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11,198 results for “organs”
Figure 4 in Anatomical characteristics and resprouting capacity of the underground organs of Bohemian knotweed (Polygonum ×bohemicum)
Figure 4. Anatomy of rhizomes and roots of Polygonum ×bohemicum. (A) Young rhizome; (B) young root; (C) mature rhizome; (D) mature root; (E) mature rhizome center; (F) mature root center. bu, rhizome bud; ca, cambium; cl, collenchyma; co, cortex; ep, epidermis; lp, lateral pith; lr, lateral root; ox, calcium oxalate; pe, pericycle; pf, phloem in formation; ph, phloem; pi, pith; pl, phellem; pr, pericyclic fibers; ra, ligneous ray; xf, xylem in formation; xy, xylem.
Figure 1 in Anatomical characteristics and resprouting capacity of the underground organs of Bohemian knotweed (Polygonum ×bohemicum)
Figure 1. Study area with the location of two wild populations in Canton Ticino (Switzerland) of Polygonum ×bohemicum (white circles), the nearby research campus (black triangle), and the two urban centers of Locarno and Bellinzona (yellow squares). (A) Map of Switzerland and (B) map of the study area (Magadino plain).
Figure 2 in Anatomical characteristics and resprouting capacity of the underground organs of Bohemian knotweed (Polygonum ×bohemicum)
Figure 2. Research workflow for the present study on anatomical characteristics and resprouting capacity of the underground organs of Polygonum ×bohemicum. RH, relative humidity.
Merged Multi-Organ Abdominal CT Segmentation Dataset
<p><strong>Version 2.0</strong></p> <p>This version maintains the same dataset as Version 1.0, the only addition is the CSV metadata file. Please note that the BTCV images do not include metadata information.<br></p> <p> </p> <p><strong>Description</strong></p> <p>The abdominal CT images and reference segmentations were drawn from three datasets: the <a href="https://doi.org/10.7303/syn3193805" target="_blank" rel="noopener">Beyond the Cranial Vault (BTCV) Abdomen dataset</a> [1], the <a href="https://amos22.grand-challenge.org/" target="_blank" rel="noopener">Multi-Modality Abdominal Multi-Organ Segmentation Challenge 2022 dataset</a> [2], and the <a href="../records/10047292">TotalSegmentator dataset</a> [3]. Given the class differences among the three datasets, their consolidation requires the elimination of several classes, resulting in a unified dataset of 680 CT images comprising 12 classes common to all three, including:</p> <ul> <li>Spleen</li> <li>Right Kidney</li> <li>Left Kidney</li> <li>Gallbladder</li> <li>Esophagus</li> <li>Liver</li> <li>Stomach</li> <li>Aorta</li> <li>Inferior Vena Cava</li> <li>Pancreas</li> <li>Right Adrenal Gland</li> <li>Left Adrenal Gland</li> </ul> <p>The original work for which this dataset was created can be found in <a href="https://github.com/nicoalpis/Robust-Abdominal-Segmentation" target="_blank" rel="noopener">this GitHub repository</a>. </p> <p> </p> <p><strong>Terms of use</strong></p> <p>The terms of use of this data set include the terms of use of the <a href="https://doi.org/10.7303/syn3193805">Beyond the Cranial Vault (BTCV) Abdomen dataset</a> (<a href="https://doi.org/10.7303/syn3193805">terms of use</a>; after <a href="https://www.synapse.org/#!Synapse:syn3193805/wiki/217753">registration</a>, you can <a href="https://www.synapse.org/#!Synapse:syn3376386">access the data</a>), <a href="https://amos22.grand-challenge.org/" target="_blank" rel="noopener">Multi-Modality Abdominal Multi-Organ Segmentation Challenge 2022 dataset</a> (<a href="https://doi.org/10.5281/zenodo.7155725" target="_blank" rel="noopener">terms of use and data access</a>), and <a href="../records/10047292">TotalSegmentator dataset</a> (<a href="../records/10047292">terms of use and data access</a>). If you use these reference segmentations, please cite the references below.</p> <p><strong>References</strong></p> <p>[1] Landman BA, Xu Z, Igelsias JE, Styner M, Langerak TR, and Klein A, "MICCAI multi-atlas labeling beyond the cranial vault - workshop and challenge," 2015, https://doi.org/10.7303/syn3193805.</p> <p>[2] Ji, Yuanfeng, et al. "Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation." Advances in Neural Information Processing Systems 35 (2022): 36722-36732.</p> <p>[3] Wasserthal, J., Breit, H. C., Meyer, M. T., Pradella, M., Hinck, D., Sauter, A. W., ... & Segeroth, M. (2023). Totalsegmentator: Robust segmentation of 104 anatomic structures in ct images. Radiology: Artificial Intelligence, 5(5).</p>
