As a new type of production factor that can empower the development of new quality productivity, the data element is an important engine to promote the high quality development of the industry. Traditional Chinese medicine(TCM) dispensing is the most basic work of TCM clinical pharmacy, and its quality directly affects the clinical efficacy of TCM. The integration of data elements and TCM dispensing can stimulate the innovation and vitality of the TCM dispensing industry and promote the high-quality and sustainable development of the industry. A large-scale, detailed, and systematic study on TCM dispensing was conducted. The innovative practice path of data fusion construction in the whole process of TCM dispensing was investigated by integrating the digital resources "nine full activities" of TCM dispensing, creating the digital dictionary of "TCM clinical information data elements", and exploring innovative applications of TCM dispensing driven by data and technology, so as to promote the standardized, digital, and intelligent development of TCM dispensing in medical health services. The research content of this project was successfully selected as the second batch of "Data element×" typical cases of National Data Administration in 2024, which is the only selected case in the field of TCM.
Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal ; Humans

Quality control is a key link in the modernization process of traditional Chinese medicine(TCM). Studies have shown that the effects of active components in TCM depend on not only their chemical composition but also their suitable physical forms and states. The physical phase structures, such as micelles, vesicles, gels, and nanoparticles, can improve the solubility, delivery efficiency, and targeting precision of active components. These structures significantly enhance the pharmacological activity while reducing the toxicity and side effects, demonstrating functional activity surpassing that of active components and highlighting the key effects of "structures" on "functions" of active components. Taking the physical phase structure as a breakthrough point, this paper outlines the common types of TCM physical phase structures. Furthermore, this paper explores how to realize the quality upgrading of TCM through the precise regulation of physical phase structures based on the current applications and potential of TCM physical phase structures in processing to increase the efficacy and reduce the toxicity, compounding and decocting processes, drug delivery systems, and quality control, aiming to provide novel insights for the future quality control of TCM.
Quality Control ; Drugs, Chinese Herbal/standards* ; Medicine, Chinese Traditional/standards* ; Humans ; Drug Delivery Systems

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Background ¹³⁷Cs in atmospheric aerosol is the product of past nuclear weapon tests and nuclear accidents. When ¹³⁷Cs is released into the atmosphere, it will deposit in dry land and marine environment, causing pollution of soil surface, water, agricultural products, and animal byproducts, and affecting public health. Objective To identify the variation pattern of ¹³⁷Cs activity concentration in aerosol and its correlation with dust concentration in Beijing area from 2017 to 2020. Methods A total of 958 aerosol samples were collected from November 1, 2017 to June 30, 2020 in Beijing with a high volume air sampler at a sampling flow rate about 600 m³·h⁻¹ and a collection time for each sample about 24 h. The activity concentration of ¹³⁷Cs in the aerosol samples was determined with a low-background high-purity germanium γ spectrometer. The dust concentration was calculated using the difference in the mass of the aerosol filter before and after sampling. The detection rate of ¹³⁷Cs and dust concentration in different seasons were compared. Spearman rank correlation test was used to analyze the correlation between ¹³⁷Cs activity concentration and dust concentration. Results From 2017 to 2020, the ¹³⁷Cs activity concentrations of 33 from 958 aerosol samples in Beijing were above the minimum detectable activityconcentration, the overall detection rate of ¹³⁷Cs was 3.4%, and the activity concentration ranged from 1.86 to 45.53 μBq·m⁻³, with a median value of 4.85 μBq·m⁻³. The detection rate of ¹³⁷Cs was highest in spring, followed by autumn, and lowest in winter and summer (8.4%, 3.0%, 1.1%, and 0.5%, respectively). The dust concentration ranged from 0.03 to 1.55 mg·m⁻³, with an average value of 0.18 mg·m⁻³. There was a statistically significant difference in the dust concentrations in spring, summer, autumn, and winter (F=45.51, P<0.05), and the highest value was 0.24 mg·m⁻³ in spring (P<0.05). The ¹³⁷Cs activity concentration was positively correlated with the dust concentration (P<0.05). Conclusion The ¹³⁷Cs activity concentration in aerosol in Beijing from 2017 to 2020 fluctuates within the range of background level, and its activity concentration is highest in spring, followed autumn, and lowest in summer and winter.

