BackgroundAddictive non-suicidal self-injury （NSSI） behaviors among adolescents have become increasingly prominent， although previous studies have identified multiple related risk factors and have examined the association between screen time and NSSI behaviors， the impact of screen time on NSSI behaviors addiction， as well as the mediating role of family dysfunction in this relationship， remain to be further clarified. ObjectiveTo investigate the mediating role of family dysfunction in the relationship between screen time and NSSI behaviors addiction among adolescent female patients with depression disorder， with the aim of providing references for reducing NSSI behaviors addiction. MethodsFrom September 2024 to November 2025， a total of 652 adolescent female patients with depression disorder were enrolled from both outpatient and inpatient departments of Xiamen Xian-yue Hospital， all of whom met the diagnostic criteria for depressive episode （F32） or recurrent depressive disorder （F33） according to the International Classification of Diseases， tenth edition （ICD-10）. Assessments included a self-developed demographic questionnaire， screen use questionnaire， Chinese Family Assessment Instrument （C-FAI）， and Ottawa Self-injury Inventory Chinese Revised version （OSIC）. Among participants with NSSI behaviors， Spearman correlation analysis was used to examine the correlation between screen time and scale scores. Model 4 of the Process 4.1 for SPSS 26.0 was then applied to test the mediating role， and Bootstrapping procedure involving 5 000 replicates was employed to confirm the statistical significance. ResultsAmong the 652 patients， 569 （87.27%） exhibited NSSI behaviors. Among them， 398 cases （69.95%） belonged to the addictive NSSI group， and 171 cases （30.05%） belonged to the non-addictive NSSI group. The OSIC addiction dimension score was positively correlated with screen time and C-FAI scores （r_s=0.114， 0.224， P<0.01）. Family dysfunction mediated the relationship between screen time and NSSI addiction， with an indirect effect value of 0.036 （95% CI： 0.016–0.062）， accounting for 35.88% of the total effect. ConclusionScreen time may affect the NSSI behaviors addiction in adolescent female patients with depression disorder through family dysfunction. ［Funded by Joint Funds for the Innovation of Science and Technology， Fujian Province （number， 2025Y9762）］

Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

ObjectiveTo investigate the association between metabolic associated fatty liver disease （MAFLD） and the risk of atherosclerotic cardiovascular disease （ASCVD）， and to provide data support for the prevention and treatment of such metabolic-associated diseases in clinical practice. MethodsAn observation cohort was established for the workers of Kailuan who underwent physical examination for the first time from June 2006 to October 2007 and had complete liver assessment data， without the history of malignant tumor， MAFLD or ASCVD. According to the presence or absence of MAFLD， the patients were divided into non-MAFLD group with 67 565 patients and MAFLD group with 29 004 patients， and according to the presence or absence of ASCVD， the patients were divided into non-ASCVD group with 69 141 patients and ASCVD group with 481 patients. The group t-test or the Wilcoxon rank-sum test was used for comparison of continuous data between the two groups. The χ² test was used for comparison of categorical data between the two groups. The life-table method was used to calculate the cumulative incidence rates of new-onset ASCVD and MAFLD； the Kaplan-Meier method was used to plot the survival curves of the cumulative incidence rates of ASCVD in the MAFLD group and the non-MAFLD group and the cumulative incidence rates of MAFLD in the ASCVD group and the non-ASCVD group， and the log-rank test was used for comparison of cumulative incidence rates between two groups. A multivariate Cox proportional-hazards regression model analysis was used to investigate the impact of MAFLD on the risk of ASCVD and the impact of ASCVD on the risk of MAFLD. ResultsCompared with the non-MAFLD group， the MAFLD group had significantly higher levels of body mass index （BMI）， waist circumference， systolic blood pressure （SBP）， diastolic blood pressure （DBP）， resting heart rate， alanine aminotransferase， uric acid （UA）， fasting blood glucose （FBG）， triglyceride （TG）， total cholesterol， low-density lipoprotein cholesterol， and high sensitivity C-reactive protein （hs-CRP）， as well as significanty lower levels of estimated glomerular