BackgroundFamily functioning is one of the factors influencing non-suicidal self-injury （NSSI） behaviors in adolescents with depressive disorders. Previous studies have treated family functioning as a unitary construct， which may obscure the differential impacts of specific dimensions on NSSI behaviors. ObjectiveTo explore the relationships between various dimensions of family functioning and NSSI behaviors in adolescents with depressive disorders， aiming to provide precise targets for family-based interventions for adolescents with depressive disorders who exhibit NSSI behaviors. MethodsIn this cross-sectional study， 217 adolescent patients who were treated at the outpatient or inpatient department of The First Psychiatric Hospital of Harbin from January to July 2025 and met the diagnostic criteria for depressive disorders as stipulated in the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5） were included as the research subjects. Assessments included a self-designed questionnaire， the Hamilton Depression Scale-17 item （HAMD-17）， and the Family Assessment Device （FAD）. Univariate Logistic regression analysis was employed to investigate the association between each dimension of family functioning and the NSSI behaviors， and multivariate Logistic regression was used to test the independent effect of each dimension of family functioning on the NSSI behaviors. ResultsA total of 204 cases （94.01%） of adolescent patients with depressive disorders completed the valid questionnaire survey. Among them， 134 cases （65.69%） exhibited NSSI behaviors （NSSI group）， and 70 cases （34.31%） did not exhibit NSSI behaviors （non-NSSI group）. Compared with the non-NSSI group， the NSSI group had a higher HAMD-17 score ［（20.97±7.50） vs. （17.79±6.95）， t=8.705， P=0.004］， a higher FAD total score ［（155.68±21.84） vs. （148.87±22.72）， t=4.348， P=0.038］， and a higher problem-solving dimension score ［（2.54±0.49） vs. （2.34±0.51）， t=7.399， P=0.007］. All the differences were statistically significant. The results of the Logistic regression analysis showed that the FAD total score （OR=1.014， 95% CI： 1.001–1.028， P=0.041） and the problem-solving dimension score （OR=2.241， 95% CI： 1.228–4.090， P=0.009） were both risk factors for NSSI behaviors. After adjusting for gender， age， residence， educational level， monthly family income， and whether being an only child， the correlation between the FAD total score and NSSI behaviors was not statistically significant （OR=1.010， 95% CI： 0.995–1.025， P=0.185）， while the correlation between the FAD problem-solving dimension score and NSSI behaviors remained statistically significant （OR=2.000， 95% CI： 1.028–3.889， P=0.041）. ConclusionImpaired problem-solving capacity within family functioning may constitute a risk factor for NSSI behaviors in adolescents with depressive disorders. ［Funded by Research Project of Heilongjiang Provincial Health Commission （number， 20240303090148， 20230303090154）］

Objective: To investigate the damaging effects of red blood cell supernatant (RBC-S) stored for different durations (7 d, 14 d, and 28 d) on vascular endothelial cells, and to explore the underlying mechanisms using bioinformatics analysis, so as to provide references for optimizing red blood cell transfusion strategies. Methods: Human umbilical vein endothelial cells (HUVECs) were co-cultured with RBC-S stored for 7, 14 and 28 days, designated as the 7 d group, 14 d group and 28 d group respectively, which were collectively defined as the experimental groups. Cell damage was evaluated by cell proliferation assay (Cell Counting Kit8, CCK8), lactate dehydrogenase (LDH) release assay, 4′, 6diamidino2phenylindole (DAPI) staining, and flow cytometry for apoptosis and reactive oxygen species (ROS) levels. The damage degree of RBC-S on vascular endothelial cells was assessed by statistical analysis of damage data among different groups. Since the damage effect reached a plateau at all time points, the 28 d storage group was selected as the representative for further mechanistic studies. Transcriptomic analysis was performed to explore the role of frizzled class receptor 1 (FZD1) and Wnt signaling pathway in red blood cell storagerelated endothelial dysfunction. Results: Compared with the control group, the storage groups treated with 7 d, 14 d, and 28 d RBC-S showed significantly decreased cell proliferation rates [control group 100%, 7 d group (69.51±2.30)%, 14 d group (74.54±2.89)%, 28 d group (73.59±2.36)%, P<0.05], significantly reduced numbers of DAPI-stained cell nuclei [control group (213±12.5) per field, 7 d group (140.33±17.04) per field, 14 d group (152.00±23.72) per field, 28 d group (144.33±19.09) per field, P<0.05] and significantly increased LDH release [control group (1), 7 d group (8.33±1.41), 14 d group (9.23±0.83), 28 d group (9.16±0.60), P<0.05]. There was no significant difference in the degree of damage caused by RBC-S among different storage groups (P>0.05). With the prolongation of storage time, free hemoglobin (FHb) gradually increased [control group (not detected), 7 d (16.57±6.38) mg/L, 14 d (76.80±22.83) mg/L, 28 d (286.97±29.02) mg/L, P<0.05]. The apoptotic rate (20.53±2.94)% and ROS relative intensity (5.13±0.91) in the 28 d storage group were significantly higher than those in the control group (P<0.05). Transcriptomic analysis showed that FZD1 played a key role in vascular endothelial dysfunction induced by red blood cell storage and was closely related to the Wnt signaling regulatory network. Conclusion: RBC-S stored for 7 d, 14 d, or 28 d can all significantly damage vascular endothelial cells, and the damaging effect reaches a plateau at 7 d of storage. Mechanistic investigation of the 28 d group indicated that the downregulation of the FZD1/Wnt signaling pathway may play a critical role in vascular endothelial dysfunction induced by red blood cell storage, providing a theoretical basis for further optimizing red blood cell storage and transfusion strategies.

