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APPENDIX 1 in Finite element analysis of the proximal phalanx of the thumb in Hominoidea during simulated stone tool use
<p>APPENDIX 1. — Loads applied to the models for each one of the species under analysis and simulated loading scenarios. Abbreviations: <b>a</b>, forces (<b>N</b>) and angles (Ɵ) relative to the longitudinal axes of the bone; <b>b</b>, muscle forces for the human and chimpanzee reference models, respectively, are separate by a slash; <b>c</b>, force reactions in the proximal and distal joints were scaled to remove size effects when computing stress distributions.</p><table><tbody><tr><th>Specimen</th><th>SC</th><th>HRFa</th><th>FPB HS /FPB PTb</th><th>AP HS /AP PTb</th><th>EPB HS /EPB PTb</th><th>ABP HS /ABP PTb</th><th>JRFc d</th><th></th><th><b><b>JRFc</b> mc</b></th><th></th></tr></tbody><tbody><tr><th></th><td></td><td><b>N</b></td><td>Ɵ</td><td><b>N</b></td><td>Ɵ</td><td><b>N</b></td><td>Ɵ</td><td><b>N</b></td><td>Ɵ</td><td><b>N</b></td><td>Ɵ</td><td><b>N</b></td><td>Ɵ</td><td><b>N</b></td><td>Ɵ</td></tr><tr><th>Modern Human</th><td>1 2 3 4</td><td>3.92 7.65 3.92 7.65</td><td>90 90 45 45</td><td>17.95/37.20 13.49/27.95 17.95/37.20 13.49/27.95</td><td>45 45 45 45</td><td>38.79/66.43 29.15/49.91 38.79/66.43 29.15/49.91</td><td>61.2 61.2 61.2 61.2</td><td>4.33/28.75 2.74/18.18 4.33/28.75 2.74/18.18</td><td>16.7 16.7 16.7 16.7</td><td>5.28/35.94 3.34/22.72 5.28/35.94 3.34/22.72</td><td>180 180 180 180</td><td>44.06/89.27 28.26/61.46 45.21/90.33 30.70/63.62</td><td>180 180 180 180</td><td>38.81/114.1 28.02/78.76 37.96/113.3 26.36/77.14</td><td>180 180 180 180</td></tr><tr><th>Neanderthal</th><td>1 2 3 4</td><td>3.92 7.65 3.92 7.65</td><td>90 90 45 45</td><td>14.47/29.99 10.87/22.54 14.47/29.99 10.87/22.54</td><td>45 45 45 45</td><td>31.28/53.56 23.50/40.24 31.28/53.56 23.50/40.24</td><td>61.2 61.2 61.2 61.2</td><td>3.49/23.18 2.21/14.66 3.49/23.18 2.21/14.66</td><td>16.7 16.7 16.7 16.7</td><td>4.26/28.98 2.69/18.32 4.26/28.98 2.69/22.72</td><td>180 180 180 180</td><td>35.55/72.02 22.79/49.58 36.46/72.85 24.75/51.29</td><td>180 180 180 180</td><td>30.75/91.35 22.36/63.11 30.27/90.88 21.41/62.18</td><td>180 180 180 180</td></tr><tr><th>Chimpanzee</th><td>1 2 3 4</td><td>3.92 7.65 3.92 7.65</td><td>90 90 45 45</td><td>18.34/38.01 13.78/28.56 18.34/38.01 13.78/28.56</td><td>45 45 45 45</td><td>39.64/67.88 29.78/51.00 39.64/67.88 29.78/51.00</td><td>61.2 61.2 61.2 61.2</td><td>– – – –</td><td>– – – –</td><td>5.39/36.72 3.41/23.22 5.39/36.76 3.41/23.22</td><td>180 180 180 180</td><td>43.78/82.63 28.05/57.36 45.11/83.92 30.92/60.02</td><td>180 180 180 180</td><td>35.51/90.61 26.15/64.17 35.78/90.89 26.7/64.7</td><td>180 180 180 180</td></tr><tr><th>Gorilla</th><td>1 2 3 4</td><td>3.92 7.65 3.92 7.65</td><td>90 90 45 45</td><td>24.78/51.36 18.62/38.59 24.78/51.36 18.62/38.36</td><td>45 45 45 45</td><td>53.55/91.71 40.24/68.91 53.55/91.71 40.24/68.91</td><td>61.2 61.2 61.2 61.2</td><td>5.97/39.69 3.78/25.10 5.97/39.69 3.78/25.10</td><td>16.7 16.7 16.7 16.7</td><td>7.29/49.61 4.61/31.37 7.29/49.61 4.61/31.37</td><td>180 180 180 180</td><td>61.17/125.1 39.33/86.13 64.27/128.2 45.94/92.39</td><td>180 180 180 180</td><td>49.14/144.11 35.31/99.38 49.57/144.53 36.15/100.2</td><td>180 180 180 180</td></tr><tr><th>Orangutan</th><td>1 2 3 4</td><td>3.92 7.65 3.92 7.65</td><td>90 90 45 45</td><td>19.74/40.91 14.83/30.74 19.74/40.91 14.83/30.74</td><td>45 45 45 45</td><td>42.66/73.06 32.06/54.90 42.66/73.06 32.06/54.90</td><td>61.2 61.2 61.2 61.2</td><td>– – – –</td><td>– – – –</td><td>5.80/39.52 3.67/24.99 5.80/39.52 3.67/24.99</td><td>180 180 180 180</td><td>47.62/89.76 30.56/62.34 49.01/91.09 33.44/65.02</td><td>180 180 180 180</td><td>47.85/117.2 