Mattias Rantalainen

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Publikationer
CV
Populärvetenskap och samverkan

Om mig

Please go to my English profile page to read more about my research.

Artiklar

Journal article: BMC CANCER. 2024;24(1):1510
Prediction of gene expression-based breast cancer proliferation scores from histopathology whole slide images using deep learning.
Ekholm A; Wang Y; Vallon-Christersson J; Boissin C; Rantalainen M
Journal article: MEDICAL IMAGE ANALYSIS. 2024;97:103257
The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue.
Weitz P; Valkonen M; Solorzano L; Carr C; Kartasalo K; Boissin C; Koivukoski S; Kuusela A; Rasic D; Feng Y; Pouplier SS; Sharma A; Eriksson KL; Robertson S; Marzahl C; Gatenbee CD; Anderson ARA; Wodzinski M; Jurgas A; Marini N; Atzori M; Müller H; Budelmann D; Weiss N; Heldmann S; Lotz J; Wolterink JM; De Santi B; Patil A; Sethi A; Kondo S; Kasai S; Hirasawa K; Farrokh M; Kumar N; Greiner R; Latonen L; Laenkholm A-V; Hartman J; Ruusuvuori P; Rantalainen M
Journal article: BREAST CANCER RESEARCH. 2024;26(1):123
Validation of an AI-based solution for breast cancer risk stratification using routine digital histopathology images
Sharma A; Lovgren SK; Eriksson KL; Wang Y; Robertson S; Hartman J; Rantalainen M
Article: BREAST CANCER RESEARCH AND TREATMENT. 2024;206(1):163-175
Clinical evaluation of deep learning-based risk profiling in breast cancer histopathology and comparison to an established multigene assay
Wang Y; Sun W; Karlsson E; Lovgren SK; Acs B; Rantalainen M; Robertson S; Hartman J
Journal article: BREAST CANCER RESEARCH. 2024;26(1):90
Deep learning-based risk stratification of preoperative breast biopsies using digital whole slide images
Boissin C; Wang Y; Sharma A; Weitz P; Karlsson E; Robertson S; Hartman J; Rantalainen M
Article: BREAST CANCER RESEARCH. 2024;26(1):17
Development and prognostic validation of a three-level NHG-like deep learning-based model for histological grading of breast cancer
Sharma A; Weitz P; Wang Y; Liu B; Vallon-Christersson J; Hartman J; Rantalainen M
Article: EUROPEAN JOURNAL OF CANCER. 2023;191:112953
Transcriptional intra-tumour heterogeneity predicted by deep learning in routine breast histopathology slides provides independent prognostic information
Wang Y; Ali MA; Vallon-Christersson J; Humphreys K; Hartman J; Rantalainen M
Article: SCIENTIFIC DATA. 2023;10(1):562
A Multi-Stain Breast Cancer Histological Whole-Slide-Image Data Set from Routine Diagnostics
Weitz P; Valkonen M; Solorzano L; Carr C; Kartasalo K; Boissin C; Koivukoski S; Kuusela A; Rasic D; Feng Y; Pouplier SS; Sharma A; Eriksson KL; Latonen L; Laenkholm A-V; Hartman J; Ruusuvuori P; Rantalainen M
Article: NPJ PRECISION ONCOLOGY. 2023;7(1):32
Prediction model for drug response of acute myeloid leukemia patients
Trac QT; Pawitan Y; Mou T; Erkers T; Ostling P; Bohlin A; Osterroos A; Vesterlund M; Jafari R; Siavelis I; Backvall H; Kiviluoto S; Orre LM; Rantalainen M; Lehtio J; Lehmann S; Kallioniemi O; Vu TN
Article: ISCIENCE. 2022;25(7):104663
Using deep learning to detect patients at risk for prostate cancer despite benign biopsies
Liu B; Wang Y; Weitz P; Lindberg J; Hartman J; Wang W; Egevad L; Gronberg H; Eklund M; Rantalainen M
