cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7915748.v1
title: Additional file 3: of Genome-wide association study of four yield-related traits at the R6 stage in soybean

description: Table S3. Summary of the polymorphic markers on the 20 chromosomes of Glycine max. (XLSX 10 kb)
DOI: 10.25582/data.2021-10.2352573/2286096
title: Data for EMSL Project 51834 from October 2021
DOI: 10.6084/m9.figshare.21545969.v1
title: Serum levels of IL-12, IL-18, and IL-21 are indicators of viral load in patients chronically infected with HBV

description: This study explored the correlation between interleukins (IL)-12, IL-18, and IL-21 and the viral load in patients with chronic hepatitis B virus (HBV). A total of 142 patients were consecutively enrolled. All were hepatitis B surface antigen (HBsAg)-positive for &gt;6 months and did not receive drug therapy. An ELISA kit was used to test the IL-12, IL-18, IL-21, and acetylcholinesterase (AchE) levels in serum samples from chronic HBV patients and healthy control groups. The amounts of IL-12 and IL-18 were highest in the 5-6log10 (high viral load) group, while IL-21 was highest in the 3-4log10 (low viral load) group. Also, the IL-21 amount was decreased in the HBsAg+/HBeAg/HBcAb+ group, and IL-12, IL-18, and IL-21 were decreased in the normal alanine aminotransferase (ALT) group compared to the abnormal ALT group. These data suggested that IL-12, IL-18, and IL-21 serum levels were positively correlated with disease progression and could reflect disease severity for different HBV-DNA loads. Detection of IL-12, IL-18, and IL-21 levels was found to be helpful for evaluating the degree of liver cell damage and predicting the progression of hepatitis.
DOI: 10.6084/m9.figshare.20495863
title: Additional file 2 of Diagnostic yield and clinical relevance of expanded genetic testing for cancer patients

description: Additional file 2: Table S2. Cancer surveillance and prophylactic surgery recommendations referred to for determining actionability of findings identified in eGT.
DOI: 10.6084/m9.figshare.21545931
title: Optimal Design of Experiments on Riemannian Manifolds

description: The theory of optimal design of experiments has been traditionally developed on an Euclidean space. In this article, new theoretical results and an algorithm for finding the optimal design of an experiment located on a Riemannian manifold are provided. It is shown that analogously to the results in Euclidean spaces, D-optimal and G-optimal designs are equivalent on manifolds, and we provide a lower bound for the maximum prediction variance of the response evaluated over the manifold. In addition, a converging algorithm that finds the optimal experimental design on manifold data is proposed. Numerical experiments demonstrate the importance of considering the manifold structure in a designed experiment when present, and the superiority of the proposed algorithm. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.21545931.v2
title: Optimal Design of Experiments on Riemannian Manifolds

description: The theory of optimal design of experiments has been traditionally developed on an Euclidean space. In this article, new theoretical results and an algorithm for finding the optimal design of an experiment located on a Riemannian manifold are provided. It is shown that analogously to the results in Euclidean spaces, D-optimal and G-optimal designs are equivalent on manifolds, and we provide a lower bound for the maximum prediction variance of the response evaluated over the manifold. In addition, a converging algorithm that finds the optimal experimental design on manifold data is proposed. Numerical experiments demonstrate the importance of considering the manifold structure in a designed experiment when present, and the superiority of the proposed algorithm. Supplementary materials for this article are available online.
DOI: 10.25582/data.2021-09.2314413/2286097
title: Data for EMSL Project 51834 from September 2021
DOI: 10.6084/m9.figshare.21545969
title: Serum levels of IL-12, IL-18, and IL-21 are indicators of viral load in patients chronically infected with HBV

