Abstract To promote adolescents active participation in physical activity and improve sleep quality, the article analyzes the relationship of adolescent physical activity with subjective sleep satisfaction, sleep latency, sleep continuity, sleep efficiency, and sleep duration. It explores potential mechanisms underlying the link between physical activity and sleep quality, including physiological mechanisms (circadian rhythms, body temperature, neuroendocrine systems, and immune function), and psychological mechanisms (stress relief, improvement of negative emotions, and promotion of mental relaxation). Based on existing research, it is recommended that adolescents engage in moderate to vigorous physical activity daily to promote improved sleep quality.

ObjectiveTo investigate the mechanisms by which Mahuang Lianqiao Chixiaodoutang （MLC） improves obesity-type polycystic ovary syndrome （PCOS） through the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt） signaling pathway. MethodsThirty-six female Sprague-Dawley （SD） rats were randomly divided into a blank control group （Con） and an obesity-type PCOS model preparation group. The model was induced by gavage with letrozole （1 mg·kg^-1） combined with a high-fat diet （HFD）. After model establishment， the obesity-type PCOS model preparation group was further divided into the model group （Mod， normal saline）， metformin group （Met， 0.3 g·kg^-1）， low-dose MLC group （MLC-L， 4.3 g·kg^-1）， medium-dose MLC group （MLC-M， 8.6 g·kg^-1）， and high-dose MLC group （MLC-H， 17.2 g·kg^-1）. Active components of MLC and targets of obesity-type PCOS were screened from databases， a protein-protein interaction （PPI） network was constructed， and gene ontology（GO）and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis was performed. The gut microbiota structure was analyzed based on 16S rRNA sequencing and correlated with network pharmacology pathways. Body weight and estrous cycle were dynamically monitored. Ovarian morphology was observed by hematoxylin-eosin （HE） staining. Cell apoptosis was detected by terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling （TUNEL）. Enzyme-linked immunosorbent assay （ELISA） was used to detect levels of follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， anti-Müllerian hormone （AMH）， testosterone （T）， and estradiol （E₂）. Western blot was used to detect the protein expression levels of phosphorylated PI3K/PI3K （p-PI3K/PI3K）， phosphorylated Akt/Akt （p-Akt/Akt）， B-cell lymphoma-2 （Bcl-2）， and Bcl-2-associated X protein （Bax）. ResultsNetwork pharmacology screening identified 124 active components of MLC and 408 overlapping targets between the herbal formula and the disease. Core targets such as Akt1 and Bcl-2 were revealed. As indicated by 16S rRNA sequencing， the abundances of Lachnospiraceae， Lachnoclostridium， and Dorea were increased in the MLC groups （P<0.05）， while the abundance of Veillonella was decreased （P<0.05）. KEGG correlation analysis integrating network pharmacology and gut microbiota data showed significant enrichment of the PI3K/Akt signaling pathway. Animal experiments showed that， compared with the Mod group， body weight decreased to normal levels in the Met， MLC-M， and MLC-H groups. The estrous cycle became regular. The number of corpora lutea increased and cystic follicles decreased. Serum levels of T， FSH， and LH/FSH were reduced （P<0.05， P<0.01）， while the E₂ level was increased （P<0.01）. Ovarian cell apoptosis was reduced （P<0.01）， and the protein expression levels of p-PI3K/PI3K， p-Akt/Akt， and Bcl-2 in ovarian tissue were significantly increased， whereas Bax protein expression was significantly decreased （P<0.05， P<0.01）. ConclusionMLC can regulate gut microbiota structure， effectively improve ovarian pathology in rats with obesity-type PCOS， and inhibit ovarian granulosa cell apoptosis. The mechanism may be associated with upregulation of the PI3K/Akt signaling pathway.

