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This study sought to assess how post-game creatine kinase (CK) levels correlate with the number of sprints and the impact of the ACTN3 polymorphism on this response. This research constituted a descriptive/observational, retrospective cross-sectional study. DNA was extracted from blood samples for ACTN3 polymorphism genotyping. CK was measured 48 h after official matches, and the number of sprints (>19 km/h) was tracked using Global Positioning System (GPS) technology. The main cohort included 23 professional soccer players from the top tier of the Brazilian Championship. We analyzed 115 GPS + CK data sets. The replication cohort comprised 18 professional soccer players from the First Division of the Championship, had the same methodology applied, and featured a total of 90 GPS (sprints > 25.2 km/h) + CK data sets. For the main cohort, a significant positive correlation was seen between the number of sprints and the CK levels (p = 0.009). Athletes with the ACTN3 RR genotype had higher CK levels as more sprints were performed during the match (p = 0.017). However, the relationship was not found for X allele carriers (p > 0.05). For the replication cohort, there was a near-significant correlation between CK levels and the number of sprints (p = 0.05), and RR individuals showed a significant association (p = 0.01), whereas X allele carriers did not (p = 0.06). A greater number of sprints during matches is linked to higher CK levels, primarily among players with the ACTN3 RR genotype, which is potentially due to an increased presence of type II muscle fibers. These findings were replicated for both cohorts of elite Brazilian soccer players, emphasizing the importance of genetic factors in injury prevention.

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This study introduces an innovative algorithm for classifying transportation modes. It categorizes modes such as walking, biking, tram, bus, taxi, and private vehicles based on data collected through sensors embedded in smartphones. The data include date, time, latitude, longitude, altitude, and speed, gathered using a mobile application specifically designed for this project. These data were collected through the smartphone's GPS to enhance the accuracy of the analysis. The stopping times of each transport mode, as well as the distance traveled and average speed, are analyzed to identify patterns and distinctive features. Conducted in Cuenca, Ecuador, the study aims to develop and validate an algorithm to enhance urban planning. It extracts significant features from mobility patterns, including speed, acceleration, and over-acceleration, and applies longitudinal dynamics to train the classification model. The classification algorithm relies on a decision tree model, achieving a high accuracy of 94.6% in validation and 94.9% in testing, demonstrating the effectiveness of the proposed approach. Additionally, the precision metric of 0.8938 signifies the model's ability to make correct positive predictions, with nearly 90% of positive instances correctly identified. Furthermore, the recall metric at 0.83084 highlights the model's capability to identify real positive instances within the dataset, capturing over 80% of positive instances. The calculated F1-score of 0.86117 indicates a harmonious balance between precision and recall, showcasing the models robust and well-rounded performance in classifying transport modes effectively. The study discusses the potential applications of this method in urban planning, transport management, public transport route optimization, and urban traffic monitoring. This research represents a preliminary stage in generating an origin-destination (OD) matrix to better understand how people move within the city.

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The MarineStar Global Navigation Satellite System (GNSS) augmentation services are widely used in bathymetric surveys to obtain the sensor position. The postprocessed kinematic (PPK) GNSS method can be used to obtain more accurate positions. Therefore, the present work aims to verify the vertical final accuracies and uncertainties of exclusive order multibeam hydrographic surveys using the Global Navigation Satellite System (GNSS) as a horizontal positioning tool through methods such MarineStar services and PPK relative positioning, with comparisons between the two methods based on the results of the hydrographic base created. We produced two surfaces with each method, representing the minimum and maximum depths of the bathymetry point cloud. A statistical analysis of the differences between the depth surfaces obtained with the two methods was carried out. When comparing the two surfaces using the PPK method, the difference was less than 10 cm at 95.1% of the points. When comparing the two surfaces to those of the MarineStar, the difference between the maximum and minimum depths was less than 10 cm at 93.1% of the points. The results suggest that using the same survey data, the products obtained with the PPK method would comply with the hydrographic standards, while the MarineStar products would not.

