Shifting the Energy Toward Los Angeles: Comparing the Energetic Contribution and Pacing Approach Between 2000- and 1500-m Maximal Ergometer Rowing.

PURPOSE: To compare the energetic contribution and pacing in 2000- and 1500-m maximal rowing-ergometer performances. METHODS: On separate visits (>48 h apart, random order), 18 trained junior (16.7 [0.4] y) male rowers completed 3 trials: a 7 × 4-minute graded exercise test, a 2000-m time trial (TT2000), and a 1500-m TT (TT1500). Respiratory gases were continuously measured throughout each trial. The submaximal power-to-oxygen-consumption relationship from the graded exercise test was used to determine the accumulated oxygen deficit for each TT. Differences in mean power output (MPO), relative anaerobic contribution, percentage of peak oxygen uptake, pacing index, maximum heart rate, rating of perceived exertion, and blood lactate concentration were assessed using linear mixed modeling. RESULTS: Compared to TT2000 (324 [24] W), MPO was 5.2% (3.3%) higher in TT1500 (341 [29 W]; P < .001, ηp2=.70). There was a 4.9% (3.3%) increase (P < .001, ηp2=.71) in anaerobic contribution from 17.3% (3.3%) (TT2000) to 22.2% (4.3%) (TT1500). Compared to TT1500, maximum heart rate, rating of perceived exertion, and blood lactate concentration were all greater (P < .05) in TT2000. The pacing index was not different between trials. Percentage increase in MPO from TT2000 to TT1500 was negatively associated with pacing variance in TT1500 (R2 = .269, P = .027). CONCLUSIONS: Maximal ergometer performance over 1500 m requires a significantly greater anaerobic contribution compared with 2000 m. Junior male athletes adopt a consistent pacing strategy across both distances. However, those who experienced greater percentage increases in MPO over the shorter test adopted a more even pacing strategy. To prepare for 1500-m performance, greater emphasis should be placed on developing capacity for work in the severe domain and completing race simulations with a more even pacing strategy.

Demarcation of Intensity From 3 to 5 Zones Aids in Understanding Physiological Performance Progression in Highly Trained Under-23 Rowing Athletes.

ABSTRACT: Watts, SP, Binnie, MJ, Goods, PSR, Hewlett, J, Fahey-Gilmour, J, and Peeling, P. Demarcation of intensity from 3 to 5 zones aids in understanding physiological performance progression in highly trained under-23 rowing athletes. J Strength Cond Res 37(11): e593-e600, 2023-The purpose of this investigation was to compare 2 training intensity distribution models (3 and 5 zone) in 15 highly trained rowing athletes ( n = 8 male; n = 7 female; 19.4 ± 1.1 years) to determine the impact on primary (2,000-m single-scull race) and secondary (2,000-m ergometer time trial, peak oxygen consumption [V̇O 2 peak], lactate threshold 2 [LT2 power]) performance variables. Performance was assessed before and after 4 months training, which was monitored through a smart watch (Garmin Ltd, Olathe, KS) and chest-strap heart rate (HR) monitor (Wahoo Fitness, Atlanta, GA). Two training intensity distribution models were quantified and compared: a 3-zone model (Z1: between 50% V̇O 2 peak and lactate threshold 1 (LT1); Z2: between LT1 and 95% LT2; Z3: >95% LT2) and a 5-zone model (T1-T5), where Z1 and Z3 were split into 2 additional zones. There was significant improvement in LT2 power for both male (4.08% ± 1.83, p < 0.01) and female (3.52% ± 3.38, p = 0.02) athletes, with male athletes also demonstrating significant improvement in 2,000-m ergometer time trial (2.3% ± 1.92, p = 0.01). Changes in V̇O 2 peak significantly correlated with high-quality aerobic training (percent time in T2 zone; r = 0.602, p = 0.02), whereas changes in LT2 power significantly correlated with "threshold" training (percent time in T4 zone; r = 0.529, p = 0.04). These correlations were not evident when examining intensity distribution through the 3-zone model. Accordingly, a 5-zone intensity model may aid in understanding the progression of secondary performance metrics in rowing athletes; however, primary (on-water) performance remains complex to quantify.

