Find research datasets worth reusing

Harnessing single cell RNA sequencing to identify dendritic cell types, characterize their biological states and infer their activation trajectory

Summary: Dendritic cells (DCs) orchestrate innate and adaptive immunity, by translating the sensing of distinct danger signals into the induction of different effector lymphocyte responses, to induce different defense mechanisms suited to face distinct types of threats. Hence, DCs are very plastic, which results from two key characteristics. First, DCs encompass distinct cell types specialized in different functions. Second, each DC type can undergo different activation states, fine-tuning its functions depending on its tissue microenvironment and the pathophysiological context, by adapting the output signals it delivers to the input signals it receives. Hence, to better understand DC biology and harness it in the clinic, we must determine which combinations of DC types and activation states mediate which functions, and how. To decipher the nature, functions and regulation of DC types and their physiological activation states, one of the methods that can be harnessed most successfully is ex vivo single cell RNA sequencing (scRNAseq). However, for new users of this approach, determining which analytics strategy and computational tools to choose can be quite challenging, considering the rapid evolution and broad burgeoning of the field. In addition, awareness must be raised on the need for specific, robust and tractable strategies to annotate cells for cell type identity and activation states. It is also important to emphasize the necessity of examining whether similar cell activation trajectories are inferred by using different, complementary methods. In this chapter, we take these issues into account for providing a pipeline for scRNAseq analysis and illustrating it with a tutorial reanalyzing a public dataset of mononuclear phagocytes isolated from the lungs of naïve or tumor-bearing mice. We describe this pipeline step-by-step, including data quality controls, dimensionality reduction, cell clustering, cell cluster annotation, inference of the cell activation trajectories and investigation of the underpinning molecular regulation. It is accompanied with a more complete tutorial on Github. We anticipate that this method will be helpful for both wet lab and bioinformatics researchers interested in harnessing scRNAseq data for deciphering the biology of DCs or other cell types, and that it will contribute to establishing high standards in the field. Data: cDC1_maturation_loom_file.rds : Loom file used for RNA Velocity Analysis

Harnessing single cell RNA sequencing to identify dendritic cell types, characterize their biological states and infer their activation trajectory

Summary: Dendritic cells (DCs) orchestrate innate and adaptive immunity, by translating the sensing of distinct danger signals into the induction of different effector lymphocyte responses, to induce different defense mechanisms suited to face distinct types of threats. Hence, DCs are very plastic, which results from two key characteristics. First, DCs encompass distinct cell types specialized in different functions. Second, each DC type can undergo different activation states, fine-tuning its functions depending on its tissue microenvironment and the pathophysiological context, by adapting the output signals it delivers to the input signals it receives. Hence, to better understand DC biology and harness it in the clinic, we must determine which combinations of DC types and activation states mediate which functions, and how. To decipher the nature, functions and regulation of DC types and their physiological activation states, one of the methods that can be harnessed most successfully is ex vivo single cell RNA sequencing (scRNAseq). However, for new users of this approach, determining which analytics strategy and computational tools to choose can be quite challenging, considering the rapid evolution and broad burgeoning of the field. In addition, awareness must be raised on the need for specific, robust and tractable strategies to annotate cells for cell type identity and activation states. It is also important to emphasize the necessity of examining whether similar cell activation trajectories are inferred by using different, complementary methods. In this chapter, we take these issues into account for providing a pipeline for scRNAseq analysis and illustrating it with a tutorial reanalyzing a public dataset of mononuclear phagocytes isolated from the lungs of naïve or tumor-bearing mice. We describe this pipeline step-by-step, including data quality controls, dimensionality reduction, cell clustering, cell cluster annotation, inference of the cell activation trajectories and investigation of the underpinning molecular regulation. It is accompanied with a more complete tutorial on Github. We anticipate that this method will be helpful for both wet lab and bioinformatics researchers interested in harnessing scRNAseq data for deciphering the biology of DCs or other cell types, and that it will contribute to establishing high standards in the field. Data:  MDAlab_cDC1_maturation.tar : Docker image used for the analysis

