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Fig. 8 in New Lower Kimmeridgian ataxioceratin ammonite from the eastern Iberian Chain, Spain: Systematic, biogeographic, and biostratigraphic relevance
Fig. 8. Ataxioceratin ammonite Geyericeras aragoniense sp. nov. [M] from the Lower Kimmeridgian Ataxioceras lothari Biozone, A. lothari Subzone, G. aragoniense biohorizon in the eastern Iberian Chain. Paratype UGR MPR.36.20; Guadalope River section at the Villarluengo area, in right (A) and left (B) side views. Arrows indicate the beginning of the body chamber. Scale for shell size reference.
Fig. 7 in New Lower Kimmeridgian ataxioceratin ammonite from the eastern Iberian Chain, Spain: Systematic, biogeographic, and biostratigraphic relevance
Fig. 7. Ataxioceratin ammonite Geyericeras aragoniense sp. nov. [m] from the Lower Kimmeridgian Ataxioceras lothari Biozone, A. lothari Subzone, G. aragoniense biohorizon in the eastern Iberian Chain, Spain. A. Holotype UGR MLG.23.20; Reservoir of Calanda section in the Calanda area, in left (A1) and right (A2) side views. B. Paratype UGR MPC.29.8; Morrón section at the Calanda area, in right side view. C. Paratype UGR MPC.28.15; Morrón section at the Calanda area, in left side view. D. Paratype UGR MPC.28.73; Morrón section at the Calanda area, in right side view. Arrows indicate the beginning of the body chamber. Scale for shell size reference.
Fig. 1 in New Lower Kimmeridgian ataxioceratin ammonite from the eastern Iberian Chain, Spain: Systematic, biogeographic, and biostratigraphic relevance
Fig. 1. Location (C), palaeogeography (B), and studied sections (A) with indication of Geyericeras records together with others ataxioceratins relevant for biostratigraphic correlation. Sections labeling as follows: Villarluengo [MPR], Berge−Molinos [MBV, MVP], Alcorisa−Gallipuén [MTG], and Calanda [MLG, MPC] areas. FAD and LAD for First and Last Appearance Data, respectively.
Dataset and code: Decarbonizing lithium-ion battery primary raw materials supply chain: Available strategies, mitigation potential and challenges
<p>Repository to share the data and code associated with the scientific article <strong>Istrate et al. Decarbonizing lithium-ion battery primary raw materials supply chain: Available strategies, mitigation potential and challenges. Joule (2024)</strong>. The repository contains data files and code to import the life cycle inventories (LCIs), reproduce the results, and generate the figures presented in the article.</p>
Electrochemical data plotted in A. Fasano, C. Guendon, A. Jacq-Bailly, A. Kpebe, J. Wozniak, C. Baffert, M. del Barrio, V. Fourmond, M. Brugna, C. Léger , « A chimeric NiFe hydrogenase heterodimer to assess the role of the electron transfer chain in tuning the enzyme's catalytic bias and oxygen tolerance », J. Am. Chem. Soc. 145, 36, 20021–20030 (2023). doi: 10.1021/jacs.3c06895
<p>Text file of all the electrochemical data shown in the following paper: A. Fasano, C. Guendon, A. Jacq-Bailly, A. Kpebe, J. Wozniak, C. Baffert, M. del Barrio, V. Fourmond, M. Brugna, C. Léger , « A chimeric NiFe hydrogenase heterodimer to assess the role of the electron transfer chain in tuning the enzyme's catalytic bias and oxygen tolerance », J. Am. Chem. Soc. 145, 36, 20021–20030 (2023). <a href="dx.doi.org/10.1021/jacs.3c06895" target="_blank" rel="noopener">doi: 10.1021/jacs.3c06895</a></p>
Fig. 1 in Polymerase chain reaction and gyrA nucleotide sequence analysis of Wolbachia endosymbionts (Rickettsiales: Anaplasmataceae) in various species of Culicidae, Cimex lectularius (Hemiptera: Cimicidae) and Dirofilaria immitis (Rhabditida: Onchocercidae)
Fig. 1. Phylogenetic tree based on Maximum Likelihood depicting the grouping of Wolbachia from various hosts based on analysis of the gyrA gene. The numerical value displayed on branches is the bootstrap value (1,000 replicates), and branches with values below 50% are collapsed. The tree illustrates that gyrA sequences distinguish Wolbachia subtypes based on host taxonomy, demonstrating that this gene may contribute to Wolbachia strain typing projects and future phylogenetic analysis.
