Homework 6 Solutions
|
|
- Jonah Bruce
- 5 years ago
- Views:
Transcription
1 Homework 6 Solutions Math 314, Fall 216 Problem 1 The HIV virus targets CD4+ T cells, sometimes called helper T cells During an infection, the total number T t) of helper T cells in the blood, the number T t) of infected helper T cells, and the number V t) of HIV virions free virus particles) in the blood can be modeled by the differential equations = kt V δt, where k, δ, π, and c are positive constants Part a) dv = πt cv, Briefly explain what each term in each of these two differential equations represents What assumptions about proportionality are being made in this model? What is the significance of the four constants k, δ, π, and c? We discuss each of the four terms: 1 In the first differential equation, kt V represents the rate at which helper T cells become infected by virions This is assumed to be proportional to both the number T of helper T cells and the number V of virions, with k being a constant of proportionality that represents the infectiousness of the virions in a given host 2 In the first differential equation, δt represents the rate at which infected helper T cells are cleared from the body, either by dying a natural death or being destroyed or cleared from the body by the immune system This rate is assumed to be proportional to the number of infected helper T cells, with δ being the clearance rate 3 In the second differential equation, πt represents the rate at which virions are produced by the infected helper T cells This is assumed to be proportional to the number of infected helper T cells, with π representing the rate at which a single infected T cell produces virions 4 In the second differential equation, cv represents the rate at which virions either die or are cleared from the body This is assumed to be proportional to the number of virions, with c being the clearance rate 1
2 Part b) A typical HIV infection spends many years in a quasi-steady state Find formulas for the ratio T /V and the total number T of helper T cells during this steady state in terms of the constants k, δ, π, and c Setting the derivatives equal to zero gives Solving the second equation for T /V gives = kt V δt and = πt cv T V = c π Substituting T = cv/π into the first equation gives = kt V δcv/π, and solving for T yields T = δc πk Part c) Administration of an RT inhibitor an antiretroviral drug) blocks the virus from infecting new cells, thereby decreasing k to zero Assuming we administer such a drug at t =, find a formula for T t) in this case, assuming the initial condition T ) = T Substituting k = into the first differential equation gives which has solution Part d) = δt T t) = T e δt Use your answer to part c) to find a general formula for V t) in the same scenario You will need to use the method of integrating factors to solve this part) Substituting T t) = T e δt into the second differential equation gives dv = πt e δt cv Adding cv to both sides and multiplying by e ct yields or equivalently ct dv e + cect V = πt e c δ)t, d [ ] e ct V = πt e c δ)t 2
3 Thus e ct V = where A is a constant Then V t) = πt e c δ)t = πt e c δ)t ) πt e δt + Ae ct + A Part e) Assuming the infection is in a quasi-steady state at t = with initial condition V ) = V, use your answers to parts b) and d) to show that V t) = ce δt δe ct) V Since the infection starts in a quasi-steady state, we know that T V = c π Substituting πt = cv into our solution from part c) yields ) cv V t) = e δt + Ae ct 1) We can solve for the constant A using the initial condition V ) = V Substituting in t = gives Solving for A and simplifying yields V = cv + A A = δv Substituting this into equation 1) above and simplifying gives us the desired equation: V t) = ce δt δe ct) V 3
4 Problem 2 A protease inhibitor is an antiviral drug that interferes with viral replication, causing newly produced virions to be non-infectious The effect of a protease inhibitor can be modeled by the differential equations = kt V I δt, dv NI = πt cv NI, dv I = cv I, where V I t) is the number of infectious HIV virions and V NI t) is the number of non-infections HIV virions Part a) Assuming a protease inhibitor is administered at t =, the number of infectious virions will decrease exponentially according to the equation V I = V e ct Find a general formula for T t) in this case, assuming that the total number T t) of helper T cells is constant Substituting V I = V e ct into the first differential equation gives = kt V e ct δt Adding δt to both sides and multiplying by e δt yields or equivalently Integrating gives where B is a constant Thus Part b) δt dt e + δeδt T = kt V e δ c)t, d ] [e δt T = kt V e δ c)t e δt T = kt V e δ c)t T = + B, ) kt V e ct + Be δt Assuming the HIV infection is in a quasi-steady state at t =, use your answer to part a) to show that δe ct T ce δt) T t) = Because the infection starts in a quasi-stead state, we know from question 1b) that T V = c π and T = δc πk 4
