ObjectiveTo explore the effects of serine hydroxymethyltransferase 1 （SHMT1） rs1979277 polymorphisms on pharmacokinetic characteristics and clinical prognosis of methotrexate （MTX） in children with acute lymphoblastic leukemia （ALL）. MethodsMatrix-assisted laser desorption/ionization time of flight mass spectrometry was used for SHMT1 rs1979277 genotyping in children with ALL . Clinical data including serum MTX concentrations， incidences of adverse events， and ALL relapse after chemotherapy with MTX were collected. The associations of SHMT1 rs1979277 G>A genotypes with dose-adjusted serum concentrations （C/D ratios）， adverse events of MTX， and relapse were analyzed. The associations between rs1979277 genotypes and SHMT1 expression were explored based on Bioinformatics methods. ResultsAmong the 146 children with ALL included， the rs1979277 GG homozygous genotype accounted for 85.62% （125/146）， while the GA heterozygous genotype accounted for 14.38% （21/146）. The frequency of the G allele was 92.81% （271/292）， while the A allele was only 7.19% （21/292）. Children with the GG homozygous genotype had higher median C/D ratios of MTX in 24 h ［12.06 （μmol·m²）/（L·g）］ and higher relapse rates （12.80%） than those in GA heterozygous genotype carriers ［10.96 （μmol·m²）/（L·g）， and 9.52%， respectively］. However， none of the above differences were statistically significant （all P>0.05）. The incidences of respiratory （19.05%） and liver disorders （33.33%） in children with the GA heterozygous genotype were significantly higher than those in GG homozygous genotype carriers （4.00% and 12.00%， respectively， P<0.05）. There were no statistically significant differences in the incidences of other adverse events. Bioinformatics analysis showed that the rs1979277 A allele was significantly associated with higher SHMT1 expression in multiple tissues， such as the tibial artery， pancreas， and adrenal gland （P<0.05）. ConclusionSHMT1 rs1979277 GA genotype may be a risk factor for respiratory and liver disorders in ALL children treated with MTX.

Objective:To assess the predictive performance of a nomogram model integrating endoscopic ultrasound（EUS）radiomic features with clinical variables for distinguishing early esophageal squamous cell carcinoma（ESCC）from non-cancerous lesions.Methods:Clinical and imaging data from 454 patients who underwent EUS for suspected esophageal malignancies were retrospectively collected in the First Affiliated Hospital of Nanjing Medical University（training cohort， n = 323）and Dongyang People's Hospital（external validation cohort， n = 131）from January 2020 to November 2023. Independent clinical predictors of early ESCC were identified using univariable and multivariable Logistic regression analyses to establish a clinical model. Pearson correlation and Least Absolute Shrinkage and Selection Operator（LASSO）algorithms were used to construct a radiomics model. A combined model integrating radiomics scores and clinical predictors was developed and visualized as a nomogram. The predictive performance of each model was assessed using the area under the ROC curve（AUC），and calibration curves were used to evaluate the model's fitting capability. Results:The training set and validation set indicated that there were statistically significant differences in age，smoking history and lesion location between the early ESCC group and the non-cancerous lesion change group（all P < 0.05）. According to univariate and multivariate Logistic regression analysis，age（ OR = 1.039，95% CI = 1.003–1.077， P = 0.036）and smoking（ OR = 2.358，95% CI = 1.270 - 4.376， P = 0.007）were identified as independent predictors and used to develop the clinical model，with AUCs of 0.608 and 0.694 in the training and validation cohorts，respectively. Fourteen optimal radiomic features were selected to construct the radiomics model，with AUCs of 0.881 and 0.807 in the training and validation cohorts，respectively. The combined nomogram model demonstrated superior predictive performance with AUCs of 0.893 and 0.830，sensitivities of 82.5% and 79.1%，and specificities of 82.2% and 81.3% in the training and validation cohorts，respectively. Conclusions:The EUS-based nomogram model demonstrates optimal predictive performance and can serve as a non-invasive tool to assist endoscopists in distinguishing early ESCC from non-cancerous lesions.

