AIM To evaluate the quality of Yanyangke Mixture.METHODS The HPLC fingerprints were established,after which cluster analysis,principal component analysis and partial least squares discriminant analysis were performed.The contents of liquiritin,rosmarinic acid,sheganoside,irisgenin,honokiol,monoammonium glycyrrhizinate,irisflorentin,isoliquiritin and magnolol were determined,the analysis was performed on a 35 ℃ thermostatic Agilent ZORBAX SB-C18 column(5 μm,250 mmx4.6 mm),with the mobile phase comprising of 0.1％phosphoric acid-acetonitrile flowing at 1 mL/min in a gradient elution manner,and multi-wavelength detection was adopted.RESULTS There were ten common peaks in the fingerprints for twelve batches of samples with the similarities of more than 0.9.Various batches of samples were clustered into three types,three principal components displayed the acumulative variance contribution rate of 87.448％,peaks 5、14(honokiol),3(liquiritin),11(monoammonium glycyrrhizinate)and 15(asarinin)were quality markers.Nine constituents showed good linear relationships within their own ranges(r＞0.999 0),whose average recoveries were 98.5％-103.6％with the RSDs of 0.92％-1.7％.CONCLUSION This stable and reliable method can provide a basis for the quality control of Yanyangke Mixture.

Objective To clarify the understanding of types of laboratories and manufacturers for GB 9706.1-2020 Medical electrical equipment-Part 1:General requirements for basic safety and essential performance by laboratory proficiency testing for creepage distance and electrical clearance test.Methods An operation guide was formed according to the testing program in GB 9706.1-2020,and the homogeneity and stability of the samples were evaluated according to CNAS-GL003:2018 Guidance on Evaluating the Homogenneity and Stability of Samples Used for Proficiency Testing.Robust statistic methods were used to assess the quantitative parameters of the test results of the participating laboratories according to the requirements in GB/T 28043-2019 Statistical methods for use in proficiency testing by interlaboratory comparison;the results reported by the expert laboratories were used as the specified values of the qualitative parameters.SPSS 25.0 statistical software was used for data analysis.Results All the results of the crreepage distance and electrical clearance tests met the requirements for homogeneity and stability.Of the 46 laboratories involved in,37 ones did have comprehensive satisfactory determinations while the remained 9 ones not.Conclusion Some laboratories don't behave well in understanding the standard,which have to be reformed accordingly to enhance their proficiencies.[Chinese Medical Equipment Journal,2024,45(10):54-59]

Objective To investigate the distribution of pathogens and change of homology of Acinetobacter bau-mannii(AB)in intensive care units(ICUs)of partial medical institutions in Shanghai before and after the pandemic of coronavirus disease 2019(COVID-19).Methods Pathogens were isolated and identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry(MALDI-TOF MS),the whole genome of AB was sequenced using Illumina Miseq sequencing platform,and its genetic relationship was explored based on multilocus sequence typing(MLST)and core genome multilocus sequence typing(cgMLST).Results The total detection rate of patho-gens in ICU environment after the pandemic was lower than before the pandemic([6.10％,101/1 656]vs[10.77％,181/1 680];P＜0.05).Before and after the pandemic,the proportion of AB detected on the surface of bedding in the ICU environment remained at the highest level.After the pandemic,the ST types showed a diverse distribution.MLST_Pasteur results showed that 162 strains of AB were divided into 20 ST types,with ST2(80.25％,n=130)being the main type.MLST_Oxford results showed that there were 19 ST types among 162 strains,with ST208(37.04％,n=60)being the main type.The clustering analysis based on cgMLST showed that ST208_Oxford had closer genetic relationship with ST540_Oxford and ST369_Oxford after the pandemic.ST164_Pasteur clone changed from ST234_Oxford before the pandemic to ST1418_Oxford after the pandemic,and 2 new types of ST_Pasteurr and 11 new types of ST_Oxford were discovered.Conclusion The detection rate of pathogens from ICU environment after the pandemic is lower than before the pandemic,and the distribution of ST types is slightly different at the same detection sites before and after the pandemic.ST2_Pasteur/ST208_Oxford is still the dominant epidemic clone before and after the pandemic,but some alleles have changed.cgMLST is more accurate than MLST_Oxford and MLST_Pasteur in homology analysis,evolution,spread,and outbreak analysis.