filtration rate （eGFR） and high-density lipoprotein cholesterol （all P <0.05）. Compared with the non-ASCVD group， the ASCVD group had significantly higher levels of BMI， waist circumference， SBP， DBP， UA， FBG， TG， and hs-CRP and a significantly lower level of eGFR （all P<0.05）. The incidence rate of new-onset ASCVD continued to increase over time in the MAFLD group and the non-MAFLD group， while the incidence rate of new-onset MAFLD firstly increased and then remained stable over time in the ASCVD group and the non-ASCVD group. There were 4 263 cases （14.70%） of new-osnet ASCVD in the MAFLD group， with an incidence density of 12.90 per 1 000 person-years， while there were 6 529 cases （9.66%） of new-osnet ASCVD in the non-MAFLD group， with an incidence density of 8.24 per 1 000 person-years， and there were significant differences in the incidence density and cumulative incidence rate of ASCVD between the two groups （χ²=519.09 and 531.80， both P<0.05）. There were 148 cases （30.77%） of new-onset MAFLD in the ASCVD group， with an incidence density of 40.10 per 1 000 person-years， while there were 32 194 cases （46.56%） of new-onset MAFLD in the non-ASCVD group， with an incidence density of 57.59 per 1 000 person-years， and there were significant differences in the incidence density and cumulative incidence rate of MAFLD between the two groups （χ²=19.29 and 30.78， both P<0.05）. The corrected multivariate Cox proportional-hazards regression model analysis showed that MAFLD was a risk factor for new-onset ASCVD （hazard ratio ［HR］=1.11， 95% confidence interval ［CI］： 1.06 — 1.16， P<0.001）， while ASCVD was a protective factor against new-onset MAFLD （HR=0.72， 95%CI： 0.61 — 0.85， P<0.001）. ConclusionThere is a significant association between MAFLD and ASCVD， with an increase in the risk of ASCVD in the MAFLD population and a reduction in the risk of MAFLD in the ASCVD population.

Background As one of the most severe occupational diseases in China, pneumoconiosis is significantly burdened by its complications, which adversely affects patients' quality of life. Objective To identify the influencing factors of complications in pneumoconiosis and to construct an early prediction model for pneumoconiosis complications, providing theoretical guidance for clinical diagnosis, treatment, and rehabilitation. Methods A case-control study was conducted using data from the Chongqing 5G Pneumoconiosis Rehabilitation Management Information Platform. A total of 1872 pneumoconiosis patients with complications, who received rehabilitation at various rehabilitation stations in Chongqing from January 2021 to December 2024, were enrolled as the case group. Concurrently, 2348 patients without complications from the same platform and period were included as the control group. Univariate analysis, LASSO regression, and logistic regression were employed to identify influencing factors for complications. An extreme gradient boosting (XGBoost) model was trained using ten-fold cross-validation to predict pneumoconiosis complications. The SHapley Additive exPlanations (SHAP) method was applied for model visualization. Results The analysis of influencing factors revealed that increased age, silicosis type, advanced stage of pneumoconiosis, dependence in activities of daily living, abnormal muscle strength, increased dyspnea index, presence of cough, viscous sputum, impaired cardiac function, severe abnormality in the 6-minute walk test (6MWT), and increased Borg score were risk factors for complications (P<0.05). The XGBoost model demonstrated an area under the curve (AUC) of receiver operating characteristic of 0.718, and a Brier score of 0.211 for the calibration curve. Decision curve analysis demonstrated a superior net benefit within the threshold probability range of 0.2 to 1.0 compared to "all-patient intervention" and "no-patient intervention" strategies, indicating good predictive performance and significant clinical utility. SHAP visualization identified the top six important features as Borg score, age, 6MWT, muscle strength, pneumoconiosis stage, and cough symptoms. Conclusion Multiple factors influence the occurrence of complications in pneumoconiosis patients. Clinical attention should be focused on elderly patients with decreased cardiopulmonary reserve, pronounced respiratory symptoms, and diminished muscle strength. The XGBoost model demonstrates satisfactory discrimination, calibration, and clinical applicability in predicting pneumoconiosis complications and may serve as a useful reference for clinical decision-making.

