New methodologies in ageing research

Ageing is arguably the most complex phenotype that occurs in humans. To understand and treat ageing as well as associated diseases, highly specialised technologies are emerging that reveal critical insight into the underlying mechanisms and provide new hope for previously untreated diseases. Herein, we describe the latest developments in cutting edge technologies applied across the field of ageing research. We cover emerging model organisms, high-throughput methodologies and machine-driven approaches. In all, this review will give you a glimpse of what will be pushing the field onwards and upwards.

[1]  P. N. Lee,et al.  Cancer and ageing in mice and men. , 1975, British Journal of Cancer.

[2]  Luigi Ferrucci,et al.  Of aging mice and men: gait speed decline is a translatable trait, with species-specific underlying properties. , 2019, The journals of gerontology. Series A, Biological sciences and medical sciences.

[3]  J. J. Crofts,et al.  Identification of novel genes associated with longevity in Drosophila melanogaster - a computational approach , 2019, Aging.

[4]  D. Promislow,et al.  The dog aging project: translational geroscience in companion animals , 2016, Mammalian Genome.

[5]  Anders Krogh,et al.  Genome analysis reveals insights into physiology and longevity of the Brandt’s bat Myotis brandtii , 2013, Nature Communications.

[6]  Matt Kaeberlein,et al.  Microfluidic technologies for yeast replicative lifespan studies , 2017, Mechanisms of Ageing and Development.

[7]  S. Brunak,et al.  Mining electronic health records: towards better research applications and clinical care , 2012, Nature Reviews Genetics.

[8]  Namory D. Bagayoko,et al.  The effects of dietary caloric restriction on antioxidant status and lipid peroxidation in mild and severe streptozotocin-induced diabetic rats. , 2004, Clinica chimica acta; international journal of clinical chemistry.

[9]  Andreas Keller,et al.  Undulating changes in human plasma proteome profiles across the lifespan , 2019, Nature Medicine.

[10]  D. Valenzano,et al.  Microbiome evolution during host aging , 2019, PLoS pathogens.

[11]  B. Robaire,et al.  HT-COMET: a novel automated approach for high throughput assessment of human sperm chromatin quality. , 2016, Human reproduction.

[12]  Param Priya Singh,et al.  A Platform for Rapid Exploration of Aging and Diseases in a Naturally Short-Lived Vertebrate , 2015, Cell.

[13]  R. Vandenbroucke,et al.  Mouse models of ageing and their relevance to disease , 2016, Mechanisms of Ageing and Development.

[14]  Sandor Beniczky,et al.  Wearable devices for sudden unexpected death in epilepsy prevention , 2018, Epilepsia.

[15]  C. Kenyon,et al.  A C. elegans mutant that lives twice as long as wild type , 1993, Nature.

[16]  Evgeny Putin,et al.  Deep biomarkers of human aging: Application of deep neural networks to biomarker development , 2016, Aging.

[17]  M. Rosenkilde,et al.  Sustained effect of glucagon on body weight and blood glucose: Assessed by continuous glucose monitoring in diabetic rats , 2018, PloS one.

[18]  M B VISSCHER,et al.  The effects of dietary caloric restriction on maturity and senescence, with particular reference to fertility and longevity. , 1947, The American journal of physiology.

[19]  J. Whitwell,et al.  Alzheimer's disease neuroimaging , 2018, Current opinion in neurology.

[20]  J. Auwerx,et al.  Automated Platform for Long-Term Culture and High-Content Phenotyping of Single C. elegans Worms , 2019, Scientific Reports.

[21]  Paola Sebastiani,et al.  The Genetics of Extreme Longevity: Lessons from the New England Centenarian Study , 2012, Front. Gene..

[22]  M. Tatar,et al.  A Mutant Drosophila Insulin Receptor Homolog That Extends Life-Span and Impairs Neuroendocrine Function , 2001, Science.

[23]  T. Misteli,et al.  Reversal of the cellular phenotype in the premature aging disease Hutchinson-Gilford progeria syndrome , 2005, Nature Medicine.

[24]  David B. Goldstein,et al.  Genome-Wide Transcript Profiles in Aging and Calorically Restricted Drosophila melanogaster , 2002, Current Biology.

[25]  D. Martinez,et al.  Mortality Patterns Suggest Lack of Senescence in Hydra , 1998, Experimental Gerontology.

