This study systematically analyzed the global research landscape, technological composition, and core patents in the field of networks target and network pharmacology, and proposes further suggestions based on the IncoPat patent citation database and VOSviewer bibliometric network visualization tool. Using patent literature metrics and scientific knowledge mapping method, technological innovation pathways, research hotspots, and future directions in this field were further revealed. In particular, this field is moving towards data-driven, intelligent, and systematic approaches. Patent analysis indicated that most patent applications in this domain focused on traditional Chinese medicine(TCM), which have provided key engineering technical approaches to explore and solve complex problems of TCM. By integrating big data and artificial intelligence technologies, network targets and network pharmacology have conferred high-precision screening and quality control of key components and targets in herbal formulations and prescriptions, accelerating the clinical translation and industrialization of TCM-based new drugs and health products with medicine-food homology. Therefore, it is essential to optimize the patent protection system and establish integrated technology platforms in this field for ensuring the competitiveness of technological achievements in research and clinical application. These efforts will advance the widespread application and high-quality development of TCM modernization, precision medicine, and innovative drug discovery.
Bibliometrics ; Patents as Topic ; Humans ; Medicine, Chinese Traditional ; Network Pharmacology/trends* ; Drugs, Chinese Herbal/pharmacology*

This study applied the grading of recommendations assessment, development and evaluation(GRADE) system and the integrated evidence chain-based effectiveness evaluation of traditional Chinese medicine(Eff-iEC) to evaluate the evidence for 12 commonly used Chinese patent medicines for the treatment of osteoporosis, which are frequently recommended in guidelines or expert consensuses. The results showed that Xianling Gubao Capsules/Tablets were rated as C(low-level evidence) according to the GRADE system, and as BA~+B~+(intermediate evidence) according to the Eff-iEC system. Jintiange Capsules were rated as C(low-level evidence) by the GRADE system, and as AA~+B(high-level evidence) by the Eff-iEC system. Gushukang Granules/Capsules were rated as C(low-level evidence) by GRADE system, and as BA~+B~+(intermediate evidence) by Eff-iEC system. Zuogui Pills were rated as C(low-level evidence) by GRADE system, and as AA~(++)B~+(high-level evidence) by Eff-iEC system. Qianggu Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AA~+B~+(high-level evidence) by Eff-iEC system. Zhuanggu Zhitong Capsules were rated as D(extremely low-level evidence) by GRADE system, and as BA~+B(intermediate evidence) by Eff-iEC system. Jingui Shenqi Pills were rated as D(extremely low-level evidence) by GRADE system, and as AA~+B(high-level evidence) by Eff-iEC system. Quanduzhong Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AD~+B~+(low-level evidence) by Eff-iEC system. Epimedium Total Flavones Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AAB~+(high-level evidence) by Eff-iEC system. Yougui Pills were rated as D(extremely low-level evidence) by GRADE system, and as AA~(++)B~(+ )(high-level evidence) by Eff-iEC system. Qigu Capsules were rated as D(extremely low-level evidence) by GRADE system, and as BB~+B(intermediate evidence) by Eff-iEC system. Liuwei Dihuang Pills were rated as C(low-level evidence) by GRADE system, and as AA~(++)B~+(high-level evidence) by Eff-iEC system. Overall, the Eff-iEC system provides a more comprehensive assessment of the effectiveness evidence for traditional Chinese medicine(TCM) than the GRADE system. However, it still has certain limitations that hinder its wider promotion and application. In terms of clinical evidence evaluation, both the Eff-iEC and GRADE systems reflect that the current clinical research quality on Chinese patent medicines for the treatment of osteoporosis is generally low. High-quality clinical trials are still needed in the future to further validate clinical efficacy.
Drugs, Chinese Herbal/therapeutic use* ; Osteoporosis/drug therapy* ; Humans ; Nonprescription Drugs/therapeutic use* ; Evidence-Based Medicine ; Medicine, Chinese Traditional

Enamel demineralization, the formation of white spot lesions, is a common issue in clinical orthodontic treatment. The appearance of white spot lesions not only affects the texture and health of dental hard tissues but also impacts the health and aesthetics of teeth after orthodontic treatment. The prevention, diagnosis, and treatment of white spot lesions that occur throughout the orthodontic treatment process involve multiple dental specialties. This expert consensus will focus on providing guiding opinions on the management and prevention of white spot lesions during orthodontic treatment, advocating for proactive prevention, early detection, timely treatment, scientific follow-up, and multidisciplinary management of white spot lesions throughout the orthodontic process, thereby maintaining the dental health of patients during orthodontic treatment.
Humans ; Consensus ; Dental Caries/etiology* ; Dental Enamel/pathology* ; Tooth Demineralization/etiology* ; Tooth Remineralization