description: This study explored the correlation between interleukins (IL)-12, IL-18, and IL-21 and the viral load in patients with chronic hepatitis B virus (HBV). A total of 142 patients were consecutively enrolled. All were hepatitis B surface antigen (HBsAg)-positive for &gt;6 months and did not receive drug therapy. An ELISA kit was used to test the IL-12, IL-18, IL-21, and acetylcholinesterase (AchE) levels in serum samples from chronic HBV patients and healthy control groups. The amounts of IL-12 and IL-18 were highest in the 5-6log10 (high viral load) group, while IL-21 was highest in the 3-4log10 (low viral load) group. Also, the IL-21 amount was decreased in the HBsAg+/HBeAg/HBcAb+ group, and IL-12, IL-18, and IL-21 were decreased in the normal alanine aminotransferase (ALT) group compared to the abnormal ALT group. These data suggested that IL-12, IL-18, and IL-21 serum levels were positively correlated with disease progression and could reflect disease severity for different HBV-DNA loads. Detection of IL-12, IL-18, and IL-21 levels was found to be helpful for evaluating the degree of liver cell damage and predicting the progression of hepatitis.
DOI: 10.6084/m9.figshare.21545976
title: Referral criteria to palliative care for patients with Parkinson’s disease: a systematic review

description: This systematic review aimed to identify the referral criteria for palliative care in patients with Parkinson’s disease. We conducted an electronic search for publications on referral criteria for palliative care in patients with Parkinson’s disease in six electronic databases. The articles were thoroughly reviewed by two independent reviewers for inclusion using a predefined data extraction list. The referral criteria were thematically classified using a coding methodology. This systematic review included 36 publications. We identified 14 referral criteria themes. The most common referral indicators were functional decline (<i>n</i> = 11 [31%]), needs assessment tools (<i>n</i> = 11 [31%]), physical or emotional symptoms (<i>n</i> = 10[28%]), need for palliative care (<i>n</i> = 10 [28%]), decision support (<i>n</i> = 9 [25%]), advanced Parkinson’s disease (<i>n</i> = 7[19%]), and diagnosis of Parkinson’s disease (<i>n</i> = 7 [19%]). However, there was a lack of consensus on symptom assessment tools. In addition, there were no agreed cut-offs or defined time for palliative care referral for patients with Parkinson’s disease. The 14 themes identified in this systematic review were categorized into disease- and needs-based criteria. These themes show the wide range of referral timing and procedures. Further studies should be conducted to reveal standardized referral criteria. Despite evidence showing the benefits of palliative care in patients with Parkinson’s disease, there is a lack of consensus on when, how, and why patients with Parkinson’s disease should be referred for palliative care. This manuscript summarizes and evaluates the criteria taken into account when making a palliative care referral for patients with Parkinson’s disease. We identified 925 publications. However, only 36 publications were included in the final analysis. Furthermore, we identified 14 themes that were categorized into disease- and needs-based criteria. This systematic review emphasizes the wide range of referral timing and procedures. Moreover, there is a need for more research to reveal standardized referral criteria.
DOI: 10.25582/data.2021-09.2318840/2286098
title: Data for EMSL Project 51834 from September 2021
DOI: 10.6084/m9.figshare.21545645.v1
title: Additional file 6 of Integrated analysis to identify the AC005154.6/hsa-miR-29c-3p/CCNL2 axis as a novel prognostic biomarker associated with immune infiltration in prostate cancer

description: Additional file 6. Prognosis model constructed by AC005154.6/hsa-miR-29c-3p/CCNL2 axis.
DOI: 10.25582/data.2022-10.2614558/2286099
title: Data for EMSL Project 51834 from October 2022
DOI: 10.6084/m9.figshare.21545648
title: Additional file 7 of Integrated analysis to identify the AC005154.6/hsa-miR-29c-3p/CCNL2 axis as a novel prognostic biomarker associated with immune infiltration in prostate cancer

description: Additional file 7. Drugs significantly associated with the expression of CCNL2.
DOI: 10.6084/m9.figshare.21545648.v1
title: Additional file 7 of Integrated analysis to identify the AC005154.6/hsa-miR-29c-3p/CCNL2 axis as a novel prognostic biomarker associated with immune infiltration in prostate cancer

