Common perinatal mental disorders, including depression, anxiety, and stress-related conditions, significantly impact maternal and child health. Despite their high prevalence, CPMDs often go undetected and untreated, particularly in low- and middle-income countries. Integrating mental health screening into routine maternal care is crucial for early identification and intervention. However, implementation faces multiple challenges. This study aims to explore the facilitators and barriers to screening perinatal women for CMDs in healthcare facilities in Bengaluru, India, from the perspectives of healthcare providers and perinatal women.

A qualitative study was conducted between October 2024 and March 2025 among 20 participants, including 10 healthcare providers and 10 perinatal women from public and private healthcare facilities in a zonal administrative unit of an Indian city, Bengaluru. Key informant interviews (KIIs) were conducted, and the data were analyzed to identify key system-level and individual-level facilitators and barriers.

Facilitators included a well-established referral system, drug availability, provider willingness to screen, privacy in consultations, and the integration of screening questions into the Thayi (Mother and Child Protection) Card. We identified several barriers, including fragmentation between maternal and mental health services, high provider workload, lack of dedicated mental health professionals, and inadequate training on mental health screening. Perinatal women faced stigma, limited awareness of mental health, reluctance to seek help, and misconceptions about treatment. The presence of family members during consultations further hindered open discussions.

These findings highlight the need for context-specific, integrated strategies, including workforce strengthening and stigma reduction, to improve perinatal mental health screening and care.

Despite the identification of numerous genetic risk variants for Alzheimer's disease (AD), mechanisms through which these variants act remain unclear. Identifying specific proteins levels affected by genetic variation can provide valuable insights into the underlying biological pathways implicated in AD.

To gain more insight into effects of genetic variation on AD-related processes, we conducted a genome-wide protein pQTL study using untargeted TMT mass spectrometry in cerebrospinal fluid (CSF) of 2,215 proteins across 487 individuals. Replication was assessed in the independent EMIF-AD MBD cohort of 242 individuals.

We identified 399 independent CSF pQTL signals (P _Bonferroni < 2.26 × 10⁻11) associated with 222 proteins, 69% of which were novel. Findings included gene-protein links such as RPS23P10/HSPA6 with CSF FCGR2A, BIN2 with CSF GALNT6, APOE with CSF HS3ST1, and the HLA-region with CSF HLA-DPB1 and PLXDC2. We replicated 230 of 270 gene-protein associations. A proteome-wide association study identified genetically predicted CSF protein levels to be associated with AD, including SIRPA, PLXDC2, and GALNT6. Many AD pQTLs in CSF were enriched in neuroimmune activation, suggesting a genetic basis for neuroimmune dysregulation in AD.

This study highlights how genetic variation shapes protein expression in the central nervous system, offering mechanistic insight into AD.

The online version contains supplementary material available at https://doi.org/10.1186/s44477-026-00048-7.

The relationship between intrathecal kappa free light chain (κ-FLC) synthesis and retinal layer atrophy in multiple sclerosis (MS) is unknown.

To investigate whether the κ-FLC index is associated with peripapillary retinal nerve fiber layer (pRNFL) and ganglion cell plus inner plexiform layer (GCIPL) thickness.

Patients with newly diagnosed clinically isolated syndrome or relapsing MS and available cerebrospinal fluid (CSF) analysis and optical coherence tomography (OCT) were included. Clinical and magnetic resonance imaging (MRI) data were also assessed. κ-FLC concentrations were measured by nephelometry, and the κ-FLC index was calculated as (CSF κ-FLC/serum κ-FLC)/albumin quotient.

A total of 100 patients at a median age of 33 (25th-75th percentile: 25-39) years and a female predominance (58%) were included. In multivariable linear regression analysis adjusted for age, sex, disease duration, number of T2-hyperintense and number of contrast-enhancing MRI lesions, the κ-FLC index was associated with pRNFL (log-transformed κ-FLC index: β: -2.51; 95% confidence interval [CI]: -4.01, -1.01; p = 0.001) and GCIPL thinning (log-transformed κ-FLC index: β: -1.24, 95% CI: -2.32, -0.17; p = 0.024).