34.51/82.77 50.55/119.84 39.78/87.92</td><td>180 180 180 180</td></tr><tr><th>Gibbon</th><td>1 2 3 4</td><td>3.92 7.65 3.92 7.65</td><td>90 90 45 45</td><td>7.08/14.66 5.32/11.02 7.08/14.66 5.32/11.02</td><td>45 45 45 45</td><td>15.29/26.1 11.49/19.68 15.29/26.19 11.49/19.68</td><td>61.2 61.2 61.2 61.2</td><td>– – – –</td><td>– – – –</td><td>2.08/14.17 1.32/8.96 2.08/14.17 1.32/8.96</td><td>180 180 180 180</td><td>17.75/32.87 11.25/22.87 17.88/33.25 12.1/23.65</td><td>180 180 180 180</td><td>19.08/45.46 13.75/32.18 19.64/46.00 14.84/33.24</td><td>180 180 180 180</td></tr></tbody></table>
TABLE 1 in Finite element analysis of the proximal phalanx of the thumb in Hominoidea during simulated stone tool use
<p>TABLE 1. — Sample. Abbreviations: <b>a</b>, age of individuals, if known; unk: unknown. <b>b</b>, M: male; F: female. <b>c</b>, R: right; L: left.</p><table><tbody><tr><th><b>Species</b></th><th><b>Common name</b></th><th><b>Age a</b></th><th><b>Sex b</b></th><th><b>Side</b></th><th><b>Digital database/ <b>no</b></b></th><th><b>CT/microCT resolution (mm)</b></th></tr></tbody><tbody><tr><th><i>Homo sapiens</i></th><td>Modern human</td><td>59</td><td>M</td><td>R</td><td>None</td><td>0.08</td></tr><tr><th><i>Homo neanderthalensis</i></th><td>Neanderthal</td><td>unk</td><td>unk</td><td>R</td><td>NESPOS/ Krapina 202</td><td>0.03</td></tr><tr><th><i>Pan troglodytes</i></th><td>Chimpanzee</td><td>29</td><td>M</td><td>L</td><td>KURPI/345</td><td>0.219</td></tr><tr><th><i>Gorilla gorilla</i></th><td>Gorilla</td><td>38</td><td>M</td><td>R</td><td>KUPRI/1353</td><td>0.500</td></tr><tr><th><i>Pongo pygmaeus</i></th><td>Orangutan</td><td>32</td><td>F</td><td>R</td><td>None</td><td>0.03</td></tr><tr><th><i>Hylobates lar</i></th><td>Gibbon</td><td>33</td><td>M</td><td>R</td><td>KUPRI/465</td><td>0.250</td></tr></tbody></table>
SFC-A68: A dataset for benchmarking space function and space access element classification methods in entire floors of multi-unit apartment buildings
<p> </p> <p><strong>SFC-A68</strong>: "A dataset for benchmarking space function and space access element classification methods in entire floors of multi-unit apartment buildings"</p> <p><strong>Authors:</strong> "Amir Ziaee, Georg Suter, Laura Keiblinger"</p> <p><strong>Copyright:</strong> "Design Computing Group TU Wien, 2024"</p> <p><strong>Credits:</strong> "Design Computing Group TU Wien"</p> <p><strong>License:</strong> "GNU GENERAL PUBLIC LICENSE Version 3"</p> <p><strong>Version:</strong> "1.0.2"</p> <p><strong>Maintainer:</strong> "Amir Ziaee"</p> <p><strong>Email:</strong> "amir.ziaee@tuwien.ac.at"</p> <p><strong>Acknowledgments:</strong> "The authors gratefully acknowledge support by Grant Austrian Science Fund (FWF): I 5171-N, Laura Keiblinger, and participants in course '259.428-2021S Architectural Morphology' at TU Wien for data collection. "</p> <p><strong>Description:</strong> "The analysis of building models for usable area, building safety, and energy efficiency requires accurate classification data of spaces and related space elements such as doors. To reduce input model preparation effort and errors, automated classification of spaces and related space elements is desirable. We introduce the SFC-A68 dataset, which models entire floors of 275 multi-unit apartment buildings in 13 countries. The SFC-A68 consists of three data representation formats: tabular, graph, and multi-view image datasets that are derived from the same source data. It covere 22 space function and six space access element classes."</p> <p> </p> <p> </p> <p> </p>
Supplementary material for "Tracing emerging contaminants from the Baltic Sea and North Sea in fjord waters in southern Norway with rare earth elements as far-field tracers"
