The Clinical Signifcance of Expression of ERCC1 and PKCalpha in Non-small Cell Lung Cancer

Background and objective Excision repair cross-complementing 1 (Excision-Repair Cross-Complementing 1, ERCC1), an important member of the DNA repair gene family, plays a key role in nucleotide excision repair and apoptosis of tumor cells. Protein kinase C-α (Protein kinase C, PKCα), an isozyme in protein kinase C family, is an important signaling molecule in signal transduction pathways of tumors, which has been implicated in malignant transformation and proliferation. The aim of this study was to explore the clinical significance of ERCC1 and PKCα in non-small cell lung cancer (NSCLC). Methods The expression of ERCC1 and PKCα were examined by immunohistochemistry (IHC) in the specimens of 51 cases of NSCLC patients tissue and 21 cases of paracancerous tissue. The relationship between detected data and patients′ clinical parameters was analyzed by SPSS 13.0 software. Results The positive expression rate of ERCC1 and PKCα in NSCLC tissues was significantly higher than paracancerous tissues (Ρ<0.05). Expression of ERCC1 was closely related to clinical stage and N stage. The positive rate of ERCC1 was higher in III+IV or N1+N2 stage patients compared with I+II or N0 stage (Ρ=0.011, P=0.015). We also found that 5-year survival of negative group of ERCC1 was remarkably higher than that of positive group by χ2 test (Ρ<0.05). Expression of ERCC1 was positively correlative to PKCα by Spearman′s correlation analysis (r=0.425, P=0.002) in NSCLC. Conclusion The results suggest ERCC1 and PKCα might be correlated with the development of NSCLC. ERCC1 might be related to prognosis of NSCLC. There might be existed a mechanism of coordination or regulation between ERCC1 and PKCα

Explainable machine learning-based prediction model for diabetic nephropathy

The aim of this study is to analyze the effect of serum metabolites on diabetic nephropathy (DN) and predict the prevalence of DN through a machine learning approach. The dataset consists of 548 patients from April 2018 to April 2019 in Second Affiliated Hospital of Dalian Medical University (SAHDMU). We select the optimal 38 features through a Least absolute shrinkage and selection operator (LASSO) regression model and a 10-fold cross-validation. We compare four machine learning algorithms, including eXtreme Gradient Boosting (XGB), random forest, decision tree and logistic regression, by AUC-ROC curves, decision curves, calibration curves. We quantify feature importance and interaction effects in the optimal predictive model by Shapley Additive exPlanations (SHAP) method. The XGB model has the best performance to screen for DN with the highest AUC value of 0.966. The XGB model also gains more clinical net benefits than others and the fitting degree is better. In addition, there are significant interactions between serum metabolites and duration of diabetes. We develop a predictive model by XGB algorithm to screen for DN. C2, C5DC, Tyr, Ser, Met, C24, C4DC, and Cys have great contribution in the model, and can possibly be biomarkers for DN

Transcriptomics of Gabra4 knockout mice reveals common NMDAR pathways underlying autism, memory, and epilepsy

Autism spectrum disorder (ASD) is a neuronal developmental disorder with impaired social interaction and communication, often with abnormal intelligence and comorbidity with epilepsy. Disturbances in synaptic transmission, including the GABAergic, glutamatergic, and serotonergic systems, are known to be involved in the pathogenesis of this disorder, yet we do not know if there is a common molecular mechanism. As mutations in the GABAergic receptor subunit gene GABRA4 are reported in patients with ASD, we eliminated the Gabra4 gene in mice and found that the Gabra4 knockout mice showed autistic-like behavior, enhanced spatial memory, and attenuated susceptibility to pentylenetetrazol-induced seizures, a constellation of symptoms resembling human high-functioning autism. To search for potential molecular pathways involved in these phenotypes, we performed a hippocampal transcriptome profiling, constructed a hippocampal interactome network, and revealed an upregulation of the NMDAR system at the center of the converged pathways underlying high-functioning autism-like and anti-epilepsy phenotypes

