cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14932954
title: The prognosis of glioblastoma: a large, multifactorial study

description: Glioblastoma is the most common and fatal primary brain tumor in adults. Even with maximal resection and a series of postoperative adjuvant treatments, the median overall survival (OS) of glioblastoma patients remains approximately 15 months. The Huashan Hospital glioma bank contains more than 2000 glioma tissue samples with long-term follow-up data; almost half of these samples are from glioblastoma patients. Several large glioma databases with long-term follow-up data have reported outcomes of glioblastoma patients from countries other than China. We investigated the prognosis of glioblastoma patients in China and compared the survival outcomes among patients from different databases. The data for 967 glioblastoma patients who underwent surgery at Huashan Hospital and had long-term follow-up records were obtained from our glioma registry (diagnosed from 29 March 2010, through 7 June 2017). Patients were eligible for inclusion if they underwent surgical resection for newly diagnosed glioblastomas and had available data of survival and personal information. Data of 778 glioblastoma patients were collected from three separate online databases (448 patients from The Cancer Genome Atlas (TCGA, https://cancergenome.nih.gov), 191 from REpository for Molecular BRAin Neoplasia DaTa (REMBRANDT) database (GSE108476) and 132 from data set GSE16011(Hereafter called as the French database). We compared the prognosis of glioblastoma patients from records among the different databases and the changes in survival outcomes of glioblastoma patients from Huashan Hospital over an 8-year period. The median OS of glioblastoma patients was 16.3 (95% CI: 15.4–17.2) months for Huashan Hospital, 13.8 (95% CI: 12.9–14.9) months for TCGA, 19.3 (95% CI: 17.0–20.0) months for the REMBRANDT database, and 9.1 months for the French database. The median OS of glioblastoma patients from Huashan Hospital improved from 15.6 (2010–2013, 95% CI: 14.4–16.6) months to 18.2 (2014–2017, 95% CI: 15.8–20.6) months over the study period (2010–2017). In addition, the prognosis of glioblastoma patients with total resection was significantly better than that of glioblastoma patients with sub-total resection or biopsy. Our study confirms that treatment centered around maximal surgical resection brought survival benefits to glioblastoma patients after adjusting to validated prognostic factors. In addition, an improvement in prognosis was observed among glioblastoma patients from Huashan Hospital over the course of our study. We attributed it to the adoption of a new standard of neurosurgical treatment on the basis of neurosurgical multimodal technologies. Even though the prognosis of glioblastoma patients remains poor, gradual progress is being made.
DOI: 10.6084/m9.figshare.11787252
title: The annotation files for the draft genome of the Tibetan black bear (Ursus thibetanus thibetanus)

description: <b>Tibetan black bear genome annotation file (gff3 format)</b>Tibetanblackbear.gff.gz<br><b>The predicted protein sequences of the annotations for the genome of Tibetan black bear (fasta format)</b>Tibetanblackbear.pep.fasta.gz<br><b>The predicted protein-codng sequences of the annotations for the genome of Tibetan black bear (fasta format)</b>Tibetanblackbear.cds.fasta.gz
DOI: 10.6084/m9.figshare.19112647.v1
title: Additional file 2 of The role of diet in renal cell carcinoma incidence: an umbrella review of meta-analyses of observational studies

