COVID-19 Biomarkers and Advanced Sensing Technologies for Point-of-Care (POC) Diagnosis

Carboxy-PEG-thiol functionalized gold nanoparticle conjugates for the detection of SARS-CoV-2: Detection tools and analytical method development

Addressing the need for accessible SARS-CoV-2 testing, carboxy-PEG 12-thiol functionalized gold nanoparticles conjugates were developed for rapid point-of-care (POC) detection against SARS-CoV-2 spike protein, pseudo-SARS-CoV-2, and authentic Beta SARS-CoV-2 virus particles. These conjugates leverage gold nanoparticles (AuNPs) as signal transducers, cross-linked to either angiotensin-converting enzyme 2 (ACE2) or SARS-CoV-2 spike protein receptor-binding domain (RBD) antibodies as bioreceptors and showed a distinct color shift from pink to blue. To assess their POC feasibility, the conjugates were integrated into facemasks and breathalyzers, wherein aerosolized SARS-CoV-2 antigens were successfully detected, producing a color change within 10 and 30 minutes for the breathalyzer and facemask prototypes, respectively. Furthermore, we explored quantitative analysis using varying concentrations of SARS-CoV-2 spike protein. Both conjugates demonstrated a linear relationship between blue color intensity and virus concentration, with linear ranges of 0.08-0.6 ng/mL and 0.04-0.5 ng/mL, respectively. Low limits of detection and quantification were also achieved. They exhibited specificity, responding solely to SARS-CoV-2 even in complex matrices containing diverse proteins, including the SARS-CoV-1 spike protein. Precision tests yielded coefficient of variations below 2 %, showcasing their remarkable reproducibility. This work presents a promising approach for rapid, sensitive, and specific POC detection of SARS-CoV-2 paving the way for improved pandemic response and management.

Crucial role of biosensors in the detection of helminth biomarkers in public health programmes

Helminthiases are highly prevalent but neglected infections that affect more than 1·5 billion people worldwide. Considering the worldwide prevalence of helminthiases, WHO has declared them a public health concern since 2001, necessitating rigorous control and elimination efforts. However, only a few reliable point-of-care diagnostic tests are available for assessing the effectiveness of public health interventions targeting helminthiases, thus increasing the risk of suboptimal outcomes, misallocation of resources, and emergence of drug-resistant helminths. This Review provides an introduction on helminthiases and strategies to achieve control, elimination, interruption in transmission, and eradication of these infections. The Review then comprehensively details the existent biosensors that can be used to detect these infections in human samples, focusing on their target biomarkers, the bioreceptors used, and the sensing readouts. The Review concludes with an in-depth discussion on the persistent challenges related to helminthiases, aiming to encourage the development of much-needed diagnostics specific to these neglected infections.

The Application of Graphene Field-Effect Transistor Biosensors in COVID-19 Detection Technology: A Review

Coronavirus disease 2019 (COVID-19) is a disease caused by the infectious agent of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2). The primary method of diagnosing SARS-CoV-2 is nucleic acid detection, but this method requires specialized equipment and is time consuming. Therefore, a sensitive, simple, rapid, and low-cost diagnostic test is needed. Graphene field-effect transistor (GFET) biosensors have become the most promising diagnostic technology for detecting SARS-CoV-2 due to their advantages of high sensitivity, fast-detection speed, label-free operation, and low detection limit. This review mainly focus on three types of GFET biosensors to detect SARS-CoV-2. GFET biosensors can quickly identify SARS-CoV-2 within ultra-low detection limits. Finally, we will outline the pros and cons of the diagnostic approaches as well as future directions.

