Eight compounds were isolated and purified from the ethyl acetate part of 70% acetone extract of Rehmannia glutinosa by various chromatographic techniques such as silica gel, MCI gel CHP-20, ODS, Toyopearl HW-40C, combined with TLC and semi-preparative HPLC. Their structures were elucidated by modern spectroscopy techniques (NMR, MS, UV, IR), and identified as neomartynoside A (1), osmanthuside B₆ (2), martynoside (3), isomartynoside (4), (E)-p-hydroxycinnamic acid (5), caffeic acid (6), ferulic acid (7), and methyl caffeate (8). Compound 1 is a new phenylethanol glycoside, which was identified as neomartynoside A. Compound 2 was isolated from Rehmannia glutinosa for the first time. In addition, compounds 2, 6 and 7 significantly increased relative glucose consumption, showing potential hypoglycemic activity.

Objective To construct a "disease-syndrome combination" mathematical representation model for pulmonary nodules based on oral microbiome data, utilizing a multimodal data algorithm framework centered on dynamic systems theory. Furthermore, to compare predictive models under various algorithmic frameworks and validate the efficacy of the optimal model in predicting the presence of pulmonary nodules. Methods A total of 213 subjects were prospectively enrolled from July 2022 to March 2023 at the Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, and the Chengdu Integrated Traditional Chinese and Western Medicine Hospital. This cohort included 173 patients with pulmonary nodules and 40 healthy subjects. A novel multimodal data algorithm framework centered on dynamic systems theory, termed VAEGANTF (Variational Auto Encoder-Generative Adversarial Network-Transformer), was proposed. Subsequently, based on a multi-dimensional integrated dataset of “clinical features-syndrome elements-microorganisms”, all subjects were divided into training (70%) and testing (30%) sets for model construction and efficacy testing, respectively. Using pulmonary nodules as dependent variables, and combining candidate markers such as clinical features, lesion location, disease nature, and microbial genera, the independent variables were screened based on variable importance ranking after identifying and addressing multicollinearity. Missing values were then imputed, and data were standardized. Eight machine learning algorithms were then employed to construct pulmonary nodule risk prediction models: random forest, least absolute shrinkage and selection operator (LASSO) regression, support vector machine, multilayer perceptron, eXtreme Gradient Boosting (XGBoost), VAE-ViT (Vision Transformer), GAN-ViT, and VAEGANTF. K-fold cross-validation was used for model parameter tuning and optimization. The efficacy of the eight predictive models was evaluated using confusion matrices and receiver operating characteristic (ROC) curves, and the optimal model was selected. Finally, goodness-of-fit testing and decision curve analysis (DCA) were performed to evaluate the optimal model. Results There were no statistically significant differences between the two groups in demographic characteristics such as age and sex. The 213 subjects were randomly divided into training and testing sets (7 : 3), and prediction models were constructed using the eight machine learning algorithms. After excluding potential problems such as multicollinearity, a total of 301 clinical feature information, syndrome elements, and microbial genera markers were included for model construction. The area under the curve (AUC) values of the random forest, LASSO regression, support vector machine, multilayer perceptron, and VAE-ViT models did not reach 0.85, indicating poor efficacy. The AUC values of the XGBoost, GAN-ViT, and VAEGANTF models all reached above 0.85, with the VAEGANTF model exhibiting the highest AUC value (AUC=0.923). Goodness-of-fit testing indicated good calibration ability of the VAEGANTF model, and decision curve analysis showed a high degree of clinical benefit. The nomogram results showed that age, sex, heart, lung, Qixu, blood stasis, dampness, Porphyromonas genus, Granulicatella genus, Neisseria genus, Haemophilus genus, and Actinobacillus genus could be used as predictors. Conclusion The “disease-syndrome combination” risk prediction model for pulmonary nodules based on the VAEGANTF algorithm framework, which incorporates multi-dimensional data features of “clinical features-syndrome elements-microorganisms”, demonstrates better performance compared to other machine learning algorithms and has certain reference value for early non-invasive diagnosis of pulmonary nodules.

