2025
Cutaneous lupus features specialized stromal niches and altered retroelement expression
Gehlhausen J, Kong Y, Baker E, Ramachandran S, Koumpouras F, Ko C, Vesely M, Little A, Damsky W, King B, Iwasaki A. Cutaneous lupus features specialized stromal niches and altered retroelement expression. Journal Of Investigative Dermatology 2025 PMID: 40409678, DOI: 10.1016/j.jid.2025.04.033.Peer-Reviewed Original ResearchRetroelement expressionCGAS-STING pathwayRIG-IType I interferonCutaneous lupusCGAS-STINGElevated expression of genesPathway enrichment analysisI interferonExpression of genesResponse to type I interferonsLupus skinRetroelement familiesInterferon-stimulated genesNucleic acid signalsApoptotic signalingSingle-cell RNAMultiple cell typesAcid signalingEnrichment analysisInflammatory cell recruitmentType II interferonInflammatory skin diseaseTumor necrosis factorCell typesGeneration of stable brain cell cultures from embryonic zebrafish to interrogate phenotypes in zebrafish mutants of neurodevelopmental disorders
Odierna G, Stednitz S, Pruitt A, Arnold J, Hoffman E, Scott E. Generation of stable brain cell cultures from embryonic zebrafish to interrogate phenotypes in zebrafish mutants of neurodevelopmental disorders. Journal Of Neuroscience Methods 2025, 418: 110426. PMID: 40086601, DOI: 10.1016/j.jneumeth.2025.110426.Peer-Reviewed Original ResearchBrain cell culturesCell culturesCell typesNeuronal culture protocolCultured primary neuronsEmbryonic zebrafishPrimary brain cell culturesZebrafish mutantsCellular consequencesStructural hallmarksMature synaptic connectionsPrimary neuronsCell survivalMammalian tissuesTranscriptional signatureCell linesEmbryonic tissuesZebrafish neuronsZebrafishNeuron purityNeuronal culturesNetwork of neuronsMixed cell typeDays in vitroModel systemGeneration of Orthogonal Gradients of the Matrix Stiffness and Chemotactic Cues in a Suspended Array of Hydrogel to Study hMSCs Migration
Xu Z, Ponek A, Thomas J, Qyang Y. Generation of Orthogonal Gradients of the Matrix Stiffness and Chemotactic Cues in a Suspended Array of Hydrogel to Study hMSCs Migration. ACS Sensors 2025, 10: 1722-1728. PMID: 40021359, DOI: 10.1021/acssensors.4c02793.Peer-Reviewed Original ResearchConceptsMatrix stiffnessChemotactic cuesHuman mesenchymal stem cellsHydrogel cylindersCell migrationDevice working principleMigration of human mesenchymal stem cellsFactor 1 alphaCellular contextOrthogonal gradientsReplica moldingGlass substratesCell migration studiesDevice fabricationWorking principleMicrofluidic devicesIn vitro assaysHydrogelsStiffnessCell typesSuspended arrayMesenchymal stem cellsConcentration gradientPoly(dimethylsiloxaneCylinderA comprehensive spatio-cellular map of the human hypothalamus
