OBJECTIVE To establish a whole-process quality management index system for traditional Chinese medicine （TCM） reserved in the department of medical institutions， providing a reference for standardized management. METHODS An initial indicator framework was determined by collecting and analyzing relevant laws， regulations， policy documents， group standards， and literature on TCM management. Two rounds of Delphi expert consultation involving 20 experts were conducted to refine and optimize the indicator system. The analytic hierarchy process was used to construct judgment matrices and convert the indicator weights into a percentage-based system； an assessment was conducted on 14 departments with reserved TCM among the affiliated units of the Quality Management and Control Center for Traditional Chinese Medicine in Hebei Province. RESULTS The response rate for both rounds of consultation was 100%， with an expert authority coefficient of 0.89. The final quality management system of TCM reserved in the department included four first-level indicators： management （composite weight： 0.366 3）， processing （composite weight： 0.119 7）， storage （composite weight： 0.291 7） and usage （composite weight： 0.222 3）， and twenty-four second-level indicators， such as establishing an organizational structure for hospital drug quality management and having dedicated regulations for backup drugs in clinical departments. Kendall’s coefficient of concordance confirmed consistency across all levels of indicators. Based on the application of the indicator system for evaluation， the average score for the standardized management of reserved TCM in the department of medical institutions increased from 67.01 points to 85.15 points over three months. CONCLUSIONS The constructed indicator system meets the standardized management requirements for reserved TCM， enabling closed-loop management across the entire process of management， processing， storage and usage. It provides a reference for medical institutions to enhance the precision and standardization of reserved TCM management.

Background As common public facilities essential to daily life, hair and beauty salons frequently contain various airborne toxic and hazardous pollutants potentially leading to adverse health effects for salon practitioners. Objective To characterize the indoor air pollution profiles of common contaminants in hair and beauty salons in Shanghai and to evaluate the associated health risks for practitioners, in order to provide a scientific basis for strengthening the public health management in Shanghai and protecting the health of practitioners. Methods The air quality monitoring data of hair and beauty salons in Shanghai from 2016 to 2024 were obtained from the “Health Hazard Factors Monitoring Program for Public Places” of the National Institute of Environmental Health, Chinese Center for Disease Control and Prevention. Monitoring indicators included particulate matter ≤10 μm in aerodynamic diameter (PM₁₀), particulate matter ≤2.5 μm in aerodynamic diameter (PM_2.5), formaldehyde, ammonia, benzene, toluene, and xylene. Indicator compliance rates were calculated across various years in accordance with GB 9666-1996 Hygienic standard for barber shop and beauty shop and GB 37488-2019 Hygiene indicators and limit for public places; specifically, PM_2.5 was assessed against the limits stipulated in GB/T 18883-2022 Standards for indoor air quality. A questionnaire survey was conducted among salon practitioners to collect weekly working days and daily working hours. The non-carcinogenic risks associated with inhalation exposure to formaldehyde, ammonia, benzene, toluene, and xylene as well as the carcinogenic risks posed by formaldehyde and benzene were evaluated following WS/T 777-2021 Technical guide for environmental health risk assessment of chemical exposure and the U.S. Environmental Protection Agency inhalation risk model. Results The overall compliance rates of PM₁₀, formaldehyde, ammonia, benzene, and toluene in the air of hair and beauty salons in Shanghai from 2016 to 2024 were 92.13%, 96.59%, 96.15%, 94.93%, and 94.97%, respectively; the overall compliance rate of xylene was a little lower (85.92%), and the overall compliance rate of PM_2.5 was 57.18%. The P₅₀ concentrations of PM₁₀, PM_2.5, formaldehyde, ammonia, benzene, toluene, and xylene did not exceed the corresponding limits. The P₅₀ of non-carcinogenic risk indicator (hazard quotient, HQ) for formaldehyde, ammonia, benzene, toluene, and xylene were <1. The probabilities of non-carcinogenic risk HQ >1 for formaldehyde and xylene were 41.4% and 10.9%, respectively, which were higher than that of other pollutants. The P₅₀ of carcinogenic risk (CR) for formaldehyde and benzene were between 1.0×10⁻⁶ and 1.0×10⁻⁴, while the probabilities of CR >1.0×10⁻⁴ were 16.9% and 14.0%, respectively. Conclusion The overall compliance rate of common pollutant concentrations in the air of hair and beauty salons in Shanghai is high, and the hygienic condition meets the requirements of national standards. The non-carcinogenic health risks posed by formaldehyde and xylene to employees (with formaldehyde being more prominent), as well as the carcinogenic risks associated with formaldehyde and benzene, deserve heightened attention in future health supervision.

