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GENeSYS-MOD pathways developed by the openENTRANCE project

This dataset contains quantitative pathways developed with the GENeSYS-MOD 3.1 model in the openENTRANCE project. You can find additional information, including all model results and native input files, at the Supplementary Material for Deliverable D3.2 of the openENTRANCE project at <a href="https://doi.org/10.5281/zenodo.7760651">https://doi.org/10.5281/zenodo.7760651</a>. The data file follows the IAMC data format and the conventions established by the openENTRANCE project. See <a href="https://github.com/openENTRANCE/openentrance">https://github.com/openENTRANCE/openentrance</a> for details. Visit the openENTRANCE Scenario Explorer at <a href="https://data.ene.iiasa.ac.at/openentrance">https://data.ece.iiasa.ac.at/openentrance</a> for more information about the openENTRANCE project and other datasets.

opencc-zeroJun 2023View details →

dryad40/100

Data from: Mitochondrial function is enhanced by thyroid hormones during zebra finch development

An organism's response to its environment is largely underpinned by changes in the energy supplied by the aerobic mitochondrial metabolism via adenosine-tri-phosphate (ATP) production. ATP is especially important under energy-demanding conditions, such as during growth. The biological mechanisms through which environmental factors feed-back on mitochondrial function, and thus growth, are poorly understood, but recent studies suggest a role of hormones. In particular, thyroid hormones (THs) are key regulators of growth and metabolism in vertebrates, which react flexibly to environmental influences, such as temperature or nutrient availability. We manipulated TH levels within physiological ranges during the main growth phase in zebra finch (Taeniopygia guttata) nestlings, to test for causal relationships with mitochondrial function and growth. Our TH-treatment accelerated skeletal growth and maximal mitochondrial working capacity, ETS – a mitochondrial trait reflecting ATP production potential. Furthermore, TH marginally elevated cellular metabolic rate and oxidative phosphorylation, the final step of ATP production. To our knowledge, this is the first study to characterize the regulation of mitochondria by TH during development in a naturalistic context and to address the implications for fitness.

Development, validation and use of artificial-intelligence-related technologies to assess basic motor skills in children: a scoping review

This project contains the following extended data: <ul> <li>Appendix 1. Supplementary Tables</li> <li>Appendix 2. Search formulas</li> </ul>

opencc-by-4.0May 2023View details →

Development of a national point-of-care ultrasound training course for physicians in Japan: A 3-year evaluation

Purpose: Point-of-care ultrasound (POCUS) allows bedside clinicians to acquire, interpret, and integrate ultrasound images into patient care. Although the availability of POCUS training courses has increased, the educational effectiveness of these courses is unclear. Methods: From 2017 to 2019, we investigated the educational effectiveness of a standardized 2-day hands-on POCUS training course and changes in pre- and post-course exam scores in relationship to participants’ (n = 571) clinical rank, years of POCUS experience, and frequency of POCUS use in clinical practice. Results: The mean pre- and post-course examination scores were 67.2 (standard deviation [SD] 12.3) and 79.7 (SD 9.7), respectively. Higher pre-course examination scores were associated with higher clinical rank, more years of POCUS experience, and more frequent POCUS use (p < 0.05). All participants showed significant changes in pre- to post-course exam scores. Though pre-course scores differed by clinical rank, POCUS experience, and frequency of POCUS use, differences in post-course scores according to participant baseline differences were non-significant. Conclusion: A standardized hands-on POCUS training course is effective for improving POCUS knowledge regardless of baseline differences in clinical rank, POCUS experience, or frequency of POCUS use. Future studies shall evaluate changes in POCUS use in clinical practice after POCUS training.

Figure 6 in Initiation and early development of the postcanine deciduous dentition in the dasyurid marsupial Dasyurus viverrinus

Figure 6. Dasyurus albopunctatus pouch young: a, (AMNH 190927; 36.64 mm skull length). Erupting teeth in the upper jaw with canine about ½ erupted. The dP1 is almost completely erupted and P3 is in early eruption. A tiny, slender dP3 is lying on the distal margins of the erupting P3, pointing posteriorly; its apex is not evident. M1 is erupted and the M2 is about ¾ erupting (not shown); b, (AMNH 221650; 37.53 mm skull length) slightly older than the preceding. The dP1 is erupted in the upper jaw and P3 is erupting (½–⅔). A tiny, elongate dP3 is evident along the posterior margins of the erupting P3; c, (BBM – NG 28247; 37.89 mm skull length). The dP1 is erupted, and the P3 is almost completely erupted in the upper jaw. A tiny, slender and elongate dP3 is evident along the distal margin of P3 and its root extends distally beneath the anterior opening of the infraorbital canal; d, (BBM – NG 97868; 47.25 mm skull length). In this older young, the P3 is almost completely erupted in the upper jaw. A tiny, slender root remnant of dP3 is evident, distal to the buccal end of P3.

