Development and analytical characteristics of a quantitative real-time PCR assay for detection of spheniscid alphaherpesvirus 1 in penguins.

Herpesviruses are associated with disease in many penguin species. Herpesvirus-associated lesions can cause significant morbidity and mortality in penguins and have been identified in African penguins (Spheniscus demersus), Humboldt penguins (Spheniscus humboldti), and a little blue penguin (Eudyptula minor) infected with spheniscid alphaherpesvirus 1 (SpAHV1). Further investigation is necessary to understand the impact of herpesviruses on penguin health, but there are no rapid, sensitive, and specific methods for detecting and quantifying herpesviral load. We therefore developed a quantitative real-time PCR (qPCR) assay for the detection of SpAHV1 in penguins. TaqMan primer-probes targeting the DNA polymerase gene were designed using a commercial software program. Inter- and intra-assay variability, dynamic range, limit of detection, and analytical specificity were assessed. We used our assay to analyze previously collected field samples from Punta San Juan, Peru, in which conventional consensus PCR had detected one SpAHV1-positive penguin sample. Our qPCR assay was highly specific for SpAHV1. It had a dynamic range of 107-101 target copies per reaction and performed with high efficiency and low intra- and inter-assay variability. Reaction efficiency was not impacted by penguin DNA from SpAHV1-negative tracheal swabs. We detected an additional field sample as positive with our newly developed qPCR assay, and although this likely represents detection of another infected penguin, the true disease status of this population is currently uncharacterized given that no gold-standard test exists for SpAHV1. Our qPCR assay may provide a valuable tool in the surveillance and characterization of SpAHV1 in penguins.

A sustainable approach toward mechanical recycling unsortable post-consumer WEEE: Reactive and non-reactive compatibilization.

While near-infrared (NIR) spectroscopy in post-consumer waste electrical and electronic equipment (WEEE) recycling accurately separates white or clear polymers, 40% containing dark plastics, termed 'unsortable WEEE,' are excluded from sorting lines and therefore incinerated or landfilled, causing environmental concerns. This study investigates the potential of using non-reactive and reactive copolymers as compatibilizers to enhance the performance of unsortable WEEE plastics free of brominated flame retardants. To the best of our knowledge, this is the first time that such copolymers have been explored as a solution for improving the compatibility of unsortable WEEE polymer blends. Initial trials with 4% of styrene-ethylene-butylene-styrene copolymer (SEBS-13) and SEBS-30-g-(maleic anhydride) copolymer (SEBS-30-g-MA MA) as compatibilizers showed insufficient results compared to virgin commercial polymers. However, the addition of higher concentrations of compatibilizers (i.e. up to 20 wt%) and the use of a SEBS having a higher styrene content (i.e. SEBS-30) improved the mechanical properties of the material, causing it to transition from brittle to ductile. This behavior was found more pronounced for the 20% non-reactive SEBS-30, for which the SEM analysis showed reduced phase segregation and revealed a more homogeneous fracture surface. This was further supported by Differential Scanning Calorimetry (DSC) analysis, which showed evidence of an interaction between one or more polymer phases. With a room temperature performance equivalent to that of virgin conventional polymers, the SEBS-30 compatibilization approach has made it possible to consider using unsortable WEEE streams as recycled materials in commercial applications.

Molecular Accessibility and Diffusion of Resorufin in Zeolite Crystals.

Invited for the cover of this issue is the group of Professor Bert Weckhuysen at Utrecht University. The image depicts the change in fluorescence color of a resorufin dye molecule when it is protonated and confined inside the micropores of zeolite-ß. Read the full text of the article at 10.1002/chem.202302553.

Fluorescent-Probe Characterization for Pore-Space Mapping with Single-Particle Tracking.

