OBJECTIVE To investigate the improvement effects and mechanism of Zhichi suanzaoren decoction （ZSD） on hippocampal oxidative stress injury in hippocampal neurons of mice with perimenopausal insomnia. METHODS The potential targets of active ingredients in ZSD were predicted using TCMSP and TCMIP databases； the targets related to insomnia were searched through GeneCards， OMIM and DisGeNET databases； protein-protein interaction network of intersecting targets of ZSD ingredients and insomnia was constructed； Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were conducted on key targets. Sixty mice were divided into sham operation group， model group， ZSD low-， medium-， and high-dose groups （11， 22， and 33 g/kg）， and eszopiclone group （positive control， 1 mg/kg）. Except for sham operation group， the perimenopausal insomnia model was constructed by ovariectomy （OVX） in the other groups. After successful modeling， mice in each group were gavaged with normal saline or the corresponding drug solution， once a day， for three consecutive weeks. The sleep status of mice was evaluated through the pentobarbital sodium sleep synergy experiment， and the pathological changes of hippocampal neurons and the expressions of related genes and proteins in mice were observed by HE staining， immunohistochemistry staining， immunofluorescence staining， transcriptome sequencing technology and Western blot. RESULTS The results of network pharmacology showed that there were 296 intersection targets between ZSD and perimenopausal insomnia. Protein kinase B1 （Akt1） was a key target for treating insomnia with ZSD. After administration of ZSD， the sleep latency of mice was shortened， the sleep duration was prolonged significantly， and the mean optical density value of neuron-specific nuclear protein in the hippocampal CA1 region was significantly increased （P＜0.01）. Additionally， hippocampal neuron damage in OVX mice was significantly alleviated. The results of transcriptome sequencing showed that ZSD significantly upregulated the transcriptional levels of Nfe2l2 gene in hippocampal tissue of OVX mice （P＜0.05）. After administration of ZSD， protein expressions of nuclear factor E2 related factor 2 （Nrf2） and heme oxygenase-1 （HO-1） in hippocampal tissue of OVX mice， as well as the phosphorylated Akt level， were increased significantly （P＜0.01）. CONCLUSIONS ZSD can ameliorate hippocampal oxidative stress injury of hippocampal neurons in perimenopausal insomnia mice by activating the Akt/Nrf2/HO-1 signaling pathway.

[Objective]To summarize Professor ZHANG Youhua's clinical experience in treating multiple-dream disorder based on the emotion syndrome differentiation theory.[Methods]By sorting out,reviewing and analyzing Professor ZHANG's medical cases related to the treatment of multiple dream disorder,this paper summarized Professor ZHANG's academic experience in the treatment of multiple-dream disorder from the aspects of etiology,pathogenesis,treatment principles and methods of traditional Chinese medicine understanding the association between dreams and emotional states,and listed one medical case for vevification.[Results]In the treatment of multiple dream disorder,Professor ZHANG emphasizes the importance of the emotional experience in dreams rather than the content of the dreams themselves.Therefore,the use of emotion syndrome differentiation method is deemed appropriate.According to the emotional experience in dreams,multiple-dream disorder is divided into five basic types:thinking,panic,anger,sad sorrow and joy syndromes.The three core pathogeneses of"Qi,phlegm and fire"are addressed through methods such as eliminating phlegm,regulating Qi and clearing fire.The medical case cited was multiple-dream disorder with panic syndrome,"phlegm stagnation and fire hyperactivity"was the main pathogenesis,the treatment of clearing fire and eliminating phlegm,calming the heart and tranquilizing the mind was adopted,and the prescription was based on Qinlian Wendan Decoction,added and subtracted according to the syndrome,and achieved a significant effect.[Conclusion]Professor ZHANG Yonghua's approach to treating multiple-dream disorder is based on the theory of emotional syndrome differentiation theory.He emphasizes the importance of emotional experiences in dreams,and his unique experience has shown remarkable clinical results.This approach is worth considering,learning from and promoting.

Objective To explore the medication experience of famous traditional Chinese medicine(TCM)Zhang Yonghua in insomnia based on the data mining and analysis,and to provide guidance for the treatment of insomnia with traditional Chinese medicine.Methods A total of 195 medical cases of famous TCM for insomnia disorder were collected.The Ancient and Modern Medical record cloud platform V 2.3.7 was used to analyze the TCM syndromes,the frequency of Chinese medicinals,formulas,four properties,five flavors and the meridian tropism of Chinese medicinals,and hierarchical cluster analysis,community analysis and complex network analysis were also carried out to summarize the medication rules of TCM Zhang Yonghua for insomnia.Results The main TCM syndrome types of insomnia were irritability and irritability and excessive thinking.A total of 115 Chinese medicinals were involved in 195 cases,with the main actions of calming the mind,clearing fire,resolving phlegm and regulating thi.Complex network analysis obtained the core traditional Chinese medicines as bupleurum,Scutellaria baicalensis,Pinellia pinellia,Poria cocos,Shouwu vine,Acacia bark,Coptis chinensis,Yuanzhi,Jujube kernel and Licorice.Conclusion Famous TCM Zhang Yonghua treated insomnia with the emotional syndrome differentiation theory.According to the pathogenesis of,phlegm,and fire,formulas of regulation,phlegm resolving,and fire clearing are prescribed respectively for its root cause,formulas of calming the mind a given for the manifestation,and finally to cure insomnia by regulating abnormal emotions.

