cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.9109322.v1
title: Additional file 2: of Dramatic response of BRAF V600E-mutant epithelioid glioblastoma to combination therapy with BRAF and MEK inhibitor: establishment and xenograft of a cell line to predict clinical efficacy

description: Figure S1. Genetic profiles of surgical tissue and the NGT41 cell line. BRAF V600E and TERT promotor (C250T) mutation was confirmed by Sanger sequencing (A), and heterozygous loss of CDKN2A/2B was identified by the multiplex ligation-dependent probe amplification method (B). Figure S2. Evaluation of BRAF V600E using ddPCR. Tumor DNA was extracted from the area of vivid tumor cells in the FFPE tissue by laser microdissection (A). Fractional abundance (FA) of mutated BRAF V600E was calculated as copies of mutated DNA/(copies of mutated DNA + wildtype DNA) (B). Scale bar A: 200 μm. Figure S3. Calculation of growth rate value in NGT41 and U87MG after combination treatment. Dose response curves on relative cell count showed marked response to BRAF and/or MEK inhibitor treatment in NGT41 (A), but minimal reduction in U87MG (B). Figure S4. BRAF and MEK inhibitor induced greater apoptosis and G0/G1 arrest in the NGT41 cell line. In BRAF V600E-mutant cell lines, each treatment significantly increased the number of apoptotic cells (n = 3, *p &lt; 0.05, **p &lt; 0.01; Two-way ANOVA) (A). G0/G1 arrest was induced by each treatment in BRAF V600E mutant-cell lines, whereas no response was observed in BRAF-wildtype cell lines (n = 3) (B). Figure S5. Effect of BRAF and MEK inhibitor in the intracranial model. pMEK and pERK were markedly suppressed in the treatment group (A). Serial body weight calculations in the treatment group were virtually the same as in the control group (B). Histological appearance of intracranial tumor in the treatment group at endpoint was similar to that of the control group (C). Scale bar C: 50 μm. Figure S6. Analysis of the TCGA database included in R2: Genomics Analysis and Visualization Platform showed that BRAF mutations were significantly correlated with CDKN2A alterations (p = 0.025) (A) and TERT promoter mutations (p = 7.03e-03) (B). (ZIP 8066 kb)
DOI: 10.6084/m9.figshare.13294982
title: Additional file 1 of Lower mutant-allele tumor heterogeneity is a biomarker in FGFR3-mutant bladder cancer for better prognosis

description: Additional file 1:Table S1 The top 50 mutated genes in BLCA.
DOI: 10.6084/m9.figshare.6487901
title: Additional file 7: of Diversification and independent domestication of Asian and European pears

description: List of genes in selective sweep regions involved in important traits during domestication from wild to cultivated pears in Asian group. (XLSX 60Â kb)
DOI: 10.6084/m9.figshare.12246425.v1
title: Additional file 1 of Casparian strip membrane domain proteins in Gossypium arboreum: genome-wide identification and negative regulation of lateral root growth

description: Additional file 1: Table S1. All primers used in this study.
DOI: 10.6084/m9.figshare.13294982.v1
title: Additional file 1 of Lower mutant-allele tumor heterogeneity is a biomarker in FGFR3-mutant bladder cancer for better prognosis

description: Additional file 1:Table S1 The top 50 mutated genes in BLCA.
DOI: 10.6084/m9.figshare.7012643.v2
title: Time Series Seasonal Adjustment Using Regularized Singular Value Decomposition

description: We propose a new seasonal adjustment method based on the Regularized Singular Value Decomposition (RSVD) of the matrix obtained by reshaping the seasonal time series data. The method is flexible enough to capture two kinds of seasonality: the fixed seasonality that does not change over time and the time-varying seasonality that varies from one season to another. RSVD represents the time-varying seasonality by a linear combination of several seasonal patterns. The right singular vectors capture multiple seasonal patterns, and the corresponding left singular vectors capture the magnitudes of those seasonal patterns and how they change over time. By assuming the time-varying seasonal patterns change smoothly over time, the RSVD uses penalized least squares with a roughness penalty to effectively extract the left singular vectors. The proposed method applies to seasonal time-series data with a stationary or nonstationary nonseasonal component. The method also has a variant that can handle the case that an abrupt change (i.e., break) may occur in the magnitudes of seasonal patterns. Our proposed method compares favorably with the state-of-art X-13ARIMA-SEATS program on both simulated and real data examples.
DOI: 10.6084/m9.figshare.7012250.v1
title: A sampling workflow based on unsupervised clusters and multi-temporal sample interpretation (UCMT) for cropland mapping

