Results 91 to 100 of about 2,835,752 (355)

Additional file 9 of Prediction and mechanistic analysis of drug-induced liver injury (DILI) based on chemical structure

, 2021
Additional file 9: TableS4. Top significant structural alerts (p-value ≤0.05). The following quality metrics are shown: precision, coverage in DILI positive compounds (%), and number of Drugbank [44] approved compounds with the substructure are shown.
Liu, Anika, Walter, Moritz, Wright, Peter, Bartosik, Aleksandra, Dolciami, Daniela, Elbasir, Abdurrahman, Hongbin Yang, Bender, Andreas   +7 more
openaire   +2 more sources

Plasma lipidomic and metabolomic profiles in high‐grade glioma patients before and after 72‐h presurgery water‐only fasting

Molecular Oncology, EarlyView.
Presurgery 72‐h fasting in GB patients leads to adaptations of plasma lipids and polar metabolites. Fasting reduces lysophosphatidylcholines and increases free fatty acids, shifts triglycerides toward long‐chain TGs and increases branched‐chain amino acids, alpha aminobutyric acid, and uric acid.
Iris Divé, Lisa Hahnefeld, Katharina J. Wenger, Donat Kögel, Joachim Steinbach, Gerd Geisslinger, Michael W. Ronellenfitsch, Irmgard Tegeder   +7 more
wiley   +1 more source

Prediction of repurposed drugs for treating lung injury in COVID-19 [PDF]

arXiv, 2020
Coronavirus disease (COVID-19) is an infectious disease discovered in 2019 and currently in outbreak across the world. Lung injury with severe respiratory failure is the leading cause of death in COVID-19, brought by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
arxiv  

Attenuation of ischemic liver injury by prostaglandin E1 analogue, misoprostol, and prostaglandin I2 analogue, OP-41483 [PDF]

, 1998
Background: Prostaglandin has been reported to have protective effects against liver injury. Use of this agent in clinical settings, however, is limited because of drugrelated side effects.
Ishizaki, N, Jin, MB, Kawashima, Y, Shimamura, T, Starzl, TE, Todo, S, Totsuka, E, Urakami, A, Zhu, Y   +8 more
core   +1 more source

Hydrophobicity causes anomalous migration of cystine/glutamate antiporter SLC7A11 in SDS‐PAGE with low acrylamide concentration

FEBS Open Bio, EarlyView.
SLC7A11 frequently migrates faster in SDS‐PAGE. The present study found that the high hydrophobicity of SLC7A11 causes its anomalous migration in SDS‐PAGE with a low concentration of acrylamide gel. Replacing isoleucine with asparagine reduced hydrophobicity and restored its normal migration at 55 kDa, revealing the role of hydrophobicity and gel ...
Nsengiyumva Emmanuel, Qian He, Yixin Kang, Dianbao Zhang, Min Gao, Minglin Wang, Kexin Fan, Jingwen Xiong, Shaobo Wu, Botao Fa, Zhengtao Xiao, Yingfang Niu, Jun Yao, Yilei Zhang   +13 more
wiley   +1 more source

REMEDI: REinforcement learning-driven adaptive MEtabolism modeling of primary sclerosing cholangitis DIsease progression [PDF]

arXiv, 2023
Primary sclerosing cholangitis (PSC) is a rare disease wherein altered bile acid metabolism contributes to sustained liver injury. This paper introduces REMEDI, a framework that captures bile acid dynamics and the body's adaptive response during PSC progression that can assist in exploring treatments.
arxiv  

Current trends in drug metabolism and pharmacokinetics. [PDF]

