Objective: To explore the related factors of college students social network addiction based on problem behavior theory, so as to provide a basis for improving social networking addiction in this population. Methods: From May to June 2023, a method combining convenient sampling and cluster random sampling was used to select 1 768 college students from five universities in Shanghai for a questionnaire survey on social networking addiction, self esteem, loneliness, depressive symptoms, social support, interpersonal needs, sense of distress and frustration; at the same time, the physical exercise, smoking and drinking of college students were investigated. Multivariate Logistic regression analysis was applied to explore the association between the three systems of the problem behavior theory (personality, behavior, and social environment) and social networking addiction among college students. Results: The score on the Social Network Addiction Tendency Scale was (21.08±6.29) among college students, and the detection rate of social networking addiction was 66.29%. After adjusting for gender, family economic status, parental divorce status, and whether being an only child, multivariate Logistic regression analysis showed that in the personality system, higher loneliness ( OR =1.66) and higher depressive symptoms ( OR =2.18) were associated with increased risk of social networking addiction among college students; in the behavior system, alcohol consumption ( OR =1.42) was associated with higher risk of soical networking addiction compared to non drinkers; and in the social environment system, low social support ( OR =1.43) was associated with increased risk of social networking addiction (all P <0.05). Conclusions The rate of social networking addiction among college students is relatively high, and the systems of personality, behavior, and social environment are all related to social network addiction. Providing social support, cultivating healthy lifestyle habits, and increasing interpersonal interactions may help reduce excessive dependence on social networking among college students.

Objective To address the inter-observer annotation variability in echocardiographic image segmentation caused by image boundary ambiguity and differences in experts’ clinical backgrounds. Methods A framework was proposed that leveraged a conditional diffusion model, guided by cardiac ultrasound images, to learn the probability distribution of multi-expert annotations. A probabilistic consensus strategy was further introduced to dynamically fuse these annotations. This approach was designed to simultaneously aggregate clinical consensus among experts and preserve the diversity of the annotation distribution, thereby jointly modeling both the stable morphological features of the target anatomy and the reasonable variations inherent in expert annotations. Given the scarcity of authentic multi-expert annotations in public datasets like CAMUS, a synthetic multi-expert annotation system was developed using morphological operations. This system was designed to simulate three typical clinical annotation style (conservative, optimal, and aggressive), to provide a reliable data foundation for validating the proposed method. Results The proposed model significantly outperformed state-of-the-art methods in both left ventricular endocardium (LVEndo) and left ventricular epicardium (LVEpi) segmentation tasks. For LVEndo, the generalized energy distance () at the end-diastolic (ED) phase reached 0.073 1, representing a 43.9% reduction compared to the D-Persona model. For LVEpi, the decreased by 42.0% and 39.0% at the ED and end-systolic phases, respectively, relative to D-Persona. Furthermore, the structural fidelity improved by 2.7-3.5 percentage points for LVEndo and 1.4-2.2 percentage points for LVEpi compared to single-expert models, indicating a superior ability to capture diverse expert preferences. Conclusion By jointly modeling population-level consensus and annotation diversity, this work enables a unified characterization of anatomical structures and their associated annotation uncertainty in cardiac ultrasound images, offering a novel approach toward robust and interpretable segmentation in clinical settings.

