Salvia miltiorrhiza injection ameliorates myocardial ischemia-reperfusion injury via downregulation of PECAM-1

Purpose: To investigate the effect of Salvia miltiorrhiza injection on myocardial ischemia-reperfusion injury and PECAM-1 related pathways. Method: Male Wistar rats were used for establishment of myocardial ischemia-reperfusion model. The rats were randomly assigned to four groups: experimental group, low dose group (Salvia miltiorrhiza injection, 10 mL/kg/day), moderate dose group (Salvia miltiorrhiza injection, 20 mL/kg/day) and high dose group (Salvia miltiorrhiza injection, 40 mL/kg/day). Myocardial ischemia-reperfusion model was established in the four groups. Evans-TTC staining was used to assess relative area of ischemiareperfusion injury. Blood samples were collected for assay of PECAM-1 expression using enzymelinked immunosorbent assay (ELISA). Fresh blood platelets were collected in all groups, and divided into two groups - control group (normal culture) and experimental group (Salvia miltiorrhiza injection). The expression of PECAM-1 in blood platelets was assayed using Western blot. Result: Compared with the experimental group, Salvia miltiorrhiza injection ameliorated myocardial ischemia-reperfusion injury, and decreased the infarction area seen in Evans/TTC staining. PECAM-1 expression in blood was decreased by Salvia miltiorrhiza injection. Blood platelets dysfunction was induced after myocardial ischemia-reperfusion, and the level of PECAM-1 increased. However, Salvia miltiorrhiza injection treatment downregulated the expression of PECAM-1 after myocardial ischemiareperfusion. Conclusion: Salvia miltiorrhiza injection maintains normal function of blood platelets and ameliorates myocardial ischemia-reperfusion injury by decreasing expression of PECAM-1

An Ensemble Deep Convolutional Neural Network Model with Improved D-S Evidence Fusion for Bearing Fault Diagnosis

Intelligent machine health monitoring and fault diagnosis are becoming increasingly important for modern manufacturing industries. Current fault diagnosis approaches mostly depend on expert-designed features for building prediction models. In this paper, we proposed IDSCNN, a novel bearing fault diagnosis algorithm based on ensemble deep convolutional neural networks and an improved Dempster–Shafer theory based evidence fusion. The convolutional neural networks take the root mean square (RMS) maps from the FFT (Fast Fourier Transformation) features of the vibration signals from two sensors as inputs. The improved D-S evidence theory is implemented via distance matrix from evidences and modified Gini Index. Extensive evaluations of the IDSCNN on the Case Western Reserve Dataset showed that our IDSCNN algorithm can achieve better fault diagnosis performance than existing machine learning methods by fusing complementary or conflicting evidences from different models and sensors and adapting to different load conditions

An Ensemble Deep Convolutional Neural Network Model with Improved D-S Evidence Fusion for Bearing Fault Diagnosis

Intelligent machine health monitoring and fault diagnosis are becoming increasingly important for modern manufacturing industries. Current fault diagnosis approaches mostly depend on expert-designed features for building prediction models. In this paper, we proposed IDSCNN, a novel bearing fault diagnosis algorithm based on ensemble deep convolutional neural networks and an improved Dempster–Shafer theory based evidence fusion. The convolutional neural networks take the root mean square (RMS) maps from the FFT (Fast Fourier Transformation) features of the vibration signals from two sensors as inputs. The improved D-S evidence theory is implemented via distance matrix from evidences and modified Gini Index. Extensive evaluations of the IDSCNN on the Case Western Reserve Dataset showed that our IDSCNN algorithm can achieve better fault diagnosis performance than existing machine learning methods by fusing complementary or conflicting evidences from different models and sensors and adapting to different load conditions

Postoperative Radiotherapy and N2 Non-small Cell Lung Cancer Prognosis: A Retrospective Study Based on Surveillance, Epidemiology, and End Results Database

The purpose of this study is to clarify the significance of postoperative radiotherapy for N2 lung cancer. This study aimed to investigate the effect of postoperative radiotherapy on the survival and prognosis of patients with N2 lung cancer. Data from 12,000 patients with N2 lung cancer were extracted from the Surveillance, Epidemiology, and End Results database (2004-2012). Age at disease onset and 5-year survival rates were calculated. Survival curves were plotted using the Kaplan-Meier method. The univariate log-rank test was performed. Multivariate Cox regression were used to examine factors affecting survival. Patients’ median age was 67 years (mean 66.46 ± 10.03). The 5-year survival rate was 12.55%. Univariate analysis revealed age, sex, pathology, and treatment regimen as factors affecting prognosis. In multivariate analysis, when compared to postoperative chemotherapy, postoperative chemoradiotherapy was better associated with survival benefits (hazard ratio [HR]= 0.85, 95% confidence interval [CI]: 0.813-0.898, P <0.001). Propensity score matching revealed that patients who had received postoperative chemoradiotherapy had a better prognosis than did patients who had received postoperative chemotherapy (HR=0.869, 95% CI: 0.817-0.925, P <0.001). Female patients and patients aged <65 years had a better prognosis than did their counterparts. Patients with adenocarcinoma had a better prognosis than did patients with squamous cell carcinoma. Moreover, prognosis worsened with increasing disease T stage. Patients who had received postoperative chemoradiotherapy had a better prognosis than did patients who had received postoperative chemotherapy. Postoperative radiotherapy was an independent prognostic factor in this patient group

Effect of light- and dark-germination on the phenolic biosynthesis, phytochemical profiles, and antioxidant activities in sweet corn (Zea mays L.) sprouts