ACE2-IgG1 fusions with improved in vitro and in vivo activity against SARS-CoV-2

These are raw data for figures in ACE2-IgG1 fusions with improved in vitro and in vivo activity against SARS-CoV-2,  in iScience:  PMID: 34957381

opencc-by-4.0Feb 2021View details →

Data package for Pozzolanic activity quantification of hollow glass microspheres

Raw data of calengorimetry, TGA, UCS and XRD tests developed as part of the research published in Cement and Concrete Composites. The dataset is deposited in a .zip file in .txt or .xls(.xlsx) file format. Linked publication: C.M. Martín, N.B. Scarponi, Y.A. Villagrán, D.G. Manzanal, T.M. Piqué, Pozzolanic activity quantification of hollow glass microspheres, Cement and Concrete Composites, Volume 118, 2021, 103981, ISSN 0958-9465, https://doi.org/10.1016/j.cemconcomp.2021.103981. (https://www.sciencedirect.com/science/article/pii/S0958946521000500)

Estimating Orchestration Load in Collaborative Learning Situations Using EDA - Activity 6

Skin conductivity of the teacher while orchestrating a Pyramid activity. The green highlight indicates an SCR concurred with the teacher report: "When students told me that after increasing time in the "improving phase" they could not continue editing their improved answer.".

Estimating Orchestration Load in Collaborative Learning Situations Using EDA - Activity 2

Skin conductivity of the teacher while orchestrating a Pyramid activity. During this activity, the teacher reported: "I noticed that the scenario for the task that I shared with student was not the one I planned (I have several ... and was confused with the one I picked) so I had to read the scenario as well .. while students where completing the Pyramid activity. In any case I know all scenarios very well and was quick for me to remember it.".

Estimating Orchestration Load in Collaborative Learning Situations Using EDA - Activity 3

Skin conductivity of the teacher while orchestrating a Pyramid activity. The teacher did not report any stressful situation during this activity.

Estimating Orchestration Load in Collaborative Learning Situations Using EDA - Activity 1

Skin conductivity of the teacher while orchestrating a Pyramid activity. The green highlight indicates an SCR concurred with the teacher report: "I was running out of time, and needed to reduce time in the XXX activity. However I'm used to this kind of situations, and was not highly stressed."

Datasheet of Anti-Inflammatory Activity and Toxicity Evaluation of 1,3-bis(p-Hydroxyphenyl)urea

Background: Inflammation is a normal protective response caused by an injury or tissue damage, through physical trauma, damaging chemicals, or invasion of pathogenic microorganisms. One of the modified p-aminophenol compounds is 1,3-bis(p-hydroxyphenyl)urea, which was estimated to have more potent analgesic activity and fewer hepatotoxic side effects than paracetamol. When the lipophilicity of this compound increases between 1.8 to 4.4, it is observed to serve as an anti-inflammatory agent. Therefore, the determination of safety precaution is very necessary while testing for the toxicity effect of 1,3-bis(p-hydroxyphenyl)urea. This is due to the effectiveness and safety of suitable drugs. Methods: An anti-inflammatory test was carried out by measuring the percentage of inflammation in rats, after the administration of 1,3-bis(p-hydroxyphenyl)urea was previously induced by the carrageenan solution intraplantar and the analysis of neutrophil values through a plethysmometer and Hematoxylin-Eosin method. Also, an acute toxicity test was performed by administering this p-aminophenol compound to female rats for 24 h and observed for 14 days. In addition, a subchronic toxicity test was conducted on male and female rats for 28 days, with continuous observations carried out for 42 days. Results: The doses of 1,3-bis(p-hydroxyphenyl)urea at 50, 100, and 200 mg/Kg BW, had anti-inflammatory activity compared to diclofenac sodium at 2.25 mg/Kg BW. Also, there is no toxicity and animal death symptoms were observed in the acute and subchronic tests. Conlclusion: This 1,3-bis(p-hydroxyphenyl)urea compound had an anti-inflammatory activity and relatively low toxicity.

