Institution
Sabancı University
Education•Istanbul, Turkey•
About: Sabancı University is a education organization based out in Istanbul, Turkey. It is known for research contribution in the topics: Neutron star & Pulsar. The organization has 2629 authors who have published 7222 publications receiving 164980 citations.
Topics: Neutron star, Pulsar, Computer science, Population, Magnetar
Papers published on a yearly basis
Papers
More filters
••
TL;DR: The authors showed that CD4+CD25+ cells contribute to maintaining self-tolerance by downregulating immune response to self and non-self Ags in an Ag-nonspecific manner, presumably at the T cell activation stage.
Abstract: Approximately 10% of peripheral CD4+ cells and less than 1% of CD8+ cells in normal unimmunized adult mice express the IL-2 receptor alpha-chain (CD25) molecules. When CD4+ cell suspensions prepared from BALB/c nu/+ mice lymph nodes and spleens were depleted of CD25+ cells by specific mAb and C, and then inoculated into BALB/c athymic nude (nu/nu) mice, all recipients spontaneously developed histologically and serologically evident autoimmune diseases (such as thyroiditis, gastritis, insulitis, sialoadenitis, adrenalitis, oophoritis, glomerulonephritis, and polyarthritis); some mice also developed graft-vs-host-like wasting disease. Reconstitution of CD4+CD25+ cells within a limited period after transfer of CD4+CD25- cells prevented these autoimmune developments in a dose-dependent fashion, whereas the reconstitution several days later, or inoculation of an equivalent dose of CD8+ cells, was far less efficient for the prevention. When nu/nu mice were transplanted with allogeneic skins or immunized with xenogeneic proteins at the time of CD25- cell inoculation, they showed significantly heightened immune responses to the skins or proteins, and reconstitution of CD4+CD25+ cells normalized the responses. Taken together, these results indicate that CD4+CD25+ cells contribute to maintaining self-tolerance by down-regulating immune response to self and non-self Ags in an Ag-nonspecific manner, presumably at the T cell activation stage; elimination/reduction of CD4+CD25+ cells relieves this general suppression, thereby not only enhancing immune responses to non-self Ags, but also eliciting autoimmune responses to certain self-Ags. Abnormality of this T cell-mediated mechanism of peripheral tolerance can be a possible cause of various autoimmune diseases.
5,929 citations
••
TL;DR: In this paper, the authors present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macro-autophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes.
For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy.
Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.
5,187 citations
••
Daniel J. Klionsky1, Fábio Camargo Abdalla2, Hagai Abeliovich3, Robert T. Abraham4 +1284 more•Institutions (463)
TL;DR: These guidelines are presented for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
4,316 citations
••
Technische Universität München1, ETH Zurich2, University of Bern3, Harvard University4, National Institutes of Health5, University of Debrecen6, University Hospital Heidelberg7, McGill University8, University of Pennsylvania9, French Institute for Research in Computer Science and Automation10, University at Buffalo11, Microsoft12, University of Cambridge13, Stanford University14, University of Virginia15, Imperial College London16, Massachusetts Institute of Technology17, Columbia University18, Sabancı University19, Old Dominion University20, RMIT University21, Purdue University22, General Electric23
TL;DR: The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) as mentioned in this paper was organized in conjunction with the MICCAI 2012 and 2013 conferences, and twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low and high grade glioma patients.
Abstract: In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low- and high-grade glioma patients—manually annotated by up to four raters—and to 65 comparable scans generated using tumor image simulation software Quantitative evaluations revealed considerable disagreement between the human raters in segmenting various tumor sub-regions (Dice scores in the range 74%–85%), illustrating the difficulty of this task We found that different algorithms worked best for different sub-regions (reaching performance comparable to human inter-rater variability), but that no single algorithm ranked in the top for all sub-regions simultaneously Fusing several good algorithms using a hierarchical majority vote yielded segmentations that consistently ranked above all individual algorithms, indicating remaining opportunities for further methodological improvements The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource
3,699 citations
••
TL;DR: In this paper, several nanometer-thick graphene oxide films were exposed to nine different heat treatments (three in Argon, three in Argon and Hydrogen, and three in ultra-high vacuum), and also a film was held at 70°C while being exposed to a vapor from hydrazine monohydrate.
2,990 citations
Authors
Showing all 2677 results
Name | H-index | Papers | Citations |
---|---|---|---|
Ismail Cakmak | 84 | 249 | 25991 |
Atac Imamoglu | 84 | 274 | 34145 |
Arnaud Doucet | 75 | 386 | 43388 |
Dimitrios Psaltis | 72 | 331 | 20565 |
Durmus A. Demir | 61 | 237 | 13637 |
Rainer Stiefelhagen | 59 | 421 | 12939 |
Hikmet Budak | 54 | 171 | 17569 |
Oguz Okay | 51 | 189 | 9263 |
Halim Yanikomeroglu | 51 | 632 | 16363 |
Ersin Gogus | 50 | 265 | 7270 |
Çağan H. Şekercioğlu | 48 | 158 | 10763 |
Yusuf Leblebici | 45 | 619 | 9846 |
Erhan Budak | 45 | 170 | 8919 |
Sandeep Verma | 44 | 285 | 7592 |
Tolga Guver | 43 | 187 | 5964 |