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Abstract Spinal cord injury (SCI) is a devastating traumatic condition accompanied with excessive inflammatory response and apoptosis of microglia. Long noncoding RNAs (lncRNAs) have been confirmed to be key regulators of cell inflammatory response. Nevertheless, the role of lncRNA KCNQ1OT1 in microglia apoptosis or inflammatory response after SCI remains to be explored. Our study focused on exploring the role and mechanism of KCNQ1OT1 in microglia after SCI. RT-qPCR showed that SCI induced the increase of KCNQ1OT1 level in mice spinal cord. Inhibition of KCNQ1OT1 suppressed the inflammatory response and apoptosis of microglia. In addition, KCNQ1OT1 was proved to bind with miR-589-5p, and NPTN was directly targeted by miR-589-5p. Furthermore, KCNQ1OT1 was negatively correlated with miR-589-5p and positively associated with NPTN. Rescue assays indicated that NPTN overexpression reversed the anti-inflammatory and anti-apoptosis effects of KCNQ1OT1 silencing. In summary, these data revealed that KCNQ1OT1 promoted inflammatory response and apoptosis of microglia by regulating the miR-589-5p/NPTN axis after SCI, which may offer a novel promising therapeutic target for SCI.

Based on the travel analysis of students in the Jiulonghu campus, this paper constructs a small-scale shared bus in the campus, explores the impact of shared traffic on campus travel, promotes the optimization design of campus space environment, and creates a more comfortable and convenient travel space. In order to overcome the shortcomings of the traditional trip-based research, this paper analyzes travel behavior from the perspective of activity-based travel concept framework, considering more activities and travel information. At the same time, in order to improve the richness of information, the explicit preference survey (RP) and the declarative preference survey (SP), which are added to the bus sharing customized travel platform, are used to collect data of personal attributes and travel diary. Firstly, based on the ArcGIS platform, this paper constructs the activity travel path generation tool, dynamic activity density distribution tool, and spatiotemporal path clustering tool and comprehensively analyzes the activity travel mode from the aspects of time distribution, spatial distribution, and category characteristics. Secondly, based on the travel activities, the location selection model (S-MNL) considering the heterogeneity of SP and RP data sources and the activity duration planning model (Cox regression), considering the nonnormal distribution of activity duration are established to analyze the impact of shared bus on students’ travel distance, travel time, and travel frequency. Finally, according to the analysis of modeling results, the impact of shared traffic on campus travel is analyzed, and the optimal design scheme of campus space is given. This paper uses the survey method based on declarative preference SP and the survey method based on explicit preference (RP) to get the actual and hypothetical travel response of travelers, which improves the data richness.

ObjectiveThe present study aimed to determine whether the polymorphisms at rs2241766 and rs1501299 on the ADIPOQ gene were related to the susceptibility of type 2 diabetes mellitus (T2DM).MethodsEight databases, PubMed, GWAS, Embase, Lochrane, Ebsco, CNKI (Chinese National Knowledge Infrastructure), VIP (Viper Database) and ChinaInfo were searched, and a meta-analysis of susceptibility was conducted between SNP45, SNP276 polymorphisms and T2DM. Furthermore, HWE test was conducted to assess the genetic balance of the study, evaluate the quality of Newcastle-Ottawa quality assessment scale (NOS), and establishing allelic, dominant, recessive, heterozygous, and homozygous gene models.ResultsThis meta-analysis included 53 articles, encompassing 9285 cases with rs2241766 and 14156 controls and 7747 cases with rs1501299 and 10607 controls. For the rs2241766 locus, a significant correlation was found in the three models by the subgroup analysis. Western Asians: dominant gene model (TT + TG vs. GG, P = 0.01); heterozygous gene model (TG vs. GG, P = 0.02); homozygous gene model (TT vs. GG, P = 0.01). South Asians: dominant gene model (TT + TG vs. GG, P = 0.004); heterozygous gene model (TG vs. GG, P = 0.009); homozygous gene model (TT vs. GG, P = 0.005). However, no statistically significant correlation was established among the five genetic models for rs1501299 locus.ConclusionThe findings of the present study indicated that the T allele of rs2241766 polymorphism is the susceptibility locus of T2DM in the West Asian population, but has a protective effect in the South Asian population, albeit further studies are needed in other populations. Also, no association was found between the ADIPOQ rs1501299 polymorphism and T2DM.

