The theory of constitution in traditional Chinese medicine （TCM） has emerged as a new discipline in recent years. Constitution plays a vital role in the onset，progression，transformation，and prognosis of diseases. At present，some clinical scholars have adopted a novel diagnostic and treatment model of "constitution differentiation-disease identification-syndrome differentiation"，in which constitution is regarded as a core element throughout the diagnostic and therapeutic process. Constitution is closely associated with etiology，onset，pathogenesis，syndrome differentiation，and treatment. Against this background，the construction of animal models based on constitution holds far-reaching significance for advancing clinical research. This paper focuses on the construction and evaluation of rodent models with Qi-deficiency constitution，aiming to explore how to further induce Qi-deficiency syndromes and related disease states on the basis of Qi-deficiency constitution models，thereby developing an integrated animal model that embodies the trinity of "constitution-disease-syndrome". The establishment of this model not only provides a solid experimental foundation for the development of new therapies and drugs in TCM targeting specific constitutions，diseases，and syndromes，but also greatly promotes the modernization and scientific advancement of TCM theory. By comprehensively applying multidisciplinary technologies and methods，the study evaluates the model's validity，reliability，and practicality，with the aim of opening new avenues for future research in TCM and promoting the development of the field.

The theory of constitution in traditional Chinese medicine （TCM） has emerged as a new discipline in recent years. Constitution plays a vital role in the onset，progression，transformation，and prognosis of diseases. At present，some clinical scholars have adopted a novel diagnostic and treatment model of "constitution differentiation-disease identification-syndrome differentiation"，in which constitution is regarded as a core element throughout the diagnostic and therapeutic process. Constitution is closely associated with etiology，onset，pathogenesis，syndrome differentiation，and treatment. Against this background，the construction of animal models based on constitution holds far-reaching significance for advancing clinical research. This paper focuses on the construction and evaluation of rodent models with Qi-deficiency constitution，aiming to explore how to further induce Qi-deficiency syndromes and related disease states on the basis of Qi-deficiency constitution models，thereby developing an integrated animal model that embodies the trinity of "constitution-disease-syndrome". The establishment of this model not only provides a solid experimental foundation for the development of new therapies and drugs in TCM targeting specific constitutions，diseases，and syndromes，but also greatly promotes the modernization and scientific advancement of TCM theory. By comprehensively applying multidisciplinary technologies and methods，the study evaluates the model's validity，reliability，and practicality，with the aim of opening new avenues for future research in TCM and promoting the development of the field.

Objective: To develop a convenient, direct, and highly sensitive method for screening trace chemical additives in complex Chinese patent medicines, thereby addressing core technological bottlenecks in pharmaceutical analysis and quality control. Methods: A brush ionization probe device was independently designed and constructed, and an efficient detection method was established through systematic optimization of key parameters. Twenty-three Chinese patent medicine samples, representing 6 dosage forms (capsules, tablets, pills, granules, powders, and liquid preparations), were analyzed using 10 common chemical additives as target analytes. Results: All samples were successfully analyzed without complex pretreatment, and 5 chemical additives were detected in 7 Chinese patent medicines. The brush ionization probe device exhibited cost-effectiveness (~0.2 USD per probe), operational simplicity, rapid analysis (~10s per sample), high efficiency, and minimal reagent consumption (~10 μL per sample). Conclusion: This advancement is expected to provide an innovative scientific tool for improving the generality and convenience of on-site quality control, while promoting technological progress in disciplines such as pharmacology and traditional Chinese medicine.

