Model-Based Therapeutic Correction of Hypothalamic-Pituitary-Adrenal Axis Dysfunction

The hypothalamic-pituitary-adrenal (HPA) axis is a major system maintaining body homeostasis by regulating the neuroendocrine and sympathetic nervous systems as well modulating immune function. Recent work has shown that the complex dynamics of this system accommodate several stable steady states, one of which corresponds to the hypocortisol state observed in patients with chronic fatigue syndrome (CFS). At present these dynamics are not formally considered in the development of treatment strategies. Here we use model-based predictive control (MPC) methodology to estimate robust treatment courses for displacing the HPA axis from an abnormal hypocortisol steady state back to a healthy cortisol level. This approach was applied to a recent model of HPA axis dynamics incorporating glucocorticoid receptor kinetics. A candidate treatment that displays robust properties in the face of significant biological variability and measurement uncertainty requires that cortisol be further suppressed for a short period until adrenocorticotropic hormone levels exceed 30% of baseline. Treatment may then be discontinued, and the HPA axis will naturally progress to a stable attractor defined by normal hormone levels. Suppression of biologically available cortisol may be achieved through the use of binding proteins such as CBG and certain metabolizing enzymes, thus offering possible avenues for deployment in a clinical setting. Treatment strategies can therefore be designed that maximally exploit system dynamics to provide a robust response to treatment and ensure a positive outcome over a wide range of conditions. Perhaps most importantly, a treatment course involving further reduction in cortisol, even transient, is quite counterintuitive and challenges the conventional strategy of supplementing cortisol levels, an approach based on steady-state reasoning

Reciprocal Hosts' Responses to Powdery Mildew Isolates Originating from Domesticated Wheats and Their Wild Progenitor

The biotroph wheat powdery mildew, Blumeria graminis (DC.) E.O. Speer, f. sp. tritici Em. Marchal (Bgt), has undergone long and dynamic co-evolution with its hosts. In the last 10,000 years, processes involved in plant evolution under domestication, altered host-population structure. Recently both virulence and genomic profiling separated Bgt into two groups based on their origin from domestic host and from wild emmer wheat. While most studies focused on the Bgt pathogen, there is significant knowledge gaps in the role of wheat host diversity in this specification. This study aimed to fill this gap by exploring qualitatively and also quantitatively the disease response of diverse host panel to powdery mildew [105 domesticated wheat genotypes (Triticum turgidum ssp. dicoccum, T. turgidum ssp. durum, and T. aestivum) and 241 accessions of its direct progenitor, wild emmer wheat (T. turgidum ssp. dicoccoides)]. A set of eight Bgt isolates, originally collected from domesticated and wild wheat was used for screening this wheat collection. The isolates from domesticated wheat elicited susceptible to moderate plant responses on domesticated wheat lines and high resistance on wild genotypes (51.7% of the tested lines were resistant). Isolates from wild emmer elicited reciprocal disease responses: high resistance of domesticated germplasm and high susceptibility of the wild material (their original host). Analysis of variance of the quantitative phenotypic responses showed a significant Isolates × Host species interaction [P(F) < 0.0001] and further supported these findings. Furthermore, analysis of the range of disease severity values showed that when the group of host genotypes was inoculated with Bgt isolate from the reciprocal host, coefficient of variation was significantly higher than when inoculated with its own isolates. This trend was attributed to the role of major resistance genes in the latter scenario (high proportion of complete resistance). By testing the association between disease severity and geographical distance from the source of inoculum, we have found higher susceptibility in wild emmer close to the source. Both qualitative and quantitative assays showed a reciprocal resistance pattern in the wheat host and are well aligned with the recent findings of significant differentiation into wild-emmer and domesticated-wheat populations in the pathogen

Inferring Gene Networks using Robust Statistical Techniques

Inference of gene networks is an important step in understanding cellular dynamics. In this work, a novel algorithm is proposed for inferring gene networks from gene expression data using linear ordinary differential equations. Under the proposed method, a combination of known statistical tools including partial least squares (PLS), leave-one-out jackknifing, and the Akaike information criterion (AIC) are used for robust estimation of gene connectivity matrix. The proposed approach is tested and validated using a computer simulated gene network model and an experimental data on a nine gene network in Eschericia coli.

Steady states of the HPA axis system.

<p>Steady-state concentration of CRH (x₁), ACTH (x₂), GR (x₃) and cortisol (x4) as a function of the external stressor <i>f</i> for the model expressed as system <i>H</i>. The system naturally accommodates 3 stable steady states at rest <i>f</i> = 0 and over a broad range of increasing values for <i>f</i>.</p

Migration of cortisol concentration from one stable point to another.

<p>Concentration of circulating cortisol plotted as a function of the external stressor <i>f</i>. A first idealized trajectory (red - -) describes the displacement of the system from rest to a peak cortisol concentration followd by an eventual lapse into a chronic hypocortisolic state. A second idealized trajectory (green - -) illustrates the effects of treatment. Here removal of cortisol can be thought of as a negative stress <i>f</i>. An increase in ACTH concentration of ∼30% above baseline serves as a signal that the treatment may be discontinued.</p

Idealized corrective control action.

<p>Concentrations of CRH (x₁), ACTH (x₂), GR (x₃) and cortisol (x4) as a function of time in response to an ideal externally applied perturbation in cortisol <i>u(t)</i>. The negative supplement in cortisol signifies a pharmaceutical removal or inactivation of circulating cortisol. ACTH concentration serves to monitor the progress of the treatment which is discontinued when ACTH increases by ∼30% over baseline.</p

Steady-state values for concentrations of CRH, ACTH, free GR and circulating cortisol.

<p>Steady-state values for concentrations of CRH, ACTH, free GR and circulating cortisol.</p