Aim To study the effect of emetine on in-sulin secretion through glucagon-like peptide-1 receptor(GLP-1R).Methods Isolating rat islets were used to carry out insulin secretion experiment.Islets were incubated with different concentrations of emetine(2,10,50 μmol·L-1),different concentrations of glu-cose solution(2.8,11.1,16.7 mmol·L-1)or spe-cific GLP-1R antagonist Exendin(9-39).The amount of insulin secretion in the supernatant of each group was determined by an enzyme-linked radioimmunoas-say.Small molecule compounds were docked to GLP-1R(PDB code:5NX2)using SYBYL-X2.0 software.Results Emetine could promote insulin secretion in high glucose(11.1 mmol·L-1)in a dose-dependent manner.In low glucose(2.8 mmol·L-1),insulin secretion did not change after intervention of emetine.But in high glucose(11.1,16.7 mmol·L-1),insu-lin secretion significantly increased under the treatment of emetine in a glucose-dependent manner.The doc-king score of emetine and GLP-1R was Total Score=6.82,C Score=5,indicating that emetine had a good binding affinity with GLP-1R.Using Exendin(9-39)to block GLP-1R,the insulinotropic effect of emetine was reduced.Conclusion Emetine could promote in-sulin secretion,which is related to the activation of GLP-1R.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

There is still a serious challenge of the measurement of critical quality attributes (CQAs) related to clinical efficacy for Chinese materia medica manufacturing. To overcome this challenge, an integrated strategy of biosensor and ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS) was proposed using Tongren niuhuang qingxin pills as a trial. Firstly, an original biosensor was created using a semiconductor chip material high electron mobility transistor (HEMT) as the transducer and the macrophage migration inhibitory factor (MIF) as the identification element. By this MIF-HEMT biosensor, the efficacy on stoke of different components from Tongren niuhuang qingxin pills was measured. It was clear that all three components of Tongren niuhuang qingxin pills had strong therapeutic effects on stroke, especially the section A, the K_D of which reached to 8.722×10^-10 g·mL^-1. Furthermore, MIF-HEMT biosensor integrated UPLC-MS/MS was introduced to identify the efficacy CQAs of different components of Tongren niuhuang qingxin pills. As a result, 19 potential CQAs, such as albiforin, paeoniflorin, and prim-O-glucosylcimifugin, were measured as the efficacy CQAs of Tongren niuhuang qingxin pills on stroke treatment by MIF. These results provided vital measurement techniques and methodological guidance for the CQAs study of Tongren niuhuang qingxin pills intervention in MIF-induced stroke treatment. This also provided an essential guideline for the efficient utilization and quality control measurement of high-quality classical recipes.

Objective: To investigate the mechanism of signal transducer and activator of transcription 3 (STAT3) and cancer associated fibroblasts (CAF) jointly generate chemo-resistance in epithelial-ovarian cancer and their effect on prognosis. Methods: A total of 119 patients with high-grade ovarian serous cancer who received surgery in Cancer Hospital of Chinese Academy of Medical Sciences from September 2009 to October 2017 were collected. The clinico-pathological data and follow-up data were complete. Multivariate Cox regression model was used to analyze the prognostic factors. Ovarian cancer tissue chips of patients in our hospital were prepared. EnVision two-step method immunohistochemistry was used to detect the protein expression levels of STAT3, the specific markers of CAF activation, fibroblast activating protein (FAP), and type Ⅰ collagen (COL1A1) secreted by CAF. The relationship between the expression of STAT3, FAP, COL1A1 protein and drug resistance and prognosis of ovarian cancer patients was analyzed, and the correlation between the expression of three proteins was analyzed. These results were verified through the gene expression and prognostic information of human ovarian cancer tissues collected in the GSE26712 dataset of gene expression omnibus (GEO) database. Results: (1) Multivariate Cox regression model analysis showed that chemotherapy resistance was an independent risk factor for overall survival (OS) of ovarian cancer (P<0.001). (2) The expression levels of STAT3, FAP, and COL1A1 proteins in chemotherapy resistant patients were significantly higher than those in chemotherapy sensitive patients (all P<0.05). Patients with high expression of STAT3, FAP, and COL1A1 had significantly shorter OS than those with low expression (all P<0.05). According to the human ovarian cancer GSE26712 dataset of GEO database, patients with high expression of STAT3, FAP, and COL1A1 also showed shorter OS than patients with low expression (all P<0.05), the verification results were consistent with the detection results of ovarian cancer patients in our hospital. (3) Correlation analysis showed that the protein level of STAT3 was positively correlated with FAP and COL1A1 in our hospital's ovarian cancer tissue chips (r=0.47, P<0.001; r=0.30, P=0.006), the analysis of GEO database GSE26712 dataset showed that the expression of STAT3 gene and FAP, COL1A1 gene were also significantly positively correlated (r=0.31, P<0.001; r=0.52, P<0.001). Conclusion: STAT3 and CAF could promote chemotherapy resistance of ovarian cancer and lead to poor prognosis.
Female ; Humans ; Cancer-Associated Fibroblasts/pathology* ; Carcinoma, Ovarian Epithelial ; Ovarian Neoplasms/pathology* ; Prognosis ; STAT3 Transcription Factor/metabolism* ; Drug Resistance, Neoplasm

