Federico Y. Fontana

Studies focused on bacterial diversity in rivers often face significant limitations. Traditional sampling approaches frequently overlook spatial and temporal variability at the reach scale. Molecular techniques, such as metabarcoding and metagenomics, can partially address this issue by providing deeper insights. However, this approach usually involves highly specialized laboratories and high costs, making large-scale and long-term monitoring of river networks unfeasible in most cases. Thus, we developed a methodology based on remote-controlled boats, allowing the collection of integrated samples in freshwater ecosystems. Combined with a portable laboratory, this approach enabled the development of new surface water monitoring strategies. Here, we describe the operational application of this system for in situ monitoring of bacterioplankton communities across 8 sections of the Ter River (Catalonia, Spain). [To explore its potential, we applied both 16S rRNA gene sequencing using Nanopore technology (MinION) in the field, and shotgun metagenomics using Illumina technology in the laboratory, acknowledging the intrinsic differences between sequencing targets, platforms, and analysis pipelinesMinIONMinION sequencing enabled microbiome characterization and identification of the main bacterial taxa just 72 h after sampling, offering significantly lower costs and reduced manpower requirements. Furthermore, amplification facilitated the full characterization of bacterioplankton diversity along the river, preventing the exclusion of uncommon taxa. While shotgun metagenomics is still necessary for understanding the functional activity of these organisms, our approach provides a cost-effective framework for developing efficient follow-up sampling methodologies.

Aims: To analyse glycaemic patterns of professional athletes with type 1 diabetes during a competitive season. Materials and Methods: We analysed continuous glucose monitoring data of 12 professional male cyclists with type 1 diabetes during exercise, recovery and sleep on days with competitive exercise ( CE ) and non‐competitive exercise ( NCE ). We assessed whether differences exist between CE and NCE days and analysed associations between exercise and dysglycaemia. Results: The mean glycated haemoglobin was 50 ± 5 mmol/mol (6.7 ± 0.5%). The athletes cycled on 280.8 ± 28.1 days (entire season 332.6 ± 18.8 days). Overall, time in range (3.9‐10 mmol/L) was 70.0 ± 13.7%, time in hypoglycaemia (10 mmol/L) was 23.6 ± 12.5%. During the nights of NCE days, athletes spent 10.1 ± 7.4% of time in hypoglycaemia, particularly after exercise in the endurance zones. The CE days were characterized by a higher time in hyperglycaemia compared with NCE days (25.2 ± 12.5% vs. 22.2 ± 12.1%, p = .012). This was driven by the CE phase, where time in range dropped to 60.4 ± 13.0% and time in hyperglycaemia was elevated (38.5 ± 12.9%). Mean glucose was higher during CE compared with NCE sessions (9.6 ± 0.9 mmol/L vs. 7.8 ± 1.1 mmol/L, p < .001). The probability of hyperglycaemia during exercise was particularly increased with longer duration, higher intensity and higher variability of exercise. Conclusions: The analysis of glycaemic patterns of professional endurance athletes revealed that overall glycaemia was generally within targets. For further improvement, athletes, team staff and caregivers may focus on hyperglycaemia during competitions and nocturnal hypoglycaemia after NCE .

A methodology to study bike handling of cyclists during individual time trials (ITT) is presented. Lateral and longitudinal accelerations were estimated from GPS data of professional cyclists (n=53) racing in two ITT of different length and technical content. Acceleration points were plotted on a plot (g-g diagram) and they were enclosed in an ellipse. A correlation analysis was conducted between the area of the ellipse and the final ITT ranking. It was hypothesized that a larger area was associated to a better performance. An analytical model for the bike-cyclist system dynamics was used to conduct a parametric analysis on the influence of riding position on the shape of the g-g diagram. A moderate (n=27, r=-0.40, p=0.038) and a very large (n=26, r=-0.83, p<0.0001) association were found between the area of the enclosing ellipse and the final ranking in the two ITT. Interestingly, this association was larger in the shorter race with higher technical content. The analytical model suggested that maximal decelerations are highly influenced by the cycling position, road slope and speed. This investigation, for the first time, explores a novel methodology that can provide insights into bike handling, a large unexplored area of cycling performance.

The problem of the automatic determination of the first and second ventilatory thresholds (VT1 and VT2) from cardiopulmonary exercise test (CPET) still leads to controversy. The reliability of the gold standard methodology (i.e. expert visual inspection) feeds into the debate and several authors call for more objective automatic methods to be used in the clinical practice. In this study, we present a framework based on a collaborative approach, where a web‐application was used to crowd‐source a large number (1245) of CPET data of individuals with different aerobic fitness. The resulting database was used to train and test an artificial intelligence (i.e. a convolutional neural network) algorithm. This automatic classifier is currently implemented in another web‐application and was used to detect the ventilatory thresholds in the available CPET. A total of 206 CPET were used to evaluate the accuracy of the estimations against the expert opinions. The neural network was able to detect the ventilatory thresholds with an average mean absolute error of 178 (198) mlO₂/min (11.1%, r = 0.97) and 144 (149) mlO₂/min (6.1%, r = 0.99), for VT1 and VT2 respectively. The performance of the neural network in detecting VT1 deteriorated in case of individuals with poor aerobic fitness. Our results suggest the potential for a collective intelligence system to outperform isolated experts in ventilatory thresholds detection. However, the inclusion of a larger number of VT1 examples certified by a community of experts will be likely needed before the abilities of this collective intelligence can be translated into the clinical use of CPET.

