MODEL4028801312
type: SBMLModel
parameter: 882421
rule: 882418
compartment: 882411
parameter: 882423
parameter: 882426
parameter: 882420
volume units: metaid_0000217
substance units: metaid_0010216
curated: false
notes: This a model from the article: Understanding the slow depletion of memory CD4+ T cells in HIV infection. Yates A, Stark J, Klein N, Antia R, Callard R. PLoS Med. 2007;4(5):e177. 17518516 , Abstract: BACKGROUND: The asymptomatic phase of HIV infection is characterised by a slow decline of peripheral blood CD4(+) T cells. Why this decline is slow is not understood. One potential explanation is that the low average rate of homeostatic proliferation or immune activation dictates the pace of a "runaway" decline of memory CD4(+) T cells, in which activation drives infection, higher viral loads, more recruitment of cells into an activated state, and further infection events. We explore this hypothesis using mathematical models. METHODS AND FINDINGS: Using simple mathematical models of the dynamics of T cell homeostasis and proliferation, we find that this mechanism fails to explain the time scale of CD4(+) memory T cell loss. Instead it predicts the rapid attainment of a stable set point, so other mechanisms must be invoked to explain the slow decline in CD4(+) cells. CONCLUSIONS: A runaway cycle in which elevated CD4(+) T cell activation and proliferation drive HIV production and vice versa cannot explain the pace of depletion during chronic HIV infection. We summarize some alternative mechanisms by which the CD4(+) memory T cell homeostatic set point might slowly diminish. While none are mutually exclusive, the phenomenon of viral rebound, in which interruption of antiretroviral therapy causes a rapid return to pretreatment viral load and T cell counts, supports the model of virus adaptation as a major force driving depletion. This model was taken from the CellML repository and automatically converted to SBML. The original model was: Yates A, Stark J, Klein N, Antia R, Callard R. (2007) - version03 The original CellML model was created by: Lloyd, Catherine, May c.lloyd@aukland.ac.nz The University of Auckland The Bioengineering Institute This model originates from BioMod…
length unit: length
parameter: 882425
units def: 013072
rule: 882417
rule: 882415
units def: 013096
parameter: 882422
time units: 013121
units def: 013121
is described by: http://identifiers.org/pubmed/17518516
area units: area
name: Yates2007_TcellHomeostasisProliferation
parameter: 882427

882421
type: Parameter
constant: false
units: dimensionless
value: 0.0
name: y

882411
type: Compartment
constant: true
units: litre
size: 1.0
spatial dimensions: 3.0

882423
type: Parameter
constant: true
units: 013096
value: 0.005
name: d1

013096
type: SBMLUnitsDef
unit: 013109
name: first_order_rate_constant

013109
type: SBMLUnit
exponent: -1.0
scale: 0
multipler: 86400.0
kind: SECOND

882426
type: Parameter
constant: false
units: 013096
value: NaN
name: d2

882420
type: Parameter
constant: false
units: dimensionless
value: 1.0
name: x

882425
type: Parameter
constant: true
units: 013096
value: 1.0
name: r

013072
type: SBMLUnitsDef
unit: 013084
name: day

013084
type: SBMLUnit
exponent: 1.0
scale: 0
multipler: 86400.0
kind: SECOND

882422
type: Parameter
constant: true
units: 013096
value: 0.03333
name: a

013121
type: SBMLUnitsDef
unit: 013133
name: time

013133
type: SBMLUnit
exponent: 1.0
scale: 0
multipler: 86400.0
kind: SECOND

882427
type: Parameter
constant: true
units: dimensionless
value: 1.0
name: kappa