Extending Remission and Reversing New-Onset Type 1 Diabetes by Targeted Ablation of Autoreactive T Cells.

Preserving endogenous insulin production is clinically advantageous and remains a vital unmet challenge in the treatment and reversal of type 1 diabetes. Although broad immunosuppression has had limited success in prolonging the so-called remission period, it comes at the cost of compromising beneficial immunity. Here, we used a novel strategy to specifically deplete the activated diabetogenic T cells that drive pathogenesis while preserving not only endogenous insulin production but also protective immunity. Effector T (Teff) cells, such as diabetogenic T cells, are naturally poised on the edge of apoptosis because of activation-induced DNA damage that stresses the p53 regulation of the cell cycle. We have found that using small molecular inhibitors that further potentiate p53 while inhibiting the G2/M cell cycle checkpoint control drives apoptosis of activated T cells in vivo. When delivered at the onset of disease, these inhibitors significantly reduce diabetogenic Teff cells, prolong remission, preserve functional islets, and protect islet allografts while leaving naive, memory, and regulatory T-cell populations functionally untouched. Thus, the targeted manipulation of p53 and cell cycle checkpoints represents a new therapeutic modality for the preservation of islet ß-cells in new-onset type 1 diabetes or after islet transplant.

The Interaction of Learning Disability Status and Student Demographic Characteristics on Mathematics Growth.

This study examined mathematics achievement growth of students without disabilities (SWoD) and students with learning disabilities (LD) and tested whether growth and LD status interacted with student demographic characteristics. Growth was estimated in a statewide sample of 79,554 students over Grades 3 to 7. The LD group was significantly lower in achievement in each grade and had less growth than the SWoD group. We also found that student demographic characteristics were significantly related to mathematics growth, but only three demographic characteristics were statistically significant as interactions. We found that LD-SWoD differences at Grade 3 were moderated by student sex, while Black race/ethnicity and free or reduced lunch (FRL) status moderated LD-SWoD differences at all grades. These results provide practitioners and policy makers with more specific information about which particular LD students show faster or slower growth in mathematics. Our results show that simply including predictors in a regression equation may produce different results than direct testing of interactions and achievement gaps may be larger for some LD subgroups of students than previously reported.

Trajectories of cannabis use disorder: risk factors, clinical characteristics and outcomes.

AIMS: To estimate cannabis use disorder (CUD) trajectory classes from ages 14 to 30 years and compare classes on clinical characteristics, risk factors and psychosocial outcomes. DESIGN: Four waves (T1-T4) of data from an epidemiological study of psychopathology among a regionally representative sample. Trajectory classes described risk for CUD as a function of age. The number of classes was determined by model fit. SETTING: Participants were selected randomly from nine high schools in western Oregon, USA. PARTICIPANTS: The sample included 816 participants [age at T1 mean = 16.6, standard deviation (SD) = 1.2; 44% male; 8% non-white]. MEASUREMENTS: Participants completed diagnostic interviews, Child Trauma Questionnaire, Social Adjustment Scale and items adapted from the Wisconsin Manual for Assessing Psychotic-Like Experiences. FINDINGS: There were three CUD trajectory classes (Lo-Mendell-Rubin likelihood ratio test < 0.001): (1) persistent increasing risk; (2) maturing out, with increasing risk then decreasing risk; and (3) stable low risk. The persistent increasing class had later initial CUD onsets (η2  = 0.16, P < 0.001) and greater cumulative CUD durations (η2  = 0.26, P < 0.001). Male sex [odds ratio (OR) = 2.57, P = 0.018], externalizing disorders between ages 24 and 30 years (OR = 2.64, P < 0.001) and psychotic experiences during early adulthood (Cohen's d = 0.44, P = 0.016) discriminated between the persistent increasing and the maturing-out classes. CONCLUSIONS: Evidence suggests three distinguishable types of trajectory for development of cannabis use disorder starting in early teens: (1) persistent increasing risk; (2) maturing out, with increasing risk then decreasing risk; and (3) stable low risk.

Growth and gaps in mathematics achievement of students with and without disabilities on a statewide achievement test.

This study estimated mathematics achievement growth trajectories in a statewide sample of 92,045 students with and without disabilities over Grades 3 to 7. Students with disabilities (SWDs) were identified in seven exceptionality categories. Students without disabilities (SWoDs) were categorized as General Education (GE) or Academically/Intellectually Gifted (AIG). Students in all groups showed significant growth that decelerated over grades as well as significant variability in achievement by student group, both at the initial assessment in Grade 3 and in rates of growth over time. Race/ethnicity, gender, parental education, free/reduced lunch status, and English language proficiency were also significant predictors of achievement. Effect size estimates showed substantial year-to-year growth that decreased over grades. Sizeable achievement gaps that were relatively stable over grades were observed between SWoDs and students in specific exceptionality categories. Our study also demonstrated the importance of statistically controlling for variation related to student demographic characteristics. Additional research is needed that expands on these results with the same and additional exceptionality groups.

Measuring and evaluating school performance: an investigation of status and growth-based achievement indicators.

Several school performance indices were evaluated using achievement data from multiple longitudinally matched middle school student cohorts in a large district in the southwestern United States. Measures designed to index the within-cohort achievement status and growth of students as well as the status and growth-based changes that occur over years between different student cohorts were studied. Within- and between-cohort status and growth-based estimates of school performance were generated by applying simple and relatively complex statistical models to the longitudinal time-series data obtained on students. Results indicated that within-cohort status-based estimates were closely related to student demographics and between-cohort estimates were associated with cohort enrollment size and initial performance level. These results suggest that schools may often be rewarded and penalized on the basis of factors over which school personnel have limited or no control. Implications for the measurement and evaluation of school performance are discussed.