Novel co-culture plate enables growth dynamic-based assessment of contact-independent microbial interactions

AbstractInteractions between microbes are central to the dynamics of microbial communities. Understanding these interactions is essential for the characterization of communities, yet challenging to accomplish in practice. There are limited available tools for characterizing diffusion-mediated, contact-independent microbial interactions. A practical and widely implemented technique in such characterization involves the simultaneous co-culture of distinct bacterial species and subsequent analysis of relative abundance in the total population. However, distinguishing between species can be logistically challenging. In this paper, we present a low-cost, vertical membrane, co-culture plate to quantify contact-independent interactions between distinct bacterial populations in co-culture via real-time optical density measurements. These measurements can be used to facilitate the analysis of the interaction between microbes that are physically separated by a semipermeable membrane yet able to exchange diffusible molecules. We show that diffusion across the membrane occurs at a sufficient rate to enable effective interaction between physically separate cultures. Two bacterial species commonly found in the cystic fibrotic lung,Pseudomonas aeruginosaandBurkholderia cenocepacia, were co-cultured to demonstrate how this plate may be implemented to study microbial interactions. We have demonstrated that this novel co-culture device is able to reliably generate real-time measurements of optical density data that can be used to characterize interactions between microbial species.

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Method for the estimation of antibacterial activity of the polyfunctional protein from transferrin family in the experimental model of the kinetics of Staphylococcus aureus development

Journal of microbiology epidemiology immunobiology ◽

10.36233/0372-9311-209 ◽

2022 ◽

Vol 98 (6) ◽

pp. 617-627

Author(s):

V. N. Tsarev ◽

I. M. Makeeva ◽

El. R. Sadchikova ◽

M. S. Podporin ◽

Yu. A. Trefilova ◽

...

Keyword(s):

Antibacterial Activity ◽

Optical Density ◽

Bacterial Species ◽

Objective Assessment ◽

Growth Curves ◽

Growth Dynamics ◽

Diagnostic Technique ◽

Bacterial Suspension ◽

Dilution Method ◽

Bacterial Populations

Introduction. Lactoferrin is a cationic monomeric glycoprotein produced by acinar cells and glands, present in different places of the mucous membrane in different concentrations. In connection with the development of various variants of hygienic and medicinal products for the treatment of inflammatory diseases of the oral cavity based on lactoferrin, there was a need for an objective assessment of its antibacterial and antibiofilms properties, followed by an analysis of the preservation of activity in various variants of the isolation of this protein from the substrate and storage.Aim - to improve the effectiveness of evaluating the antibacterial activity of lactoferrin and the duration of its preservation in various biological substrates containing the active substance and individual experimental batches of the manufactured drug using automatic cultivation.Materials and methods. As part of the experiment, a microbiological diagnostic technique employing a system for the automatic cultivation of microbial populations was used. A pre-prepared bacterial suspension was inoculated into the nutrient broth and the studied lactoferrin samples were added, followed by cultivation and analysis of the possible antibacterial effects of transferrin protein. To determine the sensitivity of the isolated strains, we used our own modification of the serial dilution method developed at the Department of microbiology, virology, immunology of the A.I. Yevdokimov Moscow State University of Medicine and Dentistry. The experiment was based on the programmed automatic cultivation using the RTS-1 bioreactor. The interpretation of the results was carried out by changing the optical density at a wavelength of λ = 850 nm. The study of the growth dynamics of microorganisms was carried out in several repetitions, which was reflected in the graphs of the development of bacterial populations. The assessment of the growth control of the corresponding bacterial species was reflected in the change in the optical density values, on the basis of which the curve was built. Results and discussion. According to the results of an experimental study of the growth curves of bacterial populations, statistically significant differences in the number of viable cells in different phases of the growth curves were noted, when using different lactoferrin samples. Higher activity of human recombinant lactoferrin samples was established. An analysis of growth dynamics revealed differences in the onset of the maximum reproduction and its inhibition under the influence of various aggravating factors during cultivation. The bacteriostatic effect of lactoferrin is realized through the binding of iron ions, depriving the bacteria of this microelement, causing inhibition of their development. Along with this, lactoferrin is active against certain virulence factors of microorganisms, splitting them like serine proteases, and thus prevents their penetration into human cells.Conclusion. The method used for automatic cultivation of microorganisms in the bioreactor used allows one to obtain reproducible results, is available for wide use, and can be recommended for obtaining objective, comparable, reliable information about the antimicrobial properties of various samples of the bactericidal protein lactoferrin produced by the domestic pharmaceutical industry. The studied substrate containing recombinant human lactoferrin of Russian production is characterized by high antibacterial activity that persists for 3 years as minimum.

