cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10640936
title: Defective mitochondrial COX1 translation due to loss of COX14 function triggers ROS-induced inflammation in liver

description: Data Content

In this data repository Ultra High-Performance Chromatography (UPLC) and Ion Chromatography (IC)- high resolution mass spectrometry (HRMS) metabolomic data is provided. The data consists of all analyzed raw files and the associated peak picking files (TraceFinder 5.1, Thermo Fisher Scientific). The data with the abreviation "Bz_QE_Plus" contains the UPLC-MS data of bezoylchloride derivatized amines, phenols, thiols, and some alcohols measured on a Q-Exactive Plus mass spectrometer), while the files with the abbreviation "IC_HF_TF" contain the anion chromatographic data measured on a Q-Exactive Plus coupled to an Integrion ion chroatograph.

The provided data is associated to an article submitted to Nature Communications (“Defective mitochondrial COX1 translation due to loss of COX14 function triggers ROS-induced inflammation in liver”), describing the analysis of COX14 and COA3 mutants (see abstract below).

The sample and data analysis section, which is also provided in the supplementary section of the above mentioned article, are also attached as, doc files to the deposited data.
description: Abstract of the article

Mitochondrial oxidative phosphorylation (OXPHOS) fuels cellular ATP demands. OXPHOS defects lead to severe human disorders with unexplained tissue specific pathologies. Mitochondrial gene expression is essential for OXPHOS biogenesis since core subunits of the complexes are mitochondrial-encoded. COX14 is required for translation of COX1, the central mitochondrial-encoded subunit of complex IV. Here we generated a COX14 mutant mouse corresponding to a patient with complex IV deficiency. COX14M19I mice display broad tissue-specific pathologies. A hallmark phenotype is severe liver inflammation linked to release of mitochondrial RNA into the cytosol sensed by RIG-1 pathway. We find that mitochondrial RNA release is triggered by increased reactive oxygen species production in the deficiency of complex IV. Additionally, we generated a COA3Y72C mouse, affected in an assembly factor in early COX1 biogenesis, which displayed a similar yet milder inflammatory phenotype. Our study provides mechanistic insight into how defective mitochondrial gene expression causes tissue-specific inflammation.
DOI: 10.17632/rz558tn77w.1
title: Authoritative Parenting style

description: The provided Python visually representation generates a visual conceptual model through a directed graph to depict relationships between attributes associated with authoritative parenting, decision-making abilities, and emotional stability. Utilizing the networkx and matplotlib.pyplot libraries, the code constructs nodes representing distinct parenting and psychological concepts, such as 'Warmth (W)' and 'Decision-Making Abilities (D)'. Directed edges between nodes signify the directional influences or relationships between these attributes. The resulting graph serves as a visual representation of the interconnections within this conceptual framework. By combining algorithmic layout determination and visualization parameters, the code offers a tangible depiction of the complex dynamics associated with authoritative parenting, decision-making, and emotional stability. This abstract underscores the utility of graphical representation as a tool for comprehending intricate relationships in psychological and parenting domains.
DOI: 10.17632/9kvg3s5j49.1
title: Table References Jordan et al: Management of Eruptive Keratoacanthomas: A Case Report and Literature Review

description: Reference list for Table References Jordan et al: Management of Eruptive Keratoacanthomas: A Case Report and Literature Review
DOI: 10.17632/cfz7d25wts.1
title: Ammonia assimilation coupled with rapid humification increases recalcitrant nitrogen reservoirs during bioaugmented mechanical composting

description: Plot data of the article "Ammonia assimilation coupled with rapid humification increases recalcitrant nitrogen reservoirs during bioaugmented mechanical composting".
1. Raw data from DNA sequencing.
2. FTIR and N1s XPS spectra of HM.
3. data of physicochemical indicators, N components, ammonia assimilation indicators, humification indicators, and mineralization indicators.
DOI: 10.17632/tww5fbwy62.2
title: Supplementary Material for JAAD