In recent years, the application of minimal residual disease (MRD) in solid tumors has gained widespread attention. MRD typically refers to the presence of residual cancer cells that remain undetectable by imaging after curative treatments, such as surgical resection. The presence of MRD post-surgery is significantly associated with an increased risk of tumor recurrence. In colorectal cancer, circulating tumor DNA (ctDNA) serves as an effective marker for assessing MRD, particularly in non-metastatic (stages I-III) colorectal cancer. As a real-time, accurate, and convenient biomarker, ctDNA can effectively predict tumor recurrence, guide postoperative adjuvant chemotherapy decisions, and provide crucial information for recurrence monitoring. The application prospects of ctDNA detection technology are vast, promising more precise and individualized treatment plans for colorectal cancer patients. This article comprehensively analyzes the progress in the application of ctDNA for detecting MRD in non-metastatic colorectal cancer patients, elaborates on its guiding role in clinical treatment decisions, and envisions the future development directions in this field.

Objective To compare the efficiency of nomogram and different machine learning algo-rithms for constructing the dental caries predictive models for middle-aged and elderly people.Methods The multi-stage stratified random sampling method was used to select 510 middle-aged and elderly people from Nanning City,Guigang City and Chongzuo City as the research subjects for conducting the questionnaire sur-vey and oral cavity examination.The univariate analysis and Lasso regression were used to screen the related variables,and the multivariate logistic regression analysis was used to determine the final independent influen-cing factors.Based on the salient features,the nomogram predictive model was established,and the seven ma-chine learning algorithms,including linear discriminant analysis (LDA),partial least squares (PLS),range Doppler algorithm (RDA),generalized linear models (GLM),random forest (RF),support vector machine (SVM) kernel function (SVM-Radial),and SVM linear kernel function (SVM-Linear),were used to construct the seven kinds of dental caries risk predictive models.The area under the receiver operating characteristic (ROC) curve (AUC) was adopted to evaluate the predictive performance of various models and the predictive performance of models constructed using different variable screening methods.Results The detection rate of dental caries in middle-aged and elderly people was 71.18％.After feature screening,the five predictive factors were ultimately retained,which were the age (OR=0.945,95％CI:0.917-0.973),brushing frequency (OR=0.688,95％CI:0.475-0.997),whether having teeth cleaning in the past one year (OR=0.303,95％CI:0.103-0.890),number of remaining teeth (OR=1.062,95％CI:1.038-1.087) and oral health assess-ment tool (OHAT) score (OR=1.363,95％CI:1.234-1.505).The results of comparison of various models showed that the predictive model constructed by the RF algorithm performed the best,the median of AUC was 0.747,followed by the nomogram,and the median of AUC was 0.733.The median of AUCs in the predic-tion model constructed by single factor+Lasso+multivariate logistic (Lasso+logistic) screening independent variables were higher than those constructed by RF algorithm screening independent variables.ConclusionBased on Lasso+logistic screening variables,RF provide more reliable predictive efficiency in predicting dental caries in middle-aged and elderly people than nomogram and the other machine learning algorithms.

Objective To develop a mental fatigue detection method for spaceflight environments in response to the mental fatigue problem that may arise during the on-orbit period of astronauts.Methods In the ground-based research,we used a 36-hour sleep deprivation experiment to induce mental fatigue state.Then the electroencephalogram(EEG)data and questionnaire scores were collected from 45 subjects.Finally,a series of EEG features relevant to mental fatigue were calculated and a mental fatigue detection method constructed with Random Forest Classifier to differentiate the mental fatigue level.Results The average accuracy over 85%was achieved in both ground-based and space-based experimental data and each evaluation index had consistent trend.Conclusion The mental fatigue detection method based on EEG signals is suited to the differences in environment and tasks,and shows precise and stable performance in both ground-based experiment and space-based one,which is feasible to be applied in spaceflight environments in the future.

Objective:To investigate the effect of the virtual simulation system-based teaching method for the experimental course of oral local nerve block anesthesia in improving the effect of traditional teaching methods.Methods:One hundred and eighteen undergraduate dental students were randomly divided into two groups, the experimental group was taught using a virtual simulation-based system, and the control group was taught using traditional teaching. The results of the teaching were comprehensively evaluated through course feedback questionnaires, analysis of theoretical test scores, evaluations of the trainees administering and receiving anesthesia on the current anesthesia, and faculty evaluations of the success of the anesthesia, and t-tests and chi-square tests were performed using SPSS 23.0.Results:There was no significant difference in baseline level between the two groups. The students in the experimental group thought that the learning was more vivid ( t=4.24, P=0.005) and had more self-confidence in local anesthesia ( t=4.99, P<0.001). The students in the experimental group felt less needle tip jitter during injection ( t=2.22, P=0.048) and better contact with the medial surface of the mandible ( t=2.22, P=0.020). The students who received anesthesia reported less pain during injection ( t=1.99, P=0.029) and better anesthesia of the inferior alveolar nerve ( t=3.36, P=0.039) in the experimental group. Teacher assessment revealed that the experimental group had a significantly lower failure rate of inferior alveolar nerve block than the control group ( χ2=4.40, P=0.036). Conclusions:The virtual simulation system can optimize the experimental teaching of oral local nerve block anesthesia and can achieve a satisfactory teaching effect.

