Founded in 1887, SUNY Buffalo Law School, the State University of New York is a graduate professional school at the University at Buffalo. It is part of the State University of New York system and is the SUNY system's only law school. U.S. News & World Report ranks the University at Buffalo Law School 100th in the nation for 2014. However, many lesser known sites rank the Law School much higher. The University at Buffalo Law School is No. 1 in Thomson Reuter's "Super Lawyers" ranking of law graduates practicing in Upstate New York, which includes 54 of the 62 counties in New York State. This is in addition to the UB Law School's 2010 national ranking, where it placed 48th out of the 180 law schools in the country that produced Super Lawyers, a measure which examines "twelve indicators of professional achievement". Also, Malcolm Gladwell, in the New Yorker Magazine, devised a formula that ranks UB within the top 50 whereas Reuters ranks UB Law as 48th overall in the nation.According to SUNY Buffalo Law School's 2013 ABA-required disclosures, 60.5% of the Class of 2013 obtained full-time, long-term, JD-required employment nine months after graduation. Wikipedia.
News Article | April 17, 2017
Dr. Chen is a compassionate and community-involved physician in Tucson, Arizona. Dr. Chen received his undergraduate degree from Washington University in St. Louis with an A.B. in Finance and Biology. He then received both his medical degree and MBA from the State University of New York at Buffalo. Dr. Chen then became the Chief Resident of Internal Residence while completing his residency and fellowship at the University of Arizona, Tucson. Tucson is his home. He is active in the Tucson community by volunteering his time as a board member of a children’s cancer non-profit organization called Candlelighters of Southern Arizona, as well as being a health educator and speaker at the Tucson Chinese Community Center. Dr. Chen is fluent in Cantonese and Mandarin and speaks conversational Korean. Dr. Chen treats his patients the way he would like his family to be treated. He believes that being a good doctor requires having empathy. It starts from understanding his patients beyond just the disease, because being sick is a lot more than just having a diagnosis. It was his dream since childhood to be a doctor because of his love for his grandparents, and they continue to inspire him as he treats his patients.
Garrett-Sinha L.A.,State University of New York at Buffalo
Cellular and Molecular Life Sciences | Year: 2013
The Ets1 transcription factor is a member of the Ets gene family and is highly conserved throughout evolution. Ets1 is known to regulate a number of important biological processes in normal cells and in tumors. In particular, Ets1 has been associated with regulation of immune cell function and with an aggressive behavior in tumors that express it at high levels. Here we review and summarize the general features of Ets1 and describe its roles in immunity and autoimmunity, with a focus on its roles in B lymphocytes. We also review evidence that suggests that Ets1 may play a role in malignant transformation of hematopoietic malignancies including B cell malignancies. © 2013 Springer Basel.
Sachs F.,State University of New York at Buffalo
Physiology | Year: 2010
Mechanosensitive ion channels (MSCs) exist in all cells, but mechanosensitivity is a phenotype not a genotype. Specialized mechanoreceptors such as the hair cells of the cochlea require elaborate mechanical impedance matching to couple the channels to the external stress. In contrast, MSCs in nonspecialized cells appear activated by stress in the bilayer local to the channel-within about three lipids. Local mechanical stress can be produced by far-field tension, amphipaths, phase separations, the cytoskeleton, the extracellular matrix, and the adhesion energy between the membrane and a patch pipette. Understanding MSC function requires understanding the stimulus. ©2010 Int. Union Physiol. Sci/Am. Physiol. Soc.
Liu X.,State University of New York at Buffalo |
Swihart M.T.,State University of New York at Buffalo
Chemical Society Reviews | Year: 2014
The creation and study of non-metallic nanomaterials that exhibit localized surface plasmon resonance (LSPR) interactions with light is a rapidly growing field of research. These doped nanocrystals, mainly self-doped semiconductor nanocrystals (NCs) and extrinsically-doped metal oxide NCs, have extremely high concentrations of free charge carriers, which allows them to exhibit LSPR at near infrared (NIR) wavelengths. In this tutorial review, we discuss recent progress in developing and synthesizing doped semiconductor and metal oxide nanocrystals with LSPR, and in studying the optical properties of these plasmonic nanocrystals. We go on to discuss their growing potential for advancing biomedical and optoelectronic applications. © 2014 the Partner Organisations.
