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We extend the scope of European palaeogenomics by sequencing the genomes of Late Upper Palaeolithic (13,300 years old, 1.4-fold coverage) and Mesolithic (9,700 years old, 15.4-fold) males from western Georgia in the Caucasus and a Late Upper Palaeolithic (13,700 years old, 9.5-fold) male from Switzerland. While we detect Late Palaeolithic-Mesolithic genomic continuity in both regions, we find that Caucasus hunter-gatherers (CHG) belong to a distinct ancient clade that split from western hunter-gatherers similar to 45 kya, shortly after the expansion of anatomically modern humans into Europe and from the ancestors of Neolithic farmers similar to 25 kya, around the Last Glacial Maximum. CHG genomes significantly contributed to the Yamnaya steppe herders who migrated into Europe similar to 3,000 BC, supporting a formative Caucasus influence on this important Early Bronze age culture. CHG left their imprint on modern populations from the Caucasus and also central and south Asia possibly marking the arrival of Indo-Aryan languages.
Introduction
We investigated blood glucose (BG) and hormone response to aerobic high-intensity interval exercise (HIIE) and moderate continuous exercise (CON) matched for mean load and duration in type 1 diabetes mellitus (T1DM).
Material and Methods
Seven trained male subjects with T1DM performed a maximal incremental exercise test and HIIE and CON at 3 different mean intensities below (A) and above (B) the first lactate turn point and below the second lactate turn point (C) on a cycle ergometer. Subjects were adjusted to ultra-long-acting insulin Degludec (Tresiba/Novo Nordisk, Denmark). Before exercise, standardized meals were administered, and short-acting insulin dose was reduced by 25% (A), 50% (B), and 75% (C) dependent on mean exercise intensity. During exercise, BG, adrenaline, noradrenaline, dopamine, cortisol, glucagon, and insulin-like growth factor-1, blood lactate, heart rate, and gas exchange variables were measured. For 24 h after exercise, interstitial glucose was measured by continuous glucose monitoring system.
Results
BG decrease during HIIE was significantly smaller for B (p = 0.024) and tended to be smaller for A and C compared to CON. No differences were found for post-exercise interstitial glucose, acute hormone response, and carbohydrate utilization between HIIE and CON for A, B, and C. In HIIE, blood lactate for A (p = 0.006) and B (p = 0.004) and respiratory exchange ratio for A (p = 0.003) and B (p = 0.003) were significantly higher compared to CON but not for C.
Conclusion
Hypoglycemia did not occur during or after HIIE and CON when using ultra-long-acting insulin and applying our methodological approach for exercise prescription. HIIE led to a smaller BG decrease compared to CON, although both exercises modes were matched for mean load and duration, even despite markedly higher peak workloads applied in HIIE. Therefore, HIIE and CON could be safely performed in T1DM.
Continuous exercise (CON) and high-intensity interval exercise (HIIE) can be safely performed with type 1 diabetes mellitus (T1DM). Additionally, continuous glucose monitoring (CGM) systems may serve as a tool to reduce the risk of exercise-induced hypoglycemia. It is unclear if CGM is accurate during CON and HIIE at different mean workloads. Seven T1DM patients performed CON and HIIE at 5% below (L) and above (M) the first lactate turn point (LTP1), and 5% below the second lactate turn point (LTP2) (H) on a cycle ergometer. Glucose was measured via CGM and in capillary blood (BG). Differences were found in comparison of CGM vs. BG in three out of the six tests (p < 0.05). In CON, bias and levels of agreement for L, M, and H were found at: 0.85 (-3.44, 5.15) mmol.L-1, -0.45 (-3.95, 3.05) mmol.L-1, -0.31 (-8.83, 8.20) mmol.L-1 and at 1.17 (-2.06, 4.40) mmol.L-1, 0.11 (-5.79, 6.01) mmol.L-1, 1.48 (-2.60, 5.57) mmol.L-1 in HIIE for the same intensities. Clinically-acceptable results (except for CON H) were found. CGM estimated BG to be clinically acceptable, except for CON H. Additionally, using CGM may increase avoidance of exercise-induced hypoglycemia, but usual BG control should be performed during intense exercise.
