Integrative transcriptome analyses of the aging brain implicate altered splicing in Alzheimer’s disease susceptibility
Published version of a preprint
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
USP6NL adds to a growing list of genes (BIN1, PICALM, RABEP1, RIN3, and SORL1) that implicate dysfunction of the myeloid endolysosomal system in AD.
“USP6NL, a GTPase-activating protein involved in control of endocytosis, adds to a growing list of genes (BIN1, PICALM, RABEP1, RIN3, and SORL1) that implicate the dysfunction of the myeloid endolysosomal system in AD37,71.”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [37]
Upregulated genes in chronological aging showed overrepresentation for genes in AD or PD GWAS loci, but not for genes in SCZ or BD.
“The upregulated genes in chronological aging showed overrepresentation for genes in AD (e.g. MS4A6A, FCER1G, and CR1) or PD (e.g. BST1, PTPN22, and TNFSF13) GWAS loci, but not for genes in schizophrenia (SCZ) or bipolar disorder (BD) (Fig. 3d).”
From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [37]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709 · see citing works
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089 · see citing works
Self-citationMeta-Analysis of 74,046 Individuals Identifies 11 New Susceptibility Loci for Alzheimer’s Disease
(EADI), E. A. D. I., Lambert, J.-C., (GERAD), G. A. E. R. I. A. D., Alzheimer's Disease Genetic Consortium (ADGC), (CHARGE), C. F. H. A. A. R. I. G. E., Ibrahim-Verbaas, C. A., Harold, D., Naj, A. C., Sims, R., Bellenguez, C., et al. (2013) · Nature Genetics · doi:10.1038/ng.2802 · Cited by 4,336 · see citing works
Self-citationGenetic Investigation of ANthropometric Traits (GIANT) Consortium, Yang, J., DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Ferreira, T., Morris, A. P., Medland, S. E., Madden, P. A. F., Heath, A. C., Martin, N. G., Montgomery, G. W., et al. (2012) · Nature Genetics · doi:10.1038/ng.2213 · Cited by 1,712 · see citing works
Annotation-free quantification of RNA splicing using LeafCutter
Li, Y. I., Knowles, D. A., Humphrey, J., Barbeira, A. N., Dickinson, S. P., Im, H. K., & Pritchard, J. K. (2018) · Nature Genetics · doi:10.1038/s41588-017-0004-9 · Cited by 765 · see citing works
Self-citationGenome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism
Parikshak, N. N., Swarup, V., Belgard, T. G., Irimia, M., Ramaswami, G., Gandal, M. J., Hartl, C., Leppa, V., Ubieta, L. D. L. T., Huang, J., et al. (2016) · Nature · doi:10.1038/nature20612 · Cited by 685 · see citing works
Polarization of the Effects of Autoimmune and Neurodegenerative Risk Alleles in Leukocytes
Raj, T., Rothamel, K., Mostafavi, S., Ye, C., Lee, M. N., Replogle, J. M., Feng, T., Lee, M., Asinovski, N., Frohlich, I., et al. (2014) · Science · doi:10.1126/science.1249547 · Cited by 506 · see citing works
Self-citationU1 small nuclear ribonucleoprotein complex and RNA splicing alterations in Alzheimer’s disease
Bai, B., Hales, C. M., Chen, P.-C., Gozal, Y., Dammer, E. B., Fritz, J. J., Wang, X., Xia, Q., Duong, D. M., Street, C., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1310249110 · Cited by 335 · see citing works
Self-citationAnalysis of alternative splicing associated with aging and neurodegeneration in the human brain
Tollervey, J. R., Wang, Z., Hortobágyi, T., Witten, J. T., Zarnack, K., Kayikci, M., Clark, T. A., Schweitzer, A. C., Rot, G., Curk, T., et al. (2011) · Genome Research · doi:10.1101/gr.122226.111 · Cited by 252 · see citing works
Tian, Y., Chang, J. C., Fan, E. Y., Flajolet, M., & Greengard, P. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1315110110 · Cited by 233 · see citing works
Raj, T., Ryan, K. J., Replogle, J. M., Chibnik, L. B., Rosenkrantz, L., Tang, A., Rothamel, K., Stranger, B. E., Bennett, D. A., Evans, D. A., et al. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddt666 · Cited by 144 · see citing works