AIM:To assess the efficacy of intravitreal conbercept for treating neovascular age-related macular degeneration(nAMD)under a treat-and-extend(T & E)regimen.METHODS: A retrospective analysis was conducted on nAMD patients followed over a 2-year period(May 2020 to May 2022). All eyes received three monthly loading intravitreal injections of conbercept, followed by a T& E regimen in which the injection interval was extended by 2 or 4 wk according to disease activity, up to a maximum of 16 wk. When disease activity recurred, the interval was shortened. Patients were divided into initial and non-initial treatment groups based on treatment history. Best-corrected visual acuity(BCVA), central macular thickness(CMT), injection frequency, and intervals between injections over the 24-month follow-up were compared.RESULTS:Totally 27 patients(15 males and 12 females, 33 eyes)were enrolled. In the initial treatment group(18 eyes, mean age 65.72±12.32 y), BCVA significantly improved at 1, 3, and 6 mo(P<0.05), and CMT significantly improved at 1 and 3 mo(P<0.05). In the non-initial treatment group(15 eyes, mean age 69.00±9.21 y), BCVA improved significantly at 3 mo(P<0.05), whereas CMT remained stable(P >0.05). Baseline CMT was similar between the groups(P>0.05). However, significant differences were observed at multiple post-injection time points(P<0.05). The total number of injections did not differ between the groups(P>0.05). Intervals between injections varied, with the majority at 4 and 3-4 mo in the initial and non-initial treatment groups, respectively.CONCLUSION:Initiating intravitreal conbercept therapy under a T & E regimen results in superior visual and anatomical outcomes compared with non-initial treatment.

Objective To evaluate the effectiveness of schistosomiasis surveillance in Jiangsu Province during the stage moving from transmission control to transmission interruption, and to analyze the current risk and challenges, so as to provide the evidence for achieving the target of schistosomiasis elimination. Methods Schistosomiasis surveillance data were collected from Jiangsu Province from 2012 to 2024, and the endemic areas, Schistosoma japonicum infections in humans and livestock, Oncomelania hupensis snail distribution and implementation of integrated interventions were descriptively analyzed. In addition, the trends in areas with snails, seroprevalence of human S. japonicum infections and numbers of advanced schistosomiasis cases were assessed using a Joinpoint regression model. Results The endemic areas of schistosomiasis continued to shrink in Jiangsu Province from 2012 to 2024, with the number of schistosomiasis-eliminated counties (cities, districts) increasing from 53 (75.71%) to 63 (96.92%), and interruption of schistosomiasis transmission was achieved across the province. A total of 4 600 300 person-times were tested for serum antibodies against S. japonicum, with 28 719 person-times positive detected; and 616 500 person-times were tested S. japonicum infections among local residents in Jiangsu Province from 2012 to 2024, with only 3 egg-positives detected, and no egg-positives found since 2017. A total of 187 600 herd-times were tested for schistosomiasis in livestock, and no S. japonicum infections were found. O. hupensis snail survey was performed covering 1 018 408.97 hm², and a total of 35 556.35 hm² was found with snail-infested habitats, including 174.40 hm2 of emerging snail-infested habitats. A total of 1 102 800 O. hupensis snails were identified for S. japonicum infections, and no infections were found. The areas of snail-infested habitats appeared a tendency towards a rise in Jiangsu Province from 2019 to 2023 (APC = 23.67%, P < 0.05), and the actual areas of snail-infested habitats appeared a tendency towards a decline from 2012 to 2015 (APC = −22.77%, P < 0.05), and towards a rise from 2015 to 2023 (APC = 9.76%, P < 0.01). The seroprevalence of anti-S. japonicum antibodies appeared a tendency towards a decline among residents in Jiangsu Province from 2017 to 2023 (APC = −14.92%, P < 0.01). In addition, the number of newly diagnosed advanced schistosomiasis cases appeared a tendency towards a decline from 2012 to 2024 (APC = −12.02%, P < 0.01), and the numbers of advanced schistosomiasis patients requiring treatment showed a tendency towards a decline from 2012 to 2021 (APC = −10.56%, P < 0.01) and from 2021 to 2023 (APC = −20.06%, P < 0.01). Conclusions Great progresses had been achieved in schistosomiasis control in Jiangsu Province following transmission control, and transmission interruption had been achieved; however, there are still snail-infested habitats. High-intensity surveillance and integrated control are required to be maintained to advance the achievement of the target of schistosomiasis elimination in Jiangsu Province.

