Introduction: Improved myocardial contractility is a critical circulatory adaptation to exercise training. However, the types of exercise that enhance left ventricular (LV) contractile and diastolic functions have not yet been established. This study investigated how high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) influence LV mechanics during exercise. Methods: Fifty-four healthy sedentary men were randomized to engage in either HIIT (3-min intervals at 40% and 80% of V˙O_2max, n = 18) or MICT (sustained 60% of V˙O_2max, n = 18) for 30 min·d⁻¹, 5 d·wk⁻¹ for 6 wk or to a control group (n = 18) that did not engage in exercise intervention. LV mechanics during semiupright bicycle exercise tests were measured by two-dimensional speckle-tracking echocardiography. Results: Before the interventions, acute bicycle exercise increased (i) peak basal/apical radial and circumferential and peak longitudinal strains and strain rates, (ii) peak basal/apical rotations and torsion, and (iii) peak systolic twisting and early diastolic untwisting velocities in the LV. After the interventions, the HIIT group exhibited greater LV mass and diastolic internal diameter as well as higher ratio of E wave to A wave and early diastolic propagation velocity than did the MICT group. Despite decreased peak apical rotation and torsion, HIIT enhanced peak apical radial strain and strain rate as well as shortened the time to reach peak untwisting velocity in the LV during exercise. However, the LV mechanics during exercise were unchanged in the control group. Conclusion: HIIT but not MICT induces eccentric myocardial hypertrophy. Moreover, HIIT effectively improves the LV mechanics during exercise by increasing contractile and diastolic functions.

The antioxidant capacity of erythrocytes protects individuals against the harmful effects of oxidative stress. Despite improved hemodynamic efficiency, the effect of eccentric cycling training (ECT) on erythrocyte antioxidative capacity remains unclear. This study investigates how ECT affects erythrocyte antioxidative capacity and metabolism in sedentary males. Thirty-six sedentary healthy males were randomly assigned to either concentric cycling training (CCT, n = 12) or ECT (n = 12) at 60% of the maximal workload for 30 min/day, 5 days/week for 6 weeks or to a control group (n = 12) that did not receive an exercise intervention. A graded exercise test (GXT) was performed before and after the intervention. Erythrocyte metabolic characteristics and O₂ release capacity were determined by UPLC-MS and high-resolution respirometry, respectively. An acute GXT depleted Glutathione (GSH), accumulated Glutathione disulfide (GSSG), and elevated the GSSG/GSH ratio, whereas both CCT and ECT attenuated the extent of the elevated GSSG/GSH ratio caused by a GXT. Moreover, the two exercise regimens upregulated glycolysis and increased glucose consumption and lactate production, leading to intracellular acidosis and facilitation of O₂ release from erythrocytes. Both CCT and ECT enhance antioxidative capacity against severe exercise-evoked circulatory oxidative stress. Moreover, the two exercise regimens activate erythrocyte glycolysis, resulting in lowered intracellular pH and enhanced O₂ released from erythrocytes.

Introduction: Physical exercise or hypoxic exposure influences erythrocyte susceptibility to osmotic stress, and the aquaporin 1 (AQP1) facilitates the transport of water in erythrocytes. This study investigated whether high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) affect erythrocyte osmotic deformability by modulating AQP1 function under hypoxic stress. Methods: Forty-five healthy sedentary males were randomized to engage in either HIIT (3-min intervals at 40% and 80% V˙O₂ reserve, n = 15) or MICT (sustained 60% V˙O₂ reserve, n = 15) on a bicycle ergometer for 30 min·d⁻¹, 5 d·wk⁻¹ for 6 wk, or to a control group that did not perform any exercise (n = 15). All subjects were analyzed with osmotic gradient ektacytometry for assessing erythrocyte membrane stability and osmotic deformability after hypoxic exercise (HE) (100 W under 12%O₂ for 30 min). Results: Before the intervention, HE increased the shear stress at 50% of maximal elongation (SS_1/2) and the ratio of SS_1/2 to maximal elongation index (SS_1/2/EI_max) on erythrocytes pretreated with 50 Pa of shear stress for 30 min and diminished HgCl₂-depressed osmolality at 50%EI_max (O_hyper). However, both HIIT and MICT for 6 wk diminished the elevations of erythrocyte SS_1/2 and SS_1/2/EI_max caused by HE. Moreover, HIIT also increased contents of erythrocyte AQP1 proteins while enhancing HgCl₂-depressed O_hyper and area under elongation index–osmolarity curve after HE. Additionally, changes in erythrocyte AQP1 contents were associated with changes in HgCl₂-depressed erythrocyte O_hyper and area under elongation index–osmolarity curve. Conclusions: Acute HE reduces erythrocyte membrane stability, whereas either HIIT or MICT attenuates the depression of erythrocyte membrane stability by HE. Moreover, HIIT increases the AQP1 content and facilitates the HgCl₂-mediated osmotic deformability of erythrocytes after HE.

