Silk Roads : Past and Future

departmental bulletin pape

Azithromycin and Roxithromycin define a new family of “senolytic” drugs that target senescent human fibroblasts

Here, we employed a “senolytic” assay system as a screening tool, with the goal of identifying and repurposing FDA-approved antibiotics, for the targeting of the senescent cell population. Briefly, we used two established human fibroblast cell lines (MRC-5 and/or BJ) as model systems to induce senescence, via chronic treatment with a DNA-damaging agent, namely BrdU (at a concentration of 100 μM for 8 days). Cell viability was then monitored by using the SRB assay, to measure protein content. As a consequence of this streamlined screening strategy, we identified Azithromycin and Roxithromycin as two novel clinically-approved senolytic drugs. However, Erythromycin – the very closely-related parent compound – did not show any senolytic activity, highlighting the dramatic specificity of these interactions. Interestingly, we also show that Azithromycin treatment of human fibroblasts was indeed sufficient to strongly induce both aerobic glycolysis and autophagy. However, the effects of Azithromycin on mitochondrial oxygen consumption rates (OCR) were bi-phasic, showing inhibitory activity at 50 μM and stimulatory activity at 100 μM. These autophagic/metabolic changes induced by Azithromycin could mechanistically explain its senolytic activity. We also independently validated our findings using the xCELLigence real-time assay system, which measures electrical impedance. Using this approach, we see that Azithromycin preferentially targets senescent cells, removing approximately 97% of them with great efficiency. This represents a near 25-fold reduction in senescent cells. Finally, we also discuss our current results in the context of previous clinical findings that specifically document the anti-inflammatory activity of Azithromycin in patients with cystic fibrosis – a genetic lung disorder that results in protein mis-folding mutations that cause protein aggregation

Brief review of regression‐based and machine learning methods in genetic epidemiology: the Genetic Analysis Workshop 17 experience

Genetics Analysis Workshop 17 provided common and rare genetic variants from exome sequencing data and simulated binary and quantitative traits in 200 replicates. We provide a brief review of the machine learning and regression‐based methods used in the analyses of these data. Several regression and machine learning methods were used to address different problems inherent in the analyses of these data, which are high‐dimension, low‐sample‐size data typical of many genetic association studies. Unsupervised methods, such as cluster analysis, were used for data segmentation and, subset selection. Supervised learning methods, which include regression‐based methods (e.g., generalized linear models, logic regression, and regularized regression) and tree‐based methods (e.g., decision trees and random forests), were used for variable selection (selecting genetic and clinical features most associated or predictive of outcome) and prediction (developing models using common and rare genetic variants to accurately predict outcome), with the outcome being case‐control status or quantitative trait value. We include a discussion of cross‐validation for model selection and assessment, and a description of available software resources for these methods. Genet. Epidemiol . 35:S5–S11, 2011. © 2011 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/88012/1/20642_ftp.pd

Injectable gellan gum hydrogels with autologous cells for the treatment of rabbit articular cartilage defects

In this work, the ability of gellan gum hydrogels coupled with autologous cells to regenerate rabbit full-thickness articular cartilage defects was tested. Five study groups were defined: (a) gellangumwith encapsulated chondrogenic predifferentiated rabbit adipose stem cells (ASCþGF); (b) gellan gum with encapsulated nonchondrogenic predifferentiated rabbit adipose stem cells (ASC); (c) gellan gum with encapsulated rabbit articular chondrocytes (AC) (standard control); (d) gellan gum alone (control); (e) empty defect (control). Fullthickness articular cartilage defects were created and the gellangum constructs were injected and left for 8 weeks. The macroscopic aspect of the explants showed a progressive increase of similarity with the lateral native cartilage, stable integration at the defect site, more pronouncedly in the cell-loaded constructs. Tissue scoring showed that ASCþGF exhibited the best results regarding tissue quality progression. Alcian blue retrieved similar results with a better outcome for the cell-loaded constructs. Regarding real-time PCR analyses, ASCþGF had the best progression with an upregulation of collagen type II and aggrecan, and a downregulation of collagen type I. Gellan gum hydrogels combined with autologous cells constitute a promising approach for the treatment of articular cartilage defects, and adipose derived cellsmayconstitute a valid alternative to currently used articular chondrocytes.J. T. Oliveira acknowledge the Portuguese Foundation for Science and Technology (FCT) for his grant (SFRH/BD17135/2004). The authors thank the medical and technical staff of the Institute for Biomedical Sciences Abel Salazar (ICBAS) of the University of Porto, Portugal and the Institute for Health and Life Sciences (ICVS) of the University of Minho, Portugal. The authors also thank Dr. Patricia Malafaya, Cristina Correia, and Rui Pereira, for their help with the histological scoring. This work was carried out under the scope of the European NoE EXPERTISSUES, and partially supported by the European Project HIPPOCRATES

Fast acoustic tomography of costal, tidally-driven temperature and current fields

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering, 1998.Includes bibliographical references (leaves 160-169).by Pierre Elisseeff.Ph.D

The senescence-associated secretory phenotype and its physiological and pathological implications

Cellular senescence is a state of terminal growth arrest associated with the upregulation of different cell cycle inhibitors, mainly p16 and p21, structural and metabolic alterations, chronic DNA damage responses, and a hypersecretory state known as the senescence-associated secretory phenotype (SASP). The SASP is the major mediator of the paracrine effects of senescent cells in their tissue microenvironment and of various local and systemic biological functions. In this Review, we discuss the composition, dynamics and heterogeneity of the SASP as well as the mechanisms underlying its induction and regulation. We describe the various biological properties of the SASP, its beneficial and detrimental effects in different physiological and pathological settings, and its impact on overall health span. Finally, we discuss the use of the SASP as a biomarker and of SASP inhibitors as senomorphic interventions to treat cancer and other age-related conditions.</p

Explanation Trees for Causal Bayesian Networks

Bayesian networks can be used to extract explanations about the observed state of a subset of variables. In this paper, we ex- plicate the desiderata of an explanation and confront them with the concept of expla- nation proposed by existing methods. The necessity of taking into account causal ap- proaches when a causal graph is available is discussed. We then introduce causal expla- nation trees, based on the construction of ex- planation trees using the measure of causal information flow (Ay and Polani, 2006). This approach is compared to several other meth- ods on known networks

Kernel Dependency Estimation

We consider the learning problem of finding a dependency between a general class of objects and another, possibly different, general class of objects. The objects can be for example: vectors, images, strings, trees or graphs. Such a task is made possible by employing similarity measures in both input and output spaces using kernel functions, thus embedding the objects into vector spaces. Output kernels also make it possible to encode prior information and/or invariances in the loss function in an elegant way. We experimentally validate our approach on several tasks: mapping strings to strings, pattern recognition, and reconstruction from partial images

Transdermal photopolymerization of hydrogels for tissue engineering

Thesis (Ph.D.)--Harvard--Massachusetts Institute of Technology Division of Health Sciences and Technology, 1999.Includes bibliographical references.by Jennifer Hartt Elisseeff.Ph.D