Humatch - fast, gene-specific joint humanisation of antibody heavy and light chains
<p>Antibodies are a popular and powerful class of therapeutic due to their ability to exhibit high affinity and specificity to target proteins. However, the majority of antibody therapeutics are not genetically human, with initial therapeutic designs typically obtained from animal models. Humanisation of these precursors is essential to reduce immunogenic risks when administered to humans.</p> <p>To aid humanisation we developed <a href="https://github.com/oxpig/Humatch" target="_blank" rel="noopener">Humatch</a>, a computational tool designed to offer experimental-like joint humanisation of heavy and light chains in seconds. Humatch consists of three lightweight Convolutional Neural Networks (CNNs) trained to identify human heavy V-genes, light V-genes, and well-paired antibody sequences with near-perfect accuracy. We show that these CNNs, alongside germline similarity, can be used for fast humanisation that aligns well with known experimental data. Throughout the humanisation process, a sequence is guided towards a specific target gene and away from others via multiclass CNN outputs and gene-specific germline data. This guidance ensures final humanised designs do not sit `between' genes, a trait that is not naturally observed. Humatch's optimisation towards specific genes and good VH/VL pairing increases the chances that final designs will be stable and express well and reduces the chances of immunogenic epitopes forming between the two chains.</p> <p>Here we share the data used to train and evaluate Humatch and the CNN weights and germline likeness lookup arrays that guide its humanisation.</p>
A combined NMR and Deep Neural Network approach for enhancing the spectral resolution of aromatic side chains in proteins
<p><span><span>Nuclear magnetic resonance (NMR) spectroscopy has become an important technique in structural biology for characterising the </span><span>structure, </span><span>dynamics</span> <span>and interactions </span><span>of </span><span>macromolecules. Wh</span><span>ile</span><span> a plethora of </span><span>NMR </span><span>methods are </span><span>now </span><span>available to inform on backbone and methyl-bearing </span><span>side-chains</span><span> of proteins, </span><span>a </span><span>characterisation</span><span> of</span><span> aromatic side chains is more challenging and often require</span><span>s</span><span> specific labelling or </span></span><span><span>13</span></span><span><span>C-detection. Here we </span><span>present</span><span> a deep neural network (DNN)</span> <span>named FID-Net-2</span><span>, which transforms NMR spectra recorded on simple uniformly </span></span><span><span>13</span></span><span><span>C labelled samples to yield high-quality </span></span><span><span>1</span></span><span><span>H</span><span>-</span></span><span><span>13</span></span><span><span>C correlation spectra of the aromatic side chains. </span><span>Key to the success of the DNN is the design of a </span><span>complementary</span><span> set of</span> <span>NMR experiment</span><span>s</span><span> that </span><span>produce</span> <span>spectra with </span><span>unique </span><span>features</span><span> to aid the</span> <span>DNN </span><span>prod</span><span>uce</span><span> high-resolution aromatic </span></span><span><span>1</span></span><span><span>H-</span></span><span><span>13</span></span><span><span>C correlation spectra with </span><span>accurate</span><span> intensities. </span><span>The </span><span>reconstructed spectra can be used for quantitative </span><span>purposes as FID-Net-2</span><span> predicts uncertainties </span><span>in </span><span>the </span><span>resulting</span> <span>spectra</span><span>. </span><span>We </span><span>have </span><span>validated</span> <span>the new </span><span>methodology</span><span> experimentally</span> <span>on protein</span><span> samples</span><span> ranging from 7 to 40 </span><span>kDa</span><span> in size. We </span><span>demonstrate</span><span> that the method can</span> <span>accurately reconstruct</span> <span>high resolution </span><span>two-dimensional </span><span>aromatic </span></span><span><span>1</span></span><span><span>H-</span></span><span><span>13</span></span><span><span>C correlation </span><span>maps</span><span>,</span> <span>high resolution </span><span>three-dimensional aromatic</span><span>-</span><span>methyl NOESY spectra to </span><span>facilitate</span><span> aromatic </span></span><span><span>1</span></span><span><span>H-</span></span><span><span>13</span></span><span><span>C assignments</span><span>,</span><span> and </span><span>that the intensities of peaks from the reconstructed</span> <span>aromatic </span></span><span><span>1</span></span><span><span>H-</span></span><span><span>13</span></span><span><span>C correlation maps </span><span>can be used to </span><span>quantitatively </span><span>characterise</span><span> the kinetics of protein folding</span><span>. </span><span>More generally, w</span><span>e believe that this strategy of</span><span> devising new</span><span> NMR</span><span> experiments</span><span> specifically</span> <span>for analysis</span> <span>using customised </span><span>DNN</span><span>s </span><span>represents</span><span> a </span><span>substantial</span><span> advance </span><span>that</span> <span>will</span><span> have a major impact on the study of molecules </span><span>using NMR </span><span>in the years to come.</span></span><span> </span></p>
Supplementary Dataset: Air quality modeling intercomparison and multi-scale ensemble chain for Latin America
<p>The Supplementary dataset of the manuscript titled "Air quality modeling intercomparison and multi-scale ensemble chain for Latin America" can be downloaded via this link:<br>https://swiftbrowser.dkrz.de/public/dkrz_3ab03fbe-db0a-42e8-8b19-caf61d10634d/PAPILA/</p> <p>The data repository contains the model data used in the model intercomparison with six global and regional chemical-transport model over Latin America and the observation datasets used in the model intercomparison. This work presents the first model intercomparison and ensemble construction for Latin America, which was assembled under the Prediction of Air Pollutants in Latin America (PAPILA project (https://papila-h2020.eu/papila). </p>
Polycondensation, Cyclization and Disproportionation of Solid Poly(L-lactide) Trifluoroethyl Esters and the Simultaneous Formation of Extended Chain Crystals and Extended Ring Crystals
<p>This set contains all data used for composing MALDI and DSC figures in "Polycondensation, Cyclization and Disproportionation of Solid Poly(L-lactide) Trifluoroethyl Esters and the Simultaneous Formation of Extended Chain Crystals and Extended Ring Crystals" for publication in POLYMER (Elsevier)</p>
Opinions and data on short food supply chains related policy analysis in 9 EU countries generated in the H2020 SMARTCHAIN Project grant number: 773785
<p>Questionnaires: Opinions and data on short food supply chains related policy analysis in 9 EU countries generated in the H2020 SMARTCHAIN Project grant number: <strong>773785</strong></p>
FIG. 8 in New Monticuliporidae (Bryozoa, Trepostomata) from the Cystoid Limestone Formation (Upper Ordovician) of the Iberian Chains (NE Spain)
FIG. 8. — Monticuliporidae sp. indet., MPZ 2006/110: A, longitudinal thin section showing the large acanthostyles (ac), the peculiar cystiphragms (cy), and the narrow mesozooecia (mz); B, tangential thin section showing the regular hexagonal autozooecia (az) with wall sections having gently beaded (bd) outline, the mesozooecia (mz) in an area where hexagonal autozooecia are not so regular, and large acanthostyles (ac); C, a high-magnification detail of the longitudinal section of an acanthostyle (ac) showing the central lumen on the lower part of the figure and lamination around the lumen; D, a high-magnification detail of the cross section of an acanthostyle (ac) showing the light coloured central lumen (lu) and surrounding dark lamina. Scale bars: A, B, 1 mm; C, D, 0.1 mm.
FIG. 1 in New Monticuliporidae (Bryozoa, Trepostomata) from the Cystoid Limestone Formation (Upper Ordovician) of the Iberian Chains (NE Spain)
FIG. 1. — Outcrops of Ordovician rocks in the Eastern Iberian Chain and their location in the Iberian Peninsula. The lower rectangle marks the location of the study area and measured sections. 1, Valdelaparra; 2, La Peña del Tormo.
FIG. 4. — Monticulipora cystiphragmata n in New Monticuliporidae (Bryozoa, Trepostomata) from the Cystoid Limestone Formation (Upper Ordovician) of the Iberian Chains (NE Spain)
FIG. 4. — Monticulipora cystiphragmata n. sp., schematic tangential section of the holotype (MPZ 2006/134). It shows the disposition of the square- and triangular-shaped mesozooecia (mz), the location of acanthostyles (ac), and the autozooecial aperture shape (az). Scale bar: 0.1 mm.
