An efficient and scalable data analysis solution for automated electrophysiology platforms.

Ion channels are drug targets for neurologic, cardiac, and immunologic diseases. Many disease-associated mutations and drugs modulate voltage-gated ion channel activation and inactivation, suggesting that characterizing state-dependent effects of test compounds at an early stage of drug development can be of great benefit. Historically, the effects of compounds on ion channel biophysical properties and voltage-dependent activation/inactivation could only be assessed by using low-throughput, manual patch clamp recording techniques. In recent years, automated patch clamp (APC) platforms have drastically increased in throughput. In contrast to their broad utilization in compound screening, APC platforms have rarely been used for mechanism of action studies, in large part due to the lack of sophisticated, scalable analysis methods for processing the large amount of data generated by APC platforms. In the current study, we developed a highly efficient and scalable software workflow to overcome this challenge. This method, to our knowledge the first of its kind, enables automated curve fitting and complex analysis of compound effects. Using voltage-gated sodium channels as an example, we were able to immediately assess the effects of test compounds on a spectrum of biophysical properties, including peak current, voltage-dependent steady state activation/inactivation, and time constants of activation and fast inactivation. Overall, this automated data analysis method provides a novel solution for in-depth analysis of large-scale APC data, and thus will significantly impact ion channel research and drug discovery.

Deep Learning-Based HCS Image Analysis for the Enterprise.

Drug discovery programs are moving increasingly toward phenotypic imaging assays to model disease-relevant pathways and phenotypes in vitro. These assays offer richer information than target-optimized assays by investigating multiple cellular pathways simultaneously and producing multiplexed readouts. However, extracting the desired information from complex image data poses significant challenges, preventing broad adoption of more sophisticated phenotypic assays. Deep learning-based image analysis can address these challenges by reducing the effort required to analyze large volumes of complex image data at a quality and speed adequate for routine phenotypic screening in pharmaceutical research. However, while general purpose deep learning frameworks are readily available, they are not readily applicable to images from automated microscopy. During the past 3 years, we have optimized deep learning networks for this type of data and validated the approach across diverse assays with several industry partners. From this work, we have extracted five essential design principles that we believe should guide deep learning-based analysis of high-content images and multiparameter data: (1) insightful data representation, (2) automation of training, (3) multilevel quality control, (4) knowledge embedding and transfer to new assays, and (5) enterprise integration. We report a new deep learning-based software that embodies these principles, Genedata Imagence, which allows screening scientists to reliably detect stable endpoints for primary drug response, assess toxicity and safety-relevant effects, and discover new phenotypes and compound classes. Furthermore, we show how the software retains expert knowledge from its training on a particular assay and successfully reapplies it to different, novel assays in an automated fashion.

Genome-Wide Analysis of Differential Gene Expression and Splicing in Excitatory Neurons and Interneuron Subtypes.

Cortical circuit activity is shaped by the parvalbumin (PV) and somatostatin (SST) interneurons that inhibit principal excitatory (EXC) neurons and the vasoactive intestinal peptide (VIP) interneurons that suppress activation of other interneurons. To understand the molecular-genetic basis of functional specialization and identify potential drug targets specific to each neuron subtype, we performed a genome wide assessment of both gene expression and splicing across EXC, PV, SST and VIP neurons from male and female mouse brains. These results reveal numerous examples where neuron subtype-specific gene expression, as well as splice-isoform usage, can explain functional differences between neuron subtypes, including in presynaptic plasticity, postsynaptic receptor function, and synaptic connectivity specification. We provide a searchable web resource for exploring differential mRNA expression and splice form usage between excitatory, PV, SST, and VIP neurons (http://research-pub.gene.com/NeuronSubtypeTranscriptomes). This resource, combining a unique new dataset and novel application of analysis methods to multiple relevant datasets, identifies numerous potential drug targets for manipulating circuit function, reveals neuron subtype-specific roles for disease-linked genes, and is useful for understanding gene expression changes observed in human patient brains.SIGNIFICANCE STATEMENT Understanding the basis of functional specialization of neuron subtypes and identifying drug targets for manipulating circuit function requires comprehensive information on cell-type-specific transcriptional profiles. We sorted excitatory neurons and key inhibitory neuron subtypes from mouse brains and assessed differential mRNA expression. We used a genome-wide analysis which not only examined differential gene expression levels but could also detect differences in splice isoform usage. This analysis reveals numerous examples of neuron subtype-specific isoform usage with functional importance, identifies potential drug targets, and provides insight into the neuron subtypes involved in psychiatric disease. We also apply our analysis to two other relevant datasets for comparison, and provide a searchable website for convenient access to the resource.

