The spine is the most common site of skeletal metastasis in lung cancer, which frequently leads to severe complications such as pathological fracture and neurological compromise and is associated with poor prognosis. The development and progression of spinal metastasis from lung cancer are linked to the unique local microenvironment and tumor microenvironment (TME) of the vertebral column. During metastatic evolution, the dense vascular network of the spine and a plethora of signaling molecules, together with the complex cellular constituents and their intricate interactions within the TME, all cooperate to facilitate the tumor invasion and colonization of the vertebral compartment. Mechanistic studies delineating the role of the TME in spinal metastasis from lung cancer have markedly expanded, fostering the emergence of innovative therapeutic strategies—including nanomedicines, sono-photodynamic therapy, gene therapy, and combination regimens. These strategies demonstrate remarkably potential for clinical translation and offer new directions for the precision management of spinal metastasis from lung cancer.

Kui was first recorded in The Rites of Zhou and is the earliest domesticated wild vegetable in China. In the Qi Min Yao Shu, Kui was called “the master of all vegetables” and has a long history of application in China. As a medicine, Kuizi was first recorded in Shen Nong’s Herbal Classic, which has a history of more than 2 000 years of medicinal use and a long history of clinical application. By researching the ancient and modern herbal literature, the first herbs texts of Kui were examined, various recorded texts, confused products and the history of the original medicinal use were clarified. It was concluded that the ancient herbal texts recorded the base plant of Kui as Malva verticillata L. belonging to family Malvaceae, which provided scientific basis for the development and utilization of Kui.

Objective To evaluate the practice effect of medical record writing training based on standardized patients and explore its application in prosthodontics practice.Methods Seventy-one undergraduate interns were randomly divided into two groups.At the first week of clinical practice,the test group(n=35)adopted the SP-based medical record writing training,and after the training,the students'evaluation of the teaching effect was investigated by questionnaire.And the control group(n=36)received traditional lectured medical record writing training.One week later,the same medical record writing exam was performed in the two groups.The scores of medical record writing of different teaching model were compared,and the evaluation of the teaching effect in the test group was carried out.Results The exam score of medical record writing of the test group(88.80±4.60)was significantly higher than that of the control group(84.92±5.51),and the difference was statistically significant(P=0.002).88.57％of the students in the test group were satisfied with the SP-based medical record writing training.The satisfaction score was 8.94.Conclusion Medical record writing training is a long-term clinical practice.SP-based medical record writing training is helpful to improve the medical record writing quality of medical students.

Objective To evaluate the practice effect of medical record writing training based on standardized patients and explore its application in prosthodontics practice.Methods Seventy-one undergraduate interns were randomly divided into two groups.At the first week of clinical practice,the test group(n=35)adopted the SP-based medical record writing training,and after the training,the students'evaluation of the teaching effect was investigated by questionnaire.And the control group(n=36)received traditional lectured medical record writing training.One week later,the same medical record writing exam was performed in the two groups.The scores of medical record writing of different teaching model were compared,and the evaluation of the teaching effect in the test group was carried out.Results The exam score of medical record writing of the test group(88.80±4.60)was significantly higher than that of the control group(84.92±5.51),and the difference was statistically significant(P=0.002).88.57％of the students in the test group were satisfied with the SP-based medical record writing training.The satisfaction score was 8.94.Conclusion Medical record writing training is a long-term clinical practice.SP-based medical record writing training is helpful to improve the medical record writing quality of medical students.

Objective To explore the effects of behavior change intervention based on the multi-ple-theory model on patients with dyslipidemic ischemic stroke.Methods A total of 93 patients with dyslipidemic ischemic stroke who were hospitalized in the vascular neurology ward of Beijing Tiantan Hospital,Capital Medical University from January to August 2024 were selected as the study subjects using the convenience sampling method.They were randomly divided into control group(n=49)and intervention group(n=44)using the envelope-drawing method.Patients in the control group re-ceived routine stroke health education,while those in the intervention group underwent a 3-month be-havior change program guided by the multiple-theory model.The levels of healthy behaviors,body mass index(BMI),total cholesterol(TC),triglycerides(TG),high-density lipoprotein(HDL-C),and low-density lipoprotein(LDL-C)were compared between the two groups.Results There were no statistically significant differences in general information and disease-related data between the two groups(P＞0.05).At 1-,3-,and 6-month after the intervention,the level of healthy behaviors in the intervention group was higher than that in the control group,with statistically significant differ-ences(P＜0.05).There was a statistically significant difference in BMI between the two groups at 6 months after the intervention(P＜0.05).The TC levels in the intervention group at 3 and 6 months after the intervention were lower than those in the control group,with statistically significant differences(P＜0.05).The HDL-C level in the intervention group at 6 months after the intervention was high-er than that in the control group,with a statistically significant difference(P＜0.05).The LDL-C levels in the intervention group at 1-,3-,and 6-month after the intervention were lower than those in the control group,with statistically significant differences(P＜0.05).There were no statistically significant differences in TG levels between the intervention group and the control group at different time points after the intervention(P＞0.05).Conclusion The behavior change intervention pro-gram based on the multiple-theory model can effectively improve and maintain healthy behaviors and improve blood lipid levels in patients with dyslipidemic ischemic stroke.