description: Additional file 2: Figure S1. Contour-enhanced funnel plots associating dietary patterns or diet quality indices with RCC incidence: A) healthy dietary pattern, B) unhealthy/Western pattern, C) drinking pattern, D) dietary inflammatory index, E) glycemic index, and F) glycemic load. Figure S2. Contour-enhanced funnel plots associating foods with RCC incidence: A) fish, B) vegetables, C) fruits, D) red meat, E) processed meat, and F) cruciferous vegetables. Figure S3. Contour-enhanced funnel plots associating foods with RCC incidence: A) poultry, B) all meat, C) fruit and non-starchy vegetables, D) non-starchy vegetables, E) tomatoes, and F) citrus fruit. Figure S4. Contour-enhanced funnel plots associating beverages with RCC incidence: A) sweet beverages (including artificially sweetened beverages and sugar-sweetened beverages), B) tea, C) coffee, and D) sweetened carbonated beverage. Figure S5. Contour-enhanced funnel plots associating alcoholic beverages with RCC incidence: A) beer, B) wine, C) spirits, D) alcohol (light), E) alcohol (moderate), F) alcohol (heavy), and G) alcohol (any). Figure S6. Contour-enhanced funnel plots associating macronutrients with RCC incidence: A) fruit fiber, B) vegetable fiber, C) cereal fiber, D) dietary fiber, E) Total fat, and F) saturated fat. Figure S7. Contour-enhanced funnel plots associating macronutrients with RCC incidence: A) monounsaturated fat, B) polyunsaturated fat, C) total protein, D) animal protein, and E) plant protein. Figure S8. Contour-enhanced funnel plots associating micronutrients with RCC incidence: A) riboflavin, B) vitamin B6, C) folate, D) vitamin B12, E) methionine, and F) choline. Figure S9. Contour-enhanced funnel plots associating micronutrients with RCC incidence: A) betaine, B) vitamin C, C) vitamin D, D) dietary nitrate, E) dietary nitrite, and F) vitamin E. Figure S10. Contour-enhanced funnel plots associating micronutrients with RCC incidence: A) alpha-carotene, B) beta-cryptoxanthin, C) lutein and zeaxanthin, D) dietary lycopene, E) total calcium (food and supplements), F) dietary calcium, and G) Calcium (supplements). Figure S11. After using the trim-and-fill method, contour-enhanced funnel plots for the association between A) vegetables, B) red meat, C) vegetable fiber, D) fruit and non-starchy vegetables, and E) lutein and zeaxanthin and the incidence of renal cell carcinoma were generated.
DOI: 10.6084/m9.figshare.19127342
title: IgAN374.xls

description: In this study, baseline
demographics , clinical and pathology data were collected for all patients
during renal biopsies, including age, gender, mean arterial pressure (MAP)
defined as diastolic pressure plus one-third of the pulse pressure, 24-hour
protein excretion and estimated glomerular filtration rate (eGFR) calculated by
the Chronic Kidney Disease Epidemiology (CKD-EPI) Collaboration equation.
Regardless of the duration and dose, the type of immunosuppression or renin-angiotensin-aldosterone system (RAAS) blockades
therapy that the patient received was recorded. Immunosuppression
was defined as treatment with corticosteroids and/or corticosteroid-sparing
agents (including cyclophosphamide, azathioprine, mycophenolate, cyclosporine
or tacrolimus). RAAS blockades included any exposure to angiotensin-converting
enzyme inhibitor and/or angiotensin receptor blocker after biopsy. The
updated Oxford Classification(MEST-C) for IgAN was applied in this study[5]. Renal biopsy samples from all patients were examined
by pathologist and nephrologist. The crescent is subdivided according to the
volume, composition and proportion of the crescent. The volume of the crescent
body is defined as the large crescent body accounting for 50% or more of the
renal sac volume and the small crescent body accounting for 50% or less of the
renal sac volume. The components of crescent body can be divided into cellular
crescent, cellular fibrous crescent and fibrous crescent. The cellular crescent
consists of &gt; 75% cells and &lt; 25% fibrous matrix. The fibrous
cellular crescent consists of 25%-75% of the cells and the remaining
fibrous matrix. Extracapillary fibrosis of fibrous crescents consists of &gt;
75% matrix and &lt; 25% cells. The crescent ratio is defined as the proportion
of the number of glomeruli with crescents in the total number of glomeruli, and
the cell / fibrous cell / fibrous crescent is evaluated according to the
relative ratio. ESRD was defined as eGFR&lt;15 mL/min/1.73 m2 for more than 3
months or initiation of dialysis or transplantation. In this study, we defined clinical outcome: the combined event (Doubling of
serum creatinine, 50% reduction in eGFR, 15% reduction in eGFR within 1 year,
30% reduction in eGFR within 2 year, 
ESRD or death ) after diagnostic kidney biopsy.<br>
<br>
DOI: 10.6084/m9.figshare.19112742
title: Additional file 12 of Multi-omics analyses revealed key factors involved in fluorescent carbon-dots-regulated secondary metabolism in Tetrastigma hemsleyanum

