Integrating Water Purification with Electrochemical Aptamer Sensing for Detecting SARS-CoV-2 in Wastewater

Wastewater analysis of pathogens, particularly SARS-CoV-2, is instrumental in tracking and monitoring infectious diseases in a population. This method can be used to generate early warnings regarding the onset of an infectious disease and predict the associated infection trends. Currently, wastewater analysis of SARS-CoV-2 is almost exclusively performed using polymerase chain reaction for the amplification-based detection of viral RNA at centralized laboratories. Despite the development of several biosensing technologies offering point-of-care solutions for analyzing SARS-CoV-2 in clinical samples, these remain elusive for wastewater analysis due to the low levels of the virus and the interference caused by the wastewater matrix. Herein, we integrate an aptamer-based electrochemical chip with a filtration, purification, and extraction (FPE) system for developing an alternate in-field solution for wastewater analysis. The sensing chip employs a dimeric aptamer, which is universally applicable to the wild-type, alpha, delta, and omicron variants of SARS-CoV-2. We demonstrate that the aptamer is stable in the wastewater matrix (diluted to 50%) and its binding affinity is not significantly impacted. The sensing chip demonstrates a limit of detection of 1000 copies/L (1 copy/mL), enabled by the amplification provided by the FPE system. This allows the integrated system to detect trace amounts of the virus in native wastewater and categorize the amount of contamination into trace (<10 copies/mL), medium (10-1000 copies/mL), or high (>1000 copies/mL) levels, providing a viable wastewater analysis solution for in-field use.

Thorectidiol A Isolated from the Marine Sponge Dactylospongia elegans Disrupts Interactions of the SARS-CoV-2 Spike Receptor Binding Domain with the Host ACE2 Receptor

Thorectidiols isolated from the marine sponge Dactylospongia elegans (family Thorectidae, order Dictyoceratida) collected in Papua New Guinea are a family of symmetrical and unsymmetrical dimeric biphenyl meroterpenoid stereoisomers presumed to be products of oxidative phenol coupling of a co-occurring racemic monomer, thorectidol (3). One member of the family, thorectidiol A (1), has been isolated in its natural form, and its structure has been elucidated by analysis of NMR, MS, and ECD data. Acetylation of the sponge extract facilitated isolation of additional thorectidiol diacetate stereoisomers and the isolation of the racemic monomer thorectidol acetate (6). Racemic thorectidiol A (1) showed selective inhibition of the SARS-CoV-2 spike receptor binding domain (RBD) interaction with the host ACE2 receptor with an IC50 = 1.0 ± 0.7 μM.

Gravity Drainage of Bitumen Induced by Solvent Leaching

Steam-based thermal recovery processes are energy-intensive and pose environmental concerns due to their high greenhouse gas emissions. The application of solvents has shown promise in reducing the environmental impact of these processes. In this work, the solvent chamber theory is used to study the gravity drainage of bitumen. The results reveal that the drainage rate can be scaled using the thermophysical properties of solvents. The drainage rate is shown to be directly related to the density difference between bitumen and solvent and inversely proportional to the mixture viscosity. A universal scaling relation between the Sherwood number, as a measure of the mass transfer, and Rayleigh number, as a measure of the natural convection, in the form of Sh = βRa is presented using the experimental data of various solvents. This linear relationship is consistent with the theoretical studies of buoyancy-driven convection. Moreover, the scaling prefactor β is found to decrease with increasing natural log of the mobility ratio (α), which results in a lower rate of convective mass transfer. Furthermore, a new critical Rayleigh number equation based on the power-law mixing rule (PLMR) is derived, and the results are compared with the available theories in the literature based on the exponential mixing rule (EMR). The findings provide insights into understanding the convective dissolution with large viscosity contrast. Furthermore, the developed scaling relation provides a useful tool to predict the convective mixing of different bitumen/solvent systems. The results find application in the design of the solvent-based bitumen recovery processes.

