Objective:To analyze the differentially expressed genes in PBMCs of patients with systemic lupus erythematosus (SLE) by bioinformatics methods screening and analyzing the key genes related to ferroptosis, and explore the possible mechanism of ferroptosis involved in the pathogenesis of SLE at the transcription level.Methods:The data sets and samples of healthy people (HC) and SLE patients who met the screening criteria were retrieved from the Gene Expression Omnibus (GEO), a sub-database of the National Center for Biotechnology Information (NCBI). The differentially expressed genes, GO enrichment analysis and KEGG pathway enrichment analysis were analyzed by GEO2R, R language and related software packages. The protein interaction network (PPI) of differential genes was analyzed by STRING, Cytoscape and other tools to explore the key genes and pathways. In addition, real-time quantitative reverse transcription PCR (RT-qPCR) was used to verify the expression of key genes. Mann-Whitney U test was used to compare the expression of key genes in PBMCs between the two groups. Spearman rank correlation analysis was used to explore the relationship between SLE disease activity and the level of key genes. Results:Six data sets were included in this study. A total of 166 genes related to ferroptosis were differentially expressed between SLE and HC groups. The differential genes were specifically expressed in alveolar macrophages, neutrophils, CD49 + cells and CD31 + cells. GO enrichment analysis and KEGG pathway enrichment analysis showed that the differentially expressed genes were mainly involved in multiple signaling pathways closely related to SLE, such as oxidative stress response, infection and TNF signaling pathway. Hub genes screened by different algorithms all suggested RELA as a key gene, and RT-qPCR confirmed that compared with the RELA gene expression level in the HC group [0.75(0.37,1.13)], the expression level in SLE group [2.02 (1.19,4.06)] was increased, the difference was statistically significant ( Z=-3.08, P=0.002), and was positively correlated with the corresponding SLEDAI score of SLE samples ( r=0.52, P=0.019). Conclusion:The ferroptosis of many immune cells, including alveolar macrophages and CD49 + NK cells, is involved in the pathogenesis of SLE. RELA may be involved in the ferroptosis of PBMCs in SLE through the NF-κB pathway.

The present study optimized the ethanol extraction process of Ziziphi Spinosae Semen-Schisandrae Sphenantherae Fructus drug pair by network pharmacology and Box-Behnken method. Network pharmacology and molecular docking were used to screen out and verify the potential active components of Ziziphi Spinosae Semen-Schisandrae Sphenantherae Fructus, and the process evaluation indexes were determined in light of the components of the content determination under Ziziphi Spinosae Semen and Schisandrae Sphenantherae Fructus in the Chinese Pharmacopoeia(2020 edition). The analytic hierarchy process(AHP) was used to determine the weight coefficient of each component, and the comprehensive score was calculated as the process evaluation index. The ethanol extraction process of Ziziphi Spinosae Semen-Schisandrae Sphenantherae Fructus was optimized by the Box-Behnken method. The core components of the Ziziphi Spinosae Semen-Schisandrae Sphenantherae Fructus drug pair were screened out as spinosin, jujuboside A, jujuboside B, schisandrin, schisandrol, schisandrin A, and schisandrin B. The optimal extraction conditions obtained by using the Box-Behnken method were listed below: extraction time of 90 min, ethanol volume fraction of 85%, and two times of extraction. Through network pharmacology and molecular docking, the process evaluation indexes were determined, and the optimized process was stable, which could provide an experimental basis for the production of preparations containing Ziziphi Spinosae Semen-Schisandrae Sphenantherae Fructus.
