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Fig. 4 in The cytotoxic activity of Sponges and Tunicates from Turkish Aegean Sea

Fig. 4 — Microscopic images of AGS cells treated with extracts for 24 h (Scale bar: 200 µm)

Fig. 5 in The cytotoxic activity of Sponges and Tunicates from Turkish Aegean Sea

Fig. 5 — Cell viability of SH-SY5Y cell line with various extract concentrations treatment for 24 h

Fig. 3 in The cytotoxic activity of Sponges and Tunicates from Turkish Aegean Sea

Fig. 3 — Cell viability of AGS cell line with various extract concentrations treatment for 24 h

Fig. 2 in The cytotoxic activity of Sponges and Tunicates from Turkish Aegean Sea

Fig. 2 — Microscopic images of L929 cells treated with extracts for 24 h (Scale bar: 200 µm)

Fig. 1 in The cytotoxic activity of Sponges and Tunicates from Turkish Aegean Sea

Fig. 1 — Cell viability of L929 cell line with various extract concentrations treatment for 24 h

Novel Activation Modulating Sites in a GPCR Identified with a Large-Scale Alchemical Mutation Scan

This dataset contains the starting configurations and mdp files for the alchemical free energy calculations using pmx. The MD parameter files (*.mdp) for the forward reaction (lambda 0 to 1, wt to mutant) and reverse reaction (lambda 1 to 0, mutant to wt) start with f (forward) and r (reverse). Mdp files are available for the energy minimization (em), npt (npt), equilibrium run (equilibrium) and non equilibrium alchemical transition (nonequilibrium).  The starting configurations for mutants of the DRD2 receptor can be found in WT7jvr and WT6cm4 for the active and inactive state respectively. Mutant folders are labeled with the residue number and the amino acid it is mutated to.

opencc-by-4.0Dec 2020View details →

Fig 1 in Antimicrobial activity of pandanus leaves extract to against Aeromonas hydrophila which attacked catfish

Fig 1: Inhibition test of Aeromonas hydrophila bacteria

Impact of Freeze-thaw Cycles on Coatings Applied to the Surface of Alkali-activated Materials

This paper focuses on the possibility of applying selected types of coatings (synthetic and epoxy) on the surface of alkali-activated materials based on finely ground granulated blast furnace slag with an admixture of cement by-pass dust and silica fly ash. Admixtures represent 30% of the binder component (15% fly ash, 15% cement by-pass dust). The mixture is activated with anhydrous disodium metasilicate. The samples were categorized into two series samples stored in water and samples wrapped in foil. Following this, the surface of these two series was modified by two methods, namely brushing with a steel brush and roughening with a diamond wheel. The properties related to the adhesion of the coating to the surface were mainly investigated before and after 100 freeze-thaw cycles. The cross-cut method and pull-off test for adhesion determined the adhesion. The cross-cut test found that the synthetic coating was less susceptible to surface modification than the epoxy coating. The samples were exposed to 100 freeze-thaw cycles. Then, the cross-cut method was applied to the coated roughened surface and the results of this test were classified into category 3. During the determination of the adhesion of the coatings by the pull-off test on the roughened surface for both methods of sample storage, the character of breakage for the synthetic coating was of the cohesive type, thus it was the tensile strength of the materials, while for the epoxy coating, it was the adhesive breakage, thus it was the adhesion between the surface and the coating.

Data from: Extremely persistent dense active fluids

<div> <div> <div> We study the dynamics of dense three-dimensional systems of active particles for large persistence times τp at constant average self-propulsion force f. These systems are fluid counterparts of previously investigated extremely persistent systems, which in the large persistence time limit relax only on the time scale of τp. We find that many dynamic properties of the systems we study, such as the mean-squared velocity, the self-intermediate scattering function, and the shear-stress correlation function, become τp-independent in the large persistence time limit. In addition, the large τp limits of many dynamic properties, such as the mean-square velocity and the relaxation times of the scattering function, and the shear-stress correlation function, depend on f as power laws with non-trivial exponents. We conjecture that these systems constitute a new class of extremely persistent active systems. </div> </div> </div>

Computing integrated activities scored for programming concepts

Educators across disciplines are implementing lessons and activities that integrate computing concepts into their curriculum to broaden participation in computing. Out of myriad important introductory computing skills, it is unknown which—and to what extent—these concepts are included in these integrated experiences, especially when compared to concepts commonly taught in introductory computer science courses. Thus, it is unclear how integrated computing activities serve the goal of broadening participation in computing. To address this deficit, we compiled a database of 81 integrated computing activities, constructed a framework of fundamental programming concepts, and scored each activity in the database for the presence of each concept. The dataset also includes different activity features, including discipline, programming language, student age, and duration of activity.