Selected Findings from the Religious Orders Study and Rush Memory and Aging Project
Bennett, D. A., Wilson, R. S., Arvanitakis, Z., Boyle, P. A., de Toledo-Morrell, L., & Schneider, J. A. (2012) · Journal of Alzheimer's Disease · doi:10.3233/jad-2012-129007 · Cited by 69 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 55
- [1]Wang ET Alternative isoform regulation in human tissue transcriptomes. Nature 456, 470– 6 (2008). 18978772 PMC2593745
- [2]Kornblihtt AR Alternative splicing: a pivotal step between eukaryotic transcription and translation. Nat Rev Mol Cell Biol 14, 153– 65 (2013). 23385723
- [3]Barbosa-Morais NL The evolutionary landscape of alternative splicing in vertebrate species. Science 338, 1587– 93 (2012). 23258890
- [4]Wang GS & Cooper TA Splicing in disease: disruption of the splicing code and the decoding machinery. Nat Rev Genet 8, 749– 61 (2007). 17726481
- [5]Dredge BK, Polydorides AD & Darnell RB The splice of life: alternative splicing and neurological disease. Nat Rev Neurosci 2, 43– 50 (2001). 11253358
- [7]Arai T TDP-43 is a component of ubiquitin-positive tau-negative inclusions in frontotemporal lobar degeneration and amyotrophic lateral sclerosis. Biochem Biophys Res Commun 351, 602– 11 (2006). 17084815
- [8]Trabzuni D MAPT expression and splicing is differentially regulated by brain region: relation to genotype and implication for tauopathies. Hum Mol Genet 21, 4094– 103 (2012). 22723018 PMC3428157
- [9]Rockenstein EM Levels and alternative splicing of amyloid beta protein precursor (APP) transcripts in brains of APP transgenic mice and humans with Alzheimer’s disease. J Biol Chem 270, 28257– 67 (1995). 7499323
- [10]Buee L, Bussiere T, Buee-Scherrer V, Delacourte A & Hof PR Tau protein isoforms, phosphorylation and role in neurodegenerative disorders. Brain Res Brain Res Rev 33, 95– 130 (2000). 10967355
- [11]Valenca GT The Role of MAPT Haplotype H2 and Isoform 1N/4R in Parkinsonism of Older Adults. PLoS One 11, e0157452 (2016). 27458716 PMC4961370
- [13]Vaquero-Garcia J A new view of transcriptome complexity and regulation through the lens of local splicing variations. Elife 5, e11752 (2016). 26829591 PMC4801060
- [17]Bennett DA, Schneider JA, Arvanitakis Z & Wilson RS Overview and findings from the religious orders study. Curr Alzheimer Res 9, 628– 45 (2012). 22471860 PMC3409291
- [19]Mostafavi S A molecular network of the aging human brain provides insights into the pathology and cognitive decline of Alzheimer’s disease. Nat Neurosci 21, 811– 819 (2018). 29802388 PMC6599633
- [21]Li YI RNA splicing is a primary link between genetic variation and disease. Science 352, 600– 4 (2016). 27126046 PMC5182069
- [23]Mitchelmore C NDRG2: a novel Alzheimer’s disease associated protein. Neurobiol Dis 16, 48– 58 (2004). 15207261
- [24]Zhang B & Horvath S A General Framework for Weighted Gene Co-Expression Network Analysis. Statistical Applications in Genetics and Molecular Biology 4, Article 17 (2005). 16646834
- [25]Wang M Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease. Genome Med 8, 104 (2016). 27799057 PMC5088659
- [26]Ongen H, Buil A, Brown AA, Dermitzakis ET & Delaneau O Fast and efficient QTL mapper for thousands of molecular phenotypes. Bioinformatics 32, 1479– 85 (2016). 26708335 PMC4866519
- [27]Bernstein BE The NIH Roadmap Epigenomics Mapping Consortium. Nat Biotechnol 28, 1045– 8 (2010). 20944595 PMC3607281
- [28]Fromer M Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat Neurosci 19, 1442– 1453 (2016). 27668389 PMC5083142
- [29]Ng B An xQTL map integrates the genetic architecture of the human brain’s transcriptome and epigenome. Nat Neurosci 20, 1418– 1426 (2017). 28869584 PMC5785926
- [30]Nicolae DL Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS. PLoS Genet 6, e1000888 (2010). 20369019 PMC2848547
