BackgroundModified electroconvulsive therapy （MECT） is a common front-line strategy widely used in psychiatric practice， and the optimal first stimulus dosage in MECT is usually estimated clinically based on the factors influencing the patient's initial seizure threshold （IST）. However， previous studies on the influencing factors of IST have mostly suffered from limitations such as small sample sizes and single-dimensional research perspectives. ObjectiveTo explore the factors influencing IST in MECT for patients with mental disorders， so as to provide references for stimulus dosing strategies in MECT for the patients. MethodsA retrospective study was used to include 1 446 inpatients fulfilling the diagnostic criteria for any specific mental disorder listed in the ICD-10 and receiving MECT at Shandong Daizhuang Hospital from January 1， 2021 to August 1， 2023. Their general and clinical data were collected， including IST， psychiatric diagnostic categories， gender， ethnicity， age， body weight， body mass index （BMI）， course of disease， family history of psychiatric disorders， first episode status， use of antiepileptic drugs the day before treatment， use of benzodiazepines the day before treatment， and previous MECT treatment history. Pearson correlation analysis was utilized to test the correlation of IST with age， height， body weight， BMI， and course of disease， and stepwise multivariate linear regression analysis was performed to identify the factors affecting IST. ResultsIST yielded statistical difference among patients in terms of gender， first episode status， use of antiepileptic drugs the day before treatment， and use of benzodiazepines the day before treatment （t=2.256， -3.059， -2.136， -3.006， P<0.05 or 0.01）. IST in patients of different ages and psychiatric diagnostic categories also demonstrated statistical difference （F=913.120， 6.212， P<0.01）. Within young population， IST varied significantly based on the psychiatric diagnostic categories （F=2.986， P<0.05）. Correlation analysis indicated that IST was positively correlated with age， body weight， BMI and course of disease （r=0.886， 0.055， 0.184， 0.456， P<0.05 or 0.01）， and negatively correlated with height （r=-0.183， P<0.01）. Stepwise multivariate linear regression analysis revealed that age， gender， and body weight were influencing factors of IST （β=0.888， -0.049， -0.035， P<0.01）. ConclusionsAge， gender and body weight may be factors influencing IST in MECT for patients with mental disorders. ［Funded by Key R&D Plan Projects of Jining City in 2024 (number, 2024YXNS202）］

In order to clarify the name,plant species and clinical use of the traditional Uyghur medicine"Heliyun",this article combed Uyghur medical classics such as Ehtiyarat bedey,Aksaray,Jimi elaj and Mehzenul edwiye,as well as modern literature.Herbal textual research was performed on its name,origin,properties,functional indications,etc.At the same time,on-site inspections were conducted to verify the clinical use of"Heliyun"in Xinjiang Uyghur Medical Hospital,medicinal samples were collected,and original plant identification was conducted.After herbal textual research,confirmation of clinical use of medicinal materials in Uyghur medicine,and botanical identification,the Uyghur medicinal material"Heliyun"is actually the dried fruit of Withania somnifera(L.)Dunal,and the Chinese name for this medicinal plant should be"Shuiqieguo",and the Uyghur name remains"Heliyun".This could provide a basis for standardizing the name,confirming the plant species,and promoting the clinical application of"Heliyun"in Uyghur medicine.

In order to clarify the name,plant species and clinical use of the traditional Uyghur medicine"Heliyun",this article combed Uyghur medical classics such as Ehtiyarat bedey,Aksaray,Jimi elaj and Mehzenul edwiye,as well as modern literature.Herbal textual research was performed on its name,origin,properties,functional indications,etc.At the same time,on-site inspections were conducted to verify the clinical use of"Heliyun"in Xinjiang Uyghur Medical Hospital,medicinal samples were collected,and original plant identification was conducted.After herbal textual research,confirmation of clinical use of medicinal materials in Uyghur medicine,and botanical identification,the Uyghur medicinal material"Heliyun"is actually the dried fruit of Withania somnifera(L.)Dunal,and the Chinese name for this medicinal plant should be"Shuiqieguo",and the Uyghur name remains"Heliyun".This could provide a basis for standardizing the name,confirming the plant species,and promoting the clinical application of"Heliyun"in Uyghur medicine.

Purpose: This study aimed to explore the potential categories of parenting sense of competence and to analyze the influence of rumination and dyadic coping on the potential categories of parenting sense of competence. Methods: A total of 199 postpartum women who met the criteria were surveyed from a tertiary grade-A hospital in Shanxi (China) from May 2023 to August 2023. The instruments included the general demographic characteristics, Chinese version of parenting sense of competence scale, Chinese event related rumination inventory, and Chinese version of dyadic coping inventory. Latent profile analysis (LPA) was used to classify the parenting sense of competence in postpartum women, and logistic regression analysis was used to identify the influencing factors. Results: The characteristics of parenting sense of competence in postpartum women can be divided into two potential categories, namely, easy-to-satisfy group (39.3%) and strict-demand group (60.7%). Logistic regression analysis showed that years of marriage, place of residence, deliberate rumination, and dyadic coping were the influencing factors of the potential categories of parenting sense of competence in postpartum women (p < .05). Conclusions Through Latent profile analysis (LPA) analysis, it was found that postpartum women's parenting sense of competence exhibits different characteristics. Clinical workers should identify the characteristics and influencing factors of different categories of women and adopt targeted intervention strategies to promote the level of parenting sense of competence.