The factors that lead to a delay between general practitioner referral of symptomatic patients and specialist diagnosis of colorectal cancer: an audit in the Bay of Plenty District Health Board.

AIM: To determine factors leading to delay between referral by the GP of symptomatic patients and subsequent specialist diagnosis of colon or rectum cancer (CRC). METHOD: A retrospective audit of patients with new CRC referred by their GP over a 30-month period to the specialist services. Analysis of referral letters, specialist grading and subsequent results of investigations. We focused on the High Index of Suspicion (HIS) criteria for suspected CRC. RESULTS: Only 65 out of 181 patients fulfilled the HIS criteria and of these only half were correctly identified in the referral letter. Only 48 who fulfilled HIS criteria were graded as urgent by the specialist and had their fast-track diagnostic test within a median of 21 days (5-114). The remaining 133 waited a median of 67 days (10-387) (p<0.001). The diagnosis was reached faster if the patient went straight to colonoscopy rather than initial outpatient assessment: median 32 versus 81 days (p=0.008). CONCLUSION: The HIS Urgent pathway only identified a third of patients and so the criteria should be reviewed. GPs frequently failed to recognise and refer those who met the criteria. A standardised referral form prompting the inclusion of all required information would improve this.

A metaplasticity view of the interaction between homeostatic and Hebbian plasticity.

Hebbian and homeostatic plasticity are two major forms of plasticity in the nervous system: Hebbian plasticity provides a synaptic basis for associative learning, whereas homeostatic plasticity serves to stabilize network activity. While achieving seemingly very different goals, these two types of plasticity interact functionally through overlapping elements in their respective mechanisms. Here, we review studies conducted in the mammalian central nervous system, summarize known circuit and molecular mechanisms of homeostatic plasticity, and compare these mechanisms with those that mediate Hebbian plasticity. We end with a discussion of 'local' homeostatic plasticity and the potential role of local homeostatic plasticity as a form of metaplasticity that modulates a neuron's future capacity for Hebbian plasticity.This article is part of the themed issue 'Integrating Hebbian and homeostatic plasticity'.

Outcome of long interval radiological surveillance of side branch pancreatic duct-involved intraductal papillary mucinous neoplasm in selected patients.

INTRODUCTION: Side branch IPMN (SB-IPMN) of the pancreas has a malignancy rate between 10 and 20%. We hypothesized that surveillance at longer intervals on selected patients with SB-IPMN might be indicated. METHODS: This is a retrospective study of prospectively collected data of 276 patients presenting from 2000 to 2010. After 2007, we opted to screen our patients with longer intervals, initially at 12 months then 24 months using MR if no "worrisome features" were present. RESULTS: Complete data sets for 261 patients were analysed and patients were aged 78 (40-91) years. 232 patients had sole SB-IPMN while 92% were incidental (n = 209) and 8% were symptomatic (n = 24). Single SB-IPMN accounted for 84% (n = 195) of all cases; maximum diameter of 15.5 (5-60) mm. The median follow up duration was 46 (32-53) months. Short interval radiological surveillance (3-9 months) was 39% (n = 90), while long interval surveillance (12-36 months) was performed in 61% (n = 142). The rate of pancreatic resection, due to concern for the development of pancreatic cancer, in the short and long interval surveillance groups was 4.4% (n = 4) and 3.5% (n = 5) respectively; p = 0.78. CONCLUSION: Our data suggests no difference in outcome between long and short interval MR surveillance of SB-IPMN patients.

Differential regulation of spontaneous and evoked inhibitory synaptic transmission in somatosensory cortex by retinoic acid.

Retinoic acid (RA), a developmental morphogen, has emerged in recent studies as a novel synaptic signaling molecule that acts in mature hippocampal neurons to modulate excitatory and inhibitory synaptic transmission in the context of homeostatic synaptic plasticity. However, it is unclear whether RA is capable of modulating neural circuits outside of the hippocampus, and if so, whether the mode of RA's action at synapses is similar to that within the hippocampal network. Here we explore for the first time RA's synaptic function outside the hippocampus and uncover a novel function of all-trans retinoic acid at inhibitory synapses. Acute RA treatment increases spontaneous inhibitory synaptic transmission in L2/3 pyramidal neurons of the somatosensory cortex, and this effect requires expression of RA's receptor RARα both pre- and post-synaptically. Intriguingly, RA does not seem to affect evoked inhibitory transmission assayed with either extracellular stimulation or direct activation of action potentials in presynaptic interneurons at connected pairs of interneurons and pyramidal neurons. Taken together, these results suggest that RA's action at synapses is not monotonous, but is diverse depending on the type of synaptic connection (excitatory versus inhibitory) and circuit (hippocampal versus cortical). Thus, synaptic signaling of RA may mediate multi-faceted regulation of synaptic plasticity. In addition to its classic roles in brain development, retinoic acid (RA) has recently been shown to regulate excitatory and inhibitory transmission in the adult brain. Here, the authors show that in layer 2/3 (L2/3) of the somatosensory cortex (S1), acute RA induces increases in spontaneous but not action-potential evoked transmission, and that this requires retinoic acid receptor (RARα) both in presynaptic PV-positive interneurons and postsynaptic pyramidal (PN) neurons.

