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FIGURE 3 in Extended diagnosis of the type species of Pseudogonatodes Ruthven 1915 (Gekkota Sphaerodactylidae)
FIGURE 3. High resolution computed tomography of the skull of Pseudogonatodes furvus (MCZ:Herp:R-29700) A–C, and P. barbouri (MCZ:Herp:R-14385) D–F.
FIGURE 1 in Extended diagnosis of the type species of Pseudogonatodes Ruthven 1915 (Gekkota Sphaerodactylidae)
FIGURE 1. Detail of external morphology of Pseudogonatodes furvus (CBUMAG:REP: 00283). (A) Head in dorsal view: blue = rostrals, yellow = postrostrals, violet = supraciliary plate. (B) Head in ventral view: orange = mental, purple = postmentals. (C) Head in lateral view: orange = loreals, yellow = supralabials, blue = infralabials. (D) Dorsals at midbody. (E) Ventrals at midbody. (F) Subcaudal patter: yellow = midventrals (denoted by Arabic numbers), gray = laterals (denoted by apostrophe [']). (G) Left hand: orange = lamellae under fourth finger. (H) Right foot: red = lamellae under fourth toe. Digital drawings by Sebastian Contreras Valencia.
FIGURE 2 in Extended diagnosis of the type species of Pseudogonatodes Ruthven 1915 (Gekkota Sphaerodactylidae)
FIGURE 2. Holotype of Pseudogonatodes furvus (UMMZ 47782), male. Photographs modified from University of Michigan Library Digital Collections (http://quod.lib.umich.edu). All the images in the collection are licensed under the Creative Commons Attribution-ShareAlike 4.0 International license (CC-BY-SA 4.0). Accessed: July 04, 2020.
FIGURE 5 in Extended diagnosis of the type species of Pseudogonatodes Ruthven 1915 (Gekkota Sphaerodactylidae)
FIGURE 5. Geographic distribution of Pseudogonatodes furvus in the northwestern and western slopes of the Sierra Nevada de Santa Marta, Magdalena, Colombia. Shape file of Google Terrain ©
Contrasting fungal responses to wildfire across different ecosystem types
<p>We took topsoil samples in burned and unburned areas across two California ecosystem types (Sonoma, California, United States) with differing fire ecologies in the immediate aftermath of a damaging wildfire in 2017. From our soil samples, we extracted DNA, amplified and sequenced fungal communities, and also measured chemistry (C%, N% and pH). Soil fungal communities of fire‐dependent oak woodlands differ from those of neighbouring mixed evergreen forests. The latter are more strongly altered compositionally by fire than the former. This repository contains code to run the analyses we presented in the associated paper (doi: 10.1111/mec.15767), as well as a phyloseq object with the molecular data and a few CSVs with the sample metadata.</p>
Progression of Wave Breaker Types on a Plane Impermeable Slope, Depending on Experimental Design DATASETs
<p>Data set from the CIAO and IH2VOF experimental tests.</p>
Evolution of honey resistance in experimental populations of bacteria depends on the type of honey, and has no major side effects for antibiotic susceptibility
<p><span><span><span><span><span><span><span><span><span><span><span>With rising antibiotic resistance, alternative treatments for communicable diseases are increasingly relevant. One possible alternative for some types of infections is honey, used in wound care since before 2000 BCE and more recently in licensed, medical-grade products. However, it is unclear whether medical application of honey results in the evolution of bacterial honey resistance, and whether this has collateral effects on other bacterial traits such as antibiotic resistance. Here, we used single-step screening assays and serial transfer at increasing concentrations to isolate honey-resistant mutants of <i>Escherichia coli</i>. We only detected bacteria with consistently increased resistance to the honey they evolved in with two of the four tested honey products, and the observed increases were small (maximum two-fold increase in IC<sub>90</sub>). Genomic sequencing and experiments with single-gene knockouts showed a key mechanism by which bacteria increased their honey resistance was by mutating genes involved in detoxifying methylglyoxal, which contributes to the antibacterial activity of <i>Leptospermum</i> honeys. Crucially, we found no evidence that honey adaptation conferred cross-resistance or collateral sensitivity against nine antibiotics from six different classes. These results reveal constraints on bacterial adaptation to different types of honey, improving our ability to predict downstream consequences of wider honey application in medicine.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: Disentangling the Pelomedusa complex using type specimens and historical DNA (Testudines: Pelomedusidae)
