Single-step multiplex reverse transcription-polymerase chain reaction for the detection and differentiation of QX-like infectious bronchitis virus from the Thai variant and vaccine strains H120, Ma5, and 4/91

Background and Aim: QX-like infectious bronchitis virus (IBV) is a highly infectious avian coronavirus that causes respiratory and kidney disease. It is linked to increased mortality and loss of performance in infected chickens worldwide, including Thailand. Thus, a simple and rapid diagnostic method for the diagnosis of QX-like IBV is needed. This study aimed to develop a single-step multiplex reverse transcription-polymerase chain reaction (mRT-PCR) assay to detect and differentiate QX-like IBV from Thai IBV and vaccine strains used in the poultry industry (H120, Ma5, and 4/91). Materials and Methods: Primer sets specific for QX-like and Thai IBV were designed to target the S1 gene. The specificity of the technique was verified using nine isolates of QX-like IBV, four isolates of Thai IBV, and other avian viral respiratory pathogens. The detection limit was evaluated using a serial ten-fold dilution of QX-like and Thai IBV. Results: The results showed that single-step mRT-PCR could detect QX-like IBV and differentiate it from Thai IBV and the vaccine strains H120, Ma5, and 4/91. The limit of detection of the developed assay was 102.2 embryo infectious dose (EID)50/mL for QX-like IBV and 101.8 EID50/mL for Thai IBV. Interestingly, the developed assay could identify mixed infection by both IBVs in a single sample. Conclusion: The single-step mRT-PCR assay developed in this study can potentially discriminate QX-like IBV from Thai IBV and the vaccine strains H120, Ma5, and 4/91 in a single reaction. It is also suitable for use in all laboratories with access to conventional PCR equipment. [ FROM AUTHOR] Copyright of Veterinary World is the property of Veterinary World and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Dual-band Air-Ground Radio Performance: Example Flight Test Results

We recently concluded a four-year University Leadership Initiative (ULI) project sponsored by NASA, which investigated multiple aviation communications technology areas aimed at enhancing future aviation safety. These areas were dual-band air-ground communications for air traffic management, detection and interdiction of small drones, and high-capacity terrestrial airport communications networking. In this paper we report on flight test results of our dual-band radios. These radios were designed to use a spectrally efficient multi-carrier modulation, filterbank multicarrier (FBMC), which we had previously shown to improve resilience to high-power distance measurement equipment (DME) adjacent-channel interference, in comparison to existing orthogonal frequency division multiplexing (OFDM) schemes. In our NASA project, we designed the FBMC radios to extend performance even further, using the following techniques: (i) simultaneous dual-band transmission and reception;(ii) ground station (GS) spatial diversity;(iii) higher-order modulation for a factor of 5 capacity increase over QPSK;(iv) a Doppler-resilient option using a smaller number of subcarriers;and, (v) 5-MHz bandwidth C-band transmissions for an order of magnitude capacity increase over existing 500-kHz channel schemes. To our knowledge, these are novel achievements for civil aviation, and our flight test results attained a technology readiness level (TRL) of 5. In this paper we briefly describe the project history, in which we spent approximately one year working with Boeing to participate in one of their Eco-Demonstrator flight trials, and obtained special temporary authorizations to transmit in both the L-band and C-band, from the FAA, the FCC, and the DoD. When COVID-19 dispersed worldwide, Boeing was no longer able to support us, so we revised our plans and teamed with the South Carolina Civil Air Patrol (SC CAP) to conduct smaller-scale flight tests. This paper summarizes the radio designs and the novel features we employed, as well as analyses, computer simulations, and laboratory tests prior to terrestrial mobile testing, all of which culminated in our successful flight tests. We show example flight test results that serve as proof of concept for all the five aforementioned radio performance enhancements. Example results include signal-to-noise ratio and bit error ratio, diversity gains, and throughput gains through both higher-order modulation and wider bandwidth channels. We also report on some lessons learned, and some ideas for future advancement of our work. © 2023 IEEE.