description: Supplementary Material for Efficacy and Safety of Intense Focused Ultrasound for Skin Rejuvenation: A Systematic Review and Meta-analysis
DOI: 10.17632/vg7v769r6s.1
title: NNPE

description: A code that automatically calculates missing data of any group of weather stations based on the station with the most consistent records of the group, called Neural Network Precipitation Estimator (NNPE)
DOI: 10.17632/tww5fbwy62.1
title: Supplementary Material for JAAD

description: Supplementary Material for Efficacy and Safety of Intense Focused Ultrasound for Skin Rejuvenation: A Systematic Review and Meta-analysis
DOI: 10.17632/6hyhsjbwkb.1
title: PoliMi-TUB dataset - LG 18650HE4 Li-Ion Battery

description: The data was obtained through tests performed at the Institute of Energy and Automation Technology in Technische Universität Berlin, Berlin, Germany with the collaboration of the Politecnico di Milano, Milan, Italy by Dr. Panagiotis Eleftheriadis (elefpana.auth@gmail.com). If this data is employed for any objective, it should be duly cited.

For this study:
A total of 6 2.5Ah LG18650HE4 battery cells were placed in a thermal chamber, specifically the Binder MK53. A Neware battery tester model BTS-4008 was utilized for cycling these battery cells. The dataset was merely pre-processed and transformed into the final structure uploaded. The dataset is suitable for State of Charge and State of Health estimations as well as their joint estimation. All information related to the setup and the test procedure are presented in the article:

[1] Joint State of Charge and State of Health Estimation using Bidirectional LSTM and Bayesian Hyperparameter Optimization
DOI: 10.17632/myd5bcf37d.1
title: Lack of agreement among analysers of infrared thermal images in the temperature of eye regions in sheep

description: Infrared thermography (IRT) is a non-invasive method to estimate body temperature in many animal species. The eye has been indicated as the ideal region for IRT, potentially serving as an early indicator of variations in body temperature triggered by various events and stimuli. Studies are being conducted to understand sources of variation in IRT temperature of the eye and develop comprehensive guidelines for veterinary medicine and animal production purposes. The present study adds information about variation in temperature estimated from different eye regions in sheep due to analysers. Thirty-one thermal images, fifteen of the right and sixteen of the left eyes of a ewe, captured with a FLIR E8-XT camera, were analysed by each of three analysers, and minimum (Tmin), maximum (Tmax) and average (Tavg) temperature in lacrimal caruncle (R1), medial canthus of the eye (R2) and eyeball (R3) were estimated. Differences among analysers were analysed by ANOVA (normal distribution) or Friedman test (non-normal distribution), considering thermal images as blocks. Limits of Agreement with the Mean (LOAM) were estimated and agreement plots were drawn. There were no differences (P&gt;0.05) among analysers in temperature (°C, mean±standard deviation or median and 2.5%-97.5% quantiles) estimated in R1 (Tmin=36.3±0.87, Tmax=37.2 (35.9-37.7), Tavg=36.7±0.67), R2 (Tmax=37.2 (36.0-37.8)) and R3 (Tavg=36.1 (34.9-37.3)) for the right eye (n=45), and in R1 (Tmin=36.0 (34.3-37.3), Tmax=36.8±0.49, Tavg=36.4±0.53), R2 (Tmin=35.9±0.71, Tmax=36.7 (35.8-37.7), Tavg=36.3 (35.5-37.5)) and R3 (Tavg=35.9 (34.8-36.6)) for the left eye (n=48); but differences (P&lt;0.05) were present in R3 (Tmin, Tmax) for both eyes and in R2 (Tmin and Tavg) for the right eye. The highest mean differences in temperature (°C) (P&lt;0.05) among analysers were in R3 from the right eye (Tmin=0.70, Tmax=0.25) and the left eye (Tmin=0.64, Tmax=0.10), and in R2 from the right eye (Tmin=0.54, Tavg=0.50). Considering both eyes and all eye regions, the total range for the LOAM (°C) was lower for Tmax (0.42 to 0.93) and Tavg (0.63 to 1.17) than for Tmin (1.49 to 2.70), indicating a higher, medium, and lower agreement among analysers for Tmax, Tavg and Tmin, respectively. Considering the eyes, the total range for the LOAM (°C) was lower in all regions from the left eye (0.42 to 1.59) compared to the right eye (0.79 to 2.70), indicating a higher agreement among analysers from the left eye. Considering the eye regions, the total range for the LOAM (°C) was generally higher in R3 (0.84 to 3.70) than in R1 (0.61 to 1.79) and R2 (0.42 to 2.03), indicating the lowest agreement among analysers in R3 for Tmin (3.70). The present study shows that in sheep, the lacrimal caruncle confers the best agreement among analysers for all estimated temperatures, and that Tmax, across different eye regions, should be regarded as the most reliable estimation.
DOI: 10.6084/m9.figshare.14820919
title: Additional file 4 of Transcriptome analysis reveals Vernalization is independent of cold acclimation in Arabidopsis

