Roles Of Neuregulin1 In Neuromuscular Junction Development

Neuromuscular junction (NMJ) development is a multistep process mediated by coordinated interactions between nerve terminals, target muscles, and peri-synaptic glial cells, and thus requires reciprocal signals derived from every cell type. Neuregulin1s (NRG1s) are a family of predominantly neuronal growth and differentiation factors that are important for many aspects of nervous system development. In this thesis, both the effects of NRG1 on NMJ development and reciprocal effects of neurotrophic factors on NRG1 expression were studied as a means to define the complex regulatory communication at the NMJ. Using the chicken embryo as a model, methods were developed to study the effects of NRG1 signaling on NMJ development in ovo using sequential, quantitative measures of NMJ formation including AChR cluster size and density, pre- and post-synaptic apposition, and alignment of peri-synaptic Schwann cells. Over-expression of soluble NRG1 increased AChR cluster density, but not size, in the early developmental stage, whereas, blocking NRG1 activity with a targeted antagonist had little effect. In the middle stage, the NRG1 antagonist led to a decrease of AChR cluster size in a temporal-specific and muscle type-dependent fashion. The NRG1 antagonist also altered the distribution of synaptic vesicles, suggesting NRG1 signaling can modulate the assembly of the pre-synaptic apparatus as well. In the late stage, pre- and post-synaptic apposition, and peri-synaptic Schwann cell alignment were modestly affected by the antagonist. In motor neurons, NRG1 expression at the axonal-Schwann cell and neuromuscular junctions is regulated by synaptic activity and neurotrophic factors, however, little is known about the mechanisms that control NRG1 isoform-specific transcription. Here we show that NRG1 expression in the chick embryo increases in motor neurons that have extended their axons and that limb bud ablation before motor axon outgrowth prevents this induction, suggesting a trophic role from the developing limb. Consistently, NRG1 induction after limb bud ablation can be rescued by adding back the neurotrophic factors BDNF and GDNF. Mechanistically, BDNF induces a rapid and transient increase in types I and III NRG1 I mRNAs that peak at 4 h in rat embryonic ventral spinal cord cultures. Blocking MAPK or PI3K signaling or blocking transcription with Actinomycin D blocks BDNF induced NRG1 gene induction. BDNF had no effects on mRNA degradation, suggesting that transcriptional activation rather than message stability is important. Furthermore, BDNF activates a reporter construct that includes 700bp upstream of the type I NRG1 start site. Protein synthesis is also required for type I NRG1 mRNA transcription as cycloheximide produced a super-induction of type I, but not type III NRG1 mRNA, possibly through a mechanism involving sustained activation of MAPK and PI3K. These findings suggest that, while not critical for development, NRG1 signaling can have important roles in fine-tuning multiple stages of NMJ development and that NRG1 isoform expression can be differentially modulated by highly responsive, transient transcriptional regulatory mechanisms mediated by neurotrophic factors and axon-target interactions. Understanding these mechanisms will be important for elucidating the role of NRG1 in both development and in pathological disorders of the nervous system

Statistical methods for patterns and interconnections between variables with applications in epigenetics data

Statistical methods for patterns and interconnections between variables with applications in epigenetics dat

The Relationship Between Self-Evaluation, Feasibility and Effective Career Planning Among College Student in China

The main objective of this study is to examine the relationship between self-evaluation, feasibility and effective career planning among college students in China. The two dimensions which namely self-evaluation and feasibility (independent variables) will be used to measure effective career planning (dependent variables). Beside this study will also try to find out which factor is more important in effective career planning. In order to attain the objectives, this study will be conducted quantitatively where data will be collected through distribution of questionnaires to 200 college students randomly in a college of China. 192 of returned and usable questionnaires are expected to be used for analysis. The data will be analyses using Person Correlation to study the relationships between independent variable and dependent variables and also through Reliability Test and Descriptive Analyses. The findings indicated that there were relationships between self-evaluation, feasibility and effective career planning. Further, the findings also revealed that establishment goal is the most important factor contributed to the effective career planning. In conclusion, the study shows that self-evaluation and feasibility being positively correlated to effective career planning

Amplitude-Duration-Persistence Trade-off Relationship for Long Term Bear Stock Markets

We study the mechanism that controls the shape of the bear market through an information diffusion perspective, and establish a frontier of market decline, in terms of a trade-off between amplitude, duration and the rate of information diffusion. Empirical analysis using data from 15 stock markets confirms the existence of this trade-off relationship. An algorithm for generating the frontier using real data is proposed and applied in several market scenarios. The results suggest that the behaviour of international stock markets during the current US credit crunch is similar to that in previous bear markets in terms of the trivariate trade-off

Amplitude-Duration-Persistence Trade-off Relationship for Long Term Bear Stock Markets

We study the mechanism that controls the shape of the bear market through an information diffusion perspective, and establish a frontier of market decline, in terms of a trade-off between amplitude, duration and the rate of information diffusion. Empirical analysis using data from 15 stock markets confirms the existence of this trade-off relationship. An algorithm for generating the frontier using real data is proposed and applied in several market scenarios. The results suggest that the behaviour of international stock markets during the current US credit crunch is similar to that in previous bear markets in terms of the trivariate trade-off

Cohort Profile: The Jiaxing Birth Cohort in China.