Gene biomarkers for the assessment of thyroid-disrupting activity in zebrafish embryos

We have conducted an exposure study on zebrafish embryos using thyroidal active compounds. Based on OECD guideline 236, freshly fertilized zebrafish embryos were exposed to two sublethal concentrations of triiodothyronine (T3), 6-Propyl-2-thiouracil (6-PTU), methimazole (MMI) and iopanoic acid (IOP) until 96 hours post fertilization. RNA was extracted and sequenced to identify thyroid-related gene expression patterns. . The uploaded data archive consists of three major data types: 1. MultiQC reports from raw RNA-Seq read processing and QC 2. Result tables from differential gene expression analysis (DGEA) with DESeq2 (apeglm shrunk results indicated by "reslfs") 3. Result tables from Overrespresentation Analysis (ORA) with clusterProfiler Gene count normalization and DGEA was conducted with DESeq2 (<a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-014-0550-8">Love et al., 2014</a>, DOI 10.1186/s13059-014-0550-8). Three biological replicates per condition, exposure treatments were compared with respect to the control group in a pairwise fashion, applying Wald’s t-test. P values were corrected for multiple testing with independent hypothesis weighting (IHW) (<a href="https://www.nature.com/articles/nmeth.3885">Ignatiadis et al., 2016</a>, DOI 10.1038/nmeth.3885 ) after Benjamini-Hochberg (BH). To improve the signal to statistical noise ratio, the obtained log2-fold change (lfc) values were shrunk with the apeglm method described by Zhu and colleagues (<a href="https://academic.oup.com/bioinformatics/article/35/12/2084/5159452?login=true">2019</a>, DOI 10.1093/bioinformatics/bty895 ) before DGEA result tables were subjected to ORA via clusterProfiler (<a href="https://www.liebertpub.com/doi/10.1089/omi.2011.0118">Yu et al., 2012</a>, DOI 10.1089/omi.2011.0118). The ArrayExpress accession numbers E-MTAB-14185 (IOP), E-MTAB-14184 (MMI), E-MTAB-14183 (T3) and E-MTAB-9054 (6-PTU), provide access to the raw and DESeq2 normalized gene count matrices upon which these analysis were performed. Genes were annotated through the biomaRt package (<a href="https://www.nature.com/articles/nprot.2009.97.pdf?origin=ppub">Durinck et al., 2009</a>, DOI 10.1038/nprot.2009.97 ) in R (<a href="https://www.r-project.org/">R Core Team 2021</a>).

Data from: Structural basis for activation and allosteric modulation of full-length calcium-sensing receptor

Calcium-sensing receptor (CaSR) is a class C G protein-coupled receptor (GPCR) that plays an important role in calcium homeostasis and parathyroid hormone secretion. Here, we present multiple cryo-electron microscopy structures of full-length CaSR in distinct ligand-bound states. Ligands (Ca2+ and l-tryptophan) bind to the extracellular domain of CaSR and induce large-scale conformational changes, leading to the closure of two heptahelical transmembrane domains (7TMDs) for activation. The positive modulator (evocalcet) and the negative allosteric modulator (NPS-2143) occupy the similar binding pocket in 7TMD. The binding of NPS-2143 causes a considerable rearrangement of two 7TMDs, forming an inactivated TM6/TM6 interface. Moreover, a total of 305 disease-causing missense mutations of CaSR have been mapped to the structure in the active state, creating hotspot maps of five clinical endocrine disorders. Our results provide a structural framework for understanding the activation, allosteric modulation mechanism, and disease therapy for class C GPCRs.

Human activities data in Wolong National Nature Reserve

Wolong National Nature Reserve (hereafter Wolong) is an internationally renowned giant panda (Ailuropoda melanoleuca) reserve. Meanwhile, the reserve is also a popular tourist destination in Giant Panda National Park. It encompasses two major towns, Wolong and Gengda, home to approximately 5,000 residents. Agriculture, tourist economy, and livestock grazing remain important income sources for the residents. Here, we combine ongoing survey data on human activity areas in Wolong and make two layers of major human activities in Wolong. The two datasets are human pressure and livestock grazing. Among them, the human pressure layer combines roads and settlement data. We use this dataset to reflect the extent of human activities in Wolong and as an important indicator to assess its interference with wildlife.