description: Additional file 4: Table S4. DEGs in ERF, LTI and SCC networks.
DOI: 10.6084/m9.figshare.14820916.v1
title: Additional file 3 of Transcriptome analysis reveals Vernalization is independent of cold acclimation in Arabidopsis

description: Additional file 3: Table S3. Information of DEGs in weighted gene co-expression network analysis.
DOI: 10.6084/m9.figshare.14820922.v1
title: Additional file 5 of Transcriptome analysis reveals Vernalization is independent of cold acclimation in Arabidopsis

description: Additional file 5: Table S5. DEGs regulated by alternative splicing mechanism and CAMTA3, MPK3, MPK6 and OST1.
DOI: 10.6084/m9.figshare.14820925
title: Additional file 6 of Transcriptome analysis reveals Vernalization is independent of cold acclimation in Arabidopsis

description: Additional file 6: Table S6. Oligous used as primers in the experiment.
DOI: 10.17632/gxd5jx63k5.1
title: Curcumin protects against aging-related stress and dysfunction through autophagy activation in rat brain

description: Curcumin (Curcuma longa) is a well-known medicinal plant that induces autophagy in various model species, helping maintain cellular homeostasis. Its role as a caloric restriction mimetic (CRM) is still being investigated. This study explores the potential of curcumin (CUR), as a CRM, to provide neuroprotection in rats with an accelerated senescence model induced by D-galactose (D-gal) via modulating autophagy. For six weeks, male rats received simultaneous supplementation of D-gal (300 mg/kg b.w., subcutaneously) and CUR (200 mg/kg b.w., oral). The oxidative stress indices, antioxidants, and electron transport chain complexes in brain tissues were measured using standard methods. Reverse transcriptase-polymerase chain reaction (RT-PCR) gene expression analysis was used to evaluate the expression of autophagy, neuroprotection, and aging marker genes. According to our results, curcumin significantly (p≤0.05) enhanced the level of antioxidants and considerably lowered the level of oxidative stress markers. Supplementing with CUR also increased the activity of electron transport chain complexes in the mitochondria of aged brain tissue, demonstrating the antioxidant potential of CUR at the mitochondrial level. CUR was found to upregulate the expression of the aging marker gene (SIRT-1) and the genes associated with autophagy (Beclin-1 and ULK-1), as well as neuroprotection (NSE) in the brain. Our findings demonstrate that CUR suppresses oxidative damage brought on by aging by modulating autophagy. These findings imply that curcumin might be beneficial for neuroprotection in aging and age-related disorders.
DOI: 10.6084/m9.figshare.20063853.v1
title: Additional file 2 of Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat

description: Additional file 2: Table S1. Analysis of variance and Pearson correlation for phenotypes.
DOI: 10.34740/kaggle/dsv/7611486
title: ⏳ endoflife.date database (duckdb)
DOI: 10.5281/zenodo.10527411
title: BIObec.WP2. T2.1. BBEC Framework Design.

description: This dataset contains Deliverable 2.1 from the BIObec project and includes



Desk Research to create an INVENTORY OF BEST PRACTICE to inform and enhance BBEC design