A boundedly rational user equilibrium model with restricted unused routes (R-BRUE) considering the restrictions of both used route cost and unused route cost is proposed. The proposed model hypothesizes that for each OD pair no traveler can reduce his/her travel time by an indifference band by unilaterally changing route. Meanwhile, no route is unutilized if its travel time is lower than sum of indifference band and the shortest route cost. The largest and smallest used route sets are defined using mathematical expression. We also show that, with the increase of the indifference band, the largest and smallest used route sets will be augmented, and the critical values of indifference band to augment these two path sets are identified by solving the mathematical programs with equilibrium constraints. Based on the largest and smallest used route sets, the R-BRUE route set without paradoxical route is generated. The R-BRUE solution set can then be obtained by assigning all traffic demands to the corresponding generated route set. Various numerical examples are also provided to illustrate the essential ideas of the proposed model and structure of R-BRUE route flow solution set.

This paper presents a Bayesian network model for estimating origin-destination matrices. Most existing Bayesian methods adopt prior OD matrixes, which are always troublesome to be obtained. Since transportation systems normally have stored large amounts of historical link flows, a Bayesian network model using these prior link flows is proposed. Based on some observed link flows, the estimation results are updated. Under normal distribution assumption, the proposed Bayesian network model considers the level of total traffic flow, the variability of link flows, and the violation of the traffic flow conservation law. Both the point estimation and the corresponding probability intervals can be provided by this model. To solve the Bayesian network model, a specific procedure which can avoid matrix inversion is proposed. Finally, a numerical example is given to illustrate the proposed Bayesian network method. The results show that the proposed method has a high accuracy and practical applicability.

This paper analyzes the activity-trip chaining behavior of urban low-income populations in Nanjing, China, based on a specific travel survey of low-income residents of Nanjing city (2010), and the database of residents travel survey of Nanjing city (2009). Individual’s information of activity participation and trip chains is extracted from the daily travel diary and matched with individual and household characteristics. On top of correlation analysis and normalization process, using the software AMOS, two structural equation models are formulated to analyze the relationship among individuals’ sociodemographics, activity duration, and trip chains of low-income populations and non-low-income populations, respectively. Seven household characteristics and six individual characteristics are chosen as the exogenous variables, while 4 indices of activity duration and 4 indices of trip chains are sleeted as the endogenous variables. The result shows that the activity-travel behavior of urban low-income populations is quite unique, which offers promising insights into activity-trip chaining behavior of the poor and extends the need to crafting effective transportation policies specifically for urban low-income populations in developing countries.

This paper extends the work on Pareto-improving hybrid rationing and pricing policy for general road networks by considering heterogeneous users with different values of time. Mathematical programming models are proposed to find a multiclass Pareto-improving pure road space rationing scheme (MPI-PR) and multiclass hybrid rationing and pricing schemes (MHPI and MHPI-S). A numerical example with a multimodal network is provided for comparing both the efficiency and equity of the three proposed policies. We discover that MHPI-S can achieve the largest reduction in total system delay, MHPI can induce the least spatial inequity and MHPI-S is a progressive policy which is appealing to policy makers. Furthermore, numerical results reveal that different classes of users react differently to the same hybrid policies and multiclass Pareto-improving hybrid schemes yield less delay reduction when compared to their single-class counterparts. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the expression of brain-derived neurotrophic factor (BDNF) in dorsal root ganglia (DRG) of a rat model of lumbar spinal stenosis (LSS). Adult male rats were divided into the operation and sham operation groups. The operation group was comprised of the rat models of LSS. Walking distance and BDNF expression levels in DRG were measured in the two groups at different time points. The total BDNF protein levels and positive cell mean optical density (MOD) values in the operation group were significantly higher at each time point compared with that of the sham operation and preoperative control groups (P<0.05). The total BDNF protein levels and MOD values following sport in the operation group were significantly higher compared with those prior to sport (P<0.05). In the sham operation group, BDNF protein levels and MOD values before and after sport at each time point showed no significant differences than those of the operation group (P>0.05). Moreover, BDNF protein levels and MOD values in the operation group indicated a negative correlation with walking distance. The present study demonstrated that the expression of BDNF in rat models of LSS increased with time and was associated with a decrease in walking distance. BDNF was therefore important for the process of intermittent claudication caused by LSS. [ABSTRACT FROM AUTHOR]