Results 101 to 110 of about 317,970 (262)
An unexpected alternative interaction site for ethyl viologen was identified in formate dehydrogenase 1 from Methylorubrum extorquens. Combined mutagenesis, kinetic analysis, and docking revealed that aromatic residues near an iron–sulfur cluster enable flavin mononucleotide‐independent electron transfer, offering a framework for engineering improved ...
Eleni G. Poloniataki, Yong Hwan Kim
wiley +1 more source
Aptamers are used both therapeutically and as targeting agents in cancer treatment. We developed an aptamer‐targeted PLGA–TRAIL nanosystem that exhibited superior therapeutic efficacy in NOD/SCID breast cancer models. This nanosystem represents a novel biotechnological drug candidate for suppressing resistance development in breast cancer.
Gulen Melike Demirbolat +8 more
wiley +1 more source
An evaluation of machine learning for soil analysis in internet of things-enabled smart farming
Soil plays a foundational role in sustaining agricultural productivity and ecological stability, yet traditional soil analysis methods remain labour-intensive, slow, and often inadequate for real-time decision-making in modern precision agriculture. With
Preety Chaudhary +5 more
doaj +1 more source
In this explorative study, the abundance of circular RNA molecules in bone marrow stem cells was found to be elevated in patients with high‐risk myelodysplastic neoplasms, and to be associated with an increased risk of progression to acute myeloid leukemia.
Eileen Wedge +17 more
wiley +1 more source
Comparative Analysis of Predictive Algorithms for Performance Measurement
Predictive algorithms, also known as mathematical models, utilize historical data to accurately predict future outcomes. These algorithms identify patterns and relationships within the data, resulting in precise predictions.
Swati Gupta, Bal Kishan, Preeti Gulia
doaj +1 more source
Subtype‐specific enhancer RNAs define transcriptional regulators and prognosis in breast cancers
This study employed machine learning methodologies to perform the subtype‐specific classification of RNA‐seq data sets, which are mapped on enhancers from TCGA‐derived breast cancer patients. Their integration with gene expression (referred to as ProxCReAM eRNAs) and chromatin accessibility profiles has the potential to identify lineage‐specific and ...
Aamena Y. Patel +6 more
wiley +1 more source
Among the many forms of cancer, liver tumours are among the most dangerous. Liver neoplasms can be effectively predicted, identified, and managed with the help of computer-aided technology and liver interventional surgery.
K. R Ananthapadmanaban +2 more
doaj +1 more source
Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson +9 more
wiley +1 more source
Deep Residual Transfer Ensemble Model for mRNA Gene-Expression-Based Breast Cancer
The last few years have witnessed exponential rise in breast cancer disease. The increasing mortality rate due to the lack of earlier diagnosis has alarmed healthcare industry to develop more efficient and scalable computer aided diagnosis (CAD) solution.
Job Prasanth Kumar Chinta Kunta +1 more
doaj +1 more source
COMP–PMEPA1 axis promotes epithelial‐to‐mesenchymal transition in breast cancer cells
This study reveals that cartilage oligomeric matrix protein (COMP) promotes epithelial‐to‐mesenchymal transition (EMT) in breast cancer. We identify PMEPA1 (protein TMEPAI) as a novel COMP‐binding partner that mediates EMT via binding to the TSP domains of COMP, establishing the COMP–PMEPA1 axis as a key EMT driver in breast cancer.
Konstantinos S. Papadakos +6 more
wiley +1 more source