BackgroundAdolescents with depressive disorder often engage in non-suicidal self-injury （NSSI） behaviors， which severely impacts their physical and mental health. Impulsivity and emotional regulation are key factors influencing NSSI behaviors. However， research on the mechanisms through which impulsivity and emotional regulation affect NSSI behaviors in adolescent depressive disorder patients with NSSI remains insufficient， limiting the development of effective intervention strategies. ObjectiveTo explore the differences in impulsivity and emotion regulation abilities between adolescent patients with depressive disorder accompanied by and without NSSI behaviors， and to analyze the association between NSSI behaviors and impulsivity and emotion regulation abilities in adolescent patients with depressive disorder accompanied by NSSI behaviors. MethodsA total of 184 adolescents hospitalized in the child and adolescent psychiatry department of Wuxi Mental Health Center from October 2023 to August 2024， who met the diagnostic criteria for depressive disorder according to the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5）， were consecutively enrolled as study subjects. Based on the diagnostic criteria for NSSI in DSM-5， patients were divided into NSSI group （n=108） and non-NSSI group （n=76）. The Barratt Impulsiveness Scale-11 （BIS-11）， the Emotion Regulation Questionnaire （ERQ）， the Adolescent Self-Harm Questionnaire， and the Positive and Negative Suicide Ideation （PANSI） were used for assessment. Spearman correlation analysis was employed to explore the correlation between the scores of the Adolescent Self-Harm Questionnaire and the scores of BIS-11 and ERQ in the NSSI group. Multiple regression analysis was conducted to examine the effects of impulsivity and emotion regulation on NSSI behaviors in the NSSI group. ResultsCompared to the non-NSSI group， the NSSI group showed significantly higher scores in BIS-11 non-planned impulsivity （Z=-4.181， P<0.05）， action impulsivity （t=4.944， P<0.05）， cognitive impulsivity （Z=-3.392， P<0.05）， and total score （t=4.763， P<0.05）， and lower scores in the cognitive reappraisal of ERQ （t=-4.094， P<0.05） and total score （Z=-2.299， P<0.05）， and higher scores in the expression inhibition of ERQ （Z=-3.019， P<0.05）. The correlation analysis results showed that the score of the adolescent self-harm questionnaire in the NSSI group was positively correlated with the behavioral impulsivity factor score in the BIS-11 （r=0.434， P<0.05）. Multiple regression analysis indicated that action impulsivity factor was a significant correlate of self-injury behaviors in the NSSI group （B=0.855， P<0.05）， explaining 22.30% of the total variance. ConclusionAdolescent patients with depressive disorder accompanied by NSSI behaviors exhibit higher levels of impulsivity and poorer emotional regulation abilities. Action impulsivity may play a significant role in the mechanism of NSSI behaviors. ［Funded by Wuxi Municipal Health Commission Research Project （number， Q202320）］

ObjectiveTo investigate the mechanisms by which Mahuang Lianqiao Chixiaodoutang （MLC） improves obesity-type polycystic ovary syndrome （PCOS） through the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt） signaling pathway. MethodsThirty-six female Sprague-Dawley （SD） rats were randomly divided into a blank control group （Con） and an obesity-type PCOS model preparation group. The model was induced by gavage with letrozole （1 mg·kg^-1） combined with a high-fat diet （HFD）. After model establishment， the obesity-type PCOS model preparation group was further divided into the model group （Mod， normal saline）， metformin group （Met， 0.3 g·kg^-1）， low-dose MLC group （MLC-L， 4.3 g·kg^-1）， medium-dose MLC group （MLC-M， 8.6 g·kg^-1）， and high-dose MLC group （MLC-H， 17.2 g·kg^-1）. Active components of MLC and targets of obesity-type PCOS were screened from databases， a protein-protein interaction （PPI） network was constructed， and gene ontology（GO）and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis was performed. The gut microbiota structure was analyzed based on 16S rRNA sequencing and correlated with network pharmacology pathways. Body weight and estrous cycle were dynamically monitored. Ovarian morphology was observed by hematoxylin-eosin （HE） staining. Cell apoptosis was detected by terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling （TUNEL）. Enzyme-linked immunosorbent assay （ELISA） was used to detect levels of follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， anti-Müllerian hormone （AMH）， testosterone （T）， and estradiol （E₂）. Western blot was used to detect the protein expression levels of phosphorylated PI3K/PI3K （p-PI3K/PI3K）， phosphorylated Akt/Akt （p-Akt/Akt）， B-cell lymphoma-2 （Bcl-2）， and Bcl-2-associated X protein （Bax）. ResultsNetwork pharmacology screening identified 124 active components of MLC and 408 overlapping targets between the herbal formula and the disease. Core targets such as Akt1 and Bcl-2 were revealed. As indicated by 16S rRNA sequencing， the abundances of Lachnospiraceae， Lachnoclostridium， and Dorea were increased in the MLC groups （P<0.05）， while the abundance of Veillonella was decreased （P<0.05）. KEGG correlation analysis integrating network pharmacology and gut microbiota data showed significant enrichment of the PI3K/Akt signaling pathway. Animal experiments showed that， compared with the Mod group， body weight decreased to normal levels in the Met， MLC-M， and MLC-H groups. The estrous cycle became regular. The number of corpora lutea increased and cystic follicles decreased. Serum levels of T， FSH， and LH/FSH were reduced （P<0.05， P<0.01）， while the E₂ level was increased （P<0.01）. Ovarian cell apoptosis was reduced （P<0.01）， and the protein expression levels of p-PI3K/PI3K， p-Akt/Akt， and Bcl-2 in ovarian tissue were significantly increased， whereas Bax protein expression was significantly decreased （P<0.05， P<0.01）. ConclusionMLC can regulate gut microbiota structure， effectively improve ovarian pathology in rats with obesity-type PCOS， and inhibit ovarian granulosa cell apoptosis. The mechanism may be associated with upregulation of the PI3K/Akt signaling pathway.

