Machine learning classification reveals robust morphometric biomarker of glial and neuronal arbors.

Neurons and glia are the two main cell classes in the nervous systems of most animals. Although functionally distinct, neurons and glia are both characterized by multiple branching arbors stemming from the cell bodies. Glial processes are generally known to form smaller trees than neuronal dendrites. However, the full extent of morphological differences between neurons and glia in multiple species and brain regions has not yet been characterized, nor is it known whether these cells can be reliably distinguished based on geometric features alone. Here, we show that multiple supervised learning algorithms deployed on a large database of morphological reconstructions can systematically classify neuronal and glial arbors with nearly perfect accuracy and precision. Moreover, we report multiple morphometric properties, both size related and size independent, that differ substantially between these cell types. In particular, we newly identify an individual morphometric measurement, Average Branch Euclidean Length that can robustly separate neurons from glia across multiple animal models, a broad diversity of experimental conditions, and anatomical areas, with the notable exception of the cerebellum. We discuss the practical utility and physiological interpretation of this discovery.

A randomized controlled behavioral intervention trial to improve medication adherence in adult stroke patients with prescription tailored Short Messaging Service (SMS)-SMS4Stroke study.

BACKGROUND: The effectiveness of mobile technology to improve medication adherence via customized Short Messaging Service (SMS) reminders for stroke has not been tested in resource poor areas. We designed a randomized controlled trial to test the effectiveness of SMS on improving medication adherence in stroke survivors in Pakistan. METHODS: This was a parallel group, assessor-blinded, randomized, controlled, superiority trial. Participants were centrally randomized in fixed block sizes. Adult participants on multiple medications with access to a cell phone and stroke at least 4 weeks from onset (Onset as defined by last seen normal) were eligible. The intervention group, in addition to usual care, received reminder SMS for 2 months that contained a) Personalized, prescription tailored daily medication reminder(s) b) Twice weekly health information SMS. The Health Belief Model and Social Cognitive theory were used to design the language and content of messages. Frontline SMS software was used for SMS delivery. Medication adherence was self-reported and measured on the validated Urdu version of Morisky Medication Adherence Questionnaire. Multiple linear regression was used to model the outcome against intervention and other covariates. Analysis was conducted by intention-to-treat principle. RESULTS: Two hundred participants were enrolled. 38 participants were lost to follow-up. After 2 months, the mean medication score was 7.4 (95 % CI: 7.2-7.6) in the intervention group while 6.7 (95 % CI: 6.4-7.02) in the control group. The adjusted mean difference (Δ) was 0.54 (95 % CI: 0.22-0.85). The mean diastolic blood pressure in the intervention group was 2.6 mmHg (95 % CI; -5.5 to 0.15) lower compared to the usual care group. CONCLUSION: A short intervention of customized SMS can improve medication adherence and effect stroke risk factors like diastolic blood pressure in stroke survivors with complex medication regimens living in resource poor areas. TRIAL REGISTRATION: Clinicaltrials.gov NCT01986023 last accessed at https://clinicaltrials.gov/ct2/show/NCT01986023.

Gossamer: Scaling Image Processing and Reconstruction to Whole Brains.

Neuronal reconstruction-a process that transforms image volumes into 3D geometries and skeletons of cells- bottlenecks the study of brain function, connectomics and pathology. Domain scientists need exact and complete segmentations to study subtle topological differences. Existing methods are diskbound, dense-access, coupled, single-threaded, algorithmically unscalable and require manual cropping of small windows and proofreading of skeletons due to low topological accuracy. Designing a data-intensive parallel solution suited to a neurons' shape, topology and far-ranging connectivity is particularly challenging due to I/O and load-balance, yet by abstracting these vision tasks into strategically ordered specializations of search, we progressively lower memory by 4 orders of magnitude. This enables 1 mouse brain to be fully processed in-memory on a single server, at 67× the scale with 870× less memory while having 78% higher automated yield than APP2, the previous state of the art in performant reconstruction.

Efficient metadata mining of web-accessible neural morphologies.

