Effects of cryolipolysis with adiposity plates located with the Crioplace concept in women

BACKGROUND

Cryolipolysis with plates is a method of applying cooling without a vacuum system, which can be used in regions with less chance of forming a "crease."

OBJECTIVE

To investigate the effects of cryolipolysis using a plate-shaped applicator (Crioplac) in the treatment of fat.

MATERIALS AND METHODS

This is an experimental study in which women aged 25 to 45 years with adiposity located in the abdomen participated. Two applications of 75 min were made, using 04 plates in the abdomen regions, with -4 degree C being programmed as a temperature parameter. Anthropometric and ultrasound assessments were performed, and a satisfaction questionnaire on the validated treatment was conducted. The reassessments were performed 30 and 60 days after the first intervention.

RESULTS

A reduction in adiposity was observed in the measurements of perimetry, plicometry and abdominal ultrasound (p<0.05). It was found that about 62.5% of the volunteers reported an improvement in water retention, about 62.5% reported the presence of loose clothing, and 31.3% reported satisfaction with the results obtained. It was observed that 18.5% of the volunteers reported that the treatment was excellent.

CONCLUSION

The Crioplace method proved to be effective in reducing adiposity, with a high clinical satisfaction with the reduction in body measurements.

Human Immunoglobulin G Adsorption in Epoxy Chitosan/Alginate Adsorbents: Evaluation of Isotherms by Artificial Neural Networks

This work aimed to evaluate the interaction of human IgG in non-conventional adsorbents based on chitosan and alginate in the absence and presence of Reactive Green, Reactive Blue and Cibacron Blue immobilized as ligands. The adsorption was evaluated at 277, 288, 298 and 310 K using sodium phosphate buffer, pH 7.6, at 25 mmol L−1. The highest adsorption capacity was observed in the experiments performed with no immobilized dye, although all showed adsorption capacity higher than 120 mg g−1. Data modeling was done using Langmuir, Langmuir-Freundlich and Temkin classical nonlinear models, and artificial neural networks (ANN) for comparison. According to the parameters obtained, a possible adsorption in multilayers was observed due to protein-adsorbent and protein-protein interactions, concluding that IgG adsorption process is favorable and spontaneous. Using an ANN structure with 3 hidden neurons (single hidden layer), the MSE (RMSE) for training, test and validation were 13.698 (3.701), 11.206 (3.347) and 7.632 (2.763), respectively, achieving correlation coefficients of 0.999 in all steps. ANN modeling proved to be effective in predicting the adsorption isotherms in addition to overcoming the difficulties caused by experimental errors and/or arising from adsorption phenomenology.