Publications by authors named "V Karthik B Prabhakar"

Smartphone-assisted urine analyzers estimate the urinary albumin by quantifying color changes at sensor pad of test strips. These strips yield color variations due to the total protein present in the sample, making it difficult to relate to color changes due to specific analyte. We have addressed it using a Lateral Flow Assay (LFA) device for automatic detection and quantification of urinary albumin.

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The prevalence and nature of somatic copy number alterations (CNAs) in breast epithelium and their role in tumor initiation and evolution remain poorly understood. Using single-cell DNA sequencing (49,238 cells) of epithelium from BRCA1 and BRCA2 carriers or wild-type individuals, we identified recurrent CNAs (for example, 1q-gain and 7q, 10q, 16q and 22q-loss) that are present in a rare population of cells across almost all samples (n = 28). In BRCA1/BRCA2 carriers, these occur before loss of heterozygosity (LOH) of wild-type alleles.

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Genetics plays a significant role in determining an individual's susceptibility to dental diseases, the response to dental treatments, and the overall prognosis of dental interventions. Here, the authors explore the various genetic factors affecting the prognosis of dental treatments focusing on dental caries, orthodontic treatment, oral cancer, prosthodontic treatment, periodontal disease, developmental disorders, pharmacogenetics, and genetic predisposition to faster wound healing. Understanding the genetic underpinnings of dental health can help personalize treatment plans, predict outcomes, and improve the overall quality of dental care.

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Article Synopsis
  • The study introduces MOSBY, a new model that uses deep neural networks to analyze H&E stained images for finding clinically relevant spatial biomarkers in cancer.
  • MOSBY employs advanced techniques to correlate image features with genetic information and has shown strong predictive power for patient survival beyond traditional gene expression analyses.
  • The model successfully identified specific spatial features linked to cancer risks and outcomes, highlighting its potential in enhancing cancer research and aiding clinical decisions.
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