Data from: Transcriptional profiling of lung macrophages following ozone exposure in mice identifies signaling pathways regulating immunometabolic activation

Macrophages play a key role in ozone-induced lung injury by regulating both the initiation and resolution of inflammation. These distinct activities are mediated by pro-inflammatory and anti-inflammatory/pro-resolution macrophages which sequentially accumulate in injured tissues. Macrophage activation is dependent, in part, on intracellular metabolism. Herein, we used RNA-sequencing (seq) to identify signaling pathways regulating macrophage immunometabolic activity following exposure of mice to ozone (0.8 ppm, 3 hr) or air control. Analysis of lung macrophages using an Agilent Seahorse showed that inhalation of ozone increased macrophage glycolytic activity and oxidative phosphorylation at 24 and 72 hr post exposure. An increase in the percentage of macrophages in the S phase of the cell cycle was observed 24 hr post ozone. RNA-seq revealed significant enrichment of pathways involved in innate immune signaling and cytokine production among differentially expressed genes at both 24 and 72 hr after ozone, while pathways involved in cell cycle regulation were upregulated at 24 hr and intracellular metabolism at 72 hr. An interaction network analysis identified tumor suppressor 53 (TP53), E2F family of transcription factors (E2Fs), Cyclin Dependent Kinase Inhibitor 1A (CDKN1a/p21), and Cyclin D1 (CCND1) as upstream regulators of cell cycle pathways at 24 hr and TP53, nuclear receptor subfamily 4 group a member 1 (NR4A1/Nur77), and estrogen receptor alpha (ESR1/ERα) as central upstream regulators of mitochondrial respiration pathways at 72 hr. These results highlight the complex interaction between cell cycle, intracellular metabolism, and macrophage activation which may be important in the initiation and resolution of inflammation following ozone exposure.

High Entropy 2D Metals Sulfides: Fast Synthesis, Exfoliation and Electrochemical Activity in Overall Water Splitting at Alkaline pH

Dataset for the article "High Entropy 2D Metals Sulfides: Fast Synthesis, Exfoliation and Electrochemical Activity in Overall Water Splitting at Alkaline pH"

Research data for: Patchy energy landscapes promote stability of small groups of active particles

Research data supporting the pubblication "Patchy energy landscapes promote stability of small groups of active particles"

opencc-by-4.0Jul 2024View details →

TGF-β neutralization attenuates tumor residency of activated T cells to enhance systemic immunity in mice