Tadross J, Steuernagel L, Dowsett G, Kentistou K, Lundh S, Porniece M, Klemm P, Rainbow K, Hvid H, Kania K, Polex-Wolf J, Knudsen L, Pyke C, Perry J, Lam B, Brüning J, Yeo G. A comprehensive spatio-cellular map of the human hypothalamus. Nature 2025, 639: 708-716. PMID: 39910307, PMCID: PMC11922758, DOI: 10.1038/s41586-024-08504-8.Peer-Reviewed Original ResearchConceptsGenome-wide association study genesRare deleterious variantsHypothalamic cell typesCell typesSingle-nucleus sequencingBody mass indexTranscription mapDeleterious variantsNeuronal cell typesG protein-coupled receptorsStudy genesBiological functions1Spatial transcriptomicsTranscriptomic identityCellular componentsExpression levelsPro-opiomelanocortin neuronsHuman hypothalamusAssociated with body mass indexPopulation levelMetabolic disordersHypothalamic cellsExpressionNeuronal clustersTranscriptomeInterneuron loss and microglia activation by transcriptome analyses in the basal ganglia of Tourette disorder
Wang Y, Fasching L, Wu F, Suvakov M, Huttner A, Berretta S, Roberts R, Leckman J, Fernandez T, Abyzov A, Vaccarino F. Interneuron loss and microglia activation by transcriptome analyses in the basal ganglia of Tourette disorder. Biological Psychiatry 2025 PMID: 39892689, DOI: 10.1016/j.biopsych.2024.12.022.Peer-Reviewed Original ResearchActivity of cis-regulatory elementsCis-regulatory elementsMedium spiny neuronsDifferential gene expression analysisChromatin accessibility analysesCell typesDifferential gene expressionGene expression changesMitochondrial oxidative metabolismGene expression analysisSnATAC-seqOpen chromatin datasetsPutative enhancersSynaptic adhesionChromatin datasetsOxidative metabolismEpigenomic regulationTranscriptome analysisActivation of immune responsesIdentified cell typesExpression analysisSynaptic dysfunctionGene expressionExpression changesTranscriptomeGenomics yields biological and phenotypic insights into bipolar disorder
Lee B, Kim J, Lee Y, Kang J, Cheon M, Kim D, Aslan M, Harvey P, Huang G. Genomics yields biological and phenotypic insights into bipolar disorder. Nature 2025, 639: 968-975. PMID: 39843750, DOI: 10.1038/s41586-024-08468-9.Peer-Reviewed Original ResearchFine-mappingGenetic architectureGenome-wide significant lociMulti-ancestry meta-analysisGenetic architecture of bipolar disorderRare variant signalsSignificant lociGenetic determinantsBipolar disorderVariant signalsLatino ancestryCell typesEast Asian cohortsPhenotypic insightsPathophysiology of bipolar disorderGenesMedium spiny neuronsBipolar disorder subtypesPatient ascertainmentAetiology of bipolar disorderGABAergic interneuronsSpiny neuronsAsian cohortGenomeGlobal burdenTrans-ancestry genome-wide study of depression identifies 697 associations implicating cell types and pharmacotherapies
Consortium M, Adams M, Streit F, Meng X, Awasthi S, Adey B, Choi K, Chundru V, Coleman J, Ferwerda B, Foo J, Gerring Z, Giannakopoulou O, Gupta P, Hall A, Harder A, Howard D, Hübel C, Kwong A, Levey D, Mitchell B, Ni G, Ota V, Pain O, Pathak G, Schulte E, Shen X, Thorp J, Walker A, Yao S, Zeng J, Zvrskovec J, Aarsland D, Actkins K, Adli M, Agerbo E, Aichholzer M, Aiello A, Air T, Als T, Andersson E, Andlauer T, Arolt V, Ask H, Bäckman J, Badola S, Ballard C, Banasik K, Bass N, Beekman A, Belangero S, Bigdeli T, Binder E, Bjerkeset O, Bjornsdottir G, Børte S, Bränn E, Braun A, Brodersen T, Brückl T, Brunak S, Bruun M, Burmeister M, Buspavanich P, Bybjerg-Grauholm J, Byrne E, Cai J, Campbell A, Campbell M, Campos A, Castelao