(E)-2,3-Bis[(E)-benzyl­idene­amino]­but-2-enedinitrile

The asymmetric unit of the title compound, C18H12N4, consists of a half-mol­ecule, where the two halves of the mol­ecule are related by inversion symmetry. The mol­ecule is effectively planar, with the largest deviation from the 22-atom mean plane, measuring 0.024 (2) Å, exhibited by the ortho-C atom of the phenyl ring. The crystal structure exhibits π-stacking, with an inter­planar spacing of 3.431 (3) Å

Genetically encoded proton sensors reveal activity-dependent pH changes in neurons

The regulation of hydrogen ion concentration (pH) is fundamental to cell viability, metabolism, and enzymatic function. Within the nervous system, the control of pH is also involved in diverse and dynamic processes including development, synaptic transmission, and the control of network excitability. As pH affects neuronal activity, and can also itself be altered by neuronal activity, the existence of tools to accurately measure hydrogen ion fluctuations is important for understanding the role pH plays under physiological and pathological conditions. Outside of their use as a marker of synaptic release, genetically encoded pH sensors have not been utilized to study hydrogen ion fluxes associated with network activity. By combining whole-cell patch clamp with simultaneous two-photon or confocal imaging, we quantified the amplitude and time course of neuronal, intracellular, acidic transients evoked by epileptiform activity in two separate in vitro models of temporal lobe epilepsy. In doing so, we demonstrate the suitability of three genetically encoded pH sensors: deGFP4, E2GFP, and Cl-sensor for investigating activity-dependent pH changes at the level of single neurons

Pro-maturational effects of human iPSC-derived cortical astrocytes upon iPSC-derived cortical neurons

Astrocytes influence neuronal maturation and function by providing trophic support, regulating the extracellular environment, andmodulating signaling at synapses. The emergence of induced pluripotent stem cell (iPSC) technology offers a human system with whichto validate and re-evaluate insights from animal studies. Here, we set out to examine interactions between human astrocytes and neuronsderived from a common cortical progenitor pool, thereby recapitulating aspects ofin vivocortical development. We show that the corticaliPSC-derived astrocytesexhibit many of the molecular and functional hallmarks of astrocytes. Furthermore, optogenetic and electrophys-iological co-culture experiments reveal that the iPSC-astrocytes can actively modulate ongoing synaptic transmission and exertpro-maturational effects upon developing networks of iPSC-derived cortical neurons. Finally, transcriptomic analyses implicate syn-apse-associated extracellular signaling in the astrocytes’ pro-maturational effects upon the iPSC-derived neurons. This work helps laythe foundation for future investigations into astrocyte-to-neuron interactions in human health and disease

Did we do everything we could have? Nurses’ contributions to medicines optimisation: a mixed method study

Aim To explore UK professionals’ interpretations of medicines optimization and expansion of nurses’ roles. Design This mixed‐methods study sought professionals’ views on nurses’ involvement, competency and engagement in monitoring patients for adverse effects of medicines, monitoring adherence, prescribing and patient education. Method An online survey and interviews were undertaken with nurses, doctors and pharmacists in Wales and England, May 2018 to July 2019. Results In all, 220 nurses, 17 doctors and 62 pharmacists responded to the online survey, and 24 professionals were interviewed. Nurses were divided over extending their roles, with 123/220 (55.9%) wishing to extend roles in monitoring patients for possible adverse drug reactions (ADRs), 111/220 (50.5%) in adherence monitoring, 121/220 (55.0%) in prescribing and 122/220 (55.4%) in patient education. The best‐qualified nurses were the most willing to increase involvement in monitoring patients for ADRs (aOR 13.00, 1.56–108.01). Interviews revealed that both nurses and doctors assumed the other profession was undertaking this monitoring. Respondents agreed that increasing nurses’ involvement in medicines optimization would improve patient care, but expressed reservations about nurses’ competencies. Collaboration between nurses and doctors was suboptimal (rated 7/10 at best) and between nurses and pharmacists even more so (6/10 at best). Conclusion Juxtaposition of datasets identified problems with medicines optimization: although most respondents agreed that increasing nurses’ involvement would positively impact practice, their educational preparation was a barrier. Only ~50% of nurses were willing to expand their roles to fill the hiatus in care identified and ensure that at least one profession was taking responsibility for ADR monitoring. Impact To improve multiprofessional team working and promote patient safety, nurse leaders should ensure patients are monitored for possible ADRs by at least one profession. Initiatives expanding nurses’ roles in medicines optimization and prescribing might be best targeted towards the more educated nurses, who have multidisciplinary support

sUPRa is a dual-color reporter for unbiased quantification of the unfolded protein response with cellular resolution