FIG. 3. — A-D, Monticulipora cystiphragmata n in New Monticuliporidae (Bryozoa, Trepostomata) from the Cystoid Limestone Formation (Upper Ordovician) of the Iberian Chains (NE Spain)
FIG. 3. — A-D, Monticulipora cystiphragmata n. sp.; A, C, longitudinal thin sections of the holotype (MPZ 2006/134) and paratype (MPZ 2006/132),respectively,showing the autozooecia (az), the large cystiphragms (cy) joined in some cases to the opposite wall by diaphragms (dp), and the narrow mesozooecia (mz); B, D, tangential thin sections of the holotype and the same paratype as in C showing square and triangular mesozooecia (mz) in B, and the cystiphragms (cy) cross sections inside autozooecial (az) sections in D; E, F, Monticulipora kolaluensis Jaroshinskaja,1962, MPZ 2006/109; E, longitudinal thin section showing the stylolitic contact with another monticuliporid bryozoan; F, tangential thin section showing the macular autozooecia (maz), the mesozooecia (mz), the acanthostyles (ac) in the common vertex of three autozooecia, and a cross section of a cystiphragm (cy) inside an autozooecial (az) section. Scale bars: 1 mm.
FIG. 2 in New Monticuliporidae (Bryozoa, Trepostomata) from the Cystoid Limestone Formation (Upper Ordovician) of the Iberian Chains (NE Spain)
FIG. 2. — Stratigraphic columns of the Cystoid Limestone Formation: A, Valdelaparra section; B, La Peña del Tormo section. The horizons where bryozoans were collected are marked with a double head arrow in A and with an asterisk in B. Scale bars: A, 10 m; B, 1 m.
FIG. 7. — Prasopora spjeldnaesi n in New Monticuliporidae (Bryozoa, Trepostomata) from the Cystoid Limestone Formation (Upper Ordovician) of the Iberian Chains (NE Spain)
FIG. 7. — Prasopora spjeldnaesi n. sp., schematic longitudinal section showing the shape and distribution of autozooecial (az) cystiphragms (cy) and diaphragms (dp) and a group of densely tabulate mesozooecia (mz) with diaphragms at the same level. In 1 a large mesozooecium divides to form two smaller mesozooecia. Scale bar: 1 mm.
FIG. 5. — A, B in New Monticuliporidae (Bryozoa, Trepostomata) from the Cystoid Limestone Formation (Upper Ordovician) of the Iberian Chains (NE Spain)
FIG. 5. — A, B, Monticulipora kolaluensis Jaroshinskaja, 1962, MPZ 2006/109, longitudinal thin sections; A, area of the zoarium with large cystiphragms (cy) attached to one side of the autozooecial (az) wall that are joined to the opposite wall by diaphragms (dp); B, an area with smaller cystiphragms (cy) located in both sides of the wall as single rows or isolated; C-E, Prasopora carnica Vinassa de Regny, 1915, MPZ 2006/113; C, longitudinal thin section showing the autozooecia (az), the cystiphragms (cy), and the mesozooecia (mz); D, E, two tangential thin sections separated by less than 3 mm and in the same depth of the colony; D, the autozooecia (az) are completely surrounded by mesozooecia (mz); E, the autozooecia (az) are in contact with other autozooecia in most part of their outline, having two cystiphragms (cy) inside, and scarce mesozooecia (mz); F, Prasopora spjeldnaesi n. sp., MPZ 2006/99, basal surface showing the concentrically wrinkled base and the initial point of growth of the zoarium (ipg). Scale bars: 1 mm.
FIG. 10 in New Monticuliporidae (Bryozoa, Trepostomata) from the Cystoid Limestone Formation (Upper Ordovician) of the Iberian Chains (NE Spain)
FIG. 10.— Monticuliporidae sp. indet.,schematic longitudinal section showing a prominent acanthostyle (ac), the shape of diaphragms (dp), cystiphragms (cy) and autozooecial tubes (az), as well as the narrow mesozooecia (mz). Scale bar: 0.1 mm.
FIG. 6. — Prasopora spjeldnaesi n in New Monticuliporidae (Bryozoa, Trepostomata) from the Cystoid Limestone Formation (Upper Ordovician) of the Iberian Chains (NE Spain)
FIG. 6. — Prasopora spjeldnaesi n. sp., holotype (MPZ 2006/99): A, general view of the colony; B, surface of the colony showing autozooecia (az) completely surrounded by mesozooecia (mz), and a cross section of a cystiphragm (cy) inside an autozooecial aperture; C, tangential thin section with abundant mesozooecia (mz) completely isolating autozooecia (az); D, longitudinal thin section showing the autozooecia (az) and mesozooecia (mz) as well as the peculiar cystiphragms (cy); E, a group of mesozooecia (mz) with their diaphragms (dp) at the same level forming a square network. Scale bars: 1 mm.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.