A Student Perspective on the 18th Monitoring Molecules in Neuroscience Meeting in Lyon.

After being postponed twice due to the global COVID-19 pandemic, approximately 200 scientists gathered in Lyon, France, in late June 2022 for the 18th Biennial Monitoring Molecules in Neuroscience (MMiN) Research Conference. Although there were unprecedented challenges involved with coordinating the 18th MMiN conference, the meeting was a huge success. The meeting provided a wonderful opportunity for young neuroscientists to network and learn about the current state of molecular monitoring in neuroscience research. The topics spanned advancements in well-established analytical techniques to novel method development. Some of the noteworthy techniques expediting our understanding of circuit-level neurochemical function include multiplexed detection of numerous neurochemicals, well-established sensors leveraging enzymes and other biologic components, and the development of diverse, customizable genetically encoded sensors.

Rapid Single-Round Pool Testing of Infectious Disease Enabled by Multicolor Digital Melting PCR.

Pooled nucleic acid amplification test is a promising strategy to reduce cost and resources for screening large populations for infectious disease. However, the benefit of pooled testing is reversed when disease prevalence is high, because of the need to retest each sample to identify infected individual when a pool is positive. Split, Amplify, and Melt analysis of Pooled Assay (SAMPA) is presented, a multicolor digital melting PCR assay in nanoliter chambers that simultaneously identify infected individuals and quantify their viral loads in a single round of pooled testing. This is achieved by early sample tagging with unique barcodes and pooling, followed by single molecule barcode identification in a digital PCR platform using a highly multiplexed melt curve analysis strategy. The feasibility is demonstrated of SAMPA for quantitative unmixing and variant identification from pools of eight synthetic DNA and RNA samples corresponding to the N1 gene, as well as from heat-inactivated SARS-CoV-2 virus. Single round pooled testing of barcoded samples with SAMPA can be a valuable tool for rapid and scalable population testing of infectious disease.

Communities Detection in Multiplex Networks Using Optimization: Study Case—Employment in Mexico during the COVID-19 Pandemic

The detection of communities in complex networks offers important information about the structure of the network as well as its dynamics. However, it is not an easy problem to solve. This work presents a methodology based of the robust coloring problem (RCP) and the vertex cover problem (VCP) to find communities in multiplex networks. For this, we consider the RCP idea of having a partial detection based onf the similarity of connected and unconnected nodes. On the other hand, with the idea of the VCP, we manage to minimize the number of groups, which allows us to identify the communities well. To apply this methodology, we present the dynamic characterization of job loss, change, and acquisition behavior for the Mexican population before and during the COVID-19 pandemic modeled as a 4- layer multiplex network. The results obtained when applied to test and study case networks show that this methodology can classify elements with similar characteristics and can find their communities. Therefore, our proposed methodology can be used as a new mechanism to identify communities, regardless of the topology or whether it is a monoplex or multiplex network.

A multiplex method for detection of SARS-CoV-2 variants based on MALDI-TOF mass spectrometry.

The recent outbreak of the coronavirus disease 2019 (COVID-19) pandemic and the continuous evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have highlighted the significance of new detection methods for global monitoring and prevention. Although quantitative reverse transcription PCR (RT-qPCR), the current gold standard for diagnosis, performs excellently in genetic testing, its multiplexing capability is limited because of the signal crosstalk of various fluorophores. Herein, we present a highly efficient platform which combines 17-plex assays with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), enabling the targeting of 14 different mutation sites of the spike gene. Diagnosis using a set of 324 nasopharyngeal swabs or sputum clinical samples with SARS-CoV-2 MS method was identical to that with the RT-qPCR. The detection consistency of mutation sites was 97.9% (47/48) compared to Sanger sequencing without cross-reaction with other respiratory-related pathogens. Therefore, the MS method is highly potent to track and assess SARS-CoV-2 changes in a timely manner, thereby aiding the continuous response to viral variation and prevention of further transmission.

