cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25582/data.2023-01.2718019/2286524
title: Data for EMSL Project 51834 from January 2023
DOI: 10.6084/m9.figshare.7915754.v1
title: Additional file 4: of Genome-wide association study of four yield-related traits at the R6 stage in soybean

description: Table S4. The ecological distribution of 133 soybean landraces from different subgroups. (XLSX 9 kb)
DOI: 10.6084/m9.figshare.7915829
title: MOESM5 of Reduced protocadherin17 expression in leukemia stem cells: the clinical and biological effect in acute myeloid leukemia

description: Additional file 5. Differentially expressed genes between AML patients with low and high PCDH17 expression.
DOI: 10.6084/m9.figshare.7915832.v1
title: MOESM6 of Reduced protocadherin17 expression in leukemia stem cells: the clinical and biological effect in acute myeloid leukemia

description: Additional file 6. Differentially expressed microRNAs between AML patients with low and high PCDH17 expression.
DOI: 10.6084/m9.figshare.7915808
title: MOESM2 of Reduced protocadherin17 expression in leukemia stem cells: the clinical and biological effect in acute myeloid leukemia

description: Additional file 2. List of 443 down-regulated probes/genes in LSCs versus normal HSCs.
DOI: 10.25582/data.2021-11.2388419/2286525
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2022-09.2610359/2286526
title: Data for EMSL Project 51834 from September 2022
DOI: 10.6084/m9.figshare.8964374
title: Ara-c induces cell cycle G1/S arrest by inducing upregulation of the INK4 family gene or directly inhibiting the formation of the cell cycle-dependent complex CDK4/cyclin D1

description: Cytosine arabinoside (Ara-c) is a pyrimidine anti-metabolite that is capable of interfering with cellular proliferation by inhibiting DNA synthesis. Each inhibitor of cyclin-dependent kinase 4 (INK4) family member has the ability to bind to cyclin-dependent kinase 4 (CDK4) and inhibit the formation of the cell cycle-dependent CDK4/cyclin D1 complex, subsequently leading to cell cycle arrest in the G1/S phase. In this study, the expression of INK4 family genes in kidney cancer and the impact of these genes on patient prognosis were examined. Additionally, the effects of INK4 family genes and Ara-c on cell proliferation and tumor formation and development were examined. Finally, a potential association between Ara-c-induced cell cycle arrest and INK4-associated gene expression was evaluated. An upregulation of INK4 family genes was found to be positively correlated with the prognosis of patients with kidney cancer. Both the INK4 family genes and Ara-c were shown to induce cell cycle arrest and inhibit tumor formation and development. Moreover, Ara-c-induced cell cycle arrest was found to be associated with an Ara-c-induced upregulation of INK4 family gene expression, which ultimately inhibited the formation of the CDK4/cyclin D1 complex. These findings suggested that an upregulation of INK4 family genes has a positive effect on kidney cancer prognosis and can inhibit the formation and development of tumors. Moreover, Ara-c was shown to promote the upregulation of INK4 family genes, at the same time, Ara-c could directly regulate the cell cycle-dependent genes <i>CDK4</i> and <i>cyclin D1</i> (<i>CCND1</i>), independent of the INK4 family genes.
DOI: 10.6084/m9.figshare.8964374.v1
title: Ara-c induces cell cycle G1/S arrest by inducing upregulation of the INK4 family gene or directly inhibiting the formation of the cell cycle-dependent complex CDK4/cyclin D1

description: Cytosine arabinoside (Ara-c) is a pyrimidine anti-metabolite that is capable of interfering with cellular proliferation by inhibiting DNA synthesis. Each inhibitor of cyclin-dependent kinase 4 (INK4) family member has the ability to bind to cyclin-dependent kinase 4 (CDK4) and inhibit the formation of the cell cycle-dependent CDK4/cyclin D1 complex, subsequently leading to cell cycle arrest in the G1/S phase. In this study, the expression of INK4 family genes in kidney cancer and the impact of these genes on patient prognosis were examined. Additionally, the effects of INK4 family genes and Ara-c on cell proliferation and tumor formation and development were examined. Finally, a potential association between Ara-c-induced cell cycle arrest and INK4-associated gene expression was evaluated. An upregulation of INK4 family genes was found to be positively correlated with the prognosis of patients with kidney cancer. Both the INK4 family genes and Ara-c were shown to induce cell cycle arrest and inhibit tumor formation and development. Moreover, Ara-c-induced cell cycle arrest was found to be associated with an Ara-c-induced upregulation of INK4 family gene expression, which ultimately inhibited the formation of the CDK4/cyclin D1 complex. These findings suggested that an upregulation of INK4 family genes has a positive effect on kidney cancer prognosis and can inhibit the formation and development of tumors. Moreover, Ara-c was shown to promote the upregulation of INK4 family genes, at the same time, Ara-c could directly regulate the cell cycle-dependent genes <i>CDK4</i> and <i>cyclin D1</i> (<i>CCND1</i>), independent of the INK4 family genes.
DOI: 10.25582/data.2022-10.2617655/2286527
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-09.2326450/2286528
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2022-09.2609872/2286529
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2021-10.2372856/2286530
title: Data for EMSL Project 51834 from October 2021
DOI: 10.25582/data.2022-09.2607878/2286531
title: Data for EMSL Project 51834 from September 2022
DOI: 10.5281/zenodo.10628242
title: Bacterial Rps3 counters oxidative and UV stress by recognizing and processing AP-sites on mRNA via a novel mechanism
title: Coordinates and maps

