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We have shown that briefly inhaled isoflurane rapidly halts convulsions and protects the central nervous system (CNS) from organophosphate-induced neuronal loss when administered at 5% for 5 min, even as late as 1 h after organophosphate exposure. In the current study we investigated if an injectable form of isoflurane was as effective as inhaled isoflurane. We used a mixture of 10% isoflurane dissolved in an IV-compatible lipid-water emulsion for intravenous administration. Rats with an implanted jugular vein cannula were infused with 1,000 μL of the 10% isoflurane-lipid emulsion (ILE) mixture at a rate of 200 μL per minute, which achieved full anesthesia lasting approximately 10 min. When administered 30 min after a highly lethal dose of the organophosphate insecticide paraoxon (POX), the short-duration administration halted convulsions over the course of the study and prevented the great majority of neuronal loss as shown by Fluoro-Jade B staining (FJB). Our results indicate that injectable isoflurane is very effective for treating organophosphate poisoning, negating the need for vaporizer equipment and enabling intravenous therapy.

Organophosphate-based chemical agents (OP), including nerve agents and certain pesticides such as paraoxon, are potent acetylcholinesterase inhibitors that cause severe convulsions and seizures, leading to permanent central nervous system (CNS) damage if not treated promptly. The current treatment regimen for OP poisoning is intramuscular injection of atropine sulfate with an oxime such as pralidoxime (2-PAM) to mitigate cholinergic over-activation of the somatic musculature and autonomic nervous system. This treatment does not provide protection against CNS cholinergic overactivation and therefore convulsions require additional medication. Benzodiazepines are the currently accepted treatment for OP-induced convulsions, but the convulsions become refractory to these GABAA agonists and repeated dosing has diminishing effectiveness. As such, adjunct anticonvulsant treatments are needed to provide improved protection against recurrent and prolonged convulsions and the associated excitotoxic CNS damage that results from them. Previously we have shown that brief, 4-min administration of 3%–5% isoflurane in 100% oxygen has profound anticonvulsant and CNS protective effects when administered 30 min after a lethal dose of paraoxon. In this report we provide an extended time course of the effectiveness of 5% isoflurane delivered for 5 min, ranging from 60 to 180 min after a lethal dose of paraoxon in rats. We observed substantial effectiveness in preventing neuronal loss as shown by Fluoro-Jade B staining when isoflurane was administered 1 h after paraoxon, with diminishing effectiveness at 90, 120 and 180 min. In vivo magnetic resonance imaging (MRI) derived T2 and mean diffusivity (MD) values showed that 5-min isoflurane administration at a concentration of 5% prevents brain edema and tissue damage when administered 1 h after a lethal dose of paraoxon. We also observed reduced astrogliosis as shown by GFAP immunohistochemistry. Studies with continuous EEG monitoring are ongoing to demonstrate effectiveness in animal models of soman poisoning.

Abstract Rigorous comparisons of human and machine learning algorithm performance on the same task help to support accurate claims about algorithm success rates and advances understanding of their performance relative to that of human performers. In turn, these comparisons are critical for supporting advances in artificial intelligence. However, the machine learning community has lacked a standardized, consensus framework for performing the evaluations of human performance necessary for comparison. We demonstrate common pitfalls in a designing the human performance evaluation and propose a framework for the evaluation of human performance, illustrating guiding principles for a successful comparison. These principles are first, to design the human evaluation with an understanding of the differences between human and algorithm cognition; second, to match trials between human participants and the algorithm evaluation, and third, to employ best practices for psychology research studies, such as the collection and analysis of supplementary and subjective data and adhering to ethical review protocols. We demonstrate our framework’s utility for designing a study to evaluate human performance on a one-shot learning task. Adoption of this common framework may provide a standard approach to evaluate algorithm performance and aid in the reproducibility of comparisons between human and machine learning algorithm performance.

