BackgroundCurrently， the problem of depressed mood in college students is becoming more prominent. The experience of childhood maltreatment is a significant contributor to depression among college students. Although the association between the two has been confirmed， the specific psychosocial mechanisms underlying how childhood maltreatment affects college students' mental health remain insufficiently evidenced. ObjectiveTo explore the mediating role of emotion regulation difficulties in the relationship between childhood maltreatment and depression among college students， and to investigate the moderated effects of psychological resilience and family socioeconomic status， aiming to provide references for improving depressive symptoms in college students. MethodsOn 14 March 2024， a cluster sampling method was employed to recruit 751 college students from a university in Heilongjiang Province. Participants were assessed with Childhood Trauma Questionnaire （CTQ）， Difficulties in Emotion Regulation Scale （DERS）， Patients' Health Questionnaire Depression Scale-9 item （PHQ-9）， 10-item Connor-Davidson Resilience Scale （CD-RISC-10） and Family Socioeconomic Status Questionnaire. Pearson correlation analysis was adopted to examine the correlation between the scores of scales. Model 4 and model 7 in Process 4.2 were used to test the mediating effects of emotional regulation difficulties and the moderated effects of psychological resilience and family socioeconomic status. Results① A total of 712 （94.81%） valid questionnaires were collected. ② College students' CTQ score was positively correlated with DERS score and PHQ-9 score （r=0.296， 0.507， P<0.01）， and negatively correlated with CD-RISC-10 score and Family Socioeconomic Status Questionnaire score （r=-0.148， -0.229， P<0.01）. ③ The indirect effect value of difficulties in emotion regulation on the relationship between childhood maltreatment and depression was 0.091 （95% CI： 0.018~0.046）， accounting for 17.95% of the total effect. ④ The first half of the mediation model "childhood maltreatment → difficulties in emotion regulation → depression" （childhood maltreatment → difficulties in emotion regulation） was moderated by psychological resilience （β=-0.030， t=-6.147， 95% CI： -0.040~-0.020） and family socioeconomic status （β=-0.051， t=-3.929， 95% CI： -0.077~-0.026）. ConclusionChildhood maltreatment exerts both a direct effect on college students' depression and an indirect effect through emotion regulation difficulties. The childhood maltreatment → emotion regulation difficulties pathway in this mediation model is moderated by psychological resilience and family socioeconomic status. ［Funded by Qiqihar Medical University Graduate Student Innovation Fund Project （number， QYYCX2023-48）； Special Research Fund Project for Young Doctors of Qiqihar Academy of Medical Sciences （number， QMSI2021B-08）］

This study aims to investigate the in vitro mechanisms underlying the beneficial effects of puerarin on hepatic insulin resistance(IR) based on the carbohydrate response element-binding protein(ChREBP)/peroxisome proliferator-activated receptor(PPAR)α/PPARγ axis involved in glucose and lipid metabolism. An IR-HepG2 cell model was established by treating cells with dexamethasone for 48 h, and the cells were then treated with 10, 20, and 40 μmol·L~(-1) puerarin for 24 h. Glucose levels and output in the extracellular fluid were measured by the glucose oxidase method, while cell viability was assessed by the cell counting kit-8(CCK-8) assay. The adenosine triphosphate(ATP) content and glycogen synthesis were evaluated through chemiluminescence and periodic acid-Schiff staining, respectively. Western blot was employed to quantify the protein levels of forkhead box protein O1(FoxO1), phosphorylated forkhead box protein O1 [p-FoxO1(Ser256)], glucagon, phosphofructokinase, liver