Stressor interactions in freshwater habitats: Effects of cold water exposure and food limitation on early‐life growth and upper thermal tolerance in white sturgeon,Acipenser transmontanus

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Photosynthesis supported by a chlorophyll f-dependent,entropy-driven uphill energy transfer in Halomicronema hongdechloris cells adapted to far-red light

Photosynthesis Research - The phototrophic cyanobacterium Halomicronema hongdechloris shows far-red light-induced accumulation of chlorophyll (Chl) f, but the involvement of the pigment in...     

Outmigration pathways of stocked juvenile European sturgeon (Acipenser sturio L., 1758) in the Lower Rhine River,as revealed by telemetry

Working towards a future Rhine Sturgeon Action Plan the outmigration pathways of stocked juvenile European sturgeon (Acipenser sturio L., 1758) were studied in the River Rhine in 2012 and 2015 using the NEDAP Trail system. A total of 87 sturgeon of 3 to 5 years old (n = 43 in 2012, n = 44 in 2015) were implanted with transponders and released in May and June in the river Rhine at the Dutch‐German border, approximately 160 km from the sea. In total three sturgeons (3%) were found dead on river banks within seven days after the release. Based upon their wounds these sturgeons were likely hit by ship‐propellers. Tracking results were obtained from 57 (66%) of the sturgeons, of which 39 (45%) indicated movement into the Port of Rotterdam. Here the sturgeons remained for an average of two weeks, which suggests they spent time to acclimatize to higher salinities before entering the North Sea. Of the 45 (52%) sturgeons that were confirmed to have entered the North Sea, ten (22%) were recaptured (mainly by shrimpers and gill‐nets) close to the Dutch coastline; nine were alive and were released. From the results we obtained the preferred outmigration pathways, movement speeds and an indication of impacting factors (i.e. ship propellers and bycatch). Bycatches provided also localisations information in the coastal area. A next step to complete this work would be to assess habitat selection in freshwater and downstream migration of young of the year (YOY sturgeons) in the Lower Rhine.     

Evolution,diversity and interactions with past human populations of recently extinct Pholidoscelis lizards (Squamata: Teiidae) from the Guadeloupe Islands (French West-Indies)

This paper aims to demonstrate how subfossil bone remains from Pleistocene and Holocene deposits can help to reconstruct the history of recently extinct taxa through the example of Pholidoscelis lizards from the Guadeloupe Islands in the French West Indies. To achieve this, we conducted a new anatomical and zooarchaeological study of fossil Pholidoscelis remains collected from 23 archaeological and paleontological deposits on the Guadeloupe Islands from which this genus is nowadays absent. Our results shed light on the past existence of large Pholidoscelis lizards on all the Guadeloupe islands but also on the difficulties of confident specific identification for these remains. Nevertheless, we suggest a possible past occurrence of the now extinct Pholidoscelis major on nearly all of the Guadeloupe islands. In addition, we identified a new Pholidoscelis species, Pholidoscelis turukaeraensis sp. nov., on Marie-Galante Island, where no Pholidoscelis lizards were previously reported. This new species underwent an increase in size after the end of the Pleistocene period, possibly due to reduced predation pressure. We also highlight the consumption of Pholidoscelis lizards by pre-Columbian Amerindians and the huge impact of European colonization, which led to the extinction of all these lizards in less than 300 years.http://zoobank.org/urn:lsid:zoobank.org:pub:15C39436-A083-483F-B35E-78807B606904     

Fine scale waterbody data improve prediction of waterbird occurrence despite coarse species data

