Low- and middle-income countries face a growing dual burden of communicable and non-communicable diseases, while services remain vertically organised. In Nigeria, tuberculosis (TB) services are established at primary care level, whereas access to cardiovascular disease (CVD) and chronic respiratory disease (CRD) care remains limited in rural settings. Artificial intelligence (AI) enabled chest X-ray can integrate TB screening with identification of other cardiopulmonary abnormalities at community level. We describe the screening outcomes and referral cascade of a community-based, AI-enabled integrated programme.

We conducted a non-randomised descriptive study using routinely collected programme data from five Local Government Areas in Ebonyi and Nasarawa States, January 2023 to December 2024. Community outreach used portable digital chest X-ray with AI software to screen individuals aged six years and above. People with presumptive TB underwent Xpert MTB/RIF (Mycobacterium tuberculosis/rifampicin) testing on the GeneXpert platform, while non-TB radiographic abnormalities were referred for further evaluation. Descriptive analyses summarised screening yield, diagnostic outcomes, and linkage to care.

In total, 9,585 individuals were screened through 93 outreach activities, and 3,166 (33%) chest radiographs were flagged as abnormal by AI. Overall, 1,336 were classified as having presumptive TB, of whom 1,123 (84%) produced sputum for Xpert MTB/RIF testing. 204 were diagnosed with bacteriologically confirmed TB, and 194 (95%) were initiated on treatment. A further 199 people were clinically diagnosed with TB following radiologist and/or clinical review. Among abnormal radiographs, 2,367 (75%) showed features suggestive of CVDs or CRDs. All such individuals were referred to tertiary facilities; however, only 12% completed the referral. Programmatic adaptations supported TB linkage but had limited impact on non-TB referral completion.

AI-enabled community chest X-ray screening is feasible for TB case finding in rural Nigeria and achieves high linkage to TB treatment. Chest radiography also identified many abnormalities requiring further evaluation for CVD and CRD, most not confirmed within the study. Limited decentralisation of non-communicable disease services constrains care continuity for CVDs and CRDs. Integrated screening programmes should be paired with strengthened primary healthcare capacity, complementary tools such as blood pressure measurement, and context-specific community engagement strategies.

The majority of deaths worldwide are attributable to non-communicable diseases, with approximately four-fifths occurring in low- and middle-income countries. Chronic Obstructive Pulmonary Disease (COPD) is currently the fourth leading cause of mortality globally and is projected to become the third leading cause by 2030.

Our objectives were to: (1) determine the self-reported burden of palliative care-related symptoms and concerns (social, spiritual, psychological, physical), and (2) identify predictors of burdensome symptoms and concerns among adults with COPD attending primary care services in South Africa (including social support).

A cross-sectional survey was conducted across eight primary care facilities in the Western Cape. Sociodemographic data (age, sex, smoking status, and number of missed medication doses in the preceding seven days), clinical data, peak expiratory flow (PEF), and Karnofsky Performance Status (KPS) were collected. Participants completed the African Palliative Care Association African Palliative Outcome Scale (APCA APOS), the Medical Outcomes Study Social Support Survey (MOS-SSS), the London Chest Activity of Daily Living scale (LCADL), and the COPD Assessment Test (CAT). Ordinal logistic regression was used to examine factors associated with palliative care-related symptoms and concerns.

A total of 387 participants were recruited (mean age 59.5 years).In terms of clinical importance APOS items with a prevalence of at least 20% that were rated at the most burdensome levels (scores of 4 or 5) included breathlessness (50.9%), need for help and advice in planning for the future (50.13%), difficulty sharing feelings (29.1%), weakness (25.32%), worry (25.26%), and pain (22.19%). Multivariable ordinal logistic regression analysis showed that greater social support (MOS-SSS) was associated with lower (better) APOS total scores (OR 0.97, 95% CI 0.96-0.98; p<0.001). Reduced ability to perform activities of daily living (LCADL) was associated with worse palliative care outcomes (OR 1.04, 95% CI 1.02-1.07; p<0.001). Higher (worse) CAT scores were also significantly associated with poorer palliative care outcomes (OR 1.13, 95% CI 1.09-1.17; p<0.001).

The impact of social support on self-report concerns demonstrates the importance of a new public health approach to palliative care for COPD patients attending primary care services in sub-Saharan Africa.

Cancer continues to be ranked high in causing mortality and morbidity among non-communicable diseases, being the second to cardiovascular diseases with 10 million deaths annually. This retrospective longitudinal hospital-based study evaluated the records of 3697 cancer patients from January 2019 to December 2021 at Bugando Medical Centre (BMC), a tertiary referral hospital in northwestern Tanzania.

