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Dayananda,Satish Kulkarni,Pala Rama Mohana Rao,Obalaiah Gopinath,dara Murthy Nirmal Kumar 한국잠사학회 2011 International Journal of Industrial Entomology Vol.23 No.2
An attempt was made to assess the potentiality of bivoltine double hybrids under simulated conditions of farmers to identify the suitable bivoltine double hybrid combination. Four bivoltine double hybrids developed at Central Sericultural Research and Training Institute (CSRTI), Mysore along with popular single hybrid, CSR2 x CSR4 as control was assessed for economic traits. The rearing results showed significant improvement of 20-24% in fecundity of the double hybrids studied over single hybrid. Among the double hybrids, [D7 ×S5]×[D13×S1] recorded significantly higher survival (89.58 %), cocoon yield (76.328 kg/50,000 eggs), cocoon price (Rs. 180.87/kg) and lower cocoon leaf ratio of 1: 21.80. The performance of the reeling traits were also found significantly superior in [D7×S5]×[D13×S1] with higher filament length (1100 m), reelability (88%), raw silk (18.55%) and neatness (92 points) compared to CSR2 × CSR4 and other double hybrids evaluated. Besides, the cocoons of [D7×S5]×[D13×S1] exhibit uniformity in size with a standard deviation of < 8. Overall data indicated the superiority of [D7×S5] × [D13×S1] compared to the other hybrids evaluated and it has profound influence in expressing the full potentiality in the field.
Dayananda, Dayananda,Kulkarni, Satish,Rao, Pala Rama Mohana,Gopinath, Obalaiah,Kumar, Sundara Murthy Nirmal Korean Society of Sericultural Science 2011 International Journal of Industrial Entomology Vol.23 No.2
An attempt was made to assess the potentiality of bivoltine double hybrids under simulated conditions of farmers to identify the suitable bivoltine double hybrid combination. Four bivoltine double hybrids developed at Central Sericultural Research and Training Institute (CSRTI), Mysore along with popular single hybrid, $CSR2{\times}CSR4$ as control was assessed for economic traits. The rearing results showed significant improvement of 20-24% in fecundity of the double hybrids studied over single hybrid. Among the double hybrids, $[D7{\times}S5]{\times}[D13{\times}S1]$ recorded significantly higher survival (89.58 %), cocoon yield (76.328 kg/ 50,000 eggs), cocoon price (Rs. 180.87/kg) and lower cocoon leaf ratio of 1: 21.80. The performance of the reeling traits were also found significantly superior in $[D7{\times}S5]{\times}[D13{\times}S1]$ with higher filament length (1100 m), reelability (88%), raw silk (18.55%) and neatness (92 points) compared to $CSR2{\times}CSR4$ and other double hybrids evaluated. Besides, the cocoons of $[D7{\times}S5]{\times}[D13{\times}S1]$ exhibit uniformity in size with a standard deviation of < 8. Overall data indicated the superiority of $[D7{\times}S5]{\times}[D13{\times}S1]$ compared to the other hybrids evaluated and it has profound influence in expressing the full potentiality in the field.
Dayananda, Kasala,Kim, Min-Sang,Kim, Bong-Sup,Lee, Doo-Sung The Polymer Society of Korea 2007 Macromolecular Research Vol.15 No.4
Block copolymer micelles are generally formed via the self-assembly of amphiphilic block copolymers in an aqueous medium. The hydrophilic and hydrophobic blocks form shell and core micelles, respectively. The block copolymers of methoxy poly(ethylene glycol) (MPEG)-b-poly(2-diisopropylamino)ethyl methacrylate (PDPA) were synthesized via atom transfer radical polymerization, with the macro initiator synthesized by the coupling of 2-bromoisobutyryl bromide with MPEG in the presence of a triethyl amine base catalyst. The atom transfer radical polymerization of 2-diisopropylamino)ethyl methacrylate was performed in conjunction with an N,N,N',N",N"-pentamethyl-diethylenetriamine/copper bromide catalyst system, in DMF, at $70^{\circ}C$. The pH induced micellization/demicellization was studied using fluorescence, with a pyrene probe. Furthermore, the pH dependent micellization was confirmed using the microviscosity method, with a dipyme fluorescence probe. The pH dependant micelle size distribution was studied using dynamic light scattering. The characterization of the synthesized polymers was established using gel permeation chromatography and from the $^1H-nuclear$ magnetic resonance spectroscopy.
Utilizing adenovirus vectors for gene delivery in cancer
Kasala, Dayananda,Choi, Joung-Woo,Kim, Sung Wan,Yun, Chae-Ok Informa UK, Ltd. 2014 Expert opinion on drug delivery Vol.11 No.3
<P><B><I>Introduction:</I></B> Adenovirus (Ad) is a promising candidate vector for cancer gene therapy because of its unique characteristics, which include efficient infection, high loading capacity and lack of insertional mutagenesis. However, systemic administration of Ad is hampered by the host's immune response, hepatocytoxicity, short half-life of the vector and low accumulation at the target site. For these reasons, clinical applications of Ad are currently restricted.</P><P><B><I>Areas covered:</I></B> In this review, we focus on recent developments in Ad nanocomplex systems that improve the transduction and targeting efficacy of Ad vectors in cancer gene therapy. We discuss the development of different Ad delivery systems, including surface modification of Ad, smart Ad/nanohybrid systems and hydrogels for sustained release of Ad.</P><P><B><I>Expert opinion:</I></B> The fusion of bioengineering and biopharmaceutical technologies can provide solutions to the obstacles encountered during systemic delivery of Ads. The <I>in vivo</I> transgene expression efficiency of Ad nanocomplex systems is typically high, and animal tumor models demonstrate that systemic administration of these Ad complexes can arrest tumor growth. However, further optimization of these smart Ad nanocomplex systems is needed to increase their effectiveness and safety for clinical application in cancer gene therapy.</P>
Multi-scale U-SegNet architecture with cascaded dilated convolutions for brain MRI Segmentation
Chaitra Dayananda(챠이트라 다야난다),Bumshik Lee(이범식) 한국방송·미디어공학회 2020 한국방송공학회 학술발표대회 논문집 Vol.2020 No.11
Automatic segmentation of brain tissues such as WM, GM, and CSF from brain MRI scans is helpful for the diagnosis of many neurological disorders. Accurate segmentaion of these brain structures is a very challenging task due to low tissue contrast, bias filed, and partial volume effects. With the aim to improve brain MRI segmentation accuracy, we propose an end-to-end convolutional based U-SegNet architecture designed with multi-scale kernels, which includes cascaded dilated convolutions for the task of brain MRI segmentation. The multi-scale convolution kernels are designed to extract abundant semantic features and capture context information at different scales. Further, the cascaded dilated convolution scheme helps to alleviated the vanishing gradient problem in the proposed model. Experimental outcomes indicate that the proposed architecture is superior to the traditional deep-learning methods such as Segnet, U-net, and U-Segnet and achieves high performance with an average DSC of 93% and 86% of JI value for brain MRI segmentation.