Role of Gene Mutations in Acute Myeloid Leukemia: A Review Article.

Acute myeloid leukemia (AML) is an immensely heterogeneous disease characterized by the clonal growth of promyelocytes or myeloblasts in bone marrow as well as in peripheral blood or tissue. Enhancement in the knowledge of the molecular biology of cancer and recognition of intermittent mutations in AML contribute to favorable circumstances to establish targeted therapies and enhance the clinical outcome. There is high interest in the development of therapies that target definitive abnormalities in AML while eradicating leukemia-initiating cells. In recent years, there has been a better knowledge of the molecular abnormalities that lead to the progression of AML, and the application of new methods in molecular biology techniques has increased that facilitating the advancement of investigational drugs. In this review, literature or information on various gene mutations for AML is discussed. English language articles were scrutinized in plentiful directories or databases like PubMed, Science Direct, Web of Sciences, Google Scholar, and Scopus. The important keywords used for searching databases is "Acute myeloid leukemia", "Gene mutation in Acute myeloid leukemia", "Genetic alteration in Acute myeloid leukemia," and "Genetic abnormalities in Acute myeloid leukemia."

Colonoscopic Profile of Lower Gastrointestinal Bleed in Adults: A Tertiary Care Center-based Study in South India.

INTRODUCTION: Lower Gastro intestinal bleeding (LGIB) is one of the most important clinical symptoms which have significant morbidity and mortality. It has an annual admission rate of 0.15% with mortality rate of 5-10%. LGIB can be caused by number of causes which includes both neoplastic and non-neoplastic lesions. Colonoscopy is the gold standard diagnostic measure which is simple, convenient and cost effective procedure. The present study was aimed to assess the Colonoscopic profile of LGIB presenting to our tertiary care centre in south India. The study was conducted for 6 months period. MATERIALS: This is a hospital based study cross-sectional observational study conducted in a tertiary health care centre. A total number of 58 adult subjects with LGIB aged above 18 years were recruited in this study and History, clinical examination, blood tests were taken. RESULT: In our study among the 58 subjects, 33 were male. Majority of our patients were between the mean age of 31-40 years. Most colonoscopic findings were suggestive of ulcerative colitis which equalled to 31%. Other different aetiologies of LGIB were as following: CA colon (15%), haemorrhoids (15%), colonic polyps (14%) CA anal canal (5%) and so on. Majority of our patients had moderate anaemia which was equal to 45%, due to persistent LGIB. CONCLUSION: The incidence of lower GI bleeding increased with increasing age among our patients. The leading cause of lower GI bleeding was found to be ulcerative colitis. It was followed by CA colon, haemorrhoids and colonic polyps hence colonoscopy is recommended in all patients chronic LGIB. References Hilsden RJ, Shaffer EA. Management of gastrointestinal hemorrhage. Can Fam Physician 1995;41:1931-6, 1939-41. Sahn B, Bitton S. Lower gastrointestinal bleeding in children. Gastrointest Endosc Clin NA 2016;26(1):75-98.

Effective prediction of heart disease using hybrid ensemble deep learning and tunicate swarm algorithm.

Heart disease (HD) is the major reason for the rampant cause of death around the world. It is deemed as a crucial illness among the middle and old age people which tends to high mortality rates. Recently, Effects of HD is presenting a shocking rise in India. Prediction of HD is considered as the major concern as people are engaged with their day-to-day life and not bothering about their health issues due to the tight schedule of work. Various symptoms may occur for the people who got affected with HD and the recognition of the disease tends to be difficult. Based on the clinical dataset, Data mining techniques are employed for gathering the hidden information. In the present effort, a Hybrid TSA-EDL (Hybrid Tunicate Swarm Algorithm and Ensemble Deep Learning) is implemented for the exact determination of HD. The main tasks indulged for the HD prediction are Pre-processing, clustering and classification. The relevant, irrelevant and redundant features are grouped by DBSCAN (Density-based clustering with noise). At last, the classification process is performed by the hybrid classifier. The proposed work is implemented using the python platform. Two datasets have been included for the analysis as University of California Irvine (UCI) and Cardiovascular Disease (CVD). The different performance metrics used for the analysis are accuracy, recall, specificity, precision, probability of misclassification error, root mean square error, F-score, false positive rate and false negative rate. The obtained performances are differentiated with the outcomes of UCI Cleveland HD dataset and other previous algorithms. As a matter of fact, the performance of the proposed work is increased by attaining the accuracy (98.33%) in CVD and (97.5%) in UCI.Communicated by Ramaswamy H. Sarma.

Efficient heart disease prediction-based on optimal feature selection using DFCSS and classification by improved Elman-SFO.

Prediction of cardiovascular disease (CVD) is a critical challenge in the area of clinical data analysis. In this study, an efficient heart disease prediction is developed based on optimal feature selection. Initially, the data pre-processing process is performed using data cleaning, data transformation, missing values imputation, and data normalisation. Then the decision function-based chaotic salp swarm (DFCSS) algorithm is used to select the optimal features in the feature selection process. Then the chosen attributes are given to the improved Elman neural network (IENN) for data classification. Here, the sailfish optimisation (SFO) algorithm is used to compute the optimal weight value of IENN. The combination of DFCSS-IENN-based SFO (IESFO) algorithm effectively predicts heart disease. The proposed (DFCSS-IESFO) approach is implemented in the Python environment using two different datasets such as the University of California Irvine (UCI) Cleveland heart disease dataset and CVD dataset. The simulation results proved that the proposed scheme achieved a high-classification accuracy of 98.7% for the CVD dataset and 98% for the UCI dataset compared to other classifiers, such as support vector machine, K-nearest neighbour, Elman neural network, Gaussian Naive Bayes, logistic regression, random forest, and decision tree.

