Psoriasis is frequently associated with non-communicable disease (NCD) comorbidities, prompting interest in how these concurrent conditions may influence psoriasis treatment outcomes.

To assess NCD prevalence and their influence on psoriasis treatment outcomes.

From 2022 to 2024, we recruited psoriasis patients in Shanghai Skin Disease Hospital. Data on demographic features, NCD comorbidities and treatment outcomes at week 4 and week 8 were systematically collected through questionnaire, physical examination, and clinical severity assessment (psoriasis area and severity index [PASI], body surface area [BSA], physician's global assessment [PGA]).

Among 1116 patients, 48.4% had at least one NCD comorbidity. NCD-free patients exhibited higher PASI₅₀ response rates at both week 4 (46.5 vs. 39.1%) and week 8 (72.2 vs. 70.9%). Log binomial regression revealed that NCDs significantly reduced the likelihood of achieving PASI₅₀ at week 4 (relative risk [RR] = 0.84, 95% confidence interval [CI]: 0.73-0.96), with a similar but non-significant trend at week 8 (RR = 0.98, 95% CI: 0.92-1.06).

NCDs negatively impact early treatment outcomes in psoriasis patients. So we propose that dermatologists should integrate systematic NCD management into psoriasis treatment regimen.

There is a growing interest in complexity research. A recent systematic review by Loffreda et al attempted to study the barriers and opportunities for the adoption and implementation of the "best buys" for non-communicable diseases (NCDs) from a political economy perspective. In this commentary we take forward the discussion on the NCD best-buys by comparing the findings of the article with one of the risk factors of tobacco use and its control in India. We reflect on the challenges in actualizing the promise of research methods and approaches while studying such complex interventions like the NCD best buys. The balance of studying complexity while still keeping the findings translatable at country levels. Future research could potentially use a comparative lens focusing on either industry/government or actor behaviour across the different risk factors to facilitate cross learning, anticipate and pre-empt adverse policy decisions and implementation outcomes.

This study aimed to explore the association between plasma big endothelin-1 (ET-1) and major adverse cardiovascular events (MACE) in CAD patients who underwent PCI with a focus on the influence of kidney function and diabetes status in secondary prevention.

A prospective cohort of CAD patients underwent PCI and patients with impaired kidney function and diabetes were initially screened and categorized separately, subdivided based on ET-1 levels. The primary outcome was MACE, including all-cause mortality, nonfatal myocardial infarction, unplanned revascularization, and stroke. Statistical analyses included Cox regression, competing risks analysis (competing for non-cardiovascular death), and restricted cubic spline to assess the relationships between ET-1 and MACE.

This study included 1344 CAD patients with impaired kidney function and 10,577 CAD patients with DM. During a median follow-up of 3 years, 20% of renal dysfunction patients and 12.9% of DM patients experienced MACE. In CAD patients with renal dysfunction, elevated ET-1 levels were associated with increased MACE risk (adjusted HR 1.333, 95% CI 1.169-1.519, p < 0.001), with those in the highest group and DM showing a 2.134-fold (95% CI, 1.334-3.413, p < 0.001) increased MACE risk. In CAD patients with DM, patients with eGFR ≤ 60 mL/min/1.73 m² and elevated ET-1 levels had a 2.297-fold (95% CI 1.822-2.895) increased risk of MACE.

ET-1 offered important prognostic value for CAD patients who underwent PCI, with especially bad prognoses observed in those with elevated ET-1 levels, renal dysfunction, and DM.

The current clinical management of pulmonary nodules relies heavily on CT follow-up, without early intervention. This retrospective study investigated the efficacy of OM-85, a standardized lysate of human respiratory bacteria, in the treatment of high-risk pulmonary nodules detected by computed tomography (CT) in patients with chronic bronchitis.

This study included 72 patients (93 enrolled nodules) who underwent treatment with OM-85 and a matched control group of 90 patients (111 control nodules). The primary endpoint included reduced size of high-risk ground glass nodules based on thin-layer CT scans during follow-up. Flow cytometry, multiplex immunofluorescence (mIF) analysis, and scRNA-seq data were employed to determine differences in the immune cell subsets between the treatment and control groups.

Oral OM-85 treatment significantly reduced lung nodule diameter (p = 0.031), the risk probability of malignancy (p = 0.003), and the likelihood of clinical disease progression (p = 0.0091). The effects of OM-85 treatment were more pronounced in older patients (> 65-year-old) (p = 0.029) and those with longer follow-up cycles (> 200 days) (p = 0.011). The peripheral blood samples showed a significantly higher proportion of natural killer (NK) cells in the treatment group. Furthermore, mIF staining of the pulmonary nodules and scRNA-seq data demonstrated a higher percentage of NK cells in the treatment group compared with the control group (p = 0.0003).

