Evaluation of somatic copy number variation detection by NGS technologies and bioinformatics tools on a hyper-diploid cancer genome.

BACKGROUND: Copy number variation (CNV) is a key genetic characteristic for cancer diagnostics and can be used as a biomarker for the selection of therapeutic treatments. Using data sets established in our previous study, we benchmark the performance of cancer CNV calling by six most recent and commonly used software tools on their detection accuracy, sensitivity, and reproducibility. In comparison to other orthogonal methods, such as microarray and Bionano, we also explore the consistency of CNV calling across different technologies on a challenging genome. RESULTS: While consistent results are observed for copy gain, loss, and loss of heterozygosity (LOH) calls across sequencing centers, CNV callers, and different technologies, variation of CNV calls are mostly affected by the determination of genome ploidy. Using consensus results from six CNV callers and confirmation from three orthogonal methods, we establish a high confident CNV call set for the reference cancer cell line (HCC1395). CONCLUSIONS: NGS technologies and current bioinformatics tools can offer reliable results for detection of copy gain, loss, and LOH. However, when working with a hyper-diploid genome, some software tools can call excessive copy gain or loss due to inaccurate assessment of genome ploidy. With performance matrices on various experimental conditions, this study raises awareness within the cancer research community for the selection of sequencing platforms, sample preparation, sequencing coverage, and the choice of CNV detection tools.

3D genomic mapping reveals multifocality of human pancreatic precancers.

Pancreatic intraepithelial neoplasias (PanINs) are the most common precursors of pancreatic cancer, but their small size and inaccessibility in humans make them challenging to study1. Critically, the number, dimensions and connectivity of human PanINs remain largely unknown, precluding important insights into early cancer development. Here, we provide a microanatomical survey of human PanINs by analysing 46 large samples of grossly normal human pancreas with a machine-learning pipeline for quantitative 3D histological reconstruction at single-cell resolution. To elucidate genetic relationships between and within PanINs, we developed a workflow in which 3D modelling guides multi-region microdissection and targeted and whole-exome sequencing. From these samples, we calculated a mean burden of 13 PanINs per cm3 and extrapolated that the normal intact adult pancreas harbours hundreds of PanINs, almost all with oncogenic KRAS hotspot mutations. We found that most PanINs originate as independent clones with distinct somatic mutation profiles. Some spatially continuous PanINs were found to contain multiple KRAS mutations; computational and in situ analyses demonstrated that different KRAS mutations localize to distinct cell subpopulations within these neoplasms, indicating their polyclonal origins. The extensive multifocality and genetic heterogeneity of PanINs raises important questions about mechanisms that drive precancer initiation and confer differential progression risk in the human pancreas. This detailed 3D genomic mapping of molecular alterations in human PanINs provides an empirical foundation for early detection and rational interception of pancreatic cancer.

Ginsenoside Rg3: A Review of its Anticancer Mechanisms and Potential Therapeutic Applications.

BACKGROUND: Traditional Chinese Medicine (TCM) has a long history of treating various diseases and is increasingly being recognized as a complementary therapy for cancer. A promising natural compound extracted from the Chinese herb ginseng is ginsenoside Rg3, which has demonstrated significant anticancer effects. It has been tested in a variety of cancers and tumors and has proven to be effective in suppressing cancer. OBJECTIVES: This work covers various aspects of the role of ginsenoside Rg3 in cancer treatment, including its biological functions, key pathways, epigenetics, and potential for combination therapies, all of which have been extensively researched and elucidated. The study aims to provide a reference for future research on ginsenoside Rg3 as an anticancer agent and a support for the potential application of ginsenoside Rg3 in cancer treatment.

An Efficient and Fast Method for Labeling and Analyzing Mouse Glomeruli.