Article: BIOINFORMATICS. 2022;38(13):3462-3469
Transcriptome-wide prediction of prostate cancer gene expression from histopathology images using co-expression-based convolutional neural networks
Weitz P; Wang Y; Kartasalo K; Egevad L; Lindberg J; Gronberg H; Eklund M; Rantalainen M
Article: ANNALS OF ONCOLOGY. 2022;33(1):89-98
Improved breast cancer histological grading using deep learning
Wang Y; Acs B; Robertson S; Liu B; Solorzano L; Wahlby C; Hartman J; Rantalainen M
Article: CANCER RESEARCH. 2021;81(19):5115-5126
Predicting Molecular Phenotypes from Histopathology Images: A Transcriptome-Wide Expression-Morphology Analysis in Breast Cancer
Wang Y; Kartasalo K; Weitz P; Acs B; Valkonen M; Larsson C; Ruusuvuori P; Hartman J; Rantalainen M
Article: BLOOD ADVANCES. 2021;5(4):1003-1016
Challenging conventional karyotyping by next-generation karyotyping in 281 intensively treated patients with AML
Mareschal S; Palau A; Lindberg J; Ruminy P; Nilsson C; Bengtzen S; Engvall M; Eriksson A; Neddermeyer A; Marchand V; Jansson M; Bjorklund M; Jardin F; Rantalainen M; Lennartsson A; Cavelier L; Gronberg H; Lehmann S
Article: NATURE COMMUNICATIONS. 2021;12(1):1054
Biological and therapeutic implications of a unique subtype of NPM1 mutated AML
Mer AS; Heath EM; Tonekaboni SAM; Dogan-Artun N; Nair SK; Murison A; Garcia-Prat L; Shlush L; Hurren R; Voisin V; Bader GD; Nislow C; Rantalainen M; Lehmann S; Gower M; Guidos CJ; Lupien M; Dick JE; Minden MD; Schimmer AD; Haibe-Kains B
Article: BLOOD CANCER JOURNAL. 2020;10(6):67
Integrated transcriptomic and genomic analysis improves prediction of complete remission and survival in elderly patients with acute myeloid leukemia
Osterroos A; Bjorklund M; Eriksson A; Lindberg J; Nilsson C; Mareschal S; Rantalainen M; Gronberg H; Lehmann S
Article: THE LANCET ONCOLOGY. 2020;21(2):222-232
Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study
Strom P; Kartasalo K; Olsson H; Solorzano L; Delahunt B; Berney DM; Bostwick DG; Evans AJ; Grignon DJ; Humphrey PA; Iczkowski KA; Kench JG; Kristiansen G; van der Kwast TH; Leite KRM; McKenney JK; Oxley J; Pan C-C; Samaratunga H; Srigley JR; Takahashi H; Tsuzuki T; Varma M; Zhou M; Lindberg J; Lindskog C; Ruusuvuori P; Wahlby C; Gronberg H; Rantalainen M; Egevad L; Eklund M
Article: CLINICAL CANCER RESEARCH. 2019;25(6):1766-1773
TP53 Outperforms Other Androgen Receptor Biomarkers to Predict Abiraterone or Enzalutamide Outcome in Metastatic Castration-Resistant Prostate Cancer
De Laere B; Oeyen S; Mayrhofer M; Whitington T; van Dam P-J; Van Oyen P; Ghysel C; Ampe J; Ost P; Demey W; Hoekx L; Schrijvers D; Brouwers B; Lybaert W; Everaert EG; De Maeseneer D; Strijbos M; Bols A; Fransis K; Beije N; de Kruijff IE; van Dam V; Brouwer A; Goossens D; Heyrman L; Van den Eynden GG; Rutten A; Del Favero J; Rantalainen M; Rajan P; Sleijfer S; Ullen A; Yachnin J; Gronberg H; Van Laere SJ; Lindberg J; Dirix LY
Article: GENOME MEDICINE. 2018;10(1):85
Cell-free DNA profiling of metastatic prostate cancer reveals microsatellite instability, structural rearrangements and clonal hematopoiesis