Purpose: This study aimed to explore the potential categories of parenting sense of competence and to analyze the influence of rumination and dyadic coping on the potential categories of parenting sense of competence. Methods: A total of 199 postpartum women who met the criteria were surveyed from a tertiary grade-A hospital in Shanxi (China) from May 2023 to August 2023. The instruments included the general demographic characteristics, Chinese version of parenting sense of competence scale, Chinese event related rumination inventory, and Chinese version of dyadic coping inventory. Latent profile analysis (LPA) was used to classify the parenting sense of competence in postpartum women, and logistic regression analysis was used to identify the influencing factors. Results: The characteristics of parenting sense of competence in postpartum women can be divided into two potential categories, namely, easy-to-satisfy group (39.3%) and strict-demand group (60.7%). Logistic regression analysis showed that years of marriage, place of residence, deliberate rumination, and dyadic coping were the influencing factors of the potential categories of parenting sense of competence in postpartum women (p < .05). Conclusions Through Latent profile analysis (LPA) analysis, it was found that postpartum women's parenting sense of competence exhibits different characteristics. Clinical workers should identify the characteristics and influencing factors of different categories of women and adopt targeted intervention strategies to promote the level of parenting sense of competence.

Objective To construct and validate a risk prediction model for enteral nutrition feeding intolerance (FI) in patients with severe cerebral hemorrhage based on machine learning algorithms. Methods The clinical data of 485 patients with cerebral hemorrhage admitted to the neurological intensive care unit of Northern Jiangsu People's Hospital Affiliated to Yangzhou University from January 2020 to December 2022 were retrospectively analyzed. The patients were randomly divided into training set (n=339) and validation set (n=146) in a 7 to 3 ratio. Five machine learning algorithms were used to construct FI risk prediction models. The receiver operating characteristic (ROC) curve was plotted, and the model with the best predictive performance was selected based on the area under the curve (AUC). A nomogram model was constructed based on the optimal model. The calibration curve and decision curve analysis (DCA) were used to evaluate the calibration and clinical net benefit of the nomogram model. Results The incidence of enteral nutrition FI in patients with severe cerebral hemorrhage was 38.4%(186/485). Among the five machine learning algorithm models, the Logistic regression model had the best predictive performance(AUC=0.88). The analysis results of the Logistic regression model showed that the use of diuretics, mechanical ventilation, Glasgow Coma Scale score ≤5, vasoactive drugs, and albumin level<35 g/L were risk factors for enteral nutrition FI in patients with severe cerebral hemorrhage. A nomogram model was further constructed based on these five risk factors. The calibration curve analysis showed that the calibration curve fitted well with the ideal curve, indicating a high calibration degree of the nomogram model. The DCA results showed that when the threshold probability was 5% to 73%, the application of the nomogram model for screening could clinically benefit patients. Conclusion The construction of a nomogram model for predicting the risk of enteral nutrition FI in patients with severe cerebral hemorrhage based on machine learning methods can help to early screen high-risk patients for enteral nutrition FI and timely formulate preventive measures, thereby reducing the incidence of enteral nutrition FI in patients with severe cerebral hemorrhage.

BACKGROUND:In recent years,some scholars in the field of tendon bone injury have attached stromal cell-derived factor 1 to tissue engineering scaffolds to promote tendon bone healing,and achieved good results.However,whether stromal cell-derived factor 1 promotes tendon bone healing mechanisms and participates in the repair of natural healing has not yet been defined. OBJECTIVE:To study the expression of stroma-cell derived factor 1 during tendon bone healing after rupture of the whole supraspinatus muscle of the rabbit rotator cuff and its migration effect and optimal in vitro migration promoting concentration on stem cells during tendon bone injury. METHODS:Totally 18 adult New Zealand rabbits were randomly selected to establish rotator cuff injury models,and an additional 3 rabbits were selected as blank controls.At 3,5,7,14,21,and 28 days after modeling,three rabbits were executed separately and the rabbits in the blank group were sacrificed.The tissues of tendon bone junction were taken and stored in a-80℃refrigerator.The expression of stromal cell-derived factor 1 was detected by ELISA at each time point after injury.Mesenchymal stem cells were isolated from the bone marrow of young rabbit femur,cultured,and identified.Transwell assay was performed to verify the migration-promoting effect of stromal cell-derived factor 1 on stem cells and the optimal migration-promoting concentration in vitro.The stem cells cultured to P3 were co-cultured with BrdU and injected into the rabbit ear marginal vein,and immunohistochemical staining was used to verify whether the stem cells migrated to the injury site. RESULTS AND CONCLUSION:(1)Stromal cell-derived factor 1 gene expression was bimodal during rotator cuff tendon bone healing.Stromal cell-derived factor 1 gene expression increased significantly at 3 days post-injury(P<0.01)and then decreased,reaching a minimum at 5 days post-injury.It increased again and reached a peak 14 days after injury(P<0.01)and then decreased.(2)Cell immunohistochemical staining displayed that stem cells labeled with BrdU did migrate to the injury site.(3)The results of the transwell experiment exhibited that 60-80 ng/mL stromal cell-derived factor 1 had the best effect on promoting migration of stem cells,while a concentration of 200 ng/mL inhibited migration.(4)Stromal cell-derived factor 1 is involved in the healing of rotator cuff tendon bone during the inflammatory response phase and the proliferation phase.The mechanism of action may be to promote the migration of stem cells to the injury and their differentiation into various types of cells to promote repair.In addition,the pro-migration effect of stromal cell-derived factor 1 exists at a range of concentrations,beyond which it may act as an inhibitor.

