cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7608431.v1
title: MOESM1 of Alteration in gut microbiota associated with hepatitis B and non-hepatitis virus related hepatocellular carcinoma

description: Additional file 1. Information of the study cohort used in this study. A total of 90 volunteers consisted of 33 healthy controls, 22 individuals of NBNC-HCC patients and 35 individuals of B-HCC patients were enrolled. The characteristics of participants including physical examination (gender, age, height, weight, BM, drinking condition), blood biochemical indexes (AFP, ALT, AST, GGT, TBil, INR, SCr, total protein, albumin, prothrombin time and activated partial thromboplastin time), Childâ Pugh score and class, and MELD score.
DOI: 10.6084/m9.figshare.12851315
title: Restoration of CTSD (cathepsin D) and lysosomal function in stroke is neuroprotective

description: Stroke is a leading cause of death and disability. The pathophysiological mechanisms associated with stroke are very complex and not fully understood. Lysosomal function has a vital physiological function in the maintenance of cellular homeostasis. In neurons, CTSD (cathepsin D) is an essential protease involved in the regulation of proteolytic activity of the lysosomes. Loss of CTSD leads to lysosomal dysfunction and accumulation of different cellular proteins implicated in neurodegenerative diseases. In cerebral ischemia, the role of CTSD and lysosomal function is not clearly defined. We used oxygen-glucose deprivation (OGD) in mouse cortical neurons and the middle cerebral artery occlusion (MCAO) model of stroke to assess the role of CTSD in stroke pathophysiology. Our results show a time-dependent decrease in CTSD protein levels and activity in the mouse brain after stroke and neurons following OGD, with concurrent defects in lysosomal function. We found that shRNA-mediated knockdown of CTSD in neurons is sufficient to cause lysosomal dysfunction. CTSD knockdown further aggravates lysosomal dysfunction and cell death in OGD-exposed neurons. Restoration of CTSD protein levels via lentiviral transduction increases CTSD activity in neurons and, thus, renders resistance to OGD-mediated defects in lysosomal function and cell death. This study indicates that CTSD-dependent lysosomal function is critical for maintaining neuronal survival in cerebral ischemia; thus, strategies focused on maintaining CTSD function in neurons are potentially novel therapeutic approaches to prevent neuronal death in stroke. <b>Abbreviations:</b> 3-MA: 3-methyladenine; ACTB: actin beta; AD: Alzheimer disease; ALS: amyotrophic lateral sclerosis; CQ: chloroquine; CTSB: cathepsin B; CTSD: cathepsin D; CTSL: cathepsin L; FTD: frontotemporal dementia, HD: Huntington disease; LAMP1: lysosomal associated membrane protein 1; LSD: lysosomal storage disease; MCAO: middle cerebral artery occlusion; OGD: oxygen glucose deprivation; OGR: oxygen glucose resupply; PD: Parkinson disease; SQSMT1: sequestosome 1; TCA: trichloroacetic acid; TTC: triphenyl tetrazolium chloride.
DOI: 10.6084/m9.figshare.12851315.v1
title: Restoration of CTSD (cathepsin D) and lysosomal function in stroke is neuroprotective