Recent research has shown that the helmeted terrapin (Pelomedusa subrufa), a species that occurs throughout sub-Saharan Africa, in Madagascar and the southwestern Arabian Peninsula, consists of several deeply divergent genetic lineages. Here we examine all nominal taxa currently synonymized with Pelomedusa subrufa (Bonnaterre, 1789) and provide mitochondrial DNA sequences of type specimens or topotypic material for most taxa. Lectotypes are designated for Testudo galeata Schoepff, 1792, Pentonyx capensis Duméril & Bibron, 1835, Pelomedusa nigra Gray, 1863, Pelomedusa galeata var. disjuncta Vaillant & Grandidier, 1910, and Pelomedusa galeata damarensis Hewitt, 1935. For Pelomedusa gasconi Rochebrune, 1884, a taxon without preserved type material, a neotype is designated. Type material of Pentonix americana Cornalia, 1849, a nominal species without credible type locality, is lost and its identity remains questionable. Also the holotype of Pelomedusa galeata orangensis Hewitt, 1935 is lost, but its allocation to the only genetic lineage occurring in South Africa is unambiguous. Phylogenetic analyses of type sequences or topotypic material reveal that the remaining nominal taxa represent three of the nine previously identified lineages of Pelomedusa. Among these three lineages is the South African one. Type specimens of Pentonyx gehafie Rüppell, 1835 correspond to an additional distinct lineage. The present study provides a sound basis for a subsequent integrative taxonomic revision of the Pelomedusa complex.
Data from: Of 11 candidate steroids, corticosterone concentration standardized for mass is the most reliable steroid-biomarker of nutritional stress across different feather types
<p>1. Measuring corticosterone in feathers has become an informative tool in avian ecology, enabling researchers to investigate carry-over effects and responses to environmental variability. Few studies have, however, explored whether corticosterone is the only hormone expressed in feathers, and is the most indicative of environmental stress. Essential questions remain as to how to compare hormone concentrations across different types of feathers and whether preening adds steroids, applied after feather growth. 2. We used liquid chromatography coupled to tandem mass spectrometry to quantify a suite of 11 steroid hormones in back, breast, tail, and primary feathers naturally grown at overlapping time intervals by rhinoceros auklet Cerorhinca monocerata captive-reared fledglings and wild-caught juveniles. The captive-reared birds were raised on either a restricted or control diet. Measured steroids included intermediates in the adrenal steroidogenesis pathway to glucocorticoids and the sex steroids pathway to androgens and estrogens. 3. Corticosterone was detected in the majority of feathers of each type. We also detected cortisone in back feathers, androstenedione in breast feathers, and testosterone in primary feathers. Captive fledglings raised on a restricted diet had higher concentrations of corticosterone in all four feather types than captive fledglings raised on a control diet. Corticosterone concentrations were reliably repeatable across feather types when standardized for feather mass, but not for feather length. Of the seven hormones looked for in uropygial gland secretions, only corticosterone was detected in one out of 23 samples. 4. We conclude that corticosterone is the best feather-steroid biomarker for detection of developmental nutritional stress, as it was the only hormone to manifest a signal of nutritional stress, and that exposure to stress can be compared among different feather types when corticosterone concentrations are standardized by feather mass.</p>
FIGURES 25–26 in Catalog of the Diptera types described by Camillo Rondani
FIGURES 25–26. Rondani Collection in Oxford. 25. Labels of the species Phytophaga cerealis Rondani, 1843. 26. One of the boxes showing how Diptera are arranged.
FIGURES 28–29 in Catalog of the Diptera types described by Camillo Rondani
FIGURES 28–29. Rondani Collection in Pavia. 28. One of the boxes showing how Diptera are arranged and labeled. 29. Rondani's original labels.
FIGURES 21–22 in Catalog of the Diptera types described by Camillo Rondani
FIGURES 21–22. Rondani Collection in Naples. 21. One of the boxes showing how Diptera are arranged and labeled. 22. Cabinet reserved for the Costa collection.