Objective To observe the effect of traditional Chinese medicine(TCM)syndrome differentiation treatment of insomnia on depressive symptoms and interleukin(IL)-6 level and tumor necrosis factor(TNF)-α level in serum.And then to discuss the effect of TCM syndrome differentiation treatment of insomnia on reducing the occurrence and development of depression.Methods Sixty patients with insomnia disorder in Hangzhou Hospital of Traditional Chinese Medicine from September 2020 to July 2022 were selected as research objects,and they were divided into intervention group and blank group 30 patients for each group,according to their treatment intention and they were treated with sleep hygiene education plus TCM syndrome differentiation treatment and sleep hygiene education alone respectively.The changes of sleep,depression,serum IL-6 level and TNF-α level were compared between two groups.Results After 2 weeks of intervention,the intervention group's Pittsburgh sleep quality index score,patient health questiomnare-9 score,TCM symptom score,and serum IL-6 and TNF-α level were all significantly reduced,and the difference was statistically significant(P＜0.05).Conclusion TCM syndrome differentiation treatment can effectively improve insomnia and depression,thus delaying the occurrence and development of depression,and is an effective method for early intervention of depression.

Purpose: Myofibroblastic cancer-associated fibroblasts (myCAFs) are important components of the tumor microenvironment closely associated with tumor stromal remodeling and immunosuppression. This study aimed to explore myCAFs marker gene biomarkers for clinical diagnosis and therapy for patients with bladder cancer (BC). Materials and Methods: BC single-cell RNA sequencing (scRNA-seq) data were obtained from the National Center for Biotechnology Information Sequence Read Archive. Transcriptome and clinical data were downloaded from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Subsequently, univariate Cox and LASSO (Least Absolute Shrinkage and Selection Operator regression) regression analyses were performed to construct a prognostic signature. Immune cell activity was estimated using single-sample gene set enrichment analysis whilst the TIDE (tumor immune dysfunction and exclusion) method was employed to assess patient response to immunotherapy. The chemotherapy response of patients with BC was evaluated using genomics of drug sensitivity in cancer. Furthermore, Immunohistochemistry was used to verify the correlation between MAP1B expression and immunotherapy efficacy. The scRNA-seq data were analyzed to identify myCAFs marker genes. Results: Combined with bulk RNA-sequencing data, we constructed a two-gene (COL6A1 and MAP1B) risk signature. In patients with BC, the signature demonstrated outstanding prognostic value, immune infiltration, and immunotherapy response. This signature served as a crucial guide for the selection of anti-tumor chemotherapy medications. Additionally, immunohistochemistry confirmed that MAP1B expression was significantly correlated with immunotherapy efficacy. Conclusions Our findings revealed a typical prognostic signature based on myCAF marker genes, which offers patients with BC a novel treatment target alongside theoretical justification.

In magnetic resonance examination,the interaction between implants and the radio frequency(RF)fields induces heating in human tissue and may cause tissue damage.To assess the RF-induced heating of implants,three steps should be executed,including electromagnetic model construction,electromagnetic model validation,and virtual human body simulations.The crucial step of assessing RF-induced heating involves the construction of a test environment for electromagnetic model validation.In this study,a hardware environment,comprised of a RF generation system,electromagnetic field measurement system,and a robotic arm positioning system,was established.Furthermore,an automated control software environment was developed using a Python-based software development platform to enable the creation of a high-precision automated integrated test environment.The results indicate that the electric field generated in this test environment aligns well with the simulated electric field,making it suitable for assessing the RF-induced heating effects of implants.

This paper investigates the mechanism of radio-frequency(RF)heating that occurs when two adjacent orthopedic implants are present together under magnetic resonance imaging(MRI)at 1.5 Tesla and 3.0 Tesla.When a patient has multiple implants close to each other,interactions between the implants may increase RF heating.Typical generic interlocking plate and antibiotic nail implants are adopted as examples.To analyze the effect of adjacent implants,the amplitude and direction of incident and scattering vector electric fields at the hot spot position are calculated and extracted using numerical simulation based on Huygens principle.It is shown that a strong coupling effect occurs due to the existence of both the incident field and a strong scattering field.Huygens principle can be used to obtain the first and second order scattering fields generated between implants.If the first-and second-order electric field terms are summed within a certain region,the RF-induced heating of this dual-implant system increases.

