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 explore the safety and efficacy of high-dose etoposide (VP-16) combined with recombinant human granulocyte colony-stimulating factor (rhG-CSF) as salvage mobilization for peripheral blood stem cells (PBSC) in newly diagnosed multiple myeloma (NDMM) patients. METHODS: From April 2021 to May 2023, eight NDMM patients who had failed to yield sufficient PBSC during initial mobilization with high-dose cyclophosphamide (CTX) combined with rhG-CSF underwent salvage mobilization with 1.2 g/m2 etoposide combined with rhG-CSF 10 μg/(kg·d). The effects and adverse reactions of initial mobilization and salvage mobilization were analyzed. RESULTS: For salvage mobilization and initial mobilization, the numbers of PBSC collections were 16 and 18, respectively. The mean value of total collected CD34⁺ cells were (11.90±5.75)×10⁶/kg and (1.67±0.75)×10⁶/kg (P =0.0010) in salvage mobilization group and initial mobilization group, respectively. The proportion of patients with a total collection of CD34⁺ cell count≥2×10⁶/kg were 100% and 37.5% (P =0.0625), and the proportion of patients with a total collection of CD34⁺ cell count≥5×10⁶/kg were 87.5% and 0% (P =0.0156) in salvage mobilization group and initial mobilization group, respectively. For five patients who underwent high-dose CTX initial mobilization but had a total CD34⁺ cell count < 2×10⁶/kg, successful collection was achieved through salvage mobilization with high-dose VP-16. Salvage mobilization with high-dose VP-16 was scheduled 2-3 weeks after failure of CTX mobilization. Adverse reactions of high-dose VP-16 mobilization did not increase compared to the initial mobilization with high-dose CTX. CONCLUSION As a salvage mobilization regimen, VP-16 1.2 g/m² combined with rhG-CSF is safe and highly effective in NDMM patients who failed to initial mobilization with high-dose CTX combined with rhG-CSF.
Humans ; Multiple Myeloma/therapy* ; Etoposide/therapeutic use* ; Hematopoietic Stem Cell Mobilization/methods* ; Cyclophosphamide/therapeutic use* ; Granulocyte Colony-Stimulating Factor ; Salvage Therapy ; Peripheral Blood Stem Cells ; Male ; Middle Aged ; Female ; Peripheral Blood Stem Cell Transplantation

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.

OBJECTIVE: To investigate the efficacy of posterior three-columns osteotomy in the treatment of severe tuberculous angular kyphosis. METHODS: Total of 33 patients with severe tuberculous angular kyphosis were treated with posterior three-columns osteotomy from January 2006 to January 2019 including 24 males and 9 females with an average age of (40.6±23.3) years old ranging from 15 to 62 years old and an average disease duration of (23.5±15.5) years ranging from 4 to 40 years. The Cobb's angle of kyphosis was (118.65±28.82)°. Interradicular bone-disc-bone osteotomy(BDBO), posterior-only vertebral column resection (PVCR) and posterior multilevel vertebral osteotomy (PMVO) were performed to correct spinal deformity individually. The visual analogue scale (VAS), Oswestry disability index (ODI), sagittal vertical axis (SVA), ASIA spinal cord functional classification and motor function score, and deformity correction rate were measured and statistically analyzed before, after and at the final follow-up. RESULTS: Total of 33 patients were followed up from 15 to 96 months with an average of (38.00±6.38) months. The last follow-up of kyphosis Cobb angle (23.88±5.45)° showed no significant loss from postoperative 12 months (20.40±9.13)°, P>0.05. The SVA, VAS, ODI and ASIA spinal cord functional classification and motor function score were significantly improved at 1 year and last follow-up after operation(P<0.01). The fusion time of the osteotomy site was (18.50±5.16) months. The ASIA classification of 15 patients with spinal cord injury were improved by at least 2 grades after operation, and their daily life and work ability were various levels of restored. Postoperative complications of spinal cord injury occurred in 3 cases. CONCLUSION Posterior three-columns osteotomy is the most effective method for the treatment of angular kyphosis of spinal tuberculosis.Careful preoperative design and individualized osteotomy can not only correct the deformity, but also a successful decompression to the spinal cord and promote the recovery of spinal cord function.
Humans ; Male ; Female ; Osteotomy/methods* ; Kyphosis/surgery* ; Adult ; Adolescent ; Middle Aged ; Young Adult ; Tuberculosis, Spinal/complications* ; Treatment Outcome

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.

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.