description: Contains the coordinates and maps corresponding to the Cryo-EM experiments of the manuscript with tentative title 'Bacterial Rps3 counters oxidative and UV stress by recognizing and processing AP-sites on mRNA via a novel mechanism'

It bears the CSIR-CDRI manuscript number 115/2023/RR
DOI: 10.5281/zenodo.10628243
title: Bacterial Rps3 counters oxidative and UV stress by recognizing and processing AP-sites on mRNA via a novel mechanism
title: Coordinates and maps

description: Contains the coordinates and maps corresponding to the Cryo-EM experiments of the manuscript with tentative title 'Bacterial Rps3 counters oxidative and UV stress by recognizing and processing AP-sites on mRNA via a novel mechanism'

It bears the CSIR-CDRI manuscript number 115/2023/RR
DOI: 10.25582/data.2021-11.2387329/2286532
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2022-10.2615505/2286533
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-12.2390563/2286534
title: Data for EMSL Project 51834 from December 2021
DOI: 10.25582/data.2022-01.2417155/2286535
title: Data for EMSL Project 51834 from January 2022
DOI: 10.25582/data.2022-10.2621662/2286536
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-11.2387263/2286537
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-09.2316678/2286538
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-09.2319132/2286539
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-12.2399878/2286540
title: Data for EMSL Project 51834 from December 2021
DOI: 10.25582/data.2022-10.2616439/2286541
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2022-09.2610411/2286542
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2022-10.2616497/2286543
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2022-04.2478873/2286544
title: Data for EMSL Project 51834 from April 2022
DOI: 10.25582/data.2021-11.2388307/2286545
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-11.2387258/2286546
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-11.2387440/2286547
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2022-01.2417400/2286548
title: Data for EMSL Project 51834 from January 2022
DOI: 10.25582/data.2021-09.2319242/2286549
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-11.2386993/2286550
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-11.2388441/2286551
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2022-10.2622450/2286552
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-09.2329563/2286553
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-10.2353362/2286554
title: Data for EMSL Project 51834 from October 2021
DOI: 10.25582/data.2021-11.2388200/2286555
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2023-01.2704689/2286556
title: Data for EMSL Project 51834 from January 2023
DOI: 10.25582/data.2021-10.2352815/2286557
title: Data for EMSL Project 51834 from October 2021
DOI: 10.25582/data.2022-10.2620157/2286558
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-10.2368068/2286559
title: Data for EMSL Project 51834 from October 2021
DOI: 10.25582/data.2021-08.2304557/2286560
title: Data for EMSL Project 51834 from August 2021
DOI: 10.25582/data.2022-10.2620809/2286561
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2022-09.2609453/2286562
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2021-08.2304589/2286563
title: Data for EMSL Project 51834 from August 2021
DOI: 10.25582/data.2021-09.2327164/2286564
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2022-09.2610636/2286565
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2022-10.2620838/2286566
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-11.2389057/2286567
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-09.2318080/2286568
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-09.2327527/2286569
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-11.2389238/2286570
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-11.2387618/2286571
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-09.2328647/2286572
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-09.2332623/2286573
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2022-10.2622074/2286574
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2022-10.2621743/2286575
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-09.2318145/2286576
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-11.2385126/2286577
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-12.2390342/2286578
title: Data for EMSL Project 51834 from December 2021
DOI: 10.25582/data.2021-09.2319238/2286579
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-11.2387274/2286580
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-09.2332526/2286581
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-09.2329599/2286582
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2022-01.2417594/2286583
title: Data for EMSL Project 51834 from January 2022
DOI: 10.6084/m9.figshare.7393130
title: MM Algorithms for Variance Components Models

