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Joynal Abedin

Bio: Joynal Abedin is an academic researcher from University of Minnesota. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 3, co-authored 3 publications receiving 4873 citations.

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Daniel J. Klionsky1, Kotb Abdelmohsen2, Akihisa Abe3, Joynal Abedin4  +2519 moreInstitutions (695)
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.

4,756 citations

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69 citations

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Daniel J. Klionsky1, Kotb Abdelmohsen2, Akihisa Abe3, Joynal Abedin4  +2519 moreInstitutions (697)
TL;DR: Author(s): Klionsky, DJ; Abdelmohsen, K; Abe, A; Abedin, MJ; Abeliovich, H; A Frozena, AA; Adachi, H, Adeli, K, Adhihetty, PJ; Adler, SG; Agam, G; Agarwal, R; Aghi, MK; Agnello, M; Agostinis, P; Aguilar, PV; Aguirre-Ghis
Abstract: Author(s): Klionsky, DJ; Abdelmohsen, K; Abe, A; Abedin, MJ; Abeliovich, H; Arozena, AA; Adachi, H; Adams, CM; Adams, PD; Adeli, K; Adhihetty, PJ; Adler, SG; Agam, G; Agarwal, R; Aghi, MK; Agnello, M; Agostinis, P; Aguilar, PV; Aguirre-Ghiso, J; Airoldi, EM; Ait-Si-Ali, S; Akematsu, T; Akporiaye, ET; Al-Rubeai, M; Albaiceta, GM; Albanese, C; Albani, D; Albert, ML; Aldudo, J; Algul, H; Alirezaei, M; Alloza, I; Almasan, A; Almonte-Beceril, M; Alnemri, ES; Alonso, C; Altan-Bonnet, N; Altieri, DC; Alvarez, S; Alvarez-Erviti, L; Alves, S; Amadoro, G; Amano, A; Amantini, C; Ambrosio, S; Amelio, I; Amer, AO; Amessou, M; Amon, A; An, Z; Anania, FA; Andersen, SU; Andley, UP; Andreadi, CK; Andrieu-Abadie, N; Anel, A; Ann, DK; Anoopkumar-Dukie, S; Antonioli, M; Aoki, H; Apostolova, N; Aquila, S; Aquilano, K; Araki, K; Arama, E; Aranda, A; Araya, J; Arcaro, A; Arias, E; Arimoto, H; Ariosa, AR; Armstrong, JL; Arnould, T; Arsov, I; Asanuma, K; Askanas, V; Asselin, E; Atarashi, R; Atherton, SS; Atkin, JD; Attardi, LD; Auberger, P; Auburger, G; Aurelian, L; Autelli, R

48 citations

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TL;DR: In this article , the authors developed and compared ten VictimFinder models for identifying rescue request tweets, three based on milestone NLP algorithms and seven BERT-based models, and evaluated the performance of each model by classification accuracy, computation cost, and model stability.
Abstract: Social media platforms are playing increasingly critical roles in disaster response and rescue operations. During emergencies, users can post rescue requests along with their addresses on social media, while volunteers can search for those messages and send help. However, efficiently leveraging social media in rescue operations remains challenging because of the lack of tools to identify rescue request messages on social media automatically and rapidly. Analyzing social media data, such as Twitter data, relies heavily on Natural Language Processing (NLP) algorithms to extract information from texts. The introduction of bidirectional transformers models, such as the Bidirectional Encoder Representations from Transformers (BERT) model, has significantly outperformed previous NLP models in numerous text analysis tasks, providing new opportunities to precisely understand and classify social media data for diverse applications. This study developed and compared ten VictimFinder models for identifying rescue request tweets, three based on milestone NLP algorithms and seven BERT-based. A total of 3191 manually labeled disaster-related tweets posted during 2017 Hurricane Harvey were used as the training and testing datasets. We evaluated the performance of each model by classification accuracy, computation cost, and model stability. Experiment results show that all BERT-based models have significantly increased the accuracy of categorizing rescue-related tweets. The best model for identifying rescue request tweets is a customized BERT-based model with a Convolutional Neural Network (CNN) classifier. Its F1-score is 0.919, which outperforms the baseline model by 10.6%. The developed models can promote social media use for rescue operations in future disaster events.

19 citations

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TL;DR: In this paper , the authors evaluated the impact of land use/land cover change on landslide susceptibility in the Rangamati municipality of Bangladesh, based on three LULC scenarios, including the existing (2018) LULC, the proposed LULC (proposed in 2010, but not yet implemented), and the simulated LULC of 2028.
Abstract: Landslide susceptibility depends on various causal factors such as geology, land use/land cover (LULC), slope, and elevation. Unlike other factors that are relatively stable over time, LULC is a dynamic factor associated with human activities. This study evaluates the impact of LULC change on landslide susceptibility in the Rangamati municipality of Rangamati district, Bangladesh, based on three LULC scenarios—the existing (2018) LULC, the proposed LULC (proposed in 2010, but not yet implemented), and the simulated LULC of 2028—using artificial neural network (ANN)-based cellular automata. The random forest model was used for landslide susceptibility mapping. The model showed good accuracy for all three LULC scenarios (existing: 82.7%; proposed: 81.4%; and 2028: 78.3%) and strong positive correlations (>0.8) between different landslide susceptibility maps. LULC is either the third or fourth most important factor in these scenarios, suggesting that is has a moderate impact on landslide susceptibility. Future LULC changes will likely increase landslide susceptibility, with up to 14.5% increases in the high susceptibility zone for both the proposed and simulated LULC scenarios. These findings may help policymakers carry out proper urban planning and highlight the importance of considering landslide susceptibility in LULC planning.