5 Substituting V = πt /c and kt = δc/π into our solution to part a) gives ) δ T T = e ct + Be δt To find the constant B, we substitute t = to get Solving for B and simplifying gives T = δ T + B so T = B = ct δe ct ce δt) T Part c) Use your answer to part b) to show that V NI t) = cv δte ct + c e δt e ct)) Substituting our answer from part b) into the differential equation for V NI gives dv NI δe ct ce δt) T = π cv NI Adding cv NI to both sides and multiplying by e ct yields or equivalently Integrating gives e ct dv NI + ce ct V NI = πt ) e c δ)t d ] [e ct V NI = πt ) e c δ)t e ct V NI = πt δt c ) ec δ)t + R where R is a constant Multiplying by e ct and substituting πt = cv gives V NI t) = cv δte ct + c ) e δt + Re ct 2) Now presumably V NI ) =, since there were no non-infectious virions before we administered to protease inhibitor Substituting t = gives us = cv ) c + R 5
6 so R = cv c ) Substituting this into equation 2) and simplifying yields the desired equation: V NI t) = cv δte ct + c e δt e ct)) 6
Decay characteristics of HIV-1- infected compartments during combination therapy
Decay characteristics of HIV-1- infected compartments during combination therapy Perelson et al. 1997 Kelsey Collins BIOL0380 September 28, 2009 SUMMARY Analyzed decay patterns of viral load of HIV- 1-infected
More informationMathematical Analysis of HIV-1 Dynamics in Vivo
SIAM REVIEW Vol. 41, No. 1, pp. 3 44 c 1999 Society for Industrial and Applied Mathematics Mathematical Analysis of HIV-1 Dynamics in Vivo Alan S. Perelson Patrick W. Nelson Abstract. Mathematical models
More informationVIRUS POPULATION DYNAMICS
MCB 137 VIRUS DYNAMICS WINTER 2008 VIRUS POPULATION DYNAMICS Introduction: The basic epidemic model The classical model for epidemics is described in [1] and [Chapter 10 of 2]. Consider a population of
More informationON ATTAINING MAXIMAL AND DURABLE SUPPRESSION OF THE VIRAL LOAD. Annah M. Jeffrey, Xiaohua Xia and Ian K. Craig
ON ATTAINING MAXIMAL AND DURABLE SUPPRESSION OF THE VIRAL LOAD Annah M. Jeffrey, Xiaohua Xia and Ian K. Craig Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria
More informationHIV-1 R.eplication Rate
HIV-1 R.eplication Rate Michelle J. Arias and Delmy Iiiguez University of California, Riverside Erika T. Camacho Wellesley College Rafael B. Castillo State University of New York at Stony Brook Eliel Melon
More information0.1 Immunology - HIV/AIDS. 0.2 History & biology of HIV
0.1 mmunology - HV/ADS n our previous models we assumed a homogeneous population where everyone was susceptible and infectious to the same degree. n contrast, the dynamics of STDs is affected by the general
More informationThe 2016 Summer Institute in Statistics and Modeling of Infectious Diseases Module 6: Infectious Diseases, Immunology and Within-Host Models Author:
The 2016 Summer Institute in Statistics and Modeling of Infectious Diseases Module 6: Infectious Diseases, Immunology and Within-Host Models Author: Andreas Handel, Department of Epidemiology and Biostatistics,
More informationHIV Treatment Using Optimal Control
Lab 1 HIV Treatment Using Optimal Control Introduction Viruses are the cause of many common illnesses in society today, such as ebola, influenza, the common cold, and Human Immunodeficiency Virus (HIV).
More informationModeling the Effects of HIV on the Evolution of Diseases
1/20 the Evolution of Mentor: Nina Fefferman DIMACS REU July 14, 2011 2/20 Motivating Questions How does the presence of HIV in the body changes the evolution of pathogens in the human body? How do different
More informationSimple Mathematical Models Do Not Accurately Predict Early SIV Dynamics
University of Tennessee, Knoxville Trace: Tennessee Research and Creative Exchange Faculty Publications and Other Works -- Mathematics Mathematics 3-13-2015 Simple Mathematical Models Do Not Accurately
More informationMathematical Models for HIV infection in vivo - A Review
ing of ODE DDE SDE s Mathematical s for HIV infection in vivo - A Department of Mathematics and Statistics Indian Institute of Technology, Kanpur Kanpur, 208016, India peeyush@iitk.ac.in January 20, 2010
More informationMODELING DISEASE FINAL REPORT 5/21/2010 SARAH DEL CIELLO, JAKE CLEMENTI, AND NAILAH HART
MODELING DISEASE FINAL REPORT 5/21/2010 SARAH DEL CIELLO, JAKE CLEMENTI, AND NAILAH HART ABSTRACT This paper models the progression of a disease through a set population using differential equations. Two
More informationWHY? Viruses are considered non-living because they do:
Viruses What is a Virus? Non-living particle WHY? Viruses are considered non-living because they do: NOT Carry out metabolism NOT Grow or develop NOT Replicate without the help of a living cell (host).
