Metabolomics covers a wide range of applications in life sciences, biomedicine, and phytology. Data acquisition (to achieve high coverage and efficiency) and analysis (to pursue good classification) are two key segments involved in metabolomics workflows. Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups. However, insufficient feature extraction, inappropriate feature selection, overfitting, or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused. Using two ginseng varieties, namely Panax japonicus (PJ) and Panax japonicus var. major (PJvm), containing the similar ginsenosides, we integrated pseudo-targeted metabolomics and deep neural network (DNN) modeling to achieve accurate species differentiation. A pseudo-targeted metabolomics approach was optimized through data acquisition mode, ion pairs generation, comparison between multiple reaction monitoring (MRM) and scheduled MRM (sMRM), and chromatographic elution gradient. In total, 1980 ion pairs were monitored within 23 min, allowing for the most comprehensive ginseng metabolome analysis. The established DNN model demonstrated excellent classification performance (in terms of accuracy, precision, recall, F1 score, area under the curve, and receiver operating characteristic (ROC)) using the entire metabolome data and feature-selection dataset, exhibiting superior advantages over random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). Moreover, DNNs were advantageous for automated feature learning, nonlinear modeling, adaptability, and generalization. This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples. This established approach holds promise for plant metabolomics and is not limited to ginseng.

Metabolomics covers a wide range of applications in life sciences,biomedicine,and phytology.Data acquisition(to achieve high coverage and efficiency)and analysis(to pursue good classification)are two key segments involved in metabolomics workflows.Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups.However,insufficient feature extraction,inappropriate feature selection,overfitting,or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused.Using two ginseng varieties,namely Panax japonicus(PJ)and Panax japonicus var.major(PJvm),containing the similar ginsenosides,we integrated pseudo-targeted metabolomics and deep neural network(DNN)modeling to achieve accurate species differentiation.A pseudo-targeted metabolomics approach was optimized through data acquisition mode,ion pairs generation,comparison between multiple reaction monitoring(MRM)and scheduled MRM(sMRM),and chromatographic elution gradient.In total,1980 ion pairs were monitored within 23 min,allowing for the most comprehensive ginseng metabolome analysis.The established DNN model demonstrated excellent classification performance(in terms of accuracy,precision,recall,F1 score,area under the curve,and receiver operating characteristic(ROC))using the entire metabolome data and feature-selection dataset,exhibiting superior advantages over random forest(RF),support vector ma-chine(SVM),extreme gradient boosting(XGBoost),and multilayer perceptron(MLP).Moreover,DNNs were advantageous for automated feature learning,nonlinear modeling,adaptability,and generalization.This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples.This established approach holds promise for plant metabolomics and is not limited to ginseng.

Tetanus consists of neonatal tetanus and non-neonatal tetanus. Non-neonatal tetanus remains a serious public health problem, although neonatal tetanus has been eliminated in China since 2012. Non-neonatal tetanus is a potential fatal disease. In the absence of medical intervention, the mortality rate of severe cases is almost 100%. Even with vigorous treatment, the mortality rate remains 30%-50% globally. These specifications aim to regulate non-neonatal tetanus diagnosis and treatment in China, in order to improve medical quality and safety. These specifications introduce the etiology, epidemiology, pathogenesis, clinical manifestations and laboratory tests, diagnosis, differential diagnosis, grading and treatment of non-neonatal tetanus.

Tetanus consists of neonatal tetanus and non-neonatal tetanus.Non-neonatal tetanus remains a serious public health problem,although neonatal tetanus has been eliminated in China since 2012.Non-neonatal tetanus is a potential fatal disease.In the absence of medical intervention,the mortality rate of severe cases is almost 100％.Even with vigorous treatment,the mortality rate is still 30％-50％ globally.These specifications aim to regulate non-neonatal tetanus diagnosis and treatment in China,in order to improve medical quality and safety.These specifications introduce the etiology,epidemiology,pathogenesis,clinical manifestations and laboratory tests,diagnosis,differential diagnosis,grading and treatment of non-neonatal tetanus.

Tetanus consists of neonatal tetanus and non-neonatal tetanus. Although neonatal tetanus in China has been eliminated since 2012, non-neonatal tetanus remains a serious public health problem. Non-neonatal tetanus is a potential fatal disease, and the mortality rate of severe cases is almost 100% in the absence of medical intervention. Even with vigorous treatment, the mortality rate is still 30~50% globally. In order to standardize the diagnosis and treatment of non-neonatal tetanus in China, this specification is hereby formulated. This standard includes etiology, epidemiology, pathogenesis, clinical manifestations, laboratory tests, diagnosis, differential diagnosis, classification, grading and treatment of non-neonatal tetanus.

Objective This study aimed to describe the sex disparities on cancer incidence and mortality in Jiashan population.Methods All data concerning incident and death cases of cancers were gathered from the database of Cancer Registry in Jiashan county.Data from the 2010 China census was used as the standard population.Sex-specific age-standardized incidence rates (ASIRs),mortality rates (ASMRs) per 100 000 persons for all cancers and types of each cancer were calculated for the years of 1990 to 1999,2000 to 2009,2010 to 2014,and 1990 to 2014.In addition,the corresponding male-to-female incidence rate ratios (IRRs) and mortality rate ratios (MRRs) were also calculated.Results The ASIR of all cancers was 226.13/105 for the whole period of 1990 to 2014,with 266.04/105 for males and 187.22/105 for females,respectivcly.The corresponding IRR was 1.42 (95％CI:1.39-1.46),with significant difference noticed in the incidence rates between males and females (P＜0.05).The ASMR of all cancers was 155.39/105,with 206.55/105 for males and 104.98/105 for females,respectively.The corresponding MRR was 1.97 (95％ CI:1.91-2.03),with significant difference between males and females (P＜0.05).Among all the cancer types,only gallbladder cancer and thyroid cancer showed female predominance in both incidence and mortality,with male predominance in all the remaining cancers.Conclusion Finding from our study suggested that a male predominance in both incidence and mortality for a majority of cancers in Jiashan population.

