Early environment influences later performance in fishes

Conditions fish encounter during embryogenesis and early life history can leave lasting effects not only on morphology, but also on growth rate, life‐history and behavioural traits. The ecology of offspring can be affected by conditions experienced by their parents and mother in particular. This review summarizes such early impacts and their ecological influences for a variety of teleost species, but with special reference to salmonids. Growth and adult body size, sex ratio, egg size, lifespan and tendency to migrate can all be affected by early influences. Mechanisms behind such phenotypically plastic impacts are not well known, but epigenetic change appears to be one central mechanism. The thermal regime during development and incubation is particularly important, but also early food consumption and intraspecific density can all be responsible for later life‐history variation. For behavioural traits, early experiences with effects on brain, sensory development and cognition appear essential. This may also influence boldness and other social behaviours such as mate choice. At the end of the review, several issues and questions for future studies are given.     

New data on mollusks from the Miocene (Tarkhanian-Chokrakian) of northern Sinop Province,Turkey

An insufficiently known bivalve and gastropod assemblage from the Early-Middle Miocene (Tarkhanian-Chokrakian) of northern Sinop Province (Turkey), is analyzed. Environments of the assemblage are reconstructed for the Chokrakian as subtidal, with prevailing lime and sandy bottom and good aeration, and partially well vegetated. Impoverishment of the mollusk biocoenose in this part of the marine basin (only 18 bivalve and 22 gastropod species recorded) compared to other areas, including the closest regions, Bulgaria on the west and Georgia on the east, is emphasized. The relatively low diversity of the fauna is probably connected not only with insufficient collecting, but with special hydrological conditions. A special aspect of the fauna is highlighted by the presence of the bivalve Circomphalus foliaceolamellosus subplicatus (Orb.), which is rare in the Chokrakian.     

Immunopathological Changes in the Brain of Immunosuppressed Mice Experimentally Infected with Toxocara canis

Toxocariasis is a soil-transmitted helminthozoonosis due to infection of humans by larvae of Toxocara canis. The disease could produce cognitive and behavioral disturbances especially in children. Meanwhile, in our modern era, the incidence of immunosuppression has been progressively increasing due to increased incidence of malignancy as well as increased use of immunosuppressive agents. The present study aimed at comparing some of the pathological and immunological alterations in the brain of normal and immunosuppressed mice experimentally infected with T. canis. Therefore, 180 Swiss albino mice were divided into 4 groups including normal (control) group, immunocompetent T. canis-infected group, immunosuppressed group (control), and immunosuppressed infected group. Infected mice were subjected to larval counts in the brain, and the brains from all mice were assessed for histopathological changes, astrogliosis, and IL-5 mRNA expression levels in brain tissues. The results showed that under immunosuppression, there were significant increase in brain larval counts, significant enhancement of reactive gliosis, and significant reduction in IL-5 mRNA expression. All these changes were maximal in the chronic stage of infection. In conclusion, the immunopathological alterations in the brains of infected animals were progressive over time, and were exaggerated under the effect of immunosuppression as did the intensity of cerebral infection.     

An evaluation of semi‐automated methods for collecting ecosystem‐level data in temperate marine systems

Historically, marine ecologists have lacked efficient tools that are capable of capturing detailed species distribution data over large areas. Emerging technologies such as high‐resolution imaging and associated machine‐learning image‐scoring software are providing new tools to map species over large areas in the ocean. Here, we combine a novel diver propulsion vehicle (DPV) imaging system with free‐to‐use machine‐learning software to semi‐automatically generate dense and widespread abundance records of a habitat‐forming algae over ~5,000 m² of temperate reef. We employ replicable spatial techniques to test the effectiveness of traditional diver‐based sampling, and better understand the distribution and spatial arrangement of one key algal species. We found that the effectiveness of a traditional survey depended on the level of spatial structuring, and generally 10–20 transects (50 × 1 m) were required to obtain reliable results. This represents 2–20 times greater replication than have been collected in previous studies. Furthermore, we demonstrate the usefulness of fine‐resolution distribution modeling for understanding patterns in canopy algae cover at multiple spatial scales, and discuss applications to other marine habitats. Our analyses demonstrate that semi‐automated methods of data gathering and processing provide more accurate results than traditional methods for describing habitat structure at seascape scales, and therefore represent vastly improved techniques for understanding and managing marine seascapes.     

A validated model of passive skeletal muscle to predict force and intramuscular pressure

The passive properties of skeletal muscle are often overlooked in muscle studies, yet they play a key role in tissue function in vivo. Studies analyzing and modeling muscle passive properties, while not uncommon, have never investigated the role of fluid content within the tissue. Additionally, intramuscular pressure (IMP) has been shown to correlate with muscle force in vivo and could be used to predict muscle force in the clinic. In this study, a novel model of skeletal muscle was developed and validated to predict both muscle stress and IMP under passive conditions for the New Zealand White Rabbit tibialis anterior. This model is the first to include fluid content within the tissue and uses whole muscle geometry. A nonlinear optimization scheme was highly effective at fitting model stress output to experimental stress data (normalized mean square error or NMSE fit value of 0.993) and validation showed very good agreement to experimental data (NMSE fit values of 0.955 and 0.860 for IMP and stress, respectively). While future work to include muscle activation would broaden the physiological application of this model, the passive implementation could be used to guide surgeries where passive muscle is stretched.