Creation of a comprehensive CENTRE READINESS LEVEL FRAMEWORK SURVEY to inform the BBEC co-creation workshops and future centre design


All 19 BIObec consortium partners submitted at least one example of best practice in education and/or industry and circa 30 best practice examples have been collected showcasing examples from a European and international perspective. Based on the inputs from the Inventory of Best Practice a survey has been created to profile the capabilities of the six BBEC locations and highlight opportunities for collaboration that will support BBEC design. This survey comprises 22 questions and was administered to all 19 partners with an accompanying guidance document - these activities provide the basis for T2.2 and T2.3 of WP2.
DOI: 10.5281/zenodo.10527412
title: BIObec.WP2. T2.1. BBEC Framework Design.

description: This dataset contains Deliverable 2.1 from the BIObec project and includes



Desk Research to create an INVENTORY OF BEST PRACTICE to inform and enhance BBEC design

Creation of a comprehensive CENTRE READINESS LEVEL FRAMEWORK SURVEY to inform the BBEC co-creation workshops and future centre design


All 19 BIObec consortium partners submitted at least one example of best practice in education and/or industry and circa 30 best practice examples have been collected showcasing examples from a European and international perspective. Based on the inputs from the Inventory of Best Practice a survey has been created to profile the capabilities of the six BBEC locations and highlight opportunities for collaboration that will support BBEC design. This survey comprises 22 questions and was administered to all 19 partners with an accompanying guidance document - these activities provide the basis for T2.2 and T2.3 of WP2.
DOI: 10.6084/m9.figshare.20063859.v1
title: Additional file 4 of Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat

description: Additional file 4: Table S3. WGCNA result for 67,016 genes.
DOI: 10.6084/m9.figshare.20063862
title: Additional file 5 of Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat

description: Additional file 5: Table S4. Predicted candidate genes and their information for each trait.
DOI: 10.6084/m9.figshare.20063853
title: Additional file 2 of Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat

description: Additional file 2: Table S1. Analysis of variance and Pearson correlation for phenotypes.
DOI: 10.6084/m9.figshare.20063856
title: Additional file 3 of Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat

description: Additional file 3: Table S2. QTLs for plant height and yield traits.
DOI: 10.6084/m9.figshare.14821121.v1
title: Additional file 2 of Genome-wide identification and evolutionary analysis of RLKs involved in the response to aluminium stress in peanut

description: Additional file 2: Complete list and classification of Al response AhRLKs in peanut.
DOI: 10.6084/m9.figshare.20063868
title: Additional file 7 of Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat

description: Additional file 7: Table S6. The primer sequence for qRT-PCR and gene marker in this study.
DOI: 10.6084/m9.figshare.20063880
title: Additional file 3 of Mettl14-mediated m6A modification is essential for visual function and retinal photoreceptor survival

description: Additional file 3. Enriched GO terms in terms of cellular component.
DOI: 10.6084/m9.figshare.20063856.v1
title: Additional file 3 of Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat

description: Additional file 3: Table S2. QTLs for plant height and yield traits.
DOI: 10.6084/m9.figshare.20063865
title: Additional file 6 of Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat

description: Additional file 6: Table S5. Genotyping of each gene marker in wheat varieties. The visualization results are shown in Fig. 6 and Figure S7.
DOI: 10.6084/m9.figshare.20063859
title: Additional file 4 of Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat

description: Additional file 4: Table S3. WGCNA result for 67,016 genes.
DOI: 10.6084/m9.figshare.20063865.v1
title: Additional file 6 of Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat

description: Additional file 6: Table S5. Genotyping of each gene marker in wheat varieties. The visualization results are shown in Fig. 6 and Figure S7.
DOI: 10.6084/m9.figshare.14821130.v1
title: Additional file 5 of Genome-wide identification and evolutionary analysis of RLKs involved in the response to aluminium stress in peanut

description: Additional file 5: Tandem duplication clusters of AhRLKs.
DOI: 10.6084/m9.figshare.14821145.v1
title: Additional file 9 of Genome-wide identification and evolutionary analysis of RLKs involved in the response to aluminium stress in peanut

