Low adsorption affinity of athabasca oil sands naphthenic acid fraction compounds to a peat-mineral mixture.

Much of the toxicity in oil sands process-affected water in Athabasca oil sands tailings has been attributed to naphthenic acids (NAs) and associated naphthenic acid fraction compounds (NAFCs). Previous work has characterized the environmental behaviour and fate of these compounds, particularly in the context of constructed treatment wetlands. There is evidence that wetlands can attenuate NAFCs in natural and engineered contexts, but relative contributions of chemical, biotic, and physical adsorption with sequestration require deconvolution. In this work, the objective was to evaluate the extent to which prospective wetland substrate material may adsorb NAFCs using a peat-mineral mix (PMM) sourced from the Athabasca Oil Sands Region (AOSR). The PMM and NAFCs were first mixed and then equilibrated across a range of NAFC concentrations (5-500 mg/L) with moderate ionic strength and hardness (∼200 ppm combined Ca2+ and Mg2+) that approximate wetland water chemistry. Under these experimental conditions, low sorption of NAFCs to PMM was observed, where sorbed concentrations of NAFCs were approximately zero mg/kg at equilibrium. When NAFCs and PMM were mixed and equilibrated together at environmentally relevant concentrations, formula diversity increased more than could be explained by combining constituent spectra. The TOC present in this PMM was largely cellulose-derived, with low levels of thermally recalcitrant carbon (e.g., lignin, black carbon). The apparent enhancement of the concentration and diversity of components in PMM/NAFCs mixtures are likely related to aqueous solubility of some PMM-derived organic materials, as post-hoc combination of dissolved components from PMM and NAFCs cannot replicate enhanced complexity observed when the two components are agitated and equilibrated together.

Solid-liquid distribution of SARS-CoV-2 in primary effluent of a wastewater treatment plant.

Distributions of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and fecal viral biomarkers between solid and liquid phases of wastewater are largely unknown. Herein, distributions of SARS-CoV-2, Pepper Mild Mottle Virus (PMMoV), and F-RNA bacteriophage group II (FRNAPH-II) were determined by viral RNA RT-qPCR. Comparison of viral recovery using three conventional fractionation methods included membrane filtration, a combination of mid-speed centrifugation and membrane filtration, and high-speed centrifugation. SARS-CoV-2 partitioned to the solids fraction in greater abundance compared to liquid fractions in a combination of mid-speed centrifugation and membrane filtration and high-speed centrifugation, but not in membrane filtration method in a particular assay, while fecal biomarkers (PMMoV and FRNAPH-II) exhibited the reciprocal relationship. The wastewater fractionation method had minimal effects on the solids-liquids distribution for all viral and phage markers tested; however, viral RNA load was significantly greater in solid-liquid fractions viral RNA loads compared with the than whole-wastewater PEG precipitation. A RNeasy PowerWater Kit with PCR inhibitor removal resulted in greater viral RNA loads and lesser PCR inhibition compared to a QIAamp Viral RNA Mini Kit without PCR inhibitor removal. These results support the development of improved methods and interpretation of WBE of SARS-CoV-2. •Distribution of SARS-CoV-2 to liquid and solid portions was addressed.•Addressing PCR inhibition is important in wastewater-based epidemiology.•Fraction methods have minimal effect.

Review: Plant microRNAs in pathogen defense: A panacea or a piece of the puzzle?

Plant microRNAs (miRNAs) control key agronomic traits that are associated with their conserved role(s) in development. However, despite a multitude of studies, the utility of miRNAs in plant-pathogen resistance remains less certain. Reviewing the literature identifies three general classes of miRNAs regarding plant pathogen defense. Firstly, a number of evolutionary dynamic 22 nucleotide miRNA families that repress large numbers of plant immunity genes, either directly, or through triggering the biogenesis of secondary siRNAs. However, understanding of their role in defense and of their manipulation to enhance pathogen resistance are still lacking. Secondly, highly conserved miRNAs that indirectly impact disease resistance through their targets that are primarily regulating development or hormone signaling. Any alteration of these miRNAs usually results in pleiotropic impacts, which may alter disease resistance in some plant species, and against some pathogens. Thirdly, are the comparatively diverse and evolutionary dynamic set of non-conserved miRNAs, some of which contribute to pathogen resistance, but whose narrow evolutionary presence will likely restrict their utility. Therefore, reflecting the diverse and evolving nature of plant-pathogen interactions, a complex interplay of plant miRNAs with pathogen responses exists. Any miRNA-based solution for pathogen resistance will likely be highly specific, rather than a general panacea.