Porous solids often contain complex pore networks with pores of various sizes. Tracking individual fluorescent probes as they diffuse through porous materials can be used to characterize pore networks at tens of nanometers resolution. However, understanding the motion behavior of fluorescent probes in confinement is crucial to reliably derive pore network properties. Here, we introduce well-defined lithography-made model pores developed to study probe behavior in confinement. We investigated the influence of probe-host interactions on diffusion and trapping of confined single-emitter quantum-dot probes. Using the pH-responsiveness of the probes, we were able to largely suppress trapping at the pore walls. This enabled us to define experimental conditions for mapping of the accessible pore space of a one-dimensional pore array as well as a real-life polymerization-catalyst-support particle.

Molecular Accessibility and Diffusion of Resorufin in Zeolite Crystals.

We have used confocal laser scanning microscopy on the small, fluorescent resorufin dye molecule to visualize molecular accessibility and diffusion in the hierarchical, anisotropic pore structure of large (~10 µm-sized) zeolite-ß crystals. The resorufin dye is widely used in life and materials science, but only in its deprotonated form because the protonated molecule is barely fluorescent in aqueous solution. In this work, we show that protonated resorufin is in fact strongly fluorescent when confined within zeolite micropores, thus enabling fluorescence microimaging experiments. We find that J-aggregation guest-guest interactions lead to a decrease in the measured fluorescence intensity that can be prevented by using non-fluorescent spacer molecules. We characterized the pore space by introducing resorufin from the outside solution and following its diffusion into zeolite-ß crystals. The eventual homogeneous distribution of resorufin molecules throughout the zeolite indicates a fully accessible pore network. This enables the quantification of the diffusion coefficient in the straight pores of zeolite-ß without the need for complex analysis, and we found a value of 3×10-15  m2  s-1 . Furthermore, we saw that diffusion through the straight pores of zeolite-ß is impeded when crossing the boundaries between zeolite subunits.

[Ventilatory management of SARS-CoV-2 acute respiratory failure]. / Prise en charge ventilatoire de l'insuffisance respiratoire aiguë à SARS-CoV-2.

COVID-19 pneumonia presents several particularities in its clinical presentation (cytokine storm, silent hypoxemia, thrombo-embolic risk) and may lead to a number of acute respiratory distress syndrome (ARDS) phenotypes. While the optimal oxygenation strategy in cases of hypoxemic acute respiratory failure (ARF) is still under debate, ventilatory management of COVID-19-related ARF has confirmed the efficacy of high-flow oxygen therapy and restored interest in other ventilatory approaches such as continuous positive airway pressure (CPAP) and noninvasive ventilation involving a helmet, which due to patient overflow are sometimes implemented outside of critical care units. However, further studies are still needed to determine which patients should be given which oxygenation technique, and under which conditions they require invasive mechanical ventilation, given that delayed initiation potentially burdens prognosis. During invasive mechanical ventilation, ventral decubitus and extracorporeal membrane oxygenation have become increasingly prevalent. While innovative therapies such as awake prone position or lung transplantation have likewise been developed, their indications, modalities and efficacy remain to be determined.

"I didn't give it enough respect" - an evaluation of preparation strategies used by GP trainees for the AKT.

The Applied Knowledge Test (AKT) is one third of the licensing exam to become a General Practitioner in the United Kingdom. It is a computer-based, machine-marked multiple-choice examination with an overall pass rate of around 70%. Statistics reveal international medical graduates to have lower rates of passing. The aim of this evaluation was to determine the key features of preparation for the exam used by successful candidates. A questionnaire survey was sent to recently successful general practice trainees in Southampton. The results were further informed by a group interview and three in-depth interviews. A series of six areas were identified within the exam preparation that featured as common areas for all candidates. Further analysis showed the parameters around these areas suggesting the ability to maximise the candidates' chances of success. The areas included: preparation; time management; expectations; peer support; change of approach and impact on trainee mental health. A period of at least 10 hours per week for at least three months revision, using four to six resources and using question banks to consolidate learning rather than as a primary tool were found to be the key parameters with successful candidates. When to take the exam should be discussed with the trainer, the difficulty of the exam needs to be acknowledged by candidates, working in study groups can be beneficial and planning of the approach to revision was found to be essential. The impact of failure on trainee mental health must not be underestimated.