description: Additional file 12: Table S2. All differentially accumulated metabolites identified between CK vs TH.
DOI: 10.6084/m9.figshare.19112736
title: Additional file 10 of Multi-omics analyses revealed key factors involved in fluorescent carbon-dots-regulated secondary metabolism in Tetrastigma hemsleyanum

description: Additional file 10: Fig. S10. Soft threshold figures for the weighted gene co-regulatory network analysis.
DOI: 10.6084/m9.figshare.19112736.v1
title: Additional file 10 of Multi-omics analyses revealed key factors involved in fluorescent carbon-dots-regulated secondary metabolism in Tetrastigma hemsleyanum

description: Additional file 10: Fig. S10. Soft threshold figures for the weighted gene co-regulatory network analysis.
DOI: 10.6084/m9.figshare.19112739.v1
title: Additional file 11 of Multi-omics analyses revealed key factors involved in fluorescent carbon-dots-regulated secondary metabolism in Tetrastigma hemsleyanum

description: Additional file 11: Table S1. All secondary metabolites identified in T. hemsleyanum.
DOI: 10.6084/m9.figshare.19112745
title: Additional file 13 of Multi-omics analyses revealed key factors involved in fluorescent carbon-dots-regulated secondary metabolism in Tetrastigma hemsleyanum

description: Additional file 13: Table S3. All differentially expressed genes identified between CK vs TH.
DOI: 10.6084/m9.figshare.19112745.v1
title: Additional file 13 of Multi-omics analyses revealed key factors involved in fluorescent carbon-dots-regulated secondary metabolism in Tetrastigma hemsleyanum

description: Additional file 13: Table S3. All differentially expressed genes identified between CK vs TH.
DOI: 10.6084/m9.figshare.19112739
title: Additional file 11 of Multi-omics analyses revealed key factors involved in fluorescent carbon-dots-regulated secondary metabolism in Tetrastigma hemsleyanum

description: Additional file 11: Table S1. All secondary metabolites identified in T. hemsleyanum.
DOI: 10.6084/m9.figshare.19112748.v1
title: Additional file 14 of Multi-omics analyses revealed key factors involved in fluorescent carbon-dots-regulated secondary metabolism in Tetrastigma hemsleyanum

description: Additional file 14: Table S4. Correspondence relation table between gene modules and gene members.
DOI: 10.6084/m9.figshare.22273129
title: 3D representative model

description: The 3D reconstruction model of the rock XCT data
DOI: 10.6084/m9.figshare.14394161
title: Metadata record for the manuscript: RIPK1 is a negative mediator in Aquaporin 1-driven triple-negative breast carcinoma progression and metastasis

description: <b>Summary</b>

This
metadata record provides details of the data supporting the claims of the
related manuscript: “RIPK1 is a negative mediator in
Aquaporin 1-driven triple-negative breast carcinoma progression and metastasis”.

The
related study reports the aberrant expression of Aquaporin 1 (AQP1) and
receptor-interacting protein kinase 1 (RIPK1) in triple-negative breast
carcinoma (TNBC) that are associated with different prognoses, then validates
the interaction of AQP1 and RIPK1 and the suppressive effect of RIPK1 on
AQP1-driven TNBC progression and metastasis, and finally identifies the
underlying mechanism of TNBC cell death resistance that AQP1 binds to the D324
site of RIPK1 and facilitates RIPK1 cleavage by promoting the caspase-8/RIPK1
negative feedback loop.