Figure 4 in Initiation and early development of the postcanine deciduous dentition in the dasyurid marsupial Dasyurus viverrinus

Figure 4. Parasagittal section through the dentition in a 25-day-old pouch young (12.5 mm head length) showing the developing teeth between dP1 and M2 in the upper jaw. Arrowhead refers to the site of the missing dP2. Abbreviation: D, location of developing dP3 follicle.

Figure 2 in Initiation and early development of the postcanine deciduous dentition in the dasyurid marsupial Dasyurus viverrinus

Figure 2. Transverse sections of early developmental stages of the dentition in marsupials: a, early tooth bud forming from the dental lamina; b, early-cap stage; c, middle-bell stage with elongate dental lamina; d, late-bell stage with odontoblasts and early lingual successional lamina; e, well-developed late-bell stage with dentin and enamel. A successional early-cap stage develops from the lingual successional lamina, showing early fragmentation of the dental lamina. Abbreviations: AM, ameloblasts; D, dentin; DL, dental lamina; DP, dental papilla; E, enamel; IEE, inner enamel epithelium; OD, odontoblasts; OEE, outer enamel epithelium; SL, successional lamina; SR, stellate reticulum; TB, tooth bud.

Figure 1 in Initiation and early development of the postcanine deciduous dentition in the dasyurid marsupial Dasyurus viverrinus

Figure 1. Four early pouch young of Dasyurus viverrinus: a, 30 hours old, 3.25 mm head length (HL); b, 5–6 days old, 4.5 mm HL; c, 14 days old, 8 mm HL; d, 25 days old, 12.5 mm HL.

Figure 3 in Initiation and early development of the postcanine deciduous dentition in the dasyurid marsupial Dasyurus viverrinus

Figure 3. Transverse section through the head at the level of the developing eyes in a 10-day-old Dasyurus viverrinus embryo (7 mm head length). Note the close compression between the large tongue (T) and the nipple (N). No developing teeth are evident.

Figure S2 in Large-scale snake genome analyses provide insights into vertebrate development

Figure S2. Snake genome features, related to Figure 2 (A) Evolution of chromosomes in snakes. In total, 23 proto-chromosomes of Serpentes were reconstructed using four lizards as outgroup. (B) Circos plots showing conserved synteny between the hypothesized Serpentes ancestor: Serpentes (red) and Hong Kong dwarf snake (Csep-blue). (C) Snake body lengths were significantly negatively correlated with the genome evolutionary rate (correlation coefficient = 0.50, p value = 0.011). (D) Length distribution of snake ancestor gain and lost genome segments. Length distribution of snake ancestor unique genome segments (left). Length distribution of snake ancestor lost genome segments (right).

Figure S3 in Large-scale snake genome analyses provide insights into vertebrate development

Figure S3. Snake-specific genome structural variations (SSSVs), snake-diverged conserved non-coding elements (SD-CNEs that were diverged in snakes but were still conserved in the outgroup) (SD-CNEs), and orthologous genes used for evolutionary analysis, related to Figure 3 and STAR Methods (A) SSSVs distribution in different genome regions. (B) Genomic reads coverage of the snake-specific lost gene GHRL across four lizards (green anole [Acar], Anan's rock agama [Lsac], Komodo dragon [Vkom],and viviparous lizard [Zviv]), and 14 newly sequenced snakes. (C) Z-score cut off of SD-CNEs. (D) The enriched MGI terms that related to snake phenotypes for genes with SD-CNE (adjusted p value <0.05). SD-CNEs (dots) are located around the transcription start site of the genes enriched in eye, eyelid, ear, lung, mandible, maxillary, sternum, and tooth development-related terms. (E) Enriched GO terms (adjusted p value <0.05) for the newly evolved coding genes in snakes. Those related to dietary excess, protein digestion, and olfactory receptor activity were colored in red, blue, and brown, respectively. (F) Enriched GO terms (adjusted p value <0.05) for snake-specific coding genes that were lost. Red, blue, orange, and green were used to indicate the terms involved in vision, lens development, appetite, and bile acid biosynthetic process, respectively. (G) SSSV deletion in the potential regulatory region of RP1. (H) Counts of orthologous genes used for evolutionary analysis among 27 selected species.