description: Accurate cropland maps are important input for various proposes, such as ecosystem service and land cover change monitoring, and the representativeness of sample training samples influence the cropland mapping accuracy significantly. This study aims to propose a new sampling workflow based on unsupervised cluster and multi-temporal interpretation (UCMT) for cropland mapping. The monthly composited image time series were unsupervised clustered using the Iterative Self organizing Data Analysis (ISODATA) and optimal temporal phases were selected using the Gini importance score calculated from Ramdom Forest (RF). Training samples for each cluster were generated and visually interpreted for the optimal temporal phases. The cropland of each temporal phase was identified using the corresponding training samples, and the cropland maps were generated by merging multi-temporal cropland results. Results in two study regions showed that training samples generated using UCMT had good potential to identify cropland with overall accuracies higher than 94% in both study regions. In addition, comparing with randomly generated training samples, UCMT samples were less affected by training sample size as Producer’s accuracies and User’s accuracies were higher than 80% when 100 training samples used.
DOI: 10.6084/m9.figshare.23265701
title: Utilizing circulating tumour DNA as a prognostic predictor of gastric cancer: a meta-analysis

description: <b>Background:</b> Circulating tumour DNA (ctDNA) has demonstrated robust diagnostic accuracy in several digestive cancers. However, the prognostic role of ctCDNA in gastric cancer (GC) is still controversial. This systematic review and meta-analysis aimed to evaluate the prognostic value of ctDNA in GC. <b>Methods:</b> PubMed, Web of Science and Cochrane databases were searched to identify studies reporting the use of ctDNA to predict GC outcome and all relevant studies published until November 2022 were enrolled for our analysis. Data were extracted by two authors independently and statistic analysis was conducted by R program with ‘meta’ and ‘metafor’ packages. <b>Results:</b> A total of 34 qualified articles with 5091 subjects were incorporated into our meta-analysis. The corresponding Hazard ratio (HR) of overall survival (OS), disease-free survival (DFS) and progression-free survival (PFS) were 2.74 (95% CI:2.24–3.35), 3.13 (95% CI:2.08–4.72) and 3.04 (95% CI:2.46–3.76), respectively, in GC patients. <b>Conclusion:</b> Blood-based ctDNA assay would be a potential novel biomarker for GC evaluation and prediction. <b>Simple Summary:</b> This is the integrated meta-analysis on the association of circulating tumour DNA (ctDNA) and prognosis of gastric cancer (GC) with an increasing number of studies exploring the prognostic value of GC in the last few years, which depicted that the detection of ctDNA could be a promising predictor in GC patients.
DOI: 10.6084/m9.figshare.12246446.v1
title: Additional file 4 of Casparian strip membrane domain proteins in Gossypium arboreum: genome-wide identification and negative regulation of lateral root growth

description: Additional file 4: Table S4. The duplication CASP gene pairs in cotton.
DOI: 10.6084/m9.figshare.12246458.v1
title: Additional file 6 of Casparian strip membrane domain proteins in Gossypium arboreum: genome-wide identification and negative regulation of lateral root growth

description: Additional file 6: Table S6. The transcript expression profiles of the GaCASP family in GA0146 and GA0149.
DOI: 10.6084/m9.figshare.22217086
title: Validation of the new EPIC DNA methylation microarray (900K EPIC v2) for high-throughput profiling of the human DNA methylome

description: DNA methylation, one of the best characterized epigenetic marks in the human genome, plays a pivotal role in gene transcription regulation and other biological processes in humans. On top of that, the DNA methylome undergoes profound changes in cancer and other disorders. However, large-scale and population-based studies are limited by high costs and the need for considerable expertise in data analysis for whole-genome bisulphite-sequencing methodologies. Following the success of the EPIC DNA methylation microarray, the newly developed Infinium HumanMethylationEPIC version 2.0 (900K EPIC v2) is now available. This new array contains more than 900,000 CpG probes covering the human genome and excluding masked probes from the previous version. The 900K EPIC v2 microarray adds more than 200,000 probes covering extra DNA cis-regulatory regions such as enhancers, super-enhancers and CTCF binding regions. Herein, we have technically and biologically validated the new methylation array to show its high reproducibility and consistency among technical replicates and with DNA extracted from FFPE tissue. In addition, we have hybridized primary normal and tumoural tissues and cancer cell lines from different sources and tested the robustness of the 900K EPIC v2 microarray when analysing the different DNA methylation profiles. The validation highlights the improvements offered by the new array and demonstrates the versatility of this updated tool for characterizing the DNA methylome in human health and disease.
DOI: 10.6084/m9.figshare.23265701.v1
title: Utilizing circulating tumour DNA as a prognostic predictor of gastric cancer: a meta-analysis