We employed a retrospective longitudinal study of cancer patients at BMC (2019-2021) using Mwanza Cancer Registry (MCR) data. Sociodemographic and clinical data were extracted and partially validated. Analyses in Stata v18 included descriptive statistics and modified Poisson regression. Geographic distribution was mapped using QGIS, with clustering assessed via Ripley's K. Ethical approval and confidentiality were maintained.

The Median age was 53 years (IQR: 39-65). The Majority (22%) of the participants were diagnosed with malignant neoplasm of cervix cancer. About (11.2%) of the participants were diagnosed with malignant neoplasm of the prostate. Participants aged 52-68 years had a 54% higher proportion of diagnosed cervix cancer cancer cases (aPR= 1.54, 95% CI = 1.21- 1.78). Participants aged 69-98 years had a 75% higher proportion of diagnosed cervix cancer cancer cases (aPR= 1.75, 95% CI = 1.12- 1.99). Some cancer hotspots prevail in different parts of the Lake Zone.

Diagnosed cancer cases in the Lake Zone are unevenly distributed, with some areas presenting more diagnosed patients as compared to others. There are vivid hotspots for different cancer types in different areas of the Lake Zone that can be used for cancer programs in the region. Cervix cancer and prostate cancer were the most common among all patients diagnosed at BMC in the last three years. The burden of cervical cancer is high in the Lake Zone.

Gastric cancer (GC) remains a major health burden because of late-stage diagnosis and resistance to systemic therapy.

In GC, the Warburg effect is driven by interconnected hypoxia and oncogenic signalling, non-coding RNA networks and transcriptional and epigenetic rewiring. These regulators converge on glucose transport and core glycolytic enzymes, including HK2, PFKFB3, PKM2 and LDHA. The resulting increase in aerobic glycolysis, pyruvate-to-lactate conversion and lactate export supports biosynthesis, redox homeostasis and survival under metabolic stress. Beyond its bioenergetic role, lactate acts as a signalling metabolite that acidifies and remodels the tumour microenvironment. It impairs CD8-positive T and natural killer cells function, promotes regulatory T cells accumulation and M2 macrophages polarisation, activates stromal cells and facilitates epithelial-mesenchymal transition and immune evasion. Together, tumour-intrinsic metabolic adaptation and lactate-mediated microenvironmental reprogramming contribute to resistance to chemotherapy, targeted therapy and immunotherapy. Translationally, metabolic imaging, circulating LDH and lactate-related markers, exosomal glycolytic enzymes, gene-expression signatures and lactylation-related features may improve prognostic assessment, treatmentresponse prediction and patient stratification. These findings support biomarker-guided combination strategies that target tumour metabolism, lactate production or transport and stromalimmune crosstalk alongside standard therapies. This review uniquely integrates direct GC-derived evidence with indirect evidence from non-GC models and clinical trials and grades biomarkers and metabolic interventions according to their translational maturity.

Overall, the Warburg effect represents both a central driver of GC progression and a clinically relevant metabolic vulnerability.

The Warburg effect in gastric cancer is a multi-module metabolic state, not a single glycolytic phenotype. Lactate links glycolytic reprogramming to stromal activation, immune evasion and therapy resistance. Microbiota, especially H. pylori, modulates glycolysis and creates actionable upstream vulnerabilities. Biomarker-guided combinations, rather than isolated glycolytic inhibition, define the translational path forward.

The Glycemia Risk Index (GRI) is a recently introduced continuous glucose monitoring (CGM)-derived metric that has been evaluated to date in a limited number of studies involving type 1 diabetic adult users of Advanced Hybrid Closed-Loop (AHCL) systems.

To further characterize its clinical utility and to investigate its correlations with CGM-derived metrics, particularly Time in Tight Range (TITR), this single-center, observational, retrospective, real-world study assessed GRI in adults with type 1 diabetes using AHCL systems (MiniMed™ 780G, n = 45; Tandem t: slim X2 IQ technology, n = 20) in routine clinical practice, over a 24-month follow-up period.

GRI showed progressive improvement throughout the observation period, consistent with sustained glycemic control. Baseline GRI was positively correlated with glycated hemoglobin and inversely correlated with Time in Tight Range (TITR) at 12 and 24 months.

These findings suggest that GRI may serve as a useful, readily interpretable metric for predicting long-term glycemic outcomes and support its complementary role alongside TITR in clinical assessment.

