ductus arteriosus (PDA), intraventricular hemorrhage (IVH), necrotizing enterocolitis (NEC), retinopathy of prematurity (ROP), late-onset sepsis (LOS), and adverse events (AEs). Bayesian random-effects meta-analysis used a binomial-normal hierarchical model to estimate pooled odds ratios (ORs), 95% credible intervals (CrIs), prediction intervals, and heterogeneity. Twelve studies were included. Umbilical cord-derived cell-based interventions showed a possible protective effect on overall BPD (OR, 0.48; 95% CrI, 0.14-1.20). Stronger associations were observed for severe BPD (OR, 0.17; 95% CrI, 0.01-0.85), moderate or severe BPD (OR, 0.28; 95% CrI, 0.09-0.70), and ROP stage ≥3 (OR, 0.17; 95% CrI, 0.02-0.65). No conclusive benefit or harm was observed for death, PPHN, PDA, IVH, NEC, or LOS. No treatment-related serious AEs were identified. However, prediction intervals were generally wide, and the certainty of evidence was low to very low for most outcomes. Umbilical cord-derived cell-based interventions may reduce the risk of moderate or severe BPD in preterm infants, with an additional potential benefit for ROP stage ≥3. Current evidence remains limited, and larger randomized trials with standardized outcomes and long-term follow-up are needed.

Humans↗

PubMed2026

Making waves: toward systems-level interpretation of hormonal and endogenous biomarkers in wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) has proven invaluable for population health monitoring, most notably during the COVID-19 pandemic. Yet current WBE largely relies on exogenous markers such as drugs, pathogens, and their metabolites, limiting surveillance to what communities are exposed to. We argue for expanding WBE towards endogenous biomarkers, particularly hormones, which provide insights into physiological stress, metabolic function, and endocrine activity. Hormone-based WBE offers new opportunities to capture population-level biological responses to societal and environmental stressors, disasters, and chronic disease burdens at the community scale. This perspective outlines a systems-level framework for integrating hormonal signals in wastewater with clinical data, behavioral indicators, environmental factors, and digital markers to support more robust and context-aware public health surveillance. We highlight key technical considerations, interpretive challenges, and opportunities for translational pilot studies. By moving beyond exposure tracking toward more integrated interpretation of biological responses, hormone-informed WBE may contribute to more resilient, inclusive, and actionable public health infrastructure.

Humans↗

PubMed2026

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence↗

PubMed2026

Plasma proteomic profiling characterizes candidate biomarkers of perimesencephalic non-aneurysmal subarachnoid hemorrhage.

OBJECT: This study aims to explore the plasma proteomic profiles of angiographically confirmed pmSAH and aSAH, and to identify candidate protein biomarkers for discriminating these subtypes on a biological level. METHODS: The differentially abundant proteins of plasma samples from patients with pmSAH (n = 30) and aSAH (n = 30) were analyzed by data-independent acquisition proteomics, and candidate biomarkers were screened. RESULTS: 291 candidate biomarkers were obtained that could be used to distinguish pmSAH patients from aSAH patients, among which 76 were upregulated and 215 were downregulated in pmSAH. Subsequently, the 10 candidate biomarkers were validated by enzyme-linked immunosorbent assay in a validation cohort of 72 subjects. ORM1, ORM2, HP and NMNAT1 were specifically down-regulated in the pmSAH group, while ANP32A was specifically up-regulated in the pmSAH group. FGL2 was specifically up-regulated in the aSAH group. The combined model of ORM2, HP and ANP32A had the best discriminative power (AUC = 0.880). CONCLUSIONS: This study identified ORM2, HP, and ANP32A as candidate biomarkers reflecting biological differences between pmSAH and aSAH. SIGNIFICANCE: Although some proteomic studies have analyzed aneurysmal subarachnoid hemorrhage, to date, there have been no reports on the circulating proteomic analysis of pmSAH. Comparative analysis of the circulating proteomic differences between pmSAH and aSAH may not only help understand the causes of pmSAH, but also contribute to a deeper understanding of mechanisms showing how pmSAH differs from the formation and rupture mechanisms of intracranial aneurysms.

Humans↗

PubMed2026

Methods for defining equity-stratifying variables: a systematic review of validation studies.