BackgroundMajor depressive disorder is one of the most disabling mental diseases. Currently， medication in combination with physiotherapy and psychotherapy remains the most commonly used treatment modality for the disease， whereas only a few randomized controlled studies have been conducted on physiotherapy， and even fewer studies have focused on medication combined with physiotherapy. ObjectiveTo explore the efficacy and safety profile of repetitive transcranial magnetic stimulation （rTMS） versus modified electroconvulsive therapy （MECT） in combination with antidepressants in the treatment of major depressive disorder， so as to provide an optimized treatment plan for patients with major depressive disorder. MethodsPatients with major depressive disorder （n=335） hospitalized in Shandong Daizhuang Hospital from January 1， 2019 to April 30， 2023 were included， all of whom met the diagnostic criteria of the International Classification of Diseases， tenth edition （ICD-10）. Depending on their disease condition， patients were subjected to either MECT in combination with drugs （n=141） or rTMS in combination with drugs （n=194） after admission. Depressive symptoms were assessed using Hamilton Depression Scale-24 item （HAMD-24） at the baseline and the end of the 1^st， 2^nd， 3^rd and 4^th week of treatment， and the adverse reactions were documented in patient's medical records. ResultsAnalysis of variance on HAMD-24 revealed a significant effect of time （F=3.081， P=0.042）， but no effect of group （F=1.023， P=0.313）， and the interaction effect between the time and the groups was not statistically significant （F=1.642， P=0.191）. No statistical difference was reported between two groups in response rate and full remission rate （P>0.05）. Throughout the course of treatment， 58 cases （41.13%） of recent memory impairment and 74 cases （52.48%） of headache or neck muscle pain occurred in MECT combined with drugs group， and 27 cases （13.92%） in rTMS combined with drugs group experienced headache or head skin discomfort. ConclusionAntidepressants in combination with rTMS or MECT show equivalent efficacy in the treatment of major depressive disorder， while rTMS combined with antidepressants demonstrates a superior safety profile compared to MECT.

Purpose: This study aimed to explore the potential categories of parenting sense of competence and to analyze the influence of rumination and dyadic coping on the potential categories of parenting sense of competence. Methods: A total of 199 postpartum women who met the criteria were surveyed from a tertiary grade-A hospital in Shanxi (China) from May 2023 to August 2023. The instruments included the general demographic characteristics, Chinese version of parenting sense of competence scale, Chinese event related rumination inventory, and Chinese version of dyadic coping inventory. Latent profile analysis (LPA) was used to classify the parenting sense of competence in postpartum women, and logistic regression analysis was used to identify the influencing factors. Results: The characteristics of parenting sense of competence in postpartum women can be divided into two potential categories, namely, easy-to-satisfy group (39.3%) and strict-demand group (60.7%). Logistic regression analysis showed that years of marriage, place of residence, deliberate rumination, and dyadic coping were the influencing factors of the potential categories of parenting sense of competence in postpartum women (p < .05). Conclusions Through Latent profile analysis (LPA) analysis, it was found that postpartum women's parenting sense of competence exhibits different characteristics. Clinical workers should identify the characteristics and influencing factors of different categories of women and adopt targeted intervention strategies to promote the level of parenting sense of competence.

Brain signals refer to electrical signals or metabolic changes that occur as a consequence of brain cell activity.Among the various non-invasive measurement methods,electroencephalogram(EEG)stands out as a widely employed technique,providing valuable insights into brain patterns.The deviations observed in EEG reading serve as indicators of abnormal brain activity,which is associated with neurological diseases.Brain?computer interface(BCI)systems enable the direct extraction and transmission of information from the human brain,facilitating interaction with external devices.Notably,the emergence of artificial intelligence(AI)has had a profound impact on the enhancement of precision and accuracy in BCI technology,thereby broadening the scope of research in this field.AI techniques,encompassing machine learning(ML)and deep learning(DL)models,have demonstrated remarkable success in classifying and predicting various brain diseases.This comprehensive review investigates the application of AI in EEG-based brain disease diagnosis,highlighting advancements in AI algorithms.