Subunit communication in the tryptophan synthase α2β2 complex Effects of β subunit ligands on proteolytic cleavage of a flexible loop in the α subunit

AbstractTo probe the structural basis for ligand-mediated communication between the α and β subunits in the tryptophan synthase α2β2 complex, we have determined the effects of ligands of the α and β subunits on proteolysis of a flexible loop in the α subunit. We find that addition of a ligand of the β subunit (l-serine, d-tryptophan, or l-tryptophan) in combination with a ligand of the α subunit (α-glycerol 3-phosphate) almost completely prevents the tryptic cleavage of the α subunit loop. Thus, the binding of a ligand to the β-site affects the conformation of the α subunit 25–30 Å distant

Recurrent Neural Network Dual Resistance Control of Multiple Memory Shape Memory Alloys

Shape memory alloys (SMAs) are materials with extraordinary thermomechanical properties which have caused numerous engineering advances. NiTi SMAs in particular have been studied for decades revealing many useful characteristics relative to other SMA compositions. Their application has correspondingly been widespread, seeing use in the robotics, automotive, and aerospace industries, among others. Nevertheless, several limitations inherent to SMAs exist which inhibit their applicability, including their inherent single transformation temperature and their complex hysteretic actuation behaviour. To overcome the former challenge, one method utilizes high energy laser processing to perform localized vaporization of nickel and accurately adjust its transformation temperatures. This method can reliably produce NiTi SMAs with multiple monolithic transformation memories. There have also been attempts to overcome the latter of the aforementioned challenges by designing systems which model NiTi's hysteretic behaviour. When applied to actuators with a single transformation memory, these methods require the use of external sensors for modeling actuators with varying current and load, driving up the cost, weight, and complexity of the actuator. Embedding a second transformation memory with different phase into NiTi actuators can overcome this issue. By measuring electrical resistance across the two phases, sufficient information can be extracted for differentiating events caused by heating from those caused by applied load. The current study examines NiTi wires with two embedded transformation memories and utilizes recurrent neural networks for interpreting the sensed data. The knowledge gained through this study was used to create a recurrent neural network-based model which can accurately estimate the position and force applied to the NiTi actuator without the use of external sensors. The first part of the research focused on obtaining a comprehensive thermomechanical characterization of laser processed and thermomechanically post-processed NiTi wires with two embedded transformation memories, with one memory exhibiting full SME and the second partial PE at room temperature. A second objective of this section was to acquire cycling data from the processed wires which would be used for training the artificial neural networks in the following section of the study. The selected laser processing and post-processing parameters resulted in a transformation temperature increase of 61.5°C and 35.3°C for Af and Ms, respectively, relative to base metal. Furthermore, the post-processing was found to successfully restore the majority of the lost mechanical properties, with the ultimate tensile strength recovered to 84% of its corresponding base metal value. This research resulted in the fabrication of NiTi wires with two distinct embedded transformation memories, exhibiting sufficient mechanical and cyclic properties for the next phase of the research. Once an acceptable amount of NiTi actuation cycling data was acquired, the second part of the research consisted of training multiple recurrent neural network architectures with varying hyperparameters on the data and selecting the model which achieved the best performance. The hyperparameter optimization was performed on data with constant applied load, resulting in a model which successfully estimated the actuator's position with 99.2% accuracy. The optimized hyperparameters were then used to create a recurrent neural network model which was trained to estimate both position and force using the full acquired data set, capitalizing on the two embedded memories. The model achieved overall position and force estimation accuracy of 98.5% and 96.0%, respectively, on data used to train it, and 96.6% and 89.8%, respectively, on data it had never before encountered. The result of this study was the successful development of an accurate RNN-based position and force estimation model for NiTi actuators with two embedded phases. Using this model, a position controller was implemented which resulted in 95.9% position accuracy under varying applied loads

Intrapericardial Delivery of Gelfoam Enables the Targeted Delivery of Periostin Peptide after Myocardial Infarction by Inducing Fibrin Clot Formation

