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991.
Lei Shi Yi Dai Boyi Jia Yafei Han Yi Guo Tianhong Xie Jiali Liu Xiang Tan Panghua Ding Junxiang Li 《Journal of cellular biochemistry》2019,120(6):9979-9991
992.
Marcelo Massa Alexandre Moreira Renato A. Costa Marcelo R. Lima Carlos R. Thiengo Walter Q. Marquez Aaron J. Coutts Marcelo S. Aoki 《Biology of sport / Institute of Sport》2022,39(2):435
This study examined the influence of birth date, salivary testosterone [sT] concentration, sexual maturity status, and general strength on the selection process of an elite Brazilian soccer club during a 12-month period, which was a 2nd phase of a 24-month selection process. The stature, body mass, sT, sexual maturity status [Tanner scale], and hand grip strength were assessed for 143 players during 2 weeks. From these 143 players, 100 players were dismissed [DIS] and 43 players were selected to integrate the club’s under-14 squad. Following 1-year training period, the under-14 team was assembled with 9 players designated as starters [STA], and then, comparisons were conducted taking into account a group of non-starters (selected; SEL = 34 players) and STA (n = 09). The DIS, SEL, STA players, and reference population, were compared for birth distribution. A greater proportion of players was born in the first trimester in the STA [75.0%], SEL [57.1%] and DIS [50.0%] groups compared to the reference population [25.8%]. One-way ANOVA showed a higher sT for STA group [516.0 ± 129.9 pmol·L-1], compared to SEL [415.5 ± 117.9 pmol·L-1] and DIS groups [390.9 ± 84.9 pmol·L-1; p = 0.003), and Kruskall-Wallis test showed a higher gonadal development for STA compared to DIS [p = 0.001]. The current findings suggest a strong influence of birth date and biological maturation on young soccer players selection process. Soccer coaches should consider these influences when making decisions about player selection of elite youth players. 相似文献
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994.
Ling Li Tanggang Deng Lin Zhang Yanpeng Wang Yangyang Zhou Yan Liu Hui Li Jing Dai Yuan Yang Neng Ling Huimin Liu Jing Liu Lanqin Cao Min Xu Mao Ye 《International journal of biological sciences》2022,18(6):2568
Breast cancer ranks as the most frequently diagnosed cancer among women worldwide. Elevated cytoplasmic p21 levels are often found in breast cancer tissues and related to a poor prognosis. However, the underlying mechanisms that lead to the stabilization of cytoplasmic p21 protein, which normally has a very short half-life, remain obscure. In this study, we found that there was a strong correlation between p21 and USP11 in the cytoplasm of breast cancer tissues and cells. Furthermore, we revealed that ERK1/2 phosphorylated USP11 at the Ser905 site, which promoted the cytoplasmic localization of USP11. In the cytoplasm, USP11 colocalized and interacted with p21. As a result, USP11 catalyzed the removal of polyubiquitin chains bound to cytoplasmic p21 and resulted in its stabilization. Functionally, USP11-mediated stabilization of cytoplasmic p21 induced breast cancer cell proliferation in vitro and in vivo. Our findings provide the first evidence that ubiquitinated p21 in the cytoplasm can be recycled through USP11-mediated deubiquitination, and we identified the USP11-p21 axis in the cytoplasm as a potential therapeutic target for breast cancer control. 相似文献
995.
996.
Ruilong Zhang Zhiping Zhou Yi Wang Xiaohui Dai Li Chen Jiangdong Dai 《仿生工程学报(英文版)》2021,18(3):559-573
Mimicry of nature drives the development of bionic materials.Bionic superhydrophobic materials are a kind of high-efficiency materials to handle oil spills and ... 相似文献
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998.
Bingchuan Wei Nicholas Woon Lu Dai Raphael Fish Michelle Tai Winode Handagama Ashley Yin Jia Sun Andrew Maier Dana McDaniel Elvira Kadaub Jessica Yang Miguel Saggu Ann Woys Oxana Pester Danny Lambert Alex Pell Zhiqi Hao Gordon Magill Jack Yim Jefferson Chan Lindsay Yang Frank Macchi Christian Bell Galahad Deperalta Yan Chen 《MABS-AUSTIN》2022,14(1)
999.
Recent developments of single cell RNA-sequencing technologies lead to the exponential growth of single cell sequencing datasets across different conditions. Combining these datasets helps to better understand cellular identity and function. However, it is challenging to integrate different datasets from different laboratories or technologies due to batch effect, which are interspersed with biological variances. To overcome this problem, we have proposed Single Cell Integration by Disentangled Representation Learning (SCIDRL), a domain adaption-based method, to learn low-dimensional representations invariant to batch effect. This method can efficiently remove batch effect while retaining cell type purity. We applied it to thirteen diverse simulated and real datasets. Benchmark results show that SCIDRL outperforms other methods in most cases and exhibits excellent performances in two common situations: (i) effective integration of batch-shared rare cell types and preservation of batch-specific rare cell types; (ii) reliable integration of datasets with different cell compositions. This demonstrates SCIDRL will offer a valuable tool for researchers to decode the enigma of cell heterogeneity. 相似文献
1000.