Showing 261 - 266 results of 266 for search '"phenotype"', query time: 0.04s Refine Results
  1. 261

    Development of delayed pulmonary toxicities and transcriptional changes in pre-existing interstitial lung disease mice after partial thoracic irradiation by Jiamei Fu, Xinglong Liu, Yuchuan Zhou, Shengnan Zhao, Liang Zeng, Yan Pan, Jianghong Zhang, Kevin M. Prise, Chunlin Shao, Yaping Xu

    Published 2025-02-01
    “…Autopsy revealed that bilateral diffuse alveolar damage (DAD) with an overlap of exudative, proliferative, and fibrosing patterns was usually presented in the sRRLI model. The histological phenotypes manifested exudative predominated DAD phase in the early phase and proliferating DAD pattern in the late phase. …”
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  2. 262

    uN2CpolyG-mediated p65 nuclear sequestration suppresses the NF-κB-NLRP3 pathway in neuronal intranuclear inclusion disease by Yu Shen, Kaiyan Jiang, Dandan Tan, Min Zhu, Yusen Qiu, Pencheng Huang, Wenquan Zou, Jianwen Deng, Zhaoxia Wang, Ying Xiong, Daojun Hong

    Published 2025-02-01
    “…In the Drosophila knock-in model, LPS significantly reduced the number of intranuclear inclusions and improved phenotypic manifestations. Conclusions This study revealed that uN2CpolyG directly interacts with and sequesters p65, thereby inhibiting the NF-κB-NLRP3 pathway and impairing autophagy. …”
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  3. 263

    Clinical, genomic, and histopathologic diversity in cerebral cavernous malformations by Jian Ren, Daochao Wang, Leiming Wang, Chendan Jiang, An Tian, Ziwei Cui, Yeqing Ren, Lisong Bian, Gao Zeng, Guolu Meng, Yongzhi Shan, Jiantao Liang, Xinru Xiao, Jie Tang, Yukui Wei, Chuan He, Liyong Sun, Yongjie Ma, Jiaxing Yu, Guilin Li, Ming Ye, Peng Hu, Jingwei Li, Ye Li, Lijian Niu, Qianwen Li, Feng Ling, Jan-Karl Burkhardt, Hongqi Zhang, Tao Hong

    Published 2025-02-01
    “…We analyzed 290 surgical specimens from symptomatic CCM patients, utilizing whole-exome sequencing, droplet digital PCR, and targeted panel sequencing, alongside immunohistology to examine genotypic and phenotypic differences. Among 290 cases, 201 had somatic MAP3K3, PIK3CA, or germline CCM mutations, each associated with distinct clinical parameters: hemorrhage risk (P < 0.001), lesion size (P = 0.019), non-hemorrhagic epilepsy (P < 0.001), Zabramski classifications (P < 0.001), developmental venous anomaly presence (P < 0.001), and MRI-detected edema (P < 0.001). …”
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  4. 264

    Sex differences in epigenetic ageing for older people living with HIVResearch in context by Carrie D. Johnston, Alina P.S. Pang, Eugenia L. Siegler, Charlene Thomas, Chelsie O. Burchett, Mia Crowley, Rochelle O'Brien, Lishomwa C. Ndhlovu, Marshall J. Glesby, Michael J. Corley

    Published 2025-03-01
    “…Hence, we generated a more representative epigenetic dataset to examine sex differences in epigenetic ageing and relationships to clinical phenotypes and proteomics. Methods: We calculated first, second, and third-generation epigenetic ages using DNA methylation data in an observational cohort of 52 females and 106 males with HIV age 50 and over. …”
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  5. 265

    An integrated microbiome- and metabolome-genome-wide association study reveals the role of heritable ruminal microbial carbohydrate metabolism in lactation performance in Holstein... by Chenguang Zhang, Huifeng Liu, Xingwei Jiang, Zhihong Zhang, Xinfeng Hou, Yue Wang, Dangdang Wang, Zongjun Li, Yangchun Cao, Shengru Wu, Sharon A. Huws, Junhu Yao

    Published 2024-11-01
    “…To address this gap, we collected and analyzed whole-genome resequencing data, rumen metagenomes, rumen metabolomes and short-chain fatty acids (SCFAs) content, and lactation performance phenotypes from a cohort of 304 dairy cows. Results The results indicated that the proportions of highly heritable subsets (h 2  ≥ 0.2) of the rumen microbial composition (55%), function (39% KEGG and 28% CAZy), and metabolites (18%) decreased sequentially. …”
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  6. 266

    Innovación en sueño by Laura Vigil, Toni Zapata, Andrea Grau, Marta Bonet, Montserrat Montaña, María Piñar

    Published 2024-10-01
    “…In addition, techniques such as cluster analysis are used to identify symptomatic patterns and phenotypes, which improves understanding of OSA pathophysiology and optimizes CPAP treatment.However, implementation of AI in hospitals faces technological, ethical, and legal barriers. …”
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