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Endurance exercise training studies frequently show modest changes in VO2max with training and very limited responses in some subjects. By contrast, studies using interval training (IT) or combined IT and continuous training (CT) have reported mean increases in VO2max of up to ~1.0 L · min(-1). This raises questions about the role of exercise intensity and the trainability of VO2max. To address this topic we analyzed IT and IT/CT studies published in English from 1965-2012. Inclusion criteria were: 1)≥ 3 healthy sedentary/recreationally active humans <45 yrs old, 2) training duration 6-13 weeks, 3) ≥ 3 days/week, 4) ≥ 10 minutes of high intensity work, 5) ≥ 1:1 work/rest ratio, and 6) results reported as mean ± SD or SE, ranges of change, or individual data. Due to heterogeneity (I(2) value of 70), statistical synthesis of the data used a random effects model. The summary statistic of interest was the change in VO2max. A total of 334 subjects (120 women) from 37 studies were identified. Participants were grouped into 40 distinct training groups, so the unit of analysis was 40 rather than 37. An increase in VO2max of 0.51 L · min(-1) (95% CI: 0.43 to 0.60 L · min(-1)) was observed. A subset of 9 studies, with 72 subjects, that featured longer intervals showed even larger (~0.8-0.9 L · min(-1)) changes in VO2max with evidence of a marked response in all subjects. These results suggest that ideas about trainability and VO2max should be further evaluated with standardized IT or IT/CT training programs.

Asymptomatic left ventricular dysfunction (ALVD) is present in 3–6% of the general population, is associated with reduced quality of life and longevity, and is treatable when found1–4. An inexpensive, noninvasive screening tool for ALVD in the doctor’s office is not available. We tested the hypothesis that application of artificial intelligence (AI) to the electrocardiogram (ECG), a routine method of measuring the heart’s electrical activity, could identify ALVD. Using paired 12-lead ECG and echocardiogram data, including the left ventricular ejection fraction (a measure of contractile function), from 44,959 patients at the Mayo Clinic, we trained a convolutional neural network to identify patients with ventricular dysfunction, defined as ejection fraction ≤35%, using the ECG data alone. When tested on an independent set of 52,870 patients, the network model yielded values for the area under the curve, sensitivity, specificity, and accuracy of 0.93, 86.3%, 85.7%, and 85.7%, respectively. In patients without ventricular dysfunction, those with a positive AI screen were at 4 times the risk (hazard ratio, 4.1; 95% confidence interval, 3.3 to 5.0) of developing future ventricular dysfunction compared with those with a negative screen. Application of AI to the ECG—a ubiquitous, low-cost test—permits the ECG to serve as a powerful screening tool in asymptomatic individuals to identify ALVD.

BACKGROUND. Convalescent plasma is the only antibody-based therapy currently available for patients with coronavlrus disease 2019 (COVID-19). It has robust historical precedence and sound biological plausibility. Although promising, convalescent plasma has not yet been shown to be safe as a treatment for COVID-19. METHODS. Thus, we analyzed key safety metrics after transfusion of ABO-compatible human COVID-19 convalescent plasma in 5000 hospitalized adults with severe or life-threatening COVID-19, with 66% in the intensive care unit, as part of the US FDA expanded access program for COVID-19 convalescent plasma. RESULTS. The incidence of all serious adverse events (SAEs), including mortality rate (0.3%), in the first 4 hours after transfusion was <1%. Of the 36 reported SAEs, there were 25 reported incidences of related SAEs, including mortality (n = 4), transfusion-associated circulatory overload (n = 7), transfusion-related acute lung injury (n = 11), and severe allergic transfusion reactions (n = 3). However, only 2 of 36 SAEs were judged as definitely related to the convalescent plasma transfusion by the treating physician. The 7-day mortality rate was 14.9%. CONCLUSION. Given the deadly nature of COVID-19 and the large population of critically ill patients included in these analyses, the mortality rate does not appear excessive. These early indicators suggest that transfusion of convalescent plasma is safe in hospitalized patients with COVID-19. TRIAL REGISTRATION. ClinicalTrials.gov NCT04338360. FUNDING. Mayo Clinic, Biomedical Advanced Research and Development Authority (75A50120C00096), National Center for Advancing Translational Sciences (UL1TR002377), National Heart, Lung, and Blood Institute (5R35HL139854 and R01 HL059842), National Institute of Diabetes and Digestive and Kidney Diseases (5T32DK07352), Natural Sciences and Engineering Research Council of Canada (PDF-532926-2019), National Institute of Allergy and Infectious Disease (R21 AI145356, R21 AI152318, and AI152078), Schwab Charitable Fund, United Health Group, National Basketball Association, Millennium Pharmaceuticals, and Octapharma USA Inc.