More informationDynamics of lentiviral infection in vivo in the absence of adaptive immune responses
Dynamics of lentiviral infection in vivo in the absence of adaptive immune responses Elissa J. Schwartz Associate Professor School of Biological Sciences Department of Mathematics & Statistics Washington
More informationKINETICS OF INFLUENZA A VIRUS INFECTIONS IN A HETEROGENEOUS CELL POPULATION. Marc J. Baron
KINETICS OF INFLUENZA A VIRUS INFECTIONS IN A HETEROGENEOUS CELL POPULATION by Marc J. Baron B.Sc (Hons.), University of Saskatchewan, Saskatoon, SK, Canada, 2008 A thesis presented to Ryerson University
More informationResearch Article Mathematical Modeling of Cytotoxic Lymphocyte-Mediated Immune Response to Hepatitis B Virus Infection
Hindawi Publishing Corporation Journal of Biomedicine and Biotechnology Volume 28, Article ID 74369, 9 pages doi:.55/28/74369 Research Article Mathematical Modeling of Cytotoxic Lymphocyte-Mediated Immune
More informationAPPLICATION OF MATHEMATICAL MODELING TO IMMUNOLOGICAL PROBLEMS
Trakia Journal of Sciences, Vol. 8, Suppl. 2, pp 49-55, 2 Copyright 29 Trakia University Available online at: http://www.uni-sz.bg ISSN 33-75 (print) ISSN 33-355 (online) APPLICATION OF MATHEMATICAL MODELING
More informationMathematical Considerations of Antiretroviral Therapy Aimed at HIV-1 Eradication or Maintenance of Low Viral Loads. Wein, D'Amato, and Perelson
Mathematical Considerations of Antiretroviral Therapy Aimed at HIV-1 Eradication or Maintenance of Low Viral Loads Wein, D'Amato, and Perelson #3939-97-MSA February, 1997 Mathematical Considerations of
More informationMathematical Analysis of an HIV/AIDS Epidemic Model
American Journal of Mathematics and Statistics 15, 5(5): 53-58 DOI: 1.593/j.ajms.1555.5 Mathematical Analysis of an HIV/AIDS Epidemic Model Udoy S. Basak 1,*, Bimal Kumar Datta, Prodip Kumar Ghose 3 1
More informationStability Analysis for an HIV Infection Model with Immune Response and Cure Rate
IOP Conference Series: Materials Science and Engineering PAPER OPEN ACCESS Stability Analysis for an HIV Infection Model with Immune Response and Cure Rate To cite this article: Linli Zhang and Lin Wang
More informationApproximately 200 million individuals worldwide
Triphasic Decline of Hepatitis C Virus RNA During Antiviral Therapy Harel Dahari, Ruy M. Ribeiro, and Alan S. Perelson When patients chronically infected with hepatitis C virus (HCV) are placed on antiviral
More informationEquation Development of Tumor-Immune ODE System
Equation Development of Tumor-Immune ODE System L.G. de Pillis and A.E. Radunskaya August 22, 2002 ThisworkwassupportedinpartbyagrantfromtheW.M.KeckFoundation 0-0 TUMOR-IMMUNE EQUATION DEVELOPMENT Overview
More informationHIV depletes T-helper17, we simply stimulate it. By Prof. Dr.Pichaet Wiriyachitra Ph.D., F.R.A.C.I.
