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Three-dimensional source apportionment and quantitative characterization of horizontal and vertical transport fluxes of O3 and its precursors in the Beijing-Tianjin-Hebei region, China.

Persistent surface ozone (O3) pollution in the Beijing-Tianjin-Hebei (BTH) region is driven by coupled precursor emissions and multi-scale transport, yet its altitude-dependent transport and source contributions remain insufficiently quantified. Here we integrated the Weather Research and Forecasting and the Comprehensive Air Quality Model with Extensions with the Ozone Source Apportionment Technology and a quantitative transport-flux framework to characterize three-dimensional source apportionment and horizontal/vertical fluxes of O3, Volatile Organic Compounds‌ (VOCs), and Nitrogen Oxides (NOx) across dynamic meteorological scenarios. Simulations showed that VOCs and NOx were dominated by local emissions near the surface (73.61 %-82.18 %), whereas surface O3 was primarily controlled by regional transport, with local contributions of only 11.01 %-13.75 %. Notably, the transport dominance further strengthened with altitude, exceeding 93 % at 1.8 km. Industrial and transportation emissions together contributed more than 75 % of precursor emissions and account for approximately 80 % of O3 formation, while favorable/unfavorable meteorological years modulated long-range transport efficiency and the vertical distribution of contributions. Horizontal flux analysis highlighted three major pathways (Northwest-Southeast, Southeast-Northwest, and Southwest-Northeast), with Shijiazhuang serving as a critical pollutant "sink" across altitude layers. Vertical fluxes revealed an altitude transition near 600 m: net downward transport dominated below 600 m, whereas enhanced summer convection promoted upward transport above 600 m. These results support altitude-dependent, scenario-specific strategies for coordinated regional O3 mitigation in the BTH region.

Ozone

The glucagon and GLP-1 receptor dual agonist DD01 for metabolic dysfunction-associated steatotic liver disease and steatohepatitis (DD01-DN-02): 12-week results from a randomised, double-blind, multicentre, placebo-controlled, phase 2 trial.

BACKGROUND: Metabolic dysfunction-associated steatohepatitis (MASH) is a major public health problem arising in the context of metabolic syndrome and obesity. DD01 is a liver-targeted GLP-1 receptor and glucagon dual agonist being investigated for the treatment of metabolic dysfunction-associated steatotic liver disease (MASLD) and MASH. The DD01-DN-02 trial aimed to evaluate the efficacy and safety of DD01 in adults with MASLD or MASH; this initial analysis reports prespecified 12-week outcomes to assess early hepatic effects. METHODS: DD01-DN-02 is an ongoing, randomised, double-blind, multicentre, placebo-controlled, phase 2 trial conducted at 12 outpatient clinical sites in the USA. Adults aged 18-70 years with obesity or who were overweight (BMI &#x2265;25 kg/m2) were included in the study. Patients with MASLD or MASH underwent liver biopsy and MRI-proton density fat fraction (PDFF) and were eligible if liver fat content was 10% or higher with metabolic risk factors, or if the biopsy confirmed MASH with a non-alcoholic fatty liver disease activity score of at least 4. Participants were randomly assigned (1:1) to receive once-weekly subcutaneous DD01 40 mg or matched placebo over 48 weeks, dose-escalated over 2 weeks, using a centrally administered interactive response technology system. The randomisation sequence was computer-generated by an independent statistician. Participants, investigators, study staff, outcome assessors, and the sponsor were masked to treatment assignment. The primary endpoint was the proportion of participants having at least a 30% relative reduction in liver fat by MRI-PDFF at week 12, which was analysed in all randomly assigned participants receiving at least one dose of study drug or placebo. Safety analyses included all participants who received at least one dose of study drug. Missing primary endpoint data were handled using multiple imputation under a missing-at-random assumption. This trial is registered with ClinicalTrials.gov (NCT06410924) and is ongoing but closed to new participants. FINDINGS: Between June 13, 2024, and Jan 30, 2025, 67 eligible participants were enrolled, of whom 33 were randomly assigned to DD01 and 34 to placebo. The mean age of participants was 48&#xb7;4 years (SD 10&#xb7;6), 42 (63%) were female, 25 (37%) were male, 57 (85%) were White, and 52 (78%) participants had biopsy-confirmed MASH. At week 12, 25 (76%) of 33 participants receiving DD01 had a 30% or higher reduction in liver fat versus four (12%) of 34 participants receiving placebo (adjusted common odds ratio 28&#xb7;8 [95% CI 7&#xb7;2-115&#xb7;2]; adjusted relative risk 6&#xb7;3 [95% CI 2&#xb7;5-15&#xb7;9]; p<0&#xb7;0001). Treatment-emergent adverse events occurred in 28 (85%) of 33 participants receiving DD01 and 23 (68%) of 34 participants receiving placebo. The most common adverse events were nausea (18 [55%] of 33 participants assigned DD01; six [18%] of 34 participants assigned placebo), diarrhoea (nine [27%] of 33; six [18%] of 34), and vomiting (ten [30%] of 33; four [12%] of 34). Treatment-emergent adverse events led to treatment discontinuation in four (12%) of 33 participants in the DD01 group and one (3%) of 34 participants in the placebo group. Two (6%) treatment-emergent serious adverse events occurred in the DD01 group (abdominal pain and acute cholecystitis) and zero in the placebo group. No deaths occurred. INTERPRETATION: In this prespecified 12-week primary analysis, DD01 produced rapid reductions in liver fat compared with placebo, supporting further evaluation in long-term studies. FUNDING: D&D Pharmatech, Neuraly.