Mayrhofer M; De Laere B; Whitington T; Van Oyen P; Ghysel C; Ampe J; Ost P; Demey W; Hoekx L; Schrijvers D; Brouwers B; Lybaert W; Everaert E; De Maeseneer D; Strijbos M; Bols A; Fransis K; Oeyen S; van Dam P-J; Van den Eynden G; Rutten A; Aly M; Nordstrom T; Van Laere S; Rantalainen M; Rajan P; Egevad L; Ullen A; Yachnin J; Dirix L; Gronberg H; Lindberg J
Article: JOURNAL OF THE NATIONAL CANCER INSTITUTE. 2018;110(10):1094-1101
Development and Validation of a Novel RNA Sequencing-Based Prognostic Score for Acute Myeloid Leukemia
Wang M; Lindberg J; Klevebring D; Nilsson C; Lehmann S; Gronberg H; Rantalainen M
Article: JOURNAL OF CLINICAL PATHOLOGY. 2018;71(9):787-794
Prognostic value of Ki67 analysed by cytology or histology in primary breast cancer
Robertson S; Stalhammar G; Darai-Ramqvist E; Rantalainen M; Tobin NP; Bergh J; Hartman J
Article: BIOINFORMATICS. 2018;34(14):2392-2400
Isoform-level gene expression patterns in single-cell RNA-sequencing data
Trung NV; Wills QF; Kalari KR; Niu N; Wang L; Pawitan Y; Rantalainen M
Article: BRIEFINGS IN FUNCTIONAL GENOMICS. 2018;17(4):273-282
Application of single-cell sequencing n human cancer
Rantalainen M
Article: HISTOPATHOLOGY. 2018;72(6):974-989
Digital image analysis of Ki67 in hot spots is superior to both manual Ki67 and mitotic counts in breast cancer
Stalhammar G; Robertson S; Wedlund L; Lippert M; Rantalainen M; Bergh J; Hartman J
Article: JOURNAL OF HEMATOLOGY AND ONCOLOGY. 2018;11(1):52
Expression levels of long non-coding RNAs are prognostic for AML outcome
Mer AS; Lindberg J; Nilsson C; Klevebring D; Wang M; Gronberg H; Lehmann S; Rantalainen M
Article: BMC CANCER. 2017;17(1):802
Intra-tumor heterogeneity in breast cancer has limited impact on transcriptomic-based molecular profiling
Karthik G-M; Rantalainen M; Stalhammar G; Lovrot J; Ullah I; Alkodsi A; Ma R; Wedlund L; Lindberg J; Frisell J; Bergh J; Hartman J
Article: LEUKEMIA. 2017;31(10):2029-2036
Validation of risk stratification models in acute myeloid leukemia using sequencing-based molecular profiling
Wang M; Lindberg J; Klevebring D; Nilsson C; Mer AS; Rantalainen M; Lehmann S; Gronberg H
Article: JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION : JAMIA. 2017;24(5):950-957
E-Science technologies in a workflow for personalized medicine using cancer screening as a case study
Spjuth O; Karlsson A; Clements M; Humphreys K; Ivansson E; Dowling J; Eklund M; Jauhiainen A; Czene K; Gronberg H; Sparen P; Wiklund F; Cheddad A; Palsdottir P; Rantalainen M; Abrahamsson L; Laure E; Litton J-E; Palmgren J
Article: CANCER RESEARCH. 2017;77(13):3708-3717
Assessment of Breast Cancer Risk Factors Reveals Subtype Heterogeneity.
Holm J; Eriksson L; Ploner A; Eriksson M; Rantalainen M; Li J; Hall P; Czene K
Article: CLINICAL CANCER RESEARCH. 2017;23(10):2584-2592
Molecular Differences between Screen-Detected and Interval Breast Cancers Are Largely Explained by PAM50 Subtypes
Li J; Ivansson E; Klevebring D; Tobin NP; Lindstrom LS; Holm J; Prochazka G; Cristando C; Palmgren J; Tornberg S; Humphreys K; Hartman J; Frisell J; Rantalainen M; Lindberg J; Hall P; Bergh J; Gronberg H; Czene K
Article: SCIENTIFIC REPORTS. 2016;6:38037
Sequencing-based breast cancer diagnostics as an alternative to routine biomarkers.
