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Conventional traffic crash analyzing methods focus on identifying the relationship between traffic crash outcomes and impact risk factors and explaining the effects of risk factors, which ignore the changes of roadway systems and can lead to inaccurate results in traffic crash predictions. To address this issue, an innovative two-step method is proposed and a support vector regression (SVR) model is formulated into state-space model (SSM) framework for traffic crash prediction. The SSM was developed in the first step to identify the dynamic evolution process of the roadway systems that are caused by the changes of traffic flow and predict the changes of impact factors in roadway systems. Using the predicted impact factors, the SVR model was incorporated in the second step to perform the traffic crash prediction. A five-year dataset that obtained from 1152 roadway segments in Tennessee was employed to validate the model effectiveness. The proposed models result in an average prediction MAPE of 7.59%, a MAE of 0.11, and a RMSD of 0.32. For the performance comparison, a SVR model and a multivariate negative binomial (MVNB) model were developed to do the same task. The results show that the proposed model has superior performances in terms of prediction accuracy compared to the SVR and MVNB models. Compared to the SVR and MVNB models, the benefit of incorporating a state-space model to identify the changes of roadway systems is significant evident in the proposed models for all crash types, and the prediction accuracy that measured by MAPE can be improved by 4.360% and 6.445% on average, respectively. Apart from accuracy improvement, the proposed models are more robust and the predictions can retain a smoother pattern. Furthermore, the results show that the proposed model has a more precise and synchronized response behavior to the high variations of the observed data, especially for the phenomenon of extra zeros.

Although IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide, its etiology remains only partly understood. It is clear that the pathogenesis of IgAN involves the formation of macromolecular IgA1 complexes and increased levels of serum IgA1 and IgA1-immune complexes(IC), due to defective IgA1 clearance. Previous studies suggest that the blood and tissue myeloid cell-expressed IgA Fc receptor (FcαR/CD89) mediates IgA-IC clearance and its dysfunction, via decreased activity or excessive levels of soluble FcαR/sCD89 induces IgAN. Such a mechanism requires robust stimulation of IgAN levels via forced expression of CD89. In the absence of unequivocal evidence supporting such a mechanism to date, we attempted to test the extent of CD89-evoked IgAN by generating a transgenic mouse strain expressing human CD89 under the control of murine CD14 promotor. No deposition of IgA-CD89 complexes or glomerulonephritis was detected, however. Further studies showed that elimination of murine IgA was mediated by Kupffer cells. In patients, however, CD89/IgA complexes were detected, and injection of patient IgA induced IgAN-like features in CD89 Tg mice. In transgenic mice, IgAN pathogenesis involves impaired clearance of abnormal IgA via CD89, primarily by the Kupffer cells. Conditional IgAN progression in CD89 transgenic mice thus reveals important aspects of IgAN pathogenesis.

Grain chalkiness is an important grain quality related to starch granules in the endosperm. A high percentage of grain chalkiness is a major problem because it diminishes grain quality in rice. Here, we report quantitative trait loci identification for grain chalkiness using high-throughput single nucleotide polymorphism genotyping of a chromosomal segment substitution line population in which each line carried one or a few introduced japonica cultivar Nipponbare segments in the genetic background of the indica cultivar ZS97. Ten quantitative trait loci regions were commonly identified for the percentage of grain chalkiness and the degree of endosperm chalkiness. The allelic effects at nine of these quantitative trait loci reduced grain chalkiness. Furthermore, a quantitative trait locus (qPGC8-2) on chromosome 8 was validated in a chromosomal segment substitution line-derived segregation population, and had a stable effect on chalkiness in a multiple-environment evaluation of the near-isogenic lines. Residing on the qPGC8-2 region, the isoamylase gene (ISA1) was preferentially expressed in the endosperm and revealed some nucleotide polymorphisms between two varieties, Nipponbare and ZS97. Transgenic lines with suppression of ISA1 by RNA interference produced grains with 20% more chalkiness than the control. The results support that the gene may underlie qPGC8-2 for grain chalkiness. The multiple-environment trials of the near-isogenic lines also show that combination of the favorable alleles such as the ISA1 gene for low chalkiness and the GS3 gene for long grains considerably improved grain quality of ZS97, which proves useful for grain quality improvement in rice breeding programs.

Histone H2B monoubiquitination is a key histone modification that has significant effects on chromatin higher-order structure and gene transcription. Multiple biological processes have been suggested to be tightly related to the dynamics of H2B monoubiquitination. However, a comprehensive understanding of biological roles of H2B monoubiquitination is still poorly understood. In the present study, we developed an efficient tool to disrupt endogenous H2B monoubiquitination levels by using an H2BK120R mutant construct expressed in human cells. Genome-wide microarray analysis of these cells revealed a potential global view of biological functions of H2B monoubiquitination. Bioinformatics analysis of our data demonstrated that while H2B monoubiquitination expectedly affected a number of previously reported biological pathways, we also uncovered the influence of this histone modification on many novel biological processes. Therefore, our work provided valuable information for understanding the role of H2B monoubiquitination and indicated potential directions for its further studies.

There is a general interest in understanding of whether and how exposure to emotionally traumatizing events can alter memory function and anxiety behaviors. Here we have developed a novel laboratory-version of mild blast exposure comprised of high decibel bomb explosion sound coupled with strong air blast to mice. This model allows us to isolate the effects of emotionally fearful components from those of traumatic brain injury or bodily injury typical associated with bomb blasts. We demonstrate that this mild blast exposure is capable of impairing object recognition memory, increasing anxiety in elevated O-maze test, and resulting contextual generalization. Our in vivo neural ensemble recording reveal that such mild blast exposures produced diverse firing changes in the anterior cingulate cortex, a region processing emotional memory and inhibitory control. Moreover, we show that these real-time neural ensemble patterns underwent post-event reverberations, indicating rapid consolidation of those fearful experiences. Identification of blast-induced neural activity changes in the frontal brain may allow us to better understand how mild blast experiences result in abnormal changes in memory functions and excessive fear generalization related to post-traumatic stress disorder.