type(PFKL), pyruvate kinase L-R(PKLR), pyruvate dehydrogenase complex 1(PDHA1), insulin receptor substrate 2(IRS2), phosphatidylinositol 3-kinase p85(PI3KR1), phosphorylated protein kinase B [p-Akt(Thr308)], glycogen synthase(GYS), glycogen phosphorylase, liver type(PYGL), adiponectin(ADPN), ChREBP, PPARα, and PPARγ. Additionally, the protein levels of acetyl-CoA carboxylase 1(ACC1), phosphorylated ATP citrate lyase [p-ACLY(Ser455)], sterol regulatory element binding protein 1c(SREBP-1c), peroxisome proliferator-activated receptor gamma coactivator 1α(PGC1α), carnitine palmitoyltransferase 1α(CPT1α), and glucagon receptor(GCGR) were also determined. Immunofluorescence was employed to visualize the expression and nuclear location of ChREBP/PPARα/PPARγ. Furthermore, quantitative PCR with the antagonists GW6471 and GW9662 was employed to assess Pparα, Pparγ, and Chrebp. The findings indicated that puerarin effectively reduced both the glucose level and glucose output in the extracellular fluid of IR-HepG2 cells without obvious effect on the cell viability, and it increased intracellular glycogen and ATP levels. Puerarin down-regulated the protein levels of FoxO1 and glucagon while up-regulating the protein levels of p-FoxO1(Ser256), PFKL, PKLR, PDHA1, IRS2, PI3KR1, p-Akt(Thr308), GYS, PYGL, ADPN, ACC1, SREBP-1c, p-ACLY(Ser455), PGC1α, CPT1α, and GCGR in IR-HepG2 cells. Furthermore, puerarin up-regulated both the mRNA and protein levels of ChREBP, PPARα, and PPARγ and promoted the translocation into the nucleus. GW6471 was observed to down-regulate the expression of Pparα while up-regulating the expression of Chrebp and Pparγ. GW9662 down-regulated the expression of Pparγ while up-regulating the expression of Pparα, with no significant effect on Chrebp. In summary, puerarin activated the hepatic ChREBP/PPARα/PPARγ axis, thereby coordinating the glucose and lipid metabolism, promoting the conversion of glucose to lipids to exert the blood glucose-lowering effect.
Isoflavones/pharmacology* ; Humans ; PPAR gamma/genetics* ; Hep G2 Cells ; Glucose/metabolism* ; Lipid Metabolism/drug effects* ; PPAR alpha/genetics* ; Liver/drug effects* ; Basic Helix-Loop-Helix Leucine Zipper Transcription Factors/genetics* ; Insulin Resistance

This paper aims to investigate the hypoglycemic effect and mechanism of berberine in improving energy metabolism based on the multi-pathway regulation of brain and muscle aromatic hydrocarbon receptor nuclear translocal protein 1(BMAL1): cyclin kaput complex of day-night spontaneous output cyclin kaput(CLOCK). The dexamethasone-induced hepatic insulin resistance(IR) HepG2 cell model was used; 0.5, 1, 5, 10, 20 μmol·L~(-1) berberine were administered at 15, 18, 21, 24, 30, 36 h. The time-dose effect of glucose content in extracellular fluid was detected by glucose oxidase method. The optimal dosage and time of berberine were determined for the follow-up study. Glucose oxidase method and chemiluminescence method were respectively performed to detect hepatic glucose output and relative content of ATP in cells; Ca~(2+), reactive oxygen species(ROS), mitochondrial structure and membrane potential were detected by fluorescent probes. Moreover, ultraviolet colorimetry method was used to detect the liver type of pyruvate kinase(L-PK) and phosphoenol pyruvate carboxykinase(PEPCK). In addition, pyruvate dehydrogenase E1 subunit α1(PDHA1), phosphate fructocrine-liver type(PFKL), forkhead box protein O1(FoxO1), peroxisome proliferator-activated receptor gamma co-activator 1α(PGC1α), glucose-6-phosphatase(G6Pase), glucagon, phosphorylated nuclear factor-red blood cell 2-related factor 2(p-Nrf2)(Ser40), heme oxygenase 1(HO-1), NAD(P)H quinone oxidoreductase 1(NQO1), fibroblast growth factor 21(FGF21), uncoupled protein(UCP) 1 and UCP2 were detected by Western blot. BMAL1:CLOCK