OBJECTIVE To construct a clinical inapplicability evaluation system for the instructions of oral Chinese patent medicines containing toxic decoction pieces， so as to provide references for the revision and improvement of such drug instructions and the formulation of instructions for new drugs. METHODS The initial indicator framework was determined based on policy documents and literature related to instruction registration and revision. Two rounds of Delphi consultation were conducted among 25 experts to refine and optimize the indicator system. The analytic hierarchy process was employed to construct judgment matrices and obtain indicator weights. The comprehensive weights were converted into a 100-point scale to evaluate 11 instructions of oral Chinese patent medicines containing toxic decoction pieces from the medical institution of the research team. RESULTS The average questionnaire recovery rate of the two rounds of consultation was 96%. The expert authority coefficients were 0.87 and 0.88， respectively， and the Kendall’s W was statistically significant （ P ＜0.001）. The final evaluation system comprised 4 first-level indicators （defect of toxicity identification， defect of dosage information， defect of risk warning， and defect of information guidance） and 24 second-level indicators （e.g.， failure to label toxic decoction pieces in 【warnings】， failure to indicate all decoction piece compositions， absence of medication course specifications， etc.）. The total scores of the 11 oral Chinese patent medicine instructions ranged from 15.50 to 50.87 points. The main clinical inapplicability issues included the absence of medication course specifications and the failure to provide warnings in items such as 【precautions】 for decoction pieces involving the “eighteen incompatibilities and nineteen mutual antagonisms”. CONCLUSIONS The constructed indicator system can meet the requirements for evaluating the clinical inapplicability of instructions for oral Chinese patent medicines containing toxic decoction pieces. All evaluated instructions exhibited certain clinical applicability defects. Pharmaceutical manufacturers should revise the instructions in accordance with policy requirements and clinical needs.

Deep learning method can be used to automatically analyze electrocardiogram (ECG) data and rapidly implement arrhythmia classification, which provides significant clinical value for the early screening of arrhythmias. How to select arrhythmia features effectively under limited abnormal sample supervision is an urgent issue to address. This paper proposed an arrhythmia classification algorithm based on an adaptive multi-feature fusion network. The algorithm extracted RR interval features from ECG signals, employed one-dimensional convolutional neural network (1D-CNN) to extract time-domain deep features, employed Mel frequency cepstral coefficients (MFCC) and two-dimensional convolutional neural network (2D-CNN) to extract frequency-domain deep features. The features were fused using adaptive weighting strategy for arrhythmia classification. The paper used the arrhythmia database jointly developed by the Massachusetts Institute of Technology and Beth Israel Hospital (MIT-BIH) and evaluated the algorithm under the inter-patient paradigm. Experimental results demonstrated that the proposed algorithm achieved an average precision of 75.2%, an average recall of 70.1% and an average F ₁-score of 71.3%, demonstrating high classification accuracy and being able to provide algorithmic support for arrhythmia classification in wearable devices.
Humans ; Arrhythmias, Cardiac/diagnosis* ; Algorithms ; Electrocardiography/methods* ; Neural Networks, Computer ; Signal Processing, Computer-Assisted ; Deep Learning ; Classification Algorithms

Triple-negative breast cancer (TNBC) represents an aggressive breast cancer subtype with poor prognosis and limited targeted treatment options. This investigation examined the anti-cancer potential of Caerulomycin A (Cae A), a natural compound derived from marine actinomycetes, against TNBC. Cae A demonstrated selective inhibition of viability and proliferation in TNBC cell lines, including 4T1, MDA-MB-231, and MDA-MB-468, through apoptosis induction. Mechanistic analyses revealed that the compound induced sustained endoplasmic reticulum (ER) stress and subsequent upregulation of C/EBP homologous protein (CHOP) expression, resulting in mitochondrial damage-mediated apoptosis. Inhibition of ER stress or CHOP expression knockdown reversed mitochondrial damage and apoptosis, highlighting the essential role of ER stress and CHOP in Cae A's anti-tumor mechanism. Both oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) decreased in TNBC cells following Cae A treatment, indicating reduced mitochondrial respiratory and glycolytic capacities. This diminished energy metabolism potentially triggers ER stress and subsequent apoptosis. Furthermore, Cae A exhibited significant anti-tumor effects in the 4T1 tumor model in vivo without apparent toxicity. The compound also effectively inhibited human TNBC organoid growth. These results indicate that Cae A may serve as a potential therapeutic agent for TNBC, with its efficacy likely mediated through the disruption of glucose metabolism and the induction of ER stress-associated apoptosis.
Humans ; Endoplasmic Reticulum Stress/drug effects* ; Triple Negative Breast Neoplasms/genetics* ; Apoptosis/drug effects* ; Cell Line, Tumor ; Female ; Animals ; Glucose/metabolism* ; Mice ; Cell Proliferation/drug effects* ; Transcription Factor CHOP/genetics* ; Antineoplastic Agents/pharmacology* ; Mitochondria/metabolism* ; Mice, Inbred BALB C

