Advanced cryo-tomography workflow developments - correlative microscopy, milling automation and cryo-lift-out

Cryo-electron tomography (cryo-ET) is a groundbreaking technology for 3D visualisation and analysis of biomolecules in the context of cellular structures. It allows structural investigations of single proteins as well as their spatial arrangements within the cell. Cryo-tomograms provide a snapshot of the complex, heterogeneous and transient subcellular environment. Due to the excellent structure preservation in amorphous ice, it is possible to study interactions and spatial relationships of proteins in their native state without interference caused by chemical fixatives or contrasting agents. With the introduction of focused ion beam (FIB) technology, the preparation of cellular samples for electron tomography has become much easier and faster. The latest generation of integrated FIB and scanning electron microscopy (SEM) instruments (dual beam microscopes), specifically designed for cryo-applications, provides advances in automation, imaging and the preparation of high-pressure frozen bulk samples using cryo-lift-out technology. In addition, correlative cryo-fluorescence microscopy provides cellular targeting information through integrated software and hardware interfaces. The rapid advances, based on the combination of correlative cryo-microscopy, cryo-FIB and cryo-ET, have already led to a wealth of new insights into cellular processes and provided new 3D image data of the cell. Here we introduce our recent developments within the cryo-tomography workflow, and we discuss the challenges that lie ahead. Lay Description This article describes our recent developments for the cryo-electron tomography (cryo-ET) workflow. Cryo-ET offers superior structural preservation and provides 3D snapshots of the interior of vitrified cells at molecular resolution. Before a cellular sample can be imaged by cryo-ET, it must be made accessible for transmission electron microscopy. This is achieved by preparing a 200-300 nm thin cryo-lamella from the cellular sample using a cryo-focused ion beam (cryo-FIB) microscope. Cryo-correlative light and electron microscopy (cryo-CLEM) is used within the workflow to guide the cryo-lamella preparation to the cellular areas of interest. We cover a basic introduction of the cryo-ET workflow and show new developments for cryo-CLEM, which facilitate the connection between the cryo-light microscope and the cryo-FIB. Next, we present our progress in cryo-FIB software automation to streamline cryo-lamella preparation. In the final section we demonstrate how the cryo-FIB can be used for 3D imaging and how bulk-frozen cellular samples (obtained by high-pressure freezing) can be processed using the newly developed cryo-lift-out technology

Candesartan Attenuates Diabetic Retinal Vascular Pathology by Restoring Glyoxalase-I Function

This is an uncopyedited electronic version of an article accepted for publication in Diabetes. The American Diabetes Association, publisher of Diabetes, is not responsible for any errors or omissions in this version of the manuscript or any version derived from it by third parties. The definitive publisher-authenticated version will be available in a future issue of Diabetes in print and online a

Perylene Diimide as a Precise Graphene-like Superoxide Dismutase Mimetic

Here we show that the active portion of a graphitic nanoparticle can be mimicked by a perylene diimide (PDI) to explain the otherwise elusive biological and electrocatalytic activity of the nanoparticle construct. Development of molecular analogues that mimic the antioxidant properties of oxidized graphenes, in this case the poly(ethylene glycolated) hydrophilic carbon clusters (PEG–HCCs), will afford important insights into the highly efficient activity of PEG–HCCs and their graphitic analogues. PEGylated perylene diimides (PEGn–PDI) serve as well-defined molecular analogues of PEG–HCCs and oxidized graphenes in general, and their antioxidant and superoxide dismutase-like (SOD-like) properties were studied. PEGn–PDIs have two reversible reduction peaks, which are more positive than the oxidation peak of superoxide (O2•–). This is similar to the reduction peak of the HCCs. Thus, as with PEG–HCCs, PEGn–PDIs are also strong single-electron oxidants of O2•–. Furthermore, reduced PEGn–PDI, PEGn–PDI•–, in the presence of protons, was shown to reduce O2•– to H2O2 to complete the catalytic cycle in this SOD analogue. The kinetics of the conversion of O2•– to O2 and H2O2 by PEG8–PDI was measured using freeze-trap EPR experiments to provide a turnover number of 133 s–1; the similarity in kinetics further supports that PEG8–PDI is a true SOD mimetic. Finally, PDIs can be used as catalysts in the electrochemical oxygen reduction reaction in water, which proceeds by a two-electron process with the production of H2O2, mimicking graphene oxide nanoparticles that are otherwise difficult to study spectroscopically

Effect of NADPH oxidase 1 and 4 blockade in activated human retinal endothelial cells

© 2018 Royal Australian and New Zealand College of Ophthalmologists. This author accepted manuscript is made available following 12 month embargo from date of publication (January 2018) in accordance with the publisher's archiving policy.Background Over‐production of reactive oxygen species (ROS) and resulting oxidative stress contribute to retinal damage in vascular diseases that include diabetic retinopathy, retinopathy of prematurity and major retinal vessel occlusions. NADPH oxidase (Nox) proteins are professional ROS‐generating enzymes, and therapeutic targeting in these diseases has strong appeal. Pharmacological inhibition of Nox4 reduces the severity of experimental retinal vasculopathy. We investigated the potential application of this drug approach in humans. Methods Differential Nox enzyme expression was studied by real‐time‐quantitative polymerase chain reaction in primary human retinal endothelial cell isolates and a characterized human retinal endothelial cell line. Oxidative stress was triggered chemically in endothelial cells, by treatment with dimethyloxalylglycine (DMOG; 100 μM); Nox4 and vascular endothelial growth factor (VEGFA) transcript were measured; and production of ROS was detected by 2′,7′‐dichlorofluorescein. DMOG‐stimulated endothelial cells were treated with two Nox1/Nox4 inhibitors, GKT136901 and GKT137831; cell growth was monitored by DNA quantification, in addition to VEGFA transcript and ROS production. Results Nox4 (isoform Nox4A) was the predominant Nox enzyme expressed by human retinal endothelial cells. Treatment with DMOG significantly increased endothelial cell expression of Nox4 over 72 h, accompanied by ROS production and increased VEGFA expression. Treatment with GKT136901 or GKT137831 significantly reduced DMOG‐induced ROS production and VEGFA expression by endothelial cells, and the inhibitory effect of DMOG on cell growth. Conclusions Our findings in experiments on activated human retinal endothelial cells provide translational corroboration of studies in experimental models of retinal vasculopathy and support the therapeutic application of Nox4 inhibition by GKT136901 and GKT137831 in patients with retinal vascular diseases