BACKGROUND AND OBJECTIVE: Disease burden is often disproportionally higher among those who are socially disadvantaged by factors defined in the PROGRESS-Plus framework (ie, Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital, with "Plus" covering features like age and disability). The accuracy and applicability of case definitions to identify these variables from administrative and clinical health data are unknown. We conducted a systematic review to explore how equity-stratifying variables, as categorized by the PROGRESS-Plus framework, have been defined and validated in epidemiologic studies using administrative health, population-level, or electronic health record (EHR) data. METHODS: Medline, EMBASE, CINAHL, Web of Science, and Google Scholar were searched from the inception of the databases to 2024 for validation studies of equity-stratifying variables in adults using administrative health datasets, health registries, or EHR data. Titles and abstracts, followed by relevant full-text articles, were screened in duplicate by two reviewers for eligibility. The data sources utilized, algorithms employed, and their associated performance measures were extracted and synthesized from included studies. Given substantial heterogeneity in study design, equity-stratifying variable definition, and performance metrics, meta-analysis was not possible. RESULTS: Of the 9099 unique citations screened, 188 full texts were reviewed and 116 were included in this review. Most studies were published between 2019 and 2024 (n = 64, 55%) and were validation studies of race/ethnicity definitions that used race/ethnicity codes or surname list algorithms (n = 66, 57%). No studies examined religion. Regarding the reported performance measure estimates, the race/ethnicity/culture/language equity-stratifying variables category had the largest variability across sensitivity, positive predictive value (PPV), and Cohen's Kappa. Occupation validation studies had the lowest variation in sensitivity and PPV. CONCLUSION: Despite an increasing number of publications reporting on the validation of equity-stratifying variables relevant to the PROGRESS-Plus framework, performance measures varied widely across studies. The significant heterogeneity in equity-stratifying variable definitions and methods used to validate them support the need for further rigorous validation of equity-stratifying variables in administrative and clinical health data. PLAIN LANGUAGE SUMMARY: Disease burden is often higher in people who experience financial hardships, lower level of education, discrimination due to race/ethnicity, and unstable housing. These social factors can be considered health equity factors and are important for understanding health inequalities. Health researchers often use large datasets, such as hospital or electronic health records (EHRs), to study these health equity factors. However, it is not clear how accurately these data sources capture information about people's social circumstances and how these factors are defined. In this study, we reviewed existing research to understand how health equity factors have been defined across health data sources and how accurate they are at measuring aspects of health equity and social disadvantage. Of the more than 9000 studies we identified, we included 116 that met our criteria for this systematic review. Most included studies focused on identifying race and ethnicity, often using codes or surname-based methods. We found that the accuracy of these methods varied widely across studies, meaning results may not always be reliable or comparable. Overall, our findings show that there are inconsistencies in how social factors are defined and measured in health data. This makes it difficult to fully understand and address health inequalities using routinely collected health data. More work is needed to develop and validate better quality and more consistent methods for capturing these important social factors.

Humans↗

PubMed2026

Upscaling Genotyping by Amplicon Sequencing With GBAS-GUI.

Genotyping by amplicon sequencing (GBAS) is a relatively low-cost approach for generating genotypic data compared with established genomic methods, making it highly scalable and particularly suitable for large-scale genetic monitoring projects. However, most existing analytical pipelines are either marker-specific, insufficiently scalable, or lacking efficient data management systems for the long-term integration of genotypic information, limiting the full potential of GBAS. Here, we address this gap by introducing GBAS-GUI (https://github.com/sonnenbe-dot/GBAS-GUI), a pipeline capable of generating GBAS-based genotypic data for a wide variety of loci at scale. GBAS-GUI integrates a graphical user interface with multiple checkpoints to improve accessibility and robustness. It implements multiprocessing architecture and a relational database that links genotypic data with associated sample metadata to enhance scalability and data management. The pipeline further enables marker screening through automated calculation of polymorphism information content (PIC) and implements a strategy to recover homologous genotypic information from paralogous loci with non-overlapping amplicon length ranges. Using multiple empirical datasets, we demonstrate substantial improvements in processing speed, database management and handling artefacts related to co-amplification of unspecific regions and duplicates of the same genomic region. We further show that incorporating the full sequence information captured by an amplicon increases marker information content beyond what is achievable with length-based genotyping alone and expands the analytical versatility of GBAS. Overall, GBAS-GUI provides a robust, scalable and versatile framework that unlocks the potential of GBAS for large-scale population genetic and phylogeographic studies.