 

Type of data:
mass spectrometry 

Subject of
data: <i>Homo sapiens</i>; Eukaryotic cell
lines; <i>Mus musculus</i>

Population
characteristics: human patients were female, diagnosed with TNBC and average
age 45.4 years; seven-week-old female BALB/c mice

Recruitment:
consecutively recruited between May 1, 2012 and April 30, 2013 at Tianjin
Medical University Cancer Institute and Hospital and the First Affiliated
Hospital of Xiamen University

 

<b>Data
access</b>

The public
data resources used in the related study are openly available from the
following sources: the Oncomine database (http://www.oncomine.org),
the Cancer Genome Atlas (TCGA, https://identifiers.org/cbioportal:brca_tcga),
Genotype-Tissue Expression (GTEx, https://gtexportal.org),
and the Gene Expression Omnibus data repository (GEO, https://identifiers.org/geo:GSE1456,
https://identifiers.org/geo:GSE6532,
and https://identifiers.org/geo:GSE7390).

The majority
of the GraphPad Prism files underlying the figures and supplementary figures of
the related article are openly available as part of this data record. However,
several are saved in institutional storage and are not publicly available to
protect the patient privacy. These may be available from the corresponding author
upon reasonable request.

All the
uncropped western blots generated during this study are available in
Supplementary Figure 6.<br>

 

<b>Corresponding author(s) for this study</b>

Fanxin
Zeng, Ph.D., Department of Clinical Research Center, Dazhou Central Hospital, No.56
Nanyuemiao St, Tongchuan District, Dazhou, 635000, China, Phone: +86-
818-2381051, E-mail: zengfx@pku.edu.cn.

Huiwen
Ren, Ph.D., Department of Pharmacology, School of Basic Medical Sciences, Tianjin
Medical University, No.22 Qixiangtai Rd. Heping District, Tianjin, 300070,
China, Phone: +86-22-83336668, E-mail: renhuiwen@tmu.edu.cn.

<br>
<b>Study approval </b>

The
study conformed to the Ethical Guidelines of the Helsinki Declaration, and was
approved by the Ethics Committee of Tianjin Medical University Cancer Institute
and Hospital, Tianjin, and the Ethics Committee of the First Affiliated
Hospital of Xiamen University, Xiamen, People’s Republic of China.
DOI: 10.6084/m9.figshare.22782609.v1
title: Sputum pathogen spectrum and clinical outcomes of upper respiratory tract infection in bronchiectasis exacerbation: a prospective cohort study

description: Upper respiratory tract infection (URTI) is common in humans. We sought to profile sputum pathogen spectrum and impact of URTI on acute exacerbation of bronchiectasis (AE). Between March 2017 and December 2021, we prospectively collected sputum from adults with bronchiectasis. We stratified AEs into events related (URTI-AE) and unrelated to URTI (non-URTI-AE). We captured URTI without onset of AE (URTI-non-AE). We did bacterial culture and viral detection with polymerase chain reaction, and explored the pathogen spectrum and clinical impacts of URTI-AE via longitudinal follow-up. Finally, we collected 479 non-AE samples (113 collected at URTI-non-AE and 225 collected at clinically stable) and 170 AE samples (89 collected at URTI-AE and 81 collect at non-URTI-AE). The viral detection rate was significantly higher in URTI-AE (46.1%) than in non-URTI-AE (4.9%) and URTI-non-AE (11.5%) (both <i>P </i>&lt; 0.01). Rhinovirus [odds ratio (OR): 5.00, 95% confidence interval (95%CI): 1.06–23.56, <i>P </i>= 0.03] detection was independently associated with URTI-AE compared with non-URTI-AE. URTI-AE tended to yield higher viral load and detection rate of rhinovirus, metapneumovirus and bacterial shifting compared with URTI-non-AE. URTI-AE was associated with higher initial viral loads (esp. rhinovirus, metapneumovirus), greater symptom burden (higher scores of three validated questionnaires) and prolonged recovery compared to those without. Having experienced URTI-AE predicted a greater risk of future URTI-AE (OR: 10.90, 95%CI: 3.60–33.05). In summary, URTI is associated with a distinct pathogen spectrum and aggravates bronchiectasis exacerbation, providing the scientific rationale for the prevention of URTI to hinder bronchiectasis progression.
DOI: 10.6084/m9.figshare.22620961
title: Additional file 15 of Residual periodontal ligament in the extraction socket promotes the dentin regeneration potential of DPSCs in the rabbit jaw

