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Studies of high-performing schools, where all students learn more than similar students in other schools, show common design elements. These elements are comprehensive, affecting the whole school, and include: (1) Clear mission guiding daily activities; (2) High, unyielding expectations that all students will learn; (3) Frequent monitoring of student progress; (4) Responsive approaches for struggling students; (5) Current, researched-based instructional techniques; (6) Uninterrupted and adequate time on core subjects; (7) Safe and orderly environment; (8) Strong home-school connection; and (9) Strong leadership and management practice. In chronically struggling schools--schools where most students or very large subgroups of students are failing--many of these elements typically are missing. In many cases, it is not a matter of not knowing about them, but rather one of not implementing them. The purpose of this guide is to help chronically struggling schools restructure. Restructuring means making major, rapid changes that affect how a school is led and how instruction is delivered. The guide translates research into practical decision-making tools that include process steps. It also offers a realistic consideration of strengths and constraints in a wide variety of school districts. The guide may be used by any district or state choosing change strategies for schools where large, swift improvement is needed to meet students' academic needs. It also may be used by districts considering school restructuring to meet the requirements of No Child Left Behind (NCLB). Education Leaders' Summary is appended. (Individual chapters contain references and list resources.) [Dana Brinson authored the successful restructuring vignettes. Other Public Impact contributors included: Jacob Rosch, Lauren Morando Rhim, and Amy Way. Warger, Eavy and Associates produced this guide.]

This guide provides users with a step by step approach to restructuring, from organizing a district team and assessing the district's capacity to govern restructuring decisions to conducting a school-by-school analysis and implementing a restructuring plan. The text of the guide is supplemented with templates, checklists, and other practical tools. This guide: (1) reflects the best education and cross-industry research on restructuring; (2) translates that research into practical decision-making tools; (3) includes process steps; and (4) includes realistic consideration of strengths and constraints in a wide variety of school districts. The major actions included in this guide are divided into four steps. These steps are presented in Tool 1 Restructuring Roadmap on page 13. Tool 2 Overall Organizer's Checklist on pages 14-16 provides detailed substeps. In summary, the four steps are as follows: (1) Take Charge of Change--Big Change; (2) Choose the Right Changes; (3) Implement the Plan; and (4) Evaluate, Improve, and Act on Failures. This guide primarily focuses on choosing among the first four options under No Child Left Behind (NCLB), which are relatively drastic and unfamiliar to district leaders. It grows out of four papers in the "What Works When" series that explore what is known about when and under what circumstances these four options improve student learning. Education Leaders' Summaries of these four papers appear at the end of this guide. State takeovers are addressed early, in Step 1, to help districts determine whether they have capacity to manage the restructuring decision process and again at the end of Step 2, when districts may consider state takeovers of some individual schools. (Contains 7 footnotes.) [This guide was produced by Learning Points Associates, Washington, DC and The Center for Comprehensive School Reform and Improvement, Washington, DC. Research was administered by Learning Point Associates in partnership with the Southwest Educational Development Laboratory (SEDL) and WestEd, under contract with the Office of Elementary and Secondary Education of the U.S. Department of Education.]

The mechanisms of obesity and type 2 diabetes (T2D)-associated impaired fracture healing are poorly studied. In a murine model of T2D reflecting both hyperinsulinemia induced by high-fat diet and insulinopenia induced by treatment with streptozotocin, we examined bone healing in a tibia cortical bone defect. A delayed bone healing was observed during hyperinsulinemia as newly formed bone was reduced by -28.4 ± 7.7% and was associated with accumulation of marrow adipocytes at the defect site +124.06 ± 38.71%, and increased density of SCA1+ (+74.99 ± 29.19%) but not Runx2+ osteoprogenitor cells. We also observed increased in reactive oxygen species production (+101.82 ± 33.05%), senescence gene signature (≈106.66 ± 34.03%), and LAMIN B1- senescent cell density (+225.18 ± 43.15%), suggesting accelerated senescence phenotype. During insulinopenia, a more pronounced delayed bone healing was observed with decreased newly formed bone to -34.9 ± 6.2% which was inversely correlated with glucose levels (R2 = 0.48, P < .004) and callus adipose tissue area (R2 = .3711, P < .01). Finally, to investigate the relevance to human physiology, we observed that sera from obese and T2D subjects had disease state-specific inhibitory effects on osteoblast-related gene signatures in human bone marrow stromal cells which resulted in inhibition of osteoblast and enhanced adipocyte differentiation. Our data demonstrate that T2D exerts negative effects on bone healing through inhibition of osteoblast differentiation of skeletal stem cells and induction of accelerated bone senescence and that the hyperglycemia per se and not just insulin levels is detrimental for bone healing.

Better drought preparedness is critically needed in the Central American Dry Corridor (CADC). Seasonal forecasts can be used to build this preparedness but need localized evaluations to ensure they are relevant and useful. This study provides a CADC-focused assessment of the SEAS5 seasonal forecasting system produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). We evaluate SEAS5 predictions of the mean, variability, and extremes of precipitation across the CADC at 1–7-month lead times. We assess differences in regional forecast quality across seasons and lead times by evaluating spatial and temporal associations with El Niño–Southern Oscillation (ENSO) phase, topography, and continentality. Results show that SEAS5 precipitation forecasts often have better skill primarily during the mid to late wet season (July–October). In these months, low/normal precipitation forecasts outperform the climatological mean (1982–2016) up to 5- or 6-month lead times in some subregions. Forecast skill is often worse, however, for predicting precipitation during the early wet season, primarily in June. Forecast skill varies spatially across the region, with higher skill concentrated in the southeast (Costa Rica and Nicaragua). Forecast skill is significantly related to continentality and topography, and together these factors account for at least a quarter of the spatial variance in annual skill at all lead times. Forecast accuracy varies depending on ENSO phase: predictions are often worse in El Niño (warm ENSO) periods during the early wet season when ENSO also has a weaker association with cumulative precipitation relative to the later wet season. SEAS5 could be a particularly useful tool during the second half of the wet season in the southeast CADC, skilfully alerting of upcoming precipitation variability with over 3-month lead times.

Cultured human bone marrow stromal (mesenchymal) stem cells (hBM-MSCs) are heterogenous cell populations exhibiting variable biological properties. Quantitative high-content imaging technology allows identification of morphological markers at a single cell resolution that are determinant for cellular functions. We determined the morphological characteristics of cultured primary hBM-MSCs and examined their predictive value for hBM-MSC functionality. BM-MSCs were isolated from 56 donors and characterized for their proliferative and differentiation potential. We correlated these data with cellular and nuclear morphological features determined by Operetta; a high-content imaging system. Cell area, cell- and nucleus geometry of cultured hBM-MSCs exhibited significant correlation with expression of hBM-MSC membrane markers: ALP, CD146, CD271. Proliferation capacity correlated negatively with cell and nucleus area and positively with cytoskeleton texture features. In addition, in vitro differentiation to osteoblasts as well as in vivo heterotopic bone formation was associated with decreased ratio of nucleus width to length. Multivariable analysis applying a stability selection procedure identified nuclear geometry and texture as predictors for hBM-MSCs differentiation potential to osteoblasts or adipocytes. Our data demonstrate that by employing a limited number of cell morphological characteristics, it is possible to predict the functional phenotype of cultured hBM-MSCs and thus can be used as a screening test for “quality” of hBM-MSCs prior their use in clinical protocols. Stem Cells Translational Medicine 2019.