complex was detected by immunofluorescence double-staining method, combined with small molecule inhibitor CLK8. Western blot was used to detect PDHA1, PFKL, FoxO1, PGC1α, G6Pase, glucagon, Nrf2, HO-1, NQO1, FGF21, UCP1 and UCP2 in the CLK8 group. The results showed that berberine downregulated the glucose content in extracellular fluid in IR-HepG2 cells in a time-and dose-dependent manner. Moreover, berberine inhibited hepatic glucose output and reduced intracellular Ca~(2+) and ROS whereas elevated JC-1 membrane potential and improved mitochondrial structure to enhance ATP production. In addition, berberine upregulated the rate-limiting enzymes such as PFKL, L-PK and PDHA1 to promote glycolysis and aerobic oxidation but also downregulated PGC1α, FoxO1, G6Pase, PEPCK and glucagon to inhibit hepatic gluconeogenesis. Berberine not only upregulated p-Nrf2(Ser40), HO-1 and NQO1 to enhance antioxidant capacity but also upregulated FGF21, UCP1 and UCP2 to promote energy metabolism. Moreover, berberine increased BMAL1, CLOCK and nuclear BMAL1:CLOCK complex whereas CLK8 reduced the nuclear BMAL1:CLOCK complex. Finally, CLK8 decreased PDHA1, PFKL, Nrf2, HO-1, NQO1, FGF21, UCP1, UCP2 and increased FoxO1, PGC1α, G6Pase and glucagon compared with the 20 μmol·L~(-1) berberine group. BMAL1:CLOCK complex inhibited gluconeogenesis, promoted glycolysis and glucose aerobic oxidation pathways, improved the reduction status within mitochondria, protected mitochondrial structure and function, increased ATP energy storage and promoted energy consumption in IR-HepG2 cells. These results suggested that berberine mediated BMAL1:CLOCK complex to coordinate the regulation of hepatic IR cells to improve energy metabolism in vitro.
Humans ; Berberine/pharmacology* ; Gluconeogenesis/drug effects* ; Hep G2 Cells ; Glucose/metabolism* ; Liver/drug effects* ; Energy Metabolism/drug effects* ; Hypoglycemic Agents/pharmacology* ; ARNTL Transcription Factors/genetics* ; Glycolysis/drug effects* ; Oxidation-Reduction/drug effects*

BACKGROUND: The protective effectiveness of an N95 respirator depends on the filtration efficiency of the material from which the N95 respirator is made of, as well as the wearers' facial fit. The facial fit of an N95 respirator mainly depends on the degree of matching between the wearers' facial dimension characteristics and the N95 respirator. Quantitative fit testing objectively evaluates the fit of N95 respirators; however, it is not easy to promote because of the limitations of testing conditions. The aim of this study is to establish a fit prediction model of N95 respirator based on facial images. METHODS: Facial images and fit factor (FF) value of 5 N95 respirators were gathered from 299 medical staffs in 10 hospitals in Beijing. Face geometry measurement was based on 3D face modelling, and the American TSI-8038 Porta Count Pro+ was used to conduct quantitative fit test. Multiple linear regression analysis was employed to identify facial dimensional features that significantly influenced the fit of N95 respirators. Through matching training of facial image and FF values, a fit prediction model has been established, enabling rapid recommendation of N95 respirators meeting the fit standard via facial image recognition. RESULTS: A fit prediction model for N95 respirators based on facial images has been developed, which enables the rapid recommendation of N95 respirators with acceptable FF value for healthcare personnel. The model demonstrated an accuracy of 55.93%, a precision of 98.43%, a recall of 51.65%, and an F1 score of 0.68. CONCLUSIONS It is feasible to utilize computer-based facial recognition technology to rapidly recommend N95 respirators for medical personnel. Given the high level of accuracy achieved, the model demonstrates significant potential for practical application.