Rantalainen M; Klevebring D; Lindberg J; Ivansson E; Rosin G; Kis L; Celebioglu F; Fredriksson I; Czene K; Frisell J; Hartman J; Bergh J; Grönberg H
Article: BIOINFORMATICS. 2016;32(14):2128-2135
Beta-Poisson model for single-cell RNA-seq data analyses
Trung NV; Wills QF; Kalari KR; Niu N; Wang L; Rantalainen M; Pawitan Y
Article: CELL REPORTS. 2016;15(9):2000-2011
Reprogramming Tumor-Associated Macrophages by Antibody Targeting Inhibits Cancer Progression and Metastasis
Georgoudaki A-M; Prokopec KE; Boura VF; Hellqvist E; Sohn S; Ostling J; Dahan R; Harris RA; Rantalainen M; Klevebring D; Sund M; Brage SE; Fuxe J; Rolny C; Li F; Ravetch JV; Karlsson MCI
Article: BREAST CANCER RESEARCH. 2016;18(1):48
Determining breast cancer histological grade from RNA-sequencing data.
Wang M; Klevebring D; Lindberg J; Czene K; Grönberg H; Rantalainen M
Article: MODERN PATHOLOGY. 2016;29(4):318-329
Digital image analysis outperforms manual biomarker assessment in breast cancer
Stalhammar G; Martinez NF; Lippert M; Tobin NP; Molholm I; Kis L; Rosin G; Rantalainen M; Pedersen L; Bergh J; Grunkin M; Hartman J
Article: SCIENTIFIC REPORTS. 2016;6:20200
Study design requirements for RNA sequencing-based breast cancer diagnostics.
Mer AS; Klevebring D; Grönberg H; Rantalainen M
Article: JOURNAL OF ALZHEIMER'S DISEASE. 2015;45(4):1061-1076
An Integrated Bioinformatics Approach for Identifying Genetic Markers that Predict Cerebrospinal Fluid Biomarker p-tau₁₈₁/Aβ_1-42 Ratio in ApoE4-Negative Mild Cognitive Impairment Patients
Sun Y; Bresell A; Rantalainen M; Hoglund K; Lebouvier T; Salter H
Article: JOURNAL OF PROTEOME RESEARCH. 2015;14(1):479-490
Integrative Transcriptomic and Metabonomic Molecular Profiling of Colonic Mucosal Biopsies Indicates a Unique Molecular Phenotype for Ulcerative Colitis
Rantalainen M; Bjerrum JT; Olsen J; Nielsen OH; Wang Y
Article: METHODS IN MOLECULAR BIOLOGY. 2015;1277:147-159
Combining metabonomics and other -omics data.
Rantalainen M
Article: PLOS ONE. 2015;10(5):e0127882
Robust Linear Models for Cis-eQTL Analysis.
Rantalainen M; Lindgren CM; Holmes CC
Article: METABOLOMICS. 2014;10(2):280-290
Integration of transcriptomics and metabonomics: improving diagnostics, biomarker identification and phenotyping in ulcerative colitis.
Bjerrum JT; Rantalainen M; Wang Y; Olsen J; Nielsen OH
Article: PLOS ONE. 2013;8(2):e55923
The Presence of Methylation Quantitative Trait Loci Indicates a Direct Genetic Influence on the Level of DNA Methylation in Adipose Tissue
Drong AW; Nicholson G; Hedman AK; Meduri E; Grundberg E; Small KS; Shin S-Y; Bell JT; Karpe F; Soranzo N; Spector TD; McCarthy MI; Deloukas P; Rantalainen M; Lindgren CM
Article: JOURNAL OF PROTEOME RESEARCH. 2012;11(9):4712-4721
Systems responses of rats to mequindox revealed by metabolic and transcriptomic profiling.
Zhao X-J; Hao F; Huang C; Rantalainen M; Lei H; Tang H; Wang Y
Article: PLOS GENETICS. 2012;8(5):e1002704
Extent, Causes, and Consequences of Small RNA Expression Variation in Human Adipose Tissue
Parts L; Hedman AK; Keildson S; Knights AJ; Abreu-Goodger C; van de Bunt M; Guerra-Assuncao JA; Bartonicek N; van Dongen S; Maegi R; Nisbet J; Barrett A; Rantalainen M; Nica AC; Quail MA; Small KS; Glass D; Enright AJ; Winn J; Deloukas P; Dermitzakis ET; McCarthy MI; Spector TD; Durbin R; Lindgren CM
Article: JOURNAL OF PROTEOME RESEARCH. 2011;10(12):5562-5567
Accounting for control mislabeling in case-control biomarker studies.