- [31]Chen L Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells. Cell 167, 1398– 1414 e24 (2016). 27863251 PMC5119954
- [32]Malik M CD33 Alzheimer’s risk-altering polymorphism, CD33 expression, and exon 2 splicing. J Neurosci 33, 13320– 5 (2013). 23946390 PMC3742922
- [33]Sibley CR, Blazquez L & Ule J Lessons from non-canonical splicing. Nat Rev Genet 17, 407– 21 (2016). 27240813 PMC5154377
- [34]Yang YC CLIPdb: a CLIP-seq database for protein-RNA interactions. BMC Genomics 16, 51 (2015). 25652745 PMC4326514
- [35]Scheckel C Regulatory consequences of neuronal ELAV-like protein binding to coding and non-coding RNAs in human brain. Elife 5 (2016). PMC4798961 26894958
- [36]Borreca A, Gironi K, Amadoro G & Ammassari-Teule M Opposite Dysregulation of Fragile-X Mental Retardation Protein and Heteronuclear Ribonucleoprotein C Protein Associates with Enhanced APP Translation in Alzheimer Disease. Mol Neurobiol 53, 3227– 3234 (2016). 26048669
- [37]Gusev A Integrative approaches for large-scale transcriptome-wide association studies. Nat Genet 48, 245– 52 (2016). 26854917 PMC4767558
- [38]Seyfried NT A Multi-network Approach Identifies Protein-Specific Co-expression in Asymptomatic and Symptomatic Alzheimer’s Disease. Cell Syst 4, 60– 72 e4 (2017). 27989508 PMC5269514
- [39]Liu JZ, Erlich Y & Pickrell JK Case-control association mapping by proxy using family history of disease. Nat Genet 49, 325– 331 (2017). 28092683
- [40]Gusev A Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights. Nat Genet 50, 538– 548 (2018). 29632383 PMC5942893
- [42]Li T GeNets: a unified web platform for network-based genomic analyses. Nat Methods 15, 543– 546 (2018). 29915188 PMC6450090
- [43]Raj T Alzheimer disease susceptibility loci: evidence for a protein network under natural selection. Am J Hum Genet 90, 720– 6 (2012). 22482808 PMC3322230
- [44]Nixon RA New perspectives on lysosomes in ageing and neurodegenerative disease. Ageing Res Rev 32, 1 (2016). 27894596
- [45]Emmett MJ Histone deacetylase 3 prepares brown adipose tissue for acute thermogenic challenge. Nature 546, 544– 548 (2017). 28614293 PMC5826652
- [47]Ingelsson M Early Abeta accumulation and progressive synaptic loss, gliosis, and tangle formation in AD brain. Neurology 62, 925– 31 (2004). 15037694
- [48]Guillozet AL, Weintraub S, Mash DC & Mesulam MM Neurofibrillary tangles, amyloid, and memory in aging and mild cognitive impairment. Arch Neurol 60, 729– 36 (2003). 12756137
- [49]Consortium GT Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348, 648– 60 (2015). 25954001 PMC4547484
- [50]Fairfax BP Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression. Science 343, 1246949 (2014). 24604202 PMC4064786
- [51]Bennett DA Overview and findings from the rush Memory and Aging Project. Curr Alzheimer Res 9, 646– 63 (2012). 22471867 PMC3439198
- [53]Patterson N, Price AL & Reich D Population structure and eigenanalysis. PLoS Genet 2, e190 (2006). 17194218 PMC1713260
- [54]Das S Next-generation genotype imputation service and methods. Nat Genet 48, 1284– 7 (2016). 27571263 PMC5157836
- [55]McCarthy S A reference panel of 64,976 haplotypes for genotype imputation. Nat Genet 48, 1279– 83 (2016). 27548312 PMC5388176
- [57]Li B & Dewey CN RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12, 323 (2011). 21816040 PMC3163565
- [58]Johnson WE, Li C & Rabinovic A Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8, 118– 27 (2007). 16632515
- [59]Hoffman GE & Schadt EE variancePartition: interpreting drivers of variation in complex gene expression studies. BMC Bioinformatics 17, 483 (2016). 27884101 PMC5123296
- [60]van de Geijn B, McVicker G, Gilad Y & Pritchard JK WASP: allele-specific software for robust molecular quantitative trait locus discovery. Nat Methods 12, 1061– 3 (2015). 26366987 PMC4626402