Objective:To assess the predictive performance of a nomogram model integrating endoscopic ultrasound（EUS）radiomic features with clinical variables for distinguishing early esophageal squamous cell carcinoma（ESCC）from non-cancerous lesions.Methods:Clinical and imaging data from 454 patients who underwent EUS for suspected esophageal malignancies were retrospectively collected in the First Affiliated Hospital of Nanjing Medical University（training cohort， n = 323）and Dongyang People's Hospital（external validation cohort， n = 131）from January 2020 to November 2023. Independent clinical predictors of early ESCC were identified using univariable and multivariable Logistic regression analyses to establish a clinical model. Pearson correlation and Least Absolute Shrinkage and Selection Operator（LASSO）algorithms were used to construct a radiomics model. A combined model integrating radiomics scores and clinical predictors was developed and visualized as a nomogram. The predictive performance of each model was assessed using the area under the ROC curve（AUC），and calibration curves were used to evaluate the model's fitting capability. Results:The training set and validation set indicated that there were statistically significant differences in age，smoking history and lesion location between the early ESCC group and the non-cancerous lesion change group（all P < 0.05）. According to univariate and multivariate Logistic regression analysis，age（ OR = 1.039，95% CI = 1.003–1.077， P = 0.036）and smoking（ OR = 2.358，95% CI = 1.270 - 4.376， P = 0.007）were identified as independent predictors and used to develop the clinical model，with AUCs of 0.608 and 0.694 in the training and validation cohorts，respectively. Fourteen optimal radiomic features were selected to construct the radiomics model，with AUCs of 0.881 and 0.807 in the training and validation cohorts，respectively. The combined nomogram model demonstrated superior predictive performance with AUCs of 0.893 and 0.830，sensitivities of 82.5% and 79.1%，and specificities of 82.2% and 81.3% in the training and validation cohorts，respectively. Conclusions:The EUS-based nomogram model demonstrates optimal predictive performance and can serve as a non-invasive tool to assist endoscopists in distinguishing early ESCC from non-cancerous lesions.

Hepatic ascites is one of the common and difficult complications in the decompensated stage of liver cirrhosis， and its incidence is increasing. In clinical practice， the prognosis of patients with hepatic ascites after surgery is worse， and the disease is recurrent. Traditional Chinese medicine （TCM） has certain advantages in treating hepatic ascites. However， there is no uniform standard for the preparation of animal models of hepatic ascites in accordance with TCM evidence. Therefore， this paper summarized the literature on animal models of hepatic ascites and analyzed the existing animal models of hepatic ascites based on the clinical diagnostic criteria of hepatic ascites in TCM and western medicine. The results show that the commonly used modeling methods for hepatic ascites mainly include the single-factor method， composite factor induction method， surgical method， and immunization method. Most of them are guided by western medicine theories， and their pathogenic mechanisms are mostly consistent with those of western medicine and are different from TCM evidence. Therefore， it is suggested that TCM intervening factors should be imposed in the process of model preparation， so as to prepare an animal model of hepatic ascites that meets the clinical evidence characteristics of TCM and western medicine.