Batteryless wireless magnetostrictive Fe30Co70/Ni clad plate for human coronavirus 229E detection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been garnered increasing for its rapid worldwide spread. Each country had implemented city-wide lockdowns and immigration regulations to prevent the spread of the infection, resulting in severe economic consequences. Materials and technologies that monitor environmental conditions and wirelessly communicate such information to people are thus gaining considerable attention as a countermeasure. This study investigated the dynamic characteristics of batteryless magnetostrictive alloys for energy harvesting to detect human coronavirus 229E (HCoV-229E). Light and thin magnetostrictive Fe-Co/Ni clad plate with rectification, direct current (DC) voltage storage capacitor, and wireless information transmission circuits were developed for this purpose. The power consumption was reduced by improving the energy storage circuit, and the magnetostrictive clad plate under bending vibration stored a DC voltage of 1.9 V and wirelessly transmitted a signal to a personal computer once every 5 min and 10 s under bias magnetic fields of 0 and 10 mT, respectively. Then, on the clad plate surface, a novel CD13 biorecognition layer was immobilized using a self-assembled monolayer of -COOH groups, thus forming an amide bond with -NH2 groups for the detection of HCoV-229E. A bending vibration test demonstrated the resonance frequency changes because of HCoV-229E binding. The fluorescence signal demonstrated that HCoV-229E could be successfully detected. Thus, because HCoV-229E changed the dynamic characteristics of this plate, the CD13-modified magnetostrictive clad plate could detect HCoV-229E from the interval of wireless communication time. Therefore, a monitoring system that transmits/detects the presence of human coronavirus without batteries will be realized soon.

Disposable Voltammetric Immunosensor for D-Dimer Detection as Early Biomarker of Thromboembolic Disease and of COVID-19 Prognosis

In this work, we report on the development of a simple electrochemical immunosensor for the detection of D-dimer protein in human plasma samples. The immunosensor is built by a simple drop-casting procedure of chitosan nanoparticles (CSNPs) as biocompatible support, Protein A (PrA), to facilitate the proper orientation of the antibody sites to epitopes as a capture biomolecule, and the D-dimer antibody onto a carboxyl functionalized multi-walled carbon nanotubes screen printed electrode (MWCNTs-SPE). The CSNPs have been morphologically characterized by Scanning Electron Microscopy (SEM) and Dynamic Light Scattering (DLS) techniques. Successively, the electrochemical properties of the screen-printed working electrode after each modification step have been characterized by differential pulse voltammetry (DPV) and electrochemical impedance spectroscopy (EIS). The resulting MWCNTs-CSNPs-PrA-D-dimer Ab immunosensor displays an optimal and promising platform for antibody immobilization and specific D-dimer detection. DPV has been used to investigate the antigen/antibody interaction at different D-dimer concentrations. The proposed voltammetric immunosensor allowed a linear range from 2 to 500 μg L^-1 with a LOD of 0.6 μg L^-1 and a sensitivity of 1.3 μA L μg^-1 cm^-2. Good stability and a fast response time (5 s) have been reported. Lastly, the performance of the voltammetric immunosensor has been tested in human plasma samples, showing satisfactory results, thus attesting to the promising feasibility of the proposed platform for detecting D-dimer in physiological samples.

Deep Learning for Detecting COVID-19 Using Medical Images

The global spread of COVID-19 (also known as SARS-CoV-2) is a major international public health crisis [...].

Hypoxia-inducible factor-1α and ischemia-modified albumin levels in intensive care COVID-19 Patients

OBJECTIVES

In this study, it was aimed to evaluate the hypoxia-inducible factor-1α (HIF-1α) and ischemia-modified albumin (IMA) levels of patients diagnosed with COVID-19 in the intensive care unit (ICU) and healthy controls. To our knowledge, this is the first study investigate HIF-1α and IMA levels in COVID-19 patients in ICUs and comparing them with a healthy control group. For this reason, our study is original and will contribute to the literature.

METHODS

A total of 70 intensive care patients diagnosed with COVID-19, and 72 healthy controls were included in the study.