Humans ; Face/anatomy & histology* ; N95 Respirators/standards* ; Male ; Adult ; Female ; Middle Aged ; Beijing

OBJECTIVE: As an age-related neurodegenerative disease, the prevalence of mild cognitive impairment (MCI) increases with age. Within the framework of traditional Chinese medicine, spleen-kidney deficiency syndrome (SKDS) is recognized as the most frequent MCI subtype. Due to the covert and gradual onset of MCI, in community settings it poses a significant challenge for patients and their families to discern between typical aging and pathological changes. There exists an urgent need to devise a preliminary diagnostic tool designed for community-residing older adults with MCI attributed to SKDS (MCI-SKDS). METHODS: This investigation enrolled 312 elderly individuals diagnosed with MCI, who were randomly distributed into training and test datasets at a 3:1 ratio. Five machine learning methods, including logistic regression (LR), decision tree (DT), naive Bayes (NB), support vector machine (SVM), and gradient boosting (GB), were used to build a diagnostic prediction model for MCI-SKDS. Accuracy, sensitivity, specificity, precision, F1 score, and area under the curve were used to evaluate model performance. Furthermore, the clinical applicability of the model was evaluated through decision curve analysis (DCA). RESULTS: The accuracy, precision, specificity and F1 score of the DT model performed best in the training set (test set), with scores of 0.904 (0.845), 0.875 (0.795), 0.973 (0.875) and 0.973 (0.875). The sensitivity of the training set (test set) of the SVM model performed best among the five models with a score of 0.865 (0.821). The area under the curve of all five models was greater than 0.9 for the training dataset and greater than 0.8 for the test dataset. The DCA of all models showed good clinical application value. The study identified ten indicators that were significant predictors of MCI-SKDS. CONCLUSION The risk prediction index derived from machine learning for the MCI-SKDS prediction model is simple and practical; the model demonstrates good predictive value and clinical applicability, and the DT model had the best performance. Please cite this article as: Ai YT, Zhou S, Wang M, Zheng TY, Hu H, Wang YC, Li YC, Wang XT, Zhou PJ. Development of a machine learning-based risk prediction model for mild cognitive impairment with spleen-kidney deficiency syndrome in the elderly. J Integr Med. 2025; 23(4): 390-397.
Humans ; Cognitive Dysfunction/diagnosis* ; Aged ; Male ; Female ; Machine Learning ; Spleen ; Aged, 80 and over ; Kidney ; Medicine, Chinese Traditional

ObjectiveTo analyze the adverse reactions associated with the clinical use of Banxia （Rhizoma Pinelliae）- Wutou （Aconitum） in the same formula， with the aim of providing a reference for the safety of their clinical application. MethodsLiterature on the clinical application of antagonistic herbs "Banxia-Wutou" used in the same formula， published from January 1st， 2014， to June 30th， 2023， was retrieved from databases including CNKI， VIP， Wanfang， SinoMed， PubMed， Cochrane Library， and Embase. A database was established， and information related to adverse reactions was extracted， including descriptions， classifications， specific manifestations， management and outcomes， patients' primary diseases （western medicine diseases and traditional Chinese medicine diagnoses and syndromes）， and medication information （dosage， ratio， administration routes， and dosage forms）. ResultsA total of 79 researches simultaneously used antagonistic herbs Banxia-Wutou in the same formula and reported associated advers reactions. Gastrointestinal adverse reactions were the most common， with 8 studies reporting management of adverse reactions and 3 studies reporting improvement with no intervention. Among the 11 researches， the adverse reaction relieved to extant， while other 69 researches didn't report the managment of adverse reaction and its prognosis. For the primary disease in western medicine system， chronic bronchitis and chronic obstructive pulmonary disease （COPD） were most common， while gastric pain was the most common symptom in traditional Chinese medicine with spleen and kidney deficiency and spleen stomach cold deficiency being the most frequent syndromes. The most common Banxia dosage was 10 g， while for the Wutou， Fuzi （Radix Aconiti Lateralis Praeparata） was predominant with the highest dose at 15 g. The most frequent herbal combination was Banxia-fuzi， with a 1∶1 ratio. The main administration route was oral， and the primary dosage form was decoction. ConclusionGastrointestinal adverse reactions are the most common in the clinical use of Banxia-Wutou antagonistic herb combinations. Research on the safety of "Banxia-Wutou" combinations should focus on respiratory system diseases and spleen-stomach related conditions.

