Results 151 to 160 of about 515,000 (271)

Cost‐Effective Identification of Hepatocellular Carcinoma from Cirrhosis or Chronic Hepatitis Virus Infection Using Eight Methylated Plasma DNA Markers

Advanced Science, EarlyView.
Early detection of hepatocellular carcinoma in patients with liver cirrhosis and/or hepatitis virus B/C infection improves survival. Through marker discovery, 8 methylated DNA markers are identified and a logistic regression model (COMET‐LR) is built in the training set, which achieved 90.0% sensitivity at 97.4% specificity in the validation set.
Tian Yang, Mingda Wang, Nanya Wang, Mingxin Pan, Yu Xu, Qiancheng You, Lanqing Yao, Jiahao Xu, Lihui Gu, Xiaodong Sun, Lei Zhang, Jiayue Xu, Bingsi Li, Guoqiang Wang, Shangli Cai, Guoyue Lv, Feng Shen   +16 more
wiley   +1 more source

Positive Feedback Regulation between KLF5 and XPO1 Promotes Cell Cycle Progression of Basal like Breast Cancer

Advanced Science, EarlyView.
KLF5 is highly expressed in BLBC patients and promotes Cyclin D1 and XPO1 transcription, ultimately leading to the inactivation of RB1. Both XPO1 inhibitor (KPT‐330) and CDK4/6 inhibitor (Palbociclib) can enhance RB1 activity and exert antitumor effects. It has been proved that the combination of KPT‐330 and Palbociclib can inhibit the proliferation of
Yu Tang, Rui Liu, Jing Zhu, Qian He, Chenglong Pan, Zhongmei Zhou, Jian Sun, Fubing Li, Longlong Zhang, Yujie Shi, Jing Yao, Dewei Jiang, Ceshi Chen   +12 more
wiley   +1 more source

DPImpute: A Genotype Imputation Framework for Ultra‐Low Coverage Whole‐Genome Sequencing and its Application in Genomic Selection

Advanced Science, EarlyView.
DPImpute is a two‐step pipeline that outperforms existing tools in whole‐genome SNP imputation, particularly under conditions of ultra‐low coverage sequencing, small sample sizes, and limited references. It enables precise imputation for single blastocyst cells, supporting genomic selection at the pre‐implantation stage.
Weigang Zheng, Wenlong Ma, Zhilong Chen, Chao Wang, Tao Sun, Wenjun Dong, Wenjing Zhang, Song Zhang, Zhonglin Tang, Kui Li, Yunxiang Zhao, Yuwen Liu   +11 more
wiley   +1 more source

Identification of serum microRNAs as potential diagnostic biomarkers for detecting precancerous lesions of gastric cancer

Annals of Gastroenterological Surgery, Volume 7, Issue 1, Page 63-70, January 2023., 2023
We found that microRNA‐196b‐5p was significantly upregulated in precancerous lesions and that combining it with other microRNAs increased the accuracy of detection. Since endoscopy is associated with risk, the identification of high‐risk groups for gastric cancer is expected to make it possible to clearly identify groups that should undergo endoscopy ...
Hajime Otsu, Sho Nambara, Qingjiang Hu, Yuichi Hisamatsu, Takeo Toshima, Kazuki Takeishi, Yusuke Yonemura, Takaaki Masuda, Eiji Oki, Koshi Mimori   +9 more
wiley   +1 more source

Macrophage HM13/SPP Enhances Foamy Macrophage Formation and Atherogenesis

Advanced Science, EarlyView.
Previous research suggests that AIP may prevent atherogenic foamy macrophage formation. This study reveals that AIP, via its chaperone interaction with AHR, inhibits p38‐c‐JUN‐mediated transactivation of HM13, which encodes the ERAD protease HM13/SPP. HM13/SPP promotes foamy macrophage formation in addition to atherogenesis and plaque foamy macrophage ...
Yu Cao, Qirong Xie, Qiang Zheng, Jingping Zhang, Mengyu Yao, Zhongyong Du, Lujun Zhang, Tianyang Hu, Yunli Zhao, Jianlin Du, Yongyong Li, Yuxing Feng, ND Melgiri, Xiaodong Zhao, Rongzhong Huang, Yang Sun   +15 more
wiley   +1 more source

Consensus statement: chromosomal microarray is a first-tier clinical diagnostic test for individuals with developmental disabilities or congenital anomalies.

