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6,467 results for “process”
Parallel processing by distinct classes of principal neurons in the olfactory cortex
<p>Understanding how distinct neuron types in a neural circuit process and propagate information is essential for understanding what the circuit does and how it does it. The olfactory (piriform, PCx) cortex contains two main types of principal neurons, semilunar (SL) and pyramidal (PYR) cells. SLs and PYRs have distinct morphologies, local connectivity, biophysical properties, and downstream projection targets. Odor processing in PCx is thought to occur in two sequential stages. First, SLs receive and integrate olfactory bulb input and then PYRs receive, transform, and transmit SL input. To test this model, we recorded from populations of optogenetically identified SLs and PYRs in awake, head-fixed mice. Notably, silencing SLs did not alter PYR odor responses, and SLs and PYRs exhibited differences in odor tuning properties and response discriminability that were consistent with their distinct embeddings within a sensory-associative cortex. Our results therefore suggest that SLs and PYRs form parallel channels for differentially processing odor information in and through PCx.</p>
Dataset - Ghost Image Processing
<p>Dataset to accompany the paper titled: Ghost Image Processing. (to be submitted)</p> <p>Files in .txt format with '_ReadMe.txt' providing context. </p>
Decomposing Monolithic Processes using the mCRL2 toolset
<p>A set of experiments consisting of mCRL2 specifications that can be decomposed into two (or more) monolithic processes using the lpscleave tool of the mCRL2 toolset. The resulting monolithic processes can be subsequently composed to obtain the state space of the original specification more efficiently than by exploring the original specification itself. The technique is described in detail in the "Decomposing Monolithic Processes in a Process Algebra with Multi-actions" paper.</p>
Maternal sweeteners intake modulates gut microbiota and exacerbates learning and memory processes in adult male offspring
<p>Background: There is increasing evidence that gut microbiota in offspring is derived in part from maternal environment such as diet. Thus, sweeteners intake including caloric or non-caloric, during perinatal period can induce gut dysbiosis and program the offspring to develop cognitive problems later in life.<br> Objective: To determine the effect of maternal high-sweeteners intake during gestation and lactation on gut microbiota shifts in adult male offspring rats and the impact on cognitive dysfunction.</p> <p>Methods: Thirty-four male pups from dams fed standard diet (Control-C, n = 10), high-sucrose diet (HS-C, n = 11), high-honey diet (Ho-C, n = 8) and high-stevia diet (HSt-C, n = 5) were fed standard diet after weaning and body weight and food intake were recorded once a week for 26 weeks. Learning and memory tests were performed at week 23 of life using the Barnes maze. Fecal samples from the breastfeeding and adulthood periods were collected and analyzed by sequencing the 16S rRNA V3-V4 region of gut microbiota.</p> <p>Results: Maternal high-sucrose and stevia diets programmed the male offspring and changes in microbial diversity by Shannon index were observed after weaning (p < 0.01). Furthermore, maternal high-stevia diet programming lasted into adulthood. The increase of Firmicutes abundance and the decrease in phylum Bacteroidetes was significantly in HS-C and HSt-C groups. This led to an increase in the Firmicutes/Bacteroidetes index although only in HS-C group was statistically significant (p < 0.05). Of note, of the downstream gram-negative Bacteroidales and the upregulation of the gram-positive Clostridiales abundance contribute to cognitive dysfunction.</p> <p>Conclusion: These results suggest that dams fed a high-sucrose and stevia diets during gestation and lactation favor a deficient memory performance in adult male offspring rats through shifts gut microbiota diversity and relative abundance at several taxa.</p>
