Intense exercise is associated with a reduction in cerebral blood flow (CBF), but regulation of CBF during strenuous exercise in the heat with dehydration is unclear. We assessed internal (ICA) and common carotid artery (CCA) haemodynamics (indicative of CBF and extra-cranial blood flow), middle cerebral artery velocity (MCA Vmean), arterial–venous differences and blood temperature in 10 trained males during incremental cycling to exhaustion in the heat (35°C) in control, dehydrated and rehydrated states. Dehydration reduced body mass (75.8 ± 3 vs. 78.2 ± 3 kg), increased internal temperature (38.3 ± 0.1 vs. 36.8 ± 0.1°C), impaired exercise capacity (269 ± 11 vs. 336 ± 14 W), and lowered ICA and MCA Vmean by 12–23% without compromising CCA blood flow. During euhydrated incremental exercise on a separate day, however, exercise capacity and ICA, MCA Vmean and CCA dynamics were preserved. The fast decline in cerebral perfusion with dehydration was accompanied by increased O2 extraction (P < 0.05), resulting in a maintained cerebral metabolic rate for oxygen (CMRO2). In all conditions, reductions in ICA and MCA Vmean were associated with declining cerebral vascular conductance, increasing jugular venous noradrenaline, and falling arterial carbon dioxide tension () (R2 ≥ 0.41, P ≤ 0.01) whereas CCA flow and conductance were related to elevated blood temperature. In conclusion, dehydration accelerated the decline in CBF by decreasing and enhancing vasoconstrictor activity. However, the circulatory strain on the human brain during maximal exercise does not compromise CMRO2 because of compensatory increases in O2 extraction.

Purpose of reviewContinuous wave near infrared spectroscopy (CW NIRS) provides non-invasive technology to measure relative changes in oxy- and deoxy-haemoglobin in a dynamic environment. This allows determination of local skeletal muscle O2 saturation, muscle oxygen consumption (trueV˙O2) and blood flow. This article provides a brief overview of the use of CW NIRS to measure exercise-limiting factors in skeletal muscle.Recent findingsNIRS parameters that measure O2 delivery and capacity to utilise O2 in the muscle have been developed based on response to physiological interventions and exercise. NIRS has good reproducibility and agreement with gold standard techniques and can be used in clinical populations where muscle oxidative capacity or oxygen delivery (or both) are impaired. CW NIRS has limitations including: the unknown contribution of myoglobin to the overall signals, the impact of adipose tissue thickness, skin perfusion during exercise, and variations in skin pigmentation. These, in the main, can be circumvented through appropriate study design or measurement of absolute tissue saturation.SummaryCW NIRS can assess skeletal muscle O2 delivery and utilisation without the use of expensive or invasive procedures and is useable in large population-based samples, including older adults.

Risk stratification is critical for the early identification of high-risk individuals and disease prevention. Here we explored the potential of nuclear magnetic resonance (NMR) spectroscopy-derived metabolomic profiles to inform on multidisease risk beyond conventional clinical predictors for the onset of 24 common conditions, including metabolic, vascular, respiratory, musculoskeletal and neurological diseases and cancers. Specifically, we trained a neural network to learn disease-specific metabolomic states from 168 circulating metabolic markers measured in 117,981 participants with ~1.4 million person-years of follow-up from the UK Biobank and validated the model in four independent cohorts. We found metabolomic states to be associated with incident event rates in all the investigated conditions, except breast cancer. For 10-year outcome prediction for 15 endpoints, with and without established metabolic contribution, a combination of age and sex and the metabolomic state equaled or outperformed established predictors. Moreover, metabolomic state added predictive information over comprehensive clinical variables for eight common diseases, including type 2 diabetes, dementia and heart failure. Decision curve analyses showed that predictive improvements translated into clinical utility for a wide range of potential decision thresholds. Taken together, our study demonstrates both the potential and limitations of NMR-derived metabolomic profiles as a multidisease assay to inform on the risk of many common diseases simultaneously.

The use of an ACE inhibitor and a statin did not change the albumin-to-creatinine ratio over time. (Funded by the Juvenile Diabetes Research Foundation and others; AdDIT ClinicalTrials.gov number, NCT01581476 .).