Brain-computer interface(BCI)devices are crucial tools for neural stimulation and recording,offering broad prospects in the diagnosis and treatment of neurological disorders.Furthermore,magnetic resonance imaging(MRI)is an effective and non-invasive technique for capturing whole-brain signals,providing detailed information on brain structures and activation patterns.Integrating the neural stimulation/recording capabilities of BCI devices with the non-invasive detection function of MRI is considered highly significant for brain function analysis.However,this combination imposes specific requirements on the magnetic and electronic performance of neural interface devices.The interaction between BCI devices and MRI is initially explored.Subsequently,potential safety risks arising from their combination are summarized and organized.Starting from the source of these hazards,such as the metallic electrodes and wires of BCI devices,the issues are analyzed,and current research countermeasures are summarized.In conclusion,the regulatory oversight of BCI's magnetic resonance safety is briefly discussed,and suggestions for enhancing the magnetic resonance compatibility of related BCI devices are proposed.

Objective:To assess the association between short-term ambient air pollution exposure and arterial stiffness and whether obesity modifies these associations.Methods:A cross-sectional study was conducted based on Fangshan family cohort in Beijing. The 24 hours average air pollutant levels on the day cohort participants took baseline survey were calculated as short-term air pollution. A generalized additive model (GAM) with Gaussian links was used to estimate changes in typical carotid artery intima-media thickness (CIMT), brachial-ankle pulse wave velocity (BAPWV), pulse pressure (PP) and ankle-branchial index (ABI) after short-term exposure to each air pollution (PM 2.5, PM 10, SO 2, NO 2, CO). The cross-product terms of each air pollution, body mass index (BMI), and waist-to-hip ratio were included in the GAM model to test the interaction. Further, they conducted a stratified analysis to test their effects on the relationship between short-term exposure to each air pollution and the arterial stiffness indicators. Results:A total of 4 211 individuals were included in the analysis. Individuals' age was (58.9±8.7) years, of which 2 268 (53.9%) were female. Several covariates, including sociodemographic factors, lifestyle behaviors, and history of drugs, were included in the analysis. The results of the GAM analysis showed that an increase in PM 2.5 ( β=2.912×10 -4, 95% CI: 1.424×10 -4-4.400×10 -4, P<0.001), CO ( β=0.027, 95% CI: 0.011-0.043, P<0.001), SO 2 ( β=2.070×10 -3, 95% CI: 7.060×10 -4-3.430×10 -3, P=0.003), and NO 2 ( β=3.650×10 -4, 95% CI: 2.340×10 -5-7.060×10 -4, P=0.036) were associated with an increase in CIMT, while an increase in PM 10 ( β=0.018, 95% CI: 0.002-0.033, P=0.028) was associated with an increase in PP in the study population. Besides, the waist-to-hip ratio had an effect-modification on the correlation of short-term exposure of PM 2.5 (interaction P=0.015), NO 2 (interaction P=0.008), and CO (interaction P=0.044) with CIMT, and the correlation between short-term exposure of PM 2.5 (interaction P=0.002), NO 2 (interaction P=0.010), CO (interaction P=0.029), PM 10 (interaction P<0.001) with PP. The significant association between CIMT, PP, and air pollution concentrations was more visible in people with lower waist-to-hip ratios. Conclusions:Short-term ambient air pollution exposure was associated with arterial stiffness indicators, and there was an effect modification of waist-to-hip ratio on these associations, and lower waist-to-hip ratios may enhance the association between air pollution exposure and indicators.

Background::Growth retardation is a common complication of chronic kidney disease in children, which can be partially relieved after renal transplantation. This study aimed to develop and validate a predictive model for growth patterns of children with end-stage renal disease (ESRD) after kidney transplantation using machine learning algorithms based on genomic and clinical variables.Methods::A retrospective cohort of 110 children who received kidney transplants between May 2013 and September 2021 at the First Affiliated Hospital of Zhengzhou University were recruited for whole-exome sequencing (WES), and another 39 children who underwent transplant from October 2021 to March 2022 were enrolled for external validation. Based on previous studies, we comprehensively collected 729 height-related single-nucleotide polymorphisms (SNPs) in exon regions. Seven machine learning algorithms and 10-fold cross-validation analysis were employed for model construction.Results::The 110 children were divided into two groups according to change in height-for-age Z-score. After univariate analysis, age and 19 SNPs were incorporated into the model and validated. The random forest model showed the best prediction efficacy with an accuracy of 0.8125 and an area under curve (AUC) of 0.924, and also performed well in the external validation cohort (accuracy, 0.7949; AUC, 0.796). Conclusions::A model with good performance for predicting post-transplant growth patterns in children based on SNPs and clinical variables was constructed and validated using machine learning algorithms. The model is expected to guide clinicians in the management of children after renal transplantation, including the use of growth hormone, glucocorticoid withdrawal, and nutritional supplementation, to alleviate growth retardation in children with ESRD.