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The Ubiquitin Ligase WWP1 Contributes to Shifts in Matrix Proteolytic Profiles and a Myocardial Aging Phenotype with Diastolic Heart Failure
<p><strong><em>Aims</em></strong>. Ubiquitylation is a key event that regulates protein turnover, and induction of the ubiquitin ligase E3 WWP1 has been associated with age. Left ventricular hypertrophy (LVH) commonly occurs as a function of age and can cause heart failure with a preserved ejection fraction (EF; HFpEF). We hypothesized that overexpression (O/E) of WWP1 in the heart would cause LVH as well as functional and structural changes consistent with the aging HFpEF phenotype.</p> <p><strong><em>Methods and Results.</em></strong> Global WWP1 O/E was achieved in mice (n=11) and echocardiography (40 MHz) performed to measure LV mass, EF, Doppler velocities (early-E, late/atrial-A), myocardial relaxation (E’), and isovolumetric relaxation time (IVRT) at 4, 6, and 8 weeks. Age matched wild type animals (n=15) were included as referent controls. LV EF was identical (60+1% vs 60+1%, p>0.90) with no difference in LV mass (67+3 vs 75+5, p>0.25) at 4 weeks. However, at 8 weeks of age, LV mass increased by over two-fold, E/A fell (impaired passive filling), and E/E’ was lower and IVRT prolonged (impaired LV relaxation) - all p<0.05. Collagen percent area increased by over two-fold and fibrillar collagen expression (rtPCR) by over 1.5 fold (p<0.05) with WWP1 O/E. WWP1 with an anti-WWP1 antibody could be identified in isolated cardiac fibroblasts with WWP1 increased by over two-fold in O/E fibroblasts (p<0.05).</p> <p><strong><em>Conclusion.</em></strong> Inducing WWP1 expression caused LVH, preserved systolic function, but impaired diastolic dysfunction, consistent with the HFpEF phenotype. Targeting the WWP1 pathway may be a novel therapeutic target for this intractable form of HF associated with aging.</p>
Data from: Transcriptome profiling of maternal stress-induced wing dimorphism in pea aphids
Wing dimorphism, i.e., wingless and winged forms, can be induced by maternal stress signals and is an adaptive response of aphids to environmental changes. Here, we investigated the ecological and molecular effects of three kinds of stress, namely, crowding, predation, and aphid alarm pheromone, on wing dimorphism. These three stressors induced high proportion of up to 60% of winged morphs in offspring. Transcriptome analysis of stress-treated female aphids revealed different changes in maternal gene expression as induced by the three stressors. Crowding elicited widespread changes in the expression of genes involved in nutrient accumulation and energy mobilization. Distinct from crowding, predation caused dramatic expression changes in cuticle protein (CP) genes. Twenty-three CP genes that belong to CP RR2 subfamily and are highly expressed in legs and embryos were greatly repressed by the presence of ladybird. By contrast, application of alarm pheromone, E--farnesene, caused slight changes in gene expression. The three factors shared a responsive gene, cuticle protein 43. This study reveals the adaptive response of aphids to environmental stresses and provides a rich resource on genome-wide expression genes for exploring molecular mechanisms of ecological adaptation in aphids.
Singapore bus charging profiles for different bus line electrification levels
<p>This data set contains the power demand profiles of bus charging stations in Singapore for six different scenarios, where the percentage of bus lines that are fully electrified varies from 30% to 100%.</p> <p>The power demand curves for each charging station were generated using the City Mobility Simulator (CityMoS), an agent-based, discrete-event, traffic simulation platform under development by research teams at TUMCREATE. This platform is able to simulate sub-microscopic traffic with high performance on large-scale road networks. A CityMoS extension models the operation and charging behavior of a fleet of public electric buses.</p> <p>The file is a python pickle file that can be opened in python by the following commands:</p> <p>import pickle<br> Powerprofile = pickle.load(open('Input/PowerProfile','rb'))</p>
Supplementary data (simulated metagenome set 1) to accompany "phyloFlash – Rapid SSU rRNA profiling and targeted assembly from metagenomes"
<p>Comparison of SSU rRNA read extraction and targeted assembly from simulated shotgun metagenome of divergent bacterial species.</p> <p>The phyloFlash software is available from https://github.com/HRGV/phyloFlash. Examples were generated with phyloFlash v3.3b.</p>
Supplementary data (comparison of multiple metagenomes) to accompany "phyloFlash – Rapid SSU rRNA profiling and targeted assembly from metagenomes"
<p>Usage example for phyloFlash, comparison of multiple metagenomes by SSU rRNA taxonomic profile. </p> <p>The phyloFlash software is available from https://github.com/HRGV/phyloFlash. Examples were generated with phyloFlash v3.3b.</p>