Hand-breathe: Non-Contact Monitoring of Breathing Abnormalities from Hand Palm

In post-covid19 world, radio frequency (RF)-based non-contact methods, e.g., software-defined radios (SDR)-based methods have emerged as promising candidates for intelligent remote sensing of human vitals, and could help in containment of contagious viruses like covid19. To this end, this work utilizes the universal software radio peripherals (USRP)-based SDRs along with classical machine learning (ML) methods to design a non-contact method to monitor different breathing abnormalities. Under our proposed method, a subject rests his/her hand on a table in between the transmit and receive antennas, while an orthogonal frequency division multiplexing (OFDM) signal passes through the hand. Subsequently, the receiver extracts the channel frequency response (basically, fine-grained wireless channel state information), and feeds it to various ML algorithms which eventually classify between different breathing abnormalities. Among all classifiers, linear SVM classifier resulted in a maximum accuracy of 88.1%. To train the ML classifiers in a supervised manner, data was collected by doing real-time experiments on 4 subjects in a lab environment. For label generation purpose, the breathing of the subjects was classified into three classes: normal, fast, and slow breathing. Furthermore, in addition to our proposed method (where only a hand is exposed to RF signals), we also implemented and tested the state-of-the-art method (where full chest is exposed to RF radiation). The performance comparison of the two methods reveals a trade-off, i.e., the accuracy of our proposed method is slightly inferior but our method results in minimal body exposure to RF radiation, compared to the benchmark method. IEEE

Impact of multi-lattice inner structures on FDM PLA 3D printed orthosis using Industry 4.0 concepts

The use of digital manufacturing for the construction of orthosis and prostheses has become common since the popularization of 3D printers and the advent of Industry 4.0. Furthermore, due to the fact that the manufacture of orthosis is interactive and for personal use, generic production is difficult. In this sense, the large-scale production of these products lacks of improvements, standardization of processes and production optimization. An aggravation of this is the recent social distance due to the COVID-19 pandemic, which makes the use of temporary orthosis made in 3D printers to have a recent growth. Parallel to this, the use of multi-lattice inner structures for internal structuring of prints has also been increasing and taking on a more consolidated form. This article aims to present the multi-lattice optimization as a solution to this problem, in order to reduce material waste while maintaining the mechanical behavior of printed parts. © 2022, The Author(s), under exclusive licence to Springer-Verlag France SAS, part of Springer Nature.

The Role of Host Cell Glycans on Virus Infectivity: The SARS-CoV-2 Case.

Glycans are ubiquitously expressed sugars, coating the cell and protein surfaces. They are found on many proteins as either short and branched chains or long chains sticking out from special membrane proteins, known as proteoglycans. This sugar cushion, the glycocalyx, modulates specific interactions and protects the cell. Here it is shown that both the expression of proteoglycans and the glycans expressed on the surface of both the host and virus proteins have a critical role in modulating viral attachment to the cell. A mathematical model using SARS-Cov-2 as an archetypical virus to study the glycan role during infection is proposed. It is shown that this occurs via a tug-of-war of forces. On one side, the multivalent molecular recognition that viral proteins have toward specific host glycans and receptors. On the other side, the glycan steric repulsion that a virus must overcome to approach such specific receptors. By balancing both interactions, viral tropism can be predicted. In other words, the authors can map out the cells susceptible to virus infection in terms of receptors and proteoglycans compositions.

Dynamic Modeling and Identification of the COVID-19 Stochastic Dispersion

In this work, the stochastic dispersion of novel coronavirus disease 2019 (COVID-19) at the borders between France and Italy has been considered using a multi-input multi-output stochastic model. The physical effects of wind, temperature and altitude have been investigated as these factors and physical relationships are stochastic in nature. Stochastic terms have also been included to take into account the turbulence effect, and the r and om nature of the above physical parameters considered. Then, a method is proposed to identify the developed model's order and parameters. The actual data has been used in the identification and prediction process as a reference. These data have been divided into two parts: The first part is used to calculate the stochastic parameters of the model which are used to predict the COVID-19 level, while the second part is used as a check data. The predicted results are in good agreement with the check data. © 2022 IEEE.