Cancer remains a leading cause of global mortality, necessitating the development of advanced therapeutic strategies with enhanced efficacy and reduced systemic toxicity. Among promising bioactive agents, lactoferrin (LF)—a multifunctional iron-binding glycoprotein abundantly found in mammalian milk and exocrine secretions—has garnered significant interest for its potent and multifaceted anti-cancer properties. This review provides a comprehensive analysis of the current understanding of LF’s role in oncology, encompassing its structural biology, diverse mechanisms of action, and groundbreaking advancements in its application through nano-engineering. LF exerts anti-tumor effects through multiple pathways, including extracellular action, intracellular action, and immune regulation. It demonstrates a remarkable affinity for cancer cell membranes, binding to overexpressed anionic components such as glycosaminoglycans and sialic acids, as well as to specific receptors including the low-density lipoprotein receptor-related protein-1 (LRP-1). This selective binding facilitates targeted uptake. Upon internalization, LF orchestrates a direct assault by inducing cell-cycle arrest in phases such as G0/G1 or S phase through the modulation of key regulators including cyclins, CDKs, and p53. Furthermore, it promotes programmed cell death via apoptotic pathways, involving caspase activation and downregulation of anti-apoptotic proteins such as survivin. A more recently elucidated mechanism is the induction of ferroptosis, an iron-dependent form of cell death characterized by overwhelming lipid peroxidation. Beyond direct cytotoxicity, LF acts as a potent immunomodulator. It enhances natural killer (NK) cell activity, modulates T-lymphocyte populations, and crucially reprograms tumor-associated macrophages (TAMs) from a pro-tumor M2 state to an anti-tumor M1 state, thereby reversing the immunosuppressive tumor microenvironment (TME). The translation of LF’s potential has been significantly accelerated by nanotechnology. The inherent biocompatibility and natural tumor-targeting capabilities of LF make it an ideal platform for sophisticated drug-delivery systems. This review details various fabrication strategies for LF-based nanoparticles (NPs), including self-assembly, sol-in-oil emulsion, and electrostatic nanocomplexes, among others. Research demonstrates that nano-formulations not only protect LF from degradation but also enhance its bioactivity and anti-cancer potency. More importantly, LF NPs serve as versatile carriers for a wide array of therapeutic agents, including conventional chemotherapeutics, natural compounds, and imaging agents. These engineered systems enable synergistic therapy and facilitate site-specific delivery. Notably, the ability of LF to bind to receptors on the blood-brain barrier (BBB) has been leveraged to develop nano-systems for glioblastoma treatment. Other innovative designs utilize LF to modulate the TME—for instance, by alleviating tumor hypoxia to sensitize cells to radiotherapy and chemotherapy. Despite compelling pre-clinical evidence, the clinical translation of LF and its nano-formulations remains nascent. While early-phase trials have established a favorable safety profile for recombinant human LF, larger Phase III studies have yielded mixed results, underscoring the complexity of its action in humans. Key challenges include enhancing drug targeting, optimizing loading efficiency, ensuring batch-to-batch reproducibility, and achieving deep tumor penetration. Future research must focus on the rational design of next-generation LF-NPs. This entails developing standardized manufacturing protocols, engineering “smart” stimuli-responsive systems for targeted drug release in the TME, and constructing multi-targeting platforms. A concerted interdisciplinary effort is paramount to bridge the gap between bench and bedside. In conclusion, LF, particularly in its nano-engineered forms, represents a highly promising and versatile agent in the oncological arsenal, holding immense potential for precise and effective cancer therapy.