Ethanol ; Molecular Docking Simulation ; Network Pharmacology ; Seeds/chemistry* ; Ziziphus/chemistry* ; Plant Extracts/chemistry* ; Schisandra/chemistry* ; Fruit/chemistry* ; Technology, Pharmaceutical

Objective: To explore the association between inflammation activity of left atrial epicardial adipose tissue (LA-EAT) measured by ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) and atrial fibrillation (AF). Methods: A total of 78 patients with AF, who underwent ¹⁸F-FDG PET/CT in the Nuclear Medicine Department of the Third Affiliated Hospital of Soochow University due to abnormally elevated levels of tumor indicators or malignant tumors from March 2018 to December 2019, were enrolled in this retrospective study. According to the examination date of PET/CT and basic characteristics of AF patients (gender, age), a 1∶1 propensity score matching was used to enroll a non-AF control group (78 patients). The maximum standard uptake value of left atrial epicardial tissue (LA-EAT FDG SUV_max) and total EAT volume (V-EAT) were measured by ¹⁸F-FDG PET/CT. Left ventricular ejection fraction (LVEF) and left atrial diameter (LAD) were obtained by echocardiography. Blood lipids and biomarkers of inflammation were measured. The differences of clinical data and EAT-related indicators were compared between the AF group and control group. Logistic multivariate regression analysis was used to determine the related factors of AF. Then the receiver operating characteristic (ROC) curve was used to determine the cutoff value of LA-EAT FDG SUV_max on the diagnosis of AF. Univariate and multivariate logistic regression analysis were used to analyze the relationship between the increase of LA-EAT FDG SUV_max and AF. Results: The age was (66.9±10.2) years and there were 55 males (70.5%) in the AF group. The age was (66.9±8.0) years, and there were 52 males (66.7%) in the control group (both P>0.05). The LAD ((44.2±5.8) mm vs. (35.4±4.4) mm), V-EAT ((122.1±42.0) cm³ vs. (91.6±34.5) cm³), and LA-EAT FDG SUV_max ((1.6±0.3) vs. (1.4±0.2)) values were significantly higher, while LVEF ((60.1±4.7)% vs. (63.9±2.9)%) was lower in the AF group than in the control group (P all<0.001). Multivariate logistic regression analysis showed that LAD (OR=1.340, 95%CI 1.195-1.502), V-EAT (OR=1.016, 95%CI 1.001-1.031), and LA-EAT FDG SUV_max (OR=1.375, 95%CI 1.095-1.723) were positively correlated with AF, LVEF (OR=0.781, 95%CI 0.659-0.926) was negatively correlated with AF(P all<0.05). The area under the ROC curve of LA-EAT FDG SUV_max for diagnosis of AF was 0.680 (95%CI 0.597-0.764, P<0.001), and the best cut-off value was 1.415 with a sensitivity of 65.4% and specificity of 61.5%. After adjusting for high-density lipoprotein cholesterol, LVEF, LAD and V-EAT, LA-EAT FDG SUV_max≥1.415 was independently associated with AF (OR=2.982, 95%CI 1.122-7.926, P=0.010). Conclusions: The inflammatory activity of LA-EAT measured by ¹⁸F-FDG PET/CT is an independent risk factor of AF, and the increased inflammatory activity of LA-EAT is positively correlated with AF.
