Gastric cancer (GC) is a leading contributor to cancer-related illness and death globally, presenting a significant public health concern in Iran. There is a lack of extensive data regarding long-term trends at both national and regional levels for GC incidence and its anticipated future impact. This research aimed to investigate the changes in gastric cancer rates in Iran from 1990 to 2021 and to forecast incidence rates through 2030 by gender, age groups, and provinces.

This research used secondary ecological data from the GBD 2021 research to investigate the incidence of GC in Iran from 1990 to 2021. Temporal trends were assessed with Joinpoint Regression to determine the Average Annual Percent Change (AAPC). Also, a Bayesian age-period-cohort model was then applied to project new cases and incidence rates up to 2030. We used from R and Joinpoint software for all analyses.

From 1990 to 2021, Iran saw nearly a twofold increase in new GC instances; however, the age-standardized incidence rate (ASIR) significantly fell from 23.12 to 14.37 per 100,000 individuals. The most significant decreases were observed in the northwestern provinces and among females. Forecasts for 2030 show that the absolute number of cases will likely increase to around 12,070, yet the ASIR is predicted to see a slight drop to 13.44, with a stagnation in decrease for individuals over 80 years old, suggesting a gradual slowdown in the overall trend.

Although there has been a persistent reduction in the age-standardized incidence rate of GC in Iran over the last thirty years, the sheer number of cases is still increasing owing to demographic growth and an aging population. To combat this rising challenge, future initiatives should focus on implementing targeted screening in high-risk areas and for elderly populations, improving geriatric healthcare, and addressing inequalities in healthcare access through better collaboration across sectors.

 With the increasing burden of non-communicable chronic diseases, it is important to empower people to self-manage their conditions. This study aimed to explore the support that persons living with chronic disease require to self-manage their conditions at a Primary Health Care (PHC) facility in the Victor-Khanye subdistrict, Delmas, Mpumalanga.

 Individual in-depth interviews were conducted with 14 adult participants who collected their monthly medication for diabetes, human immunodeficiency virus or hypertension. Data were analysed manually using thematic analysis.

 Three themes were identified: (1) individual self-management; (2) support enhancing for self-management; and (3) barriers to self-management. The study highlights that self-management requires a combination of individual beliefs, capabilities, education, access to healthcare resources, financial assistance, emotional support from family and friends, and community support. While knowledge is crucial for empowering individuals to manage their diseases effectively, challenges such as financial constraints and a lack of specific self-management support provided by healthcare workers hinder many from fully implementing self-management strategies.

 Persons living with chronic disease require comprehensive care that extends beyond healthcare and includes emotional, social and financial support. Effective self-management requires access to tailored education and community support networks that allow people to take an active role in their health.Contribution: Understanding the support persons living with chronic diseases require for effective self-management is critical for improving health outcomes, enhancing quality of life and promoting sustainable healthcare systems.

This study investigates the molecular mechanisms of renal clear cell carcinoma (RCC) induced by Aristolochic acid A (AAA) using machine learning, deep learning, and molecular docking approaches.

To identify AAA target genes associated with RCC, differential expression analysis was performed on multiple datasets. Network toxicology, machine learning, deep learning, and molecular docking were used to explore the binding interactions between AAA and target proteins. The top candidate gene was validated using molecular dynamics simulation and in vitro Western blot assays.

A total of 74 genes were identified as potential targets in AAA-induced RCC. Subsequent machine learning analysis identified seven core genes as key regulators of RCC. Deep learning classification further highlighted five of these seven genes, including PYGL, ADH1B, PTGS1, EDNRA, and AURKA. Additionally, molecular docking simulations revealed strong binding affinities between AAA and these target proteins. Molecular dynamics simulation demonstrated the binding stability of the AAA-PYGL complex, and in vitro studies highlighted PYGL as a potential target of AAA. Elevated expression of PYGL was observed in both 786-O and AAA-induced HK-2 cells. Moreover, treatment with CP-91149 (a PYGL inhibitor) or PYGL knockdown restored the expression of E-cadherin, an epithelial-mesenchymal transition (EMT) marker, in HK-2 cells.

By combining advanced computational methods with in vitro studies, this work elucidates a key toxicity mechanism of AAA in RCC. Our approach provides a feasible and efficient framework for toxicological studies, offering significant value for toxicologists with limited access to clinical specimens.

Acute myeloid leukemia (AML) is an aggressive and molecularly heterogeneous hematologic malignancy associated with poor clinical outcomes, particularly in elderly and high-risk patients. Increasing evidence suggests that metabolic reprogramming plays a critical role in leukemia progression, immune dysregulation, and therapeutic resistance. However, the prognostic value of metabolism-associated molecular networks in AML remains insufficiently understood.

