Role of Epidemiological Studies in Disease Prevention

Today's society is full of disease that are of different natures including genetic, infectious and metabolic etc. Every disease has its own mechanisms of affecting humans and different prevention mechanisms as per disease nature. These factors are included in epidemiology of disease. Other factors include prevalence and incidence of diseases in different populations. Exactly knowing about disease epidemiology helps governing authorities to prevent the disease. Unfortunately, under-developed and developing nations are not focusing on diseases epidemiology. On the other hand, all developing nations developed best public health practices based on diseases epidemiology data. These studies may vary from basic epidemiological surveys to identification of microorganism strains etc

Socialna pravičnost in enakost v Koranu v povezavi z globalnim mirom

This paper explores the profound lessons of the Qur’ān about equality and social justice, as well as how these lessons relate to promoting world peace. The goal is to clarify the fundamental ideas of the Qur’ān that support gender equality, economic justice, and human dignity while examining their applicability in the modern world. The study uses a thorough examination of Qur’ānic verses, closely examining particular allusions to social issues and their historical background to produce complex interpretations. One of the main goals is to determine the connection between social justice, equality, and world peace. The study recognizes and tackles widespread misunderstandings and historical obstacles that have impeded the successful application of Qur’ānic principles, even despite the rich Islamic tradition that places a strong emphasis on these values. Additionally, the paper evaluates the current obstacles to social justice advocacy and offers solutions. A thorough examination of the role of Muslim communities and leaders is conducted, emphasizing their obligations to advance social justice and peace worldwide. Furthermore, a comparative examination with alternative religious and ideological viewpoints is conducted to find points of agreement for interfaith communication and cooperation. The article concludes by making suggestions on how communities, governments, and legislators can incorporate the Qur’ānic teachings into real-world projects. It emphasizes the critical role that social justice and equality play in bringing about enduring world peace.V članku so obravnavani nauki Korana o enakosti in socialni pravičnosti ter njihova povezanost s spodbujanjem svetovnega miru. Cilj je pojasniti temeljne ideje Korana, ki podpirajo enakost spolov, gospodarsko pravičnost in človekovo dostojanstvo, hkrati pa preučiti njihovo uporabnost v sodobnem svetu. Članek temeljito analizira koranske verze, pri čemer natančno preučuje posamezne aluzije na družbena vprašanja in njihovo zgodovinsko ozadje ter tako oblikuje kompleksne razlage. Eden glavnih ciljev je definirati povezavo med družbeno pravičnostjo, enakostjo in svetovnim mirom. Študija prepoznava in obravnava razširjene nesporazume in zgodovinske ovire, ki so ovirali uspešno uporabo koranskih načel, celo kljub bogati islamski tradiciji, ki močno poudarja te vrednote. Poleg tega ocenjuje sedanje ovire pri zagovarjanju družbene pravičnosti in ponuja rešitve. Temeljito je preučena vloga muslimanskih skupnosti in voditeljev, pri čemer so poudarjene njihove obveznosti za spodbujanje socialne pravičnosti in miru po vsem svetu. Poleg tega članek ponuja primerjalni pregled z alternativnimi verskimi in ideološkimi stališči, da bi našli skupne točke za medversko komunikacijo in sodelovanje. Članek se zaključi s predlogi, kako lahko skupnosti, vlade in zakonodajalci vključijo nauke Korana v resničnost sveta. Poudarja ključno vlogo, ki jo imata družbena pravičnost in enakost pri vzpostavljanju trajnega svetovnega miru

A Linear Epitope in the N-Terminal Domain of CCR5 and Its Interaction with Antibody.

The CCR5 receptor plays a role in several key physiological and pathological processes and is an important therapeutic target. Inhibition of the CCR5 axis by passive or active immunisation offers one very selective strategy for intervention. In this study we define a new linear epitope within the extracellular domain of CCR5 recognised by two independently produced monoclonal antibodies. A short peptide encoding the linear epitope can induce antibodies which recognise the intact receptor when administered colinear with a tetanus toxoid helper T cell epitope. The monoclonal antibody RoAb 13 is shown to bind to both cells and peptide with moderate to high affinity (6x10^8 and 1.2x107 M-1 respectively), and binding to the peptide is enhanced by sulfation of tyrosines at positions 10 and 14. RoAb13, which has previously been shown to block HIV infection, also blocks migration of monocytes in response to CCR5 binding chemokines and to inflammatory macrophage conditioned medium. A Fab fragment of RoAb13 has been crystallised and a structure of the antibody is reported to 2.1 angstrom resolution