Introduction: Leydig cells (LCs) are the principal source of testosterone in males, underpinning male reproductive health and androgendependent physiology. Precise isolation of viable human LCs is essential for mechanistic steroidogenesis research and cell-based therapeutic development. Existing protocols rely on density-gradient centrifugation, which is technically demanding and often compromises yield and viability. Here, we describe a simplified density-gradient-free approach using differential adhesion to enrich functional human LCs from testicular tissue. Methodology: Human testicular fragments (~5 mm³) were minced and enzymatically digested with collagenase IV (2 mg/mL) at 37°C for 20 min under gentle agitation (100 RPM). The suspension was filtered (45 µm) and plated onto poly-L-lysine-coated T25 flasks. After 24 hours, non-adherent cells were removed by PBS washing. Viability exceeded 90% by trypan blue exclusion. Cells were maintained in DMEM/F12 with 10% FBS, 1% Antibiotic-Antimycotic, and 10 ng/mL luteinizing hormone (LH) to preserve the mature LC phenotype. Characterization employed immunofluorescence and flow cytometry using antibodies against SF-1, StAR, LHCGR, PDGFRA, and TEM-1. Testosterone secretion was quantified by ELISA under basal conditions and LH-stimulated conditions (10 ng/mL). Results: The protocol yielded ~1.25 × 10⁶ LCs per gram of tissue with >80% purity. Adherent HLCs displayed dense cytoplasmic lipid granules and intercellular networks consistent with active steroidogenesis. Flow cytometry confirmed 84.7% StAR⁺ cells, indicative of a robust steroidogenic population. A distinct progenitor subpopulation (PDGFRα⁺/TEM-1⁺) comprising ~28% of primary cultures, suggests retention of regenerative capacity. Basal testosterone secretion averaged 8.88 ng/mL per 24 hours, confirming preserved functional activity post-isolation. Conclusion This differential-adhesion protocol efficiently isolates functional human LCs without density-gradient media. Multimodal validation integrating immunofluorescence, flow cytometry, and ELISA confirms both phenotypic identity and steroidogenic competence, providing a reproducible and accessible platform for LC research and translational applications in male hypogonadism and androgen replacement.
Leydig Cells

Introduction: Capivasertib is a selective oral AKT inhibitor approved for hormone receptor-positive, HER2-negative advanced breast cancer with AKT pathway mutations. As AKT is integral to insulin signaling, its inhibition predisposes patients to hyperglycemia. We report a case of severe capivasertib-induced hyperglycemia with profound insulin resistance in a non-diabetic patient. Case: A 56-year-old female with metastatic breast cancer (ER/ PR-positive, HER2-negative, AKT1- and ESR1-mutated, TMB-high) presented with severe hyperglycemia following capivasertib initiation. She had no prior diabetes history, with a baseline hemoglobin A1c of 5.6%. Her first cycle (200 mg twice daily, 7 April 2025) was uncomplicated metabolically. The second cycle was escalated to 400 mg twice daily on 21 April 2025. By Day 3, blood glucose rose significantly. Premixed insulin 20 units failed to achieve glycemic control, necessitating intravenous insulin infusion. Despite escalation to 30 units per hour, euglycemia could not be achieved. Notably, there was no biochemical evidence of diabetic ketoacidosis or hyperosmolar hyperglycemic state, and the patient remained hemodynamically stable. No corticosteroids or other contributing medications were administered. Blood glucose normalized spontaneously approximately 36 hours after the last capivasertib dose, and all insulin was weaned and discontinued by 26 April 2025. She remained euglycemic without antidiabetic therapy thereafter. The patient and family opted for palliative care, and she passed away on 6 May 2025. Conclusion Capivasertib can precipitate severe, insulin-resistant hyperglycemia even in non-diabetic patients, without progression to overt hyperglycemic crisis. Spontaneous resolution upon drug cessation supports a direct drugmediated mechanism via AKT-disrupted insulin signaling. Clinicians should monitor glucose closely during therapy and consider drug cessation in refractory cases. Further studies are warranted to guide optimal glycemic management.
capivasertib ; Hyperglycemia ; Insulins

