The early and accurate differential diagnosis of parkinsonian disorders is still a significant challenge for clinicians. In recent years, a number of studies have used magnetic resonance imaging data combined with machine learning and statistical classifiers to successfully differentiate between different forms of Parkinsonism. However, several questions and methodological issues remain, to minimize bias and artefact-driven classification. In this study, we compared different approaches for feature selection, as well as different magnetic resonance imaging modalities, with well-matched patient groups and tightly controlling for data quality issues related to patient motion. Our sample was drawn from a cohort of 69 healthy controls, and patients with idiopathic Parkinson's disease (= 35), progressive supranuclear palsy Richardson's syndrome (= 52) and corticobasal syndrome (= 36). Participants underwent standardized T1-weighted and diffusion-weighted magnetic resonance imaging. Strict data quality control and group matching reduced the control and patient numbers to 43, 32, 33 and 26, respectively. We compared two different methods for feature selection and dimensionality reduction: whole-brain principal components analysis, and an anatomical region-of-interest based approach. In both cases, support vector machines were used to construct a statistical model for pairwise classification of healthy controls and patients. The accuracy of each model was estimated using a leave-two-out cross-validation approach, as well as an independent validation using a different set of subjects. Our cross-validation results suggest that using principal components analysis for feature extraction provides higher classification accuracies when compared to a region-of-interest based approach. However, the differences between the two feature extraction methods were significantly reduced when an independent sample was used for validation, suggesting that the principal components analysis approach may be more vulnerable to overfitting with cross-validation. Both T1-weighted and diffusion magnetic resonance imaging data could be used to successfully differentiate between subject groups, with neither modality outperforming the other across all pairwise comparisons in the cross-validation analysis. However, features obtained from diffusion magnetic resonance imaging data resulted in significantly higher classification accuracies when an independent validation cohort was used. Overall, our results support the use of statistical classification approaches for differential diagnosis of parkinsonian disorders. However, classification accuracy can be affected by group size, age, sex and movement artefacts. With appropriate controls and out-of-sample cross validation, diagnostic biomarker evaluation including magnetic resonance imaging based classifiers may be an important adjunct to clinical evaluation.

PURPOSE: Demonstrating multifield and inverse contrast switching of magnetocaloric high contrast ratio MRI labels that either have increasing or decreasing moment versus temperature slopes depending on the material at physiological temperatures and different MRI magnetic field strengths.

METHODS: Two iron-rhodium samples of different purity (99% and 99.9%) and a lanthanum-iron-silicon sample were obtained from commercial vendors. Temperature and magnetic field-dependent magnetic moment measurements of the samples were performed on a vibrating sample magnetometer. Temperature-dependent MRI of different iron-rhodium and lanthanum-iron-silicon samples were performed on 3 different MRI scanners at 1 Tesla (T), 4.7T, and 7T.

RESULTS: Sharp, first-order magnetic phase transition of each iron-rhodium sample at a physiologically relevant temperature (~37°C) but at different MRI magnetic fields (1T, 4.7T, and 7T, depending on the sample) showed clear image contrast changes in temperature-dependent MRI. Iron-rhodium and lanthanum-iron-silicon samples with sharp, first-order magnetic phase transitions at the same MRI field of 1T and physiological temperature of 37°C, but with positive and negative slope of magnetization versus temperature, respectively, showed clear inverse contrast image changes. Temperature-dependent MRI on individual microparticle samples of lanthanum-iron-silicon also showed sharp image contrast changes.

CONCLUSION: Magnetocaloric materials of different purity and composition were demonstrated to act as diverse high contrast ratio switchable MRI contrast agents. Thus, we show that a range of magnetocaloric materials can be optimized for unique image contrast response under MRI-appropriate conditions at physiological temperatures and be controllably switched in situ.

Extracellular vesicles (EVs) are important mediators of cell-to-cell communication and have been implicated in several pathologies including those of the central nervous system. They are released by all cell types, including neurons, and are highly heterogenous in size and composition. Yet much remains unknown regarding the biophysical characteristics of different EVs. Here, using cryo-electron microscopy (cryoEM), we analyzed the size distribution and morphology of EVs released from primary cortical neurons. We discovered massive macromolecular clusters on the luminal face of EV membranes. These clusters are predominantly found on medium-sized vesicles, suggesting that they may be specific to microvesicles as opposed to exosomes. We propose that these clusters serve as microdomains for EV signaling and play an important role in EV physiology.