Adipose Tissue/diagnostic imaging* ; Aged ; Atrial Fibrillation/diagnostic imaging* ; Fluorodeoxyglucose F18 ; Humans ; Inflammation/diagnostic imaging* ; Male ; Middle Aged ; Positron Emission Tomography Computed Tomography ; Retrospective Studies ; Stroke Volume ; Ventricular Function, Left

Objective: To explore the effect of perioperative chemotherapy on the prognosis of gastric cancer patients under real-world condition. Methods: A retrospective cohort study was carried out. Real world data of gastric cancer patients receiving perioperative chemotherapy and surgery + adjuvant chemotherapy in 33 domestic hospitals from January 1, 2014 to January 31, 2016 were collected. Inclusion criteria: (1) gastric adenocarcinoma was confirmed by histopathology, and clinical stage was cT2-4aN0-3M0 (AJCC 8th edition); (2) D2 radical gastric cancer surgery was performed; (3) at least one cycle of neoadjuvant chemotherapy (NAC) was completed; (4) at least 4 cycles of adjuvant chemotherapy (AC) [SOX (S-1+oxaliplatin) or CapeOX (capecitabine + oxaliplatin)] were completed. Exclusion criteria: (1) complicated with other malignant tumors; (2) radiotherapy received; (3) patients with incomplete data. The enrolled patients who received neoadjuvant chemotherapy and adjuvant chemotherapy were included in the perioperative chemotherapy group, and those who received only postoperative adjuvant chemotherapy were included in the surgery + adjuvant chemotherapy group. Propensity score matching (PSM) method was used to control selection bias. The primary outcome were overall survival (OS) and progression-free survival (PFS) after PSM. OS was defined as the time from the first neoadjuvant chemotherapy (operation + adjuvant chemotherapy group: from the date of operation) to the last effective follow-up or death. PFS was defined as the time from the first neoadjuvant chemotherapy (operation + adjuvant chemotherapy group: from the date of operation) to the first imaging diagnosis of tumor progression or death. The Kaplan-Meier method was used to estimate the survival rate, and the Cox proportional hazards model was used to evaluate the independent effect of perioperative chemo therapy on OS and PFS. Results: 2 045 cases were included, including 1 293 cases in the surgery+adjuvant chemotherapy group and 752 cases in the perioperative chemotherapy group. After PSM, 492 pairs were included in the analysis. There were no statistically significant differences in gender, age, body mass index, tumor stage before treatment, and tumor location between the two groups (all P>0.05). Compared with the surgery + adjuvant chemotherapy group, patients in the perioperative chemotherapy group had higher proportion of total gastrectomy (χ(2)=40.526, P<0.001), smaller maximum tumor diameter (t=3.969, P<0.001), less number of metastatic lymph nodes (t=1.343, P<0.001), lower ratio of vessel invasion (χ(2)=11.897, P=0.001) and nerve invasion (χ(2)=12.338, P<0.001). In the perioperative chemotherapy group and surgery + adjuvant chemotherapy group, 24 cases (4.9%) and 17 cases (3.4%) developed postoperative complications, respectively, and no significant difference was found between two groups (χ(2)=0.815, P=0.367). The median OS of the perioperative chemotherapy group was longer than that of the surgery + adjuvant chemotherapy group (65 months vs. 45 months, HR: 0.74, 95% CI: 0.62-0.89, P=0.001); the median PFS of the perioperative chemotherapy group was also longer than that of the surgery+adjuvant chemotherapy group (56 months vs. 36 months, HR=0.72, 95% CI:0.61-0.85, P<0.001). The forest plot results of subgroup analysis showed that both men and women could benefit from perioperative chemotherapy (all P<0.05); patients over 45 years of age (P<0.05) and with normal body mass (P<0.01) could benefit significantly; patients with cTNM stage II and III presented a trend of benefit or could benefit significantly (P<0.05); patients with signet ring cell carcinoma benefited little (P>0.05); tumors in the gastric body and gastric antrum benefited more significantly (P<0.05). Conclusion: Perioperative chemotherapy can improve the prognosis of gastric cancer patients.