Abstract Insect neural systems are a promising source of inspiration for new navigation algorithms, especially on low size, weight, and power platforms. There have been unprecedented recent neuroscience breakthroughs with Drosophila in behavioral and neural imaging experiments as well as the mapping of detailed connectivity of neural structures. General mechanisms for learning orientation in the central complex (CX) of Drosophila have been investigated previously; however, it is unclear how these underlying mechanisms extend to cases where there is translation through an environment (beyond only rotation), which is critical for navigation in robotic systems. Here, we develop a CX neural connectivity-constrained model that performs sensor fusion, as well as unsupervised learning of visual features for path integration; we demonstrate the viability of this circuit for use in robotic systems in simulated and physical environments. Furthermore, we propose a theoretical understanding of how distributed online unsupervised network weight modification can be leveraged for learning in a trajectory through an environment by minimizing orientation estimation error. Overall, our results may enable a new class of CX-derived low power robotic navigation algorithms and lead to testable predictions to inform future neuroscience experiments.

Counting the number of species, items, or genes that are shared between two groups, sets, or communities is a simple calculation when sampling is complete. However, when only partial samples are available, quantifying the overlap between two communities becomes an estimation problem. Furthermore, to calculate normalized measures of β-diversity, such as the Jaccard and Sorenson-Dice indices, one must also estimate the total sizes of the communities being compared. Previous efforts to address these problems have assumed knowledge of total community sizes and then used Bayesian methods to produce unbiased estimates with quantified uncertainty. Here, we address communities of unknown size and show that this produces systematically better estimates-both in terms of central estimates and quantification of uncertainty in those estimates. We further show how to use species, item, or gene count data to refine estimates of community size in a Bayesian joint model of community size and overlap.

Abstract Recent advances in neuroscience have enabled the exploration of brain structure at the level of individual synaptic connections. These connectomics datasets continue to grow in size and complexity; methods to search for and identify interesting graph patterns offer a promising approach to quickly reduce data dimensionality and enable discovery. These graphs are often too large to be analyzed manually, presenting significant barriers to searching for structure and testing hypotheses. We combine graph database and analysis libraries with an easy-to-use neuroscience grammar suitable for rapidly constructing queries and searching for subgraphs and patterns of interest. Our approach abstracts many of the computer science and graph theory challenges associated with nanoscale brain network analysis and allows scientists to quickly conduct research at scale. We demonstrate the utility of these tools by searching for motifs on simulated data and real public connectomics datasets, and we share simple and complex structures relevant to the neuroscience community. We contextualize our findings and provide case studies and software to motivate future neuroscience exploration.

Neuroscientists can leverage technological advances to image neural tissue across a range of different scales, potentially forming the basis for the next generation of brain atlases and circuit reconstructions at submicron resolution, using Electron Microscopy and X-ray Microtomography modalities. However, there is variability in data collection, annotation, and storage approaches, which limits effective comparative and secondary analysis. There has been great progress in standardizing interfaces for large-scale spatial image data, but more work is needed to standardize annotations, especially metadata associated with neuroanatomical entities. Standardization will enable validation, sharing, and replication, greatly amplifying investment throughout the connectomics community. We share key design considerations and a usecase developed for metadata for a recent large-scale dataset.

Abstract Bergmann’s rule is a well‐established, ecogeographical principle that states that body size varies positively with latitude, reflecting the thermoregulatory benefits of larger bodies as temperatures decline. However, this principle does not seem to easily apply to migratory species that are able to avoid the extreme temperatures during winter at higher latitudes. Further, little is known about the ontogeny of this relationship across life stages or how it is influenced by ongoing global climate change. To address these knowledge gaps, we assessed the contemporary relationship between latitude and body size in a long‐distance migratory species, the prothonotary warbler (Protonotaria citrea) across life stages (egg to adult) on their breeding grounds. We also measured historic eggs (1865‐1961) to assess if the relationship between latitude and size during this life stage has changed over time. In accordance with Bergmann’s rule, we found a positive relationship between latitude and body mass during all post‐embryonic life stages, from early nestling stage through adulthood. We observed this same predicted pattern with historic eggs, but contemporary eggs exhibited the reverse (negative) relationship. We suggest that these results indicate a genetic component to this pattern and speculate that selection for larger body size in altricial nestlings as latitude increases may possibly drive the pattern in migratory species as even rare extreme cold weather events may cause mortality during early life stages. Furthermore, the opposite relationships observed in eggs, dependent on time period, may be related to the rapidly warming environments of higher latitudes that is associated with climate change. Although it is unclear what mechanism(s) would allow for this recent reversal in eggs (but still allow for its maintenance in later life stages). This evidence of a reversal suggests that anthropogenic climate change may be in the process of altering one of the longest‐standing principles in ecology.