Humans

Influence of soil types with different soil-forming process on the qualitative and quantitative detection of microplastics by near-infrared spectroscopy.

Microplastics (MPs) have become a pressing global environmental threat, with soils-acting as sinks for MPs from multiple sources-gaining increasing attention. Near-infrared (NIR) spectroscopy offers a promising tool for MPs detection due to its rapid, non-destructive, and field-applicable features. Although previous studies have focused on the effects of individual soil components on the NIR detection performance of MPs, there is still a lack of systematic research on how the complex background-formed by the coupling of multiple physicochemical properties in natural soils-affects detection performance. This study focuses on soil types with different soil-forming processes, selected five representative agricultural soils to systematically evaluate how the combinations of physicochemical properties they represented affect the performance of NIR-based qualitative and quantitative analysis of MPs in soils. The results demonstrated that soil type significantly affected both the spectral response and detection performance of MPs. Brown Pedocals and Brown Earth exhibited clearer characteristic absorption and stronger linear responses, achieving higher identification accuracy under low (<1.5 %) or zero MPs concentrations and the best quantitative performance (R2 &#x2265; 0.988, prediction set root mean square error (RMSEP) &#x2264; 0.110 %). In contrast, Phaeozem and Red Soil were more prone to misclassification at low concentrations, while Fluvo-aquic Soil showed the poorest quantitative performance. This study is the first to reveal, at a holistic level, the critical constraints posed by natural soil complexity on the NIR detection of MPs, offering targeted empirical evidence to support the application of NIR technology in real-world soil environments.

Soil

Pharmacokinetic Differences Between Fast-Acting, Standard, and Placebo Cannabis Edibles.

INTRODUCTION: Edibles have become the second-most used cannabis product in legal U.S. states, wherein 64% of cannabis consumers reported using edibles within the past year. Among expansions to the legal cannabis industry are the newly marketed "fast-acting" edible compounds, which may address many of the issues associated with edible use related to overdose and dose management. The study hypotheses were that fast-acting edibles would reach peak concentration significantly faster than standard edibles and placebo edibles. MATERIALS AND METHODS: Twenty participants completed three arms within-subjects designed study to test hypotheses. The three arms were ingestion of a (1) fast-acting edible, (2) a standard edible, and (3) a &#x394;9-tetrahydrocannabinol (THC) terpene-derived placebo edible that was indistinguishable from the two THC-containing edibles. Blood plasma was analyzed for the presence of THC and THC analytes. The pharmacokinetic parameters tested were time to max concentration (Tmax), maximum concentration (Cmax), terminal half-life (t1/2), and area under the curve (AUC). RESULTS: Results supported study hypotheses in that Tmax was significantly faster for the fast-acting edible, observed 30 min post-ingestion and, on average, 30 min earlier than the Tmax for the standard edible. There were no significant differences between the fast-acting and standard edibles on Cmax, t1/2, and AUC; however, both the fast-acting and standard edibles were significantly different compared with the placebo across all pharmacokinetic parameters. DISCUSSION: The results indicate that the microencapsulation technology used to create the fast-acting edible enabled analyte concentrations to peak significantly faster compared to the standard and placebo edibles.

