Both Ligand- and Cell-Specific Parameters Control Ligand Agonism in a Kinetic Model of G Protein–Coupled Receptor Signaling

G protein–coupled receptors (GPCRs) exist in multiple dynamic states (e.g., ligand-bound, inactive, G protein–coupled) that influence G protein activation and ultimately response generation. In quantitative models of GPCR signaling that incorporate these varied states, parameter values are often uncharacterized or varied over large ranges, making identification of important parameters and signaling outcomes difficult to intuit. Here we identify the ligand- and cell-specific parameters that are important determinants of cell-response behavior in a dynamic model of GPCR signaling using parameter variation and sensitivity analysis. The character of response (i.e., positive/neutral/inverse agonism) is, not surprisingly, significantly influenced by a ligand's ability to bias the receptor into an active conformation. We also find that several cell-specific parameters, including the ratio of active to inactive receptor species, the rate constant for G protein activation, and expression levels of receptors and G proteins also dramatically influence agonism. Expressing either receptor or G protein in numbers several fold above or below endogenous levels may result in system behavior inconsistent with that measured in endogenous systems. Finally, small variations in cell-specific parameters identified by sensitivity analysis as significant determinants of response behavior are found to change ligand-induced responses from positive to negative, a phenomenon termed protean agonism. Our findings offer an explanation for protean agonism reported in β2-adrenergic and α2A-adrenergic receptor systems

Heart Rate and Blood Flow Velocity Variability in the Human Fetus

Much of what we know about the embryonic circulation Is derived from studies of the chick embryo (Clark and Hu 1982). The similarities between the chick, rat (Nakazawa 1988) and fetal lamb (Kirkpatrick 1976) suggest that, while the details of functional change may vary, common mechanisms are expressed In these animal groups (Nakazawa 1988). Some of the mechanisms that control the cardiovascular system in the mature animal are expressed early In development (Clark 1990). The primary determinants of cardiovascular function in the embryo as in the mature animal are preload, afterload, heart rate and myocardial contractility. These factors regulate cardiac output before the development of the functioning autonomic nervous system. The Frank-Starling relationship Is operative and effective in both the fetal lamb heart (Kirkpatrick 1976) and the chick embryo (Wagman 1990). After maturation of the autonomic nervous system, both the parasympathetic and sympathetic systems control cardiovascular function in the fetal lamb (Nuwayhid 1975)

Emerging treatment options for BRAF-mutant colorectal cancer.

The personalization of cancer care is rooted in the premise that there are subsets of patients with tumors harboring clinically relevant targets for patient-specific treatments. Colorectal cancer (CRC) is a disease that has historically been notable for its dearth of biomarkers that are predictive of response to targeted therapies. In recent years, BRAFV600E-mutated CRC has emerged as a distinct biologic entity, typically refractory to standard chemotherapy regimens approved for the treatment of metastatic CRC and associated with a dismal prognosis. Multiple clinical trials sought to replicate the successes of targeted therapies seen in BRAFV600E-mutated melanoma without success; metastatic BRAFV600E-mutated CRC is clearly a distinct biologic entity. We review a number of recent studies demonstrating the evidence of modest responses to combinations of BRAF, EGFR, and/or MEK inhibition in patients with metastatic BRAFV600E-mutated CRC; however, despite advances, overall survival remains far inferior for these patients compared to their BRAF-wild-type counterparts. Development of combination therapies to impede signaling through the MAPK pathway through alternate targets remains an area of active investigation. Reflecting the rapid evolution of efforts for this small subset of CRC patients, the first-ever Phase III study is now underway evaluating the combination of BRAF, EGFR, and MEK inhibition. Immunotherapies are also an area of active research, particularly for the subset of patients with tumors that are also microsatellite instability (MSI) high. Here, we summarize the current landscape and emerging data on the molecular, clinical, and therapeutic aspects of BRAF-mutant CRC

Pathogenic DNA detection using DNA hairpins: a Non-Linear Hybridization Chain Reaction Platform

