Screening drug target combinations in disease-related molecular networks.

BACKGROUND: For treating a complex disease such as cancer, some effective means are needed to control biological networks that underlies the disease. The one-target one-drug paradigm has been the dominating drug discovery approach in the past decades. Compared to single target-based drugs, combination drug targets may overcome many limitations of single drug target and achieve a more effective and safer control of the disease. Most of existing combination drug targets are developed based on clinical experience or text-and-trial strategy, which cannot provide theoretical guidelines for designing and screening effective drug combinations. Therefore, systematic identification of multiple drug targets and optimal intervention strategy needs to be developed. RESULTS: We developed a strategy to screen the synergistic combinations of two drug targets in disease networks based on the classification of single drug targets. The method tried to identify the sensitivity of single intervention and then the combination of multiple interventions that can restore the disease network to a desired normal state. In our strategy of screening drug target combinations, we first classified all drug targets into sensitive and insensitive single drug targets. Then, we identified the synergistic and antagonistic of drug target combinations, including the combinations of sensitive drug targets, the combinations of insensitive drug target and the combination of sensitive and insensitive targets. Finally, we applied our strategy to Arachidonic Acid (AA) metabolic network and found 18 pairs of synergistic drug target combinations, five of which have been proven to be viable by biological or medical experiments. CONCLUSIONS: Different from traditional methods for judging drug synergy and antagonism, we propose the framework of how to enhance the efficiency by perturbing two sensitive targets in a combinatorial way, how to decrease the drug dose and therefore its side effect and cost by perturbing combinatorially a main sensitive target and an auxiliary insensitive target, and how to perturb two insensitive targets to realize the transition from a disease state to a healthy one which cannot be realized by perturbing each insensitive target alone. Although the idea is mainly applied to an AA metabolic network, the strategy holds for more general molecular networks such as combinatorial regulation in gene regulatory networks.

Impulsive control of a nonlinear dynamical network and its application to biological networks.

The control of nonlinear dynamical systems is always a notable problem in science. According to control theory, suitable inputs for a controllable dynamical system are critical. Previous studies have shown some principles to determine control nodes and design control function. In this work, we propose a new control strategy of nonlinear systems by constructing impulsive control functions, i.e., we can realize the transition from an undesired state to a desired one by controlling appropriately chosen nodes in a discrete manner. In order to demonstrate the effectiveness of the strategy, we apply it to two biological networks: the epithelial-mesenchymal transition (EMT) network and the Notch1-Dll1-Jag1 signaling pathway. The strategy can not only be used to guide pharmacological design in a more feasible form but can also be applied into the fields of biological, medical and other multistable dynamical systems.

Identification of the gene Pm47 on chromosome 7BS conferring resistance to powdery mildew in the Chinese wheat landrace Hongyanglazi.

Powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), is an important disease that causes substantial yield losses in wheat (Triticum aestivum) in China and other parts of the world. This foliar disease can be effectively managed by host resistance. The Chinese landrace Hongyanglazi from Shaanxi province is highly resistant to many Bgt isolates at the seedling stage. Genetic analysis using an F2:3 population derived from a cross between Hongyanglazi and susceptible cultivar Zhongzuo 9504 indicated that Hongyanglazi carried a single recessive gene (tentatively designated PmHYLZ) conferring its resistance to Bgt isolate E09. PmHYLZ was flanked by EST marker BE606897 and microsatellite marker Xgwm46 on chromosome 7BS at genetic distances of 1.7 and 3.6 cM, respectively. This gene differed from Pm40, also located on 7BS, by origin, linked markers, and reactions to 13 Bgt isolates. Based on these findings, PmHYLZ was permanently designated as Pm47.

Ultrafast power Doppler imaging for ischemic encephalopathy: A case report.