ObjectiveIn order to provide a reference for the optimization of preparation process of stir-fried Glycyrrhizae Radix et Rhizoma（sf-GRR）， the quality changes during the processing was studied. MethodsGlycyrrhizae Radix et Rhizoma was processed by stir-frying for 17 min， and samples were collected every 1 min during the processing. The appearance color of the samples was determined by visual analysis technology， the moisture and extract of the process samples were detected by the drying method and the hot extraction method of alcohol-soluble extract in the general rules of the 2020 edition of Chinese Pharmacopoeia（part Ⅳ）， and the contents of liquiritin apioside， liquiritin， isoliquiritin apioside， isoliquiritin， licoricesaponin G₂ and glycyrrhizic acid in the process samples were determined by high performance liquid chromatography（HPLC）. Then principal component analysis（PCA）， partial least squares-discriminant analysis（PLS-DA） and Spearman correlation analysis were used for clustering， discrimination and correlation analysis of the appearance color， moisture， extract and the contents of six internal components. Based on artificial neural network and random forest algorithm， the prediction model of processing degree of sf-GRR was established. On this basis， based on the five principles of quality marker（Q-Maker）， explore the monitoring Q-Maker of sf-GRR. ResultsThe color of Glycyrrhizae Radix et Rhizoma deepened after stir-frying， and the appearance color of the sample changed from light yellow to dark yellow during processing. During the stir-frying process， the moisture content showed a decreasing trend with the extension of processing time， while the extract content showed an increasing trend with the extension of processing time. After stir-frying， the contents of liquiritin apioside， liquiritin and licoricesaponin G₂ showed an overall decreasing trend， while the contents of isoliquiritin apioside and isoliquiritin increased， and the content of glycyrrhizic acid increased slightly. The correlation analysis showed that moisture was positively correlated with brightness（L^*） and red/green value（a^*）， and negatively correlated with yellow/blue value（b^*） and total color difference（E^*ab）. Isoliquiritin apioside and isoliquiritin had negative correlation with L^* and a^*， and positive correlation with b^* and E^*ab. The processing process of sf-GRR could be divided into two stages of the early stage（0-14 min） and the late stage（15-17 min）， and could be divided into three stages of the early stage（0-6 min）， the middle stage（7-14 min） and the late stage（15-17 min） by combining the moisture， extract， the contents of 6 components and color values. Based on artificial neural network analysis and random forest algorithm， isoliquiritin apioside， isoliquiritin， liquiritin and glycyrrhizic acid were selected as monitoring markers for sf-GRR. ConclusionBased on the analysis of the exterior-interior indicators of process samples of sf-GRR， this paper ultimately identifies four processing monitoring markers， which can provide a basis for optimizing the processing technology of sf-GRR.

