Methods Dealing with Complexity in Selecting Joint Venture Contractors for Large-Scale Infrastructure Projects

The magnitude of business dynamics has increased rapidly due to increased complexity, uncertainty, and risk of large-scale infrastructure projects. This fact made it increasingly tough to “go alone” into a contractor. As a consequence, joint venture contractors with diverse strengths and weaknesses cooperatively bid for bidding. Understanding project complexity and making decision on the optimal joint venture contractor is challenging. This paper is to study how to select joint venture contractors for undertaking large-scale infrastructure projects based on a multiattribute mathematical model. Two different methods are developed to solve the problem. One is based on ideal points and the other one is based on balanced ideal advantages. Both of the two methods consider individual difference in expert judgment and contractor attributes. A case study of Hong Kong-Zhuhai-Macao-Bridge (HZMB) project in China is used to demonstrate how to apply these two methods and their advantages

Molecular Subtypes of Ovarian Cancer Based on Lipid Metabolism and Glycolysis Reveals Potential Therapeutic Targets

Background: Ovarian cancer (OC) is one of the most lethal gynecological malignant neoplasms. The aim of this study was to use high-throughput sequencing data to investigate the molecular and clinical characteristics of OC subtypes related to lipid metabolism and glycolysis, thus providing a theoretical basis for clinical decision-making. Methods: Molecular data and clinicopathological characteristics of OC patients were extracted from the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx), and the Gene Expression Omnibus (GEO). Following analysis of genes involved in lipid metabolism and glycolysis, OC was classified into subtypes by unsupervised clustering. The molecular features and clinical outcomes of these subtypes were then evaluated. Results: OC patients were divided into five subtypes based on the analysis of nine genes of interest. Amongst these, patients in subtype D had longer overall survival and more benign clinical features. Subtypes B and E had shorter overall- and progression-free survival, respectively. Both the B and E subtypes were closely related to lipid metabolism and to the glycolytic process. Subtype D was positively correlated with the infiltration of CD8+ T cells, CD4+ T cells, and macrophages, all of which play essential anti-tumor roles. Several risk models for selected subtypes were also constructed based on the expression of select genes. Conclusions: The present work revealed that irregular metabolism in OC tissues was an indicator of poor clinical outcome and altered homeostasis in cancer-related pathways. Moreover, aberrant gene expression signatures associated with lipid metabolism and glycolysis were also correlated with an immunosuppressive tumor microenvironment. Based on lipid metabolism and glycolysis, we have therefore identified several OC molecular subtypes that may prove useful for the development of potential therapeutic targets

A polymer canvas with the stiffness of the bone matrix to study and control mesenchymal stem cell response

: The possibility to reproduce in vitro the complex multiscale physical features present in the human tissues creates novel opportunities for biomedical advances and fundamental understanding of cell-environment interfaces and interactions. While stiffness has been recognized as a key property in influencing cell behavior, so far systematic studies on the role of stiffness have been limited to values in the KPa-MPa range, significantly below the stiffness of bone. Here, we report a platform enabling the tuning and control of the stiffness of a biocompatible polymeric interface up to values characteristic of the bone tissue, which are in the GPa range. The ability to fine tune the stiffness up to these large values is achieved by using extremely thin polymer films on glass and cross-linking the films using UV light irradiation. We show that a higher stiffness is related to better adhesion, proliferation, and osteogenic differentiation, and that it is also possible to switch on/off cell attachment and growth by solely tuning the stiffness of the interface, without any surface chemistry or topography modification. Since the stiffness is tuned directly by UV irradiation, this platform is ideal for rapid and simple stiffness patterning, and stiffness gradients fabrication. This materials platform represents an innovative tool for combinatorial studies of the synergistic effect of tissue environmental cues on cell behavior, and creates new opportunities for next generation biosensors, single-cell patterning, and lab-on-a-chip devices. This article is protected by copyright. All rights reserved

A Review of Research Progress on Machining Carbon Fiber-Reinforced Composites with Lasers