Introduction: The COVID‐19 pandemic has forced rapid reconsideration as to the way in which health care is delivered. One potential means to provide care while avoiding unnecessary person‐to‐person contact is to offer remote services (telemedicine). This study aimed to (1) gather real‐time information on the use and perception of telemedicine in people living with type 1 diabetes and (2) assess the challenges, such as restricted access to health care and/or medical supplies.Methods: An anonymous questionnaire was widely distributed between 24 March and 5 May 2020 using an open‐access web‐based platform. Data were analysed descriptively, and results were stratified according to age, sex and HbA_1c.Results: There were 7477 survey responses from individuals in 89 countries. Globally, 30% reported that the pandemic had affected their healthcare access due to cancelled physical appointments with their healthcare providers. Thirty‐two per cent reported no fundamental change in their medical follow‐up during this period, with 9% stating that no personal contact was established with their doctors over the duration of the study. Twenty‐eight per cent received remote care through telephone (72%) or video‐calls (28%). Of these, 86% found remote appointments useful and 75% plan to have remote appointments in the future. Glucose control, indicated by HbA_1c, was positively associated with positive perception of telemedicine. In males, 45% of respondents with an HbA_1c > 9% rated telemedicine not useful compared to those with lower HbA_1c, while 20% of females with an HbA_1c > 9% rated it not useful (χ² = 14.2, P = .0016).Conclusion: Remote appointments have largely been perceived as positive in people with type 1 diabetes with the majority (75%) stating that they would consider remote appointments beyond the pandemic. Age and level of education do not appear to influence perception of telemedicine, whereas poor glucose control, particularly in males, seems to negatively affect perception.

We tested the hypothesis that critical intensity in cycling can be determined from a single delta blood lactate in the third minute of a submaximal cycle ergometer trial. Fourteen healthy young men performed four to six constant-power-output trials on a cycle ergometer to the limit of tolerance. Critical intensity was calculated via a linear model and subsequently validated. Lactate was measured at baseline and at 3 min from exercise onset. Delta lactate was the difference between these measures. Based on individual trials, we obtained the delta lactate–% validated critical intensity relationship and thereafter an estimate of critical intensity was computed. Validated and estimated critical intensity were compared by effects sizes, paired-sample t-test and Bland–Altman analysis. Delta lactate was a linear function of the intensity of exercise, expressed as % validated critical intensity (R² = 0.89). Estimated critical intensity was not different from (d = 0.03, P = 0.98) and highly correlated with (R² = 0.88) validated critical intensity. The bias between measures was 0.03 W (≠0) with a precision of 7 W. The results suggest that critical intensity in cycling can be accurately and precisely determined from delta lactate during a sub-maximal trial and so provides a practical and valid alternative to direct determination.

New Findings: What is the central question of this study? Can the near‐infrared spectroscopy (NIRS)‐derived reperfusion rate (slope 2) of tissue oxygen saturation (StO₂) be correlated with flow‐mediated dilation (FMD), the commonly used method to assess vascular endothelial function? What is the main finding and its importance? The present data were able to establish a correlation between the reperfusion rate of StO₂ and percentage FMD in healthy young men. These data suggest that NIRS‐derived slope 2 StO₂ can be used as a measure of vascular endothelial function. Vascular impairments at the macro‐ and microcirculatory levels are associated with increased risk for cardiovascular disease. Flow‐mediated dilation (FMD) is currently the most widely used method for non‐invasive assessment of vascular endothelial function. Recently, near‐infrared spectroscopy (NIRS)‐derived measures of tissue oxygen saturation (StO₂) have been used to characterize the dynamic response of local tissue perfusion to a brief period of ischaemia. The purpose of the present study was to establish correlations between the reperfusion rate of StO₂ and FMD. Ultrasound‐derived FMD was quantified after 5 min of distal cuff occlusion of the popliteal artery in 20 healthy young men (26 ± 3 years old). Triplicate measurements of end‐diastolic arterial diameter were made every 15 s after cuff release, and FMD response was calculated as the greatest percentage change in diameter from baseline (%FMD). The StO₂ was measured using NIRS throughout the duration of each test. Two consecutive FMD tests were performed, separated by 30 min of rest, and were averaged for %FMD and StO₂. The %FMD was significantly correlated with the reperfusion slope of StO₂ after cuff release (slope 2 StO₂; r = 0.63, P = 0.003). In conclusion, the present study established a correlation between slope 2 StO₂ and %FMD in healthy young men. These data suggest that NIRS‐derived slope 2 StO₂ can be used as a measure of vascular endothelial function.