Endometriosis is a heterogeneous inflammatory condition that may influence long-term metabolic health. Prior studies have reported largely null associations with type 2 diabetes, potentially missing subtype-specific and subgroup heterogeneity. We investigated the association between endometriosis, including clinically relevant subtypes, and incident type 2 diabetes, and assessed effect modification by menopausal status, BMI and history of gestational diabetes mellitus.

We assembled a dynamic population-based cohort of 2,939,364 individuals assigned as female at birth from the Utah Population Database (1996-2021). Endometriosis and subtypes were identified using validated ICD-9/10 codes and modelled as time-varying exposures. Incident type 2 diabetes was ascertained using ICD codes. Cox proportional hazards models with calendar time as the time scale were used to estimate HRs and 95% CIs, adjusting for birth year, birth state, race/ethnicity, age and BMI at cohort entry. Stratified analyses evaluated effect modification by menopausal status, BMI and history of gestational diabetes mellitus.

During a mean follow-up duration of 10.8 years, 99,978 women were diagnosed with endometriosis. Endometriosis was associated with a 46% higher risk of type 2 diabetes compared with no endometriosis (aHR 1.46; 95% CI 1.43, 1.50). Risk varied by subtype, with the strongest associations observed for 'other site' endometriosis (specified site: aHR 2.67; 95% CI 2.51, 2.84; unspecified site: aHR 2.47; 95% CI 2.35, 2.60). Associations were stronger among premenopausal women than postmenopausal women (aHR 1.55; 95% CI 1.50, 1.60) and those with BMI <30 kg/m² than those in higher BMI categories (aHR 2.39; 95% CI 2.34, 2.44), and were present regardless of history of gestational diabetes mellitus.

Endometriosis was associated with increased type 2 diabetes risk, with substantial heterogeneity by subtype and metabolic context. Associations were strongest among individuals who are traditionally considered at lower baseline risk, although these findings should be interpreted cautiously given the potential for residual confounding and detection bias.

To examine the role of exercise training (ET), cardiorespiratory fitness (CRF), and heart rate variability (HRV)-guided training in reducing cardiometabolic risk associated with type 2 diabetes (T2DM), obesity, and metabolic syndrome (MetS), and to discuss the emerging clinical utility of wearable HRV-monitoring devices.

Low CRF is one of the strongest predictors of all-cause and cardiovascular disease (CVD) mortality, often surpassing traditional CVD risk factors such as obesity, hypertension, dyslipidemia, and T2DM. Increasing evidence supports CRF as a clinical vital sign, with each 1-metabolic equivalent increase associated with significant reductions in mortality risk. Both aerobic ET (aET) and resistance ET (rET) improve CRF and metabolic health through mechanisms involving enhanced glucose regulation, mitochondrial biogenesis, endothelial function, lipoprotein remodeling, autonomic balance, and reduced systemic inflammation. High-intensity interval training consistently produces greater maximal oxygen consumption (VO₂max) improvements than moderate-intensity continuous training, although excessive high-intensity ET without adequate recovery may impair adaptation. HRV-guided ET has emerged as a practical strategy to individualize ET intensity based on autonomic readiness, improving training efficiency while reducing excessive physiological strain and overtraining risk. Contemporary consumer wearable devices (CWDs), including WHOOP, Oura Ring, Apple Watch, Garmin, and Polar systems, increasingly allow real-time HRV monitoring outside clinical settings. ET remains a foundational therapy for cardiometabolic disease prevention and management. Current evidence supports prioritizing CRF optimization over weight-centric approaches alone, as higher CRF levels substantially attenuate mortality risk independent of adiposity. HRV-guided ET further enhances individualized ET prescription by aligning exercise intensity with physiologic recovery status. As wearable technology continues to evolve, HRV-monitoring CWDs may provide scalable tools to improve ET personalization, recovery monitoring, and long-term cardiometabolic health outcomes.

