Salmon oil supplementation in dogs affects the blood flow of testicular arteries.

The administration of fish oils is known to cause changes in several reproductive parameters of domestic animals. The ingestion of polyunsaturated fatty acids (PUFAs) of the omega-3 family, such as docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), has been described and correlated with changes in the semen quality, testosterone levels and male fertility. Nevertheless, few studies monitored and registered effects after ceasing supplementation. In the present study, we monitored the Doppler velocimetric and ultrasonographic parameters of nine dogs' testis for 90 days (D90) checking the effect of salmon oil supplementation, and monitoring continued for 60 days more, after ceasing supplementation (D150). Ultrasonographic evaluations comprised determining the Doppler velocimetric parameters, testicular and epididymal volume, and testicular echotexture. Peak systolic velocity (PSV) as well as final diastolic velocity (EDV) in the supratesticular arteries (STA), and marginal artery (MA) increased during the period of treatment and kept that level up to D150. There was no difference between the fish-oil supplementation period and the unsupplemented one regarding the testicular and epididymal volume and echogenicity and heterogeneity characteristics. A negative correlation was found between heterogeneity of testis and sperm production (r = -.41, p = .008). Doppler velocimetry indices were affected by the supplementation, leading to an increase in testicular blood flow.

Residual effect after salmon oil supplementation on semen quality and serum levels of testosterone in dogs.

The objective of present study was to evaluate the effects of oral supplementation of salmon oil on seminal parameters and testosterone serum levels in dogs, following also the residual effects for 60 days after treatment. Nine healthy male dogs with proven fertility, weighing between 10 and 36 kg, ageing from 2 to 11 years, of different breeds, fed diets supplemented with salmon oil at the manufacturer's recommended dosage. The parameters measured were sperm volume, motility, vigour, normal morphology and concentration, live/dead ratio, membrane viability by means of HOST test and serum testosterone levels. Evaluations occurred at baseline (D0), after 90 days of supplementation (D90) and at the end of the experiment, 60 days after supplementation cessation (D150). Results (mean ± SD) obtained at time D0, D90 and D150 were as follows: motility of 76.66% ± 13.7, 92.77 ± 4.41 and 93.0 ± 7.90 (p = .001); normal spermatozoa of 69.11% ± 24.90, 90.00% ± 5.15 and 80.66 ± 16.04 (p = .05); live/dead (%) from 64.44 ± 22.86 to 85.33 ± 8.41 (p = .001); and spermatozoa (%) with integral membrane in the membrane integrity (HOST) test ranging from 76.44 ± 20.74 to 91.22 ± 4.68 (p = .05). Serum levels of testosterone (ng/ml) increased from 5.50 ± 1.13 to 8.84 ± 1.13 at D90 (p = .003) and decreased after 2 months (D150) to 5.13 ± 1.13. In conclusion, a 90-day supplementation with salmon oil had a positive influence on semen quality and serum testosterone levels. The supplementation of omegas 3 and 6 at the ratio of 10:1 for 90 days determined an increase in concentration and motility of the sperm, and these effects were maintained for 60 days, with the only exception of testosterone levels.

Prediction of fluids volume fraction and barium sulfate scale in a multiphase system using gamma radiation and deep neural network.

In the oil industry, during the production of oil and gas, barium sulfate (BaSO4) scale may occur on the inner walls of the pipelines leading to the reduction of the internal diameter, making the fluids' passage difficult and complicating the calculation of the fluids volume fraction. This paper presents a methodology to predict volume fraction of fluids and BaSO4 scale thickness from obtaining spectra of two NaI(Tl) detectors that record the transmitted and scattered beams of gamma-rays. Theoretical models for a multiphase annular flow regime (gas-saltwater-oil-scale) were developed using MCNP6 code, which is a mathematical code based on the Monte Carlo method. The simulated data was used to train a deep neural network (DNN) to predict the volume fraction of gas, saltwater and oil, and the concentric scale thickness. A Python optimization library called Optuna was used for the hyperparameters search to design the DNN architecture. The methodology presented great results, especially for scale thickness prediction. Although the results for saltwater did not reach the same level, it was still possible to predict approximately 70% of the patterns up to 10% relative error. This achievement indicates the possibility to calculate the volume fraction of fluids and the concentric scale thickness in the offshore oil industry using gamma densitometry and deep learning models.