Supplementary data (low-diversity metagenome and reference database completeness) to accompany "phyloFlash – Rapid SSU rRNA profiling and targeted assembly from metagenomes"
<p>Comparison of phyloFlash and Matam on low-diversity platyhelminth metagenome, showing effect of reference database completeness on results. </p> <p>The phyloFlash software is available from https://github.com/HRGV/phyloFlash. Examples were generated with phyloFlash v3.3b.</p>
Supplementary data (Tara Oceans metagenomes) to accompany "phyloFlash – Rapid SSU rRNA profiling and targeted assembly from metagenomes"
<p>Comparison of SSU rRNA read extraction and targeted assembly by phyloFlash and Matam from environmental metagenomes from the Tara Oceans dataset.</p> <p>The phyloFlash software is available from https://github.com/HRGV/phyloFlash. Examples were generated with phyloFlash v3.3b.</p>
Developing a deep Learning network to retrieve ocean hydrographic profiles in the North Atlantic from combined satellite and in situ measurements: training datasets
<p>We provide here the datasets used for the development of a deep learning algorithm which is presently candidate for the development of a daily 3D ocean product covering the North Atlantic at 1/10° resolution, over the 2010-2018 period, as part of the European Space Agency World Ocean Circulation project (ESA-WOC). The method is based on a stacked Long Short-Term Memory neural network, coupled to a Monte-Carlo dropout approach, and allows to project satellite-derived sea surface temperature, sea surface salinity and absolute dynamic topography data at depth after training with sparse co-located in situ vertical hydrographic profiles (Buongiorno Nardelli, 2020, doi:<a href="https://www.researchgate.net/deref/http%3A%2F%2Fdx.doi.org%2F10.3390%2Frs12193151?_sg%5B0%5D=0xE-347r7Hvb80klJcEo811AhUiXq-twG_E6l4yB-BfIKkVtW-lVLGcO02mTFkUczvozYYI0WCPyUBFR3kzWNGGZKg.ftvLheFrzHIJriO4qW2bdxalvR_TWt3MpwUfvto3EemhRgvDRGwJ9Mdy4Xr0IcGCfICivf4j-VqTgKxVvXRogA">10.3390/rs12193151</a>). </p> <p>The training/test dataset presented here includes different sets of co-located temperature and salinity vertical profiles and corresponding satellite surface data: </p> <ul> <li>in situ observations extracted from the quality controlled Argo and CTD profiles produced by Copernicus Marine Environment Monitoring Service CORA 5.2 (<a href="http://marine.copernicus.eu/services-portfolio/access-to-products/">http://marine.copernicus.eu/services-portfolio/access-to-products/</a>, product_id: INSITU_GLO_TS_REP_OBSERVATIONS_013_001_b, doi: 10.17882/46219TS1, Szekely et al., 2019) and interpolated through a spline on a regularly spaced vertical grid (with 10 m intervals);</li> <li>climatological profiles extracted from World Ocean Atlas 2013 optimally interpolated monthly fields (Locarnini et al., 2013; Zweng et al., 2013), interpolated through a spline on a regularly spaced vertical grid (with 10 m intervals), upsized to a 1/10° horizontal grid through a cubic spline and linearly interpolated in time between the central day of each month;</li> <li>co-located Sea Surface Temperature taken from the level 4 (L4, i.e. interpolated) multi-year reprocessed Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) developed by U.K. Met Office and distributed (upon free registration) through the Copernicus Marine Environment Monitoring Service (CMEMS, <a href="http://marine.copernicus.eu/services-portfolio/access-to-products/">http://marine.copernicus.eu/services-portfolio/access-to-products/</a>, product_id=SST_GLO_SST_L4_REP_OBSERVATIONS_010_011);</li> <li>co-located Sea Surface Salinity taken from dataset developed within ESA-WOC project (https://doi.org/10.5281/zenodo.3943813);</li> <li>co-located Absolute Dynamic Topography (ADT) data distributed by CMEMS as reprocessed data (<a href="http://marine.copernicus.eu/services-portfolio/access-to-products/">http://marine.copernicus.eu/services-portfolio/access-to-products/</a>, product_id: SEALEVEL_GLO_PHY_L4_REP_OBSERVATIONS_008_047), upsized here to the ESA-WOC 1/10°x1/10° grid through a cubic spline and adjusted to insitu steric heights by regressing steric heights and co-located ADT data in the neighbourhood of each grid point, considering matchups within a temporal window of 10 days (as in Buongiorno Nardelli et al., 2017).</li> </ul>
Do we use FLOSS in Software Engineering Education? Mapping the Profiles and Practices of Higher Education Teachers from Brazi