E, Cervilla J, Chaumette B, Chen C, Chen H, Chen Z, Cichon S, Colodro-Conde L, Corbett A, Corfield E, Couvy-Duchesne B, Craddock N, Dannlowski U, Davies G, de Geus E, Deary I, Degenhardt F, Dehghan A, DePaulo J, Deuschle M, Didriksen M, Dinh K, Direk N, Djurovic S, Docherty A, Domschke K, Dowsett J, Drange O, Dunn E, Eaton W, Einarsson G, Eley T, Elsheikh S, Engelmann J, Benros M, Erikstrup C, Escott-Price V, Fabbri C, Fang Y, Finer S, Frank J, Free R, Gallo L, Gao H, Gill M, Gilles M, Goes F, Gordon S, Grove J, Gudbjartsson D, Gutierrez B, Hahn T, Hall L, Hansen T, Haraldsson M, Hartman C, Havdahl A, Hayward C, Heilmann-Heimbach S, Herms S, Hickie I, Hjalgrim H, Hjerling-Leffler J, Hoffmann P, Homuth G, Horn C, Hottenga J, Hougaard D, Hovatta I, Huang Q, Hucks D, Huider F, Hunt K, Ialongo N, Ising M, Isometsä E, Jansen R, Jiang Y, Jones I, Jones L, Jonsson L, Kanai M, Karlsson R, Kasper S, Kendler K, Kessler R, Kloiber S, Knowles J, Koen N, Kraft J, Kranzler H, Krebs K, Kallak T, Kutalik Z, Lahtela E, Lake M, Larsen M, Lenze E, Lewins M, Lewis G, Li L, Lin B, Lin K, Lind P, Liu Y, MacIntyre D, MacKinnon D, Maher B, Maier W, Marshe V, Martinez-Levy G, Matsuda K, Mbarek H, McGuffin P, Medland S, Meinert S, Mikkelsen C, Mikkelsen S, Milaneschi Y, Millwood I, Molina E, Mondimore F, Mortensen P, Mulsant B, Naamanka J, Najman J, Nauck M, Nenadić I, Nielsen K, Nolt I, Nordentoft M, Nöthen M, Nyegaard M, O'Donovan M, Oddsson A, Oliveira A, Olsen C, Oskarsson H, Ostrowski S, Owen M, Packer R, Palviainen T, Pan P, Pato C, Pato M, Pedersen N, Pedersen O, Peyrot W, Potash J, Preisig M, Preuss M, Quiroz J, Renteria M, Reynolds C, Rice J, Sakaue S, Santoro M, Schoevers R, Schork A, Schulze T, Send T, Shi J, Sigurdsson E, Singh K, Sinnamon G, Sirignano L, Smeland O, Smith D, Sofer T, Sørensen E, Srinivasan S, Stefansson H, Stefansson K, Straub P, Su M, Tadic A, Teismann H, Teumer A, Thapar A, Thomson P, Thørner L, Topaloudi A, Tsai S, Tzoulaki I, Uhl G, Uitterlinden A, Ullum H, Umbricht D, Ursano R, Van der Auwera S, van Hemert A, Veluchamy A, Viktorin A, Völzke H, Walters G, Wang X, Wani A, Weissman M, Wellmann J, Whiteman D, Wildman D, Willemsen G, Williams A, Winsvold B, Witt S, Xiong Y, Zillich L, Zwart J, Team T, Group C, Team E, Team G, Psychiatry H, Project T, Program V, Andreassen O, Baune B, Berger K, Boomsma D, Børglum A, Breen G, Cai N, Coon H, Copeland W, Creese B, Cruz-Fuentes C, Czamara D, Davis L, Derks E, Domenici E, Elliott P, Forstner A, Gawlik M, Gelernter J, Grabe H, Hamilton S, Hveem K, John C, Kaprio J, Kircher T, Krebs M, Kuo P, Landén M, Lehto K, Levinson D, Li Q, Lieb K, Loos R, Lu Y, Lucae S, Luykx J, Maes H, Magnusson P, Martin H, Martin N, McQuillin A, Middeldorp C, Milani L, Mors O, Müller D, Müller-Myhsok B, Okada Y, Oldehinkel A, Paciga S, Palmer C, Paschou P, Penninx B, Perlis R, Peterson R, Pistis G, Polimanti R, Porteous D, Posthuma D, Rabinowitz J, Reichborn-Kjennerud T, Reif A, Rice F, Ricken R, Rietschel M, Rivera M, Rück C, Salum G, Schaefer C, Sen S, Serretti A, Skalkidou A, Smoller J, Stein D, Stein F, Stein M, Sullivan P, Tesli M, Thorgeirsson T, Tiemeier H, Timpson N, Uddin M, Uher R, van Heel D, Verweij K, Walters R, Wassertheil-Smoller S, Wendland J, Werge T, Zwinderman A, Kuchenbaecker K, Wray N, Ripke S, Lewis C, McIntosh A. Trans-ancestry genome-wide study of depression identifies 697 associations implicating cell types and pharmacotherapies. Cell 2025, 188: 640-652.e9. PMID: 39814019, PMCID: PMC11829167, DOI: 10.1016/j.cell.2024.12.002.