A comparison of three computer models for prediction of dose in acute amitriptyline overdose.

Comparison of activated charcoal and sodium polystyrene sulfonate resin efficiency on reduction of amitriptyline oral absorption in rat as treatments for overdose and toxicities

Objective(s): Comparative in vivo studies were carried out to determine the adsorption characteristics of amitriptyline (AMT) on activated charcoal (AC) and sodium polystyrene sulfonate (SPS). AC has been long used as gastric decontamination agent for tricyclic antidepressants and SPS has showed to be highly effective on in-vitro drugs adsorption. Materials and Methods: Sprague-Dawley male rats...

Commentary: Comparison of activated charcoal and sodium polystyrene sulfonate resin efficiency on reduction of amitriptyline oral absorption in rat as treatments for overdose and toxicities

COMPARISON OF ANTIULCER EFFECTS OF TRICYCLIC ANTIDEPRESSANTS WITH CIMETIDINE AND OMEPRAZOLE IN RATS

The antiulcer effects of different tricyclic antidepressants (trimipramine, doxepin, imipramine, and amitriptyline) in comparison with those of cimetidine, pirenzepine and omeprazole were investigated in male rats with acute gastric ulcer. Acute gastric ulcer was induced by oral administration of O. 6N HCl solution, 1 mL/rat. Pretreatment of animals with doxepin, trimipramine, amitriptylin...

Thermal conductivity of Water-based nanofluids: Prediction and comparison of models using machine learning

Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...

Thermal conductivity of Water-based nanofluids: Prediction and comparison of models using machine learning

Statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. This paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. The thermal conductivity of nanofluids increases with the volume fraction and temperature. Machine learni...