[27]  P. Verstreken,et al.  A Single-Cell Transcriptome Atlas of the Aging Drosophila Brain , 2018, Cell.

[28]  T. Coşkun,et al.  Fully Implantable Arterial Blood Glucose Device for Metabolic Research Applications in Rats for Two Months , 2015, Journal of diabetes science and technology.

[29]  P. Sebastiani,et al.  Meta-analysis of genetic variants associated with human exceptional longevity , 2013, Aging.

[30]  E. Mercken,et al.  Declining NAD+ Induces a Pseudohypoxic State Disrupting Nuclear-Mitochondrial Communication during Aging , 2013, Cell.

[31]  D. Penn,et al.  Social Isolation Shortens Telomeres in African Grey Parrots (Psittacus erithacus erithacus) , 2014, PloS one.

[32]  Alexander A. Morgan,et al.  Mouse models rarely mimic the transcriptome of human neurodegenerative diseases: A systematic bioinformatics-based critique of preclinical models. , 2015, European journal of pharmacology.

[33]  N. Allbritton,et al.  A High-Throughput Organoid Microinjection Platform to Study Gastrointestinal Microbiota and Luminal Physiology , 2018, Cellular and molecular gastroenterology and hepatology.

[34]  Wei Liu,et al.  High-throughput analysis of yeast replicative aging using a microfluidic system , 2015, Proceedings of the National Academy of Sciences.

[35]  T. Johnson Advantages and disadvantages of Caenorhabditis elegans for aging research , 2003, Experimental Gerontology.

[36]  Shane T. Jensen,et al.  Potential Mechanisms for Cancer Resistance in Elephants and Comparative Cellular Response to DNA Damage in Humans. , 2015, JAMA.

[37]  Anders M. Dale,et al.  Precision medicine screening using whole-genome sequencing and advanced imaging to identify disease risk in adults , 2017, Proceedings of the National Academy of Sciences.

[38]  T. Spector,et al.  An unsupervised learning approach to identify novel signatures of health and disease from multimodal data , 2020, Genome Medicine.

[39]  D. Bellwood,et al.  Shortest recorded vertebrate lifespan found in a coral reef fish , 2005, Current Biology.

[40]  G. Amdam,et al.  The curious case of aging plasticity in honey bees , 2010, FEBS letters.

[41]  Marco Pahor,et al.  Rapamycin fed late in life extends lifespan in genetically heterogeneous mice , 2009, Nature.

[42]  T. Ideker,et al.  Genome-wide methylation profiles reveal quantitative views of human aging rates. , 2013, Molecular cell.

[43]  Markus Schuelke,et al.  The spectrum of WRN mutations in Werner syndrome patients , 2006, Human mutation.

[44]  M. Klass,et al.  Aging in the nematode Caenorhabditis elegans: Major biological and environmental factors influencing life span , 1977, Mechanisms of Ageing and Development.

[45]  J. George,et al.  The transcriptome of the bowhead whale Balaena mysticetus reveals adaptations of the longest-lived mammal , 2014, Aging.

[46]  Colin A. Depp,et al.  Artificial intelligence approaches to predicting and detecting cognitive decline in older adults: A conceptual review , 2019, Psychiatry Research.

[47]  H. Okano,et al.  Awake functional MRI detects neural circuit dysfunction in a mouse model of autism , 2020, Science Advances.

[48]  R. de Cabo,et al.  Cockayne syndrome group B protein prevents the accumulation of damaged mitochondria by promoting mitochondrial autophagy , 2012, The Journal of experimental medicine.

[49]  S. Wanless,et al.  Telomere loss in relation to age and early environment in long-lived birds , 2004, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[50]  T. Brey,et al.  Imperceptible senescence: Ageing in the ocean quahog Arctica islandica , 2008, Free radical research.

[51]  M. Pellegrini,et al.  Distinct Shifts in Microbiota Composition during Drosophila Aging Impair Intestinal Function and Drive Mortality. , 2015, Cell reports.

[52]  T. Shike,et al.  Animal models. , 2001, Contributions to nephrology.

[53]  T. Seeman,et al.  Social Environment Effects on Health and Aging , 2001, Annals of the New York Academy of Sciences.