Figure 3 in Chemotaxis of Caenorhabditis elegans Toward Volatile Organic Compounds from Stropharia rugosoannulata Induced by Amino Acids
Figure 3: Chemotaxis (percent attracted) and mortality (percent of attracted worms dead) in the groups supplemented with L-phenylalanine or L-tryptophan and the control without amino acids. The error bars indicate standard deviation. The statistical differences were analyzed using one-way ANOVA, *P <0.05, **P <0.01.
Figure 2 in Chemotaxis of Caenorhabditis elegans Toward Volatile Organic Compounds from Stropharia rugosoannulata Induced by Amino Acids
Figure 2: GC-MS total ion chromatography of different samples. A: L-phenylalanine alone, strain 1.202 alone and strain cultured on water agar plus L-phenylalanine, benzaldehyde was increased and 1-Octen-3-ol was newly produced from strain 1.2052 cultures added L-phenylalanine; B: strain 1.202 alone, L-tyrosine alone and strain cultured on water agar plus L-tyrosine, benzaldehyde was decreased and 1-Octen-3-ol and indole were newly produced were produced from strain 1.2052 cultures added L-tyrosine.
Figure 1 in Chemotaxis of Caenorhabditis elegans Toward Volatile Organic Compounds from Stropharia rugosoannulata Induced by Amino Acids
Figure 1: Chemotaxis (percent attracted) of Caenorhabditis elegans toward Stropharia rugosoannulata stain 1.2052 cultured on water agar supplemented with amino acids. Controls are phenylalanine or tyrosine alone and strain 1.2052 alone. The error bars indicate standard deviation. The statistical differences were analyzed using one-way ANOVA, *P<0.05, **P<0.01.
Figure 3 in High seeding rates, interrow mowing, and electrocution for weed management in organic no-till planted soybean
Figure 3. Monthly temperature and precipitation in Aurora, NY, USA, in 2021 and 2022. Pink lines indicate 30-yr average.
SI Figure 4: SEM images of either unwashed (left) or washed (right) E. antarcticus nematodes. A. Unwashed head region with arrows pointing to attached material and possible fungal hyphae. B. Washed head region with arrows pointing to the remaining attached material. C. Unwashed annules with arrows pointing to commonly attached foreign material. D. Washed annules with arrows pointing to remaining attached material. E. Unwashed somatic pore with arrows pointing to the common organic material. F. Washed vulva with an arrow pointing to remaining attached organic material. G. Unwashed cuticle with arrows showing a possible biofilm. H. Washed cuticle showing single attached cells indicated with arrows. I. Unwashed cuticle showing an off-axis line of attached material. J. Washed cuticle showing a similar off-axis line of material (as indicated with arrow) but reduced in quantity compared to the unwashed. in External and internal microbiomes of Antarctic nematodes are distinct, but more similar to each other than the surrounding environment
SI Figure 4: SEM images of either unwashed (left) or washed (right) E. antarcticus nematodes. A. Unwashed head region with arrows pointing to attached material and possible fungal hyphae. B. Washed head region with arrows pointing to the remaining attached material. C. Unwashed annules with arrows pointing to commonly attached foreign material. D. Washed annules with arrows pointing to remaining attached material. E. Unwashed somatic pore with arrows pointing to the common organic material. F. Washed vulva with an arrow pointing to remaining attached organic material. G. Unwashed cuticle with arrows showing a possible biofilm. H. Washed cuticle showing single attached cells indicated with arrows. I. Unwashed cuticle showing an off-axis line of attached material. J. Washed cuticle showing a similar off-axis line of material (as indicated with arrow) but reduced in quantity compared to the unwashed.
