Based on the strategy of metabolomics combined with bioinformatics, this study analyzed the potential allergens and mechanism of pseudo-allergic reactions (PARs) induced by the combined use of Reduning injection and penicillin G injection. All animal experiments and welfare are in accordance with the requirements of the First Affiliated Experimental Animal Ethics and Animal Welfare Committee of Henan University of Chinese Medicine (approval number: YFYDW2020002). Based on UPLC-Q-TOF/MS technology combined with UNIFI software, a total of 21 compounds were identified in Reduning and penicillin G mixed injection. Based on molecular docking technology, 10 potential allergens with strong binding activity to MrgprX2 agonist sites were further screened. Metabolomics analysis using UPLC-Q-TOF/MS technology revealed that 34 differential metabolites such as arachidonic acid, phosphatidylcholine, phosphatidylserine, prostaglandins, and leukotrienes were endogenous differential metabolites of PARs caused by combined use of Reduning injection and penicillin G injection. Through the analysis of the "potential allergen-target-endogenous differential metabolite" interaction network, the chlorogenic acids (such as chlorogenic acid, neochlorogenic acid, cryptochlorogenic acid, and isochlorogenic acid A) and β-lactam allergens in the combination of the two may be mainly regulated by PLD1, PLA2G12A and CYP1A1. The three upstream signal target proteins mainly activate the arachidonic acid metabolic pathway, promote the degranulation of mast cells, release downstream endogenous inflammatory mediators, and induce PARs.

Platycodonis Radix is the dry root of Platycodon grandiflorum of Campanulaceae, which has a variety of pharmacological effects and is a commonly used bulk Chinese medicine. In this study, the chloroplast genome sequences of six P. grandiflorum from different producing areas has been sequenced with Illumina HiSeq X Ten platform. The specific DNA barcodes were screened, and the germplasm resources and genetic diversity were analyzed according to the specific barcodes. The total length of the chloroplast genome of 6 P. grandiflorum samples was 172 260-172 275 bp, and all chloroplast genomes showed a typical circular tetrad structure and encoded 141 genes. The comparative genomics analysis and results of amplification efficiency demonstrated that trnG-UCC and ndhG_ndhF were the potential specific DNA barcodes for identification the germplasm resources of P. grandiflorum. A total of 305 P. grandiflorum samples were collected from 15 production areas in 9 provinces, for which the fragments of trnG-UCC and ndhG_ndhF were amplificated and the sequences were analyzed. The results showed that trnG-UCC and ndhG_ndhF have 5 and 11 mutation sites, respectively, and 5 and 7 haplotypes were identified, respectively. The combined analysis of the two sequences formed 13 haplotypes (named Hap1-Hap13), and Hap4 is the main genotype, followed by Hap1. The unique haplotypes possessed by the three producing areas can be used as DNA molecular tags in this area to distinguish from the germplasm resources of P. grandiflorum from other areas. The haplotype diversity, nucleotide diversity and genetic distance were 0.94, 4.79×10^-3 and 0.000 0-0.020 3, respectively, suggesting that the genetic diversity was abundant and intraspecific kinship was relatively close. This study laid a foundation for the identification of P. grandiflorum, the protection and utilization of germplasm resources, and molecular breeding.

Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of national bloodstream infection Bacterial Resistant Investigation Collaborative System（BRICS）were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute（CLSI）. WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:During the study period，9 035 strains of Gram-negative bacteria were collected from 51 hospitals，of which 7 895（87.4%）were Enterobacteriaceae and 1 140（12.6%）were non-fermenting bacteria. The top 5 bacterial species were Escherichia coli（ n=4 510，49.9%）， Klebsiella pneumoniae（ n=2 340，25.9%）， Pseudomonas aeruginosa（ n=534，5.9%）， Acinetobacter baumannii complex（ n=405，4.5%）and Enterobacter cloacae（ n=327，3.6%）. The ESBLs-producing rates in Escherichia coli， Klebsiella pneumoniae and Proteus spp. were 47.1%（2 095/4 452），21.0%（427/2 033）and 41.1%（58/141），respectively. The prevalence of carbapenem-resistant Escherichia coli（CREC）and carbapenem-resistant Klebsiella pneumoniae（CRKP）were 1.3%（58/4 510）and 13.1%（307/2 340）；62.1%（36/58）and 9.8%（30/307）of CREC and CRKP were resistant to ceftazidime/avibactam combination，respectively. The prevalence of carbapenem-resistant Acinetobacter baumannii（CRAB）complex was 59.5%（241/405），while less than 5% of Acinetobacter baumannii complex was resistant to tigecycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa（CRPA）was 18.4%（98/534）. There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of main Gram-negative bacteria resistance among different regions，with statistically significant differences in the prevalence of CRKP and CRPA（ χ2=20.489 and 20.252， P<0.001）. The prevalence of CREC，CRKP，CRPA，CRAB，ESBLs-producing Escherichia coli and Klebsiella pneumoniae were higher in provinicial hospitals than those in municipal hospitals（ χ2=11.953，81.183，10.404，5.915，12.415 and 6.459， P<0.01 or <0.05），while the prevalence of CRPA was higher in economically developed regions（per capita GDP ≥ 92 059 Yuan）than that in economically less-developed regions（per capita GDP <92 059 Yuan）（ χ2=6.240， P=0.012）. Conclusions:The proportion of Gram-negative bacteria in bloodstream infections shows an increasing trend，and Escherichia coli is ranked in the top，while the trend of CRKP decreases continuously with time. Decreasing trends are noted in ESBLs-producing Escherichia coli and Klebsiella pneumoniae. Low prevalence of carbapenem resistance in Escherichia coli and high prevalence in CRAB complex have been observed. The composition ratio and antibacterial spectrum of bloodstream infections in different regions of China are slightly different，and the proportion of main drug resistant bacteria in provincial hospitals is higher than those in municipal hospitals.

AIM To establish an HPLC method for the simultaneous content determination of gallic acid,protocatechuic acid,morroniside,loganin,sweroside,paeoniflorin,hypericin,astragalin,salvianolic acid B,salvianolic acid A,epimedin C and icariin in Bushen Huoxue Sanjie Capsules.METHODS The analysis was performed on a 30℃thermostatic Agilent 5 TC-C18 column(250 mm×4.6 mm,5 μm),with the mobile phase comprising of acetonitrile-0.1%phosphoric acid flowing at 1.0 mL/min in a gradient elution manner,and the detection wavelength was set at 240 nm.RESULTS Twelve constituents showed good linear relationships within their own ranges(r≥0.999 8),whose average recoveries were 97.11%-101.14%with the RSDs of 0.60%-2.65%.CONCLUSION This simple,accurate and reproducible method can be used for the quality control of Bushen Huoxue Sanjie Capsules.

AIM To study the amino acids and proteins in 16 batches of commercial fish swim-bladders with different origins.METHODS A high performance liquid chromatography method based on pre-column derivatization using 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate(AQC)was developed for the determination of contents and components of 17 amino acids in fish swim-bladders.Sodium dodecyl sulfate-polyacrylamide gel electrophoresis(SDS-PAGE)was performed to analyze the molecular weight distribution of proteins from different fish swim-bladders,and proteins in fish swim-bladders were identified by proteomics method.RESULTS The result showed that the determination of 17 amino acids had a good linear relationship(R2≥0.998 0).The average recovery rate was 85.62%-109.60%and the relative standard deviations of precision,stability and repeatability were less than 3.5%.The total content of the 17 amino acids in 16 batches of fish swim-bladders ranged from 468.31 mg/g to 620.05 mg/g.A total of 688 proteins including 11 collagens were identified from 16 batches of fish swim-bladder samples and a plenty of low-abundance proteins at 52-95 kDa were also detected in fish swim-bladders by SDS-PAGE.CONCLUSION This study provides a good reference for the quality evaluation and further utilization of fish swim-bladders.