Humans

Nanopore-based epigenomic profiling reveals the absence of widespread CpG methylation in the African swine fever virus genome.

DNA methylation is a critical epigenetic mechanism implicated in regulating replication and transcription in DNA viruses. However, the epigenetic landscape of African swine fever virus (ASFV), a large double-stranded DNA virus infecting pigs, remains controversial. Here, we systematically profiled the DNA methylome of the first ASFV strain isolated in Hong Kong (HK_NT_202103) using Oxford Nanopore Technologies (ONT) R10.4.1 sequencing. We employed a paired design: native whole-genome sequencing (WGS) against a methylation-free whole-genome amplification (WGA) control. Using conservative thresholds, we found no evidence of 5-methylcytosine (5mC), especially typical CpG methylation, across the viral genome. Importantly, clear CpG methylation signals were successfully detected in the host genome from WGS data, confirming the functionality of the workflow to detect 5mC at CG sites. While widespread 5mC seems absent, a small number of putative N6-methyladenine (6mA) loci were identified. A specific 6mA candidate exhibited raw ionic current disruptions and gene-level intersection with another ASFV isolate (CAS19-01/2019), although it lacked single-base consensus across different methylation callers or between the two isolates. Although our biological findings are restricted to a single isolate under specific experimental conditions, this study introduces a novel, highly rigorous ONT framework for viral epigenomics research. Furthermore, the absence of ASFV CpG methylation indicates that host CpG-depletion remains a viable strategy for viral metagenomic enrichment. Ultimately, our work offers a critical methodological baseline for ASFV surveillance and highlights the necessity of targeted experimental validation for rare viral modifications.

African Swine Fever Virus

The future of pediatric vesicoureteral reflux management.

BACKGROUND AND OBJECTIVE: Vesicoureteral reflux (VUR) is a common condition in pediatric urology, yet important uncertainties persist regarding risk stratification, imaging strategies, and prevention of long-term renal damage. Emerging technologies may help address these challenges. This review provides a forward-looking overview of recent advances in artificial intelligence (AI) and immunomodulation that may influence future management of pediatric VUR. METHODS: A forward-looking literature review was performed using the PubMed database (January 2000-March 2025), focusing on studies addressing AI, immunomodulation, or vaccination in the context of VUR and urinary tract infections. Criteria of inclusion were the relevance to pediatric VUR, the novelty of the proposed concept, the potential clinical implications and, for the AI literature, the existence of a clinical evaluation of the algorithm on a dataset from patients. KEY FINDINGS AND LIMITATIONS: AI-based models show promising performance in supporting clinical decision-making, including prediction of the need for voiding cystourethrography, automated grading of VUR, estimation of recurrent urinary tract infection risk and prediction of chemoprophylaxis. These tools may facilitate more individualized diagnostic and therapeutic strategies, although current evidence is largely retrospective and requires prospective validation. Immunization and immunomodulatory approaches aim to reduce infection burden and modulate inflammatory pathways associated with renal scarring. While early experimental and adult clinical data are encouraging, pediatric-specific evidence remains limited, and clinical applicability in children with VUR is not yet established. CONCLUSION: Artificial intelligence and immunologically targeted strategies represent complementary, emerging approaches that may contribute to more personalized management of pediatric VUR. At present, both should be regarded as exploratory tools whose clinical impact will depend on further validation and appropriately designed pediatric studies.

Humans

Performance comparison of rapid and native barcoding methods for Oxford Nanopore sequencing of Poliovirus Viral Protein 1 (VP1) amplicons.