Objective: To explore the independent risk factors of lymph node metastasis (LNM) in early gastric cancer, and to use nomogram to construct a prediction model for above LNM. Methods: A retrospective cohort study was conducted. Inclusion criteria: (1) primary early gastric cancer as stage pT1 confirmed by postoperative pathology; (2) complete clinicopathological data. Exclusion criteria: (1) patients with advanced gastric cancer, stump gastric cancer or history of gastrectomy; (2) early gastric cancer patients confirmed by pathology after neoadjuvant chemotherapy; (3) other types of gastric tumors, such as lymphoma, neuroendocrine tumor, stromal tumor, etc.; (4) primary tumors of other organs with gastric metastasis. According to the above criteria, 1633 patients with early gastric cancer who underwent radical gastrectomy at the Department of General Surgery of the Chinese PLA General Hospital First Medical Center from December 2005 to December 2020 were enrolled as training set, meanwhile 239 patients with early gastric cancer who underwent gastrectomy at the Department of General Surgery of the Chinese PLA General Hospital Fourth Medical Center from December 2015 to December 2020 were enrolled as external validation set. Risk factors of LNM in early gastric cancer were identified by using univariate and multivariate logistic regression analyses. A nomogram prediction model was established with significant factors screened by multivariate analysis. Area under the receiver operating characteristic curve (AUC) was used for assessing the predictive value of the model. Calibration curve was drawn for external validation. Results: Among 1633 patients in training set, the mean number of retrieved lymph nodes was 20 (13-28), and 209 patients (12.8%) had lymph node metastasis. Univariate analysis showed that gender, resection range, tumor location, tumor morphology, lymph node clearance, vascular invasion, lymphatic cancer thrombus, tumor length, tumor differentiation, microscopic presence of signet ring cells and depth of tumor invasion were associated with LNM (all P<0.05). Multivariate analysis revealed that females, tumor morphology as ulcer type, vascular invasion, lymphatic cancer thrombus, tumor length≥3 cm, deeper invasion of mucosa, and poor differentiation were independent risk factors for LNM in early gastric cancers (all P<0.05). Receiver operating characteristic curve indicated that AUC of training set was 0.818 (95%CI: 0.790-0.847) and AUC of external validation set was 0.765 (95%CI: 0.688-0.843). The calibration curve showed that the LNM probability predicted by nomogram was consistent with the actual situation (C-index: 0.818 in training set and 0.765 in external validation set). Conclusions: Females, tumor morphology as ulcer type, vascular invasion, lymphatic cancer thrombus, tumor length≥3 cm, deeper invasion of mucosa and poor differentiation are independent risk factors for LNM of early gastric cancer. The establishment of a nomogram prediction model for LNM in early gastric cancer has great diagnostic value and can provide reference for treatment selection.
Female ; Gastrectomy ; Humans ; Lymph Node Excision ; Lymph Nodes ; Lymphatic Metastasis ; Nomograms ; Retrospective Studies ; Risk Factors ; Stomach Neoplasms/surgery*

AIM: To observe the clinical effect of posterior chamber phakic refractive lens(PC-PRL)implantation in the treatment of ultra-high myopia.METHODS: Retrospective case study. A total of 36 patients(67 eyes)with ultra-high myopia who underwent PC-PRL implantation in our hospital from January 2021 to January 2022 were selected. They were and divided into two groups according to the preoperative spherical equivalent, with 16 cases(30 eyes)in spherical equivalent ≤-18.00D group and 20 cases(37 eyes)in spherical equivalent >-18.00D group. The preoperative and postoperative visual acuity, intraocular pressure(IOP), corneal endothelial cell density(ECD), central anterior chamber depth(ACD)and postoperative vault and complications were compared and analyzed.RESULTS: The uncorrected visual acuity(UCVA)at 3mo after operation of the two groups reached or exceeded the preoperative best corrected visual acuity(BCVA; all P<0.05), and the spherical equivalent >-18.00D group had a greater visual acuity improvement(P<0.01). There were significant differences in IOP and corneal ECD between the two groups at 1d after operation and before operation(all P<0.05); The vault at different time points decreased after operation, but it was within the normal range; The ACD at 3mo after operation was lower than that before operation(all P<0.01). There was no difference in intraocular pressure, ECD, ACD and postoperative vault between the two groups(P>0.05). No serious postoperative complications occurred in both groups.CONCLUSION: The PC-PRL implantation had improved early visual acuity and stable refractive state, which was safe and reliable, and there were no serious complications in the treatment of patients with ultra-high myopia.