cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2ppj64
title: CCDC 2493336: Experimental Crystal Structure Determination

description: Related Article: Yun-hou Huang, Yuan Liu, Yue Huang, Wei-ying Meng, Hong-zu Wei, Chang-chun Wen, Li-min Liu, Yan-cheng Liu|2026|J.Inorg.Biochem.|277||doi:10.1016/j.jinorgbio.2026.113228
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ppj86
title: CCDC 2493338: Experimental Crystal Structure Determination

description: Related Article: Yun-hou Huang, Yuan Liu, Yue Huang, Wei-ying Meng, Hong-zu Wei, Chang-chun Wen, Li-min Liu, Yan-cheng Liu|2026|J.Inorg.Biochem.|277||doi:10.1016/j.jinorgbio.2026.113228
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2pql45
title: CCDC 2494357: Experimental Crystal Structure Determination

description: Related Article: Yuxin Guo, Hanru Tang, Zhiyan Liu, Zhiping Wang, Long-Yong Xie, Jian Wen|2026|Org.Chem.Front.|||doi:10.1039/d5qo01607j
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2prm03
title: CCDC 2495345: Experimental Crystal Structure Determination

description: Related Article: Aparna V M, Vidya L, Neelima S, Aparna Raj, Vandana S, G Anilkumar, Anabha E R, C Sudarsanakumar|2026|J.Mol.Struct.|1358||doi:10.1016/j.molstruc.2026.145329
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2prtcn
title: CCDC 2495542: Experimental Crystal Structure Determination

description: Related Article: Saumya Kumar Gupta, Ravichandran Khazeber, Kumar S. Siddharth, Anushka Balakrishnan, Kana M. Sureshan|2025|J.Am.Chem.Soc.|||doi:10.1021/jacs.5c18292
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2pslqt
title: CCDC 2496297: Experimental Crystal Structure Determination

description: Related Article: Mohd Arbaz Tyagi, Mohd Mustaqeem, Kanishka Kashyap, Md. Najbul Hoque, Bhaskar Nath, Jehova Jire L. Hmar, Jugal Bori|2026|J.Mol.Struct.|1358||doi:10.1016/j.molstruc.2026.145353
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ptbwr
title: CCDC 2497015: Experimental Crystal Structure Determination

description: Related Article: Akshay Suresh Kshirsagar, Pei-Qin Liao, Tzuhsiung Yang, Rai-Shung Liu|2026|Org.Lett.|||doi:10.1021/acs.orglett.5c05132
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5061/dryad.sm847
title: Data from: A dataset quantifying polypharmacy in the United States

description: Polypharmacy is increasingly common in the United States, and contributes
 to the substantial burden of drug-related morbidity. Yet real-world
 polypharmacy patterns remain poorly characterized. We have counted the
 incidence of multi-drug combinations observed in four billion
 patient-months of outpatient prescription drug claims from 2007-2014 in
 the Truven Health MarketScan® Databases. Prescriptions are grouped into
 discrete windows of concomitant drug exposure, which are used to count
 exposure incidences for combinations of up to five drug ingredients or ATC
 drug classes. Among patients taking any prescription drug, half are
 exposed to two or more drugs, and 5% are exposed to 8 or more. The most
 common multi-drug combinations treat manifestations of metabolic syndrome.
 Patients are exposed to unique drug combinations in 10% of all exposure
 windows. Our analysis of multi-drug exposure incidences provides a
 detailed summary of polypharmacy in a large US cohort, which can
 prioritize common drug combinations for future safety and efficacy
 studies.
description: Data Record 1: Drug
 ingredient combinations: 1-drugdb_drugs_1s.tsvData Record 1: Drug ingredient combinations: 2-drugsSee README.txt for Data Record 1: 1-drugdb_drugs_2s.tsvData Record 1: Drug ingredient combinations: 3-drugsSee README.txt for Data Record 1: 1-drugdb_drugs_3s.tsvData Record 1: Drug ingredient combinations: 4-drugsSee README.txt for Data Record 1: 1-drugdb_drugs_4s.tsvData Record 1: Drug ingredient combinations: 5-drugsSee README.txt for Data Record 1: 1-drugdb_drugs_5s.tsvData Record 2: Drug class combinations: 1-drugSee README.txt for Data Record 1: 1-drugdb_atc_classes_1s.tsvData Record 2: Drug class combinations: 2-drugsSee README.txt for Data Record 1: 1-drugdb_atc_classes_2s.tsvData Record 2: Drug class combinations: 3-drugsSee README.txt for Data Record 1: 1-drugdb_atc_classes_3s.tsvData Record 2: Drug class combinations: 4-drugsSee README.txt for Data Record 1: 1-drugdb_atc_classes_4s.tsvData Record 2: Drug class combinations: 5-drugsSee README.txt for Data Record 1: 1-drugdb_atc_classes_5s.tsvData Record 3: Drug ingredient mappingSee README.txt for Data Record 1: 1-drugdrug_mapping_ingredients.tsvData Record 3: Drug class mappingSee README.txt for Data Record 1: 1-drugdrug_mapping_atc_classes.tsv
DOI: 10.5061/dryad.hj07m
title: Data from: Variation across mitochondrial gene trees provides evidence for systematic error: how much gene tree variation is biological?