Accurate and timely sequencing of poliovirus is critical for global eradication efforts, particularly for molecular epidemiology based on the typing region of the genome, viral protein 1 (VP1). While Oxford Nanopore Technologies (ONT) sequencing has expanded capabilities for poliovirus surveillance, the relative performance of different ONT library preparation methods, including ligation-based (Native Barcoding) and transposase-based (Rapid Barcoding) approaches, has not been systematically evaluated. In this study, we compared rapid barcoding and native barcoding workflows for sequencing VP1 amplicons from 17 type 2 poliovirus-positive samples, each processed in triplicate. Native barcoding generated significantly more sequencing output, producing approximately 2.3-fold greater total read yield than rapid barcoding, and demonstrated higher run-to-run reproducibility (R2 = 0.979-0.998 vs. 0.847-0.929, respectively; p&#x202f;<&#x202f;0.001). In addition, native barcoding generated 80% of the total yield achieved by rapid barcoding within approximately 7&#x202f;h, whereas rapid barcoding required approximately 40&#x202f;h to reach the same output. Despite these differences, both methods produced identical VP1 consensus sequences across all samples, with comparable read quality (median per-base Q-scores of approximately Q17-Q18). Rapid barcoding provided substantial practical advantages, reducing hands-on library preparation time (55 vs. 200&#x202f;min) and per-sample cost ($12.82 vs. $16.54), while simplifying workflow and reducing technical complexity. These findings indicate that sequencing yield may not be a determinant of downstream analytical outcomes for poliovirus VP1 ONT sequencing. Rapid barcoding therefore represents a cost-effective and efficient approach for routine poliovirus surveillance, whereas native barcoding remains advantageous in applications requiring rapid data generation or maximal sequencing depth.

Poliovirus

ScRNA-seq analysis reveals the effects of nitrite stress on the endocrine system of the eyestalk in Litopenaeus vannamei.

Nitrite is a harmful substance generated in Litopenaeus vannamei farming systems, largely originating from the inadequate breakdown of surplus feed and shrimp feces. Its accumulation in the water can affect the growth and physiological functions of shrimp, damage the immune system, and even cause mass mortality, thus becoming a key environmental factor restricting the green development of the industry. Under nitrite stress, the eyestalk, as an important neuroendocrine regulatory center in crustaceans, participates in the stress adaptation of the organism and exerts a protective effect by regulating energy metabolism and immune function. However, the molecular regulatory mechanism of the eyestalk in response to nitrite stress remains unclear. In this study, single-cell RNA sequencing (scRNA-seq) technology was used to analyze the heterogeneity of eyestalk cells in L. vannamei under nitrite stress. A total of 18, 394 high-quality cells were obtained, and six major cell subpopulations, including Neurosecretory cell, Motor neuron, Sensory neuron, Interneuron, Neurogliocyte, and Support cell, were identified. Differential expression analysis identified 839 differentially expressed genes, and different cell types showed distinct specific responses to nitrite stress. Functional enrichment analysis indicated that pathways such as glycolysis, oxidative phosphorylation, ribosome function, and endoplasmic reticulum protein processing were significantly activated, while signal transduction and DNA repair-related pathways were inhibited. Further analysis revealed that nitrite stress could induce mitochondrial function changes and trigger oxidative stress, thereby affecting the neuroendocrine system function of the eyestalk. This study provided insights into transcriptomic responses of the eyestalk to nitrite stress at the single-cell level, laying a theoretical foundation for the management of aquaculture environments.

Animals

Whole genome sequencing of unusual Hepatitis C virus subtypes and drug resistance analysis during direct-acting antiviral therapy in India.

INTRODUCTION AND OBJECTIVES: Pangenotypic direct-acting antivirals (DAA) are effective against highly prevalent Hepatitis C virus (HCV) subtypes, but have been clinically validated almost exclusively in high-income countries. Unusual HCV subtypes may carry natural polymorphisms, potentially impacting DAA susceptibility. We conducted full-genome characterization and resistance analysis of unusual HCV subtypes in patients receiving DAA treatment. PATIENTS AND METHODS: In this prospective hospital-based study, eligible patients were screened for anti-HCV antibodies and active infection was confirmed by diagnostic 5'NCR-based HCV RNA detection. Genotyping was performed by core region sequencing, and viral load quantified by real-time PCR. For whole genome sequencing, multiplex primers were designed using alignments of global reference sequences. Sequencing was carried out using the Oxford Nanopore Technology platform. Phylogenetic analysis used multiple sequence alignment and the HCV-GLUE resource for resistance-associated substitution (RAS) analysis. RESULTS: Predominant genotype was genotype 3 in 64.3% (n = 45); genotype 6 in 21.4% (n = 15); and genotype 1 in 14.2% (n = 10). Unusual HCV subtype 6xa was detected in two patients and showed no NS5A resistance mutations. One genotype 3b patient relapsed at 24 weeks post-DAA treatment completion and carried NS5A resistance-associated substitutions 30 K and 31 M both at baseline and at relapse, conferring high-level resistance to NS5A inhibitors. CONCLUSION: This is the first report from India of whole genome sequencing of HCV subtype 6xa. The identification of NS5A resistance mutations in the 3b relapse case underscores challenges for global HCV elimination strategies.

