Description of Tresuncinidactylus wilmienae gen. et sp. n. (Monogenea: Gyrodactylidae), from the gills of the bulldog, Marcusenius macrolepidotus (Peters) from Lake Kariba, Zimbabwe

The African continent has a rich diversity of fish and amphibians in its inland water systems that serve as hosts for monogeneans of seven genera of the Gyrodactylidae van Beneden et Hesse, 1832. In August 2011, eight gyrodactylid parasites were collected from the gills of two specimens of bulldog, Marcusenius macrolepidotus (Peters), from Lake Kariba, Zimbabwe. Morphometric evaluation and sequencing of 18S rDNA confirmed that the specimens represented a species of a new viviparous genus, Tresuncinidactylus wilmienae gen. et sp. n. The attachment apparatus consists of a single pair of large slender hamuli with prominently flattened roots that are connected by a simple, narrow dorsal bar. The ventral bar is small and possesses a thin lingulate membrane but no evident anterolateral processes. There are 16 marginal hooks of one morphological type, but of three different sizes, with large falculate sickles that are proportionaly equal in length to the length of their handles. The two largest pairs of marginal hooks are positioned closest to the opisthaptoral peduncle, the neighbouring two pairs of medium-sized marginal hook sickles are situated along the lateral margins of the opisthaptor. Four pairs of smallest marginal hooks are positioned along the posterior margin of the opisthaptor. The male copulatory organ consists of a muscular pouch armed with approximately 30 gracile spines. Phylogenetic analyses of partial sequences of the 18S rDNA using Maximum Likelihood and Bayesian Inference placed the new genus within the lineage of solely African genera and suggests Afrogyrodactylus Paperna, 1968, Citharodactylus Prikrylova, Shinn et Paladini, 2017 and Mormyrogyrodactylus Luus-Powell, Mashego et Khalil, 2003 as genera most closely related to the new genus

A Process and Outcome Evaluation of a Shelter for Homeless Young Women

To evaluate the processes and outcomes of a short-term shelter, both quantitative and qualitative data were gathered via participant observation, focus group interviews with shelter staff and residents, and individual interviews with a sample of 40 young women who had been homeless prior to using the shelter. The process evaluation showed that the shelter staff strived to utilize an empowerment philosophy in their relationships with residents, but that there were many challenges to implementing this philosophy. The outcome evaluation showed that, at a 3-month follow-up, the participants reported significant improvements in housing, income, independence, and life satisfaction, but most continued to experience poverty and a number of other difficulties. The results were discussed in terms of the implications for future research and the value and limitations of shelters for dealing with homeless youth. The need for more sustained and comprehensive program interventions and supportive social policies was underscored

Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex.

Complex network topology is characteristic of many biological systems, including anatomical and functional brain networks (connectomes). Here, we first constructed a structural covariance network from MRI measures of cortical thickness on 296 healthy volunteers, aged 14-24 years. Next, we designed a new algorithm for matching sample locations from the Allen Brain Atlas to the nodes of the SCN. Subsequently we used this to define, transcriptomic brain networks by estimating gene co-expression between pairs of cortical regions. Finally, we explored the hypothesis that transcriptional networks and structural MRI connectomes are coupled. A transcriptional brain network (TBN) and a structural covariance network (SCN) were correlated across connection weights and showed qualitatively similar complex topological properties: assortativity, small-worldness, modularity, and a rich-club. In both networks, the weight of an edge was inversely related to the anatomical (Euclidean) distance between regions. There were differences between networks in degree and distance distributions: the transcriptional network had a less fat-tailed degree distribution and a less positively skewed distance distribution than the SCN. However, cortical areas connected to each other within modules of the SCN had significantly higher levels of whole genome co-expression than expected by chance. Nodes connected in the SCN had especially high levels of expression and co-expression of a human supragranular enriched (HSE) gene set that has been specifically located to supragranular layers of human cerebral cortex and is known to be important for large-scale, long-distance cortico-cortical connectivity. This coupling of brain transcriptome and connectome topologies was largely but not entirely accounted for by the common constraint of physical distance on both networks