Genotyping Techniques↗

PubMed2026

A 20-Y Analysis of Motorcycle Trauma After Helmet Law Repeal.

INTRODUCTION: After Arkansas repealed its universal motorcycle helmet law in 1997, helmet use decreased and motorcycle-related injuries and fatalities increased. Long-term clinical and population-level impacts of this policy change remain incompletely characterized. This study integrates statewide crash and fatality data with trauma center data to evaluate trends in helmet use, injury severity, and mortality at scene and hospitalization. METHODS: We retrospectively reviewed motorcycle-related admissions and emergency department deaths at the state's only adult level I trauma center from 2004 to 2023 across three periods: 2004-2006, 2013-2015, and 2021-2023. Demographics, helmet use, injury severity, and outcomes were assessed. Logistic regression evaluated associations between helmet use, severe head injury (Abbreviated Injury Scale ≥3), and inhospital mortality. Fatality data were obtained from the National Highway Traffic Safety Administration, and crash-level data (2015-2023) were obtained from the State Department of Transportation. RESULTS: Among 1104 trauma admissions, annual admissions nearly tripled over time, with nonhelmeted riders representing 64%-72%. Helmet use was independently associated with lower odds of severe head injury (odds ratio 0.48, P < 0.001). Nonhelmeted riders had higher on-scene fatality risk (relative risk 1.21). Severe head injuries increased and were strong predictors of inhospital mortality. Population-adjusted motorcycle fatality rates rose from 2.34 to 3.18 per 100,000 residents by 2021-2023. CONCLUSIONS: Motorcycle fatalities and severe head injuries increased during the postrepeal period and were associated with helmet nonuse and severe head trauma. Clinical and statewide data show consistent associations among helmet nonuse, severe head injury, and prehospital and in-hospital mortality, highlighting helmet use as a target for injury prevention policy.

Acute brain injury↗

PubMed2026

Quo vadis, BGA? A collaborative EDNAP exercise on the challenges and progress in forensic biogeographical ancestry inference.

There is a broad consensus that forensic tests for the prediction of externally visible characteristics (EVC) and analysis of biogeographic ancestry (BGA) of an individual are technically reliable. However, interpretation of the results and population-specific genotype distribution patterns remains challenging. EVC and BGA analyses provide valuable information for population genetics studies and as investigative leads for criminal cases, as well as for historical and contemporary identification tests. However, inaccurate or incorrect predictions, for example, from subjective bias in the interpretations made, have the potential to misdirect police investigations. The legal situation regarding EVC and BGA testing varies by country: ranging from countries where it is explicitly prohibited, to those without specific regulations on biogeographic ancestry prediction, and others that have already enacted laws governing its use. The reluctance to utilize these analyses is not only due to legal restrictions and data protection concerns, but also to initial limited sets of sufficiently comprehensive forensic DNA assays. Forensic BGA marker panels typically contain up to ∼300 SNPs. This relatively small number of genetic markers, along with limited reference population data, complicates the interpretation of results from donors of unknown origin. This paper presents the results of a collaborative EDNAP study, which, for the first time, evaluated the approach to reporting EVC and BGA data between international laboratories. For the study, DNA from nine individuals with self-reported ancestry was collected and analysed using various forensic panels differing in the number and composition of ancestry-informative markers genotyped, comprising: the Precision ID mtDNA Whole Genome Panel, the VISAGE Basic Tool and the VISAGE Enhanced Tool for Appearance and Ancestry Prediction, and the Ion AmpliSeq™ PhenoTrivium Panel. To ensure full data protection, all SNP genotypes and uniparental marker haplotypes obtained were not shared with third parties. Instead, the genetic data were analysed using a range of commonly used population analysis software packages. These analysis outcomes were then distributed to twelve European forensic laboratories (both academic and law enforcement institutions), who were asked to prepare reports based on their interpretation of the phenotypes and ancestry they inferred from the analysis data. A questionnaire sent alongside the genetic information, aimed to evaluate which difficulties were encountered by the participants in processing the BGA analysis data they were given.

Humans↗

PubMed2026

Infant Dietary Patterns and Early Childhood Weight Outcomes: A Secondary Analysis from the Starting Early Program Trial.