description: The use of large genomic datasets in phylogenetics has highlighted
 extensive topological variation across genes. Much of this discordance is
 assumed to result from biological processes. However, variation among gene
 trees can also be a consequence of systematic error driven by poor model
 fit, and the relative importance of biological versus methodological
 factors in explaining gene tree variation is a major unresolved question.
 Using mitochondrial genomes to control for biological causes of gene tree
 variation, we estimate the extent of gene tree discordance driven by
 systematic error and employ posterior prediction to highlight the role of
 model fit in producing this discordance. We find that the amount of
 discordance among mitochondrial gene trees is similar to the amount of
 discordance found in other studies that assume only biological causes of
 variation. This similarity suggests that the role of systematic error in
 generating gene tree variation is underappreciated and critical evaluation
 of fit between assumed models and the data used for inference is important
 for the resolution of unresolved phylogenetic questions.
description: Linear regression
 between PPES and gene-to-reference tree
 incompatibilitiesFiles with the PPES and
 number of incompatibilities to reference tree for each gene in a given
 dataset, alongside an r script that performs linear regression between
 PPES and incompatibilities and makes barplot in Figure
 495_ref_incompatibilities_ppes_r2.zipCorrelations among test statistic PPES rankingsFiles with the ranks of genes based on test statistic PPES and r scripts for generating a null distribution of ranks between pairwise comparisons of the test statistics to calculate the spearman's rank correlation coefficient between any two test statisticsTest_Stat_Rank_Corr.zipGene-to-reference-tree incompatibilities tree filesFiles of reduced 95% consensus trees used to calculate incompatibilities with reference trees and csv files of the number of incompatibilities between gene trees and references trees.gene_to_reference_incompatibilities.zipSummary TreesMajority rule, 95% consensus, and MCC summary tree filesTreescaper input filesNexus files that contain 250 trees from the posterior distribution of each gene for a given dataset. These files are uploaded into Treescaper to calculate RF distances and NLDR plots.Treescaper_input_files.zipPython script to calculate X2 data-based test statisticPython script to call the function in P4 phylogenetics python package that calculates the X2 data-based test statisticchitest.pyPPES_calculationExample python scripts to calculation PPES from the test statistics calculated using the programs PuMA, AMP, and the chitest.py script.Supplementary MaterialsRichards_et_al_2018_supplementary.docxAlignmentsZipped folder of all nexus files for mitochondrial gene alignments used in the studynexus_alignment_files.tar.gz
DOI: 10.5061/dryad.jc203
title: Data from: "Transcriptomic resources for Hazelnut tree (Corylus avellana L.)" in Genomic Resources Notes Accepted 1 August 2015 to 31 September 2015

description: This article documents the public availability of transcriptome sequence
 data, assembled contigs, annotated contigs and molecular markers for
 Hazelnut tree (Corylus avellana).
description: Functionally annotated
 Corylus assemblyThis file lists all
 13,690 Coryllus avellana contigs with their annotation. We considered, for
 each contig (col 1), the best blast hit found in the Swissprot database
 (col2) and in the Non-redundant nucleotide database (col3). We associated
 to these contigs GO terms. GO terms IDs are listed in col4 and GO terms
 definition is listed in col 5 (MF: Molecular function; CC: Cellular
 component; BP: Biological process).corylus_assembly_with_ALL_funcat_final.txtCorylus avellana CAV2 transcriptomic assemblyIn this file, the 13,690 CAV2 contigs sequences are listed in fasta format.corylus_CLCBIO_meta_assembly_cdhitest_0.95.fastaC. avellana root and ECM-root sequences with T. melanosporum similarityRoot ("Root_" prefix) and ECM-roots ("ECM_Roots_" prefix) sequences (col 1) showing similarities with the Tuber melanosporum genome are listed in this file. Each Corylus read is associated with at least one T. melanosporum scaffold (col2).Hazel_Root_ECM_454reads_with_Tuber_hits.csvMapping of the Corylus avellana input sequences against the CAV2 assembly.Alignments of the 836,641 Corylus avellana Roche sequences against the 13,690 CAV2 contigs in bam format.mapping_all_454_renamed_on_CLCBIO_assembly.bam
DOI: 10.5061/dryad.r1hk5
title: Data from: Diversification rates have declined in the Malagasy herpetofauna