Background: Administration of a recombinant peptide of Periostin (rPN) has recently been shown to stimulate cardiomyocyte proliferation and angiogensis after myocardial infarction (MI). However, strategies for targeting the delivery of rPN to the heart are lacking. Intrapericardial administration of drug-eluting hydrogels may provide a clinically viable strategy for increasing myocardial retention, therapeutic efficacy, and bioactivity of rPN and to decrease systemic re-circulation. Methods and Results: We investigated the ability of intrapericardial injections of drug-eluting hydrogels to deliver and prolong the release of rPN to the myocardium in a large animal model of myocardial infarction. Gelfoam is an FDA-approved hemostatic material commonly used in surgery, and is known to stimulate fibrin clot formation. We show that Gelfoam disks loaded with rPN, when implanted within the pericardium or peritoneum of mammals becomes encapsulated within a non-fibrotic fibrin-rich hydrogel, prolonging the in vitro and in vivo release of rPN. Administration into the pericardial cavity of pigs, following a complete occlusion of the left anterior descending artery, leads to greater induction of cardiomyocyte mitosis, increased cardiomyocyte cell cycle activity, and enhanced angiogenesis compared to direct injection of rPN alone. Conclusions: The results of this study suggest that intrapericardial drug delivery of Gelfoam, enhanced by triggered clot formation, can be used to effectively deliver rPN to the myocardium in a clinically relevant model of myocardial infarction. The work presented here should enhance the translational potential of pharmaceutical-based strategies that must be targeted to the myocardium

Why are proteins marginally stable?

Most globular proteins are marginally stable regardless of size or activity. The most common interpretation is that proteins must be marginally stable in order to function, and so marginal stability represents the results of positive selection. We consider the issue of marginal stability directly using model proteins and the dynamical aspects of protein evolution in populations. We find that the marginal stability of proteins is an inherent property of proteins due to the high dimensionality of the sequence space, without regard to protein function. In this way, marginal stability can result from neutral, non-adaptive evolution. By allowing evolving protein sub-populations with different stability requirements for functionality to complete, we find that marginally stable populations of proteins tend to dominate. Our results show that functionalities consistent with marginal stability have a strong evolutionary advantage, and might arise because of the natural tendency of proteins towards marginal stability. Proteins 2002;46:105–109. © 2001 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/34974/1/10016_ftp.pd

Ischemia-Reperfusion Injury and Pregnancy Initiate Time-Dependent and Robust Signs of Up-Regulation of Cardiac Progenitor Cells

To explore how cardiac regeneration and cell turnover adapts to disease, different forms of stress were studied for their effects on the cardiac progenitor cell markers c-Kit and Isl1, the early cardiomyocyte marker Nkx2.5, and mast cells. Adult female rats were examined during pregnancy, after myocardial infarction and ischemia-reperfusion injury with/out insulin like growth factor-1(IGF-1) and hepatocyte growth factor (HGF). Different cardiac sub-domains were analyzed at one and two weeks post-intervention, both at the mRNA and protein levels. While pregnancy and myocardial infarction up-regulated Nkx2.5 and c-Kit (adjusted for mast cell activation), ischemia-reperfusion injury induced the strongest up-regulation which occurred globally throughout the entire heart and not just around the site of injury. This response seems to be partly mediated by increased endogenous production of IGF-1 and HGF. Contrary to c-Kit, Isl1 was not up-regulated by pregnancy or myocardial infarction while ischemia-reperfusion injury induced not a global but a focal up-regulation in the outflow tract and also in the peri-ischemic region, correlating with the up-regulation of endogenous IGF-1. The addition of IGF-1 and HGF did boost the endogenous expression of IGF and HGF correlating to focal up-regulation of Isl1. c-Kit expression was not further influenced by the exogenous growth factors. This indicates that there is a spatial mismatch between on one hand c-Kit and Nkx2.5 expression and on the other hand Isl1 expression. In conclusion, ischemia-reperfusion injury was the strongest stimulus with both global and focal cardiomyocyte progenitor cell marker up-regulations, correlating to the endogenous up-regulation of the growth factors IGF-1 and HGF. Also pregnancy induced a general up-regulation of c-Kit and early Nkx2.5+ cardiomyocytes throughout the heart. Utilization of these pathways could provide new strategies for the treatment of cardiac disease