description: Additional file 9: Expression Profiles of Al-responsive AhRLKs under Al stress.
DOI: 10.6084/m9.figshare.14821136.v1
title: Additional file 6 of Genome-wide identification and evolutionary analysis of RLKs involved in the response to aluminium stress in peanut

description: Additional file 6: Devergence time among AhRLKs tandem duplication pairs and segmental duplication pairs.
DOI: 10.34943/0c98a4f2-2b42-42dd-802c-2b32bc52a5cd
title: Bonilla Oceanographic Radar System Deployed 2019-10-04

description: The CODAR SeaSonde 5MHz BONI was deployed on 2019-10-04 at Bonilla. The Bonilla Island CODAR station contributes to an array of CODARs to monitor surface currents in the Hecate Strait. This device is a Oceanographic Radar System. Oceanographic radars measure the ocean surface currents and waves in near real-time, by timing reflected radio waves, and contribute to an accurate prediction of severe weather conditions. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 2.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.34943/f372a98e-3679-424b-b4bc-69784a1cc0dd
title: Jordan River Oceanographic Radar System Deployed 2019-09-24

description: The CODAR SeaSonde 16MHz (SN 2016479) VJOR was deployed on 2019-09-24 at Jordan River. The Jordan River CODAR station contributes to an array of CODARs to monitor surface currents in the Juan de Fuca Strait. This device is a Oceanographic Radar System. Oceanographic radars measure the ocean surface currents and waves in near real-time, by timing reflected radio waves, and contribute to an accurate prediction of severe weather conditions. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 2.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.34943/656e24f8-704b-46e9-9ae7-dfd91a5dd7b3
title: Race Rocks Oceanographic Radar System Deployed 2019-05-15

description: The CODAR SeaSonde 16MHz (SN 2016480) VROC was deployed on 2019-05-15 at Race Rocks. The Race Rocks CODAR station contributes to an array of CODARs to monitor surface currents in the Juan de Fuca Strait. This device is a Oceanographic Radar System. Oceanographic radars measure the ocean surface currents and waves in near real-time, by timing reflected radio waves, and contribute to an accurate prediction of severe weather conditions. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 2.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.34943/6d395125-37b7-4c74-8b24-424f908ca3db
title: Point Atkinson Oceanographic Radar System Deployed 2016-06-01

description: The CODAR SeaSonde 25MHz VATK was deployed on 2016-06-01 at Point Atkinson. The Point Atkinson CODAR station contributes to an array of CODARs to monitor surface currents in Strait of Georgia. This device is a Oceanographic Radar System. Oceanographic radars measure the ocean surface currents and waves in near real-time, by timing reflected radio waves, and contribute to an accurate prediction of severe weather conditions. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 2.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.34943/8f2320cb-5253-4548-b61b-e44b3a2e7eed
title: Westshore Coal Terminal Oceanographic Radar System Deployed 2019-07-30

description: The CODAR SeaSonde 25MHz VCOL was deployed on 2019-07-30 at Westshore Coal Terminal. The Westshore Coal Terminal CODAR station contributes to an array of CODARs to monitor surface currents in Strait of Georgia. This device is a Oceanographic Radar System. Oceanographic radars measure the ocean surface currents and waves in near real-time, by timing reflected radio waves, and contribute to an accurate prediction of severe weather conditions. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 2.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.34943/a0bce4e9-4061-4a01-b2ec-294a627b1768
title: Digby Island Oceanographic Radar System Deployed 2017-04-06

description: The CODAR SeaSonde 25MHz VDIG was deployed on 2017-04-06 at Digby Island. The Digby Island CODAR station contributes to an array of CODARs to monitor surface currents in Chatham Sound. This device is a Oceanographic Radar System. Oceanographic radars measure the ocean surface currents and waves in near real-time, by timing reflected radio waves, and contribute to an accurate prediction of severe weather conditions. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 2.0 digital infrastructure, with quality assurance and derived data products following established practices.