A bidirectional circuit switch reroutes pheromone signals in male and female brains.

The Drosophila sex pheromone cVA elicits different behaviors in males and females. First- and second-order olfactory neurons show identical pheromone responses, suggesting that sex genes differentially wire circuits deeper in the brain. Using in vivo whole-cell electrophysiology, we now show that two clusters of third-order olfactory neurons have dimorphic pheromone responses. One cluster responds in females; the other responds in males. These clusters are present in both sexes and share a common input pathway, but sex-specific wiring reroutes pheromone information. Regulating dendritic position, the fruitless transcription factor both connects the male-responsive cluster and disconnects the female-responsive cluster from pheromone input. Selective masculinization of third-order neurons transforms their morphology and pheromone responses, demonstrating that circuits can be functionally rewired by the cell-autonomous action of a switch gene. This bidirectional switch, analogous to an electrical changeover switch, provides a simple circuit logic to activate different behaviors in males and females.

Impact of caregiver overnight stay on postoperative outcomes.

PURPOSE: The purpose of this paper is to determine the impact of having a patient-designated caregiver remain overnight with ambulatory extended recovery patients on early postoperative clinical outcomes. DESIGN/METHODOLOGY/APPROACH: This was a retrospective cohort study of patients undergoing surgery requiring overnight stay in a highly resourced free-standing oncology ambulatory surgery center. Postoperative outcomes in patients who had caregivers stay with them overnight were compared with outcomes in those who did not. All other care was standardized. Primary outcomes were postoperative length of stay, hospital readmission rates, urgent care center (UCC) visits within 30 days and perioperative complication rates. FINDINGS: Among patients staying overnight, 2,462 (57 percent) were accompanied by overnight caregivers. In this group, time to discharge was significantly lower. Readmissions (though rare) were slightly higher, though the difference was not statistically significant (p=0.059). No difference in early (<30 day) complications or UCC visits was noted. Presence of a caregiver overnight was not associated with important differences in outcomes, though further research in a less well-structured environment is likely to show a more robust benefit. Caregivers are still recommended to stay overnight if that is their preference as no harm was identified. ORIGINALITY/VALUE: This study is unique in its evaluation of the clinical impact of having a caregiver stay overnight with ambulatory surgery patients. Little research has focused on the direct impact of the caregiver on patient outcomes, especially in the ambulatory setting. With increased adoption of minimally invasive surgical techniques and enhanced recovery pathways, a larger number of patients are eligible for short-stay ambulatory surgery. Factors that impact discharge and early postoperative complications are important.

Dimensionality reduction reveals separate translation and rotation populations in the zebrafish hindbrain.

In many brain areas, neuronal activity is associated with a variety of behavioral and environmental variables. In particular, neuronal responses in the zebrafish hindbrain relate to oculomotor and swimming variables as well as sensory information. However, the precise functional organization of the neurons has been difficult to unravel because neuronal responses are heterogeneous. Here, we used dimensionality reduction methods on neuronal population data to reveal the role of the hindbrain in visually driven oculomotor behavior and swimming. We imaged neuronal activity in zebrafish expressing GCaMP6s in the nucleus of almost all neurons while monitoring the behavioral response to gratings that rotated with different speeds. We then used reduced-rank regression, a method that condenses the sensory and motor variables into a smaller number of "features," to predict the fluorescence traces of all ROIs (regions of interest). Despite the potential complexity of the visuo-motor transformation, our analysis revealed that a large fraction of the population activity can be explained by only two features. Based on the contribution of these features to each ROI's activity, ROIs formed three clusters. One cluster was related to vergent movements and swimming, whereas the other two clusters related to leftward and rightward rotation. Voxels corresponding to these clusters were segregated anatomically, with leftward and rightward rotation clusters located selectively to the left and right hemispheres, respectively. Just as described in many cortical areas, our analysis revealed that single-neuron complexity co-exists with a simpler population-level description, thereby providing insights into the organization of visuo-motor transformations in the hindbrain.

