Point-of-care tests (POCTs) offer considerable potential for improving clinical and public health management of COVID-19 by providing timely information to guide decision-making, but data on real-world performance are in short supply. Besides SARS-CoV2-specific tests, there is growing interest in the role of surrogate (non-specific) tests such as FebriDx, a biochemical POCT which can be used to distinguish viral from bacterial infection in patients with influenza-like illnesses. This short communication assesses what is currently known about FebriDx performance across settings and populations by comparison with some of the more intensively evaluated SARS-CoV2-specific POCTs. While FebriDx shows some potential in supporting triage for early-stage infection in acute care settings, this is dependent on SARS-CoV2 being the most likely cause for influenza-like illnesses, with reduction in discriminatory power when COVID-19 case numbers are low, and when co-circulating viral respiratory infections become more prevalent during the autumn and winter. Too little is currently known about its performance in primary care and the community to support use in these contexts and further evaluation is needed. Reliable SARS CoV2-specific POCTs – when they become available – are likely to rapidly overtake surrogates as the preferred option given the greater specificity they provide.

The Special Issue brought together papers that highlighted the power of high-throughput sequencing (HTS) data to address classic questions in ecology and evolution, and/or use models/theory to infer key ecological and evolutionary processes, and make predictions, particularly focused on metabarcoding (amplicon) datasets in conjunction with complementary -omics data types. We highlight key papers that show the power of the new technology to address questions related to: (1) community assembly, and the interplay between competition, environmental filtering, and neutral processes, that can be inferred from the data, and how these change according to environmental conditions, and across successional and extended evolutionary time. (2) Interaction networks, and how these can show predictable changes over similar spatial and temporal gradients, providing insights into questions of biotic resilience. Studies also examined (3) cross scale interactions and those involving hosts and their microbiomes, with the critical development being the ease of comparison and integration across scales of organismic complexity, allowing insights at one scale to inform the other. The approach is also amenable to (4) studies of invasive species and biotic homogenization, providing insights of shifts in alpha and beta diversity across a wide range of spatial scales.

Background: Cerebral Sinus Venous Thrombosis (CSVT) is one of many side effects encountered during acute lymphoblastic leukemia (ALL) therapy. Due to the rarity of cases, lack of data, consensus management, no recommendations exist to target the population at risk. Methods: This is a retrospective chart review of 229 consecutive patients diagnosed with ALL and aged 1–21 years, treated at the Children’s Cancer Institute (CCI) between October 2007 and February 2017. Results: The incidence of CSVT was 10.5%. Using univariate analysis, increased risk of CSVT was observed with male gender, age >10 years, T-cell immunophenotype, intermediate/high risk disease, maximum Triglyceride (TG) level of > 615 mg/dL, presence of mediastinal mass, and larger body surface area. With multivariate analysis, the only statistically significant risk factors were maximum TG level, body surface area (BSA), presence of mediastinal mass, and risk stratification (intermediate/high risk). Conclusion: Our study was able to unveil TG level of > 615 mg/dL, mediastinal mass, and a larger body surface area as novel risk factors that have not been previously discussed in the literature.

This study aimed to compare the infection dynamics of three genotype II African swine fever viruses (ASFV) circulating in Europe. Eighteen domestic pigs divided into three groups were infected intramuscularly or by direct contact with two haemadsorbent ASFVs (HAD) from Poland (Pol16/DP/ OUT21) and Estonia (Est16/WB/Viru8), and with the Latvian non-HAD ASFV (Lv17/WB/Rie1). Parameters such as symptoms, pathogenicity, and distribution of the virus in tissues, humoral immune response, and dissemination of the virus by blood, oropharyngeal and rectal routes were investigated. The Polish ASFV caused a case of rapidly developing fatal acute disease, while the Estonian ASFV caused acute to subacute infections in the presence of surviving animals. In contrast, animals infected with the ASFV from Latvia developed a more subtle, mild, or even subclinical disease. Oral excretion was sporadic or even absent in the attenuated group, whereas in animals that developed an acute or subacute form of ASF, oral excretion began at the same time as in the blood, or even 3 days earlier, and persisted up to 22 days. Regardless of virulence, blood was the main route of transmission of ASFV and infectious virus was isolated from persistently infected animals for at least 19 days in the attenuated group and up to 44 days in the group of moderate virulence. Rectal excretion was limited to the acute phase of infection. In terms of diagnostics, the ASFV genome was detected in contact pigs from oropharyngeal samples earlier than in blood, independently of virulence and, together with blood, both samples could cover a longer range to detect ASFV infection. The results presented here provide quantitative data on the spread and excretion of ASFV strains of different virulence among domestic pigs that can help to better focus surveillance activities and thus increase the ability to detect ASF introductions earlier.