ß-Neurexins Control Neural Circuits by Regulating Synaptic Endocannabinoid Signaling.

α- and ß-neurexins are presynaptic cell-adhesion molecules implicated in autism and schizophrenia. We find that, although ß-neurexins are expressed at much lower levels than α-neurexins, conditional knockout of ß-neurexins with continued expression of α-neurexins dramatically decreased neurotransmitter release at excitatory synapses in cultured cortical neurons. The ß-neurexin knockout phenotype was attenuated by CB1-receptor inhibition, which blocks presynaptic endocannabinoid signaling, or by 2-arachidonoylglycerol synthesis inhibition, which impairs postsynaptic endocannabinoid release. In synapses formed by CA1-region pyramidal neurons onto burst-firing subiculum neurons, presynaptic in vivo knockout of ß-neurexins aggravated endocannabinoid-mediated inhibition of synaptic transmission and blocked LTP; presynaptic CB1-receptor antagonists or postsynaptic 2-arachidonoylglycerol synthesis inhibition again reversed this block. Moreover, conditional knockout of ß-neurexins in CA1-region neurons impaired contextual fear memories. Thus, our data suggest that presynaptic ß-neurexins control synaptic strength in excitatory synapses by regulating postsynaptic 2-arachidonoylglycerol synthesis, revealing an unexpected role for ß-neurexins in the endocannabinoid-dependent regulation of neural circuits.

Accelerated experience-dependent pruning of cortical synapses in ephrin-A2 knockout mice.

Refinement of mammalian neural circuits involves substantial experience-dependent synapse elimination. Using in vivo two-photon imaging, we found that experience-dependent elimination of postsynaptic dendritic spines in the cortex was accelerated in ephrin-A2 knockout (KO) mice, resulting in fewer adolescent spines integrated into adult circuits. Such increased spine removal in ephrin-A2 KOs depended on activation of glutamate receptors, as blockade of the N-methyl-D-aspartate (NMDA) receptors eliminated the difference in spine loss between wild-type and KO mice. We also showed that ephrin-A2 in the cortex colocalized with glial glutamate transporters, which were significantly downregulated in ephrin-A2 KOs. Consistently, glial glutamate transport was reduced in ephrin-A2 KOs, resulting in an accumulation of synaptic glutamate. Finally, inhibition of glial glutamate uptake promoted spine elimination in wild-type mice, resembling the phenotype of ephrin-A2 KOs. Together, our results suggest that ephrin-A2 regulates experience-dependent, NMDA receptor-mediated synaptic pruning through glial glutamate transport during maturation of the mouse cortex.

Nanofluidic proteomic assay for serial analysis of oncoprotein activation in clinical specimens.

Current methods of protein detection are insensitive to detecting subtle changes in oncoprotein activation that underlie key cancer signaling processes. The requirement for large numbers of cells precludes serial tumor sampling for assessing a response to therapeutics. Therefore, we have developed a nanofluidic proteomic immunoassay (NIA) to quantify total and low-abundance protein isoforms in nanoliter volumes. Our method can quantify amounts of MYC oncoprotein and B cell lymphoma protein-2 (BCL2) in Burkitt's and follicular lymphoma; identify changes in activation of extracellular signal-related kinases-1 (ERK1) and ERK2, mitogen-activated kinase-1 (MEK), signal transducer and activator of transcription protein-3 (STAT3) and STAT5, c-Jun N-terminal kinase (JNK) and caspase-3 in imatinib-treated chronic myelogeneous leukemia (CML) cells; measure an unanticipated change in the phosphorylation of an ERK2 isomer in individuals with CML who responded to imatinib; and detect a decrease in STAT3 and STAT5 phosphorylation in individuals with lymphoma who were treated with atorvastatin. Therefore, we have described a new and highly sensitive method for determining oncoprotein expression and phosphorylation in clinical specimens for the development of new therapeutics for cancer.