Effect of Kangfuxin

Objective. To evaluate the efficacy and safety of Kangfuxin Solution, a pure Chinese herbal medicine, on mucositis induced by chemoradiotherapy in nasopharyngeal carcinoma patients. Methods. A randomized, parallel-group, multicenter clinical study was performed. A total of 240 patients were randomized to receive either Kangfuxin Solution (test group) or compound borax gargle (control group) during chemoradiotherapy. Oral mucositis, upper gastrointestinal mucositis, and oral pain were evaluated by Common Terminology Criteria for Adverse Events (CTCAE) v3.0 and the Verbal Rating Scale (VRS). Results. Of 240 patients enrolled, 215 were eligible for efficacy analysis. Compared with the control group, the incidence and severity of oral mucositis in the test group were significantly reduced (P=0.01). The time to different grade of oral mucositis occurrence (grade 1, 2, or 3) was longer in test group (P<0.01), and the accumulated radiation dose was also higher in test group comparing to the control group (P<0.05). The test group showed lower incidence of oral pain and gastrointestinal mucositis than the control group (P<0.01). No significant adverse events were observed. Conclusion. Kangfuxin Solution demonstrated its superiority to compound borax gargle on mucositis induced by chemoradiotherapy. Its safety is acceptable for clinical application

Transcriptomic analyses of regenerating adult feathers in chicken

Transcriptome Expression Data. Table of mapped reads to Galgal4 transcripts for all 15 data sets. FPKM (Fragments per kilobase of exon per million fragments mapped): normalized transcript abundance values for each gene in the indicated tissues. (CSV 1314 kb

High-Resolution Numerical Simulation of the Extreme Rainfall Associated with Typhoon Morakot. Part I: Comparing the Impact of Microphysics and PBL Parameterizations with Observations

Typhoon Morakot hit Taiwan the night of 7 August 2009 as a Category 1 storm and caused up to 3000 mm of rain, leading to the worst flooding there in 50 years as well as devastating mudslides. The Weather Research and Forecasting model (WRF) is used at high resolution to simulate this extreme weather event. The model results indicate that WRF is able to capture the amount and location of the observed surface rainfall and that the typhoon-induced circulation, orographic lifting and a moisture-abundant southwest flow are the main mechanisms that together produced the tremendous rainfall in this case. Furthermore, the model results suggest that the agreement with the observed rainfall is due to the simulated storm track and intensity being in relatively good agreement with the observed. Additional simulations were made to examine the sensitivity of this case to model physics (microphysics and planetary boundary layer or PBL). Both warm rain only as well as improved microphysics yield similar significant rain amounts at the same locations as the control case. The improved microphysics lead to a better storm intensity early on but later exceed the observed intensities by about 10 hPa. The stronger storm arises from less evaporative cooling from cloud and rain and consequently weaker simulated downdrafts. Warm rain results closely match the control (i.e., the track, intensity, and maximum rainfall locations/amounts), implying ice processes (i.e., additional heat release due to ice processes) have only a secondary effect on surface rainfall. Results are less sensitive to using different PBL schemes than different microphysics

ALS/FTD Mutation-Induced Phase Transition of FUS Liquid Droplets and Reversible Hydrogels into Irreversible Hydrogels Impairs RNP Granule Function.

The mechanisms by which mutations in FUS and other RNA binding proteins cause ALS and FTD remain controversial. We propose a model in which low-complexity (LC) domains of FUS drive its physiologically reversible assembly into membrane-free, liquid droplet and hydrogel-like structures. ALS/FTD mutations in LC or non-LC domains induce further phase transition into poorly soluble fibrillar hydrogels distinct from conventional amyloids. These assemblies are necessary and sufficient for neurotoxicity in a C. elegans model of FUS-dependent neurodegeneration. They trap other ribonucleoprotein (RNP) granule components and disrupt RNP granule function. One consequence is impairment of new protein synthesis by cytoplasmic RNP granules in axon terminals, where RNP granules regulate local RNA metabolism and translation. Nuclear FUS granules may be similarly affected. Inhibiting formation of these fibrillar hydrogel assemblies mitigates neurotoxicity and suggests a potential therapeutic strategy that may also be applicable to ALS/FTD associated with mutations in other RNA binding proteins.Supported by Canadian Institutes of Health Research (PEF, PStGH), Alzheimer Society of Ontario (PEF, PStGH), Wellcome Trust (PStGH, MEV, CFK, GSK, DR, CEH), Medical Research Council (PStGH, MEV, CFK, GSK), National Institutes of Health Research, Alzheimer Research UK (CFK, GSK), Gates Cambridge Scholarship (JQL), Engineering and Physical Sciences Research Council (CFK, GSK), European Research Council Starting Grant RIBOMYLOME_309545 (GGT), European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement no. 322817 (CEH), and National Institute of Neurological Disorders and Stroke R01 NS07377 (NAS). The authors thank Tom Cech and Roy Parker for helpful discussions.This is the final version of the article. It was first available from Elsevier via http://dx.doi.org/10.1016/j.neuron.2015.10.03