Reactive Oxygen Species Mediate Activity-Regulated Dendritic Plasticity Through NADPH Oxidase and Aquaporin Regulation.

Neurons utilize plasticity of dendritic arbors as part of a larger suite of adaptive plasticity mechanisms. This explicitly manifests with motoneurons in the Drosophila embryo and larva, where dendritic arbors are exclusively postsynaptic and are used as homeostatic devices, compensating for changes in synaptic input through adapting their growth and connectivity. We recently identified reactive oxygen species (ROS) as novel plasticity signals instrumental in this form of dendritic adjustment. ROS correlate with levels of neuronal activity and negatively regulate dendritic arbor size. Here, we investigated NADPH oxidases as potential sources of such activity-regulated ROS and implicate Dual Oxidase (but not Nox), which generates hydrogen peroxide extracellularly. We further show that the aquaporins Bib and Drip, but not Prip, are required for activity-regulated ROS-mediated adjustments of dendritic arbor size in motoneurons. These results suggest a model whereby neuronal activity leads to activation of the NADPH oxidase Dual Oxidase, which generates hydrogen peroxide at the extracellular face; aquaporins might then act as conduits that are necessary for these extracellular ROS to be channeled back into the cell where they negatively regulate dendritic arbor size.

Effect of a Predictive Model on Planned Surgical Duration Accuracy, Patient Wait Time, and Use of Presurgical Resources: A Randomized Clinical Trial.

Importance: Accurate surgical scheduling affects patients, clinical staff, and use of physical resources. Although numerous retrospective analyses have suggested a potential for improvement, the real-world outcome of implementing a machine learning model to predict surgical case duration appears not to have been studied. Objectives: To assess accuracy and real-world outcome from implementation of a machine learning model that predicts surgical case duration. Design, Setting, and Participants: This randomized clinical trial was conducted on 2 surgical campuses of a cancer specialty center. Patients undergoing colorectal and gynecology surgery at Memorial Sloan Kettering Cancer Center who were scheduled more than 1 day before surgery between April 7, 2018, and June 25, 2018, were included. The randomization process included 29 strata (11 gynecological surgeons at 2 campuses and 7 colorectal surgeons at a single campus) to ensure equal chance of selection for each surgeon and each campus. Patients undergoing more than 1 surgery during the study's timeframe were enrolled only once. Data analyses took place from July 2018 to November 2018. Interventions: Cases were assigned to machine learning-assisted surgical predictions 1 day before surgery and compared with a control group. Main Outcomes and Measures: The primary outcome measure was accurate prediction of the duration of each scheduled surgery, measured by (arithmetic) mean (SD) error and mean absolute error. Effects on patients and systems were measured by start time delay of following cases, the time between cases, and the time patients spent in presurgical area. Results: A total of 683 patients were included (mean [SD] age, 55.8 [13.8] years; 566 women [82.9%]); 72 were excluded. Of the 683 patients included, those assigned to the machine learning algorithm had significantly lower mean (SD) absolute error (control group, 59.3 [72] minutes; intervention group, 49.5 [66] minutes; difference, -9.8 minutes; P = .03) compared with the control group. Mean start-time delay for following cases (patient wait time in a presurgical area), dropped significantly: 62.4 minutes (from 70.2 minutes to 7.8 minutes) and 16.7 minutes (from 36.9 minutes to 20.2 minutes) for patients receiving colorectal and gynecology surgery, respectively. The overall mean (SD) reduction of wait time was 33.1 minutes per patient (from 49.4 minutes to 16.3 minutes per patient). Improved accuracy did not adversely inflate time between cases (surgeon wait time). There was marginal improvement (1.5 minutes, from a mean of 70.6 to 69.1 minutes) in time between the end of cases and start of to-follow cases using the predictive model, compared with the control group. Patients spent a mean of 25.2 fewer minutes in the facility before surgery (173.3 minutes vs 148.1 minutes), indicating a potential benefit vis-à-vis available resources for other patients before and after surgery. Conclusions and Relevance: Implementing machine learning-generated predictions for surgical case durations may improve case duration accuracy, presurgical resource use, and patient wait time, without increasing surgeon wait time between cases. Trial Registration: ClinicalTrials.gov Identifier: NCT03471377.