Jianghuanglian is one of the representative processed products of Coptidis Rhizoma for treating cold syndrome with drugs of heat nature， and ginger is used to restrict the bitter cold of Coptidis Rhizoma， which can be traced back to Bojifang， and it is suitable for stagnation of damp-heat in middle-jiao， cold-heat mutual knots and other symptoms. Jianghuanglian retains the alkaloids， phenylpropanoids and flavonoids of Coptidis Rhizoma， and also introduces gingerol components such as 6-gingerol in ginger， which has pharmacological activities such as anti-inflammatory， antibacterial， anti-tumor， and improving gastrointestinal function. The 2020 edition of Chinese Pharmacopoeia and many local processing specifications have included the traditional processing process and quality standards of Jianghuanglian， but the specific process parameters and quality standards are incomplete， which limits the production and clinical application of this processed product. By summarizing the processing history， process research， quality evaluation， pharmacodynamic and medicinal property changes and application of Jianghuanglian in the past 20 years， there are differences in the processing methods and standards in various provinces and cities， which are mainly reflected in the preparation method， dosage， processing process and quantitative standards of ginger juice. In addition， there are also certain differences in the changes of the main components of Jianghuanglian prepared from ginger or dried ginger， as well as their efficacy and medicinal properties. The research on the processing process of Jianghuanglian plays an important role in improving its quality standards， and this review can provide a reference for improving the quality evaluation system of Jianghuanglian.

Electromagnetic fields can regulate the fundamental biological processes involved in bone remodeling. As a non-invasive physical therapy, electromagnetic fields with specific parameters have demonstrated therapeutic effects on bone remodeling diseases, such as fractures and osteoporosis. Electromagnetic fields can be generated by the movement of charged particles or induced by varying currents. Based on whether the strength and direction of the electric field change over time, electromagnetic fields can be classified into static and time-varying fields. The treatment of bone remodeling diseases with static magnetic fields primarily focuses on fractures, often using magnetic splints to immobilize the fracture site while studying the effects of static magnetic fields on bone healing. However, there has been relatively little research on the prevention and treatment of osteoporosis using static magnetic fields. Pulsed electromagnetic fields, a type of time-varying field, have been widely used in clinical studies for treating fractures, osteoporosis, and non-union. However, current clinical applications are limited to low-frequency, and research on the relationship between frequency and biological effects remains insufficient. We believe that different types of electromagnetic fields acting on bone can induce various “secondary physical quantities”, such as magnetism, force, electricity, acoustics, and thermal energy, which can stimulate bone cells either individually or simultaneously. Bone cells possess specific electromagnetic properties, and in a static magnetic field, the presence of a magnetic field gradient can exert a certain magnetism on the bone tissue, leading to observable effects. In a time-varying magnetic field, the charged particles within the bone experience varying Lorentz forces, causing vibrations and generating acoustic effects. Additionally, as the frequency of the time-varying field increases, induced currents or potentials can be generated within the bone, leading to electrical effects. When the frequency and power exceed a certain threshold, electromagnetic energy can be converted into thermal energy, producing thermal effects. In summary, external electromagnetic fields with different characteristics can generate multiple physical quantities within biological tissues, such as magnetic, electric, mechanical, acoustic, and thermal effects. These physical quantities may also interact and couple with each other, stimulating the biological tissues in a combined or composite manner, thereby producing biological effects. This understanding is key to elucidating the electromagnetic mechanisms of how electromagnetic fields influence biological tissues. In the study of electromagnetic fields for bone remodeling diseases, attention should be paid to the biological effects of bone remodeling under different electromagnetic wave characteristics. This includes exploring innovative electromagnetic source technologies applicable to bone remodeling, identifying safe and effective electromagnetic field parameters, and combining basic research with technological invention to develop scientifically grounded, advanced key technologies for innovative electromagnetic treatment devices targeting bone remodeling diseases. In conclusion, electromagnetic fields and multiple physical factors have the potential to prevent and treat bone remodeling diseases, and have significant application prospects.