Quantifying on-water performance in rowing: A perspective on current challenges and future directions.

Winning times at benchmark international rowing competitions (Olympic Games and World Championships) are known to vary greatly between venues, based on environmental conditions and the strength of the field. Further variability in boat speed for any given effort is found in the training environment, with less controlled conditions (i.e., water flow, non-buoyed courses), fewer world class competitors, and the implementation of non-race specific effort distances and intensities. This combination of external factors makes it difficult for coaches and practitioners to contextualise the performance underpinning boat speed or race results on any given day. Currently, a variety of approaches are referenced in the literature and used in practice to quantify this underpinning performance time or boat speed, however, no clear consensus exists. The use of relative performance (i.e., time compared to other competitors), accounting for influence of the weather (i.e., wind and water temperature), and the novel application of instrumented boats (with power instrumentation) have been suggested as potential methods to improve our understanding of on-water rowing speeds. Accordingly, this perspective article will discuss some of these approaches from recent literature, whilst also sharing experience from current practice in the elite environment, to further stimulate discussion and help guide future research.

Phenotypic divergence between the cultivated apple (Malus domestica) and its primary wild progenitor (Malus sieversii).

An understanding of the relationship between the cultivated apple (Malus domestica) and its primary wild progenitor species (M. sieversii) not only provides an understanding of how apples have been improved in the past, but may be useful for apple improvement in the future. We measured 10 phenotypes in over 1000 unique apple accessions belonging to M. domestica and M. sieversii from Canada's Apple Biodiversity Collection. Using principal components analysis (PCA), we determined that M. domestica and M. sieversii differ significantly in phenotypic space and are nearly completely distinguishable as two separate groups. We found that M. domestica had a shorter juvenile phase than M. sieversii and that cultivated trees produced flowers and ripe fruit later than their wild progenitors. Cultivated apples were also 3.6 times heavier, 43% less acidic, and had 68% less phenolic content than wild apples. Using historical records, we found that apple breeding over the past 200 years has resulted in a trend towards apples that have higher soluble solids, are less bitter, and soften less during storage. Our results quantify the significant changes in phenotype that have taken place since apple domestication, and provide evidence that apple breeding has led to continued phenotypic divergence of the cultivated apple from its wild progenitor species.

Cannabis labelling is associated with genetic variation in terpene synthase genes.

Analysis of over 100 Cannabis samples quantified for terpene and cannabinoid content and genotyped for over 100,000 single nucleotide polymorphisms indicated that Sativa- and Indica-labelled samples were genetically indistinct on a genome-wide scale. Instead, we found that Cannabis labelling was associated with variation in a small number of terpenes whose concentrations are controlled by genetic variation at tandem arrays of terpene synthase genes.

Apple Ripening Is Controlled by a NAC Transcription Factor.

Softening is a hallmark of ripening in fleshy fruits, and has both desirable and undesirable implications for texture and postharvest stability. Accordingly, the timing and extent of pre-harvest ripening and associated textural changes following harvest are key targets for improving fruit quality through breeding. Previously, we identified a large effect locus associated with harvest date and firmness in apple (Malus domestica) using genome-wide association studies (GWAS). Here, we present additional evidence that polymorphisms in or around a transcription factor gene, NAC18.1, may cause variation in these traits. First, we confirmed our previous findings with new phenotype and genotype data from ∼800 apple accessions. In this population, we compared a genetic marker within NAC18.1 to markers targeting three other firmness-related genes currently used by breeders (ACS1, ACO1, and PG1), and found that the NAC18.1 marker was the strongest predictor of both firmness at harvest and firmness after 3 months of cold storage. By sequencing NAC18.1 across 18 accessions, we revealed two predominant haplotypes containing the single nucleotide polymorphism (SNP) previously identified using GWAS, as well as dozens of additional SNPs and indels in both the coding and promoter sequences. NAC18.1 encodes a protein that is orthogolous to the NON-RIPENING (NOR) transcription factor, a regulator of ripening in tomato (Solanum lycopersicum). We introduced both NAC18.1 transgene haplotypes into the tomato nor mutant and showed that both haplotypes complement the nor ripening deficiency. Taken together, these results indicate that polymorphisms in NAC18.1 may underlie substantial variation in apple firmness through modulation of a conserved ripening program.

