Evolutionary paradigms of human health and nutrition center on the evolutionary discordance or "mismatch" model in which human bodies, reflecting adaptations established in the Paleolithic era, are ill-suited to modern industrialized diets, resulting in rapidly increasing rates of chronic metabolic disease. Though this model remains useful, its utility in explaining the evolution of human dietary tendencies is limited. The assumption that human diets are mismatched to the evolved biology of humans implies that the human diet is instinctual or genetically determined and rooted in the Paleolithic era. This review looks at current research indicating that human eating habits are learned primarily through behavioral, social, and physiological mechanisms that start in utero and extend throughout the life course. Adaptations that appear to be strongly genetic likely reflect Neolithic, rather than Paleolithic, adaptations and are significantly influenced by human niche-constructing behavior. Several examples are used to conclude that incorporating a broader understanding of both the evolved mechanisms by which humans learn and imprint eating habits and the reciprocal effects of those habits on physiology would provide useful tools for structuring more lasting nutrition interventions.
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http://dx.doi.org/10.1111/nure.12039 | DOI Listing |
Ann Plast Surg
January 2025
Division of Plastic Surgery, Department of Surgery, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Introduction: Although primary tumors of the brachial plexus (BP) are rare, schwannomas are the most frequently encountered type. This study evaluated the clinicopathological presentation, surgical outcomes, and prognosis of patients with BP schwannomas.
Methods: A systematic review was conducted using PubMed/MEDLINE, Embase, and Cochrane on the 25th of March 2024.
Nat Struct Mol Biol
January 2025
Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, CA, USA.
Transthyretin (TTR) is a natively tetrameric thyroxine transporter in blood and cerebrospinal fluid whose misfolding and aggregation causes TTR amyloidosis. A rational drug design campaign identified the small molecule tafamidis (Vyndamax) as a stabilizer of the native TTR fold, and this aggregation inhibitor is regulatory agency approved for the treatment of TTR amyloidosis. Here we used cryo-EM to investigate the conformational landscape of this 55 kDa tetramer in the absence and presence of one or two ligands, revealing inherent asymmetries in the tetrameric architecture and previously unobserved conformational states.
View Article and Find Full Text PDFJ Diabetes
January 2025
Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing City, Jiangsu Province, China.
Background: Iron is one of the most important elements in brain that may has a direct impact on the stability of central nervous system. The current study devoted to explore the alterations of iron distribution across the whole brain in type 2 diabetes mellitus (T2DM) patients with mild cognitive impairment (MCI).
Methods: The quantitative susceptibility mapping (QSM) technique was used to quantify the intracranial iron content of 74 T2DM patients with MCI and 86 T2DM patients with normal cognition (NC).
Sci Rep
January 2025
Department of Respiratory and Critical Care Medicine, the Third Hospital of Wuhan, Wuhan, 430030, People's Republic of China.
Phase angle (PhA) is an indicator of nutritional status. The association between PhA and all-cause mortality has been confirmed in older adults, but no relevant studies have been conducted in adults aged 18-49 years. This study aimed to investigate the relationship between PhA and all-cause mortality in adults aged 18-49 years.
View Article and Find Full Text PDFJ Diabetes
January 2025
Department of Clinical Epidemiology and Biostatistics, Peking University People's Hospital, Beijing, China.
Understanding is limited regarding strategies for addressing missing value when developing and validating models to predict cardiovascular disease (CVD) in type 2 diabetes mellitus (T2DM). This study aimed to investigate the presence of and approaches to missing data in these prediction models. The MEDLINE electronic database was systematically searched for English-language studies from inception to June 30, 2024.
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