Rantalainen M; Holmes CC
Article: PROTEOME SCIENCE. 2011;9:73
Variance decomposition of protein profiles from antibody arrays using a longitudinal twin model.
Kato BS; Nicholson G; Neiman M; Rantalainen M; Holmes CC; Barrett A; Uhlén M; Nilsson P; Spector TD; Schwenk JM
Article: ANALYTICA CHIMICA ACTA. 2011;705(1-2):72-80
Non-linear modeling of 1H NMR metabonomic data using kernel-based orthogonal projections to latent structures optimized by simulated annealing.
Fonville JM; Bylesjö M; Coen M; Nicholson JK; Holmes E; Lindon JC; Rantalainen M
Article: PLOS GENETICS. 2011;7(9):e1002270
A genome-wide metabolic QTL analysis in Europeans implicates two loci shaped by recent positive selection.
Nicholson G; Rantalainen M; Li JV; Maher AD; Malmodin D; Ahmadi KR; Faber JH; Barrett A; Min JL; Rayner NW; Toft H; Krestyaninova M; Viksna J; Neogi SG; Dumas M-E; Sarkans U; MolPAGE Consortium; Donnelly P; Illig T; Adamski J; Suhre K; Allen M; Zondervan KT; Spector TD; Nicholson JK; Lindon JC; Baunsgaard D; Holmes E; McCarthy MI; Holmes CC
Article: MOLECULAR SYSTEMS BIOLOGY. 2011;7:525
Human metabolic profiles are stably controlled by genetic and environmental variation.
Nicholson G; Rantalainen M; Maher AD; Li JV; Malmodin D; Ahmadi KR; Faber JH; Hallgrímsdóttir IB; Barrett A; Toft H; Krestyaninova M; Viksna J; Neogi SG; Dumas M-E; Sarkans U; The Molpage Consortium; Silverman BW; Donnelly P; Nicholson JK; Allen M; Zondervan KT; Lindon JC; Spector TD; McCarthy MI; Holmes E; Baunsgaard D; Holmes CC
Article: PLOS ONE. 2011;6(11):e27338
MicroRNA expression in abdominal and gluteal adipose tissue is associated with mRNA expression levels and partly genetically driven.
Rantalainen M; Herrera BM; Nicholson G; Bowden R; Wills QF; Min JL; Neville MJ; Barrett A; Allen M; Rayner NW; Fleckner J; McCarthy MI; Zondervan KT; Karpe F; Holmes CC; Lindgren CM
Article: FEMS MICROBIOLOGY ECOLOGY. 2010;73(3):577-586
Structural shifts of gut microbiota as surrogate endpoints for monitoring host health changes induced by carcinogen exposure.
Wei H; Dong L; Wang T; Zhang M; Hua W; Zhang C; Pang X; Chen M; Su M; Qiu Y; Zhou M; Yang S; Chen Z; Rantalainen M; Nicholson JK; Jia W; Wu D; Zhao L
Article: JOURNAL OF PROTEOME RESEARCH. 2009;8(5):2361-2375
Top-down systems biology modeling of host metabotype-microbiome associations in obese rodents.
Waldram A; Holmes E; Wang Y; Rantalainen M; Wilson ID; Tuohy KM; McCartney AL; Gibson GR; Nicholson JK
Article: ANALYTICAL CHEMISTRY. 2009;81(6):2075-2084
Analytic properties of statistical total correlation spectroscopy based information recovery in 1H NMR metabolic data sets.
Alves AC; Rantalainen M; Holmes E; Nicholson JK; Ebbels TMD
Article: BMC BIOINFORMATICS. 2008;9:106
K-OPLS package: kernel-based orthogonal projections to latent structures for prediction and interpretation in feature space.
Bylesjö M; Rantalainen M; Nicholson JK; Holmes E; Trygg J
Article: BMC BIOINFORMATICS. 2008;9:105
Piecewise multivariate modelling of sequential metabolic profiling data.