Chemotherapy, Adjuvant ; Female ; Gastrectomy ; Humans ; Male ; Neoadjuvant Therapy ; Neoplasm Staging ; Prognosis ; Retrospective Studies ; Stomach Neoplasms/surgery*

Objective: To analyze the current adherence to imatinib in patients with gastrointestinal stromal tumors (GIST) in China and its influencing factors. Methods: A cross-sectional survey was conducted. Study period: from October 1, 2020 to November 31, 2020. Study subjects: GIST patients taking imatinib who were diagnosed and treated in public tertiary level A general hospitals or oncology hospitals; those who had not been pathologically diagnosed, those who never received imatinib, or those who had taken imatinib in the past but stopped afterwards were excluded. The Questionnaire Star online surgery platform was used to design a questionnaire about the adherence to adjuvant imatinib therapy of Chinese GIST patients. The link of questionnaire was sent through WeChat. The questionnaire contained basic information of patients, medication status and Morisky Medication Adherence Scale. Results: A total of 2162 questionnaires from 31 provinces, autonomous regions, and municipalities were collected, of which 2005 were valid questionnaires, with an effective rate of 92.7%. The survey subjects included 1104 males and 901 females, with a median age of 56 (22-91) years old. Working status: 609 cases (30.4%) in the work unit, 729 cases (36.4%) of retirement, 667 cases of flexible employment or unemployment (33.3%). Education level: 477 cases (23.8%) with bachelor degree or above, 658 cases (32.8%) of high school, 782 cases (39.0%) of elementary or junior high school, 88 cases (4.4%) without education. Marital status: 1789 cases (89.2%) were married, 179 cases (8.9%) divorced or widowed, 37 cases (1.8%) unmarried. Two hundred and ninety-four patients (14.7%) had metastasis when they were first diagnosed, including 203 liver metastases, 52 peritoneal metastases, and 39 other metastases. One thousand eight hundred and sixty-nine patients underwent surgical treatment, of whom 1642 (81.9%) achieved complete resection. The median time of taking imatinib was 25 (1-200) months. Common adverse reactions of imatinib included 1701 cases (84.8%) of periorbital edema, 1031 cases (51.4%) of leukopenia, 948 cases (47.3%) of fatigue, 781 cases (39.0%) of nausea and vomiting, 709 cases (35.4%) of rash, and 670 cases (33.4%) of lower extremity edema. The score of the Morisky Medication Adherence Scale showed that 392 cases (19.6%) had poor adherence, 1023 cases (51.0%) had moderate adherence, and 590 cases (29.4%) had good adherence. Univariate analysis showed that gender, age, work status, economic income, residence, education level, marriage, the duration of taking medication and adverse reactions were associated with adherence to adjuvant imatinib therapy (all P<0.05). Multivariate analysis showed that female (OR=1.264, P=0.009), non-retirement (OR=1.454, P=0.001), monthly income ≤4000 yuan (OR=1.280, P=0.036), township residents (OR=1.332, P=0.005), unmarried or divorced or widowed (OR=1.362, P=0.026), the duration of imatinib medication >36 months (OR=1.478, P<0.001) and adverse reactions (OR=1.719, P=0.048) were independent risk factors for poor adherence to adjuvant imatinib. Among patients undergoing complete resection, 324 (19.7%) had poor adherence, 836 (50.9%) had moderate adherence, and 482 (29.4%) had good adherence. Meanwhile, 55 patients with good adherence (11.4%) developed recurrence after surgery, 121 patients with moderate adherence (14.5%) developed recurrence, 61 patients with poor adherence (18.8%) developed recurrence, and the difference was statistically significant (P=0.017). Conclusions: The adherence to adjuvant therapy with imatinib in Chinese GIST patients is relatively poor. Females, non-retirement, monthly income ≤4000 yuan, township residents, unmarried or divorced or widowed, the duration of imatinib medication >36 months, and adverse reactions are independently associated with poor adherence of GIST patients. Those with poor adherence have a higher risk of recurrence after surgery. Positive interventions based on the above risk factors are advocated to improve the prognosis of patients with GIST.