- [61]Degner JF DNase I sensitivity QTLs are a major determinant of human expression variation. Nature 482, 390– 4 (2012). 22307276 PMC3501342
- [62]Yang J, Lee SH, Goddard ME & Visscher PM GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet 88, 76– 82 (2011). 21167468 PMC3014363
- [63]Storey JD & Tibshirani R Statistical significance for genomewide studies. Proc Natl Acad Sci U S A 100, 9440– 5 (2003). 12883005 PMC170937
- [64]Nica AC The architecture of gene regulatory variation across multiple human tissues: the MuTHER study. PLoS Genet 7, e1002003 (2011). 21304890 PMC3033383
- [65]Giulietti M SpliceAid-F: a database of human splicing factors and their RNA-binding sites. Nucleic Acids Res 41, D125– 31 (2013). 23118479 PMC3531144
- [66]Schmidt EM GREGOR: evaluating global enrichment of trait-associated variants in epigenomic features using a systematic, data-driven approach. Bioinformatics 31, 2601– 6 (2015). 25886982 PMC4612390
- [67]Lage K A human phenome-interactome network of protein complexes implicated in genetic disorders. Nat Biotechnol 25, 309– 16 (2007). 17344885
Cited by
Sorted by citations
Grubman, A., Chew, G., Ouyang, J. F., Sun, G., Choo, X. Y., McLean, C., Simmons, R. K., Buckberry, S., Vargas-Landin, D. B., Poppe, D., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0539-4 · Cited by 956 · see citing works
Schwartzentruber, J., Cooper, S., Liu, J. Z., Barrio-Hernandez, I., Bello, E., Kumasaka, N., Young, A. M. H., Franklin, R. J. M., Johnson, T., Estrada, K., et al. (2021) · Nature Genetics · doi:10.1038/s41588-020-00776-w · Cited by 532 · see citing works
Dube, U., Del-Aguila, J. L., Li, Z., Budde, J. P., Jiang, S., Hsu, S., Ibanez, L., Fernandez, M. V., Farias, F., Norton, J., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0501-5 · Cited by 345 · see citing works
Machine learning identifies candidates for drug repurposing in Alzheimer’s disease
Rodriguez, S., Hug, C., Todorov, P., Moret, N., Boswell, S. A., Evans, K., Zhou, G., Johnson, N. T., Hyman, B. T., Sorger, P. K., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21330-0 · Cited by 299 · see citing works
Lopes, K. D. P., Snijders, G. J. L., Humphrey, J., Allan, A., Sneeboer, M. A. M., Navarro, E., Schilder, B. M., Vialle, R. A., Parks, M., Missall, R., et al. (2022) · Nature Genetics · doi:10.1038/s41588-021-00976-y · Cited by 273 · see citing works
Self-citationde Klein, N., Tsai, E. A., Vochteloo, M., Baird, D., Huang, Y., Chen, C.-Y., van Dam, S., Oelen, R., Deelen, P., Bakker, O. B., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01300-6 · Cited by 272 · see citing works
Novikova, G., Kapoor, M., TCW, J., Abud, E. M., Efthymiou, A. G., Chen, S. X., Cheng, H., Fullard, J. F., Bendl, J., Liu, Y., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21823-y · Cited by 214 · see citing works
Johnson, E. C. B., Dammer, E. B., Duong, D. M., Yin, L., Thambisetty, M., Troncoso, J. C., Lah, J. J., Levey, A. I., & Seyfried, N. T. (2018) · Molecular Neurodegeneration · doi:10.1186/s13024-018-0282-4 · Cited by 225 · see citing works
Endo-lysosomal dysregulations and late-onset Alzheimer’s disease: impact of genetic risk factors
Van Acker, Z. P., Bretou, M., & Annaert, W. (2019) · Molecular Neurodegeneration · doi:10.1186/s13024-019-0323-7 · Cited by 222 · see citing works
Tau Protein Interaction Partners and Their Roles in Alzheimer’s Disease and Other Tauopathies
Sinsky, J., Pichlerova, K., & Hanes, J. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22179207 · Cited by 220 · see citing works
Hsieh, Y.-C., Guo, C., Yalamanchili, H. K., Abreha, M., Al-Ouran, R., Li, Y., Dammer, E. B., Lah, J. J., Levey, A. I., Bennett, D. A., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.08.104 · Cited by 196 · see citing works
Self-citationPICALM and Alzheimer’s Disease: An Update and Perspectives