Inexpensive High-Throughput Multiplexed Biomarker Detection Using Enzymatic Metallization with Cellphone-Based Computer Vision.

Multiplexed biomarker detection can play a critical role in reliable and comprehensive disease diagnosis and prediction of outcome. Enzyme-linked immunosorbent assay (ELISA) is the gold standard method for immunobinding-based biomarker detection. However, this is currently expensive, limited to centralized laboratories, and usually limited to the detection of a single biomarker at a time. We present a low-cost, smartphone-based portable biosensing platform for high-throughput, multiplexed, sensitive, and quantitative detection of biomarkers from single, low-volume drops (<1 µL) of clinical samples. Biomarker binding to spotted capture antigens is converted, via enzymatic metallization, to the localized surface deposition of amplified, dry-stable, silver metal spots whose darkness is proportional to biomarker concentration. A custom smartphone application is developed, which uses real-time computer vision to enable easy optical detection of the deposited metal spots and sensitive and reproducible quantification of the biomarkers. We demonstrate the use of this platform for high-throughput, multiplexed detection of multiple viral antigen-specific antibodies from convalescent COVID-19 patient serum as well as vaccine-elicited antibody responses from uninfected vaccine-recipient serum and show that distinct multiplexed antibody fingerprints are observed among them.

Optical Chaos Based Secure Optical Body Area Network Employing Polarization Multiplexing and Free Space Optics for e-Health Applications

We propose and demonstrate an optical chaos secured optical body area network (OBAN) employing polarization multiplexing and free space optics links. The physiological data of patient coded in non-return to zero on-off keying (NRZ-OOK) format from two on-body nodes modulated on orthogonal polarization states of a continuous wave (CW) laser is secured by using additive chaos masking (ACM) technique with chaotic waveforms generated through direct modulation of semiconductor chaotic lasers (CLs). After polarization multiplexing, the secure NRZ- OOK modulated optical signals are transmitted over indoor and outdoor free space optics (FSO) links based on GammaGamma channel model towards remote healthcare center. After chaos subtraction, the NRZ-OOK modulated optical signals are photodetected and passed on to bit error rate (BER) estimator for performance analysis. The electronic health (e-health) system based on the proposed OBAN provides adequate privacy for classified patient related information with added advantages of acceptable BER results, cost efficiency, speedy installation and suitable for use in current pandemic situation. © 2022 IEEE.

Adaptive Semantic Video Conferencing for OFDM Systems

Video conferencing has become more common than ever due to the COVID-19 pandemic, which makes high-resolution video transmission a pressing issue. Although semantic video conferencing (SVC) has achieved a great success to improve the transmission efficiency by only transmitting some key-points to represent changed expressions, its performance can still be improved by adapting to varying channel scenarios, which is lack of study when designing the whole SVC in the end-to-end manner. In this paper, we first establish a standard SVC-OFDM system. Then, the receiver part of the SVC is added with an adaptive network called Switch-SVC for varying channels and improve the accuracy of the received keypoints. Some parameters in Switch-SVC are trained online so that the receiver can adapt to the current environment. Simulation results show that the proposed method can greatly improve the keypoint reconstruction performance compared to the traditional SVC-OFDM receiver without online training. © 2022 IEEE.

Efficient multiplexing and variant discrimination in reverse-transcription loop-mediated isothermal amplification with sequence-specific hybridization probes.