Aged ; Aged, 80 and over ; Antineoplastic Agents/therapeutic use* ; Chemotherapy, Adjuvant ; Cross-Sectional Studies ; Female ; Gastrointestinal Stromal Tumors/drug therapy* ; Humans ; Imatinib Mesylate/therapeutic use* ; Male ; Middle Aged ; Neoplasm Recurrence, Local/drug therapy*

A spectrum-activity relationship is established with high performance liquid chromatography(HPLC) fingerprints and the in vitro antioxidant activity to improve the quality evaluation system of Aralia taibaiensis. The HPLC profiles of 12 batches of samples were collected, and the similarity evaluation, heat map analysis and principal component analysis were conducted for the chemometric study of the fingerprint data. Combined with grey correlation analysis, the contributions of the common peaks in the fingerprints to the antioxidant activity were clarified, and the important peaks reflecting the efficacy were identified. The results showed that 17 common peaks were found in 12 batches of A. taibaiensis samples, and 6 of them were identified as saponins. Similarity evaluation, heat map analysis and principal component analysis roughly classified the A. taibaiensis herbs into two categories, i.e.,(1) S1-S10, S12 and(2) S11. Twelve batches of samples showed different antioxidant activities in a dose-dependent manner. In particular, S9 had the strongest antioxidant activity, while S11 was the weakest in antioxidant capacity, which was basically consistent with the overall score results. The results of grey correlation analysis demonstrated that the 17 common peaks scavenged DPPH radicals in the following order: X_3>X_(17)>X_4>X_8>X_7>X_(13)>X_2>X_6>X_(11)>X_(10)>X_(16)>X_(12)>X_9>X_5>X_(14)>X_1>X_(15), and scavenged ABTS radicals in the order of X_4>X_3>X_7>X_8>X_2>X_(17)>X_(13)>X_6>X_(16)>X_(11)>X_5>X_(12)>X_(10)>X_9>X_(14)>X_1>X_(15). Among them, X_3, X_4, X_7(araloside C), X_8 and X_(17) were the important peaks reflecting the efficacy of A. taibaiensis, which were basically consistent with those contained in the principal component 1. In this study, the correlation between the HPLC fingerprints of 12 batches of A. taibaiensis and its antioxidant activity provides a reference for the Q-marker screening and quality control of A. taibaiensis.
Antioxidants ; Aralia ; Chromatography, High Pressure Liquid ; Drugs, Chinese Herbal ; Saponins

This study was designed to explore the antipyretic mechanism of Pueraria radix. The method of network pharmacology was used to determine the known ingredients corresponding to Pueraria radix, predict the drug-related gene /protein targets, and analyze the interplay between key ingredients and targets. Biological Information Annotation Databases (DAVID) was used to enrich the biological processes and pathways. The result of network analysis was validated by molecular docking. It was found that 49 active ingredients of Pueraria radix not only regulate 21 targets (e.g. PTGS2, EGFR), but also affect 11 biological processes (e.g. oxidation-reduction process, prostaglandin synthesis, positive regulation of fever generation and inflammatory response) and 7 metabolic pathways (arachidonic acid metabolism, serotonergic synapse and HIF-1, et al). Molecular docking results showed that more than 65% of the active ingredients could be well docked with key targets, and the relevant literatures indicated that the active components could inhibit the expression of PTGS2, which means the result has a high reliability. These results indicated that Pueraria radix may carry its pyretic action via a "multi-ingredients-multi-targets-multi-pathways" mode, which provides a scientific basis for further research and drug development.

Objective: To identify the chemical constituents of Pinelliae Rhizoma(BX)by ultrahigh-pressure liquid chromatography coupled with electrospray time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS). Method: Chromatograpic separation was performed on a shim-pack xR-ODS Ⅲ column (2.1 mm×75 mm,1.6 μm) using a gradient elution program with mixtures of acetonitrile and 0.1% formic acid-water as mobile phases at a flow rate of 0.25 mL·min^-1. UPLC-Q-TOF-MS/MS was developed for rapid and high-throughput screening of the preliminary chemical profile of BX in positive ion modes. Result: Ninety chemical components were found in BX,according to the accurate Charge-mass Ratio and the MS/MS data,retention time of reference standard,references or databases,the fragmentation regularities of mass spectra. Eighty were identified preliminarily,including 7 alkaloids,8 poly-alcohols,12 fatty glycerides,5 flavonoids,12 lysophosphatidylcholines (LPCs),10 alcohol amines,11 amino acids,11 amides and 4 other type. Conclusion: LPCs were first found in BX. Because BX has certain toxicity,it is found that BX contains LPCs by analyzing the chemical constituents of BX,which can cause inflammatory reaction and neuronal myelin sheath loss and degeneration. Therefore,the analysis of the chemical composition of BX can explain the causes of the toxicity and provide a foundation for the basic research and quality control of the potency of BX.