<p><span>Dataset presented and discussed in the manuscript of the research article “</span><span>Tracing emerging contaminants from the Baltic Sea and North Sea in fjord waters in southern Norway with rare earth elements as far-field tracers</span><span><span>” by Zocher et al. The manuscript will be submitted to <em>Environmental Pollution</em> and was prepared by the following authors: </span></span></p> <p> </p> <p><span><span>Anna-Lena Zocher (1), Tomasz Maciej Ciesielski (2,3), Stefania Piarulli (4), Julia Farkas (4) and Michael Bau (1). </span></span></p> <p><span> </span></p> <p><span><span>(1) School of Science, Constructor University, Bremen, Germany</span></span></p> <p><span><span>(2) Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway</span></span></p> <p><span><span>(3) </span></span><span><span>Department of Arctic Technology, The University Centre in Svalbard (UNIS), Longyearbyen, Norway</span></span></p> <p><span><span>(4) SINTEF Ocean, Trondheim, Norway</span></span></p> <p> </p> <p><span>This work was conducted within the ELEMENTARY project, and we appreciate funding from the Norwegian Research Council (grant No. 301236).</span></p>
Supplementary material for "Rare earth elements and yttrium in Polish rivers and the input of anthropogenic gadolinium into the Baltic Sea"
<p>This dataset is presented and discussed in the research article “Rare earth elements and yttrium in Polish rivers and the input of anthropogenic gadolinium into the Baltic Sea” by Alemu et al. This manuscript will be submitted to Environmental Pollution and was prepared by the following authors: Addis Kokeb Alemu (1,2), Keran Zhang (1), David Ernst (1), and Michael Bau (1). </p> <p>1Critical Metals for Enabling Technologies – CritMET, School of Science, Constructor University, Campus Ring 1, 28759 Bremen, Germany</p> <p>2Department of Chemistry, College of Natural and Computational Sciences, University of Gondar, P.O. Box 196, Gondar, Ethiopia</p> <p> </p> <p> </p> <p>Table A1 includes the general information and data for all sampling stations and reference materials used. </p> <p>Figs. A1 and A2 show the concentrations of total Gd and anthropogenic Gd in samples from the Oder River (OD) and its major tributary, the Warta River (Wa), as well as the Vistula River (VS) and its major tributaries: San (Sn), Bug (BG), Brda (BR), and Narew (NR).</p>
An enhanced single Gaussian point continuum finite element formulation using automatic differentiation: Source code and data
<p>This dataset contains the source code and the data with an example of uniaxial strain of an enhanced single Gaussian point continuum finite elemnet formulation using automatic differentiation.</p> <p> </p> <p>This contribution presents a low-order 3D finite element formulation with hourglass stabilization using automatic differentiation. Here, the former Q1STc element formulation is enhanced by an approximation-free computation of the inverse of the Jacobian. The improved version is termed "Q1STc+."</p> <p> </p> <p>The corresponding publication is:</p> <p><br>Pacolli, N., Awad, A., Kehls, J., Sauren, B., Klinkel, S., Reese, S., Holthusen, H.<br><em>An enhanced single Gaussian point continuum finite elemnet formulation using automatic differentiation.</em></p> <p>Standalone_Elementroutine: <em>Q1STc+_Codes</em> contains:</p> <ul> <li><strong>main.f90</strong>: Standalone routine for local uniaxial strain test</li> <li><strong>Makefile</strong>: Makefile to create executable "Q1STc+"</li> <li><strong>elem40.f90</strong>: Element routine "Q1STc+" with elem_sub.f90 as the subroutine written in AceGen</li> <li><strong>mat52.f90</strong>: Elasto-plastic material routine with all subroutines written in AceGen</li> <li><strong>elem_mat_select.f90</strong>: The selected material routine (Here: mat52)</li> <li><strong>elem_subs.f90</strong>: Subroutines for elem40.f90</li> <li><strong>mat_subs.f90</strong>: Subroutines for mat52.f90</li> </ul>
