cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7808441.v1
title: Prediction of lymph node metastasis in oral squamous cell carcinoma based on protein profile

description: <b>Objective</b>: Lymph node metastasis leads to high mortality rates of oral squamous cell carcinoma (OSCC). However, it is still controversial to define clinically negative neck (cN0) and positive neck (cN1-3). <b>Methods</b>: We retrieved candidate biomarkers identified by proteomic analysis in OSCC from published works of literature. In training stage, immunohistochemistry (IHC) analysis was used to determine the expression of proteins and logistic regression models with stepwise variable selection were used to identify potential factors that might affect lymph node metastasis and life status. Furthermore, the prediction model was validated in validating stage. <b>Results</b>: We screened eight highly expressed proteins related to lymph node metastasis in OSCC and found that the expression levels of SOD2, BST2, CAD, ITGB6, and PRDX4 were significantly elevated in patients with lymph node metastasis compared to the patients without lymph node metastasis. Furthermore, in training and validating stages, the prediction model base on the combination of CAD, SOD2 expression levels, and histopathologic grade was developed and validated in patients with OSCC. <b>Conclusions</b>: Our findings showed that the developed model well predicts the lymph node metastasis and life status in patients with OSCC, independent of TNM stage.
DOI: 10.6084/m9.figshare.9905666
title: CDS of GuUGT from GuUGT, a glycosyltransferase from <i>Glycyrrhiza uralensis</i>, exhibits glycyrrhetinic acid 3- and 30-O-glycosylation.

description: nucleotide sequence of GuUGT
DOI: 10.6084/m9.figshare.9905666.v1
title: CDS of GuUGT from GuUGT, a glycosyltransferase from <i>Glycyrrhiza uralensis</i>, exhibits glycyrrhetinic acid 3- and 30-O-glycosylation

description: nucleotide sequence of GuUGT
DOI: 10.6084/m9.figshare.9905666.v2
title: CDS of GuUGT from GuUGT, a glycosyltransferase from <i>Glycyrrhiza uralensis</i>, exhibits glycyrrhetinic acid 3- and 30-O-glycosylation.

description: nucleotide sequence of GuUGT
DOI: 10.6084/m9.figshare.7284251
title: Lake Catchment Set

description: A freely available data set of inland lake catchments including lakes, location, shape, area, perimeter, etc. over the Qiangtang Plateau which is a main part of the Tibetan Plateau. The data set is derived from Landset8 images, Google Earth and Digital Elevation Model (DEM). It will provide important basic information for researchers to study the changes of meteorology, hydrology and environment and its mechanism in Qinghai-Tibet Plateau.
DOI: 10.6084/m9.figshare.20391030.v1
title: Additional file 1 of Leukocyte inflammatory phenotype and function in migraine patients compared with matched non-migraine volunteers: a pilot study

description: Additional file 1. Supplemental Table 1.1 Means, standard deviations, and medians for groups defined by control and migraine status, sub-setting by chronic vs episodic and medication overuse. Supplemental Table 1.2  Means, standard deviations, and medians for groups defined by control and migraine status, sub-setting by chronic vs episodic and medication overuse. Supplemental Table 1.3  Means, standard deviations, and medians for groups defined by control and migraine status, sub-setting by chronic vs episodic and medication overuse.
DOI: 10.48597/4azk-exau
title: Measurement of Particle_number_size_distribution at Leipzig-Mitte

description: Measurement of Particle_number_size_distribution at Leipzig-Mitte
DOI: 10.6084/m9.figshare.20391030
title: Additional file 1 of Leukocyte inflammatory phenotype and function in migraine patients compared with matched non-migraine volunteers: a pilot study

description: Additional file 1. Supplemental Table 1.1 Means, standard deviations, and medians for groups defined by control and migraine status, sub-setting by chronic vs episodic and medication overuse. Supplemental Table 1.2  Means, standard deviations, and medians for groups defined by control and migraine status, sub-setting by chronic vs episodic and medication overuse. Supplemental Table 1.3  Means, standard deviations, and medians for groups defined by control and migraine status, sub-setting by chronic vs episodic and medication overuse.
DOI: 10.6084/m9.figshare.19867232
title: Downregulation of long noncoding RNA breast cancer anti-estrogen resistance 4 inhibits cell proliferation, invasion, and migration in esophageal squamous cell carcinoma by regulating the microRNA-181c-5p/LIM and SH3 protein 1 axis

