Digital Library: Browsing DSpace

A Visualization Technique for Mapping the Velocity of Raising Fibers Production in an Electrostatic Field 1

A Vital Power Resource for Southeast Florida 18 A modernization project at a gas-fired power plant serving an area near Fort Lauderdale, Florida, has provided needed upgrades to the facility, and improved the reliability and resilience of the area's electricity supply. 1

A watermarking-based asymmetric cryptosystem using gyrator transform, QZ modulation, and fractional vortex toroidal phase mask 1

A Wavelet Approach for Automatically Detecting DDoS Attacks 1

A Word to Mother: Realisation of Reading in Between Lines 1

A world of just online money: The future is already here 1

a-Aminoisobutyric acid: A single amino acid chain inverter 1

A-connected fibrewise topological spaces 1

A. Kapoor· M. Raghunathan . P. Kumar· S.C. Tripathi • S. Haque· D.B. Pal 7. anotechnology Driven Lipid and Metalloid Based Formulations Targeting Blood-Brain Barrier (3B) for Brain Tumor 2

Aadhi Malayalam 1

Aatmanirbhar India - Manufacturing locally 1

Aatmanirbhar R&D – Allocation from Universal Service Obligation Fund (USOF) 1

ABB launches power solutions for datacentres 1

ABD-ELHAMED:Applications on soft somewhere dense sets 1

Abhilasha Jindagi Kumari-Englisg Parameters Indira Dangi Tr. MahendraJagannath Dutte-Hindi 1

Abhivyakti 1

About Implementation of the International Standards and Limits of.Reception of Foreign Experience to the Sphere of Execution of the Punishment in the Republic of Kazakhstan. 1

Abstract Background: Pancreatic Ductal Adenocarcinoma (PDAC) is a cancer of the exocrine pancreas and 5-year survival rates remain constant at 7%. Along with PDAC, Periampullary Adenocarcinoma (PAC) accounts for 0.5–2% of all gastrointestinal malignancies. Genomic observations were well concluded for PDAC and PACs in western countries but no reports are available from India till now. Methods: Targeted Next Generation Sequencing were performed in 8 (5 PDAC and 3 PAC) tumour normal pairs, using a panel of 412 cancer related genes. Primary findings were replicated in 85 tumour samples (31 PDAC and 54 PAC) using the Sanger sequencing. Mutations were also validated by ASPCR, RFLP, and Ion Torrent sequencing. IHC along with molecular dynamics and docking studies were performed for the p.A138V mutant of TP53. Key polymorphisms at TP53 and its associated genes were genotyped by PCR-RFLP method and association with somatic mutations were evaluated. All survival analysis was done using the Kaplan-Meier survival method which revealed that the survival rates varied significantly depending on the somatic mutations the patients harboured. Results: Among the total 114 detected somatic mutations, TP53 was the most frequently mutated (41%) gene, followed by KRAS, SMAD4, CTNNB1, and ERBB3. We identified a novel hotspot TP53 mutation (p.A138V, in 17% of all patients). Low frequency of KRAS mutation (33%) was detected in these samples compared to patients from Western counties. Molecular Dynamics (MD) simulation and DNA-protein docking analysis predicted p.A138V to have oncogenic characteristics. Patients with p.A138V mutation showed poorer overall survival (p = 0.01). So, our finding highlights elevated prevalence of the p53p.A138V somatic mutation in PDAC and pancreatobiliary PAC patients. Conclusion: Detection of p.A138V somatic variant in TP53 might serve as a prognostic marker to classify patients. It might also have a role in determining treatment regimes. In addition, low frequency of KRAS hotspot mutation mostly in Indian PDAC patient cohort indicates presence of other early drivers in malignant transformation. Keywords: Pancreatic ductal adenocarcinoma, Periampullary adenocarcinoma, Novel somatic hotspot mutation, Frequently mutated genes, Next generation sequencing 1

Abstract Oralism 1

Abstract-Diabetic Maculopathy (DME) is the serious impediments of diabetes, which may cause permanent blindness unless timely detected. Vision impairment because of diabetes is substantially avoidable with well-timed screening and intervention at primary stages. Presence of most primitive and distinctive signs on the retinal surface is micro-aneurysm and haemorrhage, signify as dark spots and hard and soft exudates signifies as bright lesions. Hence, recognition of all these bright lesions is the first step of automated recognition of DME. In this paper, we present a multi class, multi-layer stacked ensemble classifier-based model with four base learners and one meta-learner for improved exudates (EXs) classification accuracy and maculopathy gradation system. The proposed system involves pre-processing, Scale-Space Extrema Detection(SSED) based extraction of clinically significant bright lesions, shape, colour, intensity, and statistical functions-based feature set creation, Minimum Redundancy-Maximum Relevance (mRMR) feature selection, stacking classifier with Bayesian optimization (BO) for hyper-parameter tuning and severity gradation. Information of location of all types of exudates is accounted for to provide the level of severity of DME. At both the image and lesions levels, the proposed system’s quan- titative assessment is carried out utilising publicly available databases. When compared to other state-of-the-art methodologies, our system’s results have achieved competitive performance in three and two class exudates classification and DME gradation. 1

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