[54]  R. de Cabo,et al.  Animal models of aging research: implications for human aging and age-related diseases. , 2015, Annual review of animal biosciences.

[55]  R. Mortimer,et al.  Life Span of Individual Yeast Cells , 1959, Nature.

[56]  A. A. Romanovsky,et al.  Body Temperature Measurements for Metabolic Phenotyping in Mice , 2017, Front. Physiol..

[57]  Mathias Jucker,et al.  The benefits and limitations of animal models for translational research in neurodegenerative diseases , 2010, Nature Medicine.

[58]  Christopher Probst,et al.  High-throughput organ-on-a-chip systems: Current status and remaining challenges , 2018, Current Opinion in Biomedical Engineering.

[59]  N. Marshall,et al.  Toward an MRI-Based Mesoscale Connectome of the Squid Brain , 2020, iScience.

[60]  Olivier Elemento,et al.  A Bayesian machine learning approach for drug target identification using diverse data types , 2019, Nature Communications.

[61]  S. Luo,et al.  Relationship between Homocysteine and Muscle Strength Decline: The Baltimore Longitudinal Study of Aging , 2018, The journals of gerontology. Series A, Biological sciences and medical sciences.

[62]  S. Horvath DNA methylation age of human tissues and cell types , 2013, Genome Biology.

[63]  Richard D. Emes,et al.  TP53 copy number expansion is associated with the evolution of increased body size and an enhanced DNA damage response in elephants , 2015, bioRxiv.

[64]  M. Levine,et al.  DNA methylation-based measures of biological age: meta-analysis predicting time to death , 2016, Aging.

[65]  Hai Su,et al.  Pathologist-level interpretable whole-slide cancer diagnosis with deep learning , 2019, Nat. Mach. Intell..

[66]  Kristine L Witt,et al.  Next generation high throughput DNA damage detection platform for genotoxic compound screening , 2018, Scientific Reports.

[67]  H. Weimerskirch,et al.  Patterns of aging in the long-lived wandering albatross , 2010, Proceedings of the National Academy of Sciences.

[68]  S. Studenski,et al.  Gait speed and survival in older adults. , 2011, JAMA.

[69]  Alex P. Reiner,et al.  DNA methylation GrimAge strongly predicts lifespan and healthspan , 2019, Aging.

[70]  David M. Wilson,et al.  A high-fat diet and NAD(+) activate Sirt1 to rescue premature aging in cockayne syndrome. , 2014, Cell metabolism.

[71]  Saket Navlakha,et al.  Predicting age from the transcriptome of human dermal fibroblasts , 2018, Genome Biology.

[72]  Evgeny Putin,et al.  Population Specific Biomarkers of Human Aging: A Big Data Study Using South Korean, Canadian, and Eastern European Patient Populations , 2018, The journals of gerontology. Series A, Biological sciences and medical sciences.

[73]  Param Priya Singh,et al.  The African Turquoise Killifish Genome Provides Insights into Evolution and Genetic Architecture of Lifespan , 2015, Cell.

[74]  E. Nishida,et al.  Lifespan-regulating genes in C. elegans , 2016, npj Aging and Mechanisms of Disease.

[75]  Ashish Rajput,et al.  Systematic analysis of the gerontome reveals links between aging and age-related diseases , 2016, Human molecular genetics.

[76]  Lijun Wu,et al.  Comparative Analysis of Bat Genomes Provides Insight into the Evolution of Flight and Immunity , 2013, Science.

[77]  C. Franceschi,et al.  Genes involved in immune response/inflammation, IGF1/insulin pathway and response to oxidative stress play a major role in the genetics of human longevity: the lesson of centenarians , 2005, Mechanisms of Ageing and Development.

[78]  D. Selkoe Alzheimer's disease. , 2011, Cold Spring Harbor perspectives in biology.

[79]  L. Kunkel,et al.  Exceptional Familial Clustering for Extreme Longevity in Humans , 2000, Journal of the American Geriatrics Society.

[80]  C. Franceschi,et al.  The impact of mitochondrial DNA on human lifespan: A view from studies on centenarians , 2008, Biotechnology journal.

[81]  J. Jarvis,et al.  The naked mole rat--a new record for the oldest living rodent. , 2002, Science of aging knowledge environment : SAGE KE.

[82]  C. López-Otín,et al.  Mouse Models to Disentangle the Hallmarks of Human Aging , 2018, Circulation research.

