This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

BACKGROUND AND OBJECTIVE: Hypertension (HT) and atrial fibrillation (AF) are highly prevalent cardiovascular conditions that frequently coexist. Coronary artery disease (CAD) is a major global cause of mortality. The co-occurrence of HT, AF, and CAD presents significant management challenges. This study aims to explore the clinical characteristics and risk factors associated with CAD in patients with HT and persistent AF (HT-AF). METHODS: In this retrospective cross-sectional study, data were collected from 384 hospitalized HT-AF patients at the People's Liberation Army General Hospital between January 2010 and December 2019. CAD diagnosis was confirmed by coronary angiography or computed tomography angiography. Clinical characteristics and comorbidities were compared between patients with and without CAD. Multivariate logistic regression analyses were performed to identify independent risk factors associated with CAD development. RESULTS: The prevalence of CAD among HT-AF patients was 66.41% (255/384). Cardiovascular complications, particularly heart failure (44.7% vs 25.6%, P < 0.05), were significantly more prevalent in the CAD group than in the non-CAD group. Only age was identified as an independent risk factor for CAD (adjusted OR: 1.047; 95% CI: 1.022-1.073; P = 0.000). Of all HT-AF patients, 54.7% had a CHA₂DS₂-VASc score of ≥4, indicating high stroke risk. There was a slightly higher anticoagulant usage rate in the CAD group than those without CAD (8.6% vs 4.7%, P = 0.157), and the overall anticoagulant usage remained low. CONCLUSION: There is a high prevalence of CAD among hospitalized HT-AF patients, among whom age is the sole independent risk factor for CAD. Despite a high stroke risk, the utilization of oral anticoagulants is alarmingly low.
Humans ; Atrial Fibrillation/epidemiology* ; Coronary Artery Disease/etiology* ; Hypertension/epidemiology* ; Male ; Female ; Risk Factors ; Middle Aged ; Retrospective Studies ; Cross-Sectional Studies ; Aged ; Prevalence

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective:To determine whether the Rb1 of ginsenoside has protective effects on PA induced oxidative stress in endothelial cells.Methods:Established a model of palmitic acid-induced oxidative stress injury in human umbilical vein endothelial cells(HUVECs).Using MTT assay,flow cytometry,fluorescent probe staining,and Western blot analysis to detect whether Rb1 of ginsenoside has effects on the cell viability,apoptosis rate,ROS and NO production,mitochondrial membrane potential,and the expression levels of related proteins.Results:MTT assay and flow cytometry revealed that ginsenoside Rb1 can reduce PA-induced apoptosis in HUVECs(P＜0.05).The mechanism may be related to the following two points:(1)reducing ROS production and increasing NO levels,thereby enhancing the antioxidant capacity of HUVECs;(2)regulating the expression of Bcl-2 family proteins,increasing the BCL-2/Bax ratio(P＜0.05),modulating mitochondrial membrane permeability,reducing cytochrome C release(P＜0.001),and decreasing Caspase protein activation(P＜0.01),thereby attenuating PA-induced apoptosis.Conclusion:After the stimulation with PA,ROS production in human umbilical vein endothelial cells increased while NO content and cell activity decreased,oxidative stress induced apoptosis in cells.By regulating the production of ROS and NOx stabilizing the mitochondrial transmembrane potential,reducing the leakage of cytochrome C,Ginsenoside Rb1 can reduce HUVECs apoptosis induced by PA.