description: Stroke is a leading cause of death and disability. The pathophysiological mechanisms associated with stroke are very complex and not fully understood. Lysosomal function has a vital physiological function in the maintenance of cellular homeostasis. In neurons, CTSD (cathepsin D) is an essential protease involved in the regulation of proteolytic activity of the lysosomes. Loss of CTSD leads to lysosomal dysfunction and accumulation of different cellular proteins implicated in neurodegenerative diseases. In cerebral ischemia, the role of CTSD and lysosomal function is not clearly defined. We used oxygen-glucose deprivation (OGD) in mouse cortical neurons and the middle cerebral artery occlusion (MCAO) model of stroke to assess the role of CTSD in stroke pathophysiology. Our results show a time-dependent decrease in CTSD protein levels and activity in the mouse brain after stroke and neurons following OGD, with concurrent defects in lysosomal function. We found that shRNA-mediated knockdown of CTSD in neurons is sufficient to cause lysosomal dysfunction. CTSD knockdown further aggravates lysosomal dysfunction and cell death in OGD-exposed neurons. Restoration of CTSD protein levels via lentiviral transduction increases CTSD activity in neurons and, thus, renders resistance to OGD-mediated defects in lysosomal function and cell death. This study indicates that CTSD-dependent lysosomal function is critical for maintaining neuronal survival in cerebral ischemia; thus, strategies focused on maintaining CTSD function in neurons are potentially novel therapeutic approaches to prevent neuronal death in stroke. <b>Abbreviations:</b> 3-MA: 3-methyladenine; ACTB: actin beta; AD: Alzheimer disease; ALS: amyotrophic lateral sclerosis; CQ: chloroquine; CTSB: cathepsin B; CTSD: cathepsin D; CTSL: cathepsin L; FTD: frontotemporal dementia, HD: Huntington disease; LAMP1: lysosomal associated membrane protein 1; LSD: lysosomal storage disease; MCAO: middle cerebral artery occlusion; OGD: oxygen glucose deprivation; OGR: oxygen glucose resupply; PD: Parkinson disease; SQSMT1: sequestosome 1; TCA: trichloroacetic acid; TTC: triphenyl tetrazolium chloride.
DOI: 10.6084/m9.figshare.7608440
title: MOESM2 of Alteration in gut microbiota associated with hepatitis B and non-hepatitis virus related hepatocellular carcinoma

description: Additional file 2. Relative abundance of bacteria at the phylum level.
DOI: 10.6084/m9.figshare.7608440.v1
title: MOESM2 of Alteration in gut microbiota associated with hepatitis B and non-hepatitis virus related hepatocellular carcinoma

description: Additional file 2. Relative abundance of bacteria at the phylum level.
DOI: 10.6084/m9.figshare.7608443
title: Additional file 4: of PAGE4 promotes prostate cancer cells survive under oxidative stress through modulating MAPK/JNK/ERK pathway

description: Table S2. 425 shared DEGs in 22RV1 and DU145 cell lines. (XLS 90 kb)
DOI: 10.6084/m9.figshare.7608443.v1
title: Additional file 4: of PAGE4 promotes prostate cancer cells survive under oxidative stress through modulating MAPK/JNK/ERK pathway

description: Table S2. 425 shared DEGs in 22RV1 and DU145 cell lines. (XLS 90 kb)
DOI: 10.6084/m9.figshare.7608446
title: MOESM3 of Alteration in gut microbiota associated with hepatitis B and non-hepatitis virus related hepatocellular carcinoma

description: Additional file 3. Relative abundance of bacteria at the order level.
DOI: 10.6084/m9.figshare.7608446.v1
title: MOESM3 of Alteration in gut microbiota associated with hepatitis B and non-hepatitis virus related hepatocellular carcinoma

description: Additional file 3. Relative abundance of bacteria at the order level.
DOI: 10.6084/m9.figshare.7608455
title: MOESM4 of Alteration in gut microbiota associated with hepatitis B and non-hepatitis virus related hepatocellular carcinoma

description: Additional file 4. Relative abundance of bacteria at the genus level.
DOI: 10.6084/m9.figshare.7608455.v1
title: MOESM4 of Alteration in gut microbiota associated with hepatitis B and non-hepatitis virus related hepatocellular carcinoma

description: Additional file 4. Relative abundance of bacteria at the genus level.
DOI: 10.6084/m9.figshare.12851337
title: Gene-Based Association Testing of Dichotomous Traits With Generalized Functional Linear Mixed Models Using Extended Pedigrees: Applications to Age-Related Macular Degeneration