AI Tool Use and Adoption in Software Development by Individuals and Organizations: A Grounded Theory Study
<div> <p>This data represents four artifacts from our research in studying what impacts AI adoption and use in SE. It includes our interview questions, the codebook with example quotes, survey questions, and table with the code to category generation.</p> <p>This page includes supplementary materials associated with our paper entitled "<span>AI Tool Use and Adoption in Software Development by </span><span>Individuals and Organizations: A Grounded Theory Study</span>".</p> </div>
FTIR Microscopy for Direct Observation of Conformational Changes on Immobilized ω-Transaminase: Effect of Water Activity and Organic Solvent on Biocatalyst Performance
<p>Enzyme immobilization is a key strategy to expand the scope of enzyme applications and to enable the recycling of biocatalysts, resulting in greener and more cost-efficient processes. The full exploitation of the technology advantages is strictly connected to the optimal selection of the carriers and the rational development of the immobilization protocol. The present study achieved such objectives by investigating the activity of a ω-transaminase in organic solvent (toluene) upon immobilization on commercially controlled porosity glass carriers (EziG™) with diverse porosity and surface functionalization. In addition to more conventional wet-chemistry approaches and confocal microscopy, infrared microspectroscopy and imaging were exploited to highlight the enzyme distribution in a label-free manner and provide details on the immobilized enzyme's conformation with respect to the native form. Contrary to what could be expected, the highest activity of the enzyme in organic solvent was achieved for the immobilization protocol on the most hydrophilic support that more severely affects the enzyme secondary structure, promoting a beta-sheet rich folding. Experimental data show that values of water activity above 0.90 in the reaction system had a positive effect on the efficiency of the transaminase reaction. The present study represents the first example of rational development of immobilization protocols relying on direct observation of the enzyme conformation upon immobilization, shedding light on the mutual interaction between the diverse process parameters and the carrier properties.</p>
Supplementary dataset for "Low molecular weight organic acids stabilise siderite against oxidation and influence the composition of iron (oxyhydr)oxide oxidation products"
<p>Supplementary dataset for "Low molecular weight organic acids stabilise siderite against oxidation and influence the composition of iron (oxyhydr)oxide oxidation products"</p>
Figure 5 in Organic geochemistry of a high-latitude Lower Cretaceous lacustrine sediment sample from the Koonwarra Fossil Beds, South Gippsland, Victoria, Australia
Figure 5: Partial m/z 178, 202 and 228 mass chromatograms showing the distribution of common polycyclic aromatic hydrocarbons (PAH) in the aromatic fraction.
Figure 4 in Organic geochemistry of a high-latitude Lower Cretaceous lacustrine sediment sample from the Koonwarra Fossil Beds, South Gippsland, Victoria, Australia
Figure 4: Partial m/z 191 and 217 mass chromatograms used in calculation of sterane/hopane ratio. A ratio of 0.03 indicates that a very significant proportion of overall biomass in the lake was derived from bacteria.
Figure 2 in Organic geochemistry of a high-latitude Lower Cretaceous lacustrine sediment sample from the Koonwarra Fossil Beds, South Gippsland, Victoria, Australia
Figure 2: An uncommon example of disarticulation of a fish carcass, collected during an excavation of the Koonwarra Fossil Beds led by Tom Rich in 2013. This specimen was collected approximately 5 m from the bottom of the unit (defined here as the first> 20 cm thick unit of green siltstone/mudstone; the underlying rocks are predominantly cross-bedded, fluviatile arkosic sandstone).
