A Side-Constrained Peer-to-Peer Carpooling Stochastic User Equilibrium Model

Peer-to-peer (P2P) carpooling has become an effective way to utilize the idle car capacity and ease traffic congestion. However, the interactive relationship between carpooling and traffic congestion has not been fully quantified. To make up for this gap, this paper constructs a side-constrained P2P carpooling stochastic user equilibrium model to disclose the effects of carpooling on traffic congestion. Next, the proposed model was transformed into a linear constrained minimization problem, and the problem was proved to have a unique solution. The case study shows that the travellers prefer carpooling at a high fuel price and a low inconvenient cost

Self-assembling and pH-responsive protein nanoparticle as potential platform for targeted tumor therapy

Frequent injections at high concentrations are often required for many therapeutic proteins due to their short in vivo half-life, which usually leads to unsatisfactory therapeutic outcomes, adverse side effects, high cost, and poor patient compliance. Herein we report a supramolecular strategy, self-assembling and pH regulated fusion protein to extend the in vivo half-life and tumor targeting ability of a therapeutically important protein trichosanthin (TCS). TCS was genetically fused to the N-terminus of a self-assembling protein, Sup35p prion domain (Sup35), to form a fusion protein of TCS-Sup35 that self-assembled into uniform spherical TCS-Sup35 nanoparticles (TCS-Sup35 NP) rather than classic nanofibrils. Importantly, due to the pH response ability, TCS-Sup35 NP well retained the bioactivity of TCS and possessed a 21.5-fold longer in vivo half-life than native TCS in a mouse model. As a result, in a tumor-bearing mouse model, TCS-Sup35 NP exhibited significantly improved tumor accumulation and antitumor activity without detectable systemic toxicity as compared with native TCS. These findings suggest that self-assembling and pH responding protein fusion may provide a new, simple, general, and effective solution to remarkably improve the pharmacological performance of therapeutic proteins with short circulation half-lives

Survey and Visual Detection of Zaire ebolavirus in Clinical Samples Targeting the Nucleoprotein Gene in Sierra Leone

Ebola virus (EBOV) can lead to severe hemorrhagic fever with a high risk of death in humans and other primates. To guide treatment and prevent spread of the viral infection, a rapid and sensitive detection method is required for clinical samples. Here, we described and evaluated a reverse transcription loop-mediated isothermal amplification (RT-LAMP) method to detect Zaire ebolavirus using the nucleoprotein gene (NP) as a target sequence. Two different techniques were used, a calcein/Mn2+ complex chromogenic method and real-time turbidity monitoring. The RT-LAMP assay detected the NP target sequence with a limit of 4.56 copies/μL within 45 min under 61°C, a similar even or increase in sensitivity than that of real-time reverse transcription-polymerase chain reaction (RT-PCR). Additionally, all pseudoviral particles or non- Zaire EBOV genomes were negative for LAMP detection, indicating that the assay was highly specific for EBOV. To appraise the availability of the RT-LAMP method for use in clinical diagnosis of EBOV, of 417 blood or swab samples collected from patients with clinically suspected infections in Sierra Leone, 307 were identified for RT-LAMP-based surveillance of EBOV. Therefore, the highly specific and sensitive RT-LAMP method allows the rapid detection of EBOV, and is a suitable tool for clinical screening, diagnosis, and primary quarantine purposes

Identification of gene mutations in six Chinese patients with maple syrup urine disease

Background: Maple syrup urine disease (MSUD) is a rare autosomal recessive amino acid metabolic disease. This study is to identify the pathogenic genetic factors of six cases of MUSD and evaluates the application value of high-throughput sequencing technology in the early diagnosis of MUSD.Methods: Clinical examination was carried out for patients and used blood tandem mass spectrometry (MS/MS), urine gas chromatography-mass spectrometry (GC/MS), and the application of high-throughput sequencing technology for detection. Validate candidate mutations by polymerase chain reaction (PCR)—Sanger sequencing technology. Bioinformatics software analyzed the variants’ pathogenicity. Using Swiss PDB Viewer software to predict the effect of mutation on the structure of BCKDHA and BCKDHB proteins.Result: A total of six MSUD patients were diagnosed, including four males and two females. Nine variants were found in three genes of six MSUD families by high-throughput sequencing, including four missense mutations: c.659C>T(p.A220V), c.818C>T(p.T273I), c.1134C>G(p.D378E), and c.1006G>A(p.G336S); two non-sense mutations: c.1291C>T(p.R431*) and c.331C>T(p.R111*); three deletion mutations: c.550delT (p.S184Pfs*46), c.718delC (p.P240Lfs*14), and c.795delG (p.N266Tfs*64). Sanger sequencing’s results were consistent with the high-throughput sequencing. The bioinformatics software revealed that the mutations were harmful, and the prediction results of Swiss PDB Viewer suggest that variation affects protein conformation.Conclusion: This study identified nine pathogenic variants in the BCKDHA, BCKDHB, and DBT genes in six MSUD families, including two novel pathogenic variants in the BCKDHB gene, which enriched the genetic mutational spectrum of the disease. High-throughput sequencing is essential for the MSUD’s differential diagnosis, early treatment, and prenatal diagnosis

Robust and Task-Independent Spatial Profile of the Visual Word Form Activation in Fusiform Cortex

Written language represents a special category of visual information. There is strong evidence for the existence of a cortical region in ventral occipitotemporal cortex for processing the visual form of written words. However, due to inconsistent findings obtained with different tasks, the level of specialization and selectivity of this so called visual word form area (VWFA) remains debated. In this study, we examined category selectivity for Chinese characters, a non-alphabetic script, in native Chinese readers. In contrast to traditional approaches of examining response levels in a restricted predefined region of interest (ROI), a detailed distribution of the BOLD signal across the mid-fusiform cortical surface and the spatial patterns of responses to Chinese characters were obtained. Results show that a region tuned for Chinese characters could be consistently found in the lateral part of the left fusiform gyrus in Chinese readers, and this spatial pattern of selectivity for written words was not influenced by top-down tasks such as phonological or semantic modulations. These results provide strong support for the robust spatial coding of category selective response in the mid-fusiform cortex, and demonstrate the utility of the spatial distribution analysis as a more meaningful approach to examine functional magnetic resonance imaging (fMRI) data

The DEA Game Cross-efficiency Model for Supplier Selection Problem under Competition

Abstract: As the most important responsibility of purchasing management, the problem of supplier evaluation and selection has always received a great deal of attention from practitioners and researchers. This management decision is a challenge due to the complexity and various criteria involved. Many methods based on data envelopment analysis(DEA) emerged, especially the cross efficiency. But it exists some limitations, such as the cross efficiency value is often non-unique, average cross efficiency measure is not good because it is not pareto solution. This paper considers the competition between the suppliers and presents game cross efficiency which is based on DEA to assess supplier performance. This method can get a unique efficiency and it is pareto solution. Numerical example is used to illustrate application and feasibility of the proposed methodology

An Effective Heuristic Algorithm for Robust Supply Chain Network Design under Uncertainty

Abstract: This paper addressing a study on robust supply chain network design under uncertainty environment. We use decomposition and coordination strategy to decompose the model as two parties: the first part is facility location decision which only concludes 0−1 decision variable, tabu search algorithm is used to determine the 0−1 decision variables, and then regard the 0−1 variables as known input parameters. The second part is flow decision, all-or-nothing method is proposed to design the capacity of the facility. From the numerical example, we can see that, the model and algorithm is valid and effective, the robust optimization model not only reduces the risk of market, but avoids the error from the shortage cost