Objective:To discuss the effect of prostaglandin E2(PGE2),a pyrogenic mediator,on the discharge activity of warm-sensitive neurons(WSNs)in median preoptic nucleus(MnPO)of hypothalamus in the female mice,and to clarify its mechanism.Methods:Coronal brain slices of MnPO were prepared from the female mice.The slices were then perfused with artificial cerebrospinal fluid(ACSF)containing synaptic transmission blockers(STBs).The discharge frequency was monitored using the patch clamp technique while changing the temperature of the perfusate to identify the WSNs.A total of 32 MnPO WSNs were divided into base line group(n=32)and PEG2(n=32).The patch clamp technique was employed to monitor the discharge frequencies of MnPO WSNs following the perfusion of ACSF and 1 μmol·L-1 PGE2,respectively.The MnPO WSNs with good activity and significant change in discharge frequency after PGE2 perfusion were divided into PGE2 receptor E-series prostaglandin receptrol(EP)1 antagonist(EP1 ant)+PGE2 group(n=7),EP3 ant+PGE2 group(n=7),and EP4 ant+PGE2 group(n=7).The patch clamp technique was used to monitor the discharge frequencies of MnPO WSNs following the perfusion of 3 μmol·L-1 EP1 ant and 1 μmol·L-1 PGE2 mixture,10 μmol·L-1 EP3 ant and 1 μmol·L-1 PGE2mixture,and 10 μmol·L-1 EP4 ant and 1 μmol·L-1 PGE2 mixture,respectively.Resluts:After perfuson of the ACSF containing STBs,a total of 188 MnPO neurons from the female mice with an intrinsic temperature sensitivity coefficient(m value)were identified;out of these,32 neurons had an m value of ≥0.8 and were identified as MnPO WSNs,accounting for approximately 17％of all recorded neurons.Compared with baseline discharge frequency,the discharge frequency of MnPO WSNs after addition of PGE2 was decreased(P＜0.05).Compared with PGE2 group,the percentage change in discharge frequency of MnPO WSNs in EP3 ant+PGE2 group was significantly decreased(P＜0.05).Compared with PGE2 group,the percentage change in discharge frequency of MnPO WSNs in EP1 ant+PGE2 group had no significant difference(P＞0.05).Compared with PGE2 group,the percentage change in discharge frequency of MnPO WSNs in EP4 ant+PGE2 group had no significant difference(P＞0.05).Conclusion:In the female mice,WSNs make up approximately 17％of the total neurons in MnPO.PGE2 can directly inhibit the discharge activity of MnPO WSNs in the female mice through postsynaptic mechanism involving EP3 receptors.

Drug resistance is one of the key factors affecting the effectiveness of cancer treatment methods, including chemotherapy, radiotherapy, and immunotherapy. Its occurrence is related to factors such as mRNA expression and methylation within cancer cells. If drug resistance in patients can be accurately identified early, doctors can devise more effective treatment plans, which is of great significance for improving patients' survival rates and quality of life. Cancer drug resistance prediction based on artificial intelligence (AI) technology has emerged as a current research hotspot, demonstrating promising application prospects in guiding clinical individualized and precise medication for cancer patients. This review aims to comprehensively summarize the research progress in utilizing AI algorithms to analyze multi-omics data including genomics, transcriptomics, epigenomics, proteomics, metabolomics, radiomics, and histopathology, for predicting cancer drug resistance. It provides a detailed exposition of the processes involved in data processing and model construction, examines the current challenges faced in this field and future development directions, with the aim of better advancing the progress of precision medicine.

