Childhood simple obesity has become a significant public health issue in China. Modern medicine primarily relies on lifestyle interventions and often suffers from poor long-term compliance， while pharmacological options are limited and associated with potential adverse effects. Traditional Chinese Medicine （TCM） has a long history in the prevention and management of this condition， demonstrating eight distinct advantages， including systematic theoretical foundation， diversified therapeutic approaches， definite therapeutic efficacy， high safety profile， good patient compliance， comprehensive intervention strategies， emphasis on prevention， and stepwise treatment protocols. Additionally， TCM is characterized by six distinctive features： the use of natural medicinal substances， non-invasive external therapies， integration of medicinal dietetics， simple exercise regimens， precise syndrome differentiation， and diverse dosage forms. By combining internal and external treatments， TCM facilitates individualized regimen adjustment and holistic regulation， demonstrating remarkable effects in improving obesity-related metabolic indicators， regulating constitutional imbalance， and promoting healthy behaviors. However， challenges remain， such as inconsistent operational standards， insufficient high-quality clinical evidence， and a gap between basic research and clinical application. Future efforts should focus on accelerating the standardization of TCM diagnosis and treatment， conducting multicenter randomized controlled trials， and fostering interdisciplinary integration， so as to enhance the scientific validity and international recognition of TCM in the prevention and treatment of childhood obesity.

Objective:To construct a nomogram based on preoperative MRI imaging features for the prediction of muscle-invasive upper urinary tract urothelial carcinoma（UTUC）and evaluate its performance.Methods:This retrospective cohort study analyzed the clinical data of 99 UTUC patients treated at the First Affiliated Hospital of Nanjing Medical University from April 2018 to May 2024. Among them，69（69.7%）were male and 30（30.3%）were female，with a median age of 67.0 years. All patients underwent preoperative MRI and radical nephroureterectomy. According to postoperative pathology，tumors staged ≥ T 2 were assigned to the muscle-invasive group，and those staged ≤ T 1 were assigned to the non-muscle-invasive group. Baseline data，pathological information，and imaging characteristics were collected and compared between the two groups. Logistic regression analysis was performed to identify risk factors for muscle-invasive UTUC，and a nomogram was constructed. The diagnostic performance of the model was assessed using receiver operating characteristic（ROC）curves，calibration curves，and decision curve analysis（DCA）. Results:Among the 99 patients，70（70.7%）were diagnosed with muscle-invasive UTUC，and 29（29.3%）with non-muscle-invasive UTUC. The muscle-invasive group had significantly larger tumor size［4.5（2.8，7.0）cm vs. 3.0（2.3，4.5）cm， P = 0.029］，a higher incidence of multifocal tumors［37.1%（26/70）vs. 3.5%（1/29）， P < 0.001］，patchy tumors［30.0%（21/70）vs. 6.9%（2/29）， P = 0.019］，spiculated tumor margins［52.9%（37/70）vs. 17.2%（5/29）， P = 0.001］，tumor compression on renal parenchyma or periureteral/peripelvic fat［68.6%（48/70）vs. 10.3%（3/29）， P < 0.001］，high-grade pathology［92.9%（65/70）vs. 75.9%（22/29）， P = 0.043］，lymph node metastasis［28.6%（20/70）vs. 0， P = 0.001］，and lymphovascular invasion［42.9%（30/70）vs. 10.3%（3/29）， P=0.002］. The apparent diffusion coefficient（ADC）values［0.9（0.8，1.1）× 10 -3 mm2/s vs. 1.1（1.0，1.4）× 10 -3 mm2/s， P < 0.001］and normalized ADC（NADC）values［0.8（0.7，1.0）vs. 0.9（0.8，1.1）， P = 0.002］were significantly lower in the muscle-invasive group. Univariate logistic regression identified multifocality，patchy tumor patterns，spiculated tumor margins，tumor compression on renal parenchyma or periureteral/peripelvic fat，and low NADC values as risk factors for muscle-invasive UTUC（all P < 0.05）. Multivariate analysis revealed multifocality（ OR = 17.903，95% CI 1.650 - 194.253， P = 0.018），tumor compression on renal parenchyma or perirenal / ureteral fat（ OR = 14.690，95% CI 3.069 - 70.323， P < 0.001），and low NADC value（ OR = 0.016，95% CI 0.001 - 0.471， P = 0.017）as independent risk factors. A nomogram was constructed based on these factors. The area under the ROC curve（AUC）of the model was 0.898（95% CI 0.838 - 0.957），with an optimal cutoff value of 0.639. The model showed an accuracy of 83.8%，sensitivity of 81.4%，and specificity of 89.7%. Calibration curves indicated good calibration，and DCA showed that the model provided substantial clinical net benefit. Conclusions:This study constructed a nomogram based on preoperative MRI features，including tumor multifocality，compression on renal parenchyma or periureteral/peripelvic fat and NADC value，which demonstrates good predictive performances for muscle-invasive UTUC.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