RNA in Municipal Wastewater Reveals Magnitudes of COVID-19 Outbreaks across Four Waves Driven by SARS-CoV-2 Variants of Concern

There are no standardized protocols for quantifying severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater to date, especially for population normalization. Here, a pipeline was developed, applied, and assessed to quantify SARS-CoV-2 and key variants of concern (VOCs) RNA in wastewater at Saskatoon, Canada. Normalization approaches using recovery ratio and extraction efficiency, wastewater parameters, or population indicators were assessed by comparing to daily numbers of new cases. Viral load was positively correlated with daily new cases reported in the sewershed. Wastewater surveillance (WS) had a lead time of approximately 7 days, which indicated surges in the number of new cases. WS revealed the variant α and δ driving the third and fourth wave, respectively. The adjustment with the recovery ratio and extraction efficiency improved the correlation between viral load and daily new cases. Normalization of viral concentration to concentrations of the artificial sweetener acesulfame K improved the trend of viral load during the Christmas and New Year holidays when populations were dynamic and variable. Acesulfame K performed better than pepper mild mottle virus, creatinine, and ammonia for population normalization. Hence, quality controls to characterize recovery ratios and extraction efficiencies and population normalization with acesulfame are promising for precise WS programs supporting decision-making in public health.

Rapid transition between SARS-CoV-2 variants of concern Delta and Omicron detected by monitoring municipal wastewater from three Canadian cities

Monitoring the communal incidence of COVID-19 is important for both government and residents of an area to make informed decisions. However, continuous reliance on one means of monitoring might not be accurate because of biases introduced by government policies or behaviours of residents. Wastewater surveillance was employed to monitor concentrations of SARS-CoV-2 RNA in raw influent wastewater from wastewater treatment plants serving three Canadian Prairie cities with different population sizes. Data obtained from wastewater are not directly influenced by government regulations or behaviours of individuals. The means of three weekly samples collected using 24 h composite auto-samplers were determined. Viral loads were determined by RT-qPCR, and whole-genome sequencing was used to charaterize variants of concern (VOC). The dominant VOCs in the three cities were the same but with different proportions of sub-lineages. Sub-lineages of Delta were AY.12, AY.25, AY.27 and AY.93 in 2021, while the major sub-lineage of Omicron was BA.1 in January 2022, and BA.2 subsequently became a trace-level sub-variant then the predominant VOC. When each VOC was first detected varied among cities; However, Saskatoon, with the largest population, was always the first to present new VOCs. Viral loads varied among cities, but there was no direct correlation with population size, possibly because of differences in flow regimes. Population is one of the factors that affects trends in onset and development of local outbreaks during the pandemic. This might be due to demography or the fact that larger populations had greater potential for inter- and intra-country migration. Hence, wastewater surveillance data from larger cities can typically be used to indicate what to expect in smaller communities.

Fast and Effective Deactivation of Human Coronavirus with Copper Oxide Suspensions

The COVID-19 pandemic has demonstrated the need for versatile and robust countermeasures against viral threats. A wide range of viruses, including SARS-CoV-2, the virus that causes COVID-19, can be deactivated by metal and metal-oxide surface coatings. However, such coatings are expensive and cannot easily be retrofitted to existing infrastructure. Low-cost materials to halt the propagation of a variety of viruses must be produced with minimal quantities of expensive precursors. In this regard, we show that commercially available copper oxide nanoparticle suspensions can deactivate more than 99.55% of the human coronavirus 229E in 30 min, confirming the particles' efficiency as a fast antiviral material.

Early Warning Measurement of SARS-CoV-2 Variants of Concern in Wastewaters by Mass Spectrometry

Wastewater surveillance has rapidly emerged as an early warning tool to track COVID-19. However, the early warning measurement of new SARS-CoV-2 variants of concern (VOCs) in wastewaters remains a major challenge. We herein report a rapid analytical strategy for quantitative measurement of VOCs, which couples nested polymerase chain reaction and liquid chromatography-mass spectrometry (nPCR-LC-MS). This method showed a greater selectivity than the current allele-specific quantitative PCR (AS-qPCR) for tracking new VOC and allowed the detection of multiple signature mutations in a single measurement. By measuring the Omicron variant in wastewaters across nine Ontario wastewater treatment plants serving over a three million population, the nPCR-LC-MS method demonstrated a better quantification accuracy than next-generation sequencing (NGS), particularly at the early stage of community spreading of Omicron. This work addresses a major challenge for current SARS-CoV-2 wastewater surveillance by rapidly and accurately measuring VOCs in wastewaters for early warning.