description: The evolutionary origins of Madagascar's biodiversity remain
 mysterious despite the fact that relative to land area, there is no other
 place with consistently high levels of species richness and endemism
 across a range of taxonomic levels. Most efforts to explain
 diversification on the island have focused on geographical models of
 speciation, but recent studies have begun to address the island's
 accumulation of species through time, although with conflicting results.
 Prevailing hypotheses for diversification on the island involve either
 constant diversification rates or scenarios where rates decline through
 time. Using relative-time-calibrated phylogenies for seven endemic
 vertebrate clades and a model-fitting framework, I find evidence that
 diversification rates have declined through time on Madagascar. I show
 that diversification rates have clearly declined throughout the history of
 each clade, and models invoking diversity-dependent reductions to
 diversification rates best explain the diversification histories for each
 clade. These results are consistent with the ecological theory of adaptive
 radiation, and, coupled with ancillary observations about ecomorphological
 and life-history evolution, strongly suggest that adaptive radiation was
 an important formative process for one of the most species-rich regions on
 the Earth. These results cast the Malagasy biota in a new light and
 provide macroevolutionary justification for conservation initiatives.
description: MCC and Posterior Trees
 - output from BEASTThis compressed file
 contains the posterior distribution of trees as well as the MCC tree (with
 mean node heights) for each clade.rawtrees.zipTrees pruned of extraneous taxa for diversification analysesThese are the MCC and posterior trees of each clade that have been pruned of inappropriate taxa for the diversification analyses. Pruned tips are not from Madagascar, are intraspecific samples, and/or are not valid species.droptip_trees.zipModel fitting results and summariesThis file contains the results of the HMM model fits for each clade. Each clade was analyzed at two levels of taxonomic sampling completeness - 100% and 50%. Thus, the files that include "_1_Complete" or "_0.5_Complete" refer to 100% or 50% complete respectively. The files with "AnalyzedTrees" in their names are the randomly selected trees from the posterior distributions that were analyzed. Note that in producing these lists, the MCC tree was placed on top of all posterior trees. Thus, the first row in all refers to the MCC tree (1), and the remaining 49 rows are the number of the randomly selected posterior tree plus 1.modelstats.zipR code and functions to run this analysisThis contains relevant functions and the code I used to collect these data. See the README within for more details.Rcode.zip
DOI: 10.5061/dryad.8v0v6
title: Data from: Comparative transcriptome atlases reveal altered gene expression modules between two Cleomaceae C3 and C4 plant species

description: C4 photosynthesis outperforms the ancestral C3 state in a wide range of
 natural and agro-ecosystems by affording higher water-use and nitrogen-use
 efficiencies. It therefore represents a prime target for engineering
 novel, high-yielding crops by introducing the trait into C3 backgrounds.
 However, the genetic architecture of C4 photosynthesis remains largely
 unknown. To define the divergence in gene expression modules between C3
 and C4 photosynthesis during leaf ontogeny, we generated comprehensive
 transcriptome atlases of two Cleomaceae species, Gynandropsis gynandra
 (C4) and Tarenaya hassleriana (C3), by RNA sequencing. Overall, the gene
 expression profiles appear remarkably similar between the C3 and C4
 species. We found that known C4 genes were recruited to photosynthesis
 from different expression domains in C3, including typical housekeeping
 gene expression patterns in various tissues as well as individual
 heterotrophic tissues. Furthermore, we identified a structure-related
 module recruited from the C3 root. Comparison of gene expression patterns
 with anatomy during leaf ontogeny provided insight into genetic features
 of Kranz anatomy. Altered expression of developmental factors and cell
 cycle genes is associated with a higher degree of endoreduplication in
 enlarged C4 bundle sheath cells. A delay in mesophyll differentiation
 apparent both in the leaf anatomy and the transcriptome allows for
 extended vein formation in the C4 leaf.
description: Supplemental Datasets C3
 vs C4 Cleomaceae transcriptome atlasesTranscriptome atlases
 from two Cleomaceae species and down-stream analyses. Reads generated on
 the HISEQ2000 Illumina platform, and mapped with BLAT
 V35.Supplemental_Datasets_Kuelahoglu2014.xlsx
DOI: 10.5281/zenodo.18381201
title: VITAMIN B12 IN ENERGY METABOLISM AND ITS ASSOCIATION WITH BODY WEIGHT

