Comprehensive Performance Analysis of Neurodegenerative disease Incidence in the Females of 60-96 year Age Group

Neurodegenerative diseases such as Alzheimer's disease and dementia are gradually becoming more prevalent chronic diseases, characterized by the decline in cognitive and behavioral symptoms. Machine learning is revolu-tionising almost all domains of our life, including the clinical system. The application of machine learning has the potential to enormously augment the reach of neurodegenerative care thus building it more proficient. Throughout the globe, there is a massive burden of Alzheimer's and demen-tia cases; which denotes an exclusive set of difficulties. This provides us with an exceptional opportunity in terms of the impending convenience of data. Harnessing this data using machine learning tools and techniques, can put scientists and physicians in the lead research position in this area. The ob-jective of this study was to develop an efficient prognostic ML model with high-performance metrics to better identify female candidate subjects at risk of having Alzheimer's disease and dementia. The study was based on two diverse datasets. The results have been discussed employing seven perfor-mance evaluation measures i.e. accuracy, precision, recall, F-measure, Re-ceiver Operating Characteristic (ROC) area, Kappa statistic, and Root Mean Squared Error (RMSE). Also, a comprehensive performance analysis has been carried out later in the study

An Exploratory Study to Find the Early Trend and Pattern Recognition of COVID-19 Infection in India: A Severity Model-Based Prediction

Background: Recent Coronavirus Disease 2019 (COVID-19) pandemic has inflicted the whole world critically. Although India has been listed amongst the top ten highly affected countries to date, one cannot rule out COVID-19 associated complications in the near future. Aim & Objective: We aim to build the COVID-19 severity model employing logistic function which determines the inflection point and help in the prediction of the future number of confirmed cases. Methods and Material: An empirical study was performed on the COVID-19 patient status in India. We performed the study commencing from 30 January 2020 to 12 July 2020 for the analysis. Exploratory data analysis (EDA) tools and techniques were applied to establish a correlation amongst the various features. The acute stage of the disease was mapped in order to build a robust model. We collected five different datasets to execute the study. Results: We found that men were more prone to get infected with the coronavirus disease as compared to women. On 165-days based analysis, we found a trending pattern of confirmed, recovered, deceased and active cases of COVID-19 in India. The as-developed growth model provided an inflection point of 72.0 days. It also predicted the number of confirmed cases as 17,80,000.0 in the future i.e. after 12th July. A growth rate of 32.0 percent was obtained. We achieved statistically significant correlations amongst growth rate and predicted COVID-19 confirmed cases. Conclusions: This study demonstrated the effective application of EDA and analytical modeling in building a mathematical severity model for COVID-19 in India

Selective Targeting of 4SO4-N-Acetyl-Galactosamine Functionalized Mycobacterium tuberculosis Protein Loaded Chitosan Nanoparticle to Macrophages: Correlation With Activation of Immune System

In the present study, we investigated potential of chitosan-based nanoparticles (CNPs) to deliver loaded therapeutic molecules to pathogen harboring macrophages. We fabricated stable CNPs employing ionic cross-linking method and evaluated their potential to target RAW 264.7 cells. The physicochemical characterization of as-synthesized CNPs was determined using electron microscopy, infrared microscopy and zeta potential measurement. Next, cellular uptake and intracellular localization studies of CNPs were followed in living RAW264.7 cells using confocal microscopy. We found that both Acr-1 loaded (CNP-A) and 4-SO4-GalNAc ligand harboring (CNP-L) chitosan nanoparticle experience increased cellular uptake by Mycobacterium smegmatis infected RAW cells. Following cellular digestion in model macrophage cell line (RAW), CNPs provide an increased immune response. Further, 4-SO4-GalNAc bearing CNP-L exhibits high binding affinity as well as antibacterial efficacy toward M. smegmatis. The data of the present study suggest that CNP-based nanoparticle offer a promising delivery strategy to target infected macrophages for prevention and eradication of intracellular pathogens such as M. smegmatis

Comment : Utopianism and Communitarianism

千葉大学公共研究センター21世紀プログラム「持続可能な福祉社会に向けた公共研究拠点

Mycobacterium tuberculosis host cell interaction: Role of latency associated protein Acr-1 in differential modulation of macrophages.

Mycobacterium tuberculosis (M.tb) contrives intracellular abode as a strategy to combat antibody onslaught. Additionally, to thrive against hostile ambiance inside host macrophages, the pathogen inhibits phago-lysosomal fusion. Finally, to further defy host cell offensives, M.tb opts for dormant phase, where it turns off or slows down most of its metabolic process as an added stratagem. While M.tb restrains most of its metabolic activities during dormancy, surprisingly latency-associated alpha-crystallin protein (Acr-1) is expressed most prominently during this phase. Interestingly, several previous studies described the potential of Acr-1 to induce the robust immuno-prophylactic response in the immunized host. It is intriguing to comprehend the apparent discrepancy that the microbe M.tb overexpresses a protein that has the potential to prime host immune system against the pathogen itself. Keeping this apparent ambiguity into consideration, it is imperative to unravel intricacies involved in the exploitation of Acr-1 by M.tb during its interaction with host immune cells. The present study suggests that Acr-1 exhibits diverse role in the maturation of macrophages (MΦs) and related immunological responses. The early encounter of bone marrow derived immune cells (pre-exposure during differentiation to MΦs) with Acr-1 (AcrMΦpre), results in hampering of their function. The pre-exposure of naïve MΦs with Acr-1 induces the expression of TIM-3 and IL-10. In contrast, exposure of fully differentiated MΦs to Acr-1 results in their down-modulation and induces the phosphorylation of STAT-1 and STAT-4 in host MΦs. Furthermore, Acr-1 mediated activation of MΦs results in the induction of Th1 and Th17 phenotype by activated T lymphocyte

Illuminating the Petite Picture of T Cell Memory Responses to Listeria monocytogenes

The ease to culture, moderately less safety constraints in handling, and above all, hurdle free induction of an anticipated infection in mouse rendered Listeria monocytogenes the rank of a model organism for studying a variety of host immune responses. Listeria monocytogenes being an intracellular pathogen evokes potent CD8 T cell response during which CD8 T cells pass through a massive expansion phase. This is generally followed by contraction phase wherein majority of activated cells undergo apoptosis leaving behind a population of memory CD8 T cells that has potential to confer enhanced protection upon reencounter with the same pathogen. Functional attributes of various cytokines, transcription factors, receptors, adaptors, and effectors pertaining to the generation of robust memory T cell response have begun to be unravelled for better understanding of memory and opening avenues to create superior vaccine strategies. This review is an attempt to unveil related discoveries along with updating recent advances on this issue