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Institution

Stony Brook University

EducationStony Brook, New York, United States
About: Stony Brook University is a education organization based out in Stony Brook, New York, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 32534 authors who have published 68218 publications receiving 3035131 citations. The organization is also known as: State University of New York at Stony Brook & SUNY Stony Brook.


Papers
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Journal ArticleDOI
TL;DR: Although mechanistically different, both transcription-independent modes of apoptosis induction converge, as they both initiate permeabilization of the outer mitochondrial membrane via activation of the pro-apoptotic Bcl-2 family members Bax or Bak.

463 citations

Proceedings ArticleDOI
R. C. Sekar1, A. Gupta1, J. Frullo1, T. Shanbhag1, A. Tiwari1, H. Yang1, S. Zhou1 
18 Nov 2002
TL;DR: Whereas feature selection was a crucial step that required a great deal of expertise and insight in the case of previous anomaly detection approaches, it is shown that the use of protocol specifications in the approach simplifies this problem.
Abstract: Unlike signature or misuse based intrusion detection techniques, anomaly detection is capable of detecting novel attacks. However, the use of anomaly detection in practice is hampered by a high rate of false alarms. Specification-based techniques have been shown to produce a low rate of false alarms, but are not as effective as anomaly detection in detecting novel attacks, especially when it comes to network probing and denial-of-service attacks. This paper presents a new approach that combines specification-based and anomaly-based intrusion detection, mitigating the weaknesses of the two approaches while magnifying their strengths. Our approach begins with state-machine specifications of network protocols, and augments these state machines with information about statistics that need to be maintained to detect anomalies. We present a specification language in which all of this information can be captured in a succinct manner. We demonstrate the effectiveness of the approach on the 1999 Lincoln Labs intrusion detection evaluation data, where we are able to detect all of the probing and denial-of-service attacks with a low rate of false alarms (less than 10 per day). Whereas feature selection was a crucial step that required a great deal of expertise and insight in the case of previous anomaly detection approaches, we show that the use of protocol specifications in our approach simplifies this problem. Moreover, the machine learning component of our approach is robust enough to operate without human supervision, and fast enough that no sampling techniques need to be employed. As further evidence of effectiveness, we present results of applying our approach to detect stealthy email viruses in an intranet environment.

463 citations

Journal ArticleDOI
TL;DR: Rafts have been widely studied by isolating l(o)-phase detergent-resistant membranes from cells, but recent findings have shown that DRMs are not the same as preexisting rafts, prompting a major revision of the raft model.
Abstract: Lipid rafts are liquid-ordered (lo) phase microdomains proposed to exist in biological membranes. Rafts have been widely studied by isolating lo-phase detergent-resistant membranes (DRMs) from cells. Recent findings have shown that DRMs are not the same as preexisting rafts, prompting a major revision of the raft model. Nevertheless, raft-targeting signals identified by DRM analysis are often required for protein function, implicating rafts in a variety of cell processes.

462 citations

Journal ArticleDOI
TL;DR: The role of saliva, the prevalence of oral dryness and the consequent importance of salivary flow as well as the relationship between xerostomia and Salivary gland hypofunction amongst the causes of Oral dryness are reviewed.

462 citations

Journal ArticleDOI
TL;DR: It has unambiguously been proven that this tumor-targeting DDS works exactly as designed and shows high potency toward specific cancer cell lines, thereby forming a solid foundation for further development.
Abstract: A novel single-walled carbon nanotube (SWNT)-based tumor-targeted drug delivery system (DDS) has been developed, which consists of a functionalized SWNT linked to tumor-targeting modules as well as prodrug modules. There are three key features of this nanoscale DDS: (a) use of functionalized SWNTs as a biocompatible platform for the delivery of therapeutic drugs or diagnostics, (b) conjugation of prodrug modules of an anticancer agent (taxoid with a cleavable linker) that is activated to its cytotoxic form inside the tumor cells upon internalization and in situ drug release, and (c) attachment of tumor-recognition modules (biotin and a spacer) to the nanotube surface. To prove the efficacy of this DDS, three fluorescent and fluorogenic molecular probes were designed, synthesized, characterized, and subjected to the analysis of the receptor-mediated endocytosis and drug release inside the cancer cells (L1210FR leukemia cell line) by means of confocal fluorescence microscopy. The specificity and cytotoxicity of the conjugate have also been assessed and compared with L1210 and human noncancerous cell lines. Then, it has unambiguously been proven that this tumor-targeting DDS works exactly as designed and shows high potency toward specific cancer cell lines, thereby forming a solid foundation for further development.

461 citations


Authors

Showing all 32829 results

NameH-indexPapersCitations
Zhong Lin Wang2452529259003
Dennis W. Dickson1911243148488
Hyun-Chul Kim1764076183227
David Baker1731226109377
J. N. Butler1722525175561
Roderick T. Bronson169679107702
Nora D. Volkow165958107463
Jovan Milosevic1521433106802
Thomas E. Starzl150162591704
Paolo Boffetta148145593876
Jacques Banchereau14363499261
Larry R. Squire14347285306
John D. E. Gabrieli14248068254
Alexander Milov142114393374
Meenakshi Narain1421805147741
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023124
2022453
20213,609
20203,747
20193,426
20183,127