RESULTS

When we compared the patient and healthy control group; there were no statistically significant differences between the groups in terms of age and gender (p>0.05). No exitus was observed in the patient group. We found weak correlation between HIF-1α and IMA (r: 0.320). However, there were statistically significant differences in HIF-1α and IMA levels in the patient group. The receiver operating characteristic (ROC) curve demonstrated an area under curve (AUC) value of 0.651 for HIF-1α and 0.937 for IMA.

CONCLUSIONS

The HIF-1α and IMA levels were significantly higher among COVID-19 patients in ICU compared with healthy controls. HIF-1α and IMA levels can be used as reliable markers for the prognosis of COVID-19.

Angiotensin-Converting Enzyme 2-Based Biosensing Modalities and Devices for Coronavirus Detection

Rapid and cost-effective diagnostic tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are a critical and valuable weapon for the coronavirus disease 2019 (COVID-19) pandemic response. SARS-CoV-2 invasion is primarily mediated by human angiotensin-converting enzyme 2 (hACE2). Recent developments in ACE2-based SARS-CoV-2 detection modalities accentuate the potential of this natural host-virus interaction for developing point-of-care (POC) COVID-19 diagnostic systems. Although research on harnessing ACE2 for SARS-CoV-2 detection is in its infancy, some interesting biosensing devices have been developed, showing the commercial viability of this intriguing new approach. The exquisite performance of the reported ACE2-based COVID-19 biosensors provides opportunities for researchers to develop rapid detection tools suitable for virus detection at points of entry, workplaces, or congregate scenarios in order to effectively implement pandemic control and management plans. However, to be considered as an emerging approach, the rationale for ACE2-based biosensing needs to be critically and comprehensively surveyed and discussed. Herein, we review the recent status of ACE2-based detection methods, the signal transduction principles in ACE2 biosensors and the development trend in the future. We discuss the challenges to development of ACE2-biosensors and delineate prospects for their use, along with recommended solutions and suggestions.

Advances in Biosensing Technologies for Diagnosis of COVID-19

The COVID-19 pandemic has severely impacted normal human life worldwide. Due to its rapid community spread and high mortality statistics, the development of prompt diagnostic tests for a massive number of samples is essential. Currently used traditional methods are often expensive, time-consuming, laboratory-based, and unable to handle a large number of specimens in resource-limited settings. Because of its high contagiousness, efficient identification of SARS-CoV-2 carriers is crucial. As the advantages of adopting biosensors for efficient diagnosis of COVID-19 increase, this narrative review summarizes the recent advances and the respective reasons to consider applying biosensors. Biosensors are the most sensitive, specific, rapid, user-friendly tools having the potential to deliver point-of-care diagnostics beyond traditional standards. This review provides a brief introduction to conventional methods used for COVID-19 diagnosis and summarizes their advantages and disadvantages. It also discusses the pathogenesis of COVID-19, potential diagnostic biomarkers, and rapid diagnosis using biosensor technology. The current advancements in biosensing technologies, from academic research to commercial achievements, have been emphasized in recent publications. We covered a wide range of topics, including biomarker detection, viral genomes, viral proteins, immune responses to infection, and other potential proinflammatory biomolecules. Major challenges and prospects for future application in point-of-care settings are also highlighted.

A Short Review Comparing Carbon-Based Electrochemical Platforms With Other Materials For Biosensing SARS-Cov-2

Due to the 2019 SARS-CoV-2 outbreak, low-cost, fast, and user-friendly diagnostic kits for biosensing SARS-CoV-2 in real samples employing multiple working electrodes are in high demand. Choosing SARS-CoV-2 detecting electrodes is difficult because each has advantages and limitations. Carbon-based electrochemical sensing applications have attracted attention from the electrochemical sensing community because carbon and carbon-based materials have been a godsend for testing utilizing an electrochemical platform. Carbon working electrode electrochemical platforms are cost-effective and fast. Covid-sensors use carbon-based materials because they can be easily changed (with inorganic and organic functionalities), have quick response kinetics, and are chemically resistant. Covid-19 sensing materials include graphene and graphite. This review explains how carbon materials have been employed in N and S protein electrochemical detection. Here, we discussed a carbon-based technology for SARS-CoV-2 biosensing. We've compared carbon-based electrochemical sensing to different electrodes.