Emergence and spread of SARS-CoV-2 variants of concern in Canada: a retrospective analysis from clinical and wastewater data.

BACKGROUND: The spread of SARS-CoV-2 has been studied at unprecedented levels worldwide. In jurisdictions where molecular analysis was performed on large scales, the emergence and competition of numerous SARS-CoV-2lineages have been observed in near real-time. Lineage identification, traditionally performed from clinical samples, can also be determined by sampling wastewater from sewersheds serving populations of interest. Variants of concern (VOCs) and SARS-CoV-2 lineages associated with increased transmissibility and/or severity are of particular interest. METHOD: Here, we consider clinical and wastewater data sources to assess the emergence and spread of VOCs in Canada retrospectively. RESULTS: We show that, overall, wastewater-based VOC identification provides similar insights to the surveillance based on clinical samples. Based on clinical data, we observed synchrony in VOC introduction as well as similar emergence speeds across most Canadian provinces despite the large geographical size of the country and differences in provincial public health measures. CONCLUSION: In particular, it took approximately four months for VOC Alpha and Delta to contribute to half of the incidence. In contrast, VOC Omicron achieved the same contribution in less than one month. This study provides significant benchmarks to enhance planning for future VOCs, and to some extent for future pandemics caused by other pathogens, by quantifying the rate of SARS-CoV-2 VOCs invasion in Canada.

Assessment of rapid wastewater surveillance for determination of communicable disease spread in municipalities.

Wastewater surveillance (WS) helps to improve the understanding of the spread of communicable diseases in communities. WS can assist public health decision-makers in the design and implementation of timely mitigation measures. There is an increased need to use reliable, cost-effective, simple, and rapid WS systems, given traditional analytical (or 'gold-standard') programs are instrument/time-intensive, and dependent on highly skilled personnel. This study investigated the application of the portable GeneXpert platform for WS of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A virus (IAV), influenza B virus (IBV), and respiratory syncytial virus (RSV). The GeneXpert system with the Xpert Xpress-SARS-CoV-2/Flu/RSV test kit uses reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to analyze wastewater samples. From September 2022 through January 2023, wastewater samples were collected from the influents of municipal wastewater treatment plants (MWTPs) of Saskatoon, Prince Albert, and North Battleford in the province of Saskatchewan, Canada. Both raw and concentrated wastewater samples were subjected to the GeneXpert analysis. Results showed that the Saskatoon wastewater viral loads were significantly correlated to Saskatchewan's influenza and COVID-19 clinical cases, with a lead time of 10 days for IAV and a lag time of 4 days for SARS-CoV-2. Additionally, the GeneXpert analysis of the three cities' wastewater samples showed that the raw WS could capture the dynamics of SARS-CoV-2 and IAV due to their correlation with concentrated WS. Interestingly, IBV loads were not detected in any wastewater samples, while the Saskatoon and Prince Albert wastewater samples collected following the 2023 holiday season (end of December and beginning of January) were positive for RSV. This study indicates that the GeneXpert has excellent potential for use in the development of an early warning system for transmissible disease in municipalities and limited-resource communities while simultaneously providing stakeholders with an efficient WS methodology.

A wastewater-based risk index for SARS-CoV-2 infections among three cities on the Canadian Prairie.