Ensembles of ecosystem service models can improve accuracy and indicate uncertainty.

Many ecosystem services (ES) models exist to support sustainable development decisions. However, most ES studies use only a single modelling framework and, because of a lack of validation data, rarely assess model accuracy for the study area. In line with other research themes which have high model uncertainty, such as climate change, ensembles of ES models may better serve decision-makers by providing more robust and accurate estimates, as well as provide indications of uncertainty when validation data are not available. To illustrate the benefits of an ensemble approach, we highlight the variation between alternative models, demonstrating that there are large geographic regions where decisions based on individual models are not robust. We test if ensembles are more accurate by comparing the ensemble accuracy of multiple models for six ES against validation data across sub-Saharan Africa with the accuracy of individual models. We find that ensembles are better predictors of ES, being 5.0-6.1% more accurate than individual models. We also find that the uncertainty (i.e. variation among constituent models) of the model ensemble is negatively correlated with accuracy and so can be used as a proxy for accuracy when validation is not possible (e.g. in data-deficient areas or when developing scenarios). Since ensembles are more robust, accurate and convey uncertainty, we recommend that ensemble modelling should be more widely implemented within ES science to better support policy choices and implementation.

Lineage of measurable residual disease in patients with chronic myeloid leukemia in treatment-free remission.

Approximately half of patients with chronic myeloid leukemia (CML) in sustained deep molecular response who discontinue tyrosine kinase inhibitors (TKIs) remain in treatment-free remission (TFR). Some of these patients have measurable residual disease (MRD) by BCR-ABL1 mRNA testing, and most have detectable BCR-ABL1 DNA by highly sensitive methods. We used fluorescence-activated cell sorting and BCR-ABL1 DNA PCR to investigate the lineage of residual CML cells in TFR. Twenty patients in TFR for >1 year provided blood for sorting into granulocytes, monocytes, B cells, T cells, and NK cells. MRD was identified predominantly in the lymphoid compartment and never in granulocytes. B cells were more often BCR-ABL1 positive than T cells (18 vs 11/20 patients) and at higher levels (median 10-4.9 vs 10-5.7; P = 0.014). In 13 CML patients studied at diagnosis lymphocytes expressing BCR-ABL1 mRNA comprised a small proportion of total leukocytes. These data improve our understanding of TFR biology, since it is now clear that MRD in the blood of TFR patients need not imply the persistence of multipotent CML cells. Lineage-specific assessment of MRD could be explored as a means to improve the prediction of TFR.

Modelling potential habitat for snow leopards (Panthera uncia) in Ladakh, India.

The snow leopard Panthera uncia is an elusive species inhabiting some of the most remote and inaccessible tracts of Central and South Asia. It is difficult to determine its distribution and density pattern, which are crucial for developing conservation strategies. Several techniques for species detection combining camera traps with remote sensing and geographic information systems have been developed to model the habitat of such cryptic and low-density species in challenging terrains. Utilising presence-only data from camera traps and direct observations, alongside six environmental variables (elevation, aspect, ruggedness, distance to water, land cover, and prey habitat suitability), we assessed snow leopard habitat suitability across Ladakh in northern India. This is the first study to model snow leopard distribution both in India and utilising direct observation data. Results suggested that elevation and ruggedness are the two most influential environmental variables for snow leopard habitat suitability, with highly suitable habitat having an elevation range of 2,800 m to 4,600 m and ruggedness of 450 m to 1,800 m. Our habitat suitability map estimated approximately 12% of Ladakh's geographical area (c. 90,000 km2) as highly suitable and 18% as medium suitability. We found that 62.5% of recorded livestock depredation along with over half of all livestock corrals (54%) and homestays (58%) occurred within highly suitable snow leopard habitat. Our habitat suitability model can be used to assist in allocation of conservation resources by targeting construction of livestock corrals to areas of high habitat suitability and promoting ecotourism programs in villages in highly suitable snow leopard habitat.