description: Vitamin B12 (cobalamin) is an important water-soluble micronutrient that serves as one of the key inputs for cellular metabolism, especially DNA synthesis, methylation, and mitochondrial function. Its function spreads to fundamental energy production pathways by serving predominantly as a co-factor with two important mammalian enzymes such as methionine synthase (MTR) and methylmalonyl-CoA mutase (MMUT). The MMUT-catalyzed reaction bridges catabolism of certain amino acids and odd-chain fatty acids to the tricarboxylic acid (TCA) cycle, a cellular energy production-evolving center. The MTR reaction is essential for the methionine cycle and global methylation during nucleotide synthesis. These essential functions have led to heightened interest in the association of vitamin B12 in metabolic health and, as such, body weight control. Serum B12 levels consistently have an inverse association with body mass index (BMI), with lower reported levels reported in individuals with obesity. It remains uncertain, though, whether low levels of B12 in the body promote weight gain or if obesity-related factors lead to lower B12 levels. This review summarizes the biochemical status of vitamin B12, discuss its unique roles within energy metabolism, and review the evidence from human studies relating B12 status and body weight. We assess possible mechanisms of action like lipid metabolism, insulin resistance, or mitochondrial performance, but we emphasize that research to date is limited and B12 itself should not be regarded as an actual weight-losing agent. Grasping this nuanced interplay will be particularly important for students of the biochemistry and the medicine disciplines who wish to link micro-nutrient status with metabolic health on a systemic level.
DOI: 10.5281/zenodo.18381202
title: VITAMIN B12 IN ENERGY METABOLISM AND ITS ASSOCIATION WITH BODY WEIGHT

description: Vitamin B12 (cobalamin) is an important water-soluble micronutrient that serves as one of the key inputs for cellular metabolism, especially DNA synthesis, methylation, and mitochondrial function. Its function spreads to fundamental energy production pathways by serving predominantly as a co-factor with two important mammalian enzymes such as methionine synthase (MTR) and methylmalonyl-CoA mutase (MMUT). The MMUT-catalyzed reaction bridges catabolism of certain amino acids and odd-chain fatty acids to the tricarboxylic acid (TCA) cycle, a cellular energy production-evolving center. The MTR reaction is essential for the methionine cycle and global methylation during nucleotide synthesis. These essential functions have led to heightened interest in the association of vitamin B12 in metabolic health and, as such, body weight control. Serum B12 levels consistently have an inverse association with body mass index (BMI), with lower reported levels reported in individuals with obesity. It remains uncertain, though, whether low levels of B12 in the body promote weight gain or if obesity-related factors lead to lower B12 levels. This review summarizes the biochemical status of vitamin B12, discuss its unique roles within energy metabolism, and review the evidence from human studies relating B12 status and body weight. We assess possible mechanisms of action like lipid metabolism, insulin resistance, or mitochondrial performance, but we emphasize that research to date is limited and B12 itself should not be regarded as an actual weight-losing agent. Grasping this nuanced interplay will be particularly important for students of the biochemistry and the medicine disciplines who wish to link micro-nutrient status with metabolic health on a systemic level.
DOI: 10.5061/dryad.m5g7d
title: Data from: Using trait and phylogenetic diversity to evaluate the generality of the stress-dominance hypothesis in eastern North American tree communities

description: The stress-dominance hypothesis (SDH) is a model of community assembly
 predicting that the relative importance of environmental filtering
 increases and competition decreases along a gradient of increasing
 environmental stress. Tests of the SDH at limited spatial scales have thus
 far demonstrated equivocal support and no prior study has assessed the
 generality of the SDH at continental scales. We examined over 53 000 tree
 communities spanning the eastern United States to determine whether
 functional trait variation and phylogenetic diversity support the SDH for
 gradients of water and soil nutrient availability. This analysis
 incorporated two complementary datasets, those of the U.S. Forest Service
 Forest Inventory and Analysis National program and the Carolina Vegetation
 Survey, and was based on three ecologically important traits: leaf
 nitrogen, seed mass, and wood density. We found that mean trait values
 were weakly correlated with water and soil nutrient availability, but that
 trait diversity did not vary consistently along either gradient. This did
 not conform to trait variation expected under the SDH and instead
 suggested that environmental filters structure tree communities throughout
 both gradients, without evidence for an increased role of competition in
 less stressful environments. Phylogenetic diversity of communities was
 principally driven by the ratio of angiosperms to gymnosperms and
 therefore did not exhibit the pattern of variation along stress gradients
 expected under the SDH. We conclude that the SDH is not a general paradigm
 for all eastern North American tree communities, although it may operate
 in certain contexts.
description: FIA_data_derivedFIA plots: species richness, commmunity mean trait values and trait diversity (seed mass, leaf nitrogen content, wood density), phylogenetic diversity, water deficit, soil nutrient availability, and geographic coordinates.CVS_data_derivedCommunity and environmental data for CVS plots.FIA_siteXsp_matrixTree species abundance matrix for FIA plots.CVS_siteXsp_matrixTree species abundance matrix for CVS plots.CVS_phylogenyPhylogenetic tree of taxa in CVS plots.FIA_phylogenyPhylogenetic tree of taxa in FIA plots.READMEDescribes files included in this data package.