Publications by authors named "D Nayar"

Background: Stimulant use has been associated with an increased risk of stroke, though data on clinical characteristics and exact risk are limited. This retrospective case-control study examines stroke risk in individuals with stimulant use disorder using data from a national U.S.

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Article Synopsis
  • Biomolecules in living cells experience crowded environments due to high concentrations of cosolutes and macromolecules, affecting their dynamics and structure.
  • This study uses molecular dynamics simulations to analyze how confinement and the presence of cosolutes like urea influence the collapse equilibria of three different model polymers.
  • The findings reveal that confinement usually promotes polymer collapse, but the effects of urea vary: it weakens collapses in hydrophobic polymers while enhancing collapses in hydrophilic ones, leading to complex interactions that impact the stability of biomolecules in cells.
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Accounting for the crowding effects inside a living cell is crucial to obtain a comprehensive view of the biomolecular processes and designing responsive polymer-based materials for biomedical applications. These effects have long been synonymous with the entropic volume exclusion effects. The role of soft, attractive intermolecular interactions remains elusive.

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It is widely accepted that deciphering biomolecular structure and function requires going beyond the single-molecule or single-complex paradigm. The densely packed macromolecules, cosolutes, and metabolites in the living cell impose crowding effects on the biomolecular structure and dynamics that need to be accounted for. Molecular simulations have proven to be a powerful tool to advance the current molecular-level understanding of such a highly concentrated, complex milieu.

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Unlabelled: A substantial percentage of the population remains at risk for cervical cancer due to pre-existing human papillomavirus (HPV) infections, despite prophylactic vaccines. Early diagnosis and treatment are crucial for better disease outcomes. The development of new treatments heavily relies on suitable preclinical model systems.

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