Traditional Chinese medicine （TCM） diagnostics is a discipline that studies the basic theories and fundamental skills of diagnostic methods， disease diagnosis， and differentiation in accordance with the theories of TCM. The artificial intelligence （AI） technology has gained remarkable achievements in the intelligentization of the four diagnostic methods in TCM and the standardization of differentiation and diagnosis. However， it still faces many challenges. The standardization of clinical data collection is difficult， and the data quality is uneven， which affects the usability of the data. The integration of the four diagnostic information is insufficient. Most instruments can only collect data from a single diagnostic method， lacking overall integrity. The scientific nature of the diagnostic model needs to be improved. The existing models lack dynamics and the reasoning logic of TCM differentiation. The accuracy of intelligent methods needs to be improved， and the existing evaluation indicators cannot fully reflect the practical application effect of the model. Furthermore， the relevant laws and regulations are still not perfect， and data security and patient privacy lack guarantees. The cultivation of compound talents is insufficient， and there is a lack of interdisciplinary talents who are proficient in both TCM and AI. On this basis， this paper expounded on the current development status， difficulties， and bottlenecks of AI in TCM diagnosis and then explored the development trend of AI in the field of TCM diagnosis. It proposed solutions such as optimizing the data collection process， constructing multimodal diagnostic models， facilitating multi-disciplinary exchanges and cooperation， improving laws and regulations， and cultivating compound talents. It is hoped that modern， standardized， normalized， and intelligent TCM diagnosis can be further promoted， thereby providing new impetus and methods for the inheritance and innovation of TCM.

Loss-of-function variants in CSDE1 have been strongly linked to neuropsychiatric disorders, yet the precise role of CSDE1 in neurogenesis remains elusive. In this study, we demonstrate that knockout of Csde1 during cortical development in mice results in impaired neural progenitor proliferation, leading to abnormal cortical lamination and embryonic lethality. Transcriptomic analysis revealed that Csde1 upregulates the transcription of genes involved in the cell cycle network. Applying a dual thymidine-labelling approach, we further revealed prolonged cell cycle durations of neuronal progenitors in Csde1-knockout mice, with a notable extension of the G1 phase. Intersection with CLIP-seq data demonstrated that Csde1 binds to the 3' untranslated region (UTR) of mRNA transcripts encoding cell cycle genes. Particularly, we uncovered that Csde1 directly binds to the 3' UTR of mRNA transcripts encoding Cdk6, a pivotal gene in regulating the transition from the G1 to S phases of the cell cycle, thereby maintaining its stability. Collectively, this study elucidates Csde1 as a novel regulator of Cdk6, sheds new light on its critical roles in orchestrating brain development, and underscores how mutations in Csde1 may contribute to the pathogenesis of neuropsychiatric disorders.
Animals ; Neurogenesis/genetics* ; Cell Cycle/genetics* ; Mice, Knockout ; Mice ; Neural Stem Cells/metabolism* ; DNA-Binding Proteins/metabolism* ; Cyclin-Dependent Kinase 6/genetics* ; Cell Proliferation ; 3' Untranslated Regions ; Cerebral Cortex/embryology* ; RNA-Binding Proteins ; Mice, Inbred C57BL

N6-methyladenosine (m6A) modification, as a widespread and high-profile type of epigenetic modification, can dynamically and reversibly regulate the whole process of RNA metabolism. This modification governs RNA stability, splicing, and translation via m6A regulators, which are categorized as Writers, Erasers, and Readers. m6A modification also plays a critical role in the development of tumors. Disruptions in the homeostasis of m6A modification levels lead to dysregulation of m6A regulators. Consequently, these dysregulated regulators modulate the proliferation, migration, and invasion of tumor cells and interfere with the normal functions of suppressor genes and oncogenes. This article aims to comprehensively elucidate the specific regulatory impacts of m6A modification on tumor-related gene expression. It focuses on the regulatory mechanisms of m6A modification on mRNA stability. Additionally, it explores the influence of m6A on the molecular translation of key signaling pathways. Moreover, it investigates the indirect regulatory effects mediated by non-coding RNAs (ncRNAs), etc. The intention is to offer a novel analysis of the pathogenesis of cancer at a new level, and also provide a theoretical basis for finding new effective treatment methods.