description: Variance components estimation and mixed model analysis are central themes in statistics with applications in numerous scientific disciplines. Despite the best efforts of generations of statisticians and numerical analysts, maximum likelihood estimation (MLE) and restricted MLE of variance component models remain numerically challenging. Building on the minorization–maximization (MM) principle, this article presents a novel iterative algorithm for variance components estimation. Our MM algorithm is trivial to implement and competitive on large data problems. The algorithm readily extends to more complicated problems such as linear mixed models, multivariate response models possibly with missing data, maximum a posteriori estimation, and penalized estimation. We establish the global convergence of the MM algorithm to a Karush–Kuhn–Tucker point and demonstrate, both numerically and theoretically, that it converges faster than the classical EM algorithm when the number of variance components is greater than two and all covariance matrices are positive definite. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.7393130.v1
title: MM Algorithms for Variance Components Models

description: Variance components estimation and mixed model analysis are central themes in statistics with applications in numerous scientific disciplines. Despite the best efforts of generations of statisticians and numerical analysts, maximum likelihood estimation (MLE) and restricted MLE of variance component models remain numerically challenging. Building on the minorization–maximization (MM) principle, this article presents a novel iterative algorithm for variance components estimation. Our MM algorithm is trivial to implement and competitive on large data problems. The algorithm readily extends to more complicated problems such as linear mixed models, multivariate response models possibly with missing data, maximum a posteriori estimation, and penalized estimation. We establish the global convergence of the MM algorithm to a Karush–Kuhn–Tucker point and demonstrate, both numerically and theoretically, that it converges faster than the classical EM algorithm when the number of variance components is greater than two and all covariance matrices are positive definite. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.7393130.v2
title: MM Algorithms for Variance Components Models

description: Variance components estimation and mixed model analysis are central themes in statistics with applications in numerous scientific disciplines. Despite the best efforts of generations of statisticians and numerical analysts, maximum likelihood estimation (MLE) and restricted MLE of variance component models remain numerically challenging. Building on the minorization–maximization (MM) principle, this article presents a novel iterative algorithm for variance components estimation. Our MM algorithm is trivial to implement and competitive on large data problems. The algorithm readily extends to more complicated problems such as linear mixed models, multivariate response models possibly with missing data, maximum a posteriori estimation, and penalized estimation. We establish the global convergence of the MM algorithm to a Karush–Kuhn–Tucker point and demonstrate, both numerically and theoretically, that it converges faster than the classical EM algorithm when the number of variance components is greater than two and all covariance matrices are positive definite. Supplementary materials for this article are available online.
DOI: 10.25582/data.2022-09.2612217/2286584
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2021-08.2304725/2286585
title: Data for EMSL Project 51834 from August 2021
DOI: 10.25582/data.2022-04.2479157/2286586
title: Data for EMSL Project 51834 from April 2022
DOI: 10.25582/data.2021-11.2387639/2286587
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2022-10.2617155/2286588
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2022-01.2417417/2286589
title: Data for EMSL Project 51834 from January 2022
DOI: 10.25582/data.2021-11.2388443/2286590
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2022-09.2608759/2286591
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2021-08.2305277/2286592
title: Data for EMSL Project 51834 from August 2021
DOI: 10.25582/data.2021-11.2387032/2286593
title: Data for EMSL Project 51834 from November 2021
DOI: 10.6084/m9.figshare.19450202
title: A new dipnoan genus from the Middle Devonian of Huize, Yunnan, China

description: A new genus and species of tooth-plated lungfishes, <i>Dianodipterus huizeensis</i> gen. et sp. nov., is described from the Qujing Formation (late Eifelian, Middle Devonian) of Huize County, Qujing, north-eastern Yunnan, China. It differs from other lungfishes in the small proportion of the tooth-bearing part on the pterygoid (less than one-quarter), the extensively developed anteromedial edentulous portion of the pterygoid, and tooth rows few in number (only four). Phylogenetic analysis reveals that <i>Dianodipterus</i> is more plesiomorphic than <i>Dipterus</i>, yet crownward of <i>Melanognathus</i>. As the ninth Devonian lungfish genus from China, the new taxon displays a novel schema of lungfish dentition and increases the diversity of early lungfishes. http://zoobank.org/urn:lsid:zoobank.org:pub:207B0E6E-EBBF-4E92-83F4-78FDAD6EBB60
DOI: 10.25582/data.2022-04.2479090/2286594
title: Data for EMSL Project 51834 from April 2022
DOI: 10.6084/m9.figshare.7915808.v1
title: MOESM2 of Reduced protocadherin17 expression in leukemia stem cells: the clinical and biological effect in acute myeloid leukemia

description: Additional file 2. List of 443 down-regulated probes/genes in LSCs versus normal HSCs.
DOI: 10.6084/m9.figshare.7915811
title: MOESM3 of Reduced protocadherin17 expression in leukemia stem cells: the clinical and biological effect in acute myeloid leukemia