Purpose::To identify the risk factors for training-related lower extremity muscle injuries in young males by a non-invasive method of body composition analysis.Methods::A total of 282 healthy young male volunteers aged 18 -20 years participated in this cohort study. Injury location, degree, and injury rate were adjusted by a questionnaire based on the overuse injury assessment methods used in epidemiological studies of sports injuries. The occurrence of training injuries is monitored and diagnosed by physicians and treated accordingly. The body composition was measured using the BodyStat QuadScan 4000 multifrequency Bio-impedance system at 5, 50, 100 and 200 kHz to obtain 4 impedance values. The Shapiro-Wilk test was used to check whether the data conformed to a normal distribution. Data of normal distribution were shown as mean ± SD and analyzed by t-test, while those of non-normal distribution were shown as median (Q 1, Q 3) and analyzed by Wilcoxon rank sum test. The receiver operator characteristic curve and logistic regression analysis were performed to investigate risk factors for developing training-related lower extremity injuries and accuracy. Results::Among the 282 subjects, 78 (27.7%) developed training injuries. Lower extremity training injuries revealed the highest incidence, accounting for 23.4% (66 cases). These patients showed higher percentages of lean body mass ( p = 0.001), total body water (TBW, p=0.006), extracellular water ( p=0.020) and intracellular water ( p=0.010) as well as a larger ratio of basal metabolic rate/total weight ( p=0.006), compared with those without lower extremity muscle injuries. On the contrary, the percentage of body fat ( p=0.001) and body fat mass index ( p=0.002) were lower. Logistic regression analysis showed that TBW percentage > 65.35% ( p=0.050, odds ratio =3.114) and 3rd space water > 0.95% ( p=0.045, odds ratio =2.342) were independent risk factors for lower extremity muscle injuries. Conclusion::TBW percentage and 3rd space water measured with bio-impedance method are potential risk factors for predicting the incidence of lower extremity muscle injuries in young males following training.

Human brain banks use a standardized protocol to collect,process and store post-mortem human brains and related tissues,along with relevant clinical information,and to provide the tissue samples and data as a resource to foster neuroscience research according to a standardized operating protocols(SOP).Human brain bank serves as the foundation for neuroscience research and the diagnosis of neurological disorders,highlighting the crucial rule of ensuring the consistency of standardized quality for brain tissue samples.The first version of SOP in 2017 was published by the China Human Brain Bank Consortium.As members increases from different regions in China,a revised SOP was drafted by experts from the China Human Brain Bank Consortium to meet the growing demands for neuroscience research.The revised SOP places a strong emphasis on ethical standards,incorporates neuropathological evaluation of brain regions,and provides clarity on spinal cord sampling and pathological assessment.Notable enhancements in this updated version of the SOP include reinforced ethical guidelines,inclusion of matching controls in recruitment,and expansion of brain regions to be sampled for neuropathological evaluation.

