Heat Shock Alters the Proteomic Profile of Equine Mesenchymal Stem Cells

The aim of this research was to determine the impact of heat stress on cell differentiation in an equine mesenchymal stem cell model (EMSC) through the application of heat stress to primary EMSCs as they progressed through the cell specialization process. A proteomic analysis was performed using mass spectrometry to compare relative protein abundances among the proteomes of three cell types: progenitor EMSCs and differentiated osteoblasts and adipocytes, maintained at 37 °C and 42 °C during the process of cell differentiation. A cell-type and temperature-specific response to heat stress was observed, and many of the specific differentially expressed proteins were involved in cell-signaling pathways such as Notch and Wnt signaling, which are known to regulate cellular development. Furthermore, cytoskeletal proteins profilin, DSTN, SPECC1, and DAAM2 showed increased protein levels in osteoblasts differentiated at 42 °C as compared with 37 °C, and these cells, while they appeared to accumulate calcium, did not organize into a whorl agglomerate as is typically seen at physiological temperatures. This altered proteome composition observed suggests that heat stress could have long-term impacts on cellular development. We propose that this in vitro stem cell culture model of cell differentiation is useful for investigating molecular mechanisms that impact cell development in response to stressors.     

Ubiquitin Ligases in Longevity and Aging Skeletal Muscle

The development and prevalence of diseases associated with aging presents a global health burden on society. One hallmark of aging is the loss of proteostasis which is caused in part by alterations to the ubiquitin–proteasome system (UPS) and lysosome–autophagy system leading to impaired function and maintenance of mass in tissues such as skeletal muscle. In the instance of skeletal muscle, the impairment of function occurs early in the aging process and is dependent on proteostatic mechanisms. The UPS plays a pivotal role in degradation of misfolded and aggregated proteins. For the purpose of this review, we will discuss the role of the UPS system in the context of age-related loss of muscle mass and function. We highlight the significant role that E3 ubiquitin ligases play in the turnover of key components (e.g., mitochondria and neuromuscular junction) essential to skeletal muscle function and the influence of aging. In addition, we will briefly discuss the contribution of the UPS system to lifespan. By understanding the UPS system as part of the proteostasis network in age-related diseases and disorders such as sarcopenia, new discoveries can be made and new interventions can be developed which will preserve muscle function and maintain quality of life with advancing age.     

Proteomic Biomarkers of the Apnea Hypopnea Index and Obstructive Sleep Apnea: Insights into the Pathophysiology of Presence,Severity, and Treatment Response

Obstructive sleep apnea (OSA), a disease associated with excessive sleepiness and increased cardiovascular risk, affects an estimated 1 billion people worldwide. The present study examined proteomic biomarkers indicative of presence, severity, and treatment response in OSA. Participants (n = 1391) of the Stanford Technology Analytics and Genomics in Sleep study had blood collected and completed an overnight polysomnography for scoring the apnea–hypopnea index (AHI). A highly multiplexed aptamer-based array (SomaScan) was used to quantify 5000 proteins in all plasma samples. Two separate intervention-based cohorts with sleep apnea (n = 41) provided samples pre- and post-continuous/positive airway pressure (CPAP/PAP). Multivariate analyses identified 84 proteins (47 positively, 37 negatively) associated with AHI after correction for multiple testing. Of the top 15 features from a machine learning classifier for AHI ≥ 15 vs. AHI < 15 (Area Under the Curve (AUC) = 0.74), 8 were significant markers of both AHI and OSA from multivariate analyses. Exploration of pre- and post-intervention analysis identified 5 of the 84 proteins to be significantly decreased following CPAP/PAP treatment, with pathways involving endothelial function, blood coagulation, and inflammatory response. The present study identified PAI-1, tPA, and sE-Selectin as key biomarkers and suggests that endothelial dysfunction and increased coagulopathy are important consequences of OSA, which may explain the association with cardiovascular disease and stroke.     