Improving the Process of Shared Decision-Making by Integrating Online Structured Information and Self-Assessment Tools
<p>Data of the SDM cases.</p>
Characterization of Molting Process during the Different De-velopmental Stages of the Diamondback Moth Plutella xy-lostella
<p><strong>Supplementary Materials: </strong> Figure S1: The pre-ecdysis behavior of the larval-larval ecdysis of <em>P. xylostella</em> larva; Figure S2: The “peeled” prepupa of <em>P. xylostella</em> and the “eclosion hole” of on <em>P. xylostella</em> cocoon; Video S1: The hatching process of <em>P. xylostella</em> ; Video S2: The pre-ecdysis I behavior of larval-larval ecdysis of <em>P. xylostella</em>; Video S3: The pre-ecdysis II behavior of larval-larval ecdysis of <em>P. xylostella</em>; Video S4: The ecdysis behavior of larval-larval ecdysis of <em>P. xylostella</em>; Video S5: The cocooning behavior of larval-pupal metamorphosis of <em>P. xylostella</em>; Video S6: The pre-ecdysis I behavior of larval-pupal metamorphosis of <em>P. xylostella</em>; Video S7: The pre-ecdysis II behavior of larval-pupal metamorphosis of <em>P. xylostella</em>; Video S8: The ecdysis behavior of larval-pupal metamorphosis of <em>P. xylostella</em>; Video S9: The pre-eclosion behavior of <em>P. xylostella</em> pupa; Video S10: The intersegmental membrane of the abdomen of <em>P. xylostella</em> pupa inflates before eclosion; Video S11: The eclosion behavior of <em>P. xylostella</em>; Video S12: The stage II of the post-eclosion behavior of <em>P. xylostella</em> adult; Video S13: The stage III of the post-eclosion behavior of <em>P. xylostella</em> adult; Video S14: The stage IV of the post-eclosion behavior of <em>P. xylostella</em> adult.</p>
Quantifying interaction uncertainty between subwatersheds and base-flow partitions on hydrological processes
<p><strong>Data Availability Statement:</strong> The meteorological data ((S1 Data File) and hydrological data (S2 Data File) in the manuscript can be downloaded and publicly available to anyone.</p>
Specific mutations in the cholesterol-binding site of APP alter its processing and favor the production of shorter, less toxic Aβ peptides.
<p>Mass Spectrometry data of Abeta secreted peptides from HEK293 stable clones expressing APP or APPK28A treated or not with methylbetacyclodextrin-cholesterol.</p>
Figure 5 from: Tzankov S, Tzankov B (2019) Process optimization of preparation of pentoxifylline – extended release tablets. Pharmacia 66(2): 45-48. https://doi.org/10.3897/pharmacia.66.e35132
Figure 5 Drug release profiles from pentoxifillyne tablets, containing 5% HPMC (black curve) and 10% HPMC (grey curve)
Figure 4 from: Tzankov S, Tzankov B (2019) Process optimization of preparation of pentoxifylline – extended release tablets. Pharmacia 66(2): 45-48. https://doi.org/10.3897/pharmacia.66.e35132
Figure 4 Swelling (mm3×102) of the hydrogel tablets containing PEG 6000 and PEG 6000 + 10% HPMC in water.
Figure 3 from: Tzankov S, Tzankov B (2019) Process optimization of preparation of pentoxifylline – extended release tablets. Pharmacia 66(2): 45-48. https://doi.org/10.3897/pharmacia.66.e35132
Figure 3 Change in the density of granules, obtained after granulation with PEG 6000 and after addition of 5% and 10% HPMC K4M.
Figure 1 from: Tzankov S, Tzankov B (2019) Process optimization of preparation of pentoxifylline – extended release tablets. Pharmacia 66(2): 45-48. https://doi.org/10.3897/pharmacia.66.e35132
Figure 1 Drug release profiles from pentoxifillyne tablets, obtained after granulation with 5% HPMC K4M (black curve) and 10% HPMC K4M (grey curve).
Figure 2 from: Tzankov S, Tzankov B (2019) Process optimization of preparation of pentoxifylline – extended release tablets. Pharmacia 66(2): 45-48. https://doi.org/10.3897/pharmacia.66.e35132
Figure 2 Change in the compressibility index of granules, obtained after granulation with PEG 6000 and after addition of 5% and 10% HPMC K4M.