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesCell-type enrichment analysisSingle-cell dataTrans-ancestryAdmixed ancestrySingle-cell analysisFine-mappingPotential repurposing opportunitiesAssociation studiesGene associationsEnrichment analysisReceptor clusteringPolygenic scoresRepurposing opportunitiesPostsynaptic densityCell typesStudies of depressionMedium spiny neuronsAncestryAntidepressant targetSpiny neuronsAmygdala neuronsLociBiological targetsEffective treatment
2024
Sodium channels in non-excitable cells: powerful actions and therapeutic targets beyond Hodgkin and Huxley
Vasylyev D, Liu C, Waxman S. Sodium channels in non-excitable cells: powerful actions and therapeutic targets beyond Hodgkin and Huxley. Trends In Cell Biology 2024 PMID: 39743470, DOI: 10.1016/j.tcb.2024.11.009.Peer-Reviewed Original ResearchVoltage-gated sodium channelsSodium channelsInvolvement of voltage-gated sodium channelsFunction of voltage-gated sodium channelsCellular functionsTherapeutic targetNon-excitable cellsRegulate diverse cellular functionsDiverse cellular functionsPropagation of action potentialsCardiac myocytesDynamic expression patternCytokine releaseInflammatory disordersAction potentialsMuscle cellsTherapeutic interventionsCell typesPathological conditionsPhysiological processesCellsCurrent knowledgeOsteoarthritisHodgkinSINGLE-CELL ANALYSIS OF SOMATIC MUTATIONS IN HUMAN LUNG REVEALS ASSOCIATION WITH TRANSCRIPTIONAL CHANGES IN AGING
De Man R, Adams T, McDonough J, Cala-Garcia J, Moss B, Yan X, Rosas I, Kaminski N. SINGLE-CELL ANALYSIS OF SOMATIC MUTATIONS IN HUMAN LUNG REVEALS ASSOCIATION WITH TRANSCRIPTIONAL CHANGES IN AGING. Innovation In Aging 2024, 8: 571-572. PMCID: PMC11690935, DOI: 10.1093/geroni/igae098.1872.Peer-Reviewed Original ResearchSomatic mutationsMutational burdenCell type annotationAlveolar type 1DNA damage response genesAnalysis of somatic mutationsSomatic mutation accumulationAccumulation of somatic mutationsCell typesUbiquitin ligase geneDamage response genesLoss of cell functionAnalyzed somatic mutationsDecreased expressionSingle-cell RNAseqLigase geneMutation accumulationTop genesSignaling genesCell marker genesResponse genesTranscriptional changesAlveolar type 1 cellsGenesMarker genesMulti-omics approaches to decipher the interactions of nanoparticles and biological systems