Intrathecal plasma cell activity, as measured by the κ-FLC index, is associated with neuroaxonal damage, as reflected by pRNFL and GCIPL atrophy.

Somalia continues to face multidimensional public health challenges driven by prolonged conflict, political instability, fragmented governance, climate-related disasters, displacement, poverty, and a fragile health system. The country carries a dual burden of communicable and non-communicable diseases (NCDs), alongside persistently high maternal and child mortality and recurrent nutrition and WASH emergencies. These pressures are intensified by workforce shortages, limited laboratory and surveillance capacity, unequal access to care, and heavy dependence on externally financed programmes. In this perspective, health-system resilience refers to Somalia's capacity to anticipate, absorb, adapt to, and recover from shocks while maintaining equitable delivery of essential services. We argue that resilience cannot be achieved through disease-specific or short-term humanitarian programmes alone; it requires stronger public stewardship, coordinated federal-state governance, sustainable financing, integrated primary health care, a retained and equitably distributed workforce, interoperable surveillance, and climate-resilient WASH and referral systems. The central recommendation is therefore a transition from fragmented, crisis-driven service delivery toward an accountable, primary-health-care-centred system that links communities, public and private providers, laboratories, referral facilities, and emergency response mechanisms.

Type 1 diabetes mellitus (T₁DM) is common and can cause cardiac complications. Subclinical myocardial involvement, particularly impaired diastolic function, is a concern in pediatric patients with T₁DM.

This study aimed to assess cardiac function, with a particular focus on diastolic indices, in children with T₁DM.

In this cross-sectional comparative study, children aged 6 - 12 years were divided into two groups: a case group with T₁DM and a control group of healthy children. Participants were recruited in 2023 from the Endocrinology Clinic at Amirkola Children's Hospital, Babol, Iran. All children underwent clinical evaluation, pubertal status assessment using the Marshall-Tanner criteria, electrocardiography, and echocardiography.

A total of 150 children were included, comprising 50 children with T₁DM and 100 controls. Overall, 52% of the participants were boys, and the mean age was 9.28 ± 1.85 years. Late diastolic tissue velocity (A') was significantly higher in the T₁DM group (P = 0.02), suggesting subclinical diastolic impairment. However, most other cardiac parameters, including all systolic indices, ejection fraction, fractional shortening, and electrocardiographic findings, were comparable between the groups (all P > 0.4). The T₁DM group also had higher mean weight, height, body mass index, and body mass index percentiles (all P < 0.05).

Children with T₁DM exhibited subtle diastolic dysfunction, reflected by elevated A', whereas systolic function and other cardiac parameters were comparable with those in controls. Given the cross-sectional design, limited sample size, and potential confounding by body mass index and selection bias, these findings should be interpreted cautiously. The standardized single-center methodology supports internal validity; however, multicenter longitudinal studies with larger, z-score-adjusted samples are needed to confirm these results and clarify their clinical implications.

Sarcopenic obesity is closely related to the occurrence of metabolically associated fatty liver disease (MASLD), but the factors that influence the effectiveness of dietary supplements in increasing muscle mass have not yet been clarified.

In our study, we examined the effects of a diabetes-specific dietary supplement containing beta-hydroxy-beta-methylbutyrate (HMB) on total body muscle mass after a treatment lasting for 6 months, and measured by densitometry in patients with type 2 diabetes who were treated for sarcopenic obesity and also met the criteria of MASLD. Then, we looked for linear correlations between the degree of muscle mass change and age, as well as the lean mass index, and various metabolic parameters such as hemoglobin A1c, C-peptide, and triglyceride levels. Our goal was also to determine the predictive value of these parameters in forecasting of the effectiveness of the dietary supplement.