Evaluation and modelling of methane production from corn stover pretreated with various physicochemical techniques

Lignocellulosic by-products from agricultural crops represent an important raw material for anaerobic digestion and clean renewable, which is a key component of the circular economy. Lignocellulose is recalcitrant to biodegradation and pretreatments are required to increase methane yield during anaerobic digestion. In this work, the efficacy of different physicochemical pretreatments was compared using corn stover biomass as substrate. Anaerobic digestion of untreated and pretreated corn stover was performed in batch mode at mesophilic temperature (38°C) and organic matter solubilization of pretreated substrates was also investigated. The highest organic matter solubilization occurred in autoclave pretreatment (soluble chemical oxygen demand = 5630 ± 42 mg O₂ L^-1). However, the highest methane yield was obtained using alkaline pretreatment (367 ± 35 mL CH₄ g^-1 VS_added). Alkaline pretreatment increased methane yield by 43.3% compared to untreated control (256 ± 15 mL CH₄ g^-1 VS_added). Two mathematical models (i.e. first-order kinetics and transfer function) were utilized to fit the experimental data with the aim of assessing anaerobic biodegradation and to obtain the kinetic constants in all cases studied. Both models adequately fit the experimental results. The kinetic constant, k, of the first-order model increased by 92.8% when stover was pretreated with sulphuric acid compared with control. The transfer function model revealed that the maximum methane production rate, R_m, was obtained for the sulphuric acid treatment, which was 63.5% higher compared to control.

RNA in Municipal Wastewater Reveals Magnitudes of COVID-19 Outbreaks across Four Waves Driven by SARS-CoV-2 Variants of Concern

There are no standardized protocols for quantifying severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater to date, especially for population normalization. Here, a pipeline was developed, applied, and assessed to quantify SARS-CoV-2 and key variants of concern (VOCs) RNA in wastewater at Saskatoon, Canada. Normalization approaches using recovery ratio and extraction efficiency, wastewater parameters, or population indicators were assessed by comparing to daily numbers of new cases. Viral load was positively correlated with daily new cases reported in the sewershed. Wastewater surveillance (WS) had a lead time of approximately 7 days, which indicated surges in the number of new cases. WS revealed the variant α and δ driving the third and fourth wave, respectively. The adjustment with the recovery ratio and extraction efficiency improved the correlation between viral load and daily new cases. Normalization of viral concentration to concentrations of the artificial sweetener acesulfame K improved the trend of viral load during the Christmas and New Year holidays when populations were dynamic and variable. Acesulfame K performed better than pepper mild mottle virus, creatinine, and ammonia for population normalization. Hence, quality controls to characterize recovery ratios and extraction efficiencies and population normalization with acesulfame are promising for precise WS programs supporting decision-making in public health.

Wastewater surveillance gave early warnings of four waves of COVID-19. Quality controls and normalization with acesulfame K significantly improved the accuracy of the wastewater-based epidemiology.

Why not both? Rethinking categorical and continuous approaches to bilingualism

AIMS AND OBJECTIVES

Bilingualism is a complex construct, and it can be difficult to define and model. This paper proposes that the field of bilingualism can draw from other fields of psychology, by integrating advanced psychometric models that incorporate both categorical and continuous properties. These models can unify the widespread use of bilingual and monolingual groups that exist in the literature with recent proposals that bilingualism should be viewed as a continuous variable.

APPROACH

In the paper, we highlight two models of potential interest: the factor mixture model and the grade-of-membership model. These models simultaneously allow for the formation of different categories of speakers and for continuous variation to exist within these categories. We discuss how these models could be implemented in bilingualism research, including how to develop these models. When using either of the two models, researchers can conduct their analyses on either the categorical or continuous information, or a combination of the two, depending on which is most appropriate to address their research question.

CONCLUSIONS

The field of bilingualism research could benefit from incorporating more complex models into definitions of bilingualism. To help various subfields of bilingualism research converge on appropriate models, we encourage researchers to pre-register their model selection and planned analyses, as well as to share their data and analysis scripts.