HIV depletes T-helper17, we simply stimulate it By Prof. Dr.Pichaet Wiriyachitra Ph.D., F.R.A.C.I. Natural Healthcare for HIV infected HIV depletes T-helper17, we simply stimulate it Dr.Pichaet Wiriyachitra
More informationViruses. Rotavirus (causes stomach flu) HIV virus
Viruses Rotavirus (causes stomach flu) HIV virus What is a virus? A virus is a microscopic, infectious agent that may infect any type of living cell. Viruses must infect living cells in order to make more
More informationAppendix (unedited, as supplied by the authors)
Appendix (unedited, as supplied by the authors) Details of the mathematical model The model used for the simulations in this manuscript was adapted from a previously described model of HCV transmission
More informationSome living things are made of ONE cell, and are called. Other organisms are composed of many cells, and are called. (SEE PAGE 6)
Section: 1.1 Question of the Day: Name: Review of Old Information: N/A New Information: We tend to only think of animals as living. However, there is a great diversity of organisms that we consider living
More informationSummary Report for HIV Random Clinical Trial Conducted in
Summary Report for HIV Random Clinical Trial Conducted in 9-2014 H.T. Banks and Shuhua Hu Center for Research in Scientific Computation North Carolina State University Raleigh, NC 27695-8212 USA Eric Rosenberg
More informationModeling of HIV and CTL Response
Modeling of HIV and CTL Response Catherine Tran Diana Lubyanaya Advisors: Dr. Dominik Wodarz* and Dr. Frederic Wan** *Department of Ecology and Evolutionary Biology **Department of Mathematics University
More informationInfluence of anti-viral drug therapy on the evolution of HIV-1 pathogens
Influence of anti-viral drug therapy on the evolution of HIV-1 pathogens and Libin Rong Department of Mathematics Purdue University Outline HIV-1 life cycle and Inhibitors Age-structured models with combination
More informationDynamic Multidrug Therapies for HIV: Optimal and STI Control Approaches
Dynamic Multidrug Therapies for HIV: Optimal and STI Control Approaches B. M. Adams 1, H. T. Banks, Hee-Dae Kwon 3, and H. T. Tran Center for Research in Scientific Computation Box 85 North Carolina State
More informationLESSON 1.4 WORKBOOK. Viral structures. Just how small are viruses? Workbook Lesson 1.4 1
Eukaryotes- organisms that contain a membrane bound nucleus and organelles Prokaryotes- organisms that lack a nucleus or other membrane-bound organelles Viruses-small acellular (lacking a cell) infectious
More information5/6/17. Diseases. Disease. Pathogens. Domain Bacteria Characteristics. Bacteria Viruses (including HIV) Pathogens are disease-causing organisms
5/6/17 Disease Diseases I. II. Bacteria Viruses (including HIV) Biol 105 Chapter 13a Pathogens Pathogens are disease-causing organisms Domain Bacteria Characteristics 1. Domain Bacteria are prokaryotic.
More informationThe Effects of HIV 1 Infection on Latent Tuberculosis
Mathematical Modelling of Natural Phenomena Issue- Name of The Issue Vol. 00, No. 00, Month Year, Page 00-00 Amy L. Bauer 1,2, Ian B. Hogue 3, Simeone Marino 3 and Denise E. Kirschner 3 1 Theoretical Division,
More informationEpidemiological Model of HIV/AIDS with Demographic Consequences
Advances in Applied Mathematical Biosciences. ISSN 2248-9983 Volume 5, Number 1 (2014), pp. 65-74 International Research Publication House http://www.irphouse.com Epidemiological Model of HIV/AIDS with
More informationUpdated information and services can be found at: These include: Supplemental material
SUPPLEMENTAL MATERIAL REFERENCES CONTENT ALERTS Reassessing the Human Immunodeficiency Virus Type 1 Life Cycle through Age-Structured Modeling: Life Span of Infected Cells, Viral Generation Time, and Basic
More informationAbstract. Keywords. Gelayol Nazari Golpayegani 1, Amir Homayoun Jafari 2,3*, Nader Jafarnia Dabanloo 1
J. Biomedical Science and Engineering, 2017, 10, 77-106 http://www.scirp.org/journal/jbise ISSN Online: 1937-688X ISSN Print: 1937-6871 Providing a Therapeutic Scheduling for HIV Infected Individuals with
More informationDelay Differential Model for Tumor-Immune Dynamics with HIV Infection of CD4 + T Cells
Delay Differential Model for Tumor-Immune Dynamics with HIV Infection of CD4 + T Cells Fathalla A. Rihan Duaa H. Abdel-Rahman ICM 2012, 11-14 March, Al Ain Abstract In this paper, we introduce a mathematical
More informationImmuno-modulatory Strategies for Reduction of HIV Reservoir Cells
Immuno-modulatory Strategies for Reduction of HIV Reservoir Cells H.T. Banks, Kevin B. Flores and Shuhua Hu Center for Research in Scientific Computation North Carolina State University Raleigh, NC 27695-8212
More informationNOTE: You must show your work to receive full credit. Simply stating the answer will not suffice.
MATH 1314 Review #3 Name NOTE: You must show your work to receive full credit. Simply stating the answer will not suffice. Graph the function by making a table of coordinates. 1) f() = 4 6 y 1) 4 2-6 -4-2
More informationMathematical Models of Hepatitis B Virus Dynamics during Antiviral Therapy
Mathematical Models of Hepatitis B Virus Dynamics during Antiviral Therapy Andrea Carracedo Rodriguez Thesis submitted to the Faculty of the Virginia Polytechnic Institute and State University in partial
More informationHIV Infection and Epidemiology: Can There Be a Cure? Dr. Nedwidek
HIV Infection and Epidemiology: Can There Be a Cure? Dr. Nedwidek The Viral Life Cycle A typical virus (DNA or RNA + protein) enters the host cell, makes more of itself, and exits. There are two major
More informationModeling Plasma Virus Concentration and CD4+ T Cell Kinetics during Primary HIV Infection
Modeling Plasma Virus Concentration and CD4+ T Cell Kinetics during Primary HIV Infection Max A. Stafford Yunzhen Cao David D. Ho Lawrence Corey Crystal L. Mackall SFI WORKING PAPER: 1999-05-036 SFI Working
More information1) Complete the Table: # with Flu
Name: Date: The Math Behind Epidemics A Study of Exponents in Action Many diseases can be transmitted from one person to another in various ways: airborne, touch, body fluids, blood only, etc. How can
More informationStructure of viruses
Antiviral Drugs o Viruses are obligate intracellular parasites. o lack both a cell wall and a cell membrane. o They do not carry out metabolic processes. o Viruses use much of the host s metabolic machinery.
