The Increased Ischemic Risk During the Early Period After Clopidogrel Noncompliance in Patients with Acute Coronary Syndrome: A Meta-Analysis.

Although dual antiplatelet therapy for secondary prevention in acute coronary syndrome (ACS) is highly recommended by current guidelines, P2Y12 inhibitor non-adherence often occurs and devastates prognosis. To evaluate whether the ischemic risk during the early period of clopidogrel noncompliance was increased among ACS patients, a comprehensive search of PubMed, Embase, and Web of Science was conducted to identify studies reporting early ischemic risk after clopidogrel noncompliance in ACS patients. The primary endpoint was a composite of death or myocardial infarction (MI). Effect sizes were synthesized in patients with or without revascularization. A total of 7 observational studies focusing on clopidogrel noncompliance were included in this meta-analysis, whereas no studies involving ticagrelor or prasugrel were retrieved. A significantly increased risk of death or MI 0 to 90 days after clopidogrel noncompliance was found compared with that during 90 to 180 or 90 to 360 days regardless of revascularization (incidence rate ratio [IRR]: 2.01, 95% confidence interval (CI): 1.62-2.49, P < .001, I2 = 9%) or not (IRR: 1.61, 95% CI: 1.05-2.48, P < .001, I2 = 74%). Patients undergoing percutaneous coronary intervention had a higher risk of death or MI 0 to 90 days after clopidogrel noncompliance compared with 90-180 or 90-360 days irrespective of drug-eluting stent or bare metal stent implantation (P < .05 for both). The early ischemic risk after clopidogrel noncompliance is significantly higher than the late risk in ACS patients. Antiplatelet noncompliance remains a serious concern.

Synergistic Interaction Between Paired Combinations of Natural Antimicrobials Against Poultry-Borne Pathogens.

Natural antimicrobials (NAM) are promising candidates for the successful control of poultry-borne bacteria, carrying potent antimicrobial activity (AMA) against a wide range of multidrug-resistant pathogens. Individual activities of carvacrol, eugenol, trans-cinnamaldehyde, oregano, and thymol, along with the combined activity of paired compounds, were examined using broth microdilution and checkerboard techniques. The characteristic interactions between the compounds were calculated using an improved method, based on combination index (CI) values. The bacteria examined herein were selected due to their known genetic resistance to at least one antibiotic. Our results indicated that thymol was most effective, exhibiting the lowest minimum inhibitory concentration (MIC) value against Salmonella pullorum, Escherichia coli, and Klebsiella pneumoniae, establishing the order of antimicrobial efficacy as: thymol > oregano > carvacrol > trans-cinnamaldehyde > eugenol. In the interaction study, the paired combination of carvacrol and thymol showed synergistic effects and was highly effective in reducing the antibiotic resistance of all the evaluated pathogens. Notably, all CI values were <1.0 in evaluations of S. pullorum, indicating the absence of antagonism between eugenol and thymol (or oregano). In K. pneumoniae, majority of CI values, which had a few concentration points, were smaller than 1.0, indicating a synergistic effect between eugenol and carvacrol (oregano or thymol), and trans-cinnamaldehyde and carvacrol. In E. coli, apart from some concentration points, some CI values were smaller than 1.0, demonstrating a synergistic effect between eugenol and carvacrol, and thymol and carvacrol (eugenol or oregano). It is therefore of great significance to investigate and illuminate the minimal effect concentration of these five components when they are used in combination as feed additives. Moreover, the improved evaluation method of this study provides a precise and extensive means to assess the synergistic effects of NAM.

Effect of Bacterial Resistance of Escherichia coli From Swine in Large-Scale Pig Farms in Beijing.

With widespread use of antibiotics in the aquaculture industry, bacterial resistance has recently attracted increasing attention. Continuous emergence of multi-resistant bacteria has greatly threatened human and animal health, as well as the quality and safety of livestock products. To control bacterial resistance, the effect of bacterial resistance needs to be well understood. The purpose of this study was to explore the factors influencing Escherichia coli (E. coli) drug resistance in large-scale pig farms. In this study, 296 strains of E. coli isolated and identified from large-scale pig farms in Beijing were used as the research objects. In vitro drug sensitivity tests were used to determine the sensitivity to 10 antibiotics of pig-derived E. coli. SPSS logistic regression was employed to analyze the effects of the season, pig type, sampling point (medication type) and sampling location on resistance and multi-drug resistance of E. coli from pigs. The degrees of drug resistance to 10 antibiotics of the 296 strains of pig-derived E. coli were varied, their resistance rates were between 4.05 and 97.64%, and their multi-drug resistance was appalling, with the highest resistance to six antibiotics being 26.35%. The isolated strains were proven more resistant to tetracyclines, penicillin and chloramphenicol, which are commonly used for disease prevention in pig farms, and less resistant to quinolones and aminoglycosides, which are not used in pig farms. The resistance of the isolated strains in spring and summer was generally higher than that in winter. E. coli resistance in piglets, fattening pigs and sows was more serious than that in nursery and sick pigs. The results showed that the season, type of medication and type of pig had an influence on the pig-derived E. coli resistance, among which the type of medication was the most influencing factor.