OM-85 reduced the size of high-risk pulmonary nodules and decreased the risk of malignant probability and disease progression in patients with chronic bronchitis by increasing the proportion of NK cells. Therefore, OM-85 is a potential drug for the treatment of high-risk pulmonary nodules in patients with chronic bronchitis.

In Pakistan, cultural and religious beliefs restrict autopsies, limiting their prevalence. Additionally, many deaths occur at home, outside of hospital systems, making cause-of-death (CoD) determination challenging. This study aims to overcome these challenges by using a community-based verbal autopsy approach in Karachi to identify CoD.

The research was conducted in two peri-urban communities within the Health Demographic Site Surveillance catchment area. A total of 1500 deaths were investigated using the World Health Organization 2016 Verbal Autopsy Questionnaire. Interviewers received extensive training to ensure culturally sensitive data collection, and physicians analysed the data to determine CoD. The 10th edition of the International Classification of Diseases (ICD-10) was integrated with verbal autopsy data for a detailed analysis of mortality causes.

The study identified that 52.8% of deaths were male, and 47.1% female, with 51.2% occurring in hospitals and 48.7% at home. Among home deaths, 31.5% were children under five years and 55.4% were above 18 years. Analysis revealed that major CoD included non-communicable diseases: acute cardiac disease (12.6%), liver cirrhosis (7%), and stroke (4.3%), alongside communicable diseases like diarrheal disease (6.4%), pneumonia (4.1%), and sepsis (3.4%). In adults over 18, acute cardiac disease (25.0%) and liver cirrhosis (13.1%) were prevalent, whereas neonatal sepsis (12.8%) and perinatal asphyxia (11.7%) were the most common causes in children under five years. External causes included road traffic crashes (1.6%) and accidental drowning (0.7%).

The study underscores the need for targeted health care strategies to address the diverse CoD and varying health-seeking behaviours observed. Improving access to health care, particularly for home-based deaths and vulnerable age groups, is essential for better health outcomes. Tailored interventions are crucial to address both communicable and non-communicable diseases effectively in resource-constrained settings.

Artificial intelligence (AI) has become an important tool in global health, improving disease diagnosis and management. Despite advancements, tuberculosis (TB) remains a public health challenge, particularly in low- and middle-income countries where diagnostic methods are limited. In this scoping review, we aim to examine the potential role of AI in TB control.

We conducted a search on 25 August 2024 for the past five years, in the PubMed database using keywords related to AI and TB. We included laboratory-based and observational studies focussing on AI applications in TB, excluding non-original research.

There were 34 eligible studies, identifying eight overarching aspects associated with TB control, including active case finding (ACF), triage, pleural effusion diagnosis, multidrug-resistant (MDR) TB and extensively drug-resistant (XDR) TB, differential diagnosis distinguishing active TB from TB infection and other pulmonary communicable diseases, TB and other pulmonary communicable and non-communicable diseases (NCDs), treatment outcome prediction, pleural effusion, and predictions of regional and national trends. AI may transform TB control through enhanced ACF methods and triage, improving detection rates in high-burden regions. With high accuracy, AI may diagnose pleural diagnosis, differentiate TB active and TB infection, TB and non-tuberculous mycobacterial lung disease, COVID-19, and pulmonary NCDs. AI applications may facilitate the prediction of treatment success and adverse effects. Furthermore, AI-driven hotspot mapping may identify undiagnosed TB cases at rates surpassing traditional notification methods. Lastly, predictive modelling and clinical decision support systems may improve the management of MDR-TB.

This scoping review highlights the potential of AI-driven predictions in national TB programmes to enhance diagnostics, track trends, and strengthen public health surveillance. While promising for reducing transmission and supporting TB care in low-resource settings, these models require large-scale validation to ensure real-world applicability, especially for high-risk groups.

