Ruben De Man
About
Research
Publications
2026
A74-12 An Ex Vivo Model of Induced Lung Aging Reveals Age-dependent Predisposition to Oxidative Stress and Cellular Senescence
De Man R, Rangel R, Marti Munoz J, Khoury J, Anderson S, Lin L, Adams T, Ahangari F, Manning E, Kaminski N. A74-12 An Ex Vivo Model of Induced Lung Aging Reveals Age-dependent Predisposition to Oxidative Stress and Cellular Senescence. American Journal Of Respiratory And Critical Care Medicine 2026, 212: aamag162.5347. DOI: 10.1093/ajrccm/aamag162.5347.Peer-Reviewed Original ResearchPrecision-cut lung slicesProportion of Ki67-positive cellsEx vivo modelKi67-positive cellsAging LungLung diseasePositive cellsCellular senescenceLung slicesAge-related lung diseasePredisposition to oxidative stressProportion of positive cellsSenescence inductionHydrogen peroxide treatmentSenescence marker p21P21-positive cellsCdkn1a (p21Differential gene expressionDose-dependent effectDose-dependent mannerOxidative stress-induced cellular senescenceFetal bovine serumAlveolar simplificationStress-induced cellular senescenceProliferation markersProximal Pulmonary Artery Stiffening as a Biomarker of Cardiopulmonary Aging
De Man R, Cai Z, Doddaballapur P, Guerrera N, Regan A, Lin L, Schwarz E, Justet A, Abu Hussein N, Di Palo J, Cavinato C, Raredon M, Heerdt P, Singh I, Yan X, Kang M, Bruns D, Lee P, Tellides G, Humphrey J, Kaminski N, Ramachandra A, Manning E. Proximal Pulmonary Artery Stiffening as a Biomarker of Cardiopulmonary Aging. Aging Cell 2026, 25: e70383. PMID: 41589414, PMCID: PMC12836046, DOI: 10.1111/acel.70383.Peer-Reviewed Original ResearchConceptsProximal pulmonary arteriesPulmonary arterySmooth muscle cellsPerivascular macrophagesMouse modelMuscle cellsRight ventricle functionMedial smooth muscle cellsPulmonary arterial stiffeningRight ventricleVentricle functionAssociated with senescenceECM turnoverLung functionArterial stiffeningArteryAdventitial fibroblastsMolecular targetsAge-relatedGeroscience hypothesisLungAgeIntercellular signalingMiceMacrophagesSingle-cell atlas of human lung aging identifies cell type dyssynchrony and increased transcriptional entropy
De Man R, McDonough J, Adams T, Nikola F, Rangel R, Anderson S, Manning E, Cala Garcia J, Moss B, Waich A, Poli F, Cardenas R, Coarfa C, Song Q, Bar-Joseph Z, Vanaudenaerde B, Wuyts W, Niklason L, Raredon M, Yan X, Rosas I, Kaminski N. Single-cell atlas of human lung aging identifies cell type dyssynchrony and increased transcriptional entropy. Nature Communications 2026, 17: 2095. PMID: 41571679, PMCID: PMC12953888, DOI: 10.1038/s41467-026-68810-9.Peer-Reviewed Original ResearchConceptsGenomic landscapeLung ageSingle-cell atlasAlveolar epithelialIndependent predictorsAnalysis of somatic mutationsSingle-cell dataSingle-cell RNA sequencingEndothelial cellsLoss of differentiationAlveolar epithelial cellsRNA sequencingTranscriptional changesCell-typeEndothelial cell typesSomatic mutationsMutational burdenAT2 cellsLung diseaseCell typesAge-related changesEpithelial cellsRisk factorsSenescence signatureEpithelial
2025
Epigenetic age acceleration in idiopathic pulmonary fibrosis revealed by DNA methylation clocks
