Results 221 to 230 of about 365,495 (322)

Imidazolinium-Based NHC-Metal Complexes Overcome Both Cancer Multidrug Resistance and Cisplatin Resistance In Vitro. [PDF]

Int J Mol Sci
Szlávik M, Haffarases LI, Mandel R, Fekecs F, Apáti Á, Paczal A, Kotschy A, Szakács G, Tóth S.   +8 more
europepmc   +1 more source

Microarray analysis of gene expression profile of multidrug resistance in pancreatic cancer

, 2007
Yupei Zhao, Ge Chen, Bin Feng, Taiping Zhang, Enling Ma, Yuan-de Wu   +5 more
openalex   +1 more source

Antimicrobial Cyclic Peptidomimetics

Macromolecular Rapid Communications, EarlyView.
Singular macromolecular cationic, amphipathic cyclic peptidomimetics with poly(2‐oxazoline)s‐esque backbone structure that undergo self‐assembly in water to form uniform nanoparticles were developed. The cyclic peptidomimetics, which act on bacterial cell membranes, exhibit hydrophobic‐dependent antimicrobial activity and toxicity.
Hao Luo, Edgar H. H. Wong
wiley   +1 more source

Targeting NFAT2 for Reversing the P-gp-Mediated Multidrug Resistance to Paclitaxel by Manidipine. [PDF]

Cancers (Basel)
Zhou J, Wang N, Lin YK, Li QL, Liu RM, Hu JQ, Zhou H, Lan H, Xie Y.   +8 more
europepmc   +1 more source

Multidrug resistance-associated protein 1 and lung function decline with or without long-term corticosteroids treatment in COPD

, 2012
Simona E. Budulac, Dirkje S. Postma, Pieter S. Hiemstra, Thérèse Lapperre, Lisette I.Z. Kunz, Judith M. Vonk, H. Marike Boezen, Wim Timens, the GLUCOLD study group   +8 more
openalex   +2 more sources

Uncovering Key Characteristics of Antibacterial Peptides through Machine Learning

Macromolecular Rapid Communications, EarlyView.
Machine‐learning (ML) techniques using random forest classification models revealed key characteristics that predict effective antimicrobial peptides (AMPs) targeting Gram‐negative bacteria, Gram‐positive bacteria, and mycobacteria. The ideal cLogP (<$ < $−6) and net‐charge (≤+4) threshold was the same for all three targets with variations in the ...
Jooyoung Roh, Cyrille Boyer, Priyank V. Kumar   +2 more
wiley   +1 more source

Suppressing protein damage response to overcome multidrug resistance in cancer therapy. [PDF]

Cell Discov
Shao F, Li Z, Xiao H, Chen Y, Zhang Y, Li L, Peng Y, Li X, Hou Y, Li B, Chu X, Ran M, Tang D, Han X, Yao J, Zhang C, Wang L, Li H, Shao N, Miao K, Xu X, Shi Y, Zhang C, Yan J, Lin Y, Deng CX.   +25 more
europepmc   +1 more source

Synergistic Reversal Of Multidrug Resistance In Colon Cancer Via A Ratiometric Paclitaxel-Baicalein Co-Crystal Embedded Nanoemulsion: From Molecular Engineering To Mechanistic Efficacy

Amanpreet Kaur Dumda, Swati Rawat, Dr. Radhakrishnan, M. Tigote   +3 more
openalex   +1 more source

Machine Learning for Predictive Modeling in Nanomedicine‐Based Cancer Drug Delivery

Med Research, EarlyView.
The integration of AI/ML into nanomedicine offers a transformative approach to therapeutic design and optimization. Unlike conventional empirical methods, AI/ML models (such as classification, regression, and neural networks) enable the analysis of complex clinical and formulation datasets to predict optimal nanoparticle characteristics and therapeutic
Rohan Chand Sahu, Sanchit Arora, Dinesh Kumar, Ashish Kumar Agrawal   +3 more
wiley   +1 more source

Downregulation of hepatic sulfotransferase 1E1 expression associated with decreased expression of multidrug resistance-associated protein 2. [PDF]

Drug Metab Dispos
Fujino C, Ueshima S, Fukami T, Nakajima M, Katsura T.   +4 more
europepmc   +1 more source