Tumor-Localized Administration of α-GalCer to Recruit Invariant Natural Killer T Cells and Enhance Their Antitumor Activity against Solid Tumors

Invariant natural killer T (iNKT) cells have the capacity to mount potent anti-tumor reactivity and have therefore become a focus in the development of cell-based immunotherapy. iNKT cells attack tumor cells using multiple mechanisms with a high efficacy; however, their clinical application has been limited because of their low numbers in cancer patients and difficulties in infiltrating solid tumors. In this study, we aimed to overcome these critical limitations by using α-GalCer, a synthetic glycolipid ligand specifically activating iNKT cells, to recruit iNKT to solid tumors. By adoptively transferring human iNKT cells into tumor-bearing humanized NSG mice and administering a single dose of tumor-localized α-GalCer, we demonstrated the rapid recruitment of human iNKT cells into solid tumors in as little as one day and a significantly enhanced tumor killing ability. Using firefly luciferase-labeled iNKT cells, we monitored the tissue biodistribution and pharmacokinetics/pharmacodynamics (PK/PD) of human iNKT cells in tumor-bearing NSG mice. Collectively, these preclinical studies demonstrate the promise of an αGC-driven iNKT cell-based immunotherapy to target solid tumors with higher efficacy and precision.     

A new approach to the learning effect: Beyond the learning curve restrictions

In this paper, we bring into the scheduling field a new model of the learning effect, where in two ways the existing approach is generalized. First we relax one of the rigorous constraints, and thus in our model each job can provide different experience to the processor. Second we formulate the job processing time as a non-increasing k-stepwise function, that, in general, is not restricted to a certain learning curve, thereby it can accurately fit every possible shape of a learning function. Furthermore, we prove that the problem of makespan minimization with the considered model is polynomially solvable if every job provides the same experience to the processor, and it becomes NP-hard if the experiences are diversified. The most essential result is a pseudopolynomial time algorithm that solves optimally the makespan minimization problem with any function of an experience-based learning model reduced into the form of the k-stepwise function.     

A sensor-driven approach to Web-based machining

The objective of this research is to develop a framework named Wise-ShopFloor and the enabling technologies for collaborative manufacturing in a decentralized environment. Particularly, this paper presents our latest development on Web-based and sensor-driven remote machining. Once a product design is given, its process plan and NC codes are generated by using a distributed process planning (DPP) system. The NC codes are then used for remote machining via a standard Web browser and a Java GUI interface running inside the browser. In this paper, the focus is given to the concept, architecture and a prototype implementation of the enabling technology. A case study of a test part machining on a 5-axis milling machine is also completed for testing and validation. It is expected that the developed technology can be applied to design verification via remote machining as well as real part production in a distributed manufacturing environment.     

Energy-based scatter correction for 3-D PET scanners using NaI(T1) detectors

Earlier investigations with BGO positron emission tomography (PET) scanners showed that the scatter correction technique based on multiple acquisitions with different energy windows are problematic to implement because of the poor energy resolution of BGO (22%), particularly for whole-body studies. We believe that these methods are likely to work better with NaI(TI) because of the better energy resolution achievable with NaI(TI) detectors (10%). Therefore, we investigate two different choices for the energy window, a low-energy window (LEW) on the Compton spectrum at 400-450 keV, and a high-energy window (HEW) within the photopeak (lower threshold above 511 keV). The results obtained for our three-dimensional (3-D) (septa-less) whole-body scanners [axial field of view (FOV) of 12.8 cm and 25.6 cm] as well as for our 3-D brain scanner (axial FOV of 25.6 cm) show an accurate prediction of the scatter distribution for the estimation of trues method (ETM) using a HEW, leading to a significant reduction of the scatter contamination. The dual-energy window (DEW) technique using a LEW is shown to be intrinsically wrong; in particular, it fails for line source and bar phantom measurements. However, the method is able to produce good results for homogeneous activity distributions. Both methods are easy to implement, are fast, have a low noise propagation, and will be applicable to other PET scanners with good energy resolution and stability, such as hybrid NaI(TI) PET/SPECT dual-head cameras and future PET cameras with GSO or LSO scintillators.     