[83]  R. M. Lanner,et al.  Does bristlecone pine senesce? , 2001, Experimental Gerontology.

[84]  C. Ramsey,et al.  Eye lens radiocarbon reveals centuries of longevity in the Greenland shark (Somniosus microcephalus) , 2016, Science.

[85]  L. Guarente,et al.  Extrachromosomal rDNA Circles— A Cause of Aging in Yeast , 1997, Cell.

[86]  L. Guarente,et al.  The NAD+/Sirtuin Pathway Modulates Longevity through Activation of Mitochondrial UPR and FOXO Signaling , 2013, Cell.

[87]  Geraint Rees,et al.  Clinically applicable deep learning for diagnosis and referral in retinal disease , 2018, Nature Medicine.

[88]  Stefan Klöppel,et al.  Estimating the age of healthy subjects from T1-weighted MRI scans using kernel methods: Exploring the influence of various parameters , 2010, NeuroImage.

[89]  Zhengdong D. Zhang,et al.  Comparative analysis of genome maintenance genes in naked mole rat, mouse, and human , 2015, Aging cell.

[90]  J. Maciejewski,et al.  New drugs for pharmacological extension of replicative life span in normal and progeroid cells , 2019, npj Aging and Mechanisms of Disease.

[91]  Ruey-Feng Chang,et al.  A computer-aided diagnosis system for differentiation and delineation of malignant regions on whole-slide prostate histopathology image using spatial statistics and multidimensional DenseNet. , 2019, Medical physics.

[92]  Q. Ouyang,et al.  Single Cell Analysis of Yeast Replicative Aging Using a New Generation of Microfluidic Device , 2012, PloS one.

[93]  A. Yashin,et al.  Genes, demography, and life span: the contribution of demographic data in genetic studies on aging and longevity. , 1999, American journal of human genetics.

[94]  T. Misteli,et al.  A high-content imaging-based screening pipeline for the systematic identification of anti-progeroid compounds. , 2016, Methods.

[95]  M. Portero-Otín,et al.  A Stress-Resistant Lipidomic Signature Confers Extreme Longevity to Humans , 2017, The journals of gerontology. Series A, Biological sciences and medical sciences.

[96]  Marcia K. Johnson,et al.  Cross-trial prediction of treatment outcome in depression: a machine learning approach. , 2016, The lancet. Psychiatry.

[97]  A. Ehrenberg,et al.  Comprehensive Geriatric Assessment for Frail Older People in Swedish Acute Care Settings (CGA-Swed): A Randomised Controlled Study , 2020, Geriatrics.

[98]  A. Fire,et al.  Ingestion of bacterially expressed dsRNAs can produce specific and potent genetic interference in Caenorhabditis elegans. , 2001, Gene.

[99]  R. Faragher,et al.  What Can Progeroid Syndromes Tell Us About Human Aging? , 2004, Science.

[100]  Matthias Heinemann,et al.  Whole lifespan microscopic observation of budding yeast aging through a microfluidic dissection platform , 2012, Proceedings of the National Academy of Sciences.

[101]  K. Hughes,et al.  Gene expression patterns associated with queen honey bee longevity , 2005, Mechanisms of Ageing and Development.

[102]  P. Blier,et al.  The extreme longevity of Arctica islandica is associated with increased peroxidation resistance in mitochondrial membranes , 2012, Aging cell.

[103]  Olga Kononova,et al.  Unsupervised word embeddings capture latent knowledge from materials science literature , 2019, Nature.

[104]  V. Labunskyy,et al.  Emerging Omics Approaches in Aging Research. , 2017, Antioxidants & redox signaling.

[105]  T. Crawford,et al.  Survival probability in ataxia telangiectasia , 2005, Archives of Disease in Childhood.

[106]  Ali Işın,et al.  Cardiac arrhythmia detection using deep learning , 2017 .

[107]  P. Schofield,et al.  Review and meta-analysis of genetic polymorphisms associated with exceptional human longevity , 2018, Mechanisms of Ageing and Development.

[108]  A. Bang,et al.  High-throughput screen for compounds that modulate neurite growth of human induced pluripotent stem cell-derived neurons , 2018, Disease Models & Mechanisms.

[109]  Feng-hua Liu,et al.  A systematic analysis , 2020 .