FIGURES 16–17. 16 in Catalog of the Diptera types described by Camillo Rondani
FIGURES 16–17. 16. Targioni Tozzetti's expense note for his stay in Parma (30 October 1881). 17. Shipment boxes.
FIGURES 14–15 in Catalog of the Diptera types described by Camillo Rondani
FIGURES 14–15. Letter sent to Prof. Adolfo Targioni Tozzetti by the "Physical and Natural Sciences Section" of the Royal Institute of Practical Higher Studies and Specialization (22 June 1881).
FIGURES 10–13 in Catalog of the Diptera types described by Camillo Rondani
FIGURES 10–13. Letter sent to Prof. Adolfo Targioni Tozzetti by Pellegrino Strobel (21 November 1868).
FIGURES 18–20 in Catalog of the Diptera types described by Camillo Rondani
FIGURES 18–20. Rondani Collection in Florence. 18. Cabinet reserved for the collection. 19. One of the boxes showing how Diptera are arranged and labeled. 20. Rondani's original labels.
FIGURES 23–24 in Catalog of the Diptera types described by Camillo Rondani
FIGURES 23–24. Rondani Collection in Genoa. 23. One of the boxes showing how Diptera are arranged and labeled. 24. Rondani's original labels.
FIGURE 27 in Catalog of the Diptera types described by Camillo Rondani
FIGURE 27. Rondani Collection in Bologna. One of the boxes showing how Diptera are arranged and labeled.
Data from: Are Niemann-Pick type C proteins key players in cnidarian-dinoflagellate endosymbioses?
The symbiotic interaction between cnidarians, such as corals and sea anemones, and the unicellular algae Symbiodinium is regulated by yet poorly understood cellular mechanisms, despite the ecological importance of coral reefs. These mechanisms, including host-symbiont recognition and metabolic exchange, control symbiosis stability under normal conditions, but also lead to symbiosis breakdown (bleaching) during stress. This study describes the repertoire of the sterol-trafficking proteins Niemann-Pick type C (NPC1 and NPC2) in the symbiotic sea anemone Anemonia viridis. We found one NPC1 gene instead of two in vertebrates. While only one NPC2 gene is present in most metazoans, this gene has been duplicated in cnidarians and we detected four NPC2 genes in A. viridis. However, only one gene (AvNPC2-d) was upregulated in symbiotic sea anemones and displayed higher expression in the gastrodermis (symbiont-containing tissue) than in the epidermis. We performed immunolabeling experiments on tentacle cross sections and demonstrated that the AvNPC2-d protein was closely associated with symbiosomes. In addition, AvNPC1 and AvNPC2-d gene expression was strongly downregulated during stress, especially at the onset of symbiosis breakdown. These data suggest that AvNPC2-d is involved in both the stability and dysfunction of cnidarian-dinoflagellate symbioses.
Data from: Egg mimicry by the pacific koel: mimicry of one host facilitates exploitation of other hosts with similar egg types
When brood parasites exploit multiple host species, egg rejection by hosts may select for the evolution of host-specific races, where each race mimics a particular host's egg type. However, some brood parasites that exploit multiple hosts with the ability to reject foreign eggs appear to have only a single egg type. In these cases, it is unclear how the parasite egg escapes detection by its hosts. Three possible explanations are: (i) host-specific races are present, but differences in egg morphology are difficult for the human eye to detect; (ii) the brood parasite evolves a single egg type that is intermediate in appearance between the eggs of its hosts; (iii) or the parasite evolves mimicry of one of its hosts, which subsequently allows it to exploit other species with similar egg morphology. Here we test these possibilities by quantifying parameters of egg appearance of the brood-parasitic Pacific Koel (Eudynamys orientalis) and seven of its hosts. Koel eggs laid in the nests of different hosts did not show significant differences in colour or pattern, suggesting that koels have not evolved host-specific races. Koel eggs were similar in colour, luminance and pattern to the majority of hosts, but were significantly more similar in colour and luminance to one of the major hosts than to two other major hosts, supporting hypothesis (iii). Our findings suggest that mimicry of one host can allow a brood parasite to exploit new hosts with similar egg morphologies, which could inhibit the evolution of host defences in naïve hosts.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.