This study aimed to identify metabolism-related hub genes involved in AML progression and to establish a robust prognostic signature for survival prediction.

Integrated transcriptomic analyses were performed using multiple Gene Expression Omnibus datasets and the TCGA-LAML cohort. Weighted gene co-expression network analysis identified AML-associated gene modules, followed by protein-protein interaction and functional enrichment analyses. Metabolic-related hub genes were selected through integration with curated metabolic gene sets. A prognostic model was subsequently developed using univariable and least absolute shrinkage and selection operator (LASSO) Cox regression analyses and validated in independent cohorts. A four-gene metabolic signature consisting of CYP4F3, PFKL, G6PD, and DNMT3A was identified as an independent predictor of overall survival. Patients in the high-risk group showed significantly poorer survival outcomes compared with low-risk patients (p < 0.0001). The prognostic model demonstrated stable and reliable predictive performance across training, testing, and validation cohorts. Functional enrichment analyses revealed that the identified genes are closely associated with metabolic pathways, immune-related signaling, and leukemic microenvironment remodeling. Notably, increased expression of G6PD and PFKL was associated with adverse prognosis, supporting the contribution of altered glycolysis and redox homeostasis to AML pathogenesis.

Our findings establish a metabolic-based prognostic signature with strong predictive utility in AML. The identified metabolic hub genes provide insight into the interaction between metabolic dysregulation and immune remodeling in leukemia and may serve as promising biomarkers for risk stratification and potential therapeutic targets.

Increasing multimorbidity among people with human immunodeficiency virus (PWH; HIV) in sub-Saharan Africa can result in hospitalization. We investigated longitudinal associations between multimorbidity trajectories and hospitalization risk within the African Cohort Study (AFRICOS).

AFRICOS enrolls people with and without HIV from HIV clinics in Uganda, Kenya, Tanzania, and Nigeria. These analyses restricted PWH aged ≥18 years enrolled between 2013 and 2024. Multimorbidity (≥chronic conditions in addition to HIV) was ascertained from International Classification of Diseases codes and clinical measurements. Multimorbidity was categorized into 3 trajectories: resilient, developed, and continued. Hospitalization reasons were ascertained by medical record review. Andersen-Gill extensions of Cox proportional hazards models estimated adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for the association of multimorbidity trajectory and hospitalization.

Among 3028 PWH, 36.6% (n = 1109) had multimorbidity at enrollment. Over 17 740 person-years, 721 hospitalizations occurred (incidence density: 4.06 per 100 person-years). Systemic infections (n = 209, 29.0%), predominantly malaria (n = 182, 87.1%), led admissions. In adjusted models, PWH with continued multimorbidity had a significantly higher risk of hospitalization (aHR = 1.27, 95% CI: 1.06-1.53) compared with resilient PWH.

PWH with continued multimorbidity have a significantly increased risk of hospitalization. Intervening early with optimal ART and comprehensive chronic disease management is critical for improving long-term outcomes in sub-Saharan Africa.

 Non-communicable diseases (NCDs) disproportionately affect low- and middle-income countries, including Ethiopia. However, community health workers' (CHWs') capacity in NCD health promotion is sometimes limited.

 This study aimed to co-design a contextually appropriate intervention with and for CHWs to support their NCD health promotion services.

 This co-design study was conducted in Gondar City, northwest Ethiopia. The workshops were held in the meeting hall at the University of Gondar.

 A qualitative participatory action research design, guided by the PRODUCES (Problem, Objective, Design, User, Co-creators, Evaluation, and Scalability) framework, was employed. Sixteen participants, including CHWs (n = 6), community-dwelling adults with (n = 3) and without NCD diagnoses (n = 3), and health system managers (n = 4) were recruited using convenience and purposive sampling. Participants attended three workshops. In workshop 1, participants discussed the roles of CHWs in health promotion and areas for improvement. Workshop 2 focused on intervention components and delivery approaches. A draft of the intervention was reviewed during workshop 3. Discussion notes and artefacts were thematically analysed in NVivo.

 A 6-week, multicomponent intervention, 'Empower Community Health', was co-designed. Key themes included: (1) knowledge capacity building, (2) personal behaviour change, and (3) community-outreach initiatives. Proposed intervention topics included: (1) learning about NCDs; (2) skill motivational interviewing; and (3) behaviour change for diet and physical activity.