Deep-Time Marine Sedimentary Element Database
<p>The Deep-Time Marine Sedimentary Element Database (DM-SED), built upon the Sedimentary Geochemistry and Paleoenvironments Project (SGP; n = 28,753) database with an additional 433 studies and 34,874 data entries, totaling 63,627 entries. This database contains 2,522,255 discrete proxy values covering the distributions of major and trace elements and some isotopes in ancient marine sediments. It includes 9,207 entries from the Precambrian and 54,420 entries from the Phanerozoic, thus providing significant references for reconstructing deep-time Earth system evolution.</p>
GREEN-DB: Genomic Regulatory Elements ENcyclopedia
<p>GREEN-DB is a comprehensive collection of 2.4 million regulatory elements in the human genome collected from previously published databases, high-throughput screenings and functional studies. Regulatory regions are classified as enhancers, promoters, silencers, bivalent and information on the controlled gene(s), tissue(s) and associated phenotype(s) are provided for each element when possible. We also calculated a variation constraint metric (range 0-1) for these regulatory regions and showed that genes controlled by constrained regions are enriched for disease-associated genes and essential genes from mouse knock-out screenings.</p> <p>The database also includes information from ENCODE TFBS and DNase peaks; ultra-conserved non-coding elements (UCNE), super-enhancers (dbSuper) and TAD domains (TAD-KB).</p> <p>This release includes 5 files:</p> <ul> <li>GREEN-DB_v2.5.db.gz: The full database in SQLite format</li> <li>GRCh37_GREEN-DB.bed.gz[.csi]: A indexed BED file using GRCh37 genome coordinates describing the regulatory regions and associated information useful for variant annotations (controlled genes, closest gene/TSS, constraint metric).</li> <li>GRCh38_GREEN-DB.bed.gz[.csi]: A indexed BED file using GRCh38 genome coordinates describing the regulatory regions and associated information useful for variant annotations (controlled genes, closest gene/TSS, constraint metric).</li> </ul> <p>To annotate a VCF file with information from GREEN-DB you can use the bed files and our tool GREEN-VARAN (<a href="https://github.com/edg1983/GREEN-VARAN">https://github.com/edg1983/GREEN-VARAN</a>).</p> <p>For more information on the GREEN-DB please refer to our publication (<a href="https://doi.org/10.1101/2020.09.17.301960">https://doi.org/10.1101/2020.09.17.301960</a>) and to online documentation (<a href="https://green-varan.readthedocs.io/en/latest/">https://green-varan.readthedocs.io/en/latest/</a>)</p> <p>GREEN-DB is free to use for academic users, please refer to the attached LICENSE file.</p> <p> </p> <p><strong>Changes from the previous version:</strong></p> <p>- We fixed an issue with alias symbols conversion that caused a small fraction of region-gene links to point to the wrong gene</p> <p>- Due to the problem above, we removed any region-gene link where the region and the controlled gene were located on different chromosomes</p> <p>- GREEN-DB now includes also TAD domain information from TAD-KB (http://dna.cs.miami.edu/TADKB/) and region-gene interactions are now annotated for occurrence within the same TAD</p> <p>- Better constraint metric model that now takes into account overlap with exonic regions</p> <p>- In addition to the closest gene, an annotation for the closest TSS and its distance is now provided </p>
Transposable elements mark a repeat-rich region associated with migratory phenotypes of willow warblers (Phylloscopus trochilus).