Wastewater surveillance (WWS) is useful to better understand the spreading of coronavirus disease 2019 (COVID-19) in communities, which can help design and implement suitable mitigation measures. The main objective of this study was to develop the Wastewater Viral Load Risk Index (WWVLRI) for three Saskatchewan cities to offer a simple metric to interpret WWS. The index was developed by considering relationships between reproduction number, clinical data, daily per capita concentrations of virus particles in wastewater, and weekly viral load change rate. Trends of daily per capita concentrations of SARS-CoV-2 in wastewater for Saskatoon, Prince Albert, and North Battleford were similar during the pandemic, suggesting that per capita viral load can be useful to quantitatively compare wastewater signals among cities and develop an effective and comprehensible WWVLRI. The effective reproduction number (Rt) and the daily per capita efficiency adjusted viral load thresholds of 85 × 106 and 200 × 106 N2 gene counts (gc)/population day (pd) were determined. These values with rates of change were used to categorize the potential for COVID-19 outbreaks and subsequent declines. The weekly average was considered 'low risk' when the per capita viral load was 85 × 106 N2 gc/pd. A 'medium risk' occurs when the per capita copies were between 85 × 106 and 200 × 106 N2 gc/pd. with a rate of change <100 %. The start of an outbreak is indicated by a 'medium-high' risk classification when the week-over-week rate of change was >100 %, and the absolute magnitude of concentrations of viral particles was >85 × 106 N2 gc/pd. Lastly, a 'high risk' occurs when the viral load exceeds 200 × 106 N2 gc/pd. This methodology provides a valuable resource for decision-makers and health authorities, specifically given the limitation of COVID-19 surveillance based on clinical data.

Efficacy of drug regimen with and without oseltamivir in hospitalized patients with COVID-19: A retrospective study.

Introduction: Coronavirus disease 2019 (COVID-19) is the most critical issue in nowadays medicine. We aimed to evaluate the use and therapeutic outcomes of oseltamivir, an antiviral drug for patients with COVID-19. Materials and method: In an observational study conducted at Imam Khomeini Hospital in Amol, Iran, data for 544 patients with laboratory and CT scan result confirmed COVID-19 were retrospectively collected between February 24th and April 13th 2020. To compare the characteristics of patients based on gender, the chi-square test was used. Logistic regression was used to evaluate the effect of oseltamivir on the outcome of treatment. Logrank test were used to compare the length of hospital stay in people treated with oseltamivir and drugs other than oseltamivir. Results: Kaplan-Meier and logrank test showed no significant reduction in hospitalization time and survival rate following treatment with oseltamivir. However, a significant increase in lymphocytes count and reduction of C-reactive protein (CRP) level detected. Conclusion: Administration of oseltamivir for patients with COVID-19 didn't show any improvement in hospitalization duration and survival rate.

Introducción: la enfermedad por coronavirus 2019 (COVID-19) es el tema más crítico en la medicina actual. Nuestro objetivo fue evaluar el uso y los resultados terapéuticos de oseltamivir, un medicamento antiviral para pacientes con COVID-19. Materiales y método: en un estudio observacional realizado en el Hospital Imam Khomeini en Amol, Irán, los datos de 544 pacientes con resultados de laboratorio y tomografía computarizada confirmados de COVID-19 se recopilaron retrospectivamente entre el 24 de febrero y el 13 de abril de 2020. Para comparar las características de los pacientes en función del género se utilizó la prueba de chi-cuadrado. Se utilizó regresión logística para evaluar el efecto de oseltamivir en el resultado del tratamiento. Se utilizó la prueba de rango logarítmico para comparar la duración de la estancia hospitalaria en personas tratadas con oseltamivir y otros fármacos distintos del oseltamivir. Resultados: Kaplan­Meier y la prueba de rango logarítmico no mostraron una reducción significativa en el tiempo de hospitalización y la tasa de supervivencia después del tratamiento con oseltamivir. Sin embargo, se detectó un aumento significativo en el recuento de linfocitos y una reducción del nivel de proteína C reactiva (PCR). Conclusión: la administración de oseltamivir para pacientes con COVID-19 no mostró ninguna mejora en la duración de la hospitalización y la tasa de supervivencia.

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.

Optimization and assessment of an electrochemical advanced oxidation system for synthetic stormwater treatment.

