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Articles by R. Suresh Kumar
Total Records ( 2 ) for R. Suresh Kumar
  M. Kausar Neyaz , R. Suresh Kumar , Showket Hussain , Samar H. Naqvi , Indu Kohaar , Nisha Thakur , Veena Kashyap , Bhudev C. Das , Syed Akhtar Husain and Mausumi Bharadwaj
  As current evidence suggests the involvement of epigenetic modification of tumour suppressor genes in human cancer, we investigated the aberrant promoter methylation of FHIT and RASSF1A genes in human papillomavirus (HPV)-mediated cervical cancer in Indian women. We analysed 60 cervical cancer tissue biopsies of different clinical stage and histological grading and 23 healthy control samples with normal cervical cytology. Methylation-specific polymerase chain reaction (MSP) was performed to analyse the methylation status of FHIT and RASSF1A genes and confirmed by sequencing. Both patients and controls were screened for HPV infection and 98% of the HPV-infected cases showed positivity for HPV type 16. Aberrant promoter methylation of the FHIT gene was found in 28.3% (17/60) of cases and of the RASSF1A gene in 35.0% (21/60) of cases; promoter methylation of both the genes was found in 13.3% (8/60) of cervical cancer cases. Methylation was significantly (p<0.01) associated with the cervical cancer cases compared with controls. None of the 23 controls was found to be methylated in either of these genes. This is the first study indicating a correlation between the promoter methylation of FHIT and RASSF1A genes and the clinical stage and histological grading of cervical carcinoma in Indian women. Future studies are underway to examine the practical implications of these findings for use as a biomarker.
  R. Suresh Kumar and P. Manimegalai
  Bio-medical signal processing is one of the most important techniques of multichannel sensor network and it has a substantial concentration in medical application. However, the real time and recorded signals in multisensory instruments contains different and huge amount of noise and great work has been completed in developing most favorable structures for estimating the signal source from the noisy signal in multichannel observations. Methods have been developed to obtain the optimal linear estimation of the output signal through the Wide-Sense-Stationary (WSS) process with the help of time invariant filters. In this process, the input signal and the noise signal are assumed to achieve the linear output signal. During the process, the non-stationary signals arise in the bio-medical signal processing in addition to it there is no effective structure to deal with them. Wavelets transform has been proved to be the efficient tool for handling the non-stationary signals but wavelet provide any possible way to approach multichannel signal processing. Based on the basic structure of linear estimation of non-stationary multichannel data and statistical models of spatial signal coherence acquire through the wavelet transform in multichannel estimation. The above methods can be used for Electroencephalography (EEG) signal denoising through the original signal and then implement the noise reduction technique in VLSI to evaluate their parameters such as area utilization, power dissipation and computation time.
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