Currently, 3.2 billion people are at risk of being infected with malaria, with 1.2 billion of those being at high risk (\u3e1 in 1000 chance of getting malaria in a year). Thus, there is a need for a biosensor that is highly sensitive, cost effective, and simple to use for point-of-care diagnosis. The biosensing platform, PathVis, has achieved this by measuring changes in fluid properties after a loop-mediated isothermal amplification (LAMP). LAMP is a DNA amplification system that requires enzymes and a temperature of 65degrees C. LAMP currently limits PathVis by being costly, requiring refrigeration, and difficult to design. We seek to overcome these limitations by replacing this reaction with a non-enzymatic, low-cost, shelf stable, room temperature DNA amplification reaction. The hybridization chain reaction system (HCR) consists of two DNA hairpins that polymerize into long chains in the presence of target DNA. HCR can be designed to grow as linear polymers or branching polymers, the ladder providing exponential signal growth. We have developed an algorithm to generate hairpin systems for a given target DNA sequence. Using this algorithm, we have developed a branching HCR system for detecting malaria. We have found that this algorithm is extremely versatile and can generate hairpin systems for whole chromosomes (\u3e1,000,000 base pairs) in under five minutes. We have found that this malaria detection system theoretically amplifies in the presence of its target; resulting in a system that is ready to be optimized, experimentally tested, and validated on the PathVis biosensing platform

Selective Protein Labelling to Visualize Cellular Differentiation

Protein post-translational modifications serve to give proteins new cellular function, spatial localization, or enzymatic activity. Myristoylation is a common post-translational modification where the enzyme N-myristoyltransferase adds myristic acid onto the N-terminus of a variety of proteins. In this work we use a myristic acid analog, 12-azidododecanoic acid (12ADA) to facilitate the implementation of azide-alkyne cycloaddition reactions on myristoylated proteins. Selective protein labeling methods such as these are useful in research because they can be used to help determine the biological function of this protein lipid modification and can be extended to study disregulated protein myristoylation in disease states. To validate 12ADA incorporation onto proteins, C2C12 myoblast cell lysates were reacted with an alkyne functionalized fluorophore and analyzed via SDS-PAGE. In order to visualize 12ADA tagged proteins in vivo, fixed C2C12 cells were reacted with an alkyne functionalized fluorophore and were imaged with a fluorescent microscope. The results clearly indicate selective protein tagging in in vitro lysates and in vivo. There is a distinct difference in the patterning of 12ADA protein tagging between differentiated and non-differentiated cells. The purpose of this research is to develop a selective protein labeling method. In our research, this selective protein labeling method is used to studying cellular differentiation in the context of developmental biology. Currently, there is not a clear understanding of the proteins associated with cellular differentiation related to development. Understanding this can allow scientists to track development progress and understand unique proteins associated with differentiating cells

Horticulture of Nutmeg: Germination, Propagation and Cultivation

The living collection of plants in the nutmeg family, Myristicaceae, has been increasing at the Botanic Garden of Delft University of Technology (Delft BG) since 2001. Horticultural and research staff there have been exploring the horticultural requirements, molecular structure and chemical composition of these plants since then. This paper comments on the historical importanceof this family and the processes required to acquire live plant material. In recent years the significance of the mycorrhizal associations formed by the family and the consequences for their cultivation have been identified and these are described here along with the most effective methods of propagation as identified by staff at Delft BG

Competitive Tuning of Calmodulin Target Protein Activation Drives E-LTP Induction in CA1 Hippocampal Neurons

A number of neurological disorders are caused by disruptions in dynamic neuronal connections called synapses. Normally, electrical activity between neurons activates protein cascades that cause long-lasting, localized changes in the structure and molecular composition of synapses. These changes either increase or decrease the strength of synaptic connections, leading to long-term-potentiation (LTP) or long-term-depression (LTD), respectively. The protein cascades responsible for this synaptic plasticity are initiated in a stimulus-dependent manner by the Ca2+ sensor calmodulin (CaM). Ultimately, it is disruptions within these signaling pathways that cause disease. Traditionally, these protein networks are studied in the laboratory, but limitations in existing experimental technology have created demand for computational models capable of predicting molecular phenomena. These predictions can then guide focused experimental investigations. Although CaM binds and regulates over 100 different target proteins, the competitive dynamics of these proteins and their effect on LTP induction have not been investigated. Using a system of ordinary differential equations to model competition between four neuronal CaM target proteins, we found that the stimulus-dependence of target protein activation is tuned by competition and that this competitive tuning is unique to each protein. We therefore conclude that competition-free models fail to capture the true stimulus-dependence of Ca2+/calmodulin-dependent protein kinase II (CaMKII) and protein phosphatase 2B (PP2B/calcineurin/CaN) activation. Furthermore, these results suggest that competitive tuning drives early LTP (E-LTP) induction in CA1 hippocampal neurons and is an important dynamic process underlying learning and memory. Therapeutics that re-tune CaM-dependent proteins through competition may be useful in treating neurological disorders