[110]  João Pedro de Magalhães,et al.  Human Ageing Genomic Resources: new and updated databases , 2017, Nucleic Acids Res..

[111]  Y. Jan,et al.  Genome-wide study of aging and oxidative stress response in Drosophila melanogaster. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[112]  G. Amdam,et al.  Age-related learning deficits can be reversible in honeybees Apis mellifera , 2012, Experimental Gerontology.

[113]  B. Rogina,et al.  Genetics of aging in the fruit fly, Drosophila melanogaster. , 2003, Annual review of genetics.

[114]  Evgeny Putin,et al.  Human microbiome aging clocks based on deep learning and tandem of permutation feature importance and accumulated local effects , 2018, bioRxiv.

[115]  J. Hoeijmakers DNA damage, aging, and cancer. , 2009, The New England journal of medicine.

[116]  Demis Hassabis,et al.  Improved protein structure prediction using potentials from deep learning , 2020, Nature.

[117]  E. Kirkness,et al.  Precision medicine integrating whole-genome sequencing, comprehensive metabolomics, and advanced imaging , 2020, Proceedings of the National Academy of Sciences.

[118]  S. Gatti The rôle of sponges in high-Antarctic carbon and silicon cycling - a modelling approach = Die Rolle der Schwämme im hochantarktischen Kohlenstoff- und Silikatkreislauf - ein Modellierungsansatz , 2002 .

[119]  K. White,et al.  Giant tortoise genomes provide insights into longevity and age-related disease , 2018, Nature Ecology & Evolution.

[120]  T. Johnson,et al.  A mutation in the age-1 gene in Caenorhabditis elegans lengthens life and reduces hermaphrodite fertility. , 2002, Genetics.

[121]  D. Rueckert,et al.  Machine learning in whole-body MRI: experiences and challenges from an applied study using multicentre data. , 2019, Clinical radiology.

[122]  David K. Wood,et al.  Single cell trapping and DNA damage analysis using microwell arrays , 2010, Proceedings of the National Academy of Sciences.

[123]  Björn Egert,et al.  Metabolite patterns predicting sex and age in participants of the Karlsruhe Metabolomics and Nutrition (KarMeN) study , 2017, PloS one.

[124]  Manuel Serrano,et al.  The Hallmarks of Aging , 2013, Cell.

[125]  N. Grishin,et al.  Insights into the Evolution of Longevity from the Bowhead Whale Genome , 2015, Cell reports.

[126]  L. Ferrucci,et al.  Objectively Measured Physical Activity and Falls in Well-Functioning Older Adults: Findings From the Baltimore Longitudinal Study of Aging , 2017, American journal of physical medicine & rehabilitation.

[127]  Sebastian Thrun,et al.  Dermatologist-level classification of skin cancer with deep neural networks , 2017, Nature.

[128]  Steve Iliffe,et al.  Comprehensive geriatric assessment for older adults , 2011, BMJ : British Medical Journal.

[129]  Peter Langhorne,et al.  Comprehensive geriatric assessment for older adults admitted to hospital. , 2011, The Cochrane database of systematic reviews.

[130]  M. Scheibye-Knudsen,et al.  Monogenic Diseases of DNA Repair , 2017, The New England journal of medicine.

[131]  R. Pamplona,et al.  Exceptional human longevity is associated with a specific plasma phenotype of ether lipids , 2019, Redox biology.

[132]  Artem Sevastopolsky,et al.  PhotoAgeClock: deep learning algorithms for development of non-invasive visual biomarkers of aging , 2018, Aging.

[133]  Thomas Julou,et al.  Monitoring single-cell gene regulation under dynamically controllable conditions with integrated microfluidics and software , 2018, Nature Communications.

[134]  Patrick M. Smith,et al.  Regulation of life span by the gut microbiota in the short-lived African turquoise killifish , 2017, bioRxiv.

[135]  M. Acar,et al.  Yeast Replicator: A High-Throughput Multiplexed Microfluidics Platform for Automated Measurements of Single-Cell Aging. , 2015, Cell reports.

[136]  H. Dowse,et al.  Longitudinal assessment of health-span and pre-death morbidity in wild type Drosophila , 2019, Aging.

[137]  P. Brigidi,et al.  Through Ageing, and Beyond: Gut Microbiota and Inflammatory Status in Seniors and Centenarians , 2010, PloS one.

