Animals: 38 male Wistar rats, age 21 days (50g) (come from the CCA-UFOP) divided randomly, into 4 groups (4 animals/box): (1) sedentary rats fed with standard diet (S-SD), n = 14; (2) T rats fed with standard diet (T-SD), n = 9; (3) sedentary rats fed with high sucrose diet (S-SUD), n = 05; and (4) T rats fed with SUD (T-SUD), n = 10; marked on the tail; allocated in a room at a temperature of 24 ± 2 °C and 12-hour light/dark cycle (7 am - 7 pm). Body weight assessments: realized at weeks 1, 4, 5, 7, and 11. Food intake assessments: realized at weeks 1, 5, and 10. Approval of the study: by the Ethics Committee for Animal Use, UFOP (Protocol 45/2014). The experimental design scheme was shown in figure S2.
Diets: SD - commercial rodent feed in pellets (Nuvilab CR1 Quimtia®) and SUD as previously published [13] administered for 12 weeks from weaning.
Exercise training and evaluation of endurance capacity: Local - collective glass tank of CCA-UFOP with warm water at 28 ± 2 ºC and 45 cm depth. Adaptation period: 15 min (first day) increased by 15min each day until reaching 60 min (fourth day) (adapted from [14]). Maximal test: at the 4th and 12th (24 h after the last training section) weeks as proposed by others [15]. Fatigue point was adapted from [16]. Training: swimming for 8 weeks. The first 4 weeks didn’t use a workload, but that was added at the fifth week (60% of that obtained in maximal test) as adapted from [15].
Water Intake, Urinary Volume and Water Balance Measurements in 24h:
Rats were allocated in metabolic cages (Tecnoplast® SPA) during the 12-week period (CCA-UFOP); weighed (SF–400 scale), individually housed for a period of 24 h with free access to water and food. Measurements of urine volume and water intake were realized. Samples of urine 1.5 mL were obtained, labeled, and frozen at −20 °C. Calculation of water balance was done according to the equation:
Equation 1:
Water Balance (mL/24h) = (Water Intake [mL/24h]− Urinary Volume [mL/24h]).
Euthanasia: 48 h after the last T session. Collected materials: Adipose tissues inguinal, retroperitoneal and epididymal (IAT, RAT and EAT, respectively), blood and kidneys. Blood was centrifuged (CENTRIBIO 80-2 B scale) at 3000 rpm for 10 min to separate the plasma and then maintained at a temperature of −20 ºC. Details: Supplementary Material (Table S2).
Determination of the LI:
LI was measured according to [17]. Animals’ body mass and the nasoanal length [17], were calculated using the formula below:
Equation 2:
![](data:image/png;base64,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)
Determination of the BAI:
BAI was measured according to [19]. The EAT, IAT, and RAT were removed and weighed (BEL precision scale), and used in the following equation:
Equation 3:
![](data:image/png;base64,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)
Evaluation of RAT:
RAT analyse provide an assessment of the risk of developing cardiovascular diseases [20].
Plasma and Urine Creatinine Concentration and Urine Protein:
Samples - plasma and urine; kit - commercially available kit (Labtest, Belo Horizonte/MG, Brazil) – by colorimetric modified Jaffé approach. Calculation of creatinine clearance (CrCl):
Equation 4:
![](data:image/png;base64,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)
Proteinuria was determined with the use of pyrogallol red technique using a commercially available kit (Bioclin, Belo Horizonte, Brazil), n = 38 rats. Results were expressed in mg/dL.
Renal Histology:Collected material - right kidneys; Stage and calculation - as described by others [21, 22]. Equipment - light microscope (Leica DM5000). Analysis - Analysis and Image Processing Software Leica Qwin (Germany) [23].
Data and Statistical Analysis: Normality test - Kolmogorov-Smirnov. Statistical tests used - One-way or two-way analysis of variance (ANOVA) and Tukey’s post-test for multiple comparisons following ANOVA. Software used - GraphPad Prism 7.0 for Windows (GraphPad Software, San Diego California USA). Data were expressed as mean ± standard deviation of mean and differences between pairs of means were considered significant when the probability of type I error was less than 5% (p < 0.05). The data were analyzed blindly by the researchers involved.