OBJECTIVE To investigate the impact of the methionine synthase reductase （MTRR） rs10380 C＞T gene polymorphism on methotrexate （MTX） plasma concentration， adverse drug reaction， and prognosis in children with intracranial tumors. METHODS Peripheral blood was collected from children with intracranial tumors， and genomic DNA was extracted. The MTRR rs10380 C＞T genotype was analyzed using matrix-assisted laser desorption/ionization-time of flight-mass spectrometry. The association of the MTRR rs10380 C＞T gene polymorphism with the ratio of MTX plasma concentration to dose （C/D ratio）， adverse drug reaction， tumor recurrence， and metastasis was analyzed. Bioinformatics analysis was used to explore the association of the rs10380 genotype and MTRR gene expression and its possible mechanisms. RESULTS A total of 75 children were included in the study. The distribution frequencies of the wild-type CC genotype and C allele of rs10380 were 62.67% and 81.33%， respectively， while the distribution frequencies of the variant CT genotype and T allele were 37.33% and 18.67%， respectively， which were in accordance with Hardy-Weinberg equilibrium（P＞0.05）. The incidence of electrolyte disorders （51.06%） and tumor metastasis rate （57.45%） in children with the CC genotype were significantly higher than those with the CT genotype （P＜0.05）. No significant differences were observed in the 24-hour and 42-hour C/D ratios and recurrence rates between the two genotypes of children （P＞0.05）. Bioinformatics analysis showed that MTRR protein mainly works in conjunction with 10 proteins， including MMAA， and was involved in various biological processes such as sulfur amino acid biosynthesis. CONCLUSIONS The MTRR rs10380 CC genotype may be a risk factor for electrolyte disorders and tumor metastasis in children with intracranial tumors after MTX chemotherapy.

ObjectiveTo collect and analyze the properties and application characteristics of external use of roots and rhizomes of Chinese herbal medicines in the Chinese Materia Medica（《中华本草》） to provide data references for the research on clinical external use of Chinese medicine， in order to provide data reference for clinical external use of traditional Chinese medicine（TCM）. MethodThe Chinese herbal medicines included in the Chinese Materia Medica were systematically screened. The inclusion criterion was the explicit mention of terms like "root", "rhizome", "root bark", "tuber", "tuberous root", etc. under the "Source" in the Chinese Materia Medica. Information on properties, flavors, meridian tropism, medicinal parts, fresh use, toxicity, efficacies and indications, and dosage of roots and rhizomes of Chinese herbal medicines was collected. The information was then entered into an Excel spreadsheet for statistical analysis. ResultThe Chinese Materia Medica records 2 662 roots and rhizomes of Chinese herbal medicines, of which 1 653 are suitable for external use. The predominant properties and flavors are cool, cold, bitter, pungent, and sweet. These Chinese herbal medicines mainly act on the liver, lung, and spleen meridians. The primary medicinal parts used include root, rhizome, and root bark. More than half of the roots and rhizomes of Chinese herbal medicines can be used in their fresh form. The main efficacies include clearing heat, removing toxins, resolving stasis, dispersing accumulation, resolving blood stasis and stopping bleeding, reducing swelling and alleviating pain, dispelling dampness and relieving pain. The main indications are skin sores, traumatic injuries, and rheumatic diseases. Common external application methods include poultice, decoction for washing, and applying powdered form. Most of these Chinese herbal medicines lack specific dosage guidelines for external use, with an emphasis on using an appropriate amount. ConclusionThe Chinese Materia Medica contains a wide range of roots and rhizomes of Chinese herbal medicines suitable for external use, with definite therapeutic effects, providing a broad perspective for the application of Chinese medicine externally. However, there are still problems such as unclear dosages and limited research. Further studies are necessary to better utilize the advantages of the external use of Chinese medicine.

