Photorhabdus luminescens TccC3 Toxin Targets the Dynamic Population of F-Actin and Impairs Cell Cortex Integrity

Due to its essential role in cellular processes, actin is a common target for bacterial toxins. One such toxin, TccC3, is an effector domain of the ABC-toxin produced by entomopathogenic bacteria of Photorhabdus spp. Unlike other actin-targeting toxins, TccC3 uniquely ADP-ribosylates actin at Thr-148, resulting in the formation of actin aggregates and inhibition of phagocytosis. It has been shown that the fully modified F-actin is resistant to depolymerization by cofilin and gelsolin, but their effects on partially modified actin were not explored. We found that only F-actin unprotected by tropomyosin is the physiological TccC3 substrate. Yet, ADP-ribosylated G-actin can be produced upon cofilin-accelerated F-actin depolymerization, which was only mildly inhibited in partially modified actin. The affinity of TccC3-ADP-ribosylated G-actin for profilin and thymosin-β4 was weakened moderately but sufficiently to potentiate spontaneous polymerization in their presence. Interestingly, the Arp2/3-mediated nucleation was also potentiated by T148-ADP-ribosylation. Notably, even partially modified actin showed reduced bundling by plastins and α-actinin. In agreement with the role of these and other tandem calponin-homology domain actin organizers in the assembly of the cortical actin network, TccC3 induced intense membrane blebbing in cultured cells. Overall, our data suggest that TccC3 imposes a complex action on the cytoskeleton by affecting F-actin nucleation, recycling, and interaction with actin-binding proteins involved in the integration of actin filaments with each other and cellular elements.     

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.     

Smart Innovation Engineering: Toward Intelligent Industries of the Future

ABSTRACT

Knowledge-based engineering systems are founded upon integration of knowledge into computer systems and are one of the core requirements for the future Industry 4.0. This paper presents a system called smart innovation engineering (SIE) capable of facilitating product innovation process semi-automatically. It enhances decision-making processes using the explicit knowledge of formal decision events. The SIE system carries the promise to support the innovation processes of manufactured products in a quick and efficient way. It stores and reuses past decisional events or sets of experiences related to innovation issues, which significantly enhances innovation progression. The analysis of basic concepts and implementation method proves that SIE system is an advanced form of cyber physical systems. It is flexible, systematic, fast, and supports customization. It can play a vital role toward Industry 4.0 development.     

Computerized container-ship load planning: A methodology and evaluation

A heuristic is developed to plan loads for containerized cargo ships. It is designed to serve a port which uses gantry cranes (transtainers) and trucks to handle containers. The model recognizes constraints on ship stability, placing containers in a bay with the proper length, limits on stack height in under-deck bays, limits on stack weight in on-deck bays, refrigerated containers, and the need for support under a container. Provisions are made for the operator to handle overstowage of cargo for different ports and placement of oversize cargo. The model uses minimization of transtainer movement time and minimization of rehandles in the yard as an objective. The heuristic uses strategies for container placement similar to those used in manual load planning. A test of two ships and four voyages at the Port of Portland produced feasible load plans for each voyage. Transtainer movement and rehandling time varied for the four voyages; but on the average, the heuristic reduced a composite material handling measure by 4.8%.     

Efficient Boustrophedon Multi-Robot Coverage: an algorithmic approach

This paper presents algorithmic solutions for the complete coverage path planning problem using a team of mobile robots. Multiple robots decrease the time to complete the coverage, but maximal efficiency is only achieved if the number of regions covered multiple times is minimized. A set of multi-robot coverage algorithms is presented that minimize repeat coverage. The algorithms use the same planar cell-based decomposition as the Boustrophedon single robot coverage algorithm, but provide extensions to handle how robots cover a single cell, and how robots are allocated among cells. Specifically, for the coverage task our choice of multi-robot policy strongly depends on the type of communication that exists between the robots. When the robots operate under the line-of-sight communication restriction, keeping them as a team helps to minimize repeat coverage. When communication between the robots is available without any restrictions, the robots are initially distributed through space, and each one is allocated a virtually-bounded area to cover. A greedy auction mechanism is used for task/cell allocation among the robots. Experimental results from different simulated and real environments that illustrate our approach for different communication conditions are presented.     