description: <b>Background:</b> Circulating tumour DNA (ctDNA) has demonstrated robust diagnostic accuracy in several digestive cancers. However, the prognostic role of ctCDNA in gastric cancer (GC) is still controversial. This systematic review and meta-analysis aimed to evaluate the prognostic value of ctDNA in GC. <b>Methods:</b> PubMed, Web of Science and Cochrane databases were searched to identify studies reporting the use of ctDNA to predict GC outcome and all relevant studies published until November 2022 were enrolled for our analysis. Data were extracted by two authors independently and statistic analysis was conducted by R program with ‘meta’ and ‘metafor’ packages. <b>Results:</b> A total of 34 qualified articles with 5091 subjects were incorporated into our meta-analysis. The corresponding Hazard ratio (HR) of overall survival (OS), disease-free survival (DFS) and progression-free survival (PFS) were 2.74 (95% CI:2.24–3.35), 3.13 (95% CI:2.08–4.72) and 3.04 (95% CI:2.46–3.76), respectively, in GC patients. <b>Conclusion:</b> Blood-based ctDNA assay would be a potential novel biomarker for GC evaluation and prediction. <b>Simple Summary:</b> This is the integrated meta-analysis on the association of circulating tumour DNA (ctDNA) and prognosis of gastric cancer (GC) with an increasing number of studies exploring the prognostic value of GC in the last few years, which depicted that the detection of ctDNA could be a promising predictor in GC patients.
DOI: 10.6084/m9.figshare.20120190.v1
title: Long non-coding RNA LOC644135 is a potential prognostic indicator in cytogenetically normal acute myeloid leukemia

description: Acute myeloid leukemia (AML) is a hematological malignancy with highly clinical heterogeneity resulting in poor outcomes. We aim to identify novel prognostic lncRNA in AML expecting to provide new clues for therapy in AML. Three cohorts were enrolled in this study. Differentially expressed lncRNAs between TCGA-AML cohort and GTEx cohort was identified by DESeq2. The relationship between expression level of LOC644135 and prognosis in AML was analyzed by multiple methods. Pan-cancer analysis indicated that LOC644135 was most highly expressed in AML across 33 types of cancer. Patients with high expression of LOC644135 had poor overall prognosis in both TCGA-AML cohort and the TARGET-AML cohort. Especially, high expression of LOC644135 indicated inferior overall survival and event-free survival in CN-AML patients in the TCGA-AML cohort. Besides, CN-AML patients had higher expression of LOC644135 than normal samples. Multivariable analysis suggested that LOC644135 was an independent prognostic factor in AML. GSEA analysis showed that LOC644135 was associated with some immune-related pathways. Besides, high expression of LOC644135 was associated with less infiltration of CD8<sup>+</sup> T cell. Our findings indicated that LOC644135 was an independent prognostic factor in AML and provided a new idea in the development of therapy in AML.
DOI: 10.6084/m9.figshare.12246452
title: Additional file 5 of Casparian strip membrane domain proteins in Gossypium arboreum: genome-wide identification and negative regulation of lateral root growth

description: Additional file 5: Table S5. Orthologous relationships between G. arboreum and other three Gossypium species.
DOI: 10.6084/m9.figshare.13294963
title: Additional file 6 of Speciation and adaptive evolution reshape antioxidant enzymatic system diversity across the phylum Nematoda

description: Additional file 6: Table S6. Expression of antioxidant enzymes in 20 nematode developmental stages and pairwise comparison of antioxidant enzymes in 11 nematodes (blue sheets) detected by GFOLD.
DOI: 10.6084/m9.figshare.12246458
title: Additional file 6 of Casparian strip membrane domain proteins in Gossypium arboreum: genome-wide identification and negative regulation of lateral root growth

