Current approaches and future role of high content imaging in safety sciences and drug discovery

High content imaging combines automated microscopy with image analysis approaches to simultaneously quantify multiple phenotypic and/or functional parameters in biological systems. The technology has become an important tool in the fields of safety sciences and drug discovery, because it can be used for mode-of-action identification, determination of hazard potency and the discovery of toxicity targets and biomarkers. In contrast to conventional biochemical endpoints, high content imaging provides insight into the spatial distribution and dynamics of responses in biological systems. This allows the identification of signaling pathways underlying cell defense, adaptation, toxicity and death. Therefore high content imaging is considered a promising technology to address the challenges for the Toxicity testing in the 21st century approach. Currently high content imaging technologies are frequently applied in academia for mechanistic toxicity studies and in pharmaceutical industry for the ranking and selection of lead drug compounds or to identify/confirm mechanisms underlying effects observed in vivo. A recent workshop gathered scientists working on high content imaging in academia, pharmaceutical industry and regulatory bodies with the objective to compile the state-of-the-art of the technology in the different institutions. They defined technical and methodological gaps, addressed the need for quality control, suggested control compounds and acceptance criteria, highlighted cell sources and new readouts and discussed future requirements for regulatory implementation. This review summarizes the discussion, proposed solutions and recommendations of the specialists contributing to the workshop.JRC.I.5-Systems Toxicolog

Development of a Three-Dimensional In Vitro Model for Longitudinal Observation of Cell Behavior: Monitoring by Magnetic Resonance Imaging and Optical Imaging

Purpose: The aim of this study is the development of a three-dimensional multicellular spheroid cell culture model for the longitudinal comparative and large-scale screening of cancer cell proliferation with noninvasive molecular imaging techniques under controlled and quantifiable conditions. Procedures: The human glioblastoma cell line Gli36ΔEGFR was genetically modified to constitutively express the fluorescence protein mCherry, and additionally labeled with iron oxide nanoparticles for high-field MRI detection. The proliferation of aggregates was longitudinally monitored with fluorescence imaging and correlated with aggregate size by light microscopy, while MRI measurements served localization in 3D space. Irradiation with γ-rays was used to detect proliferational response. Results: Cell proliferation in the stationary three-dimensonal model can be observed over days with high accuracy. A linear relationship of fluorescence intensity with cell aggregate size was found, allowing absolute quantitation of cells in a wide range of cell amounts. Glioblastoma cells showed pronounced suppression of proliferation for several days following high-dose γ-irradiation. Conclusions: Through the combination of two-dimensional optical imaging and 3D MRI, the position of individual cell aggregates and their corresponding light emission can be detected. This allows an exact quantification of cell proliferation, with a focus on very small cell amounts (below 100 cells) using high resolution noninvasive techniques as a well-controlled basis for further cell transplantation studies

Oscillatory brain dynamics supporting impaired Stroop task performance in schizophrenia-spectrum disorder.

The Stroop color-word interference task, prompting slower response to color-incongruent than to congruent items, is often used to study neural mechanisms of inhibitory control and dysfunction in schizophrenia-spectrum disorders. Inconsistent findings of an augmented Stroop effect limit identification of relevant dysfunctional mechanism(s) in schizophrenia. The present study sought to advance understanding of normal and impaired neural oscillatory dynamics by distinguishing interference detection and response preparation during the Stroop task in schizophrenia-spectrum disorders via analysis of behavioral performance and 4-7 Hz (theta) and 10-30 Hz (alpha/beta) EEG oscillations in 40 patients (SZ) and 27 healthy comparison participants (HC). SZ responded more slowly and showed less dorsal anterior cingulate (dACC) theta enhancement during INC trials, less enhancement of dACC-sensorimotor cortex connectivity (theta phase synchrony) during INC trials, more alpha/beta suppression though less enhancement of that suppression during INC trials, and slower post-response alpha/beta rebound than did HC. Reaction time distributions showed larger group and Stroop effects during the 25% of trials with the slowest responses. Poorer theta phase coherence in patients indicates impaired communication between regions associated with interference processing (dACC) and response preparation (sensorimotor cortex). Results suggest a failure cascade in which compromised behavioral Stroop effects are driven at least in part by dysfunctional interference processing (less theta power increase) prompting dysfunctional motor response preparation (less alpha/beta power suppression). Inconsistent Stroop effects in past studies of schizophrenia may result from differing task parameters sampling different degrees of Stroop task difficulty