[138]  M. Labouesse [Caenorhabditis elegans]. , 2003, Medecine sciences : M/S.

[139]  Kristin Branson,et al.  Machine vision methods for analyzing social interactions , 2017, Journal of Experimental Biology.

[140]  Sang-Goo Lee,et al.  Using DNA Methylation Profiling to Evaluate Biological Age and Longevity Interventions. , 2017, Cell metabolism.

[141]  Steve Horvath,et al.  Epigenetic Predictor of Age , 2011, PloS one.

[142]  M. Scheibye-Knudsen,et al.  A defined human aging phenome. , 2019, Aging.

[143]  P. Baldi,et al.  Population-wide analysis of differences in disease progression patterns in men and women , 2019, Nature Communications.

[144]  H. Völzke,et al.  Measuring Biological Age via Metabonomics: The Metabolic Age Score. , 2016, Journal of proteome research.

[145]  David A. Mucciarone,et al.  Extreme longevity in proteinaceous deep-sea corals , 2009, Proceedings of the National Academy of Sciences.

[147]  Christopher J. Murakami,et al.  A molecular mechanism of chronological aging in yeast , 2009, Cell cycle.

[148]  Alán Aspuru-Guzik,et al.  Deep learning enables rapid identification of potent DDR1 kinase inhibitors , 2019, Nature Biotechnology.

[149]  Alessandro Cellerino,et al.  Extremely short lifespan in the annual fish Nothobranchius furzeri , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[150]  Susana Carvalho,et al.  Chimpanzee face recognition from videos in the wild using deep learning , 2019, Science Advances.

[151]  B. Thiers Phenotype and Course of Hutchinson–Gilford Progeria Syndrome , 2009 .

[152]  J. Binder,et al.  Across the Life Span , 2013 .

[153]  Robert I. Reid,et al.  Development of a cerebrovascular magnetic resonance imaging biomarker for cognitive aging , 2018, Annals of neurology.

[154]  Andrew Janowczyk,et al.  Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases , 2016, Journal of pathology informatics.

[155]  João Pedro de Magalhães,et al.  The Business of Anti-Aging Science. , 2017, Trends in biotechnology.

[156]  L. Ferrucci,et al.  Hearing loss and cognition in the Baltimore Longitudinal Study of Aging. , 2011, Neuropsychology.

[157]  Andrew H. Beck,et al.  Computationally-Guided Development of a Stromal Inflammation Histologic Biomarker in Lung Squamous Cell Carcinoma , 2018, Scientific Reports.

[158]  Akihiro Nakamura,et al.  Low-cost three-dimensional gait analysis system for mice with an infrared depth sensor , 2015, Neuroscience Research.

[159]  R. de Cabo,et al.  A toolbox for the longitudinal assessment of healthspan in aging mice , 2020, Nature Protocols.

[160]  J. Goodship,et al.  The Cockayne Syndrome Natural History (CoSyNH) study: clinical findings in 102 individuals and recommendations for care , 2015, Genetics in Medicine.

[161]  Walter Fontana,et al.  The Caenorhabditis elegans Lifespan Machine , 2013, Nature Methods.

[162]  J. Cleaver,et al.  Xeroderma pigmentosum: a human disease in which an initial stage of DNA repair is defective. , 1969, Proceedings of the National Academy of Sciences of the United States of America.

[163]  P. Sivaramakrishnan,et al.  Microbial Genetic Composition Tunes Host Longevity , 2017, Cell.

[164]  Prolonging Life. , 1910, Journal of the National Medical Association.

[165]  Andreas V Larentzakis,et al.  Can Wearable Devices Accurately Measure Heart Rate Variability? A Systematic Review , 2018, Folia medica.

[166]  R. E. Page,et al.  Aging and development in social insects with emphasis on the honey bee, Apis mellifera L. , 2001, Experimental Gerontology.

[167]  L. Brace,et al.  Defective Mitophagy in XPA via PARP-1 Hyperactivation and NAD+/SIRT1 Reduction , 2014, Cell.

[168]  R. Effros,et al.  Decline in CD28+ T cells in centenarians and in long-term T cell cultures: A possible cause for both in vivo and in vitro immunosenescence , 1994, Experimental Gerontology.