Ando, K., Nagaraj, S., Küçükali, F., de Fisenne, M.-A., Kosa, A.-C., Doeraene, E., Lopez Gutierrez, L., Brion, J.-P., & Leroy, K. (2022) · Cells · doi:10.3390/cells11243994 · Cited by 104 · see citing works
Bishof, I., Dammer, E. B., Duong, D. M., Kundinger, S. R., Gearing, M., Lah, J. J., Levey, A. I., & Seyfried, N. T. (2018) · Journal of Biological Chemistry · doi:10.1074/jbc.ra118.001747 · Cited by 80 · see citing works
Identification of Conserved Proteomic Networks in Neurodegenerative Dementia
Swarup, V., Chang, T. S., Duong, D. M., Dammer, E. B., Dai, J., Lah, J. J., Johnson, E. C. B., Seyfried, N. T., Levey, A. I., & Geschwind, D. H. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107807 · Cited by 78 · see citing works
Identification of conserved proteomic networks in neurodegenerative dementia
Swarup, V., Chang, T. S., Duong, D. M., Dammer, E. B., Lah, J. J., Johnson, E. E. C. B., Seyfried, N. T., Levey, A. I., & Geschwind, D. H. (2019) · doi:10.1101/825802 · Cited by 78 · see citing works
The three-dimensional landscape of cortical chromatin accessibility in Alzheimer’s disease
Bendl, J., Hauberg, M. E., Girdhar, K., Im, E., Vicari, J. M., Rahman, S., Fernando, M. B., Townsley, K. G., Dong, P., Misir, R., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01166-7 · Cited by 65 · see citing works
PICALM Alzheimer’s risk allele causes aberrant lipid droplets in microglia
Kozlova, A., Zhang, S., Sudwarts, A., Zhang, H., Smirnou, S., Byeon, S. K., Thapa, C., Sun, X., Stephenson, K., Zhao, X., et al. (2025) · Nature · doi:10.1038/s41586-025-09486-x · Cited by 53 · see citing works
Self-citationGenetics of Gene Expression in the Aging Human Brain Reveal TDP-43 Proteinopathy Pathophysiology
Yang, H.-S., White, C. C., Klein, H.-U., Yu, L., Gaiteri, C., Ma, Y., Felsky, D., Mostafavi, S., Petyuk, V. A., Sperling, R. A., et al. (2020) · Neuron · doi:10.1016/j.neuron.2020.05.010 · Cited by 47 · see citing works
Self-citationNovikova, G., Kapoor, M., TCW, J., Abud, E. M., Efthymiou, A. G., Cheng, H., Fullard, J. F., Bendl, J., Roussos, P., Poon, W. W., et al. (2019) · doi:10.1101/694281 · Cited by 27 · see citing works
Lutz, B. M., & Peng, J. (2018) · Proteomes · doi:10.3390/proteomes6040046 · Cited by 27 · see citing works
Jaye, S., Sandau, U. S., & Saugstad, J. A. (2024) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2024.1378576 · Cited by 26 · see citing works
Zhu, Q., Niu, Y., Gundry, M., & Zong, C. (2021) · Science Advances · doi:10.1126/sciadv.abf3329 · Cited by 18 · see citing works
Lu, L., Kotowska, A. M., Kern, S., Fang, M., Rudd, T. R., Alexander, M. R., Scurr, D. J., & Zhu, Z. (2024) · Analytical Chemistry · doi:10.1021/acs.analchem.4c01201 · Cited by 15 · see citing works
Comprehensive characterization of the transcriptional landscape in Alzheimer’s disease (AD) brains
Chen, C., Zhang, Z., Liu, Y., Hong, W., Karahan, H., Wang, J., Li, W., Diao, L., Yu, M., Saykin, A. J., et al. (2025) · Science Advances · doi:10.1126/sciadv.adn1927 · Cited by 6 · see citing works
“…highlighted specific molecular pathways, gene expression networks, and alternative splicing events associated with AD pathology ( 8 – 12 ), providing insights into molecular mechanisms of selective regional vulnerability ( 8 ) and associated AD susceptibility loci to specific genes ( 9 , 11 , 12 ).”
- Authors
- Raj, T., Li, Y. I., Wong, G., Humphrey, J., Wang, M., Ramdhani, S., Wang, Y.-C., Ng, B., Gupta, I., Haroutunian, V., Schadt, E. E., Young-Pearse, T., Mostafavi, S., Zhang, B., Sklar, P., Bennett, D. A., & De Jager, P. L.
- ORCID
- Venue
- Nature Genetics
- Published
- 2018-10-08
- Volume
- 50
- Issue
- 11
- Pages
- 1584-1592
- ISSN
- 1061-4036
- 1546-1718
- PMC
- PMC6354244
- Cited by
- 430
- References
- 12
- Language
- en
- Licence
- www.springer.com/tdm (tdm)
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review