Multimodal Analysis for Human ex vivo Studies Shows Extensive Molecular Changes from Delays in Blood Processing
<p>This is an assembled raw data in Seurat object. Expression profiling data can be accessed from <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE156989">https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE156989</a>.</p>
Code, Quality, and Process Metrics in Graduated and Retired ASFI Projects
<p>Data for the Code, Quality, and Process Metrics in Graduated and Retired ASFI Projects paper.</p>
Experimental observations about rupture nucleation process
<p>Dataset of experiments carried out in order to observe the rupture nucleation phase with heterogeneous interface. The is the strain gage data for each experiment and the videogram of each event in .mat format file.</p>
Fig. 2. RPI values for 20 in Growth Processes In The Postembryonic Development In Altricial Birds On The Example Of Song Thrush, Turdus Philomelos (Passeriformers, Turdidae): A Multivariate Approach
Fig. 2. RPI values for 20 traits during the phase of rapid growth (0–8 days), phase of slow growth (8–14 days) and after leaving the nest (14 days to adulthood). Numbers of traits as given in table 1.
Fig. 4 in Growth Processes In The Postembryonic Development In Altricial Birds On The Example Of Song Thrush, Turdus Philomelos (Passeriformers, Turdidae): A Multivariate Approach
Fig. 4. Dynamics of DRPI values of body, head, wing and leg in the breeding period of song thrush nestling development.
Supplementary Material: Predictive model using Cross Industry Standard Process for Data Mining
<p>The Supplementary Material of the paper "Supplementary Material: Predictive model using Cross Industry Standard Process for Data Mining" includes: <br> 1) APPENDIX 1: SQL Statements for data extraction. Appendix 2: Interview for operating Staff.<br> 2) The DataSet of the normalized data to define the predictive model.</p>
Data from: Global change impacts on arid zone ecosystems: Seedling establishment processes are threatened by temperature and water stress
<p><span><span><span><span><span><span><span><span><span><span><span>Recruitment for many arid-zone plant species is expected to be impacted by the projected increase in soil temperature and prolonged droughts associated with global climate change. As seed dormancy is considered a strategy to avoid unfavourable conditions, understanding the mechanisms underpinning vulnerability to these factors is critical for plant recruitment in intact communities, as well as for restoration efforts in arid ecosystems. This study determined the effects of temperature and water stress on recruitment processes in six grass species in the genus <i>Triodia </i>R.Br. from the Australian arid zone. Experiments in controlled environments were conducted on dormant and less-dormant seeds at constant temperatures of 25, 30, 35 and 40°C, under well-watered (Psi<sub>soil</sub> = -0.15 MPa) and water-limited (Psi<sub>soil</sub> = -0.35 MPa) conditions. Success at three key recruitment stages – seed germination, emergence and survival– and final seed viability of un-germinated seeds was assessed.<i> </i>For all species, less dormant seeds germinated to higher proportions under all conditions, however, subsequent seedling emergence and survival was higher in the more dormant seed treatment. An increase in temperature (35–40°C) under water-limited conditions caused 95–100% recruitment failure, regardless of the dormancy state. Ungerminated seeds maintained viability in dry soil, however, when exposed to warm (30-40°C) and well-watered conditions, loss of viability was greater from the less dormant seeds across all species. This work demonstrates that the transition from seed to established seedling is highly vulnerable to microclimatic constraints, and represents a critical filter for plant recruitment in the arid-zone. As we demonstrated temperature and water stress-driven mortality between seeds and established seedlings, understanding how these factors influence recruitment in other arid-zone species should be a high priority consideration for management actions to mitigate the impacts of global change on ecosystem resilience. The knowledge gained from these outcomes must be actively incorporated into restoration initiatives.</span></span></span></span></span></span></span></span></span></span></span></p>
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.