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 construct a closed-loop management model for externally dispensed intravenous prescriptions， and to provide reference for standardized management of externally dispensed intravenous prescriptions. METHODS Based on the Expert Consensus on Closed-loop Management of Externally Dispensed Intravenous Prescriptions in Guangxi Zhuang Autonomous Region previously formulated by our hospital， risk points during the entire process were systematically identified through multidisciplinary team brainstorming and a fishbone diagram. A series of strategies were subsequently formulated and implemented， including qualifying designated external dispensing pharmacies and the drug catalogs， operating and maintaining the hospital information system and the Pharmacy Intravenous Admixture Service （PIVAS） intelligent management platform， and strengthening differentiated training for staff in the whole workflow. A whole-process closed-loop management system was constructed with PIVAS as the co re hub and the daytime chemotherapy center as the safety terminal. RESULTS A total of 3 cooperating pharmacies and an initial drug list comprising 35 product specifications were selected. A closed‑loop management process encompassing hospital outpatient prescribing， patient drug purchase in designated pharmacies， PIVAS drug dispensing， and medication use in daytime chemotherapy center was successfully established. This system enabled the mandatory grouping and association of externally dispensed intravenous prescriptions with in-hospital diluents， full-process verification based on drug traceability codes， intelligent monitoring of infusion parameters， and whole-process data traceability. CONCLUSIONS The constructed model effectively resolves the coordination and safety oversight during the use of externally dispensed intravenous drugs from out-of-hospital circulation to in-hospital use， and has preliminarily enabled procedural standardization， whole-process information traceability， and proactive control of medication risks.

Houpo Sanwutang， included in the Catalogue of Ancient Classical Prescriptions （Second Batch）， was first recorded in the Synopsis of Golden Chamber written by ZHANG Zhongjing from the Eastern Han dynasty and was modified by successive generations of medical experts. A total of 37 pieces of effective data involving 37 ancient Chinese medical books were retrieved from different databases. Through literature mining， statistical analysis， and data processing， combined with modern articles， this study employed bibliometrics to investigate the historical origin， composition， decoction methods， clinical application， and other key information. The results showed that the medicinal origin of Houpo Sanwutang was clearly documented in classic books. Based on the conversion of the measurements from the Han Dynasty， it is recommended that 110.4 g Magnolia Officinalis Cortex， 55.2 g Rhei Radix et Rhizoma， and 72 g Aurantii Fructus Immaturus should be taken. Magnolia Officinalis Cortex and Aurantii Fructus Immaturus should be decocted with 2 400 mL water first， and 1 000 mL should be taken from the decocted liquid. Following this， Rhei Radix et Rhizoma should be added for further decoction， and then 600 mL should be taken from the decocted liquid. A single dose of administration is 200 mL， and the medication can be stopped when patients restore smooth bowel movement. Houpo Sanwutang has the effect of moving Qi， relieving stuffiness and fullness， removing food stagnation， and regulating bowels. It can be used in treating abdominal distending pain， guarding， constipation， and other diseases with the pathogenesis of stagnated heat and stagnated Qi in the stomach. The above results provide reference for the future development and research of Houpo Sanwutang.

