Draft genome sequence of a multidrug-resistant CTX-M-15 β-lactamase-producing uropathogenic Escherichia coli isolate (ST131-O25b-H30) from Pakistan exhibiting high potential virulence

Objectives: Uropathogenic Escherichia coli (UPEC) is the leading cause of urinary tract infections (UTI). The pandemic ST131 clonal type is associated with multidrug resistance and virulence. We report the first draft genome of an ST131-O25b-H30 strain from Pakistan, isolated from a patient with community-acquired UTI. Methods: Next-generation sequencing was performed using MiSeq and HiSeq 2500 platforms. De novo assembly of the reads was performed using SPAdes (v 3.11.). The genomic features were determined with PATRIC and RAST tool kit. Results: The 5,327,975 bp draft genome sequence has 5433 CDS and 82 tRNAs, an array of resistance genes (blaCTXM-15, blaOXA-1, blaCMY-2, sul2, catB, dfrA17, mph(A)), one class 1 integron, 77 IS elements, one transposon (Tn3-like), multiple virulence markers and seven intact prophage loci. Conclusion: In conclusion, the genome sequence of this new UPEC isolate from Pakistan provides novel insight into the genetic attributes of an epidemic clone associated with high level of resistance and virulence

The Role of FDI on Stock Market Development: The Case of Pakistan

The purpose of this study is to empirically analyze the role of foreign direct investment in developing host country’s stock markets and to examine whether they are related or not. The key interest turns around the admiring role of FDI in Stock market development of Pakistan. Our work also aims to investigate the effect of foreign direct investment along with domestic savings, exchange rate and inflation in developing Pakistan stock markets in a rapidly changing political environment. This study applies Ordinary Least Square (OLS) method of regression by using annual time series data for the period 1988-2009 in case of Pakistan to estimate empirical relationships among variables. The results disclose a positive impact of foreign direct investment along with other explanatory variables in developing Stock markets of Pakistan. The study findings can be used to help government policy makers to encourage FDI and take various steps to provide incentives and save foreign investors interest in a volatile political environment that prevailing in the country. Adequate facility of infrastructure can enhance FDI. The volatility of exchange rate and inflation rate should also be minimized through monitory policy while domestic savings must also be encouraged in the country through appropriate and encouraging saving policies. Our effort exclusively study development of Stock markets in Pakistan with special reference to foreign direct investment and other variables. Our study depicts a closer relationship between FDI and Stock Market Development

Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis and prevention.

Artificial Intelligence (AI) has gained huge attention in computer-aided decision-making in the healthcare domain. Many novel AI methods have been developed for disease diagnosis and prognosis which may support in the prevention of disease. Most diseases can be cured early and managed better if timely diagnosis is made. The AI models can aid clinical diagnosis; thus, they make the processes more efficient by reducing the workload of physicians, nurses, radiologists, and others. However, the majority of AI methods rely on the use of single-modality data. For example, brain tumor detection uses brain MRI, skin lesion detection uses skin pathology images, and lung cancer detection uses lung CT or x-ray imaging (1). Single-modality AI models lack the much-needed integration of complex features available from different modality data, such as electronic health records (EHR), unstructured clinical notes, and different medical imaging modalities– otherwise form the backbone of clinical decision-making

ARE BEHAVIORAL BIASES INFLUENCED BY DEMOGRAPHIC CHARACTERISTICS & PERSONALITY TRAITS? EVIDENCE FROM PAKISTAN

The study investigates the influence of demographics (residential area, age, gender, marital status, education background) and personality traits (extraversion, openness, conscientiousness, neuroticism, and agreeableness) on the financial behavioral biases (overconfidence, herding/mass behavior and disposition effect) and risk taking behavior in Pakistan. The study will be beneficial for the financial advisors and individual investors. As it will help financial advisor to know potential behavioral biases in each type of investors while making investment decision and therefore they can advise investors properly to mitigate such biases. Personality dimensions are categorized under Big Five Personality model. Questionnaire survey method is used to collect the data from a Sample size of 225 respondents that includes bankers, finance students as well as investors. Structure equation modeling (SEM) analysis is used to analyze the impact of personality traits and demographics on the investment biases through Amos 20. The results show that big five personality traits have a significant relationship with overconfidence, herding/mass behavior and risk taking except disposition effect

Defending SDN against packet injection attacks using deep learning

The (logically) centralised architecture of the software-defined networks makes them an easy target for packet injection attacks. In these attacks, the attacker injects malicious packets into the SDN network to affect the services and performance of the SDN controller and overflow the capacity of the SDN switches. Such attacks have been shown to ultimately stop the network functioning in real-time, leading to network breakdowns. There have been significant works on detecting and defending against similar DoS attacks in non-SDN networks, but detection and protection techniques for SDN against packet injection attacks are still in their infancy. Furthermore, many of the proposed solutions have been shown to be easily by-passed by simple modifications to the attacking packets or by altering the attacking profile. In this paper, we develop novel Graph Convolutional Neural Network models and algorithms for grouping network nodes/users into security classes by learning from network data. We start with two simple classes - nodes that engage in suspicious packet injection attacks and nodes that are not. From these classes, we then partition the network into separate segments with different security policies using distributed Ryu controllers in an SDN network. We show in experiments on an emulated SDN that our detection solution outperforms alternative approaches with above 99\% detection accuracy on various types (both old and new) of injection attacks. More importantly, our mitigation solution maintains continuous functions of non-compromised nodes while isolating compromised/suspicious nodes in real-time. All code and data are publicly available for reproducibility of our results.Comment: 15 Pages, 15 Figure