The timing and magnitude of sex differences in athletic performance during early human development, prior to adulthood, is unknown. To compare swimming velocity of boys and girls for all Olympic-length freestyle swimming events to determine the age of divergence in swimming performance. We collected the all-time top 100 U.S. freestyle swimming performance times of boys and girls age 5 to 18 years for the 50m to 1500m events. Swimming performance improved with increasing age for boys and girls (p<0.001) until reaching a plateau, which initiated at a younger age for girls (15 years) than boys (17 years; sex×age; p<0.001). Prior to age 10, the top 5 swimming records for girls were 3% faster than the top boys (p<0.001). For the 10th-50th places, however, there were no sex-related differences in swimming performance prior to age 10 (p = 0.227). For both the top 5 and 10th-50th places, the sex difference in performance increased from age 10 (top 5, 2.5%; 10th-50th places, 1.0%) until age 17 (top 5, 7.6%; 10th-50th places, 8.0%). For all places, the sex difference in performance at age 18 was larger for sprint events (9.6%; 50-200m) than endurance events (7.1%; 400-1500m; p<0.001). Additionally, the sex-related difference in performance increased across age and US ranking from 2.4% for 1st place to 4.3% for 100th place (p<0.001), indicating less depth of performance in girls than boys. However, annual participation was ~20% higher in girls than boys for all ages (p<0.001). The top 5 girls demonstrated faster swimming velocities and the 10th-50th place girls demonstrated similar swimming velocities than boys (until ~10 years). After age 10, however, boys demonstrated increasingly faster swimming velocities than girls until 17 years. Collectively, these data suggest girls are faster, or at least not slower, than boys prior to the performance-enhancing effects of puberty.

Evaluation of the existence of a diurnal pattern of glucose tolerance after mixed meals is important to inform a closed-loop system of treatment for insulin requiring diabetes. We studied 20 healthy volunteers with normal fasting glucose (4.8 ± 0.1 mmol/L) and HbA(1c) (5.2 ± 0.0%) to determine such a pattern in nondiabetic individuals. Identical mixed meals were ingested during breakfast, lunch, or dinner at 0700, 1300, and 1900 h in randomized Latin square order on 3 consecutive days. Physical activity was the same on all days. Postprandial glucose turnover was measured using the triple tracer technique. Postprandial glucose excursion was significantly lower (P < 0.01) at breakfast than lunch and dinner. β-Cell responsivity to glucose and disposition index was higher (P < 0.01) at breakfast than lunch and dinner. Hepatic insulin extraction was lower (P < 0.01) at breakfast than dinner. Although meal glucose appearance did not differ between meals, suppression of endogenous glucose production tended to be lower (P < 0.01) and insulin sensitivity tended to be higher (P < 0.01) at breakfast than at lunch or dinner. Our results suggest a diurnal pattern to glucose tolerance in healthy humans, and if present in type 1 diabetes, it will need to be incorporated into artificial pancreas systems.

Although artificial intelligence (AI) algorithms have been shown to be capable of identifying cardiac dysfunction, defined as ejection fraction (EF) ≤ 40%, from 12-lead electrocardiograms (ECGs), identification of cardiac dysfunction using the single-lead ECG of a smartwatch has yet to be tested. In the present study, a prospective study in which patients of Mayo Clinic were invited by email to download a Mayo Clinic iPhone application that sends watch ECGs to a secure data platform, we examined patient engagement with the study app and the diagnostic utility of the ECGs. We digitally enrolled 2,454 unique patients (mean age 53 ± 15 years, 56% female) from 46 US states and 11 countries, who sent 125,610 ECGs to the data platform between August 2021 and February 2022; 421 participants had at least one watch-classified sinus rhythm ECG within 30 d of an echocardiogram, of whom 16 (3.8%) had an EF ≤ 40%. The AI algorithm detected patients with low EF with an area under the curve of 0.885 (95% confidence interval 0.823–0.946) and 0.881 (0.815–0.947), using the mean prediction within a 30-d window or the closest ECG relative to the echocardiogram that determined the EF, respectively. These findings indicate that consumer watch ECGs, acquired in nonclinical environments, can be used to identify patients with cardiac dysfunction, a potentially life-threatening and often asymptomatic condition. In this proof-of-concept prospective study, single-lead electrocardiograms obtained by smartwatches were able to identify individuals with left ventricular dysfunction, potentially serving as an early warning system for heart failure.