description: Additional file 6: Table S6. The transcript expression profiles of the GaCASP family in GA0146 and GA0149.
DOI: 10.6084/m9.figshare.12246425
title: Additional file 1 of Casparian strip membrane domain proteins in Gossypium arboreum: genome-wide identification and negative regulation of lateral root growth

description: Additional file 1: Table S1. All primers used in this study.
DOI: 10.6084/m9.figshare.6487919
title: Additional file 8: of Diversification and independent domestication of Asian and European pears

description: List of QTL regions and association SNPs. (XLSX 48Â kb)
DOI: 10.6084/m9.figshare.23265047
title: Additional file 1 of Are patients with preoperative synovitis suitable for unicompartmental knee arthroplasty? Magnetic resonance imaging evidence from a retrospective cohort study

description: Additional file 1.
DOI: 10.6084/m9.figshare.6487952
title: Additional file 2: of Modifier locus mapping of a transgenic F2 mouse population identifies CCDC115 as a novel aggressive prostate cancer modifier gene in humans

description: Logistic regression analysis of eleven candidate genes using tumor expression data derived from TCGA, GSE21032 and GSE46691. Five of eleven candidate genes CCDC115, DNAJC10, RNF149, STYXL1, and ZNF502 that harbored significant associations with aggressive disease traits in TCGA cohort only. (XLSX 17 kb)
DOI: 10.6084/m9.figshare.22740884
title: Ridge Regression Under Dense Factor Augmented Models

description: This article establishes a comprehensive theory of the optimality, robustness, and cross-validation selection consistency for the ridge regression under factor-augmented models with possibly dense idiosyncratic information. Using spectral analysis for random matrices, we show that the ridge regression is asymptotically efficient in capturing both factor and idiosyncratic information by minimizing the limiting predictive loss among the entire class of spectral regularized estimators under large-dimensional factor models and mixed-effects hypothesis. We derive an asymptotically optimal ridge penalty in closed form and prove that a bias-corrected <i>k</i>-fold cross-validation procedure can adaptively select the best ridge penalty in large samples. We extend the theory to the autoregressive models with many exogenous variables and establish a consistent cross-validation procedure using the what-we-called double ridge regression method. Our results allow for nonparametric distributions for, possibly heavy-tailed, martingale difference errors and idiosyncratic random coefficients and adapt to the cross-sectional and temporal dependence structures of the large-dimensional predictors. We demonstrate the performance of our ridge estimators in simulated examples as well as an economic dataset. All the proofs are available in the supplementary materials, which also includes more technical discussions and remarks, extra simulation results, and useful lemmas that may be of independent interest.
DOI: 10.6084/m9.figshare.12246434
title: Additional file 2 of Casparian strip membrane domain proteins in Gossypium arboreum: genome-wide identification and negative regulation of lateral root growth

description: Additional file 2: Table S2. The information of CASPs gene family in cotton.
DOI: 10.6084/m9.figshare.12246440
title: Additional file 3 of Casparian strip membrane domain proteins in Gossypium arboreum: genome-wide identification and negative regulation of lateral root growth

description: Additional file 3: Table S3. The general information of the GaCASP family.
DOI: 10.6084/m9.figshare.22740884.v1
title: Ridge Regression Under Dense Factor Augmented Models

description: This paper establishes a comprehensive theory of the optimality, robustness, and cross-validation selection consistency for the ridge regression under factor-augmented models with possibly dense idiosyncratic information. Using spectral analysis for random matrices, we show that the ridge regression is asymptotically efficient in capturing both factor and idiosyncratic information by minimizing the limiting predictive loss among the entire class of spectral regularized estimators under large-dimensional factor models and mixed-effects hypothesis. We derive an asymptotically optimal ridge penalty in closed form and prove that a bias-corrected k-fold cross-validation procedure can adaptively select the best ridge penalty in large samples. We extend the theory to the autoregressive models with many exogenous variables and establish a consistent cross-validation procedure using the what-we-called double ridge regression method. Our results allow for non-parametric distributions for, possibly heavy-tailed, martingale difference errors and idiosyncratic random coefficients and adapt to the cross-sectional and temporal dependence structures of the large-dimensional predictors. We demonstrate the performance of our ridge estimators in simulated examples as well as an economic dataset. All the proofs are available in the supplement, which also includes more technical discussions and remarks, extra simulation results, and useful lemmas that may be of independent interest.
DOI: 10.6084/m9.figshare.6488240
title: Additional file 1 of Escherichia coli B2 strains prevalent in inflammatory bowel disease patients have distinct metabolic capabilities that enable colonization of intestinal mucosa