The glomeruli are fundamental units in the kidney; hence, studying the glomeruli is pivotal for understanding renal function and pathology. Biological imaging provides intuitive information; thus, it is of great significance to label and observe the glomeruli. However, the glomeruli observation methods currently in use require complicated operations, and the results may lose label details or three-dimensional (3D) information. The clear, unobstructed brain imaging cocktails and computational analysis (CUBIC) tissue clearing technology has been widely used in renal research, allowing for more accurate detection and deeper detection depth. We found that mouse glomeruli can be rapidly and effectively labeled by tail vein injection of medium molecular weight FITC-Dextran followed by the CUBIC clearing method. The cleared mouse kidney could be scanned by a light-sheet microscope (or a confocal microscope when sliced) to obtain three-dimensional image stacks of all the glomeruli in the entire kidney. Processed with appropriate software, the glomeruli signals could be easily digitized and further analyzed to measure the number, volume, and frequency of the glomeruli.

Cefepime pharmacokinetics in adult extracorporeal membrane oxygenation patients.

BACKGROUND: The impact of extracorporeal membrane oxygenation (ECMO) on the pharmacokinetics/dynamics (PK/PD) of beta-lactam antibiotics have not been well studied in general, but cefepime specifically has the least amount of data. We aimed to investigate whether ECMO alters the PK of cefepime in adult intensive care unit (ICU) patients. METHODS: This single-center, retrospective case-control study evaluated cefepime therapeutic drug monitoring (TDM) results from ECMO patients that were matched 1:1 with TDM results in non-ECMO patients for drug regimen and renal function. The primary outcome was the difference in PK/PD of cefepime in ECMO compared with non-ECMO ICU patients. Secondary outcomes included hospital length of stay, treatment failure, superinfection, bacterial resistance, and survival to discharge. RESULTS: Eighty-two patients were included with 44 matched cefepime concentrations in each group. ECMO patients had higher free maximum concentrations (fCmax) (p = 0.003), lower free minimum concentration (fCmin)/1x minimum inhibitory concentration (MIC) ratios (p = 0.040), and lower attainment of free Cmin/4x MIC (p = 0.010). There were no differences between the groups for free Cmin, time above 1xMIC or 4x MIC, and pharmacokinetic parameters (ke, half-life, and Vd). Of those who survived to discharge, hospital length of stay was longer in the ECMO group (p < 0.001). Patients on ECMO were more likely to experience treatment failure (p = 0.036). The incidence of bacterial resistance, superinfection, or survival were similar among the groups. CONCLUSION: These data suggest that more aggressive empiric dosing may be warranted in patients on ECMO. Therapeutic drug monitoring and future prospective studies would provide more evidence to guide decision making regarding dose adjustments.

A simple and effective vascular network labeling method for transparent tissues of mice.

Vascular network labeling in transparent tissues provides more complete information on blood vessels. To achieve a fast and efficient method for vascular network labeling in transparent tissues, we compared various vascular labeling methods under different tissue clearing protocols. FITC-Dextran labeling and CUBIC cleaning treatment were found to be the best options for vascular network labeling in cleared mouse tissues. Satisfactory labeling of vascular networks in various organs can be achieved by selecting FITC-Dextran with different molecular weights and different administration methods.

Three-dimensional genomic mapping of human pancreatic tissue reveals striking multifocality and genetic heterogeneity in precancerous lesions.