Technological advances in imaging and data acquisition are leading to the development of petabyte-scale neuroscience image datasets. These large-scale volumetric datasets pose unique challenges since analyses often span the entire volume, requiring a unified platform to access it. In this paper, we describe the Brain Observatory Storage Service and Database (BossDB), a cloud-based solution for storing and accessing petascale image datasets. BossDB provides support for data ingest, storage, visualization, and sharing through a RESTful Application Programming Interface (API). A key feature is the scalable indexing of spatial data and automatic and manual annotations to facilitate data discovery. Our project is open source and can be easily and cost effectively used for a variety of modalities and applications, and has effectively worked with datasets over a petabyte in size.

Improving our understanding of migratory behaviors and connectivity is fundamental for identifying limiting factors and drivers of population decline. With advances in miniaturized tracking technology, we are now able to study these critical aspects of avian ecology, which, for secretive species, was once an exceptional challenge. Here, we identify several unknown aspects of the migratory behavior and connectivity of the elusive Swainson’s Warbler (Limnothlypis swainsonii), by tracking individuals from populations breeding in Louisiana, U.S., and wintering in Jamaica. We identified a migratory divide between the western and eastern portions of the species’ distribution, showing that most Louisiana breeders overwintered in southern Mexico and the Yucatan peninsula, whereas the Jamaica individuals migrated to the eastern portion of the Swainson’s Warbler breeding range. Geolocator data documented that a portion of migratory flights in both populations were sustained well into the day, suggesting that birds migrated over large bodies of water (i.e., Gulf of Mexico and Caribbean Sea) during both spring and fall migration. Furthermore, the phenology and rate of migration differed between populations. Additional research efforts across a broader portion of the range are necessary to better understand the demographic consequences of high migratory connectivity and the implications for the conservation of the species.

Why bilaterally symmetrical organisms express handedness remains an important question in evolutionary biology. In some species, anatomical asymmetries have evolved that accompany behavioral handedness, yet we know remarkably little about causal links between asymmetric morphological traits and behavior. Here, we explore if a dextral or sinistral orientation of the male intromittent organ predicts side preferences in male behaviors. Our study addresses this question in the Costa Rican livebearing fish, Xenophallus umbratilis. This fish has a bilaterally symmetrical body plan, with one exception—the male anal fin (gonopodium), used to inseminate females, terminates with a distinct left- or right-handed corkscrew morphology. We used a detour assay to test males for side biases in approach behavior when exposed to four different stimuli (predator, potential mate, novel object, empty tank control). We found that left morph males preferred using their right eye to view potential mates, predators, and the control, and that right morph males preferred to use their left eye to view potential mates and predators, and their right eye to view the control. Males of both morphs displayed no eye bias when approaching the novel object. Our results suggest that there is a strong link between behavior and gonopodium orientation, with right and left morph males responding with opposite directional behaviors when presented with the same stimuli. This presents the intriguing possibility that mating preferences—in this case constrained by gonopodial morphology—could be driving lateralized decision making in a variety of non-mating behaviors.