The aim of this updated guideline is to provide comprehensive recommendations for the management of gout in patients with common comorbidities, such as chronic kidney disease(CKD), cardiovascular disease(CVD), diabetes, osteoarthritis(OA), and gastrointestinal disorders. This guideline was developed by a multidisciplinary expert panel consisting of specialists in endocrinology, rheumatology, nephrology, cardiology, gastroenterology, and methodology. The development process adhered to standard methodologies, including PICO(population, intervention, comparator, and outcomes) question deconstruction, systematic literature review, the Grading of Recommendations Assessment, Development and Evaluation(GRADE) for evidence and recommendation evaluation, Delphi voting, and expert consensus. The guideline presents 26 evidence-based recommendations addressing 7 clinical questions for patients with hyperuricemia and gout in the context of comorbidities. Key recommendations include the maintenance of strict serum urate targets, particularly for patients with CKD stage≥3, chronic gouty arthritis, and OA, in order to prevent disease progression. In patients with CVD or diabetes, intra-articular triamcinolone is preferred over systemic glucocorticoids. Prioritized anti-inflammatory treatments for patients with CKD, gastrointestinal diseases and OA are recommended. The guideline also introduces emerging therapies, such as interleukin-1 inhibitors and selective urate transport inhibitors, as potential treatment options for refractory cases. The update offers a comprehensive, patient-centered approach to managing gout, particularly in individuals with associated comorbidities. Multidisciplinary collaboration and emerging new treatments and evidence ensure the optimization of the recommendations.

OBJECTIVES: The mechanism of the odontogenic differentiation of apical papillary cells (APCs) stimulated by bioactive glass 45S5 is still unclear. This study aims to investigate the effect of autophagy on the odontogenic differentiation of APCs stimulated by bioactive glass 45S5. METHODS: APCs were isolated and cultured in vitro, and the cell origin was identified by flow cytometry. The culture medium was prepared with 1 mg/mL 45S5, and its pH and ion concentration were determined. The experiments were divided into control, 45S5, and 3-methyladenine (3-MA) 45S5 groups. In the 45S5 group, APCs were induced to culture with 1 mg/mL 45S5. In the 3-MA 45S5 group, the autophagy inhibitor 3-MA was added to 1 mg/mL 45S5. Protein immunoblotting assay (Western blot) was used to detect the expression of autophagy-associated proteins of microtubule-associated protein 1 light-chain 3β (LC3B) and P62 after 24 h of induction culture in each group. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression of bone sialoprotein (BSP), Runt-related transcription factor 2 (Runx2), dentin sialophosphoprotein (DSPP), and dentin matrix protein-1 (DMP-1) after 7 d of induction culture. Cellular alkaline phosphatase (ALP) staining analyzed cellular ALP activity at 7 d of induction, and alizarin red staining evaluated the formation of mineralized nodules at 21 d of induction. RESULTS: The pH of the 45S5 extract culture medium was 8.65±0.01, which was not significantly different from that of the control group (P>0.05). The silicon ion concentration of the 45S5 induction culture medium was (1.56±0.07) mmol/L, which was higher than that of the control group (0.08±0.01) mmol/L (P<0.05). The calcium ion concentration of the 45S5 induction culture was (1.57±0.15) mmol/L, which was not significantly different from that of the control group (P>0.05). Western blot results showed that LC3B-Ⅱ/Ⅰ ratio increased and P62 expression decreased in the 45S5 group compared with those in the control group (P<0.05). By contrast, the ratio decreased and the expression increased in the 3-MA 45S5 group compared with those in the 45S5 group (P<0.05). RT-qPCR results showed that the expression of BSP, Runx2, DMP-1, and DSPP enhanced in the 45S5 group compared with that in the control group (P<0.05), but the expression decreased in the 3-MA 45S5 group compared with that in the 45S5 group (P<0.05). Semi-quantitative analysis of ALP staining and alizarin red staining showed that the ALP activity was enhanced, and the formation mineralized nodule increased in the 45S5 group compared with those in the control group. The ALP activity weakened, and the formation mineralized nodules were reduced in the 3-MA 45S5 group compared with that those in the 45S5 group. CONCLUSIONS Cell autophagy participates in the odontogenic differentiation of APCs induced by 1 mg/mL 45S5 in vitro.