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This paper proposes a new sensor using optical flow to stabilize a quadrotor when a GPS signal is not available. Normally, optical flow varies with the attitude of the aerial vehicle. This produces positive feedback on the attitude control that destabilizes the orientation of the vehicle. To avoid this, we propose a novel sensor using an optical flow camera with a 6DoF IMU (Inertial Measurement Unit) mounted on a two-axis anti-shake stabilizer mobile aerial gimbal. We also propose a robust algorithm based on Sliding Mode Control for stabilizing the optical flow sensor downwards independently of the aerial vehicle attitude. This method improves the estimation of the position and velocity of the quadrotor. We present experimental results to show the performance of the proposed sensor and algorithms.

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This study investigated the effects of match location, quality of opposition (classified into: strong [1st to 4th position]; intermediate [5th to 15th position]; weak [16th to 20th position]), and match outcome on the match running performance of starters and non-starters from a top elite Brazilian soccer team. Absolute measures were calculated using total distance, high-speed (19.8-25.2 km·h-1), sprinting (≥ 25.2 km·h-1), total distance high-acceleration (> 2m·s2), and deceleration (< -2m·s2) were recorded by GPS units from a sample of young soccer players (N = 25) in a total of 17 matches. Relative measures were calculated by dividing absolute measures by the total duration of the matches. Non-starters covered greater total distance (p = 0.02), sprinting (p = 0.02), high-acceleration and deceleration (p = 0.04), sprinting distance relative per minute played (p = 0.005), and high-acceleration and deceleration relative per minute played (p < 0.001) when the team plays at home, strong opponents, and wins the matches. Starters covered greater total distance in high-speed running (p = 0.04), high-acceleration and deceleration (p = 0.03), and high-speed running relative per minute played (p = 0.04) when the team plays strong opponents and wins the matches. These findings highlight the impact of contextual factors during matches on the locomotor performance of young soccer players.

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The increased need for water resources in urban sprawls and intense droughts has forced more aggressive groundwater extraction resulting in numerous urban areas undergoing land subsidence. In most cases, only some large metropolitan areas have been well-characterized for subsidence. However, there is no existing country-wide assessment of urban areas, population, and households exposed to this process. This research showcases a methodology to systematically evaluate urban localities with land subsidence higher than - 2.8 cm/year throughout Mexico. We used Interferometric Synthetic Aperture Radar (InSAR) tools with a dataset of 4611 scenes from European Space Agency's Sentinel-1 A/B SAR sensors acquired from descending orbits from September 2018 through October 2019. This dataset was processed at a supercomputer using InSAR Scientific Computing Environment and the Miami InSAR Time Series software in Python software. The quality and calibration of the resulting velocity maps are assessed through a large-scale comparison with observations from 100 continuous GPS sites throughout Mexico. Our results show that an urban area of 3797 km2, 6.9 million households, and 17% of the total population in Mexico is exposed to subsidence velocities of faster than - 2.8 cm/year, in more than 853 urban localities within 29 land subsidence regions. We also confirm previous global potential estimations of subsidence occurrence in low relief areas over unconsolidated deposits and where groundwater aquifers are under stress. The presented research demonstrates the capabilities for surveying urban areas exposed to land subsidence at a country-scale level by combining Sentinel-1 velocities with spatial national census data. Supplementary Information: The online version contains supplementary material available at 10.1007/s11069-023-06259-5.