Pancreatic intraepithelial neoplasia (PanIN) is a precursor to pancreatic cancer and represents a critical opportunity for cancer interception. However, the number, size, shape, and connectivity of PanINs in human pancreatic tissue samples are largely unknown. In this study, we quantitatively assessed human PanINs using CODA, a novel machine-learning pipeline for 3D image analysis that generates quantifiable models of large pieces of human pancreas with single-cell resolution. Using a cohort of 38 large slabs of grossly normal human pancreas from surgical resection specimens, we identified striking multifocality of PanINs, with a mean burden of 13 spatially separate PanINs per cm3 of sampled tissue. Extrapolating this burden to the entire pancreas suggested a median of approximately 1000 PanINs in an entire pancreas. In order to better understand the clonal relationships within and between PanINs, we developed a pipeline for CODA-guided multi-region genomic analysis of PanINs, including targeted and whole exome sequencing. Multi-region assessment of 37 PanINs from eight additional human pancreatic tissue slabs revealed that almost all PanINs contained hotspot mutations in the oncogene KRAS, but no gene other than KRAS was altered in more than 20% of the analyzed PanINs. PanINs contained a mean of 13 somatic mutations per region when analyzed by whole exome sequencing. The majority of analyzed PanINs originated from independent clonal events, with distinct somatic mutation profiles between PanINs in the same tissue slab. A subset of the analyzed PanINs contained multiple KRAS mutations, suggesting a polyclonal origin even in PanINs that are contiguous by rigorous 3D assessment. This study leverages a novel 3D genomic mapping approach to describe, for the first time, the spatial and genetic multifocality of human PanINs, providing important insights into the initiation and progression of pancreatic neoplasia.

From Start to Finish: Examining Factors Associated With Higher Likelihood of Publication Among Abstracts Presented at an International Infectious Diseases Scientific Meeting.

Background: The landscape of infectious diseases research by interprofessional teams continues to change in both scope and engagement. Limited information exists regarding publication metrics and factors associated with publication of abstracts presented at professional infectious diseases meetings. Methods: This was a retrospective, observational study evaluating abstracts presented at IDWeek in 2017 and 2018. The primary endpoint was the proportion of abstracts that were subsequently published in peer-reviewed journals. Factors associated with publication were evaluated, and a description of publication metrics was reported. Results: Of the 887 abstracts analyzed from the IDWeek meetings, 236 (26.6%) were published. Significantly more abstracts were published if they were presented as a platform presentation versus poster presentation (35% vs 21%, P < .001). Inclusion of a PhD author significantly increased the likelihood of publication (P = .0014). Prospective studies, greater number of authors, and greater number of study subjects were more common among published abstracts. Median time to publication was 10.9 months, and the majority were published in infectious diseases journals, with an overall average impact factor of 7.7 across all journals. Conclusions: Abstracts from IDWeek presented as oral platforms and those including a PhD author were more likely to be published. Large, diverse authorship teams were common among published abstracts. The high quality of resulting manuscripts is evident by the destination journals and their respective impact factors. These data may be used to inform and motivate clinicians and trainees engaging in infectious diseases-related research.

Estimation of cancer cell fractions and clone trees from multi-region sequencing of tumors.

MOTIVATION: Multi-region sequencing of solid tumors can improve our understanding of intratumor subclonal diversity and the evolutionary history of mutational events. Due to uncertainty in clonal composition and the multitude of possible ancestral relationships between clones, elucidating the most probable relationships from bulk tumor sequencing poses statistical and computational challenges. RESULTS: We developed a Bayesian hierarchical model called PICTograph to model uncertainty in assigning mutations to subclones, to enable posterior distributions of cancer cell fractions (CCFs) and to visualize the most probable ancestral relationships between subclones. Compared with available methods, PICTograph provided more consistent and accurate estimates of CCFs and improved tree inference over a range of simulated clonal diversity. Application of PICTograph to multi-region whole-exome sequencing of tumors from individuals with pancreatic cancer precursor lesions confirmed known early-occurring mutations and indicated substantial molecular diversity, including 6-12 distinct subclones and intra-sample mixing of subclones. Using ensemble-based visualizations, we highlight highly probable evolutionary relationships recovered in multiple models. PICTograph provides a useful approximation to evolutionary inference from cross-sectional multi-region sequencing, particularly for complex cases. AVAILABILITY AND IMPLEMENTATION: https://github.com/KarchinLab/pictograph. The data underlying this article will be shared on reasonable request to the corresponding author. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Multiregion whole-exome sequencing of intraductal papillary mucinous neoplasms reveals frequent somatic KLF4 mutations predominantly in low-grade regions.

