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The deadly novel coronavirus SARS-CoV-2 is responsible for COVID-19, which was first recognized in Wuhan, China, in December 2019. Rapid identification at primary stage of the novel coronavirus, SARS-CoV-2, is important to restrict it and prevent the pandemic. Real-time RT-PCR assays are the best diagnostic tests presently available for SARS-CoV-2 detection, which are highly sensitive, even though expensive equipment and trained technicians are necessary. Furthermore, the method has moderately long time bound. This deadly viral infection can also be detected by applying various spectroscopic techniques as spectroscopy can provide fast, precise identification and monitoring, leading to the overall understanding of its mutation rates, which will further facilitate antiviral drug development as well as vaccine development. It is an innovative and non-invasive technique for combating the spread of novel coronavirus. Selleck Infigratinib This review article demonstrates the application of various spectroscopic techniques to detect COVID-19 rapidly. Different spectroscopy-based detection protocols and additional development of new, novel sensors and biosensors along with diagnostic kits had been described here stressing the status of sensitive diagnostic systems to handle with the COVID-19 outbreak.

Spectroscopy A versatile sensing tool for cost-effective and rapid detection of novel Coronavirus (COVID-19).

Spectroscopy A versatile sensing tool for cost-effective and rapid detection of novel Coronavirus (COVID-19).Decision-making in two-alternative forced choice tasks has several underlying components including stimulus encoding, perceptual categorization, response selection, and response execution. Sequential sampling models of decision-making are based on an evidence accumulation process to a decision boundary. Animal and human studies have focused on perceptual categorization and provide evidence linking brain signals in parietal cortex to the evidence accumulation process. In this exploratory study, we use a task where the dominant contribution to response time is response selection and model the response time data with the drift-diffusion model. EEG measurement during the task show that the Readiness Potential (RP) recorded over motor areas has timing consistent with the evidence accumulation process. The duration of the RP predicts decision-making time, the duration of evidence accumulation, suggesting that the RP partly reflects an evidence accumulation process for response selection in the motor system. Thus, evidence accumulation may be a neural implementation of decision-making processes in both perceptual and motor systems. The contributions of perceptual categorization and response selection to evidence accumulation processes in decision-making tasks can be potentially evaluated by examining the timing of perceptual and motor EEG signals.An efficient building should be able to control its internal temperature in a manner that considers both the building's energy efficiency and the comfort level of its occupants. Thermostats help to control the temperature within a building by providing real-time data on the temperature inside that space to determine whether it is within the acceptable range of that building's control system, and proper thermostat placement helps to better control a building's temperature. More thermostats can provide better control of a building, as well as a better understanding of the building's temperature distribution. In order to determine the minimum number of thermostats required to accurately measure and control the internal temperature distribution of a building, it is necessary to find the locations that show similar environmental conditions. In this paper, we analyzed high resolution temperature measurements from a commercial building using wireless sensors to assess the performance and health of the building's HVAC zoning and controls system. Then we conducted two cluster analyses to evaluate the efficiency of the existing zoning structure and to find the optimal number of clusters. K-means and time series clustering were used to identify the temperature clusters per building floor. Based on statistical assessments, we observed that time series clustering showed better results than k-means clustering.Human norovirus (HuNoV) is a highly contagious pathogenic virus that is transmitted through contaminated food, water, high-touch surfaces and aerosols. Globally, there are an estimated 685 million infections annually due to norovirus, including 200 million affecting children under the age of 5. HuNoV causes approximately 50, 000 child deaths per year and costs an estimated USD $60 billion annually in healthcare. This study sought to determine the inactivation profile of ultraviolet subtype C (UVC) against norovirus using a UVC light-emitting diode (LED) array, KL265-50V-SM-WD. The array emitted radiation at 269 nm peak wavelength and a measured fluence of 1.25 mW cm-2 at a 7 cm source-surface distance. Since the HuNoV is not cultivable, the study utilized feline calicivirus (FCV) ATCC VR-782, a recommended surrogate as challenge organism. The test followed modified ASTM E2197. Assessment of virus inactivation was performed using a plaque assay method. With irradiance at a UVC dose of 22.5 mJ cm-2, the study obtained 99.9 % virus reduction (3 log reduction). The results demonstrate that the UVC LED array can provide effective inactivation of HuNoV.Vegetation complexity is potentially important for urban green space designs aimed at fostering microbial biodiversity to benefit human health. Exposure to urban microbial biodiversity may influence human health outcomes via immune training and regulation. In this context, improving human exposure to microbiota via biodiversity-centric urban green space designs is an underused opportunity. There is currently little knowledge on the association between vegetation complexity (i.e. diversity and structure) and soil microbiota of urban green spaces. Here, we investigated the