Free S.J.,State University of New York at Buffalo
Advances in Genetics | Year: 2013
The composition and organization of the cell walls from Saccharomyces cerevisiae, Candida albicans, Aspergillus fumigatus, Schizosaccharomyces pombe, Neurospora crassa, and Cryptococcus neoformans are compared and contrasted. These cell walls contain chitin, chitosan, β-1,3-glucan, β-1,6-glucan, mixed β-1,3-/β-1,4-glucan, α-1,3-glucan, melanin, and glycoproteins as major constituents. A comparison of these cell walls shows that there is a great deal of variability in fungal cell wall composition and organization. However, in all cases, the cell wall components are cross-linked together to generate a cell wall matrix. The biosynthesis and properties of each of the major cell wall components are discussed. The chitin and glucans are synthesized and extruded into the cell wall space by plasma membrane-associated chitin synthases and glucan synthases. The glycoproteins are synthesized by ER-associated ribosomes and pass through the canonical secretory pathway. Over half of the major cell wall proteins are modified by the addition of a glycosylphosphatidylinositol anchor. The cell wall glycoproteins are also modified by the addition of O-linked oligosaccharides, and their N-linked oligosaccharides are extensively modified during their passage through the secretory pathway. These cell wall glycoprotein posttranslational modifications are essential for cross-linking the proteins into the cell wall matrix. Cross-linking the cell wall components together is essential for cell wall integrity. The activities of four groups of cross-linking enzymes are discussed. Cell wall proteins function as cross-linking enzymes, structural elements, adhesins, and environmental stress sensors and protect the cell from environmental changes. © 2013 Elsevier Inc.
Nolan J.P.,State University of New York at Buffalo
Hepatology | Year: 2010
From the mid-1950s, it was observed that liver injury by a variety of toxins greatly sensitized the host to the effects of administered lipopolysaccharide. In the nutritional cirrhosis of choline deficiency, and in acute toxic injury as well, the need for the presence of enteric endotoxin was demonstrated. The universality of this association was striking for almost all agents associated with liver injury. In addition, the presence of endotoxemia in human liver disease was documented in the 1970s, when the hypothesis was first proposed, and correlated with the severity of the disease. Despite imposing evidence of the critical role of enteric endotoxin in liver injury, it did not excite much interest in investigators until the 1980s. With the ability to study effects of alcohol in newer delivery systems, and an increased understanding of the role of Kupffer cells in the process, the original hypothesis has been accepted. This historical review details the progress of this novel concept of disease initiation and suggests future directions to bring potential therapies to the bedside. © 2010 American Association for the Study of Liver Diseases.
Chung D.D.L.,State University of New York at Buffalo
Carbon | Year: 2012
This paper reviews carbon materials for significant emerging applications that relate to structural self-sensing (a structural material sensing its own condition), electromagnetic interference shielding (blocking radio wave) and thermal interfacing (improving thermal contacts by using thermal interface materials). These applications pertain to electronics, lighting (light emitting diodes), communication, security, aircraft, spacecraft and civil infrastructure. High-performance and cost-effective materials in various forms of carbon have been developed for these applications. The forms of carbon materials include carbon fiber, carbon nanofiber, exfoliated graphite, carbon black and composite materials. Short carbon fiber cement-matrix composites and continuous carbon fiber polymer-matrix composites are particularly effective for structural self-sensing, with the attributes sensed including strain, stress, damage and temperature. Flexible graphite as a monolithic material and nickel-coated carbon nanofiber as a filler are particularly effective for electromagnetic shielding. Carbon black paste, graphite nanoplatelet paste and flexible graphite (filled with carbon black paste) are particularly effective for thermal interfacing; carbon nanotube arrays are less effective than these pastes. The associated science pertains to the relationship among processing, structure and properties in relation to the abovementioned applications. The criteria behind the design of materials for these applications and the mechanisms of the associated phenomena are also addressed. © 2011 Elsevier Ltd. All rights reserved.
Agency: NSF | Branch: Standard Grant | Program: | Phase: DATANET | Award Amount: 2.91M | Year: 2016
This project directly addresses the goals of the Materials Genome Initiative -- to accelerate the pace of discovery and deployment of advanced material systems. To obtain insights for the discovery of new materials and to study existing materials, scientists and engineers rely heavily on an ever-growing number of materials research databases and scholarly research publications that date back many decades. New materials innovation often takes years, sometimes decades, to develop a new material. The project addresses the challenges through several steps, including automatic extraction of data from relevant electronic publications, storage of the data in formats that support comparison and analysis, development of advanced computational tools to improve the analysis, integration of the tools into a data laboratory to support the discovery of new trends and relationships among materials properties, and to predict new materials with desired properties.
