TGF-beta1 in Aplysia: role in long-term changes in the excitability of sensory neurons and distribution of TbetaR-II-like immunoreactivity.

Exogenous recombinant human transforming growth factor beta-1 (TGF-beta1) induced long-term facilitation of Aplysia sensory-motor synapses. In addition, 5-HT-induced facilitation was blocked by application of a soluble fragment of the extracellular portion of the TGF-beta1 type II receptor (TbetaR-II), which presumably acted by scavenging an endogenous TGF-beta1-like molecule. Because TbetaR-II is essential for transmembrane signaling by TGF-beta, we sought to determine whether Aplysia tissues contained TbetaR-II and specifically, whether neurons expressed the receptor. Western blot analysis of Aplysia tissue extracts demonstrated the presence of a TbetaR-II-immunoreactive protein in several tissue types. The expression and distribution of TbetaR-II-immunoreactive proteins in the central nervous system was examined by immunohistochemistry to elucidate sites that may be responsive to TGF-beta1 and thus may play a role in synaptic plasticity. Sensory neurons in the ventral-caudal cluster of the pleural ganglion were immunoreactive for TbetaR-II, as well as many neurons in the pedal, abdominal, buccal, and cerebral ganglia. Sensory neurons cultured in isolation and cocultured sensory and motor neurons were also immunoreactive. TGF-beta1 affected the biophysical properties of cultured sensory neurons, inducing an increase of excitability that persisted for at least 48 hr. Furthermore, exposure to TGF-beta1 resulted in a reduction in the firing threshold of sensory neurons. These results provide further support for the hypothesis that TGF-beta1 plays a role in long-term synaptic plasticity in Aplysia.

A community-based assessment of the spatiotemporal distribution of influenza in a U.S.-Mexico border county during the spring 2009 novel H1N1 swine-origin influenza A pandemic

This study retrospectively evaluated the spatial and temporal disease patterns associated with influenza-like illness (ILI), positive rapid influenza antigen detection tests (RIDT), and confirmed H1N1 S-OIV cases reported to the Cameron County Department of Health and Human Services between April 26 and May 13, 2009 using the space-time permutation scan statistic software SaTScan in conjunction with geographical information system (GIS) software ArcGIS 9.3. The rate and age-adjusted relative risk of each influenza measure was calculated and a cluster analysis was conducted to determine the geographic regions with statistically higher incidence of disease. A Poisson distribution model was developed to identify the effect that socioeconomic status, population density, and certain population attributes of a census block-group had on that area's frequency of S-OIV confirmed cases over the entire outbreak. Predominant among the spatiotemporal analyses of ILI, RIDT and S-OIV cases in Cameron County is the consistent pattern of a high concentration of cases along the southern border with Mexico. These findings in conjunction with the slight northward space-time shifts of ILI and RIDT cluster centers highlight the southern border as the primary site for public health interventions. Finally, the community-based multiple regression model revealed that three factors—percentage of the population under age 15, average household size, and the number of high school graduates over age 25—were significantly associated with laboratory-confirmed S-OIV in the Lower Rio Grande Valley. Together, these findings underscore the need for community-based surveillance, improve our understanding of the distribution of the burden of influenza within the community, and have implications for vaccination and community outreach initiatives.^

Kawasaki syndrome: Cluster analysis of incident cases presenting to a pediatric tertiary care hospital in Texas from January 1, 2005 to December 31, 2009

Background: Despite almost 40 years of research into the etiology of Kawasaki Syndrome (KS), there is little research published on spatial and temporal clustering of KS cases. Previous analysis has found significant spatial and temporal clustering of cases, therefore cluster analyses were performed to substantiate these findings and provide insight into incident KS cases discharged from a pediatric tertiary care hospital. Identifying clusters from a single institution would allow for prospective analysis of risk factors and potential exposures for further insight into KS etiology. ^ Methods: A retrospective study was carried out to examine the epidemiology and distribution of patients presenting to Texas Children’s Hospital in Houston, Texas, with a diagnosis of Acute Febrile Mucocutaneous Lymph Node Syndrome (MCLS) upon discharge from January 1, 2005 to December 31, 2009. Spatial, temporal, and space-time cluster analyses were performed using the Bernoulli model with case and control event data. ^ Results: 397 of 102,761 total patients admitted to Texas Children’s Hospital had a principal or secondary diagnosis of Acute Febrile MCLS upon over the 5 year period. Demographic data for KS cases remained consistent with known disease epidemiology. Spatial, temporal, and space-time analyses of clustering using the Bernoulli model demonstrated no statistically significant clusters. ^ Discussion: Despite previous findings of spatial-temporal clustering of KS cases, there were no significant clusters of KS cases discharged from a single institution. This implicates the need for an expanded approach to conducting spatial-temporal cluster analysis and KS surveillance given the limitations of evaluating data from a single institution.^