Wang Y, Xiao Z, Wang Z, Lee D, Ma Y, Wilhelm S, Wang H, Kim B, Jiang W. Multi-omics approaches to decipher the interactions of nanoparticles and biological systems. Nature Reviews Bioengineering 2024, 1-16. DOI: 10.1038/s44222-024-00264-4.Peer-Reviewed Original ResearchMulti-omics approachNano-bio interactionsMulti-omicsMulti-omics pipelineMulti-omics dataSubcellular levelHigh-throughput mannerApplication of transcriptomicsNanoparticles in vivoMetabolomics technologyTreatment strategiesNanoparticle uptakeBiological systemsOptimized nanoparticlesEngineered nanoparticlesBiological informationImplementation of nanoparticlesClinical settingInteraction of nanoparticlesCell typesNano-bio interfaceEpigenomeTranscriptomeMetabolomicsBioinformaticsEffects of gene dosage on cognitive ability: A function-based association study across brain and non-brain processes
Huguet G, Renne T, Poulain C, Dubuc A, Kumar K, Kazem S, Engchuan W, Shanta O, Douard E, Proulx C, Jean-Louis M, Saci Z, Mollon J, Schultz L, Knowles E, Cox S, Porteous D, Davies G, Redmond P, Harris S, Schumann G, Dumas G, Labbe A, Pausova Z, Paus T, Scherer S, Sebat J, Almasy L, Glahn D, Jacquemont S. Effects of gene dosage on cognitive ability: A function-based association study across brain and non-brain processes. Cell Genomics 2024, 4: 100721. PMID: 39667348, PMCID: PMC11701252, DOI: 10.1016/j.xgen.2024.100721.Peer-Reviewed Original ResearchConceptsCopy-number variantsGenome-wide association studiesAssociation studiesCognitive abilitiesBiological processesEffect of gene dosageNeurodevelopmental disordersAssociated with cognitionHigher cognitive performanceGene dosageGene setsAssociated with higher cognitive performanceCognitive performanceGenesCell typesEffect sizeCognitionDeletionDuplicationDisordersNon-brain tissuesMedical comorbiditiesAbilityVariantsBrainπ-HuB: the proteomic navigator of the human body
He F, Aebersold R, Baker M, Bian X, Bo X, Chan D, Chang C, Chen L, Chen X, Chen Y, Cheng H, Collins B, Corrales F, Cox J, E W, Van Eyk J, Fan J, Faridi P, Figeys D, Gao G, Gao W, Gao Z, Goda K, Goh W, Gu D, Guo C, Guo T, He Y, Heck A, Hermjakob H, Hunter T, Iyer N, Jiang Y, Jimenez C, Joshi L, Kelleher N, Li M, Li Y, Lin Q, Liu C, Liu F, Liu G, Liu Y, Liu Z, Low T, Lu B, Mann M, Meng A, Moritz R, Nice E, Ning G, Omenn G, Overall C, Palmisano G, Peng Y, Pineau C, Poon T, Purcell A, Qiao J, Reddel R, Robinson P, Roncada P, Sander C, Sha J, Song E, Srivastava S, Sun A, Sze S, Tang C, Tang L, Tian R, Vizcaíno J, Wang C, Wang C, Wang X, Wang X, Wang Y, Weiss T, Wilhelm M, Winkler R, Wollscheid B, Wong L, Xie L, Xie W, Xu T, Xu T, Yan L, Yang J, Yang X, Yates J, Yun T, Zhai Q, Zhang B, Zhang H, Zhang L, Zhang L, Zhang P, Zhang Y, Zheng Y, Zhong Q, Zhu Y. π-HuB: the proteomic navigator of the human body. Nature 2024, 636: 322-331. PMID: 39663494, DOI: 10.1038/s41586-024-08280-5.Peer-Reviewed Original ResearchNeuroinflammation in Alzheimer disease
Heneka M, van der Flier W, Jessen F, Hoozemanns J, Thal D, Boche D, Brosseron F, Teunissen C, Zetterberg H, Jacobs A, Edison P, Ramirez A, Cruchaga C, Lambert J, Laza A, Sanchez-Mut J, Fischer A, Castro-Gomez S, Stein T, Kleineidam L, Wagner M, Neher J, Cunningham C, Singhrao S, Prinz M, Glass C, Schlachetzki J, Butovsky O, Kleemann K, De Jaeger P, Scheiblich H, Brown G, Landreth G, Moutinho M, Grutzendler J, Gomez-Nicola D, McManus R, Andreasson K, Ising C, Karabag D, Baker D, Liddelow S, Verkhratsky A, Tansey M, Monsonego A, Aigner L, Dorothée G, Nave K, Simons M, Constantin G, Rosenzweig