Mutations in neuroligin-3 in male mice impact behavioral flexibility but not relational memory in a touchscreen test of visual transitive inference

Cognitive dysfunction including disrupted behavioral flexibility is central to neurodevelopmental disorders such as Autism Spectrum Disorder (ASD). A cognitive measure that assesses relational memory, and the ability to flexibly assimilate and transfer learned information is transitive inference. Transitive inference is highly conserved across vertebrates and disrupted in cognitive disorders. Here, we examined how mutations in the synaptic cell-adhesion molecule neuroligin-3 (Nlgn3) that have been documented in ASD impact relational memory and behavioral flexibility. We first refined a rodent touchscreen assay to measure visual transitive inference, then assessed two mouse models of Nlgn3 dysfunction (Nlgn3−/y and Nlgn3R451C). Deep analysis of touchscreen behavioral data at a trial level established we could measure trajectories in flexible responding and changes in processing speed as cognitive load increased. We show that gene mutations in Nlgn3 do not disrupt relational memory, but significantly impact flexible responding. Our study presents the first analysis of reaction times in a rodent transitive inference test, highlighting response latencies from the touchscreen system are useful indicators of processing demands or decision-making processes. These findings expand our understanding of how dysfunction of key components of synaptic signaling complexes impact distinct cognitive processes disrupted in neurodevelopmental disorders, and advance our approaches for dissecting rodent behavioral assays to provide greater insights into clinically relevant cognitive symptoms

Low Apparent Survival and Heterogeneous Movement Patterns of Invasive Blue Catfish in a Coastal River

Blue Catfish Ictalurus furcatus were purposefully introduced into freshwater tributaries to Chesapeake Bay in the past, and populations have subsequently spread to new areas, negatively impacting native communities and causing concern for resource managers. To aid development of management strategies, we implemented a multiyear (2012-2015) tagging study of invasive Blue Catfish in a 40-km stretch of the Potomac River to estimate survival and assess movement patterns. Blue Catfish (N = 1,237) were captured by electrofishing and double-tagged to allow us to estimate tag retention rates; we used reward tags to increase reporting rates. Recaptured fish (N = 104; 8.4% return rate) were at large for between 2 and 1,208 d. Tag retention rates were 0.88 (SE = 0.045) after 1 year and declined to 0.31 (SE = 0.107) after 2.7 years. The mean minimum distance moved by fish was 24.1 km (range = 0.0-112.6 km). Most (63%) fish displayed downriver movements, but distance moved was unrelated to fish size or days at large. Greater distances were observed among fish that moved downriver (34.4 km) than those that moved upriver (6.7 km). These results suggest high variability in movement behaviors for Blue Catfish inhabiting the tidal Potomac River from freshwater reaches to estuarine habitats. We estimated an annual apparent survival rate of 0.56 (SE = 0.057; Brownie tag-return model) across the study period. This survival rate is lower than survival rates reported from their native range. Long-distance movements of Blue Catfish in the Potomac River indicate that robust, large-scale control measures will be needed to reduce population abundance and minimize negative impacts of this species on native communities

Specifying who delivers behaviour change interventions: development of an Intervention Source Ontology [version 1; peer review: awaiting peer review]

BACKGROUND: Identifying how behaviour change interventions are delivered, including by whom, is key to understanding intervention effectiveness. However, information about who delivers interventions is reported inconsistently in intervention evaluations, limiting communication and knowledge accumulation. This paper reports a method for consistent reporting: The Intervention Source Ontology. This forms one part of the Behaviour Change Intervention Ontology, which aims to cover all aspects of behaviour change interventions. METHODS: The Intervention Source Ontology was developed following methods for ontology development and maintenance used in the Human Behaviour-Change Project, with seven key steps: 1) define the scope of the ontology, 2) identify key entities and develop their preliminary definitions by reviewing existing classification systems (top-down) and reviewing 100 behaviour change intervention reports (bottom-up), 3) refine the ontology by piloting the preliminary ontology on 100 reports, 4) stakeholder review by 34 behavioural science and public health experts, 5) inter-rater reliability testing of annotating intervention reports using the ontology, 6) specify ontological relationships between entities and 7) disseminate and maintain the Intervention Source Ontology. RESULTS: The Intervention Source Ontology consists of 140 entities. Key areas of the ontology include Occupational Role of Source, Relatedness between Person Source and the Target Population, Sociodemographic attributes and Expertise. Inter-rater reliability was found to be 0.60 for those familiar with the ontology and 0.59 for those unfamiliar with it, levels of agreement considered ‘acceptable’. CONCLUSIONS: Information about who delivers behaviour change interventions can be reliably specified using the Intervention Source Ontology. For human-delivered interventions, the ontology can be used to classify source characteristics in existing behaviour change reports and enable clearer specification of intervention sources in reporting