OBJECTIVE: To evaluate the efficacy and safety of Shexiang Tongxin Dropping Pill (STDP) in treating stable angina patients with phlegm-heat and blood-stasis syndrome by exercise duration and metabolic equivalents. METHODS: This multicenter, randomized, double-blind, placebo-controlled clinical trial enrolled stable angina patients with phlegm-heat and blood-stasis syndrome from 22 hospitals. They were randomized 1:1 to STDP (35 mg/pill, 6 pills per day) or placebo for 56 days. The primary outcome was the exercise duration and metabolic equivalents (METs) assessed by the standard Bruce exercise treadmill test after 56 days of treatment. The secondary outcomes included the total angina symptom score, Chinese medicine (CM) symptom scores, Seattle Angina Questionnaire (SAQ) scores, changes in ST-T on electrocardiogram and adverse events (AEs). RESULTS: This trial enrolled 309 patients, including 155 and 154 in the STDP and placebo groups, respectively. STDP significantly prolonged exercise duration with an increase of 51.0 s, compared to a decrease of 12.0 s with placebo (change rate: -11.1% vs. 3.2%, P<0.01). The increase in METs was significantly greater in the STDP group than in the placebo group (change: -0.4 vs. 0.0, change rate: -5.0% vs. 0.0%, P<0.01). The improvement of total angina symptom scores (25.0% vs. 0.0%), CM symptom scores (38.7% vs. 11.8%), reduction of nitroglycerin consumption (100.0% vs. 11.3%), and all domains of SAQ, were significantly greater with STDP than placebo (all P<0.01). The changes in Q-T intervals at 28 and 56 days from baseline were similar between the two groups (both P>0.05). Twenty-five participants (16.3%) with STDP and 16 (10.5%) with placebo experienced AEs (P=0.131), with no serious AEs observed. CONCLUSION STDP could improve exercise tolerance in patients with stable angina and phlegm-heat and blood stasis syndrome, with a favorable safety profile. (Registration No. ChiCTR-IPR-15006020).
Humans ; Double-Blind Method ; Drugs, Chinese Herbal/adverse effects* ; Male ; Female ; Middle Aged ; Angina, Stable/physiopathology* ; Aged ; Syndrome ; Treatment Outcome ; Placebos ; Tablets

Traditional Chinese medicine (TCM) serves as a treasure trove of ancient knowledge, holding a crucial position in the medical field. However, the exploration of TCM's extensive information has been hindered by challenges related to data standardization, completeness, and accuracy, primarily due to the decentralized distribution of TCM resources. To address these issues, we developed a platform for TCM knowledge discovery (TCMKD, https://cbcb.cdutcm.edu.cn/TCMKD/). Seven types of data, including syndromes, formulas, Chinese patent drugs (CPDs), Chinese medicinal materials (CMMs), ingredients, targets, and diseases, were manually proofread and consolidated within TCMKD. To strengthen the integration of TCM with modern medicine, TCMKD employs analytical methods such as TCM data mining, enrichment analysis, and network localization and separation. These tools help elucidate the molecular-level commonalities between TCM and contemporary scientific insights. In addition to its analytical capabilities, a quick question and answer (Q&A) system is also embedded within TCMKD to query the database efficiently, thereby improving the interactivity of the platform. The platform also provides a TCM text annotation tool, offering a simple and efficient method for TCM text mining. Overall, TCMKD not only has the potential to become a pivotal repository for TCM, delving into the pharmacological foundations of TCM treatments, but its flexible embedded tools and algorithms can also be applied to the study of other traditional medical systems, extending beyond just TCM.

