scholarly journals Robotic platform for microinjection into single cells in intact tissue

2018 ◽  
Author(s):  
Gabriella Shull ◽  
Christiane Haffner ◽  
Wieland B. Huttner ◽  
Elena Taverna ◽  
Suhasa B Kodandaramaiah
Keyword(s):  
High Performance ◽  
Single Cells ◽  
Cell Manipulation ◽  
Human Brain Tissue ◽  
Embryonic Mouse ◽  
Intact Tissue ◽  
Junctional Communication ◽  
Order Of Magnitude ◽  
Newborn Neurons ◽  
High Level

AbstractMicroinjection into single cells in intact tissue allows the delivery of membrane-impermeant molecules such as nucleic acids and proteins is a powerful technique to study and manipulate the behavior of these cells and, if applicable, their progeny. However, a high level of skill is required to perform such microinjection and is a low-throughput and low-yield process. The automation of microinjection into cells in intact tissue would empower an increasing number of researchers to perform these challenging experiments and could potentially open up new avenues of experimentation. We have developed the ‘Autoinjector’, a robot that utilizes images acquired from a microscope to guide a microinjection needle into tissue to deliver femtoliter volumes of liquids into single cells. The robotic operation enables microinjection of hundreds of cells within a single organotypic slice, resulting in an overall yield that is an order of magnitude greater than manual microinjection. We validated the performance of the Autoinjector by microinjecting both apical progenitors (APs) and newborn neurons in the embryonic mouse telencephalon, APs in the embryonic mouse hindbrain, and neurons in fetal human brain tissue. We demonstrate the capability of the Autoinjector to deliver exogenous mRNA into APs. Further, we used the Autoinjector to systematically study gap-junctional communication between neural progenitors in the embryonic mouse telencephalon and found that apical contact is a characteristic feature of the cells that are part of a gap junction-coupled cell cluster. The throughput and versatility of the Autoinjector will not only render microinjection a broadly accessible high-performance cell manipulation technique but will also provide a powerful new platform for bioengineering and biotechnology for performing single-cell analyses in intact tissue.

scholarly journals PETRA

2021 ◽  
Vol 18 (2) ◽  
pp. 1-26
Author(s):  
Ramin Izadpanah ◽  
Christina Peterson ◽  
Yan Solihin ◽  
Damian Dechev
Keyword(s):  
Data Structures ◽  
High Performance ◽  
Transactional Memory ◽  
Superior Performance ◽  
New Approach ◽  
Ordering Constraints ◽  
Level Information ◽  
Order Of Magnitude ◽  
Persistent Data ◽  
High Level

Emerging byte-addressable Non-Volatile Memories (NVMs) enable persistent memory where process state can be recovered after crashes. To enable applications to rely on persistent data, durable data structures with failure-atomic operations have been proposed. However, they lack the ability to allow users to execute a sequence of operations as transactions. Meanwhile, persistent transactional memory (PTM) has been proposed by adding durability to Software Transactional Memory (STM). However, PTM suffers from high performance overheads and low scalability due to false aborts, logging, and ordering constraints on persistence. In this article, we propose PETRA, a new approach for constructing persistent transactional linked data structures. PETRA natively supports transactions, but unlike PTM, relies on the high-level information from the data structure semantics. This gives PETRA unique advantages in the form of high performance and high scalability. Our experimental results using various benchmarks demonstrate the scalability of PETRA in all workloads and transaction sizes. PETRA outperforms the state-of-the-art PTMs by an order of magnitude in transactions of size greater than one, and demonstrates superior performance in transactions of size one.

scholarly journals GigaSOM.jl: High-performance clustering and visualization of huge cytometry datasets

2020 ◽  
Author(s):  
Miroslav Kratochvíl ◽  
Oliver Hunewald ◽  
Laurent Heirendt ◽  
Vasco Verissimo ◽  
Jiří Vondrášek ◽  
...  
Keyword(s):  
Single Cell ◽  
High Performance ◽  
Single Cells ◽  
Distributed Processing ◽  
Multidimensional Data ◽  
List Type ◽  
Technological Advances ◽  
Data Points ◽  
High Level ◽  
Complex Phenomena

