P-score: a reputation bibliographic index that complements citation counts

Scientometrics - The notions of reputation and popularity in academia are critical for taking decisions on research grants, faculty position tenure, and research excellence awards. These notions...     

Mitogenic and oncogenic properties of the small G protein Rap1b

It has been widely reported that the small GTP-binding protein Rap1 has an anti-Ras and anti-mitogenic activity. Thus, it is generally accepted that a normal physiological role of Rap1 proteins is to antagonize Ras mitogenic signals, presumably by forming nonproductive complexes with proteins that are typically effectors or modulators of Ras. Rap1 is activated by signals that raise intracellular levels of cAMP, a molecule that has long been known to exert both inhibitory and stimulatory effects on cell growth. We have now tested the intriguing hypothesis that Rap1 could have mitogenic effects in systems in which cAMP stimulates cell proliferation. The result of experiments addressing this possibility revealed that Rap1 has full oncogenic potential. Expression of Rap1 in these cells results in a decreased doubling time, an increased saturation density, and an unusual anchorage-dependent morphological transformation. Most significantly, however, Rap1-expressing cells formed tumors when injected into nude mice. Thus, we propose that the view that holds Rap1 as an antimitogenic protein should be restricted and conclude that Rap1 is a conditional oncoprotein.     

Determination of synthetic estrogens in illegal veterinary formulations by HPTLC and HPLC

To determine the actual amount of diethylstilbestrol, hexestrol, and dienestrol in formulations such as pellets and oily injections that are illegally available on the Brazilian market, a simple methanol extraction is used for the analysis of the pellets and an ether extraction with Sephadex columns (for clean-up) is used for the oily injections. High-performance thin-layer chromatography is used for identification (as a qualitative and semiquantitative method), and high-performance liquid chromatography is used for quantitation. The results of the analysis show that all the formulations are not in accordance with the information listed on their labels.     

The Debye environment for Web data management

The paper discusses the Debye (Data Extraction By Example) environment which lets users extract and manage semistructured data available from Web sources, using an extended form of nested tables as its fundamental paradigm. Currently, the Debye tools are fully implemented as prototypes for applications that use data from heterogeneous Web sources. For instance, developers have recently used Debye to build a repository that integrates data from the digital libraries of several universities.     

An information retrieval approach for approximate queries

With the growing availability of online information systems, a need for user interfaces that are flexible and easy to use has arisen. For such type of systems, an interface that allows the formulation of approximate queries can be of great utility since these allow the user to quickly explore the database contents even when he is unaware of the exact values of the database instances. Our work focuses on this problem, presenting a new model for ranking approximate answers and a new algorithm to compute the semantic similarity between attribute values, based on information retrieval techniques. To demonstrate the utility and usefulness of the approach, we perform a series of usability tests. The results suggest that our approach allows the retrieval of more relevant answers with less effort by the user.     

Image retrieval using multiple evidence ranking

The World Wide Web is the largest publicly available image repository and a natural source of attention. An immediate consequence is that searching for images on the Web has become a current and important task. To search for images of interest, the most direct approach is keyword-based searching. However, since images on the Web are poorly labeled, direct application of standard keyword-based image searching techniques frequently yields poor results. We propose a comprehensive solution to this problem. In our approach, multiple sources of evidence related to the images are considered. To allow combining these distinct sources of evidence, we introduce an image retrieval model based on Bayesian belief networks. To evaluate our approach, we perform experiments on a reference collection composed of 54000 Web images. Our results indicate that retrieval using an image surrounding text passages is as effective as standard retrieval based on HTML tags. This is an interesting result because current image search engines in the Web usually do not take text passages into consideration. Most important, according to our results, the combination of information derived from text passages with information derived from HTML tags leads to improved retrieval, with relative gains in average precision figures of roughly 50 percent, when compared to the results obtained by the use of each source of evidence in isolation.