AuNP-based biosensors for the diagnosis of pathogenic human coronaviruses: COVID-19 pandemic developments

The outbreak rate of human coronaviruses (CoVs) especially highly pathogenic CoVs is increasing alarmingly. Early detection of these viruses allows treatment interventions to be provided more quickly to people at higher risk, as well as helping to identify asymptomatic carriers and isolate them as quickly as possible, thus preventing the disease transmission chain. The current diagnostic methods such as RT-PCR are not ideal due to high cost, low accuracy, low speed, and probability of false results. Therefore, a reliable and accurate method for the detection of CoVs in biofluids can become a front-line tool in order to deal with the spread of these deadly viruses. Currently, the nanomaterial-based sensing devices for detection of human coronaviruses from laboratory diagnosis to point-of-care (PoC) diagnosis are progressing rapidly. Gold nanoparticles (AuNPs) have revolutionized the field of biosensors because of the outstanding optical and electrochemical properties. In this review paper, a detailed overview of AuNP-based biosensing strategies with the varied transducers (electrochemical, optical, etc.) and also different biomarkers (protein antigens and nucleic acids) was presented for the detection of human coronaviruses including SARS-CoV-2, SARS-CoV-1, and MERS-CoV and lowly pathogenic CoVs. The present review highlights the newest trends in the SARS-CoV-2 nanobiosensors from the beginning of the COVID-19 epidemic until 2022. We hope that the presented examples in this review paper convince readers that AuNPs are a suitable platform for the designing of biosensors.

LW-CovidNet: Automatic covid-19 lung infection detection from chest X-ray images

Coronavirus Disease 2019 (Covid-19) overtook the worldwide in early 2020, placing the world's health in threat. Automated lung infection detection using Chest X-ray images has a ton of potential for enhancing the traditional covid-19 treatment strategy. However, there are several challenges to detect infected regions from Chest X-ray images, including significant variance in infected features similar spatial characteristics, multi-scale variations in texture shapes and sizes of infected regions. Moreover, high parameters with transfer learning are also a constraints to deploy deep convolutional neural network(CNN) models in real time environment. A novel covid-19 lightweight CNN(LW-CovidNet) method is proposed to automatically detect covid-19 infected regions from Chest X-ray images to address these challenges. In our proposed hybrid method of integrating Standard and Depth-wise Separable convolutions are used to aggregate the high level features and also compensate the information loss by increasing the Receptive Field of the model. The detection boundaries of disease regions representations are then enhanced via an Edge-Attention method by applying heatmaps for accurate detection of disease regions. Extensive experiments indicate that the proposed LW-CovidNet surpasses most cutting-edge detection methods and also contributes to the advancement of state-of-the-art performance. It is envisaged that with reliable accuracy, this method can be introduced for clinical practices in the future.

Integration of Power-Free and Self-Contained Microfluidic Chip with Fiber Optic Particle Plasmon Resonance Aptasensor for Rapid Detection of SARS-CoV-2 Nucleocapsid Protein

The global pandemic of COVID-19 has created an unrivalled need for sensitive and rapid point-of-care testing (POCT) methods for the detection of infectious viruses. For the novel coronavirus SARS-CoV-2, the nucleocapsid protein (N-protein) is one of the most abundant structural proteins of the virus and it serves as a useful diagnostic marker for detection. Herein, we report a fiber optic particle plasmon resonance (FOPPR) biosensor which employed a single-stranded DNA (ssDNA) aptamer as the recognition element to detect the SARS-CoV-2 N-protein in 15 min with a limit of detection (LOD) of 2.8 nM, meeting the acceptable LOD of 10⁶ copies/mL set by the WHO target product profile. The sensor chip is a microfluidic chip based on the balance between the gravitational potential and the capillary force to control fluid loading, thus enabling the power-free auto-flowing function. It also has a risk-free self-contained design to avoid the risk of the virus leaking into the environment. These findings demonstrate the potential for designing a low-cost and robust POCT device towards rapid antigen detection for early screening of SARS-CoV-2 and its related mutants.

