Sarcopenia and frailty are age-related syndromes with negative effects on the quality of life of older people and on public health costs. Although extensive research has been carried out on the effects of physical exercise and physical syndromes, there is a knowledge gap when it comes to the effect of resistance training on muscular strength, physical performance, and body composition at early (prevention) and late (treatment) stages in both syndromes combined. We conducted this systematic review and meta-analysis (CRD42019138253) to gather the evidence of randomized controlled trials examining the effects of resistance training programs lasting ≥8 weeks on strength, physical function, and body composition of adults ≥65 years old diagnosed with pre-sarcopenia, sarcopenia, pre-frailty, or frailty. A search from the earliest record up to and including December 2020 was carried out using the PubMed, Scopus, Web of Science, and Cochrane Library databases. A total of 25 studies (n = 2267 participants) were included. Meta-analysis showed significant changes in favour of resistance training for handgrip (ES = 0.51, p = 0.001) and lower-limb strength (ES = 0.93, p < 0.001), agility (ES = 0.78, p = 0.003), gait speed (ES = 0.75, p < 0.001), postural stability (ES = 0.68, p = 0.007), functional performance (ES = 0.76, p < 0.001), fat mass (ES = 0.41, p = 0.001), and muscle mass (ES = 0.29, p = 0.002). Resistance training during early stages had positive effects in all variables during early stages (ES > 0.12), being particularly effective in improving gait speed (ES = 0.63, p = 0.016) and functional strength (ES = 0.53, p = 0.011). Based on these results, resistance training should be considered as a highly effective preventive strategy to delay and attenuate the negative effects of sarcopenia and frailty in both early and late stages.

When does the mind begin? Infant psychology is mysterious in part because we cannot remember our first months of life, nor can we directly communicate with infants. Even more speculative is the possibility of mental life prior to birth. The question of when consciousness, or subjective experience, begins in human development thus remains incompletely answered, though boundaries can be set using current knowledge from developmental neurobiology and recent investigations of the perinatal brain. Here, we offer our perspective on how the development of a sensory perturbation complexity index (sPCI) based on auditory (“beep-and-zip”), visual (“flash-and-zip”), or even olfactory (“sniff-and-zip”) cortical perturbations in place of electromagnetic perturbations (“zap-and-zip”) might be used to address this question. First, we discuss recent studies of perinatal cognition and consciousness using techniques such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and, in particular, magnetoencephalography (MEG). While newborn infants are the archetypal subjects for studying early human development, researchers may also benefit from fetal studies, as the womb is, in many respects, a more controlled environment than the cradle. The earliest possible timepoint when subjective experience might begin is likely the establishment of thalamocortical connectivity at 26 weeks gestation, as the thalamocortical system is necessary for consciousness according to most theoretical frameworks. To infer at what age and in which behavioral states consciousness might emerge following the initiation of thalamocortical pathways, we advocate for the development of the sPCI and similar techniques, based on EEG, MEG, and fMRI, to estimate the perinatal brain’s state of consciousness.

Background: Resistance training (RT) is considered as an effective method to increase muscle strength and physical performance in elderly people. Methods: A search from the earliest record up to and including June 2019 was carried out using the following electronic databases: PubMed, Scopus and Web of Science. The search strategy employed combined the terms related to the population (e.g. ‘sarcopenia’, ‘frailty’) with terms for the intervention (e.g. ‘resistance training’, ‘strength training’). Results: 11 studies including 2691 subjects were included in our meta-analysis (aged 64-98). Training duration ranged from 8 to 48 weeks and intensity up to 80% of 1-RM. According to the meta-analyses, RT had statistically significant effect on all the measures except handgrip strength. In handgrip strength Effect size (ES) was 0.58 (95 % CI: - 0.10 to 1.26) p = 0.076 with the moderate heterogeneity (I 2 = 58.6%). ES in legs strength was 0.52 (95 % CI 0.11 to 0.92) p = 0.022, I 2 = 42.0 %. The biggest ES was in TUG test where ES was 0.90 (95 % CI 0.19 to 1.60) p = 0.022, however, there was a high heterogeneity I 2 = 89.6. The high ES was found also in FFM 0.69 (95 % CI 0.17 to 1.20) p = 0.025, and gait speed 0.41 (95 % CI 0.11 to 0.72) p = 0.017. In both cases, there was small heterogeneity I 2 = 13.2 % respective 38.3 %. The overall ES was estimated 0.67 (95 % CI 0.40 to 0.93) p <0.001. Nevertheless, the heterogeneity was high I 2 = 78.1 %.Conclusion: RT interventions in pre-frail, frail, pre-sarcopenic and sarcopenic older adults, provided evidence that RT has positive effects on most of the outcome measurements included in the current revision except handgrip strength.

Motivation, a complex construct that influences behavior, plays a critical role in an athlete’s success and has been extensively researched in sports sciences. However, motivation is still primarily assessed through self-reportmotivational questionnaires, resulting in a lack of objective, continuous measurements during athletic performance. Biosignals, increasingly used to assess psychological processes, have gained relevance due to their integration into wearable sensors, allowing non-stationary and unobtrusive data collection. Therefore, we assessed performance data, cardiovascular signals, andeye-tracking metrics to investigate the psychological and physiological processes under two different conditions designed to induce different motivational states via gamification. In this study, gamification elements, aligned with self-determination theory, were used to influence soccer players’ motivation in an immersive space, with N = 42 participants completing a passing drill in both Gamified and Non-Gamified scenarios. Features were extracted from session recordings and wearable sensors to assess whether performance or biosignals differed between conditions using a combination of machine learning and conventional statistical analysis. While self-report questionnaires and performancemetrics revealed no significant differences, the machine learning classifiers were able to distinguish between scenarios based on eye-tracking-related features. The best-performing model, a k-nearest neighbor classifier, reached a macro F1-score of 82.75 %. We identified by feature importance methods that blink behavior and pupil dynamics, indicative of visual attention, were the main contributors. This study contributes to a deeper understanding of the value of integrating multimodal data and advanced evaluation methods to uncover implicit processes in applied sports contexts involving complex and heterogeneous data.