Brain’s functional network clustering coefficient changes in response to instruction (RTI) in students with and without reading disabilities: Multi-leveled reading brain’s RTI

In students in grades 4 to 9 (22 males, 20 females), two reading disability groups—dyslexia (n = 20) or oral and written language learning disability (OWL LD) (n = 6)—were compared to each other and two kinds of control groups—typical readers (n = 6) or dysgraphia (n = 10) on word reading/spelling skills and fMRI imaging before and after completing 18 computerized reading lessons. Mixed ANOVAs showed significant time effects on repeated measures within participants and between groups effects on three behavioral markers of reading disabilities—word reading/spelling: All groups improved on the three behavioral measures, but those without disabilities remained higher than those with reading disabilities . On fMRI reading tasks, analyzed for graph theory derived clustering coefficients within a neural network involved in cognitive control functions, on a word level task the time x group interaction was significant in right medial cingulate; on a syntax level task the time x group interaction was significant in left superior frontal and left inferior frontal gyri; and on a multi-sentence text level task the time x group interaction was significant in right middle frontal gyrus. Three white matter-gray matter correlations became significant only after reading instruction: axial diffusivity in left superior frontal region with right inferior frontal gyrus during word reading judgments; mean diffusivity in left superior corona radiata with left middle frontal gyrus during sentence reading judgments; and mean diffusivity in left anterior corona radiata with right middle frontal gyrus during multi-sentence reading judgments. Significance of results for behavioral and brain response to reading instruction (RTI) is discussed

A Robust Automated Measure of Average Antibody Staining in Immunohistochemistry Images

Identifying and scoring cancer markers plays a key role in oncology, helping to characterize the tumor and predict the clinical course of the disease. The current method for scoring immunohistochemistry (IHC) slides is labor intensive and has inherent issues of quantitation. Although multiple attempts have been made to automate IHC scoring in the past decade, a major limitation in these efforts has been the setting of the threshold for positive staining. In this report, we propose the use of an averaged threshold measure (ATM) score that allows for automatic threshold setting. The ATM is a single multiplicative measure that includes both the proportion and intensity scores. It can be readily automated to allow for large-scale processing, and it is applicable in situations in which individual cells are hard to distinguish. The ATM scoring method was validated by applying it to simulated images, to a sequence of images from the same tumor, and to tumors from different patient biopsies that showed a broad range of staining patterns. Comparison between the ATM score and manual scoring by an expert pathologist showed that both methods resulted in essentially identical scores when applied to these patient biopsies. This manuscript contains online supplemental material at http://www.jhc.org. Please visit this article online to view these materials. (J Histochem Cytochem 58:95–107, 2010