Hybrid composites of silica glass fibre/nano-hydroxyapatite/polylactic acid for medical application

Fibre reinforced composites (FRC) have shown great potential for the application of internal bone fixation due to mechanical properties that are similar to those of human cortical bones. Ternary composites of silica glass fibres, nano-hydroxyapatite (n-HA) and polylactic acid (PLA) were prepared by compression moulding and their mechanical properties were characterized in this study. With the volumetric content of glass fibre remained constantly at 30% and the volume fraction of n-HA increased from 0% to 5%, the flexural strengths of composites decreased from 625.68 MPa to 206.55 MPa, whereas a gradual increment of flexural modulus from 11.01 to 14.08 GPa were observed at the same time. Within a 28-day degradation period, the flexural strengths decreased by 30%, while no obvious trend of modulus variation was found. The flexural properties of all composites prepared in this study were all found to be close to the reported flexural properties. On the other hand, as more n-HA were incorporated, the water absorption percentages increased, whereas negligible mass loss were recorded. SEM images revealed that the impregnation of fibre mats was poor as loose fibres were observed, which shall be solved in future research to further improve the mechanical properties as well as endurance against degradation. © 2017 International Committee on Composite Materials. All rights reserved

Cooperative action in eukaryotic gene regulation: physical properties of a viral example

The Epstein-Barr virus (EBV) infects more than 90% of the human population, and is the cause of several both serious and mild diseases. It is a tumorivirus, and has been widely studied as a model system for gene (de)regulation in human. A central feature of the EBV life cycle is its ability to persist in human B cells in states denoted latency I, II and III. In latency III the host cell is driven to cell proliferation and hence expansion of the viral population, but does not enter the lytic pathway, and no new virions are produced, while the latency I state is almost completely dormant. In this paper we study a physico-chemical model of the switch between latency I and latency III in EBV. We show that the unusually large number of binding sites of two competing transcription factors, one viral and one from the host, serves to make the switch sharper (higher Hill coefficient), either by cooperative binding between molecules of the same species when they bind, or by competition between the two species if there is sufficient steric hindrance.Comment: 7 pages, 6 figures, 1 tabl

Site-Mutation of Hydrophobic Core Residues Synchronically Poise Super Interleukin 2 for Signaling: Identifying Distant Structural Effects through Affordable Computations

A superkine variant of interleukin-2 with six site mutations away from the binding interface developed from the yeast display technique has been previously characterized as undergoing a distal structure alteration which is responsible for its super-potency and provides an elegant case study with which to get insight about how to utilize allosteric effect to achieve desirable protein functions. By examining the dynamic network and the allosteric pathways related to those mutated residues using various computational approaches, we found that nanosecond time scale all-atom molecular dynamics simulations can identify the dynamic network as efficient as an ensemble algorithm. The differentiated pathways for the six core residues form a dynamic network that outlines the area of structure alteration. The results offer potentials of using affordable computing power to predict allosteric structure of mutants in knowledge-based mutagenesis.This work was supported by the Natural Science Foundation of China (No. 20475019 & 21473065 to Yanfang Cui), and Wuhan Science and Technology R&D Program (No. 201060623259 & No. 200860423220 to Yanfang Cui)

Twenty Novel Disease Group-Specific and 12 New Shared Macrophage Pathways in Eight Groups of 34 Diseases Including 24 Inflammatory Organ Diseases and 10 Types of Tumors.

The mechanisms underlying pathophysiological regulation of tissue macrophage (Mφ) subsets remain poorly understood. From the expression of 207 Mφ genes comprising 31 markers for 10 subsets, 45 transcription factors (TFs), 56 immunometabolism enzymes, 23 trained immunity (innate immune memory) enzymes, and 52 other genes in microarray data, we made the following findings. (1) When 34 inflammation diseases and tumor types were grouped into eight categories, there was differential expression of the 31 Mφ markers and 45 Mφ TFs, highlighted by 12 shared and 20 group-specific disease pathways. (2) Mφ in lung, liver, spleen, and intestine (LLSI-Mφ) express higher M1 Mφ markers than lean adipose tissue Mφ (ATMφ) physiologically. (3) Pro-adipogenic TFs C/EBPα and PPARγ and proinflammatory adipokine leptin upregulate the expression of M1 Mφ markers. (4) Among 10 immune checkpoint receptors (ICRs), LLSI-Mφ and bone marrow (BM) Mφ express higher levels of CD274 (PDL-1) than ATMφ, presumably to counteract the M1 dominant status via its reverse signaling behavior. (5) Among 24 intercellular communication exosome mediators, LLSI- and BM- Mφ prefer to use RAB27A and STX3 than RAB31 and YKT6, suggesting new inflammatory exosome mediators for propagating inflammation. (6) Mφ in peritoneal tissue and LLSI-Mφ upregulate higher levels of immunometabolism enzymes than does ATMφ. (7) Mφ from peritoneum and LLSI-Mφ upregulate more trained immunity enzyme genes than does ATMφ. Our results suggest that multiple new mechanisms including the cell surface, intracellular immunometabolism, trained immunity, and TFs may be responsible for disease group-specific and shared pathways. Our findings have provided novel insights on the pathophysiological regulation of tissue Mφ, the disease group-specific and shared pathways of Mφ, and novel therapeutic targets for cancers and inflammations

CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution

Modern deep-learning-based lane detection methods are successful in most scenarios but struggling for lane lines with complex topologies. In this work, we propose CondLaneNet, a novel top-to-down lane detection framework that detects the lane instances first and then dynamically predicts the line shape for each instance. Aiming to resolve lane instance-level discrimination problem, we introduce a conditional lane detection strategy based on conditional convolution and row-wise formulation. Further, we design the Recurrent Instance Module(RIM) to overcome the problem of detecting lane lines with complex topologies such as dense lines and fork lines. Benefit from the end-to-end pipeline which requires little post-process, our method has real-time efficiency. We extensively evaluate our method on three benchmarks of lane detection. Results show that our method achieves state-of-the-art performance on all three benchmark datasets. Moreover, our method has the coexistence of accuracy and efficiency, e.g. a 78.14 F1 score and 220 FPS on CULane. Our code is available at https://github.com/aliyun/conditional-lane-detection

Automated Path Searching Reveals the Mechanism of Hydrolysis Enhancement by T4 Lysozyme Mutants

Bacteriophage T4 lysozyme (T4L) is a glycosidase that is widely applied as a natural antimicrobial agent in the food industry. Due to its wide applications and small size, T4L has been regarded as a model system for understanding protein dynamics and for large-scale protein engineering. Through structural insights from the single conformation of T4L, a series of mutations (L99A,G113A,R119P) have been introduced, which have successfully raised the fractional population of its only hydrolysis-competent excited state to 96%. However, the actual impact of these substitutions on its dynamics remains unclear, largely due to the lack of highly efficient sampling algorithms. Here, using our recently developed travelling-salesman-based automated path searching (TAPS), we located the minimum-free-energy path (MFEP) for the transition of three T4L mutants from their ground states to their excited states. All three mutants share a three-step transition: the flipping of F114, the rearrangement of α0/α1 helices, and final refinement. Remarkably, the MFEP revealed that the effects of the mutations are drastically beyond the expectations of their original design: (a) the G113A substitution not only enhances helicity but also fills the hydrophobic Cavity I and reduces the free energy barrier for flipping F114; (b) R119P barely changes the stability of the ground state but stabilizes the excited state through rarely reported polar contacts S117OG:N132ND2, E11OE1:R145NH1, and E11OE2:Q105NE2; (c) the residue W138 flips into Cavity I and further stabilizes the excited state for the triple mutant L99A,G113A,R119P. These novel insights that were unexpected in the original mutant design indicated the necessity of incorporating path searching into the workflow of rational protein engineering

State-of-arts: workflow management for grid computing

Grid computing is now becoming a new computing paradigm and solution for distributed systems and applications. Currently, increasing resources are involved in Grid environments and a great deal of applications is running on computational Grids. Unfortunately, Grid computing technology is still far away from reach of inexperienced application users, e.g. computational scientists and engineers. Workflow system, originally coming from business process automation, is introduced into Grid computing to alleviate Grid users’ burden of running applications, especially for complex applications, on computational Grids. In recent years, dozens of workflow systems and model languages are proposed for Grid computing. Workflow management has become an interesting research field of Grid computing. However, great research challenges and issues still remain unsolved, which would block Grid computing paradigm from further acceptance by ad-hoc users. This chapter firstly studies the concepts of workflow, workflow system and workflow management. Current status of workflow management for Grid computing is investigated, including models, languages of popular workflow management systems in computational Grids. Further, major research issues and technological challenges are identified and discussed