BACKGROUND: Severely elevated intracranial pressure due to various reasons, such as decreased cerebral perfusion, can lead to devastating neurological outcomes, such as brain herniation. Decompression craniectomy is a life-saving procedure that is commonly performed for such a critical situation, but the changes in cerebral microvessels after brain herniation and decompression are unclear. Ultrafast power Doppler imaging (uPDI) is a new microvascular imaging technology that utilizes high frame rate plane/diverging wave transmission and advanced clutter filters. uPDI significantly improves Doppler sensitivity and can detect microvessels, which are usually invisible using traditional ultrasound Doppler imaging. CASE SUMMARY: In this report, uPDI was used for the first time to observe the brain blood flow of a hypoperfusion area in a 4-year-old girl who underwent decompression craniectomy due to refractory intracranial hypertension (ICP) after malignant brain tumor surgery. B-mode imaging was used to verify the increased densities of the cerebral cortex and basal ganglia that were observed by computed tomography. CONCLUSION: uPDI showed the local blood supplies and anatomical structures of the patient after decompressive craniectomy. uPDI is potentially a more intuitive and noninvasive method for evaluating the effects of severe ICP on cerebral microvessels.

Feedback regulation in a stem cell model with acute myeloid leukaemia.

BACKGROUND: The haematopoietic lineages with leukaemia lineages are considered in this paper. In particular, we mainly consider that haematopoietic lineages are tightly controlled by negative feedback inhibition of end-product. Actually, leukemia has been found 100 years ago. Up to now, the exact mechanism is still unknown, and many factors are thought to be associated with the pathogenesis of leukemia. Nevertheless, it is very necessary to continue the profound study of the pathogenesis of leukemia. Here, we propose a new mathematical model which include some negative feedback inhibition from the terminally differentiated cells of haematopoietic lineages to the haematopoietic stem cells and haematopoietic progenitor cells in order to describe the regulatory mechanisms mentioned above by a set of ordinary differential equations. Afterwards, we carried out detailed dynamical bifurcation analysis of the model, and obtained some meaningful results. RESULTS: In this work, we mainly perform the analysis of the mathematic model by bifurcation theory and numerical simulations. We have not only incorporated some new negative feedback mechanisms to the existing model, but also constructed our own model by using the modeling method of stem cell theory with probability method. Through a series of qualitative analysis and numerical simulations, we obtain that the weak negative feedback for differentiation probability is conducive to the cure of leukemia. However, with the strengthening of negative feedback, leukemia will be more difficult to be cured, and even induce death. In contrast, strong negative feedback for differentiation rate of progenitor cells can promote healthy haematopoiesis and suppress leukaemia. CONCLUSIONS: These results demonstrate that healthy progenitor cells are bestowed a competitive advantage over leukaemia stem cells. Weak g1, g2, and h1 enable the system stays in the healthy state. However, strong h2 can promote healthy haematopoiesis and suppress leukaemia.

Meta-analysis on the association between xeroderma pigmentosum Group A A23G polymorphism and esophageal cancer in a Chinese population.

AIM OF THE STUDY: Several studies have evaluated the correlation between xeroderma pigmentosum Group A (XPA) A23G polymorphism (rs 1800975) and esophageal cancer in Chinese people. However, the results are inconsistent. To assess the effects of XPA A23G variants on the risk for development of esophageal cancer in the Chinese population, a meta-analysis was performed. MATERIALS AND METHODS: Studies were identified using PubMed and Chinese databases through December 2015. The associations were assessed with pooled odds ratios (ORs) and 95% confidence intervals (95% CIs). RESULTS: This meta-analysis identified seven studies including 1514 esophageal cancer cases and 2120 controls. In the overall analysis, no significant association between XPA A23G polymorphism and esophageal cancer was found in the Chinese population. In the subgroup analyses by geographic area(s) and source of controls, significant results were only found in studies with hospital-based controls (GG vs. AA: OR = 0.42, 95% CI = 0.28-0.62; GG vs. AA + AG: OR = 0.55, 95% CI = 0.39-0.78; GG + AG vs. AA: OR = 0.54, 95% CI = 0.40-0.72; G vs. A: OR = 0.61, 95% CI = 0.50-0.75). CONCLUSIONS: This meta-analysis suggested that XPA A23G gene polymorphism may be one low-penetrant risk factor for esophageal cancer in Chinese individuals.