Cancer remains a leading cause of global mortality, necessitating the development of advanced therapeutic strategies with enhanced efficacy and reduced systemic toxicity. Among promising bioactive agents, lactoferrin (LF)—a multifunctional iron-binding glycoprotein abundantly found in mammalian milk and exocrine secretions—has garnered significant interest for its potent and multifaceted anti-cancer properties. This review provides a comprehensive analysis of the current understanding of LF’s role in oncology, encompassing its structural biology, diverse mechanisms of action, and groundbreaking advancements in its application through nano-engineering. LF exerts anti-tumor effects through multiple pathways, including extracellular action, intracellular action, and immune regulation. It demonstrates a remarkable affinity for cancer cell membranes, binding to overexpressed anionic components such as glycosaminoglycans and sialic acids, as well as to specific receptors including the low-density lipoprotein receptor-related protein-1 (LRP-1). This selective binding facilitates targeted uptake. Upon internalization, LF orchestrates a direct assault by inducing cell-cycle arrest in phases such as G0/G1 or S phase through the modulation of key regulators including cyclins, CDKs, and p53. Furthermore, it promotes programmed cell death via apoptotic pathways, involving caspase activation and downregulation of anti-apoptotic proteins such as survivin. A more recently elucidated mechanism is the induction of ferroptosis, an iron-dependent form of cell death characterized by overwhelming lipid peroxidation. Beyond direct cytotoxicity, LF acts as a potent immunomodulator. It enhances natural killer (NK) cell activity, modulates T-lymphocyte populations, and crucially reprograms tumor-associated macrophages (TAMs) from a pro-tumor M2 state to an anti-tumor M1 state, thereby reversing the immunosuppressive tumor microenvironment (TME). The translation of LF’s potential has been significantly accelerated by nanotechnology. The inherent biocompatibility and natural tumor-targeting capabilities of LF make it an ideal platform for sophisticated drug-delivery systems. This review details various fabrication strategies for LF-based nanoparticles (NPs), including self-assembly, sol-in-oil emulsion, and electrostatic nanocomplexes, among others. Research demonstrates that nano-formulations not only protect LF from degradation but also enhance its bioactivity and anti-cancer potency. More importantly, LF NPs serve as versatile carriers for a wide array of therapeutic agents, including conventional chemotherapeutics, natural compounds, and imaging agents. These engineered systems enable synergistic therapy and facilitate site-specific delivery. Notably, the ability of LF to bind to receptors on the blood-brain barrier (BBB) has been leveraged to develop nano-systems for glioblastoma treatment. Other innovative designs utilize LF to modulate the TME—for instance, by alleviating tumor hypoxia to sensitize cells to radiotherapy and chemotherapy. Despite compelling pre-clinical evidence, the clinical translation of LF and its nano-formulations remains nascent. While early-phase trials have established a favorable safety profile for recombinant human LF, larger Phase III studies have yielded mixed results, underscoring the complexity of its action in humans. Key challenges include enhancing drug targeting, optimizing loading efficiency, ensuring batch-to-batch reproducibility, and achieving deep tumor penetration. Future research must focus on the rational design of next-generation LF-NPs. This entails developing standardized manufacturing protocols, engineering “smart” stimuli-responsive systems for targeted drug release in the TME, and constructing multi-targeting platforms. A concerted interdisciplinary effort is paramount to bridge the gap between bench and bedside. In conclusion, LF, particularly in its nano-engineered forms, represents a highly promising and versatile agent in the oncological arsenal, holding immense potential for precise and effective cancer therapy.