Exploring the Performance of an Evolutionary Algorithm for Greenhouse Control

Evolutionary algorithms for optimization of dynamic problems have recently received increasing attention. Online control is a particularly interesting class of dynamic problems, because of the interactions between the controller and the controlled system. In this paper, we report experimental results on two aspects of the direct control strategy in relation to a crop-producing greenhouse. In the first set of experiments, we investigated how to balance the available computation time between population size and generations. The second experiments were on different control horizons, and showed the importance of this aspect for direct control. Finally, we discuss the results in the wider context of dynamic optimization

Value creating factors in sharing economy platform businesses

Sharing economy in 2022 is more relevant than ever, when the world is recovering from a once in a lifetime pandemic that shut down most global commerce for nearly two years. Almost overnight, the world went from global supply chains and production optimization to local production and resourcing. Even now, after more than two years since the pandemic started, global supply chains are still suffering from production disruptions and scarcity of resources. Limitless quantitative easing combined with supply chain issues have skyrocketed inflation up to a level not seen in the 21st century, while cheap interest rate fueled lending has increased the level of debt to new global heights, making interest rate hikes difficult. With global travel almost all but eliminated, the travel and hospitality industries as well as ride-hailing industries suffered immensely for two years. Now, with the world opening, shortages in building materials and vehicle production have made the rebound difficult for traditional companies. Luckily the new sharing economy platform companies within these industries have shown incredible resilience and adaptability, and this resilience has allowed them to bounce back much quicker than their traditional competitors. The purpose of this thesis is to find out what are the factors behind sharing economy platform businesses that allow them to thrive in today’s competitive landscape and ensure a durable, competitive advantage. The study is composed of a theoretical and empirical part, where two industries (hospitality and ride-hailing) are analyzed and compared with each other. In the ride-hailing industry there are two companies, Uber Technologies and Lyft, and in the hospitality industries there are Airbnb, Booking Holdings, Expedia Group, TripAdvisor and Trip.com. Earlier research on this area has yielded some ideas of which factors seem to have a positive impact on value creation, but there is a serious gap in empirical evidence that would support their views. This thesis attempts to close this gap by taking an in-depth look at different value driving factors and testing their effect on revenue generation by running a series of regressions on different variables. The study relies on the assumption that market efficiency theories hold true and that the value of a business is all its future cash flows to shareholders discounted to today with the appropriate discount rate. Findings are mixed in this research, supporting some of the value creating factors found in academic research. There are three main value driving factors within the sharing economy platform businesses: attracting a network of users and incentivizing them, incremental improvements to the platform and saturating the market. Some of the factors seem to have a bigger impact than others and show a higher correlation, however, proving a conclusive causation between factors and value proved to be impractical. This thesis also argues that there are no major differences between platform businesses and any other business when it comes to sustained success. Platform companies also have to build a rational business model that is protected against outside threats and manage them in a way that is intelligent, focused on the long-term and offer products that bring true value to the participants. The findings of this thesis shed some light on the intricate nature of platform value, which as a concept is not well understood in the current theoretical grounding

Analysis and modeling of control tasks in dynamic systems

Copyright © 2002 IEEEMost applications of evolutionary algorithms deal with static optimization problems. However, in recent years, there has been a growing interest in time-varying (dynamic) problems, which are typically found in real-world scenarios. One major challenge in this field is the design of realistic test-case generators (TCGs), which requires a systematic analysis of dynamic optimization tasks. So far, only a few TCGs have been suggested. Our investigation leads to the conclusion that these TCGs are not capable of generating realistic dynamic benchmark tests. The result of our research is the design of a new TCG capable of producing realistic nonstationary landscapesRasmus K. Ursem, Thiemo Krink, Mikkel T. Jensen, and Zbigniew Michalewic