description: Additional file 15: KEGG enrichment analysis of differentially expressed mRNAs in DPSCs regulated by PDLSCs.
DOI: 10.6084/m9.figshare.7068857
title: M. oryzae transcriptomic data matrix covering a range of experiments

description: Normalized (same total expression) <i>M. oryzae </i>expression (Log2
values) from a range of experiments with the fungus infecting a plant. Column labels
are experiment codes from the database found at https://www.ncbi.nlm.nih.gov/geo
DOI: 10.6084/m9.figshare.19112748
title: Additional file 14 of Multi-omics analyses revealed key factors involved in fluorescent carbon-dots-regulated secondary metabolism in Tetrastigma hemsleyanum

description: Additional file 14: Table S4. Correspondence relation table between gene modules and gene members.
DOI: 10.6084/m9.figshare.7068860
title: F. graminearum transcriptomic data matrix covering a range of in planta experiments

description: Normalized (Same total expression) <i>F graminearum</i> expression (Log2 values) from a range of experiments with
the fungus infecting a plant. Column labels are experiment codes from the database http://www.plexdb.org/modules/PD_general/downloadphp?species=Fusarium
DOI: 10.6084/m9.figshare.14394161.v1
title: Metadata record for the manuscript: RIPK1 is a negative mediator in Aquaporin 1-driven triple-negative breast carcinoma progression and metastasis

description: <b>Summary</b>

This
metadata record provides details of the data supporting the claims of the
related manuscript: “RIPK1 is a negative mediator in
Aquaporin 1-driven triple-negative breast carcinoma progression and metastasis”.

The
related study reports the aberrant expression of Aquaporin 1 (AQP1) and
receptor-interacting protein kinase 1 (RIPK1) in triple-negative breast
carcinoma (TNBC) that are associated with different prognoses, then validates
the interaction of AQP1 and RIPK1 and the suppressive effect of RIPK1 on
AQP1-driven TNBC progression and metastasis, and finally identifies the
underlying mechanism of TNBC cell death resistance that AQP1 binds to the D324
site of RIPK1 and facilitates RIPK1 cleavage by promoting the caspase-8/RIPK1
negative feedback loop.

 

Type of data:
mass spectrometry 

Subject of
data: <i>Homo sapiens</i>; Eukaryotic cell
lines; <i>Mus musculus</i>

Population
characteristics: human patients were female, diagnosed with TNBC and average
age 45.4 years; seven-week-old female BALB/c mice

Recruitment:
consecutively recruited between May 1, 2012 and April 30, 2013 at Tianjin
Medical University Cancer Institute and Hospital and the First Affiliated
Hospital of Xiamen University

 

<b>Data
access</b>

The public
data resources used in the related study are openly available from the
following sources: the Oncomine database (http://www.oncomine.org),
the Cancer Genome Atlas (TCGA, https://identifiers.org/cbioportal:brca_tcga),
Genotype-Tissue Expression (GTEx, https://gtexportal.org),
and the Gene Expression Omnibus data repository (GEO, https://identifiers.org/geo:GSE1456,
https://identifiers.org/geo:GSE6532,
and https://identifiers.org/geo:GSE7390).

The majority
of the GraphPad Prism files underlying the figures and supplementary figures of
the related article are openly available as part of this data record. However,
several are saved in institutional storage and are not publicly available to
protect the patient privacy. These may be available from the corresponding author
upon reasonable request.

All the
uncropped western blots generated during this study are available in
Supplementary Figure 6.<br>

 

<b>Corresponding author(s) for this study</b>

Fanxin
Zeng, Ph.D., Department of Clinical Research Center, Dazhou Central Hospital, No.56
Nanyuemiao St, Tongchuan District, Dazhou, 635000, China, Phone: +86-
818-2381051, E-mail: zengfx@pku.edu.cn.