<p>This upload contains the relevant data (alignments, trees, html TE landscape files, and datasheets) used in the manuscript: "The importance of repeat-rich regions in the migratory phenotypes of the willow warbler (Phylloscopus trochilus): transposable elements as a marker."</p>
OPT data from: A novel cis-regulatory element drives early expression of Nkx3.2 in the gnathostome primary jaw joint
<p><span>The acquisition of movable jaws was a major event during vertebrate evolution. The role of NK3 homeobox 2 (Nkx3.2) transcription factor in patterning the primary jaw joint of gnathostomes (jawed vertebrates) is well known, however, knowledge about its regulatory mechanism is lacking. In this study, we report a proximal enhancer element of <em>Nkx3.2</em> that is deeply conserved in most gnathostomes but undetectable in the jawless hagfish and lamprey. This enhancer is active in the developing jaw joint region of the zebrafish <em>Danio rerio</em>, and was thus designated as <em>jaw joint regulatory sequence 1</em> (JRS1). We further show that JRS1 enhancer sequences from a range of gnathostome species, including a chondrichthyan and mammals, have the same activity in the jaw joint as the native zebrafish enhancer, indicating a high degree of functional conservation despite the divergence of cartilaginous and bony fish lineages or the transition of the primary jaw joint into the middle ear of mammals. Finally, we show that deletion of JRS1 from the zebrafish genome using CRISPR/Cas9 results in a significant reduction of early gene expression of <em>Nkx3.2</em> and leads to transient jaw joint deformation and partial fusion. The emergence of this <em>Nkx3.2 </em>enhancer in early gnathostomes may have contributed to the origin and shaping of the articulating surfaces of vertebrate jaws.</span></p>
Numerical discrimination of sets of elements by Archerfish
<p>Debates have arisen as to whether non-human animals actually can learn abstract non-symbolic numerousness or whether they always rely on some continuous physical aspect of the stimuli, covarying with number. Here we investigated archerfish (<em>Toxotes jaculatrix</em>) non-symbolic numerical discrimination with accurate control for co-varying continuous physical stimulus attributes. Archerfish were trained to select one of two groups of black dots (Exp. 1: 3 <em>vs. </em>6 elements; Exp. 2: 2 <em>vs.</em> 3 elements); these were controlled for several combinations of physical variables (elements' size, overall area, overall perimeter, density and sparsity), ensuring that only numerical information was available. Generalization tests with novel numerical comparisons (2 <em>vs.</em> 3, 5 <em>vs.</em> 8 and 6 <em>vs.</em> 9 in Exp. 1; 3 <em>vs.</em> 4, 3 <em>vs.</em> 6 in Exp. 2) revealed choice for the largest or smallest numerical group according to the relative number that was rewarded at training. None of the continuous physical variables, including spatial frequency, were affecting archerfish performance. Results provide evidence that archerfish spontaneously use abstract relative numerical information for both small and large numbers when only numerical cues are available.</p>
Impact of green clay authigenesis on element sequestration in marine settings
<p>Supplementary Information to article "<strong>Impact of green clay authigenesis on element sequestration in marine settings</strong>", published in Nature Communications (Baldermann et al., 2022).</p>
Inputdata for CESM2.3x compset F2000climo with spectral-element dynamical core.and refined grid over Greenland
<p>Input data necessary to run a CESM2.3x case for the F2000 compset and a variable resolution mesh with a 1 degree global horizontal resolution grid and regional refinement of 1/4 degree resolution over the broader Arctic region plus an additionally 1/8 degree refinement over Greenland</p>
Supplementary dataset for "High-resolution Finite Fault Slip Inversion of the 2019 Ridgecrest Earthquake using 3D Finite Element Modeling."