, 2019
Pharmacokinetics (PK) is the study of the absorption, distribution, metabolism, and excretion (ADME) processes of a drug. Understanding PK properties is essential for drug development and precision medication.
Abduljalil, Aghazadeh-Habashi, Aigrain, Aitman, Al Za'abi, Alegre, Alnaqeeb, Aspromonte, Babiskin, Baert, Bakke, Barnett, Bhattacharyya, Cang, Cannady, Cao, Cao, Capecchi, Chen, Chen, Chen, Chen, Chen, Chen, Chen, Cheng, Cheng, Crawford, Currie, De Lange, Dean, Deng, Di Paolo, Dietrich, Diliberto, Dluzen, Dowling, Dragin, Dreisbach, Duan, Edeogu, Edginton, El-Arabey, El-Kadi, EMA, Eum, Falany, Fang, FDA, Feng, Feng, Feng, Ferri, Fleming, Foti, Fox, Freedman, Frye, Fukami, Gaj, Gan, Gao, Gao, Gao, Gao, Gao, Ge, Genovese, Gingell, Gingell, Gong, Graham, Gufford, Guo, Guo, Guo, Guévin, Han, Harrison, Hartz, Hasegawa, He, He, He, He, He, Ho, Ho, Hou, Hsu, Hsueh, Hu, Hu, Hu, Huo, Hwang, Ito, Jacob, Jeong, Jeong, Jia, Jian, Jiang, Jiang, Jiang, Jiang, Jilek, Jilek, Johnson, Jorga, Jung, Kaivosaari, Kalthoff, Kaminsky, Kannan, Karibe, Kesisoglou, Kim, Kim, Knights, Kong, Kota, Kumar, Kurokawa, Lai, Lan, Lanchote, Lee, Lehouritis, Li, Li, Li, Li, Li, Li, Li, Li, Li, Li, Li, Liang, Lin, Liu, Liu, Liu, Liu, Liu, Liu, Liu, Liu, Liu, Liu, Liu, Liu, Lopes-Rodrigues, Lu, Lu, Lu, Löfgren, Mano, Marchitti, Margolskee, Martin, Matsson, Mattick, Mazerska, Mei, Mencia, Meng, Min, Mitra, Miyajima, Müller, Nair, Nakano, Nakano, Nakano, Nebert, Nguyen, Niederalt, Nieto Montesinos, Niu, Notenboom, Nozaki, Ohtsuki, Ono, Oostendorp, Pan, Pan, Papageorgiou, Papageorgiou, Park, Pea, Pedersen, Pelkonen, Pellegrino, Pettersson Bergstrand, Qi, Qin, Qiu, Qiu, Raaska, Rives, Riviere, Roberts, Robey, Rocha, Rose, Routy, Rowland, Ruwali, Saini, Satoh, Savage, Scheer, Scheer, Schlender, Schmitt, Schneider, Seitz, Showande, Shu, Shu, Shu, Shugarts, Siu, Song, Staudinger, Strong, Suarez-Sharp, Suh, Suiko, Sukkummee, Sun, Sun, Sutliff, Takeda, Tan, Tan, Tao, Tatsumi, Teorell, Tsai, Tsang, Tsuchiya, Tsume, Tu, Ulldemolins, van Waterschoot, von Richter, Vugmeyster, Vuppugalla, Wagner, Wagner, Wagner, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wang, Wassenaar, Watanabe, Wei, Wijayakumara, Wilkinson, Wong, Wu, Xia, Xie, Xie, Xu, Xu, Xu, Xu, Xu, Xue, Yamagata, Yamaguchi, Yan, Yang, Yang, Yang, Ye, Yellepeddi, Yi, Yi, Yigitaslan, Yim, Yin, Yoshida, Yoshida, Yoshimi, Yu, Yu, Yu, Yu, Yu, Yu, Yu, Zakeri-Milani, Zanger, Zeng, Zeng, Zhai, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhang, Zhao, Zhao, Zhao, Zhao, Zhou, Zhou, Zhou, Zhou, Zhou, Zhu, Zhu, Zhu, Zhuang, Zimmermann   +332 more
core   +1 more source

Prediction of Drug-Induced Liver Injury: From Molecular Physicochemical Properties and Scaffold Architectures to Machine Learning Approaches.

Chemical Biology and Drug Design
The process of developing new drugs is widely acknowledged as being time-intensive and requiring substantial financial investment. Despite ongoing efforts to reduce time and expenses in drug development, ensuring medication safety remains an urgent ...
Yulong Zhao, Zhoudong Zhang, Xiaotian Kong, Kai Wang, Yaxuan Wang, Jie Jia, Huanqiu Li, Sheng Tian   +7 more
semanticscholar   +1 more source

METTL3 knockout accelerates hepatocarcinogenesis via inhibiting endoplasmic reticulum stress response

FEBS Open Bio, EarlyView.
Liver‐specific knockout of N6‐methyladenosine (m6A) methyltransferase METTL3 significantly accelerated hepatic tumor initiation under various oncogenic challenges, contrary to the previously reported oncogenic role of METTL3 in liver cancer cell lines or xenograft models. Mechanistically, METTL3 deficiency reduced m6A deposition on Manf transcripts and
Bo Cui, Silin Tu, Haibo Li, Zhancheng Zeng, Ruiqi Xiao, Jing Guo, Xiaoqi Liang, Chang Liu, Lijie Pan, Wenjie Chen, Mian Ge, Xiaofen Zhong, Linsen Ye, Huaxin Chen, Qi Zhang, Yan Xu   +15 more
wiley   +1 more source

Discovering Drug-Drug and Drug-Disease Interactions Inducing Acute Kidney Injury Using Deep Rule Forests [PDF]

arXiv, 2020
Patients with Acute Kidney Injury (AKI) increase mortality, morbidity, and long-term adverse events. Therefore, early identification of AKI may improve renal function recovery, decrease comorbidities, and further improve patients' survival. To control certain risk factors and develop targeted prevention strategies are important to reduce the risk of ...
arxiv