The study was supported by Novartis.

The present study aimed to investigate the potential effects of growth differentiation factor 11 (GDF11) on isoproterenol (ISO)-induced heart failure (HF) and identify the underlying molecular mechanisms. A rat model of HF was induced in vivo by intraperitoneally administering ISO (5 mg/kg/day) for 7 days. After 4 weeks following establishment of the HF model, hemodynamic analysis demonstrated that ISO induced a significant increase in the left ventricular end-diastolic pressure and a decrease in the left ventricular systolic pressure and maximum contraction velocity. The plasma levels of myocardial injury markers, including lactate dehydrogenase (LDH), creatine kinase (CK), CK-muscle/brain which were determined using the corresponding assay kits and plasma brain natriuretic peptide which was detected by an ELISA kit, an important biomarker of HF, increased following ISO treatment. Furthermore, levels of GDF11 expression and protein, which were estimated using reverse transcription-quantitative polymerase chain reaction and an ELISA kit in plasma and western blotting in the heart tissue, respectively, significantly increased following ISO treatment. To demonstrate the effects of ISO on GDF11 production in cardiomyocytes, H9C2 cells (a cardiomyoblast cell line derived from embryonic rat heart tissue) were treated with ISO (50 nM) for 24 h in vitro ; it was revealed that GDF11 protein and mRNA expression levels significantly increased following ISO treatment. In addition, recombinant GDF11 (rGDF11) administered to ISO-treated H9C2 cells resulted in decreased proliferation, which was detected via a CCK-8 assay, and increased LDH levels and cell apoptosis of cells, which was determined using Caspase-3 activity and Hoechst 33258 staining. Additionally, rGDF11 increased the levels of reactive oxygen species and malondialdehyde due to the upregulation of nicotinamide adenine dinucleotide phosphate oxidase 4 (Nox4) following rGDF11 treatment. Conversely, GDF11 knockdown reduced ISO-induced apoptosis by inhibiting oxidative stress injury. The results suggested that GDF11 production was upregulated in ISO-induced rats with HF and in ISO-treated H9C2 cells, and that rGDF11 treatment increased ISO-induced oxidative stress injury by upregulating Nox4 in H9C2 cells.

Background: Patients with chronic pancreatitis (CP) have an increased risk of developing pancreatic cancer (PC). The purpose of this study was to identify predictors of PC in CP patients.Methods: Electronic medical records (EMRs) of CP patients from two cohorts were collected, and a logistic regression analysis was performed to investigate the risk factors for PC. Subsequently, we validated the value of the risk prediction model with the EMRs of a third cohort. Results:The derivation cohort consisted of 2,545 CP patients, and among them, 14 patients developed PC 7 years after CP diagnosis. Cyst of the pancreas [COP; odds ratio (OR): 4.37, 95% confidence interval (CI):

Maize (Zea mays L.) is the most important food security crop worldwide. Northern corn leaf blight (NCLB), caused by Exserohilum turcicum, severely reduces production causing millions of dollars in losses worldwide. Therefore, this study aimed to identify significant QTLs associated with NCLB by utilizing next-generation sequencing-based bulked-segregant analysis (BSA). Parental lines GML71 (resistant) and Gui A10341 (susceptible) were used to develop segregating population F2. Two bulks with 30 plants each were further selected from the segregating population for sequencing along with the parental lines. High throughput sequencing data was used for BSA. We identified 10 QTLs on Chr 1, Chr 2, Chr 3, and Chr 5 with 265 non-synonymous SNPs. Moreover, based on annotation information, we identified 27 candidate genes in the QTL regions. The candidate genes associated with disease resistance include AATP1, At4g24790, STICHEL-like 2, BI O 3-BIO1, ZAR1, SECA2, ABCG25, LECRK54, MKK7, MKK9, RLK902, and DEAD-box ATP-dependent RNA helicase. The annotation information suggested their involvement in disease resistance-related pathways, including protein phosphorylation, cytoplasmic vesicle, protein serine/threonine kinase activity, and ATP binding pathways. Our study provides a substantial addition to the available information regarding QTLs associated with NCLB, and further functional verification of identified candidate genes can broaden the scope of understanding the NCLB resistance mechanism in maize.

BackgroundAcute kidney injury (AKI) following wasp stings is a serious and common health hazard, however the early prediction remains challenging. The study aimed to establish a model to predict AKI following wasp stings and validate it.MethodsIn the multicenter prospective cohort study, 508 patients with wasp stings from Jul 2015 to Dec 2019 were randomly divided into the training set (n = 381) and validation set (n = 127) for internal and external validation. A model that based on the multivariable logistic regression analysis was utilized to predict the probability of AKI following wasp stings by a predictive formula and a nomogram. The performances of the model were assessed by using the area under the curve (AUC) and accuracy (ACC) of the receiver operating characteristic curve. The calibration curves were utilized for estimating the consistency between the actual observed outcome and the nomogram predicted AKI probability. Decision curve analysis (DCA) demonstrated the net benefit associated with the use of the nomogram-derived probability for the prediction of AKI following wasp stings.Results Number of stings, hemoglobin (HB) < 110 g/dl, total bilirubin (TBI) > 34 mg/dl, alanine transaminase (ALT) > 40 U/L and activated partial thromboplastin time (APTT) > 47 s were demonstrated as the independent risk factors for AKI following wasp stings (all P value < 0.05) and were incorporated into the model. The performances of the model were validated (AUC = 0.912, ACC = 0.869 and AUC = 0.936, ACC = 0.898 in the training set and validation set respectively). The predictive formula and nomogram of the model could be utilized to predict the AKI following wasp stings, which having sufficient accuracies, good predictive capabilities and good net benefits.ConclusionIn conclusion, we proved that number of stings, HB < 110 g/dl, TBI > 34 mg/dl, ALT > 40 U/L and APTT > 47 s were independence risk factors for AKI following wasp stings. The predictive formula and the individual nomogram of the model might serve as promising predictive tools to assess the probability of the AKI following wasp stings.