OBJECTIVE: To explore the clinical significance of anti-endothelial cell antibodies (AECA) in predicting early miscarriage. METHODS: A total of 122 pregnant women with no history of autoimmune diseases who underwent prenatal examination at Peking University People's Hospital from January 2020 to December 2022 were selected, and they were tested for AECA. Based on the history of early miscarriage (gestational age at miscarriage < 12 weeks), the participants were divided into an early miscarriage group and a control group. t-tests, non-parametric Wilcoxon tests, Chi-square tests, and Fisher's exact probability method were used to compare general information and laboratory indicators between the two groups. A multivariate Logistic regression model was used to analyze the factors associated with early miscarriage. The natural miscarriage rates were assessed through follow-up with pregnant women, and Kaplan-Meier survival analysis was employed to compare the natural miscarriage rates between AECA-positive and AECA-negative pregnant women. RESULTS: (1) A total of 122 pregnant women were enrolled, comprising 35 cases (28.7%) in the early miscarriage group, with an average age of (32.1±6.1) years, and 87 cases (71.3%) in the control group, with an average age of (30.7±5.1) years. The early miscarriage group had higher gravidity [3 (2, 4) vs. 1 (1, 2), Z=-6.402, P < 0.001] and a higher prevalence of hypertension (11.4% vs.1.1%, P=0.024). The positive rate of AECA in the early miscarriage group (34.3% vs. 8.0%, χ²=13.070, P < 0.001) and the proportion of elevated immunoglobulin G (17.1% vs. 4.6%, P=0.032) were significantly higher than that in the control group. (2) Multivariate logistic regression analysis showed that higher gravidity (OR=4.149, 95%CI: 2.287-7.529, P < 0.001), AECA positivity (OR= 4.288, 95% CI: 1.157-15.893, P=0.029), and elevated immunoglobulin G levels (OR =6.177, 95%CI: 1.156-33.015, P=0.033) were risk factors for early miscarriage. (3) The 122 pregnant women were categorized into two groups: the AECA-positive group (19 cases) and the AECA-negative group (103 cases). Survival analysis demonstrated that at the end of 12 weeks of gestation, the fetal survival rate in the AECA-positive group was significantly lower than that in the AECA-negative group (84.2% vs. 96.1%, P= 0.035). CONCLUSION Higher gravidity, AECA positivity, and elevated immunoglobulin G levels are significant risk factors for early miscarriage. The results demonstrate that AECA is a novel predicting test in early miscarriage.
Humans ; Female ; Pregnancy ; Adult ; Infant ; Abortion, Spontaneous ; Autoantibodies ; Immunoglobulin G ; Hypertension

Objective: To investigate the prognostic value of preoperative inflammatory and nutritional condition detection in the postoperative survival, and establish a prognostic model for predicting the survival of patients with gastric cancer. Methods: The clinicopathological data of 1123 patients with gastric cancer who had undergone radical gastrectomy in Tianjin Medical University Cancer Institute & Hospital from January 2005 to December 2014 were retrospectively analyzed. Patients with history of other malignancy, with history of gastrectomy, who had received preoperative treatment, who died during the initial hospital stay or first postoperative month, and missing clinical and pathological information were excluded. Cox univariate and multivariate analyses were used to identify independent clinicopathological factors associated with the survival of these gastric cancer patients. Cox univariate analysis was used to identify preoperative inflammatory and nutritional indexes related to the survival of patients with gastric cancer after radical gastrectomy. Moreover, the Cox proportional regression model for multivariate survival analysis (forward stepwise regression method based on maximum likelihood estimation) was used. The independent clinicopathological factors that affect survival were incorporated into the following three new prognostic models: (1) an inflammatory model: significant preoperative inflammatory indexes identified through clinical and univariate analysis; (2) a nutritional model: significant preoperative nutritional indexes identified through clinical and univariate analysis; and (3) combined inflammatory/nutritional model: significant preoperative inflammatory and nutritional indexes identified through clinical and univariate analysis. A model that comprised only pT and pN stages in tumor TNM staging was used as a control model. The integrated area under the receiver operating characteristic curve (iAUC) and C-index were used to evaluate the discrimination of the model. Model fitting was evaluated by Akaike information criterion analysis. Calibration curves were used to assess agreement between the predicted probabilities and actual probabilities at 3-year or 5-year overall survival (OS). Results: The study cohort comprised 1 123 patients with gastric cancer. The mean age was 58.9±11.6 years, and 783 were males. According to univariate analysis, age, surgical procedure, extent of lymph node dissection, tumor location, maximum tumor size, number of examined lymph nodes, pT stage, pN stage, and nerve invasion were associated with 5-year OS after radical gastrectomy for gastric cancer (all P<0.050). Multivariate analysis further identified age (HR: 1.18, 95%CI: 1.03-1.36, P=0.019), maximum tumor size (HR: 1.19, 95%CI: 1.03-1.38, P=0.022), number of examined lymph nodes (HR: 0.79, 95%CI: 0.68-0.92, P=0.003), pT stage (HR: 1.40, 95%CI: 1.26-1.55, P<0.001) and pN stage (HR: 1.28, 95%CI: 1.21-1.35, P<0.001) as independent prognostic factors for OS of gastric cancer patients. Additionally, according to univariate survival analysis, the preoperative inflammatory markers of neutrophil count, percentage of neutrophils, neutrophil/lymphocyte ratio, platelet/neutrophil ratio and preoperative nutritional indicators of serum albumin and body mass index were potential prognostic factors for gastric cancer (all P<0.05). On the basis of the above results, three models for prediction of prognosis were constructed. Variables included in the three models are as follows. (1) Inflammatory model: age, maximum tumor size, number of examined lymph nodes, pT stage, pN stage, percentage of neutrophils, and neutrophil-lymphocyte ratio; (2) nutritional model: age, maximum tumor size, number of examined lymph nodes, pT stage, pN stage, and serum albumin; and (3) combined inflammatory/nutritional model: age, maximum tumor size, number of examined lymph nodes, pT stage, pN stage, percentage of neutrophils, neutrophil-lymphocyte ratio, and serum albumin. We found that the predictive accuracy of the combined inflammatory/nutritional model, which incorporates both inflammatory indicators and nutrition indicators (iAUC: 0.676, 95% CI: 0.650-0.719, C-index: 0.698),was superior to that of the inflammation model (iAUC: 0.662, 95% CI: 0.673-0.706;C-index: 0.675), nutritional model (iAUC: 0.666, 95% CI: 0.642-0.698, C-index: 0.672), and TNM staging control model (iAUC: 0.676, 95% CI: 0.650-0.719, C-index: 0.658). Furthermore, the combined inflammatory/nutritional model had better fitting performance (AIC: 10 762) than the inflammatory model (AIC: 10 834), nutritional model (AIC: 10 810), and TNM staging control model (AIC: 10 974). Conclusions: Preoperative percentage of neutrophils, NLR, and BMI have predictive value for the prognosis of gastric cancer patients. The inflammatory / nutritional model can be used to predict the survival and prognosis of gastric cancer patients on an individualized basis.
Male ; Humans ; Middle Aged ; Aged ; Female ; Prognosis ; Retrospective Studies ; Stomach Neoplasms/pathology* ; Neoplasm Staging ; Gastrectomy ; Serum Albumin