Pre-admission is a critical initiative to optimize medical service processes and alleviate the challenge of "difficult access to healthcare. "However, there is currently a lack of standardized protocols for pre-admission procedures. This study aims to systematically analyze key nodes and risk factors in pre-admission process design and propose optimization strategies, providing a foundation for policy formulation and hospital practices. By constructing a "forward-reverse" dual-process model of pre-admission and identifying risk points based on stakeholder theory (patients, hospitals, healthcare administration, and insurance), the study reveals that while pre-admission can reduce the average length of stay, improve bed turnover rates, and enhance patient satisfaction, it also presents risks such as cross-period financial settlement, challenges in insurance policy adaptability, demands for information system integration, and the need for defining medical safety boundaries. To optimize the pre-admission process and mitigate these risks, this study explores framework improvements in areas including eligibility criteria, mode selection, cost settlement, transition between pre-admission and inpatient status, and cancellation of pre-admission, offering practical guidance for public hospitals. The authors argue that pre-admission requires tripartite collaboration among hospitals, insurers, and healthcare administrations: hospitals should establish top-level design, continuously refine processes, and implement dynamic risk assessment mechanisms; insurance providers should support cross-period settlement policies; and healthcare administrations should issue guiding policies or standardized protocols. Through multi-department coordination and collaborative efforts, the optimization and innovation of pre-admission processes can be advanced, ultimately delivering more efficient and convenient healthcare experiences for patients.

With the growing emphasis on maternal and child oral health, the significance of managing oral health across preconception, pregnancy, and infancy stages has become increasingly apparent. Oral health challenges extend beyond affecting maternal well-being, exerting profound influences on fetal and neonatal oral development as well as immune system maturation. This expert consensus paper, developed using a modified Delphi method, reviews current research and provides recommendations on maternal and child oral health management. It underscores the critical role of comprehensive oral assessments prior to conception, diligent oral health management throughout pregnancy, and meticulous oral hygiene practices during infancy. Effective strategies should be seamlessly integrated across the life course, encompassing preconception oral assessments, systematic dental care during pregnancy, and routine infant oral hygiene. Collaborative efforts among pediatric dentists, maternal and child health workers, and obstetricians are crucial to improving outcomes and fostering clinical research, contributing to evidence-based health management strategies.
Humans ; Pregnancy ; Female ; Infant ; Consensus ; Mouth Diseases/therapy* ; Pregnancy Complications/therapy* ; Oral Health ; Infant, Newborn ; Delphi Technique ; Oral Hygiene

Drug development encompasses multiple processes, wherein protein subcellular localization is essential. It promotes target identification, treatment development, and the design of drug delivery systems. In this research, a deep learning framework called LocPro is presented for predicting protein subcellular localization. Specifically, LocPro is unique in (a) combining protein representations from the pre-trained large language model (LLM) ESM2 and the expert-driven tool PROFEAT, (b) implementing a hybrid deep neural network architecture that integrates convolutional neural network (CNN), fully connected (FC) layer, and bidirectional long short-term memory (BiLSTM) blocks, and (c) developing a multi-label framework for predicting protein subcellular localization at multiple granularity levels. Additionally, a dataset was curated and divided using a homology-based strategy for training and validation. Comparative analyses show that LocPro outperforms existing methods in sequence-based multi-label protein subcellular localization prediction. The practical utility of this framework is further demonstrated through case studies on drug target subcellular localization. All in all, LocPro serves as a valuable complement to existing protein localization prediction tools. The web server is freely accessible at https://idrblab.org/LocPro/.