A transcriptomic axis predicts state modulation of cortical interneurons

Transcriptomics has revealed that cortical inhibitory neurons exhibit a great diversity of fine molecular subtypes1-6, but it is not known whether these subtypes have correspondingly diverse patterns of activity in the living brain. Here we show that inhibitory subtypes in primary visual cortex (V1) have diverse correlates with brain state, which are organized by a single factor: position along the main axis of transcriptomic variation. We combined in vivo two-photon calcium imaging of mouse V1 with a transcriptomic method to identify mRNA for 72 selected genes in ex vivo slices. We classified inhibitory neurons imaged in layers 1-3 into a three-level hierarchy of 5 subclasses, 11 types and 35 subtypes using previously defined transcriptomic clusters3. Responses to visual stimuli differed significantly only between subclasses, with cells in the Sncg subclass uniformly suppressed, and cells in the other subclasses predominantly excited. Modulation by brain state differed at all hierarchical levels but could be largely predicted from the first transcriptomic principal component, which also predicted correlations with simultaneously recorded cells. Inhibitory subtypes that fired more in resting, oscillatory brain states had a smaller fraction of their axonal projections in layer 1, narrower spikes, lower input resistance and weaker adaptation as determined in vitro7, and expressed more inhibitory cholinergic receptors. Subtypes that fired more during arousal had the opposite properties. Thus, a simple principle may largely explain how diverse inhibitory V1 subtypes shape state-dependent cortical processing

Morphometric Similarity Networks Detect Microscale Cortical Organization and Predict Inter-Individual Cognitive Variation.

Macroscopic cortical networks are important for cognitive function, but it remains challenging to construct anatomically plausible individual structural connectomes from human neuroimaging. We introduce a new technique for cortical network mapping based on inter-regional similarity of multiple morphometric parameters measured using multimodal MRI. In three cohorts (two human, one macaque), we find that the resulting morphometric similarity networks (MSNs) have a complex topological organization comprising modules and high-degree hubs. Human MSN modules recapitulate known cortical cytoarchitectonic divisions, and greater inter-regional morphometric similarity was associated with stronger inter-regional co-expression of genes enriched for neuronal terms. Comparing macaque MSNs with tract-tracing data confirmed that morphometric similarity was related to axonal connectivity. Finally, variation in the degree of human MSN nodes accounted for about 40% of between-subject variability in IQ. Morphometric similarity mapping provides a novel, robust, and biologically plausible approach to understanding how human cortical networks underpin individual differences in psychological functions

Flexible Working and Performance: A Systematic Review of the Evidence for a Business Case

Interest in the outcomes of flexible working arrangements dates from the mid 1970s, when researchers attempted to assess the impact of flexitime on worker performance. This paper reviews the literature on the link between flexible working arrangements and performance related outcomes. Taken together, the evidence fails to demonstrate a business case for the use of flexible working arrangements. This paper attempts to explain the findings by analysing the theoretical and methodological perspectives adopted, as well as the measurements and designs used. In doing so, gaps in this vast and disparate literature are identified and a research agenda is developed

Sensory Communication

Contains table of contents for Section 2, an introduction and reports on twelve research projects.National Institutes of Health Grant 5 R01 DC00117National Institutes of Health Contract 2 P01 DC00361National Institutes of Health Grant 5 R01 DC00126National Institutes of Health Grant R01-DC00270U.S. Air Force - Office of Scientific Research Contract AFOSR-90-0200National Institutes of Health Grant R29-DC00625U.S. Navy - Office of Naval Research Grant N00014-88-K-0604U.S. Navy - Office of Naval Research Grant N00014-91-J-1454U.S. Navy - Office of Naval Research Grant N00014-92-J-1814U.S. Navy - Naval Training Systems Center Contract N61339-93-M-1213U.S. Navy - Naval Training Systems Center Contract N61339-93-C-0055U.S. Navy - Naval Training Systems Center Contract N61339-93-C-0083U.S. Navy - Office of Naval Research Grant N00014-92-J-4005U.S. Navy - Office of Naval Research Grant N00014-93-1-119

Time as a bridge from brain to behavior

Time has mystified philosophers, artists, and scientists for centuries, but only recently has it become possible to study the neurobiology of time. Time is critical for cognition, and the mechanisms through which it impacts neural processes, such as those for decision-making, are starting to be better understood. Standard mathematical models for decision-making are not suited to studying stimuli or strategies which change over time, so we construct a generalization of a standard model as well as an efficient computational framework, providing insight at both the behavioral and the neural level. We use this framework to understand behavior and single-neuron recordings in the frontal eye field (FEF) for a perceptual decision-making task with stimuli which change over time. First, we perform a high-throughput screen across potential models of decision-making strategies to understand how uncertainty in stimulus onset influences decision-making. Next, we examine the neural response immediately after the change in evidence, and show how this can be used to further clarify decision-making strategy. We also show that a signal representing elapsed time predicted by several behavioral strategies is abundant in FEF neurons. Finally, we determine how high-dimensional data analysis might be impacted by the presence of signals which vary smoothly over time. Overall, this demonstrates the critical role of time in cognition, providing concrete details of its strategic role and neural implementation. This sets the stage for the study of time in neurological and neuropsychiatric disorders