Comparative Analysis of Platelet-Derived Extracellular Vesicles Using Flow Cytometry and Nanoparticle Tracking Analysis

Growing interest in extracellular vesicles (EVs) has prompted the advancements of protocols for improved EV characterization. As a high-throughput, multi-parameter, and single particle technique, flow cytometry is widely used for EV characterization. The comparison of data on EV concentration, however, is hindered by the lack of standardization between different protocols and instruments. Here, we quantified EV counts of platelet-derived EVs, using two flow cytometers (Gallios and CytoFLEX LX) and nanoparticle tracking analysis (NTA). Phosphatidylserine-exposing EVs were identified by labelling with lactadherin (LA). Calibration with silica-based fluorescent beads showed detection limits of 300 nm and 150 nm for Gallios and CytoFLEX LX, respectively. Accordingly, CytoFLEX LX yielded 40-fold higher EV counts and 13-fold higher counts of LA⁺CD41⁺ EVs compared to Gallios. NTA in fluorescence mode (F-NTA) demonstrated that only 9.5% of all vesicles detected in scatter mode exposed phosphatidylserine, resulting in good agreement of LA⁺ EVs for CytoFLEX LX and F-NTA. Since certain functional characteristics, such as the exposure of pro-coagulant phosphatidylserine, are not equally displayed across the entire EV size range, our study highlights the necessity of indicating the size range of EVs detected with a given approach along with the EV concentration to support the comparability between different studies.     

Isolate-Specific Effect of Entomopathogenic Endophytic Fungi on Population Growth of Two-Spotted Spider Mite (Tetranychus urticae Koch) and Levels of Steroidal Glycoalkaloids in Tomato

Journal of Chemical Ecology - Entomopathogenic fungi (EPF) can be experimentally established in several plant species as endophytes. Ecological effects of EPF inoculations on plant growth and...     

Investigations on the Corrosion Properties of Sn–1Cu–1Ni–xAg Lead Free Solders in 3.5% NaCl Solution

Protection of Metals and Physical Chemistry of Surfaces - Due to the directions and environmental legislations from RoHS (Restrictions of Hazardous Substances), WEEE (World Electrical and...     

Towards artificial intelligence at scale in the chemical industry

In the Industry 4.0 era, the chemical industry is embracing broad adoption of artificial intelligence (AI) and machine learning (ML) methods. This article provides a holistic view of how the industry is transforming digitally towards AI at scale. First, a historical perspective on how the industry used AI to aid humans in better decision-making is shown. Then state-of-the-art AI research addressing industrial needs on reliability and safety, process optimization, supply chain, material discovery, and reaction engineering is highlighted. Finally, a vision of the plant of the future is illustrated with critical components of AI-ready culture, model life cycle management, and renewed role of humans in chemical manufacturing.     

Priority Aware and Spectrum Efficient Scheduling of Co-existing Wireless Body Area Networks

Real-time continuous and remote health monitoring has become widespread due to the developments in Wireless body area networks (WBANs). Based on the criticality of health data to be transmitted, regular healthcare data and critical emergency health data must be provided differential service. In this paper, we consider the beyond WBAN communication in a system comprising multiple WBANs with different quality of service (QoS) requirements and multiple access points (APs), and propose two hybrid approaches for resource allocation. In the first approach, the AP association to the WBANs and channel allocation to the APs are done jointly and is modelled as an optimization problem, which is computationally complex and it also requires global network information. In order to reduce the involvement of APs in making decisions for resource allocations of WBANs, the problem is reformulated as a Stackelberg game with price update, which guarantees QoS of the critical users. A learning based algorithm, namely distributed learning for Pareto optimality, is used by the normal users, in this second approach. The performance of both the proposed approaches are evaluated and compared, in terms of the throughput of the critical and normal users as well as the QoS guarantee of the critical users.

     

A cathode support structure for use in a magnetron oscillator experiment

A low temperature co-fired ceramic (LTCC) material system has been used to develop a protype field emission cathode structure for use in an experimental magnetron oscillator. The structure is designed for used with 30 gated field emission array (GFEA) die electrically connected through silver metal traces and electrical vias. To approximate a cylinder, the cathode structure (48 mm long and 13.7 mm in diameter) is comprised of 10 faceted plates which cover the GFEA dies. Slits in the facet plates allow electron injection. The GFEA die (3 mm × 8 mm) are placed in axial columns of 3 and spaced azimuthally around a cylindrical support structure in a staggered configuration resulting in 10 azimuthal locations. LTCC manufacturing techniques were developed in order to fabricate the newly designed cathode with seven layers wrapped to form the cylinder with electrical traces and vias. Two different cathode wrapping techniques and two different via filling techniques were studied and compared. Two different facet plate manufacturing techniques were studied. Finally, four different support stand configurations for firing the cylindrical structure were also compared with a square post stand having the best circularity and linearity measurements of the fired structure.     

Design of a thermal management system for a battery pack in an electric vehicle using Dymola

As the world moves toward more green and efficient means of modes of transport, electric vehicles are the most suitable and ideal choice to fulfill this requirement. Rapid developments in the field of battery technology are the main reason for their progress, but thermal management in such systems has been an area of concern for a long time. The work undertaken is to design and develop a battery management system (BMS) with a specific focus on the thermal behavior of the battery pack with varying vehicle loads as well as environmental conditions. To design an efficient BMS, one needs to model the battery behavior covering the thermal as well as electrical aspects of the battery. Apart from the battery model, a mathematical model of the electrical vehicle to mimic the various road load conditions for battery also needs to be modeled. Depending on the need for cooling based on battery behavior, the cooling circuit is modeled for the battery pack used. The entire study has been carried out using Dymola, a mathematical modeling software.     

Investigations on the Effect of Tungsten Carbide and Graphite Reinforcements during Spark Erosion Machining of Aluminium Alloy (AA 5052) Hybrid Composite

Silicon - Reinforcements introduced to metal matrix composites are known for their inherent properties like corrosion resistance, wear resistance and machinability. This study deals with the...     

A new approach to characterizing asphalt concrete in the linear/nonlinear small strain domain

Mechanics of Time-Dependent Materials - Asphalt concrete (AC) material characterization is usually performed on laboratory prepared specimens, a procedure that does not ensure that the material...