<p>Supplementary dataset for "High-resolution Finite Fault Slip Inversion of the 2019 Ridgecrest Earthquake using 3D Finite Element Modeling." </p>
PC338 major elements and Sr-Nd isotopes
<p>Major elements and Sr-Nd isotopes data for the core PC338 from South China Sea.</p>
Woodpecker drum evolution: an analysis of covariation in elements of a multicomponent acoustic display among and within species
<p>Multicomponent signals are found throughout the animal kingdom, but how these elaborate displays evolve and diversify is still unclear. Here, we explore the evolution of the woodpecker drum display. Two components of this territorial, sexually selected signal, drum speed and drum length, are used by territory holders to assess the threat level of an intruding drummer. We explore the coevolution of these display components both among and within species. Among species, we find evidence for strong coevolution of drum speed and length. Within species, we find that drum speed and length vary largely independent of each other. However, in some species, there is evidence of covariation in certain portions of the drum length distribution. The observed differences in component covariation at the macro- and microevolutionary scales highlights the importance of studying signal structure both among and within species. In all cases of covariation at both evolutionary scales, the relationship between drum speed and length is positive, indicating mutual elaboration of display components, and not a performance trade-off.</p>
Multifunctional corrosion control system as a sustainable approach for reinforced concrete elements
<p>Corrosion inhibitors can be utilized to decrease the corrosion kinetics and therefore increase the durability of reinforced concrete structures. Recently, a green synthesized organic compound, 1-benzyl-4-phenyl-1H-1,2,3-triazole (BPT), was shown to be a successful green organic corrosion inhibitor for mild steel. Studies suggested that the BPT adsorbs chemically onto the steel and acts as a mixed inhibitor, suppressing both the anodic and cathodic corrosion kinetics of steel. In addition, microcapsules have shown to be an efficient way for a controlled inhibitor release in reinforced concrete structures. On the other hand, geopolymers (GPs) comprised of a long range of covalently bonded alumino-silicates, with amorphous network structure are generally considered as a suitable substitute for OPC for many structural applications due to their high strength and durability. The use of recycled waste materials or natural abundant materials for the production of GPs has attracted world-wide attention as it presents an environment-friendly aspect that may shed light on for replacing traditional OPC by its sustainability. One of the advantages of GPs is the significant reduction to CO2 emission due to the energy consumption, the geopolymers utilize materials such as fly-ash, which is a byproduct of coal combustion, or natural precursor materials (clays, basalt rocks, etc.) and their derives (metakaolin), which does not produce net CO2 emission. Recent studies have shown that GPs based cements can hinder the corrosion of reinforcement steel in concrete structures when compared to OPC, mostly because of lower chloride ingress (due to barrier protective capabilities) and the highly alkaline pH nature of geopolymer cements.</p>
Artificial selection on cis-element of Abl contributes cocoon yield increase in domestic silkworm
<p><span>The silkworm (</span><em><span>Bombyx mori</span></em><span>) is an important silk-producing domestic insect.</span><span> The quality and yield of the silk produced by <em>B. mori </em>exceeds that of its ancestor, the wild silkworm <em>B. mandarina</em>. However, to date little is known about the molecular mechanisms underlying domestication-related increases in silk yield. Here, we identified a gene associated with both domestication and silk-related quantitative trait locus (QTL): Abelson tyrosine protein kinase (<em>Abl</em>). </span><span>Population genomic data for <em>B. mori</em> and <em>B. mandarina</em> identified obvious signatures of artificial selection in the genomic region bearing the <em>Abl</em></span><span><em> </em>gene. T</span><span>here were two fixed nucleotide substitutions (−244 and −1311) in the </span><span>tran</span><span>scription factor binding motif of the upstream regulatory region of <em>B. mori Abl</em>.