Electrochemical advanced oxidation processes (eAOPs) such as the current advanced oxidation system (AOS) are a type of electrochemical wastewater treatment that creates oxidative species, such as iodide species, chloride species, and hydroxyl radicals, that can treat even the most recalcitrant contaminants. It is important to determine the concentrations and locations of oxidative species in eAOPs for optimization of the wastewater treatment process. In this study, a spectrophotometric methodology was used to determine concentrations of iodide and chloride oxidative species (starting at 10, 25, and 50 ppm) within an AOS under various input voltages (6, 12, and 24 V). Overall, it was found that iodate and chlorite were the dominant species created in their respective treatments. Additionally, the concentration of iodide oxidative species increased with increasing voltage, whereas the chloride species decreased with increasing voltage. The optimal conditions for the efficient creation of AOS oxidative species were 12 V and 10 ppm potassium iodide and 6 V and 10 ppm sodium chloride, respectively. In addition, the use of iodide is recommended for wastewater treatment using the AOS to effectively create oxidative species. Following optimization, the AOS performance was tested for synthetic stormwater. Results indicated that the AOS performed well for reduction of Escherichia coli; however, reduction of other contaminants was inconsistent as would be expected given the AOS was optimized for disinfection, not decontamination. Further AOS optimization for decontamination would be expected to result in improved decontamination performance.

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.

Greenhouse gas emission estimation from municipal wastewater using a hybrid approach of generative adversarial network and data-driven modelling.

Greenhouse gas (GHG) emissions including carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) created via wastewater treatment processes are not easily modeled given the non-linearity and complexity of biological processes. These factors are also impacted by limited data availability making the development of artificial data generation algorithms, such as a generative adversarial network (GAN), useful for determination of GHG emission rate estimates (EREs). The main objective of this study was to develop a hybrid approach of using GAN and regression modelling to determine GHG EREs from a cold-region biological nutrient removal (BNR) municipal wastewater treatment plant (MWTP) in which the aerobic reactor has previously been established as the main GHG emission source. To our knowledge, this is the first application of GAN used for MWTP modelling purposes. The EREs were generated from laboratory-scale reactors used in conjunction with facility-monitored operating parameters to develop the GAN and regression models. Results showed that regression models provided reasonable EREs using parameters including hydraulic retention time (HRT), temperature, total organic carbon, and dissolved oxygen (DO) concentrations for CO2 EREs; HRT, temperature, DO and phosphate (PO43-) concentrations for CH4 EREs; and temperature, DO, and nitrogen (nitrite, nitrate, and ammonium) concentrations for N2O EREs. Additionally, the addition of 100 GAN-created virtual data points improved regression model metrics including increased correlation coefficient and index agreement values, and decreased root mean square error values. Clearly, virtual data augmentation using GAN is a valuable resource in supplementation of limited data for improved modelling outcomes. Genetic algorithm optimization was also used to determine operating parameter modifications resulting in potential for minimization (or maximization) of GHG emissions.

Biogas maximization using data-driven modelling with uncertainty analysis and genetic algorithm for municipal wastewater anaerobic digestion.

Anaerobic digestion processes create biogases that can be useful sources of energy. The development of data-driven models of anaerobic digestion processes via operating parameters can lead to increased biogas production rates, resulting in greater energy production, through process modification and optimization. This study assessed processed and unprocessed input operating parameter variables for the development of regression models with transparent structures ('white-box' models) to: (1) estimate biogas production rates from municipal wastewater treatment plant (MWTP) anaerobic digestors; (2) compare their performances to artificial neural network (ANN) and adaptive network-based fuzzy inference system (ANFIS) models with opaque structures ('black-box' models) using Monte Carlo Simulation for uncertainty analysis; and (3) integrate the models with a genetic algorithm (GA) to optimize operating parameters for maximization of MWTP biogas production rates. The input variables were anaerobic digestion operating parameters from a MWTP including volatile fatty acids, total/fixed/volatile solids, pH, and inflow rate, which were processed via correlation tests and principal component analysis. Overall, the results indicated that the processed data did not improve regression model performances. Additionally, the developed non-linear regression model with the unprocessed inputs had the best performance based on values including R = 0.81, RMSE = 0.95, and IA = 0.89. However, this model was less accurate, but interestingly had less uncertainty, as compared to ANN and ANFIS models which indicates the compromise between model accuracy and uncertainty. Thus, all three models were coupled with GA optimization with maximum biogas production rate estimates of 22.0, 23.1, and 28.6 m3/min for ANN, ANFIS, and non-linear regression models, respectively.

Estimation of greenhouse gas and odour emissions from a cold region municipal biological nutrient removal wastewater treatment plant.