N, Pascual A, Petzold G, Kipnis J, Venegas C, Colonna M, Walter J, Tenner A, O’Banion M, Steinert J, Feinstein D, Sastre M, Bhaskar K, Hong S, Schafer D, Golde T, Ransohoff R, Morgan D, Breitner J, Mancuso R, Riechers S. Neuroinflammation in Alzheimer disease. Nature Reviews Immunology 2024, 1-32. PMID: 39653749, DOI: 10.1038/s41577-024-01104-7.Peer-Reviewed Original ResearchAlzheimer's diseasePathogenesis of Alzheimer's diseaseMultiple lines of informationGenetic studiesInfluence of geneticsLines of informationCell typesDisease developmentDementia-causing diseasesStages of Alzheimer's diseasePathological roleMultiple linesTherapeutic strategiesImmune processesPreclinical stage of Alzheimer's diseaseCellsAdaptive immune activationTargeting neuroinflammationPathological mechanismsLifestyle factorsGeneticsSingle-nucleus multi-omics analyses reveal cellular and molecular innovations in the anterior cingulate cortex during primate evolution
Yuan J, Dong K, Wu H, Zeng X, Liu X, Liu Y, Dai J, Yin J, Chen Y, Guo Y, Luo W, Liu N, Sun Y, Zhang S, Su B. Single-nucleus multi-omics analyses reveal cellular and molecular innovations in the anterior cingulate cortex during primate evolution. Cell Genomics 2024, 4: 100703. PMID: 39631404, PMCID: PMC11701334, DOI: 10.1016/j.xgen.2024.100703.Peer-Reviewed Original ResearchConceptsChromatin accessibilitySingle-nucleusGene expressionTranscription factor bindingPatterns of gene expressionSingle-nucleus resolutionCell lineage originACC gene expressionPrimate evolutionMulti-omics analysisAnterior cingulate cortexFactor bindingEvolutionary roleFunctional innovationSequence changesMolecular innovationsVon Economo neuronsMolecular regulationMarker genesPublished mouse dataCell typesChromatinMolecular identityHuman originCingulate cortexVEXAS Syndrome: Histiocytoid Cells With Feathery Cytoplasm as a Clue to the Diagnosis
Ko C, Odell I, Gehlhausen J, Leventhal J, McNiff J, Zubek A. VEXAS Syndrome: Histiocytoid Cells With Feathery Cytoplasm as a Clue to the Diagnosis. Journal Of Cutaneous Pathology 2024, 52: 108-112. PMID: 39610062, DOI: 10.1111/cup.14757.Peer-Reviewed Original ResearchCosGeneGate selects multi-functional and credible biomarkers for single-cell analysis
Liu T, Long W, Cao Z, Wang Y, He C, Zhang L, Strittmatter S, Zhao H. CosGeneGate selects multi-functional and credible biomarkers for single-cell analysis. Briefings In Bioinformatics 2024, 26: bbae626. PMID: 39592241, PMCID: PMC11596696, DOI: 10.1093/bib/bbae626.Peer-Reviewed Original ResearchThe cell-type underpinnings of the human functional cortical connectome
Anderson K, Chopra S, Dhamala E, Emani P, Gerstein M, Margulies D, Holmes A. The cell-type underpinnings of the human functional cortical connectome. Nature Neuroscience 2024, 28: 150-160. PMID: 39572742, DOI: 10.1038/s41593-024-01812-2.Peer-Reviewed Original ResearchSingle-nucleus RNA sequencing dataCell-type distributionRNA sequencing dataMicroarray dataSingle-nucleusIn vivo organizationCortical sheetCortical connectomeAllen Human Brain AtlasCell typesFunctional magnetic resonance imagingCellular fingerprintsCortical tissue samplesHuman Brain AtlasOrganization of cortexFunctional organization of cortexCellular compositionBrain atlasesFunctional organizationCellsEnriched cellsAssociative territoryFunctional propertiesTissue samplesSpatial topographyMetabolic complementation between cells drives the evolution of tissues and organs
