2013
DOI: 10.4161/sysb.28948
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Succumbing to the laws of attraction

Abstract: systems Biomedicine Volume 1 Issue 3 PF, TJAC, RMdR, and MAR performed computational simulations and analysis of computational results. PF, TJAC, ALS, VAF, and GB, compiled physiological data and developed the immune-endocrine connectivity network. PF, TJAC, and GB performed comparisons between experimental and computational data and interpreted the results. MAF and NGK collected and analyzed the experimental data. TJAC, RMdR, MAR, GdV, and GB conceived of the discrete logical analysis algorithm. All authors c… Show more

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Cited by 16 publications
(20 citation statements)
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“…We found that even this coarse-grained model could support multiple steady states, 2 of which were proximal to immune marker profiles exhibited by patients with ME/CFS. 26,27 Although useful in showing the potential involvement of endocrineeimmune coregulatory control in supporting the persistence of this condition, these initial models remained coarse in resolution.…”
Section: Introductionmentioning
confidence: 99%
“…We found that even this coarse-grained model could support multiple steady states, 2 of which were proximal to immune marker profiles exhibited by patients with ME/CFS. 26,27 Although useful in showing the potential involvement of endocrineeimmune coregulatory control in supporting the persistence of this condition, these initial models remained coarse in resolution.…”
Section: Introductionmentioning
confidence: 99%
“…In previous work, our group updated and further developed the network of documented immune signaling interactions used by the agent-based Basic Immune Simulator (Folcik et al, 2007) to create an augmented model of innate and adaptive immune cell signaling (Fritsch et al, 2013). In this model, various adaptive immune cell subsets were aggregated into functional groups (namely, T helper cell populations Th1, Th2, Th17, and cytotoxic T lymphocytes CTL) as were sub-populations of innate immune cells (natural killer cells NK and dendritic cells DC).…”
Section: Aggregating Cytokines Into Functional Setsmentioning
confidence: 99%
“…Toward this we have extended sampling to include 8 blood draws collected prior to, during and up to 4 h after peak exercise in n = 12 veterans with GWI and n = 11 healthy control veterans (HC). In an effort to cast this data in the context of a priori knowledge, we apply as a mechanistic scaffold an extension of a literaturebased model of immune signaling (Fritsch et al, 2013) previously reported by our group. We group individual cytokine and chemokine measurements into the functional sets reported by Folcik et al (2007Folcik et al ( , 2011 and apply a rate equation framework which leverages the basic topological features of biological networks to infer regulatory control actions rather than rely on a more conventional structurally naïve fit to data (Vashishtha et al, 2015).…”
Section: Introductionmentioning
confidence: 99%
“…Recent studies have indicated that the 'normal' immune and physiological homeostatic states (involving inflammatory / anti-inflammatory balance), which arises from feedback between the immune and endocrine systems (being different between males / females), lies in three equilibrium positions. Illnesses such as Gulf War Syndrome (GWI) and chronic-fatigue syndrome (CFS) establish alternative (and sub-optimal) equilibrium positions [214]. The evidence for one of these sub-optimal positions usually lies in immune activation and cytokine production.…”
Section: Disease Time Cascadesmentioning
confidence: 99%
“…This is exactly what has been described in this review for the effects of cytomegalovirus against certain 'sensitive' members of the population. Some 14% of soldiers experienced GWS [214], and CMV studies indicate that around 20% of persons have high CMV IgG (with elevated IL-6 or CRP). This proportion is higher in those with CMV-mediated disease as in CAD, diabetes, etc.…”
Section: Disease Time Cascadesmentioning
confidence: 99%