Postoperative cognitive dysfunction (POCD) is a clinically significant complication in elderly patients, largely driven by surgery-induced neuroinflammation. The cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway, a crucial regulator of innate immunity, has been implicated in neuroinflammatory activation. This study investigated whether electroacupuncture (EA) improves POCD by modulating this pathway in aged rats. Aged male Sprague-Dawley rats were subjected to sevoflurane anesthesia and splenectomy to establish a POCD model. Animals were divided into sham, POCD, POCD+EA, and POCD+EA+cGAS inhibitor groups. The EA groups received stimulation at Baihui (Governor Vessel 20 (GV20)), Neiguan (Pericardium 6 (PC6)), and Zusanli (Stomach 36 (ST36)) acupoints. Cognitive function was evaluated using the Morris water maze, while hippocampal expression of cGAS-STING pathway components and downstream effectors—interferon regulatory factor 3 (IRF3), nuclear factor kappa B (NF-κB), and interleukin-1 beta (IL-1β)—was assessed by Western blot. Cellular localization was determined by immunofluorescence staining. Compared with the Sham group, rats in the POCD group showed significant impairments in spatial memory, accompanied by upregulated protein expression of cGAS, STING, NF-κB, IRF3, and IL-1β in the hippocampus. Upon pathway activation, cGAS and STING proteins were predominantly co-localized with neurons, and their fluorescence intensity in the hippocampus was markedly increased. These behavioral deficits and molecular alterations were partially reversed in both the POCD+EA and POCD+EA+inhibitor groups. Electroacupuncture alleviates POCD in aged rats by inhibiting hippocampal cGAS-STING pathway activation and reducing neuroinflammation, suggesting a promising non-pharmacological strategy for POCD management.

Blood transfusion is an important life-support measure in modern medicine. As clinical demand for transfusion continues to rise, blood supply remains under persistent strain, making the efficient utilization of this precious medical resource a critical component of blood management. Accurate prediction of transfusion needs is of great significance for optimizing blood resource allocation and conserving blood products. Traditional transfusion decision-making relies on clinical experience and simplified scoring systems, which are insufficient to meet the demands of precision medicine. Machine learning (ML) technology can integrate multidimensional data—including demographic characteristics, laboratory indicators, surgical information, and dynamic physiological waveforms—to construct high-performance predictive models, offering a new approach to transfusion prediction. This article systematically reviews the application progress of ML in transfusion prediction across clinical scenarios such as trauma, the perioperative period, and obstetrics. In trauma, ML has been applied to early massive transfusion prediction, prehospital transfusion decision-making, and precise prediction in pediatric trauma. In the perioperative field, applications span specialties including traumatic brain injury, orthopedic surgery, cardiovascular and major vascular surgery, and hepatic surgery. In obstetrics, models can effectively predict postpartum hemorrhage and transfusion requirements associated with cesarean section. Studies have shown that algorithms such as random forest, gradient boosting machines, and deep neural networks achieve area under the receiver operating characteristic curve (AUC) values of 0.83-0.98 in massive transfusion prediction, 0.75-0.97 in perioperative scenarios, and 0.80-0.89 in obstetric transfusion prediction—significantly outperforming traditional scoring tools. However, current studies are generally limited by single-center retrospective designs, insufficient external validation, and inadequate reporting standards; limited model interpretability and challenges in clinical integration further constrain practical translation. Future research should focus on constructing multicenter data cohorts, integrating multimodal data, conducting prospective implementation studies, and deeply embedding models within electronic health record systems, thereby advancing the application of ML to optimize clinical transfusion decision-making.

