Digital technologies are being harnessed to support the public-health response to COVID-19 worldwide, including population surveillance, case identification, contact tracing and evaluation of interventions on the basis of mobility data and communication with the public. These rapid responses leverage billions of mobile phones, large online datasets, connected devices, relatively low-cost computing resources and advances in machine learning and natural language processing. This Review aims to capture the breadth of digital innovations for the public-health response to COVID-19 worldwide and their limitations, and barriers to their implementation, including legal, ethical and privacy barriers, as well as organizational and workforce barriers. The future of public health is likely to become increasingly digital, and we review the need for the alignment of international strategies for the regulation, evaluation and use of digital technologies to strengthen pandemic management, and future preparedness for COVID-19 and other infectious diseases. Public-health need Digital tool or technology Example of use Refs. Digital epidemiological surveillance Machine learning Web-based epidemic intelligence tools and online syndromic surveillance Web-based epidemic intelligence tools: 20-23,25 Based on social media or online search data: 30-33 Survey apps and websites Symptom reporting 37,38,48,49 Data extraction and visualization Data dashboard 39-45 Rapid case identification Connected diagnostic device Point-of-care diagnosis 58 Sensors including wearables Febrile symptoms checking 51-53 Machine learning Medical image analysis 65,66

We show a similar time course for Akt-mTOR-S6K phosphorylation during the initial 60-min recovery period after divergent contractile stimuli. Conversely, enhanced phosphorylation status of proteins that promote glucose transport and glycogen synthesis only occurred after endurance exercise. Our results indicate that endurance and resistance exercise initiate translational signaling, but high-load, low-repetition contractile activity failed to promote phosphorylation of pathways regulating glucose metabolism.

We determined myofibrillar and mitochondrial protein fractional synthesis rates (FSR), intramuscular signaling protein phosphorylation, and mRNA expression responses after isolated bouts of resistance exercise (RE), aerobic exercise (AE), or in combination [termed concurrent exercise (CE)] in sedentary middle-aged men. Eight subjects (age = 53.3 ± 1.8 yr; body mass index = 29.4 ± 1.4 kg·m(2)) randomly completed 8 × 8 leg extension repetitions at 70% of one repetition-maximum, 40 min of cycling at 55% peak aerobic power output (AE), or (consecutively) 50% of the RE and AE trials (CE). Biopsies were obtained (during a primed, constant infusion of l-[ring-(13)C(6)]phenylalanine) while fasted, and at 1 and 4 h following postexercise ingestion of 20 g of protein. All trials increased mitochondrial FSR above fasted rates (RE = 1.3-fold; AE = 1.5; CE = 1.4; P < 0.05), although only CE (2.2) and RE (1.8) increased myofibrillar FSR (P < 0.05). At 1 h postexercise, phosphorylation of Akt on Ser(473) (CE = 7.7; RE = 4.6) and Thr(308) (CE = 4.4; RE = 2.9), and PRAS40 on Thr(246) (CE = 3.8; AE = 2.5) increased (P < 0.05), with CE greater than AE for Akt Ser(473)-Thr(308) and greater than RE for PRAS40 (P < 0.05). Despite increased phosphorylation of Akt-PRAS40, phosphorylation of mammalian target of rapamycin (Ser(2448)) remained unchanged (P > 0.05), while rpS6 (Ser(235/236)) increased only in RE (10.4) (P < 0.05). CE and AE both resulted in increased peroxisome proliferator receptor-γ coactivator 1-α (PGC1α) expression at 1 h (CE = 2.9; AE = 2.8; P < 0.05) and 4 h (CE = 2.6; AE = 2.4) and PGC1β expression at 4 h (CE = 2.1; AE = 2.6; P < 0.05). These data suggest that CE-induced acute stimulation of myofibrillar and mitochondrial FSR, protein signaling, and mRNA expression are equivalent to either isolate mode (RE or AE). These results occurred without an interference effect on muscle protein subfractional synthesis rates, protein signaling, or mRNA expression.

Sleep loss and associated reductions in muscle glycogen and perceptual stress reduced sprint performance and slowed pacing strategies during intermittent-sprint exercise for male team-sport athletes.

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