<p>Context:Software Engineering (SE) is a key topic in undergraduate computing-related courses that provides the basic knowledge and skills necessary for professional practice in the software industry. Teaching SE principles, concepts and practices and relating them to real-world scenarios are challenging tasks, and the adoption of Free/Libre/Open Source Software (FLOSS) projects can help to face these challenges. On the other hand, using FLOSS projects as a didactic resource may introduce additional challenges to professors that are not familiar with the FLOSS ecosystem. Objective: This research aims to identify and map the profiles of professors of SE courses in Brazil, as well as to present the pedagogical practices used in the experience with FLOSS projects in Software Engineering Education (SEE). Method: We performed a survey with higher education professors in Brazil, used K-modes algorithm to identify clusters and Decision Tree algorithm to identify characteristics that determine the use of FLOSS projects in a sample of professors who had not used this approach in the classroom.Results:The results of the research revealed characteristics of professors who use, or not,FLOSS projects in SEE, of professors grouped in the two clusters generated by the application of the K-modes algorithm, of professors grouped by the application of the Decision Tree algorithm,in addition to presenting similar characteristics the pedagogical practices evidenced by each group of SE professors.</p>
Comparison of health literacy profile of patients with end stage kidney disease on dialysis versus non-dialysis chronic kidney disease and the influencing factors: a cross-sectional study
<p><strong>Objectives</strong>: Lower health literacy (HL) is associated with poor outcomes in patients with kidney disease. Since HL matches the patient's competencies with the complexities of the care package, the level of HL sufficient in earlier stages of chronic kidney disease (CKD) may be inadequate for end-stage kidney disease (ESKD) patients on dialysis. We aimed to analyse the HL profile of ESKD and non-dialysis CKD patients and examine if there were significant associations with covariates which could be targeted to address HL deficits, thereby improving patient outcomes.</p> <p><strong>Design and setting</strong>: Cross-sectional study of CKD and ESKD patients from a single Australian health district.</p> <p><strong>Methods</strong>: We assessed the HL profile of 114 CKD and 109 ESKD patients using a 44-item multi-domain HL Questionnaire (HLQ) and examined its association with demographic factors (age, gender, race), smoking, income, education, comorbidities, carer status, cognitive function and depression. Using multi-variable logistic regression models, HL profiles of CKD and ESKD patients were evaluated after adjusting for covariates.</p> <p><strong>Results</strong>: Patients with ESKD had similar demographics and educational levels compared to CKD patients. ESKD had significantly higher frequency of vascular disease, cognitive impairment and depression. ESKD patients had better HL scores for the social support domain (37.1% vs 19.5% in higher HLQ4 tertile, p=0.004), whereas all other HL domains including engagement with healthcare providers were comparable to CKD. Depression was independently associated with nearly all of the HL domains (HLQ1: OR 2.6, p=0.030, HLQ2: OR 7.9, p=<0.001, HLQ3: OR 7.6, p<0.001, HLQ4: OR 3.5, p=0.010, HLQ5: OR 8.9, p=0.001, HLQ6: OR 3.9, p=0.002, HLQ7: OR 4.8, p=0.001, HLQ8: OR 5.3, p=0.001) and education with HL domains relevant to processing health related information (HLQ8: OR 2.6, p=0.008, HLQ9: OR 2.5, p=0.006).</p> <p><strong>Conclusions</strong>: Despite very frequent interactions with health systems, ESKD patients on dialysis did not have higher HL in engagement with health providers and most other HL domains, compared to CKD patients. Strategies promoting patient-provider engagement and managing depression which strongly associates with lower HL may address the impact of HL deficits and favourably modify clinical outcomes in renal patients. </p>
An algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles: Data availability
<p>DEPTH evaluates the tumor heterogeneity level of each tumor sample based on gene expression profiles Heterogeneity score. </p>
Coagulation profile of COVID-19 patients admitted to the ICU: an exploratory study
Background <p>Coagulation abnormalities in COVID-19 patients have not been addressed in depth. <b>Objective</b>: To perform a longitudinal evaluation of coagulation profile of patients admitted to the ICU with COVID-19.</p> Methods <p>Conventional coagulation tests, rotational thromboelastometry (ROTEM), platelet function, fibrinolysis, antithrombin, protein C and S were measured at days 0, 1, 3, 7 and 14. Based on median total maximum SOFA score, patients were divided in two groups: SOFA ≤ 10 and SOFA > 10.