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Related Concept Videos

Response Surface Methodology01:16

Response Surface Methodology

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Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
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Drug Biotransformation: Overview01:16

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Pharmaceutical substances known as xenobiotics are predominantly lipophilic and nonionized. This enables them to permeate lipid bilayers, such as cell membranes, and interact with intracellular target receptors. Lipophilic drugs have an advantage in crossing biological barriers and reaching their intended sites of action. However, lipophilic drugs often have a restricted capacity for renal expulsion or elimination from the body. When these drugs enter the kidneys and undergo glomerular...
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Drug Biotransformation: Overview01:28

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Biotransformation, also known as drug metabolism, is a vital physiological process that chemically alters drugs, facilitating their elimination from the body and terminating their action. This process involves two main phases: phase I and phase II reactions. Phase I reactions, including oxidation, reduction, and hydrolysis, introduce or unmask polar functional groups on the drug molecule, thereby increasing its water solubility. By enhancing water solubility, the drug becomes more hydrophilic...
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Factors Affecting Drug Biotransformation: Biological01:19

Factors Affecting Drug Biotransformation: Biological

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Biological factors significantly impact drug metabolism, influencing drug clearance, efficacy, and potential toxicity.
Species differences: Variations in enzyme systems across species can cause disparities in drug metabolism. For instance, humans may metabolize certain drugs faster than rodents, altering therapeutic effects.
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Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

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Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
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Factors Affecting Drug Biotransformation: Physicochemical and Chemical Properties of Drugs01:21

Factors Affecting Drug Biotransformation: Physicochemical and Chemical Properties of Drugs

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A drug's physicochemical properties fundamentally influence its metabolism. For instance, a drug's molecular size and shape critically determine its interaction with enzymes and transporters — larger drugs may face difficulty reaching enzyme active sites, altering their metabolic pathways. The pKa of a drug, which establishes its ionization state, can impact its solubility and absorption, thereby influencing metabolism.
The drug's acidity or basicity is essential in...
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Related Experiment Video

Updated: Jan 23, 2026

Author Spotlight: Optimization of Processing Technology for Tiebangchui with Zanba Based on CRITIC Combined with Box-Behnken Response Surface Method
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Arsenite biotransformation by Rhodococcus sp.: Characterization, optimization using response surface methodology and

Nisha Kumari1, Anu Rana1, Sheeja Jagadevan1

  • 1Department of Environmental Science and Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, Jharkhand 826004, India.

The Science of the Total Environment
|June 20, 2019
PubMed
Summary

This study explored arsenic resistance and biotransformation in three bacteria for groundwater bioremediation. Rhodococcus sp. showed significant potential, removing 48.34% of arsenic (As III) in 6 hours under optimized conditions.

Keywords:
ArsenicBiosorptionMicrobial remediation mechanismMinimum inhibitory concentrationOxidationResponse surface methodology

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Area of Science:

  • Environmental Microbiology
  • Bioremediation
  • Water Quality

Background:

  • Arsenic contamination of groundwater poses a significant global health risk.
  • Bioremediation using bacteria offers a sustainable solution for arsenic removal.

Purpose of the Study:

  • To investigate arsenic resistance and biotransformation capabilities of Bacillus arsenicus, Rhodococcus sp., and Alcaligenes faecalis.
  • To evaluate Rhodococcus sp. as a candidate for groundwater bioremediation.
  • To optimize parameters for arsenic removal using response surface methodology.

Main Methods:

  • Assessing bacterial tolerance to pH and arsenite (MIC values).
  • Qualitative confirmation of arsenite bio-oxidation to arsenate.
  • Cellular morphology analysis using scanning electron microscopy and Atomic Force Microscopy.
  • Optimization of arsenic removal using response surface methodology.

Main Results:

  • All three bacteria demonstrated the ability to convert arsenite to arsenate.
  • Arsenite tolerance varied, with Rhodococcus sp. showing the highest MIC (12 mM).
  • Optimized conditions led to 48.34% removal of As (III) in 6 hours, with complete removal in 48 hours.
  • Arsenic removal occurred via bioaccumulation, biotransformation, and biosorption.

Conclusions:

  • Rhodococcus sp. is a promising candidate for arsenic bioremediation.
  • Understanding bacterial arsenic tolerance and detoxification mechanisms is crucial for in-situ bioremediation programs.
  • This study provides the first evidence of Rhodococcus sp. arsenic removal in synthetic groundwater using whole-cell assays.