As an important setting for the administration of vaccinations, the reasonable setting up and standardized management of vaccination clinics will enhance immunization service quality, public satisfaction, and improve the vaccination rate to protect people′s health. In recent years, various provinces in China are continuously promoting the standardized construction and management of vaccination clinics. However, the level of standardization management remains unbalanced, and the capacity of vaccination services needs to be further improved. This paper reviews the standardized management process of vaccination clinics, summarizes the practice and achievements in various regions, and analyzes the challenges and issues during these processes, to provide reference for improving the standardized management level of vaccination clinics in the future.

Objective:To evaluate the potential value of 18×10 3 translocator protein (TSPO) radioligand ( N, N-diethy1-2-(2-(4-(2- 18F-fluoroethoxy) phenyl)-5, 7-dimethylpyrazolo[1, 5-A]pyrimidin-3-yl)acetamide, 18F-DPA-714) PET compared with conventional MR in the detection of autoimmune encephalitis (AE), the correlation with clinical symptoms, and the monitoring of immunotherapy efficacy in patients with AE. Methods:From December 2021 to June 2024, 45 AE patients (17 males, 28 females, age (38.3±17.0) years) diagnosed at Ruijin Hospital, Shanghai Jiao Tong University School of Medicine and 10 healthy volunteers (7 males, 3 females, age (28.7±5.1) years) were enrolled in this prospective study. All participants underwent baseline 18F-DPA-714 PET/MR scans, and 23 of these AE patients underwent further follow-up 18F-DPA-714 PET/MR scans. 18F-DPA-714 PET positivity was defined as having an uptake intensity threshold higher than the mean SUV ratio (SUVR)+ 2 s of the corresponding brain region in healthy controls. MR positivity was defined as abnormal hyperintensity in a specific brain region or multiple brain regions on the T 2 fluid attenuated inversion recovery (FLAIR). The positive detection rates of 18F-DPA-714 PET and MR was analyzed using McNemar χ2 test, and the differences in the uptake intensity (SUVR) of 18F-DPA-714 between symptomatic and non-symptomatic groups, and between remission and non-remission groups after immunotherapy were compared using independent-sample t test or Wilcoxon rank sum test. Spearman rank correlation analysis was used to analyze the correlation between the changing rate of SUVR and the changing of the modified Rankin Scale (mRS) score before and after treatment. Results:The positive detecting rate of 18F-DPA-714 PET for AE was significantly higher than that of MR (73.3%(33/45) vs 35.6%(16/45); χ2=11.56, P=0.001). The cerebellar SUVR of ataxia patients was significantly higher than that of asymptomatic patients (1.22(1.06, 1.33) vs 1.08(0.99, 1.20); Z=-2.14, P=0.034). Follow-up imaging showed that the SUVR of patients in the remission group after immunotherapy was significantly lower than that in the non-remission group ((-15.19±10.17)% vs (14.26±13.36)%; t=5.81, P<0.001). There was a significant correlation between the changing rate of SUVR and the changing of the mRS score before and after treatment ( rs=0.65, P<0.001). Conclusion:Compared with conventional MR, 18F-DPA-714 PET has a higher positive detecting rate for AE, and has the potential to reflect the clinical symptoms of AE and monitor the efficacy of immunotherapy.

Gene regulation relies on the precise binding of transcription factors (TFs) at regulatory elements, but simultaneously detecting hundreds of TFs on chromatin is challenging. We developed cFOOT-seq, a cytosine deaminase-based TF footprinting assay, for high-resolution, quantitative genome-wide assessment of TF binding in both open and closed chromatin regions, even with small cell numbers. By utilizing the dsDNA deaminase SsdAtox, cFOOT-seq converts accessible cytosines to uracil while preserving genomic integrity, making it compatible with techniques like ATAC-seq for sensitive and cost-effective detection of TF occupancy at the single-molecule and single-cell level. Our approach enables the delineation of TF footprints, quantification of occupancy, and examination of chromatin influences on TF binding. Notably, cFOOT-seq, combined with FootTrack analysis, enables de novo prediction of TF binding sites and tracking of TF occupancy dynamics. We demonstrate its application in capturing cell type-specific TFs, analyzing TF dynamics during reprogramming, and revealing TF dependencies on chromatin remodelers. Overall, cFOOT-seq represents a robust approach for investigating the genome-wide dynamics of TF occupancy and elucidating the cis-regulatory architecture underlying gene regulation.
Transcription Factors/genetics* ; Humans ; Chromatin/genetics* ; Animals ; Binding Sites ; Mice ; DNA Footprinting/methods*