description: Recently, abnormal expression of long non-coding RNAs (lncRNAs) has been observed in esophageal squamous cell carcinoma (ESCC). In various human cancers, breast cancer anti‑estrogen resistance 4 (BCAR4) was reported to be highly expressed, while the biological roles of BCAR4 in ESCC remain unclear. In ESCC cells and tissues, BCAR4 and microRNA −181c-5p (miR-181c-5p) expression, and phosphorylated signal transducer and activator of transcription (p-STAT3) and COX2 expression were evaluated by real-time reverse transcription PCR (qRT-PCR) and Western blot analysis. Cell function was evaluated by colony formation, CCK-8 assay, transwell and flow cytometer assays. Interactions between BCAR4 and miR-181c-5p, as well as miR-181c-5p and LIM and SH3 protein 1 (LASP1) were evaluated by RIP and luciferase reporter assay. ESCC cell malignancy with inhibition of BCAR4 was confirmed by a tumor xenograft model <i>in vivo</i>. In both ESCC tissues and cell lines, BCAR4 was upregulated. Downregulation of BCAR4 effectively induced cell apoptosis and inhibited invasion and migration <i>in vitro</i>, and reduced tumorigenesis in nude mice. BCAR4 was a sponge of miR-181c-5p to upregulate LASP1. Moreover, knockdown of BCAR4 and overexpression of miR-181c-5p inhibited the activation of the STAT3/COX2 signaling, which was reversed by overexpression of LASP1. In conclusion, BCAR4 promotes ESCC tumorigenesis by targeting the miR-181c-5p/LASP1 axis, which may act as a treatment and diagnosis biomarker for ESCC.
DOI: 10.6084/m9.figshare.19867232.v1
title: Downregulation of long noncoding RNA breast cancer anti-estrogen resistance 4 inhibits cell proliferation, invasion, and migration in esophageal squamous cell carcinoma by regulating the microRNA-181c-5p/LIM and SH3 protein 1 axis

description: Recently, abnormal expression of long non-coding RNAs (lncRNAs) has been observed in esophageal squamous cell carcinoma (ESCC). In various human cancers, breast cancer anti‑estrogen resistance 4 (BCAR4) was reported to be highly expressed, while the biological roles of BCAR4 in ESCC remain unclear. In ESCC cells and tissues, BCAR4 and microRNA −181c-5p (miR-181c-5p) expression, and phosphorylated signal transducer and activator of transcription (p-STAT3) and COX2 expression were evaluated by real-time reverse transcription PCR (qRT-PCR) and Western blot analysis. Cell function was evaluated by colony formation, CCK-8 assay, transwell and flow cytometer assays. Interactions between BCAR4 and miR-181c-5p, as well as miR-181c-5p and LIM and SH3 protein 1 (LASP1) were evaluated by RIP and luciferase reporter assay. ESCC cell malignancy with inhibition of BCAR4 was confirmed by a tumor xenograft model <i>in vivo</i>. In both ESCC tissues and cell lines, BCAR4 was upregulated. Downregulation of BCAR4 effectively induced cell apoptosis and inhibited invasion and migration <i>in vitro</i>, and reduced tumorigenesis in nude mice. BCAR4 was a sponge of miR-181c-5p to upregulate LASP1. Moreover, knockdown of BCAR4 and overexpression of miR-181c-5p inhibited the activation of the STAT3/COX2 signaling, which was reversed by overexpression of LASP1. In conclusion, BCAR4 promotes ESCC tumorigenesis by targeting the miR-181c-5p/LASP1 axis, which may act as a treatment and diagnosis biomarker for ESCC.
DOI: 10.6084/m9.figshare.8857202
title: Additional file 1: of Comparative proteomic analysis of Tibetan pig spermatozoa at high and low altitudes

description: Table S1. Details of the DEPs. (XLSX 26 kb)
DOI: 10.6084/m9.figshare.8857202.v1
title: Additional file 1: of Comparative proteomic analysis of Tibetan pig spermatozoa at high and low altitudes

description: Table S1. Details of the DEPs. (XLSX 26 kb)
DOI: 10.6084/m9.figshare.8857205
title: Additional file 2: of Comparative proteomic analysis of Tibetan pig spermatozoa at high and low altitudes

description: Table S2. GO Analysis of DEPs. (XLS 140 kb)
DOI: 10.6084/m9.figshare.8857205.v1
title: Additional file 2: of Comparative proteomic analysis of Tibetan pig spermatozoa at high and low altitudes

description: Table S2. GO Analysis of DEPs. (XLS 140 kb)
DOI: 10.5281/zenodo.10722687
title: Backup Doktorarbeit Susanne Colley CVRL 2024