AbstractBackgroundThe amount of data generated in large clinical and phenotyping studies that use single-cell cytometry is constantly growing. Recent technological advances allow to easily generate data with hundreds of millions of single-cell data points with more than 40 parameters, originating from thousands of individual samples. The analysis of that amount of high-dimensional data becomes demanding in both hardware and software of high-performance computational resources. Current software tools often do not scale to the datasets of such size; users are thus forced to down-sample the data to bearable sizes, in turn losing accuracy and ability to detect many underlying complex phenomena.ResultsWe present GigaSOM.jl, a fast and scalable implementation of clustering and dimensionality-reduction for flow and mass cytometry data. The implementation of GigaSOM.jl in the high-level and high-performance programming language Julia makes it accessible to the scientific community, and allows for efficient handling and processing of datasets with billions of data points using distributed computing infrastructures. We describe the design of GigaSOM.jl, measure its performance and horizontal scaling capability, and showcase the functionality on a large dataset from a recent study.ConclusionsGigaSOM.jl facilitates utilization of the commonly available high-performance computing resources to process the largest available datasets within minutes, while producing results of the same quality as the current state-of-art software. Measurements indicate that the performance scales to much larger datasets. The example use on the data from an massive mouse phenotyping effort confirms the applicability of GigaSOM.jl to huge-scale studies.Key pointsGigaSOM.jl improves the applicability of FlowSOM-style single-cell cytometry data analysis by increasing the acceptable dataset size to billions of single cells.Significant speedup over current methods is achieved by distributed processing and utilization of efficient algorithms.GigaSOM.jl package includes support for fast visualization of multidimensional data.

What Can Digitization Do For Formulated Product Innovation and Development

2020 ◽  
Author(s):  
James McDonagh ◽  
William Swope ◽  
Richard L. Anderson ◽  
Michael Johnston ◽  
David J. Bray
Keyword(s):  
High Performance ◽  
Quality Data ◽  
High Quality Data ◽  
Base Level ◽  
Hybrid Approaches ◽  
Digital Ecosystem ◽  
Recent Developments ◽  
Chemical Simulation ◽  
High Level ◽  
Physical And Chemical

Digitization offers significant opportunities for the formulated product industry to transform the way it works and develop new methods of business. R&D is one area of operation that is challenging to take advantage of these technologies due to its high level of domain specialisation and creativity but the benefits could be significant. Recent developments of base level technologies such as artificial intelligence (AI)/machine learning (ML), robotics and high performance computing (HPC), to name a few, present disruptive and transformative technologies which could offer new insights, discovery methods and enhanced chemical control when combined in a digital ecosystem of connectivity, distributive services and decentralisation. At the fundamental level, research in these technologies has shown that new physical and chemical insights can be gained, which in turn can augment experimental R&D approaches through physics-based chemical simulation, data driven models and hybrid approaches. In all of these cases, high quality data is required to build and validate models in addition to the skills and expertise to exploit such methods. In this article we give an overview of some of the digital technology demonstrators we have developed for formulated product R&D. We discuss the challenges in building and deploying these demonstrators.<br>

https://imsciences.edu.pk/files/journals/vol12_2/New%201%20MA.864.pdf

2020 ◽  
Vol 12 (2) ◽  
pp. 19-50 ◽  
Author(s):  
Muhammad Siddique ◽  
Shandana Shoaib ◽  
Zahoor Jan
Keyword(s):  
Organizational Performance ◽  
Structural Equation ◽  
High Performance ◽  
Service Sector ◽  
Performance Outcomes ◽  
Theory And Practice ◽  
Relational Coordination ◽  
Multiple Sources ◽  
And Performance ◽  
High Level

A key aspect of work processes in service sector firms is the interconnection between tasks and performance. Relational coordination can play an important role in addressing the issues of coordinating organizational activities due to high level of interdependence complexity in service sector firms. Research has primarily supported the aspect that well devised high performance work systems (HPWS) can intensify organizational performance. There is a growing debate, however, with regard to understanding the “mechanism” linking HPWS and performance outcomes. Using relational coordination theory, this study examines a model that examine the effects of subsets of HPWS, such as motivation, skills and opportunity enhancing HR practices on relational coordination among employees working in reciprocal interdependent job settings. Data were gathered from multiple sources including managers and employees at individual, functional and unit levels to know their understanding in relation to HPWS and relational coordination (RC) in 218 bank branches in Pakistan. Data analysis via structural equation modelling, results suggest that HPWS predicted RC among officers at the unit level. The findings of the study have contributions to both, theory and practice.