Objective:To establish a model for the combined detection of serum copeptin and inflammatory markers in acute stroke (AS), and to explore the value of copeptin and inflammatory marker detection in the clinical diagnosis and prognosis assessment of AS.Methods:A total of 75 patients were diagnosed with acute ischemic stroke (AIS) [46 males, age (64.1±11.7) years] and 45 patients with acute intracerebral hemorrhage (ICH) [28 males, age (61.0±13.9) years] who were admitted to the First Affiliated Hospital of Hunan University of Chinese Medicine through the emergency department from January 1 to July 31, 2024, were included as the observation group. Meanwhile, 60 healthy individuals [39 males, age (64.4±8.2) years] were selected as the control group (HC). The differences in serum copeptin levels and inflammatory markers among different groups were compared. ROC curves were drawn to analyze the value of copeptin and inflammatory markers in the clinical diagnosis and prognosis assessment of AIS. The Kaplan-Meier method was used to draw survival curves to analyze the in-hospital survival rates of patients in different groups. Cox regression analysis was conducted to identify the risk factors affecting the prognosis of AIS patients.Results:The level of copeptin was significantly elevated in AS, with the results showing ICH>AIS>HC ( H=100.11, P<0.001). Copeptin demonstrated the highest efficacy in the early diagnosis of AIS and ICH (AUC=0.893, sensitivity 89.3%, specificity 75.0%; AUC=0.986, sensitivity 95.6%, specificity 93.3%) and the assessment of prognosis (AUC=0.997, sensitivity 100%, specificity 96.8%; AUC=0.907, sensitivity 86.7%, specificity 86.7%), outperforming other single indicators. The combined detection of copeptin with the neutrophil-to-lymphocyte ratio (NLR) and the systemic immune-inflammation index (SIIRI) was the best combination for the early diagnosis of AIS and ICH (AUC=0.937, sensitivity 77.3%, specificity 98.3%; AUC=0.989, sensitivity 95.6%, specificity 95.0%) and for the assessment of prognosis (AUC=0.996, sensitivity 100%, specificity 96.8%; AUC=0.944, sensitivity 86.7%, specificity 90.0%). Kaplan-Meier survival curves showed that AIS patients in the low-value group of copeptin and NLR had a higher survival rate during hospitalization than those in the high-value group ( HR 54.46, 7.608, P<0.01, respectively), and ICH patients in the low-value group of copeptin, SIIRI, SIRI, and SII had a higher survival rate during hospitalization than those in the high-value group ( HR 12.67, 7.923, 3.567, 5.925, P<0.05); Cox regression showed that copeptin, NLR, NIHSS, and mRS were independent risk factors affecting the prognosis of patients with AIS ( HR 1.421, 1.368, 1.158, and 1.188, respectively, P<0.05), copeptin and SIIRI were independent risk factors affecting the prognosis of ICH ( HR 1.308, 1.113, P<0.05), and GCS was a protective factor affecting ICH prognosis ( HR=0.741, P<0.05). Conclusion:Copeptin and inflammatory indicators can reflect the severity of different subtypes of stroke. The single or combined detection shows good value in the clinical application of AS. The combination of copeptin-NLR and copeptin-SIIRI is respectively the best comprehensive biomarker combination for the early diagnosis and prognosis assessment of AIS and ICH.