Analysis of Stochastic Strategies in Bacterial Competence: A Master Equation Approach

Competence is a transiently differentiated state that certain bacterial cells reach when faced with a stressful environment. Entrance into competence can be attributed to the excitability of the dynamics governing the genetic circuit that regulates this cellular behavior. Like many biological behaviors, entrance into competence is a stochastic event. In this case cellular noise is responsible for driving the cell from a vegetative state into competence and back. In this work we present a novel numerical method for the analysis of stochastic biochemical events and use it to study the excitable dynamics responsible for competence in Bacillus subtilis. Starting with a Finite State Projection (FSP) solution of the chemical master equation (CME), we develop efficient numerical tools for accurately computing competence probability. Additionally, we propose a new approach for the sensitivity analysis of stochastic events and utilize it to elucidate the robustness properties of the competence regulatory genetic circuit. We also propose and implement a numerical method to calculate the expected time it takes a cell to return from competence. Although this study is focused on an example of cell-differentiation in Bacillus subtilis, our approach can be applied to a wide range of stochastic phenomena in biological systems

Determination of ππ\pi\pi scattering lengths from measurement of π+π−\pi^+\pi^- atom lifetime

The DIRAC experiment at CERN has achieved a sizeable production of $\pi^+\pi^-$ atoms and has significantly improved the precision on its lifetime determination. From a sample of 21227 atomic pairs, a 4% measurement of the S-wave $\pi\pi$ scattering length difference $|a_0-a_2| = (.0.2533^{+0.0080}_{-0.0078}|_\mathrm{stat}.{}^{+0.0078}_{-0.0073}|_\mathrm{syst})M_{\pi^+}^{-1}$ has been attained, providing an important test of Chiral Perturbation Theory.Comment: 6 pages, 6 figure

The Impact of Task Load on the Integration of Explicit Contextual Priors and Visual Information during Anticipation

© 2020 The Authors. There is limited knowledge about the impact of task load on experts’ integration of contextual priors and visual information during dynamic and rapidly evolving anticipation tasks. We examined how experts integrate contextual priors––specifically, prior information regarding an opponent's action tendencies––with visual information such as movement kinematics, during a soccer‐specific anticipation task. Furthermore, we combined psychophysiological measures and retrospective self‐reports to gain insight into the cognitive load associated with this integration. Players were required to predict the action of an oncoming opponent, with and without the explicit provision of contextual priors, under two different task loads. In addition to anticipation performance, we compared continuous electroencephalography (EEG) and self‐reports of cognitive load across conditions. Our data provide tentative evidence that increased task load may impair performance by disrupting the integration of contextual priors and visual information. EEG data suggest that cognitive load may increase when contextual priors are explicitly provided, whereas self‐report data suggested a decrease in cognitive load. The findings provide insight into the processing demands associated with integration of contextual priors and visual information during dynamic anticipation tasks, and have implications for the utility of priors under cognitively demanding conditions. Furthermore, our findings add to the existing literature, suggesting that continuous EEG may be a more valid measure than retrospective self‐reports for in‐task assessment of cognitive load

Numerical Weather Prediction (NWP) and hybrid ARMA/ANN model to predict global radiation

We propose in this paper an original technique to predict global radiation using a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (ALADIN). We particularly look at the Multi-Layer Perceptron. After optimizing our architecture with ALADIN and endogenous data previously made stationary and using an innovative pre-input layer selection method, we combined it to an ARMA model from a rule based on the analysis of hourly data series. This model has been used to forecast the hourly global radiation for five places in Mediterranean area. Our technique outperforms classical models for all the places. The nRMSE for our hybrid model ANN/ARMA is 14.9% compared to 26.2% for the na\"ive persistence predictor. Note that in the stand alone ANN case the nRMSE is 18.4%. Finally, in order to discuss the reliability of the forecaster outputs, a complementary study concerning the confidence interval of each prediction is proposedComment: Energy (2012)

Towards nationally curated data archives for clinical radiology image analysis at scale: Learnings from national data collection in response to a pandemic

The prevalence of the coronavirus SARS-CoV-2 disease has resulted in the unprecedented collection of health data to support research. Historically, coordinating the collation of such datasets on a national scale has been challenging to execute for several reasons, including issues with data privacy, the lack of data reporting standards, interoperable technologies, and distribution methods. The coronavirus SARS-CoV-2 disease pandemic has highlighted the importance of collaboration between government bodies, healthcare institutions, academic researchers and commercial companies in overcoming these issues during times of urgency. The National COVID-19 Chest Imaging Database, led by NHSX, British Society of Thoracic Imaging, Royal Surrey NHS Foundation Trust and Faculty, is an example of such a national initiative. Here, we summarise the experiences and challenges of setting up the National COVID-19 Chest Imaging Database, and the implications for future ambitions of national data curation in medical imaging to advance the safe adoption of artificial intelligence in healthcare