Objective:To construct and validate the best predictive model for 28-day death risk in patients with septic shock based on different supervised machine learning algorithms.Methods:The patients with septic shock meeting the Sepsis-3 criteria were selected from Medical Information Mart for Intensive Care-Ⅳ v2.0 (MIMIC-Ⅳ v2.0). According to the principle of random allocation, 70% of these patients were used as the training set, and 30% as the validation set. Relevant predictive variables were extracted from three aspects: demographic characteristics and basic vital signs, serum indicators within 24 hours of intensive care unit (ICU) admission and complications possibly affecting indicators, functional scoring and advanced life support. The predictive efficacy of models constructed using five mainstream machine learning algorithms including decision tree classification and regression tree (CART), random forest (RF), support vector machine (SVM), linear regression (LR), and super learner [SL; combined CART, RF and extreme gradient boosting (XGBoost)] for 28-day death in patients with septic shock was compared, and the best algorithm model was selected. The optimal predictive variables were determined by intersecting the results from LASSO regression, RF, and XGBoost algorithms, and a predictive model was constructed. The predictive efficacy of the model was validated by drawing receiver operator characteristic curve (ROC curve), the accuracy of the model was assessed using calibration curves, and the practicality of the model was verified through decision curve analysis (DCA).Results:A total of 3?295 patients with septic shock were included, with 2?164 surviving and 1?131 dying within 28 days, resulting in a mortality of 34.32%. Of these, 2?307 were in the training set (with 792 deaths within 28 days, a mortality of 34.33%), and 988 in the validation set (with 339 deaths within 28 days, a mortality of 34.31%). Five machine learning models were established based on the training set data. After including variables at three aspects, the area under the ROC curve (AUC) of RF, SVM, and LR machine learning algorithm models for predicting 28-day death in septic shock patients in the validation set was 0.823 [95% confidence interval (95% CI) was 0.795-0.849], 0.823 (95% CI was 0.796-0.849), and 0.810 (95% CI was 0.782-0.838), respectively, which were higher than that of the CART algorithm model (AUC = 0.750, 95% CI was 0.717-0.782) and SL algorithm model (AUC = 0.756, 95% CI was 0.724-0.789). Thus above three algorithm models were determined to be the best algorithm models. After integrating variables from three aspects, 16 optimal predictive variables were identified through intersection by LASSO regression, RF, and XGBoost algorithms, including the highest pH value, the highest albumin (Alb), the highest body temperature, the lowest lactic acid (Lac), the highest Lac, the highest serum creatinine (SCr), the highest Ca 2+, the lowest hemoglobin (Hb), the lowest white blood cell count (WBC), age, simplified acute physiology score Ⅲ (SAPSⅢ), the highest WBC, acute physiology score Ⅲ (APSⅢ), the lowest Na +, body mass index (BMI), and the shortest activated partial thromboplastin time (APTT) within 24 hours of ICU admission. ROC curve analysis showed that the Logistic regression model constructed with above 16 optimal predictive variables was the best predictive model, with an AUC of 0.806 (95% CI was 0.778-0.835) in the validation set. The calibration curve and DCA curve showed that this model had high accuracy and the highest net benefit could reach 0.3, which was significantly outperforming traditional models based on single functional score [APSⅢ score, SAPSⅢ score, and sequential organ failure assessment (SOFA) score] with AUC (95% CI) of 0.746 (0.715-0.778), 0.765 (0.734-0.796), and 0.625 (0.589-0.661), respectively. Conclusions:The Logistic regression model, constructed using 16 optimal predictive variables including pH value, Alb, body temperature, Lac, SCr, Ca 2+, Hb, WBC, SAPSⅢ score, APSⅢ score, Na +, BMI, and APTT, is identified as the best predictive model for the 28-day death risk in patients with septic shock. Its performance is stable, with high discriminative ability and accuracy.