Deep TCR sequencing was performed using the TCR Profiling Kit from MiLaboratories (Mouse α/β TCR RNA; Kit MiLaboratories; TMMR-001). Deep TCR sequencing was analyzed using the MiXCR software from MiLaboratories per manufacturer's recommendations. The files correspond to the TCR-beta sequences. The files are named as follows:   <table> <tbody> <tr> <td>file_name</td> <td>cell type sequenced</td> <td>tissue of origin</td> <td>treatment</td> <td>mouse_id</td> </tr> <tr> <td>21BA1dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>bintrafusp alpha</td> <td>1</td> </tr> <tr> <td>23BA2dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>bintrafusp alpha</td> <td>2</td> </tr> <tr> <td>25BA3dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>bintrafusp alpha</td> <td>3</td> </tr> <tr> <td>27BA4dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>bintrafusp alpha</td> <td>4</td> </tr> <tr> <td>29BA5dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>bintrafusp alpha</td> <td>5</td> </tr> <tr> <td>22BA1SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>bintrafusp alpha</td> <td>1</td> </tr> <tr> <td>24BA2SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>bintrafusp alpha</td> <td>2</td> </tr> <tr> <td>26BA3SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>bintrafusp alpha</td> <td>3</td> </tr> <tr> <td>28BA4SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>bintrafusp alpha</td> <td>4</td> </tr> <tr> <td>30BA5SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>bintrafusp alpha</td> <td>5</td> </tr> <tr> <td>31CON1dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>control</td> <td>6</td> </tr> <tr> <td>33CON2dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>control</td> <td>7</td> </tr> <tr> <td>35CON3dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>control</td> <td>8</td> </tr> <tr> <td>37CON4dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>control</td> <td>9</td> </tr> <tr> <td>39CON5dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>control</td> <td>10</td> </tr> <tr> <td>32CON1SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>control</td> <td>6</td> </tr> <tr> <td>34CON2SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>control</td> <td>7</td> </tr> <tr> <td>36CON3SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>control</td> <td>8</td> </tr> <tr> <td>38CON4SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>control</td> <td>9</td> </tr> <tr> <td>40CON5SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>control</td> <td>10</td> </tr> <tr> <td>1aPDL11dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-PDL1 antibody</td> <td>11</td> </tr> <tr> <td>3aPDL12dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-PDL1 antibody</td> <td>12</td> </tr> <tr> <td>5aPDL13dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-PDL1 antibody</td> <td>13</td> </tr> <tr> <td>7aPDL14dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-PDL1 antibody</td> <td>14</td> </tr> <tr> <td>9aPDL15dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-PDL1 antibody</td> <td>15</td> </tr> <tr> <td>2aPDL11SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-PDL1 antibody</td> <td>11</td> </tr> <tr> <td>4aPDL12SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-PDL1 antibody</td> <td>12</td> </tr> <tr> <td>6aPDL13SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-PDL1 antibody</td> <td>13</td> </tr> <tr> <td>8aPDL14SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-PDL1 antibody</td> <td>14</td> </tr> <tr> <td>10aPDL15SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-PDL1 antibody</td> <td>15</td> </tr> <tr> <td>11aTGFB1dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-TGF-beta antibody</td> <td>16</td> </tr> <tr> <td>13aTGFB2dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-TGF-beta antibody</td> <td>17</td> </tr> <tr> <td>15aTGFB3dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-TGF-beta antibody</td> <td>18</td> </tr> <tr> <td>17aTGFB4dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-TGF-beta antibody</td> <td>19</td> </tr> <tr> <td>19aTGFB5dLN.clones_TRB.tsv</td> <td>T cells</td> <td>tumor-draining lymph node</td> <td>anti-TGF-beta antibody</td> <td>20</td> </tr> <tr> <td>12aTGFB1SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-TGF-beta antibody</td> <td>16</td> </tr> <tr> <td>14aTGFB2SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-TGF-beta antibody</td> <td>17</td> </tr> <tr> <td>16aTGFB3SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-TGF-beta antibody</td> <td>18</td> </tr> <tr> <td>18aTGFB4SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-TGF-beta antibody</td> <td>19</td> </tr> <tr> <td>20aTGFB5SP.clones_TRB.tsv</td> <td>T cells</td> <td>spleen</td> <td>anti-TGF-beta antibody</td> <td>20</td> </tr> </tbody> </table>

Accompanying data for the paper "Making Sense of Wildlife Habitat Use on Active Oil Sands Mines: Quasi-experiments, Occupancy Models, Trends Assessments, and Upland Habitat Reclamation"

This data set contains both the raw species detection records and the derived occupancy model data used to assess usage patterns for the nine species of wildlife.  Data have been anonymized by using non-identifying company and lease names. These attributes are not required to reproduce the results in this paper and was done per contractual requirements between LGL Limited and its clients. Data is currently being reviewed by the client and will be shared publicly once final approval has been received.

Data Set for Self-adapting short-range correlation functional for complete active space-based approximations

Data Set to accompany:  Self-adapting short-range correlation functional for complete active space-based approximations

Reorganisation of circadian activity and the pacemaker circuit under novel light regimes

Many environmental features are cyclic, with predictable changes across the day, seasons and latitudes. Additionally, anthropogenic, artificial light-induced changes in photoperiod or shiftwork-driven novel light/dark cycles also occur. Endogenous timekeepers or circadian clocks help organisms cope with such changes. The remarkable plasticity of clocks is evident in the waveforms of behavioural and molecular rhythms they govern. Despite detailed mechanistic insights into the functioning of the circadian clock, practical means to manipulate activity waveform are lacking. Previous studies using a nocturnal rodent model showed that novel light regimes caused locomotor activity to bifurcate such that mice showed two bouts of activity restricted to the dimly lit phases. Here, we explore the generalizability of these findings and leverage the genetic toolkit of Drosophila melanogaster to obtain mechanistic insights into this unique phenomenon. We find that dim scotopic illumination of specific durations induces circadian photoreceptor CRYPTOCHROME-dependent activity bifurcation in male flies. We show circadian re-organisation of the pacemaker circuit wherein the 'evening' neurons regulate the timing of both bouts of activity under novel light regimes. Our findings indicate that environmental regimes can be exploited to design light regimes to ease the circadian waveform into synchronising with challenging conditions.