OBJECTIVES: To estimate postmortem interval (PMI) by analyzing the protein changes in skeletal muscle tissues with the protein chip technology combined with multivariate analysis methods. METHODS: Rats were sacrificed for cervical dislocation and placed at 16 ℃. Water-soluble proteins in skeletal muscles were extracted at 10 time points (0 d, 1 d, 2 d, 3 d, 4 d, 5 d, 6 d, 7 d, 8 d and 9 d) after death. Protein expression profile data with relative molecular mass of 14 000-230 000 were obtained. Principal component analysis (PCA) and orthogonal partial least squares (OPLS) were used for data analysis. Fisher discriminant model and back propagation (BP) neural network model were constructed to classify and preliminarily estimate the PMI. In addition, the protein expression profiles data of human skeletal muscles at different time points after death were collected, and the relationship between them and PMI was analyzed by heat map and cluster analysis. RESULTS: The protein peak of rat skeletal muscle changed with PMI. The result of PCA combined with OPLS discriminant analysis showed statistical significance in groups with different time points (P<0.05) except 6 d, 7 d and 8 d after death. By Fisher discriminant analysis, the accuracy of internal cross-validation was 71.4% and the accuracy of external validation was 66.7%. The BP neural network model classification and preliminary estimation results showed the accuracy of internal cross-validation was 98.2%, and the accuracy of external validation was 95.8%. There was a significant difference in protein expression between 4 d and 25 h after death by the cluster analysis of the human skeletal muscle samples. CONCLUSIONS The protein chip technology can quickly, accurately and repeatedly obtain water-soluble protein expression profiles in rats' and human skeletal muscles with the relative molecular mass of 14 000-230 000 at different time points postmortem. The establishment of multiple PMI estimation models based on multivariate analysis can provide a new idea and method for PMI estimation.
Animals ; Humans ; Rats ; Multivariate Analysis ; Postmortem Changes ; Protein Array Analysis ; Technology