Background and Purpose: ISX9 is a neurogenesis-promoting small molecule compound which can upregulate the expression of NeuroD1 and induce differentiation of neuronal, cardiac and islet endocrine progenitors. So far, the molecular mechanisms underlying the action of ISX9 still remain elusive. Experimental Approach: To identify a novel agonist of the Wnt/β‐catenin, a cell-based SuperTOPFlash reporter system was used to screen known-compound libraries. An activation effect of ISX9 on the Wnt/β‐catenin pathway was analysed with the SuperTOPFlash or SuperFOPFlash reporter system. Effects of ISX9 on Axin1/LRP6 interaction were examined using a mammalian two-hybrid system, co‐immunoprecipitation, microscale thermophoresis (MST), emission spectra and mass spectroscopy assays. The expression of Wnt target and stemmness marker genes were evaluated with real‐time PCR and immunoblotting. In vivo hair regeneration abilities of ISX9 were analysed by immunohistochemical staining, real‐time PCR and immunoblotting in hair regrowth model using C57BL/6J mice. Key Results: In this study, ISX9 was identified as a novel agonist of the Wnt/β‐catenin pathway. ISX9 targeted Axin1 by covalently binding to its N-terminal region and potentiated the LRP6-Axin1 interaction, thereby resulting in the stabilization of β‐catenin and upregulation of Wnt target genes and stemmness marker genes. Moreover, the topical application of ISX9 markedly promoted hair regrowth in C57BL/6J mice and induced hair follicle transition from telogen to anagen via enhancing Wnt/β‐catenin pathway. Conclusions and Implications: Taken together, our study unraveled that ISX9 could activate Wnt/β‐catenin signaling by potentiating the association between LRP6 and Axin1, and may be a promising therapeutic agent for alopecia treatment

This commentary discusses a framework for the benchmarking of hydrological models for different purposes when the datasets for different catchments might involve epistemic uncertainties. The approach might be expected to result in an ensemble of models that might be used in prediction (including models of different types) but also provides for model rejection to be the start of a learning process to improve understanding.

Understanding landscape connectivity has become a global priority for mitigating the impact of landscape fragmentation on biodiversity. Link-based methods traditionally rely on relating pairwise genetic distance between individuals or demes to their landscape distance (e.g., geographic distance, cost distance). In this study, we present an alternative to conventional statistical approaches to refine cost surfaces by adapting the Gradient Forest (GF) approach to produce a resistance surface. Used in community ecology, GF is an extension of random forest (RF), and has been implemented in genomic studies to model species genetic offset under future climatic scenarios. By design, this adapted method, resGF, has the ability to handle multiple environmental predicators and is not subjected to traditional assumptions of linear models such as independence, normality and linearity. Using genetic simulations, resGF performance was compared to other published methods. In univariate scenarios, resGF was able to distinguish the true surface contributing to genetic diversity among competing surfaces better than the compared methods. In multivariate scenarios, the GF approach performed similarly to the other RF-based approach using least-cost transect analysis (LCTA). Additionally, two worked examples are provided using two previously published datasets. This machine learning algorithm has the potential to improve our understanding of landscape connectivity and can inform long-term biodiversity conservation strategies.