Evaluation of fracture resistance and mode of failure of premolars restored with nanohybrid composite, ORMOCER and ceramic inlays.

OBJECTIVES: To evaluate the fracture resistance and mode of failure of maxillary premolars restorations restored with nanohybrid Composite, ORMOCER and Ceramic Inlays. MATERIALS AND METHOD: 100 extracted first maxillary premolar were collected. Samples were divided into five groups. Group I - Intact premolars, Group II -MOD cavities without restorations, Group III - MOD cavities restored with composite restoration, GROUP IV - MOD cavities restored with ORMOCER restoration and GROUP V - MOD cavities restored with ceramic inlays. All the samples were sent for the axial compression test under the universal testing machine. Fracture resistance and fracture modes were recorded. RESULT: Highest fracture resistance was achieved in Group V (1324.74 ± 336.78) almost comparable to that of natural tooth (1381.07 ± 259.36) (p < 0.05), followed by Group IV (MOD cavities with ORMOCER restorations) (1082.27 ± 351.27) (p < 0.01) and least fracture resistance in Group III (MOD cavities with composite restorations) (778.35 ± 100.25) (p < 0.0001). Mode of fracture in Group IV and Group V are almost similar and In Group III 65% of the cases showed non-restorable fractures. CONCLUSION: ORMOCER fracture resistance along with other groups of clinically restorable fracture stand better than Nanohybrid composite. CLINICAL RELEVANCE: Based on the present study, the dentist can utilize the ORMOCER material as a restoration material for the cavities of posterior teeth which is better in terms of fracture resistance and durability of the restoration when compare to nanohybrid composite.

Palato-radicular groove and localized periodontitis: a series of case reports.

AIM: The aim of this report is to present the management of three cases of different magnitude affecting the periodontal attachment apparatus due to the presence of a palato-radicular groove (PRG). BACKGROUND: The palato-radicular groove is a developmental anomaly often associated with localized periodontitis and pulpal necrosis. CASE DESCRIPTION: The authors present three cases involving the management of teeth with a palato-radicular groove. In the first case, a 20-year-old woman presented with a 5mm periodontal pocket associated with the maxillary right central incisor but no evidence of pulpal involvement. In the second case, there was extensive bone loss and pulpal necrosis of the maxillary right lateral incisor in a 35-year-old man. The third case involved severe localized periodontitis of the right and left maxillary lateral incisors of a 47-year-old man. This report describes the diagnosis and periodontal management of these three clinical situations. SUMMARY: Periodontal complications due to a palatal-radicular groove are relatively rare. However, when they do occur, the diagnosis of a pulpal or localized periodontal lesion can sometimes present a dilemma for the general dentist, particularly if a palato-radicular groove is the etiologic factor. This is because a radicular groove can act like a "funnel," aiding microbial plaque accumulation, and lead to gingivitis, localized periodontitis, and even pulpal necrosis. But with a timely diagnosis and proper clinical management, the tooth or teeth involved can be treated and often retained. CLINICAL SIGNIFICANCE: Thorough examination of the morphological anomalies associated with the lateral and central incisors, in particular, aided by appropriate diagnostic aids, can lead to accurate diagnosis and management of a tooth or teeth with a palato-radicular groove.

Gingival crevicular fluid levels of neopterin in healthy subjects and in patients with different periodontal diseases.

BACKGROUND: Neopterin, a metabolite of guanosine, belongs to the class of chemical compounds known as pteridines and is an early and valuable marker of cellular immunity. Recently, it was shown to be associated with the initiation and progression of periodontal disease. The aim of the present study was to assess the relationship between clinical parameters and concentrations of neopterin within gingival crevicular fluid (GCF) from inflamed gingiva and periodontitis sites before and after the treatment of periodontitis. METHODS: Sixty age (35 to 65 years)- and gender-matched (30 males and 30 females) subjects were recruited and divided into the following four groups of 15 subjects each based on gingival index, Ramfjord periodontal disease index, clinical attachment loss (CAL), and radiographic parameters (bone loss): healthy (group 1), gingivitis (group 2), mild periodontitis (group 3), and moderate to severe periodontitis (group 4). A fifth group consisted of the 15 subjects from group 4, 6 to 8 weeks after treatment (scaling and root planing). GCF was collected from each patient, and the neopterin levels were determined by enzyme immunoassay. Results were analyzed statistically. RESULTS: The mean concentration of neopterin in GCF was the highest in group 4 (51 nmol/l) and the lowest in group 1 (1.36 nmol/l). The mean neopterin concentrations in group 2 (9.69 nmol/l) and group 3 (16.58 nmol/l) fell between the highest and lowest values. This suggested a positive correlation between CAL and GCF neopterin concentrations. Neopterin levels in group 4 decreased to 1.77 nmol/l after treatment (group 5). CONCLUSIONS: Neopterin increased in parallel with the severity of inflammatory disease. Its levels in GCF may be potentially useful as an indicator of periodontal inflammation and the host response.