Sweet corn is one of the most widely planted crops in China. Sprouting of grains is a new processes to increase the nutritional value of grain products. The present study explores the effects of light on the nutritional quality of sweet corn sprouts. Gene expression of phenolic biosynthesis, phytochemical profiles and antioxidant activity were studied. Two treatments (light and dark) were selected and the morphological structure of sweet corn sprouts, as well as their biochemical composition were investigated to determine the effects of light on the regulation of genes responsible for nutritional compounds. Transcription analyses for three key-encoding genes in the biosynthesis of the precursors of phenolic were studied. Results revealed a negative regulation in the expression of ZmPAL with total phenolic content (TPC) in the light group. TPC and total flavonoid content (TFC) increased during germination and this was correlated with an increase in antioxidant activity (r = 0.95 and 1.0). The findings illustrate that the nutritional value of sweet corn for the consumer can be improved through germination to the euphylla stage

Effects of α-lipoic acid on growth performance, body composition, antioxidant status and lipid catabolism of juvenile Chinese mitten crab Eriocheir sinensis fed different lipid percentage

This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 24 month embargo from date of publication (Sept 2017) in accordance with the publisher’s archiving policyThis study evaluates the effects of dietary lipid percentage (7% and 13%) on growth performance, body composition, antioxidative status and hepatopancreas lipid catabolism of Chinese mitten crab Eriocheir sinensis. Each lipid diet was supplemented with three concentrations of α-lipoic acid at 0, 700 and 1400 mg/kg, and fed to E. sinensis juveniles for eight weeks. The weight gain and specific growth rate of crabs fed the diets supplemented with α-LA were significantly higher than those fed the control diet without α-LA, regardless of dietary lipid percentage. The α-LA significantly increased lipid accumulation in the whole body and hepatopancreas in a dose-dependent manner. Crabs fed 13% lipid showed a significantly higher hepatosomatic index than those fed 7% lipid. The mRNA expressions of triacylglycerol lipase and intracellular lipase increased with the increase of α-LA concentration in crabs fed 7% lipid. No significant difference was found in the CPT-1 mRNA expression among all treatments. The α-LA supplementation at 1400 mg/kg significantly improved oxidative stress due to lipid accumulation in the hepatopancreas of crabs fed 7% lipid as indicated by the high activity of superoxide dismutase and glutathione peroxidase and a low level of malondialdehyde. The diet with 13% lipid increased the lipid content in the hepatopancreas but suppressed glutathione peroxidase. Meanwhile, the total antioxidant capacity increased with the increase of α-LA concentration in crabs fed 13% lipid. This study indicates that α-LA supplementation can improve growth performance and accelerate lipid accumulation in the hepatopancreas by increasing lipid utilization efficiency. Furthermore, α-LA can relieve hepatopancreas oxidative damage induced by lipid accumulation and improve the health of E. sinensis

Estimates of daily ground-level NO2 concentrations in China based on big data and machine learning approaches

Nitrogen dioxide (NO2) is one of the most important atmospheric pollutants. However, current ground-level NO2 concentration data are lack of either high-resolution coverage or full coverage national wide, due to the poor quality of source data and the computing power of the models. To our knowledge, this study is the first to estimate the ground-level NO2 concentration in China with national coverage as well as relatively high spatiotemporal resolution (0.25 degree; daily intervals) over the newest past 6 years (2013-2018). We advanced a Random Forest model integrated K-means (RF-K) for the estimates with multi-source parameters. Besides meteorological parameters, satellite retrievals parameters, we also, for the first time, introduce socio-economic parameters to assess the impact by human activities. The results show that: (1) the RF-K model we developed shows better prediction performance than other models, with cross-validation R2 = 0.64 (MAPE = 34.78%). (2) The annual average concentration of NO2 in China showed a weak increasing trend . While in the economic zones such as Beijing-Tianjin-Hebei region, Yangtze River Delta, and Pearl River Delta, the NO2 concentration there even decreased or remained unchanged, especially in spring. Our dataset has verified that pollutant controlling targets have been achieved in these areas. With mapping daily nationwide ground-level NO2 concentrations, this study provides timely data with high quality for air quality management for China. We provide a universal model framework to quickly generate a timely national atmospheric pollutants concentration map with a high spatial-temporal resolution, based on improved machine learning methods

Cannabinoids help to unravel etiological aspects in common and bring hope for the treatment of autism and epilepsy

Desde 1843 que as propriedades anticonvulsivantes da Cannabis são conhecidas pela ciência ocidental. Em 1980, ensaios clínicos demonstraram que canabidiol possui atividade antiepilética em pacientes de epilepsia refratária, sendo sonolência o único efeito colateral. O embargo imposto pela proibição do uso medicinal da Cannabis, no entanto, prejudicou imensamente o desenvolvimento científico e a exploração dessas propriedades. Multiplicam-se, contudo, os casos bem sucedidos de uso ilegal e sem orientação para o tratamento de síndromes caracterizadas por epilepsia e autismo regressivo. Os resultados corroboram evidências científicas que indicam a existência de processos etiológicos comuns entre o autismo e a epilepsia. Estudos em modelos animais confirmam envolvimento do sistema endocanabinoide. Esses avanços apontam o início de uma revolução no entendimento e tratamento desses transtornos.Since 1843 the anticonvulsant properties of Cannabis are known by the Western science. In 1980, clinical trials have shown that cannabidiol has antiepileptic activity in refractory epilepsy patients, with drowsiness as the only side effect. The embargo imposed by banning medicinal Cannabis use, however, harmed scientific development and the exploration of these properties. However, there is a growing number of successful cases of illegal use without guidance for the treatment of syndromes characterized by epilepsy and regressive autism. The results corroborate scientific evidence that indicates the existence of common etiological aspects between autism and epilepsy. Studies in animal models have confirmed involvement of the endocannabinoid system. These advances indicate the beginning of a revolution in the understanding and treatment of these disorders