Autophagy/drug effects* ; Cell Differentiation/drug effects* ; Odontogenesis/drug effects* ; Dental Papilla/cytology* ; Humans ; Microtubule-Associated Proteins/metabolism* ; Glass/chemistry* ; Cells, Cultured ; Core Binding Factor Alpha 1 Subunit/metabolism* ; Extracellular Matrix Proteins/metabolism* ; Ceramics/pharmacology* ; Adenine/pharmacology* ; Sialoglycoproteins/metabolism* ; Phosphoproteins/metabolism* ; Integrin-Binding Sialoprotein/metabolism* ; Alkaline Phosphatase/metabolism* ; RNA-Binding Proteins

Objective To explore the application value of CT-based radiomics in differentiating pneumonia-type mucinous adenocarcinoma(PTMA)from organizing pneumonia(OP).Methods A total of 52 PTMA patients and 102 OP patients were retrospectively included and randomly divided into training set(n=124)and test set(n=30)in an 8∶2 ratio.Eight PTMA patients and 22 OP patients from another hospital during the same period were included as external validation set(n=30).Clinical characteristics and CT signs of the patients were selected to construct the clinical model.Radiomics features were extracted and dimensionality reduction was performed through the least absolute shrinkage and selection operator(LASSO)algorithm.A radiomics model was constructed and the Radiomics score(Radscore)was calculated.The Radscore was combined with clinical factors to establish the combined model and a nomogram was illustrated.The models' fitting degree was analyzed by the calibration curve,while their efficacy was evaluated by the receiver operating characteristic(ROC)curve and decision curve analysis(DCA).Results The clinical model,established based on the border,cystic space and bronchial leafless tree sign,achieved area under the curve(AUC)of 0.850,0.782,and 0.759 in the training set,test set,and external validation set,respectively.Thirteen features were obtained to construct the radiomics model,with AUC of 0.925,0.865,and 0.830,respectively.The AUC of the combined model were 0.970,0.905,and 0.864,respectively,in which the calibration curve demonstrated good model fitting.DCA indicated that the combined model had the greatest clinical net benefit.Conclusion The combined model based on CT radiomics can effectively distinguish PTMA from OP.

Objective To explore the application value of CT-based radiomics in differentiating pneumonia-type mucinous adenocarcinoma(PTMA)from organizing pneumonia(OP).Methods A total of 52 PTMA patients and 102 OP patients were retrospectively included and randomly divided into training set(n=124)and test set(n=30)in an 8∶2 ratio.Eight PTMA patients and 22 OP patients from another hospital during the same period were included as external validation set(n=30).Clinical characteristics and CT signs of the patients were selected to construct the clinical model.Radiomics features were extracted and dimensionality reduction was performed through the least absolute shrinkage and selection operator(LASSO)algorithm.A radiomics model was constructed and the Radiomics score(Radscore)was calculated.The Radscore was combined with clinical factors to establish the combined model and a nomogram was illustrated.The models' fitting degree was analyzed by the calibration curve,while their efficacy was evaluated by the receiver operating characteristic(ROC)curve and decision curve analysis(DCA).Results The clinical model,established based on the border,cystic space and bronchial leafless tree sign,achieved area under the curve(AUC)of 0.850,0.782,and 0.759 in the training set,test set,and external validation set,respectively.Thirteen features were obtained to construct the radiomics model,with AUC of 0.925,0.865,and 0.830,respectively.The AUC of the combined model were 0.970,0.905,and 0.864,respectively,in which the calibration curve demonstrated good model fitting.DCA indicated that the combined model had the greatest clinical net benefit.Conclusion The combined model based on CT radiomics can effectively distinguish PTMA from OP.