Selective vulnerability of different brain regions is seen in many neurodegenerative disorders. The hippocampus and cortex are selectively vulnerable in Alzheimer’s disease (AD), however the degree of involvement of the different brain regions differs among patients. We classified corticolimbic patterns of neurofibrillary tangles in postmortem tissue to capture extreme and representative phenotypes. We combined bulk RNA sequencing with digital pathology to examine hippocampal vulnerability in AD. We identified hippocampal gene expression changes associated with hippocampal vulnerability and used machine learning to identify genes that were associated with AD neuropathology, including SERPINA5 , RYBP , SLC38A2 , FEM1B , and PYDC1 . Further histologic and biochemical analyses suggested SERPINA5 expression is associated with tau expression in the brain. Our study highlights the importance of embracing heterogeneity of the human brain in disease to identify disease-relevant gene expression. Alzheimer’s disease (AD) is typically associated with hippocampal and cortical pathology, although hippocampal sparing and limbic predominant forms exist. The authors use transcriptomic analysis and neuropathology to identify genes associated with selective hippocampal vulnerability in AD.

The US Food and Drug Administration authorized COVID-19 convalescent plasma (CCP) therapy for hospitalized COVID-19 patients via the Expanded Access Program (EAP) and the Emergency Use Authorization (EUA), leading to use in about 500,000 patients during the first year of the pandemic for the USA. We tracked the number of CCP units dispensed to hospitals by blood banking organizations and correlated that usage with hospital admission and mortality data. CCP usage per admission peaked in Fall 2020, with more than 40% of inpatients estimated to have received CCP between late September and early November 2020. However, after randomized controlled trials failed to show a reduction in mortality, CCP usage per admission declined steadily to a nadir of less than 10% in March 2021. We found a strong inverse correlation (r = -0.52, p=0.002) between CCP usage per hospital admission and deaths occurring 2 weeks after admission, and this finding was robust to examination of deaths taking place 1, 2, or 3 weeks after admission. Changes in the number of hospital admissions, SARS-CoV-2 variants, and age of patients could not explain these findings. The retreat from CCP usage might have resulted in as many as 29,000 excess deaths from mid-November 2020 to February 2021. A strong inverse correlation between CCP use and mortality per admission in the USA provides population-level evidence consistent with the notion that CCP reduces mortality in COVID-19 and suggests that the recent decline in usage could have resulted in excess deaths. There was no specific funding for this study. AC was supported in part by RO1 HL059842 and R01 AI1520789; MJJ was supported in part by 5R35HL139854. This project has been funded in whole or in part with Federal funds from the Department of Health and Human Services; Office of the Assistant Secretary for Preparedness and Response; Biomedical Advanced Research and Development Authority under Contract No. 75A50120C00096.

Successful therapeutics and vaccines for coronavirus disease 2019 (COVID-19) have harnessed the immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Evidence that SARS-CoV-2 exists as locally evolving variants suggests that immunological differences may impact the effectiveness of antibody-based treatments such as convalescent plasma and vaccines. Considering that near-sourced convalescent plasma likely reflects the antigenic composition of local viral strains, we hypothesize that convalescent plasma has a higher efficacy, as defined by death within 30 days of transfusion, when the convalescent plasma donor and treated patient were in close geographic proximity. Results of a series of modeling techniques applied to approximately 28,000 patients from the Expanded Access to Convalescent Plasma program (ClinicalTrials.gov number: NCT04338360) support this hypothesis. This work has implications for the interpretation of clinical studies, the ability to develop effective COVID-19 treatments, and, potentially, for the effectiveness of COVID-19 vaccines as additional locally-evolving variants continue to emerge. Regional differences in SARS-CoV-2 variants may affect treatment outcome. Here, the authors show that near-sourced convalescent plasma has higher efficacy, as defined by death within 30 days of transfusion, than plasma sourced more than 150 miles away.