Loop-mediated isothermal amplification (LAMP) has proven a robust and reliable nucleic acid amplification method that is well suited for simplified and rapid molecular diagnostics. Various approaches have emerged for sequence-specific detection of LAMP products, but with limitations to their widespread utility or applicability for single-nucleotide polymorphism detection and multiplexing. Here we demonstrate the use of simple hybridization probes (as used for qPCR) that enable simple multiplexing and SARS-CoV-2 variant typing in reverse-transcription LAMP. This approach requires no modification to the LAMP primers and is amenable to the detection of single-nucleotide polymorphisms and small sequence changes, which is usually difficult in LAMP. By extending LAMP's ability to be utilized for multitarget and single-base change detection, we hope to increase its potential to enable more and better molecular diagnostic testing.

Enhanced Enzymatically Amplified Metallization on Nanostructured Surfaces for Multiplexed Point-of-Care Electrical Detection of COVID-19 Biomarkers.

Inexpensive yet sensitive and specific biomarker detection is a critical bottleneck in diagnostics, monitoring, and surveillance of infectious diseases such as COVID-19. Multiplexed detection of several biomarkers can achieve wider diagnostic applicability, accuracy, and ease-of-use, while reducing cost. Current biomarker detection methods often use enzyme-linked immunosorbent assays (ELISA) with optical detection which offers high sensitivity and specificity. However, this is complex, expensive, and limited to detecting only a single analyte at a time. Here, it is found that biomarker-bound enzyme-labeled probes act synergistically with nanostructured catalytic surfaces and can be used to selectively reduce a soluble silver substrate to generate highly dense and conductive, localized surface silver metallization on microelectrode arrays. This enables a sensitive and quantitative, simple, direct electronic readout of biomarker binding without the use of any intermediate optics. Furthermore, the localized and dry-phase stable nature of the metallization enables multiplexed electronic measurement of several biomarkers from a single drop (<10 µL) of sample on a microchip.This method is applied for the multiplexed point-of-care (POC) quantitative detection of multiple COVID-19 antigen-specific antibodies. Combining a simple microchip and an inexpensive, cellphone-interfaced, portable reader, the detection and discrimination of biomarkers of prior infection versus vaccination is demonstrated.

Multiplexed Point-of-Care Electrical Detection of COVID-19 Biomarkers Using Enzymatically Amplified Metallization on Nanostructured Surfaces

We present a multiplexed, electronic enzyme-linked immunosorbent assay (E2LISA) microchip for direct electrical detection and quantitation of multiple biomarkers from a single microliter-scale drop of sample. Spatially distinct spots on the microchip, each containing an interdigitated microelectrode array, are coated with specific capture agents and used to bind different analytes. Enzyme-labeled probes are then used to convert this analyte binding to an electrical impedance signal via the amplified, localized deposition of silver on the nanostructured, catalytic surface of the chip prepared using gold nanoparticles. We use this microchip with a custom handheld, cellphone interfaced reader to detect COVID-19 biomarkers including antigen-specific antibodies and viral antigens. Further, we demonstrate the multiplexed measurement of distinct antibody responses in serum samples from convalescent COVID-19 patients versus uninfected vaccine recipients. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

Potential of Reverse Transcription Loop-Mediated Isothermal Amplification (RT-LAMP) as a Simple Rapid Molecular Diagnostic Tool to Detect SARS-CoV-2 Nucleocapsid Gene

