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Nanopore deep sequencing as a tool to characterize and quantify aberrant splicing caused by variants in inherited retinal dystrophy genes
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Supplementary data for ZeroPM Deliverable 2.1 - List of viable alternatives for uses of PFAS and PM substances with hazard characterization
<p>This dataset contains the data collected for all the studies which are mentioned in the ZeroPM deliverable D2.1 titled "List of viable alternatives for uses of PFAS and PM substances with hazard characterization".</p>
Characterization of the mean and extreme Mediterranean cyclones and their variability during the period 1500 BCE to 1850 CE
<p>Essential files for reproduction of Figures in manuscript "Characterization of the mean and extreme Mediterranean cyclones and their variability during the period 1500 BCE to 1850 CE".</p> <p>Respository contains cyclone tracking output (cyclone_tracking.txt), cyclone frequency files of CESM and ERA5 for the common period 1981-2010 (cyclone_freq_ERA5_1981_2010.nc, cyclone_freq_CESM_1981_2010.nc), the cyclones that make up the composites (cmed_composites.zip, emed_composites.zip, zip files contain multiple nc files), the Pearson correlation coefficients between the PCs of the modes of circulation and cyclone characteristics (correlations.zip, containing multiple nc files), and the cyclone frequencies used for the superposed epoch analysis (freq_pre_eruption.nc, freq_post_eruption.nc)</p>
Figure 1 in Morphological characterization of striped seabream (Lithognathus mormyrus, Sparidae) in some Mediterranean lagoons
Figure 1. - Sampling localities of Lithognathus mormyrus: (1) Mellah lagoon (Algeria); (2) Bizerta lagoon (Tunisia); (3) Ghar El Melh lagoon (Tunisia); (4) El Biban lagoon (Tunisia); (5) Farwa lagoon (Libya); (6) Venice lagoon (Italy).
Figure 3 in Morphological characterization of striped seabream (Lithognathus mormyrus, Sparidae) in some Mediterranean lagoons
Figure 3. - FDA scores on the three first discriminant functions for the Mediterranean lagoon samples projected on FD1×FD2 plane (A) and on FD1×FD3 plane (B).
Figure 2 in Morphological characterization of striped seabream (Lithognathus mormyrus, Sparidae) in some Mediterranean lagoons
Figure 2. - Conventional linear variables and truss elements. Locations of the 11 landmarks (1-11) used to define the truss network on L. mormyrus. Landmarks are illustrated as black dots and truss measurements between the dots as discontinued lines. Abbreviations in Annex II.
Fig. 5 in Characterization of the entomopathogenic fungal species Conoideocrella luteorostrata on the scale insect pest Fiorinia externa infesting the Christmas tree Abies fraseri in the USA
Fig. 5. Maximum Likelihood phylogenetic reconstruction of Conoideocrella species, using an SSU-LSU-tef1-ITS concatenated dataset with Metarhizium granulomatis (Sigler) Kepler, S.A. Rehner & Humber (Clavicipitaceae) as designated outgroup taxon, and showing host, sexual state and county of isolation. Ex-type species denoted as ExT.
Fig. 4 in Characterization of the entomopathogenic fungal species Conoideocrella luteorostrata on the scale insect pest Fiorinia externa infesting the Christmas tree Abies fraseri in the USA
Fig. 4. Features of Conoideocrella luteorostrata: (A) stromatic tissue (white arrow) on Fiorinia externa (black arrow); (B) details of stromatic hyphae on 10% KOH, 40×; (C) 1 mo old culture on PDA (lef) and oatmeal agar (right); (D) conidiophore; and (E) spores, 100×.
Fig. 3 in Characterization of the entomopathogenic fungal species Conoideocrella luteorostrata on the scale insect pest Fiorinia externa infesting the Christmas tree Abies fraseri in the USA
Fig. 3. Field view of Fiorinia externa collected on Abies fraseri from Glade Creek, North Carolina, USA (FDACS-DPI, sample #2019-6449) (A); its slide-mounted view (B); antennae on submargin of the head with short spur (C); anterior spiracle with pores (D); pygidium with five marginal macroducts (E); close-up of wide macroduct (F); antennae on the margin of head, with a long spur, of F. fioriniae collected on Chamaerops humilis from Ocala, Florida, USA (2019-4546) (G); antennae on the margin of head, with a short spur and processing between antennae, of F. phantasma collected on Ligustrum japonicum from Boynton Beach, Florida, USA (2020-1365) (H); pygidium with 4 marginal macroducts (I); close-up of narrow macroduct (J).
Fig. 2 in Characterization of the entomopathogenic fungal species Conoideocrella luteorostrata on the scale insect pest Fiorinia externa infesting the Christmas tree Abies fraseri in the USA
Fig. 2. Original localities of intercepted shipments of Christmas trees in 2019 (shown as circle) and 2020 (triangle). Samples with entomopathogenic fungus Conoideocrella luteorostrata are colored in blue and without fungus in red. Major cities are shown as black diamonds.
Fig. 1 in Characterization of the entomopathogenic fungal species Conoideocrella luteorostrata on the scale insect pest Fiorinia externa infesting the Christmas tree Abies fraseri in the USA
Fig. 1. Features of Fiorinia externa: (A) 30× view of alive first instar (crawler); (B) 30× view of adult female body (inside cover) with exuviae of first and second instar; (C) naked eye view of entomopathogenic fungus Conoideocrella luteorostrata on different stages of F. externa (black arrow heads); (D) close-up of C. luteorostrata covering F. externa (black arrow heads).