AIM:To investigate the effects of extracellular cysteine/cystine redox potential (EhCys/CySS) on the mitochondrial function of nonalcoholic fatty liver disease ( NAFLD) hepatocytes.METHODS:LO2 cells were incuba-ted with EhCys/CySS of the oxidized (0 mV), the normal (-80 mV), or the reduced (-150 mV) status medium, then treated with oleic acid to establish NAFLD model in vitro.DCFH-DA and MitoSOX were used as the fluorescent probes for determining reactive oxygen species (ROS).Apocynin (NADPH oxidase inhibitor), MitoQ10 (mitochondria-targeted an-tioxidant), rotenone (mitochondrial respiratory chain complex I inhibitor) and antimycin A (mitochondrial respiratory chain complex III inhibitor) were used to investigate the sources of ROS.RESULTS:An increase in ROS in LO2 cells by oleic acid was aggravated by the oxidized extracellular EhCys/CySS (0 mV), which was removed by the reduced EhCys/CySS (-150 mV) .ROS generation by 0 mV was significantly eliminated by MitoQ10 .ROS levels were dependent on ex-tracellular Eh Cys/CySS in rotenone treated LO2 cells.A decline of mitochondrial membrane potential in the cells with NAFLD was aggravated by 0 mV and reversed by -150 mV.CONCLUSION:The oxidized extracellular Eh Cys/CySS via inhibitiing of complex I intensifies ROS generation and reducing the mitochondrial membrane potential in the NAFLD hepa-tocytes, which were reversed by reduced Eh Cys/CySS.

Objective To study the microbial strains,risk factors and resistance profiles of lower respiratory tract fungal infection in hospital of Zhoushan archipelago area.Methods A total of 204 patients who were hospitalized for lower respiratory tract infection were retrospectively analyzed from May 2008 to April 2011 in Zhoushan archipelago area,and collected 204 fungal strains isolated from confirmed lower respiratory tract fungal infection cases.Chi-square test and Logistic regression analysis were performed.Results Among the 204 fungal strains isolated from lower respiratory tract specimens,110 (53.8％) strains of Candidaalbicans,32 (15.7％) strains of Candida tropicalis,24 (11.8％) strains of Candida glabrata,12 (5.9％) strains of Candida krusei,14 (6.9％) strains of other Candida,and 12 (5.9％) strains of Aspergillus were detected.Logistic regression analysis showed that chronic obstructive pulmonary disease,bacterial pneumonia,long-term use of broadspectrum antibiotics and corticosteroids,endotracheal intubation or incision,old age,exposure in intensive care unit (ICU),and hospitalization ≥7 days were major risk factors (P=0.000,0.001,0.000,0.000,0.012,0.000,0.000,0.000).The resistance rates of isolated Candida against amphotericin B,5-flucytosine,voriconazole,itraconazole and fluconazole were 0,2.1％,4.2％,14.8％ and 22.9％,respectively.Conclusions Candida albicans is the major pathogen of lower respiratory tract fungal infection in hospital of Zhoushan archipelago area,and Candida is sensitive to amphotericin B,5-flucytosine and voriconazole.

HepG2 cells were pre-incubated with insulin (Ins 0,1,0. 1,0.01 μol/L) and dexamethasone ( Dex 0,3,0. 3,0.03 μol/L) alone or together for 24 h to induce insulin resistance (IR) in vitro, the resistant level was estimated by glucose consumption, the optimal model of insulin resitance was chosen, and at the same time its lasting time of resistance was determined. In order to investigate the effects and mechanisms of mifepristone on in sulin-resistant HepG2 cells induced by insulin and dexamethasone, mifepristone and pioglitazone were adminis tered 24 h after the optimal model of insulin-resistant HepG2 cells was established. The glucose consumption, in tracellular concentrations of glucose, glycogen, ATP, and free fatty acid (FFA) in each group were detected. The expression of InsR-mRNA and GR-mRNA was detected by semi-quantitative reverse transcription and polymerase chain reaction (SqRT-PCR). Results revealed that pretreatment with insulin (0. 1 μmol/L) and dexamethasone (0.3 (μol/L) for 24 h caused optimal insulin resistance of HepG2 cells which lasted for 36 h. Compared with control group, the glucose consumption, intracellular glucose, glycogen, ATP contents and the level of InsR-mRNA in model cells decreased while FFAs concentrations and GR-mRNA increased. However, the tendency of insulin resistant HepG2 cells was obviously attenuated by pioglitazone at the concentration of 0. 2 mmol/L and mifepris tone at 200μmol/L and 20 μol/L while mifepristone at 2 μol/L had no effect on insulin-resistant cells. The findings indicated that mifepristone at 200 μol/L and 20 μol/L improved the insulin resistance via modulating intracellular glucolipid metabolism and the expression of InsR-mRNA and GR-mRNA.

Glucocorticoids are among those most important hormones that maintain the energy metabolic homeostasis within body.The actions of glucocorticoids on target tissues,such as liver and adipose tissue,are not only dependent on circulating glucocorticoid levels but also on glucocorticoid receptor expression.The elevated level of circulating glucocorticoid caused by exogenous or endogenous reasons may contribute to insulin resistance and the other metabolic syndrome such as dyslipidemia,visceral obesity and hypertension.This review summarizes recent advances in the study of glucocorticoid receptor-mediated insulin resistance and its antagonists.