Association between Polymorphisms of ERCC1 and Response in Patients with Advanced Non-small Cell Lung Cancer Receiving Cisplatin-based Chemotherapy

Background and objective Results of studies on genetic polymorphisms of ERCC1 gene in DNA repair pathway which may affect response to platinum-based chemotherapy and survival in patients with non-small cell lung cancer are conflicting. The aim of this study is to prospectively assess the association between single nucleotide polymorphisms of C8092A and codon118 in ERCC1 and drug response in 90 patients with advanced non-small cell lung cancer treated with cisplatin-based chemotherapy. Methods All patients were treated with cisplatin-based chemotherapy. Genotypes of ERCC1 C8092A and codon118 were examined by sequencing, and the association between genotypes and response was evaluated. Results Genotype frequencies of ERCC1 C8092A were CC 40.0% (36/90), CA 48.9% (44/90) and AA 11.1% (10/90), frequencies of codon118 were CC 58.9% (53/90), CT 34.4% (31/90) and TT 6.7% (6/90). There was no significant difference in response rate of patients carrying with CC, compared with CA plus AA in C8092A (33.3% vs 29.6%, P=0.71). Response rate of patients carrying with CC in ERCC1 118 was 32.1%, 24.3% with CT plus CC (P=0.43). There was no difference in progression free survival between patients carrying with CC and CT plus TT in C8092A (5.2 months vs 5.4 months, P=0.62). There was no difference in progression free survival between patients carrying with CC and CA plus AA (5.5 months vs 5.3 months, P=0.59). Conclusion The results suggest that there is no association between polymorphisms in ERCC1 C8092A and codon118 and response in patients with advanced non-small cell lung cancer receiving cisplatin-based chemotherapy

Improving Lake Mixing Process Simulations in the Community Land Model by Using K Profile Parameterization

We improved lake mixing process simulations by applying a vertical mixing scheme, K profile parameterization (KPP), in the Community Land Model (CLM) version 4.5, developed by the National Center for Atmospheric Research. Vertical mixing of the lake water column can significantly affect heat transfer and vertical temperature profiles. However, the current vertical mixing scheme in CLM requires an arbitrarily enlarged eddy diffusivity to enhance water mixing. The coupled CLM-KPP considers a boundary layer for eddy development, and in the lake interior water mixing is associated with internal wave activity and shear instability. We chose a lake in Arctic Alaska and a lake on the Tibetan Plateau to evaluate this improved lake model. Results demonstrated that CLM-KPP reproduced the observed lake mixing and significantly improved lake temperature simulations when compared to the original CLM. Our newly improved model better represents the transition between stratification and turnover. This improved lake model has great potential for reliable physical lake process predictions and better ecosystem services

Pilot-scale open fermentation of food waste to produce lactic acid without inoculum addition

Lactic acid (LA) production through non-sterilized open fermentation of food waste without inoculum addition was investigated. Results from laboratory-scale experiments indicated that the optimal solid–liquid ratio was 1 : 1 (water content 91.7%). Addition of α-amylase could significantly accelerate the hydrolysis of food waste and consequently increase LA productivity. During the pilot-scale fermentation, the highest LA concentration (21.5 g L−1) was achieved at 48 h. After 48 h, the LA concentration decreased and the byproducts (mainly acetic acid and propionic acid) concentration increased, which was likely caused by the increased cell density of microorganisms other than lactic acid bacteria. After 48 h of fermentation, the total sugar and suspended solids concentration decreased by 65.7% and 61.8%, respectively, suggesting that the LA fermentation was beneficial to achieve the harmless reduction of food waste. The results from this study demonstrated the feasibility of LA production from food waste fermentation without sterilization and extra inoculum addition

Early identification of Parkinson’s disease with anxiety based on combined clinical and MRI features

ObjectiveTo identify cortical and subcortical volume, thickness and cortical area features and the networks they constituted related to anxiety in Parkinson’s disease (PD) using structural magnetic resonance imaging (sMRI), and to integrate multimodal features based on machine learning to identify PD-related anxiety.MethodsA total of 219 patients with PD were retrospectively enrolled in the study. 291 sMRI features including cortical volume, subcortical volume, cortical thickness, and cortical area, as well as 17 clinical features, were extracted. Graph theory analysis was used to explore structural networks. A support vector machine (SVM) combination model, which used both sMRI and clinical features to identify participants with PD-related anxiety, was developed and evaluated. The performance of SVM models were evaluated. The mean impact value (MIV) of the feature importance evaluation algorithm was used to rank the relative importance of sMRI features and clinical features within the model.Results17 significant sMRI variables associated with PD-related anxiety was used to build a brain structural network. And seven sMRI and 5 clinical features with statistically significant differences were incorporated into the SVM model. The comprehensive model achieved higher performance than clinical features or sMRI features did alone, with an accuracy of 0.88, a precision of 0.86, a sensitivity of 0.81, an F1-Score of 0.83, a macro-average of 0.85, a weighted-average of 0.92, an AUC of 0.88, and a result of 10-fold cross-validation of 0.91 in test set. The sMRI feature right medialorbitofrontal thickness had the highest impact on the prediction model.ConclusionWe identified the brain structural features and networks related to anxiety in PD, and developed and internally validated a comprehensive model with multimodal features in identifying