BACKGROUND: The Starting Early Program (StEP) promotes healthy nutrition during early life and leads to healthier child weight, but whether dietary patterns contribute to weight or mediate StEP weight outcomes has not been studied. OBJECTIVES: This secondary analysis identified infant dietary patterns in StEP, determined associations between dietary patterns and child weight outcomes, and examined whether dietary patterns mediated the relationship between StEP and child weight. METHODS: Data were from 377 mother-infant dyads in a randomized trial testing the efficacy of StEP. Dietary patterns at 10 months were identified using latent class analysis. Child weights were abstracted from medical records at 12, 24, and 36 months. Associations between infant dietary patterns and weight-for-age z-score (WFAz) and likelihood of being classified as overweight (WFA ≥85th percentile) were assessed using linear and logistic multivariable regression models. Mediation was used to assess intervention effects on WFAz via impacts on infant dietary patterns. RESULTS: Four classes of infant dietary patterns were identified: Breastfed-High variety, Formula fed-High variety, Formula fed-Low variety, and Mixed fed-Low variety. Compared to the Breastfed-High variety class, infants in the Formula fed-Low variety class had higher WFAz and were more likely to be classified as overweight at 24 and 36 months. Participation in StEP increased membership in Breastfed-High variety, which mediated the association between StEP and lower WFAz at 24 months. CONCLUSIONS: Infant dietary patterns were identified, and some were associated with child overweight. StEP was associated with a dietary pattern most consistent with guidelines, which mediated intervention effects on child weight.

Humans↗

PubMed2026

Cisplatin-Induced Hearing Loss Prevention With Intratympanic Therapy Systematic Review and Meta-Analysis.

INTRODUCTION: Cisplatin-induced hearing loss (CIHL) is a well-described, long-term consequence of cisplatin treatment for malignancy. Intratympanic (IT) injections have been trialed to prevent CIHL in humans. To provide clarity on which agents have been studied through IT injection and to review their efficacy for hearing loss prevention, we performed a systematic review and meta-analysis. DATA SOURCES: OVID Medline, Embase, Web of Science, and Cochrane Library were queried. METHODS: Databases were searched in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Prospective randomized trials were included, and a systematic review was performed for all studies. Demographic, audiometric, and therapeutic data were collected. Random-effects models were used to compare across studies, and subgroup analyses were performed for each IT agent. RESULTS: The initial database search yielded 1017 articles, which were screened according to inclusion and exclusion criteria. Ten studies were identified, involving a total of 284 patients. Studies included data on IT dexamethasone, IT N-acetylcysteine (NAC), and IT sodium thiosulfate (STS). Pooled analysis across all agents and frequencies did not reveal a significant difference in hearing thresholds between treatment and control ears [prediction interval [-3.77, 3.20], negative favors treatment). Subgroup analysis of IT dexamethasone [-1.74, 3.80] and IT NAC [-1.02, 4.64] also did not demonstrate significant differences. STS data were not amenable to pooled analysis; however, one study demonstrated a significant decrease in ASHA-defined ototoxicity (40% vs. 85%, P =0.0027). CONCLUSIONS: To date, no IT agent has consistently prevented CIHL, although limited data suggest that IT STS may decrease ototoxicity. More trials are necessary to fully elucidate these effects.

Humans↗

PubMed2026

Dengue and chikungunya vaccines past, present and future: implications for travelers.

PURPOSE OF REVIEW: Novel vaccines for dengue and chikungunya viruses offer new prevention options against two globally important arboviral diseases. This review summarizes recent developments in vaccine licensure, implementation, real-world experience and research priorities, with emphasis on implications for both endemic populations and travelers. RECENT FINDINGS: Of the three live-attenuated dengue vaccines licensed to date, TAK-003 is authorized in >40 countries and Butantan-DV in Brazil, while manufacturing of CYD-TDV is discontinued. Long-term and postmarketing data continue to refine understanding of serotype-specific protection, waning immunity, and rare adverse events.For chikungunya, two single-dose vaccines are licensed-a live-attenuated vaccine (VLA1553) and virus-like particle vaccine (PXVX0317). Uptake is guided by emerging safety and effectiveness data, with each platform offering potential advantages in different settings.Further data on long-term protection, safety, effectiveness, use in vulnerable populations and integration into outbreak management and immunization systems is anticipated. SUMMARY: Dengue and chikungunya vaccines are increasingly being used in immunization programs and pretravel consultations. Further real-world data are needed-particularly for seronegative dengue vaccine recipients and older, immunocompromised or medically at-risk adults. Research priorities include developing single-dose, nonlive dengue vaccines suitable for high-risk groups, understanding long-term chikungunya vaccine performance, and exploring broader flaviviral or pan-arboviral platforms.