Objective This study conducted molecular biological identification of the viruses carried by Culex pipiens pallens specimens collected in Shunyi District, Beijing in 2023, and observed the changes in the infection rate of the viruses carried by Cx. pipiens pallens at different collection times. Methods Cx. pipiens pallens were collected using carbon dioxide mosquito traps. The mosquito samples were ground in batches and analyzed by molecular biology technologies. The virus infection rate at different collection times was analyzed statistically. Results 17 strains of Culex pipiens pallens densovirus(CppDNV)were identified from Cx. pipiens pallens samples collected in Shunyi District, Beijing, in 2023. The nucleotide sequence analysis of the virus genome coding region showed that CppDNV was a single-stranded DNA virus with a total length of 3 335 nt, encoding 2 non-structural proteins(NS1, NS2)and 1 capsid protein(VP). The nucleotide(amino acid)sequence lengths of the three proteins were 2 376 nt(791 aa),1 092 nt(363 aa)and 1 071 nt(356 aa), respectively. Phylogenetic analysis showed that CppDNV was located in genus Brevihamaparvovirus. Statistical analysis showed no significant difference in infection rates across collection times(χ2=4.429, P=0.194). Conclusions CppDNV was identified in Cx. pipiens pallens in Beijing, and it was stably maintained in this natural population.

ObjectiveTo explore the current situation of forensic ethics practice and education by designing a questionnaire on forensic ethics， with a view to exploring the path of forensic ethics education construction. MethodsA total of 667 valid questionnaires were collected using the online survey method， basically covering various regions across the country and all sub-specialties of forensic medicine. Descriptive analysis was used to analyze the relevant data. ResultsMost practitioners had relevant ethical reflections in the process of forensic practice. 69.12% of the respondents indicated that they had studied the relevant rules， but approximately half stated that there were no corresponding ethical norms or standard operating manuals. The specific behaviors violating ethics in different units were diverse. 23.04% of the respondents reported that they had encountered unethical behaviors， but only 4.9% of them reported such violations. In terms of forensic ethics education， 87.75% of the respondents believed that there were issues with the current model of forensic ethics education. Meanwhile， the respondents showed a high degree of recognition for receiving forensic ethics education， with 84.15% of respondents expressing willingness to participate in relevant courses. More than half of respondents were willing to participate in forensic ethics education during undergraduate studies， new employee training， and regular post-employment training. ConclusionCurrently， there is a problem of ethical neglect in forensic work in China. Combining ethics courses with professional courses at the practitioner training stage and providing regular training at the practice stage are effective measures to popularize forensic ethics knowledge， enhance ethical awareness， and improve the quality of practice.

Under the influence of long-term space flights and the confined space environment,it is very easy to induce space depression syndrome,mainly manifested as decreased emotional stability,sleep disorders,mental fatigue,etc.,which seriously affect the living conditions and working abilities of astronauts.The current treatment methods mainly focus on psychological support and drug intervention.Acupuncture has a good effect in treating depression.Therefore,starting from the TCM pathogenesis and modern medical pathogenesis of aerospace depression syndrome,we conducted literature retrieval from databases such as the Chinese Medical Classic,China National Knowledge Infrastructure(CNKI),Wanfang,VIP,PubMed,and Web of science.For the included literature,we adopted the stratified evidence scoring method and combined the TCM mechanism and modern medical mechanism of the effect of acupuncture.A prescription for acupuncture points was constructed to provide a basis for selecting acupuncture points for the prevention of aerospace depression syndrome through acupuncture.

ObjectiveTo investigate the triglyceride-glucose (TyG) index and the level of serum homocysteine (Hcy) in association with the incidence of stroke in type 2 diabetes mellitus (T2DM) patients. MethodsBased on the chronic disease risk factor surveillance cohort in Pudong New Area, Shanghai, excluding those with stroke in baseline survey, T2DM patients who joined the cohort from January 2016 to October 2020 were selected as the research subjects. During the follow-up period, a total of 318 new-onset ischemic stroke patients were selected as the case group, and a total of 318 individuals matched by gender without stroke were selected as the control group. The Cox proportional hazards regression model was used to adjust for confounding factors and explore the serum TyG index and the Hcy biochemical indicator in association with the risk of stroke. ResultsThe Cox proportional hazards regression results showed that after adjusting for confounding factors, the risk of stroke in T2DM patients with 10 μmol·L⁻¹-¹ and Hcy>15 μmol·L⁻¹ was 1.532 times (95%CI: 1.017‒2.309 times, P=0.041) and 1.738 times (95%CI: 1.119‒2.699 times, P=0.014) higher respectively, compared to T2DM patients with Hcy≤10 μmol·L⁻¹. T2DM patients with TyG>9.074 had 1.396 times higher risk of stroke (95%CI: 1.091‒1.787, P=0.008) compared to those with TyG≤9.074. The study found that urea and α1-antitrypsin (α1-AT) were independent risk factors for the incidence of stroke in T2DM patients. For every unit increase in urea andα1-AT, the risk of stroke in T2DM patients increased by 233.6% (HR=3.336, 95%CI: 1.588‒7.009, P=0.001) and 11.3% (HR=1.113, 95%CI: 1.028‒1.205, P=0.008), respectively. Cumulative risk curves showed that Hcy>10 μmol·L⁻¹ and TyG>9.074 accelerated the time to stroke occurrence in T2DM patients. ConclusionElevated levels of Hcy>10 μmol·L⁻¹ and a higher TyG index are risk factors for stroke in T2DM patients. Effective interventions for Hcy and TyG should be conducted for diabetic patients to reduce the incidence of stroke.