The unfolded protein response (UPR) maintains proteostasis upon endoplasmic reticulum (ER) stress, and is initiated by a range of physiological and pathological processes. While there have been advances in developing fluorescent reporters for monitoring individual signaling pathways of the UPR, this approach may not capture a cell’s overall UPR activity. Here we describe a novel sensor of UPR activity, sUPRa, which is designed to report the global UPR. sUPRa displays excellent response characteristics, outperforms reporters of individual UPR pathways in terms of sensitivity and kinetics, and responds to a range of different ER stress stimuli. Furthermore, sUPRa’s dual promoter and fluorescent protein design ensures that both UPR-active and inactive cells are detected, and controls for reporter copy number. Using sUPRa, we reveal UPR activation in layer 2/3 pyramidal neurons of mouse cerebral cortex following a period of sleep deprivation. sUPRa affords new opportunities for quantifying physiological UPR activity with cellular resolution

Somnotate: a probabilistic sleep stage classifier for studying vigilance state transitions

Electrophysiological recordings from freely behaving animals are a widespread and powerful mode of investigation in sleep research. These recordings generate large amounts of data that require sleep stage annotation (polysomnography), in which the data is parcellated according to three vigilance states: awake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep. Manual and current computational annotation methods ignore intermediate states because the classification features become ambiguous, even though intermediate states contain important information regarding vigilance state dynamics. To address this problem, we have developed "Somnotate"—a probabilistic classifier based on a combination of linear discriminant analysis (LDA) with a hidden Markov model (HMM). First we demonstrate that Somnotate sets new standards in polysomnography, exhibiting annotation accuracies that exceed human experts on mouse electrophysiological data, remarkable robustness to errors in the training data, compatibility with different recording configurations, and an ability to maintain high accuracy during experimental interventions. However, the key feature of Somnotate is that it quantifies and reports the certainty of its annotations. We leverage this feature to reveal that many intermediate vigilance states cluster around state transitions, whereas others correspond to failed attempts to transition. This enables us to show for the first time that the success rates of different types of transition are differentially affected by experimental manipulations and can explain previously observed sleep patterns. Somnotate is open-source and has the potential to both facilitate the study of sleep stage transitions and offer new insights into the mechanisms underlying sleep-wake dynamics

Targeted single-cell RNA sequencing of transcription factors facilitates biological insights from human cell experimental models

Single-cell RNA sequencing (scRNA-seq) is a widely used method for identifying cell types and trajectories in biologically heterogeneous samples, but it is limited in its detection and quantification of lowly expressed genes. This results in missing important biological signals, such as the expression of key transcription factors (TFs) driving cellular differentiation. We show that targeted sequencing of ∼1000 TFs (scCapture-seq) in iPSC-derived neuronal cultures greatly improves the biological information garnered from scRNA-seq. Increased TF resolution enhanced cell type identification, developmental trajectories, and gene regulatory networks. This allowed us to resolve differences among neuronal populations, which were generated in two different laboratories using the same differentiation protocol. ScCapture-seq improved TF-gene regulatory network inference and thus identified divergent patterns of neurogenesis into either excitatory cortical neurons or inhibitory interneurons. Furthermore, scCapture-seq revealed a role for of retinoic acid signaling in the developmental divergence between these different neuronal populations. Our results show that TF targeting improves the characterization of human cellular models and allows identification of the essential differences between cellular populations, which would otherwise be missed in traditional scRNA-seq. scCapture-seq TF targeting represents a cost-effective enhancement of scRNA-seq, which could be broadly applied to improve scRNA-seq resolution

Targeted single-cell RNA sequencing of transcription factors facilitates biological insights from human cell experimental models

