ObjectiveTo explore the relationship between negative life events and depression severity in adolescent patients with depressive disorder， as well as the chain mediating role of insomnia symptoms and quality of life. Methods374 outpatient patients and hospitalized patients with adolescent depressive disorders were enrolled. The Adolescent Life Event Scale （ASLEC）， the Insomnia Severity Index （ISI）， the World Health Organization Quality of Life Questionnaire Short Form （WHOQOL-BREF）， and the Center for Epidemiology Depression Scale （CES-D） were used to evaluate the negative life event situation， insomnia symptoms， quality of life level and depression severity of the subjects， respectively. In addition， the PROCESS 4.0 macroprogram was used to analyze the chain mediating effect of insomnia symptoms and quality of life between negative life events and depression severity in patients with adolescent depressive disorder. ResultsThe results of correlation analysis showed that there was a significant correlation between negative life events and insomnia symptoms， quality of life， and depression severity （all P<0.05）. In addition， the results of chain mediation showed that negative life events had a significant direct effect on depression severity， with an effect size of 0.12 （P<0.001）. Insomnia symptoms and quality of life played a mediating role in the relationship between negative life events and depression severity in patients with adolescent depressive disorders， with indirect effect sizes of 0.062 （95%CI： 0.040-0.087） and 0.091 （95%CI： 0.059-0.123）， respectively. It could also play a chain mediation role， and the effect size was 0.039 （95%CI： 0.024-0.057）. ConclusionNegative life events experienced by patients with adolescent depressive disorder not only directly affect the severity of depressive symptoms， but may also indirectly exacerbate depression through insomnia symptoms and quality of life.

With the integration of 5G communication technology and robotic surgical systems, remote robot-assisted thoracic surgery is overcoming geographical barriers, offering an innovative approach to addressing the uneven distribution of medical resources. This study conducted a systematic literature review—using databases such as PubMed and CNKI, with the search period extending up to 2025—incorporating clinical studies, case reports, and review articles to comprehensively evaluate the clinical efficacy and safety of 5G-enabled remote robot-assisted thoracic surgery (5G-RRATS). The analysis also examined current technological limitations and potential future development trajectories. Existing evidence indicates that, given adequate technical support, 5G-RRATS can achieve perioperative outcomes comparable to those of conventional local robotic surgeries across procedures including pulmonary wedge resection, lobectomy, and esophagectomy. Furthermore, it demonstrates potential advantages in minimizing surgical incisions and reducing intraoperative blood loss. Nevertheless, challenges related to network stability, latency control, interdisciplinary collaboration between medical and engineering teams, and legal, regulatory, and ethical considerations continue to hinder widespread clinical adoption. Looking ahead, the emergence of a "one-to-many" remote surgical model, combined with the integration of artificial intelligence and augmented reality technologies, as well as advancements in low-orbit satellite communications, may enable 5G-RRATS to further advance precision and efficiency in thoracic surgery, thereby facilitating equitable access to high-quality care for a broader patient population.

Objective To investigate the role of circular RNA,circMYCBP2,which is highly expressed in lymph node(LN)metastatic bladder cancer(BCa)tissues,in enhancing BCa cell adhesion and mediating lymphovascular invasion(LVI),and to evaluate its clinical relevance and potential therapeutic value.Methods High-throughput sequencing identified circRNAs with high expression in LN metastatic BCa tissues.Further validation of their expression in bladder cancer tissues was conducted through clinical samples.The coding ability of circMYCBP2 was predicted by circBank bioinformatics website,and the encoded short peptide was detected by immunoprecipitation(co-IP)combined with silver staining and Western blot(WB).Then,by constructing BCa cells with overexpression and knockdown of circMYCBP2 in vitro,the invasive ability of BCa cells was verified by wound healing and transendothelial cell migration assays.The underlying mechanism of circMYCBP2 in the forma-tion of LVI was explored through RNA pulldown,qRT-PCR and WB.Results High-throughput sequencing and clinical sample validation confirmed that circMYCBP2 is highly expressed in LN metastatic BCa.In vitro experi-ments demonstrated that circMYCBP2 overexpression significantly enhanced BCa cell migration across lymphatic endothelial cells.Mechanistically,circMYCBP2 encodes the short peptide MYCBP2-227aa via an IRES-dependent mechanism by interacting with EIF3H.Overexpression of MYCBP2-227aa increased the mRNA stability of VCAM-1,thereby enhancing the invasive capacity of UM-UC-3 cells.Conclusions CircMYCBP2 encodes the short peptide MYCBP2-227aa through an EIF3H-mediated,IRES-dependent translation mechanism.MYCBP2-227aa regulates VCAM-1 expression and promotes the invasive behavior of BCa cells.Our findings elucidate the critical biological role and molecular mechanism of circMYCBP2 in the formation of LVI and LN metastasis of BCa,providing a potential biomarker and therapeutic target for early lymphatic metastasis in BCa.

