Robotics & Machine Learning Daily News2024,Issue(Jun.14) :106-107.

Researchers at University of Calabria Have Reported New Data on Machine Learning (Machine Learning-based Prediction of Reduction Potentials for Ptiv Complexes)

卡拉布里亚大学的研究人员报告了机器学习(基于机器学习的Ptiv复合物还原电位预测)的新数据

Robotics & Machine Learning Daily News2024,Issue(Jun.14) :106-107.

Researchers at University of Calabria Have Reported New Data on Machine Learning (Machine Learning-based Prediction of Reduction Potentials for Ptiv Complexes)

卡拉布里亚大学的研究人员报告了机器学习(基于机器学习的Ptiv复合物还原电位预测)的新数据

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摘要

由一名新闻记者兼机器人与机器学习的工作人员新闻编辑每日新闻-关于机器学习的详细数据已经呈现。根据NewsRx记者在意大利Arcavacata di Rende的新闻报道,研究表明,“使用六配位Pt-IV复合物作为惰性前药,可以克服临床批准的Pt-II复合物的一些众所周知的缺点,这些前药在细胞还原剂还原后释放相应的四配位活性Pt-II物种。因此,Pt-IV前药作用机制的关键因素是它们的减少趋势,当所涉及的机构为外球型时,用还原电位值来测量。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news reporting originating in Arcavacata di Rende, Italy, by NewsRx journalists, research stated, “Some of the well-known drawback s of clinically approved Pt-II complexes can be overcome using six-coordinate Pt -IV complexes as inert prodrugs, which release the corresponding four-coordinate active Pt-II species upon reduction by cellular reducing agents. Therefore, the key factor of Pt-IV prodrug mechanism of action is their tendency to be reduced which, when the involved mechanism is of outer-sphere type, is measured by the value of the reduction potential.”

Key words

Arcavacata di Rende/Italy/Europe/Chemicals/Cyborgs/Electrochemicals/Emerging Technologies/Machine Learning/University of Calabria

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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