Figure 3 in Large-scale snake genome analyses provide insights into vertebrate development

Figure 3. Genetic basis of skeletal system evolution and organ adaptation in snakes PSGs, REGs, WGCNA hub genes, lost genes, SSSV-related genes, newly evolved genes, and SD-CNE-associated genes are marked in different colors and are represented by rectangles. (A) Renewal of genomic elements contributing to snake skull development and digestion. Related genes are shown in their corresponding regions. (B) The evolution of genomic elements has potentially facilitated the evolution of the elongated body plan of snakes. (C) The evolution of genes related to lung development and function. The heatmap shows the expression levels of WGCNA hub genes, PSGs, and SSSV-related genes in green anole (Acar), keeled slug snake (Pber), and many-banded krait (Bmul) (The ''_numbers'' represents the different copies of a multi-copy gene). (D) Whole-body X-ray images and relative lengths of the fourth forelimb phalanx and third hindlimb phalanx of wild and PTCH1-mutated mice (eight samples per group, the significance is indicated as *p <0.05). Mean ± SD is shown by error bar. See also Figure S4 and Table S3.

Figure S1 in Large-scale snake genome analyses provide insights into vertebrate development

Figure S1. Phylogenetic and divergent time tree of snakes, related to Figure 1 (A) Phylogenetic tree distributions of selected snake species, topology inferred from a previous study.173 (B) Maximum likelihood (ML) phylogenetic tree inferred from the 31-taxon whole-genome alignments. Ultrafast bootstraps were repeated 3,000 times, with NNI UFBoot tree optimization and SH-like approximate likelihood ratio test (SH-aLRT) performed. SH-aLRT support rate/ultrafast bootstrap support rate is indicated at each node. (C) Inferred ML phylogenetic tree using orthologous genes. 1,980 1:1 orthologous genes were concatenated to a super gene sequence for constructing the ML phylogenetic tree using IQ-TREE. 10,000 ultrafast bootstraps were carried out and the two support rates were marked at each node. (D) ML phylogenetic tree inferred from 4d sites. 4d sites were extracted from the orthologous genes and taken as input for IQ-TREE to infer the ML phylogenetic tree. The two supports were computed by 10,000 ultrafast bootstraps and SH-aLRT. (E) Inferred ML phylogenetic tree of conserved non-coding elements (CNEs). All CNEs were identified and concatenated into a single sequence for the ML phylogenetic tree inferred using 5,000 ultrafast bootstraps and SH-aLRT. (F) Coalescent phylogenetic tree inferred from 51,302 1-kb orthologous genomic segments using ASTRAL-III. (G) Coalescent phylogenetic tree inferred from 1,980 1:1 orthologous genes using ASTRAL-III. The poorly supported nodes are indicated in red. (H) DicoVista gene tree topologies frequency analysis. The frequency of three topologies (t1–t3) is shown, and the red is the main topology. The divergence time (million years ago [mya]) of the species is estimated using r8s and the incongruent clades are in red. (I) Divergence time of the 31 species. r8s estimated divergence time using the whole-genome alignments.The estimated divergence time (million years ago [mya]) is labeled on each node and 6 calibrating nodes used are marked. (J) MCMCTree estimated divergence time of the 31 species using 4d sites. Six calibrating nodes used are marked and the estimated divergence time represented in million years is labeled.

Figure 5 in Large-scale snake genome analyses provide insights into vertebrate development

Figure 5. Evolution of blind and infrared-sensitive snakes (A) Specialized traits of blind snakes. (B) Gene regression underlies eye degeneration in blind snakes. Lost genes are shown in green. Heatmap showing the significant down-regulation of the expression of genes in blind snake eyes (QN, quantile normalized). (C) BSD-CNE-associated genes enriched in odontogenesis and bone-development-related GO terms. (D) Amino acids sequences alignment (left) and enzymatic activity (right) of CHIA. The amino acids in red are positively selected sites in blind snakes. The error bar represents mean ± SD of enzymatic activity. The enzymatic activity is significantly higher in Diard's blind snake (Student's t-test p value = 8.78e-09). (E) Infrared sensing-related genes in infrared-sensitive snakes. PSGs, REGs, and variation-shared genes are indicated in purple, blue, and red, respectively. Average expression levels (represented by FPKM) of these genes in seven tissues of the brown-spotted pitviper are shown. See also Figure S5 and Tables S4 and S5.