Datasheet of Anti-Inflammatory Activity and Toxicity Evaluation of 1,3 bis(p-Hydroxyphenyl)urea

Background: Inflammation is a normal protective response caused by an injury or tissue damage, through physical trauma, damaging chemicals, or invasion of pathogenic microorganisms. One of the modified p-aminophenol compounds is 1,3 bis (p-Hydroxyphenyl) urea, which was estimated to have more potent analgesic activity and fewer hepatotoxic side effects than paracetamol. When the lipophilicity of this compound increases between 1.8 to 4.4, it is observed to serve as an an- ti-inflammatory agent. Therefore, the determination of safety precaution is very necessary while testing for the toxicity effect of 1,3 bis (p-Hydroxyphenyl) urea. This is due to the effectiveness and safety of suitable drugs. Methods: An anti-inflammatory test was carried out by measuring the per-centage of inflammation in rats, after the administration of 1,3 bis (p-Hydroxyphenyl) urea was previously induced by the carrageenan solution intraplantar and the analy- sis of neutrophil values through a plethysmometer and Hematoxylin-Eosin method. Also, an acute toxicity test was performed by administering this p-aminophenol com- pound to female rats for 24 h and observed for 14 days. In addition, a subchronic toxicity test was conducted on male and female rats for 28 days, with continuous observations carried out for 42 days. Results:The doses of 1,3 bis (p-Hydroxyphenyl) urea at 50, 100, and 200 mg/Kg BW, had anti-inflammatory activity compared to diclofenac sodium at 2.25 mg/Kg BW. Also, there is no toxicity and animal death symp-toms were observed in the acute and subchronic tests. Conlclusion:This p-aminophenol compound had an anti-inflammatory activity and relatively low toxicity.

opencc-zeroJan 2022View details →

dryad36/100

Miniaturization eliminates detectable impacts of drones on bat activity

A new way to survey wildlife populations may be possible with advancements in drones, or unmanned aerial vehicles (UAVs) that render aerial technology more accessible and promote surveying in inapproachable habitats. However, it remains unclear whether UAV disturbance deters animals, which would make this method inaccurate for data collection and hazardous to wildlife welfare. This study addresses the viability of UAV use for wildlife research by measuring the effects of UAV flight on acoustic bat detection and comparing bat activity in response to varying UAV models. Depending on the way UAVs effect bat detection rate, it may be possible to identify whether wildlife surveys should be done with UAVs and the drone models best suited for this purpose. The results reveal that larger and louder UAVs deterred significantly more bats, and the smallest and quietest model had no effect on bat detection. Indeed, drone noise was positively correlated with drone size, but drone size had little effect on the range of frequencies emitted. While detecting bats with small and quiet UAVs may be possible, complications still arise with acoustic detection and the species-specific effects of drone flight. The reliability of automatic identification with the acoustic detecting software is limited, as over a quarter of detections were triggered by non-bat noises yet still classified as bats (25.99%). Overall, using drones for wildlife detection should be approached with caution, as this study illustrates that some drones deter and disturb wild bats. If drones are used in wildlife habitat, consider flying smaller and quieter models, which are significantly less disturbing. Otherwise, large and loud drones will likely deter more animals and skew the results of the survey.

Multi-stakeholder Validation of Entrustable Professional Activities in Family Medicine - Survey Responses

Survey Responses from the 2021 Multi-Stakeholder Validation of Entrustable Professional Activities in Family Medicine medical education research project.

opencc-by-4.0Nov 2020View details →

Extraction, Chemical Characterization and Antioxidant Activity of Bioactive Plant Extracts

Recording of the talk “Extraction, chemical characterization and antioxidant activity of bioactive plant extracts”, presented by Beatriz Nunes Silva at the 1st International Electronic Conference on Food Science and Functional Foods; MDPI Foods. Online virtual meeting (10-25 Nov 2020).