While modelling habitat suitability and species distribution, ecologists must deal with issues related to the spatial resolution of species occurrence and environmental data. Indeed, given that the spatial resolution of species and environmental datasets range from centimeters to hundreds of kilometers, it underlines the importance of choosing the optimal combination of resolutions to achieve the highest possible modelling prediction accuracy. We evaluated how the spatial resolution of land cover/waterbody datasets (meters to 1 km) affect waterbird habitat suitability models based on atlas data (grid cell of 12 × 11 km). We hypothesized that the area, perimeter and number of waterbodies computed from high resolution datasets would explain distributions of waterbirds better because coarse resolution datasets omit small waterbodies affecting species occurrence. Specifically, we investigated which spatial resolution of waterbodies better explain the distribution of seven waterbirds nesting on ponds/lakes with areas ranging from 0.1 ha to hundreds of hectares. Our results show that the area and perimeter of waterbodies derived from high resolution datasets (raster data with 30 m resolution, vector data corresponding with map scale 1:10 000) explain the distribution of the waterbirds better than those calculated using less accurate datasets despite the coarse grain of the species data. Taking into account the spatial extent (global vs regional) of the datasets, we found the Global Inland Waterbody Dataset to be the most suitable for modelling distribution of waterbirds. In general, we recommend using land cover data of a resolution sufficient to capture the smallest patches of the habitat suitable for a given species’ presence for both fine and coarse grain habitat suitability and distribution modelling.     

Predicting drug polypharmacology from cell morphology readouts using variational autoencoder latent space arithmetic

A variational autoencoder (VAE) is a machine learning algorithm, useful for generating a compressed and interpretable latent space. These representations have been generated from various biomedical data types and can be used to produce realistic-looking simulated data. However, standard vanilla VAEs suffer from entangled and uninformative latent spaces, which can be mitigated using other types of VAEs such as β-VAE and MMD-VAE. In this project, we evaluated the ability of VAEs to learn cell morphology characteristics derived from cell images. We trained and evaluated these three VAE variants—Vanilla VAE, β-VAE, and MMD-VAE—on cell morphology readouts and explored the generative capacity of each model to predict compound polypharmacology (the interactions of a drug with more than one target) using an approach called latent space arithmetic (LSA). To test the generalizability of the strategy, we also trained these VAEs using gene expression data of the same compound perturbations and found that gene expression provides complementary information. We found that the β-VAE and MMD-VAE disentangle morphology signals and reveal a more interpretable latent space. We reliably simulated morphology and gene expression readouts from certain compounds thereby predicting cell states perturbed with compounds of known polypharmacology. Inferring cell state for specific drug mechanisms could aid researchers in developing and identifying targeted therapeutics and categorizing off-target effects in the future.     

Chronic Collection of Cerebrospinal Fluid from Rhesus Macaques (Macaca mulatta) with Cisterna Magna Ports: Update on Refinements

More than 20 y ago, we developed an animal model for chronic and continuous collection of cerebrospinal fluid (CSF) from conscious rhesus macaques. Since our previous publication in 2003, we have successfully implanted 168 rhesus macaques using this approach. Our experience enables us to provide up-to-date information regarding the model, including refinements to our implant design, reductions in maintenance, and new procedures for dealing with contamination. The results of our experiences have reduced the number of surgeries required and helped to increase the longevity of the implant, with some functioning for more than 18 y. Building on our success in rhesus macaques, we attempted to develop similar animal models in the African green monkeys and dogs but have been unable to develop reliable chronic models for CSF collection in these species.Abbreviation: CMP, cisterna magna port; CSF, cerebrospinal fluid

Cerebrospinal (CSF) biomarkers and pharmacokinetics are reliable tools for monitoring the therapeutic effect of compounds used for the treatment of various neurodegenerative diseases. CSF can be collected by using several methods, including lumbar and cisterna magna punctures or implanted devices.^{3,6,8,9,11-13} Each method has its own specific challenges but no matter which technique is used, performing CSF collections safely is imperative to avoiding risks to the animals and to providing the best CSF samples for analysis.¹ To support our research focus on neurocognitive disorders (including Alzheimer disease, Parkinson disease, and sleep disorders), we developed an NHP model of chronic CSF collection (the cisterna magna port [CMP] model) more than 20 y ago.⁴ This model allows safe, repeatable and reliable collections of CSF samples from the cisterna magna in conscious rhesus macaques (Macaca mulatta). The information summarized herein updates this animal model since its introduction in 2003 and reflects our 18 additional years of experience with it. We also provide information regarding our attempts to develop CMP models in African green monkeys and dogs. We recommend that readers review the 2003 article for further information and understanding of the CMP model.⁴