Voice Features of Sustained Phoneme as COVID-19 Biomarker

BACKGROUND

The COVID-19 pandemic has resulted in enormous costs to our society. Besides finding medicines to treat those infected by the virus, it is important to find effective and efficient strategies to prevent the spreading of the disease. One key factor to prevent transmission is to identify COVID-19 biomarkers that can be used to develop an efficient, accurate, noninvasive, and self-administered screening procedure. Several COVID-19 variants cause significant respiratory symptoms, and thus a voice signal may be a potential biomarker for COVID-19 infection.

AIM

This study investigated the effectiveness of different phonemes and a range of voice features in differentiating people infected by COVID-19 with respiratory tract symptoms.

METHOD

This cross-sectional, longitudinal study recorded six phonemes (i.e., /a/, /e/, /i/, /o/, /u/, and /m/) from 40 COVID-19 patients and 48 healthy subjects for 22 days. The signal features were obtained for the recordings, which were statistically analyzed and classified using Support Vector Machine (SVM).

RESULTS

The statistical analysis and SVM classification show that the voice features related to the vocal tract filtering (e.g., MFCC, VTL, and formants) and the stability of the respiratory muscles and lung volume (Intensity-SD) were the most sensitive to voice change due to COVID-19. The result also shows that the features extracted from the vowel /i/ during the first 3 days after admittance to the hospital were the most effective. The SVM classification accuracy with 18 ranked features extracted from /i/ was 93.5% (with F1 score of 94.3%).

CONCLUSION

A measurable difference exists between the voices of people with COVID-19 and healthy people, and the phoneme /i/ shows the most pronounced difference. This supports the potential for using computerized voice analysis to detect the disease and consider it a biomarker.

Progress and Challenges of Point-of-Need Photonic Biosensors for the Diagnosis of COVID-19 Infections and Immunity

The new coronavirus disease, COVID-19, caused by SARS-CoV-2, continues to affect the world and after more than two years of the pandemic, approximately half a billion people are reported to have been infected. Due to its high contagiousness, our life has changed dramatically, with consequences that remain to be seen. To prevent the transmission of the virus, it is crucial to diagnose COVID-19 accurately, such that the infected cases can be rapidly identified and managed. Currently, the gold standard of testing is polymerase chain reaction (PCR), which provides the highest accuracy. However, the reliance on centralized rapid testing modalities throughout the COVID-19 pandemic has made access to timely diagnosis inconsistent and inefficient. Recent advancements in photonic biosensors with respect to cost-effectiveness, analytical performance, and portability have shown the potential for such platforms to enable the delivery of preventative and diagnostic care beyond clinics and into point-of-need (PON) settings. Herein, we review photonic technologies that have become commercially relevant throughout the COVID-19 pandemic, as well as emerging research in the field of photonic biosensors, shedding light on prospective technologies for responding to future health outbreaks. Therefore, in this article, we provide a review of recent progress and challenges of photonic biosensors that are developed for the testing of COVID-19, consisting of their working fundamentals and implementation for COVID-19 testing in practice with emphasis on the challenges that are faced in different development stages towards commercialization. In addition, we also present the characteristics of a biosensor both from technical and clinical perspectives. We present an estimate of the impact of testing on disease burden (in terms of Disability-Adjusted Life Years (DALYs), Quality Adjusted Life Years (QALYs), and Quality-Adjusted Life Days (QALDs)) and how improvements in cost can lower the economic impact and lead to reduced or averted DALYs. While COVID19 is the main focus of these technologies, similar concepts and approaches can be used and developed for future outbreaks of other infectious diseases.

