Detection of Breast Cancer using AI Techniques – A Survey

Cancer refers to any one of a large number of diseases characterized by the development of abnormal cells that divide uncontrollably and have the ability to infiltrate and destroy normal body tissue.Without treatment, it can cause serious health issues andresult in a loss of life. Breast cancer is the most common cancer among women around the world. Despite enormous medical progress, breast cancer has still remained the second leading cause of death worldwide. Early detection of cancer may reduce mortality and morbidity. This paper presents a review of the detection methods for cancer through Artificial Intelligence (AI) in different ways. Previously Microscopic reviews of tissues on glass slides are used for cancer diagnostics to improve diagnostic accuracy. We can use different techniques such as digital imaging and artificial intelligence algorithm. Cancer care is also advancing thanks to AI’s ability to collect and process data. Due to the nature of processing this information, the task is often a time-consuming and tedious job for doctors. This process may be made much easier, quicker and efficient through the advancement as well as by using modified technologies

Transcriptomic Responses of the Honey Bee Brain to Infection with Deformed Wing Virus

Managed colonies of European honey bees (Apis mellifera) are under threat from Varroa destructor mite infestation and infection with viruses vectored by mites. In particular, deformed wing virus (DWV) is a common viral pathogen infecting honey bees worldwide that has been shown to induce behavioral changes including precocious foraging and reduced associative learning. We investigated how DWV infection of bees affects the transcriptomic response of the brain. The transcriptomes of individual brains were analyzed using RNA-Seq after experimental infection of newly emerged adult bees with DWV. Two analytical methods were used to identify differentially expressed genes from the ~15,000 genes in the Apis mellifera genome. The 269 genes that had increased expression in DWV infected brains included genes involved in innate immunity such as antimicrobial peptides (AMPs), Ago2, and Dicer. Single bee brain NMR metabolomics methodology was developed for this work and indicates that proline is strongly elevated in DWV infected brains, consistent with the increased presence of the AMPs abaecin and apidaecin. The 1361 genes with reduced expression levels includes genes involved in cellular communication including G-protein coupled, tyrosine kinase, and ion-channel regulated signaling pathways. The number and function of the downregulated genes suggest that DWV has a major impact on neuron signaling that could explain DWV related behavioral changes

Enhanced Biosynthetically Directed Fractional Carbon-13 Enrichment of Proteins for Backbone NMR Assignments

Routes to carbon-13 enrichment of bacterially expressed proteins include achieving uniform or positionally selective (e.g. ILV-Me, or (13)C\u27, etc.) enrichment. We consider the potential for biosynthetically directed fractional enrichment (e.g. carbon-13 incorporation in the protein less than 100%) for performing routine n-(D)dimensional NMR spectroscopy of proteins. First, we demonstrate an approach to fractional isotope addition where the initial growth media containing natural abundance glucose is replenished at induction with a small amount (e.g. 10%(w/w)u-(13)C-glucose) of enriched nutrient. The approach considered here is to add 10% (e.g. 200mg for a 2g/L culture) u-(13)C-glucose at the induction time (OD600=0.8), resulting in a protein with enhanced (13)C incorporation that gives almost the same NMR signal levels as an exact 20% (13)C sample. Second, whereas fractional enrichment is used for obtaining stereospecific methyl assignments, we find that (13)C incorporation levels no greater than 20%(w/w) yield (13)C and (13)C-(13)C spin pair incorporation sufficient to conduct typical 3D-bioNMR backbone experiments on moderate instrumentation (600MHz, RT probe). Typical 3D-bioNMR experiments of a fractionally enriched protein yield expected backbone connectivities, and did not show amino acid biases in this work, with one exception. When adding 10% u-(13)C glucose to expression media at induction, there is poor preservation of (13)Calpha-(13)Cbeta spin pairs in the amino acids ILV, leading to the absence of Cbeta signals in HNCACB spectra for ILV, a potentially useful editing effect. Enhanced fractional carbon-13 enrichment provides lower-cost routes to high throughput protein NMR studies, and makes modern protein NMR more cost-accessible.Copyright 2015 Elsevier Inc. All rights reserved

A Persuasive in the Management of Indralupta (Alopecia areata) with Ayurvedic approach

The aim of the case study is to evaluate the efficacy of Leech therapy along with ayurvedic treatment in Alopecia areata (INDRALUPTA). It is prospective interventional case report on alopecia areata treated with leech therapy and ayurvedic formulations. Using a subjective evaluation, an improvement in growth of hair on bald patches over scalp region was observed. An 18-year-old female patient, resident of Delhi, presented with complaints of two bald patches (right parietal & vertex) over the scalp without any secondary changes. With these complaints, the patient visited Shalya Tantra, Outpatient department (OPD No 16) at Chaudhary Brahm Prakash Ayurved Charak Sansthan, New Delhi. She took treatment for six weeks and got complete remission in her symptoms. Line of treatment adopted was tridosha shamaka, rakta-shodhaka and raktamokashana (Leech application). Leech therapy supplemented with ayurvedic formulations have definite role in Alopecia Areata (Indralupta) especially of recent origin. A case series or pilot study may further strengthen above case report and open new treatment arena for such cases. This case report can also be used to formulate hypothesis for management of baldness from an ayurvedic perspective