Lipomatous hypertrophy of the interatrial septum (LHIAS) is a benign cardiac tumor. Differential diagnosis of LHIAS consists of atrial masses such as myxomas or lipomas. Herein, we report a 66-year-old male, admitted as a case of severe COVID-19 and was found to have a LHIAS extending to the crista terminalis.

There is ample evidence that macroscopic animals form geographic clusters termed as zoogeographic realms (zones), whereas distributions of species of microscopic animals are still poorly understood. The common view has been that micrometazoans, thanks to their putatively excellent dispersal abilities, are subject to the ‘Everything is Everywhere but environment selects’ hypothesis (EiE). One of such groups, <1 mm in length, are limnoterrestrial water bears (Tardigrada), which can additionally enter cryptobiosis that should further enhance their potential for long distance dispersion (e.g. by wind). However, an increasing number of studies, including the most recent phylogeny of a eutardigrade genus Milnesium, seem to question the general applicability of the EiE hypothesis to tardigrade species. Nevertheless, all the Milnesium phylogenies published to date were based on a limited number of populations, which are likely to falsely suggest limited geographic ranges. Thus, in order to comprehensively test the EiE hypothesis, here, we considerably enlarged the Milnesium dataset both taxonomically and geographically, and we analysed it in tandem with climate type and reproductive mode. Additionally, we time-calibrated our phylogeny to align it with major geological events. Our results show that, although cases of long distance dispersal are present, they seem to be rare and mostly ancient. Overall, Milnesium species are restricted to single zoogeographic realms, which suggests that these tardigrades have limited dispersal abilities. Finally, our results also suggest that the breakdown of Gondwana may influenced the evolutionary history of Milnesium. In conclusion, phylogenetic relationships within the genus seem to be determined mainly by paleogeography.

The demand for electricity is increasing all over the world. In Bangladesh, there are many rural areas where the grid connection has not reached yet. In this paper, a performance evaluation was done with a solar-wind hybrid renewable energy system with diesel backup for a school located in a remote area, Baje Fulchari village in Gaibandha district, Bangladesh. For the proposed site, the load demand was considered 10.468 kWh/day for a normal working day (taken from a field survey) having peak demand of 3.3 kW. HOMER software was used for the simulation. The solar radiation and wind speed data were collected from NASA Surface meteorology and Solar Energy database. The NPC for the most economical system configuration is found USD 6,191 with a COE of 0.125 $/ kWh. Compared to the conventional power plants the proposed system can reduce the COE and GHG emission of about 29.85% and 69% respectively. The system evaluated in this work might be implemented in a school or any other location of similar load profile anywhere in the world having the same geographical and meteorological conditions.

Environmental DNA is an effective tool for describing fish biodiversity in lotic environments, but the downstream transport of eDNA released by organisms makes it difficult to interpret species detection at the local scale. In addition to biophysical degradation and exchanges at the water-sediment interface, hydrological conditions control the transport distance. We have developed an eDNA transport model that considers downstream retention and degradation processes in combination with hydraulic conditions and assumes that the sedimentation rate of very fine particles is a correct estimate of the eDNA deposition rate. Based on meta-analyses of available studies, we successively modelled the particle size distribution of fish eDNA (PSD), the relationship between the sedimentation rate and the size of very fine particles in suspension, and the influence of temperature on the degradation rate of fish eDNA. After combining the results in a mechanistic-based model, we correctly simulated the eDNA uptake distances observed in a compilation of previous experimental studies. eDNA degradation is negligible at low flow and temperature but has a comparable influence to background transfer when hydraulic conditions allow a long uptake distance. The wide prediction intervals associated with the simulations reflect the complexity of the processes acting on eDNA after shedding. This model can be useful for estimating eDNA detection distance downstream from a source point and discussing the possibility of false positive detection in eDNA samples, as shown in an example.