OBJECTIVE: Intraductal papillary mucinous neoplasms (IPMNs) are non-invasive precursor lesions that can progress to invasive pancreatic cancer and are classified as low-grade or high-grade based on the morphology of the neoplastic epithelium. We aimed to compare genetic alterations in low-grade and high-grade regions of the same IPMN in order to identify molecular alterations underlying neoplastic progression. DESIGN: We performed multiregion whole exome sequencing on tissue samples from 17 IPMNs with both low-grade and high-grade dysplasia (76 IPMN regions, including 49 from low-grade dysplasia and 27 from high-grade dysplasia). We reconstructed the phylogeny for each case, and we assessed mutations in a novel driver gene in an independent cohort of 63 IPMN cyst fluid samples. RESULTS: Our multiregion whole exome sequencing identified KLF4, a previously unreported genetic driver of IPMN tumorigenesis, with hotspot mutations in one of two codons identified in >50% of the analyzed IPMNs. Mutations in KLF4 were significantly more prevalent in low-grade regions in our sequenced cases. Phylogenetic analyses of whole exome sequencing data demonstrated diverse patterns of IPMN initiation and progression. Hotspot mutations in KLF4 were also identified in an independent cohort of IPMN cyst fluid samples, again with a significantly higher prevalence in low-grade IPMNs. CONCLUSION: Hotspot mutations in KLF4 occur at high prevalence in IPMNs. Unique among pancreatic driver genes, KLF4 mutations are enriched in low-grade IPMNs. These data highlight distinct molecular features of low-grade and high-grade dysplasia and suggest diverse pathways to high-grade dysplasia via the IPMN pathway.

Integrated Informatics Analysis of Cancer-Related Variants.

PURPOSE: The modern researcher is confronted with hundreds of published methods to interpret genetic variants. There are databases of genes and variants, phenotype-genotype relationships, algorithms that score and rank genes, and in silico variant effect prediction tools. Because variant prioritization is a multifactorial problem, a welcome development in the field has been the emergence of decision support frameworks, which make it easier to integrate multiple resources in an interactive environment. Current decision support frameworks are typically limited by closed proprietary architectures, access to a restricted set of tools, lack of customizability, Web dependencies that expose protected data, or limited scalability. METHODS: We present the Open Custom Ranked Analysis of Variants Toolkit1 (OpenCRAVAT) a new open-source, scalable decision support system for variant and gene prioritization. We have designed the resource catalog to be open and modular to maximize community and developer involvement, and as a result, the catalog is being actively developed and growing every month. Resources made available via the store are well suited for analysis of cancer, as well as Mendelian and complex diseases. RESULTS: OpenCRAVAT offers both command-line utility and dynamic graphical user interface, allowing users to install with a single command, easily download tools from an extensive resource catalog, create customized pipelines, and explore results in a richly detailed viewing environment. We present several case studies to illustrate the design of custom workflows to prioritize genes and variants. CONCLUSION: OpenCRAVAT is distinguished from similar tools by its capabilities to access and integrate an unprecedented amount of diverse data resources and computational prediction methods, which span germline, somatic, common, rare, coding, and noncoding variants.

High-Throughput Prediction of MHC Class I and II Neoantigens with MHCnuggets.