Objective:To determine whether the Rb1 of ginsenoside has protective effects on PA induced oxidative stress in endothelial cells.Methods:Established a model of palmitic acid-induced oxidative stress injury in human umbilical vein endothelial cells(HUVECs).Using MTT assay,flow cytometry,fluorescent probe staining,and Western blot analysis to detect whether Rb1 of ginsenoside has effects on the cell viability,apoptosis rate,ROS and NO production,mitochondrial membrane potential,and the expression levels of related proteins.Results:MTT assay and flow cytometry revealed that ginsenoside Rb1 can reduce PA-induced apoptosis in HUVECs(P＜0.05).The mechanism may be related to the following two points:(1)reducing ROS production and increasing NO levels,thereby enhancing the antioxidant capacity of HUVECs;(2)regulating the expression of Bcl-2 family proteins,increasing the BCL-2/Bax ratio(P＜0.05),modulating mitochondrial membrane permeability,reducing cytochrome C release(P＜0.001),and decreasing Caspase protein activation(P＜0.01),thereby attenuating PA-induced apoptosis.Conclusion:After the stimulation with PA,ROS production in human umbilical vein endothelial cells increased while NO content and cell activity decreased,oxidative stress induced apoptosis in cells.By regulating the production of ROS and NOx stabilizing the mitochondrial transmembrane potential,reducing the leakage of cytochrome C,Ginsenoside Rb1 can reduce HUVECs apoptosis induced by PA.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objectives To explore the feasibility of temporary veno-venous extracorporeal membrane oxygenation(VV-ECMO)technology for early on-site treatment,through establishing an animal model of severe blast lung injury in goats by free-field chemical explosion experiments in high-altitude regions.Methods A total of 16 adult goats were selected,and divided into the control group and the treatment group according to the random number table method,with 8 goats in each group.A model of severe blast lung injury was established at an altitude of 4 600 meters above sea level,then the goats in the control group were given respiratory support and the goats in the treatment group were given temporary VV-ECMO treatment.The survival status of the goats 15 minutes after injury was recorded,the vital signs[including body temperature,respiration rate,heart rate,and mean arterial pressure(MAP)]and arterial blood gas analysis indicators[including pH,arterial partial pressure of oxygen(PO2),arterial partial pressure of carbon dioxide(PCO2),oxygen saturation(SaO2),lactate(LAC),calcium(Ca2+),hematocrit(HCT),and hemoglobin(Hb)]before injury and 1 hour,2 hours,3 hours after injury were compared in the two groups.The post-mortem examination was performed on all dead goats and sacrificed goats after treatment,the severity of lung injury was assessed by organ injury scaling(OIS),and the lung injury score was evaluated by abbreviated injury scale(AIS).The wet-to-dry weight ratio(W/D)and lung coefficient were calculated.Results Within 15 minutes after the explosion,4 goats in the control group died and 4 goats survived;and 5 goats in the treatment group died and 3 goats survived.There was no statistically significant difference in the body temperature,respiration rate,heart rate,or MAP before and after injury between the two groups(P>0.05).The PaO2 and SaO2 1 hour,2 hours,and 3 hours after injury in the treatment group were superior than those in the control group(P<0.05),the Ca2+ 2 hours after injury was significantly higher than that in the control group(P<0.05),and there was no statistically significant difference in the pH,PCO2,LAC,HCT or Hb at different time points after injury between the two groups(P>0.05).There was no statistically significant difference in the OIS,AIS or lung coefficient between the two groups(P>0.05),but the W/D of the lung tissue in the control group was lower than that in the treatment group(P<0.05).Conclusion We have established a novel,feasible,and stable treatment effect temporary VV-ECMO animal treatment strategy for the first time in the high-altitude regions,which can provide animal experiment evidence for the early on-site VV-ECMO treatment of severe blast lung injury in high-altitude regions.

OBJECTIVE To provide a detailed report and interpretation of the method and results for determining the weights of the technical indicators from the “multi-dimensional and multi-criteria comprehensive evaluation index system （first edition）” stated in Guideline for Multi-dimensional and Multi-criteria Comprehensive Evaluation of Chinese Patent Medicine. METHODS Normalization calculations were performed on the comprehensive weight values calculated by the analytic hierarchy process and expert weighting method to obtain the objective weights of the indicators. RESULTS The weight results of the six primary dimensions in the current comprehensive evaluation indicator system of Chinese patent medicine showed effectiveness dimension＞ safety dimension＞standard dimension＞application dimension＞scientific dimension＞economic dimension， with weight values of 0.281 0， 0.268 5， 0.195 8， 0.107 3， 0.096 1 and 0.051 3 respectively， consistent with the results of most researches currently. CONCLUSIONS The process of weight determination in this indicator system is scientifically reasonable， with clear methods and clear interpretations， and is worthy of further optimization and widespread application.