Humans

Test-retest reliability of spatiotemporal, kinematic, and kinetic measures in marker-based 3D gait analysis: A systematic review.

BACKGROUND: Marker-based 3D gait analysis (3DGA) is widely used to quantify impairments and evaluate treatment effects. For longitudinal clinical interpretation, clinicians and researchers need reference values for inter-session measurement error. For this purpose, this systematic review synthesized Standard Error of Measurement (SEM) values for spatiotemporal, kinematic, and kinetic (moments) outcomes obtained from marker-based 3DGA studies. METHODS: PubMed and Scopus were searched (final search: 11 December 2025). Studies reporting inter-session test-retest SEM and/or MDC for steady-state overground or treadmill walking using marker-based motion capture were included. Two authors screened records and appraised methodological/reporting quality using a custom tool informed by COSMIN, GRRAS, and biomechanics-specific items. Due to heterogeneity, results were synthesized descriptively using study-level median SEM values, stratified by joint, plane, population (healthy, pathological, single subgroups), and walking condition. Minimal Detectable Change (MDC) values were computed for all available data. RESULTS: Thirty-four studies (762 participants, 44.2% females) were included, with substantially more evidence for overground than treadmill walking. Overground spatiotemporal outcomes showed low errors (walking speed SEM of 0.06 m/s; timing typically &#x2264;0.03 s; spatial parameters generally &#x2264;0.03 m). For joint kinematics during overground walking, median SEMs were 2.4&#xb0; (sagittal), 1.9&#xb0; (frontal), and 3.3&#xb0; (transverse). The corresponding joint-kinetic SEMs were approximately 0.06, 0.04, and 0.03 Nm/kg, respectively. Treadmill data followed similar patterns. SIGNIFICANCE: Marker-based 3DGA allows for accurate assessment of spatiotemporal, kinematic, and kinetic gait features. We provided detailed SEM/MDC lookup tables to support clinical decision-making. Results further offer a benchmark for validating emerging gait assessment technologies (e.g., markerless systems) against realistic limits of marker-based 3DGA.

Humans

A contextual activity score (CAS) for inferring ADAR-associated transcriptional activity across RNA-seq, single-cell, and spatial transcriptomics.

BACKGROUND AND OBJECTIVE: Adenosine-to-inosine RNA editing, catalyzed by Adenosine Deaminases Acting on RNA (ADARs), is a widespread modification involved in neural function, immune regulation, and cancer. The Alu Editing Index (AEI) is the standard metric to estimate ADAR activity but requires raw sequencing reads and is poorly suited for single-cell and spatial transcriptomic data. This study aimed to develop an alternative framework for inferring ADAR-associated transcriptional activity from gene expression data across diverse transcriptomic technologies. METHODS: We developed the Contextual Activity Score (CAS), a framework based on transcriptional signatures from ADAR perturbation experiments. Context-specific signatures were generated for human neurons, mouse neurons, and cancer models to infer ADAR1 and ADAR2 activity. CAS was computed from normalized gene expression matrices using regulon-based enrichment analysis. Performance was evaluated by comparing with the Alu Editing Index across bulk RNA sequencing datasets, simulated sequencing depths, and library preparation protocols. RESULTS: CAS showed strong concordance with the Alu Editing Index across multiple datasets, while remaining robust to reduced sequencing depth and different library protocols. Unlike the Alu Editing Index, CAS can be applied to single-cell and spatial transcriptomic data and enables the independent assessment of ADAR2 activity. In cancer and neuronal contexts, CAS captured biologically meaningful variations in ADAR-associated transcriptional activity at sample, cell-type, and spatial levels. CONCLUSION: CAS provides a scalable approach applicable across multiple RNA-seq protocols for estimating ADAR-associated transcriptional activity using gene expression data. This method, implemented in an open-source R package for broad adoption, expands the ability to study ADAR-associated transcriptional activity across transcriptomic modalities where direct editing quantification is challenging, such as single-cell and spatial transcriptomics.