association between vegetation complexity and soil bacteria in urban green spaces in Bournemouth, UK; Haikou, China; and the City of Playford, Australia by sequencing the 16S rRNA V4 gene region of soil samples and assessing bacterial diversity. We characterized these green spaces as having 'low' or 'high' vegetation complexity and explored whether these two broad categories contained similar bacterial community compositions and diversity around the world. Within cities, we observed significantly different alpha and beta diversities between vegetation complexities; however, these results varied between cities. Rare genera ( less then 1% relative abundance individually, on average 35% relative abundance when pooled) were most likely to be significantly different in sequence abundance between vegetation complexities and therefore explained much of the differences in microbial communities observed. Overall, general associations exist between soil bacterial communities and vegetation complexity, although these are not consistent between cities. Therefore, more in-depth work is required to be done locally to derive practical actions to assist the conservation and restoration of microbial communities in urban areas.Sewage-based surveillance for COVID-19 has been described in multiple countries and multiple settings. However, nearly all are based on testing sewage treatment plant inflows and outflows using structured sewage networks and treatment systems. Many resource-limited countries worldwide have open canals, lakes and other such waste-contaminated water bodies that act as a means of sewage effluent discharge. These could serve as hyperlocal testing points for detecting COVID-19 incidence using the effluents from nearby communities. However, a sensitive, robust and economical method of SARS-CoV-2 RNA detection from open waste contaminated water bodies in resource-constrained regions is currently lacking. A protocol employed in Bangalore, India, where SARS-CoV-2 RNA levels were evaluated using two open canal systems during the first and second waves in the present study. SARS-CoV-2 RNA was measured using two strategies a modified TrueNATTM microchip-based rapid method and traditional real-time reverse transcription-PCR (rRT-PCR), which were compared for analytical sensitivity, cost and relative ease of use. SARS-CoV-2 RNA levels were detected at lower levels during the earlier half compared to the later half of the first wave in 2020. The opposite trend was seen in the second wave in 2021. Interestingly, the change in RNA levels corresponded with the community burden of COVID-19 at both sites. The modified TrueNATTM method yielded concordant results to traditional rRT-PCR in sensitivity and specificity and cost. It provides a simple, cost-effective method for detecting and estimating SARS-CoV-2 viral RNA from open-water sewage canals contaminated with human excreta and industrial waste that can be adopted in regions or countries that lack structured sewage systems.Staphylococcus aureus (SA) colonization has significant implications in healthcare-associated infections. Here we describe a prospective study conducted in pre-surgical outpatients, done with the aim of identifying demographic and clinical risk factors for SA colonization. We found younger age to be a potential predictor of SA colonization.Salmonella enterica subspecies enterica serovar Corvallis (S. Corvallis) has been identified as a human pathogen and as a food contaminant. Diarrhoeal disease is a common diagnosis in tourists visiting Southeast Asia, often with unknown aetiology. However, numerous public health institutes have identified Salmonella as a common causative agent when consuming contaminated food and water. Genomic data from environmental isolates from a Cambodian informal market were uploaded to the National Center for Biotechnology Information (NCBI) platform, allowing the novel sequences to be compared to global whole-genome sequence archives. The comparison revealed that two human clinical isolates from England and four of the environmental isolates were closely related, with an average single nucleotide polymorphism (SNP) difference of 1 (0-3 SNPs). A maximum-likelihood tree based on core SNPs was generated comparing the 4 isolates recovered from a Cambodian informal market with 239 isolates of S. Corvallis received from routine surveillance of human salmonellosis in England and confirmed the close relationship. In addition, the environmental isolates clustered into a broader phylogenetic group within the S. Corvallis population containing 68 additional human isolates, of which 42 were from patients who reported recent international travel, almost exclusively to Southeast Asia. The environmental isolates of S. Corvallis isolated from an informal market in Cambodia are concerning for public health due to their genetic similarity to isolates (e.g. clinical isolates from the UK) with known human virulence and pathogenicity. This study emphasizes the benefits of global and public data sharing of pathogen genomes.Coral reefs are declining due to anthropogenic disturbances, including climate change. Therefore, improving our understanding of coral ecosystems is vital, and the influence of bacteria on coral health has attracted particular interest. However, a gnotobiotic coral model that could enhance studies of coral-bacteria interactions is absent. To address this gap, we tested the ability of treatment with seven antibiotics for 3 weeks to deplete bacteria in Exaiptasia diaphana, a sea anemone widely used as a coral model. Digital droplet PCR (ddPCR) targeting anemone Ef1-α and bacterial 16S rRNA genes was used to quantify bacterial load, which was found to decrease six-fold. However, metabarcoding of bacterial 16S rRNA genes showed that alpha and beta diversity of the anemone-associated bacterial communities increased significantly. Therefore, gnotobiotic E. diaphana with simplified, uniform bacterial communities were not generated, with biofilm formation in the culture vessels most likely impeding efforts to eliminate bacteria.