</span> <span>Compared to <em>Abl </em>in the wild silkworm <em>B. mandarina</em>, <em>B. mori Abl</em> exhibited significantly greater promoter activity and was upregulated in the silk gland from the last day of the 5<sup>th</sup> larval instar to pupal stage (P0). Compared to the wild type, CRISPR/Cas9-generated <em>Abl </em>loss-of-function mutants </span><span>exhibited a higher sensitivity to diseases, shorter developmental duration, and reductions in economically important silk traits, including cocoon weight, pupal weight, and cocoon layer thickness. Comparison of silk-gland transcriptomes between the wild type and the mutant indicated that genes enriched in ribosome biosynthesis, splicing, RNA transport, and the carbon metabolism were significantly downregulated in the mutants. Weighted gene co-expression network analysis (WGCNA) confirmed that genes related to ribosome biosynthesis were pivotal, driving the significant differentiation in silk yield between <em>B. mori</em> and <em>B. mandarina</em>. Here, we demonstrated that artificial selection acts on the cis-elements of silk-trait QTL gene <em>Abl </em>in a novel case (the domestic silkworm), and that this selection pressure increased <em>Abl </em>promoter activity and expression level. By promoting protein translation and synthesis, artificial selection further enhanced the robustness of silkworm larvae and improved cocoon silk synthesis.</span></p>
Quantitative assessment of trace and macro element compositions of Cassava (Manihot esculenta) storage roots enriched with Β-Carotene as influenced by genotypes and growing locations
Cassava's important mineral contents depends on some factors, including genetic and growing locational factors. The study aimed to evaluate the influence of genotype and growing locations on the mineral concentrations in yellow-fleshed cassava root genotypes. Twenty-five pipeline yellow-fleshed cassava genotypes and three white-fleshed varieties (check samples) were planted at five different experimental fields for two seasons, each representing the major agroecological zones in Nigeria. Standard laboratory protocols were employed in the sampling to ensure zero contamination, and the trace and macro elements were determined using the inductively coupled plasma optical emission spectroscopic method (ICPOES). The trace and macro elements identified in all the genotypes and varieties investigated were Fe, Mn, B, Cu, Mo, Co, Ni, Zn, and Al; Ca, Mg, Na, K. P, and S respectively. Genotype and growing location had a highly significant (p < 0.05) effect on all the trace elements except Ti and Cr. However, there was no interactive effect between genotype and growing location on all the trace elements except for Pb and Zn. Among the explanatory variables, the variable growing location was the most influential on macro and trace elements. Conclusively, genotypes 01/1442 and 01/1273 have outstanding trace and macro element concentrations.
Conserved structural elements specialize ATAD1 as a membrane protein extraction machine
<p>The mitochondrial AAA protein ATAD1 (in humans; Msp1 in yeast) removes mislocalized membrane proteins, as well as stuck import substrates from the mitochondrial outer membrane, facilitating their re-insertion into their cognate organelles and maintaining mitochondria's protein import capacity. In doing so, it helps to maintain proteostasis in mitochondria. How ATAD1 tackles the energetic challenge to extract hydrophobic membrane proteins from the lipid bilayer and what structural features adapt ATAD1 for its particular function has remained a mystery. Previously, we determined the structure of Msp1 in complex with a peptide substrate (Wang et al., 2020). The structure showed that Msp1's mechanism follows the general principle established for AAA proteins while adopting several structural features that specialize it for its function. Among these features in Msp1 was the utilization of multiple aromatic amino acids to firmly grip the substrate in the central pore. However, it was not clear whether the aromatic nature of these amino acids were required, or if they could be functionally replaced by aliphatic amino acids. In this work, we determined the cryo-EM structures of the human ATAD1 in complex with a peptide substrate at near atomic resolution. The structures show that phylogenetically conserved structural elements adapt ATAD1 for its function while generally adopting a conserved mechanism shared by many AAA proteins. We developed a microscopy-based assay reporting on protein mislocalization, with which we directly assessed ATAD1's activity in live cells and showed that both aromatic amino acids in pore-loop 1 are required for ATAD1's function and cannot be substituted by aliphatic amino acids. A short α-helix at the C-terminus strongly facilitates ATAD1's oligomerization, a structural feature that distinguishes ATAD1 from its closely related proteins.</p>
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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.