More informationMODELLING VIRAL AND IMMUNE SYSTEM DYNAMICS
MODELLING VIRAL AND IMMUNE SYSTEM DYNAMICS Alan S. Perelson During the past 6 years, there have been substantial advances in our understanding of human immunodeficiency virus 1 and other viruses, such
More informationViruses. Picture from:
Viruses Understand the structure of bacteriophages & human immunodeficiency virus (HIV) Appreciate that viruses replicate in host cells (thereby destroying them) Picture from: http://eands.caltech.edu/articles/lxvii1/viruses.html
More informationMathematical Models for Linking Within-Host and Between-Host Viral Dynamics
Mathematical Models for Linking Within-Host and Between-Host Viral Dynamics The Effect of Antibodies on the Probability of Transmission Aidan Backus Angelica Bloomquist Carlos Villanueva-Chavez J Montgomery
More informationA Comparison Study of the Mathematical Model of HIV Infection of CD 4 + T Cells Using Homotopy Perturbation and Variational Iteration Methods
Applied Mathematical Sciences, Vol. 12, 218, no. 27, 1325-134 HIKARI Ltd, www.m-hikari.com https://doi.org/1.12988/ams.218.81136 A Comparison Study of the Mathematical Model of HIV Infection of CD 4 +
More informationMathematical-Statistical Modeling to Inform the Design of HIV Treatment Strategies and Clinical Trials
Mathematical-Statistical Modeling to Inform the Design of HIV Treatment Strategies and Clinical Trials Marie Davidian and H.T. Banks North Carolina State University Eric S. Rosenberg Massachusetts General
More informationModeling of cancer virotherapy with recombinant measles viruses
Modeling of cancer virotherapy with recombinant measles viruses Thomas W. Carr Department of Mathematics Southern Methodist University Dallas, TX Collaborators: Krešimir Josić Dept. of Mathematics, University
More informationHuman Immunodeficiency Virus
Human Immunodeficiency Virus Virion Genome Genes and proteins Viruses and hosts Diseases Distinctive characteristics Viruses and hosts Lentivirus from Latin lentis (slow), for slow progression of disease
More informationHierarchical Bayesian Methods for Estimation of Parameters in a Longitudinal HIV Dynamic System
Hierarchical Bayesian Methods for Estimation of Parameters in a Longitudinal HIV Dynamic System Yangxin Huang, Dacheng Liu and Hulin Wu Department of Biostatistics & Computational Biology University of
More informationMathematical Model Approach To HIV/AIDS Transmission From Mother To Child
Mathematical Model Approach To HIV/AIDS Transmission From Mother To Child Basavarajaiah.D. M. B. Narasimhamurthy, K. Maheshappa. B. Leelavathy ABSTRACT:- AIDS is a devastating disease, more than 2.50 million
More informationANTIRETROVIRAL therapy generally entails the application of drugs in a fixed
University of Pretoria etd Jeffrey, A M (2006) Chapter 5 Drug Dosage Design ANTIRETROVIRAL therapy generally entails the application of drugs in a fixed dosage regimen. A typical initial regimen would
More informationThere are approximately 30,000 proteasomes in a typical human cell Each proteasome is approximately 700 kda in size The proteasome is made up of 3
Proteasomes Proteasomes Proteasomes are responsible for degrading proteins that have been damaged, assembled improperly, or that are of no profitable use to the cell. The unwanted protein is literally
More informationA Model for the CD4 Cell Counts in an HIV/AIDS Patient and its Application in Treatment Interventions
American Journal of Infectious Diseases (): 6-65, 5 ISSN: 553-63 5 Science Publications A Model for the CD4 Cell Counts in an HIV/AIDS Patient and its Application in Treatment Interventions Richard O.