15 citations


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TL;DR: A functional classification of cell death subroutines is proposed that applies to both in vitro and in vivo settings and includes extrinsic apoptosis, caspase-dependent or -independent intrinsic programmed cell death, regulated necrosis, autophagic cell death and mitotic catastrophe.
Abstract: In 2009, the Nomenclature Committee on Cell Death (NCCD) proposed a set of recommendations for the definition of distinct cell death morphologies and for the appropriate use of cell death-related terminology, including 'apoptosis', 'necrosis' and 'mitotic catastrophe'. In view of the substantial progress in the biochemical and genetic exploration of cell death, time has come to switch from morphological to molecular definitions of cell death modalities. Here we propose a functional classification of cell death subroutines that applies to both in vitro and in vivo settings and includes extrinsic apoptosis, caspase-dependent or -independent intrinsic apoptosis, regulated necrosis, autophagic cell death and mitotic catastrophe. Moreover, we discuss the utility of expressions indicating additional cell death modalities. On the basis of the new, revised NCCD classification, cell death subroutines are defined by a series of precise, measurable biochemical features.

2,041 citations

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Lorenzo Galluzzi1, Lorenzo Galluzzi2, Ilio Vitale3, Stuart A. Aaronson4  +183 moreInstitutions (111)
TL;DR: The Nomenclature Committee on Cell Death (NCCD) has formulated guidelines for the definition and interpretation of cell death from morphological, biochemical, and functional perspectives.
Abstract: Over the past decade, the Nomenclature Committee on Cell Death (NCCD) has formulated guidelines for the definition and interpretation of cell death from morphological, biochemical, and functional perspectives. Since the field continues to expand and novel mechanisms that orchestrate multiple cell death pathways are unveiled, we propose an updated classification of cell death subroutines focusing on mechanistic and essential (as opposed to correlative and dispensable) aspects of the process. As we provide molecularly oriented definitions of terms including intrinsic apoptosis, extrinsic apoptosis, mitochondrial permeability transition (MPT)-driven necrosis, necroptosis, ferroptosis, pyroptosis, parthanatos, entotic cell death, NETotic cell death, lysosome-dependent cell death, autophagy-dependent cell death, immunogenic cell death, cellular senescence, and mitotic catastrophe, we discuss the utility of neologisms that refer to highly specialized instances of these processes. The mission of the NCCD is to provide a widely accepted nomenclature on cell death in support of the continued development of the field.

1,949 citations

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TL;DR: A way forward is suggested for the effective targeting of autophagy by understanding the context-dependent roles of autophile and by capitalizing on modern approaches to clinical trial design.
Abstract: Autophagy is a mechanism by which cellular material is delivered to lysosomes for degradation, leading to the basal turnover of cell components and providing energy and macromolecular precursors. Autophagy has opposing, context-dependent roles in cancer, and interventions to both stimulate and inhibit autophagy have been proposed as cancer therapies. This has led to the therapeutic targeting of autophagy in cancer to be sometimes viewed as controversial. In this Review, we suggest a way forwards for the effective targeting of autophagy by understanding the context-dependent roles of autophagy and by capitalizing on modern approaches to clinical trial design.

1,018 citations

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07 Dec 2012-Cell
TL;DR: This work identifies syntaxin 17 (Stx17) as the autophagosomal SNARE required for fusion with the endosome/lysosome, and reveals a mechanism by which the SNARE protein is available to the completed Autophagosome.
Abstract: The lysosome is a degradative organelle, and its fusion with other organelles is strictly regulated. In contrast to fusion with the late endosome, the mechanisms underlying autophagosome-lysosome fusion remain unknown. Here, we identify syntaxin 17 (Stx17) as the autophagosomal SNARE required for fusion with the endosome/lysosome. Stx17 localizes to the outer membrane of completed autophagosomes but not to the isolation membrane (unclosed intermediate structures); for this reason, the lysosome does not fuse with the isolation membrane. Stx17 interacts with SNAP-29 and the endosomal/lysosomal SNARE VAMP8. Depletion of Stx17 causes accumulation of autophagosomes without degradation. Stx17 has a unique C-terminal hairpin structure mediated by two tandem transmembrane domains containing glycine zipper-like motifs, which is essential for its association with the autophagosomal membrane. These findings reveal a mechanism by which the SNARE protein is available to the completed autophagosome.

801 citations

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TL;DR: A panel of leading experts in the field attempts here to define several autophagy‐related terms based on specific biochemical features to formulate recommendations that facilitate the dissemination of knowledge within and outside the field of autophagic research.
Abstract: Over the past two decades, the molecular machinery that underlies autophagic responses has been characterized with ever increasing precision in multiple model organisms. Moreover, it has become clear that autophagy and autophagy-related processes have profound implications for human pathophysiology. However, considerable confusion persists about the use of appropriate terms to indicate specific types of autophagy and some components of the autophagy machinery, which may have detrimental effects on the expansion of the field. Driven by the overt recognition of such a potential obstacle, a panel of leading experts in the field attempts here to define several autophagy-related terms based on specific biochemical features. The ultimate objective of this collaborative exchange is to formulate recommendations that facilitate the dissemination of knowledge within and outside the field of autophagy research.

796 citations