Computational prediction of binding between neoantigen peptides and major histocompatibility complex (MHC) proteins can be used to predict patient response to cancer immunotherapy. Current neoantigen predictors focus on in silico estimation of MHC binding affinity and are limited by low predictive value for actual peptide presentation, inadequate support for rare MHC alleles, and poor scalability to high-throughput data sets. To address these limitations, we developed MHCnuggets, a deep neural network method that predicts peptide-MHC binding. MHCnuggets can predict binding for common or rare alleles of MHC class I or II with a single neural network architecture. Using a long short-term memory network (LSTM), MHCnuggets accepts peptides of variable length and is faster than other methods. When compared with methods that integrate binding affinity and MHC-bound peptide (HLAp) data from mass spectrometry, MHCnuggets yields a 4-fold increase in positive predictive value on independent HLAp data. We applied MHCnuggets to 26 cancer types in The Cancer Genome Atlas, processing 26.3 million allele-peptide comparisons in under 2.3 hours, yielding 101,326 unique predicted immunogenic missense mutations (IMM). Predicted IMM hotspots occurred in 38 genes, including 24 driver genes. Predicted IMM load was significantly associated with increased immune cell infiltration (P < 2 × 10-16), including CD8+ T cells. Only 0.16% of predicted IMMs were observed in more than 2 patients, with 61.7% of these derived from driver mutations. Thus, we describe a method for neoantigen prediction and its performance characteristics and demonstrate its utility in data sets representing multiple human cancers.

Intraductal Papillary Mucinous Neoplasms Arise From Multiple Independent Clones, Each With Distinct Mutations.

BACKGROUND & AIMS: Intraductal papillary mucinous neoplasms (IPMNs) are lesions that can progress to invasive pancreatic cancer and constitute an important system for studies of pancreatic tumorigenesis. We performed comprehensive genomic analyses of entire IPMNs to determine the diversity of somatic mutations in genes that promote tumorigenesis. METHODS: We microdissected neoplastic tissues from 6-24 regions each of 20 resected IPMNs, resulting in 227 neoplastic samples that were analyzed by capture-based targeted sequencing. Somatic mutations in genes associated with pancreatic tumorigenesis were assessed across entire IPMN lesions, and the resulting data were supported by evolutionary modeling, whole-exome sequencing, and in situ detection of mutations. RESULTS: We found a high prevalence of heterogeneity among mutations in IPMNs. Heterogeneity in mutations in KRAS and GNAS was significantly more prevalent in IPMNs with low-grade dysplasia than in IPMNs with high-grade dysplasia (P < .02). Whole-exome sequencing confirmed that IPMNs contained multiple independent clones, each with distinct mutations, as originally indicated by targeted sequencing and evolutionary modeling. We also found evidence for convergent evolution of mutations in RNF43 and TP53, which are acquired during later stages of tumorigenesis. CONCLUSIONS: In an analysis of the heterogeneity of mutations throughout IPMNs, we found that early-stage IPMNs contain multiple independent clones, each with distinct mutations, indicating their polyclonal origin. These findings challenge the model in which pancreatic neoplasms arise from a single clone. Increasing our understanding of the mechanisms of IPMN polyclonality could lead to strategies to identify patients at increased risk for pancreatic cancer.

Single-cell sequencing defines genetic heterogeneity in pancreatic cancer precursor lesions.

Intraductal papillary mucinous neoplasms (IPMNs) are precursors to pancreatic cancer; however, little is known about genetic heterogeneity in these lesions. The objective of this study was to characterize genetic heterogeneity in IPMNs at the single-cell level. We isolated single cells from fresh tissue from ten IPMNs, followed by whole genome amplification and targeted next-generation sequencing of pancreatic driver genes. We then determined single-cell genotypes using a novel multi-sample mutation calling algorithm. Our analyses revealed that different mutations in the same driver gene frequently occur in the same IPMN. Two IPMNs had multiple mutations in the initiating driver gene KRAS that occurred in unique tumor clones, suggesting the possibility of polyclonal origin or an unidentified initiating event preceding this critical mutation. Multiple mutations in later-occurring driver genes were also common and were frequently localized to unique tumor clones, raising the possibility of convergent evolution of these genetic events in pancreatic tumorigenesis. Single-cell sequencing of IPMNs demonstrated genetic heterogeneity with respect to early and late occurring driver gene mutations, suggesting a more complex pattern of tumor evolution than previously appreciated in these lesions. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Kirigami-inspired, highly stretchable micro-supercapacitor patches fabricated by laser conversion and cutting.