Pavlicev M, DiFrisco J, Love A, Wagner G. Metabolic complementation between cells drives the evolution of tissues and organs. Biology Letters 2024, 20: 20240490. PMID: 39561800, PMCID: PMC11583983, DOI: 10.1098/rsbl.2024.0490.Peer-Reviewed Original ResearchConceptsMetabolic complementationEvolutionary transitionsCell typesSpecialized cell typesConstituent cell typesMetabolic constraintsMetabolic burdenCellular metabolismEvolution of tissuesSpecialized cellsSpecialized tissuesLevels of organizationCellsComplementOrganizationTissueNervous systemTypeMetabolismTargeting β-Catenin Protein Degradation in Refractory B-Cell Malignancies
Cosgun K, Robinson M, Agadzhanian N, Berning P, Fonseca-Arce D, Leveille E, Kothari S, Davids M, Jellusova J, Müschen M. Targeting β-Catenin Protein Degradation in Refractory B-Cell Malignancies. Blood 2024, 144: 1412. DOI: 10.1182/blood-2024-208598.Peer-Reviewed Original ResearchProtein degradationRepression of MYCTranscriptional repression of MYCTranscriptional repressionPromote survivalProteasome inhibitorsProtein degradation pathwaysCell typesN-terminal residuesInduce cell deathRefractory B-cell malignanciesB-cateninB-cell malignanciesRNAi screenInteractome studiesB cell selectionRepressive complexesGene dependenciesProteasomal degradationB cellsChemogenomic screensProteasome inhibitor bortezomibActivated mycDeletion of Ctnnb1Cell deathArtificial Intelligence-Powered Digital Pathology to Improve Diagnosis and Personalized Prognostic Assessment in Patient with Myeloid Neoplasms
Asti G, Curti N, Maggioni G, Carlini G, Lanino L, Campagna A, D'Amico S, Sauta E, Delleani M, Bonometti A, Lancellotti C, Rahal D, Ubezio M, Todisco G, Tentori C, Russo A, Crespi A, Figini G, Buizza A, Riva E, Zampini M, Brindisi M, Ficara F, Crisafulli L, Ventura D, Pinocchio N, Zazzetti E, Bicchieri M, Grondelli M, Forcina Barrero A, Savevski V, Santoro A, Santini V, Sole F, Platzbecker U, Fenaux P, Diez-Campelo M, Komrokji R, Haferlach T, Kordasti S, Di Tommaso L, Zeidan A, Loghavi S, Garcia-Manero G, Castellani G, Della Porta M. Artificial Intelligence-Powered Digital Pathology to Improve Diagnosis and Personalized Prognostic Assessment in Patient with Myeloid Neoplasms. Blood 2024, 144: 3598-3598. DOI: 10.1182/blood-2024-206248.Peer-Reviewed Original ResearchLeukemia-free survivalMyeloid neoplasmsOverall survivalConcordance indexGenomic informationBone marrowPredictive of overall survivalMD Anderson Cancer CenterCell typesProportion of patientsHarrell's concordance indexSomatic gene mutationsMorphological featuresHumanitas Research HospitalGenomic dataMGG smearsPersonalized risk assessmentRUNX1 mutationsBM aspiratesClinically relevant informationClinical entityBiopsy dataMN patientsPrognostic assessmentWhole slide images
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