Laser Surface Texturing for Ground Surface: Frictional Effect of Plateau Roughness and Surface Textures under Oil Lubrication

Laser surface texturing has proven beneficial in improving tribological performance in different lubrication regimes. However, the interaction between plateau roughness and surface texture remains to be further investigated, even though rough surfaces are common in engineering applications. In the present study, we investigated the frictional influence of surface texturing of ground surfaces under different lubrication conditions. Channel textures with different depths and area ratios were fabricated on ground surfaces, and their friction was tested in reciprocating tests. The experimental findings indicate that the textures caused increased friction for ground surfaces under boundary or mixed lubrication when the interface is well lubricated. Nevertheless, when the oil supply was limited, an up to 40% friction reduction was observed under test conditions

Recent advances in clustering methods for protein interaction networks

The increasing availability of large-scale protein-protein interaction data has made it possible to understand the basic components and organization of cell machinery from the network level. The arising challenge is how to analyze such complex interacting data to reveal the principles of cellular organization, processes and functions. Many studies have shown that clustering protein interaction network is an effective approach for identifying protein complexes or functional modules, which has become a major research topic in systems biology. In this review, recent advances in clustering methods for protein interaction networks will be presented in detail. The predictions of protein functions and interactions based on modules will be covered. Finally, the performance of different clustering methods will be compared and the directions for future research will be discussed

Periodic and uniform nanogratings formed on cemented carbide by femtosecond laser scanning

Periodic and uniform nanogratings are fabricated by femtosecond laser scanning on cemented carbide. Specifically, three experiments are designed to study the influence of single pulse energy, scanning speed, and scanning spacing on the period and the uniformity of the formed nanogratings. The results show that the sample with single pulse energy of 2 μJ, scanning speed of 1000 μm/s, and scanning spacing of 5 μm shows the best quality of nanogratings among all the tested samples at different processing parameters. The uniformity of the nanogratings is largely determined by single pulse energy, scanning speed, and scanning spacing. Single pulse energy and scanning speed significantly affect the period of the nanogratings, whereas the period of the nanogratings maintains a fixed value under different scanning spacings. The period of the nanogratings increases gradually with the decrease of the single pulse energy and the increase of the scanning speed, respectively

Primary Tumor Standardized Uptake Value Measured on F18-Fluorodeoxyglucose Positron Emission Tomography Is of Prediction Value for Survival and Local Control in Non–Small-Cell Lung Cancer Receiving Radiotherapy: Meta-Analysis

Introduction:The 2-[18F]-Fluorodeoxyglucose (FDG) positron emission tomography (PET/CT) has become an imaging tool for clinical assessment of tumor, node, metastasis in non–small-cell lung cancer (NSCLC). Primary tumor maximum standardized uptake value (SUVmax) on 18F-FDG PET/CT before and after radiation therapy (RT) has been studied as a potential prognostic factor for NSCLC patients receiving radiotherapy. However, the sample sizes of most studies were small, and the results of the prediction value of SUVmax remained undetermined, which lead us to perform a meta-analysis to improve the precision in estimating its effect.Methods:We performed a meta-analysis of published literature for primary tumor SUVmax-based biomarkers of the outcome of NSCLC receiving radiotherapy. The required data for estimation of individual hazard ratios (HRs) to compare patients with a low and a high SUVmax were extracted from each publication. A combined HR was calculated by Stata statistical software (Version 11). All of the results were verified by two persons to ensure its accuracy.Results:Thirteen studies were finally included into this meta-analysis; data are available in 13 studies for pre-RT primary tumor SUVmax and in five studies for post-RT. For overall survival, the combined HR estimate was 1.05 (95% confidence interval [CI], 1.02–1.08) and 1.32 (95% CI, 1.15–1.51) for pre-RT SUVmax and post-RT SUVmax, respectively; 1.26 (95% CI, 1.05–1.52) and 2.01 (95% CI, 1.16–3.46) for local control (LC). In stereotactic body radiotherapy (SBRT) group, HR for LC was 1.11 (95% CI, 1.06–1.18) and 2.19 (95% CI, 1.34–3.60) for pre-SBRT SUVmax and post-SBRT SUVmax, respectively.Conclusion:Both pre-RT and post-RT primary tumor SUVmax can predict the outcome of patients with NSCLC treated with radiotherapy. Patients with high levels of pre-RT SUVmax seemed to have poorer overall survival and LC

Identifying New Cancer Genes Based on the Integration of Annotated Gene Sets Via Hypergraph Neural Networks

Motivation Identifying cancer genes remains a significant challenge in cancer genomics research. Annotated gene sets encode functional associations among multiple genes, and cancer genes have been shown to cluster in hallmark signaling pathways and biological processes. The knowledge of annotated gene sets is critical for discovering cancer genes but remains to be fully exploited. Results Here, we present the DIsease-Specific Hypergraph neural network (DISHyper), a hypergraph-based computational method that integrates the knowledge from multiple types of annotated gene sets to predict cancer genes. First, our benchmark results demonstrate that DISHyper outperforms the existing state-of-the-art methods and highlight the advantages of employing hypergraphs for representing annotated gene sets. Second, we validate the accuracy of DISHyper-predicted cancer genes using functional validation results and multiple independent functional genomics data. Third, our model predicts 44 novel cancer genes, and subsequent analysis shows their significant associations with multiple types of cancers. Overall, our study provides a new perspective for discovering cancer genes and reveals previously undiscovered cancer genes. Availability and implementation DISHyper is freely available for download at https://github.com/genemine/DISHyper

cTFbase: a database for comparative genomics of transcription factors in cyanobacteria

BACKGROUND: Comprehensive identification and classification of the transcription factors (TFs) in a given genome is an important aspect in understanding transcriptional regulatory networks of a specific organism. Cyanobacteria are an ancient group of gram-negative bacteria with strong variation in genome size ranging from about 1.6 to 9.1 Mb and little is known about their TF repertoires. Therefore, we constructed the cTFbase database to classify and analyze all the putative TFs in cyanobacterial genomes, followed by genome-wide comparative analysis. DESCRIPTION: In the current release, cTFbase contains 1288 putative TFs identified from 21 fully sequenced cyanobacterial genomes. Through its user-friendly interactive interface, users can employ various criteria to retrieve all TF sequences and their detailed annotation information, including sequence features, domain architecture and sequence similarity against the linked databases. Furthermore, cTFbase provides phylogenetic trees of individual TF family, multiple sequence alignments of the DNA-binding domains and ortholog identification from any selected genomes. Comparative analysis revealed great variability of the TF sequences in cyanobacterial genomes. The high variance on the gene number and domain organization would be related to their diverse biological functions and their adaptation to various environmental conditions. CONCLUSION: cTFbase provides a centralized warehouse for comparative analysis of putative TFs in cyanobacterial genomes. The availability of such an extensive database would be of great interest for the community of researchers working on TFs or transcriptional regulatory networks in cyanobacteria. cTFbase can be freely accessible at and will be continuously updated when the newly sequenced cyanobacterial genomes are available