American Journal of Human Genetics, 2010
David T. Miller, M. Adam, M. Adam, S. Aradhya, L. Biesecker, A. Brothman, N. Carter, D. Church, J. Crolla, E. Eichler, C. Epstein, W. Faucett, L. Feuk, J. Friedman, A. Hamosh, L. Jackson, E. B. Kaminsky, K. Kok, I. Krantz, R. Kuhn, Charles Lee, J. Ostell, C. Rosenberg, S. Scherer, N. Spinner, D. Stavropoulos, J. Tepperberg, E. Thorland, J. Vermeesch, D. Waggoner, M. Watson, C. Martin, D. Ledbetter   +32 more
semanticscholar   +1 more source

The Super Enhancer‐Driven Long Noncoding RNA PRKCQ‐AS1 Promotes Neuroblastoma Tumorigenesis by Interacting With MSI2 Protein and Is Targetable by Small Molecule Compounds

Advanced Science, EarlyView.
PRKCQ‐AS1 is overexpressed due to transcriptional super‐enhancers. PRKCQ‐AS1 RNA forms a complex with MSI2 protein to induce BMX mRNA stabilization and overexpression, ERK protein phosphorylation and neuroblastoma cell proliferation. Compound NSC617570 blocks PRKCQ‐AS1 binding to MSI2, leading to BMX mRNA disassociation from MSI2 protein, BMX reduction,
Sujanna Mondal, Pei Y. Liu, Janith Seneviratne, Antoine De Weck, Pooja Venkat, Chelsea Mayoh, Jing Wu, Jesper Maag, Jingwei Chen, Matthew Wong, Nenad Bartonicek, Poh Khoo, Lei Jin, Louise E. Ludlow, David S. Ziegler, Toby Trahair, Pieter Mestdagh, Belamy B. Cheung, Jinyan Li, Marcel E. Dinger, Ian Street, Xu D. Zhang, Glenn M. Marshall, Tao Liu   +23 more
wiley   +1 more source

An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1,809 patients

Breast Cancer Research and Treatment, 2010
Balázs Győrffy, A. Lánczky, A. Eklund, C. Denkert, J. Budczies, Qiyuan Li, Z. Szallasi   +6 more
semanticscholar   +1 more source

Icaritin Represses Autophagy to Promote Colorectal Cancer Cell Apoptosis and Sensitized Low‐Temperature Photothermal Therapy via Targeting HSP90‐TXNDC9 Interactions

Advanced Science, EarlyView.
Icaritin demonstrates broad antitumor effects by inhibiting colorectal cancer (CRC) cell proliferation, migration, invasion, and causing cell cycle arrest. It induces apoptosis by repressing autophagic flux through disrupting HSP90‐TXNDC9 interactions.
Dan He, Siliang Chen, Xiaoyun Wang, Xiang Wen, Changyang Gong, Lei Liu, Gu He   +6 more
wiley   +1 more source

Machine Learning‐Enabled Drug‐Induced Toxicity Prediction

Advanced Science, EarlyView.
Unexpected toxicity accounts for 30% of drug development failures. This review highlights ML innovations in predicting drug‐induced toxicity, emphasizing comparative analyses, interpretable algorithms, and multi‐source data integration. It categorizes toxicity types, summarizes ML models, and organizes key databases, offering strategies to address ...
Changsen Bai, Lianlian Wu, Ruijiang Li, Yang Cao, Song He, Xiaochen Bo   +5 more
wiley   +1 more source