Objective To investigate the role of circular RNA,circMYCBP2,which is highly expressed in lymph node(LN)metastatic bladder cancer(BCa)tissues,in enhancing BCa cell adhesion and mediating lymphovascular invasion(LVI),and to evaluate its clinical relevance and potential therapeutic value.Methods High-throughput sequencing identified circRNAs with high expression in LN metastatic BCa tissues.Further validation of their expression in bladder cancer tissues was conducted through clinical samples.The coding ability of circMYCBP2 was predicted by circBank bioinformatics website,and the encoded short peptide was detected by immunoprecipitation(co-IP)combined with silver staining and Western blot(WB).Then,by constructing BCa cells with overexpression and knockdown of circMYCBP2 in vitro,the invasive ability of BCa cells was verified by wound healing and transendothelial cell migration assays.The underlying mechanism of circMYCBP2 in the forma-tion of LVI was explored through RNA pulldown,qRT-PCR and WB.Results High-throughput sequencing and clinical sample validation confirmed that circMYCBP2 is highly expressed in LN metastatic BCa.In vitro experi-ments demonstrated that circMYCBP2 overexpression significantly enhanced BCa cell migration across lymphatic endothelial cells.Mechanistically,circMYCBP2 encodes the short peptide MYCBP2-227aa via an IRES-dependent mechanism by interacting with EIF3H.Overexpression of MYCBP2-227aa increased the mRNA stability of VCAM-1,thereby enhancing the invasive capacity of UM-UC-3 cells.Conclusions CircMYCBP2 encodes the short peptide MYCBP2-227aa through an EIF3H-mediated,IRES-dependent translation mechanism.MYCBP2-227aa regulates VCAM-1 expression and promotes the invasive behavior of BCa cells.Our findings elucidate the critical biological role and molecular mechanism of circMYCBP2 in the formation of LVI and LN metastasis of BCa,providing a potential biomarker and therapeutic target for early lymphatic metastasis in BCa.

Objective To review the application of artificial intelligence(AI)in the identification,monitoring and intervention of sleep disorders in the elderly and the effect. Methods A scoping review was conducted by searching relevant literature ahout the application of AI in the field of sleep disorders among the elderly from databases including PubMed,Web of Science,CNKI,and Wanfang data,covering literatures from the establishment to June,2024. Results A total of ten articles were included,originating from seven countries and involving 36 344 elderly participants.The publication dates ranged from 2020 to 2024.The study types included six cross-sectional studies,one pro-spective study,one self-controlled study and two randomized controlled trials.The articles mainly came from the fields of clinical medicine,sleep research,rehabilitation medicine and information engineering.AI was primarily used for monitoring the entire sleep process of the elderly,predicting and identifying sleep disorders,and inter-ventions such as biofeedback,online consultations and cognitive-behavioral therapy based on mobile platforms. Conclusion AI not only improves the accuracy of diagnosing sleep disorders,but also provides robust data support for clinical intervention.Online sleep interventions based on big data and intelligent algorithms can offer effective health management for the elderly.