How to Regulate the Acute Physiological Response to "Aerobic" High-Intensity Interval Exercise
(2015)
The acute physiological processes during "aerobic" high-intensity interval exercise (HIIE) and their regulation are inadequately studied. The main goal of this study was to investigate the acute metabolic and cardiorespiratory response to long and short HIIE compared to continuous exercise (CE) as well as its regulation and predictability. Six healthy well-trained sport students (5 males, 1 female; age: 25.7 +/- 3.1 years; height: 1.80 +/- 0.04 m; weight: 76.7 +/- 6.4 kg; VO2max: 4.33 +/- 0.7 l.min(-1)) performed a maximal incremental exercise test (IET) and subsequently three different exercise sessions matched for mean load (P-mean) and exercise duration (28 min): 1) long HIIE with submaximal peak workloads (P-peak = power output at 95 % of maximum heart rate), peak workload durations (t(peak)) of 4 min, and recovery durations (t(rec)) of 3 min, 2) short HIIE with P-peak according to the maximum power output (P-max) from IET, t(peak) of 20 s, and individually calculated t(rec) (26.7 +/- 13.4 s), and 3) CE with a target workload (P-target) equating to P-mean of HIIE. In short HIIE, mean lactate (La-mean) (5.22 +/- 1.41 mmol.l(-1)), peak La (7.14 +/- 2.48 mmol.l(-1)), and peak heart rate (HRpeak) (181.00 +/- 6.66 b.min(-1)) were significantly lower compared to long HIIE (La-mean: 9.83 +/- 2.78 mmol.l(-1); La-peak: 12.37 +/- 4.17 mmol.l(-1), HRpeak: 187.67 +/- 5.72 b.min(-1)). No significant differences in any parameters were found between short HIIE and CE despite considerably higher peak workloads in short HIIE. The acute metabolic and peak cardiorespiratory demand during "aerobic" short HIIE was significantly lower compared to long HIIE and regulable via Pmean. Consequently, short HIIE allows a consciously aimed triggering of specific and desired or required acute physiological responses.
Continuous exercise (CON) and high-intensity interval exercise (HIIE) can be safely performed with type 1 diabetes mellitus (T1DM). Additionally, continuous glucose monitoring (CGM) systems may serve as a tool to reduce the risk of exercise-induced hypoglycemia. It is unclear if CGM is accurate during CON and HIIE at different mean workloads. Seven T1DM patients performed CON and HIIE at 5% below (L) and above (M) the first lactate turn point (LTP1), and 5% below the second lactate turn point (LTP2) (H) on a cycle ergometer. Glucose was measured via CGM and in capillary blood (BG). Differences were found in comparison of CGM vs. BG in three out of the six tests (p < 0.05). In CON, bias and levels of agreement for L, M, and H were found at: 0.85 (−3.44, 5.15) mmol·L−1, −0.45 (−3.95, 3.05) mmol·L−1, −0.31 (−8.83, 8.20) mmol·L−1 and at 1.17 (−2.06, 4.40) mmol·L−1, 0.11 (−5.79, 6.01) mmol·L−1, 1.48 (−2.60, 5.57) mmol·L−1 in HIIE for the same intensities. Clinically-acceptable results (except for CON H) were found. CGM estimated BG to be clinically acceptable, except for CON H. Additionally, using CGM may increase avoidance of exercise-induced hypoglycemia, but usual BG control should be performed during intense exercise.
Species diversity promotes the delivery of multiple ecosystem functions (multifunctionality). However, the relative functional importance of rare and common species in driving the biodiversity multifunctionality relationship remains unknown. We studied the relationship between the diversity of rare and common species (according to their local abundances and across nine different trophic groups), and multifunctionality indices derived from 14 ecosystem functions on 150 grasslands across a land use intensity (LUI) gradient. The diversity of above- and below-ground rare species had opposite effects, with rare above-ground species being associated with high levels of multifunctionality, probably because their effects on different functions did not trade off against each other. Conversely, common species were only related to average, not high, levels of multifunctionality, and their functional effects declined with LUI. Apart from the community level effects of diversity, we found significant positive associations between the abundance of individual species and multifunctionality in 6% of the species tested. Species specific functional effects were best predicted by their response to LUI: species that declined in abundance with land use intensification were those associated with higher levels of multifunctionality. Our results highlight the importance of rare species for ecosystem multifunctionality and help guiding future conservation priorities.