Publications by authors named "S Sakthi Selva Kumar"

Purpose: Identifying therapeutic targets for Signet Ring Cell Carcinoma (SRCC) of the colon and rectum is a clinical challenge due to the lack of Patient-Derived Organoids (PDO) or Xenografts (PDX). We present a robust method to establish PDO and PDX models to answer address this unmet need. We demonstrate that these models identify novel therapeutic strategies targeting therapy resistance and peritoneal metastasis.

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Article Synopsis
  • The emergence of Next Generation Sequencing (NGS) technology has transformed clinical diagnostics, providing extensive microbiome data for personalized medicine.
  • Despite its potential, microbiome data's complexity and variability pose challenges for traditional statistical and machine learning approaches, including deep learning.
  • The paper presents a novel feature engineering technique that combines two data feature sets, significantly improving the Deep Neural Network's performance in colorectal cancer detection, raising the Area Under the Curve (AUC) from 0.800 to 0.923, thus enhancing microbiome data analysis and disease detection capabilities.
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The current review delves into the transformative role of precision medicine in addressing Colorectal Cancer [CRC], a pressing global health challenge. It examines closely signalling pathways, genetic and epigenetic modifications, and microsatellite in-stability. The primary focus is on elucidating biomarkers revolutionizing CRC diagnosis and treatment.

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We recently demonstrated polarisation differential phase contrast microscopy () as a robust, low-cost single-shot implementation of (semi)quantitative phase imaging based on differential phase microscopy. utilises a polarisation-sensitive camera to simultaneously acquire four obliquely transilluminated images from which phase images mapping spatial variation of optical path difference can be calculated. microscopy can be implemented on existing or bespoke microscopes and can utilise radiation at a wide range of visible to near infrared wavelengths and so is straightforward to integrate with fluorescence microscopy.

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Putrescine is a kind of physical diamine that is closely related to food deterioration and food quality safety. This study employs a novel fiber optic biosensor based on S-tapered and waist extension techniques, as well as localized surface plasmon resonance (LSPR), to detect putrescine accurately. The gold nanoparticles (AuNPs) are fixed on the fiber to excite LSPR.

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