Objective To explore the effectiveness of the generative large language model MedGo in nursing decision-making for elderly patients with multimorbidity. Methods A quasi-randomized controlled trial study was conducted involving 6 junior nurses, 6 senior nurses and the MedGo model from January 1, 2025 to March 31, 2025 at the Emergency Internal Medicine Ward of Shanghai East Hospital Affiliated to Tongji University. Clinical data of 120 elderly patients with multimorbidity were analyzed to compare the performance of the three groups in four tasks (nursing diagnosis assessment, nursing intervention formulation, complication identification, and complication prevention) from three evaluation dimensions: decision-making time consumption, decision accuracy, and decision-making quality. Results In terms of decision-making time, the senior nurse group completed all four tasks faster than the junior nurse group (P＜0.01), and the MedGo group completed all four tasks faster than the junior nurse group (P＜0.001) and the senior nurse group (P＜0.001). In terms of decision-making accuracy, senior nurse group scored higher than junior nurse group in all four tasks (P＜0.001), while the MedGo group outperformed the senior nurse group only in complication identification (P＜0.001). In terms of decision-making quality, the MedGo group scored higher than junior nurse group (P＜0.001) and senior nurse group (P＜0.001) in all four tasks. Conclusions The MedGo model demonstrates advantages of high efficiency, accuracy, and quality in nursing decision-making for elderly patients with multimorbidity; senior nurses outperform junior nurses in decision-making, providing diverse references for clinical nursing decision-making.

ObjectiveTo investigate the changes in chemical components of Gardeniae Fructus（GF） before and after being charred， providing data support for research on the material basis of GF Carbonisata（GFC）. MethodsUltra-performance liquid chromatography-quadrupole-electrostatic field orbitrap high-resolution mass spectrometry（UPLC-Q-Orbitrap MS/MS） was used to conduct a comprehensive analysis of the chemical components in GF and GFC under positive and negative ion modes with Compound Discoverer 3.3 software and online database. Then， principal component analysis and partial least squares-discriminant analysis in SIMCA14.1 software were used to analyze the MS data of each sample. Based on the principle of variable importance in the projection（VIP） value>1， differential secondary and primary metabolites before and after carbonization were screened. In addition， MetaboAnalyst website was used for pathway enrichment of Kyoto Encyclopedia of Genes and Genomes（KEGG）， so as to provide a reference for clarifying the processing mechanism. ResultsA total of 185 components were identified， including 96 secondary metabolites and 89 primary metabolites. These components were classified into nine categories， primarily including iridoid glycosides， flavonoids， and terpenoids， their fragmentation pathways were also analyzed. Simultaneously， multivariate statistical analysis was performed on the secondary and primary metabolites， identifying 70 and 59 differential metabolites， respectively. The secondary metabolites were enriched in two metabolic pathways， including C5-branched dibasic acid metabolism and flavonoid and flavonol biosynthesis， while the primary differential metabolites were enriched in seven pathways such as linoleic acid metabolism and tyrosine metabolism. ConclusionThe chemical components of GF change significantly after carbonization， with a significant decrease in the contents of iridoid glycosides and terpenoids such as hydroxyisogeniposide， crocin Ⅱ， crocetin， and jasminoside B. while the contents of 4-hydroxycoumarin， geniposidic acid， gentiopicroside， and gardenoside methyl ester increase significantly. This change is presumed to be associated with the enhanced cooling and hemostatic effects of the processed products. The identified key components provide a basis for elucidating the material basis underlying the efficacy changes before and after carbonization.