The recent developments in material sciences and rational structural designs have advanced the field of compliant and deformable electronics systems. However, many of these systems are limited in either overall stretchability or areal coverage of functional components. Here, we design a construct inspired by Kirigami for highly deformable micro-supercapacitor patches with high areal coverages of electrode and electrolyte materials. These patches can be fabricated in simple and efficient steps by laser-assisted graphitic conversion and cutting. Because the Kirigami cuts significantly increase structural compliance, segments in the patches can buckle, rotate, bend and twist to accommodate large overall deformations with only a small strain (<3%) in active electrode areas. Electrochemical testing results have proved that electrical and electrochemical performances are preserved under large deformation, with less than 2% change in capacitance when the patch is elongated to 382.5% of its initial length. The high design flexibility can enable various types of electrical connections among an array of supercapacitors residing in one patch, by using different Kirigami designs.

Temporal Control of Mammalian Cortical Neurogenesis by m6A Methylation.

N6-methyladenosine (m6A), installed by the Mettl3/Mettl14 methyltransferase complex, is the most prevalent internal mRNA modification. Whether m6A regulates mammalian brain development is unknown. Here, we show that m6A depletion by Mettl14 knockout in embryonic mouse brains prolongs the cell cycle of radial glia cells and extends cortical neurogenesis into postnatal stages. m6A depletion by Mettl3 knockdown also leads to a prolonged cell cycle and maintenance of radial glia cells. m6A sequencing of embryonic mouse cortex reveals enrichment of mRNAs related to transcription factors, neurogenesis, the cell cycle, and neuronal differentiation, and m6A tagging promotes their decay. Further analysis uncovers previously unappreciated transcriptional prepatterning in cortical neural stem cells. m6A signaling also regulates human cortical neurogenesis in forebrain organoids. Comparison of m6A-mRNA landscapes between mouse and human cortical neurogenesis reveals enrichment of human-specific m6A tagging of transcripts related to brain-disorder risk genes. Our study identifies an epitranscriptomic mechanism in heightened transcriptional coordination during mammalian cortical neurogenesis.

Zika-Virus-Encoded NS2A Disrupts Mammalian Cortical Neurogenesis by Degrading Adherens Junction Proteins.

Zika virus (ZIKV) directly infects neural progenitors and impairs their proliferation. How ZIKV interacts with the host molecular machinery to impact neurogenesis in vivo is not well understood. Here, by systematically introducing individual proteins encoded by ZIKV into the embryonic mouse cortex, we show that expression of ZIKV-NS2A, but not Dengue virus (DENV)-NS2A, leads to reduced proliferation and premature differentiation of radial glial cells and aberrant positioning of newborn neurons. Mechanistically, in vitro mapping of protein-interactomes and biochemical analysis suggest interactions between ZIKA-NS2A and multiple adherens junction complex (AJ) components. Functionally, ZIKV-NS2A, but not DENV-NS2A, destabilizes the AJ complex, resulting in impaired AJ formation and aberrant radial glial fiber scaffolding in the embryonic mouse cortex. Similarly, ZIKA-NS2A, but not DENV-NS2A, reduces radial glial cell proliferation and causes AJ deficits in human forebrain organoids. Together, our results reveal pathogenic mechanisms underlying ZIKV infection in the developing mammalian brain.

Role of copper in regression of cardiac hypertrophy.