NBLAST: Rapid, Sensitive Comparison of Neuronal Structure and Construction of Neuron Family Databases.

Neural circuit mapping is generating datasets of tens of thousands of labeled neurons. New computational tools are needed to search and organize these data. We present NBLAST, a sensitive and rapid algorithm, for measuring pairwise neuronal similarity. NBLAST considers both position and local geometry, decomposing neurons into short segments; matched segments are scored using a probabilistic scoring matrix defined by statistics of matches and non-matches. We validated NBLAST on a published dataset of 16,129 single Drosophila neurons. NBLAST can distinguish neuronal types down to the finest level (single identified neurons) without a priori information. Cluster analysis of extensively studied neuronal classes identified new types and unreported topographical features. Fully automated clustering organized the validation dataset into 1,052 clusters, many of which map onto previously described neuronal types. NBLAST supports additional query types, including searching neurons against transgene expression patterns. Finally, we show that NBLAST is effective with data from other invertebrates and zebrafish. VIDEO ABSTRACT.

Image Sharing Technologies and Reduction of Imaging Utilization: A Systematic Review and Meta-analysis.

INTRODUCTION: Image sharing technologies may reduce unneeded imaging by improving provider access to imaging information. A systematic review and meta-analysis were conducted to summarize the impact of image sharing technologies on patient imaging utilization. METHODS: Quantitative evaluations of the effects of PACS, regional image exchange networks, interoperable electronic heath records, tools for importing physical media, and health information exchange systems on utilization were identified through a systematic review of the published and gray English-language literature (2004-2014). Outcomes, standard effect sizes (ESs), settings, technology, populations, and risk of bias were abstracted from each study. The impact of image sharing technologies was summarized with random-effects meta-analysis and meta-regression models. RESULTS: A total of 17 articles were included in the review, with a total of 42 different studies. Image sharing technology was associated with a significant decrease in repeat imaging (pooled effect size [ES] = -0.17; 95% confidence interval [CI] = [-0.25, -0.09]; P < .001). However, image sharing technology was associated with a significant increase in any imaging utilization (pooled ES = 0.20; 95% CI = [0.07, 0.32]; P = .002). For all outcomes combined, image sharing technology was not associated with utilization. Most studies were at risk for bias. CONCLUSIONS: Image sharing technology was associated with reductions in repeat and unnecessary imaging, in both the overall literature and the most-rigorous studies. Stronger evidence is needed to further explore the role of specific technologies and their potential impact on various modalities, patient populations, and settings.

Clonal analysis of olfaction in Drosophila: generation of flies with mosaic labeling.

Clonal analysis with the MARCM (mosaic analysis with a repressible cell marker) system can be used for studying cell lineage, development, and anatomy in the Drosophila olfactory system and other parts of the fly brain. This protocol gives a method for generating flies with mosaic labeling. It describes how to establish a mating cage for MARCM in PNs (projection neurons) of the fly antennal lobe and then select appropriate flies for dissection and staining using immunohistochemistry. The protocol can be adapted to determine the birth order of neuroblast lineages or individual cells. Alternatively, it can be used to dissect a complicated Gal4 line into its component neuroblast lineages to help elucidate projection patterns and connectivity. Collecting newly hatched larvae during a short time window allows for precise control of the stage during development at which the heat shock is applied.

Clonal analysis of olfaction in Drosophila: immunochemistry and imaging of fly brains.

Clonal analysis with the MARCM (mosaic analysis with a repressible cell marker) system can be used for studying cell lineage, development, and anatomy in the Drosophila olfactory system and other parts of the fly brain. This protocol describes the dissection, staining, and imaging of brains from Drosophila with mosaic labeling. Staining for the presynaptic marker Bruchpilot (nc82) is performed in the example given here. The well-stained whole brain images that are obtained can be used to examine neuronal morphology. They are of sufficient quality to be used for image registration, which allows one to compare confocal images of labeled neurons in different brains.

