Publications by authors named "R C Trivedi"

Alzheimer's disease (AD) remains a major challenge in developing effective treatments due to its complex pathophysiology, including the accumulation of amyloid-beta plaques and tau tangles. Small interfering RNA (siRNA) technology offers promise for targeted gene silencing, but effective delivery to the central nervous system remains a significant obstacle. Viral vectors have emerged as potent delivery vehicles for transporting siRNA to neural tissues.

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Introduction In their routine practice, dentists frequently encounter dentinal hypersensitivity, which is caused by the pulpal nerves' increased excitability due to fluid movement in the dentinal tubules. It is treated in-office using dentin desensitizers, which reduce hypersensitivity by obstructing the open tubules or desensitizing the free nerve endings present within the tubules. However, no substance or treatment plan has ever been proven to be the gold standard for the efficient treatment of dentinal hypersensitivity.

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Context: The coexistence of tuberculosis (TB) and mental disorder presents a daunting public health challenge. Studies suggest that TB patients often experience co-morbid mental health problems, highlighting a dual burden of illness. However, due to limited research in Gujarat, we cannot draw definitive conclusions or develop targeted mental health interventions for this population.

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Head trauma from blast exposure is a growing health concern, particularly among active military personnel, and is considered the signature injury of the Gulf War. However, it remains elusive whether fundamental differences exist between blast-related Traumatic Brain Injuries (TBI) and TBI due to other mechanisms. Considering the importance of lipid metabolism associated with neuronal membrane integrity and its compromise during TBI, we sought to find changes in lipidomic profiling during blast or blunt (Stereotaxically Controlled Contusison-SCC)-mediated TBI.

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Recent advancements in technology, such as the emergence of artificial intelligence (AI) and machine learning (ML), have facilitated the progression of the biopharmaceutical industry toward the implementation of Industry 4.0. As per the guidelines set by the USFDA, process validation for biopharmaceutical production consists of three stages: process design, process qualification, and continuous process verification (CPV).

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