With the frequent occurrence of respiratory viral infectious diseases,global public health is facing major challenges,and finding effective prevention and treatment methods has become a top priority.As an important part of traditional Chinese medicine,Chinese medicine has shown unique advantages in antiviral treatment.This article aims to review the modern scientific research pro-gress of Chinese medicine against respiratory viral infectious diseases,explore its advantages in clinical application and how to deeply understand the scientific connotation of Chinese medicine intervention in the whole-life cycle of viruses through multidisciplinary cross-integration,and systematically analyze the research strategy of the antiviral infection mechanism of Chinese medicine compound.It pro-vides a reference for the reserve of candidate Chinese medicine for future prevention and control of virus safety risks,which is of great significance for effectively supporting the prevention,control and treatment of new and emerging viral infectious diseases in China.

ObjectiveTo construct a macro-evaluation tool for dampness syndrome （DS） animal model， which will provide a basis for experimental research on dampness syndrome in traditional Chinese medicine （TCM）. MethodsConceptual framework of this study was clarified through discussions within the core working group， and dimensions of the evaluation of the animal model of DS were identified according to TCM principles. We searched CNKI， Wanfang， VIP and SinoMed databases from the inception to June 30th， 2023， on experiments involving dampness syndrome animals to create a pool of items about DS animal models. The core items were selected and extracted for factor analysis and cluster analysis. An expert importance rating questionnaire was developed based on the results of the literature review， analyzing the distribution of item scores， importance averages， and coefficient of variation. Through a comprehensive analysis of literature， expert importance scoring， and specific expert opinions， items that did not meet anyone of the criteria of average importance rating ≥2.04， coefficient of variation ≤30%， or literature eva-luation frequency ≥2% were removed， thereafter， the macro-evaluation tool for DS animal model was preliminarily constructed. ResultsSpirit and body state， autonomic activity state， body surface characteristics， diet， urination and defecation， tongue manifestation， and motor behavior assessment were constructed as the seven dimensions in the evaluation of DS animal model. A total of 348 papers about animal experiments were included and analyzed， resulting in a saturated pool of 72 items， which was refined to 38 core items of DS animal models. Factor analysis obtained 16 common factors， which were further clustered into two categories， named dampness transforming from heat syndrome and dampness transforming from cold syndrome. The expert importance scoring showed that the Kendall harmony coefficient was 0.359 （P＜0.05） indicating a high level of agreement， coordination and reliability among the experts. Notably， 50% or more of the experts considered the items thick and greasy tongue coating， unclean perianal area， loose stools， lethargy， unformed stools， and listless expression as very important. The median scores for all items were 2.04（1.73， 2.37）， with a coefficient of variation ranging from 19.73% to 53.38%. After expert evaluation， the macro-evaluation tool for DS animal model in TCM with 33 items and corresponding criteria for assessing the formation of DS models was finally contructed. ConclusionThe Macro-evaluation tool for DS animal model in TCM is highly scientific， credible， and operable， and can be utilized in DS animal experiments after its characteristics are actually evaluated.

Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal hematopoietic stem cell disease caused by abnormal expression of glycosylphosphatidylinositol (GPI) on the cell membrane due to mutations in the phosphatidylinositol glycan class A(PIGA) gene. It is commonly characterized by intravascular hemolysis, repeated thrombosis, and bone marrow failure, as well as multiple systemic involvement symptoms such as renal dysfunction, pulmonary hypertension, swallowing difficulties, chest pain, abdominal pain, and erectile dysfunction. Due to the rarity of PNH and its strong heterogeneity in clinical manifestations, multidisciplinary collaboration is often required for diagnosis and treatment. Peking Union Medical College Hospital, relying on the rare disease diagnosis and treatment platform, has invited multidisciplinary clinical experts to form a unified opinion on the diagnosis and treatment of PNH, and formulated the Expert Consensus of Multidisciplinary Diagnosis and Treatment for Paroxysmal Nocturnal Hemoglobinuria (2024), with the hope of promoting the standardization of PNH diagnosis and treatment.