description: Backup Doktorarbeit Susanne Colley CVRL 2024
DOI: 10.5281/zenodo.10722688
title: Backup Doktorarbeit Susanne Colley CVRL 2024

description: Backup Doktorarbeit Susanne Colley CVRL 2024
DOI: 10.6084/m9.figshare.19342966.v1
title: Additional file 20 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 20: Supplementary Table S8. Clustering benchmarks on 24 Human Microbiome Project datasets.
DOI: 10.6084/m9.figshare.19342942.v1
title: Additional file 13 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 13: Supplementary Table S1. Information of 100 genomes collected from NCBI.
DOI: 10.6084/m9.figshare.19342951.v1
title: Additional file 16 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 16: Supplementary Table S4. Clustering benchmarks on CAMI II Mouse gut datasets.
DOI: 10.6084/m9.figshare.19342957
title: Additional file 18 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 18: Supplementary Table S6. Clustering benchmarks on two datasets from a high-CO2 cold-water geyser.
DOI: 10.6084/m9.figshare.19342945
title: Additional file 14 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 14: Supplementary Table S2. Clustering benchmarks on a simulated dataset (20,412 contigs).
DOI: 10.6084/m9.figshare.19342945.v1
title: Additional file 14 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 14: Supplementary Table S2. Clustering benchmarks on a simulated dataset (20,412 contigs).
DOI: 10.6084/m9.figshare.19342948.v1
title: Additional file 15 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 15: Supplementary Table S3. Clustering benchmarks on CAMI I Medium and High Complexity datasets.
DOI: 10.6084/m9.figshare.19342966
title: Additional file 20 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 20: Supplementary Table S8. Clustering benchmarks on 24 Human Microbiome Project datasets.
DOI: 10.6084/m9.figshare.19342954.v1
title: Additional file 17 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 17: Supplementary Table S5. Clustering benchmarks on five CAMI II Human Microbiome Project datasets.
DOI: 10.6084/m9.figshare.19342957.v1
title: Additional file 18 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 18: Supplementary Table S6. Clustering benchmarks on two datasets from a high-CO2 cold-water geyser.
DOI: 10.6084/m9.figshare.19342969
title: Additional file 21 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 21: Supplementary Table S9. Taxonomic classifications of clusters identified by MetaDecoder with contamination &lt;= 0.10 and completeness &gt;= 0.50 on 24 hmp datasets.
DOI: 10.6084/m9.figshare.19342972
title: Additional file 22 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 22: Supplementary Table S10. Clustering benchmarks on a cohort of T2D study.
DOI: 10.6084/m9.figshare.19342972.v1
title: Additional file 22 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 22: Supplementary Table S10. Clustering benchmarks on a cohort of T2D study.
DOI: 10.6084/m9.figshare.19342942
title: Additional file 13 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 13: Supplementary Table S1. Information of 100 genomes collected from NCBI.
DOI: 10.6084/m9.figshare.19342948
title: Additional file 15 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 15: Supplementary Table S3. Clustering benchmarks on CAMI I Medium and High Complexity datasets.
DOI: 10.6084/m9.figshare.19342951
title: Additional file 16 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 16: Supplementary Table S4. Clustering benchmarks on CAMI II Mouse gut datasets.
DOI: 10.6084/m9.figshare.19342975.v1
title: Additional file 23 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 23: Supplementary Table S11. Taxonomic classifications of clusters with contamination &lt;= 0.10 and completeness &gt;= 0.50.
DOI: 10.6084/m9.figshare.19342978
title: Additional file 24 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 24: Supplementary Table S12. Analysis of relative abundance in IGT, IGT and T2D samples.
DOI: 10.6084/m9.figshare.19342954
title: Additional file 17 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 17: Supplementary Table S5. Clustering benchmarks on five CAMI II Human Microbiome Project datasets.
DOI: 10.6084/m9.figshare.19342960
title: Additional file 19 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 19: Supplementary Table S7. Taxonomic classifications of clusters identified by MetaDecoder with contamination &lt;= 0.10 and completeness &gt;= 0.50 on two datasets from a high-CO2 cold-water geyser.
DOI: 10.6084/m9.figshare.19342975
title: Additional file 23 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 23: Supplementary Table S11. Taxonomic classifications of clusters with contamination &lt;= 0.10 and completeness &gt;= 0.50.
DOI: 10.6084/m9.figshare.19342978.v1
title: Additional file 24 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 24: Supplementary Table S12. Analysis of relative abundance in IGT, IGT and T2D samples.
DOI: 10.6084/m9.figshare.19342960.v1
title: Additional file 19 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 19: Supplementary Table S7. Taxonomic classifications of clusters identified by MetaDecoder with contamination &lt;= 0.10 and completeness &gt;= 0.50 on two datasets from a high-CO2 cold-water geyser.
DOI: 10.6084/m9.figshare.19342981
title: Additional file 25 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 25: Supplementary Table S13. Runtime and memory comparison on CAMI I Medium and High Complexity datasets.
DOI: 10.6084/m9.figshare.19342981.v1
title: Additional file 25 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 25: Supplementary Table S13. Runtime and memory comparison on CAMI I Medium and High Complexity datasets.
DOI: 10.6084/m9.figshare.19342969.v1
title: Additional file 21 of MetaDecoder: a novel method for clustering metagenomic contigs

