Integrating Quantitative Knowledge into a Qualitative Gene Regulatory Network

Despite recent improvements in molecular techniques, biological knowledge remains incomplete. Any theorizing about living systems is therefore necessarily based on the use of heterogeneous and partial information. Much current research has focused successfully on the qualitative behaviors of macromolecular networks. Nonetheless, it is not capable of taking into account available quantitative information such as time-series protein concentration variations. The present work proposes a probabilistic modeling framework that integrates both kinds of information. Average case analysis methods are used in combination with Markov chains to link qualitative information about transcriptional regulations to quantitative information about protein concentrations. The approach is illustrated by modeling the carbon starvation response in Escherichia coli. It accurately predicts the quantitative time-series evolution of several protein concentrations using only knowledge of discrete gene interactions and a small number of quantitative observations on a single protein concentration. From this, the modeling technique also derives a ranking of interactions with respect to their importance during the experiment considered. Such a classification is confirmed by the literature. Therefore, our method is principally novel in that it allows (i) a hybrid model that integrates both qualitative discrete model and quantities to be built, even using a small amount of quantitative information, (ii) new quantitative predictions to be derived, (iii) the robustness and relevance of interactions with respect to phenotypic criteria to be precisely quantified, and (iv) the key features of the model to be extracted that can be used as a guidance to design future experiments

Assessing mechanical integrity of spinal fusion by in situ endochondral osteoinduction in the murine model

<p>Abstract</p> <p>Background</p> <p>Historically, radiographs, micro-computed tomography (micro-CT) exams, palpation and histology have been used to assess fusions in a mouse spine. The objective of this study was to develop a faster, cheaper, reproducible test to directly quantify the mechanical integrity of spinal fusions in mice.</p> <p>Methods</p> <p>Fusions were induced in ten mice spine using a previously described technique of in situ endochondral ossification, harvested with soft tissue, and cast in radiolucent alginate material for handling. Using a validated software package and a customized mechanical apparatus that flexed and extended the spinal column, the amount of intervertebral motion between adjacent vertebral discs was determined with static flexed and extended lateral spine radiographs. Micro-CT images of the same were also blindly reviewed for fusion.</p> <p>Results</p> <p>Mean intervertebral motion between control, non-fused, spinal vertebral discs was 6.1 ± 0.2° during spine flexion/extension. In fusion samples, adjacent vertebrae with less than 3.5° intervertebral motion had fusions documented by micro-CT inspection.</p> <p>Conclusions</p> <p>Measuring the amount of intervertebral rotation between vertebrae during spine flexion/extension is a relatively simple, cheap (<$100), clinically relevant, and fast test for assessing the mechanical success of spinal fusion in mice that compared favorably to the standard, micro-CT.</p

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

New York: The Next Mecca for Judgment Creditors? An Analysis of Koehler v. Bank of Bermuda Ltd.

New York may have just become a great place to be a judgment creditor. In the summer of 2009, the Court of Appeals of New York handed down its decision in Koehler v. Bank of Bermuda Ltd. In Koehler, the court upheld a turnover order directing a garnishee to transfer a nonresident judgment debtor’s assets, deposited in a Bermuda bank, into New York. Under Koehler, assets anywhere in the world may now be garnishable in New York so long as the garnishee is subject to the state’s jurisdiction. This decision greatly broadens New York courts’ power to enforce judgments by reaching property located outside of New York. Accordingly, the decision is an incredible victory for judgment creditors, yet a serious defeat for judgment debtors. Because of New York’s status as a financial and corporate capital—and the concomitant number of institutions doing business within the state—this decision has a potentially far-reaching impact. Perhaps not surprisingly, the Koehler decision raises some serious constitutional and policy concerns. As some commentators fear, the decision may ultimately turn New York courts into a “mecca” for judgment creditors seeking to reach assets located anywhere in the world. This Comment seeks to explore the issues raised by the Koehler decision. In doing so, this Comment analyzes theories of due process and state power in the realm of postjudgment garnishments. This Comment ultimately concludes that the Koehler decision was correctly decided, particularly because it will afford judgment creditors an incredibly useful tool in satisfying their judgments

Functional adaptation of bone: The mechanostat and beyond

The conceptual model of the mechanostat proposed by Harold Frost in 1983 is among the most significant contributions to musculoskeletal research today. This model states that bone and other musculoskeletal tissues including cartilage, tendon and muscle respond to habitual exercise/loading and that changes in the loading environment lead to adequate structural adaptation of (bone) tissue architecture. The analogy with a thermostat clearly indicates presence of a physiological feedback system which is able to adjust bone mass and structure according to the engendered loads. In the bioengineering community, the mechanostat has been mathematically formulated as a feedback algorithm using a set point criterion based on a particular mechanical quantity such as strain, strain energy density among others. As pointed out by Lanyon and Skerry, while it is widely thought that in a single individual, there exists a single mechanostat set point, this view is flawed by the fact that different bones throughout the skeleton require a specific strain magnitude to maintain bone mass. Consequently, different bones respond differently to increases or decreases in loading depending on the sensitivity of the mechanostat. Osteocytes, i.e., cells embedded in the bone matrix are believed to be the major bone cells involved in sensing and transduction of mechanical loads. The purpose of this chapter is to review the concept of the mechanostat and its role in bone pathophysiology. To do this we provide examples of why and how the skeleton responds to complex loading stimuli made up of numerous different parameters including strain magnitude, frequency and rest intervals among others. We describe latest in vivo and ex vivo loading models, which allow exploration of various mechanobiological relations in the mechanostat model utilising controlled mechanical environments. A review of the bone cells and signalling transduction cascades involved in mechanosensation and bone adaptation will also be provided. Furthermore, we will discuss the mechanostat in a clinical context, e.g., how factors such as sex, age, genetic constitution, concomitant disease, nutrient availability, and exposure to drugs all affect bone’s response to mechanical loading. Understanding the mechanostat and mechanobiological regulatory factors involved in mechanosensation and desensitisation is essential for our ability to control bone mass based on physiological loading, either directly through different exercise regimens, or by manipulating bone cells in a targeted manner using tailored site and individual specific stimuli including pharmaceuticals