Vertebrates and invertebrates initiate a series of defence mechanisms following infection by Gram-negative bacteria by sensing the presence of lipopolysaccharide (LPS), a major component of the cell wall of the invading pathogen. In humans, monocytes and macrophages respond to LPS by inducing the expression of cytokines, cell-adhesion proteins, and enzymes involved in the production of small proinflammatory mediators. Under pathophysiological conditions, LPS exposure can lead to an often fatal syndrome known as septic shock. Sensitive responses of myeloid cells to LPS require a plasma protein called LPS-binding protein and the glycosylphosphatidylinositol-anchored membrane protein CD14. However, the mechanism by which the LPS signal is transduced across the plasma membrane remains unknown. Here we show that Toll-like receptor 2 (TLR2) is a signalling receptor that is activated by LPS in a response that depends on LPS-binding protein and is enhanced by CD14. A region in the intracellular domain of TLR2 with homology to a portion of the interleukin (IL)-1 receptor that is implicated in the activation of the IL-1-receptor-associated kinase is required for this response. Our results indicate that TLR2 is a direct mediator of signalling by LPS.

We propose a noniterative solution for the Perspective-n-Point ({\rm P}n{\rm P}) problem, which can robustly retrieve the optimum by solving a seventh order polynomial. The central idea consists of three steps: 1) to divide the reference points into 3-point subsets in order to achieve a series of fourth order polynomials, 2) to compute the sum of the square of the polynomials so as to form a cost function, and 3) to find the roots of the derivative of the cost function in order to determine the optimum. The advantages of the proposed method are as follows: First, it can stably deal with the planar case, ordinary 3D case, and quasi-singular case, and it is as accurate as the state-of-the-art iterative algorithms with much less computational time. Second, it is the first noniterative {\rm P}n{\rm P} solution that can achieve more accurate results than the iterative algorithms when no redundant reference points can be used (n\le 5). Third, large-size point sets can be handled efficiently because its computational complexity is O(n).

This randomized field trial comparing Strategies for Teaching based on Autism Research and Structured Teaching enrolled educators in 33 kindergarten-through-second-grade autism support classrooms and 119 students, aged 5–8 years in the School District of Philadelphia. Students were assessed at the beginning and end of the academic year using the Differential Ability Scales. Program fidelity was measured through video coding and use of a checklist. Outcomes were assessed using linear regression with random effects for classroom and student. Average fidelity was 57% in Strategies for Teaching based on Autism Research classrooms and 48% in Structured Teaching classrooms. There was a 9.2-point (standard deviation = 9.6) increase in Differential Ability Scales score over the 8-month study period, but no main effect of program. There was a significant interaction between fidelity and group. In classrooms with either low or high program fidelity, students in Strategies for Teaching based on Autism Research experienced a greater gain in Differential Ability Scales score than students in Structured Teaching (11.2 vs 5.5 points and 11.3 vs 8.9 points, respectively). In classrooms with moderate fidelity, students in Structured Teaching experienced a greater gain than students in Strategies for Teaching based on Autism Research (10.1 vs 4.4 points). The results suggest significant variability in implementation of evidence-based practices, even with supports, and also suggest the need to address challenging issues related to implementation measurement in community settings.

An image segmentation system is proposed for the segmentation of color image based on neural networks. In order to measure the color difference properly, image colors are represented in a modified L*u* v* color space. The segmentation system comprises unsupervised segmentation and supervised segmentation. The unsupervised segmentation is achieved by a two-level approach, i.e., color reduction and color clustering. In color reduction, image colors are projected into a small set of prototypes using self-organizing map (SOM) learning. In color clustering, simulated annealing (SA) seeks the optimal clusters from SOM prototypes. This two-level approach takes the advantages of SOM and SA, which can achieve the near-optimal segmentation with a low computational cost. The supervised segmentation involves color learning and pixel classification. In color learning, color prototype is defined to represent a spherical region in color space. A procedure of hierarchical prototype learning (HPL) is used to generate the different sizes of color prototypes from the sample of object colors. These color prototypes provide a good estimate for object colors. The image pixels are classified by the matching of color prototypes. The experimental results show that the system has the desired ability for the segmentation of color image in a variety of vision tasks.