Micro- and Nanoscale Heterogeneities in Zeolite Beta as Measured by Atom Probe Tomography and Confocal Fluorescence Microscopy.

Micro- and nanoscale information on the activating and deactivating coking behaviour of zeolite catalyst materials increases our current understanding of many industrially applied processes, such as the methanol-to-hydrocarbon (MTH) reaction. Atom probe tomography (APT) was used to reveal the link between framework and coke elemental distributions in 3D with sub-nanometre resolution. APT revealed 10-20 nanometre-sized Al-rich regions and short-range ordering (within nanometres) between Al atoms. With confocal fluorescence microscopy, it was found that the morphology of the zeolite crystal as well as the secondary mesoporous structures have a great effect on the microscale coke distribution throughout individual zeolite crystals over time. Additionally, a nanoscale heterogeneous distribution of carbon as residue from the MTH reaction was determined with carbon-rich areas of tens of nanometres within the zeolite crystals. Lastly, a short length-scale affinity between C and Al atoms, as revealed by APT, indicates the formation of carbon-containing molecules next to the acidic sites in the zeolite.

Classification-based motion analysis of single-molecule trajectories using DiffusionLab.

Single-particle tracking is a powerful approach to study the motion of individual molecules and particles. It can uncover heterogeneities that are invisible to ensemble techniques, which places it uniquely among techniques to study mass transport. Analysis of the trajectories obtained with single-particle tracking in inorganic porous hosts is often challenging, because trajectories are short and/or motion is heterogeneous. We present the DiffusionLab software package for motion analysis of such challenging data sets. Trajectories are first classified into populations with similar characteristics to which the motion analysis is tailored in a second step. DiffusionLab provides tools to classify trajectories based on the motion type either with machine learning or manually. It also offers quantitative mean squared displacement analysis of the trajectories. The software can compute the diffusion constant for an individual trajectory if it is sufficiently long, or the average diffusion constant for multiple shorter trajectories. We demonstrate the DiffusionLab approach via the analysis of a simulated data set with motion types frequently observed in inorganic porous hosts, such as zeolites. The software package with graphical user interface and its documentation are freely available.

Dual Fluorescence in Glutathione-Derived Carbon Dots Revisited.

Dual-fluorescence carbon dots have great potential as nanosensors in life and materials sciences. Such carbon dots can be obtained via a solvothermal synthesis route with glutathione and formamide. In this work, we show that the dual-fluorescence emission of the synthesis products does not originate from a single carbon dot emitter, but rather from a mixture of physically separate compounds. We characterized the synthesis products with UV-vis, Raman, infrared, and fluorescence spectroscopy, and identified blue-emissive carbon dots and red-emissive porphyrin. We demonstrate an easy way to separate the two compounds without the need for time-consuming dialysis. Understanding the nature of the system, we can now steer the synthesis toward the desired product, which paves the way for a cheap and environmentally friendly synthesis route toward carbon dots, water-soluble porphyrin, and mixed systems.

Unravelling Channel Structure-Diffusivity Relationships in Zeolite ZSM-5 at the Single-Molecule Level.

The development of improved zeolite materials for applications in separation and catalysis requires understanding of mass transport. Herein, diffusion of single molecules is tracked in the straight and sinusoidal channels of the industrially relevant ZSM-5 zeolites using a combination of single-molecule localization microscopy and uniformly oriented zeolite thin films. Distinct motion behaviors are observed in zeolite channels with the same geometry, suggesting heterogeneous guest-host interactions. Quantification of the diffusion heterogeneities in the sinusoidal and straight channels suggests that the geometry of zeolite channels dictates the mobility and motion behavior of the guest molecules, resulting in diffusion anisotropy. The study of hierarchical zeolites shows that the addition of secondary pore networks primarily enhances the diffusivity of sinusoidal zeolite channels, and thus alleviating the diffusion limitations of microporous zeolites.