Carbon fiber-reinforced composites are widely used in automobile, aerospace and military lightweight manufacturing due to their excellent mechanical properties such as light weight, excellent fracture resistance, corrosion resistance and wear resistance, etc. However, because of their high hardness, anisotropy and low interlayer strength characteristics, there are many problems with machine carbon fiber-reinforced composites with traditional methods. As a non-contact processing technology, laser machining technology has lots of advantages in carbon fiber-reinforced composites processing. However, there are also some defects produced in laser machining process such the heat affected zone, delamination and fiber extraction due to the great difference of physical properties between the carbon fibers and the resin matrix. To improve the quality of carbon fiber-reinforced composites laser machining, lots of works have been carried out. In this paper, the research progress of carbon fiber-reinforced composites laser machining parameters optimization and numerical simulation was summarized, the characteristics of laser cutting carbon fiber-reinforced composites and cutting quality influence factors were discussed, and the developing trend of the carbon fiber-reinforced composites laser cutting was prospected

Soluble CD24 is an inflammatory biomarker in early and seronegative rheumatoid arthritis

AbstractIntroduction: Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease characterized by autoantibody production, joint inflammation and bone destruction. Nearly 1/3 of RA patients with the active disease also exhibit a normal range of ESR and CRP. Here we assessed the performance and clinical significance of soluble CD24 (sCD24) as a biomarker of disease activity in RA.Methods: A total of 269 RA patients, 59 primary Sjogren’s syndrome (SS) patients, 81 systematic lupus erythematosus (SLE) patients, 76 osteoarthritis (OA) patients and 97 healthy individuals (HC) were included in this study. Soluble CD24 in sera were detected by ELISA. Therefore, the concentration of sCD24 was analyzed in RA patients with different disease activity statuses.Results: The sCD24 was significantly increased in RA (2970 pg/mL), compared to other rheumatic diseases (380-520 pg/mL) and healthy individuals (320 pg/mL). Moreover, sCD24 was elevated in 66.67% of early RA and 61.11% of seronegative RA patients. In addition, sCD24 was significantly correlated with the disease duration and inflammatory indicators.Conclusion: The sCD24 could be an inflammatory biomarker in RA patients, especially in early and seronegative patients

Soluble CD24 is an inflammatory biomarker in early and seronegative rheumatoid arthritis

Introduction: Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease characterized by autoantibody production, joint inflammation and bone destruction. Nearly 1/3 of RA patients with the active disease also exhibit a normal range of ESR and CRP. Here we assessed the performance and clinical significance of soluble CD24 (sCD24) as a biomarker of disease activity in RA. Methods: A total of 269 RA patients, 59 primary Sjogren’s syndrome (SS) patients, 81 systematic lupus erythematosus (SLE) patients, 76 osteoarthritis (OA) patients and 97 healthy individuals (HC) were included in this study. Soluble CD24 in sera were detected by ELISA. Therefore, the concentration of sCD24 was analyzed in RA patients with different disease activity statuses. Results: The sCD24 was significantly increased in RA (2970 pg/mL), compared to other rheumatic diseases (380-520 pg/mL) and healthy individuals (320 pg/mL). Moreover, sCD24 was elevated in 66.67% of early RA and 61.11% of seronegative RA patients. In addition, sCD24 was significantly correlated with the disease duration and inflammatory indicators. Conclusion: The sCD24 could be an inflammatory biomarker in RA patients, especially in early and seronegative patients.</p

Differing toxicity of ambient particulate matter (PM) in global cities

Air quality is often assessed using particulate matter (PM) mass concentration without considering its toxicity, thus possibly leading to improper control policies or inadequate health protection. Here, we studied differences in oxidative potentials (OPs) of PM samples collected using automobile air conditioning (AC) filters from 19 global cities, as well as influences from microbial contents. Dithiothreitol (DTT) assay showed remarkable differences in the PM OPs among cities (p-values <= 0.001, Kruskal-Wallis test). For example, the normalized index of oxidant generation (NIOG) of PM samples in San Francisco (2.20 x 10(-2), annual average PM10 = 16 mu g/m(3)) was found to be twice that in Beijing (1.14 x 10(-2), annual average PM10 = 135 mu g/m(3)). Limulus amebocyte lysate (LAL) assay found that PM-borne endotoxin ranged from 12.16 EU/mg (Florianopolis, Brazil) to 2518.23 EU/mg (Chennai, India) among cities. Besides, culturing method and real-time qPCR revealed significant differences of up to similar to 100-fold in both bacterial and fungal levels among 19 cities. Spearman's correlation analysis implied that PM-borne microbes such as bacteria and fungi as well as metals could strongly influence the PM OP. As an example, our results in Xfan, China further suggest that the PM2.5 OP evolves for a particular city over the time, which is attributable to both the urbanization and air pollution control measures. This work highlights the importance in optimizing the current air quality control measures by considering the toxicity factor and its microbial constituents