Objective: To analyse the effects of physical activity on neurocognitive function in children with autism spectrum disorder (ASD),so as to provide a theoretical basis and specific guidance for the clinical cognitive function rehabilitation practice of ASD children. Methods: Relevant literature on the effects of physical activity on neurocognitive function in children with ASD were searched in the China National Knowledge Infrastructure (CNKI), Wanfang, Web of Science, and EBSCO databases from their inception to March 2024 using specific subject terms. Information on authors, countries, publication dates, study populations, diagnostic criterion, interventions, measurement tools and study results were extracted postscreening. The methodological quality of the articles was assessed using the PEDro Scale, followed by a systematic review. Results: A total of seventeen articles and were included in the study and English literature, most of them were of good quality. The study included 10 randomized controlled trials, 4 quasiexperimental designs, and 3 preand posttest designs. The rehabilitative effects of physical activity on children with ASD were primarily observed in enhanced attention and executive function, as well as improvements in brain structure and function. Children with ASD showed varying cognitive effects in physical and skillbased programs, with skillbased activities like basketball and table tennis notably improving cognitive function. Conclusion Physical activity is an effective intervention that enhances cognitive abilities such as attention and executive function, as well as brain structure and function in children with ASD.

As people's living standards improve， the development trend of diabetes has gradually become severe. Diabetes is a chronic inflammatory disease associated with abnormal expression of nuclear factor-kappa B （NF-κB） in patients. NF-κB exists in various tissue cells and participates in the regulation of a variety of genes related to immune function and inflammation. Varieties of factors can activate NF-κB when the body is stimulated by external factors， so as to produce inflammation and other reactions. Previous studies on NF-κB mainly focus on cancer， and the pathological mechanism of the treatment of diabetes by related signaling pathways and the progress of traditional Chinese medicine （TCM） treatment have not been systematically elaborated on. By referring to the relevant literature in China and abroad， it was found that NF-κB is not isolated in the development and progression of diabetes but is associated with signal molecules related to inflammation， oxidative stress， and energy metabolism， and it is involved in mediating inflammation， pancreatic β cell apoptosis， insulin signal transduction， and other physiological functions. Therefore， blocking the transmission of NF-κB signaling pathway is beneficial to the treatment of diabetes. At present， Western medicine for the treatment of diabetes mainly includes oral hypoglycemic drugs and insulin injections， but the adverse reactions are obvious. TCM has been characterized by multi-target， extensive action， and excellent curative effects in the treatment of diabetes. TCM and its compounds with functions of tonifying Qi and promoting blood circulation， regulating qi and eliminating phlegm， clearing heat and detoxifying， and nourishing Yin and moistening dryness can effectively intervene in the abnormal expression of NF-κB signaling pathway in vivo through anti-inflammatory effects. In this paper， the association between NF-κB signaling pathway and diabetes was summarized， and the modern research progress of TCM intervention of NF-κB signaling pathway in the treatment of diabetes in the past five years was reviewed， so as to lay a laboratory foundation for the study of a new pathological mechanism of diabetes based on NF-κB signaling pathway and provide new targets and research direction for the prevention and treatment of diabetes and development of related TCM.

ObjectiveTo systematically review the effect of neurofeedback training on cognitive function in the elderly within the framework of the International Classification of Diseases 11th Revision (ICD-11), and International Classification of Functioning, Disability and Health (ICF). MethodsA PICO framework was constructed. Randomized controlled trials on neurofeedback training for cognitive function in the elderly from PubMed, Web of Science, ProQuest, and CNKI up to July, 2023 were systematically reviewed. Methodological quality assessment of the included literature was performed using Physiotherapy Evidence Database scale. ResultsA total of 15 researches were included, from ten countries, involving 520 participants, who were healthy elderly individuals or those with mild cognitive impairment. Various neurofeedback waveforms were utilized, such as alpha, beta, theta, beta/alpha, and sensorimotor rhythm (SMR) waves. Intervention duration ranged from 20 to 90 minutes, with intervention frequencies spanning from a long-term intervention of 30 sessions over 12 weeks to a high-frequency short-term intervention of eight sessions over one week. The primary health outcomes focused on cognitive function, including memory, attention, inhibitory control and executive function. ConclusionNeurofeedback training can improve the cognitive function of the eldery, and alleviate cognitive aging.