The aim of this study is to assess endothelial progenitor cells (EPCs) and circulating endothelial cells (CECs) at the time of type 1 diabetes (T1D) recognition concerning patients' clinical state, remaining insulin secretion, and further partial remission (PR) occurrence. We recruited 45 children that were admitted to hospital due to newly diagnosed T1D (median age 10.8 yrs), and 20 healthy peers as a control group. EPC and CEC levels were measured at disease onset in PBMC isolated from whole peripheral blood with the use of flow cytometry. Clinical data regarding patients' condition, C-peptide secretion, and further PR prevalence were analyzed. T1D-diagnosed patients presented higher EPC levels than the control group (p = 0.026), while no statistical differences in CEC levels and EPC/CEC ratio were observed. Considering only T1D patients, those with better clinical conditions presented lower EPCs (p = 0.021) and lower EPC/CEC ratios (p = 0.0002). Patients with C-peptide secretion within a normal range at disease onset presented lower EPC/CEC ratios (p = 0.027). Higher levels of EPCs were observed more frequently in patients with higher glucose, decreased fasting C-peptide, and lower stimulated C-peptide (all p < 0.05). The presence of DKA was related to higher EPC/CEC ratios (p = 0.034). Significantly higher levels of CECs were observed in patients who presented partial remission of the disease at 6 months after diagnosis (p = 0.03) only. In the study group, positive correlations of CECs with age, BMI at onset, and BMI in following years were observed. EPC/CEC ratios correlated positively with glucose levels at hospital admission and negatively with age, BMI, pH, and stimulated C-peptide level. We reveal a new potential for the application of EPCs and CECs as biomarkers, reflecting both endothelial injury and reconstruction processes in children with T1D. There is a need for further research in order to reduce cardiovascular risk in children with T1D.

The increasing prevalence of diabetes mellitus necessitates the development of advanced glucose-monitoring systems that are non-invasive, reliable, and capable of real-time analysis. Wearable electrochemical biosensors have emerged as promising tools for continuous glucose monitoring (CGM), particularly through sweat-based platforms. This review highlights recent advancements in enzymatic and non-enzymatic wearable biosensors, with a specific focus on the pivotal role of nanomaterials in enhancing sensor performance. In enzymatic sensors, nanomaterials serve as high-surface-area supports for glucose oxidase (GOx) immobilization and facilitate direct electron transfer (DET), thereby improving sensitivity, selectivity, and miniaturization. Meanwhile, non-enzymatic sensors leverage metal and metal oxide nanostructures as catalytic sites to mimic enzymatic activity, offering improved stability and durability. Both categories benefit from the integration of carbon-based materials, metal nanoparticles, conductive polymers, and hybrid composites, enabling the development of flexible, skin-compatible biosensing systems with wireless communication capabilities. The review critically evaluates sensor performance parameters, including sensitivity, limit of detection, and linear range. Finally, current limitations and future perspectives are discussed. These include the development of multifunctional sensors, closed-loop therapeutic systems, and strategies for enhancing the stability and cost-efficiency of biosensors for broader clinical adoption.

Endothelial dysfunction appears early in type 1 diabetes (T1D). The detection of the first vascular disturbances in T1D patients is crucial, and the introduction of novel techniques, such as flow-mediated skin fluorescence (FMSF) and adaptive optics retinal camera (Rtx) imaging, gives hope for better detection and prevention of angiopathies in the future. In this study, we aimed to investigate microcirculation disturbances in pediatric patients with T1D with the use of FMSF and Rtx imaging. This research focused especially on the relationship between microvascular parameters obtained in FMSF and Rtx measurements, and the glycemic control evaluated in continuous glucose monitoring (CGM) reports. We observed significantly increased wall thickness (WT) and wall-to-lumen ratio (WLR) values in T1D patients in comparison to the control group. Although we did not observe significant differences between the T1D and control groups in the FMSF results, a trend toward significance between the time in range (TIR) and hyperemic response (HR_max) and an interesting correlation between the carotid intima-media thickness (cIMT_max) and HR_max. were observed. In conclusion, FMSF and Rtx measurments are innovative techniques enabling the detection of early microvascular disturbances.

This study aimed to examine 1) the relationship between domain-specific physical activity (PA) and the prevalence of chronic kidney disease (CKD), as well as 2) the association between meeting PA and resistance exercise (RE) guideline and CKD prevalence in individuals with diabetes.

The study analyzed data from the 2019-2021 Korea National Health and Nutrition Examination Survey, a cross-sectional study that included 22559 participants. From this group, 2381 adults with diabetes were selected. CKD was defined as an estimated glomerular filtration rate <60 mL/min/1.73m², a urinary albumin-to-creatinine ratio ≥30 mg/g, or a physician's diagnosis. Logistic regression models were used to assess the association between compliance with the WHO's PA guidelines and CKD prevalence, with further stratification according to known CKD risk factors.

Individuals with diabetes who met the PA guidelines through leisure physical activity (LPA) and RE were significantly inversely associated with the odds of CKD [odds ratio (OR): 0.55, 95% confidence interval (CI) 0.34-0.89]. This inverse association was pronounced in individuals with lower body mass index (OR: 0.31, 95% CI 0.15-0.65). However, individuals who met the recommended amount of PA through work-related physical activity and RE guideline were not significantly associated with the odds of CKD (OR: 1.46, 95% CI 0.44-4.82).

Meeting PA and RE guidelines are associated with reduced prevalence of CKD in individuals with diabetes. These findings underscore the potential benefits of LPA and RE in the prevention of CKD in individuals with diabetes.