The shortage of Paridis Rhizoma promotes comprehensive utilization and development research of waste aerial parts of the original plant. The chemical compositions of the aerial parts of Paris polyphylla var. chinensis were clarified based on the ultrahigh performance liquid chromatography tandem quadrupoles time of flight mass spectrometry(UPLC-QTOF-MS/MS) in the previous investigation, and a series of flavonoids and steroidal saponins were isolated. The present study continued the isolation and structure identification of the new potential compounds discovered based on UPLC-QTOF-MS/MS. By using silica gel, ODS, flash rapid preparation, and other column chromatography techniques, combined with prepared high performance liquid chromatography, five compounds were isolated from the 75% ethanol extract of the aerial parts of P. polyphylla var. chinensis, and their structures were identified by spectral data combined with chemical transformations, respectively, as(23S,25R)-23,27-dihydroxy-diosgenin-3-O-α-L-rhamnopyranosyl-(1→2)-[β-D-glucopyranosyl-(1→3)]-β-D-glucopyranoside(1),(25R)-26-O-β-D-glucopyranosyl-furost-5-en-3β,22α,26-triol-3-O-α-L-rhamnopyranosyl-(1→2)-[β-D-glucopyranosyl-(1→4)-α-L-rhamnopyranosyl-(1→4)]-β-D-glucopyranoside(2),(25R)-27-O-β-D-glucopyranosyl-5-en-3β,27-dihydroxyspirost-3-O-α-L-rhamnopyranosyl-(1→2)-[β-D-glucopyranosyl-(1→4)-α-L-rhamnopyranosyl-(1→4)]-β-D-glucopyranoside(3),(25R)-27-O-β-D-glucopyranosyl-5-en-3β,27-dihydroxyspirost-3-O-α-L-rhamnopyranosyl-(1→2)-[β-D-glucopyranosyl-(1→3)]-β-D-glucopyranoside(4), and aculeatiside A(5). Among them, compounds 1-4 were new ones, and compound 5 was isolated from P. polyphylla var. chinensis for the first time.
Tandem Mass Spectrometry ; Saponins/analysis* ; Liliaceae/chemistry* ; Chromatography, High Pressure Liquid ; Rhizome/chemistry* ; Melanthiaceae ; Molecular Structure

Alkaloids are important active ingredients occurring in many traditional Chinese medicines, and alkaloid glycosides are one of their existence forms. The introduction of saccharide units improves the water solubility of alkaloid glycosides thus presenting better biological activity.Because of the low content in plants, alkaloid glycosides have been not comprehensively studied. In this study, ultrahigh performance liquid chromatography-quadrupole time of flight-tandem mass spectrometry(UPLC-QTOF-MS/MS) was employed to identify and analyze the alkaloid glycosides in Coptis chinensis, Phellodendron chinense, Menispermum dauricum, Sinomenium acutum, Tinospora sagittata and Stephania tetrandra. The results showed that except Tinospora sagittata, the other five herbal medicines contained alkaloid glycosides. Furthermore, the alkaloid glycosides in each herbal medicine were identified based on UV absorption spectra, quasimolecular ion peaks in MS, fragment ions information in the MS/MS, and previous literature reports. A total of 42 alkaloid glycosides were identified. More alkaloid glycosides were identified in C. chinensis and Menispermum dauricum, and eleven in C. chinensis were potential new compounds. Furthermore, the alkaloid glycosides in the water extract of C. chinensis were coarsely se-parated by macroporous adsorption resin, purified by column chromatography with D151 cation exchange resin, ODS and MCI, combined with semi-preparative high performance liquid chromatography. Two new alkaloid glycosides were obtained, and their structures were identified by mass spectrometry and NMR data as(S)-7-hydroxy-1-(p-hydroxybenzyl)-2,2-N,N-dimethyl-1,2,3,4-tetrahydroisoquinoline-6-O-β-D-glucopyranoside and(S)-N-methyltetrahydropalmatubine-9-O-β-D-glucopyranoside, respectively. This study is of great significance for enriching the information about the chemical composition and the in-depth development of C. chinensis. Meanwhile, it can provide a reference for rapid identification and isolation of alkaloid glycosides from other Chinese herbal medicines.
Glycosides/chemistry* ; Medicine, Chinese Traditional ; Tandem Mass Spectrometry/methods* ; Coptis chinensis ; Drugs, Chinese Herbal/chemistry* ; Alkaloids/analysis* ; Plant Extracts/chemistry* ; Antineoplastic Agents ; Plants, Medicinal/chemistry* ; Water ; Chromatography, High Pressure Liquid/methods* ; Coptis/chemistry*