Seasonal temperature variations in cold regions worldwide lead to variable gas emissions from municipal wastewater treatment plants (MWTPs) due to changing wastewater temperatures in open-to-air treatment processes. The objective of this study was to determine the greenhouse gas (including carbon dioxide, CO2; methane, CH4; and nitrous oxide, N2O) and odour (including ammonia, NH3; and hydrogen sulphide, H2S) emission rate estimates (EREs) from the open-to-air processes of a biological nutrient removal (BNR) type MWTP in Saskatoon, SK, Canada. This MWTP experiences seasonal temperatures from -40 °C to 30 °C with the resultant wastewater temperatures considered herein of 13 °C and 17 °C being chosen based on monitoring data for winter and summer, respectively. Laboratory-scale reactors simulating anaerobic, anoxic, aerobic, and settling treatment processes were used to monitor gas EREs using wastewater samples taken from the analogous MWTP processes during the winter and summer seasons. Results indicated that the overall winter EREs for CO2, CH4, and N2O were 45,129 kg CO2/d, 21.9 kg CH4/d, and 3.20 kg N2O/d, respectively, while the H2S EREs were insignificant. The higher temperature for the summer samples resulted in increased EREs for CH4, N2O, and H2S EREs of 33.0 kg CH4/d, 3.87 kg N2O/d, and 2.29 kg H2S/d, respectively. However, the CO2 EREs were reduced to 37,794 kg CO2/d. Overall, the aerobic reactor was the dominant source of the GHG emissions for both seasons. In addition, studied changes in the aerobic reactor aeration rates (in reactor) and BNR treatment configurations (from site) further impacted the EREs.

Biogas production estimation using data-driven approaches for cold region municipal wastewater anaerobic digestion.

The objective of this study was to estimate biogas (including methane, carbon dioxide and hydrogen sulphide) production rates from the anaerobic digesters at the Saskatoon Wastewater Treatment Plant (SWTP), Saskatchewan, Canada. Average daily ambient temperatures typically fluctuate between -40 °C and 30 °C over the year making the management of the SWTP processes challenging. Operating parameters were taken from 2014 to 2016 including volatile fatty acids (VFAs), total solids, fixed solids, volatile solids, pH, and inflow rate. The input parameters were processed using two methods including a correlation test and principal component analysis (PCA) to determine highly correlated variables prior to use in models. The two models used to estimate biogas production rates are a multi-layered perceptron feed forward artificial neural network (ANN) and an adaptive network-based fuzzy inference system (ANFIS) with grid partition (GP), subtractive clustering (SC) and fuzzy c-means clustering (FCMC). The models using PCA processed variables had reasonable performances with shorter model processing times, while reducing model input data. Among various structures of ANN and ANFIS models for estimation of biogas generation, the ANFIS-FCMC results had better agreement with the observed data. Its average approximation of emission rates of CH4, CO2 and H2S from the wastewater digesters were 3,086, 6,351, and 41.5 g/min, respectively. Our group is assessing similar estimation methodology for the remaining SWTP wastewater treatment processes that are more highly impacted by the seasonal temperature variations including primary and secondary treatment processes.

Burn scar reconstruction of the neck with FTSG obtained from lower abdominal skin.

Burns account for a significant proportion of injuries, and of these the face, neck, and anterior torso are commonly affected. Burn scars remain a lasting reminder of the insult both for the patient and the outside world. There is little doubt that the change in appearance and the limitation imposed by a burn scar contribute to negative body image. Treatment of hypertrophic scars in the neck has been quite challenging if there is no intact tissue for local flaps. So application of full-thickness skin grafts could be of great value. We applied full-thickness grafts obtained from lower abdominal skin for treatment of severe neck contractures in four patients when other treatment modalities such as local flaps could not be used. Full-thickness skin graft of the neck is a safe and reliable treatment option with fairly good functional and aesthetic results. It has little donor site morbidity in spite of providing a large surface area of full-thickness skin.

Razi's description and treatment of facial paralysis.

In the modern medical era, facial paralysis is linked with the name of Charles Bell. This disease, which is usually unilateral and is a peripheral facial palsy, causes facial muscle weakness in the affected side. Bell gave a complete description of the disease; but historically other physicians had described it several hundred years prior although it had been ignored for different reasons, such as the difficulty of the original text language. The first and the most famous of these physicians who described this disease was Mohammad Ibn Zakaryya Razi (Rhazes). In this article, we discuss his opinion.