</p> Results <p>Thirty patients were studied. Conventional coagulation tests remained unchanged during the study period, while the majority of patients exhibited a hypercoagulability state based on ROTEM. Fibrinogen levels were increased in both groups. ROTEM maximum clot firmness increased in both groups. ROTEM – FIBTEM maximum clot firmness was high in both groups, with a slight decrease from day 0 to day 14 in group SOFA ≤ 10 and a slight increase during the same period in group SOFA > 10. Fibrinolysis was low and decreased over time in all groups, with the most pronounced decrease observed in INTEM maximum lysis in group SOFA > 10. Protein C plasma levels increased over time in both groups, although patients in group SOFA > 10 exhibited lower values in comparison to patients in group SOFA ≤ 10.</p> Conclusion <p>COVID-19 patients have a pronounced hypercoagulability state, characterized by impaired endogenous anticoagulation and decreased fibrinolysis. The magnitude of coagulation abnormalities seems to correlate with the severity of organ dysfunction. The hypercoagulability state of COVID-19 patients was only detected by ROTEM.</p>
Row data from: Screening and response profile of Iraqi barley accessions under PEG- induced drought conditions
<p><span>Among the abiotic stresses, drought influences plant growth and productivity, and plant stress responses depend on stress intensity and genotype. The effects of simulated drought stress on germination parameters were tested for tolerance and sensitivity in 59 barley accessions from all regions of Iraq and phenotypic, physiological and biochemical responses associated with drought stress were investigated. Stress treatments with polyethylene glycol (PEG) reduced the germination rate and dramatically delayed the development of the seedlings. Significant changes in the physiological and biochemical profiles in barley accessions were observed. A smaller reduction in water absorption of seeds was observed across all accessions, while all biochemical characteristics except total flavonoid content were increased with the increase in water deficiency in most accessions. Among the 59 barley accessions, ABN was the most tolerant accession, while Black-Garmiyan was the most drought-prone. Significant relationships were found between most trait pairs, with 32 significant associations under no stress, 39 significant correlations under the 10.25% PEG treatment, and 81 significant correlations under the 20.50% PEG treatment. According to the key importance analysis, seed water uptake, total phenol content, soluble sugar content and catalase are classified as relative significance traits for germination percentage, root and shoot length under stress conditions.</span></p>
Dataset related to the article "Human Cardiac Mesenchymal Stromal Cells From Right and Left Ventricles Display Differences in Number, Function, and Transcriptomic Profile"
<p>This record contains raw data related to the article "Human Cardiac Mesenchymal Stromal Cells From Right and Left Ventricles Display Differences in Number, Function, and Transcriptomic Profile". </p> <p><strong>Background:</strong> Left ventricle (LV) and right ventricle (RV) are characterized by well-known physiological differences, mainly related to their different embryological origin, hemodynamic environment, function, structure, and cellular composition. Nevertheless, scarce information is available about cellular peculiarities between left and right ventricular chambers in physiological and pathological contexts. Cardiac mesenchymal stromal cells (C-MSC) are key cells affecting many functions of the heart. Differential features that distinguish LV from RV C-MSC are still underappreciated.</p> <p><strong>Aim:</strong> To analyze the physiological differential amount, function, and transcriptome of human C-MSC in LV versus (vs.) RV.</p> <p><strong>Methods:</strong> Human cardiac specimens of LV and RV from healthy donors were used for tissue analysis of C-MSC number, and for C-MSC isolation. Paired LV and RV C-MSC were compared as for surface marker expression, cell proliferation/death ratio, migration, differentiation capabilities, and transcriptome profile.</p> <p><strong>Results:</strong> Histological analysis showed a greater percentage of C-MSC in RV vs. LV tissue. Moreover, a higher C-MSC amount was obtained from RV than from LV after isolation procedures. LV and RV C-MSC are characterized by a similar proportion of surface markers. Functional studies revealed comparable cell growth curves in cells from both ventricles. Conversely, LV C-MSC displayed a higher apoptosis rate and RV C-MSC were characterized by a higher migration speed and collagen deposition. Consistently, transcriptome analysis showed that genes related to apoptosis regulation or extracellular matrix organization and integrins were over-expressed in LV and RV, respectively. Besides, we revealed additional pathways specifically associated with LV or RV C-MSC, including energy metabolism, inflammatory response, cardiac conduction, and pluripotency.</p> <p><strong>Conclusion:</strong> Taken together, these results contribute to the functional characterization of RV and LV C-MSC in physiological conditions. This information suggests a possible differential role of the stromal compartment in chamber-specific pathologic scenarios.</p>