Figure 3 in Organic geochemistry of a high-latitude Lower Cretaceous lacustrine sediment sample from the Koonwarra Fossil Beds, South Gippsland, Victoria, Australia
Figure 3: Saturate fraction total ion chromatogram and m/z 85 mass chromatogram showing distribution and relative abundances of n-alkanes and isoprenoids pristane and phytane.
Figure 1 in Organic geochemistry of a high-latitude Lower Cretaceous lacustrine sediment sample from the Koonwarra Fossil Beds, South Gippsland, Victoria, Australia
Figure 1: Location of the Lower Cretaceous Koonwarra Fossil Beds in South Gippsland, Victoria, Australia
Figure 9. Nuchal organs. A in Systematics, evolution and phylogeny of Annelida - a morphological perspective
Figure 9. Nuchal organs. A. Schematic representation of nuchal organ in Nerillidium troglochaetoides (Nerillidae). After TEM observations, modified from Purschke (1997). B. Eusyllis (?) sp. (Syllidae). Nuchal organs (encircled) visible as ciliary patches in the posterior region of the prostomium, micrograph from living animal. C. Saccocirrus sp. (Saccocirridae). Nuchal organs form oval patches (encircled). D. Myrianida prolifera (Syllidae). Nuchal epaulettes form u-shaped ciliary band extending posteriorly on peristomium and 1st chaetiger. - ey = eye, la = lateral antenna, ma = median antenna, mc = motile cilium, mv = microvillus, oc = olfactory chamber, pa = palp, pr = prostomium, rm = retractor muscle, sd = sensory dendrite, so = soma of receptor cell, suc = supportive cell. C, D: SEM micrographs, W. Mangerich, S. Raabe, Osnabrück.
Total data for global pattern of organic carbon pools in forest soil
<p>Understanding the mechanisms of soil organic carbon (SOC) sequestration in forests is vital to ecosystem carbon budgeting, and helps gain insight in the functioning and sustainable management of world forests. An explicit knowledge of the mechanisms driving global SOC sequestration in forests is still lacking because of the complex interplays between climate, soil and forest type in influencing SOC pool size and stability. Based on a synthesis of 1179 observations from 292 studies across global forests, we quantified the relative importance of climate, soil property and forest type on total SOC content and the specific contents of physical (particulate vs. mineral-associated SOC) and chemical (labile vs. recalcitrant SOC) pools in upper 10 cm mineral soils, as well as SOC stock in the O horizons. The variability in the total SOC content of the mineral soils was better explained by climate (47~60%) and soil factors (26%~50%) than by NPP (10~20%). The total SOC content and contents of particulate (POC) and recalcitrant SOC (ROC) of the mineral soils all decreased with increasing mean annual temperature because SOC decomposition overrides the C replenishment under warmer climate. The content of mineral-associated organic carbon (MAOC) was influenced by temperature, which directly affected microbial activity. Additionally, the presence of clay and iron oxides physically protected SOC by forming MAOC. The SOC stock in the O horizons was larger in the temperate zone and Mediterranean regions than in the boreal and sub/tropical zones. Mixed forests had 64% larger SOC pools than either broadleaf or coniferous forests, because of i) higher productivity, and ii) litter input from different tree species resulting in diversification of molecular composition of SOC and microbial community. While climate, soil and forest type jointly determine the formation and stability of SOC, climate predominantly controls the global patterns of SOC pools in forest ecosystems.</p>
Fig. 4 in Spatial Organization And Home Range Of Apodemus Flavicollis And A. Agrarius On Mt. Avala, Serbia
Fig. 4. Least-squared corrected means of observed range length (ORL) values (four possible density combination showing the interaction effects): A = A. flavicollis, B = A. agrarius
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.