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Physical activity (PA) and sport play an essential role in promoting body development and maintaining optimal health status both in the short and long term. Despite the benefits, a long-lasting heavy training can promote several detrimental physiological changes, including transitory immune system malfunction, increased inflammation, and oxidative stress, which manifest as exercise-induced muscle damages (EIMDs). Meat and derived products represent a very good source of bioactive molecules such as proteins, lipids, amino acids, vitamins, and minerals. Bioactive molecules represent dietary compounds that can interact with one or more components of live tissue, resulting in a wide range of possible health consequences such as immune-modulating, antihypertensive, antimicrobial, and antioxidative activities. The health benefits of meat have been well established and have been extensively reviewed elsewhere, although a growing number of studies found a significant positive effect of meat molecules on exercise performance and recovery of muscle function. Based on the limited research, meat could be an effective post-exercise food that results in favorable muscle protein synthesis and metabolic performance.
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http://dx.doi.org/10.3390/ijerph19095145 | DOI Listing |
Stroke
September 2025
Brain Language Laboratory, Freie Universität Berlin, Germany (A.-T.P.J., M.R.O., A.S., F.P.).
Background: Intensive language-action therapy treats language deficits and depressive symptoms in chronic poststroke aphasia, yet the underlying neural mechanisms remain underexplored. Long-range temporal correlations (LRTCs) in blood oxygenation level-dependent signals indicate persistence in brain activity patterns and may relate to learning and levels of depression. This observational study investigates blood oxygenation level-dependent LRTC changes alongside therapy-induced language and mood improvements in perisylvian and domain-general brain areas.
View Article and Find Full Text PDFNeurotrauma Rep
August 2025
Department of Radiology, Weill Cornell Medicine; New York, New York, USA.
Traumatic brain injury (TBI) impairs attention and executive function, often through disrupted coordination between cognitive and autonomic systems. While electroencephalography (EEG) and pupillometry are widely used to assess neural and autonomic responses independently, little is known about how these systems interact in TBI. Understanding their coordination is essential to identify compensatory mechanisms that may support attention under conditions of neural inefficiency.
View Article and Find Full Text PDFNeurotrauma Rep
August 2025
Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing, China.
Accurate differentiation between persistent vegetative state (PVS) and minimally conscious state and estimation of recovery likelihood in patients in PVS are crucial. This study analyzed electroencephalography (EEG) metrics to investigate their relationship with consciousness improvements in patients in PVS and developed a machine learning prediction model. We retrospectively evaluated 19 patients in PVS, categorizing them into two groups: those with improved consciousness ( = 7) and those without improvement ( = 12).
View Article and Find Full Text PDFCurr Dev Nutr
September 2025
Department of Sport, Exercise and Nutrition, Atlantic Technological University, Galway, Ireland.
Background: Nutrition underpins athletic performance, enhancing training, reducing injury risk, and accelerating recovery. In the event of an injury, performance dietitians (PDs) and nutritionists' (PNs) play a vital role by tailoring nutritional strategies to support tissue repair, optimize athlete's recoveries, and return to play.
Objectives: This study explored nutritional strategies recommended and employed by Irish PDs and PNs to assess, manage, and support athletes during the initial stages of sports-related injuries.
Front Rehabil Sci
August 2025
Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, CA, United States.
Introduction: Spinal cord injury (SCI) presents a significant burden to patients, families, and the healthcare system. The ability to accurately predict functional outcomes for SCI patients is essential for optimizing rehabilitation strategies, guiding patient and family decision making, and improving patient care.
Methods: We conducted a retrospective analysis of 589 SCI patients admitted to a single acute rehabilitation facility and used the dataset to train advanced machine learning algorithms to predict patients' rehabilitation outcomes.