BACKGROUND: Neoadjuvant chemoradiotherapy followed by radical surgery has been a common practice for patients with locally advanced rectal cancer, but the response rate varies among patients. This study aimed to develop a ResNet-Vision Transformer based magnetic resonance imaging (MRI)-endoscopy fusion model to precisely predict treatment response and provide personalized treatment. METHODS: In this multicenter study, 366 eligible patients who had undergone neoadjuvant chemoradiotherapy followed by radical surgery at eight Chinese tertiary hospitals between January 2017 and June 2024 were recruited, with 2928 pretreatment colonic endoscopic images and 366 pelvic MRI images. An MRI-endoscopy fusion model was constructed based on the ResNet backbone and Transformer network using pretreatment MRI and endoscopic images. Treatment response was defined as good response or non-good response based on the tumor regression grade. The Delong test and the Hanley-McNeil test were utilized to compare prediction performance among different models and different subgroups, respectively. The predictive performance of the MRI-endoscopy fusion model was comprehensively validated in the test sets and was further compared to that of the single-modal MRI model and single-modal endoscopy model. RESULTS: The MRI-endoscopy fusion model demonstrated favorable prediction performance. In the internal validation set, the area under the curve (AUC) and accuracy were 0.852 (95% confidence interval [CI]: 0.744-0.940) and 0.737 (95% CI: 0.712-0.844), respectively. Moreover, the AUC and accuracy reached 0.769 (95% CI: 0.678-0.861) and 0.729 (95% CI: 0.628-0.821), respectively, in the external test set. In addition, the MRI-endoscopy fusion model outperformed the single-modal MRI model (AUC: 0.692 [95% CI: 0.609-0.783], accuracy: 0.659 [95% CI: 0.565-0.775]) and the single-modal endoscopy model (AUC: 0.720 [95% CI: 0.617-0.823], accuracy: 0.713 [95% CI: 0.612-0.809]) in the external test set. CONCLUSION The MRI-endoscopy fusion model based on ResNet-Vision Transformer achieved favorable performance in predicting treatment response to neoadjuvant chemoradiotherapy and holds tremendous potential for enabling personalized treatment regimens for locally advanced rectal cancer patients.
Humans ; Rectal Neoplasms/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Middle Aged ; Neoadjuvant Therapy/methods* ; Aged ; Adult ; Chemoradiotherapy/methods* ; Endoscopy/methods* ; Treatment Outcome

ObjectiveTo provide technical support for the molecular surveillance of pathogenic bacteria strains carrying mobile colistin resistance-1 （mcr⁃1） gene isolate from inlet of wastewater treatment plants （WWTP）. MethodsThe Enterobacteriaceae strains carrying mcr⁃1 resistance gene isolate from inlet of WWTP during April 1 to June 30， 2023 in Shanghai were cultured on blood-rich and SS culture medium and were identified using a mass spectrometry analyzer. The mcr⁃1 gene and copy number were detected by real-time fluorescence quantitative PCR. Drug susceptibility test was performed by microbroth dilution method. The copy numbers of Escherichia coli carrying mcr⁃1 gene isolated from wastewater and human fecel were statistically analyzed by SPSS 25.0. ResultsA total of 14 strains carrying the mcr⁃1 gene were isolated from 49 WWTP samples， and the positive isolation rate was 28.6%， including 12 non-diarrheal E. coli strains and 2 Klebsiella pneumoniae strains. The drug susceptibility results showed that all 14 strains were multi-drug resistant bacteria. They were all sensitive to imipenem and tigecycline， but were ampicillin- and cefazolin-resistant. There was no significant difference in the copy number between human-sourced diarrheal E. coli and wastewater-sourced non-diarrheal E. coli （t=0.647， P>0.05）. ConclusionThe isolation and identification of strains carrying the mcr⁃1 gene from inlet of WWTP samples were firstly established in Shanghai. The multi-drug resistance among the isolated strains is severe. To effectively prevent and control the spread of colistin-resistant bacteria， more attention should be paid to the surveillance of mcr⁃1 gene.