The Large Enriched Germanium Experiment for Neutrinoless Double Beta Decay (LEGEND)

The observation of neutrinoless double-beta decay (0${\nu}{\beta}{\beta}$) would show that lepton number is violated, reveal that neutrinos are Majorana particles, and provide information on neutrino mass. A discovery-capable experiment covering the inverted ordering region, with effective Majorana neutrino masses of 15 - 50 meV, will require a tonne-scale experiment with excellent energy resolution and extremely low backgrounds, at the level of $\sim$0.1 count /(FWHM$\cdot$t$\cdot$yr) in the region of the signal. The current generation $^{76}$Ge experiments GERDA and the MAJORANA DEMONSTRATOR utilizing high purity Germanium detectors with an intrinsic energy resolution of 0.12%, have achieved the lowest backgrounds by over an order of magnitude in the 0${\nu}{\beta}{\beta}$ signal region of all 0${\nu}{\beta}{\beta}$ experiments. Building on this success, the LEGEND collaboration has been formed to pursue a tonne-scale $^{76}$Ge experiment. The collaboration aims to develop a phased 0${\nu}{\beta}{\beta}$ experimental program with discovery potential at a half-life approaching or at $10^{28}$ years, using existing resources as appropriate to expedite physics results.Comment: Proceedings of the MEDEX'17 meeting (Prague, May 29 - June 2, 2017

Phosphoproteomics Identifies Oncogenic Ras Signaling Targets and Their Involvement in Lung Adenocarcinomas

Ras is frequently mutated in a variety of human cancers, including lung cancer, leading to constitutive activation of MAPK signaling. Despite decades of research focused on the Ras oncogene, Ras-targeted phosphorylation events and signaling pathways have not been described on a proteome-wide scale.By functional phosphoproteomics, we studied the molecular mechanics of oncogenic Ras signaling using a pathway-based approach. We identified Ras-regulated phosphorylation events (n = 77) using label-free comparative proteomics analysis of immortalized human bronchial epithelial cells with and without the expression of oncogenic Ras. Many were newly identified as potential targets of the Ras signaling pathway. A majority (∼60%) of the Ras-targeted events consisted of a [pSer/Thr]-Pro motif, indicating the involvement of proline-directed kinases. By integrating the phosphorylated signatures into the Pathway Interaction Database, we further inferred Ras-regulated pathways, including MAPK signaling and other novel cascades, in governing diverse functions such as gene expression, apoptosis, cell growth, and RNA processing. Comparisons of Ras-regulated phosphorylation events, pathways, and related kinases in lung cancer-derived cells supported a role of oncogenic Ras signaling in lung adenocarcinoma A549 and H322 cells, but not in large cell carcinoma H1299 cells.This study reveals phosphorylation events, signaling networks, and molecular functions that are regulated by oncogenic Ras. The results observed in this study may aid to extend our knowledge on Ras signaling in lung cancer

Long-Baseline Neutrino Facility (LBNF) and Deep Underground Neutrino Experiment (DUNE) Conceptual Design Report Volume 2: The Physics Program for DUNE at LBNF

The Physics Program for the Deep Underground Neutrino Experiment (DUNE) at the Fermilab Long-Baseline Neutrino Facility (LBNF) is described