Linear programming based computational technique for leukemia classification using gene expression profile.

Cancer is a serious public health concern worldwide and is the leading cause of death. Blood cancer is one of the most dangerous types of cancer. Leukemia is a type of cancer that affects the blood cell and bone marrow. Acute leukemia is a chronic condition that is fatal if left untreated. A timely, reliable, and accurate diagnosis of leukemia at an early stage is critical to treating and preserving patients' lives. There are four types of leukemia, namely acute lymphocytic leukemia, acute myelogenous leukemia, chronic lymphocytic in extracting, and chronic myelogenous leukemia. Recognizing these cancerous development cells is often done via manual analysis of microscopic images. This requires an extraordinarily skilled pathologist. Leukemia symptoms might include lethargy, a lack of energy, a pale complexion, recurrent infections, and easy bleeding or bruising. One of the challenges in this area is identifying subtypes of leukemia for specialized treatment. This Study is carried out to increase the precision of diagnosis to assist in the development of personalized plans for treatment, and improve general leukemia-related healthcare practises. In this research, we used leukemia gene expression data from Curated Microarray Database (CuMiDa). Microarrays are ideal for studying cancer, however, categorizing the expression pattern of microarray information can be challenging. This proposed study uses feature selection methods and machine learning techniques to predict and classify subtypes of leukemia in gene expression data CuMiDa (GSE9476). This research work utilized linear programming (LP) as a machine-learning technique for classification. Linear programming model classifies and predicts the subtypes of leukemia Bone_Marrow_CD34, Bone Marrow, AML, PB, and PBSC CD34. Before using the LP model, we selected 25 features from the given dataset of 22283 features. These 25 significant features were the most distinguishing for classification. The classification accuracy of this work is 98.44%.

Cronkhite-Canada Syndrome- The first case from Pakistan: a case report.

Chronkhite-Canada Syndrome is characterised by diffuse gastrointestinal polyposis, dystrophic changes of the fingernails, cutaneous hyperpigmentation, alopecia, diarrhoea, weight loss, and abdominal pain. This disease is also associated with peripheral neuropathies and autoimmune disorders. Its association with other diseases may cause the polyps to turn into malignant tumours and worsen the condition. The first-line treatment is a combination of prednisone and mesalamine. NSAIDs and antibiotic administration is based on the symptoms and needs of patients. Here, we describe a 51-year-old male who presented to us with abdominal pain and significant weight loss. His physical examination showed dystrophic nails, alopecia and hyperpigmentation. Endoscopy and colonoscopy showed multiple polyps. His manifestations were consistent with Cronkhite-Canada syndrome. We prescribed oral corticosteroids, which improved his condition.

Iron coordination to pyochelin siderophore influences dynamics of FptA receptor from Pseudomonas aeruginosa: a molecular dynamics simulation study.

FptA is a TonB-dependent transporter that permits the high affinity binding and transport of Fe(III)-pyochelin complex across the outer membrane of Pseudomonas aeruginosa. Molecular dynamics simulations were employed to FptA receptor and its complexes with pyochelin, and co-crystallized Fe(III)-pyochelin-ethanediol and Fe(III)-pyochelin-water embedded in dilauroyl phosphatidyl choline bilayer for the evaluation of their structural and dynamical properties. The evaluation of properties of the receptor bound to pyochelin molecule and Fe(III)-pyochelin complexes helped to figure out the iron coordination effect on the receptor properties. Moreover, comparison of these four simulation systems revealed further information on the dynamical changes occurred in extracellular loops, in particular loop-7 corresponding to the missing amino acid residues including the close-by loop-8 that was largely affected by the metal coordination to pyochelin. The binding of iron to pyochelin molecule affected the overall structure of the receptor therefore, evaluation fo the gyration radii and hydrogen bonding were evaluated as well as analysis of the pore size were also carried out to understand the effect of metal coordination on the dynamics of the helices which form a kind of translocation channel to transport the siderophore across the FptA protein into the periplasmic space. The properties of each component of the molecular systems were therefore observed to be perturbed by the incorporation of iron to the pyochelin molecule thus demonstrating that the bacteria use its receptor to abstract and transport iron from extracellular environment for its survival and that was made possible to understand at the molecular level through successful implementation of molecular dynamics simulations.