OnionMHC: a deep learning model for peptide - HLA-A*02:01 binding predictions

The peptide binding to Major Histocompatibility Complex (MHC) proteins is an important step in the antigen-presentation pathway. Thus, predicting the binding potential of peptides with MHC is essential for the design of peptide-based therapeutics. Most of the available machine learning-based models predict the peptide-MHC binding based on the sequence of amino acids alone. Given the importance of structural information in determining the stability of the complex, here we have utilized both the complex structure and the peptide sequence features to predict the binding affinity of peptides to human receptor HLA-A*02:01. To our knowledge, no such model has been developed for the human HLA receptor before that incorporates both structure and sequence-based features. We have applied machine learning techniques through the natural language processing (NLP) and convolutional neural network to design a model that performs comparably with the existing state-of-the-art models. Our model shows that the information from both sequence and structure domains results in enhanced performance in the binding prediction compared to the information from one domain alone. The testing results in 18 weekly benchmark datasets provided by the Immune Epitope Database (IEDB) as well as experimentally validated peptides from the whole-exome sequencing analysis of the breast cancer patients indicate that our model has achieved state-of-the-art performance. We have developed a deep-learning model (OnionMHC) that incorporates both structure as well as sequence-based features to predict the binding affinity of peptides with human receptor HLA-A*02:01. The model demonstrates state-of-the-art performance on the IEDB benchmark dataset as well as the experimentally validated peptides. The model can be used in the screening of potential neo-epitopes for the development of cancer vaccines or designing peptides for peptide-based therapeutics.Doctor of Philosoph

Integrated scheduling and vehicle routing at cross-dock distribution centre: a simulated annealing approach

Cross-docking is a popular strategy for distributing products with short shelf-life that must be delivered within their pre-specified time windows to customers. Cross-docks receive shipments from suppliers which are stored in a temporary storage area before being consolidated and transferred to outbound vehicles for delivery to customers. This research tackles the joint problems of vehicle routing and scheduling at the cross-dock, along with product consolidation, by means of a mixed-integer programming model with the objective of minimising the total cost of operations. Our approach does not pre-cluster customers into zones and allows vehicles to deliver in less than truckload. To solve real-life sized problems, we develop simulated annealing algorithms which can solve the instances in 2-3 hours, achieving close to optimal solutions, making them suitable for decision support at cross-dock distribution centres, which process dozens of vehicles and deliver to hundreds of customers daily.Submitted/Accepted versio

nAlysis: A hard disk diagnostic tool

The goal of this project was to build a hard drive diagnostic tool which allows the user to execute ATA commands and interpret the results. The application can be used as a disk health monitoring utility and has scripting capabilities that can automate quality assurance processes. The functionality is wrapped inside a library of different modules with an API to allow users to write system specific implementations. The user interfacing is done via a command line interface

Consumer Rating Analysis and Recommendation Methodology Using Machine Learning

In the era of online shopping, Online platforms are loaded with online shopping. Nowadays, online shopping has become a trend and a necessity of fast delivery to home. Online platforms sites like Twitter, in this new time, is stacked with product marketing and feedback information. One of the most broadly utilized miniatures writing for a blog webpage, Twitter, is the place where individuals share their thoughts as tweets and thusly it becomes perhaps the best hotspot for nostalgic investigation of feedback of products. Assessments can be generally assembled into three classifications for positive, negative and neutral and the method involved with dissecting contrasts of conclusions and gathering them in this large number of classes is done by data modeling. Data mining is fundamentally utilized to uncover applicable data from tweets information particularly from the informal communication destinations. A Model is also designed with Micro blogging solution for the evaluation of reviews. In many social sites there are many online marketing recommendation may be done with recommendation post from the product consumer which would initiate the growth of any business and also eliminate the need of any raw data for analysis of the consumer rating. In the model, we propose a methodology two methodology, one is analysis from social sites like Facebook and other social platform and another is recommendation method which decrease the marketing strategy required for the consumer to consumer connection. A testing recommendation helps to remove not required information from the product consumer to product consumer communication and this helps for the product recommendation analysis to be done properly. © 2022 IEEE

Study to assess the functional outcome of Intramedullary Titanium Elastic Nails in the Paediatric Lower Limb Long Bone Fractures