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This study aimed to analyze the effects of contextual variables (i.e., match location and match outcome) and season periods on match load (i.e., internal and external load) in professional Brazilian soccer players. Thirty-six professional players from the same soccer team participated in this study. The season was split into four phases: matches 1-16 (i.e., Phase 1 = P1); matches 17-32 (i.e., Phase 2 = P2); matches 33-48, (i.e., Phase 3 = P3); matches 49-65 (i.e., Phase 4 = P4). Considering match outcome, when the team wins, Cognitive load, Emotional load, and Affective load were significantly higher in away vs. home matches (p < 0.05). Considering season phases, in P3, Mental Fatigue was significantly higher in drawing than in losing matches (p < 0.05). Additionally, considering the match outcome, when the team lost, Total Distance (TD)/min and TD > 19 km·h-1/min were significantly lower in P1 than P2 (p < 0.001), P3 (p < 0.001), and P4 (p < 0.001). These results suggest to strength and conditioning coaches the need to consider the outcome and location of the previous game when planning the week, as well as the phase of the season they are in to reduce fatigue and injury risk.

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In the last decade, a large amount of data from vehicle location sensors has been generated due to the massification of GPS systems to track them. This is because these sensors usually include multiple variables such as position, speed, angular position of the vehicle, etc., and, furthermore, they are also usually recorded in very short time intervals. On the other hand, routes are often generated so that they do not correspond to reality, due to artifacts such as buildings, bridges, or sensor failures and where, due to the large amount of data, visual analysis of human expert is unable to detect genuinely anomalous routes. The presence of such abnormalities can lead to faulty sensors being detected which may allow sensor replacement to reliably track the vehicle. However, given the reliability of the available sensors, there are very few examples of such anomalies, which can make it difficult to apply supervised learning techniques. In this work we propose the use of unsupervised deep neural network models based on stacked autoencoders to detect anomalous routes in vehicles within Santiago de Chile. The results show that the proposed model is capable of effectively detecting anomalous paths in real data considering validation given by an expert user, reaching a performance of 82.1% on average. As future work, we propose to incorporate the use of Long Short-Term Memory (LSTM) and attention-based networks in order to improve the detection of anomalous trajectories.

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PURPOSE: To understand the applicability and unique contributions of global positioning system (GPS) and geographic information system (GIS) technologies to investigate individuals' participation in the community. METHODS: A scoping review was conducted to summarize studies that employed GPS and/or GIS to assess community participation. Systematic literature searches were performed using nine electronic databases, up to April 2022. Two independent reviewers screened studies for eligibility and extracted data from the selected studies. RESULTS: The searches retrieved 628 articles, of which 36 met the inclusion criteria. In 31 studies, a GPS unit or GPS-enabled device monitored the community mobility of individuals with different health conditions. Tracking periods varied from five hours to 30 consecutive days. The spatiotemporal parameters obtained from satellite-based data provided information about individuals' presence in the community. Most studies combined GPS with other measuring tools (self-report diaries/questionnaires, qualitative interviews) to capture a broader description of community participation. CONCLUSIONS: GPS and GIS are viable approaches for advancing research as they provide unique information about community participation not easily captured by other methods. The combination of available methods comprehensively address the physical and social dimensions of this construct.IMPLICATIONS FOR REHABILITATIONGlobal positioning system (GPS) and geographic information system (GIS) technology allows direct and real-time quantification of patterns of individuals' community mobility.The geographic area where individuals participate in daily living activities complements information from self-report diaries/questionnaires.Combining GPS technology with self-report diaries/questionnaires allows a broader description of individuals' community participation, addressing respectively both its physical and social dimensions.Knowledge of individuals' access to and involvement in community locations/situations may help therapists design interventions to improve community participation.

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This study aimed to examine the differences in physical match activities and heart rate (HR) responses experienced by Brazilian field referees (FRs) and assistant referees (ARs) during official matches from Serie A, Serie B and Regional championships. The sample was composed of 51 FRs and 87 ARs. Match activities derived from Global Position System and HR response were collected during official matches. FRs and ARs covered higher distances at high-intensity running (HIR; d = 1.17 and 2.53, p < 0.001), sprinting (d = 0.82 and 0.48, p < 0.005) and high-intensity activities (HIA; d = 1.07 and 1.97, p < 0.001) in Serie A and Serie B than in Regional. Changes in the distances covered at HIR (0.80 < d < 3.25, p < 0.005), sprinting (d = 0.42, p = 0.050) and HIA (0.93 < d < 3.01, p < 0.005) between half-matches were observed during Serie A and Serie B. The average %HRmax was progressively increased in both half-matches (0.85 < d < 3.54, p < 0.001) during all championships. For FRs, Serie A and Regional elicited the highest average %HRmax (0.80 3C d < 1.37, p < 0.030). For ARs, Serie A and Serie B elicited the highest average %HRmax (2.14 < d< 3.87, p < 0.001). In conclusion, the physical match activities and average %HRmax of Brazilian FRs and ARs differ across championship levels. FRs and ARs acting in Regional championships are likely to need specific preparation to support the higher physical demand observed at higher competition levels.