Background/Aims: Dysregulated cholesterol metabolism is a hallmark of hepatocellular carcinoma (HCC) that drives tumor initiation and progression. However, clinical targeting of cholesterol metabolism has yielded limited benefits due to stringent feedback in tumor cells. Identifying a central mediator capable of restoring cholesterol homeostasis within the cell’s intrinsically fine-tuned regulatory framework is urgently needed. Methods: We integrated a proteomic dataset from patients with cholesterol-dysregulated HCC into a global cholesterol metabolic regulatory network to identify potential therapeutic targets for disrupted cholesterol homeostasis. The prognostic significance of the candidate targets was further validated in an independent cohort through immunohistochemistry. Functional and mechanistic studies were conducted in vitro using HCC cell lines and in vivo using mouse models. The pharmacological efficacy of the candidate agent was evaluated in both subcutaneous and orthotopic HCC mouse models. Results: ER lipid raft-associated 1 (ERLIN1), a pivotal regulator of cholesterol metabolism reprogramming, was identified as an independent favorable prognostic indicator in HCC. ERLIN1 constrains HCC progression both in vitro and in vivo by stabilizing the INSIG1–SCAP–SREBP2 axis and maintaining the metabolic balance of intracellular cholesterol. Under hypoxia, impaired factor-inhibiting hypoxia-1-dependent hydroxylation of ASB11 at asparagine residues 90 and 92 enhances ASB11-mediated ERLIN1 degradation. Pharmacological targeting of this axis using zoledronic acid (ZoA) attenuated HCC progression by weakening the ASB11–ERLIN1 interaction and restoring cholesterol homeostasis. Conclusions ERLIN1 represents a druggable metabolic vulnerability in cholesterol-dysregulated HCC. Targeting the ASB11–ERLIN1 axis with the clinically approved ZoA reestablishes cholesterol homeostasis and offers a promising therapeutic strategy to overcome the current limitations of cholesterol-targeted HCC therapies.

Objective: This study examined whether baseline levels of 14 serum biomarkers predicted antidepressant remission differently by sex at 12 weeks and 12 months. Methods: In a prospective cohort, 1,086 outpatients with depressive disorders received stepwise antidepressant treatment following a naturalistic protocol. Baseline serum samples were analyzed for biomarkers from six systems: immune (high-sensitivity C-reactive protein, tumor necrosis factor-alpha, interleukin-1 beta, interleukin-6, interleukin-4, interleukin-10), metabolic (leptin, ghrelin, total cholesterol), neurotrophic (brain-derived neurotrophic factor), neurotransmitter (serotonin), endocrine (cortisol), and nutritional (folate, homocysteine). Remission, defined as a Hamilton Depression Rating Scale scores ≤ 7, was assessed at 12 weeks and 12 months. Logistic regression models with biomarker-by-sex interaction and stratified analyses were used, adjusting for clinical covariates. Results: Higher baseline serotonin predicted 12-week remission in males but not in females. At 12 months, lower leptin and higher folate predicted remission only in males, while lower cortisol predicted remission only in females. These showed significant biomarker-sex interactions. No sex-specific interactions were found for immune markers. Conclusion Baseline serum biomarkers across biological systems showed sex-specific associations with treatment outcomes. Neurotransmitter, metabolic, endocrine, and nutritional markers may offer predictive value for sex-tailored, biomarker-informed treatment strategies in depression.

Background: Studies on whether donor-to-recipient sex match status affects long-term survival after liver transplantation (LT) have yielded contradictory results. This study evaluated whether donor-to-recipient sex match status influenced long-term survival after living donor liver transplantation (LDLT) or deceased donor liver transplantation (DDLT) at a high-volume center. Methods: The study included 6,664 patients who underwent primary LT between January 2000 and December 2022 at our institution. Patients were divided into four groups according to donor-to-recipient sex match status: male-to-male (n=3,427 [51.4%]), male-to-female (n=1,152 [17.3%]), female-to-male (n=1,385 [20.8%]), and female-to-female (n=700 [10.5%]). Results: Regarding clinical characteristics, the four groups differed significantly regarding background liver disease (P<0.001), model for end-stage liver disease score (P<0.001), serum protein induced by vitamin K absence or antagonist II level (P=0.003), presence of concurrent hepatocellular carcinoma (HCC; P<0.001), and type of LT (P=0.003). Overall survival (OS) of all LT recipients did not differ significantly among the groups (P=0.377). Donor-to-recipient sex match status did not affect long-term OS in either LDLT (P=0.176) or DDLT (P=0.220) groups. In addition, sex match status did not significantly influence posttransplant OS among patients who underwent LDLT without HCC (P=0.464), LDLT with HCC (P=0.236), DDLT without HCC (P=0.338), or DDLT with HCC (P=0.818). Conclusions Donor-to-recipient sex match status does not significantly affect posttransplant patient survival or HCC prognosis after LDLT or DDLT.

OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic had direct effects on population health through infection and morbidity, as well as indirect effects on population mental health. We estimated the network structure of post-traumatic stress symptoms (PTSS) and depressive symptoms throughout the pandemic in Korea and aimed to identify the most central and bridging symptoms. METHODS: Participants aged 30–64 years completed mental health surveys across 3 phases of the COVID-19 pandemic: March 2020 (n=1,925), February–March 2021 (n=1,754), and December 2021–January 2022 (n=1,595). Using PTSS and depressive symptom data, we conducted network analyses, and the primary measures of symptom importance (centrality) were expected influence and bridge expected influence. RESULTS: In the comorbidity network, although the most central symptoms fluctuated over the course of the pandemic, sleep problems were consistently identified as the most influential bridge symptoms throughout. The symptom network structure differed between the subacute and chronic phases of the pandemic. CONCLUSIONS We found evidence of changes in the network structure of PTSS and depressive symptoms, even as sleep problems retained a consistent role as a bridging symptom. Although overall network structures varied across phases of the pandemic, the bridging role of sleep-related symptoms remained consistently strong, suggesting that sleep problems may represent a general and enduring mechanism underlying PTSS–depression comorbidity. During future pandemics, prompt screening for sleep problems may help prevent the development of comorbidity between PTSS and depressive symptoms.

OBJECTIVES: This mixed-methods observational study aimed to examine the temporal relationship between trends in cigarette smoking prevalence and lung cancer mortality and incidence rates, and to estimate the latency period between smoking initiation and lung cancer diagnosis among smokers at the individual level. METHODS: Smoking prevalence data for 1960–2022 were reconstructed using data from the Korea National Health and Nutrition Examination Survey (1998–2022). Lung cancer mortality data (1983–2022) and incidence data (1999–2022) were obtained from Statistics Korea and the Korea Central Cancer Registry. The population latency period was estimated using peak comparison and distributed lag non-linear models. The individual latency period was estimated as the average time interval between age at smoking initiation and age at lung cancer diagnosis using individual-level data from the National Health Insurance Service cohort. RESULTS: In men, smoking prevalence peaked around 1985, whereas lung cancer mortality peaked around 2000 during 1960–2022, indicating a lag time of approximately 15 years. In women, lung cancer mortality peaked in 2002, while smoking prevalence peaked around the same time. The population-level latency period between smoking and lung cancer incidence was estimated to be 15 years after adjustment for age, gender, and year of outcome. The individual latency period was estimated to be 42.6 years (standard deviation [SD], 12.5) in men and 34.4 years (SD, 14.2) in women. Smoking intensity and age at initiation did not appear to shorten the individual latency period. CONCLUSIONS Estimates of the smoking-attributable lung cancer burden should account for historical smoking prevalence from approximately 15 years earlier.

OBJECTIVES: For employees, work-time control (WTC) may protect against burnout and turnover. However, evidence from Korean workplaces is limited. This study aimed to examine whether WTC is associated with burnout and turnover intention and to test whether burnout mediates this relationship. METHODS: We analyzed data from 4,745 wage workers in the 2024 wave of the Korean Work, Sleep, and Health Study. WTC was assessed across 6 domains, burnout was measured using the Korean Burnout Syndrome Scale, and turnover intention was assessed using a validated 4-item scale. Logistic regression was used to estimate the associations of WTC quartile with burnout and turnover intention, and mediation analysis was used to decompose the association between WTC and turnover intention through burnout. RESULTS: Among 4,745 workers, the prevalence of burnout was 3.9% and turnover intention was 34.5%; both increased stepwise across lower WTC quartiles. In adjusted models, workers in the lowest WTC quartile had higher odds of burnout (odds ratio [OR], 3.95; 95% confidence interval [CI], 2.41 to 6.47) and turnover intention (OR, 2.24; 95% CI, 1.85 to 2.71) than those in the highest quartile. Mediation analysis showed that burnout explained 36.6% (95% CI, 22.3 to 51.0) of the association between WTC and turnover intention. CONCLUSIONS Lower WTC was linked to higher burnout and turnover intention, with burnout explaining more than one-third of this relationship.