Introduction: The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), identified in December of 2019, is the cause of the coronavirus disease 2019 (COVID-19). Due to the high reproductive rate of the virus, the best way to slow down the spread is to identify and isolate patients at the early stage of infections. The current diagnostic methods are either too expensive, slow or have low accuracy. Variants of SARS-CoV-2 with mutations at the primer binding sites may cause evasion of polymerase chain reaction (PCR) detection using current primers. Reverse transcription loop-mediated isothermal amplification (RT-LAMP) has potential as a rapid molecular test that is easy to conduct. Methods: LAMP primers were design based on the highly conserved regions of the SARS-CoV-2 Nucleocapsid (N) gene. RT-LAMP assays were conducted using an optimized Bst 3.0 polymerase protocol on T7 RNA polymerase synthesized RNA template. The LAMP sensitivity assay was tested on 1:10 serial diluted pJET1.2 vector with SARSCoV2 N gene inserts. A specificity test was conducted by running the test on plasmids containing SARS-CoV and MERS-CoV N genes. The results were visualised via gel electrophoresis, SYBR Green staining and Lateral Flow Dipstick (LFD). Results: The optimized protocol is sensitive enough to detect SARS-CoV-2 genetic material within 10 minutes but is most sensitive at 30 minutes. Additionally, it is specific to only the genetic materials of SARS-CoV-2. Furthermore, an LFD with multiple test lines was successful for multiplexed LAMP reactions with different genic regions of the virus. Conclusion: The multiplexed LFD-LAMP is potentially a simple yet specific and sensitive method of rapid molecular diagnostics of COVID-19.

A Dual-Encoded Bead-Based Immunoassay with Tunable Detection Range for COVID-19 Serum Evaluation.

Serological assay for coronavirus 2019 (COVID-19) patients including asymptomatic cases can inform on disease progression and prognosis. A detection method taking into account multiplex, high sensitivity, and a wider detection range will help to identify and treat COVID-19. Here we integrated color-size dual-encoded beads and rolling circle amplification (RCA) into a bead-based fluorescence immunoassay implemented in a size sorting chip to achieve high-throughput and sensitive detection. We used the assay for quantifying COVID-19 antibodies against spike S1, nucleocapsid, the receptor binding domain antigens. It also detected inflammatory biomarkers including interleukin-6, interleukin-1ß, procalcitonin, C-reactive protein whose concentrations range from pg mL-1 to µg mL-1 . Use of different size beads integrating with RCA results in a tunable detection range. The assay can be readily modified to simultaneously measure more COVID-19 serological molecules differing by orders of magnitude.

Fluorescent Biosensors for the Detection of Viruses Using Graphene and Two-Dimensional Carbon Nanomaterials.

Two-dimensional carbon nanomaterials have been commonly employed in the field of biosensors to improve their sensitivity/limits of detection and shorten the analysis time. These nanomaterials act as efficient transducers because of their unique characteristics, such as high surface area and optical, electrical, and magnetic properties, which in turn have been exploited to create simple, quick, and low-cost biosensing platforms. In this review, graphene and two-dimensional carbon material-based fluorescent biosensors are covered between 2010 and 2021, for the detection of different human viruses. This review specifically focuses on the new developments in graphene and two-dimensional carbon nanomaterials for fluorescent biosensing based on the Förster resonance energy transfer (FRET) mechanism. The high-efficiency quenching capability of graphene via the FRET mechanism enhances the fluorescent-based biosensors. The review provides a comprehensive reference for the different types of carbon nanomaterials employed for the detection of viruses such as Rotavirus, Ebola virus, Influenza virus H3N2, HIV, Hepatitis C virus (HCV), and Hepatitis B virus (HBV). This review covers the various multiplexing detection technologies as a new direction in the development of biosensing platforms for virus detection. At the end of the review, the different challenges in the use of fluorescent biosensors, as well as some insights into how to overcome them, are highlighted.

NIRVANA for Simultaneous Detection and Mutation Surveillance of SARS-CoV-2 and Co-infections of Multiple Respiratory Viruses.

Detection and mutation surveillance of SARS-CoV-2 are crucial for combating the COVID-19 pandemic. Here we describe a lab-based method for multiplex isothermal amplification-based sequencing and real-time analysis of multiple viral genomes. It can simultaneously detect SARS-CoV-2, influenza A, human adenovirus, and human coronavirus and monitor mutations for up to 96 samples in real time. The method proved to be rapid and sensitive (limit of detection: 29 viral RNA copies/µL of extracted nucleic acid) in detecting SARS-CoV-2 in clinical samples. We expect it to offer a promising solution for rapid field-deployable detection and mutational surveillance of pandemic viruses.