description: Additional file 21: Supplementary Table S9. Taxonomic classifications of clusters identified by MetaDecoder with contamination &lt;= 0.10 and completeness &gt;= 0.50 on 24 hmp datasets.
DOI: 10.6084/m9.figshare.9905807
title: Additional file 2: of Divergent neuronal DNA methylation patterns across human cortical development reveal critical periods and a unique role of CpH methylation

description: Table S1. WGBS Phenotype, Sequencing Data. Table S2. RNA Phenotype, Sequencing Data. Table S3. Number of cytosines measured and distribution of methylation by context. Table S4. Number of Low Methylation Regions (LMRs) and Unmethylated Regions (UMRs) per sample. Table S5. Cell type-specific, developmental differentially methylated regions (cdDMRs). Table S6. mC association with cell type and age in postnatal cell type-specific samples. Table S7. Molecular function gene ontology enrichment for genes including exons whose expression is associated with cytosine methylation levels. Table S8. GWAS traits assessed using LDSC. Table S9. Stratified linkage disequilibrium score regression results. Table S10. Enrichment of DMRs and mCpH for disease-associated gene sets. Table S11. Enrichment for disease gene sets in DNAm-splicing association features. Table S12. Variable dictionary for TableÂ 1. (XLSX 437 kb)
DOI: 10.6084/m9.figshare.21351200.v1
title: Additional file 2 of Identification of a novel interaction site between the large hepatitis delta antigen and clathrin that regulates the assembly of genotype III hepatitis delta virus

description: Additional file 2. Table S1. HDAg-L C-terminal sequences retrieved from NCBI using taxid:12475 (HDV).
DOI: 10.6084/m9.figshare.9905807.v1
title: Additional file 2: of Divergent neuronal DNA methylation patterns across human cortical development reveal critical periods and a unique role of CpH methylation

description: Table S1. WGBS Phenotype, Sequencing Data. Table S2. RNA Phenotype, Sequencing Data. Table S3. Number of cytosines measured and distribution of methylation by context. Table S4. Number of Low Methylation Regions (LMRs) and Unmethylated Regions (UMRs) per sample. Table S5. Cell type-specific, developmental differentially methylated regions (cdDMRs). Table S6. mC association with cell type and age in postnatal cell type-specific samples. Table S7. Molecular function gene ontology enrichment for genes including exons whose expression is associated with cytosine methylation levels. Table S8. GWAS traits assessed using LDSC. Table S9. Stratified linkage disequilibrium score regression results. Table S10. Enrichment of DMRs and mCpH for disease-associated gene sets. Table S11. Enrichment for disease gene sets in DNAm-splicing association features. Table S12. Variable dictionary for TableÂ 1. (XLSX 437 kb)
DOI: 10.6084/m9.figshare.21351200
title: Additional file 2 of Identification of a novel interaction site between the large hepatitis delta antigen and clathrin that regulates the assembly of genotype III hepatitis delta virus

description: Additional file 2. Table S1. HDAg-L C-terminal sequences retrieved from NCBI using taxid:12475 (HDV).
DOI: 10.5281/zenodo.10722992
title: Original data for "Cathodic reactivity of intermetallic particles in AA7175 alloy buried under 6 µm thick anodized oxide layer revealed by in situ reflective microscopy"

description: This upload includes  original data and data processing scripts for the publication "Cathodic reactivity of intermetallic particles in AA7175 alloy buried under 6 µm thick anodized oxide layer revealed by in situ reflective microscopy" by Florian Raffin, Aleksei Makogon, Viacheslav Shkirskiy, Frédéric Kanoufi and Polina Volovitch.

The file "Original_data.zip" contains the original optical image of the interface in npy format, SEM images and python scripts, used to process these images

The file "Bubble_detection.pdf" provides output of the main jupyter notebook. Original jupyter notebook is available in the archive "Original_data.zip".