Advancements in neuroscience research have led to steadily accelerating data production and sharing. The online community repository of neural reconstructions NeuroMorpho.Org grew from fewer than 1000 digitally traced neurons in 2006 to more than 140,000 cells today, including glia that now constitute 10.1% of the content. Every reconstruction consists of a detailed 3D representation of branch geometry and connectivity in a standardized format, from which a collection of morphometric features is extracted and stored. Moreover, each entry in the database is accompanied by rich metadata annotation describing the animal subject, anatomy, and experimental details. The rapid expansion of this resource in the past decade was accompanied by a parallel rise in the complexity of the available information, creating both opportunities and challenges for knowledge mining. Here, we introduce a new summary reporting functionality, allowing NeuroMorpho.Org users to efficiently download digests of metadata and morphometrics from multiple groups of similar cells for further analysis. We demonstrate the capabilities of the tool for both glia and neurons and present an illustrative statistical analysis of the resulting data.

Large scale similarity search across digital reconstructions of neural morphology.

Most functions of the nervous system depend on neuronal and glial morphology. Continuous advances in microscopic imaging and tracing software have provided an increasingly abundant availability of 3D reconstructions of arborizing dendrites, axons, and processes, allowing their detailed study. However, efficient, large-scale methods to rank neural morphologies by similarity to an archetype are still lacking. Using the NeuroMorpho.Org database, we present a similarity search software enabling fast morphological comparison of hundreds of thousands of neural reconstructions from any species, brain regions, cell types, and preparation protocols. We compared the performance of different morphological measurements: 1) summary morphometrics calculated by L-Measure, 2) persistence vectors, a vectorized descriptor of branching structure, 3) the combination of the two. In all cases, we also investigated the impact of applying dimensionality reduction using principal component analysis (PCA). We assessed qualitative performance by gauging the ability to rank neurons in order of visual similarity. Moreover, we quantified information content by examining explained variance and benchmarked the ability to identify occasional duplicate reconstructions of the same specimen. We also compared two different methods for selecting the number of principal components using this benchmark. The results indicate that combining summary morphometrics and persistence vectors with applied PCA using maximum likelihood based automatic dimensionality selection provides an information rich characterization that enables efficient and precise comparison of neural morphology. We have deployed the similarity search as open-source online software both through a user-friendly graphical interface and as an API for programmatic access.

An open-source framework for neuroscience metadata management applied to digital reconstructions of neuronal morphology.

Research advancements in neuroscience entail the production of a substantial amount of data requiring interpretation, analysis, and integration. The complexity and diversity of neuroscience data necessitate the development of specialized databases and associated standards and protocols. NeuroMorpho.Org is an online repository of over one hundred thousand digitally reconstructed neurons and glia shared by hundreds of laboratories worldwide. Every entry of this public resource is associated with essential metadata describing animal species, anatomical region, cell type, experimental condition, and additional information relevant to contextualize the morphological content. Until recently, the lack of a user-friendly, structured metadata annotation system relying on standardized terminologies constituted a major hindrance in this effort, limiting the data release pace. Over the past 2 years, we have transitioned the original spreadsheet-based metadata annotation system of NeuroMorpho.Org to a custom-developed, robust, web-based framework for extracting, structuring, and managing neuroscience information. Here we release the metadata portal publicly and explain its functionality to enable usage by data contributors. This framework facilitates metadata annotation, improves terminology management, and accelerates data sharing. Moreover, its open-source development provides the opportunity of adapting and extending the code base to other related research projects with similar requirements. This metadata portal is a beneficial web companion to NeuroMorpho.Org which saves time, reduces errors, and aims to minimize the barrier for direct knowledge sharing by domain experts. The underlying framework can be progressively augmented with the integration of increasingly autonomous machine intelligence components.

Effect of 5-Minute Movies Shown via a Mobile Phone App on Risk Factors and Mortality After Stroke in a Low- to Middle-Income Country: Randomized Controlled Trial for the Stroke Caregiver Dyad Education Intervention (Movies4Stroke).