description: Additional file 7. Drugs significantly associated with the expression of CCNL2.
DOI: 10.25582/data.2022-10.2620109/2286100
title: Data for EMSL Project 51834 from October 2022
DOI: 10.6084/m9.figshare.20497279
title: Knockdown of GSG2 inhibits the development and progression of non-small cell lung cancer <i>in vitro</i> and <i>in vivo</i>

description: Lung cancer has been recognized as the most common malignant neoplasm of the respiratory system with extremely high morbidity, among which non-small cell lung cancer (NSCLC) accounts for the majority. Many published literatures have revealed the roles of GSG2 in the progression of ovarian cancer, bladder cancer and breast cancer. However, there were no reports on the relationship between GSG2 and NSCLC. Herein, GSG2 was identified as a potential tumor promoter in NSCLC development, whose abundant expression was observed in NSCLC tissues compared with adjacent nonmalignant tissues and statistically correlated with more advanced tumor stage, more malignant grade and higher risk of lymphatic metastasis. Subsequent <i>in vitro</i> loss-of-function experiments indicated that GSG2 depletion could arrest cell cycle and suppress cell proliferation and migration while enhancing cell apoptosis. At the same time, the suppressive effects of GSG2 depletion on NSCLC development were verified by <i>in vivo</i> experiments. In conclusion, the current study identified GSG2 as a tumor promoter in development and progression of NSCLC, which could work as a novel therapeutic target for NSCLC.
DOI: 10.6084/m9.figshare.21546089.v1
title: METTL3-mediated long non-coding RNA MIR99AHG methylation targets miR-4660 to promote bone marrow mesenchymal stem cell osteogenic differentiation

description: Whether long non-coding RNA Mir-99a-Let-7c Cluster Host Gene (LncRNA MIR99AHG) is involved in osteoporosis (OP) remains vague, so we hereby center on its implication. Old C57BL/6J mice were injected with the silencing lentivirus of MIR99AHG and subjected to microCT analysis and immunohistochemistry on osteogenic cells. The osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) with or without transfection was determined by alkaline phosphatase (ALP) and Alizarin Red S staining. Total N(6)-methyladenosine (m<sup>6</sup>A) on the bone marrow mesenchymal stem cells (BMSCs) was quantified. The potential methylation site and the complementary binding sites with candidate microRNA (miR) were predicted via bioinformatic analyses, with the latter being confirmed via dual-luciferase reporter, RNA immunoprecipitation and RNA pull-down assays. Quantitative real-time PCR and Western blot were used for quantification assays. MIR99AHG was decreased during the osteogenic differentiation of BMSCs, where increased Osterix (OSX), Collagen, Type I, Alpha 1 (Col1A1), Osteocalcin (OCN) and RUNX Family Transcription Factor 2 (RUNX2) as well as more color-stained areas were found. Also, silencing MIR99AHG relieved the OP in mice and reduced the loss of osteogenic cells. M<sup>6</sup>A methylation in undifferentiated BMSCs was low and MIR99AHG overexpression abolished the effects of overexpressed METTL3 on promoting osteogenic differentiation. MiR-4660, which was downregulated in BMSCs without differentiation but increased during osteogenic differentiation, could bind with MIR99AHG. Furthermore, miR-4660 promoted osteogenic differentiation and reversed the effects of overexpressed MIR99AHG. The present study demonstrated that METTL3-mediated LncRNA MIR99AHG methylation enhanced the osteogenic differentiation of BMSCs via targeting miR-4660.
DOI: 10.25582/data.2021-09.2330011/2286101
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-11.2386998/2286102
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-11.2389601/2286103
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2022-10.2623226/2286104
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-11.2387248/2286105
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-11.2389240/2286106
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2022-01.2417391/2286107
title: Data for EMSL Project 51834 from January 2022
DOI: 10.25582/data.2021-11.2375820/2286115
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-08.2305264/2286116
title: Data for EMSL Project 51834 from August 2021
DOI: 10.25582/data.2021-10.2361395/2286117
title: Data for EMSL Project 51834 from October 2021
DOI: 10.6084/m9.figshare.7915820.v1
title: MOESM4 of Reduced protocadherin17 expression in leukemia stem cells: the clinical and biological effect in acute myeloid leukemia