Clonal analysis of olfaction in Drosophila: image registration.

Clonal analysis with the MARCM (mosaic analysis with a repressible cell marker) system can be used for studying cell lineage, development, and anatomy in the Drosophila olfactory system and other parts of the fly brain. To compare confocal images of labeled neurons in different brains, it may be desirable to register them to a template or standard brain. There are various image registration approaches available. Some depend on manually specifying landmarks on the brains to be registered. Others depend only on the grayscale intensity value of one of the channels in the confocal image. Another important difference between registration approaches is whether they apply linear or nonlinear (warping) transformations. Linear transformations typically include translation, rotation, and scaling along each axis. Nonlinear transformations are much more computationally intensive, but are required to register brains with different shapes. Here we describe the practical steps required for an intensity-based nonlinear registration that has been used to map the higher olfactory centers of the Drosophila brain using the staining for the presynaptic marker Bruchpilot (nc82). This registration is in fact a two-step process. The first step is a linear transformation that roughly aligns the two brains, followed by a second nonlinear step that allows different parts of the brain to move in slightly different directions.

A mutual information approach to automate identification of neuronal clusters in Drosophila brain images.

Mapping neural circuits can be accomplished by labeling a small number of neural structures per brain, and then combining these structures across multiple brains. This sparse labeling method has been particularly effective in Drosophila melanogaster, where clonally related clusters of neurons derived from the same neural stem cell (neuroblast clones) are functionally related and morphologically highly stereotyped across animals. However identifying these neuroblast clones (approximately 180 per central brain hemisphere) manually remains challenging and time consuming. Here, we take advantage of the stereotyped nature of neural circuits in Drosophila to identify clones automatically, requiring manual annotation of only an initial, smaller set of images. Our procedure depends on registration of all images to a common template in conjunction with an image processing pipeline that accentuates and segments neural projections and cell bodies. We then measure how much information the presence of a cell body or projection at a particular location provides about the presence of each clone. This allows us to select a highly informative set of neuronal features as a template that can be used to detect the presence of clones in novel images. The approach is not limited to a specific labeling strategy and can be used to identify partial (e.g., individual neurons) as well as complete matches. Furthermore this approach could be generalized to studies of neural circuits in other organisms.

Sexual dimorphism in the fly brain.

BACKGROUND: Sex-specific behavior may originate from differences in brain structure or function. In Drosophila, the action of the male-specific isoform of fruitless in about 2000 neurons appears to be necessary and sufficient for many aspects of male courtship behavior. Initial work found limited evidence for anatomical dimorphism in these fru+ neurons. Subsequently, three discrete anatomical differences in central brain fru+ neurons have been reported, but the global organization of sex differences in wiring is unclear. RESULTS: A global search for structural differences in the Drosophila brain identified large volumetric differences between males and females, mostly in higher brain centers. In parallel, saturating clonal analysis of fru+ neurons using mosaic analysis with a repressible cell marker identified 62 neuroblast lineages that generate fru+ neurons in the brain. Coregistering images from male and female brains identified 19 new dimorphisms in males; these are highly concentrated in male-enlarged higher brain centers. Seven dimorphic lineages also had female-specific arbors. In addition, at least 5 of 51 fru+ lineages in the nerve cord are dimorphic. We use these data to predict >700 potential sites of dimorphic neural connectivity. These are particularly enriched in third-order olfactory neurons of the lateral horn, where we provide strong evidence for dimorphic anatomical connections by labeling partner neurons in different colors in the same brain. CONCLUSION: Our analysis reveals substantial differences in wiring and gross anatomy between male and female fly brains. Reciprocal connection differences in the lateral horn offer a plausible explanation for opposing responses to sex pheromones in male and female flies.