Objective: To explore the long term trend of forced vital capacity to weight index (FWI) among Chinese Han students aged 7-18 from 2000 to 2019, and to predict its changes over the next decade, so as to provide scientific evidences for targeted health interventions and school health policies. Methods: Based on the data of the five Chinese National Surveys on Students Constitution and Health conducted from 2000 to 2019, a total of 216 500, 233 565, 215 267, 214 256 and 212 632 Han students aged 7-18 were included, respectively. The long term trend of FWI among students was analyzed, and the GM (1,1) grey model was used to predict FWI changes over the next decade. Subgroup analyses were conducted by sex, age, and urban-rural residence. Results: The FWI levels of Chinese Han students aged 7-18 were (55.30±11.47)(47.43±11.92)(48.11±12.46)(48.75±12.81)(50.93±13.11)mL/kg in 2000, 2005, 2010, 2014, and 2019, respectively. The FWI of Chinese Han students showed a decreasing then increasing trend from 2000 to 2019, reaching the lowest point of approximately 47.03 mL/kg around 2006, and was projected to recover to 52.88 mL/kg by 2029. Boys had higher FWI for each year and the total level than girls from 2000 to 2019( t =72.58-304.66), and the decline between 2000 and 2005 was smaller in boys (13.1%) than in girls (15.4%). However, the gender gap gradually narrowed and was projected to reduce to 5.36 mL/kg by 2029. FWI increased with age, with the largest difference observed in 2014 between the 7-9 and 16-18 age groups (8.62 mL/kg). Before 2014, urban boys had slightly lower FWI than rural boys; the gap narrowed thereafter, and their FWI levels were expected to become similar by 2029. Urban girls generally had higher FWI than rural girls, and the urban-rural gap showed an increasing trend. By 2029, the largest difference was projected to occur in the 13-15 age group, reaching 7.74 mL/kg. Conclusions The FWI of Chinese Han students showed a trend of initial decline followed by a gradual increase from 2000 to 2019, with notable differences across sex, age, and urban-rural residence. Greater attention should be paid to the respiratory health of rural girls, and effective measures should be taken to reduce urban-rural disparities.

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline, functional impairment, and neuropsychiatric symptoms. It represents the most prevalent form of dementia among the elderly population. Accumulating evidence indicates that oxidative stress plays a pivotal role in the pathogenesis of AD. Notably, elevated levels of oxidative stress have been observed in the brains of AD patients, where excessive reactive oxygen species (ROS) can cause extensive damage to lipids, proteins, and DNA, ultimately compromising neuronal structure and function. Amyloid β‑protein (Aβ) has been shown to induce mitochondrial dysfunction and calcium overload, thereby promoting the generation of ROS. This, in turn, exacerbates Aβ aggregation and enhances tau phosphorylation, leading to the formation of two pathological features of AD: extracellular Aβ plaque deposition and intracellular neurofibrillary tangles (NFTs). These events ultimately culminate in neuronal death, forming a vicious cycle. The interplay between oxidative stress and these pathological processes constitutes a core link in the pathogenesis of AD. The signaling pathways mediating oxidative stress in AD include Nrf2, RCAN1, PP2A, CREB, Notch1, NF‑κB, ApoE, and ferroptosis. Nrf2 signaling pathway serves as a key regulator of cellular redox homeostasis, exerts important antioxidant capacity and protective effects in AD. RCAN1 signaling pathway, as a calcineurin inhibitor, and modulates AD progression through multiple mechanisms. PP2A signaling pathway is involved in regulating tau phosphorylation and neuroinflammation processes. CREB signaling pathway contributes to neuroplasticity and memory formation; activation of CREB improves cognitive function and reduce oxidative stress. Notch1 signaling pathway regulates neuronal development and memory, participates in modulation of Aβ production, and interacts with Nrf2 toco-regulate antioxidant activity. NF‑κB signaling pathway governs immune and inflammatory responses; sustained activation of this pathway forms “inflammatory memory”, thereby exacerbating AD pathology. ApoE signaling pathway is associated with lipid metabolism; among its isoforms, ApoE-ε4 significantly increases the risk of AD, leading to elevated oxidative stress, abnormal lipid metabolism, and neuroinflammation. The ferroptosis signaling pathway is driven by iron-dependent lipid peroxidation, and the subsequent release of lipid peroxidation products and ROS exacerbate oxidative stress and neuronal damage. These interconnected pathways form a complex regulatory network that regulates the progression of AD through oxidative stress and related pathological cascades. In terms of therapeutic strategies targeting oxidative stress, among the drugs currently used in clinical practice for AD treatment, memantine and donepezil demonstrate significant therapeutic efficacy and can improve the level of oxidative stress in AD patients. Some compounds with antioxidant effects (such asα-lipoic acid and melatonin) have shown certain potential in AD treatment research and can be used as dietary supplements to ameliorate AD symptoms. In addition, non-drug interventions such as calorie restriction and exercise have been proven to exerted neuroprotective effects and have a positive effect on the treatment of AD. By comprehensively utilizing the therapeutic characteristics of different signaling pathways, it is expected that more comprehensive multi-target combination therapy regimens and combined nanomolecular delivery systems will be developed in the future to bypass the blood-brain barrier, providing more effective therapeutic strategies for AD.