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The objective of the present study was to describe the total and fragmented external loads, at different intensities, of soccer referees in European and South American competitions during official matches through a systematic review and meta-analysis of cross-sectional studies. A systematic review was conducted in April, 2020. In all, 32 studies were included, incorporating 578 referees evaluated in 3170 games through video analysis or a global positioning system. Regarding external loads, it was observed that the total average distance covered by the referees was 10,461.74 m, with running speeds predominantly below 13 km.h-1. The total distance covered by the referees in the European competitions was higher and more intense than that of the referees in the South American tournaments, being 11,187.02 m and 9319.61 m, respectively. We suggest that referees' training can be organized according to the distances found at different intensities, in which low-intensity races can be performed below 13 km.h-1 with distances of approximately 4500 m, while high-intensity training can be developed with speeds from 18 to 24 km.h-1 for approximately 800 m. In addition, planning must consider the competition characteristics.

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Wireless sensor networks (WSNs) have gained a positive popularity for structural health monitoring (SHM) applications. The underlying reason for using WSNs is the vast number of devices supporting wireless networks available these days. However, some of these devices are expensive. The main objective of this paper is to develop a cost-effective WSN based on low power consumption and long-range radios, which can perform real-time, real-scale acceleration data analyses. Since a detection system for vibration propagation is proposed in this paper, the synchronized monitoring of acceleration data is necessary. To meet this need, a Pulse Per Second (PPS) synchronization method is proposed with the help of GPS (Global Positioning System) receivers, representing an addition to the synchronization method based on real-time clock (RTC). As a result, RTC+PPS is the term used when referring to this method in this paper. In summary, the experiments presented in this research consist in performing specific and synchronized measurements on a full-scale steel I-beam. Finally, it is possible to perform measurements with a synchronization success of 100% in a total of 30 samples, thereby obtaining the propagation of vibrations in the structure under consideration by implementing the RTS+PPS method.

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Collecting GPS data using mobile devices is essential to understanding human mobility. However, getting this type of data is tricky because of some specific features of mobile operating systems, the high-power consumption of mobile devices, and users' privacy concerns. Therefore, data of this kind are rarely publicly available for scientific purposes, while private companies that own the data are often reluctant to share it. Here we present a large anonymous longitudinal dataset of Activity Point Location (APL) generated from mobile devices' GPS tracking. The GPS data were collected by using the Google Location History (GLH), accessible in the Google Maps application. Our dataset, named AnLoCOV hereafter, includes anonymised data from 338 persons with corresponding socio-demographics over approximately ten years (2012-2022), thus covering pre- and post-COVID periods, and calculates over 2 million weekly-classified APL extracted from approximately 16 million GPS tracking points in Ecuador. Furthermore, we made our models publicly available to enable advanced analysis of human mobility and activity spaces based on the collected datasets.