Effects of channel thickness variation on bias stress instability of InGaZnO thin-film transistors

Here, we report on the effects of channel (or active) layer thickness on the bias stress instability of InGaZnO (IGZO) thin-film transistors (TFTs). The investigation on variations of TFT characteristics under the electrical bias stress is very crucial for commercial applications. In this work, the initial electrical characteristics of the tested TFTs with different channel layer thicknesses (40, 50, and 60 nm) are performed. Various gate bias (V_GS) stresses (10, 20, and 30 V) are then applied to the tested TFTs. For all V_GS stresses with different channel layer thickness, the experimentally measured threshold voltage shift (ΔV_th) as a function of stress time is precisely modeled with stretched-exponential function. It is indicated that the ΔV_th is generated by carrier trapping but not defect creation. It is also observed that the ΔV_th shows incremental behavior as the channel layer thickness increases. Thus, it is verified that the increase of total trap states (N_T) and free carriers resulted in the increase of ΔV_th as the channel layer thickness increases.     

Carbon‐Nanotube–PDMS Composite Coatings on Optical Fibers for All‐Optical Ultrasound Imaging

Polymer–carbon nanotube composite coatings have properties that are desirable for a wide range of applications. However, fabrication of these coatings onto submillimeter structures with the efficient use of nanotubes has been challenging. Polydimethylsiloxane (PDMS)–carbon nanotube composite coatings are of particular interest for optical ultrasound transmission, which shows promise for biomedical imaging and therapeutic applications. In this study, methods for fabricating composite coatings comprising PDMS and multiwalled carbon nanotubes (MWCNTs) with submicrometer thickness are developed and used to coat the distal ends of optical fibers. These methods include creating a MWCNT organogel using two solvents, dip coating of this organogel, and subsequent overcoating with PDMS. These coated fibers are used as all‐optical ultrasound transmitters that achieve high ultrasound pressures (up to 21.5 MPa peak‐to‐peak) and broad frequency bandwidths (up to 39.8 MHz). Their clinical potential is demonstrated with all‐optical pulse‐echo ultrasound imaging of an aorta. The fabrication methods in this paper allow for the creation of thin, uniform carbon nanotube composites on miniature or temperature‐sensitive surfaces, to enable a wide range of advanced sensing capabilities.     

Modelling the effects of past and future climate on the risk of bluetongue emergence in Europe

Vector-borne diseases are among those most sensitive to climate because the ecology of vectors and the development rate of pathogens within them are highly dependent on environmental conditions. Bluetongue (BT), a recently emerged arboviral disease of ruminants in Europe, is often cited as an illustration of climate''s impact on disease emergence, although no study has yet tested this association. Here, we develop a framework to quantitatively evaluate the effects of climate on BT''s emergence in Europe by integrating high-resolution climate observations and model simulations within a mechanistic model of BT transmission risk. We demonstrate that a climate-driven model explains, in both space and time, many aspects of BT''s recent emergence and spread, including the 2006 BT outbreak in northwest Europe which occurred in the year of highest projected risk since at least 1960. Furthermore, the model provides mechanistic insight into BT''s emergence, suggesting that the drivers of emergence across Europe differ between the South and the North. Driven by simulated future climate from an ensemble of 11 regional climate models, the model projects increase in the future risk of BT emergence across most of Europe with uncertainty in rate but not in trend. The framework described here is adaptable and applicable to other diseases, where the link between climate and disease transmission risk can be quantified, permitting the evaluation of scale and uncertainty in climate change''s impact on the future of such diseases.