OBJECTIVE To evaluate the effect of bundled property management under multidisciplinary coopera-tion mode on prevention and control of multidrug-resistant organisms(MDROs)in intensive care units(ICUs)and explore the evidence-based methods for prevention and control of MDROs.METHODS A control study before and after the same time period was designed,the post-intervention period was 2024 when the bundled measures were fully implemented,and the pre-intervention period was 2023.Totally 8 ICUs of general and special depart-ments of a three-A hospital in Hubei Province were recruited as research subjects,the multidisciplinary coopera-tion team was established,the bundled management measures were introduced to optimize the quality of property cleaning work.The quality of service of the property cleaning work was evaluated through surveillance of hospital-associated infections and environmental hygiene surveillance before and after the bundled measures were imple-mented.RESULTS The isolation rate of MDROs from object surfaces of ICU environment declined from 0.34％to 0.10％after the bundled management measures under multidisciplinary cooperation model were implemented(P＜0.05).The incidence of MDROs hospital-associated infections was reduced from 0.07％to 0.03％(P＜0.05);the isolation rate of MDROs from patients decreased from 14.68％to 12.69％(P＜0.05);the performance as-sessment score of the cleaning staff was raised from(85.56±7.21)points to(91.06±3.07)points,however,there was no significant difference.The hand hygiene compliance rate of the cleaning staff was raised from 42.86％to 68.52％(P＜0.05).The positive rate of random ATP fluorescent test for environmental object surfaces de-clined from 25.41％to 10.05％(P＜0.05).Other environmental hygiene indexes for the cleaning and disinfection effects were improved in varying degrees.CONCLUSION The bundled management measures under multidiscipli-nary cooperation mode boost the property service quality,enhance the cleaning staff's awareness of disinfection,prevention and control,reduce the isolation rate of MDROs in environment,and thus decrease the incidence of MDROs hospital-associated infections and prevent the transmission.

OBJECTIVE To explore the effect of failure mode and effect analysis(FMEA)on management of hospi-tal-associated infections(HAIs)in hemodialysis center.METHODS In Nov.2023,the risk priority number(RPN)integrated with action priority(AP)was adopted to identify,analyze and evaluate the risk factors in man-agement of HAIs in hemodialysis center of Tongji Hospital Affiliated to Tongji Medical College,Huazhong Uni-versity of Science and Technology by FMEA method.The high risk points that needed to be taken interventions were screened out,and the targeted measures were formulated to control the risks.At the end of the intervention period,a second round of risk assessment was carried out for improvement status of the high-risk points in Nov.2024,and the effect on the management of HAIs was evaluated.RESULTS The risk assessment was carried out for 48 risk points covering eight aspects,including organizational structure,self-inspection and supervision,staff management,environmental layout,cleaning and disinfection,surveillance,operation procedures and i-tem management.There were 9 risk points with the RPN values greater than 125,3 of which were with the AP value of"H".There were 8 risk points with the RPN value less than 125 and 6 risk points with the AP value drop-ping down to L after the targeted intervention measures were taken,indicating that the risk management has a-chieved favorable effect.CONCLUSIONS The RPN and AP integrated with FMEA can accurately identify the high-risk points in the quality management of the hemodialysis center.It is necessary to take targeted interven-tion measures so as to boost the effect on prevention and control of HAIs in the hemodialysis center and reduce the risk of HAIs in the hemodialysis patients.

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Objective:To investigate the prognostic value of 18F-FDG PET/CT-based habitat radiomics combined with stacking ensemble learning model in overall survival (OS) of patients with hepatocellular carcinoma (HCC). Methods:A total of 136 HCC patients (114 males, 22 females, age (55.3±10.4) years) who underwent 18F-FDG PET/CT before treatment between January 2018 and January 2023 were retrospectively analyzed. Eighty-five cases from Tianjin First Central Hospital and 51 cases from Tianjin Medical University Cancer Institute and Hospital were used as a training cohort and an external validation cohort, respectively. The tumor volume of interest (VOI) was delineated on PET and CT images, and a total of 4 habitats were segmented by using the Otsu algorithm, including PET high ∩ CT low, PET low ∩ CT low, PET high ∩ CT high, and PET low ∩ CT high. After the feature selection, a total of 36 stacking ensemble learning models were established, and the optimal model was selected based on the calculated concordance index (C-index). Moreover, a combined model was developed by integrating the optimal model with clinical information. The predictive efficacy of those models was assessed by time-dependent ROC curves. Results:The model based on PET high ∩ CT high habitat radiomics features with multilayer perceptron (MLP) classifier had the highest C-index (0.770) in the external validation cohort, and it was regarded as the optimal radiomics model. The combined model incorporating this model with clinical information achieved an improved C-index of 0.815 in the external validation cohort. The combined model outperformed the other models for OS prediction, with a time-dependent AUC of 0.919, 0.900, and 0.862 in predicting the 1-year, 2-year, and 3-year OS, respectively. Conclusions:18F-FDG PET/CT-based habitat analysis outperforms traditional radiomics in OS prediction for HCC patients. By integrating the optimal habitat model with the clinical model, the combined model is able to improve the predictive efficacy.