More informationMedChem 401~ Retroviridae. Retroviridae
MedChem 401~ Retroviridae Retroviruses plus-sense RNA genome (!8-10 kb) protein capsid lipid envelop envelope glycoproteins reverse transcriptase enzyme integrase enzyme protease enzyme Retroviridae The
More informationAntiviral Drugs Lecture 5
Antiviral Drugs Lecture 5 Antimicrobial Chemotherapy (MLAB 366) 1 Dr. Mohamed A. El-Sakhawy 2 Introduction Viruses are microscopic organisms that can infect all living cells. They are parasitic and multiply
More informationACQUIRED IMMUNODEFICIENCY SYNDROME AND ITS OCULAR COMPLICATIONS
ACQUIRED IMMUNODEFICIENCY SYNDROME AND ITS OCULAR COMPLICATIONS Acquired immunodeficiency syndrome (AIDS ) is an infectious disease caused by a retrovirus, the human immunodeficiency virus(hiv). AIDS is
More informationMini Project 3. Understanding The Mathematics of HIV Transmission In Concentrated Settings. Dimitrios Voulgarelis
CoMPLEX University College London Mini Project 3 Understanding The Mathematics of HIV Transmission In Concentrated Settings Dimitrios Voulgarelis Supervisors: Dr Jasmina Panovska-Griffiths, Dr Zindoga
More informationLESSON 4.6 WORKBOOK. Designing an antiviral drug The challenge of HIV
LESSON 4.6 WORKBOOK Designing an antiviral drug The challenge of HIV In the last two lessons we discussed the how the viral life cycle causes host cell damage. But is there anything we can do to prevent
More informationMathematical modeling of escape of HIV from cytotoxic T lymphocyte responses
Mathematical modeling of escape of HIV from cytotoxic T lymphocyte responses arxiv:1207.5684v1 [q-bio.pe] 24 Jul 2012 Vitaly V. Ganusov 1, Richard A. Neher 2 and Alan S. Perelson 3 1 Department of Microbiology,
More informationAntiretroviral Prophylaxis and HIV Drug Resistance. John Mellors University of Pittsburgh
Antiretroviral Prophylaxis and HIV Drug Resistance John Mellors University of Pittsburgh MTN Annual 2008 Outline Two minutes on terminology Origins of HIV drug resistance Lessons learned from ART Do these
More informationA Mathematical Approach to Characterize the Transmission Dynamics of the Varicella-Zoster Virus
Proceedings of The National Conference On Undergraduate Research (NCUR) 2012 Weber State University, Ogden Utah March 29 31, 2012 A Mathematical Approach to Characterize the Transmission Dynamics of the
More informationThe Global Viral Hepatitis Summit 15 th International Symposium on Viral Hepatitis and Liver Disease Presentation O-09
REP 2139 monotherapy and combination therapy with pegylated interferon: Safety and potent reduction of HBsAg and HDV RNA in Caucasian Patients with chronic HBV / HDV co-infection M. Bazinet 1, V. Pântea
More informationReduction of Mortality Rate Due to AIDS When Treatment Is Considered
Pure and Applied Mathematics Journal 216; 5(4): 97-12 http://www.sciencepublishinggroup.com/j/pamj doi: 1.11648/j.pamj.21654.12 ISSN: 2326-979 (Print); ISSN: 2326-9812 (Online) Reduction of Mortality Rate
More informationA DYNAMIC MODEL FOR HIV INFECTION
Technical Report, Department of Mathematics, University of Ioannina, Vol.... No...., pp.... A DYNAMIC MODEL FOR HIV INFECTION LAZAROS MOYSIS 1, IOANNIS KAFETZIS 1, AND MARIOS POLITIS Abstract. A dynamical
More informationMicropathology Ltd. University of Warwick Science Park, Venture Centre, Sir William Lyons Road, Coventry CV4 7EZ
www.micropathology.com info@micropathology.com Micropathology Ltd Tel 24hrs: +44 (0) 24-76 323222 Fax / Ans: +44 (0) 24-76 - 323333 University of Warwick Science Park, Venture Centre, Sir William Lyons
More informationMargaret A. Daugherty. Announcements! Fall Michaelis Menton Kinetics and Inhibition. Lecture 14: Enzymes & Kinetics III
Lecture 14: Enzymes & Kinetics III Michaelis Menton Kinetics and Inhibition Margaret A. Daugherty Fall 2004 Announcements! Monday 10/11 lecture: starts at 10:15; Taught by Dr. Stephen Everse o ffice our/review
More informationARV Mode of Action. Mode of Action. Mode of Action NRTI. Immunopaedia.org.za
ARV Mode of Action Mode of Action Mode of Action - NRTI Mode of Action - NNRTI Mode of Action - Protease Inhibitors Mode of Action - Integrase inhibitor Mode of Action - Entry Inhibitors Mode of Action
More informationCOINFECTIONS OF THE RESPIRATORY TRACT: VIRAL COMPETITION FOR RESOURCES
COINFECTIONS OF THE RESPIRATORY TRACT: VIRAL COMPETITION FOR RESOURCES by LUBNA PINKY Bachelor of Science, 2010 Khulna University of Engineering and Technology Khulna, Bangladesh Submitted to the Graduate
More informationInternational Journal of Pharma and Bio Sciences V1(2)2010 A STUDY ON PRESCRIPTION PATTERN AND COST ANALYSIS OF ANTIRETROVIRAL DRUGS.