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LOW COST REAL TIME ROCKET TELEMETRY SYSTEM DESIGN

10.26678/abcm.cobem2019.cob2019-1585 ◽

2019 ◽

Author(s):

Gabriel de Almeida Souza ◽

Larissa Barbosa ◽

Glênio Ramalho ◽

Alexandre Zuquete Guarato

Keyword(s):

System Design ◽

Real Time ◽

Low Cost ◽

Telemetry System

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Low-Cost High-Speed Techniques for Real-Time Simulation of Power Electronic Systems

10.21236/ada485330 ◽

2007 ◽

Author(s):

R. E. Crosbie ◽

J. J. Zenor ◽

R. Bednar ◽

D. Word ◽

N. G. Hingorani

Keyword(s):

Real Time ◽

High Speed ◽

Low Cost ◽

Electronic Systems ◽

Power Electronic ◽

Real Time Simulation ◽

Time Simulation

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Application of Deep Learning in Integrated Pest Management: A Real-Time System for Detection and Diagnosis of Oilseed Rape Pests

Mobile Information Systems ◽

10.1155/2019/4570808 ◽

2019 ◽

Vol 2019 ◽

pp. 1-14 ◽

Cited By ~ 2

Author(s):

Yong He ◽

Hong Zeng ◽

Yangyang Fan ◽

Shuaisheng Ji ◽

Jianjian Wu

Keyword(s):

Deep Learning ◽

Integrated Pest Management ◽

Pest Management ◽

Real Time ◽

Oilseed Rape ◽

Data Augmentation ◽

Low Cost ◽

Response Speed ◽

Original Model ◽

Real Time System

In this paper, we proposed an approach to detect oilseed rape pests based on deep learning, which improves the mean average precision (mAP) to 77.14%; the result increased by 9.7% with the original model. We adopt this model to mobile platform to let every farmer able to use this program, which will diagnose pests in real time and provide suggestions on pest controlling. We designed an oilseed rape pest imaging database with 12 typical oilseed rape pests and compared the performance of five models, SSD w/Inception is chosen as the optimal model. Moreover, for the purpose of the high mAP, we have used data augmentation (DA) and added a dropout layer. The experiments are performed on the Android application we developed, and the result shows that our approach surpasses the original model obviously and is helpful for integrated pest management. This application has improved environmental adaptability, response speed, and accuracy by contrast with the past works and has the advantage of low cost and simple operation, which are suitable for the pest monitoring mission of drones and Internet of Things (IoT).

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Real-Time Low-Cost Drift Compensation for Chemical Sensors Using a Deep Neural Network with Hadamard Transform and Additive Layers

IEEE Sensors Journal ◽

10.1109/jsen.2021.3084220 ◽

2021 ◽

pp. 1-1

Author(s):

Diaa Badawi ◽

Agamyrat Agambayev ◽

Sule Ozev ◽

A. Enis Cetin

Keyword(s):

Neural Network ◽

Real Time ◽

Chemical Sensors ◽

Deep Neural Network ◽

Low Cost ◽

Hadamard Transform ◽

Drift Compensation

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A Low-Cost, Mobile Real-Time Kinematic Geolocation Service for Engineering and Research Applications

HardwareX ◽

10.1016/j.ohx.2021.e00203 ◽

2021 ◽

pp. e00203

Author(s):

André Broekman ◽

Petrus Johannes Gräbe

Keyword(s):

Real Time ◽

Low Cost ◽

Real Time Kinematic

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Low-Cost Embedded System Using Convolutional Neural Networks-Based Spatiotemporal Feature Map for Real-Time Human Action Recognition

Applied Sciences ◽

10.3390/app11114940 ◽

2021 ◽

Vol 11 (11) ◽

pp. 4940

Author(s):

Jinsoo Kim ◽

Jeongho Cho

Keyword(s):

Embedded System ◽

Real Time ◽

Action Recognition ◽

Processing Speed ◽

Recognition Accuracy ◽

Low Cost ◽

Human Action Recognition ◽

Human Action ◽

Video Data ◽

Feature Maps

The field of research related to video data has difficulty in extracting not only spatial but also temporal features and human action recognition (HAR) is a representative field of research that applies convolutional neural network (CNN) to video data. The performance for action recognition has improved, but owing to the complexity of the model, some still limitations to operation in real-time persist. Therefore, a lightweight CNN-based single-stream HAR model that can operate in real-time is proposed. The proposed model extracts spatial feature maps by applying CNN to the images that develop the video and uses the frame change rate of sequential images as time information. Spatial feature maps are weighted-averaged by frame change, transformed into spatiotemporal features, and input into multilayer perceptrons, which have a relatively lower complexity than other HAR models; thus, our method has high utility in a single embedded system connected to CCTV. The results of evaluating action recognition accuracy and data processing speed through challenging action recognition benchmark UCF-101 showed higher action recognition accuracy than the HAR model using long short-term memory with a small amount of video frames and confirmed the real-time operational possibility through fast data processing speed. In addition, the performance of the proposed weighted mean-based HAR model was verified by testing it in Jetson NANO to confirm the possibility of using it in low-cost GPU-based embedded systems.

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