ObjectiveTo investigate the effect of rutin on the browning of 3T3-L1 preadipocytes and the mechanism. MethodCell counting kit-8 （CCK-8） assay was used to detect the effect of different concentration of rutin （3.125， 6.25， 12.5， 25， 50， 100， 200 μmol·L^-1） on 3T3-L1 cell activity， and Western blot to examine the effect of rutin （12.5， 25， 50 μmol·L^-1） on the expression of thermogenesis-associated proteins uncoupling protein 1 （UCP1）， PR domain containing 16 （PRDM16） and peroxisome proliferator-activated receptor γ coactivator-1α （PGC-1α） in adipocytes. After the optimal concentration of rutin was determined， the effect of rutin on lipid droplet formation in adipocytes was observed based on oil red O staining， and the expression of nuclear respiratory factor 1 （NRF1）， nuclear respiratory factor 2 （NRF2） and mitochondrial transcription factor A （TFAM）， which were the landmark proteins of mitochondrial biosynthesis， was detected by Western blot. ResultCompared with the blank group， 200 μmol·L^-1 rutin inhibited 3T3-L1 cell activity （P<0.01）. Compared with the blank group， at the concentration of 12.5， 25， 50 μmol·L^-1 rutin significantly promoted the expression of thermogenesis-associated proteins （UCP1， PRDM16， and PGC-1α） （P<0.01）， which was determined as the optimal concentration. Compared with the blank group， 50 μmol·L^-1 rutin significantly increased the immunofluorescence intensity of mitochondrial UCP1 protein in 3T3-L1 cells （P<0.01） and the expression of the markers of mitochondrial biosynthesis （NRF1， NRF2， and TFAM） （P<0.01）. In addition， 50 μmol·L^-1 rutin significantly inhibited lipid droplet formation of 3T3-L1 adipocytes （P<0.01）. ConclusionRutin inhibited lipid droplet deposition in 3T3-L1 adipocytes and increased the expression of thermogenesis-related proteins （UCP1， PRDM16， and PGC-1α） and markers of mitochondrial biosynthesis （NRF1， NRF2， and TFAM）， thereby inducing the browning of 3T3-L1 adipocytes. This lays a basis for the development of drugs that safely regulate the browning of white cells.

Background With the increasing exposure to hazardous chemicals in the workplace and frequency of occupational injuries and occupational safety accidents, the acquisition of occupational exposure limits of hazardous chemicals is imminent. Objective To obtain more unknown immediately dangerous to life or health (IDLH) concentrations of hazardous chemicals in the workplace by exploring the application of quantitative structure-activity relationship (QSAR) prediction method to IDLH concentrations, and to provide a theoretical basis and technical support for the assessment and prevention of occupational injuries. Methods QSAR was used to correlate the IDLH values of 50 benzene and its derivatives with the molecular structures of target compounds. Firstly, affinity propagation algorithm was applied to cluster sample sets. Secondly, Dragon 2.1 software was used to calculate and pre-screen 537 molecular descriptors. Thirdly, the genetic algorithm was used to select six characteristic molecular descriptors as dependent variables and to construct a multiple linear regression model (MLR) and two nonlinear models using support vector machine (SVM) and artificial neural network (ANN) respectively. Finally, model performance was evaluated by internal and external validation and Williams diagram was drawn to determine the scopes of selected models. Results The ANN model results showed that \begin{document}$ {R}_{\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{i}\mathrm{n}}^{2} $\end{document}=0.8526 and \begin{document}$ {R}_{\mathrm{t}\mathrm{e}\mathrm{s}\mathrm{t}}^{2} $\end{document}=0.8505 respectively, root mean square (RMSE) error=0.5243, mean absolute error (MAE)=0.4610, internal and external validation coefficients \begin{document}$ {Q}_{\mathrm{l}00}^{2} $\end{document}=0.8476 and \begin{document}$ {Q}_{\mathrm{e}\mathrm{x}\mathrm{t}}^{2} $\end{document}=0.8905 respectively. By comparison, the performance verification parameters of the ANN model were superior to the MLR and SVM models, and all substances were in the applicable domain. Conclusion At present, the ANN model has the best performance in fitting ability, stability, and prediction, and is suitable for predicting IDLH concentrations of benzene and its derivatives. Predicting the IDLH concentraitons of benzene and its derivatives by QSAR method is an effective method, and provides a theoretical basis and technical support for the development of occupational health and safety.