Aim: prediction of coronary disease using novel support vector machine and comparing its accuracy with logistic regression algorithm. Materials and methods: Two social affairs are proposed for predicting the accuracy (%) of coronary disease. To be explicit, the novel supports vector machine and logistic regression algorithms. Here we take 20 samples each for appraisal and compare. The sample size was calculated using G power with pretest power at 80% and the alpha of 0.05 value. Result: The logistic regression gives better precision (87.82%) than the novel support vector machine (SVM) accuracy (81.30%). Thus the real significance of logistic regression is better than novel support vector machine algorithms. Conclusion: From the result, it might be gathered that logistic regression helps in expecting the coronary sickness with more accuracy to appear differently in relation to novel support vector machine algorithms.

Aim: The major goal of this study is to compare the effectiveness of the Logistic Regression classifier with the Least Squares Support Vector Machine classifier in detecting plaque in the heart with high accuracy. Materials and Methods: In this work, the Logistic Regression and least squares Support Vector Machine methods are compared. There were a total of 20 samples in the Kaggle dataset on Heart Plaque disease. To calculate sample G power of 0.08 with 95% confidence interval, Clincalc is utilized. There are two groups in the training dataset (n = 489 (70 percent)) and the test dataset (n = 277 (30 percent)). Results: The accuracy of both the Logistic Regression and Least Squares Support Vector Machine algorithms is evaluated. The Least Squares Support Vector Machine approach was only 67.3 % accurate, while the Logistic Regression method was 96 % accurate. Since p(2-tailed) < 0.05, in SPSS statistical analysis, a significant difference exists between the two groups. Conclusion: The Logistic Regression algorithm is significantly better than Least Squares Support Vector Machine algorithm in this study in detecting cardiac plaque disease in the dataset.

Introduction: Oral candidiasis is the most common opportunistic infection of the oral cancer patients. Identification of Candida isolates and its susceptibility to antifungal agents will be helpful in the therapeutic management. Aim and Objective: To study the Genetic relatedness and antifungal susceptibility pattern of Candida isolates recovered from the oral cancer patients. Material and Methods: The present study was conducted in the Department of Microbiology at Santosh Medical College, Ghaziabad, U.P. & VarunArjun Medical College & Rohilkhand Hospital, Shahjahanpur, Uttar Pradesh. A total of 377 oropharyngeal cancer patients were selected for the study. The study was conducted from 2019 to 2021. Oropharyngeal swab was cultured by semi-quantitative method on Sabouraud dextrose agar (SDA) and Hi-Chrome agar and followed by identification and Antifungal susceptibility test. The Molecular characterization of Candida albicans and non albicans Candida isolates was performed by DNA extraction and PCR. Results: Out of the 377 oropharyngeal cancer cases, 292 (78.8%) were males and 85 (21.2%) females. The male: female ratio was 3.4:1. Of the 377 oral cancer cases, 152 (40.3%) cases were culture positive for Candida species. 191 isolates were recovered from oral cavity of the cancer patients with oral candidiasis. Isolates included Candida albicans (n = 42, 22.0%), Candida tropicalis (n = 36, 18.8%), Candida parapsilosis (n = 34, 17.9%), Candida dubliniensis (n= 30, 15.7%), Candida krusei (n= 30, 15.7%), Candida glabrata (n = 19, 9. 9%). 142 (74.3%) isolates were susceptible to miconazole followed by Ketoconazole 112 (58.6%), and of and Itraconazole 111 (58.1 %). Conclusion: The decreased effectiveness of antifungal drugs is a serious issue, especially in cancer patients. Hence, addition to emphasis on topical use of Miconazole application in the first stage of oral candidiasis in patients, using alternative systemic drugs such as Ketoconazole and Itraconazole may prove fruitful.

Chronic Renal Failure is a worldwide public health problem with an increasing incidence and prevalence, poor outcomes and high costs. The health teaching regarding hemodialysis and self care is important to improve the health and well being for patients with chronic renal failure. The aim of the study was to evaluate the effectiveness of video assisted teaching on knowledge and attitude regarding hemodialysis among patients with chronic renal failure. Pre experimental one group pretest post design was used. The setting of the study were out patient department at Dhanalakshmi Srinivasan Medical College and Hospital.50 samples were selected by non probability purposive sampling technique. After self introduction and explanation, the participants were given questionnaire to fill. The post test was done after the video assisted teaching, two weeks later. Result of the study were mean post test score of knowledge level 22.72 (SD±3.81)was significantly higher than the mean pre test score 14.31 (sd-3.67) and the mean difference were 8.38. Paired‘t’ value 28.28 (table value =2.02) which is significant ant p <0.05 level, for attitude, the mean post test score 74.66 (SD±7.31) was significantly higher than the mean pre test score 65.82 (sd-6.92) and the mean difference was 8.84. Paired “t” value of knowledge and attitude, the finding revealed that the mean value of knowledge is 22.72 with SD (3.81) and the mean value of attitude is 74.66 with SD (7.31) project ‘r’ value of 0.329 (table value=0.273) which shows positively mild correlation. The result reveals that there is a significant association between the knowledge and the demographic variables of food habits, educational qualification and duration of dialysis and significant association between the attitude and the demographic variables of age and educational qualification (table value =3.84, p <0.05). The finding revealed that there is a significant improvement in knowledge and attitude after intervention. Imprint Dhanalakshmi J, Malathi S. Effectiveness of video assisted teaching programme on knowledge and attitude regarding hemodialysis among patients with chronic renal failure.