scholarly journals Dietary and Ergogenic Supplementation to Improve Elite Soccer Players’ Performance

2021 ◽  
pp. 1-7
Author(s):  
Haniel Fernandes
Keyword(s):  
Dietary Supplements ◽  
High Performance ◽  
Scientific Literature ◽  
Soccer Players ◽  
Competitive Sport ◽  
Beetroot Juice ◽  
Improve Performance ◽  
Sustained Release Tablets ◽  
High Level ◽  
Ergogenic Supplements

<b><i>Background:</i></b> Soccer is an extremely competitive sport, where the most match important moments can be defined in detail. Use of ergogenic supplements can be crucial to improve the performance of a high-performance athlete. Therefore, knowing which ergogenic supplements are important for soccer players can be an interesting strategy to maintain high level in this sport until final and decisive moments of the match. In addition, other supplements, such as dietary supplements, have been studied and increasingly referenced in the scientific literature. But, what if ergogenic supplements were combined with dietary supplements? This review brings some recommendations to improve performance of soccer athletes on the field through dietary and/or ergogenic supplements that can be used simultaneously. <b><i>Summary:</i></b> Soccer is a competitive sport, where the match important moments can be defined in detail. Thus, use of ergogenic supplements covered in this review can improve performance of elite soccer players maintaining high level in the match until final moments, such as creatine 3–5 g day<sup>−1</sup>, caffeine 3–6 mg kg<sup>−1</sup> BW around 60 min before the match, sodium bicarbonate 0.1–0.4 g kg<sup>−1</sup> BW starting from 30 to 180 min before the match, β-alanine 3.2 and 6.4 g day<sup>−1</sup> provided in the sustained-release tablets divided into 4 times a day, and nitrate-rich beetroot juice 60 g in 200 mL of water (6 mmol of NO3<sup>−</sup> L) around 120 min before match or training, including a combination possible with taurine 50 mg kg<sup>−1</sup> BW day<sup>−1</sup>, citrulline 1.2–3.4 g day<sup>−1</sup>, and arginine 1.2–6 g day<sup>−1</sup>. <b><i>Key Messages:</i></b> Soccer athletes can combine ergogenic and dietary supplements to improve their performance on the field. The ergogenic and dietary supplements used in a scientifically recommended dose did not demonstrate relevant side effects. The use of various evidence-based supplements can add up to further improvement in the performance of the elite soccer players.

scholarly journals Long Term Interactions of Native and Invasive Species in a Marine Protected Area Suggest Complex Cascading Effects Challenging Conservation Outcomes

Diversity ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 71
Author(s):  
Charalampos Dimitriadis ◽  
Ivoni Fournari-Konstantinidou ◽  
Laurent Sourbès ◽  
Drosos Koutsoubas ◽  
Stelios Katsanevakis
Keyword(s):  
Invasive Species ◽  
Native Species ◽  
High Performance ◽  
Marine Protected Area ◽  
Habitat Degradation ◽  
Population Increase ◽  
Rocky Reef ◽  
Cascading Effects ◽  
High Level

Understanding the interactions among invasive species, native species and marine protected areas (MPAs), and the long-term regime shifts in MPAs is receiving increased attention, since biological invasions can alter the structure and functioning of the protected ecosystems and challenge conservation efforts. Here we found evidence of marked modifications in the rocky reef associated biota in a Mediterranean MPA from 2009 to 2019 through visual census surveys, due to the presence of invasive species altering the structure of the ecosystem and triggering complex cascading effects on the long term. Low levels of the populations of native high-level predators were accompanied by the population increase and high performance of both native and invasive fish herbivores. Subsequently the overgrazing and habitat degradation resulted in cascading effects towards the diminishing of the native and invasive invertebrate grazers and omnivorous benthic species. Our study represents a good showcase of how invasive species can coexist or exclude native biota and at the same time regulate or out-compete other established invaders and native species.

scholarly journals Multiplexed In Situ Protein Profiling with High-Performance Cleavable Fluorescent Tyramide

Molecules ◽  
2021 ◽  
Vol 26 (8) ◽  
pp. 2206
Author(s):  
Thai Pham ◽  
Renjie Liao ◽  
Joshua Labaer ◽  
Jia Guo
Keyword(s):  
High Performance ◽  
Single Cells ◽  
Protein Quantification ◽  
Cellular Systems ◽  
Protein Profiling ◽  
High Signal ◽  
Protein Targets ◽  
Chemical Reagents ◽  
Ffpe Tissues