description: Table S1: Metadata of 110 strains. Table S2: Genes associated with mucus degradation. Table S3: Metabolic reactions added to previous reconstruction. (XLSX 32 kb)
DOI: 10.6084/m9.figshare.7012250
title: A sampling workflow based on unsupervised clusters and multi-temporal sample interpretation (UCMT) for cropland mapping

description: Accurate cropland maps are important input for various proposes, such as ecosystem service and land cover change monitoring, and the representativeness of sample training samples influence the cropland mapping accuracy significantly. This study aims to propose a new sampling workflow based on unsupervised cluster and multi-temporal interpretation (UCMT) for cropland mapping. The monthly composited image time series were unsupervised clustered using the Iterative Self organizing Data Analysis (ISODATA) and optimal temporal phases were selected using the Gini importance score calculated from Ramdom Forest (RF). Training samples for each cluster were generated and visually interpreted for the optimal temporal phases. The cropland of each temporal phase was identified using the corresponding training samples, and the cropland maps were generated by merging multi-temporal cropland results. Results in two study regions showed that training samples generated using UCMT had good potential to identify cropland with overall accuracies higher than 94% in both study regions. In addition, comparing with randomly generated training samples, UCMT samples were less affected by training sample size as Producer’s accuracies and User’s accuracies were higher than 80% when 100 training samples used.
DOI: 10.6084/m9.figshare.12246452.v1
title: Additional file 5 of Casparian strip membrane domain proteins in Gossypium arboreum: genome-wide identification and negative regulation of lateral root growth

description: Additional file 5: Table S5. Orthologous relationships between G. arboreum and other three Gossypium species.
DOI: 10.6084/m9.figshare.6488240.v1
title: Additional file 1 of Escherichia coli B2 strains prevalent in inflammatory bowel disease patients have distinct metabolic capabilities that enable colonization of intestinal mucosa

description: Table S1: Metadata of 110 strains. Table S2: Genes associated with mucus degradation. Table S3: Metabolic reactions added to previous reconstruction. (XLSX 32 kb)
DOI: 10.6084/m9.figshare.12246434.v1
title: Additional file 2 of Casparian strip membrane domain proteins in Gossypium arboreum: genome-wide identification and negative regulation of lateral root growth

description: Additional file 2: Table S2. The information of CASPs gene family in cotton.
DOI: 10.6084/m9.figshare.12246440.v1
title: Additional file 3 of Casparian strip membrane domain proteins in Gossypium arboreum: genome-wide identification and negative regulation of lateral root growth

description: Additional file 3: Table S3. The general information of the GaCASP family.
DOI: 10.6084/m9.figshare.20120190
title: Long non-coding RNA LOC644135 is a potential prognostic indicator in cytogenetically normal acute myeloid leukemia

description: Acute myeloid leukemia (AML) is a hematological malignancy with highly clinical heterogeneity resulting in poor outcomes. We aim to identify novel prognostic lncRNA in AML expecting to provide new clues for therapy in AML. Three cohorts were enrolled in this study. Differentially expressed lncRNAs between TCGA-AML cohort and GTEx cohort was identified by DESeq2. The relationship between expression level of LOC644135 and prognosis in AML was analyzed by multiple methods. Pan-cancer analysis indicated that LOC644135 was most highly expressed in AML across 33 types of cancer. Patients with high expression of LOC644135 had poor overall prognosis in both TCGA-AML cohort and the TARGET-AML cohort. Especially, high expression of LOC644135 indicated inferior overall survival and event-free survival in CN-AML patients in the TCGA-AML cohort. Besides, CN-AML patients had higher expression of LOC644135 than normal samples. Multivariable analysis suggested that LOC644135 was an independent prognostic factor in AML. GSEA analysis showed that LOC644135 was associated with some immune-related pathways. Besides, high expression of LOC644135 was associated with less infiltration of CD8<sup>+</sup> T cell. Our findings indicated that LOC644135 was an independent prognostic factor in AML and provided a new idea in the development of therapy in AML.
DOI: 10.6084/m9.figshare.12246461
title: Additional file 7 of Casparian strip membrane domain proteins in Gossypium arboreum: genome-wide identification and negative regulation of lateral root growth

description: Additional file 7: Table S7. Tissue specificity regulatory elements found in the GaCASP27 promoter region.