Proanthocyanidin B_2(PAC-B_2), a polyphenolic dimeric compound comprising two epicatechin molecules linked by a C-C bond, is extensively found in traditional Chinese medicines, with anti-tumor and anti-oxidant activities. Given the limited bioavailability, a thorough investigation and comprehensive understanding of PAC-B_2 metabolism in vivo are essential for elucidating therapeutic forms and mechanisms. In the present study, ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS) in the negative ion mode was employed to acquire the MS/MS information of PAC-B_2 and metabolites in urine and feces samples of the rats administrated with PAC-B_2. Online energy-resolved MS(ER-MS) was applied as supplementary to obtain the full collision energy ramp-MS~2 spectra(FCER-MS~2) of isomers-of-interest, which implied comprehensive MS~2 information of targeted compounds. Finally, the possible metabolic pathways of PAC-B_2 in rats were proposed. The primary fragmentation behaviors of PAC-B_2 in the negative ion mode included quinone methide fission between C_4-C_8 bond, retro Diels-Alder cracking of F-ring, heterocyclic ring fission of C-ring, and neutral loss of small molecules such as H_2O. A total of 25 metabolites were tentatively elucidated in urine and feces samples of rats administrated with PAC-B_2 by fragmentation pattern and reported literature. Two groups of isomers, M3/M4/M5 and M9/M11, were confirmatively differentiated based on the relationships between optimal collision energy provided by FCER-MS~2 and bond properties, including bond length and bond dissociation energy. In addition to the ring-opening and methylation, PAC-B_2 could also be metabolized into epicatechin and low molecular weight phenolic acids, which were subsequently subjected to dehydroxylation, ring-opening, methylation, sulfation, and glucuronidation. The structural information provided by online ER-MS and FCER-MS~2 enabled the differentiation of isomers and improved the identification confidence. More importantly, the present study deeply analyzes the in vivo metabolic pathways of PAC-B_2, providing a basis for the research on the pharmacological mechanism of this compound.
Animals ; Proanthocyanidins/urine* ; Rats ; Male ; Drugs, Chinese Herbal/chemistry* ; Rats, Sprague-Dawley ; Tandem Mass Spectrometry ; Chromatography, High Pressure Liquid ; Feces/chemistry* ; Molecular Structure

Accurate prediction of drug-target interactions (DTIs) plays a pivotal role in drug discovery, facilitating optimization of lead compounds, drug repurposing and elucidation of drug side effects. However, traditional DTI prediction methods are often limited by incomplete biological data and insufficient representation of protein features. In this study, we proposed KG-CNNDTI, a novel knowledge graph-enhanced framework for DTI prediction, which integrates heterogeneous biological information to improve model generalizability and predictive performance. The proposed model utilized protein embeddings derived from a biomedical knowledge graph via the Node2Vec algorithm, which were further enriched with contextualized sequence representations obtained from ProteinBERT. For compound representation, multiple molecular fingerprint schemes alongside the Uni-Mol pre-trained model were evaluated. The fused representations served as inputs to both classical machine learning models and a convolutional neural network-based predictor. Experimental evaluations across benchmark datasets demonstrated that KG-CNNDTI achieved superior performance compared to state-of-the-art methods, particularly in terms of Precision, Recall, F1-Score and area under the precision-recall curve (AUPR). Ablation analysis highlighted the substantial contribution of knowledge graph-derived features. Moreover, KG-CNNDTI was employed for virtual screening of natural products against Alzheimer's disease, resulting in 40 candidate compounds. 5 were supported by literature evidence, among which 3 were further validated in vitro assays.
Alzheimer Disease/drug therapy* ; Biological Products/therapeutic use* ; Humans ; Neural Networks, Computer ; Machine Learning ; Drug Discovery/methods* ; Algorithms ; Drug Evaluation, Preclinical/methods*

