Scientific Program

Conference Series Ltd invites all the participants across the globe to attend 3rd International Conference on Infection, Disease Control and Prevention Vancouver, Canada.

Day 1 :

Keynote Forum

Anil Kaul

Oklahoma State University, USA

Keynote: Trichomonas vaginalis and Chlamydia trachomatis Co-Infections

Time : 10:00-10:45

OMICS International Infection Control  2018 International Conference Keynote Speaker Anil Kaul photo

Anil Kaul was graduated from Madras Medical College in Medicine, King Georges’ Medical College in Dentistry and in Public Health from University of Minnesota. He currently serves as the Director of High-Complexity Clinical Laboratories and a Faculty at Oklahoma State University-Center for Health Sciences. He has been awarded 6 patents and has published more than 50 scientific papers. He has served as Senior Health Advisor to the US Department of State and received “Expeditionary Service Award”. In 2014, he also received “Lifetime Achievement Award” at Global Health Summit and in 2008 he was named as Sony’s “Scientist of the Year Award”.


Trichomonas vaginalis (TV) is a common sexually transmitted protozoal infection associated with adverse health outcomes such as preterm birth and symptomatic vaginitis. TV has infected 3.7 million individuals in the United States with new infections expected to increase globally. While wet mount is the least sensitive test for TV, it is still the most common testing method used, despite other methods, including molecular assays being more effective. Chlamydia trachomatis (CT) is a sexually transmitted disease (STI) with a prevalence of more than 645 cases per 100,000 females in 2015. CT can cause infertility, pelvic inflammatory disease (PID), pregnancy complications, and increased risk of other STIs. Unlike TV, CT is tested through nucleic acid amplification test (NAAT), DNA probe tests, enzyme linked immunosorbent assay (ELISA), and direct florescent antibody test (DFA). By understanding the co-infection rate between TV and CT, better diagnostic protocols can be used for TV diagnosis based on other diagnosis of other common STIs. Therefore, in this study, we investigated the co-infection rates of CT and TV and collected CT positive patient samples from our clinics. We also collected their de-identified demographic information and performed NAAT based molecular test (Aptima TV assay) using Panther Platform (Hologic Inc. Marlborough, MA) on these patient samples. We determined incidence rate for the overall population and in various demographic sub-groups. Our results indicate an overall CT/TV co-infection rate of around 22%. The highest co-infection rate was amongst black women in the 18 to 24-year age group. Overall, the co-infection rate in the white population was one-third of the rate in the black population. Because of the high co-infection rates in black women, specifically in the 18-24 age group, interventions are necessary in this demographic group. Sexual education is critical in preventing future high STI rates. Educating schoolchildren would be ideal, but due to stigma surrounding STIs and sex education, this may not be very effective. Therefore, other methods such as online videos, informational websites, interactive games, social media, and smart phone applications must be explored.




OMICS International Infection Control  2018 International Conference Keynote Speaker Benfang Lei photo

Benfang Lei has completed his PhD from University of Houston, Texas and postdoctoral study at the Rocky Mountain Laboratories, NIAID, NIH at Hamilton, Montana. He is an Associate Professor at Department of Microbiology and Immunology, Montana State University. He has published 70 primary research papers and has been serving as an academic editor of PloS One and an editorial board member of Infection and Immunity.



Group A Streptococcus (GAS) causes common pharyngitis and occasional severe invasive infections. There is a significant knowledge gap on why noninvasive upper respiratory GAS infections usually do not result in lower respiratory infections while certain GAS strains can cause pneumonia and how invasive GAS disseminates systemically. A pulmonary murine infection model is used to address these questions. Paryngeal GAS isolates induced robust neutrophil recruitment and was effectively cleared in a NADPH Oxidase-dependent mechansim by neutrophils. In contrast, invasive isolates with mutations in virulence regulators CovRS and/or RopB inhibited neutrophil recruitment and caused pulmonary infections. Natural GAS RopB mutants caused infection only in the alveolar region whereas natural CovS and RopB double GAS mutants invade the perivascular interstitium, disrupts smooth muscle and endothelial layers of the blood vessels, and penetrates into the lumen of endothelial layer and the systemic circulation. Correction of the CovS mutation abolished the capacity of GAS to invade the vascular system. To identify virulecence factors that are critical for GAS innate immune evasion and vascular invasion, we tested single
and double deletion mutants of CovRS-controlled virulence genes of hypervirulent GAS. Only a surface protein was found to be critical for the vascular invasion, and the inhibition of neutrophil recruitment requires both streptolysin S and the plateletactivating factor acetyl hydroslase Sse. Thus, Streptolysin S- and Sse-dependent evasion of neutrophil response is critical for the capacity of GAS to cause pulmonary infection, and GAS invasion of the vascular system requires the surface protein

Keynote Forum

KC Santosh

University of South Dakota, USA

Keynote: Artificial Intelligence and Machine Learning in Medical Imaging Science/Radiography

Time : 11:45-12:30

OMICS International Infection Control  2018 International Conference Keynote Speaker KC Santosh photo

K C Santosh worked as a research fellow at the U.S. National Library of Medicine (NLM), National Institutes of Health (NIH). He worked as a postdoctoral research scientist at the LORIA research centre, Universite de Lorraine in direct collaboration with industrial partner ITESOFT, France, for 2 years. He also worked as a research scientist at the INRIA Nancy Grand Est research centre for 3 years, until 2011. K C Santosh has demonstrated expertise in pattern recognition, image processing, computer vision and machine learning with various applications in handwriting recognition, graphics recognition, document information content exploitation, medical image analysis and biometrics. He published more than 60 research articles, including a book section in encyclopedia of electrical and electronics engineering.


Artificial intelligence and machine-learning techniques can definitely advance the medical imaging science, since one can work on pixel-level (with no loss of information), which is completely different from how experts’ eyes do. Further, one can handle large volume of data at once, which is the real need as we are required to deal with them and check the consistency in parallel. Machine, once trained with a large data can produce consistent results until we do not change the set up. Besides, for a resource-constrained areas/regions, use of the AI and machine-learning tool is the must. In my talk, I will focus on the need for screening HIV+ populations in resource-constrained regions for exposure to Tuberculosis (TB), using chest radiographs (CXRs). The primary focus of the talk will be how important/essential data can be extracted from images in a way that one radiologist does as his/her routine work; and how such a data can be used for detecting abnormalities, i.e. pathologies by using machine learning algorithms. In the latter part of the talk, a real-world project will be demonstrated with satisfactory receiver operating characteristic curves.