Good vs poor responder RNAseq transcriptome profiles in DBA/2J mice
<p>Major depressive disorder is the most prevalent mental illness worldwide, still its pharmacological treatment is limited by various challenges, such as the large heterogeneity in treatment response and the lack of insight into the neurobiological pathways underlying this phenomenon. To decode the molecular mechanisms shaping antidepressant response and to distinguish those from general paroxetine effects, we used a previously established approach targeting extremes (i.e. good vs. poor responder mice). Transcriptome profiling on micro-dissected DG granule cells as well as on peripheral blood samples was performed to <i>i</i>) reveal celltype specific changes in paroxetine-induced gene expression (paroxetine vs. vehicle) and <i>ii</i>) to identify molecular signatures of treatment response within a cohort of paroxetine-treated animals. In this datasheet, we provide the mapped and norm-counted RNAseq results of our experiments in an user-friendly excel file.</p>
Turbulence profiles from the R/V Sanna cruise to Northwest Greenland fjords, August 11-31, 2016
<p>The data set contains micro-scale turbulence measurements from six fjords along northwestern Greenland carried out on the R/V Sanna cruise in August 2016. The data set is described and analysed in:</p> <p>Bendtsen, J., Rysgaard, S., Carlson, D. F., Meire, L., & Sejr, M. K. (2021). Vertical mixing in stratified fjords near tidewater outlet glaciers along Northwest Greenland. <em>Journal of Geophysical Research: Oceans</em>, 126, e2020JC016898. <a href="https://doi.org/10.1029/2020JC016898">https://doi.org/10.1029/2020JC016898</a></p> <p>Please cite this publication when using the data.</p>
Acceleration time histories and road elevation profiles
<p><span><span><span><span><span><span><span><span><span><span><span><span><span>Low-cost smartphone-based sensing approaches have recently emerged as an alternative to the traditional and oftentimes expensive or laborious road surface monitoring technologies. </span></span>We develop an approach, resting on a rigorously derived mechanistic and stochastic model in spectral domain, that relates the vertical acceleration signal measured by a smartphone positioned in a moving car to road surface roughness metrics. <span><span>We illustrate that the inferred roughness metrics from the acceleration data sets, acquired with different smartphones and vehicle types, are in good agreement with the ones obtained from the expensive laser measurements.</span></span> The data set we used for our analysis is hence comprised of (I) acceleration signals recorded by smartphones placed at different locations of the vehicle, and (II) laser-measured road longitudinal profiles. <span><span>The validation analysis is performed for two test tracks: </span></span> (1) 13.8 km of a thoroughfare with a dominating inner-city component with poor ride quality, and (2) 11.6 km of a highway with good ride quality. The coordinates (latitude and longitude) of the two test tracks are also available in the provided data set.</span></span></span></span></span></span></span></span></span></span></span></p>
Figures 1-3 from: Ribeiro PVA, Baesse CQ, Cury MC, de Melo C (2020) Leukocyte profile of the helmeted manakin, Antilophia galeata (Passeriformes: Pipridae) in a Cerrado forest fragment. Zoologia 37: 1-9. https://doi.org/10.3897/zoologia.37.e46441
Figures 1-3 Number of lymphocytes for Antilophia galeata in relation to sex (1), presence/absence of incubation patch (2) and presence/absence of ticks (3). Boxes represent mean values while bars represent the standard error.
Figure 4 from: Logoyda L (2021) Novel HPLC-UV method for simultaneous determination of valsartan and atenolol in fixed dosage form; Study of green profile assessment. Pharmacia 68(1): 43-51. https://doi.org/10.3897/pharmacia.68.e53631
Figure 4 Chromatogram obtained using Shimadzu Nexera XR UPLC system and mobile phase 20% acetonitrile, 80% of 0.16% ammonium acetate and 0.2% of 1.5 M tetramethylammonium hydroxide (V/V), column Discovery C18 (4.6 mm i.d. × 150 mm, 5 μm) at 2 wavelengths 225 nm and 237 nm (first figure), with 3-D UV contour diagram extracted analytes UV spectra and peak purity (second figure).
Figure 6 from: Logoyda L (2021) Novel HPLC-UV method for simultaneous determination of valsartan and atenolol in fixed dosage form; Study of green profile assessment. Pharmacia 68(1): 43-51. https://doi.org/10.3897/pharmacia.68.e53631
Figure 6 Chromatogram obtained using final established, optimized and validated chromatographic method at wavelength 237 nm.
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.