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| http://dx.doi.org/10.1007/s00125-009-1370-3 | DOI Listing |
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Insulin resistance compromises midbrain organoid neuronal activity and metabolic efficiency predisposing to Parkinson's disease pathology.
J Tissue Eng
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Developmental and Cellular Biology, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg.
Growing evidence indicates that type 2 diabetes (T2D) is associated with an increased risk of developing Parkinson's disease (PD) through shared disease mechanisms. Studies show that insulin resistance, which is the driving pathophysiological mechanism of T2D plays a major role in neurodegeneration by impairing neuronal functionality, metabolism and survival. To investigate insulin resistance caused pathological changes in the human midbrain, which could predispose a healthy midbrain to PD development, we exposed iPSC-derived human midbrain organoids from healthy individuals to either high insulin concentration, promoting insulin resistance, or to more physiological insulin concentration restoring insulin signalling function.
View Article and Find Full Text PDFAssociation Between Weight-Adjusted Waist Index and Cognitive Function in Older Adults Without Diabetes: A Cross-Sectional Study.
Clin Interv Aging
January 2025
Department of Laboratory Medicine, Qilu Hospital of Shandong University Dezhou Hospital, Dezhou, Shandong, 253000, People's Republic of China.
Background: This study investigates the correlation between the weight-adjusted waist index (WWI) and cognitive performance in the senior American population, focusing on those without diabetes from 2011 to 2014.
Methods: We analyzed data from the 2011-2012 and 2013-2014 National Health and Nutrition Examination Surveys (NHANES), focusing on non-diabetic participants aged 60 and older who completed cognitive tests: Establish a Registry for Alzheimer's disease (CERAD), the Animal Fluency test (AFT), and Digit Symbol Substitution test (DSST). WWI was calculated using waist circumference divided by the square root of body weight.
Nutrition users' guides: systematic reviews part 1 -structured guide for methodological assessment, interpretation and application of systematic reviews and meta-analyses of non-randomised nutritional epidemiology studies.
BMJ Nutr Prev Health
August 2024
Department of Nutrition, College of Agriculture and Life Sciences, Texas A&M University, College Station, Texas, USA.
Due to the challenges of conducting randomised controlled trials (randomised trials) of dietary interventions, evidence in nutrition often comes from non-randomised (observational) studies of nutritional exposures-called nutritional epidemiology studies. When using systematic reviews of such studies to advise patients or populations on optimal dietary habits, users of the evidence (eg, healthcare professionals such as clinicians, health service and policy workers) should first evaluate the rigour (validity) and utility (applicability) of the systematic review. Issues in making this judgement include whether the review addressed a sensible question; included an exhaustive literature search; was scrupulous in the selection of studies and the collection of data; and presented results in a useful manner.
View Article and Find Full Text PDFPrimary care providers' perspectives on referrals to the Diabetes Prevention Programme: a qualitative comparative study across varied referral patterns.
BMJ Nutr Prev Health
August 2024
Medicine and Population Health, New York University Grossman School of Medicine, New York, New York, USA.
Introduction: Despite the effectiveness of Diabetes Prevention Programmes (DPP) in reducing diabetes risk, primary care provider (PCP) referrals remain low, especially among men and racial/ethnic minorities, exacerbating their under-representation in DPPs. Understanding PCPs' perspectives on referrals is crucial for enhancing the intervention's reach and effectiveness.
Research Design And Methods: We conducted a qualitative study to explore PCPs' experiences, perspectives and engagement with DPP referrals, focusing on factors influencing variations in referral rates.
Nutrition Users' Guides: RCTs Part 2 - structured guide for interpreting and applying study results from randomised controlled trials on therapy or prevention questions.
BMJ Nutr Prev Health
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Department of Nutrition, College of Agriculture and Life Sciences, Texas A&M University, College Station, Texas, USA.
This article continues from a prior commentary on evaluating the risk of bias in randomised controlled trials addressing nutritional interventions. Having provided a synopsis of the risk of bias issues, we now address how to understand trial results, including the interpretation of best estimates of effect and the corresponding precision (eg, 95% CIs), as well as the applicability of the evidence to patients based on their unique circumstances (eg, patients' values and preferences when trading off potential desirable and undesirable health outcomes and indicators (eg, cholesterol), and the potential burden and cost of an intervention). Authors can express the estimates of effect for health outcomes and indicators in relative terms (relative risks, relative risk reductions, OR or HRs)-measures that are generally consistent across populations-and absolute terms (risk differences)-measures that are more intuitive to clinicians and patients.
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