Publications by authors named "Connor Quinn"

Objective: Caloric restriction (CR) is known to enhance insulin sensitivity and reduce the risk of metabolic disorders; however, its molecular mechanisms are not fully understood. This study aims to elucidate specific proteins and pathways responsible for these benefits.

Methods: We examined adipose tissue from participants in the Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy Phase 2 (CALERIE 2) study, comparing proteomic profiles from individuals after 12 and 24 months of CR with baseline and an ad libitum group.

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  • Estrogen receptor (ER) alpha is a key factor in ER+/HER2- breast cancer, and combining current therapies with new drugs is essential due to resistance issues like ESR1 mutations.
  • Vepdegestrant (ARV-471) is a new drug that efficiently degrades both wild-type and mutant ER, showing significant tumor growth inhibition in various breast cancer models, outperforming the standard treatment fulvestrant.
  • The study suggests that vepdegestrant could be a more effective treatment option for patients with ER+/HER2- breast cancer, especially when combined with other therapies like CDK4/6, mTOR, or PI3K inhibitors.
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  • The study focuses on developing VHL-binding PROTACs that specifically target and degrade the BRM protein in lung cancer cells.
  • These PROTACs show significant selectivity, degrading BRM up to 100 times more than its similar cousin, BRG1, and hinder the growth of BRG1-mutant NSCLC cells that rely on BRM.
  • Further testing in animal models demonstrated that achieving over 95% BRM degradation is crucial for effective antitumor responses, linking BRM activity to tumor growth regulation.
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  • Targeted protein degradation (TPD) is highlighted as a new therapeutic strategy using PROTAC technology to selectively degrade proteins in cells.
  • Researchers discovered small-molecule ligands that specifically target the E3 ligase KLHDC2, expanding the options available for TPD.
  • The study reveals how the KLHDC2 E3 ligase forms a dynamic tetrameric structure, which can be influenced by the interaction with substrates and ligands, enhancing our understanding of its functioning and potential applications.
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Hepatic fibrosis is the primary determinant of mortality in patients with metabolic dysfunction-associated steatohepatitis (MASH). Transforming growth factor-β (TGFβ), a master profibrogenic cytokine, is a promising therapeutic target that has not yet been translated into an effective therapy in part because of liabilities associated with systemic TGFβ antagonism. We have identified that soluble folate receptor γ (FOLR3), which is expressed in humans but not in rodents, is a secreted protein that is elevated in the livers of patients with MASH but not in those with metabolic dysfunction-associated steatotic liver disease, those with type II diabetes, or healthy individuals.

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  • Scientists studied a protein called SMARCA4 that often has mutations in cancer and found that cancer cells rely on another protein called SMARCA2 when SMARCA4 is broken.
  • They created a special molecule called A947 that can specifically target and get rid of SMARCA2 without affecting other proteins.
  • Tests showed that A947 works well against cancer cells with broken SMARCA4, offering hope for new treatments for patients with this kind of cancer.
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Nonalcoholic fatty liver disease (NAFLD) is the number one cause of chronic liver disease worldwide, with 25% of these patients developing nonalcoholic steatohepatitis (NASH). NASH significantly increases the risk of cirrhosis and decompensated liver failure. Past studies in rodent models have shown that glycine--methyltransferase (GNMT) knockout results in rapid steatosis, fibrosis, and hepatocellular carcinoma progression.

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Understanding the neural processes that underlie learning to read can provide a scientific foundation for literacy education but studying these processes in real-world contexts remains challenging. We present behavioural data from adult participants learning to read artificial words and name artificial objects over two days. Learning profiles and generalisation confirmed that componential learning of visual-verbal associations distinguishes reading from object naming.

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