Understanding the composition, function and regulation of complex cellular systems requires tools that quantify the expression of multiple proteins at their native cellular context. Here, we report a highly sensitive and accurate protein in situ profiling approach using off-the-shelf antibodies and cleavable fluorescent tyramide (CFT). In each cycle of this method, protein targets are stained with horseradish peroxidase (HRP) conjugated antibodies and CFT. Subsequently, the fluorophores are efficiently cleaved by mild chemical reagents, which simultaneously deactivate HRP. Through reiterative cycles of protein staining, fluorescence imaging, fluorophore cleavage, and HRP deactivation, multiplexed protein quantification in single cells in situ can be achieved. We designed and synthesized the high-performance CFT, and demonstrated that over 95% of the staining signals can be erased by mild chemical reagents while preserving the integrity of the epitopes on protein targets. Applying this method, we explored the protein expression heterogeneity and correlation in a group of genetically identical cells. With the high signal removal efficiency, this approach also enables us to accurately profile proteins in formalin-fixed paraffin-embedded (FFPE) tissues in the order of low to high and also high to low expression levels.

scholarly journals Evaluation of Static Mapping for Dynamic Space-Shared Multi-task Processing on FPGAs

2021 ◽  
Author(s):  
Umar Ibrahim Minhas ◽  
Roger Woods ◽  
Georgios Karakonstantis
Keyword(s):  
High Performance ◽  
Design Space Exploration ◽  
Design Space ◽  
System Throughput ◽  
Design Parameters ◽  
Temporal Constraints ◽  
Shared Resources ◽  
Task Processing ◽  
High Level ◽  
Performance Computing

AbstractWhilst FPGAs have been used in cloud ecosystems, it is still extremely challenging to achieve high compute density when mapping heterogeneous multi-tasks on shared resources at runtime. This work addresses this by treating the FPGA resource as a service and employing multi-task processing at the high level, design space exploration and static off-line partitioning in order to allow more efficient mapping of heterogeneous tasks onto the FPGA. In addition, a new, comprehensive runtime functional simulator is used to evaluate the effect of various spatial and temporal constraints on both the existing and new approaches when varying system design parameters. A comprehensive suite of real high performance computing tasks was implemented on a Nallatech 385 FPGA card and show that our approach can provide on average 2.9 × and 2.3 × higher system throughput for compute and mixed intensity tasks, while 0.2 × lower for memory intensive tasks due to external memory access latency and bandwidth limitations. The work has been extended by introducing a novel scheduling scheme to enhance temporal utilization of resources when using the proposed approach. Additional results for large queues of mixed intensity tasks (compute and memory) show that the proposed partitioning and scheduling approach can provide higher than 3 × system speedup over previous schemes.

scholarly journals High-Level Parallel Ant Colony Optimization with Algorithmic Skeletons

2021 ◽  
Author(s):  
Breno A. de Melo Menezes ◽  
Nina Herrmann ◽  
Herbert Kuchen ◽  
Fernando Buarque de Lima Neto
Keyword(s):  
Ant Colony Optimization ◽  
High Performance ◽  
Optimization Problems ◽  
Programming Model ◽  
Parallel Implementation ◽  
Ant Colony ◽  
Algorithmic Skeletons ◽  
Low Level ◽  
Programming Patterns ◽  
High Level

AbstractParallel implementations of swarm intelligence algorithms such as the ant colony optimization (ACO) have been widely used to shorten the execution time when solving complex optimization problems. When aiming for a GPU environment, developing efficient parallel versions of such algorithms using CUDA can be a difficult and error-prone task even for experienced programmers. To overcome this issue, the parallel programming model of Algorithmic Skeletons simplifies parallel programs by abstracting from low-level features. This is realized by defining common programming patterns (e.g. map, fold and zip) that later on will be converted to efficient parallel code. In this paper, we show how algorithmic skeletons formulated in the domain specific language Musket can cope with the development of a parallel implementation of ACO and how that compares to a low-level implementation. Our experimental results show that Musket suits the development of ACO. Besides making it easier for the programmer to deal with the parallelization aspects, Musket generates high performance code with similar execution times when compared to low-level implementations.

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