Combined Biostimulant Applications of Trichoderma spp. with Fatty Acid Mixtures Improve Biocontrol Activity, Horticultural Crop Yield and Nutritional Quality

Raw Data of "Combined Biostimulant Applications of Trichoderma spp. with Fatty Acid Mixtures Improve Biocontrol Activity, Horticultural Crop Yield and Nutritional Quality".

Immune disease risk variants regulate gene expression dynamics during CD4+ T cell activation

During activation, T cells undergo extensive changes in gene expression which shape the properties of cells to exert their effector function. Therefore, understanding the genetic regulation of gene expression during T cell activation provides essential insights into how genetic variants influence the response to infections and immune diseases. We generated a single-cell map of expression quantitative trait loci (eQTL) across a T cell activation time-course. We profiled 655,349 CD4+ naive and memory T cells, capturing transcriptional states of unstimulated cells and three time points of cell activation in 119 healthy individuals. We identified 38 cell clusters, including stable clusters such as central and effector memory T cells and transient clusters that were only present at individual time points of activation, such as interferon-responding cells. We mapped eQTLs using a T cell activation trajectory and identified 6,407 eQTL genes, of which a third (2,265 genes) were dynamically regulated during T cell activation. We integrated this information with GWAS variants for immune-mediated diseases and observed 127 colocalizations, with significant enrichment in dynamic eQTLs. Immune disease loci colocalized with genes that are involved in the regulation of T cell activation, and genes with similar functions tended to be perturbed in the same direction by disease risk alleles. Our results emphasize the importance of mapping context-specific gene expression regulation, provide insights into the mechanisms of genetic susceptibility of immune diseases, and help prioritize new therapeutic targets. This dataset comprises of summary stats for eQTLs identified in the study (parquet files) and the ones which passed significance threshold  (tensor_out.tar.gz archive). Files are described by cell subset (CD4 Naive, CD 4 Memory, TEMRA, TCM, etc.), time since activation (16h, 4h, 5days)  as described in the publication (preprint https://doi.org/10.1101/2021.12.06.470953)

Differences in gut microbiome abundances and diversity by physical activity levels and BMI among patients with colorectal cancer

We investigated associations of physical activity, BMI, and combinations of physical activity levels/BMI with gut microbiome diversity and differential abundances among colorectal cancer patients. Pre-surgery stool samples from 179 colorectal cancer patients were used to perform 16S rRNA gene sequencing.

Author list of Anti-Inflammatory Activity and Toxicity Evaluation of 1,3-bis(p-Hydroxyphenyl)urea

Multi-method monitoring of rockfall activity along the classic route up Mont Blanc (4809ma.s.l.) to encourage adaptation by mountaineers

The file Mourey et al._NHESS_2021_128.xlsx gathers the data used in the article "Multi-method monitoring of rockfall activity along the classic route up Mont Blanc (4809ma.s.l.) to encourage adaptation by mountaineers" at an hourly time scale.

Mind Map of The European Bioinformatic infrastructure for the Life Sciences (ELIXIR) activities

This diagram showcases the organisation of the different components of the ELIXIR network, with brief description of the activities therein.

Synthesis, Herbicidal Activity, Crop Safety and Soil Degradation of Pyrimidine- and Triazine-Substituted Chlorsulfuron Derivatives Supplementary Information

The content include SI1-Melting points, 1H-NMR, 13C-NMR and HRMS of W103-W111, SI2-Crystal data of compound W110(CCDC number 2142702), SI3-Biological assay and crop safety, SI4-Soil degradation assay, SI5-Report of soil analysis in Chinese, and SI6-Report of soil analysis in English.