A label-free, impedance-based real time assay to identify drug-induced toxicities and differentiate cytostatic from cytotoxic effects

Cell-based assays are key tools in drug safety assessment. However, they usually provide only limited information about time-kinetics of a toxic effect and implementing multiple measurements is often complex. To overcome these issues we established an impedance-based approach which is able to differentiate cytostatic from cytotoxic drugs by recording time-kinetics of compound-effects on cells. NIH 3T3 fibroblasts were seeded on xCELLigence E-plates and impedance was continuously measured over 5 days. The obtained results reflected cytotoxicity and cell proliferation, as confirmed by neutral red uptake in vitro. Based on known toxicants, we established an algorithm able to discriminate cytostatic, cytotoxic and non-toxic compounds based on the shape of the impedance curves. Analyzing impedance curve patterns of additional 37 compounds allowed the identification and differentiation of these distinct effects as results correlated well with previous in vivo findings. We show that impedance-based real-time cell analysis is a convenient tool to characterize and discriminate effects of compounds on cells in a time-dependent and label-free manner. The presented impedance assay could be used to further characterize toxicities observed in vivo or in vitro. Due to the ease of performance it may also be a suitable screening tool. 2012 Elsevier Lt

Electroencephalography-based power spectra allow coma outcome prediction within 24 h of cardiac arrest.

Outcome prediction in comatose patients following cardiac arrest remains challenging. Here, we assess the predictive performance of electroencephalography-based power spectra within 24 h from coma onset. We acquired electroencephalography (EEG) from comatose patients (n = 138) on the first day of coma in four hospital sites in Switzerland. Outcome was categorised as favourable or unfavourable based on the best state within three months. Data were split in training and test sets. We evaluated the predictive performance of EEG power spectra for long term outcome and its added value to standard clinical tests. Out of 138 patients, 80 had a favourable outcome. Power spectra comparison between favourable and unfavourable outcome in the training set yielded significant differences at 5.2-13.2 Hz and above 21 Hz. Outcome prediction based on power at 5.2-13.2 Hz was accurate in training and test sets. Overall, power spectra predicted patients' outcome with maximum specificity and positive predictive value: 1.00 (95% with CI: 0.94-1.00 and 0.89-1.00, respectively). The combination of power spectra and reactivity yielded better accuracy and sensitivity (0.81, 95% CI: 0.71-0.89) than prediction based on power spectra alone. On the first day of coma following cardiac arrest, low power spectra values around 10 Hz, typically linked to impaired cortico-thalamic structural connections, are highly specific of unfavourable outcome. Peaks in this frequency range can predict long-term outcome

Brain functional connectivity during the first day of coma reflects long-term outcome.

In patients with disorders of consciousness (DOC), properties of functional brain networks at rest are informative of the degree of consciousness impairment and of long-term outcome. Here we investigate whether connectivity differences between patients with favorable and unfavorable outcome are already present within 24 h of coma onset. We prospectively recorded 63-channel electroencephalography (EEG) at rest during the first day of coma after cardiac arrest. We analyzed 98 adults, of whom 57 survived beyond unresponsive wakefulness. Functional connectivity was estimated by computing the 'debiased weighted phase lag index' over epochs of five seconds duration. We evaluated the network's topological features, including clustering coefficient, path length, modularity and participation coefficient and computed their variance over time. Finally, we estimated the predictive value of these topological features for patients' outcomes by splitting the patient sample in training and test datasets. Group-level analysis revealed lower clustering coefficient, higher modularity and path length variance in patients with favorable compared to those with unfavorable outcomes (p < 0.01). Within all features, the path length variance in the network provided the best positive predictive value (PPV) for favorable outcome and specificity for unfavorable outcome in the test dataset (PPV: 0.83, p < 0.01; specificity: 0.86, p < 0.01) with above-chance negative predictive value and accuracy. Of note, the exclusion of patients with epileptiform activity (20 in total) eliminates all false positive predictions (n = 6) for path length variance. Topological features of functional connectivity differ as a function of long-term outcome in patients on the first day of coma. These differences are not interpretable in terms of consciousness levels as all patients were in a deep unconscious state. The time variance of path length is informative of comatose patients' outcome, as patients with favorable outcome exhibit a richer repertoire of path length than those with unfavorable outcomes