Humans↗

PubMed2026

Identification of CD55 as a downstream factor of EP4 receptor signaling in colorectal cancer cells.

Prostaglandin E2 (PGE2) signaling through the E-type prostanoid 4 (EP4) receptor has been implicated in the pathophysiology of colorectal cancer (CRC). We herein identified decay-accelerating factor, also known as CD55, as a novel CRC-associated downstream factor of the EP4 receptor. The integration of transcriptomic profiling of PGE2-stimulated HCA-7 human colon cancer cells with analyses of cancer genomic databases predicted CD55 as a potential EP4 receptor-regulated target. Inhibitor-based experiments showed the induction of CD55 after a PGE2 stimulation required the EP4 receptor and Gi protein in HCA-7 cells, whereas protein kinase A signaling was dispensable. In combination with a toxicogenomic database analysis, p38 mitogen-activated protein kinase (MAPK) was identified as the predominant effector connecting the EP4 receptor to CD55 upregulation. A single-cell RNA-seq re-analysis of human CRC tissues revealed CD55 upregulation and p38 MAPK-related gene set enrichment in epithelial cells expressing the EP4 receptor, suggesting that this induction mechanism may operate in a subset of epithelial cells in clinical specimens. Collectively, these results delineate a PGE2/EP4 receptor/Gi protein/p38 MAPK signaling axis that induces CD55 expression in HCA-7 cells and epithelial tumor cells, provide new mechanistic clues for understanding the regulation of complement regulatory molecule CD55 expression by prostaglandin signaling.

Humans↗

PubMed2026

A genome-wide coverage-based pipeline for the identification of host-derived candidate DNA biomarkers from cell-free blood.

We have created a new data-analysis pipeline for the discovery of host-specific candidate DNA biomarkers derived from sequencing data of cell-free blood. Unlike approaches that rely on specific molecular or genetic signatures, our method leverages the coverage distribution of cell-free DNA sequences mapped to a reference genome, applying statistical analyses to identify informative short genomic regions for biomarker discovery. The pipeline is applicable to diverse diseases and can be used to analyze cell-free DNA sequences from plasma or serum to identify candidate biomarkers that are characteristic of disease states in mammals. Core functionalities were developed in Java and integrated with open-source software tools for the preprocessing of raw sequencing data, complemented by Python scripts for the machine-learning analysis and statistical validation. The pipeline is designed for HPC use and users can access the pipeline through a Galaxy workflow, which offers a user-friendly web interface for input selection prior to execution and analysis progress monitoring. Performance tests, carried out using duplicate sets of COVID-19 samples and controls, showed linear scalability of execution time with an increasing dataset size, as well as a substantial reduction in execution time through parallelized computation, whereby each HPC node is used to process the data of one chromosome. Further statistical tests confirmed the quality of the pipeline's results by showing that the set of identified candidate biomarkers remained stable across varying dataset sizes.

Biomarkers↗

PubMed2026

Azithromycin-resistant Salmonella enterica Typhi with AcrB R717L/Q mutations in the United States.

BACKGROUND AND OBJECTIVES: Azithromycin is a critical oral treatment for typhoid fever caused by Salmonella enterica serovar Typhi (Salmonella Typhi), since XDR has rendered other first-line treatment options ineffective. Azithromycin resistance conferred by amino acid changes in AcrB, an AcrAB-TolC efflux pump component, represents an emerging public health concern. Leveraging phenotypic and genotypic data from U.S. Salmonella Typhi surveillance systems, this study describes the prevalence, phenotype and genomic epidemiology of Salmonella Typhi with AcrB mutations in U.S. patients since the first detection in 2015. METHODS: AST and WGS data of >3000 Salmonella Typhi isolates were used to identify all cases with an AcrB mutation in the United States (2015-2025). We calculated annual prevalence and MIC ranges. Phylogenetic analysis was used to contextualize U.S. cases of Salmonella Typhi with an AcrB mutation within all globally reported cases. RESULTS: While the prevalence of AcrB mutations in the United States is low (1.5%), it has risen significantly in recent years, from 0.2% in 2016-2022 to 2.2% in 2023-2025. This increase is predominantly driven by clonal expansion of existing strains circulating in South Asia. AcrB mutations do not reliably confer resistance to azithromycin (MIC ≥ 32 mg/L), complicating clinical interpretation. CONCLUSIONS: The prevalence of AcrB mutations in Salmonella Typhi is increasing in the United States, and likely globally, given that U.S. data function as an informal proxy for regions without routine surveillance infrastructure. Clinical outcomes data are needed to inform Salmonella Typhi treatment guidelines and potentially amend clinical breakpoints for azithromycin.

