Publications by authors named "R Tauman"

Background/objectives: Studies have shown that chronobiological factors may adversely affect glycemic control in patients with type 2 diabetes mellitus. We assessed the association of chronobiological factors with glycemic control and neonatal birth weight in women with GDM.

Methods: A prospective cohort study included 208 women aged 18-45 years with a singleton pregnancy who were randomly selected from among women undergoing follow-up for GDM at the Maternal-Fetal Medicine Unit of a tertiary medical center.

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Polysomnography, the gold standard diagnostic tool in sleep medicine, is performed in an artificial environment. This might alter sleep and may not accurately reflect typical sleep patterns. While macro-structures are sensitive to environmental effects, micro-structures remain more stable.

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Article Synopsis
  • The study focuses on how motor learning can be generalized to improve skill acquisition under varying conditions, particularly looking at the effects of sleep on performance.
  • In the first experiment with healthy young participants, it was found that learning a new motor task led to both immediate skill improvement and additional gains over time, with sleep enhancing accuracy but not speed.
  • The second experiment compared young healthy individuals with drug-naïve Parkinson's patients, revealing that while both groups improved in accuracy post-sleep, the Parkinson's group showed difficulties in recalling motor sequences due to cognitive challenges linked to the disease.
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Objective: Maternal lipid levels increase in normal pregnancies. Here, we examine whether pregnancies with the highest total cholesterol, low-density lipoprotein (LDL) or triglyceride levels or the lowest high-density lipoprotein (HDL) levels predict future dyslipidemia post-pregnancy.

Design: Longitudinal cohort study.

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Background: Sleep staging is critical for diagnosing sleep disorders. Traditional methods in clinical settings involve time-intensive scoring procedures. Recent advancements in data-driven algorithms using photoplethysmogram (PPG) time series have shown promise in automating sleep staging in adults.

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