On the role of softness in ionic microgel interactions.

Thermoresponsive microgels are a popular model system to study phase transitions in soft matter, because temperature directly controls their volume fraction. Ionic microgels are additionally pH-responsive and possess a rich phase diagram. Although effective interaction potentials between microgel particles have been proposed, these have never been fully tested, leading to a gap in our understanding of the link between single-particle and collective properties. To help resolve this gap, four sets of ionic microgels with varying crosslinker density were synthesised and characterised using light scattering techniques and confocal microscopy. The resultant structural and dynamical information was used to investigate how particle softness affects the phase behaviour of ionic microgels and to validate the proposed interaction potential. We find that the architecture of the microgel plays a marked role in its phase behaviour. Rather than the ionic charges, it is the dangling ends which drive phase transitions and interactions at low concentration. Comparison to theory underlines the need for a refined theoretical model which takes into consideration these close-contact interactions.

ArGSLab: a tool for analyzing experimental or simulated particle networks.

Microscopy and particle-based simulations are both powerful techniques to study aggregated particulate matter such as colloidal gels. The data provided by these techniques often contains information on a wide array of length scales, but structural analysis methods typically focus on the local particle arrangement, even though the data also contains information about the particle network on the mesoscopic length scale. In this paper, we present a MATLAB software package for quantifying mesoscopic network structures in colloidal samples. ArGSLab (Arrested and Gelated Structures Laboratory) extracts a network backbone from the input data, which is in turn transformed into a set of nodes and links for graph theory-based analysis. The routines can process both image stacks from microscopy as well as explicit coordinate data, and thus allows quantitative comparison between simulations and experiments. ArGSLab furthermore enables the accurate analysis of microscopy data where, e.g., an extended point spread function prohibits the resolution of individual particles. We demonstrate the resulting output for example datasets from both microscopy and simulation of colloidal gels, in order to showcase the capability of ArGSLab to quantitatively analyze data from various sources. The freely available software package can be used either with a provided graphical user interface or directly as a MATLAB script.

Decision tree analysis for pathogen identification based on circumstantial factors in outbreaks of bovine respiratory disease in calves.

Respiratory tract infections continue to be a leading cause of economic loss, hampered animal welfare and intensive antimicrobial use in cattle operations, worldwide. To better target antimicrobial therapy, control and prevention towards the involved pathogens, there is a growing interest in microbiological tests on respiratory samples. However, these tests are time consuming, cost money and sampling might compromise animal welfare. Therefore, the objective of the present study was to develop immediately applicable decision trees for pathogen identification in outbreaks of bovine respiratory disease based on circumstantial factors. Data from a cross sectional study, involving 201 outbreaks of bovine respiratory disease in dairy and beef farms between 2016 and 2019 was used. Pathogens were identified by a semi-quantitative PCR (polymerase chain reaction) on a pooled non-endoscopic broncho-alveolar lavage sample from clinically affected animals. Potential risk factors of involved animals, environment, management and housing were obtained by enquiry. Classification and regression tree analysis was used for decision tree development with cross-validation. Different trees were constructed, involving a general 3-group classification tree (viruses, Mycoplasma bovis or Pasteurellaceae family) and a tree for each single pathogen. The general 3- group classification tree was 52.7 % accurate and had a sensitivity of 81.5 % and a specificity 52.2 % for viruses, respectively 51.7 % and 84.4 % for M. bovis and 28.9 % and 93.6 % for Pasteurellaceae. The single-pathogen trees were more specific than sensitive: Histophilus somni (Se = 25.8 %; Sp = 94.5 %), Mannheimia haemolytica (Se = 69.2 %; Sp = 70.6 %), bovine coronavirus (Se = 42.2 %; Sp = 89.6 %) and bovine respiratory syncytial virus (Se = 34.0 %; Sp = 96.6 %). For Pasteurella multocida, M. bovis and parainfluenzavirus type 3 no meaningful tree was obtained. The concept and trees are promising, but currently lack sensitivity and specificity in order to be a reliable tool for practice. For now, the obtained trees can already be informative for decision making to some extend depending on the end node in which an outbreak falls.