Objective: To investigate the awareness of knowledge about hepatitis C prevention and control among outpatients in Ningbo City, Zhejiang Province, and its influencing factors, so as to provide the evidence for strengthening health education on hepatitis C prevention and control. Methods: Based on sentinel surveillance of hepatitis C, the outpatients aged 15 to 65 years at seven hospitals in Yinzhou District, Cixi City and Xiangshan County of Ningbo City were selected using the convenient sampling method from April to June during 2020 and 2022. Demographic information, knowledge and behaviors related to hepatitis C prevention and control were collected through questionnaire surveys. The influencing factors for knowledge about hepatitis C prevention and control were analyzed using a multivariable logistic regression model. Results: A total of 2 792 participants were surveyed, including 1 157 males (41.44%) and 1 635 females (58.56%). The awareness rate of knowledge about hepatitis C prevention and control was 56.23%, and was lower in knowledge about hepatitis C vaccine and treatment. The awareness rates of knowledge about hepatitis C prevention and control among outpatients from 2020 to 2022 were 47.11%, 53.22% and 70.65%, respectively, showing an upward trend (P<0.05). Multivariable logistic regression analysis showed that participants aged 25 to <50 years (OR=1.358, 95%CI: 1.073-1.719), with an educational level of high school or junior college (OR=1.431, 95%CI: 1.134-1.806) or above junior college (OR=3.728, 95%CI: 2.958-4.699), with household monthly income per capita of 3 000 to <5 000 yuan (OR=1.828, 95%CI: 1.344-2.486) or ≥5 000 yuan (OR=1.858, 95%CI: 1.366-2.526), without a history of invasive treatments such as pedicure in public places (OR=1.287, 95%CI: 1.024-1.618), without a history of contact with family members' blood-contaminated items (OR=2.050, 95%CI: 1.552-2.707), and always using condoms during sexual contacts (OR=1.740, 95%CI: 1.273-2.378) had higher awareness of knowledge about hepatitis C prevention and control. Conclusions The awareness of knowledge about hepatitis C vaccine and treatment among outpatients in Ningbo City needs to be improved. Age, educational level, household monthly income per capita, history of invasive treatments such as pedicure in public places, history of contact with family members' blood-contaminated items and frequency of condom use during sexual contacts are associated with outpatients' awareness of knowledge about hepatitis C prevention and control.

This study aims to explore the synergistic effects of the main components in salvianolic acids for Injection(SAFI) on key pathological events in cerebral ischemia, elucidating the pharmacological characteristics of SAFI in neuroprotection. Two major pathological gene modules related to endothelial injury and neuroinflammation in cerebral ischemia were mined from single-cell data. According to the topological distance calculated in network medicine, potential synergistic component combinations of SAFI were screened out. The results showed that the combination of caffeic acid and salvianolic acid B scored the highest in addressing both endothelial injury and neuroinflammation, demonstrating potential synergistic effects. The cell experiments confirmed that the combination of these two components at a ratio of 1∶1 significantly protected brain microvascular endothelial cells(bEnd.3) from oxygen-glucose deprivation/reoxygenation(OGD/R)-induced reperfusion injury and effectively suppressed lipopolysaccharide(LPS)-induced neuroinflammatory responses in microglial cells(BV-2). This study provides a new method for uncovering synergistic effects among active components in traditional Chinese medicine(TCM) and offers novel insights into the multi-component, multi-target acting mechanisms of TCM.
Brain Ischemia/metabolism* ; Neuroprotective Agents/pharmacology* ; Animals ; Drugs, Chinese Herbal/administration & dosage* ; Benzofurans/pharmacology* ; Mice ; Drug Synergism ; Caffeic Acids/pharmacology* ; Polyphenols/pharmacology* ; Humans ; Alkenes/pharmacology* ; Endothelial Cells/drug effects* ; Depsides