The incidence of mechanical complications of acute coronary syndromes (ACS) needing cardiac surgery has reduced significantly in the last years due to early diagnosis and treatments. Covid-19 pandemic, however, would generate in the patients a sense of fear regarding access to the ERs so they probably underestimate symptoms such as chest pain or angina equivalents until situation does not became critical. In this way, this behaviour could create a vast pool of patients who will enter the hospital in much more critical situations and with mechanical complications of an evolving ACS needing cardiac surgery treatment.

Advanced and accurate forecasting of COVID-19 cases plays a crucial role in planning and supplying resources effectively. Artificial Intelligence (AI) techniques have proved its capability in time series forecasting of the non-linear problems. In the present study, the relationship between weather factor and COVID-19 cases was assessed and also developed a forecasting model using long short term memory (LSTM), a deep learning model. The study found that the specific humidity has a strong positive correlation, whereas there is a negative correlation with maximum temperature and positive correlation with minimum temperature was observed in various geographic locations of India. The weather data and COVID-19 confirmed cases data (1st April-30th June 2020) was used to optimize univariate and multivariate LSTM time series forecast models. The optimized models were utilized to forecast the COVID-19 cases for the period 1st July 2020 to 31st July 2020 with 1 to 14 days of lead time. The results showed that the univariate LSTM model was reasonably good for the short term (1day lead) forecast of COVID-19 cases (relative error < 20%). Moreover, the multivariate LSTM model improved the medium-range forecast skill (1-7days) after including the weather factors. The study observed that the specific humidity played a crucial role in improving the forecast skill majorly in the West and northwest region of India. Similarly, the temperature played a significant role in model enhancement in the Southern and Eastern regions of India.

A study is considered to a steady, two-dimensional boundary layer flow of an incompressible MHD fluid for the Blasius and Sakiadis flows about a flat plate in the presence of thermo-diffusion (Dufour) and thermal-diffusion (Soret) effects for variable parameters. The governing partial differential equations are transformed into a system of nonlinear ordinary differential equations using similarity variables. The transformed systems are solved numerically by Runge-Kutta Gills method with shooting techniques. The variations of the flow velocity, temperature and concentration as well as the characteristics of heat and mass transfer are presented graphically with tabulated results. The numerical computations show that thermal boundary layer thickness is found to be increased with increasing values of Eckert number (Ec), Prandtl number (Pr) and local Grashof number (Gr_x) for both Blasius and Sakiadis flow. The Blasius flow elevates the thickness of the thermal boundary layer compared with the Sakiadis flow. The local magnetic field has shown that flow is retarded in the boundary layer but enhances temperature and concentration distributions.

The thylakoid membrane is in a temperature-sensitive equilibrium that shifts repeatedly during the life cycle in response to ambient temperature or solar irradiance. Plants respond to seasonal temperature by changing their thylakoid lipid composition, while a more rapid mechanism for short-term heat exposure is required. The emission of the small organic molecule isoprene has been postulated as one such possible rapid mechanism. The protective mechanism of isoprene is not known, but some plants emit isoprene during periods of high-temperature stress. In this work, we investigate the dynamics and structure for lipids within a thylakoid membrane at different temperatures and varied isoprene content using classical molecular dynamics simulations. The results are compared with experimental findings from across the literature for temperature-dependent changes in the lipid composition and shape of thylakoids. We find that the surface area, volume, and flexibility of the membrane, as well as the lipid diffusion, increase with temperature, while the membrane thickness decreases. Saturated thylakoid 34:3 glycolipids derived from eukaryotic synthesis pathways exhibit significantly different dynamics than lipids from prokaryotic synthesis paths, which could explain the upregulation of specific lipid synthesis pathways at different temperatures. Increasing isoprene concentration was not observed to have a significant thermoprotective effect on the thylakoid membranes, and that isoprene readily permeated the membrane models tested here.