Adenosine Deaminase

Public health, public protest: The role of health burdens and healthcare access in protest mobilisation.

Health and politics are intertwined, yet few studies have examined the association between health and protest. This study examined whether population health burdens were associated with protest incidence and whether healthcare access modified these associations. Analysis was based on an unbalanced 2004-2023 country-year panel, combining protest counts from ACLED with rates for 22 GBD causes. Mixed-effects negative-binomial models estimated incidence-rate ratios (IRRs) with interactions for healthcare access (&#xb1;1 SD). Two-way fixed-effects Poisson models were estimated as a benchmark to distinguish cross-national associations from within-country dynamics. Health burdens were systematically, but heterogeneously, associated with protest. Rates for several non-communicable burdens were associated with protest, notably musculoskeletal disorders (IRR 1.72, 95% CI 1.37-2.15), neoplasms (1.24, 1.06-1.44), substance-use disorders (1.32, 1.12-1.56) and HIV/AIDS and other STIs (1.24, 1.12-1.38). Higher healthcare access generally attenuated health-protest associations. Fixed-effects models confirmed several associations (e.g. HIV/AIDS, neoplasms) but revealed that others (e.g. maternal/neonatal disorders, enteric infections) were driven primarily by cross-national differences. Population health burdens were associated with cross-national variation in protest mobilisation. Chronic, non-communicable burdens were associated with heightened protest, whereas poverty-linked and early-life burdens were associated with lower mobilisation. Healthcare access was associated with attenuation of these relationships.

Humans

Effectiveness of artificial intelligence in nursing simulation education: A systematic review, meta-analysis and bibliometric visualization analysis.

OBJECTIVES: To synthesize the roles and core functions of AI in nursing simulation education for nursing students via systematic review, quantitatively evaluate its effects on students' knowledge and skill outcomes through meta-analysis, and map the research landscape and development trends of this field through bibliometric visualization analysis. DESIGN: Systematic review, meta-analysis and bibliometric visualization analysis. DATA SOURCES: Eight electronic databases: PubMed, Web of Science, MEDLINE, ERIC, Academic Search Complete, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Chinese Science and Technology Journal Database (VIP) were employed to search studies from the time of construction to 16 December 2025. REVIEW METHODS: Studies meeting the inclusion criteria were screened. The revised Cochrane Risk of Bias tool (ROB 2) and Joanna Briggs Institute (JBI) critical appraisal checklists were used for quality assessment. Meta-analysis was performed with Review Manager 5.4, and bibliometric visualization analysis was conducted using VOSviewer 1.6.20 and Bibliometrix (based on R4.4.3). RESULTS: A total of 61 studies were included. AI primarily played two roles in nursing simulation education: peer-type new subject (n&#xa0;=&#xa0;24) and direct mediator (n&#xa0;=&#xa0;22). Meta-analysis showed that AI interventions significantly improved nursing students' knowledge (SMD&#xa0;=&#xa0;1.49, 95% CI [0.55,2.43], p&#xa0;=&#xa0;0.002) and skills (SMD&#xa0;=&#xa0;0.66, 95% CI [0.02,1.31], p&#xa0;=&#xa0;0.04). Bibliometric analysis identified that the United States of America and China were the two main contributing countries in this field, and the key motor themes included generative artificial intelligence, virtual patients, and geriatric care. CONCLUSIONS: AI exerts positive effects on nursing students' knowledge acquisition and skill enhancement in simulation education, with peer-type new subject and direct mediator as the dominant roles. Future research should focus on expanding AI applications in multi-specialty simulation scenarios, activating the data-driven value of machine learning, and strengthening international collaboration and standardization construction, so as to promote the sustainable development of AI-integrated nursing simulation education.

Humans

Leading with Innovation: Maternal Health Transformation in New York City Health + Hospitals.