description: Additional file 4. Methylation levels of PCDH17 as measured by targeted bisulfite sequencing.
DOI: 10.25582/data.2021-11.2384660/2286118
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2022-10.2620603/2286119
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2022-09.2612994/2286120
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2021-11.2388151/2286121
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2022-10.2617161/2286122
title: Data for EMSL Project 51834 from October 2022
DOI: 10.6084/m9.figshare.15253977
title: Additional file 1 of Association of germline genetic variants with breast cancer-specific survival in patient subgroups defined by clinic-pathological variables related to tumor biology and type of systemic treatment

description: Additional file 1: Supplementary Table S1, Supplementary Table S2, Supplementary Table S3, and Supplementary Table S4. Supplementary Table S1. Shows an overview of the Breast Cancer Association Consortium studies included in the analyses. Supplementary Table S2. Includes the rationale and references to the literature supporting the choice of each subgroup for inclusion in a genome-wide association study on breast cancer-specific survival. Supplementary Table S3. Shows the characteristics of the breast cancer patients included in the 15-year breast cancer-specific survival analyses, overall and by subgroup. Supplementary Table S4. Shows the characteristics of the breast cancer patients included in the 5-year breast cancer-specific survival analyses for subgroups defined based on type of systemic treatment received.
DOI: 10.25582/data.2022-10.2615743/2286123
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-11.2387692/2286124
title: Data for EMSL Project 51834 from November 2021
DOI: 10.6084/m9.figshare.15253995.v1
title: Additional file 3 of Association of germline genetic variants with breast cancer-specific survival in patient subgroups defined by clinic-pathological variables related to tumor biology and type of systemic treatment

description: Additional file 3: Supplementary Table S8, Supplementary Table S9, Supplementary Table S10, Supplementary Table S11, and Supplementary Table S12. Supplementary Table S8. Shows the BFDPs under two more restrictive prior probabilities of true association (10-5 and 10-6) for the results presented in Table 1. Supplementary Table S9. Shows the BFDPs under two more restrictive prior probabilities of true association (10-5 and 10-6) for the results presented in Table 2. Supplementary Table S10. Shows power calculation by subgroup, at the two-sided 5E-08 level for varying genotype hazard ratio (GHR) and minor allele frequency (MAF), based on number of cases and event rate from the 15-year breast cancer-specific analyses. Supplementary Table S11. Shows power calculation by subgroup, at the two-sided 5E-08 level for varying genotype hazard ratio (GHR) and minor allele frequency (MAF), based on number of cases and event rate from the 5-year breast cancer-specific analyses. Supplementary Table S12. Shows the subgroup-specific associations detected by previous studies and corresponding estimates from the current study.
DOI: 10.25582/data.2021-10.2363292/2286125
title: Data for EMSL Project 51834 from October 2021
DOI: 10.25582/data.2021-11.2380524/2286126
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2022-10.2616517/2286127
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-09.2322384/2286128
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2022-10.2620729/2286129
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2022-09.2606258/2286130
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2022-10.2615881/2286131
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2022-09.2612639/2286132
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2022-09.2608883/2286133
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2022-09.2609402/2286134
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2021-10.2369806/2286135
title: Data for EMSL Project 51834 from October 2021
DOI: 10.25582/data.2021-12.2397065/2286136
title: Data for EMSL Project 51834 from December 2021
DOI: 10.25582/data.2021-12.2404765/2286137
title: Data for EMSL Project 51834 from December 2021
DOI: 10.25582/data.2022-10.2616471/2286138
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-10.2363328/2286139
title: Data for EMSL Project 51834 from October 2021
DOI: 10.25582/data.2021-11.2384634/2286140
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-11.2387371/2286141
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-08.2305309/2286142
title: Data for EMSL Project 51834 from August 2021
DOI: 10.25582/data.2021-12.2389796/2286143
title: Data for EMSL Project 51834 from December 2021
DOI: 10.25582/data.2022-09.2609469/2286144
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2021-12.2389928/2286145
title: Data for EMSL Project 51834 from December 2021
DOI: 10.25582/data.2022-01.2417143/2286146
title: Data for EMSL Project 51834 from January 2022
DOI: 10.25582/data.2022-04.2478900/2286147
title: Data for EMSL Project 51834 from April 2022
DOI: 10.25582/data.2021-11.2387617/2286148
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2022-04.2479069/2286149
title: Data for EMSL Project 51834 from April 2022
DOI: 10.25582/data.2022-09.2606276/2286150
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2021-11.2387093/2286151
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-08.2305282/2286152
title: Data for EMSL Project 51834 from August 2021
DOI: 10.25582/data.2021-10.2368088/2286153
title: Data for EMSL Project 51834 from October 2021
DOI: 10.25582/data.2021-11.2389259/2286154
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-11.2387293/2286155
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-11.2389108/2286156
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-12.2390397/2286157
title: Data for EMSL Project 51834 from December 2021
DOI: 10.25582/data.2022-10.2620115/2286158
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2022-01.2417156/2286159
title: Data for EMSL Project 51834 from January 2022
DOI: 10.25582/data.2022-09.2607911/2286160
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2021-10.2353290/2286161
title: Data for EMSL Project 51834 from October 2021
DOI: 10.25582/data.2021-11.2384672/2286162
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-10.2363315/2286163
title: Data for EMSL Project 51834 from October 2021
DOI: 10.25582/data.2021-11.2380673/2286164
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-09.2327587/2286165
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2022-09.2612103/2286166
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2022-10.2615086/2286167
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-10.2353162/2286168
title: Data for EMSL Project 51834 from October 2021
DOI: 10.6084/m9.figshare.7916057
title: MOESM1 of The specific status of Melastoma kudoi (Melastomataceae, Melastomeae)