The objective of this cohort study was to determine the incidence of Parkinson’s disease (PD) and the effects of race/ethnicity, other demographic characteristics, geography, and healthcare utilization on probability of diagnosis. The authors used the Pennsylvania state Medicaid claims dataset from 1999 to 2003 to identify newly diagnosed cases of PD among the 182,271 Medicaid enrolled adults age 40–65; 319 incident cases of PD were identified. The 4-year cumulative incidence of PD was 45 per 100,000; 54 per 100,000 among whites, 23 per 100,000 among African-Americans and 40 per 100,000 among Latinos (P < 0.0001), corresponding to a relative risk (RR) of PD of 0.43 for African-Americans (P < 0.0001) compared with whites. After adjusting for age, sex, geography, reason for Medicaid eligibility, and average number of visits, African-Americans were still half as likely to be diagnosed with PD as whites (RR 0.45, P < 0.0001). Older age, more healthcare visits and Medicaid eligibility because of income alone also were significantly associated with PD diagnosis, while male sex was not. Observed racial differences in incidence of PD are not explained by differences in age, sex, income, insurance or healthcare utilization but still may be explained by biological differences or other factors such as education or aging beliefs. Better understanding of the complex biological and social determinants of these disparities is critical to improve PD care.

This study evaluated the association of fidelity to each of the components of the Strategies for Teaching based on Autism Research (STAR) program, a comprehensive treatment package for children with autism that includes discrete trial training, pivotal response training, and teaching in functional routines, on outcomes for 191 students ages 5–8 years in a large public school district. Fidelity to all components was relatively low, despite considerable training and support, suggesting the need to develop new implementation strategies. Fidelity to pivotal response training, but not discrete trial training or functional routines, was positively associated with gains in cognitive ability despite low levels of fidelity, and may be an effective intervention choice in under-resourced settings.

BackgroundChildren with autism receive most of their intervention services in public schools, but implementation of evidence-based practices (EBPs) for autism varies. Studies suggest that individual (attitudes) and organizational characteristics (implementation leadership and climate) may influence providers’ use of EBPs, but research is relatively limited in this area. This study examined individual and organizational factors associated with implementation of three EBPs—discrete trial training, pivotal response training, and visual schedules—for children with autism in special education classrooms in public elementary schools.MethodsParticipants included 67 autism support teachers and 85 other classroom staff from 52 public elementary schools in the northeastern United States. Participants reported their attitudes toward EBPs (e.g., intuitive appeal, willingness if required, openness, and divergence), implementation leadership and climate of their school, and the frequency with which they deliver each of three EBPs. Linear regression was used to estimate the association of attitudes about EBPs with organizational characteristics and intensity of EBP use. Demographic covariates with a bivariate association with EBP use significant at p < .20 were entered into the adjusted models.ResultsThere were significant findings for only one EBP, discrete trial training. Teachers who reported higher perceived divergence (perceived difference of usual practice with academically developed or research-based practices) between EBPs and current practices used less discrete trial training (f2 = .18), and teachers who reported higher appeal (willingness to adopt EBPs given their intuitive appeal) of EBPs used more discrete trial training (f2 = .22). No organizational factors were significantly associated with implementation with any of the three EBPs.ConclusionsAttitudes toward EBPs may affect teachers’ decisions to use EBPs; however, implementation leadership and climate did not predict EBP use. Future implementation efforts ought to consider the type of EBP and its fit within the context in terms of the EBP’s similarities to and differences from existing practices and programs in the setting. Implementation strategies that target individual attitudes about EBPs may be warranted in public schools.

Objective This study examined child- and county-level factors associated with age of diagnosis of autism among Medicaid-enrolled children and the change in age of diagnosis over time. Methods National Medicaid claims from 2002 to 2004 were used to identify age of diagnosis and characteristics of children younger than ten years old with a diagnosis of autism (ICD-9 codes 299, 299.0x, or 299.8x). These data were linked to county-level education and health care variables. Linear regression with random effects for state and county was used to examine associations between these variables and age of diagnosis. Results A total of 28,722 Medicaid-enrolled children newly diagnosed with an autism spectrum disorder were identified. Their average age of diagnosis was 64.9 months. Adjusted average age of diagnosis dropped 5.0 months for autistic disorder and 1.8 months for other spectrum disorders during the study period. Asian children were diagnosed earlier than children in other racial or ethnic groups, although these differences were much more pronounced for other spectrum disorders than for autistic disorder. Children eligible for Medicaid through the poverty category were diagnosed earlier, on average, than children who were eligible through disability, foster care, or other reasons, although this difference decreased over time. Children in large urban or rural counties were diagnosed later than children in small urban or suburban counties. Conclusions Findings showed that diagnosis of autism occurs much later than it should among Medicaid-enrolled children, although timeliness is improving over time. Analyses suggest that most of the observed variation is accounted for by child-level variables, rather than county-level resources or state policies.