SANKAR VEINTRAMUTHU 1 *, RUCKMANI KANDASAMY 2, VELAYUTHAM KANNIYAPPAN 1, NITHYANANTH MUNUSAMY 1 1 Department of Pharmaceutics, PSG College of Pharmacy, Coimbatore- 641004. 2 Department of Pharmaceutical
More informationMathematical-Statistical Modeling to Inform the Design of HIV Treatment Strategies and Clinical Trials
Mathematical-Statistical Modeling to Inform the Design of HIV Treatment Strategies and Clinical Trials 2007 FDA/Industry Statistics Workshop Marie Davidian Department of Statistics North Carolina State
More informationFind the slope of the line that goes through the given points. 1) (-9, -68) and (8, 51) 1)
Math 125 Semester Review Problems Name Find the slope of the line that goes through the given points. 1) (-9, -68) and (8, 51) 1) Solve the inequality. Graph the solution set, and state the solution set
More informationAntibacterials and Antivirals
Structure of a Bacterium: Antibacterials and Antivirals Capsule: protective layer made up of proteins, sugars and lipids Cell wall: provides the bacteria with its shape and structure Cell membrane: permeable
More informationAntiviral Chemotherapy
12 Antiviral Chemotherapy Why antiviral drugs? Vaccines have provided considerable success in preventing viral diseases; However, they have modest or often no therapeutic effect for individuals who are
More informationA Simulation Model Including Vaccination and Seasonality for Influenza A-H1N1 Virus
Applied Mathematical Sciences, Vol. 10, 2016, no. 26, 1269-1276 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/10.12988/ams.2016.511694 A Simulation Model Including Vaccination and Seasonality for Influenza
More informationAli Alabbadi. Bann. Bann. Dr. Belal
31 Ali Alabbadi Bann Bann Dr. Belal Topics to be discussed in this sheet: Particles-to-PFU Single-step and multi-step growth cycles Multiplicity of infection (MOI) Physical measurements of virus particles
More informationPharmacokinetics Overview
Pharmacokinetics Overview Disclaimer: This handout and the associated lectures are intended as a very superficial overview of pharmacokinetics. Summary of Important Terms and Concepts - Absorption, peak
More informationDr. Ahmed K. Ali. Outcomes of the virus infection for the host
Lec. 9 Dr. Ahmed K. Ali Outcomes of the virus infection for the host In the previous few chapters we have looked at aspects of the virus replication cycle that culminate in the exit of infective progeny
More informationStudy population The patient population comprised HIV-positive pregnant women whose HIV status was known.
Prevention of mother-to-child transmission of HIV-1 infection: alternative strategies and their cost-effectiveness Ratcliffe J, Ades A E, Gibb D, Sculpher M J, Briggs A H Record Status This is a critical
More informationCOMPETITIVE INTERFERENCE BETWEEN INFLUENZA VIRAL STRAINS
CANADIAN APPLIED MATHEMATICS QUARTERLY Volume 17, Number 2, Summer 2009 COMPETITIVE INTERFERENCE BETWEEN INFLUENZA VIRAL STRAINS SEYED M. MOGHADAS, CHRISTOPHER S. BOWMAN AND JULIEN ARINO ABSTRACT. We propose
More informationParasitism. Key concepts. Tasmanian devil facial tumor disease. Immunizing and non-immunizing pathogens. SI, SIS, and SIR epidemics
Parasitism Key concepts Immunizing and non-immunizing pathogens SI, SIS, and SIR epidemics Basic reproduction number, R 0 Tasmanian devil facial tumor disease The Tasmanian devil Sarcophilus harrisii is
More informationPopulation Viral Kinetic Modeling: SVR Prediction in HCV GT-3 Cirrhotic Patients With 24 Weeks of Daclatasvir + Sofosbuvir Administration
Population Viral Kinetic Modeling: SVR Prediction in HCV GT-3 Cirrhotic Patients With 24 Weeks of Daclatasvir + Sofosbuvir Administration Emi Tafoya, Yasong Lu, Melody Luo, Premkumar Narasimhan, Neelima
More informationFOR TEACHERS ONLY. The University of the State of New York REGENTS HIGH SCHOOL EXAMINATION GEOMETRY
FOR TEACHERS ONLY The University of the State of New Yk REGENTS HIGH SCHOOL EXAMINATION GEOMETRY Wednesday, January 28, 2015 9:15 a.m. to 12:15 p.m., only SCORING KEY AND RATING GUIDE Mechanics of Rating
More informationSensitivity analysis for parameters important. for smallpox transmission
