The sexual safety of people in mental health inpatient units is an increasingly important concern. Following provision of a co-designed staff training package (the Welcome Project) to support sexual safety on an Australian adult mental health inpatient unit, this qualitative study aimed to gain an understanding of barriers and enablers to implementation of sexual safety practices from the perspective of staff in this setting. Data was collected through semi-structured interviews with eleven clinicians. Directed content analysis was used to map data against the Consolidated Framework for Implementation Research and the Capability Opportunity and Motivation Model of behaviour change. The findings describe barriers and enablers to sexual safety related to key aspects of these frameworks: knowledge about sexual safety, knowledge about trauma-informed care, time to talk about sexual safety, role clarity, reluctance to talk about sexual safety, culture, leadership, physical environment, staffing, consumer and carer peer workers, and acuity. While training improved awareness, results from this study suggest that education alone was insufficient to support routine sexual safety discussions. Future implementation requires a multilevel approach that combines targeted training with clear role expectations, as well as adequate staffing, supportive leadership, and organisational commitment to sexual safety. In conclusion, while staff knowledge is important, the physical environment and leadership need to be considered and strategies in place to support clinicians to implement sexual safety training and routinely have conversations with consumers about sexual safety during inpatient admissions.

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.

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.

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.

Multi-cancer early detection (MCED) tests present a paradigm transform in cancer screening by detecting multiple cancer types from one blood sample. While studies have shown high levels of public interest in MCED screening, little is known about factors shaping individuals' perception of the emerging technology. Guided by the PRECEDE-PROCEED framework, we aimed to identify factors associated with the perception of value of MCED testing among American adults.

We conducted a cross-sectional secondary analysis of the Health Information National Trends Survey cycle 7 (HINTS 7) to identify factors associated with the perceived value of MCED screening. After removing respondents with missing outcome data, our final sample size was 6,728. Using the PRECEDE-PROCEED framework, candidate predictors were grouped into predisposing, reinforcing, and enabling factors. We used descriptive, survey-weighted analyses, spearman correlation analyses, survey-weighted multivariable logistic regression, and supervised machine learning analyses (logistic regression and random forest) to explore the associations.

Overall, 74.9% of the sample perceived MCED testing as very valuable. Trust-related domains showed the strongest associations with the outcome, including trust in physicians (OR = 1.89), trust in science (OR = 1.80), and trust in the healthcare system (OR = 1.64). Cancer information seeking (OR = 1.59), online health information use (OR = 1.63), smartphone access (OR = 1.54), cancer fatalistic beliefs (OR = 1.52), trust in government (OR = 1.50), knowledge of hepatitis B as a cancer risk factor (OR = 1.48), and family history of cancer (OR = 1.45) were also significantly associated with higher perceived value. Machine learning analyses demonstrated consistent predictor rankings, highlighting trust and health information engagement as the most influential determinants.

The value of MCED screening was largely driven by trust, cancer information seeking, and access to healthcare and health information resources. Our study highlights the efficacy of the PRECEDE-PROCEED approach to studying factors associated with complex health outcomes. Future implementation strategies should prioritize equitable communication, strengthen public trust, and improve access to reliable health information to facilitate informed decision-making regarding MCED testing.

Real-world oncology data are essential for clinical research and precision cancer care. However, genomic biomarkers are often embedded in scanned, unstructured clinical documents requiring manual abstraction before becoming available in cancer registries, delaying real-world evidence generation. This study evaluated and compared three open-source optical character recognition (OCR) approaches, Tesseract, EasyOCR, and a hybrid implementation, to determine which best enables automated extraction of Oncotype DX recurrence scores and improves the timeliness and quality of real-world oncology data.

We evaluated the feasibility of automated genomic data extraction using 675 Oncotype DX reports from a Midwestern U.S. health system. EasyOCR, Tesseract, and a hybrid OCR approach were used to extract recurrence scores from scanned reports. OCR-derived values were compared with manually abstracted scores and local cancer registry data. Performance was assessed using agreement, precision, recall, F1 score, and processing time. Multivariable logistic regression was performed to identify factors associated with discordance between registry-reported and manually abstracted scores.

The hybrid OCR approach demonstrated the highest performance, achieving 97% agreement with manual abstraction, precision of 0.997, recall of 0.972, and an F1 score of 0.984. Registry abstraction demonstrated comparable performance but required greater manual effort. Automated extraction substantially reduced processing time while maintaining high accuracy. Logistic regression showed registry discordance was largely independent of patient and tumor characteristics, with unknown progesterone receptor (PR) status as the only significant predictor.

Automated extraction of genomic biomarkers represents a scalable approach to reducing delays in cancer data availability. Earlier capture of genomic information may support cancer registry modernization and improve real-world evidence generation in precision oncology.

Immunotherapy-targeted combination therapy has transformed hepatocellular carcinoma (HCC) treatment, yet longitudinal patient-reported outcome (PRO) trajectories remain poorly characterized. We prospectively examined decision regret, hope, fatigue and quality of life during first-line treatment.

This convergent mixed-methods study enrolled 33 patients initiating first-line immunotherapy-targeted therapy at a Taiwan medical center (December 2022-October 2023). PROs were assessed across six cycles using validated instruments, and all participants were interviewed. Strands were integrated through joint display analysis.

Twenty-one patients (63.6%) completed six cycles; 12 (36.4%) discontinued. Completers maintained stable PROs with low regret, whereas discontinuers declined faster in EQ-5D utility (interaction B =  - 0.169 per cycle, p = .007) and showed a larger, non-significant rise in regret (+ 9.58, p = .051, d = 0.50; between-group p = .042). Hope declined in both groups (- 1.48, p = .003), correlating negatively with regret (r =  - .383, p = .028). Interviews centered on treatment-related discomfort (24/33), sustained hope for disease control (31/33) and financial strain (25/33); where regret was voiced (3/33) it concerned earlier points in the illness course rather than the current treatment decision. Integration yielded four expanded meta-inferences and one discordance, between measured and voiced regret.

Treatment completers maintain stable PROs, but more than one-third discontinued and experienced worse fatigue and greater regret, supporting pre-treatment counselling that is honest and informative rather than reassuring. Discontinuation marks a psychologically vulnerable transition, while universal hope decline warrants psychosocial monitoring for all patients. Given the sample size, predictors of regret are hypothesis-generating.