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.

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve

The neurophysiological mechanisms by which exercise improves cognitive function have not been fully elucidated. A comprehensive and systematic review of current domestic and international neurophysiological evidence on exercise improving cognitive function was conducted from multiple perspectives. At the molecular level, exercise promotes nerve cell regeneration and synaptogenesis and maintains cellular development and homeostasis through the modulation of a variety of neurotrophic factors, receptor activity, neuropeptides, and monoamine neurotransmitters, and by decreasing the levels of inflammatory factors and other modulators of neuroplasticity. At the cellular level, exercise enhances neural activation and control and improves brain structure through nerve regeneration, synaptogenesis, improved glial cell function and angiogenesis. At the structural level of the brain, exercise promotes cognitive function by affecting white and gray matter volumes, neural activation and brain region connectivity, as well as increasing cerebral blood flow. This review elucidates how exercise improves the internal environment at the molecular level, promotes cell regeneration and functional differentiation, and enhances the brain structure and neural efficiency. It provides a comprehensive, multi-dimensional explanation of the neurophysiological mechanisms through which exercise promotes cognitive function.
Animals ; Humans ; Brain/physiology* ; Cognition/physiology* ; Exercise/physiology* ; Nerve Regeneration/physiology* ; Neuronal Plasticity/physiology*

BACKGROUND: Non-invasive computed tomography angiography (CTA)-based fractional flow reserve (CT-FFR) could become a gatekeeper to invasive coronary angiography. Deep learning (DL)-based CT-FFR has shown promise when compared to invasive FFR. To evaluate the performance of a DL-based CT-FFR technique, DeepVessel FFR (DVFFR). METHODS: This retrospective study was designed for iScheMia Assessment based on a Retrospective, single-center Trial of CT-FFR (SMART). Patients suspected of stable coronary artery disease (CAD) and undergoing both CTA and invasive FFR examinations were consecutively selected from the Beijing Anzhen Hospital between January 1, 2016 to December 30, 2018. FFR obtained during invasive coronary angiography was used as the reference standard. DVFFR was calculated blindly using a DL-based CT-FFR approach that utilized the complete tree structure of the coronary arteries. RESULTS: Three hundred and thirty nine patients (60.5 ±10.0 years and 209 men) and 414 vessels with direct invasive FFR were included in the analysis. At per-vessel level, sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of DVFFR were 94.7%, 88.6%, 90.8%, 82.7%, and 96.7%, respectively. The area under the receiver operating characteristics curve (AUC) was 0.95 for DVFFR and 0.56 for CTA-based assessment with a significant difference (P < 0.0001). At patient level, sensitivity, specificity, accuracy, PPV and NPV of DVFFR were 93.8%, 88.0%, 90.3%, 83.0%, and 95.8%, respectively. The computation for DVFFR was fast with the average time of 22.5 ± 1.9 s. CONCLUSIONS The results demonstrate that DVFFR was able to evaluate lesion hemodynamic significance accurately and effectively with improved diagnostic performance over CTA alone. Coronary artery disease (CAD) is a critical disease in which coronary artery luminal narrowing may result in myocardial ischemia. Early and effective assessment of myocardial ischemia is essential for optimal treatment planning so as to improve the quality of life and reduce medical costs.

OBJECTIVE: To investigate the relationship between physical activity and genetic risk and their combined effects on the risk of developing chronic obstructive pulmonary disease. METHODS: This prospective cohort study included 318,085 biobank participants from the UK. Physical activity was assessed using the short form of the International Physical Activity Questionnaire. The participants were stratified into low-, intermediate-, and high-genetic-risk groups based on their polygenic risk scores. Multivariate Cox regression models and multiplicative interaction analyses were used. RESULTS: During a median follow-up period of 13 years, 9,209 participants were diagnosed with chronic obstructive pulmonary disease. For low genetic risk, compared to low physical activity, the hazard ratios ( HRs) for moderate and high physical activity were 0.853 (95% confidence interval [ CI]: 0.748-0.972) and 0.831 (95% CI: 0.727-0.950), respectively. For intermediate genetic risk, the HRs were 0.829 (95% CI: 0.758-0.905) and 0.835 (95% CI: 0.764-0.914), respectively. For participants with high genetic risk, the HRs were 0.809 (95% CI: 0.746-0.877) and 0.818 (95% CI: 0.754-0.888), respectively. A significant interaction was observed between genetic risk and physical activity. CONCLUSION Moderate or high levels of physical activity were associated with a lower risk of developing chronic obstructive pulmonary disease across all genetic risk groups, highlighting the need to tailor activity interventions for genetically susceptible individuals.
Humans ; Pulmonary Disease, Chronic Obstructive/epidemiology* ; Exercise ; Male ; Female ; Middle Aged ; Prospective Studies ; Aged ; Genetic Predisposition to Disease ; Risk Factors ; United Kingdom/epidemiology* ; Incidence ; Adult

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.