Adipokinetic Hormone (AKH) is the primary insect hormone that mobilizes stored energy and is functional equivalent to mammalian glucagon. While most studies have focused on exploring the functional roles of AKH, relatively little is known about how AKH secretion is regulated. We assessed the AKH cell transcriptome and mined the data set for specific insight into the identities of different ion channels expressed in this cell lineage. We found reliable expression of multiple ion channel genes with multiple members for each ionic species. Specifically, we found significant signals for 39 of the either known or suspected ion channel genes within the Drosophila genome. We next performed a targeted RNAi screen aimed to identify the functional contribution of these different ion channels that may participate in excitation-secretion coupling in AKH producing cells (APCs). We assessed starvation survival, because changes in AKH signaling have previously been shown to impact starvation sensitivity. Genetic knockdown of three genes (Ca-Beta, Sur, and sei), in AKH producing cells caused highly significant changes (P < 0.001) in both male and female lifespan, and knockdown of six other genes (Shaw, cac, Ih, NaCP60E, stj, and TASK6) caused significant changes (P < 0.05) in only female lifespan. Specifically, the genetic knockdown of Ca-Beta and Sur led to increases in starvation lifespan, whereas the knockdown of sei decreased starvation survivorship. Focusing on these three strongest candidates from the behavioral screen, we assessed other AKH-dependent phenotypes. The AKH hormone is required for starvation-induced hyperactivity, and we found that these three ion channel gene knockdowns changed activity profiles and further suggest a modulatory role of these channels in AKH release. We eliminated the possibility that these genetic elements caused AKH cell lethality, and using independent methods, we verified expression of these genes in AKH cells. Collectively, these results suggest a model of AKH-cell excitability and establish an experimental framework for evaluating intrinsic mechanisms of AKH release.

Knowledge on how antibody responses have evolved is critical for the induction of protective immunity. Here the authors analyse, using high-throughput sequencing of both exon and intron regions, the mutation and lineage development of an HIV-neutralizing antibody to find an unexpected early emergence of broadly neutralizing species.

Abstract Leptin is an adipokine produced by fat cells that regulates food consumption and metabolic activity. Sexual dimorphism in leptin and fat stores have been observed in humans and rodents with females having more leptin and greater levels of subcutaneous fat than males. One potential mechanism leading to this dimorphism is steroid hormone regulated synthesis of transcripts encoding leptin. Identification of direct regulatory mechanisms is difficult in animals or primary adipocytes due to these intertwined dimorphisms. We used well-characterized 3T3-L1 murine adipocytes to demonstrate that dihydrotestosterone (DHT) reduced Leptin (Lep) transcript abundance and cytosolic and secreted leptin protein. The magnitude of this effect was greatest on secreted leptin, which was decreased by DHT to 30% of the control. In contrast, 17β-estradiol significantly increased the abundance of transcripts encoding leptin and increased secreted leptin to 230% of the control. Treatment with estrogen and androgen receptor antagonists had opposite effects on Lep transcript abundance to steroid treatments, indicating that these transcriptional effects are mediated through the canonical steroid hormone signaling pathways. These results indicate that short-term treatments with steroid hormones are sufficient to alter both Lep transcript accumulation and leptin protein secretion, and may play a role in the sexual dimorphism of this adipokine.

There has been disagreement over the functional roles of the painless gene product in the detection and subsequent behavioral aversion to the active ingredient in wasabi, allyl isothiocyanate (AITC). Originally, painless was reported to eliminate the behavioral aversion to AITC, although subsequent reports suggested that another trpA homolog, dTRPA1, was responsible for AITC aversion. We re-evaluated the role of the painless gene in the detection of AITC, employing several different behavioral assays. Using the proboscis extension reflex (PER) assay, we observed that AITC did not reduce PER frequencies in painless or dTRPA1 mutants but did in wild-type genotypes. Quantification of food intake showed a significant decline in food consumption in the presence of AITC in wild-type, but not painless mutants. We adapted an oviposition choice assay and found wild-type oviposit on substrates lacking AITC, in contrast to painless and dTRPA1 mutants. Lastly, tracking individual flies relative to a point source of AITC, showed a consistent clustering of wild-type animals away from the point source, which was absent in painless mutants. We evaluated expression patterns of both dTRPA1 and painless, which showed expression in distinct central and peripheral populations. We identified the transmitter phenotypes of subsets of painless and dTRPA1 neurons and found similar neuropeptides as those expressed by mammalian trpA expressing neurons. Using a calcium reporter, we observed AITC-evoked responses in both painless and dTRPA1 expressing neurons. Collectively, these results reaffirm the necessity of painless in nociceptive behaviors and suggest experiments to further resolve the molecular basis of aversion.