Proposing Two Local Modeling Approaches for Discriminating PGI Sunite Lamb from Other Origins Using Stable Isotopes and Machine Learning.

For the protection of Protected Geographical Indication (PGI) Sunite lamb, PGI Sunite lamb samples and lamb samples from two other banners in the Inner Mongolia autonomous region were distinguished by stable isotopes (δ13C, δ15N, δ2H, and δ18O) and two local modeling approaches. In terms of the main characteristics and predictive performance, local modeling was better than global modeling. The accuracies of five local models (LDA, RF, SVM, BPNN, and KNN) obtained by the Adaptive Kennard-Stone algorithm were 91.30%, 95.65%, 91.30%, 100%, and 91.30%, respectively. The accuracies of the five local models obtained by an approach of PCA-Full distance based on DD-SIMCA were 91.30%, 91.30%, 91.30%, 100%, and 95.65%, respectively. The accuracies of the five global models were 91.30%, 91.30%, 91.30%, 100%, and 91.30%, respectively. Stable isotope ratio analysis combined with local modeling can be used as an effective indicator for protecting PGI Sunite lamb.

Acrosomal vesicle protein in predicting progression of pancreatitis in Chinese patients with acute pancreatitis.

The present preliminary investigation was designed to identify biomarkers in the progression of pancreatitis in Chinese patients with acute pancreatitis. Chinese patients aged <60 years with a confirmed diagnosis of acute pancreatitis were enrolled. A saliva sample was collected using salimetrics oral swab in precooled polypropylene tubes to prevent degradation of sensitive peptides. All samples were then centrifuged at 700 × g for 15 min at 4°C to remove debris. The supernatant of each sample was fractionated into 100µL aliquots and frozen at -70°C until analyses using affymetrix HG U133 Plus 2.0 array technique. Bedside index for severity acute pancreatitis (BISAP) score and CT severity index were recorded for each enrolled patient to assess the progression and severity of acute pancreatitis. Data from a total of 210 patients (105 patients in each group) were analyzed. Among identified biomarkers, acrosomal vesicle protein 1 was significantly higher in patients with disease progression as compared to patient without disease progression. Logistic regression model showed that acrosomal vesicle protein 1 (ACRV1) were positively correlated with the progression of diseases. The present reports showed that a mRNA salivary biomarker (ACRV1) are associated with progression of pancreatitis in patients with early stage of pancreatitis. This study suggest that mRNA salivary biomarker (ACRV1) is a predictor of pancreatitis progression.

Chemical Analysis Combined with Multivariate Statistical Methods to Determine the Geographical Origin of Milk from Four Regions in China.

Traceability of milk origin in China is conducive to the implementation of the protection of regional products. In order to distinguish milk from different geographical distances in China, we traced the milk of eight farms in four neighboring provinces of China (Inner Mongolia autonomous region, Hebei, Ningxia Hui autonomous and Shaanxi), and multivariate data analysis was applied to the data including elemental analysis, stable isotope analysis and fatty acid analysis. In addition, orthogonal partial least squares discriminant analysis (OPLS-DA) is used to determine the optimal classification model, and it is explored whether the combination of different technologies is better than a single technical analysis. It was confirmed that in the inter-provincial samples, the combination of the two techniques was better than the analysis using a single technique (fatty acids: R2 = 0.716, Q2 = 0.614; fatty acid-binding isotopes: R2 = 0.760, Q2 = 0.635). At the same time, milk produced by farms with different distances of less than 11 km in each province was discriminated, and the discriminant distance was successfully reduced to 0.7 km (Ningxia Hui Autonomous Region: the distance between the two farms was 0.7 km, R2 = 0.771, Q2 = 0.631). For short-distance samples, the combination multiple technologies are not completely superior to a single technique, and sometimes, it is easy to cause model over-fitting.