Pressure overload causes an accumulation of homocysteine in the heart, which is accompanied by copper depletion through the formation of copper-homocysteine complexes and the excretion of the complexes. Copper supplementation recovers cytochrome c oxidase (CCO) activity and promotes myocardial angiogenesis, along with the regression of cardiac hypertrophy and the recovery of cardiac contractile function. Increased copper availability is responsible for the recovery of CCO activity. Copper promoted expression of angiogenesis factors including vascular endothelial growth factor (VEGF) in endothelial cells is responsible for angiogenesis. VEGF receptor-2 (VEGFR-2) is critical for hypertrophic growth of cardiomyocytes and VEGFR-1 is essential for the regression of cardiomyocyte hypertrophy. Copper, through promoting VEGF production and suppressing VEGFR-2, switches the VEGF signaling pathway from VEGFR-2-dependent to VEGFR-1-dependent, leading to the regression of cardiomyocyte hypertrophy. Copper is also required for hypoxia-inducible factor-1 (HIF-1) transcriptional activity, acting on the interaction between HIF-1 and the hypoxia responsible element and the formation of HIF-1 transcriptional complex by inhibiting the factor inhibiting HIF-1. Therefore, therapeutic targets for copper supplementation-induced regression of cardiac hypertrophy include: (1) the recovery of copper availability for CCO and other critical cellular events; (2) the activation of HIF-1 transcriptional complex leading to the promotion of angiogenesis in the endothelial cells by VEGF and other factors; (3) the activation of VEGFR-1-dependent regression signaling pathway in the cardiomyocytes; and (4) the inhibition of VEGFR-2 through post-translational regulation in the hypertrophic cardiomyocytes. Future studies should focus on target-specific delivery of copper for the development of clinical application.

Isolation and characterization of endothelial progenitor cells from Rhesus monkeys.

BACKGROUND: Endothelial progenitor cells (EPCs) are increasingly becoming a major focus of regenerative medicine research and practice. The present study was undertaken to establish an appropriate procedure for isolation and characterization of EPCs from Rhesus monkeys for regenerative medicine research. RESULT: Selective CD34+ and nonselective mononuclear EPCs were isolated from bone marrow and cultured under varying conditions. The results showed that nonselective mononuclear EPCs were a better choice for high yield of the target cells. The cells grew in M 200 better than in EGM-2, and supplementation with fetal bovine serum promoted cell proliferation; but serum level at 7.5% was better than at 10%. In addition, surface coating of the culture dishes with human fibronectin significantly improved the proliferation and ontogeny of the isolated EPCs. Immunocytochemistry including detection of markers CD34, CD133 and CD31 and double-staining for Ac-LDL and lectin verified the purity of the cultured mononuclear EPCs. CONCLUSION: By a thorough analysis, we established a practical procedure for isolation and propagation of EPCs from Rhesus monkeys. This procedure would help using these valuable cells for regenerative medicine research.

Rejuvenation: an integrated approach to regenerative medicine.

The word "rejuvenate" found in the Merriam-Webster dictionary is (1) to make young or youthful again: give new vigor to, and (2) to restore to an original or new state. Regenerative medicine is the process of creating living, functional tissues to repair or replace tissue or organ function lost due to age, disease, damage, or congenital defects. To accomplish this, approaches including transplantation, tissue engineering, cell therapy, and gene therapy are brought into action. These all use exogenously prepared materials to forcefully mend the failed organ. The adaptation of the materials in the host and their integration into the organ are all uncertain. It is a common sense that tissue injury in the younger is easily repaired and the acute injury is healed better and faster. Why does the elder have a diminished capacity of self-repairing, or why does chronic injury cause the loss of the self-repairing capacity? There must be some critical elements that are involved in the repair process, but are suppressed in the elder or under the chronic injury condition. Rejuvenation of the self-repair mechanism would be an ideal solution for functional recovery of the failed organ. To achieve this, it would involve renewal of the injury signaling, reestablishment of the communication and transportation system, recruitment of the materials for repairing, regeneration of the failed organ, and rehabilitation of the renewed organ. It thus would require a comprehensive understanding of developmental biology and a development of new approaches to activate the critical players to rejuvenate the self-repair mechanism in the elder or under chronic injury condition. Efforts focusing on rejuvenation would expect an alternative, if not a better, accomplishment in the regenerative medicine.