Objective To analyze the characteristics of adult anomalous aortic origin of coronary artery(AAOCA)and the causes of missed diagnosis by transthoracic echocardiography(TTE)so as to facilitate TTE in diagnosing adult AAOCA.Methods A total of 37 adult patients with AAOCA diagnosed by non-invasive coronary CT angiography(CCTA)and/or invasive coronary angiography(ICA)were selected as research samples at some hospital from January 2019 to December 2022,and their clinical symptoms and the findings of 12-lead electrocardiogram,cardiac enzymes and TTE were summarized;the patients were typed according to the site of origin of coronary artery anomalies,and the causes for the missed diagnosis of TTE were eplored.Chi-square test was used to compare the differences in TTE missed diagnoses.Results Of the 37 patients,31 ones had no or only mild symptoms;most ones had negative results in terms of 12-lead electrocardiography,cardiac enzymes,changes in the size of the cardiac chambers,segmental ventricular wall motion abnormalities and left ventricular systolic function.The patients with anomalous origin of the right coronary artery from left sinus(ARCA-L)gained the largest proportion of 59.45％(22/37);21 patients were diagnosed with anomalous origin of coronary artery arising from the opposite sinus(ACAOS)in the two examinations of TTE,of whom there were 19 cases of ARCA-L,and the detection rate of ACAOS by TTE was 87.5％;all the 13 patients origins in branches and high-grade openings were missed by TTE.The detection rate of ACAOS by TTE was significantly higher than that of coronary artery anomalies originating in branches and in high openings,and the difference was statistically significant(21/24 vs 0/13,P＜0.001).Conclusion Most adult AAOCA patients lack specificity in symptoms and related examination results.TTE has a high detection rate of ACAOS,while it is easy to miss the diagnosis of coronary artery anomalies originating from branches and high openings.Ultrasonographers have to identify false negative AAOCA by multi-section and multi-angle scanning and color Doppler flow imaging in order to reduce the rate of missed diagnosis.[Chinese Medical Equipment Journal,2024,45(1):71-75]

ObjectiveMolecular docking plays a critical role in predicting binding modes and affinity between molecules, serving as a pivotal method in structural biology and computer-aided drug design research. Our research team has recently developed a novel template-based docking method called FitDock, which outperforms commonly used molecular docking methods in terms of accuracy and speed, particularly when approximate protein-ligand templates are available. To enhance the accessibility of the FitDock method and promote its broader application in the field of molecular simulation, the development of a graphical software tool is imperative. MethodsUtilizing Python-based graphical programming, we have created FitDockApp, a plugin software for the molecular visualization software PyMOL. ResultsFitDockApp enables template-based molecular docking and ligand structure alignment through an interactive graphical interface, providing real-time visualization of predicted three-dimensional structures. It also offers the convenience of uploading docking files to a laboratory server to obtain the optimal template. Additionally, FitDockApp includes batch docking functionality. ConclusionFitDockApp simplifies the docking process through its user-friendly interface and provides robust functionality to assist researchers in obtaining precise docking results. FitDockApp is a free software compatible with both Windows and Linux systems and can be downloaded from http://cao.labshare.cn/fitdock/.

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.

This study was aimed at exploring the epidemiological characteristics of plague,and the evolutionary relation-ships among the isolated plague strains in the Yunnan border area,to provide clues for further studying epidemic causes and ep-idemiological patterns.Plague epidemic data in the border area during the second epidemic period(1982-2007)were collected and analyzed with descriptive epidemiological methods.Whole genome sequences of 262 strains of Yersinia pestis in the border area were obtained for phylogenetic analysis.Plague outbreaks occurred in 17 counties(cities)among 25 border counties(cit-ies);a total of 552 epidemic foci and 123 human cases were identified.The 1.ORI2,1.ORI3,1.IN3,2.ANT and 2.MED geno-types were identified among Yersinia pestis isolated from the Yunnan border area,among which the 1.ORI2 population was dominant.A total of 258 strains of Yersinia pestis from the 1.OR12 population belonged to four subclusters.The Myanmar and Vietnam clade was embedded within the Yunnan clade in the overall phylogeny.The above results indicated that during the sec-ond period of the epidemic,the intensity of plague epidemics in Yunnan's border areas was high,showing a trend of devel-opment from west to south and east.Our findings indicated a risk of cross-border transmission of plague between Yunnan and neighboring countries;therefore,the surveillance,pre-vention,and control of plague in border areas should be strengthened.