description: Genetics plays a role in age-related macular degeneration (AMD), a common cause of blindness in the elderly. There is a need for powerful methods for carrying out region-based association tests between a dichotomous trait like AMD and genetic variants on family data. Here, we apply our new generalized functional linear mixed models (GFLMM) developed to test for gene-based association in a set of AMD families. Using common and rare variants, we observe significant association with two known AMD genes: <i>CFH</i> and <i>ARMS2</i>. Using rare variants, we find suggestive signals in four genes: <i>ASAH1</i>, <i>CLEC6A</i>, <i>TMEM63C</i>, and <i>SGSM1</i>. Intriguingly, <i>ASAH1</i> is down-regulated in AMD aqueous humor, and <i>ASAH1</i> deficiency leads to retinal inflammation and increased vulnerability to oxidative stress. These findings were made possible by our GFLMM which model the effect of a major gene as a fixed mean, the polygenic contributions as a random variation, and the correlation of pedigree members by kinship coefficients. Simulations indicate that the GFLMM likelihood ratio tests (LRTs) accurately control the Type I error rates. The LRTs have similar or higher power than existing retrospective kernel and burden statistics. Our GFLMM-based statistics provide a new tool for conducting family-based genetic studies of complex diseases. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
DOI: 10.6084/m9.figshare.12851337.v2
title: Gene-Based Association Testing of Dichotomous Traits With Generalized Functional Linear Mixed Models Using Extended Pedigrees: Applications to Age-Related Macular Degeneration

description: Genetics plays a role in age-related macular degeneration (AMD), a common cause of blindness in the elderly. There is a need for powerful methods for carrying out region-based association tests between a dichotomous trait like AMD and genetic variants on family data. Here, we apply our new generalized functional linear mixed models (GFLMM) developed to test for gene-based association in a set of AMD families. Using common and rare variants, we observe significant association with two known AMD genes: <i>CFH</i> and <i>ARMS2</i>. Using rare variants, we find suggestive signals in four genes: <i>ASAH1</i>, <i>CLEC6A</i>, <i>TMEM63C</i>, and <i>SGSM1</i>. Intriguingly, <i>ASAH1</i> is down-regulated in AMD aqueous humor, and <i>ASAH1</i> deficiency leads to retinal inflammation and increased vulnerability to oxidative stress. These findings were made possible by our GFLMM which model the effect of a major gene as a fixed mean, the polygenic contributions as a random variation, and the correlation of pedigree members by kinship coefficients. Simulations indicate that the GFLMM likelihood ratio tests (LRTs) accurately control the Type I error rates. The LRTs have similar or higher power than existing retrospective kernel and burden statistics. Our GFLMM-based statistics provide a new tool for conducting family-based genetic studies of complex diseases. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
DOI: 10.6084/m9.figshare.7608458
title: MOESM5 of Alteration in gut microbiota associated with hepatitis B and non-hepatitis virus related hepatocellular carcinoma

description: Additional file 5. Relative abundance of the top 35 genera.
DOI: 10.6084/m9.figshare.7608458.v1
title: MOESM5 of Alteration in gut microbiota associated with hepatitis B and non-hepatitis virus related hepatocellular carcinoma

description: Additional file 5. Relative abundance of the top 35 genera.
DOI: 10.6084/m9.figshare.7608461
title: MOESM6 of Alteration in gut microbiota associated with hepatitis B and non-hepatitis virus related hepatocellular carcinoma

description: Additional file 6. Relative abundance of the top 25 genera for canonical correspondence analysis.
DOI: 10.6084/m9.figshare.7608461.v1
title: MOESM6 of Alteration in gut microbiota associated with hepatitis B and non-hepatitis virus related hepatocellular carcinoma

description: Additional file 6. Relative abundance of the top 25 genera for canonical correspondence analysis.
DOI: 10.34740/kaggle/dsv/7629921
title: US Board on Geographic Names
DOI: 10.6084/m9.figshare.7608473
title: MOESM8 of Alteration in gut microbiota associated with hepatitis B and non-hepatitis virus related hepatocellular carcinoma

description: Additional file 8. Relative abundance of the significantly different genera (Pâ &lt;â 0.050 by Wilcoxon rank sum test).
DOI: 10.6084/m9.figshare.7608473.v1
title: MOESM8 of Alteration in gut microbiota associated with hepatitis B and non-hepatitis virus related hepatocellular carcinoma

description: Additional file 8. Relative abundance of the significantly different genera (Pâ &lt;â 0.050 by Wilcoxon rank sum test).
DOI: 10.6084/m9.figshare.7608476
title: MOESM9 of Alteration in gut microbiota associated with hepatitis B and non-hepatitis virus related hepatocellular carcinoma