description: Additional file 1: Table S1. Source of materials studied and GenBank accession numbers for nrITS, 6 nuclear genes and 2 chloroplast markers. Sequences downloaded from GenBank are indicated in bold.
DOI: 10.6084/m9.figshare.7916057.v1
title: MOESM1 of The specific status of Melastoma kudoi (Melastomataceae, Melastomeae)

description: Additional file 1: Table S1. Source of materials studied and GenBank accession numbers for nrITS, 6 nuclear genes and 2 chloroplast markers. Sequences downloaded from GenBank are indicated in bold.
DOI: 10.25582/data.2022-09.2608830/2286169
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2021-09.2322501/2286170
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2022-10.2616198/2286171
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-10.2353285/2286172
title: Data for EMSL Project 51834 from October 2021
DOI: 10.25582/data.2022-09.2606812/2286173
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2021-11.2387624/2286174
title: Data for EMSL Project 51834 from November 2021
DOI: 10.6084/m9.figshare.7391831.v1
title: Additional file 1: of Sex chromosomal dimorphisms narrated by X-chromosome translocation in a spiny frog (Quasipaa boulengeri)

description: Table S1. Sequence data of the sex-linked marker B08 in Quasipaa boulengeri. (XLSX 14.6 kb)
DOI: 10.25582/data.2022-04.2479169/2286175
title: Data for EMSL Project 51834 from April 2022
DOI: 10.25582/data.2021-11.2375972/2286176
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-09.2327987/2286177
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-09.2322428/2286178
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-09.2327399/2286179
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-09.2327540/2286180
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-11.2389185/2286181
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2022-09.2609881/2286182
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2022-10.2622292/2286183
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-11.2384684/2286184
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2022-09.2607506/2286185
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2022-01.2417775/2286186
title: Data for EMSL Project 51834 from January 2022
DOI: 10.25582/data.2021-09.2328619/2286187
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2022-04.2479163/2286188
title: Data for EMSL Project 51834 from April 2022
DOI: 10.25582/data.2021-09.2322510/2286189
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-12.2389841/2286190
title: Data for EMSL Project 51834 from December 2021
DOI: 10.25582/data.2021-09.2314359/2286191
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-09.2322552/2286192
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-12.2400007/2286193
title: Data for EMSL Project 51834 from December 2021