Accurate characterization of the chemical composition of complex traditional Chinese medicine (TCM) is an essential foundation for the modern scientific interpretation of TCM principles. Mass spectrometry is the most dominant technique in current research on the material basis of TCM, offering the highest sensitivity and the richest information provision. Establishing mass spectrometry databases represents the most effective approach to facilitating the structural analysis of TCM chemical components. This paper systematically searches and reviews literature published from January 2005 to January 2025 through online databases such as China National Knowledge Infrastructure, PubMed, and Web of Science, using “mass spectrometry database” and “traditional Chinese medicine” as keywords. It reviews the current status of seven TCM chemical component mass spectrometry databases and seven natural product mass spectrometry databases. The key advancements of these mass spectrometry databases for natural products are summarized, detailing their characteristics, search methodologies, included information, and data sources. Additionally, challenges related to data quality, standardization, timely updates, database interaction, retrieval functionality, and data sharing and security are discussed in depth. Furthermore, the paper explores prospective development directions for TCM mass spectrometry databases, emphasizing the importance of open data sharing, technological innovation, and data security. Through this analysis, the paper aims to offer theoretical guidance and practical recommendations for the precise identification of TCM components, as well as for the construction and application of these databases.

Cervical spinal cord injury without fracture-dislocation (CSCIWFD) is referred to as a special type of cervical spinal cord injury characterized by traumatic spinal cord dysfunction and no significant bony structural abnormalities on imagines. Duo to the high risk of missed diagnosis during the initial consultation, CSCIWFD may lead to progressive neurological deterioration or even complete paralysis, severely impacting patients′ prognosis. Currently, there are no established consensuses over the diagnosis and treatment of CSCIWFD, such as the lack of evidence-based standards for indications of non-surgical treatment and risk of secondary neurological injury, as well as debates over the optimal timing for surgical intervention and indications for different surgical approaches. To address these issues, the Spine Trauma Group of the Orthopedic Branch of the Chinese Medical Doctor Association organized experts in the relevant fields to formulate Diagnosis and treatment guideline for acute cervical spinal cord injury without fracture- dislocation in adults ( version 2025) . Based on evidence-based medicine and the principles of scientific rigor and clinical applicability, the guidelines proposed 11 recommendations covering terminology, diagnosis, evaluation treatment, and rehabilitation, etc., aiming to standardize the management of CSCIWFD.

In recent years, with the rapid development of artificial intelligence technology, the application of deep learning in the field of pathology has been continuously expanding. Particularly, the rise of multimodal data fusion methods has opened up new technical paths for the precise diagnosis, prognosis assessment, and individualized treatment of tumors. By integrating multi-level and multi-source data such as clinical information, pathological omics, molecular omics, and imaging omics, deep learning models can identify potential associated features and key biological mechanisms that are difficult to reveal by a single modality, thereby significantly improving the accuracy of disease classification and the scientific nature of risk stratification. This article systematically reviews the research progress of multimodal data fusion methods based on deep learning in the field of pathology in recent years, focuses on sorting out different types of fusion strategies, evaluates their advantages and challenges in practical clinical applications, and looks forward to future development trends.