Macroporous adsorption resin, MCI, Toyopearl HW-40C and silica gel column chromatography combined with the semi-preparative HPLC were used to isolate and purify the water extract of Cornus officinalis. And the structures of compounds were identified by HRESIMS, NMR, IR, UV and ECD. A total of twelve compounds were isolated from the fruits of Cornus officinalis. They were identified as neolignan B (1), 2,3-dihydro-7-methoxy-2-(4′-hydroxy-3′-methoxyphenyl)-3a-O-β-D-xylopyranosyloxymethyl-5-benzofuranpropanol (2), cornucadinoside A (3), 3,4-dihydroxyacetophenone (4), n-butyl gallate (5), 3-hydroxybenzoic acid (6), n-butyl quininate (7), 5-hydroxymaltol (8), 2-furolic acid (9), 5-hydroxymethylfurfural (10), 5-(methoxycarbonyl)-2-pyrrolidone (11), and dimethyl malate (12). Compound 1 is a new biphenyl lignan, named as neolignan B. Compounds 2, 4, 5, 7-9 and 11 were isolated from Cornus officinalis for the first time.

Eleven compounds were isolated from Eucommia ulmoides by silica gel, Sephadex LH-20, HW-40C column chromatography and semi-preparative HPLC. Their structures were identified by modern spectroscopic methods as neoeucommiate A (1), (7S,8R)-dihydrodehydrodiconiferyl alcohol (2), urolignoside (3), ficusal (4), tiruneesiin (5), glochidioboside (6), forsythialansides B (7), ecdysanol B (8), (+)-syringaresinol-4-O-β-D-glucopyranoside (9), (+)-pinoresinol 4-O-[6ʹʹ-O-vanilloyl]-β-D-glucopyranoside (10), samsesquinoside (11). Compound 1 is a new compound, compounds 3-7, 10 and 11 were isolated from Eucommia ulmoides for the first time.

Objective To investigate the toxicokinetic differences of 3,4-methylenedioxy-N-methylamphetamine(MDMA)and its metabolite 4,5-methylene dioxy amphetamine(MDA)in rats af-ter single and continuous administration of MDMA,providing reference data for the forensic identifica-tion of MDMA.Methods A total of 24 rats in the single administration group were randomly divided into 5,10 and 20 mg/kg experimental groups and the control group,with 6 rats in each group.The ex-perimental group was given intraperitoneal injection of MDMA,and the control group was given intraperi-toneal injection of the same volume of normal saline as the experimental group.The amount of 0.5 mL blood was collected from the medial canthus 5 min,30 min,1 h,1.5 h,2 h,4 h,6 h,8 h,10 h,12 h after administration.In the continuous administration group,24 rats were randomly divided into the experi-mental group(18 rats)and the control group(6 rats).The experimental group was given MDMA 7 d by continuous intraperitoneal injection in increments of 5,7,9,11,13,15,17 mg/kg per day,respectively,while the control group was given the same volume of normal saline as the experimental group by in-traperitoneal injection.On the eighth day,the experimental rats were randomly divided into 5,10 and 20 mg/kg dose groups,with 6 rats in each group.MDMA was injected intraperitoneally,and the con-trol group was injected intraperitoneally with the same volume of normal saline as the experimental group.On the eighth day,0.5 mL of blood was taken from the medial canthus 5 min,30 min,1 h,1.5 h,2 h,4 h,6 h,8 h,10 h,12 h after administration.Liquid chromatography-triple quadrupole tandem mass spectrometry was used to detect MDMA and MDA levels,and statistical software was employed for data analysis.Results In the single-administration group,peak concentrations of MDMA and MDA were reached at 5 min and 1 h after administration,respectively,with the largest detection time limit of 12 h.In the continuous administration group,peak concentrations were reached at 30 min and 1.5 h af-ter administration,respectively,with the largest detection time limit of 10 h.Nonlinear fitting equations for the concentration ratio of MDMA and MDA in plasma and administration time in the single-administration group and continuous administration group were as follows:T=10.362C-1.183,R2=0.974 6;T=7.397 3C-0.694,R2=0.961 5(T:injection time;C:concentration ratio of MDMA to MDA in plasma).Conclusions The toxicokinetic data of MDMA and its metabolite MDA in rats,obtained through single and continuous administration,including peak concentration,peak time,detection time limit,and the relationship between concentration ratio and administration time,provide a theoretical and data foundation for relevant forensic identification.