Journal Article↗

PubMed2026

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans↗

PubMed2026

Trends in demographic and health survey publications based on a bibliometric analysis.

BACKGROUND: The Demographic and Health Surveys (DHS) Program, launched in 1984, provides high-quality population health data that underpins a vast body of global health research. However, the scale and growth patterns of DHS-based publications remain underexplored, particularly as donor funding uncertainties threaten program sustainability. OBJECTIVE: We examine temporal trends in DHS-based research output from 1984 to 2025, quantifying growth patterns and publication delays to inform understanding of the program's global research expansion. METHODS: A systematic bibliometric review was conducted following PRISMA guidelines across PubMed, Scopus, Web of Science, Dimensions, Wiley, and CINAHL. Eligible peer-reviewed articles using DHS data between 1984 and 2025 were identified. Annual publication counts were analyzed, segmented regression identified growth inflection points, and timeliness was assessed by calculating lag between survey completion and publication. RESULTS: Over 10,000 DHS-based publications were identified. Annual output rose from isolated studies in the 1980s to several hundred annually by the 2010s. Segmentation analysis revealed two rapid growth phases: a 56-publications/year increase from 2004-2012, and a 71-publications/year increase from 2012 to 2024. Despite this growth, median lag from survey completion to publication remained approximately 5 years, with only a modest recent improvement (Kendall's τ =  -0.623, p < 0.001). CONCLUSION: DHS data have fueled exponential growth in global health research over four decades, confirming their vital role in evidence generation. However, persistent publication delays highlight the need to shorten the pathway from data collection to dissemination through strengthened research capacity in low- and middle-income countries. Sustained funding is essential to maintain this critical evidence source.

Bibliometrics↗

PubMed2026

Clinical outcomes of Epstein-Barr virus infection/reactivation following CAR-T cell therapy: A systematic review.

BACKGROUND: Epstein-Barr virus (EBV) infection or reactivation is an emerging but underrecognized complication following chimeric antigen receptor T-cell (CAR-T) therapy and is likely associated with treatment-induced immune dysregulation. Data regarding its clinical impact remain limited. OBJECTIVE: To evaluate the reported occurrence, clinical manifestations, and outcomes of EBV infection or reactivation in adults undergoing CAR-T therapy. METHODS: A systematic review was conducted in accordance with the PRISMA 2020 guidelines. PubMed, Embase, and Cochrane CENTRAL were searched from inception to March 2025 for studies reporting EBV infection or reactivation after CAR-T therapy in adults. Due to limited and heterogeneous data, results were synthesized descriptively. RESULTS: Five studies comprising 80 patients were included (median age, 55 years; 52.6% male among patients with reported sex data [10/19]). Across the included studies, 11 EBV infection/reactivation events were identified among 80 described CAR-T recipients, representing 13.8% of the reported sample rather than a true incidence estimate. Among events with usable individualized timing data, the median interval from CAR-T infusion to EBV detection/reactivation was 9.8 months (approximate range, 1-44 months). Because EBV surveillance strategies and definitions were inconsistently reported across studies, this proportion should not be interpreted as a true incidence estimate. Four patients (36.4%) developed EBV-associated disease, including three cases of EBV-related lymphoproliferative disorder and one case of EBV-associated diffuse large B-cell lymphoma. Among seven patients with reported post-CAR-T treatment response, four achieved Complete Remission/ Continuous Complete Remission; treatment response should be interpreted separately from final survival status. Confirmed EBV-related mortality occurred in 2/11 patients with reported EBV infection/reactivation and in 2/4 patients with EBV-associated disease; all-cause mortality could not be reliably estimated because patient-level vital status could not be fully attributed to the EBV-reactivated subgroup. Reported toxicities predominantly consisted of low-grade cytokine-release syndrome; however, toxicity data were limited. CONCLUSION: Although infrequently reported, EBV infection or reactivation after CAR-T therapy may be associated with substantial morbidity and mortality among affected patients. However, the available evidence is limited by the small sample size, heterogeneous study designs, and inconsistent EBV surveillance practices.

Humans↗