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El objetivo del presente estudio fue determinar el rendimiento físico de jugadores sub 14, durante los partidos del Torneo Nacional de Asociaciones 2019, disputado en la Provincia de Córdoba, Argentina. Se monitorearon cinco encuentros (tres de fase de grupo; uno, semi final y uno, final). La muestra fue de 50 casos monitorizados por unidades GPS (PlayerTek Plus), divididos por posición: Defensores Centrales (n = 2), Defensores Laterales (n = 5), Volantes (n = 4) y Delanteros (n = 6). Las variables analizadas fueron divididas en dos, por un lado, las variables de volumen y, por otro, las de intensidad. Las primeras fueron: Distancia Total (m) 4718 ± 0,95; Distancia en Sprint (entre 16 a 19 km/h) (m) 484,67 ± 268,28; Cantidad de Sprints (>19 km/h) (rep) 17,70 ± 9,67; Aceleraciones >2 m/s2 (rep) 32,28 ± 13,39 y Desaceleraciones >-2 m/s2 (rep) 44,47 ± 17,08. En cambio, las variables de intensidad fueron: Metros por minuto (m) 101,18 ± 13,52; Distancia en Sprint por Minuto (m) 10,35 ± 5,96; Cantidad de Sprint por Minuto (rep) 0,37 ± 0,22. En conclusión, se consideró que analizar objetivamente, el rendimiento físico de los jóvenes jugadores es de vital importancia ya que podríamos establecer planes estratégicos para mejorar su performance, como también, bajar la incidencia lesiva.

The objective of this study was to determine the physical performance of U14 players, during the matches of the 2019 National Association Tournament, played in the Province of Córdoba, Argentina. 5 matches were monitored (3 group phase, 1 semi-final and 1 final). The sample consisted of 50 cases monitored by GPS units (PlayerTek Plus), divided by position: Central Defenders (n = 2), Side Defenders (n = 5), Midfielders (n = 4) and Forwards (n = 6). The analyzed variables were divided into 2: the volume variables and the intensity variables. The first ones were: Total Distance (m) 4718 ± 0.95; Sprint distance (between 16 to 19 km/h) (m) 484.67 ± 268.28; Number of Sprints (> 19 km/h) (rep) 17.70 ± 9.67; Accelerations> 2 m/s2 (rep) 32.28 ± 13.39 and Decelerations> -2 m/s2 (rep) 44.47 ± 17.08. Instead, the intensity variables were Meters per minute (m) 101.18 ± 13.52; Distance in Sprint per minute (m) 10.35 ± 5.96; and Amount of Sprint per minute (rep) 0.37 ± 0.22. In conclusion, it was considered that objectively analyzing the physical performance of young players is of vital importance, since we could establish strategic plans to improve their performance, as well as lower the incidence of injury.

O objetivo deste estudo foi determinar o desempenho físico de jogadores menores de 14 anos, durante as partidas do Torneio de Associações Nacionais 2019, disputadas na Província de Córdoba, Argentina. Foram monitorizados 5 jogos (3 fases de grupos, 1 semifinal e 1 final). A amostra foi composta por 50 casos monitorados por GPS (PlayerTek Plus), divididos por posição: Defensores Centrais (n=2), Defensores Laterais (n=5), Meio-campistas (n=4) e Atacantes (n=6). As variáveis analisadas foram divididas em 2, de um lado as variáveis de volume e, de outro, as variáveis de intensidade. As primeiras foram: Distância Total (m) 4718 ± 0,95; Distância em Sprint (entre 16 a 19 km/h) (m) 484,67 ± 268,28; Número de Sprints (>19 km/h) (rep) 17,70 ± 9,67; Aceleração >2 m/s2 (rep) 32,28 ± 13,39 e desacelerações >-2 m/s2 (rep) 44,47 ± 17,08. Em vez disso, as variáveis de intensidade foram: Metros por minuto (m) 101,18 ± 13,52; Distância em Sprint por Minuto (m) 10,35 ± 5,96; Quantidade de Sprint por Minuto (rep) 0,37 ± 0,22. Em conclusão, considerou-se que analisar objetivamente o desempenho físico de jovens jogadores é de vital importância, pois podemos estabelecer planos estratégicos para melhorar seu desempenho, bem como diminuir a incidência de lesões.