Exploring the risk "time interval window" of sequential medication of Reduning injection (RDN) and penicillin G injection (PG) by detecting the correlation between serum biochemical indexes and plasma metabonomic characteristics, in order to reduce the risk of adverse reactions caused by the combination of RDN and PG. All animal experiments and welfare are in accordance with the requirements of the First Affiliated Experimental Animal Ethics and Animal Welfare Committee of Henan University of Chinese Medicine (approval number: YFYDW2020002). The changes of biochemical indexes in serum of rats were detected by enzyme-linked immunosorbent assay. It was determined that RDN combined with PG could cause pseudo-allergic reactions (PARs) activated by complement pathway. Further investigation was carried out at different time intervals (1.5, 2, 3.5, 4, 6, and 8 h PG+RDN). It was found that sequential administration within 3.5 h could cause significant PARs. However, PARs were significantly reduced after administration interval of more than 4 h. LC-MS was used for plasma metabolomics analysis, and the levels of serum biochemical indicators and plasma metabolic profile characteristics were compared in parallel. 22 differential metabolites showed similar or opposite trends to biochemical indicators before and after 3.5 h. And enriched to 10 PARs-related pathways such as arachidonic acid metabolism, steroid hormone biosynthesis, linoleic acid metabolism, glycerophospholipid metabolism, and tryptophan metabolism. In conclusion, there is a risk "time interval window" phenomenon in the adverse drug reactions caused by the sequential use of RDN and PG, and the interval medication after the "time interval window" can significantly reduce the risk of adverse reactions.

The purpose of this study was to investigate the intervention effect and mechanism of Lycium barbarum leaves on letrozole-induced polycystic ovary syndrome (PCOS) mice. The PCOS model was prepared by letrozole combined with high-fat diet. After successful modeling, 40 mice were randomly divided into PCOS group, positive drug metformin group, low-dose Lycium barbarum leaves group, and high-dose Lycium barbarum leaves group. The corresponding drugs were given by gavage for 29 days. At the end of the experiment, the eyeballs were removed for blood collection and ovarian tissue was collected. The ovarian mass, fasting blood glucose (FBG), fasting insulin (FINS), testosterone (T), anti-Mullerian hormone (AMH), luteinizing hormone (LH), follicle stimulating hormone (FSH), and estradiol (E₂) levels were measured in each group. The morphology of ovarian tissue was observed by hematoxylin-eosin staining, and the oocytes, cystic follicles and corpus luteum were counted. Cecal contents of mice were collected for analysis of intestinal flora composition and differential flora. The animal experiment process was approved by the Animal Ethics Committee of Nanjing University of Traditional Chinese Medicine. The results showed that the estrous cycle of PCOS mice was disordered. Compared with the PCOS group, the Lycium barbarum leaves group can significantly reduce the ovarian damage of mice, reduce the number of cystic dilated follicles, and normalize the estrous cycle. After the intervention of Lycium barbarum leaves, the levels of FBG, FINS, T, AMH, LH, FSH and LH/FSH were significantly decreased (P < 0.05), while the level of E₂ was significantly increased (P < 0.001). In addition, Lycium barbarum leaves can regulate the disorder of intestinal flora diversity in PCOS mice, increase the abundance of Bacteroidetes, and reduce the abundance of Firmicutes, Ileibacterium, Romboutsia and Faecalibaculum. In summary, Lycium barbarum leaves can play a therapeutic role in PCOS mice by improving insulin resistance, regulating reproductive hormone disorders and gut microbiota imbalance. It provides scientific basis and useful reference for the rational utilization and development of Lycium barbarum leaves.