We recommend opening the Jupyter Lab files in a Python 3 environment. PDF files in the root directory provide outputs of all uploaded Jupyter Lab files.
DOI: 10.5281/zenodo.10722993
title: Original data for "Cathodic reactivity of intermetallic particles in AA7175 alloy buried under 6 µm thick anodized oxide layer revealed by in situ reflective microscopy"

description: This upload includes  original data and data processing scripts for the publication "Cathodic reactivity of intermetallic particles in AA7175 alloy buried under 6 µm thick anodized oxide layer revealed by in situ reflective microscopy" by Florian Raffin, Aleksei Makogon, Viacheslav Shkirskiy, Frédéric Kanoufi and Polina Volovitch.

The file "Original_data.zip" contains the original optical image of the interface in npy format, SEM images and python scripts, used to process these images

The file "Bubble_detection.pdf" provides output of the main jupyter notebook. Original jupyter notebook is available in the archive "Original_data.zip".

We recommend opening the Jupyter Lab files in a Python 3 environment. PDF files in the root directory provide outputs of all uploaded Jupyter Lab files.
DOI: 10.15468/x4jmds
title: The fauna of the aquatic invertebrates of the small stream ecosystem under conditions of continuous logging (middle taiga, Komi Republic, Russia)

description: This dataset provides current data on aquatic invertebrate’s fauna (zooplankton and zoobenthos) of the small water body (Komi Republic, Russia; middle taiga) in the zone impacted the logging zone. Data include revealed taxonomic groups of zoobenthos (27) and lower-rank taxa (species, subspecies) for some (model) groups (113): Oligochaeta, Mollusca, Cladocera, Copepoda, Coleoptera, Ephemeroptera, Plecoptera, Trichoptera, and 54 taxa (species, subspecies) of zooplankton (Rotifera, Cladocera, Copepoda). A total of 1990 occurrences are included in the resource.
DOI: 10.15472/okotgw
title: Flora y análisis de suelos de la expedición Montes de María

description: En el marco del Contrato de prestación de servicios No. 0102-2022 (N° 22-352 numeración Instituto Humboldt), entre la Fundación Tecnalia Colombia -como apoyo técnico, financiero y logístico del Ministerio de Ciencia Tecnología e Innovación (Minciencias) en la evaluación y seguimiento de proyectos y actividades de ciencia tecnología e innovación (CTeI)– y el Instituto Humboldt, que tiene por objeto desarrollar la Expedición científica sobre la biodiversidad funcional asociada a los agroecosistemas de Montes de María bajo contextos de transformación y cambio climático, en los Municipios de Ovejas, San Juan Nepomuceno (Vereda Canito), Carmen de Bolívar (Corregimiento San Isidro) y San Jacinto (Vereda Brasilar), Montes de María en Colombia.
description: Se entendieron los arreglos productivos en los agroecosistemas del bosque seco montemariano a través de muestreos biológicos de plantas e insectos y de un diálogo de saberes en torno al uso, manejo y oportunidades de la agrobiodiversidad. Donde se realizaron muestreos focales en cultivos de yuca de las asociaciones campesinas que hicieron parte del proyecto. Produciendo conocimiento sobre la biodiversidad y sus funciones en contextos de transformación del bosque seco tropical y cambio climático.
description: Respecto a la flora de la región, se realizaron 91 conglomerados, conformados por un transecto central de 10*2m, que se trazo en el cultivo de yuca, y en los 4 puntos cardinales del transecto central se realizaron transectos satélites, evaluando la diversidad de flora alrededor de los cultivos. Cómo resultados se registraron se registraron 2438 individuos distribuidos en 61 familias, 185 géneros y 271 especies entre portes arbóreos/arbustivos y herbáceos. Adicionalmente, se presentan análisis de suelos, para el transecto central, en donde están los cultivos de yuca.
DOI: 10.6084/m9.figshare.8857256
title: Additional file 7: of Genome-wide analysis of the bHLH gene family in Chinese jujube (Ziziphus jujuba Mill.) and wild jujube

description: Table S2. Summary information for 92 ZjbHLH proteins in STRING database. (XLS 95 kb)
DOI: 10.6084/m9.figshare.8857256.v1
title: Additional file 7: of Genome-wide analysis of the bHLH gene family in Chinese jujube (Ziziphus jujuba Mill.) and wild jujube

description: Table S2. Summary information for 92 ZjbHLH proteins in STRING database. (XLS 95 kb)