Figure 4 in Large-scale snake genome analyses provide insights into vertebrate development

Figure 4. Genome features associated with snake-specific sense organ evolution, highlighting PSGs, REGs, newly evolved genes, SD-CNEassociated genes, lost genes, and SSSV-associated genes (A) Lost and highly expressed genes in snake eyes. Diagram of the snake eye showing lost genes in blue. Heatmap of highly expressed genes (QN, quantile normalized). (B) Diagram of the snake inner ear. Twelve SD-CNE-associated genes and four SSSV-associated genes are involved in ear development. Expression levels (scaled fragments per kilobase per million mapped reads [FPKM]) of sound perception-related PSGs and REGs in 10 keeled slug snake (Pber) tissues are shown in circles. Circle size is positively correlated to the expression level. (C) Diagram of the taste transduction process. Solid lines indicate direct interactions, and dotted lines indicate indirect interactions. See also Table S3.

Figure 1 in Large-scale snake genome analyses provide insights into vertebrate development

Figure 1. Phylogeny of snakes Maximum-likelihood phylogenetic tree inferred from whole-genome sequences of 31 species. Divergence times of all nodes were estimated by r8s with whole-genome sequences using six calibration points (Figures S1I and S1J). All genomes generated in this study are in red. Maps were taken from those in a previous study.24

Figure S5 in Large-scale snake genome analyses provide insights into vertebrate development

Figure S5. Genome evolution of snake sensory system, related to Figures 4 and 5 (A) Expression patterns of genes associated with eye development in human embryos at different embryonic stages (4.7–8 weeks post conception [wpc]) and red cornsnake embryos at 10, 30, and 50 days post oviposition (dpo). (B) KMT2C specific amino acids residue lost in snakes and its associated snakes divergent CNE (SD-CNE). The black line portrays gene structure with blue blocks representing CDSs and the numbers indicate the exact positions on the European glass lizard reference genome. Three segments of snake-specific amino acid residue loss are manifested by internal numbers ''4002–4004,'' ''2110–2112,'' and ''1983–1987.'' One SD-CNE located at 30 regulate region of KMT2C is marked by a red block. (C) Alignment of SSSV that inserted into the 5 kb upstream of PDZD7 transcription start site. This SSSV conveys a new EBF1 binding site with a regulatory potential (RP) score: 0.78. (D) Taste transduction involved genes were expressed in tongue and brain of three snakes (plumbeous water snake [Hplu], keeled slug snake [Pber], and Asian vine snake [Apra]). The numbers in cells indicate the scaled FPKM values. (E) Comparison of eye structures between Diard's blind snake and Asian vine snake, keeled slug snake. The magnifications were marked as ''*×'' at the bottomright corner of each histological sections. (F) GOChord plot (produced by GOplot package) of blind snake divergent CNEs involved coding gene-enriched GO terms (p value <0.05). Left half of GOChord displayed genes of different GO terms and the right showed the GO term descriptions. Each gene was linked to a GO term by the colored bands. (G) REVIGO clusters of significantly overrepresented (p value <0.01) GO terms for blind snake REGs. (H) Expression levels of TRPV4 and TRPA1 in seven tissues of brown spotted pitviper. (I) Genome locations of pitviper diverged conserved non-coding elements (PVD-CNEs), and the infrared-sensitive python and boa divergent conserved non-coding elements (ISPBD-CNEs) in PMP22 and NFIB.

Data and supplementary materials in support of "Development and Preliminary Validation of an Open Access, Open Data and Open Outreach Indicator"

Data and supplementary materials in support of  "Evgenios Vlachos, Regine Ejstrup, Thea Marie Drachen, Bertil Fabricius Dorch (2023) Development and Preliminary Validation of an Open Access, Open Data and Open Outreach Indicator, Frontiers in Research Metrics and Analytics, doi: 10.3389/frma.2023.1218213"   It includes the anonymized dataset with the OADO values for all researchers from 10 departments (2 per faculty), the R code to perform the analysis and the graphs, the Scopus search string for the background search on Open Access and metrics, and the documentation for pulling data out from Pure.

NewSOC, supplementary information to WT2.3 "Development of doped lanthanum chromite based fuel electrodes", WT2.5 "Electrochemical characterization of single cells"