PriorVAE: encoding spatial priors with variational autoencoders for small-area estimation

Gaussian processes (GPs), implemented through multivariate Gaussian distributions for a finite collection of data, are the most popular approach in small-area spatial statistical modelling. In this context, they are used to encode correlation structures over space and can generalize well in interpolation tasks. Despite their flexibility, off-the-shelf GPs present serious computational challenges which limit their scalability and practical usefulness in applied settings. Here, we propose a novel, deep generative modelling approach to tackle this challenge, termed PriorVAE: for a particular spatial setting, we approximate a class of GP priors through prior sampling and subsequent fitting of a variational autoencoder (VAE). Given a trained VAE, the resultant decoder allows spatial inference to become incredibly efficient due to the low dimensional, independently distributed latent Gaussian space representation of the VAE. Once trained, inference using the VAE decoder replaces the GP within a Bayesian sampling framework. This approach provides tractable and easy-to-implement means of approximately encoding spatial priors and facilitates efficient statistical inference. We demonstrate the utility of our VAE two-stage approach on Bayesian, small-area estimation tasks.     

Consecutive Aromatic Residues Are Required for Improved Efficacy of β-Sheet Breakers

Alzheimer’s disease is a fatal neurodegenerative malady which up to very recently did not have approved therapy modifying its course. After controversial approval of aducanumab (monoclonal antibody clearing β-amyloid plaques) by FDA for use in very early stages of disease, possibly new avenue opened for the treatment of patients. In line with this approach is search for compounds blocking aggregation into amyloid oligomers subsequently forming fibrils or compounds helping in getting rid of plaques formed by β-amyloid fibrils. Here we present in silico work on 627 sixtapeptide β-sheet breakers (BSBs) containing consecutive three aromatic residues. Three of these BSBs caused dissociation of one or two β-amyloid chains from U-shaped β-amyloid protofibril model 2BEG after docking and subsequent molecular dynamics simulations. Thorough analysis of our results let us postulate that the first steps of binding these successful BSBs involve π–π interactions with stacked chains of F19 and later also with F20 (F3 and F4 in 2BEG model of protofibril). The consecutive location of aromatic residues in BSBs makes them more attractive for chains of stacked F3 and F4 within the 2BEG model. Spotted by us, BSBs may be prospective lead compounds for an anti-Alzheimer’s therapy.     

In Vitro Cytotoxicity,Colonisation by Fibroblasts and Antimicrobial Properties of Surgical Meshes Coated with Bacterial Cellulose

Hernia repairs are the most common abdominal wall elective procedures performed by general surgeons. Hernia-related postoperative infective complications occur with 10% frequency. To counteract the risk of infection emergence, the development of effective, biocompatible and antimicrobial mesh adjuvants is required. Therefore, the aim of our in vitro investigation was to evaluate the suitability of bacterial cellulose (BC) polymer coupled with gentamicin (GM) antibiotic as an absorbent layer of surgical mesh. Our research included the assessment of GM-BC-modified meshes’ cytotoxicity against fibroblasts ATCC CCL-1 and a 60-day duration cell colonisation measurement. The obtained results showed no cytotoxic effect of modified meshes. The quantified fibroblast cells levels resembled a bimodal distribution depending on the time of culturing and the type of mesh applied. The measured GM minimal inhibitory concentration was 0.47 µg/mL. Results obtained in the modified disc-diffusion method showed that GM-BC-modified meshes inhibited bacterial growth more effectively than non-coated meshes. The results of our study indicate that BC-modified hernia meshes, fortified with appropriate antimicrobial, may be applied as effective implants in hernia surgery, preventing risk of infection occurrence and providing a high level of biocompatibility with regard to fibroblast cells.