Electromyographic reactivity measured with scalp-EEG contributes to prognostication after cardiac arrest.

To assess whether stimulus-induced modifications of electromyographic activity observed on scalp EEG have a prognostic value in comatose patients after cardiac arrest. 184 adult patients from a multi-centric prospective register who underwent an early EEG after cardiac arrest were included. Auditory and somatosensory stimulation was performed during EEG-recording. EEG reactivity (EEG-R) and EMG reactivity (EMG-R) were retrospectively assessed visually by board-certified electroencephalographers, and compared with clinical outcome (cerebral performance category, CPC) at three months. A favorable functional outcome was defined as CPC 1-2, an unfavorable outcome as CPC 3-5. Both EEG-R and EMG-R were predictors for good outcome (EEG-R accuracy 72% (95%-CI 66-79), sensitivity 86% (78-93), specificity 60% (50-69); EMG-R accuracy 65% (58-72), sensitivity 61% (51-75), specificity 69% (60-78)). When reactivity was defined as EEG-R and/or EMG-R, the accuracy was 73% (67-70), the sensitivity 94% (90-99), and the specificity 53% (43-63). Taking EMG into account when assessing reactivity of EEG seems to reduce false negative predictions for identifying patients with favorable outcome after cardiac arrest

Vaginal delivery in SARS-CoV-2-infected pregnant women in Northern Italy: a retrospective analysis

Objective: To report mode of delivery and immediate neonatal outcome in women infected with COVID-19. Design: Retrospective study. Setting: Twelve hospitals in northern Italy. Participants: Pregnant women with COVID-19-confirmed infection who delivered. Exposure: COVID 19 infection in pregnancy. Methods: SARS-CoV-2-infected women who were admitted and delivered from 1 to 20 March 2020 were eligible. Data were collected from the clinical records using a standardised questionnaire on maternal general characteristics, any medical or obstetric co-morbidity, course of pregnancy, clinical signs and symptoms, treatment of COVID 19 infection, mode of delivery, neonatal data and breastfeeding. Main outcome and measures: Data on mode of delivery and neonatal outcome. Results: In all, 42 women with COVID-19 delivered at the participating centres; 24 (57.1%, 95% CI 41.0–72.3) delivered vaginally. An elective caesarean section was performed in 18/42 (42.9%, 95% CI 27.7–59.0) cases: in eight cases the indication was unrelated to COVID-19 infection. Pneumonia was diagnosed in 19/42 (45.2%, 95% CI 29.8–61.3) cases: of these, 7/19 (36.8%, 95% CI 16.3–61.6) required oxygen support and 4/19 (21.1%, 95% CI 6.1–45.6) were admitted to a critical care unit. Two women with COVID-19 breastfed without a mask because infection was diagnosed in the postpartum period: their newborns tested positive for SARS-Cov-2 infection. In one case, a newborn had a positive test after a vaginal operative delivery. Conclusions: Although postpartum infection cannot be excluded with 100% certainty, these findings suggest that vaginal delivery is associated with a low risk of intrapartum SARS-Cov-2 transmission to the newborn. Tweetable abstract: This study suggests that vaginal delivery may be associated with a low risk of intrapartum SARS-Cov-2 transmission to the newborn