KAI1, A prostate metastasis suppressor: Prediction of solvated structure and interactions with binding partners; integrins, cadherins, and cell‐surface receptor proteins† [PDF]
Rachelle J. Bienstock, J. Carl Barrett
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Objective This study investigated whether sleep disturbance can predict the extent to which pain interferes with daily functioning in patients with early rheumatoid arthritis (RA). Methods Data were from adults with early RA (joint symptoms ≤12 months) enrolled in the Canadian Early Arthritis Cohort between 2016 and 2023.
Burcu Aydemir+16 more
wiley +1 more source
Adaptive gradient scaling: integrating Adam and landscape modification for protein structure prediction. [PDF]
Kapitan V, Choi M.
europepmc +1 more source
DeepFold: enhancing protein structure prediction through optimized loss functions, improved template features, and re-optimized energy function. [PDF]
Lee JW+18 more
europepmc +1 more source
PREDICTION OF PROTEIN SECONDARY STRUCTURE USING LOGICAL ANALYSIS OF DATA ALGORITHM [PDF]
Jacek Błażewicz+2 more
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Objective Administrative claims are used to evaluate oral glucocorticoid use in rheumatoid arthritis (RA), despite limited evidence to support accuracy. We aimed to evaluate the performance of claims‐based algorithms for glucocorticoid use compared to self‐report in an RA population.
Beth I. Wallace+16 more
wiley +1 more source
Emerging frontiers in protein structure prediction following the AlphaFold revolution. [PDF]
Rennie ML, Oliver MR.
europepmc +1 more source
The axolotl's remarkable regenerative abilities decline with age, the causes may include the numerous repetitive elements within its genome. This study uncovers how Ty3 retrotransposons and coexpression networks involving muscle and immune pathways respond to aging and regeneration, suggesting that transposons respond to physiological shifts and may ...
Samuel Ruiz‐Pérez+8 more
wiley +1 more source
Protein structure prediction via deep learning: an in-depth review. [PDF]
Meng Y+7 more
europepmc +1 more source
Protein folding simulation with a coarse graind model : towards structure prediction
Shoji Takada
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