Effects of Exercise Training on Muscle Quality in Older Individuals: A Systematic Scoping Review with Meta-Analyses

Exploring determinant factors influencing muscle quality and sarcopenia in Bilbao's older adult population through machine learning: A comprehensive analysis approach

BACKGROUND

Sarcopenia and reduced muscle quality index have garnered special attention due to their prevalence among older individuals and the adverse effects they generate. Early detection of these geriatric pathologies holds significant potential, enabling the implementation of interventions that may slow or reverse their progression, thereby improving the individual's overall health and quality of life. In this context, artificial intelligence opens up new opportunities to identify the key identifying factors of these pathologies, thus facilitating earlier intervention and personalized treatment approaches.

OBJECTIVES

investigate anthropomorphic, functional, and socioeconomic factors associated with muscle quality and sarcopenia using machine learning approaches and identify key determinant factors for their potential future integration into clinical practice.

METHODS

A total of 1253 older adults (89.5% women) with a mean age of 78.13 ± 5.78 voluntarily participated in this descriptive cross-sectional study, which examines determining factors in sarcopenia and MQI using machine learning techniques. Feature selection was completed using a variety of techniques and feature datasets were constructed according to feature selection. Three machine learning classification algorithms classified sarcopenia and MQI in each dataset, and the performance of classification models was compared.

RESULTS

The predictive models used in this study exhibited AUC scores of 0.7671 for MQI and 0.7649 for sarcopenia, with the most successful algorithms being SVM and MLP. Key factors in predicting both conditions have been shown to be relative power, age, weight, and the 5STS. No single factor is sufficient to predict either condition, and by comprehensively considering all selected features, the study underscores the importance of a holistic approach in understanding and addressing sarcopenia and MQI among older adults.

CONCLUSIONS

Exploring the factors that affect sarcopenia and MQI in older adults, this study highlights that relative power, age, weight, and the 5STS are significant determinants. While considering these clinical markers and using a holistic approach, this can provide crucial information for designing personalized and effective interventions to promote healthy aging.

Non invasive techniques for direct muscle quality assessment after exercise intervention in older adults: a systematic review

BACKGROUND

The aging process induces neural and morphological changes in the human musculoskeletal system, leading to a decline in muscle mass, strength and quality. These alterations, coupled with shifts in muscle metabolism, underscore the essential role of physical exercise in maintaining and improving muscle quality in older adults. Muscle quality's morphological domain encompasses direct assessments of muscle microscopic and macroscopic aspects of muscle architecture and composition. Various tools exist to estimate muscle quality, each with specific technical requirements. However, due to the heterogeneity in both the studied population and study methodologies, there is a gap in the establishment of reference standards to determine which are the non-invasive and direct tools to assess muscle quality after exercise interventions. Therefore, the purpose of this review is to obtain an overview of the non-invasive tools used to measure muscle quality directly after exercise interventions in healthy older adults, as well as to assess the effects of exercise on muscle quality.

MAIN TEXT

To address the imperative of understanding and optimizing muscle quality in aging individuals, this review provides an overview of non-invasive tools employed to measure muscle quality directly after exercise interventions in healthy older adults, along with an assessment of the effects of exercise on muscle quality.

RESULTS

Thirty four studies were included. Several methods of direct muscle quality assessment were identified. Notably, 2 studies harnessed CT, 20 utilized US, 9 employed MRI, 2 opted for TMG, 2 adopted myotonometry, and 1 incorporated BIA, with several studies employing multiple tests. Exploring interventions, 26 studies focus on resistance exercise, 4 on aerobic training, and 5 on concurrent training.

CONCLUSIONS

There is significant diversity in the methods of direct assessment of muscle quality, mainly using ultrasound and magnetic resonance imaging; and a consistent positive trend in exercise interventions, indicating their efficacy in improving or preserving muscle quality. However, the lack of standardized assessment criteria poses a challenge given the diversity within the studied population and variations in methodologies.. These data emphasize the need to standardize assessment criteria and underscore the potential benefits of exercise interventions aimed at optimizing muscle quality.