Physical exercise or hypoxic exposure influences hemorheology and acid-base homeostasis. Band 3 protein in erythrocytes modulates cells' rheological properties and anion transport ability. This study investigated how cycling aerobic interval training (AIT) and moderate continuous training (MCT) affect the rheological function and band 3 activity of erythrocytes under hypoxic exercise (HE) stress. Forty-five healthy sedentary men were randomized to engage in either AIT (3-min intervals at 40% and 80% of VO2max, n = 15) or MCT (sustained 60% of VO2max, n = 15) on a bicycle ergometer for 30 min · d(-1) (5 d · wk(-1) for 5 wk) or to a control group that did not perform any exercise (n = 15). Erythrocyte rheological responses to HE (100 W under 12% O2 for 30 min) were determined before and after various regimens. Acute HE increased the aggregation and osmotic fragility of erythrocytes, decreased the deformability of erythrocytes, and depressed erythrocyte band 3 activity, as indicated by lowered anion transport ability. Following 5 wk of intervention, the AIT group exhibited maximal work rate and VO2max higher than those in the MCT and control groups. Moreover, cycling AIT and MCT diminished the extent of erythrocytes' enhanced aggregation and osmotic fragility and reduced their deformability and band 3 activity caused by HE. Additionally, erythrocyte band 3 activity was directly related to erythrocyte deformability and inversely related to erythrocyte aggregation and osmotic fragility. Cycling AIT is superior to cycling MCT in enhancing aerobic capacity. Moreover, either cycling AIT or MCT effectively alleviates HE-evoked impairments of erythrocyte rheological characteristics and band 3 function.

Pathological erythrocyte aggregation reduces capillary perfusion and oxygen transfer to tissue, which is determined by the negative surface charge on the erythrocyte membrane (intrinsic aggregability) and fibrinogen–erythrocyte interaction (extrinsic factor). Exercise-induced oxidative stress is important for rheological adaptation to training but may also cause erythrocyte senescence. This study clarifies the effects of hypoxic exercise training on intrinsic/extrinsic factors of aggregation. In total, 60 healthy sedentary males were randomly assigned to either hypoxic (HE; F_IO₂ = 0.15) or normoxic exercise training (NE; F_IO₂ = 0.21) groups for 30 min·d⁻¹, 5 d·wk⁻¹ for 6 weeks at 60 % of the maximum work rate or to a control group (CTL). A hypoxia exercise test (HET, F_IO₂ = 0.12) was performed before and after the intervention. Erythrocyte aggregation was assessed by ektacytometry, and fibrinogen binding affinity and senescence biomarkers were assessed by flow cytometry. An acute 12% oxygen HET significantly enhanced erythrocyte global aggregation through intrinsic aggregability. Resting aggregation is promoted by both intrinsic aggregability and fibrinogen binding probability and force after HE, whereas NE is mainly associated with ameliorated fibrinogen–erythrocyte interactions. The HET still facilitated global aggregation after HE because of the augmented fibrinogen-related factors, even though the intrinsic factor was suppressed. Additionally, HE further increased reticulocyte counts while reducing the expression of CD47 and CD147. Resting aggregability is promoted by both intrinsic and extrinsic factors after HE, whereas NE is mainly associated with an ameliorated affinity for fibrinogen. Although an accelerated turnover rate was observed, HE further led to erythrocyte senescence.

Background: Low peak oxygen consumption (V̇O ₂ ) is associated with higher cardiovascular and all-cause mortality, while improvements in peak V̇O ₂ reduce this risk. Although early detection allows timely intervention, practical screening tools remain lacking. As electrocardiograms (ECGs) reflect both cardiac and age-related changes, they may offer a viable screening approach. Objective: This study aimed to detect low peak V̇O ₂ using resting 12-lead ECGs analyzed by a trained neural network. Methods: The low peak V̇O ₂ estimation model was developed using data from 965 individuals (n=540, 56% with cardiac or pulmonary disorders) mainly at Chang Gung Memorial Hospital, Linkou, and validated in an independent cohort of 242 individuals (n=194, 80% with cardiac disorders) at the Keelung branch. Resting ECGs were recorded immediately before cardiopulmonary exercise testing. Low peak V̇O ₂ was defined as a peak V̇O ₂ of <14 mL/kg/min. Results: The mean peak V̇O ₂ was 17.5 (SD 6.1) and 15.4 (SD 3.9) mL/kg/min in the training and validation datasets, with 27% (261/965) and 38% (92/242) classified as low peak V̇O ₂ , respectively. Wavelet analysis improved model accuracy, underscoring its value for feature extraction. Three input models were compared: (1) individual characteristics (IC; age, sex, BMI, resting heart rate, and heart rate variability), (2) ECG alone, and (3) ECG plus IC. ECG alone outperformed IC, and combining both yielded the highest accuracy. For low peak V̇O ₂ prediction, ECG plus IC achieved mean area under the curve, precision, and recall values of 0.89, 0.72, and 0.72 in cross-validation, and 0.87, 0.67, and 0.61 in external validation. Conclusions: An artificial intelligence–driven ECG-based algorithm showed strong potential for screening low peak V̇O ₂ , enabling early identification of individuals with low peak V̇O ₂ and facilitating timely clinical intervention.