Fig. 1 in Genetic identification and biological characterization of Baculovirus isolated from Helicoverpa armigera (Lepidoptera: Noctuidae) in Brazil
Fig. 1. Phylogenetic relationships among HearNPV isolates (BR1, BR2, BR3, Br4, and GEM) based on analysis of concatenated nucleotide sequences of the lef-8 and lef-9. The evolutionary history was inferred by using the Maximum Likelihood method. The tree with the highest log likelihood (−799.3699) is shown. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Initial tree(s) for the heuristic search were obtained by applying the Neighbor-Joining method to a matrix of pairwise dis- tances estimated using the Maximum Composite Likelihood (MCL) approach. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The analysis involved 14 nucleotide sequences. All posi- tions containing gaps and missing data were eliminated.
Fig. 2 in Genetic identification and biological characterization of Baculovirus isolated from Helicoverpa armigera (Lepidoptera: Noctuidae) in Brazil
Fig. 2. Survival curves of Helicoverpa armigera (Lepidoptera: Noctuidae) afer feeding on corn leaves inoculated with 1 × 106 polyhedra per mL of baculovirus isolated. Gemstar®LC, BR1, BR2, BR3, BR4, and in control obtained with KaplanMeier estimator.
Variations in microscopic properties of biomass char: Implications for biochar characterization
<p><strong>Submitted data was used to write an article:</strong> <span>Mastalerz, M., Drobniak, A., Briggs, D., Bradburn, J., 2023, Variations in microscopic properties of biomass char: Implications for biochar characterization. International Journal of Coal Geology 271, 104235. https://doi.org/10.1016/j.coal.2023.104235</span></p> <p> </p> <p><strong>Funding acknowledgments:</strong> The project is co-financed by the Polish National Agency for Academic Exchange within the Polish Returns Programme (BPN/PPO/2021/1/00005/DEC/1), the National Science Center, Poland (2022/01/1/ST10/00024), and the research activities co-financed by the funds granted under the Research Excellence Initiative of the University of Silesia in Katowice, Poland. </p> <p> </p> <p><strong>Article Abstract</strong>: Biochar, a carbon-rich material produced during the thermochemical conversion of biomass, is considered to be an important material for environmental applications and sustainable agriculture. With interest in its use growing, it is essential to understand how pyrolysis parameters control biochar properties and, subsequently, which analytical methods can be applied effectively in characterizing biochar. While various methods are already in use, the potential of reflected light microscopy analysis has not yet been widely explored. This paper focuses on examining the microscopic properties of various biochars by implementing reflected light microscopy and assessing whether this technique has the potential to deliver quick, reliable, and essential information for biochar characterization. To support microscopic observations, selected physical (density and surface area) and chemical parameters (carbon and sulfur content, functional group distribution) of biochar samples were also determined. Megascopically and microscopically there is a considerable difference among biochars of different feeds including their size and shape, porosity, ratio of the abundance of cellular to non-cellular pores, inorganic matter content, the ratio of thick-walled to thin-walled inertinite, or the ratio between high-reflectance inertinite to low reflectance inertinite and their reactivity. The biochars studied also showed variations in the oxygenated groups contribution, a wide range of carbon content (14.7 to 98.8%), density (1.45 to 2.47 g/cm3), and surface areas (from <1 to 363.6 m2/g). Our results demonstrate that microscopic characteristics and reflectance of biochar can provide crucial diagnostic value for predicting biochar properties and, in combination with other physical and chemical properties, help to enhance information about the biomass conversion process and potential practical use of biochar.</p>
Figure 8 in Neutron imaging investigation of fossil woods: non-destructive characterization of microstructure and detection of in situ changes as occurring in museum cabinets
Figure 8. Evolution of I(q) vs. q upon drying for (a) Rivecourt and (b) Angeac. The inset is a close-up of the area between 0.01 and 0.07 µm−1.
Figure 5 in Neutron imaging investigation of fossil woods: non-destructive characterization of microstructure and detection of in situ changes as occurring in museum cabinets
Figure 5. Evolution of I(q) vs. q upon wetting for (a) Rivecourt and (b) Angeac. The inset is a close-up of the area between 0.01 and 0.07 µm−1.
Figure 3 in Neutron imaging investigation of fossil woods: non-destructive characterization of microstructure and detection of in situ changes as occurring in museum cabinets
Figure 3. Evolution with time of average grey levels in the wetting experiment for (a) Rivecourt and (b) Angeac. (c) Evolution with time of normalized grey levels. Blue: Rivecourt sample. Red: Angeac sample (see text for details).
Figure 2 in Neutron imaging investigation of fossil woods: non-destructive characterization of microstructure and detection of in situ changes as occurring in museum cabinets
Figure 2. Radiographic images of sample upon sorption experiments. The three pictures on the top are from the Angeac sample, while the four on the bottom are that of Rivecourt. The scale represents 1 cm. The marked areas correspond to the zones used for measuring average grey levels.
Figure 1 in Neutron imaging investigation of fossil woods: non-destructive characterization of microstructure and detection of in situ changes as occurring in museum cabinets
Figure 1. (a) Picture of neutron guide through experimental chamber. (b) Sorption experiment setup and radiographic image obtained. Wood samples were placed in an aluminum cup filled with water. Water appears dark, while aluminum is transparent to neutrons. (c) Desorption experiment setup and radiographic image obtained. Wood samples were wrapped in aluminum foils and placed in a tube, with direct air input (plastic tube, on top).
Figure 7 in Neutron imaging investigation of fossil woods: non-destructive characterization of microstructure and detection of in situ changes as occurring in museum cabinets
Figure 7. Evolution with time of average grey levels in the drying experiment for (a) Rivecourt and (b) Angeac. (c) Evolution with time of normalized grey levels. Blue: Rivecourt sample. Red: Angeac sample (see text for details). (d) Evolution of average grey levels in the drying experiments plotted as a function of the square root of time. Blue: Rivecourt sample. Red: Angeac sample.
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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.