These are experimental data related to CERTH participation in NewSOC project (874577) regarding WT2.3 “Development of doped lanthanum chromite based fuel electrodes”, WT2.5 “Electrochemical characterization of single cells”. The data set includes: <ul> <li>physicochemical characterization (ICP, BET, XRD and SEM) of the powders and electrodes or cells produced (SEM)</li> <li>electrochemical characterization (iV characteristics, impedance, stability tests)</li> </ul>   LSCrF0.1.rar: The zip folder contains data related to La0.75Sr0.25Cr0.9Fe0.1O3-δ material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, (B) SEM images of electrodes and cells and (C) data set including iV, EIS and stability testing for button cells using different electrolyte substrates (formulation and thickness) and oxygen electrode materials operating under steam electrolysis, co-electrolysis of steam and carbon dioxide and reversible operation in steam or carbon dioxide cycle. LSCrF0.5.rar: The zip folder contains data related to La0.75Sr0.25Cr0.5Fe0.5O3-δ material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, (B) SEM images of electrodes and cells and (C) data set including iV and EIS for button cells operating under steam electrolysis and co-electrolysis of steam and carbon dioxide.   LSCrNi0.1.rar: The zip folder contains data related to La0.75Sr0.25Cr0.9Ni0.1O3-δ material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, (B) SEM images of electrodes and cells and (C) data set including iV and EIS for button cells operating under steam electrolysis and co-electrolysis of steam and carbon dioxide.  LSCrNi0.5.rar: The zip folder contains data related to La0.75Sr0.25Cr0.5Ni0.5O3-δ material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, and (B) data set including iV and EIS for button cells operating under steam electrolysis and co-electrolysis of steam and carbon dioxide. LSCrMn0.1.rar: The zip folder contains data related to La0.75Sr0.25Cr0.9Mn0.1O3-δ material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, (B) SEM images of electrodes and cells and (C) data set including iV and EIS for button cells operating under steam electrolysis and co-electrolysis of steam and carbon dioxide.    LSCrF0.05Ti0.05.rar: The zip folder contains data related to La0.75Sr0.25Cr0.9Fe0.05Ti0.05O3-δ material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM and (B) data set including iV and EIS for button cells operating under steam electrolysis, co-electrolysis of steam and carbon dioxide. LSCrF0.05V0.05.rar: The zip folder contains data related to La0.75Sr0.25Cr0.9Fe0.05V0.05O3-δ material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM and (B) data set including iV and EIS for button cells operating under steam electrolysis, co-electrolysis of steam and carbon dioxide. LSCrF0.25Ti0.25.rar: The zip folder contains data related to La0.75Sr0.25Cr0.5Fe0.25Ti0.25O3-δ material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM and (B) data set including iV and EIS for button cells operating under steam electrolysis, co-electrolysis of steam and carbon dioxide.  LSCrF0.25V0.25.rar: The zip folder contains data related to La0.75Sr0.25Cr0.5Fe0.25V0.25O3-δ material. (A) powder physicochemical characterization including ICP, BET, XRD and SEM, (B) SEM images of electrodes and cells and (C) data set including iV and EIS for button cells operating under steam electrolysis and co-electrolysis of steam and carbon dioxide. Ni-GDC.rar: The zip folder contains data related to button cell stability testing using a commercial Ni-GDC fuel electrode material operating under steam electrolysis.    LARGE CELLS.rar: Data set for large cells (5x5 cm2) including iV, EIS and short-term stability testing employing Keracell III cell, Ni-GDC and LSCrF0.1 fuel electrodes operating under steam electrolysis and co-electrolysis of steam and carbon dioxide.

Infants on the Move: Bibliometric Analyses of Observational versus Digital Means of Screening Infant Development

Datasets, High Resolution Images and Video tutorials for Bibliometric use on neonatal General Movements Assessment Neurodevelopmental disorder diagnoses have increased significantly over the years, though the average age of detection is 4.5 years old. This delay is partly due to reliance on social-communication criteria. These criteria require a level of maturation that takes much longer than scaffolding elements of neuromotor control. Early components of neurodevelopment include early evolution of reflexes, development of interactions between central pattern generators and cortical structures, maturation of intentional movements and their overall sensation. Such elements have been studied in General Movement Assessment (GMA) using observational means, but the last two decades have seen a surge in digital tools (biosensors, video-based pose estimation and algorithms) that permit non-invasive tracking of newborns’ movements. Despite their importance, these tools are not yet broadly used. In this work, using CiteSpace, VOSViewer and SciMAT software, we investigate the evolution of the literature on GMA and the methods in use today, to estimate how digital techniques are being adopted. To that end, we created maps of key word co-occurrence networks, co-author networks, document co-citation analysis and strategic diagrams of 295 publications based on a search in the Web of Science, Dimensions and SCOPUS databases for: ‘general movement assessment’ OR ‘general movements assessment’. The nodes on the maps were categorized by size, cluster groups and year of publication. We found that the state-of-the-art methodology to diagnose neurodevelopmental disorders still relies heavily on observation. Several groups in classical GMA research have branched out to incorporate new techniques, but few groups have adopted digital means. We report on additional analyses of methods and biosensors usage and propose that combining traditional clinical observation criteria with digital means may allow earlier diagnoses and interventional therapies for infants.