Talents are the main force for the development of traditional Chinese medicine（TCM）， and the construction of TCM talents and the reformation of talent evaluation system are essential to promote the inheritance and innovation of TCM. At present， we are still exploring and developing in the fields of the formulation， implementation and evaluation indicators of TCM talent evaluation system. However， there are shortcomings and difficulties. For instance， insufficient stratification in the evaluation， excessive emphasis on the quantity of achievements， neglecting the quality of the achievements and the actual contribution， imperfect assessment indicators， and the weak characteristics of TCM. Therefore， national ministries and commissions have jointly issued a document requesting to break the four only and set a new standard， in order to promote the construction of a scientific and technological talent evaluation system oriented by innovation value， ability and contribution. For the evaluation of TCM clinical talents， China Association for Science and Technology commissioned China Association of Chinese Medicine to build the China Clinical Cases Library of TCM（CCCL-TCM）， which aims at collecting the most authoritative and representative TCM clinical cases and exploring the advantages of applying clinical cases as masterpiece of achievement in TCM clinical talents evaluation. CCCL-TCM can promote the construction of a talent evaluation system that is more in line with the development characteristics of TCM industry， and to carry out relevant pilot in TCM colleges and institutions across the country in order to promote the reformation of TCM talent evaluation system.

BACKGROUND:Kinesio taping has been widely used as a means of sports protection,but its role as a means to correct abnormal biomechanical changes of the lower limbs during side-step cutting remains unclear. OBJECTIVE:To analyze and compare the changes in lower limb kinematics and dynamics when the subjects complete the side-step cutting of the knee joint under the conditions of kinesio taping,placebo taping and blank control. METHODS:Thirty-nine male college students majoring in basketball were recruited as subjects.Each subject was tested with kinesio taping,placebo taping or no taping.The mechanical correction method was used to patch the dominant knee joint of each subject.The run-up speed of 4.5-5.5 m/s was selected to complete the 45° side-step cutting motion,and the kinematics and kinetics data were collected synchronously by the three-dimensional dynamic capture system and the force measuring platform.The kinematics and kinetics parameters at the moment of initial touchdown and peak ground reaction force were selected for data analysis.SPSS 27.0 software was used for statistical analysis of the test data. RESULTS AND CONCLUSION:Kinematic indexes:compared with no taping and placebo taping,the hip abduction and knee valgus angles at the initial touchdown moment were significantly decreased when kinesio taping was used(P<0.05);at the moment of peak lateral ground reaction force,the angles of hip abduction,knee valgus and ankle plantar flexion decreased significantly(P<0.05),and the knee flexion angle was significantly increased(P<0.05).Kinetic indexes:Compared with no taping,both kinesio taping and placebo taping significantly reduced hip abduction and external rotation torque,knee valgus and external rotation torque at the moment of initial touchdown(P<0.05),and significantly reduced peak vertical ground reaction force and peak horizontal backward ground reaction force(P<0.05);in addition,kinesio taping significantly reduced peak lateral ground reaction force compared with no taping and placebo taping(P<0.05).These results indicate that kinesio taping of the knee joint may improve some kinematic and kinetic indexes associated with lower limb injury risk factors during the completion of the side-step cutting in basketball specialized college students to some extent,and may have a positive effect on the prevention of injury during the side-step cutting.In addition,the trends in the effects of placebo taping and kinesio taping on the knee joint are more consistent in terms of changes in some indexes,suggesting that there may be a placebo effect on the mechanism of action of kinesio taping.