Our cross-sectional study included 48 patients with type 2 diabetes (aged 55-84 years, 40 female and 8 male, average age 72.48 ± 8.26 years). As a control group, we chose 20 persons of similar age with no serious comorbidities, who had neither diabetes nor MASLD. We confirmed liver steatosis using transient elastography. After identifying the relationships between the degree of muscle mass change and other examined parameters using simple linear regression, we evaluated the predictive value of individual parameters for the extent of muscle mass change with logistic regression.

The average pre-treatment values of patients' parameters were: body mass index: 27.80 ± 4.63, hemoglobin A1c: 6.27 ± 0.73, degree of steatosis: 289 ± 42 dB/m, appendicular muscle mass index: 6213 ± 786 g/m², android fat ratio: 47.59 ± 9.80%, total fat ratio: 41.82 ± 9.31%. After a 6-month treatment, we observed an increase in muscle mass in 28 patients. Of those, the increase reached up to 5% of the original muscle mass in 16 patients, it was above 5% in 8 patients, and it exceeded 10% of the original mass in 4 patients. We observed a slight decrease in muscle mass in 20 patients, with the decrease reaching up to 5% of the original muscle mass in all of them. We found a significant positive linear relationship between the degree of muscle mass increase and other baseline parameters in terms of C-peptide (r = 0.42, p = 0.03) and alkaline phosphatase (r = 0.51, p = 0.01), and a negative relationship in terms of age (r= -0.39, p = 0.05) and triglycerides (r = -0.41, p = 0.04). We did not find a significant relationship with any body composition parameter. Based on the logistic regression analysis, the predictors of muscle mass change were as follows: age appeared as a negative predictor (OR = 0.87, CI: 0.77-0.99, p = 0.04), and triglycerides appeared as a borderline negative predictor (OR = 0.21, CI 0.04-1.03, p = 0.05).

Taking HMB-containing dietary supplements led to an increase or maintenance of muscle mass in a significant portion of patients; however, the changes in muscle mass did not reach the level of statistical significance, although individual responses to the intervention varied, with higher age and higher triglyceride levels having a negative impact. So, in this regard, the conclusion of the study can be considered as negative. Interpretation of these results is limited by the small number of participants and the cross-sectional nature of the study, hence larger prospective studies are needed to confirm them. Orv Hetil. 2026; 167(38): 1507-1515.

Managing diabetes in children is challenging and requires continuous monitoring and structured self-care support. Artificial intelligence (AI)-driven digital tools may enhance self-management and improve health outcomes. This scoping review aimed to synthesize the existing evidence on AI-driven digital tools for pediatric diabetes self-management, focusing on their functionalities, benefits, and limitations.

From an initial pool of 97 articles published between January 2010 and March 1, 2025, 19 studies met the predefined inclusion criteria. A systematic search was conducted in PubMed, Scopus, Web of Science, CINAHL, PsycINFO, and Embase using predefined keywords. Two independent reviewers performed screening and data extraction. Methodological quality was appraised using the Cochrane Risk of Bias Tool, the Newcastle-Ottawa Scale, and the Critical Appraisal Skills Programme (CASP) Checklist. Qualitative and quantitative findings were synthesized thematically.

The 19 included studies addressed several overlapping application domains of AI-driven digital tools for pediatric diabetes self-management. Overall, 8 studies focused primarily on glucose prediction, glycemic monitoring, or pattern recognition; 4 studies evaluated insulin dosing optimization and clinical decision-support systems; 6 studies investigated personalized education, behavioral support, user engagement, or self-management learning interventions; 5 studies examined telemedicine, remote monitoring, or healthcare access; and 5 studies primarily addressed ethical, methodological, transparency, or implementation challenges.

AI-based digital tools have considerable potential to support diabetes self-management in children. Future research should prioritize long-term evaluations, the inclusion of diverse populations, and rigorous assessments of clinical outcomes, data privacy, and algorithm performance.