 The involvement of intervention users and stakeholders allowed for the sharing of experiences and fostered ownership in the 'Empower Community Health' programme.Contribution: The meaningful engagement of stakeholders ensures that the intervention is tailored to their needs, fosters ownership and enhances intervention buy-in. This study provides practical guidance for future co-designed health promotion programmes.

Acinetobacter baumannii is a major contributor to antimicrobial resistance (AMR), particularly in hospitals. Its rising resistance presents significant clinical and economic concerns. This study evaluated the national burden and economic impact of A. baumannii infections in Iran from 2000 to 2021 using GBD 2021 AMR data.

We estimated mortality and disability-adjusted life years (DALYs) per 100,000 people with 95% UIs under two scenarios: resistant infections replaced by susceptible ones (attributable burden) and replaced by no infection (associated burden). Economic burden was calculated using GDP per capita and purchasing power parity (PPP)-adjusted estimates.

From 2000 to 2021, total associated DALYs declined from 90,391.9 (95% UI: 80,178.0-100,605.9) to 69,740.5 (65,132.4-74,348.6) and attributable DALYs from 35,284.5 (30,843.1-39,725.9) to 28,085.9 (25,415.9-30,755.9). However, associated deaths increased from 2019.5 (1870.3-2168.8) to 2523.7 (2322.5-2724.9), with neonates and individuals aged 50 years and older most affected. Bloodstream and lower respiratory infections contributed most to DALYs. Resistance remained highest for cephalosporins and carbapenems. The economic burden peaked in 2010 at 584.6 million PPP and decreased to 435.2 million in 2021.

Although disease burden declined, rising mortality and resistance trends highlight the need for stronger infection control and stewardship to reduce A. baumannii-related AMR in Iran.

Human T-lymphotropic virus type 1 (HTLV-1) is considered a health issue in Iran. However, its genetic diversity and molecular epidemiologic phylogeny remain poorly characterized.

The Tax gene of 9 asymptomatic individuals across Alborz, Gilan, and Ardabil provinces of Iran was sequenced and analyzed phylogenetically using MEGA-X.

All strains clustered within the Cosmopolitan subtype a, showing high genetic similarity to Japanese and Chinese references. Positive selection (dN/dS > 1) was observed in all samples. Strikingly, the Alborz ISO32 strain exhibited 10 unique nonsynonymous mutations, suggesting regional evolutionary divergence.

This study, as the first multi-provincial study in Iran, reveals the essential requirement for systematic tracking of HTLV-1 genetic diversity and designing prevention programs tailored to each region.

Current literature is limited regarding the impact of diabetes mellitus (DM) on short- and long-term postoperative complications following distal femur (DF) fracture surgery in geriatric patients. Although DM is a known risk factor for adverse outcomes following hip fracture and lower-extremity arthroplasty, large-scale data specific to DF fractures, which pose distinct fixation, weight-bearing, and healing challenges, remain limited. This study evaluates short- and long-term postoperative complication rates among geriatric patients undergoing operative treatment for DF fractures, comparing those with and without DM.

Using a nationally representative multi-institutional database, we conducted a retrospective analysis of patients aged ≥ 65 years who underwent DF fracture surgery between January 2012 and January 2022. Patients were categorized as having DM or not, and propensity score matching controlled for demographic and comorbidity differences. A subgroup analysis stratified diabetic patients into complicated and uncomplicated DM to assess whether disease severity modified risk. Follow-up periods were 6 months, 1 year, and 3 years.

A total of 9390 patients were matched into each cohort. Patients with DM had significantly higher risks of myocardial infarction, transfusion, acute kidney failure, glomerular disease, pneumonia, mortality, cardiac arrest, and wound dehiscence across all follow-up intervals. Surgical site infection was more frequent in the DM cohort at 6-month and 1-year follow-up but did not reach statistical significance at 3 years. No significant differences were observed in deep vein thrombosis, pulmonary embolism, hematoma, DF nonunion, or DF malunion. In the subgroup analysis, patients with complicated DM showed higher rates of major complications, including acute kidney failure and myocardial infarction, compared with matched patients with uncomplicated DM.

Geriatric patients with DM were observed to have significantly higher rates of medical and infectious complications following distal femur fracture surgery compared with matched non-diabetic patients. These findings identify DM, and particularly complicated DM, as an important risk marker and may warrant consideration of enhanced perioperative co-management. Because this is a retrospective observational study, findings represent associations rather than causal relationships; prospective and interventional studies are needed to clarify modifiable factors in geriatric patients with DM undergoing DF fracture surgery.