Gestational diabetes mellitus (GDM) affects maternal metabolism and may be associated with altered placental bacterial DNA community profiles and early neonatal gut microbiota. This prospective cohort study assesses GDM's impact on the placental-neonatal gut microbial axis and links key bacterial taxa to short-term perinatal outcomes and clinical significance. Pregnant women with GDM and healthy controls were enrolled. Placental tissue and first-pass neonatal meconium samples were collected. Bacterial community composition, diversity, and differential genera were analyzed using 5-region 16S rRNA sequencing. FEAST was used to model potential maternal-neonatal microbial sources. Associations among gestational weight gain (GWG), microbial features, and the risk of neonatal hospitalization were also assessed. The GDM and control groups showed significant differences in placental and early neonatal meconium microbial community structures, with increased α-diversity and distinct community separation in both sample types. In placental samples, Brevundimonas was decreased, whereas Lactobacillus and Sphingomonas were enriched. In neonatal meconium, potentially inflammation-related genera, including Staphylococcus, Streptococcus, and Clostridium, were enriched. GWG had limited effects on overall community structure but exerted refined regulation on specific genera. Source tracking showed a reduced placenta-attributed similarity contribution to neonatal meconium microbiota in the GDM group. The abundances of specific placental genera, including Escherichia, Curvibacter, and Pelomonas, were significantly associated with neonatal hospitalization. GDM is associated with altered placental bacterial DNA community profiles and early neonatal meconium microbiota, potentially affecting maternal-neonatal microbial continuity. Specific bacterial genera are associated with early neonatal hospitalization. The study provides a microbial perspective for understanding GDM-related perinatal risk.

Nitrate levels and diabetes are important factors influencing the risk of periodontitis. This study intended to assess the combined impact of urinary nitrate levels and diabetes on periodontitis risk in the general population.

This cross-sectional study employed the data on individuals aged 30 and above from the 2009-2014 National Health and Nutrition Examination Survey (NHANES) database. The urinary nitrate levels were divided into three groups based on the tertiles (low, median, and high). A multivariate logistic regression model was used to investigate the relationship between urinary nitrate levels and the risk of stage III/IV periodontitis, with stratified analysis conducted according to diabetes. The multiplicative interaction between nitrate levels and diabetes on periodontitis risk was analysed using the likelihood ratio test. A restricted cubic splines curve was utilised to assess the non-linear association.

Among the 3,292 included participants, 841 (19.28%) individuals had stage III/IV periodontitis, while 2,451 (80.72%) did not. Compared with median nitrate levels, high nitrate levels (odds ratio [OR] = 1.58, 95% confidence interval [CI]: 1.12 to 2.22]) were associated with higher odds of stage III/IV periodontitis, but no statistically significant association was observed between low nitrate levels and periodontitis risk (P > 0.05). Urinary nitrate levels and diabetes showed a multiplicative interaction on the risk of stage III/IV periodontitis (P = 0.020). Specifically, high urinary nitrate levels (OR = 1.68, 95% CI: 1.16 to 2.43) were correlated with a higher risk of periodontitis in non-diabetic individuals, whereas in diabetic individuals, low urinary nitrate levels (OR = 1.66, 95% CI: 1.07 to 2.58) were associated with a higher risk of periodontitis. Moreover, urinary nitrate levels exhibited a statistically significant nonlinear relationship with stage III/IV periodontitis risk in the general population.

High nitrate levels and diabetes exhibit a multiplicative interaction on periodontitis risk. Clinicians may need to monitor both blood glucose and urinary nitrate levels to screen individuals at high risk of periodontitis.

Lipopolysaccharide (LPS), a component of Gram-negative bacteria, is a potent activator of the innate immune system and has been implicated in the pathogenesis of eye diseases, including age-related macular degeneration (AMD), primary open-angle glaucoma (POAG), and diabetic retinopathy (DR). LPS enters systemic circulation through bacterial lysis or active secretion, leading to endotoxemia-either acute or chronic. Chronic endotoxemia, often resulting from gut dysbiosis, may link microbial imbalances to eye diseases. Indeed, chronic LPS exposure may contribute to both systemic and local inflammation. Within the retina, it activates resident immune and structural cells triggering pro-inflammatory cytokine production, oxidative stress, complement cascade activation, and inflammasome activation. These immune cascades compromise blood-retinal barrier integrity, increase vascular leakage, and impair neuronal viability. LPS exposure can stimulate the secretion of pro-angiogenic factors, promoting the development of neovascularization within the retina. Furthermore, the aging retina may be particularly vulnerable to LPS-mediated damage due to an increased exposure to LPS (linked to microbial dysbiosis and alterations of both intestinal and blood-retinal barriers) as well as a reduced capacity for repair. Although direct human evidence remains limited, emerging experimental data support a mechanistic role for LPS in AMD, glaucoma, and DR. This review emphasizes that addressing the impact of chronic endotoxemia represents a promising avenue for both understanding and treating eye diseases. Continued investigation into the multifaceted roles of LPS may yield innovative biomarkers and therapeutic targets to slow or prevent neurodegenerative, vascular, and inflammatory processes underlying conditions such as AMD, glaucoma, and DR.