Tracing the recent updates on vaccination approaches and significant adjuvants being developed against HIV.

INTRODUCTION: Human Immunodeficiency Virus type 1 (HIV1); the causative agent of Acquired Immunodeficiency Syndrome (AIDS), has been a major target of the scientific community to develop an anti-viral therapy. Some successful discoveries have been made during the last two decades in the form of availability of antiviral therapy in endemic regions. Nevertheless, a total cure and safety vaccine has not yet been designed to eradicate HIV from the world. AREAS COVERED: The purpose of this comprehensive study is to compile recent data regarding therapeutic interventions against HIV and to determine future research needs in this field. A systematic research strategy has been used to gather data from recent, most advanced published electronic sources. Literature based results show that experiments at the invitro level and animal models are continuously in research annals and are providing hope for human trials. EXPERT OPINION: There is still a gap and more work is needed in the direction of modern drug and vaccination designs. Moreover coordination is necessary among researchers, educationists, public health workers, and the general community to communicate and coordinate the repercussions associated with the deadly disease. It is important for taking timely measures regarding mitigation and adaptation with HIV in future.

Predicting Quality of Life Changes in Hemodialysis Patients Using Machine Learning: Generation of an Early Warning System.

Objective To predict changes in the quality of life scores of hemodialysis patients for the coming month and the development of an early warning system using machine learning Methods It was a prospective cohort study (one-month duration) at the dialysis center of a tertiary care hospital in Pakistan. The study started on 1st October 2016. About 78 patients have been enrolled till now. Bachelor of Medicine and Bachelor of Surgery (MBBS) qualified doctors administered a proforma with demographics and the validated Urdu version of World Health Organization Quality Of Life-BREF (WHOQOL-BREF). It was to be repeated after one month to the same patient by the same investigator. Simple statistics were computed using SPSS version 24 (IBM Corp., Armonk, NY) while machine learning was performed using R (version 3.0) and Orange (version 3.1). Results Using machine learning algorithms, two models (classification tree and Naïve Bayes) were generated to predict an increase or decrease of 5% in a patient's WHOQOL-BREF score over one month. The classification tree was selected as the most accurate model with an area under curve (AUC) of 83.3% (accuracy: 81.9%) for the prediction of 5% increase in QOL and an AUC of 76.2% (accuracy: 81.8%) for the prediction of 5% decrease in QOL over the coming month. The factors associated with an increase of QOL by 5% or more over the next month included younger age (<19 years) and higher iron sucrose doses (>278mg/month). Drops in psychological, physical, and social domain scores lead to a decrease of 5% or more in QOL scores over the following month. Conclusion An early warning system, dialysis data interpretation for algorithmic-prediction on quality of life (DIAL) was built for the early detection of deteriorating QOL scores in the hemodialysis population using machine learning algorithms. The model pointed out that working on psychological and environmental domains, in particular, may prevent the drop in QOL scores from occurring. DIAL, if implemented on a larger scale, is expected to help patients in terms of ensuring a better QOL and in reducing the financial burden in the long term.

Current trends in undergraduate medical and dental research: a picture from Pakistan.

BACKGROUND: Initiatives taken over the last few years have led us to the day when most of the medical and dental institutions in the developed countries have established a strong research culture at undergraduate level but the situation is quite the contrary in Pakistan. This study was carried out to investigate the current trends in undergraduate medical and dental research and to highlight the research barriers. METHODS: A cross-sectional study was conducted at six medical and dental colleges of Rawalpindi and Islamabad. A structured questionnaire was used to collect data from 300 students. Results were recorded as percentages. Findings of current survey were compared with those of already reported in literature using chi-square test. RESULTS: Out of 300 students, 206 (68.7%) students had already participated in research as principal researcher, co-researcher or as a research volunteer. Internet was most effective method of publicity of research opportunities reported by 74% of students. Only 36.7% students reported the presence of student research office at their institute. Accessibility to medical and dental journals and availability of research funds were reported by 77.2% and 13.4% of students, respectively. Lack of funding and academic overload were two main research barriers reported by 92.6% and 91.9% of students, respectively. CONCLUSION: The fraction of medical and dental students who are confident that they can plan, conduct and write a research study has increased over last four years. There is an improvement in the availability of research promoting activities but the number of research barriers is still high.