Objective The purpose of this study was to investigate the bacterial communities of biting midges and ticks collected from three sites in the Poyang Lake area,namely,Qunlu Practice Base,Peach Blossom Garden,and Huangtong Animal Husbandry,and whether vectors carry any bacterial pathogens that may cause diseases to humans,to provide scientific basis for prospective pathogen discovery and disease prevention and control. Methods Using a metataxonomics approach in concert with full-length 16S rRNA gene sequencing and operational phylogenetic unit(OPU)analysis,we characterized the species-level microbial community structure of two important vector species,biting midges and ticks,including 33 arthropod samples comprising 3,885 individuals,collected around Poyang Lake. Results A total of 662 OPUs were classified in biting midges,including 195 known species and 373 potentially new species,and 618 OPUs were classified in ticks,including 217 known species and 326 potentially new species.Surprisingly,OPUs with potentially pathogenicity were detected in both arthropod vectors,with 66 known species of biting midges reported to carry potential pathogens,including Asaia lannensis and Rickettsia bellii,compared to 50 in ticks,such as Acinetobacter lwoffii and Staphylococcus sciuri.We found that Proteobacteria was the most dominant group in both midges and ticks.Furthermore,the outcomes demonstrated that the microbiota of midges and ticks tend to be governed by a few highly abundant bacteria.Pantoea sp7 was predominant in biting midges,while Coxiella sp1 was enriched in ticks.Meanwhile,Coxiella spp.,which may be essential for the survival of Haemaphysalis longicornis Neumann,were detected in all tick samples.The identification of dominant species and pathogens of biting midges and ticks in this study serves to broaden our knowledge associated to microbes of arthropod vectors. Conclusion Biting midges and ticks carry large numbers of known and potentially novel bacteria,and carry a wide range of potentially pathogenic bacteria,which may pose a risk of infection to humans and animals.The microbial communities of midges and ticks tend to be dominated by a few highly abundant bacteria.

Objectives:To assess the prognostic impact of the neoadjuvant rectal (NAR) score following neoadjuvant short-course radiotherapy and consolidation chemotherapy in locally advanced rectal cancer (LARC), as well as its value in guiding decisions for adjuvant chemotherapy.Methods:Between August 2015 and August 2018, patients were eligible from the STELLAR phase III trial (NCT02533271) who received short-course radiotherapy plus consolidation chemotherapy and for whom the NAR score could be calculated. Based on the NAR score, patients were categorized into low (＜8), intermediate (8-16), and high (＞16) groups. The Kaplan-Meier method, log rank tests, and multivariate Cox proportional hazard regression models were used to evaluate the impact of the NAR score on disease-free survival (DFS).Results:Out of the 232 patients, 24.1%, 48.7%, and 27.2% had low (56 cases), intermediate (113 cases), and high NAR scores (63 cases), respectively. The median follow-up period was 37 months, with 3-year DFS rates of 87.3%, 68.3%, and 53.4% ( P＜0.001) for the low, intermediate, and high NAR score groups. Multivariate analysis demonstrated that the NAR score (intermediate NAR score: HR, 3.10, 95% CI, 1.30-7.37, P=0.011; high NAR scores: HR=5.44, 95% CI, 2.26-13.09, P＜0.001), resection status ( HR, 3.00, 95% CI, 1.64-5.52, P＜0.001), and adjuvant chemotherapy ( HR, 3.25, 95% CI, 2.01-5.27, P＜0.001) were independent prognostic factors for DFS. In patients with R0 resection, the 3-year DFS rates were 97.8% and 78.0% for those with low and intermediate NAR scores who received adjuvant chemotherapy, significantly higher than the 43.2% and 50.6% for those who did not ( P＜0.001, P=0.002). There was no significant difference in the 3-year DFS rate (54.2% vs 53.3%, P=0.214) among high NAR score patients, regardless of adjuvant chemotherapy. Conclusions:The NAR score is a robust prognostic indicator in LARC following neoadjuvant short-course radiotherapy and consolidation chemotherapy, with potential implications for subsequent decisions regarding adjuvant chemotherapy. These findings warrant further validation in studies with larger sample sizes.