A proteomics-MM/PBSA dual approach for the analysis of SARS-CoV-2 main protease substrate peptide specificity

The main protease M^pro of SARS-CoV-2 is a well-studied major drug target. Additionally, it has been linked to this virus' pathogenicity, possibly through off-target effects. It is also an interesting diagnostic target. To obtain more data on possible substrates as well as to assess the enzyme's primary specificity a two-step approach was introduced. First, Terminal Amine Isobaric Labeling of Substrates (TAILS) was employed to identify novel M^pro cleavage sites in a mouse lung proteome library. In a second step, using a structural homology model, the MM/PBSA variant MM/GBSA (Molecular Mechanics Poisson-Boltzmann/Generalized Born Surface Area) free binding energy calculations were carried out to determine relevant interacting amino acids. As a result, 58 unique cleavage sites were detected, including six that displayed glutamine at the P1 position. Furthermore, modeling results indicated that M^pro has a far higher potential promiscuity towards substrates than expected. The combination of proteomics and MM/PBSA modeling analysis can thus be useful for elucidating the specificity of M^pro, and thus open novel perspectives for the development of future peptidomimetic drugs against COVID-19, as well as diagnostic tools.

Assessing, Pricing and Funding Point-of-Care Diagnostic Tests for Community-Acquired Acute Respiratory Tract Infections-Overview of Policies Applied in 17 European Countries

Point-of-care diagnostic tests for community-acquired acute respiratory tract infections (CA-ARTI) can support doctors by improving antibiotic prescribing. However, little is known about health technology assessment (HTA), pricing and funding policies for CA-ARTI diagnostics. Thus, this study investigated these policies for this group of devices applied in the outpatient setting in Europe. Experts from competent authority responded to a questionnaire in Q4/2020. Information is available for 17 countries. Studied countries do not base their pricing and funding decision for CA-ARTI diagnostics on an HTA. While a few countries impose price regulation for some publicly funded medical devices, the prices of CA-ARTI diagnostics are not directly regulated in any of the surveyed countries. Indirect price regulation through public procurement is applied in some countries. Reimbursement lists of medical devices eligible for public funding exist in several European countries, and in some countries these lists include CA-ARTI diagnostics. In a few countries, the public payer funds the health professional for performing the service of conducting the test. Given low levels of regulation and few incentives, the study findings suggest room for strengthening pricing and funding policies of CA-ARTI diagnostics to contribute to increased acceptance and use of these point-of-care tests.

Advances in diagnostic tools for respiratory tract infections: from tuberculosis to COVID-19 - changing paradigms?

Respiratory tract infections (RTIs) are one of the most common reasons for seeking healthcare, but are amongst the most challenging diseases in terms of clinical decision-making. Proper and timely diagnosis is critical in order to optimise management and prevent further emergence of antimicrobial resistance by misuse or overuse of antibiotics. Diagnostic tools for RTIs include those involving syndromic and aetiological diagnosis: from clinical and radiological features to laboratory methods targeting both pathogen detection and host biomarkers, as well as their combinations in terms of clinical algorithms. They also include tools for predicting severity and monitoring treatment response. Unprecedented milestones have been achieved in the context of the COVID-19 pandemic, involving the most recent applications of diagnostic technologies both at genotypic and phenotypic level, which have changed paradigms in infectious respiratory diseases in terms of why, how and where diagnostics are performed. The aim of this review is to discuss advances in diagnostic tools that impact clinical decision-making, surveillance and follow-up of RTIs and tuberculosis. If properly harnessed, recent advances in diagnostic technologies, including omics and digital transformation, emerge as an unprecedented opportunity to tackle ongoing and future epidemics while handling antimicrobial resistance from a One Health perspective.

