1. MicroRNA21 and the various types of myeloid leukemia
Senthil Kumar S R, Biruntha M, Sivakurunathan P, Karthigeyan M, Pethanen Sivakumare, Durairaj Sekar, Mani Panagal, Vincent Gopinathe Cancer Gene Ther . 2018 Aug;25(7-8):161-166. doi: 10.1038/s41417-018-0025-2.
Myeloid leukemia (ML) is heterogeneous cancer classified by abnormal growth of myeloid cells due to genetic aberrations and mutations. It is generally categorized by clonal disorders of hematopoietic stem cells and differentiation. The molecular mechanism behind the myeloid malignancies is not yet known, but recent sequencing analysis reveals all the mutated factors. As we know that there is currently no compromise on therapy for such types of malignancies and at the present painful process like chemotherapy and radiation therapy are not effective for the treatment of ML, so there is an urgent need to develop a non-invasive biomarker for different types of ML. MicroRNAs (MiRNAs) is a small non-coding RNAs that have been involved in a wide range of biological function and it is the main cause of the manifestation of many diseases. Among the reported MiRNAs, MIR-21 is considered to be an important MiRNA, which is frequently elevated in many types of types of cancer, suggesting that it plays an important role in cancer progressions. So far, there is no paper that signifies the role of miR-21 in all types of ML and the number of studies on the different category of ML is sparse. Therefore, the main thrust of this paper is to provide an overview of the current clinical evidence and significance of miR-21 in ML. It was found that MiR-21 was found to be normally upregulated in all types of ML, however, we summarize the important research findings surrounding the role of miR-21 in different types of ML.
2. Characterization of surface-modified natural cellulosic fiber extracted from the root of Ficus religiosa tree
Ravindran D, Sundara Bharathi S R, Indran S, Suganya Priyadharshini G, Arul Marcel Moshi A Int J Biol Macromol . 2020 Aug 1;156:997-1006. doi: 10.1016/j.ijbiomac.2020.04.117.
The foremost intention of this work is to test the suitability of the Ficus religiosa Root Fiber (FRRF) as the better reinforcement for the natural fiber-reinforced composite structures. In the current work, the attempts have been made with the view of improving the physical, thermal, chemical, surface, and crystalline properties of FRRF employing 5 wt% of NaOH solution. Five samples of FRRF have been prepared by soaking the raw fiber in the alkali solution under different soaking times. The thermogravimetric analysis results reveal that the alkali-treated FRRF soaked for 60 min holds a maximum range of thermal stability (improved by 9.54%); in turn, the remaining analyses have been carried out with that fiber samples. The increased quantity of cellulose contents was witnessed over the surface of treated FRRF. The improvement in the CI from 42.92-48.64% was noted as the result of X-Ray Diffraction test. The morphology study results ensured that the surface of the treated FRRF became so rough comparably, which confirms the removal of unwanted wax and impurities on the fiber surface. All the above observations validated that the proposed fiber is suitable to prepare the composite structures after the optimal alkali treatment.
3. Efficient Denoising Framework for Mammogram Images with a New Impulse Detector and Non-Local Means
Sannasi Chakravarthy S R, Harikumar Rajaguru Asian Pac J Cancer Prev . 2020 Jan 1;21(1):179-183. doi: 10.31557/APJCP.2020.21.1.179.
Objective:The survival rates of breast cancer are increasing as screening and diagnosis improve. The removal of noise is revealed to be a significant step for automatic - computer aided detection (CAD) of microcalcification in digital mammography.Methods:In this paper, a combined approach for eradicating impulse noise from digital mammograms is proposed. The process is achieved in two stages, detection of noise followed by filtering of noise. The detection of noise is carried out by using Modified Robust Outlyingness Ratio (mROR) trailed by an extended NL (Non-Local)-means filter for filtering mechanism.Results:According to the value of mROR, all pixels in mammogram images are divided into four distinct groups. In each cluster, many decision rules are then applied for detecting the impulse noise. Filtering is done with NL-means filter by providing a reference mammogram image.Conclusion:The comparative analysis and evaluated results are compared with some existing filters which indicate that the proposed structure outperforms the analysed result of others.