Identification of hub genes and key signaling pathways by weighted gene co-expression network analysis for human aortic stenosis and insufficiency

BackgroundHuman aortic valve stenosis (AS) and insufficiency (AI) are common diseases in aging population. Identifying the molecular regulatory networks of AS and AI is expected to offer novel perspectives for AS and AI treatment.MethodsHighly correlated modules with the progression of AS and AI were identified by weighted genes co-expression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by the clusterProfiler program package. Differentially expressed genes (DEGs) were identified by the DESeqDataSetFromMatrix function of the DESeq2 program package. The protein-protein interaction (PPI) network analyses were implemented using the STRING online tool and visualized with Cytoscape software. The DEGs in AS and AI groups were overlapped with the top 30 genes with highest connectivity to screen out ten hub genes. The ten hub genes were verified by analyzing the data in high throughput RNA-sequencing dataset and real-time PCR assay using AS and AI aortic valve samples.ResultsBy WGCNA algorithm, 302 highly correlated genes with the degree of AS, degree of AI, and heart failure were identified from highly correlated modules. GO analyses showed that highly correlated genes had close relationship with collagen fibril organization, extracellular matrix organization and extracellular structure organization. KEGG analyses also manifested that protein digestion and absorption, and glutathione metabolism were probably involved in AS and AI pathological courses. Moreover, DEGs were picked out for 302 highly correlated genes in AS and AI groups relative to the normal control group. The PPI network analyses indicated the connectivity among these highly correlated genes. Finally, ten hub genes (CD74, COL1A1, TXNRD1, CCND1, COL5A1, SERPINH1, BCL6, ITGA10, FOS, and JUNB) in AS and AI were found out and verified.ConclusionOur study may provide the underlying molecular targets for the mechanism research, diagnosis, and treatment of AS and AI in the future

1A6/DRIM, a Novel t-UTP, Activates RNA Polymerase I Transcription and Promotes Cell Proliferation

BACKGROUND: Ribosome biogenesis is required for protein synthesis and cell proliferation. Ribosome subunits are assembled in the nucleolus following transcription of a 47S ribosome RNA precursor by RNA polymerase I and rRNA processing to produce mature 18S, 28S and 5.8S rRNAs. The 18S rRNA is incorporated into the ribosomal small subunit, whereas the 28S and 5.8S rRNAs are incorporated into the ribosomal large subunit. Pol I transcription and rRNA processing are coordinated processes and this coordination has been demonstrated to be mediated by a subset of U3 proteins known as t-UTPs. Up to date, five t-UTPs have been identified in humans but the mechanism(s) that function in the t-UTP(s) activation of Pol I remain unknown. In this study we have identified 1A6/DRIM, which was identified as UTP20 in our previous study, as a t-UTP. In the present study, we investigated the function and mechanism of 1A6/DRIM in Pol I transcription. METHODOLOGY/PRINCIPAL FINDINGS: Knockdown of 1A6/DRIM by siRNA resulted in a decreased 47S pre-rRNA level as determined by Northern blotting. Ectopic expression of 1A6/DRIM activated and knockdown of 1A6/DRIM inhibited the human rDNA promoter as evaluated with luciferase reporter. Chromatin immunoprecipitation (ChIP) experiments showed that 1A6/DRIM bound UBF and the rDNA promoter. Re-ChIP assay showed that 1A6/DRIM interacts with UBF at the rDNA promoter. Immunoprecipitation confirmed the interaction between 1A6/DRIM and the nucleolar acetyl-transferase hALP. It is of note that knockdown of 1A6/DRIM dramatically inhibited UBF acetylation. A finding of significance was that 1A6/DRIM depletion, as a kind of nucleolar stress, caused an increase in p53 level and inhibited cell proliferation by arresting cells at G1. CONCLUSIONS: We identify 1A6/DRIM as a novel t-UTP. Our results suggest that 1A6/DRIM activates Pol I transcription most likely by associating with both hALP and UBF and thereby affecting the acetylation of UBF

Photo(electro)catalyst of Flower-Like Cobalt Oxide Co-Doped g-C3N4: Degradation of Methylene Blue under Visible Light Illumination

This work reported on the solid state synthesis of the flower-like Co(OH)2/g-C3N4 nanocomposite, using a modified hydrothermal method, for the degradation of MB, an organic pollutant. These nanomaterials were characterized for structure, surface morphology and composition using XRD, SEM and XPS, respectively. The photocatalytic activities of the as-prepared materials loaded on FTO glass substrates were evaluated for their degradation of methylene blue (MB) under visible irradiation and constant voltage. The promoting effect of Fw-Co(OH)2 on g-C3N4 was investigated under the influence of introduced various Co(OH)2 amounts. The fabricated composite catalyst showed significantly improved catalytic performance compared to pristine g-C3N4. Degradation by 25% Fw-Co(OH)2/g-C3N4 can achieve about a 100% ratio within 180 min under visible light in a three-electrode system. Moreover, Fw-Co(OH)2/g-C3N4 was easily regenerated and reused, and still possessed good degradation ability. These results suggest that Fw-Co(OH)2/g-C3N4 could be promising for application as a low-cost and high-efficiency catalyst for wastewater treatment and organic pollutant degradation