Convolutional Neural Network-Based Automated Segmentation of Skeletal Muscle and Subcutaneous Adipose Tissue on Thigh MRI in Muscular Dystrophy Patients

We aim to develop a deep learning-based algorithm for automated segmentation of thigh muscles and subcutaneous adipose tissue (SAT) from T1-weighted muscle MRIs from patients affected by muscular dystrophies (MDs). From March 2019 to February 2022, adult and pediatric patients affected by MDs were enrolled from Azienda Ospedaliera Universitaria Pisana, Pisa, Italy (Institution 1) and the IRCCS Stella Maris Foundation, Calambrone-Pisa, Italy (Institution 2), respectively. All patients underwent a bilateral thighs MRI including an axial T1 weighted in- and out-of-phase (dual-echo). Both muscles and SAT were manually and separately segmented on out-of-phase image sets by a radiologist with 6 years of experience in musculoskeletal imaging. A U-Net1 and U-Net3 were built to automatically segment the SAT, all the thigh muscles together and the three muscular compartments separately. The dataset was randomly split into the on train, validation, and test set. The segmentation performance was assessed through the Dice similarity coefficient (DSC). The final cohort included 23 patients. The estimated DSC for U-Net1 was 96.8%, 95.3%, and 95.6% on train, validation, and test set, respectively, while the estimated accuracy for U-Net3 was 94.1%, 92.9%, and 93.9%. Both of the U-Nets achieved a median DSC of 0.95 for SAT segmentation. The U-Net1 and the U-Net3 achieved an optimal agreement with manual segmentation for the automatic segmentation. The so-developed neural networks have the potential to automatically segment thigh muscles and SAT in patients affected by MDs.

Research Progress on Cognitive Frailty in Older Adults with Chronic Kidney Disease

BACKGROUND

As the medical challenges posed by the ageing population become increasingly severe, the proportion of older people among patients with chronic kidney disease (CKD) is increasing every year.

SUMMARY

The prevalence of frailty in patients with CKD is significantly higher than that in the general population, and older patients are also a high-risk group for frailty and cognitive impairment. Cognitive frailty, as an important subtype of frailty, is a syndrome characterised by cognitive dysfunction caused by physiological factors, excluding Alzheimer's disease and other types of dementia. It is characterised by the coexistence of physical frailty and cognitive impairment. Previous studies have mainly focused on cognitive impairment, and there is limited research on cognitive frailty, particularly in older patients with CKD.

KEY MESSAGES

This article provides a comprehensive review of the concept, epidemiology, screening methods, prevention, and treatment measures and possible pathogenesis of cognitive frailty in patients with CKD.

Physical training attenuates systemic cytokine response and tissue damage triggered by apical periodontitis

Apical periodontitis (AP) is a condition characterized by inflammatory and infectious components in the tooth canal. AP affects periradicular tissues and has systemic repercussions. Physical exercise is a structured activity that requires cardiorespiratory function, and can modulate the inflammatory profile in pathological conditions. As a result, this study aimed to determine the effects of aerobic physical training (PT) on the alveolar bone with and without AP, and its systemic inflammatory repercussions. AP was induced in the mandibular first molars, and PT was performed on a treadmill for five consecutive days over four weeks, with progressive increases in speed and activity time. Blood samples were collected to determine serum cytokine levels using immunoassays, and alveolar bone samples were collected for histopathological evaluation, lesion volume and microarchitecture assessment using computed microtomography. Animals with AP had increased pro-inflammatory cytokines levels compared to those without AP; however, these levels were attenuated or restored by PT. Compared to the AP group, the AP + PT group had a smaller lesion volume and greater preservation of the bone trabeculae in the remaining alveolar bone surrounding the lesion. In overall, PT minimized the severity of AP proving to be a valid strategy for individuals undergoing endodontic treatment.