BACKGROUND: Pakistan is the sixth most populous nation in the world and has an estimated 4 million stroke survivors. Most survivors are taken care of by community-based caregivers, and there are no inpatient rehabilitation facilities. OBJECTIVE: The objective of this study was to evaluate the effectiveness and safety of locally designed 5-min movies rolled out in order of relevance that are thematically delivered in a 3-month program to deliver poststroke education to stroke survivor and caregiver dyads returning to the community. METHODS: This study was a randomized controlled, outcome assessor-blinded, parallel group, single-center superiority trial in which participants (stroke survivor-caregiver dyads) with first-ever stroke (both ischemic and hemorrhagic) incidence were randomized within 48 hours of their stroke into either the video-based education intervention group or the control group. The video-based education intervention group had health education delivered through short videos that were shown to the participants and their caregivers at the time of admission, before discharge, and the first and third months of follow-up after discharge. The control group had standardized care including predischarge education and counseling according to defined protocols. All participants enrolled in the video education intervention and control groups were followed for 12 months after discharge for outcome assessment in the outpatient stroke clinics. The primary outcome measures were the proportion of participants achieving control of blood pressure, blood sugar, and blood cholesterol in the video intervention versus the control group. Several predefined secondary outcomes were included in this study, of which we report the mortality and functional disability in this paper. Analysis was by performed using the intention-to-treat principle. RESULTS: A total of 310 stroke survivors and their caregiver dyads (participant dyads) were recruited over a duration of 6 months. In total, 155 participant dyads were randomized into the intervention and control groups, each. The primary outcome of control of three major risk factors revealed that at 12 months, there was a greater percentage of participants with a systolic BP<125 mm Hg (18/54, 33% vs 11/52, 21%; P=.16), diastolic BP<85 mm Hg (44/54, 81% vs 37/52, 71%; P=.21), HbA1c level<7% (36/55, 65% vs 30/40, 75%; P=.32), and low-density lipoprotein level<100 mg/dL (36/51, 70% vs 30/45, 67%; P=.68) in the intervention group than in the control group. The secondary outcome reported is the mortality among the stroke survivors because the number of stroke-related complications was higher in the control group than in the intervention group (13/155, 8.4% vs 2/155, 1.3%), and this difference was statistically significant (P<.001). CONCLUSIONS: The Movies4Stroke trial failed to achieve its primary specified outcome. However, secondary outcomes that directly related to survival skills of stroke survivors demonstrated the effectiveness of the video-based intervention on improving stroke-related mortality and survival without disability. TRIAL REGISTRATION: ClinicalTrials.gov NCT02202330; https://www.clinicaltrials.gov/ct2/show/NCT02202330.

Genetic Single Neuron Anatomy Reveals Fine Granularity of Cortical Axo-Axonic Cells.

Parsing diverse nerve cells into biological types is necessary for understanding neural circuit organization. Morphology is an intuitive criterion for neuronal classification and a proxy of connectivity, but morphological diversity and variability often preclude resolving the granularity of neuron types. Combining genetic labeling with high-resolution, large-volume light microscopy, we established a single neuron anatomy platform that resolves, registers, and quantifies complete neuron morphologies in the mouse brain. We discovered that cortical axo-axonic cells (AACs), a cardinal GABAergic interneuron type that controls pyramidal neuron (PyN) spiking at axon initial segments, consist of multiple subtypes distinguished by highly laminar-specific soma position and dendritic and axonal arborization patterns. Whereas the laminar arrangements of AAC dendrites reflect differential recruitment by input streams, the laminar distribution and local geometry of AAC axons enable differential innervation of PyN ensembles. This platform will facilitate genetically targeted, high-resolution, and scalable single neuron anatomy in the mouse brain.

An open repository for single-cell reconstructions of the brain forest.

NeuroMorpho.Org was launched in 2006 to provide unhindered access to any and all digital tracings of neuronal morphology that researchers were willing to share freely upon request. Today this database is the largest public inventory of cellular reconstructions in neuroscience with a content of over 80,000 neurons and glia from a representative diversity of animal species, anatomical regions, and experimental methods. Datasets continuously contributed by hundreds of laboratories worldwide are centrally curated, converted into a common non-proprietary format, morphometrically quantified, and annotated with comprehensive metadata. Users download digital reconstructions for a variety of scientific applications including visualization, classification, analysis, and simulations. With more than 1,000 peer-reviewed publications describing data stored in or utilizing data retrieved from NeuroMorpho.Org, this ever-growing repository can already be considered a mature resource for neuroscience.