As a major challenge in the global field of critical care medicine, sepsis is associated with high morbidity and mortality, driving intensive research into the development of precise risk prediction models. Among these, machine learning and deep learning-based predictive models have garnered particular attention. This article systematically reviews the evolution of sepsis risk prediction models and the challenges associated with their clinical translation, with a focus on their clinical applicability in common septic complications, including acute kidney injury, encephalopathy, and coagulation disorders. Current evidence indicates that machine learning models, by integrating multidimensional dynamic data from electronic health records, significantly enhance early warning capabilities and individualized predictive performance. However, major bottlenecks limiting clinical translation include insufficient data standardization, lack of model interpretability, and inadequate external validation. Future research should prioritize multicenter collaboration, time-series modeling strategies, and explainable artificial intelligence frameworks to optimize clinical translation pathways and facilitate the paradigm shift from traditional empirical approaches to data-driven precision strategies in sepsis risk stratification.

Objective To analyze the association between eye-related behaviors and myopia among preschool chil-dren in Ningxia Hui Autonomous Region,and to develop a predictive nomogram model.Methods Using stratified cluster random sampling,36 062 preschool children from 400 randomly selected kindergartens in Ningxia Hui Autonomous Region were enrolled between October and December 2023.Primary caregivers of participants completed structured question-naires.Data were randomly split into a training set(n=25 243,70％)and a validation set(n=10 819,30％)in a ratio of 7∶3.The training set was used for model construction,and the validation set for external validation.Calibration plots and the Hosmer-Lemeshow(H-L)goodness-of-fit test assessed agreement between predicted and observed risks.Decision curve analysis(DCA)and clinical impact curve analysis(CICA)evaluated clinical utility.Results The myopia preva-lence among preschool children in Ningxia Hui Autonomous Region was 3.8％.A nomogram model based on binary Logistic regression showed area under the curve(AUC)values of 0.88(95％CI:0.87-0.89)for the training set and 0.89(95％CI:0.87-0.90)for the validation set,indicating strong discriminative ability.Calibration curves and H-L tests revealed good model fit(training set:x2=4.92,P=0.766;validation set:x2=5.52,P=0.961),with all P＞0.05.DCA and CICA confirmed clinical utility.The nomogram identified parental myopia,academic pressure,frequency of eye fatigue,daily screen time,and regular vision checks as the top five predictors of myopia.Conclusion The nomogram demonstrates promising potential for predicting myopia risk in preschool children in Ningxia Hui Autonomous Region,serving as a robust tool for clinical and educational myopia risk assessment.

This consensus was developed by the Orthodontic Society of the Chinese Stomatological Association to provide a systematic, scientific, and practical guideline for informed consent in orthodontic care. Orthodontic treatment is typically lengthy, highly individualized, and involves multiple factors such as growth and development, occlusal function, and facial esthetics. Rapid technological advances and diverse risk profiles make the traditional reliance on orthodontist experience or institutional templates insufficient to ensure patients′ full understanding and autonomous decision-making. To address this, the expert panel conducted extensive reviews of domestic and international guidelines, analyzed representative dispute cases, and performed multicenter patient-clinician surveys. Using a multi-round Delphi method, the group established a standardized informed consent framework covering the initial consultation, treatment, and retention phases. The consensus emphasizes that informed consent is not only a fundamental legal and ethical requirement but also a key step in building trust, improving patient compliance, and enhancing treatment satisfaction. Orthodontists should clearly and comprehensively explain treatment plans, potential risks, uncertainties, and associated costs, while respecting the autonomy of patients or guardians, and maintain continuous communication and dynamic evaluation throughout the treatment process. The release of this consensus provides unified and authoritative guidance for clinical orthodontics, helping to standardize informed consent, enhance its transparency, safeguard patient rights, reduce medical risks, and promote high-quality, sustainable development of orthodontic practice.