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The current brief research report aimed to investigate the influence of contextual variables on peak running performance in male elite soccer players. We analyzed 29 matches of an elite soccer team during the Brazilian Serie A 2019. Twenty players were tracked using GPS units. Peak physical performance was determined using moving average running values with different time windows (1, 3, and 5-min periods). The variables analyzed were total distance covered, total distance covered in high-intensity running (≥19.8 km·h-1), and the distance in accelerations (≥2 m·s-2) and decelerations ( ≤-2 m·s-2). Four contextual variables were considered: 1) positional status; 2) match location; 3) match outcome; and 4) match status. Central defenders showed a lower 1-min peak total distance in relation to all other positions (p = 0.001-0.03). Peak physical performance was higher in away matches for high-intensity running, acceleration, and deceleration (p = 0.01-0.03). In matches that ended in losses, peak values for high-intensity running and acceleration were higher compared to draws and wins (p = 0.01-0.04). Regarding the match status, higher values were observed in draws than wins and losses (p = 0.01). Peak running performance vary according to contextual variables of the match in male elite soccer players. Positional differences were found for peak periods, and physical performance was higher in away matches.

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The lowest water availability area in Brazil is the Northeast Atlantic Eastern Hydrographic Region (NAERH). It plays a fundamental role in the lives of 24.1 million inhabitants spread throughout 874 cities. Drought is recurrent in this semiarid climate, affecting agriculture, biodiversity, the ecosystem and other environmental spheres. Therefore, the goal of this research is to combine different drought indexes to quantify drought intensity and duration in the NAERH. Besides the traditionally used rainfall data, multi-temporal data from the Gravity Recovery and Climate Experiment (GRACE) and Global Positioning System (GPS) were also used. The indexes are the Combined Climatic Deviation Index (CCDI), Drought Severity Index (DSI) and Vertical Crustal Deformation Index (DIVCD). The Standardized Precipitation Index (SPI) was used for validation of the other indexes through the Spearman rank correlation, which retrieved ρ = 0.76 and 0.68 between the CCDI and the SPI-03/06. On the other hand, DSI correlated with the SPI-24/36 with ρ = 0.67/0.75. Despite limitations, the DIVCD accurately detected the frequencies of hydrological droughts. All indexes identified the last severe drought from 2012 to 2018, and its persistence throughout 2019 and 2020. The combined indexes approach reveals nuances of the indexes, improving the baseline to thoroughly understand drought at different temporal scales.

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Individual decisions regarding how, why and when organisms interact with one another and with their environment scale up to shape patterns and processes in communities. Recent evidence has firmly established the prevalence of intraspecific variation in nature and its relevance in community ecology, yet challenges associated with collecting data on large numbers of individual conspecifics and heterospecifics have hampered integration of individual variation into community ecology. Nevertheless, recent technological and statistical advances in GPS-tracking, remote sensing and behavioural ecology offer a toolbox for integrating intraspecific variation into community processes. More than simply describing where organisms go, movement data provide unique information about interactions and environmental associations from which a true individual-to-community framework can be built. By linking the movement paths of both conspecifics and heterospecifics with environmental data, ecologists can now simultaneously quantify intraspecific and interspecific variation regarding the Eltonian (biotic interactions) and Grinnellian (environmental conditions) factors underpinning community assemblage and dynamics, yet substantial logistical and analytical challenges must be addressed for these approaches to realize their full potential. Across communities, empirical integration of Eltonian and Grinnellian factors can support conservation applications and reveal metacommunity dynamics via tracking-based dispersal data. As the logistical and analytical challenges associated with multi-species tracking are surmounted, we envision a future where individual movements and their ecological and environmental signatures will bring resolution to many enduring issues in community ecology.

