Publications by authors named "M ELKIN"
Predicting novel mutations has long-lasting impacts on life science research. Traditionally, this problem is addressed through wet-lab experiments, which are often expensive and time consuming. The recent advancement in neural language models has provided stunning results in modeling and deciphering sequences.
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- * The study reveals new methods for processing methyl groups in terpenoids, through a combination of silylation and oxidation, leading to various transformations such as substitution and integration of the methyl carbon.
- * These processes not only allow for the creation of novel chemical structures with expanded rings but also show potential applications in medicinal chemistry by adding functional groups to complex compounds.
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- Nuclear magnetic resonance (NMR) spectroscopy is crucial for analyzing chemical compounds but often requires manual interpretation, limiting its use in high-throughput experiments.
- Current automation methods depend on existing spectral databases, making them ineffective for discovering new chemicals.
- By treating NMR spectra as joint probability distributions and applying advanced computational methods, researchers can accurately analyze complex mixtures without prior spectral references, achieving high accuracy in identifying compounds and their concentrations.
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- - This study explores the link between an anaerobic bacterium associated with periodontal disease and the development of pancreatic ductal adenocarcinoma (PDAC) by analyzing its impact in a mouse model.
- - Researchers tracked how the bacteria moved from the mouth to the pancreas and observed that it accelerated the progression from pancreatic intraepithelial neoplasia (PanIN) to PDAC while affecting cell behavior in vitro.
- - The findings suggest that this bacterium plays a significant role in promoting pancreatic cancer, indicating a potential new avenue for understanding cancer development.
Pancreatic ductal adenocarcinoma (PDAC) is an aggressive tumor, which is highly resistant to existing therapies and characterized by one of the lowest survival rates known for solid cancers. Among the reasons for this poor prognosis are unique pathophysiological features of PDAC, such as dense extracellular matrix [ECM] creating barriers to drug delivery, as well as systemically-deregulated glucose metabolism manifested by diabetic conditions (i.e.
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