Microfluidic devices have been introduced for phenotypic screening of zebrafish larvae in both fundamental and pre-clinical research. One of the remaining challenges for the broad use of microfluidic devices is their limited throughput, especially in behavioural assays. Previously, we introduced the tail locomotion of a semi-mobile zebrafish larva evoked on-demand with electric signal in a microfluidic device. Here, we report the lessons learned for increasing the number of specimens from one to four larvae in this device. Multiple parameters including loading and testing time per fish and loading and orientation efficiencies were refined to optimize the performance of modified designs. Simulations of the flow and electric field within the final device provided insight into the flow behavior and functionality of traps when compared to previous single-larva devices. Outcomes led to a new design which decreased the testing time per larva by approximately 60%. Further, loading and orientation efficiencies increased by more than 80%. Critical behavioural parameters such as response duration and tail beat frequency were similar in both single and quadruple-fish devices. The optimized microfluidic device has significant advantages for greater throughput and efficiency when behavioral phenotyping is required in various applications, including chemical testing in toxicology and gene screening.

High-latitude tundra ecosystems are increasingly affected by climate warming. As an important fraction of soil microorganisms, fungi play essential roles in carbon (C) degradation, especially the old, chemically recalcitrant C. However, it remains obscure how fungi respond to climate warming and whether fungi, in turn, affect C stability of tundra. In a two-year winter soil warming experiment of 2 °C by snow fences, we investigated responses of fungal communities to warming in the active layer of the Alaskan tundra. Although fungal community composition, revealed by 28S rRNA gene amplicon sequencing, remained unchanged (P > 0.05), fungal functional gene composition, revealed by a microarray named GeoChip, was altered (P < 0.05). Changes in functional gene composition were linked to winter soil temperature, thaw depth, soil moisture, and gross primary productivity (Canonical Correlation Analysis, P < 0.05). Specifically, relative abundances of fungal genes encoding invertase, xylose reductase, and vanillin dehydrogenase significantly increased (P < 0.05), indicating higher C degradation capacities of fungal communities under warming. Accordingly, we detected changes of fungal gene networks under warming, including higher average path distance, lower average clustering coefficient, and lower percentage of negative links, indicating that warming potentially changed fungal interactions. Together, our study revealed higher C degradation capacities of fungal communities under short-term warming and highlights the potential impacts of fungal communities on mediating tundra ecosystem respiration, and consequently future C stability of high-latitude tundra.

Background: Many arguments suggest that neutrophils could play a prominent role in COVID-19. However, the role of key components of neutrophil innate immunity in severe forms of COVID-19 has deserved insufficient attention. We aimed to evaluate the involvement of Neutrophil Elastase, histone-DNA, and DNases in systemic and multi-organ manifestations of COVID-19. Methods: We performed a multicenter study of markers of neutrophil innate immunity in 155 cases consecutively recruited in a screening center (ambulatory subjects), local hospitals, and two regional university hospitals. The case were evaluated according to clinical and biological markers of severity and multi-organ manifestations and compared to 35 healthy controls. Results: Blood Neutrophil Elastase, histone-DNA, myeloperoxidase-DNA and free dsDNA were dramatically increased, and DNase activity decreased by 10-fold, compared to controls. Neutrophil Elastase and histone-DNA were associated with intensive care admission, body temperature, lung damage and markers of cardiovascular outcomes, renal failure and increased IL-6, IL-8 and CXCR2. Neutrophil Elastase was an independent predictor of the computed tomography score of COVID-19 lung damage and the number of affected organs, in multivariate analyses. The increased blood concentrations of NE and neutrophil extracellular traps were related to exacerbation of neutrophil stimulation through IL8 and CXCR2 increased concentrations and increased serum DAMPs, and to impaired degradation of NETs as a consequence of the dramatic decrease of blood DNase activity. Conclusion: Our results point out the key role of neutrophil innate immunity exacerbation in COVID-19. Neutrophil Elastase and DNase could be potential biomarkers and therapeutic targets of severe systemic manifestations of COVID-19.