A polarized arrangement of neuronal microtubule arrays is the foundation of membrane trafficking and subcellular compartmentalization. Conserved among both invertebrates and vertebrates, axons contain exclusively 'plus-end-out' microtubules while dendrites contain a high percentage of 'minus-end-out' microtubules, the origins of which have been a mystery. Here we show that in the dendritic growth cone contains a non-centrosomal microtubule organizing center, which generates minus-end-out microtubules along outgrowing dendrites and plus-end-out microtubules in the growth cone. RAB-11-positive endosomes accumulate in this region and co-migrate with the microtubule nucleation complex γ-TuRC. The MTOC tracks the extending growth cone by kinesin-1/UNC-116-mediated endosome movements on distal plus-end-out microtubules and dynein clusters this advancing MTOC. Critically, perturbation of the function or localization of the MTOC causes reversed microtubule polarity in dendrites. These findings unveil the endosome-localized dendritic MTOC as a critical organelle for establishing axon-dendrite polarity.

We engineered electrochromic fluorescence resonance energy transfer (eFRET) genetically encoded voltage indicators (GEVIs) with “positive-going” fluorescence response to membrane depolarization through rational manipulation of the native proton transport pathway in microbial rhodopsins. We transformed the state-of-the-art eFRET GEVI Voltron into Positron, with kinetics and sensitivity equivalent to Voltron but flipped fluorescence signal polarity. We further applied this general approach to GEVIs containing different voltage sensitive rhodopsin domains and various fluorescent dye and fluorescent protein reporters.

Retroviruses selectively incorporate a specific subset of host cell proteins and lipids into their outer membrane when they bud out from the host plasma membrane. This specialized viral membrane composition is critical for both viral survivability and infectivity. Here, we review recent findings from live cell imaging of single virus assembly demonstrating that proteins and lipids sort into the HIV retroviral membrane by a mechanism of lipid-based phase partitioning. The findings showed that multimerizing HIV Gag at the assembly site creates a liquid-ordered lipid phase enriched in cholesterol and sphingolipids. Proteins with affinity for this specialized lipid environment partition into it, resulting in the selective incorporation of proteins into the nascent viral membrane. Building on this and other work in the field, we propose a model describing how HIV Gag induces phase separation of the viral assembly site through a mechanism involving transbilayer coupling of lipid acyl chains and membrane curvature changes. Similar phase-partitioning pathways in response to multimerizing structural proteins likely help sort proteins into the membranes of other budding structures within cells.

Undergraduate researchers are the next-generation scientists. Here, we call for more attention from our community to the proper training of undergraduates in biomedical research laboratories. By dissecting common pitfalls, we suggest how to better mentor undergraduates and prepare them for flourishing careers.

Behavior is readily classified into patterns of movements with inferred common goals-actions. Goals may be discrete; movements are continuous. Through the careful study of isolated movements in laboratory settings, or via introspection, it has become clear that animals can exhibit exquisite graded specification to their movements. Moreover, graded control can be as fundamental to success as the selection of which action to perform under many naturalistic scenarios: a predator adjusting its speed to intercept moving prey, or a tool-user exerting the perfect amount of force to complete a delicate task. The basal ganglia are a collection of nuclei in vertebrates that extend from the forebrain (telencephalon) to the midbrain (mesencephalon), constituting a major descending extrapyramidal pathway for control over midbrain and brainstem premotor structures. Here we discuss how this pathway contributes to the continuous specification of movements that endows our voluntary actions with vigor and grace. Expected final online publication date for the , Volume 43 is July 8, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Genetically encodable calcium ion (Ca) indicators (GECIs) based on green fluorescent proteins (GFP) are powerful tools for imaging of cell signaling and neural activity in model organisms. Following almost 2 decades of steady improvements in the GFP-based GCaMP series of GECIs, the performance of the most recent generation (i.e., jGCaMP7) may have reached its practical limit due to the inherent properties of GFP. In an effort to sustain the steady progression toward ever-improved GECIs, we undertook the development of a new GECI based on the bright monomeric GFP, mNeonGreen (mNG). The resulting indicator, mNG-GECO1, is 60% brighter than GCaMP6s in vitro and provides comparable performance as demonstrated by imaging Ca dynamics in cultured cells, primary neurons, and in vivo in larval zebrafish. These results suggest that mNG-GECO1 is a promising next-generation GECI that could inherit the mantle of GCaMP and allow the steady improvement of GECIs to continue for generations to come.