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INTRODUCTION:
Cysteine is one of the “biogenic” amino acids, structurally it belongs sulfur-containing amino acids, the sulfur atom in the side chain is involved in the formation of a reactive sulfhydryl (–SH) group.
The R groups in these amino acids are more hydrophilic than the analogous amino acids bearing a nonpolar side chain. L-cysteine plays a multipurpose role in the biological system, from forming a structural component of both proteins and the precursor of the radical scavenger GHS, to playing a protective role against several diseases.
Cysteine is the building block of about 2% of proteins, and plays a key role in the biosynthesis of lipids and cell membranes. It is also involved in the synthesis of taurine, which is an imperative factor in conducting electrical nerve impulses in the digestive and vascular systems.
L-cysteine is commonly given intravenously to patients with acetaminophen poisoning to prevent kidney and liver damage.
When given in its precursor form as NAC, cysteine has a protective role in several disorders like angina pectoris, chronic bronchitis, COPD, inflammation, asthma, cystic fibrosis, emphysema, and in doing so by boosting the levels of GHS it may also prevent lung damage.1-4
Introduction to Design of Experiments (DoE):
DOE is an essential piece of the reliability program pie. It plays an important role in Design for Reliability (DFR) programs, allowing the simultaneous investigation of the effects of various factors and thereby facilitating design optimization.
DOE helps in: Identifying relationships between cause and effect. Providing an understanding of interactions among causative factors. Determining the levels at which to set the controllable factors (product dimension, alternative material, alternative designs, etc.) in order to optimize reliability. Minimizing experimental error (noise). Improving the robustness of the design or process to variation.
With modern technological advances, products and processes are becoming exceedingly complicated. As the cost of experimentation rises rapidly, it is becoming impossible for the analyst, who is already constrained by resources and time, to investigate the numerous factors that affect these complex processes using trial and error methods. Instead, a technique is needed that identifies the "vital few" factors in the most efficient manner and then directs the process to its best setting to meet the ever-increasing demand for improved quality and increased productivity. Designed experiments are...