Improving the robustness of neural networks using K-support norm based adversarial training

It is of significant importance for any classification and recognition system, which claims near or better than human performance to be immune to small perturbations in the dataset. Researchers found out that neural networks are not very robust to small perturbations and can easily be fooled to persistently misclassify by adding a particular class of noise in the test data. This, so-called adversarial noise severely deteriorates the performance of neural networks, which otherwise perform really well on unperturbed dataset. It has been recently proposed that neural networks can be made robust against adversarial noise by training them using the data corrupted with adversarial noise itself. Following this approach, in this paper, we propose a new mechanism to generate a powerful adversarial noise model based on K-support norm to train neural networks. We tested our approach on two benchmark datasets, namely the MNIST and STL-10, using muti-layer perceptron and convolutional neural networks. Experimental results demonstrate that neural networks trained with the proposed technique show significant improvement in robustness as compared to state-of-the-art techniques

Angiotensin-converting enzyme defines matrikine-regulated inflammation and fibrosis

The neutrophil chemoattractant proline-glycine-proline (PGP) is generated from collagen by matrix metalloproteinase-8/9 (MMP-8/9) and prolyl endopeptidase (PE), and it is concomitantly degraded by extracellular leukotriene A4 hydrolase (LTA4H) to limit neutrophilia. Components of cigarette smoke can acetylate PGP, yielding a species (AcPGP) that is resistant to LTA4H-mediated degradation and can, thus, support a sustained neutrophilia. In this study, we sought to elucidate if an antiinflammatory system existed to degrade AcPGP that is analogous to the PGP-LTA4H axis. We demonstrate that AcPGP is degraded through a previously unidentified action of the enzyme angiotensin-converting enzyme (ACE). Pulmonary ACE is elevated during episodes of acute inflammation, as a consequence of enhanced vascular permeability, to ensure the efficient degradation of AcPGP. Conversely, we suggest that this pathway is aberrant in chronic obstructive pulmonary disease (COPD) enabling the accumulation of AcPGP. Consequently, we identify a potentially novel protective role for AcPGP in limiting pulmonary fibrosis and suggest the pathogenic function attributed to ACE in idiopathic pulmonary fibrosis (IPF) to be a consequence of overzealous AcPGP degradation. Thus, AcPGP seemingly has very divergent roles: it is pathogenic in its capacity to drive neutrophilic inflammation and matrix degradation in the context of COPD, but it is protective in its capacity to limit fibrosis in IPF

“A Study On The Sustainable Investment Funds With Sepcial Reference To State Bank Of India Esg Mutual Fund Shcemes”

Socially Responsible Investment (SRI) refers to the allocation of funds in certain practises that have a high social impact. It includes assessing businesses on the Environmental , Social and Governance (ESG) screens. A socially conscious investor may either invest directly in financial markets or through investment instruments such as mutual funds via ESG fund schemes. Very few of the numerous mutual fund organizations have implemented ESG Fund schemes to appeal to SRI investors. The SBI Mutual Fund is the first AMC to follow this and has been benchmarked against the Nifty 100 ESG indices. A correlation analysis is made among the results of the SBI Mutual Fund and the NIFTY to compare the four different types of SBI ESG funds and their sector wise participation in different industries. This research paper is methodological in nature as it interprets the published secondary data sources of the SBI Mutual Fund and the NIFTY indices. The goal of this paper is to assess the efficacy of the ESG Equity Fund in the investment portfolio of mutual fund investors and to enable small and medium-sized investors to contribute their money to ESG-driven mutual fund schemes

Detection of myocardial infarction on recent dataset using machine learning

In developing countries such as India, with a large aging population and limited access to medical facilities, remote and timely diagnosis of myocardial infarction (MI) has the potential to save the life of many. An electrocardiogram is the primary clinical tool utilized in the onset or detection of a previous MI incident. Artificial intelligence has made a great impact on every area of research as well as in medical diagnosis. In medical diagnosis, the hypothesis might be doctors' experience which would be used as input to predict a disease that saves the life of mankind. It is been observed that a properly cleaned and pruned dataset provides far better accuracy than an unclean one with missing values. Selection of suitable techniques for data cleaning alongside proper classification algorithms will cause the event of prediction systems that give enhanced accuracy. In this proposal detection of myocardial infarction using new parameters is proposed with increased accuracy and efficiency of the existing model. Additional parameters are used to predict MI with more accuracy. The proposed model is used to predict an early diagnosis of MI with the help of expertise experiences and data gathered from hospitals