  Introduction: Femoral and tibial shaft fractures add up to less than 2% of all pediatric fractures, the preferred management has remained a real challenge to the orthopaedic fraternity. Upto the recent past conservative treatment was the method of choice for the treatment of shaft fractures in young adolescents and children. In order to avoid the effects of long immobilization, to decrease the loss of schooling and for finer post operative care, the operative approach has been popular for the last twenty years. Material and Methods: This study was conducted in department of orthopaedics, Rohilkhand medical college and hospital after seeking clearance from institutional ethical committee. The aim is to assess the functional outcome of intramedullary titanium elastic nails in paediatric lower limb long bones fractures. The patients attending the OPD and emergency department diagnosed with the fracture of femur and tibia was admitted for the study. This one year study was conducted from November 2018 to October 2019. A total of 30 children with diaphyseal fracture femur and tibia were enrolled in the study. When the patient arrives, a detailed history was gathered from the parents and/or attendants about age, sex, mode of injury and duration. Patients were assessed for associated injuries. Clinical and local examination was then performed following surgery. Results: The results were assessed as per criteria adopted by Flynn et al. Total of 20 patients had excellent outcome. There were no poor results. All the patients of the present series were able to squat and sit cross-legged at final follow up which was statistically significant. Conclusion: Titanium elastic nailing system technique, through the theory of two opposing balancing forces gives good firmness at the fracture site to allow early mobilization, it provides a biological environment that amplifies both quantity of callus formation and fracture healing.It may be considered to be a physiological method of treatment and it may prove to be the ideal implant to treat many paediatric femoral and tibial fractures. The technique is relatively simple, minimally invasive and healing occurs in extremely natural way with adequate mass of callus

Sclerotherapy by Pilodocanol as the new treatment modality for aneurysmal bone cysts

Objective: To ascertain the effectiveness of percutaneous sclerotherapy in the management of aneurysmal bone cyst. Material and method: Ten patients with aneurysmal bone cyst were treated by the percutaneous approach with pilodocanol in our institution Rohilkhand medical college and hospital Bareilly, from May 2018 to September 2020. The cysts were present in the lower limb. Under general anesthesia percutaneous sclerotherapy was done using computed tomography and fluoroscopy. 12 to 24 months (avg18 months) follow up for clinical and imaging was done and the outcomes were tabulated. Results: In five patients therapy was repeated 2-5 times. No failure was found in our series. There were some complications which included: local skin colour change, small blister and discharge. All patients got relieved. Conclusion: Percutaneous sclerotherapy of aneurysmal bone cyst with Polidocanol is fruitful and harmless. Thus a substitute to operative procedures, especially when it is unfeasible or not suggested in co-morbidity associated patients. Sclerotherapy is better than other treatment modality. If we can use sclerotherapy for non-reassessable sites then why we cannot use sclerotherapy in reassessable sites

Modelling metabolic rewiring during melanoma progression using Flux Balance Analysis

Improvements in melanoma diagnosis, treatment and prognosis are urgently warranted, given that it causes 3 out of 4 skin cancer deaths. A large amount of genomic and molecular data indicate that alterations occur at multiple scales in different stages of melanoma. Metabolic rewiring is a characteristic feature of progressive cancers that facilitates sustenance of tumors, and caters to the changing energy requirements. Since such rewiring involves multiple variations in the metabolic network that are orchestrated, a systems perspective is necessary to understand the nature, significance, mechanisms and identification of the key steps. To address this, we integrate patient transcriptome data with a prior human reference metabolic model and construct stage-specific genome-scale metabolic models. Using flux balance analysis, we simulate the metabolic flows and compute the reaction fluxes specific to normal skin, primary melanoma and metastatic melanoma, from which the reactions with flux differences between conditions were identified. Reactions related to Warburg effect, as anticipated and in addition, ROS detoxification and tyrosine metabolism were largely altered in all stages of melanoma. Vitamin A and vitamin C sub-systems are identified to be involved in different stages, consistent with experimental studies from literature that indicate their support to cancer progression. Gene essentiality studies using the melanoma model identified 5 important genes NME2, CMPK1, HSD17B4, DTYMK and PRODH for the proliferation of melanoma cells, which can be explored as potential drug targets