Objective:To preliminarily explore therapeutic effects and possible molecular mechanisms of sinomenine on atopic dermatitis (AD) -like mouse models.Methods:Thirty female BALB/c mice (6 - 8 weeks old) were randomly divided into 5 groups: blank control group, model group, positive control group, topical sinomenine group, and oral sinomenine group. Except for the blank control group, all groups were subjected to repeated topical stimulation with 2,4-dinitrochlorobenzene (DNCB) on the dorsal skin to establish an AD-like mouse model. After modeling, no special treatment was given to the blank control group, the positive control group was topically treated with 100 μg of 0.1% mometasone furoate cream twice daily on the lesions, the topical sinomenine group was topically treated with 100 μl of 10 mg/ml sinomenine solution twice daily on the lesions, and the oral sinomenine group was gavaged with sinomenine solution at a dose of 100 mg·kg -1·d -1 (100 μl per dose, twice daily) . Treatments lasted for 14 days. Twelve hours after the final treatment, the severity of skin lesions in each group was assessed. Blood samples were collected via enucleation, and serum levels of interleukin (IL) -1β, IL-6, and immunoglobulin E (IgE) were measured using enzyme-linked immunosorbent assay (ELISA) . Histopathological changes in dorsal skin lesions were observed, and immunohistochemical study was performed to detect the expression levels of p38 mitogen-activated protein kinase (MAPK) and nuclear factor (NF) -κB p65 in skin tissues, expressed as the percentage of the immunopositive area. One-way analysis of variance was used for multiple group comparisons, while Tukey′s test or the Games-Howell test was applied for post-hoc comparisons between groups. Results:Compared with the blank control group, the model group exhibited epidermal hyperkeratosis with parakeratosis, thickening of the spinous layer, spongiosis, significant inflammatory cell infiltration, and prominent angiogenesis. In contrast, the positive control group, topical sinomenine group, and oral sinomenine group showed reduced spinous layer thicknesses, decreased inflammatory cell infiltration, and less pronounced angiogenesis compared to the model group. In the blank control group, model group, positive control group, topical sinomenine group, and oral sinomenine group, the severity scores of skin lesions were 0, 8.83 ± 0.75, 4.33 ± 1.08, 2.58 ± 0.49, 2.83 ± 0.93 respectively, the serum levels of IL-1β were 52.58 ± 1.72, 168.40 ± 7.23, 57.07 ± 6.39, 85.74 ± 4.15, 100.30 ± 11.55 pg/ml respectively, IL-6 levels were 86.88 ± 4.60, 215.00 ± 5.02, 79.34 ± 4.91, 127.20 ± 1.06, 149.00 ± 6.21 pg/ml respectively, IgE levels were 2 159.00 ± 176.00, 3 493.00 ± 89.61, 2 294.00 ± 158.10, 2 550.00 ± 214.70, 2 814.00 ± 119.70 μg/ml respectively, the expression levels of p38 MAPK in skin tissues were 3.03% ± 3.38%, 12.95% ± 6.89%, 2.14% ± 1.28%, 5.28% ± 3.71%, 3.85% ± 2.26% respectively, and NF-κB p65 expression levels were 0.61% ± 0.49%, 18.92% ± 6.96%, 3.77% ± 1.90%, 5.66% ± 2.28%, 6.25% ± 3.14% respectively; the differences in all the above parameters were statistically significant among groups (all P < 0.05) . Compared with the blank control group, the model group had significantly increased skin lesion severity scores, serum IL-1β, IL-6, and IgE levels, as well as elevated expression of p38 MAPK and NF-κB p65 in skin tissues (all P < 0.01) . Compared with the model group, the positive control group, topical sinomenine group, and oral sinomenine group showed significantly reduced skin lesion severity scores, decreased serum IL-1β, IL-6, and IgE levels, and lower expression of p38 MAPK and NF-κB p65 in skin tissues (all P < 0.05) . Compared with the positive control group, the topical and oral sinomenine groups exhibited further reductions in skin lesion severity scores (both P < 0.05) . Additionally, the topical sinomenine group showed significantly lower serum levels of IL-1β and IL-6 compared with the oral sinomenine group (both P < 0.05) . Conclusion:Sinomenine solution could obviously alleviate the severity of skin lesions in AD-like mouse models, likely by down-regulating the expression of IL-1β, IL-6 and IgE, inhibiting the MAPK/NF-κB signaling pathway, and thus reducing the degree of inflammation.