Objective To explore the value of serum matrix metalloproteinase 7 combined with glutamyl transferase and total bile acids in the diagnosis of biliary atresia.Methods 112 children hospitalized in Kunming Children's Hospital with the cholestatic jaundice from July 2023 to September 2024 were selected as the research subjects.According to the surgical exploration,intraoperative cholangiography,liver biopsy and follow-up,the children were divided into the biliary atresia group(BA)(n=52)and non-biliary atresia group(Non-BA)(n=60)respecvely.The age,gender,serum matrix metalloproteinase 7(MMP-7),glutamyl transferase(GGT),alanine aminative aminotransferase(ALT),aspartate aminotransferase(AST),total bilirubin(TB),direct bilirubin(DB),total bile acid(TBA)and aspartate aminotransferase/platelet index(APRI)were compared between the two groups.Statistically significant indicators were included in receiver operating characteristic curve(ROC)analysis,and the area under the ROC curve(AUC)and optimal diagnostic margin(Youden index)were calculated.Results There was no significant difference in age,ALT,AST,DB,TB and APRI levels between the two groups of patients(P>0.05);There was a difference in gender composition ratio between the two groups(P=0.006);MMP-7,GGT,TBA levels in the BA group were significantly higher than those in the Non-BA group,and the difference was statistically significant(P<0.05);the AUC of MMP-7,GGT,and TBA in diagnosing BA were 0.946(95%CI 0.897～0.996),0.857(95%CI 0.789～0.926),0.654(95%CI 0.552～0.755)respectively;When the cut-off value of MMP-7 was 22.37 ng/ml,the sensitivity and specificity for diagnosing BA were 0.923 and 0.933 respectively;When the cut-off value of GGT was 151.5 U/L,the sensitivity and specificity of diagnosing BA were 0.885 and 0.733 respectively;When the cut-off value of TBA was 119.5 μmol/L,the sensitivity and specificity of diagnosing BA were 0.788 and 0.500,respectively.The AUC of MMP-7+GGT and MMP-7+TBA combined to diagnose BA were 0.971(95%CI 0.946～0.997)and 0.943(95%CI 0.889～0.996)respectively.Conclusion Serum MMP-7 has the good diagnostic value as a single indicator for diagnosing BA;MMP-7 combined with GGT is better than a single indicator for diagnosing BA;MMP-7 combined with TBA cannot improve the diagnostic efficiency.

Traditional Chinese medicine(TCM)serves as a treasure trove of ancient knowledge,holding a crucial position in the medical field.However,the exploration of TCM's extensive information has been hindered by challenges related to data standardization,completeness,and accuracy,primarily due to the decen-tralized distribution of TCM resources.To address these issues,we developed a platform for TCM knowledge discovery(TCMKD,https://cbcb.cdutcm.edu.cn/TCMKD/).Seven types of data,including syndromes,formulas,Chinese patent drugs(CPDs),Chinese medicinal materials(CMMs),ingredients,targets,and diseases,were manually proofread and consolidated within TCMKD.To strengthen the integration of TCM with modern medicine,TCMKD employs analytical methods such as TCM data mining,enrichment analysis,and network localization and separation.These tools help elucidate the molecular-level commonalities between TCM and contemporary scientific insights.In addition to its analytical capabilities,a quick question and answer(Q&A)system is also embedded within TCMKD to query the database efficiently,thereby improving the interactivity of the platform.The platform also provides a TCM text annotation tool,offering a simple and efficient method for TCM text mining.Overall,TCMKD not only has the potential to become a pivotal repository for TCM,delving into the pharmaco-logical foundations of TCM treatments,but its flexible embedded tools and algorithms can also be applied to the study of other traditional medical systems,extending beyond just TCM.

Objective To analyze the influencing factors of malaria infection of labor service exported to overseas in Langfang City, in order to establish a visualization tool to assist clinicians in predicting the risk of malaria. Methods A total of 4 774 expatriate employees of the Nibei Pipeline Project of the Pipeline Bureau from October 2021 to August 2023 were taken as the subjects, and the gender, age, overseas residence area and Knowledge of malaria controlscores of the study subjects were investigated by questionnaire survey, and the possible risk factors of malaria were screened by logistic regression model. At the same time, the nomogram prediction model was established, and the subjects were divided into the training group and the validation group at a ratio of 2:1, and the area under the curve (ROC) and the decision curve were plotted to evaluate the prediction ability and practicability of the prediction model in this study. Results Among the 4 774 study subjects, 96 cases of malaria occurred, and the detection rate was 2.01%. Junior school （OR=1.723，95% CI:1.361-2.173）， and residence in rural areas（OR=2.091，95%CI:1.760 -3.100）were risk factors (OR>1), while protective measures（OR=0.826，95% CI : 0.781 - 0.901） and high malaria education scores （OR=0.872，95% CI : 0.621 - 0.899）were protective factors.The nomogram prediction model results showed that the area under the curve of the nomogram prediction model in the training group was 0.94 (95% CI : 0.85 - 1.00), while the validation group was 0.93 (95% CI : 0.80 - 1.00). The results of the decision curve showed that when the threshold probability of the population was 0-0.9, the nomogram model was used to predict the risk of malaria occurrence with the highest net income. Conclusion The nomogram prediction model (including gender, education, region, protection and malaria education score) established and validated in this study is of great value for clinicians to screen high-risk patients with malaria.

ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.