SARS-CoV-2 Detection Methods

A fast and highly specific detection of COVID-19 infections is essential in managing the virus dissemination networks. The most relevant technologies developed for SARS-CoV-2 detection, along with their advantages and limitations, will be presented and fully explored. Additionally, some of the newest and emerging COVID-19 diagnosis tools, such as biosensing platforms, will also be introduced. Considering the extreme relevance that all these technologies assume in pandemic control, it is of the utmost relevance to have an intrinsic knowledge of the parameters that need to be taken into consideration before choosing the most adequate test for a particular situation. Moreover, the new variants of the virus and their potential impact on the detection method’s effectiveness will be discussed. In order to better manage the pandemic, it is essential to maintain continuous research into the SARS-CoV-2 genome and updated genomic surveillance at the global level. This will allow for timely detection of new mutations and viral variants, which may affect the performance of COVID-19 detection tests.

Microfluidic-Based Novel Optical Quantification of Red Blood Cell Concentration in Blood Flow

The optical quantification of hematocrit (volumetric percentage of red blood cells) in blood flow in microfluidic systems provides enormous help in designing microfluidic biosensing platforms with enhanced sensitivity. Although several existing methods, such as centrifugation, complete blood cell count, etc., have been developed to measure the hematocrit of the blood at the sample preparation stage, these methods are impractical to measure the hematocrit in dynamic microfluidic blood flow cases. An easy-to-access optical method has emerged as a hematocrit quantification technique to address this limitation, especially for the microfluidic-based biosensing platform. A novel optical quantification method is demonstrated in this study, which can measure the hematocrit of the blood flow at a targeted location in a microchannel at any given instant. The images of the blood flow were shot using a high-speed camera through an inverted transmission microscope at various light source intensities, and the grayscale of the images was measured using an image processing code. By measuring the average grayscale of the images of blood flow at different luminous exposures, a relationship between hematocrit and grayscale has been developed. The quantification of the hematocrit in the microfluidic system can be instant and easy with this method. The innovative proposed technique has been evaluated with porcine blood samples with hematocrit ranging from 5% to 70%, flowing through 1000 µm wide and 100 µm deep microchannels. The experimental results obtained strongly supported the proposed optical technique of hematocrit measurement in microfluidic systems.

Measuring the Possibility of Middle Ear Discharge for COVID-19 Test Material

The COVID-19 pandemic is still ongoing, and new variants continue to emerge. Various examination methods and sampling specimens are continuously being developed and published. The standard for sampling is in the nasopharynx. However, in children, this is often uncomfortable and at risk of eliciting complications. Therefore, it is necessary to look for other alternative sampling sites such as fluid from the middle ear. Scientific evidence shows that the middle ear can be a place for the attachment and growth of the SARS-CoV-2 virus. Currently, to the best of the author's knowledge, there have been no publications on middle ear discharge as a sample for the determination of the diagnosis of COVID-19. Based on this, the authors would like to explore the possibility of middle ear discharge for COVID-19 test material. A narrative review on the use of middle ear discharge as a potential diagnostic specimen for COVID-19 was conducted. The searches were conducted in the PubMed and ProQuest databases.

Self-Powered Wireless Sensor Matrix for Air Pollution Detection with a Neural Predictor

Predicting the status of particulate air pollution is extremely important in terms of preventing possible vascular and lung diseases, improving people’s quality of life and, of course, actively counteracting pollution magnification. Hence, there is great interest in developing methods for pollution prediction. In recent years, the importance of methods based on classical and more advanced neural networks is increasing. However, it is not so simple to determine a good and universal method due to the complexity and multiplicity of measurement data. This paper presents an approach based on Deep Learning networks, which does not use Bayesian sub-predictors. These sub-predictors are used to marginalize the importance of some data part from multisensory platforms. In other words—to filter out noise and mismeasurements before the actual processing with neural networks. The presented results shows the applied data feature extraction method, which is embedded in the proposed algorithm, allows for such feature clustering. It allows for more effective prediction of future air pollution levels (accuracy—92.13%). The prediction results shows that, besides using standard measurements of temperature, humidity, wind parameters and illumination, it is possible to improve the performance of the predictor by including the measurement of traffic noise (Accuracy—94.61%).