ObjectiveTo provide more basic information of comparative medicine for the study of biological changes and pathogenesis of COVID-19 by systematical sorting and analyzing the transcriptome data.MethodsFollowing a retrieval strategy, using COVID-19 and SARS-CoV-2 as key words, transcriptome datasets related to COVID-19 from January 2020 to May 2023 were collected from GEO, ArrayExpress and GEN Transcriptome databases. The composition, distribution, and research application of COVID-19 transcriptome data resources were analyzed. Data distribution was visually displayed and correlation analysis was performed. The research applications and limitations of existing COVID-19 transcriptome data were analyzed from the perspectives of clinical medicine and comparative medicine, focusing on clinical-related molecular mechanisms, biomarkers and related immune responses, treatment intervention strategies, etc. The research value and application prospects were discussed.Results A total of 975 sets of COVID-19 transcriptome data were included. Among three databases, datasets from humans accounted for the highest proportion, namely 71.9%, 77.9%, and 90%, respectively. Species other than humans, such as mice, were the main sources of data, with the respiratory and nervous systems having the highest distribution of data. Twenty-seven datasets were associated with clinical significance. Analysis revealed that respiratory tract injury and other related molecular mechanisms were obtained through transcriptome data mining. Biomarkers such as cfDNA could be used as therapeutic targets. The severity of COVID-19 infection was associated with cell changes and disorders represented by M1 macrophages. Comparative medical analysis showed that mice, hamsters, and other animals were susceptible to SARS-CoV-2. Rhesus monkeys and cynomolgus monkeys exhibited infection characteristics highly similar to human. Apart from respiratory symptoms, hamsters also exhibited digestive system symptoms. SARS-CoV-2 can replicate in the respiratory organs of various susceptible animals, the intestines of ferrets and the ears of minks, resulting in interstitial pneumonia, diffuse lung injury and other pathological changes of varying degrees. Based on the differences in immune responses, hamsters can be used for neutralizing antibody reaction research.Conclusion Currently there is a wealth of COVID-19 transcriptome data, but there is a lack of comparative transcriptome research. Transcriptomics can be combined with comparative medicine to further explore the differences in comparative medicine of COVID-19.

Drugs and physical stimulation,including light,electricity,and magnetic fields,can be used to influence how neurons operate,among which chemogenetic and optogenetic technologies are most widely used.In recent years,magnetogenetic technology has also been developed that can acti-vate neurons in magnetic fields through magnetic sensitive actuators,leading to non-invasive and instanta-neous activation of specific brain regions.This article reviews the evolution of and problems with chemoge-netic and optogenetic techniques commonly used in brain science research.It also outlines the latest progress in magnetogenetic technologies,which are not full-fledged yet,as well as the role of transcra-nial electrical stimulation,transcranial magnetic stimulation,deep brain stimulation and transcranial ultra-sound stimulation technology in the functional regulation of brain diseases.Constant adjustment and improvement can make it possible for these technologies to be used more widely for the study of brain sciences and the treatment of brain diseases.

Objective This study analyzes the omics data resources in human-infecting coronavirus animal models collected from various public databases,focusing on data distribution,dataset quantity,data types,species,strains,and research content.It aims to enhance our understanding of biological characteristics and pathogenic mechanisms of coronaviruses,thereby providing a solid foundation for devising effective therapeutic strategies and preventive measures.Methods Query strategies,including specific virus names,time ranges,and inclusion and exclusion criteria,were defined to retrieve data from major public omics databases such as GEO and ArrayExpress.Secondary filtering was performed based on different field types to obtain a more accurate data list.An omics data text database was established for bibliometric analysis.Co-occurrence networks were constructed for the analysis of the correlation strengths between different research themes,technical methods,and involved species.The cell types,organs,and biological pathways involved in studies were examined to further elucidate the pathogenic interplay between pathogens and hosts.Results About twenty public databases containing coronavirus-related omics data were identified,with a primary focus on novel coronavirus infection.Commonly used species include humans,mice,hamsters,and monkeys,while the commonly used virus strains are Wuhan-Hu-1 and USA-WA1/2020.Lung tissues are primarily used in animal models such as mice,macaques,and ferrets,while airway epithelial cells and Calu-3 cells are predominantly employed in human-related studies.Expression profiling data indicate that gene pathways involved in inflammation,cytokine response,complement pathway,cell damage,proliferation,and differentiation are significantly upregulated after infection.Proteomics studies reveal significant changes in phosphoproteome,ubiquitinome,and total proteome of patient samples at different infection stages.Specific protein categories,including viral receptors and proteases,transcription factors,cytokines,proteins associated with coagulation system,angiogenesis-related proteins,and fibrosis markers,show alterations after coronavirus infection.In addition,metabolomics data suggest that phosphocholine,phosphoethanolamine,arachidonic acid,and oleic acid could serve as potential metabolic markers.Epigenomics research indicates m6A methylation plays a role in SARS-CoV-2 replication,infection,and transmission,affecting host cell-virus interactions.Among these,N,S,and non-structural proteins 2 and 3 exhibit the most significant ubiquitination.Trends in microbiomics research suggest that microbial communities in the gut and wastewater are emerging as new research focuses.Conclusion The data types of coronavirus omics are diverse,with a wide variety of models and cell types used.The selection of species and technical methods for modelling varies based on the characteristics of different viruses.Multi-omics data from animal models of coronavirus infection can reveal key interactions between hosts and pathogens,identifying biomarkers and potential therapeutic targets,and provide valuable information for a deeper understanding of biological characteristics and infection mechanisms of coronaviruses.