Articular cartilage regeneration using acellular bioactive affinity-binding alginate hydrogel: A 6-month study in a mini-pig model of osteochondral defects

Background: Despite intensive research, regeneration of articular cartilage largely remains an unresolved medical concern as the clinically available modalities still suffer from long-term inconsistent data, relatively high failure rates and high prices of more promising approaches, such as cell therapy. In the present study, we aimed to evaluate the feasibility and long-term efficacy of a bilayered injectable acellular affinity-binding alginate hydrogel in a large animal model of osteochondral defects. Methods: The affinity-binding alginate hydrogel is designed for presentation and slow release of chondrogenic and osteogenic inducers (transforming growth factor-β1 and bone morphogenic protein 4, respectively) in two distinct and separate hydrogel layers. The hydrogel was injected into the osteochondral defects created in the femoral medial condyle in mini-pigs, and various outcomes were evaluated after 6 months. Results: Macroscopical and histological assessment of the defects treated with growth factor affinity-bound hydrogel showed effective reconstruction of articular cartilage layer, with major features of hyaline tissue, such as a glossy surface and cellular organisation, associated with marked deposition of proteoglycans and type II collagen. Microcomputed tomography showed incomplete bone formation in both treatment groups, which was nevertheless augmented by the presence of affinity-bound growth factors. Importantly, the physical nature of the applied hydrogel ensured its shear resistance, seamless integration and topographical matching to the surroundings and opposing articulating surface. Conclusions: The treatment with acellular injectable growth factor–loaded affinity-binding alginate hydrogel resulted in effective tissue restoration with major hallmarks of hyaline cartilage, shown in large animal model after 6-month follow-up. The translational potential of this article: This proof-of-concept study in a clinically relevant large animal model showed promising potential of an injectable acellular growth factor–loaded affinity-binding alginate hydrogel for effective repair and regeneration of articular hyaline cartilage, representing a strong candidate for future clinical development. Keywords: Affinity-binding alginate, Bone morphogenic protein 4, Hyaline cartilage, Osteochondral defect, Transforming growth factor-β

Automatic GAN-based MRI volume synthesis from US volumes: a proof of concept investigation

Usually, a baseline image, either through magnetic resonance imaging (MRI) or computed tomography (CT), is captured as a reference before medical procedures such as respiratory interventions like Thoracentesis. In these procedures, ultrasound (US) imaging is often employed for guiding needle placement during Thoracentesis or providing image guidance in MISS procedures within the thoracic region. Following the procedure, a post-procedure image is acquired to monitor and evaluate the patient’s progress. Currently, there are no real-time guidance and tracking capabilities that allow a surgeon to perform their procedure using the familiarity of the reference imaging modality. In this work, we propose a real-time volumetric indirect registration using a deep learning approach where the fusion of multi-imaging modalities will allow for guidance and tracking of surgical procedures using US while displaying the resultant changes in a clinically friendly reference imaging modality (MRI). The deep learning method employs a series of generative adversarial networks (GANs), specifically CycleGAN, to conduct an unsupervised image-to-image translation. This process produces spatially aligned US and MRI volumes corresponding to their respective input volumes (MRI and US) of the thoracic spine anatomical region. In this preliminary proof-of-concept study, the focus was on the T9 vertebrae. A clinical expert performs anatomical validation of randomly selected real and generated volumes of the T9 thoracic vertebrae and gives a score of 0 (conclusive anatomical structures present) or 1 (inconclusive anatomical structures present) to each volume to check if the volumes are anatomically accurate. The Dice and Overlap metrics show how accurate the shape of T9 is when compared to real volumes and how consistent the shape of T9 is when compared to other generated volumes. The average Dice, Overlap and Accuracy to clearly label all the anatomical structures of the T9 vertebrae are approximately 80% across the board