Sensitivity analysis for parameters important for smallpox transmission Group Members: Michael A. Jardini, Xiaosi Ma and Marvin O Ketch Abstract In order to determine the relative importance of model parameters
More informationThe Mathematics of Flu, Explained
The Mathematics of Flu, Explained Richard C. Larson rclarson@mit.edu Massachusetts Institute of Technology Cambridge, Massachusetts 02139 USA September 5, 2009 Thank you for doing this exercise in your
More informationMathematical modeling of viral infection dynamics in spherical organs
J. Math. Biol. (2013) 67:1425 1455 DOI 10.1007/s00285-012-0593-y Mathematical Biology Mathematical modeling of viral infection dynamics in spherical organs Ricardo Dunia Roger Bonnecaze Received: 16 November
More informationA Delay-Differential Equation Model of
International Mathematical Forum, Vol. 7, 2012, no. 30, 1475-1481 A Delay-Differential Equation Model of HIV Infection of CD4 + T-Cells with Cure Rate 1 Mei Yan 2 and Zhongyi Xiang 1,2 1 Key Laboratory
More information8/13/2009. Diseases. Disease. Pathogens. Domain Bacteria Characteristics. Bacteria Shapes. Domain Bacteria Characteristics
Disease Diseases I. Bacteria II. Viruses including Biol 105 Lecture 17 Chapter 13a are disease-causing organisms Domain Bacteria Characteristics 1. Domain Bacteria are prokaryotic 2. Lack a membrane-bound
More informationOriginally published as:
Originally published as: Ratsch, B.A., Bock, C.-T. Viral evolution in chronic hepatitis B: A branched way to HBeAg seroconversion and disease progression? (2013) Gut, 62 (9), pp. 1242-1243. DOI: 10.1136/gutjnl-2012-303681
More informationMathematical Model of Hepatitis B in. the Bosomtwe District of Ashanti Region, Ghana
Applied Mathematical Sciences, Vol. 8, 2014, no. 67, 3343-3358 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/10.12988/ams.2014.44263 Mathematical Model of Hepatitis B in the Bosomtwe District of Ashanti
More informationCh. 19 Viruses & Bacteria: What Is a Virus?
Ch. 19 Viruses & Bacteria: What Is a Virus? A virus is an invective agent consisting of a nucleic acid in a protein coat, able to multiply only within the living cells of a host. A bacteriophage ( bacteria
More informationIntroduction to the Impact of Resistance in Hepatitis C
Introduction to the Impact of Resistance in Hepatitis C Sponsored by AbbVie 2/1/2017 Presented by Sammy Saab, MD, MPH, FACG, AGAF, FAASLD February 1 st, 2017 1 AbbVie disclosures This is an Abbvie sponsored
More informationUnderstand the physiological determinants of extent and rate of absorption
Absorption and Half-Life Nick Holford Dept Pharmacology & Clinical Pharmacology University of Auckland, New Zealand Objectives Understand the physiological determinants of extent and rate of absorption
More informationStochastic and Numerical Modeling of HIV/AIDS. Spread in a Complex System and Its Application to. the HIV Cases in Indonesia
Applied Mathematical Sciences, Vol. 9, 2015, no. 122, 6095-6106 HIKAI Ltd, www.m-hikari.com http://dx.doi.org/10.12988/ams.2015.59564 Stochastic and Numerical Modeling of HIV/AIDS Spread in a Complex System
More informationAPPLICATION OF FUZZY DIFFERENTIAL EQUATION IN HIV INFECTION
RESEARCH ARTICE APPICATION OF FZZY DIFFERENTIA EQATION IN HIV INFECTION Dr. EMAN A. HSSIAN 1, MAZIN H. SHHIEM 2 1 Department of Mathematics, College of Sciences, A-Mustansiriyah niversity, Baghdad, Iraq
More informationSearch for the Mechanism of Genetic Variation in the pro Gene of Human Immunodeficiency Virus
JOURNAL OF VIROLOGY, Oct. 1999, p. 8167 8178 Vol. 73, No. 10 0022-538X/99/$04.00 0 Copyright 1999, American Society for Microbiology. All Rights Reserved. Search for the Mechanism of Genetic Variation
More informationInvestigations in Number, Data, and Space, Grade 4, 2nd Edition 2008 Correlated to: Washington Mathematics Standards for Grade 4
Grade 4 Investigations in Number, Data, and Space, Grade 4, 2nd Edition 2008 4.1. Core Content: Multi-digit multiplication (Numbers, Operations, Algebra) 4.1.A Quickly recall multiplication facts through
More information