Crystal-to-Crystal Transitions in Binary Mixtures of Soft Colloids.

In this article, we demonstrate a method for inducing reversible crystal-to-crystal transitions in binary mixtures of soft colloidal particles. Through a controlled decrease of salinity and increasingly dominating electrostatic interactions, a single sample is shown to reversibly organize into entropic crystals, electrostatic attraction-dominated crystals, or aggregated gels, which we quantify using microscopy and image analysis. We furthermore analyze crystalline structures with bond order analysis to discern between two crystal phases. We observe the different phases using a sample holder geometry that allows both in situ salinity control and imaging through confocal laser scanning microscopy and apply a synthesis method producing particles with high resolvability in microscopy with control over particle size. The particle softness provides for an enhanced crystallization speed, while altering the re-entrant melting behavior as compared to hard sphere systems. This work thus provides several tools for use in the reproducible manufacture and analysis of binary colloidal crystals.

Pathogen-specific risk factors in acute outbreaks of respiratory disease in calves.

Respiratory tract infections (bovine respiratory disease) are a major concern in calf rearing. The objective of this study was to identify pathogen-specific risk factors associated with epidemic respiratory disease in calves. A cross-sectional study was conducted, involving 128 outbreaks (29 dairy, 58 dairy-mixed, and 41 beef) in Belgium (2016-2018). A semiquantitative PCR for 7 respiratory pathogens was done on a pooled nonendoscopic bronchoalveolar lavage sample for each herd. Potential risk factors were collected by questionnaire and derived from the national cattle registration databank. Most outbreaks occurred between October and March, and single and multiple viral infections were detected in 58.6% (75/128) and 13.3% (17/128), respectively. Bovine coronavirus (BCV) was the most frequently isolated virus (38.4%), followed by bovine respiratory syncytial virus (bRSV; 29.4%) and parainfluenzavirus type 3 (PI-3; 8.1%). Mycoplasma bovis, Mannheimia haemolytica, Pasteurella multocida, and Histophilus somni were detected in 33.3, 41.2, 89.1, and 36.4% of the herds, respectively. Specific risk factors for BCV detection were detection of M. haemolytica [odds ratio (OR) = 2.8 (95% confidence interval = 1.1-7.5)], increasing herd size [OR = 1.3 (1.0-1.8) for each increase with 100 animals] and detection of BCV by antigen ELISA on feces in calves in the last year [OR = 3.6 (1.2-11.1)]. A seasonal effect was shown for bRSV only {more in winter compared with autumn [OR = 10.3 (2.8-37.5)]}. Other factors associated with bRSV were PI-3 detection [OR = 13.4 (2.1-86.0)], prevalence of calves with respiratory disease [OR = 1.02 (1.00-1.04) per 1% increase], and number of days with respiratory signs before sampling [OR = 0.99 (0.98-0.99) per day increase]. Next to its association with BCV, M. haemolytica was more frequently detected in herds with 5 to 10 animals per pen [OR = 8.0 (1.4-46.9)] compared with <5 animals, and in herds with sawdust as bedding [OR = 18.3 (1.8-191.6)]. Also, for H. somni, housing on sawdust was a risk factor [OR = 5.2 (1.2-23.0)]. Purchase of cattle [OR = 2.9 (1.0-8.0)] and housing of recently purchased animals in the same airspace [OR = 5.0 (1.5-16.5)] were risk factors for M. bovis. This study identified pathogen-specific risk factors that might be useful for the development of customized control and prevention and for the design of decision support tools to justify antimicrobial use by predicting the most likely pathogen before sampling results are available.