Air Pollution and Its Effect on Human Health: A Case Study in Dera Ghazi Khan Urban Areas, Pakistan

Presently, air pollution is a principal global health threats which is responsible for enhancing the chances for spreading of many chronic diseases. This problem occurred over past few decades due to fast growth in urbanization, industrialization and massive of vehicles volume in developed and under developed countries.  The contaminated air leads the detrimental effects on the human health. Principal air pollutants are particulate matter, sulpher dioxide, nitrogen oxides, ammonia, carbon monoxide and ozone. When the level of these pollutants is increased at certain degree, the outcome may cause serious respiratory problems which lead to happening of deaths. In recent years, rapidly increasing population, economic and educational developments in the city brought a huge pressure of traffic. So, the current study was planned to determine the roots and examine the awful consequences of air pollution on the humanity health. Public opinions on exposure are severe in examining human reaction and adoption of concerned strategies. Hence, viewing people’ perception is vital in establishing the plan of suitable managing actions.  We arranged this study in Dera Ghazi Khan City to obtain the local people know-how of the existing air pollution situation and their postures towards measures to control of air pollution. Multistage sampling technique was applied for the selection of 120 respondents and data was collected by developing questioners.  Most of the interviewees illustrated that air pollution is very hazardous for the people health and is responsible for the cause of many diseases. Keywords: Air Pollution, Human health, Pollutants, Environment, Dera Ghazi Kha

Production and use of estimates for monitoring progress in the health sector: the case of Bangladesh

Background: In order to support the progress towards the post-2015 development agenda for the health sector, the importance of high-quality and timely estimates has become evident both globally and at the country level

An evaluation of the emerging vaccines and immunotherapy against staphylococcal pneumonia in children

<p>Abstract</p> <p>Background</p> <p>Staphylococcus aureus is a commensal of human skin and nares. It is also one of the leading nosocomial pathogens in both developed and developing countries and is responsible for a wide range of life threatening infections, especially in patients who are immunocompromised, post-surgery, undergoing haemodialysis and those who are treated with catheters and ventilators. Over the past two decades, the incidence of nosocomial staphylococcal infections has increased dramatically. Currently there are at least seven vaccine and immunotherapy candidates against S. aureus in the developmental phase targeting both active and passive immunization.</p> <p>Methods</p> <p>We used a modified CHNRI methodology for setting priorities in health research investments. This was done in two stages. In Stage I, we systematically reviewed the literature related to emerging vaccines against Staphylococcus aureus relevant to several criteria of interest: answerability; cost of development, production and implementation; efficacy and effectiveness; deliverability, affordability and sustainability; maximum potential impact on disease burden reduction; acceptability to the end users and health workers; and effect on equity. In Stage II, we conducted an expert opinion exercise by inviting 20 experts (leading basic scientists, international public health researchers, international policy makers and representatives of pharmaceutical companies) to participate. The policy makers and industry representatives accepted our invitation on the condition of anonymity, due to sensitive nature of their involvement in such exercises. They answered questions from CHNRI framework and their “collective optimism” towards each criterion was documented on a scale from 0 to 100%.</p> <p>Results</p> <p>The panel of experts expressed low levels of optimism (score around or below 50%) on the criteria of answerability, efficacy, maximum disease burden reduction potential, low cost of production, low cost of implementation and affordability; moderate levels of optimism (scores around 60 to 80%) that these vaccines could be developed at a low cost, and thus on the deliverability, sustainability and impact on equity; and high levels of optimism (scores above 80%) regarding acceptable of such a product to both the end-users and health workers. While assessing the candidates for passive immunization against S.aureus, the experts were poorly optimistic regarding low production cost, low implementation cost, efficacy, deliverability, sustainability, affordability and equity; moderately optimistic regarding answerability and acceptability to health workers and end-users. They were of the opinion that these interventions would have only a modest impact (3 to 5%) on the burden of childhood pneumonia. .</p> <p>Conclusion</p> <p>In order to provide an effective vaccine against <it>S. aureus</it>, a number of unresolved issues in vaccine development relating to optimal antigenic target identification, criteria for acceptable efficacy, identification of target population, commercial development limitations, optimal timing of immunization strategy, storage, cold chain requirements and cost need to be addressed properly. There is still a great deal unknown about the complex interaction between <it>S. aureus</it> and the human host. However, given the nature of <it>S. aureus</it> and the lessons learned from the recent failure of two emerging vaccines, it is clear that a multi-component vaccine is essential. Combating only one virulence factor is not sufficient in the human host but finding the right combination of factors will be very challenging.</p