description: Additional file 9. Relative abundance of the top 35 predicated biological pathways.
DOI: 10.6084/m9.figshare.7608476.v1
title: MOESM9 of Alteration in gut microbiota associated with hepatitis B and non-hepatitis virus related hepatocellular carcinoma

description: Additional file 9. Relative abundance of the top 35 predicated biological pathways.
DOI: 10.6084/m9.figshare.12851361
title: Bayesian Joint Modeling of Multiple Brain Functional Networks

description: Investigating the similarity and changes in brain networks under different mental conditions has become increasingly important in neuroscience research. A standard separate estimation strategy fails to pool information across networks and hence has reduced estimation accuracy and power to detect between-network differences. Motivated by an fMRI Stroop task experiment that involves multiple related tasks, we develop an integrative Bayesian approach for jointly modeling multiple brain networks that provides a systematic inferential framework for network comparisons. The proposed approach explicitly models shared and differential patterns via flexible Dirichlet process-based priors on edge probabilities. Conditional on edges, the connection strengths are modeled via Bayesian spike-and-slab prior on the precision matrix off-diagonals. Numerical simulations illustrate that the proposed approach has increased power to detect true differential edges while providing adequate control on false positives and achieves greater network estimation accuracy compared to existing methods. The Stroop task data analysis reveals greater connectivity differences between task and fixation that are concentrated in brain regions previously identified as differentially activated in Stroop task, and more nuanced connectivity differences between exertion and relaxed task. In contrast, penalized modeling approaches involving computationally burdensome permutation tests reveal negligible network differences between conditions that seem biologically implausible. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
DOI: 10.6084/m9.figshare.12851361.v2
title: Bayesian Joint Modeling of Multiple Brain Functional Networks

description: Investigating the similarity and changes in brain networks under different mental conditions has become increasingly important in neuroscience research. A standard separate estimation strategy fails to pool information across networks and hence has reduced estimation accuracy and power to detect between-network differences. Motivated by an fMRI Stroop task experiment that involves multiple related tasks, we develop an integrative Bayesian approach for jointly modeling multiple brain networks that provides a systematic inferential framework for network comparisons. The proposed approach explicitly models shared and differential patterns via flexible Dirichlet process-based priors on edge probabilities. Conditional on edges, the connection strengths are modeled via Bayesian spike-and-slab prior on the precision matrix off-diagonals. Numerical simulations illustrate that the proposed approach has increased power to detect true differential edges while providing adequate control on false positives and achieves greater network estimation accuracy compared to existing methods. The Stroop task data analysis reveals greater connectivity differences between task and fixation that are concentrated in brain regions previously identified as differentially activated in Stroop task, and more nuanced connectivity differences between exertion and relaxed task. In contrast, penalized modeling approaches involving computationally burdensome permutation tests reveal negligible network differences between conditions that seem biologically implausible. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
DOI: 10.6084/m9.figshare.12851367
title: Distribution-Free Consistent Independence Tests via Center-Outward Ranks and Signs

description: This article investigates the problem of testing independence of two random vectors of general dimensions. For this, we give for the first time a distribution-free consistent test. Our approach combines distance covariance with the center-outward ranks and signs developed by Marc Hallin and collaborators. In technical terms, the proposed test is consistent and distribution-free in the family of multivariate distributions with nonvanishing (Lebesgue) probability densities. Exploiting the (degenerate) <i>U</i>-statistic structure of the distance covariance and the combinatorial nature of Hallin’s center-outward ranks and signs, we are able to derive the limiting null distribution of our test statistic. The resulting asymptotic approximation is accurate already for moderate sample sizes and makes the test implementable without requiring permutation. The limiting distribution is derived via a more general result that gives a new type of combinatorial noncentral limit theorem for double- and multiple-indexed permutation statistics. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.12851367.v2
title: Distribution-Free Consistent Independence Tests via Center-Outward Ranks and Signs