Huiwen
Ren, Ph.D., Department of Pharmacology, School of Basic Medical Sciences, Tianjin
Medical University, No.22 Qixiangtai Rd. Heping District, Tianjin, 300070,
China, Phone: +86-22-83336668, E-mail: renhuiwen@tmu.edu.cn.

<br>
<b>Study approval </b>

The
study conformed to the Ethical Guidelines of the Helsinki Declaration, and was
approved by the Ethics Committee of Tianjin Medical University Cancer Institute
and Hospital, Tianjin, and the Ethics Committee of the First Affiliated
Hospital of Xiamen University, Xiamen, People’s Republic of China.
DOI: 10.6084/m9.figshare.19112628.v1
title: Additional file 2 of YBX1 mediates alternative splicing and maternal mRNA decay during pre-implantation development

description: Additional files 2: Table S1. Differentially expressed genes at the 8-cell stage YBX1 knockdown embryos.
DOI: 10.6084/m9.figshare.19112631.v1
title: Additional file 3 of YBX1 mediates alternative splicing and maternal mRNA decay during pre-implantation development

description: Additional files 3: Table S2. Differential alternative splicing events between the 8-cell stage YBX1 knockdown embryos and the controls.
DOI: 10.6084/m9.figshare.22620961.v1
title: Additional file 15 of Residual periodontal ligament in the extraction socket promotes the dentin regeneration potential of DPSCs in the rabbit jaw

description: Additional file 15: KEGG enrichment analysis of differentially expressed mRNAs in DPSCs regulated by PDLSCs.
DOI: 10.6084/m9.figshare.6530015
title: Additional file 2: of Genome-wide expression profiling of leaves and roots of watermelon in response to low nitrogen

description: The expression of chlorophyll, cytochrome 450, photosystem I, II, and phytochrome-related genes in watermelon leaves exposed to different levels of nitrogen supply (0.2Â mM, 9Â mM) (XLSX 27Â kb)
DOI: 10.6084/m9.figshare.6530021.v1
title: Additional file 3: of Genome-wide expression profiling of leaves and roots of watermelon in response to low nitrogen

description: Transcription factors (TFs) found to be affected in the leaf and root tissues of watermelon exposed to different levels of nitrogen (0.2Â mM, 9Â mM) (XLSX 76Â kb)
DOI: 10.6084/m9.figshare.13360511
title: IFAA: Robust Association Identification and Inference for Absolute Abundance in Microbiome Analyses

description: The target of inference in microbiome analyses is usually relative abundance (RA) because RA in a sample (e.g., stool) can be considered as an approximation of RA in an entire ecosystem (e.g., gut). However, inference on RA suffers from the fact that RA are calculated by dividing absolute abundances (AAs) over the common denominator (CD), the summation of all AA (i.e., library size). Because of that, perturbation in one taxon will result in a change in the CD and thus cause false changes in RA of all other taxa, and those false changes could lead to false positive/negative findings. We propose a novel analysis approach (IFAA) to make robust inference on AA of an ecosystem that can circumvent the issues induced by the CD problem and compositional structure of RA. IFAA can also address the issues of overdispersion and handle zero-inflated data structures. IFAA identifies microbial taxa associated with the covariates in Phase 1 and estimates the association parameters by employing an independent reference taxon in Phase 2. Two real data applications are presented and extensive simulations show that IFAA outperforms other established existing approaches by a big margin in the presence of unbalanced library size. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.6530024.v1
title: Additional file 4: of Genome-wide expression profiling of leaves and roots of watermelon in response to low nitrogen

description: The expression pattern of different genes in the leaf tissues of watermelon exposed to different levels of nitrogen (0.2Â mM, 9Â mM) (XLSX 1109Â kb)
DOI: 10.6084/m9.figshare.6530024
title: Additional file 4: of Genome-wide expression profiling of leaves and roots of watermelon in response to low nitrogen

description: The expression pattern of different genes in the leaf tissues of watermelon exposed to different levels of nitrogen (0.2Â mM, 9Â mM) (XLSX 1109Â kb)