The infrastructure building blocks developed under this project enable researchers to (i) use document processing technologies to process scientific publications and data from scientific databases in materials science to create a knowledge base; (ii) use machine learning technologies to learn from the data in this enhanced knowledge base to address a variety of use cases in materials science and engineering; and (iii) use innovative information retrieval and visualization tools for insightful analysis, facilitating faster discovery of new materials. The tools will be hosted and disseminated through a web portal built on the HubZero platform, which will also provide users with the ability to query and visualize data, and run simulations and experiments. The data laboratory portal also provides the ability to run simulations and experiments on high-performance computing clusters using the building blocks. The data laboratory provides a platform for materials informatics, enabling prediction of properties of metal alloys and interaction with the materials discovery and engineering user community. While the primary target is the interdisciplinary field of materials research, the tools are designed to be domain agnostic as the core technologies can be applied to documents and databases across a broad swath of disciplines to enhance the pace of scientific discoveries.
This award by the Advanced Cyberinfrastructure Division is jointly supported by the NSF Directorate for Mathematical & Physical Sciences (Division of Materials Research).
Agency: NSF | Branch: Standard Grant | Program: | Phase: ITEST | Award Amount: 1.20M | Year: 2017
This project will advance efforts of the Innovative Technology Experiences for Students and Teachers (ITEST) program to better understand and promote practices that increase students motivations and capacities to pursue careers in fields of science, technology, engineering, or mathematics (STEM) by its focus on geotechnology (also called GIS or geospatial information systems) careers. The programmatic goal of this project is to prepare teachers to engage middle and high schools students in high-needs and high-potential school districts with cutting-edge web GIS knowledge and skills in order to motivate students to pursue formal school-based and informal out-of-school educational experiences. Project research, guided by social-cognitive career development theory and other work, will investigate what programmatic experiences contribute to student motivation and cognitive gains and what factors contribute to teacher integration of GIS content into the school curriculum.
During three years of the project, the project will offer a summer teacher workshop and a student GIS summer camp each year, The camp will include field trips to GIS-related industry and government agencies, supported by mentors from these organizations. The workshop and camp will support teachers and students in learning GIS concepts and skills. Teachers will also learn approaches to integrate GIS- and career-related in STEM and social studies classes. Students who attended the summer camp will be supported in organizing a GIS after-school club. This project will research one of the guiding questions of the ITEST program: What coherent sets of experiences effectively and efficiently support student competency, motivation and persistence for productive participation in the STEM-related workforce of today and the future? The project will use mixed methods research design including a quasi-experimental study. Research findings from this project will help educators better understand and address the context and factors that influence integration of GIS in middle and high school curricula.
Agency: NSF | Branch: Standard Grant | Program: | Phase: DATANET | Award Amount: 2.73M | Year: 2017
Big Data promises to have a positive impact on many aspects of our lives, but assembling the data to answer questions or derive predictive models can be challenging. Data scientists must typically go through multiple rounds of curation, or wrangling, where data are organized, refined, cleaned up, and merged together before they can be analyzed. Curation is often slow and costly, but is essential for obtaining useful and trustworthy answers. This project develops a software tool called Vizier that aims to streamline data curation and enable domain experts who do not have computer science expertise to curate their own data. Easier curation magnifies the value of big data by enabling a wide range of users to improve data quality, and in doing so benefits numerous types of data-driven work in government, industry, and science.
Vizier features an intuitive interface combining elements of notebooks and spreadsheets, allowing analysts to quickly see, edit, and revise data. This capability is complemented by a framework for automated data cleaning steps that are seamlessly integrated with manual curation operations. The heart of Vizier is a system for managing uncertainty and provenance of curation workflows and data, enabling the user to keep track of higher-level curation operations as well as track the lineage of data. By transparently maintaining the history of all the users actions and their effect on the curated data, Vizier enables regret-free exploration and curation where any changes to the data and their transitive effects can be undone. By learning from past curation histories, the system will also be able to provide users with context-dependent recommendations for additional curation actions.
This award by the Advanced Cyberinfrastructure Division is jointly supported by the NSF Directorate for Social, Behavioral and Economic Sciences (Division of Social and Economic Sciences).