ORIGINALITY

The paper uniquely proposes the incorporation of advanced statistical psychometric methods for defining and modeling bilingualism.

SIGNIFICANCE

Conceptualizing bilingualism within the context of these more flexible models will allow a wide variety of research questions to be addressed. Ultimately, this will help to advance theory and lead to a fuller and deeper understanding of bilingualism.

Genetic Variability of the SARS-CoV-2 Pocketome

In the absence of effective treatment, COVID-19 is likely to remain a global disease burden. Compounding this threat is the near certainty that novel coronaviruses with pandemic potential will emerge in years to come. Pan-coronavirus drugs-agents active against both SARS-CoV-2 and other coronaviruses-would address both threats. A strategy to develop such broad-spectrum inhibitors is to pharmacologically target binding sites on SARS-CoV-2 proteins that are highly conserved in other known coronaviruses, the assumption being that any selective pressure to keep a site conserved across past viruses will apply to future ones. Here we systematically mapped druggable binding pockets on the experimental structure of 15 SARS-CoV-2 proteins and analyzed their variation across 27 α- and β-coronaviruses and across thousands of SARS-CoV-2 samples from COVID-19 patients. We find that the two most conserved druggable sites are a pocket overlapping the RNA binding site of the helicase nsp13 and the catalytic site of the RNA-dependent RNA polymerase nsp12, both components of the viral replication-transcription complex. We present the data on a public web portal (https://www.thesgc.org/SARSCoV2_pocketome/), where users can interactively navigate individual protein structures and view the genetic variability of drug-binding pockets in 3D.

Growth rates for freshwater ferromanganese concretions indicate regional climate change in eastern Canada at the Northgrippian-Meghalayan boundary

The existence of freshwater ferromanganese concretions has been known for decades, but we are not aware of a generally accepted explanation for their formation, and there has been little research into their potential use as records of Holocene climate and paleohydrology. A conceptual model is presented to describe the environmental and geochemical processes which result in the formation and growth of freshwater ferromanganese concretions. In order to evaluate their potential as historical geochemical records, a concretion from Magaguadavic Lake, New Brunswick, Canada is the focus of a detailed geochronological and geochemical investigation. The radiocarbon data provide a coherent growth curve and a maximum age for the concretion of 8448 ± 43 years, consistent with the establishment of Magaguadavic Lake as a stable post-glacial lacustrine system. The data suggest accretion rates of 1.5 and 3.4 mm per 1000 years during the Northgrippian and Meghalayan stages of the Holocene, respectively. The abrupt change in growth rate observed at the stage boundary may be an indicator of Holocene climate change. These features are consistent with inferences from previous research that warmer climate in the Northgrippian led to eutrophication in some lakes in eastern North America. The results confirm that freshwater Fe-Mn concretions may yield important information about past climatic and environmental conditions.

Prefrontal-hippocampal interaction during the encoding of new memories

The hippocampus rapidly forms associations among ongoing events as they unfold and later instructs the gradual stabilisation of their memory traces in the neocortex. Although this two-stage model of memory consolidation has gained substantial empirical support, parallel evidence from rodent studies suggests that the neocortex, in particular the medial prefrontal cortex, might work in concert with the hippocampus during the encoding of new experiences. This opinion article first summarises findings from behavioural, electrophysiological, and molecular studies in rodents that uncovered immediate changes in synaptic connectivity and neural selectivity in the medial prefrontal cortex during and shortly after novel experiences. Based on these findings, I then propose a model positing that the medial prefrontal cortex and hippocampus might use different strategies to encode information during novel experiences, leading to the parallel formation of complementary memory traces in the two regions. The hippocampus captures moment-to-moment changes in incoming inputs with accurate spatial and temporal contexts, whereas the medial prefrontal cortex may sort the inputs based on their similarity and integrates them over time. These processes of pattern recognition and integration enable the medial prefrontal cortex to, in real time, capture the central content of novel experience and emit relevancy signal that helps to enhance the contrast between the relevant and incidental features of the experience. This hypothesis serves as a framework for future investigations on the potential top-down modulation that the medial prefrontal cortex may exert over the hippocampus to enable the selective, perhaps more intelligent encoding of new information.