description: This article investigates the problem of testing independence of two random vectors of general dimensions. For this, we give for the first time a distribution-free consistent test. Our approach combines distance covariance with the center-outward ranks and signs developed by Marc Hallin and collaborators. In technical terms, the proposed test is consistent and distribution-free in the family of multivariate distributions with nonvanishing (Lebesgue) probability densities. Exploiting the (degenerate) <i>U</i>-statistic structure of the distance covariance and the combinatorial nature of Hallin’s center-outward ranks and signs, we are able to derive the limiting null distribution of our test statistic. The resulting asymptotic approximation is accurate already for moderate sample sizes and makes the test implementable without requiring permutation. The limiting distribution is derived via a more general result that gives a new type of combinatorial noncentral limit theorem for double- and multiple-indexed permutation statistics. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.12851367.v1
title: Distribution-free consistent independence tests via center-outward ranks and signs

description: This paper investigates the problem of testing independence of two random vectors of general dimensions. For this, we give for the first time a distribution-free consistent test. Our approach combines distance covariance with the center-outward ranks and signs developed in Hallin (2017). In technical terms, the proposed test is consistent and distribution-free in the family of multivariate distributions with nonvanishing (Lebesgue) probability densities. Exploiting the (degenerate) U-statistic structure of the distance covariance and the combinatorial nature of Hallin’s center-outward ranks and signs, we are able to derive the limiting null distribution of our test statistic. The resulting asymptotic approximation is accurate already for moderate sample sizes and makes the test implementable without requiring permutation. The limiting distribution is derived via a more general result that gives a new type of combinatorial non-central limit theorem for double- and multiple-indexed permutation statistics.
DOI: 10.6084/m9.figshare.12851391
title: AdaBoost Semiparametric Model Averaging Prediction for Multiple Categories

description: Model average techniques are very useful for model-based prediction. However, most earlier works in this field focused on parametric models and continuous responses. In this article, we study varying coefficient multinomial logistic models and propose a semiparametric model averaging prediction (SMAP) approach for multi-category outcomes. The proposed procedure does not need any artificial specification of the index variable in the adopted varying coefficient sub-model structure to forecast the response. In particular, this new SMAP method is more flexible and robust against model misspecification. To improve the practical predictive performance, we combine SMAP with the AdaBoost algorithm to obtain more accurate estimations of class probabilities and model averaging weights. We compare our proposed methods with all existing model averaging approaches and a wide range of popular classification methods via extensive simulations. An automobile classification study is included to illustrate the merits of our methodology. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.12851391.v2
title: AdaBoost Semiparametric Model Averaging Prediction for Multiple Categories

description: Model average techniques are very useful for model-based prediction. However, most earlier works in this field focused on parametric models and continuous responses. In this article, we study varying coefficient multinomial logistic models and propose a semiparametric model averaging prediction (SMAP) approach for multi-category outcomes. The proposed procedure does not need any artificial specification of the index variable in the adopted varying coefficient sub-model structure to forecast the response. In particular, this new SMAP method is more flexible and robust against model misspecification. To improve the practical predictive performance, we combine SMAP with the AdaBoost algorithm to obtain more accurate estimations of class probabilities and model averaging weights. We compare our proposed methods with all existing model averaging approaches and a wide range of popular classification methods via extensive simulations. An automobile classification study is included to illustrate the merits of our methodology. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.7608515
title: Additional file 1: of Integrated physiological and proteomic analysis of embryo and endosperm reveals central salt stress response proteins during seed germination of winter wheat cultivar Zhengmai 366

description: Table S1–1. DAPs from embryo samples identified by MALDI-TOF/TOF-MS under salt stress. Table S1–2. DAPs from endosperm samples identified by MALDI-TOF/TOF-MS under salt stress. Table S2–1. The peptide information of all the identified proteins in the embryo under salt stress. Table S2–2. The peptide information of all the identified proteins in the endosperm under salt stress. (XLSX 161 kb)
DOI: 10.6084/m9.figshare.18094277
title: Distinct size dependence and diurnal variation of OA hygroscopicity, volatility, and CCN activity at a rural site in the Pearl River Delta (PRD) region, China

description: This is a data set from a field campaign carried out during November and December at a rural site in the Pearl River Delta region, China. It includes particle number size distribution, particle hygroscopicity, particle volatility, chemical composition, PMF result, CCN number concentration, PM2.5 concentration, wind direction, and wind speed.