945 research outputs found

    Dynamic Pax6 expression during the neurogenic cell cycle influences proliferation and cell fate choices of retinal progenitors

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    BACKGROUND: The paired homeobox protein Pax6 is essential for proliferation and pluripotency of retinal progenitors. However, temporal changes in Pax6 protein expression associated with the generation of various retinal neurons have not been characterized with regard to the cell cycle. Here, we examine the dynamic changes of Pax6 expression among chicken retinal progenitors as they progress through the neurogenic cell cycle, and determine the effects of altered Pax6 levels on retinogenesis. RESULTS: We provide evidence that during the preneurogenic to neurogenic transition, Pax6 protein levels in proliferating progenitor cells are down-regulated. Neurogenic retinal progenitors retain a relatively low level of Pax6 protein, whereas postmitotic neurons either elevate or extinguish Pax6 expression in a cell type-specific manner. Cell imaging and cell cycle analyses show that neurogenic progenitors in the S phase of the cell cycle contain low levels of Pax6 protein, whereas a subset of progenitors exhibits divergent levels of Pax6 protein upon entering the G2 phase of the cell cycle. We also show that M phase cells contain varied levels of Pax6, and some correlate with the onset of early neuronal marker expression, forecasting cell cycle exit and cell fate commitment. Furthermore, either elevating or knocking down Pax6 attenuates cell proliferation and results in increased cell death. Reducing Pax6 decreases retinal ganglion cell genesis and enhances cone photoreceptor and amacrine interneuron production, whereas elevating Pax6 suppresses cone photoreceptor and amacrine cell fates. CONCLUSION: These studies demonstrate for the first time quantitative changes in Pax6 protein expression during the preneurogenic to neurogenic transition and during the neurogenic cell cycle. The results indicate that Pax6 protein levels are stringently controlled in proliferating progenitors. Maintaining a relatively low Pax6 protein level is necessary for S phase re-entry, whereas rapid accumulation or reduction of Pax6 protein during the G2/M phase of the cell cycle may be required for specific neuronal fates. These findings thus provide novel insights on the dynamic regulation of Pax6 protein among neurogenic progenitors and the temporal frame of neuronal fate determination

    (E)-Ethyl N′-(3-hy­droxy­benzyl­idene)hydrazinecarboxyl­ate dihydrate

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    The asymmetric unit of the title compound, C10H12N2O3·2H2O, contains two organic mol­ecules with similar conformations and four water mol­ecules. Each organic mol­ecule is close to planar (r.m.s. deviations = 0.035 and 0.108 Å) and adopts a trans conformation with respect to its C=N bond. In the crystal, the components are linked into a three-dimensional network by N—H⋯O, O—H⋯O, O—H⋯N and C—H⋯O hydrogen bonds, some of which are bifurcated. An R 2 2(8) loop occurs between adjacent organic mol­ecules

    Dynamic response and dangerous point stress analysis of gear transmission system

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    Gear transmission is the principal power transmission mode of many machine, the reliability of transmission system has important influence on the accomplishment of daily task. This paper made a gear transmission system as the research object, we build the two-stage gear transmission system model and calculate its dynamic response in theory. Then, we study the mesh stiffness of gear concerning the variation of the mesh position from the gear transmission system. On the basis of these work, we establish the gear system’s finite element simulation model considering the tooth contact of internal gear system. After the simulation, we had get the contact response and the time history of some important area’s equivalent stress. Through these work, we can study the contact stress of the two-stage gear system in theory method and finite element simulation method, which has a guiding significance on the optimum structural design of two-stage transmission gear system

    Qualifying Chinese Medical Licensing Examination with Knowledge Enhanced Generative Pre-training Model

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    Generative Pre-Training (GPT) models like ChatGPT have demonstrated exceptional performance in various Natural Language Processing (NLP) tasks. Although ChatGPT has been integrated into the overall workflow to boost efficiency in many domains, the lack of flexibility in the finetuning process hinders its applications in areas that demand extensive domain expertise and semantic knowledge, such as healthcare. In this paper, we evaluate ChatGPT on the China National Medical Licensing Examination (CNMLE) and propose a novel approach to improve ChatGPT from two perspectives: integrating medical domain knowledge and enabling few-shot learning. By using a simple but effective retrieval method, medical background knowledge is extracted as semantic instructions to guide the inference of ChatGPT. Similarly, relevant medical questions are identified and fed as demonstrations to ChatGPT. Experimental results show that directly applying ChatGPT fails to qualify the CNMLE at a score of 51 (i.e., only 51\% of questions are answered correctly). While our knowledge-enhanced model achieves a high score of 70 on CNMLE-2022 which not only passes the qualification but also surpasses the average score of humans (61). This research demonstrates the potential of knowledge-enhanced ChatGPT to serve as versatile medical assistants, capable of analyzing real-world medical problems in a more accessible, user-friendly, and adaptable manner
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