The biological nitrogen removal technology utilizing heterotrophic nitrification-aerobic denitrification (HN-AD) bacteria has shown effectiveness in wastewater treatment. However, the nitrogen removal efficiency of HN-AD bacteria significantly decreases as the salinity increases. To tackle the challenge of treating high-salt and high-nitrogen wastewater, we isolated a moderately halophilic HN-AD strain 5505 from a salt lake in Xinjiang. The strain was identified based on morphological, physiological, and biochemical characteristics and the 16S rRNA gene sequence. Single-factor experiments were carried out with NH₄⁺-N, NO₃^--N, and NO₂^--N as sole or mixed nitrogen sources to study the nitrifying effect, denitrifying effect, and nitrogen metabolism pathway of the strain. The strain was identified as Halomonas sp.. It can grow in the presence of 1%-25% (W/V) NaCl and exhibited efficient nitrogen removal ability in the presence of 3%-8% NaCl. At the optimal NaCl concentration (8%), the strain showed the NH₄⁺-N, NO₃^--N and NO₂^--N removal rates of 100.0%, 94.11% and 74.43%, respectively. Strain 5505 removed inorganic nitrogen mainly by assimilation, which accounted for over 62.68% of total nitrogen removal. In the presence of mixed nitrogen sources, strain 5505 showed a preference for utilizing ammonia, with a potential HN-AD pathway of NH₄⁺→NH₂OH→NO₂^-→NO₃^-→NO₂^-→NO/N₂O/N₂. The findings provide efficient salt-tolerant bacterial resources, enhance our understanding of biological nitrogen removal, and contribute to the nitrogen removal efficiency improvement in the treatment of high-salt and high-nitrogen wastewater.
Halomonas/classification* ; Nitrogen/isolation & purification* ; Denitrification ; Nitrification ; Wastewater/microbiology* ; Aerobiosis ; Biodegradation, Environmental ; Salinity

Objective To identify disulfidptosis-related gene(DRG)in acute myocardial infarction(AMI)by bioinformatics,analyze the molecular pattern of DRGs in AMI,and construct a DRGs-related prediction model.Methods AMI-related datasets were downloaded from the Gene Expression Omnibus database,and DRGs with differential expression were screened in AMI.CIBERSORT method was used to analyze the immune infiltration.Based on the differentially expressed DRGs,the AMI patients were classified into distinct subtypes via consensus clustering,followed by immune infiltration analysis,differential expression analysis,gene ontology and Kyoto encyclopedia of genes and genomes enrichment analysis,and gene set variation analysis.Weighted gene co-expression network analysis(WGCNA)was then performed to construct subtype-associated modules and identify hub genes.Finally,least absolute shrinkage and selection operator,random forest,and support vector machine-recursive feature elimination were used to screen feature genes to construct a DRGs-related prediction model.The model's diagnostic efficacy was evaluated by nomogram and receiver operating characteristic(ROC)curve analysis,followed by external validation.Results Nine differentially expressed DRGs were identified between AMI patients and controls.Based on the expression levels of these nine DRGs,AMI patients were divided into two DRGs subtypes,C1 and C2.Increased infiltration of monocytes,M0 macrophages,and neutrophils was observed in AMI patients and C1 subtype(all P<0.05),indicating a close correlation between DRGs and immune cells.There were 257 differentially expressed genes between the C1 and C2 subtypes,which were related to biological processes such as myeloid leukocyte activation and positive regulation of cytokines.Fcγ receptor-mediated phagocytosis and NOD-like receptor signaling pathway activity were enhanced in C1 subtype.WGCNA analysis suggested that the brown module exhibited the strongest correlation with DRG subtypes(r=0.67),from which 23 differentially expressed genes were identified.The feature genes screened by three machine learning methods were interpolated to obtain a DRGs-related prediction model consisting of three genes(AQP9,F5 and PYGL).Nomogram and ROC curves(AUC_train=0.891,AUC_test=0.840)showed good diagnostic efficacy.Conclusions DRGs were closely related to the occurrence and progression of AMI.The DRGs-related prediction model consisting of AQP9,F5 and PYGL may provide targets for the diagnosis and personalized treatment of AMI.
Humans ; Myocardial Infarction/diagnosis* ; Transcriptome ; Computational Biology ; Gene Expression Profiling ; ROC Curve ; Gene Regulatory Networks ; Nomograms ; Disulfidptosis