This is the author accepted manuscript. It is currently under an indefinite embargo pending publication by Oxford University Press.This work was supported by the National Basic Research Program of China (973 Program: 2015CB553604); by National Natural Science Foundation of China (NSFC: 81273054); and by the Ph.D. Programs Foundation of Ministry of Education of China (20120101110107)

Imetelstat, A Telomerase Inhibitor, is Capable of Depleting Myelofibrosis Stem and Progenitor Cells

Clinical trials of imetelstat therapy have indicated that this telomerase inhibitor might have disease-modifying effects in a subset of patients with myelofibrosis (MF). The mechanism by which imetelstat induces such clinical responses has not been clearly elucidated. Using in vitro hematopoietic progenitor cell (HPC) assays and in vivo hematopoietic stem cell (HSC) assays, we examined the effects of imetelstat on primary normal and MF HSCs/HPCs. Treatment of CD34(+) cells with imetelstat reduced the numbers of MF but not cord blood HPCs (colony-forming unit-granulocyte/macrophage, burst-forming unit-erythroid, and colony-forming unit-granulocyte/erythroid/macrophage/megakaryocyte) as well as MF but not normal CD34(+)ALDH(+) cells irrespective of the patient\u27s mutational status. Moreover, imetelstat treatment resulted in depletion of mutated HPCs from JAK2V617F(+) MF patients. Furthermore, treatment of immunodeficient mice that had been previously transplanted with MF splenic CD34(+) cells with imetelstat at a dose of 15 mg/kg, 3 times per week for 4 weeks had a limited effect on the degree of chimerism achieved by normal severe combined immunodeficiency repopulating cells but resulted in a significant reduction in the degree of human MF cell chimerism as well as the proportion of mutated donor cells. These effects were sustained for at least 3 months after drug treatment was discontinued. These actions of imetelstat on MF HSCs/HPCs were associated with inhibition of telomerase activity and the induction of apoptosis. Our findings indicate that the effects of imetelstat therapy observed in MF patients are likely attributable to the greater sensitivity of imetelstat against MF as compared with normal HSCs/HPCs as well as the intensity of the imetelstat dose schedule

Vision-Language Models can Identify Distracted Driver Behavior from Naturalistic Videos

Recognizing the activities, causing distraction, in real-world driving scenarios is critical for ensuring the safety and reliability of both drivers and pedestrians on the roadways. Conventional computer vision techniques are typically data-intensive and require a large volume of annotated training data to detect and classify various distracted driving behaviors, thereby limiting their efficiency and scalability. We aim to develop a generalized framework that showcases robust performance with access to limited or no annotated training data. Recently, vision-language models have offered large-scale visual-textual pretraining that can be adapted to task-specific learning like distracted driving activity recognition. Vision-language pretraining models, such as CLIP, have shown significant promise in learning natural language-guided visual representations. This paper proposes a CLIP-based driver activity recognition approach that identifies driver distraction from naturalistic driving images and videos. CLIP's vision embedding offers zero-shot transfer and task-based finetuning, which can classify distracted activities from driving video data. Our results show that this framework offers state-of-the-art performance on zero-shot transfer and video-based CLIP for predicting the driver's state on two public datasets. We propose both frame-based and video-based frameworks developed on top of the CLIP's visual representation for distracted driving detection and classification task and report the results.Comment: 15 pages, 10 figure

Unsupervised SAR Image Segmentation Based on a Hierarchical TMF Model in the Discrete Wavelet Domain for Sea Area Detection

Unsupervised synthetic aperture radar (SAR) image segmentation is a fundamental preliminary processing step required for sea area detection in military applications. The purpose of this step is to classify large image areas into different segments to assist with identification of the sea area and the ship target within the image. The recently proposed triplet Markov field (TMF) model has been successfully used for segmentation of nonstationary SAR images. This letter presents a hierarchical TMF model in the discrete wavelet domain of unsupervised SAR image segmentation for sea area detection, which we have named the wavelet hierarchical TMF (WHTMF) model. The WHTMF model can precisely capture the global and local image characteristics in the two-pass computation of posterior distribution. The multiscale likelihood and the multiscale energy function are constructed to capture the intrascale and intrascale dependencies in a random field (X,U). To model the SAR data related to radar backscattering sources, the Gaussian distribution is utilized. The effectiveness of the proposed model for SAR image segmentation is evaluated using synthesized and real SAR data