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Autonomous navigation in mining tunnels is challenging due to the lack of satellite positioning signals and visible natural landmarks that could be exploited by ranging systems. Solutions requiring stable power feeds for locating beacons and transmitters are not accepted because of accidental damage risks and safety requirements. Hence, this work presents an autonomous navigation approach based on artificial passive landmarks, whose geometry has been optimized in order to ensure drift-free localization of mobile units typically equipped with lidar scanners. The main contribution of the approach lies in the design and optimization of the landmarks that, combined with scan matching techniques, provide a reliable pose estimation in modern smoothly bored mining tunnels. A genetic algorithm is employed to optimize the landmarks' geometry and positioning, thus preventing that the localization problem becomes ill-posed. The proposed approach is validated both in simulation and throughout a series of experiments with an industrial skid-steer CAT 262C robotic excavator, showing the feasibility of the approach with inexpensive passive and low-maintenance landmarks. The results show that the optimized triangular and symmetrical landmarks improve the positioning accuracy by 87.5% per 100 m traveled compared to the accuracy without landmarks. The role of optimized artificial landmarks in the context of modern smoothly bored mining tunnels should not be understated. The results confirm that without the optimized landmarks, the localization error accumulates due to odometry drift and that, contrary to the general intuition or belief, natural tunnel features alone are not sufficient for unambiguous localization. Therefore, the proposed approach ensures grid-based SLAM techniques can be implemented to successfully navigate in smoothly bored mining tunnels.

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BACKGROUND: This study compared the physical, physiological, and spatiotemporal responses of soccer athletes in small-sided games (SSG) in two experimental conditions: progression to the target rule (PG), in which they should take the ball to the opponent's endline to score points, and SSG with regular rules (RG), in which they should score goals to win the game. METHODS: Twenty U-20 athletes played both SSG formats. The SSG were played as four 4-minute bouts with four minutes of passive recovery in two consecutive days. Heart rate, physical (distances and accelerations), and positional data (length, width, and spatial exploration) were collected by a 10 hz GPS device and compared between the protocols using a MANOVA with Bonferroni's correction for multiple comparisons. RESULTS: Results showed that the RG condition demanded more spatial exploration eliciting greater occupation of the pitch width. There were higher mean and maximum heart rates and greater low-to-moderate distances and accelerations in the RG, while the PG rule increased the distances covered at the highest speed and acceleration zones. CONCLUSIONS: The progression to the target rule should be adopted to emphasize players' ability to use the width during the offensive phase. Additionally, the PG rule should also be used to emphasize the development of speed and acceleration skills.

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Cardiovascular manifestations account for marked morbi-mortality in autosomal dominant polycystic kidney disease (ADPKD). Pkd1- and Pkd2-deficient mice develop cardiac dysfunction, however the underlying mechanisms remain largely unclear. It is unknown whether impairment of polycystin-1 cleavage at the G-protein-coupled receptor proteolysis site, a significant ADPKD mutational mechanism, is involved in this process. We analyzed the impact of polycystin-1 cleavage on heart metabolism using Pkd1V/V mice, a model unable to cleave this protein and with early cardiac dysfunction. Pkd1V/V hearts showed lower levels of glucose and amino acids and higher lipid levels than wild-types, as well as downregulation of p-AMPK, p-ACCß, CPT1B-Cpt1b, Ppara, Nppa and Acta1. These findings suggested decreased fatty acid ß-oxidation, which was confirmed by lower oxygen consumption by Pkd1V/V isolated mitochondria using palmitoyl-CoA. Pkd1V/V hearts also presented increased oxygen consumption in response to glucose, suggesting that alternative substrates may be used to generate energy. Pkd1V/V hearts displayed a higher density of decreased-size mitochondria, a finding associated with lower MFN1, Parkin and BNIP3 expression. These derangements were correlated with increased apoptosis and inflammation but not hypertrophy. Notably, Pkd1V/V neonate cardiomyocytes also displayed shifts in oxygen consumption and p-AMPK downregulation, suggesting that, at least partially, the metabolic alterations are not induced by kidney dysfunction. Our findings reveal that disruption of polycystin-1 cleavage leads to cardiac metabolic rewiring in mice, expanding the understanding of heart dysfunction associated with Pkd1 deficiency and likely with human ADPKD.

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