description: Additional file 3. List of 863 hypermethylated CpGs in LSCs versus normal HSCs.
DOI: 10.25582/data.2021-11.2384661/2286595
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-10.2363330/2286596
title: Data for EMSL Project 51834 from October 2021
DOI: 10.6084/m9.figshare.7393220
title: Differentially Private Significance Tests for Regression Coefficients

description: Many data producers seek to provide users access to confidential data without unduly compromising data subjects’ privacy and confidentiality. One general strategy is to require users to do analyses without seeing the confidential data; for example, analysts only get access to synthetic data or query systems that provide disclosure-protected outputs of statistical models. With synthetic data or redacted outputs, the analyst never really knows how much to trust the resulting findings. In particular, if the user did the same analysis on the confidential data, would regression coefficients of interest be statistically significant or not? We present algorithms for assessing this question that satisfy differential privacy. We describe conditions under which the algorithms should give accurate answers about statistical significance. We illustrate the properties of the proposed methods using artificial and genuine data. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.7391597.v1
title: Photocontrol of helix handedness in curled liquid crystal elastomers

description: In this manuscript, we describe a photo-responsive dual-layer polysiloxane-based liquid crystal elastomer (LCE) soft actuator with switchable handedness of helical curling motions. Benefited from the embedded organic near-infrared (NIR) absorbing dye, the LCE ribbon can perform an impressive one-handed helical curling deformation under NIR light irradiation, meanwhile execute another-handed helical curling deformation under ultraviolet (UV) light irradiation due to the <i>trans-cis</i> isomerisation effect of azobenzene. This work demonstrates that the handedness of helical curling motions of LCE soft actuators can be reversibly altered by modulating the wavelength band of light stimuli (UV vs. NIR), which might have potential applications in control devices.
DOI: 10.6084/m9.figshare.7393220.v2
title: Differentially Private Significance Tests for Regression Coefficients

description: Many data producers seek to provide users access to confidential data without unduly compromising data subjects’ privacy and confidentiality. One general strategy is to require users to do analyses without seeing the confidential data; for example, analysts only get access to synthetic data or query systems that provide disclosure-protected outputs of statistical models. With synthetic data or redacted outputs, the analyst never really knows how much to trust the resulting findings. In particular, if the user did the same analysis on the confidential data, would regression coefficients of interest be statistically significant or not? We present algorithms for assessing this question that satisfy differential privacy. We describe conditions under which the algorithms should give accurate answers about statistical significance. We illustrate the properties of the proposed methods using artificial and genuine data. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.7393220.v1
title: Differentially Private Significance Tests for Regression Coefficients

description: Many data producers seek to provide users access to confidential data without unduly compromising data subjects’ privacy and confidentiality. One general strategy is to require users to do analyses without seeing the confidential data; for example, analysts only get access to synthetic data or query systems that provide disclosure-protected outputs of statistical models. With synthetic data or redacted outputs, the analyst never really knows how much to trust the resulting findings. In particular, if the user did the same analysis on the confidential data, would regression coefficients of interest be statistically significant or not? We present algorithms for assessing this question that satisfy differential privacy. We describe conditions under which the algorithms should give accurate answers about statistical significance. We illustrate the properties of the proposed methods using artificial and genuine data. Supplementary materials for this article are available online.
DOI: 10.25582/data.2021-09.2316500/2286597
title: Data for EMSL Project 51834 from September 2021
DOI: 10.6084/m9.figshare.13160447
title: Ascaris ovis mitochondrion, complete genome

description: The mitochondrial genome of Ascaris ovis from the sheep in Southwest China was determined using Illumina sequencing technology. The assembled genome was 14,205 bp in size and encoded 36 genes, including 12 protein-coding genes, 22 transfer RNA genes and two ribosomal RNA genes.
DOI: 10.25582/data.2021-11.2385069/2286598
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2022-10.2621253/2286599
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-11.2387751/2286600
title: Data for EMSL Project 51834 from November 2021
DOI: 10.25582/data.2021-09.2322555/2286601
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-08.2305238/2286602
title: Data for EMSL Project 51834 from August 2021
DOI: 10.25582/data.2022-01.2417466/2286603
title: Data for EMSL Project 51834 from January 2022
DOI: 10.25582/data.2021-09.2322392/2286604
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-10.2369610/2286605
title: Data for EMSL Project 51834 from October 2021
DOI: 10.25582/data.2022-10.2616483/2286606
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-09.2327600/2286607
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2022-09.2609664/2286608
title: Data for EMSL Project 51834 from September 2022
DOI: 10.25582/data.2021-09.2322449/2286609
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2022-10.2622331/2286610
title: Data for EMSL Project 51834 from October 2022
DOI: 10.25582/data.2021-09.2322373/2286611
title: Data for EMSL Project 51834 from September 2021
DOI: 10.25582/data.2021-09.2322379/2286612
title: Data for EMSL Project 51834 from September 2021