Single-cell RNA sequencing (scRNA-seq) is a widely used method for identifying cell types and trajectories in biologically heterogeneous samples, but it is limited in its detection and quantification of lowly expressed genes. This results in missing important biological signals, such as the expression of key transcription factors (TFs) driving cellular differentiation. We show that targeted sequencing of ∼1000 TFs (scCapture-seq) in iPSC-derived neuronal cultures greatly improves the biological information garnered from scRNA-seq. Increased TF resolution enhanced cell type identification, developmental trajectories, and gene regulatory networks. This allowed us to resolve differences among neuronal populations, which were generated in two different laboratories using the same differentiation protocol. ScCapture-seq improved TF-gene regulatory network inference and thus identified divergent patterns of neurogenesis into either excitatory cortical neurons or inhibitory interneurons. Furthermore, scCapture-seq revealed a role for of retinoic acid signaling in the developmental divergence between these different neuronal populations. Our results show that TF targeting improves the characterization of human cellular models and allows identification of the essential differences between cellular populations, which would otherwise be missed in traditional scRNA-seq. scCapture-seq TF targeting represents a cost-effective enhancement of scRNA-seq, which could be broadly applied to improve scRNA-seq resolution

Assessing similarity to primary tissue and cortical layer identity in induced pluripotent stem cell-derived cortical neurons through single-cell transcriptomics

Induced pluripotent stem cell (iPSC)-derived cortical neurons potentially present a powerful new model to understand corticogenesis and neurological disease. Previous work has established that differentiation protocols can produce cortical neurons, but little has been done to characterize these at cellular resolution. In particular, it is unclear to what extent in vitro two-dimensional, relatively disordered culture conditions recapitulate the development of in vivo cortical layer identity. Single-cell multiplex reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) was used to interrogate the expression of genes previously implicated in cortical layer or phenotypic identity in individual cells. Totally, 93.6% of single cells derived from iPSCs expressed genes indicative of neuronal identity. High proportions of single neurons derived from iPSCs expressed glutamatergic receptors and synaptic genes. And, 68.4% of iPSC-derived neurons expressing at least one layer marker could be assigned to a laminar identity using canonical cortical layer marker genes. We compared single-cell RNA-seq of our iPSC-derived neurons to available single-cell RNA-seq data from human fetal and adult brain and found that iPSC-derived cortical neurons closely resembled primary fetal brain cells. Unexpectedly, a subpopulation of iPSC-derived neurons co-expressed canonical fetal deep and upper cortical layer markers. However, this appeared to be concordant with data from primary cells. Our results therefore provide reassurance that iPSC-derived cortical neurons are highly similar to primary cortical neurons at the level of single cells but suggest that current layer markers, although effective, may not be able to disambiguate cortical layer identity in all cells

Differential Expression of VEGFA Isoforms Regulates Metastasis and Response to Anti-VEGFA Therapy in Sarcoma

Elevated plasma concentrations of soluble VEGFA isoforms are associated with poor prognosis in parallel with improved response to treatment with the anti-VEGFA antibody bevacizumab. To uncover the underlying mechanism to these observations, we administered anti-VEGFA therapy to mice bearing luminescent mouse fibrosarcomas expressing single VEGFA isoforms or their wild-type counterparts expressing all isoforms (fs120, fs164, fs188, or fsWT). Expression of the more soluble isoforms conferred an advantage for lung metastasis from subcutaneous tumors (fs120/164 vs. fs188/WT); fs120 cells also produced more lung colonies than fs188 cells when injected intravenously. Metastasis from subcutaneous fs120 tumors was more sensitive than fs188 to treatment with the anti-VEGFA antibody B20-4.1.1. Despite elevated plasma levels of VEGFA in fs120 tumor-bearing mice and a dependence on VEGF receptor 1 activity for metastasis to the lung, B20-4.1.1 did not affect survival in the lung on intravenous injection. B20-4.1.1 inhibited subcutaneous tumor growth and decreased vascular density in both fs120 and fs188 tumors. However, migration of fs120, but not fs188 cells, in vitro was inhibited by B20-4.1.1. The greater survival of fs120 cells in the lung was associated with VEGFR1-dependent accumulation of CD11b-positive myeloid cells and higher expression of the VEGFR1 ligand, PlGF2, by the fs120 cells in vitro and in the plasma and lungs of fs120 tumor-bearing mice. We conclude that soluble VEGFA isoform expression increases fibrosarcoma metastasis through multiple mechanisms that vary in their sensitivity to anti-VEGF/VEGFR inhibition, with VEGFA-targeted therapy suppressing metastasis through effects on the primary tumor rather than the metastatic site