Resolve survey Photometry and volume-limited calibration of the Photometric gas fractions technique

We present custom-processed ultraviolet, optical, and near-infrared photometry for the REsolved Spectroscopy of a Local VolumE (RESOLVE) survey, a volume-limited census of stellar, gas, and dynamical mass within two subvolumes of the nearby universe (RESOLVE-A and RESOLVE-B). RESOLVE is complete down to baryonic mass 10 ~ 9.1 9.3 - M, probing the upper end of the dwarf galaxy regime. In contrast to standard pipeline photometry (e.g., SDSS), our photometry uses optimal background subtraction, avoids suppressing color gradients, and employs multiple flux extrapolation routines to estimate systematic errors. With these improvements, we measure brighter magnitudes, larger radii, bluer colors, and a real increase in scatter around the red sequence. Combining stellar mass estimates based on our optimized photometry with the nearly complete H I mass census for RESOLVE-A, we create new z = 0 volume-limited calibrations of the photometric gas fractions (PGF) technique, which predicts gas-to-stellar mass ratios (G/S) from galaxy colors and optional additional parameters. We analyze G/S-color residuals versus potential third parameters, finding that axial ratio is the best independent and physically meaningful third parameter. We define a “modified color” from planar fits to G/S as a function of both color and axial ratio. In the complete galaxy population, upper limits on G/S bias linear and planar fits. We therefore model the entire PGF probability density field, enabling iterative statistical modeling of upper limits and prediction of full G/S probability distributions for individual galaxies. These distributions have two-component structure in the red color regime. Finally, we use the RESOLVE-B 21 cm census to test several PGF calibrations, finding that most systematically under- or overestimate gas masses, but the full probability density method performs well

ECO AND RESOLVE: GALAXY DISK GROWTH IN ENVIRONMENTAL CONTEXT

We study the relationships between galaxy environments and galaxy properties related to disk (re)growth, considering two highly complete samples that are approximately baryonic mass limited into the high-mass dwarf galaxy regime, the Environmental COntext catalog (data release herein) and the B-semester region of the REsolved Spectroscopy Of a Local VolumE survey. We quantify galaxy environments using both group identification and smoothed galaxy density field methods. We use by-eye and quantitative morphological classifications plus atomic gas content measurements and estimates. We find that blue early-type (E/S0) galaxies, gas-dominated galaxies, and UV-bright disk host galaxies all become distinctly more common below group halo mass $\sim {10}^{11.5}\;{M}_{\odot }$, implying that this low group halo mass regime may be a preferred regime for significant disk growth activity. We also find that blue early-type and blue late-type galaxies inhabit environments of similar group halo mass at fixed baryonic mass, consistent with a scenario in which blue early-types can regrow late-type disks. In fact, we find that the only significant difference in the typical group halo mass inhabited by different galaxy classes is for satellite galaxies with different colors, where at fixed baryonic mass red early- and late-types have higher typical group halo masses than blue early- and late-types. More generally, we argue that the traditional morphology–environment relation (i.e., that denser environments tend to have more early-types) can be largely attributed to the morphology-galaxy mass relation for centrals and the color–environment relation for satellites

Novel exomphalos genetic mouse model: The importance of accurate phenotypic classification.

Rodent models of abdominal wall defects (AWD) may provide insight into the pathophysiology of these conditions including gut dysfunction in gastroschisis, or pulmonary hypoplasia in exomphalos. Previously, a Scribble mutant mouse model (circletail) was reported to exhibit gastroschisis. We further characterise this AWD in Scribble knockout mice

Ontologies relevant to behaviour change interventions: a method for their development [version 2; peer review: 1 not approved]

Background: Behaviour and behaviour change are integral to many aspects of wellbeing and sustainability. However, reporting behaviour change interventions accurately and synthesising evidence about effective interventions is hindered by lacking a shared, scientific terminology to describe intervention characteristics. Ontologies are knowledge structures that provide controlled vocabularies to help unify and connect scientific fields. To date, there is no published guidance on the specific methods required to develop ontologies relevant to behaviour change. We report the creation and refinement of a method for developing ontologies that make up the Behaviour Change Intervention Ontology (BCIO). / Aims: (1) To describe the development method of the BCIO and explain its rationale; (2) To provide guidance on implementing the activities within the development method. / Method and results: The method for developing ontologies relevant to behaviour change interventions was constructed by considering principles of good practice in ontology development and identifying key activities required to follow those principles. The method’s details were refined through application to developing two ontologies. The resulting ontology development method involved: (1) defining the ontology’s scope; (2) identifying key entities; (3) refining the ontology through an iterative process of literature annotation, discussion and revision; (4) expert stakeholder review; (5) testing inter-rater reliability; (6) specifying relationships between entities, and; (7) disseminating and maintaining the ontology. Guidance is provided for conducting relevant activities for each step. / Conclusions: We have developed a detailed method for creating ontologies relevant to behaviour change interventions, together with practical guidance for each step, reflecting principles of good practice in ontology development. The most novel aspects of the method are the use of formal mechanisms for literature annotation and expert stakeholder review to develop and improve the ontology content. We suggest the mnemonic SELAR3, representing the method’s first six steps as Scope, Entities, Literature Annotation, Review, Reliability, Relationships