Cannabis sativa, a medicinal plant rich in cannabinoids, terpenoids, and flavonoids, has been shown to have various pharmacological activities. This study investigated the antidiabetic potential of C. sativa inflorescence extracts using in vitro and computational models. Dried C. sativa inflorescences were extracted sequentially with hexane, dichloromethane, and methanol, before their metabolites were identified by GC-MS. The extracts were tested for α-amylase and α-glucosidase inhibition, glucose uptake activity, and antioxidant effects using DPPH and nitric oxide (NO) inhibition assays. Thirty-six metabolites were further docked against diabetes-related proteins. Among the extracts, the hexane extract showed the strongest bioactivity with notable α-amylase inhibition (IC₅₀: 727 µg/mL), DPPH free radical scavenging (IC₅₀: 478.62 µg/mL), and nitric oxide inhibition activity (IC₅₀: 356.51 µg/mL). Docking analyses revealed strong binding affinities for 8-hydroxy-delta-9-THC, cannabivarin, and 9-tetrahydrocannabinol with DPP-4, PTP1B, and other target proteins. These findings highlight the potential of C. sativa inflorescences as a source of antidiabetic agents, warranting further in vivo and clinical validation.

Given that alpinetin possesses hypoglycemic and cardioprotective properties, it holds potential for co-administration with the antidiabetic agent glimepiride. The aim was to evaluate the impact of alpinetin on the pharmacokinetics and hypoglycemic efficacy of glimepiride, thereby providing a foundation for the development of alpinetin and informing its potential clinical translation. Pharmacokinetic studies were performed in rats following oral administration of glimepiride (1 mg/kg) alone or combined with alpinetin (30 mg/kg). The effect of the combination of glimepiride and alpinetin on blood glucose levels was investigated in a rat model of type 2 diabetes mellitus (T2DM). In vitro experiments were conducted to evaluate the effect of alpinetin on glimepiride metabolic stability and to assess its role on cytochrome P450 2C9 (CYP2C9) activity. Co-administration of glimepiride with alpinetin resulted in significant changes in the pharmacokinetics of glimepiride, as evidenced by an increase in area under the concentration-time curve (AUC), elimination half-life (t_1/2), maximum concentration (C_max), and a decrease in clearance. Glimepiride in combination with alpinetin enhanced the hypoglycemic effect in T2DM rats. Mechanistic studies in liver microsomes revealed that alpinetin improved glimepiride metabolic stability and inhibited CYP2C9 activity. The combination of glimepiride with alpinetin may increase the systemic exposure of glimepiride through inhibition of CYP2C9 activity. This likely contributes to the enhanced hypoglycemic effect observed, but also underscores the need for caution regarding the potential risk of hypoglycemia.

Sodium-glucose cotransporter 2 (SGLT2) inhibitors, including dapagliflozin and empagliflozin, are widely used for glycemic control in type 2 diabetes but may affect the risk of urinary tract infection (UTI).

This study compared the incidence of UTIs among women with diabetes treated with dapagliflozin versus empagliflozin.

In this randomized, double-blind clinical trial, 149 diabetic women aged ≥ 18 years were assigned to receive dapagliflozin 5 mg (n = 79) or empagliflozin 10 mg (n = 70) daily for three months. Fasting blood sugar (FBS), glycated hemoglobin (HbA1c), and serum creatinine (Cr) were measured at baseline and after treatment. Urinalysis and urine culture were used to confirm UTIs. Data were analyzed using SPSS version 28.0, with P < 0.05 considered statistically significant.

The mean age was 62.7 ± 9.7 years, with no baseline differences between groups. UTIs occurred in 12 patients overall: 2 (2.5%) in the dapagliflozin group and 10 (14.3%) in the empagliflozin group (OR = 0.16; 95% CI, 0.03 - 0.74; P = 0.009). No significant intergroup differences were observed in FBS, HbA1c, or Cr levels.

Empagliflozin was associated with a higher short-term incidence of UTIs than dapagliflozin, despite similar metabolic outcomes. Monitoring for UTIs is recommended when prescribing SGLT2 inhibitors, particularly empagliflozin. Trial Registration: This trial is registered with the Iranian Registry of Clinical Trials (IRCT20250129064554N1).