Rantalainen M; Cloarec O; Ebbels TMD; Lundstedt T; Nicholson JK; Holmes E; Trygg J
Article: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA. 2008;105(6):2117-2122
Symbiotic gut microbes modulate human metabolic phenotypes.
Li M; Wang B; Zhang M; Rantalainen M; Wang S; Zhou H; Zhang Y; Shen J; Pang X; Zhang M; Wei H; Chen Y; Lu H; Zuo J; Su M; Qiu Y; Jia W; Xiao C; Smith LM; Yang S; Holmes E; Tang H; Zhao G; Nicholson JK; Li L; Zhao L
Article: ANALYTICAL CHEMISTRY. 2007;79(15):5682-5689
Statistical correlation and projection methods for improved information recovery from diffusion-edited NMR spectra of biological samples.
Smith LM; Maher AD; Cloarec O; Rantalainen M; Tang H; Elliott P; Stamler J; Lindon JC; Holmes E; Nicholson JK
Article: JOURNAL OF CHEMOMETRICS. 2007;21(7-9):376-385
Kernel-based orthogonal projections to latent structures (K-OPLS)
Rantalainen M; Bylesjoe M; Cloarec O; Nicholson JK; Holmes E; Trygg J
Article: JOURNAL OF PROTEOME RESEARCH. 2006;5(10):2642-2655
Statistically integrated metabonomic-proteomic studies on a human prostate cancer xenograft model in mice.
Rantalainen M; Cloarec O; Beckonert O; Wilson ID; Jackson D; Tonge R; Rowlinson R; Rayner S; Nickson J; Wilkinson RW; Mills JD; Trygg J; Nicholson JK; Holmes E
Article: JOURNAL OF CHEMOMETRICS. 2006;20(8-10):341-351
OPLS discriminant analysis:: combining the strengths of PLS-DA and SIMCA classification
Bylesjo M; Rantalainen M; Cloarec O; Nicholson JK; Holmes E; Trygg J
Article: MOLECULAR BIOSYSTEMS. 2006;2(3-4):193-202
The comparative metabonomics of age-related changes in the urinary composition of male Wistar-derived and Zucker (fa/fa) obese rats.
Williams RE; Lenz EM; Rantalainen M; Wilson ID
Article: MOLECULAR BIOSYSTEMS. 2005;1(2):166-175
The metabonomics of aging and development in the rat: an investigation into the effect of age on the profile of endogenous metabolites in the urine of male rats using 1H NMR and HPLC-TOF MS.
Williams RE; Lenz EM; Lowden JS; Rantalainen M; Wilson ID
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Alla övriga publikationer

Review: EUROPEAN UROLOGY FOCUS. 2021;7(4):687-691
Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies-Current Status and Next Steps
Kartasalo K; Bulten W; Delahunt B; Chen P-HC; Pinckaers H; Olsson H; Ji X; Mulliqi N; Samaratunga H; Tsuzuki T; Lindberg J; Rantalainen M; Wahlby C; Litjens G; Ruusuvuori P; Egevad L; Eklund M
Review: JOURNAL OF INTERNAL MEDICINE. 2020;288(1):62-81
Artificial intelligence as the next step towards precision pathology
Acs B; Rantalainen M; Hartman J
Letter: JAMA ONCOLOGY. 2019;5(7):1060-1062
Androgen Receptor Burden and Poor Response to Abiraterone or Enzalutamide in TP53 Wild-Type Metastatic Castration-Resistant Prostate Cancer
De Laere B; Rajan P; Gronberg H; Dirix L; Lindberg J; Mayrhofer M; Whitington T; van Dam P-J; Van Oyen P; Ghysel C; Ampe J; Ost P; Demey W; Hoela L; Schrijvers D; Brouwers B; Lybaert W; Everaert E; De Maeseneer D; Strijbos M; Bols A; Fransis K; Beije N; de Kruijff I; van Dam V; Brouwer A; Goossens D; Heyrman L; Van den Eynden G; Rutten A; Del Favero J; Rantalainen M; Sleijfer S; Ullen A; Yachnin J; Van Laere S; De laere L; Develter T; Vantieghem S; Herman S; Coifs G; Lamotte V; Boumans A; Baitar A; Haeck R; Wallays G

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