BACKGROUND:The traditional fixation method for femoral neck fractures is three hollow screws inverted triangle fixation,and the optimal fixation method for femoral neck fractures that have not achieved anatomical reduction is inconclusive. OBJECTIVE:To compare the biomechanical properties of cannulated screws internal fixation for sub-capitated femoral neck fracture with different reduction qualities based on finite element analysis. METHODS:The three-dimensional digital model was reconstructed using CT data of the proximal femur from a healthy male volunteer.The femur was modeled to sub-capitated femoral neck fractures.Fracture models were divided into anatomical reduction group,coxa vara group,and coxa valgus group.All fracture model groups were transferred using the standard group,screw depression group,and screw elevation group.A vertical downward stress of 1 400 N was applied to the femoral head at the top of the acetabulum.The displacement and stress distribution of the femur and internal fixator under different fixation methods were observed,and the maximum stress and displacement of the femur and fixator were compared. RESULTS AND CONCLUSION:(1)For anatomical reduction femoral neck fracture,the peak stress of fixation in the standard group,screw depression group and screw elevation group was 41.35,31.27 and 43.32 MPa,respectively.The maximum peak stress of the femur was found on the screw elevation group(28.58 MPa),and the standard group had the maximum peak displacement.(2)During hip varus,the stresses in the three subgroups were relatively dispersed and even.The peak stress of the femur in the standard group was the smallest,but the peak displacement was the largest.The stability of fixation might be poor.The peak displacement of the femur in the screw depression group was the smallest.(3)In the hip valgus,obvious screw stress concentration appeared in the screw depression group,and the peak displacement was the largest among the three subgroups,and an in-out-in phenomenon appeared.The peak stress of the screws in the screw elevation group was the largest among the three subgroups,but the peak displacement was the smallest.(4)It is concluded that for sub-capitated femoral neck fractures that are completely anatomically reduced,it is recommended to use standard inverted triangular nails for fixation.When the hip varus and hip valgus occur within the allowable range of the reduction standard,it is recommended to use the inverted triangle screw to fix it by rotating the corresponding angle in the same direction as the hip varus or valgus.

Lipopolysaccharides (LPS) are major outer membrane components of Gram-negative bacteria. Unlike most Gram-negative bacteria, Acinetobacter baumannii can still survive and acquire polymyxin resistance after complete loss of LPS. Previous studies of LPS-deficient Acinetobacter baumannii mostly focused on LPS-deficient strains induced by polymyxin, whose background was complex and unstable. To investigate LPS loss-mediated polymyxin resistant-Acinetobacter baumannii, this study constructed a stable and clear background LPS-deficient strain by knocking out lpxC gene in Acinetobacter baumannii ATCC 19606 with CIRSPR/Cas9, and then studied the phenotypic changes of the lpxC-deficient strain including morphology, growth rate, antibiotic susceptibility, virulence, membrane permeability, and membrane potential. Animal experiments were approved by the Animal Care and Welfare Committee Institute of Medicinal Biotechnology, CAMS and PUMC (approval number: IMB-20240119D₉). The results indicated that the lpxC gene of Acinetobacter baumannii ATCC 19606 was successfully knocked out. After losing the lpxC, the strain underwent the morphological change from rod-shaped to spherical. Furthermore, it leads to reduced growth rate, enhanced membrane permeability, decreased membrane potential, lower virulence, and increased antibiotic susceptibility to β-lactams, quinolones, aminoglycosides, macrolides, glycopeptides. The lpxC deletion results in significant changes in membrane homeostasis and adaptability of Acinetobacter baumannii. Understanding the phenotypic changes of colistin-resistant Acinetobacter baumannii mediated by LPS loss is useful for exploring the resistance mechanism of Acinetobacter baumannii and developing new therapeutic strategies.