Aim: The goal is to compare the antibiofilm characteristics of carbohydrate derivatives to commercial antibiotics, and docking will be used to see how the ligand, protein, and antibiotic interact molecularly. Materials and methods: The protein structure was obtained from the PDB (protein data bank) website, while the ligand structure was obtained from the NCBI-PubChem website. The biofilm from Staphylococcus aureus (bap-c1) as a protein, gluconolactone as a ligand, and nafcillin as an antibiotic are the three different types of chemicals employed for docking. The sample size was calculated using G power with pretest power at 80% and alpha value of 0.05. The sample size per group is 10 and total sample size is 30. Docking studies of protein and ligands were performed using Auto dock software. Statistics of the interactions were analyzed using IBM SPSS software. Result: Molecular interactions revealed that nafcillin shows more affinity towards the protein compared to gluconolactone and clindamycin. The binding affinity values were compared using SPSS software, it reveals that the statistical insignificance observed between the gluconolactone and nafcillin is 0.73 and for gluconolactone and clindamycin is 0.565 Conclusion: The antibiotic nafcillin appears to be more specific and selective in its antibacterial activity against the target protein.

Coronary artery disease is the buildup of plaque in the arteries that supply oxygen-rich blood to your heart. Plaque causes a narrowing or blockage that could result in a heart attack. Symptoms include chest pain or discomfort and shortness of breath. Treatment includes lifestyle changes and medication that target your risk factors and or possible surgery. Coronary artery disease is caused by atherosclerosis. Atherosclerosis is the buildup of plaque inside your arteries. Plaque consists of cholesterol fatty substance, waste products, calcium and the clot making substance fibrin. As plaque continues to collect on your artery walls, your arteries narrow and stiffen. Plaque can clog or damage your arteries, which limits or stops blood flow to your muscle. If your heart does not get enough blood, it can’t get the oxygen and nutrients it needs to work properly. This condition is called ischemia. Not getting enough blood supply to your heart muscle can lead to chest discomfort or chest pain called angina. It puts you at risk for a heart attack. The present study aims to assess the role of HDL to triglycerides Vs LDL to triglycerides as an indicator in coronary artery disease. Quantitative experimental research was conducted among 60 coronary artery disease. A Purposive sampling technique was used to select the samples. Self-structured questionnaires were used to collect demographic data. The study results show, LDL to triglyceride had significant role as an indicator in coronary artery disease., p<0.001. Thereby, this indicates that this ratio of LDL to triglycerides as an indicator of coronary artery disease.

Computer Aided Detection (CAD) and diagnostic technologies and their application have emerged in the last decade. CAD applications have concentrated on identification of the region of interest, for example nodules in the lung in the images, and analysis of the characteristics of objects. CAD technologies take advantages of computer systems as well as image processing and analysis techniques to overcome perceptual and interpretive errors caused by radiologists in the process of image observation and interpretation. This fact is inevitable in the context of medical practice since experience of image readers may vary and each observer (such as a radiologist) has a unique visual search on an image. Furthermore, there are always inter and intra observer variability for interpretation of an image. To overcome these difficulties, different CAD systems are developed for medical image analysis. This paper presents a systematic review on different CAD systems for lung cancer classification using computed tomography images.

The altered glucose metabolism in cancer cells, known as the Warburg effect, is a new area of research of anticancer agents [1]. To date, many compounds have been identified that address the glucose metabolism. However, many of them failed at the early stages of clinical trials, demonstrating systemic toxicity [2, 3]. The glycolysis inhibitor iodoacetate (IA) has a good antitumor effect, but, like other glycolysis inhibitors, it has an unsafe profile. Liposomes (LS) are a good element to provide the required targeted delivery and reduce the systemic toxicity of drugs. The aim of our study was to identify the effect of iodoacetate encapsulation in liposomes made on its antitumor properties and assess the systemic toxicity thereof.

Mouse models using primary patient’s tumors (patient-derived xenograft, PDX) are an effective tool for studying the mechanisms of metastasizing. Tumor plasticity, i.e. the phenomenon of cell phenotype change in response to dynamic microenvironmental conditions is one of the key processes basic to metastasizing.

The most frequent arrhythmias are atrial fibrillation. Although the mechanisms underlying are not fully understood, they encompass postoperative and intraoperative phenomena like cardiac ischemia sympathetic activation and inflammation that ends up causing atrial fibrillation. Atrial fibrillation is frequently associated with the presence of pre-existing factors, making the atria susceptible to atrial fibrillation. There are various treatments have been used to manage the condition. However, they are sometimes ineffective, costly, and have side effects stressing the need to explore alternative medicine. The alternative medicine which is now being explored for treating a variety of conditions is primarily involving botanical sources. However, the present research aims at exploring the potential targeting ability of crocetin, a phytochemical from saffron against Interleukin-18 which is an emerging target for atrial fibrillations using a computational approach with Autodock4. The results of the study revealed binding energy of -7.01 Kcal/mol for the most favorable docked confirmation which further suggests the potential of phytocompounds from saffron in treating and managing atrial fibrillation.