Objective: To investigate the distribution characteristics and related factors of weight loss behavior among middle school students in Shanghai, so as to provide a reference for guiding scientific weight loss among middle school students. Methods: From May to June 2021, a stratified cluster random sampling method was used to select 16 758 junior and high school students in 16 districts of Shanghai. Youth Risk Behavior Surveillance System was administered to assess the basic condition and weight loss behaviors of the students. An unordered multinomial Logistic regression model was employed to analyze the factors associated with weight loss behaviors. Results: A total of 5 881 (35.09%) reported engaging in exercise for weight loss, 6 344 (37.86%) reported dieting for weight loss, and 461 (2.75%) engaged in unhealthy weight loss behaviors. The unordered multinomial Logistic regression analysis indicated that compared with the no weight loss behavior group, students from urban areas( OR =1.35,95% CI =1.10-1.66), those with Internet addiction ( OR =1.71,95% CI =1.23-2.38), those with victims of bullying ( OR =2.09, 95% CI =1.68-2.61), those experiencing insomnia ( OR =2.33,95% CI = 1.74-3.11), those feelings of sadness or despair ( OR =3.10, 95% CI =2.42- 3.97 ), and those who perceived their body weight as slightly heavy ( OR =2.77, 95% CI = 2.17-3.55) or very heavy ( OR =3.41, 95% CI =2.44-4.75) were more likely to engage in unhealthy weight loss behaviors ( P <0.05). Conclusions There are significant differences in weight loss behaviors among middle school students with varying characteristics in Shanghai. Negative emotions such as insomnia and feelings of sadness or despair, Internet addiction, cognitive bias in weight and experiences of bullying are identified as related factors for unhealthy weight loss behaviors. Targeted intervention measures should be implemented to guide students towards scientific approaches to weight management.

A growing body of research points out that gut microbiota plays a key role in tumor immunotherapy. By optimizing the composition of intestinal microbiota, it is possible to effectively improve immunotherapy resistance and enhance its therapeutic effect. This article comprehensively analyzes the mechanism of intestinal microbiota influencing tumor immunotherapy resistance, expounds the current strategies for targeted regulation of intestinal microbiota, such as traditional Chinese medicine and plant components, fecal microbiota transplantation, probiotics, prebiotics and dietary therapy, and explores the potential mechanisms of these strategies to improve patients' resistance to tumor immunotherapy. At the same time, the article also briefly discusses the prospects and challenges of targeting intestinal microbiota to improve tumor immunotherapy resistance, which provides a reference for related research to help the strategy research of reversing tumor immunotherapy resistance.

Objective: To analyze the temporal variation patterns of sickness absenteeism among primary and secondary school students in Shanghai, so as to explore models suitable for predicting peaks and intensity of absenteeism rates. Methods: The seasonal and trend decomposition using loess (STL) method was used to analyze the seasonal and long term trend changes in sickness absenteeism among primary and secondary school students from September 1 in 2010 to June 30 in 2018, in Shanghai. A hierarchical clustering method based on Dynamic Time Warping (DTW) was employed to classify absenteeism symptoms with similar temporal patterns. Based on historical data, the study constructed and evaluated different time series algorithms and machine learning models to optimize the accuracy of predicting the trend of sickness absenteeism. Results: During the research period, the average new absenteeism rate due to illness was 16.86 per 10 000 person day for every academic year, and the trend of sickness absenteeism exhibited both seasonality and a long term upward trend, reaching its highest point in the 2017 academic year (22.47 per 10 000 person day). The symptoms of absenteeism were divided into three categories: high incidence in winter and spring (respiratory symptoms, fever and general discomfort, etc.), high incidence in summer (eye symptoms, nosebleeds, etc.) and those without obvious seasonality (skin symptoms, accidental injuries, etc.).The constructed time series models effectively predicted the trend of absenteeism due to illness, although the accuracy of predicting peak intensity was relatively low. Among them, the multi layer perceptron (MLP) model performed the best, with an root mean squared error (RMSE) of 8.96 and an mean absolute error (MAE) of 4.37, reducing 36.51% and 39.02% compared to the baseline model. Conclusion Time series models and machine learning algorithms could effectively predict the trend of sickness absenteeism, and corresponding prevention and control measures can be taken for absenteeism caused by different symptoms during peak periods.