University of Guadalajara

About: University of Guadalajara is a education organization based out in Guadalajara, Mexico. It is known for research contribution in the topics: Population & Context (language use). The organization has 13040 authors who have published 17399 publications receiving 168085 citations. The organization is also known as: UdeG & UdG.

Enhanced oncogenicity of Asian-American human papillomavirus 16 is associated with impaired E2 repression of E6/E7 oncogene transcription.

Abstract: Asian-American (AA) variants of human papillomavirus 16 (HPV-16) are linked to a high incidence of cervical cancer in Mexico, with some evidence strongly suggesting that they are more oncogenic than European (E) variants, including their association with younger women and their higher associated risk of cervical cancer. Differences in the regulation of viral E6/E7 oncogene transcription by the E2 protein may be involved in the higher oncogenicity of AA variants. In E variants, E6/E7 oncogene transcription is repressed by the E2 protein and is frequently up-regulated by the destruction of the E2 gene during viral integration. In contrast, the E2 gene is retained in full in most AA-positive carcinomas, raising the possibility of alternative mechanisms for increasing viral oncogene transcription. The authors investigated whether the higher oncogenicity of AA variants is linked to differences in E6/E7 oncogene transcription and the mechanism of E2 deactivation. E6/E7 and E1/E2 transcripts were explored by RT-PCR in 53 HPV-16-positive cervical carcinomas, 39 retaining (20 European and 19 AA) and 14 having lost (12 European and 2 AA) the E1/E2 genes, and transcription repression activity of the AA E2 genes was tested in four cell lines that constitutively express the β-galactosidase reporter or E6/E7 genes driven by the viral long control region. E6/E7 oncogene transcripts were found in all carcinomas, but only those positive for AA variants with E1/E2 genes had complete E2 transcripts. E2 transcripts were down-regulated by splicing in E-positive carcinomas retaining E1/E2. AA E2 genes were impaired for repression of E6/E7 oncogene transcription in vivo. These results suggest that E6/E7 oncogene expression starts earlier in AA than E variant infections, since E variants need E2 to be destroyed or down-regulated.

Ionizing radiation and breast cancer in men (United States)

Abstract: The purposes of this study were to determine whether exposure of the vestigial male breast to ionizing radiation is associated with an increase in risk of breast cancer and, if so, to determine whether the apparent effects on risk in men are similar to those reported for women. A population-based case-control study of breast cancer in men was conducted in 10 geographic areas of the United States. Information on possible prior exposure to ionizing radiation, and on other potential risk factors for breast cancer, was obtained from personal interviews of 227 cases and 300 controls who were recruited from October 1983 to September 1986. Evidence from this study that ionizing radiation can cause breast cancer in men includes: a modest trend of increasing risk with frequency of chest X-rays; an increase in risk in men with three or more radiographic examinations, especially if received prior to 1963; and an increase in risk in men who received X-ray treatments to the chest and adjacent body areas. Risk was increased only from 20 to 35 years after initial exposure from either radiographic examinations or X-ray treatments, and declined after three to four decades since last exposure, suggesting a wave of increased risk of finite duration following exposure. The doses of radiation received could not be estimated precisely, but those from diagnostic procedures were likely similar to those received by prepubertal females in prior studies, and the results of those and the present investigation are compatible. The carcinogenic effects of ionizing radiation may be similar in the male and prepubertal female breast.

Thermoresponsive nanostructured poly(N-isopropylacrylamide) hydrogels made via inverse microemulsion polymerization

Abstract: The synthesis of nanostructured poly(N-isopropylacrylamide) (polyNIPA) hydrogels by a two-stage polymerization process is reported here. The process involves the synthesis of slightly crosslinked polyNIPA nanoparticles by inverse (w/o) microemulsion polymerization; then, these particles are dried, cleaned and dispersed in an aqueous solution of NIPA and a crosslinking agent (N,N-methylene-bis-acrylamide or NMBA) and polymerized to produce the nanostructured hydrogels. Their swelling and de-swelling kinetics, volume phase transition temperatures (T VPT) and mechanical properties at the equilibrium swollen state are investigated as a function of the weight ratio of polyNIPA particles to monomer (NIPA). The nanostructured gels exhibit larger equilibrium water uptake, faster swelling and de-swelling rates and similar T VPT than those of the conventional ones; moreover, the elastic and Young moduli are larger than those of the conventional hydrogels at similar swelling ratios. The fast swelling and de-swelling kinetics are explained in terms of the controlled inhomogeneities introduced by the method of synthesis.

A modeling approach for estimating execution time of long-running scientific applications

Abstract: In a grid computing environment, resources are shared among a large number of applications. Brokers and schedulers find matching resources and schedule the execution of the applications by monitoring dynamic resource availability and employing policies such as first- come-first-served and back-filling. To support applications with timeliness requirements in such an environment, brokering and scheduling algorithms must address an additional problem - they must be able to estimate the execution time of the application on the currently available resources. In this paper, we present a modeling approach to estimating the execution time of long-running scientific applications. The modeling approach we propose is generic; models can be constructed by merely observing the application execution "externally" without using intrusive techniques such as code inspection or instrumentation. The model is cross-platform; it enables prediction without the need for the application to be profiled first on the target hardware. To show the feasibility and effectiveness of this approach, we developed a resource usage model that estimates the execution time of a weather forecasting application in a multi-cluster grid computing environment. We validated the model through extensive benchmarking and profiling experiments and observed prediction errors that were within 10% of the measured values. Based on our initial experience, we believe that our approach can be used to model the execution time of other time-sensitive scientific applications; thereby, enabling the development of more intelligent brokering and scheduling algorithms.