Araloside A is one of the main active ingredients of Aralia taibaiensis. In this study, HPLC-MS/MS analysis method of araloside A in the main organs of SD rats was established. At the same time, the content of araloside A in the main organs (heart, liver, spleen, lung, kidney, brain) after oral administration with araloside A (50 mg•kg⁻¹) were determined to explore the tissue distribution characteristics of araloside A in vivo. The results showed that the methodological study of araloside A in the main organs of SD rats met the requirements, araloside A distributed in heart, liver, spleen, lung, kidney and brain tissues reached peak at 1 h or 2 h after oral administration with 50 mg•kg-1.The distributions of araloside A at different time points after administration were distinct as follows： the content of araloside A at 20 min：liver>heart>spleen>lung>kidney>brain; the content of araloside A at 1 h： liver>spleen>kidney>lung>heart>brain; the content of araloside A at 2 h： liver>kidney>heart>spleen>lung>brain; the content of araloside A at 4 h： kidney>liver>spleen>heart>lung>brain; the content of araloside A at 8 h： spleen>heart>liver>kidney>lung>brain. Therefore, araloside A was mainly distributed in liver tissue, which had a certain correlation with the common use of Aralia taibaiensis in the treatment of hepatic disease. In addition, araloside A shows a low content but an obvious distribution in brain tissues, which indicates that the drug can pass through blood-brain barrier, and provides the basis for the study of araloside A in brain tissue.

Objective: To describe the distribution and drug resistance of pathogens at hematology department of Jiangsu Province from 2014 to 2015 to provide reference for empirical anti-infection treatment. Methods: Pathogens were from hematology department of 26 tertiary hospitals in Jiangsu Province from 2014 to 2015. Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or agar dilution method. Collection of drug susceptibility results and corresponding patient data were analyzed. Results: The separated pathogens amounted to 4 306. Gram-negative bacteria accounted for 64.26%, while the proportions of gram-positive bacteria and funguses were 26.99% and 8.75% respectively. Common gram-negative bacteria were Escherichia coli (20.48%) , Klebsiella pneumonia (15.40%) , Pseudomonas aeruginosa (8.50%) , Acinetobacter baumannii (5.04%) and Stenotropho-monas maltophilia (3.41%) respectively. CRE amounted to 123 (6.68%) . Common gram-positive bacteria were Staphylococcus aureus (4.92%) , Staphylococcus hominis (4.88%) and Staphylococcus epidermidis (4.71%) respectively. Candida albicans were the main fungus which accounted for 5.43%. The rates of Escherichia coli and Klebsiella pneumonia resistant to carbapenems were 3.5%-6.1% and 5.0%-6.3% respectively. The rates of Pseudomonas aeruginosa resistant to tobramycin and amikacin were 3.2% and 3.3% respectively. The resistant rates of Acinetobacter baumannii towards tobramycin and cefoperazone/sulbactam were both 19.2%. The rates of Stenotrophomonas maltophilia resistant to minocycline and sulfamethoxazole were 3.5% and 9.3% respectively. The rates of Staphylococcus aureus, Enterococcus faecium and Enterococcus faecalis resistant wards vancomycin were 0, 6.4% and 1.4% respectively; also, the rates of them resistant to linezolid were 1.2%, 0 and 1.6% respectively; in addition, the rates of them resistant to teicoplanin were 2.8%, 14.3% and 8.0% respectively. Furthermore, MRSA accounted for 39.15% (83/212) . Conclusions Pathogens were mainly gram-negative bacteria. CRE accounted for 6.68%. The rates of Escherichia coli and Klebsiella pneumonia resistant to carbapenems were lower compared with other antibacterial agents. The rates of gram-positive bacteria resistant to vancomycin, linezolid and teicoplanin were still low. MRSA accounted for 39.15%.