Representation of behaviour change interventions and their evaluation: Development of the Upper Level of the Behaviour Change Intervention Ontology [version 2; peer review: 1 approved, 1 approved with reservations]

Background: Behaviour change interventions (BCI), their contexts and evaluation methods are heterogeneous, making it difficult to synthesise evidence and make recommendations for real-world policy and practice. Ontologies provide a means for addressing this. They represent knowledge formally as entities and relationships using a common language able to cross disciplinary boundaries and topic domains. This paper reports the development of the upper level of the Behaviour Change Intervention Ontology (BCIO), which provides a systematic way to characterise BCIs, their contexts and their evaluations. Methods: Development took place in four steps. (1) Entities and relationships were identified by behavioural and social science experts, based on their knowledge of evidence and theory, and their practical experience of behaviour change interventions and evaluations. (2) The outputs of the first step were critically examined by a wider group of experts, including the study ontology expert and those experienced in annotating relevant literature using the initial ontology entities. The outputs of the second step were tested by (3) feedback from three external international experts in ontologies and (4) application of the prototype upper-level BCIO to annotating published reports; this informed the final development of the upper-level BCIO. Results: The final upper-level BCIO specifies 42 entities, including the BCI scenario, elaborated across 21 entities and 7 relationship types, and the BCI evaluation study comprising 10 entities and 9 relationship types. BCI scenario entities include the behaviour change intervention (content and delivery), outcome behaviour, mechanism of action, and its context, which includes population and setting. These entities have corresponding entities relating to the planning and reporting of interventions and their evaluations. Conclusions: The upper level of the BCIO provides a comprehensive and systematic framework for representing BCIs, their contexts and their evaluations. Keyword

Development of an Intervention Setting Ontology for behaviour change: Specifying where interventions take place

Background: Contextual factors such as an intervention's setting are key to understanding how interventions to change behaviour have their effects and patterns of generalisation across contexts. The intervention's setting is not consistently reported in published reports of evaluations. Using ontologies to specify and classify intervention setting characteristics enables clear and reproducible reporting, thus aiding replication, implementation and evidence synthesis. This paper reports the development of a Setting Ontology for behaviour change interventions as part of a Behaviour Change Intervention Ontology, currently being developed in the Wellcome Trust funded Human Behaviour-Change Project. Methods: The Intervention Setting Ontology was developed following methods for ontology development used in the Human Behaviour-Change Project: 1) Defining the ontology's scope, 2) Identifying key entities by reviewing existing classification systems (top-down) and 100 published behaviour change intervention reports (bottom-up), 3) Refining the preliminary ontology by literature annotation of 100 reports, 4) Stakeholder reviewing by 23 behavioural science and public health experts to refine the ontology, 5) Assessing inter-rater reliability of using the ontology by two annotators familiar with the ontology and two annotators unfamiliar with it, 6) Specifying ontological relationships between setting entities and 7) Making the Intervention Setting Ontology machine-readable using Web Ontology Language (OWL) and publishing online. Results: The Intervention Setting Ontology consists of 72 entities structured hierarchically with two upper-level classes: Physical setting including Geographic location, Attribute of location (including Area social and economic condition, Population and resource density sub-levels) and Intervention site (including Facility, Transportation and Outdoor environment sub-levels), as well as Social setting. Inter-rater reliability was found to be 0.73 (good) for those familiar with the ontology and 0.61 (acceptable) for those unfamiliar with it. Conclusion: The Intervention Setting Ontology can be used to code information from diverse sources, annotate the setting characteristics of existing intervention evaluation reports and guide future reporting

Diffusion microscopic MRI of the mouse embryo: Protocol and practical implementation in the splotch mouse model

Advanced methodologies for visualizing novel tissue contrast are essential for phenotyping the ever-increasing number of mutant mouse embryos being generated. Although diffusion microscopic MRI (μMRI) has been used to phenotype embryos, widespread routine use is limited by extended scanning times, and there is no established experimental procedure ensuring optimal data acquisition