Kurbanov D, Ahangari F, Adams T, De Man R, Tang J, Carlon M, Abu Hussein N, Cortesi E, Zapata M, De Sadelaar L, Wuyts W, Vanaudenaerde B, Kaminski N, McDonough J. Epigenetic age acceleration in idiopathic pulmonary fibrosis revealed by DNA methylation clocks. American Journal Of Physiology - Lung Cellular And Molecular Physiology 2025, 328: l456-l462. PMID: 39970931, PMCID: PMC12169420, DOI: 10.1152/ajplung.00171.2024.Peer-Reviewed Original ResearchConceptsIdiopathic pulmonary fibrosisIdiopathic pulmonary fibrosis tissuePulmonary fibrosisLung tissueEpigenetic clocksPotential of DNA methylationDNA methylation levelsDebilitating lung diseaseIllumina MethylationEPIC arrayHuman lung tissueEpigenetic ageDNA methylation clocksBiological ageAffected lung tissueIPF casesClinical prognosisMethylation patternsDNA methylationLung diseaseHealthy controlsAcceleration of biological agingMethylation levelsMethylationEPIC arrayAge accelerationClinical assessment
2024
Predicting lung aging using scRNA-Seq data
Song Q, Singh A, McDonough J, Adams T, Vos R, De Man R, Myers G, Ceulemans L, Vanaudenaerde B, Wuyts W, Yan X, Schupp J, Hagood J, Kaminski N, Bar-Joseph Z. Predicting lung aging using scRNA-Seq data. PLOS Computational Biology 2024, 20: e1012632. PMID: 39700255, PMCID: PMC11741621, DOI: 10.1371/journal.pcbi.1012632.Peer-Reviewed Original ResearchA Single-cell Atlas of Human Lung Aging Reveals Cell-type Specific Signatures
De Man R, McDonough J, Adams T, Sharma P, Moss B, Yan X, Rosas I, Kaminski N. A Single-cell Atlas of Human Lung Aging Reveals Cell-type Specific Signatures. American Journal Of Respiratory And Critical Care Medicine 2024, 209: a3195-a3195. DOI: 10.1164/ajrccm-conference.2024.209.1_meetingabstracts.a3195.Peer-Reviewed Original ResearchFENDRR LNCRNA Knockout Leads to Age-associated Senescence Signature in Mouse Lung Endothelial Cells
De Man R, Cosme C, Adams T, Ahangari F, Manning E, Sakamoto K, Kaminski N. FENDRR LNCRNA Knockout Leads to Age-associated Senescence Signature in Mouse Lung Endothelial Cells. American Journal Of Respiratory And Critical Care Medicine 2024, 209: a3196-a3196. DOI: 10.1164/ajrccm-conference.2024.209.1_meetingabstracts.a3196.Peer-Reviewed Original Research
2019
Hybrid Neural Networks for Mortality Prediction from LDCT Images
Yan P, Guo H, Wang G, De Man R, Kalra MK. Hybrid Neural Networks for Mortality Prediction from LDCT Images. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2019, 00: 6243-6246. PMID: 31947269, DOI: 10.1109/embc.2019.8857180.Peer-Reviewed Original ResearchConceptsLow-dose CTMortality predictionLung cancer patientsCancer mortality predictionsMortality risk predictionLung cancer subjectsCause mortalityHigh morbidityCancer patientsLung cancerImaging featuresCardiovascular diseaseCancer subjectsHigh riskMortality riskRisk scoreMortality rateClinical practiceDeadly diseaseRisk predictionLDCT imagesDiseaseRiskSame populationScoring methodComparison of deep learning and human observer performance for lesion detection and characterization
De Man R, Gang G, Li X, Wang G. Comparison of deep learning and human observer performance for lesion detection and characterization. Proceedings Of SPIE--the International Society For Optical Engineering 2019, 11072: 110721f-110721f-5. DOI: 10.1117/12.2532331.Peer-Reviewed Original ResearchComparison of deep learning and human observer performance for detection and characterization of simulated lesions
De Man R, Gang GJ, Li X, Wang G. Comparison of deep learning and human observer performance for detection and characterization of simulated lesions. Journal Of Medical Imaging 2019, 6: 025503-025503. PMID: 31263738, PMCID: PMC6586983, DOI: 10.1117/1.jmi.6.2.025503.Peer-Reviewed Original Research