Objective:To investigate the feasibility of deep learning radiomics model in the prediction of neoadjuvant chemotherapy (NAC) response in breast cancer based on ultrasound images at an early stage.Methods:Between January 2018 and June 2021, 218 patients with breast cancer who underwent NAC were enrolled in the retrospective study. All patients received a full cycle of NAC before surgery and underwent standard ultrasound examination before NAC and after the second cycles of NAC. Of all the patients, 166 patients came from institution 1 (the First Affiliated Hospital of Nanjing Medical University) were allocated into a primary cohort.Based on the architecture of Resnet 50 convolutional neural, a deep learning prediction model was built.Further validation was performed in an external testing cohort ( n=52) from institution 2 (General Hospital of Eastern Theater Command, PLA). The clinical model was constructed using independent clinical variables. To evaluate the predictive performance, areas under the curve (AUCs) of these models and two radiologists were compared by using the DeLong method. Results:The Resnet 50 model predicted the response of NAC with accuracy. The deep learning model, achieving an AUC of 0.923 (95% CI=0.884-0.962) in the primary cohort and an AUC of 0.896 (95% CI=0.807-0.980) in the test cohort, outperformed the clinical model and also performed better than two radiologists′ prediction (all P<0.05). Furthermore, the two radiologists achieved a better predictive efficacy (AUC 0.832 and 0.808 for radiologists 1 and 2, respectively) when assisted by the DL model (all P<0.01). Conclusions:The deep learning radiomics model is able to predict therapy response in the early-stage of NAC for breast cancer patients, which could guide clinicians and provide benefit for timely treatment strategy adjustment.

ObjectiveTo count and analyze the toxic traditional Chinese medicines and their characteristics in Chinese Materia Medica， so as to provide reference for the development and application of toxic drugs. MethodThe traditional Chinese medicines included in Chinese Materia Medica were screened one by one， and the inclusion criteria were "drug properties"， "usage and dosage" and "major poison， highly poisonous， poisonous， slightly poisonous， slightly poisonous" appearing in ancient books. Standard toxic traditional Chinese medicines were entered into an excel sheet for statistical analysis. ResultA total of 1 408 toxic Chinese medicines were included. The properties and flavors were mainly cold， bitter， pungent and sweet； the main meridians were liver， lung， spleen and stomach； the root， whole grass and leaves were the most used medicinal parts， and there were many toxic drugs. The pre-treatment methods are mainly sun-dried， fresh， fried， calcined， and sunburned； the efficacy categories are mainly heat-clearing drugs， rheumatism drugs， blood-activating and stasis-removing drugs； oral administration methods are mainly decoctions， pills， and powders ， mainly for external application， dipping， and coating； the dosage for oral administration is mostly 9-15 g， 3-9 g， 3-6 g， and an appropriate amount is mainly for external use. ConclusionThere are many toxic Chinese medicines clearly recorded in Chinese Materia Medica， but only 83 kinds of clearly toxic Chinese medicines are included in Chinese Pharmacopoeia， which need to be further strengthened by experimental observation and clinical data verification. The clinical application of toxic traditional Chinese medicine is mainly based on heat toxin blood syndrome and rheumatic arthralgia， which is closely related to its nature， taste and meridian return. Able to move， has the effect of activating Qi and activating blood， "sweet" can replenish energy and slow down， and has the effect of tonic， alleviation and pain relief， and mostly used for the treatment of heat syndrome， blood syndrome and arthralgia syndrome. However， there are certain limitations in the classification and processing conditions of toxic traditional Chinese medicines， which need to be further improved and scientifically verified.

The construction of medical knowledge platform is a core value of the intelligent construction of electronic medical records. The hospital-wide knowledge base construction covers a wide range of content, including multiple healthcare scenarios such as medicine, testing, inspection, surgery, blood transfusion and nursing. This article introduced how Jiangsu Province People′s Hospital used knowledge graphs and rule engine to construct a hospital knowledge management platform, realize the integration of knowledge-based knowledge base and a non-knowledge-based knowledge base, and embed clinical diagnosis and treatment rules into the information system for different flexible application scenarios.Finally, a multi-dimensional knowledge base was formed to realize the unified knowledge information integration of various clinical expert knowledge, and to provide integrated display and decision support for all departments, as well as realizing real-time data verification, prompting and control in each link.

Electronic data capture(EDC) plays an important role in improving the quality of clinical research.The authors introduced the main functions of EDC and the use flow, then from its core function, analyzed the role of EDC in improving the quality of clinical research and scientific research management. Then they proposed the thinking of finding and solving problems from EDC " big data".Their efforts aim at enabling research administrators in extending clinical research management scope and management quality.