Using Patchy Particles to Prevent Local Rearrangements in Models of Non-equilibrium Colloidal Gels.

Simple models based on isotropic interparticle attractions often fail to capture experimentally observed structures of colloidal gels formed through spinodal decomposition and subsequent arrest: the resulting gels are typically denser and less branched than their experimental counterparts. Here, we simulate gels formed from soft particles with directional attractions ("patchy particles"), designed to inhibit lateral particle rearrangement after aggregation. We directly compare simulated structures with experimental colloidal gels made using soft attractive microgel particles, by employing a "skeletonization" method that reconstructs the three-dimensional backbone from experiment or simulation. We show that including directional attractions with sufficient valency leads to strongly branched structures compared to isotropic models. Furthermore, combining isotropic and directional attractions provides additional control over aggregation kinetics and gel structure. Our results show that the inhibition of lateral particle rearrangements strongly affects the gel topology and is an important effect to consider in computational models of colloidal gels.

Reversible Formation of Thermoresponsive Binary Particle Gels with Tunable Structural and Mechanical Properties.

We investigate the collective behavior of suspended thermoresponsive microgels that expel solvent and subsequently decrease in size upon heating. Using a binary mixture of differently thermoresponsive microgels, we demonstrate how distinctly different gel structures form, depending on the heating profile used. Confocal laser scanning microscopy (CLSM) imaging shows that slow heating ramps yield a core-shell network through sequential gelation, while fast heating ramps yield a random binary network through homogelation. Here, secondary particles are shown to aggregate in a monolayer fashion upon the first gel, which can be qualitatively reproduced through Brownian dynamics simulations using a model based on a temperature-dependent interaction potential incorporating steric repulsion and van der Waals attraction. Through oscillatory rheology it is shown that secondary microgel deposition enhances the structural integrity of the previously formed single species gel, and the final structure exhibits higher elastic and loss moduli than its compositionally identical homogelled counterpart. Furthermore, we demonstrate that aging processes in the scaffold before secondary microgel deposition govern the final structural properties of the bigel, which allows a detailed control over these properties. Our results thus demonstrate how the temperature profile can be used to finely control the structural and mechanical properties of these highly tunable materials.

Identification of CASZ1 NES reveals potential mechanisms for loss of CASZ1 tumor suppressor activity in neuroblastoma.

As a transcription factor, localization to the nucleus and the recruitment of cofactors to regulate gene transcription is essential. Nuclear localization and nucleosome remodeling and histone deacetylase (NuRD) complex binding are required for the zinc-finger transcription factor CASZ1 to function as a neuroblastoma (NB) tumor suppressor. However, the critical amino acids (AAs) that are required for CASZ1 interaction with NuRD complex and the regulation of CASZ1 subcellular localization have not been characterized. Through alanine scanning, immunofluorescence cell staining and co-immunoprecipitation, we define a critical region at the CASZ1 N terminus (AAs 23-40) that mediates the CASZ1b nuclear localization and NuRD interaction. Furthermore, we identified a nuclear export signal (NES) at the N terminus (AAs 176-192) that contributes to CASZ1 nuclear-cytoplasmic shuttling in a chromosomal maintenance 1-dependent manner. An analysis of CASZ1 protein expression in a primary NB tissue microarray shows that high nuclear CASZ1 staining is detected in tumor samples from NB patients with good prognosis. In contrast, cytoplasmic-restricted CASZ1 staining or low nuclear CASZ1 staining is found in tumor samples from patients with poor prognosis. These findings provide insight into mechanisms by which CASZ1 regulates transcription, and suggests that regulation of CASZ1 subcellular localization may impact its function in normal development and pathologic conditions such as NB tumorigenesis.