Objective:To investigate differences in serum lipid profiles between patients with dermatomyositis (DM) and healthy controls.Methods:A retrospective analysis was conducted on the clinical data and serum samples collected from 51 patients with DM who visited the First Affiliated Hospital, Anhui Medical University from September 2020 to January 2022. Serum samples were also collected from 66 healthy controls during the same period. Serum lipid profiles were analyzed using ultra-performance liquid chromatography-mass spectrometry in both groups. Differential lipids were screened using principal component analysis and orthogonal partial least squares-discriminant analysis. The predictive value of these differential lipids for DM was evaluated by receiver operating characteristic (ROC) curve analysis, and their correlations with clinical indicators were also evaluated.Results:A total of 51 patients with DM were enrolled, including 27 males and 24 females, with ages ( M[ Q1, Q3]) of 55.00 (47.00, 66.00) years and body mass index (BMI) values of 22.64 (19.79, 24.75) . The control group included 66 healthy individuals (33 males and 33 females) , with ages of 51.00 (43.75, 56.00) years and BMI values of 23.60 (21.18, 25.19) . No significant differences were observed between the two groups in terms of sex, age, or BMI (all P > 0.05) . A total of 341 lipid metabolites were identified, and 16 lipid metabolites such as ceramides (Cer) , sphingomyelins, phosphatidylcholines (PC) , phosphatidylethanolamines, lysophosphatidylcholines (LPC) , and triglycerides (TG) significantly differed between the DM group and the control group, of which 8 were upregulated and 8 were downregulated in the DM group. ROC curve analysis identified 7 differential lipids with area under the curve (AUC) values of > 0.9, of which 2 were Cer, 3 were TG, 1 was phosphatidylethanolamine, and 1 was LPC. In the DM patients, serum LPC (22∶1) levels were negatively correlated with creatine kinase isoenzyme MB levels ( r = -0.276, P < 0.05) , serum PC (15∶1/16∶0) levels were negatively correlated with aspartate aminotransferase levels ( r = -0.305, P < 0.05) , and serum Cer (d18∶1/18∶0) levels were positively correlated with C-reactive protein levels ( r = 0.283, P < 0.05) . Significant differences in serum lipid levels were observed between some DM subgroups (all P < 0.05) : sphingomyelin (d24∶0) levels significantly differed between anti-Sj?gren syndrome type A/Ro52 antibody-positive and -negative DM patients; LPC (17∶1) levels significantly differed between anti-PM-SCL75 antibody-positive and -negative DM patients; LPC (20∶0) and PC (32∶1p) levels significantly differed between anti-Mi-2 antibody-positive and -negative DM patients; LPC (22∶1) and TG (9∶0/9∶0/9∶0) levels significantly differed between anti-TIF1-γ antibody-positive and -negative DM patients; Cer (d18∶1/18∶0) levels significantly differed between DM patients with and without Heliotrope's sign. Conclusion:Lipid profiles were significantly altered in DM patients compared with healthy controls, and some lipids showed potential diagnostic value for DM.

Accurate characterization of the chemical composition of complex traditional Chinese medicine(TCM)is an essential foundation for the modern scientific interpretation of TCM principles.Mass spectrometry is the most dominant technique in current research on the material basis of TCM,offering the highest sensitivity and the richest information provision.Establishing mass spectrometry databases represents the most effective approach to facilitating the structural analysis of TCM chemical components.This paper systematically searches and reviews literature published from January 2005 to January 2025 through online databases such as China National Knowledge Infrastructure,PubMed,and Web of Science,using"mass spectrometry database"and"traditional Chinese medicine"as keywords.It reviews the current status of seven TCM chemical component mass spectrometry databases and seven natural product mass spectrometry databases.The key advancements of these mass spectrometry databases for natural products are summarized,detailing their characteristics,search methodologies,included information,and data sources.Additionally,challenges related to data quality,standardization,timely updates,database interaction,retrieval functionality,and data sharing and security are discussed in depth.Furthermore,the paper explores prospective development directions for TCM mass spectrometry databases,emphasizing the importance of open data sharing,technological innovation,and data security.Through this analysis,the paper aims to offer theoretical guidance and practical recommendations for the precise identification of TCM components,as well as for the construction and application of these databases.