New York City's (NYC) maternal health crisis drew close attention in the late 2010s, driven by alarming data: Approximately 30 women died annually during childbirth in NYC, Black non-Hispanic women were 12 times more likely to die than white women, and more than 3,000 women experienced life-threatening birth complications each year. In response, NYC committed $12.8 million in July 2018 to reduce maternal mortality and eliminate racial disparities.NYC Health + Hospitals (H+H)-the nation's largest public health system, serving 1.1 million patients annually with roughly 15,000 births per year-became the primary vehicle for this initiative. With 80 percent of the system's deliveries covered by Medicaid and a patient population that is 51.2 percent Hispanic and 27.1 percent Black, H+H is uniquely positioned to lead the fight against maternal health inequity.Three flagship programs anchor H+H's response to the city's maternal mortality rate. The OB Simulation Program, launched in 2012 and expanded in 2018, was the first in the nation to use mannequins of color to train thousands of providers in obstetric emergencies. The Maternal Home Program, piloted at H+H's Kings County Hospital in 2019 and scaled system-wide by 2021, has served more than 10,341 patients, generating more than 33,000 referrals for social, behavioral health, and community resources. The Cardio-Obstetrics Program located at Kings County Hospital targets cardiovascular disease-the leading cause of maternal death among Black women-through screening, education, and community outreach. These programs are a health equity imperative, made more urgent by impending federal Medicaid cuts resulting from the H.R.1 One Big Beautiful Bill Act (passed on July 4, 2025).

Humans

Digital health interventions for diabetes management in the eastern mediterranean region: A systematic review of types and effectiveness.

AIM: The aim of this study was to systematically review and evaluate the types and effectiveness of digital health interventions used for diabetes management in the Eastern Mediterranean Region (EMRO). METHODS: This systematic review, conducted according to PRISMA guidelines, searched PubMed, Web of Science, and Scopus up to May 2025 to identify studies on digital interventions for diabetes management in EMRO countries. Methodological&#xa0;quality of the included studies was evaluated using the EPHPP tool, and findings were categorized by intervention type, outcome measures, and intervention effectiveness. RESULTS: A total of 46 studies were included, mainly from Iran and Saudi Arabia. Phone calls and SMS were the most common digital tools. Digital interventions significantly improved HbA1c, fasting blood sugar, and several behavioral outcomes such as physical activity, medication adherence, and self-efficacy, while effects on psychological outcomes were mixed. CONCLUSION: Digital health interventions, especially phone calls and SMS, effectively improve glycemic control and self-care behaviors, though their impact on psychological outcomes remains inconsistent.

Humans

Experimental validation of an AI-driven digital healthcare platform for oral health behavior and plaque assessment among vietnamese children.

BACKGROUND: Oral health among children in developing countries, including Vietnam, remains a significant public health concern. Innovative approaches leveraging artificial intelligence AI-based digital health platforms may offer effective strategies for managing dental plaque and promoting better oral hygiene behaviors among school-aged children. This study aimed to evaluate the effectiveness of an AI-driven oral healthcare platform (Denti-i Vietnam) in improving oral hygiene and behavioral outcomes among Vietnamese primary school students. METHODS: A total of 204 primary school students aged 8-10&#xa0;years in Hanoi, Vietnam, participated in this experimental study. Participants were randomly assigned to an intervention group (n&#xa0;=&#xa0;107), which used the AI-driven oral healthcare platform, and a comparison group (n&#xa0;=&#xa0;97), which received traditional oral health education via pamphlets. Oral health behaviors, dental plaque levels (Simplified Oral Hygiene Index; OHI-S), and caries indices (dft/DMFT) were assessed at baseline and after the intervention period. RESULTS: The intervention group demonstrated a significant reduction in the OHI-S score compared to baseline (2.49&#xa0;&#xb1;&#xa0;0.60 to 1.70&#xa0;&#xb1;&#xa0;0.76, p&#xa0;<&#xa0;0.001), particularly in the debris component, indicating enhanced plaque control. Notable improvements were also observed in oral hygiene behaviors, including increased frequency of toothbrushing before and after breakfast (p&#xa0;<&#xa0;0.01) and more frequent parental assistance during brushing (p&#xa0;=&#xa0;0.03). Furthermore, parental awareness of dental caries significantly increased in the intervention group (p&#xa0;=&#xa0;0.001). CONCLUSIONS: The AI-driven oral healthcare platform significantly improved both oral hygiene behaviors and plaque control among Vietnamese primary school children. These findings suggest that AI-driven digital health tools can serve as practical and scalable solutions for promoting oral health in developing countries.

Humans