Atlanta Public Schools

BackgroundAtherosclerotic cardiovascular diseases (ASCVDs) are the leading cause of worldwide adult mortality. Although broad classes of dietary fats have been shown to alter ASCVD risk, the roles that individual dietary fatty acids play in influencing ASCVD risk are unclear. ObjectivesThe aim of this prospective cohort study was to examine the relationships of the total fat classes and individual fatty acids with the risk of ASCVD. MethodsThe Million Veteran Program is a prospective cohort whereby dietary intake of fatty acids was assessed in 158,198 participants that had enrolled between January 2011 and November 2018 and were free of ASCVD at baseline. Incident ASCVD was ascertained from the Veterans Affairs electronic health records and the National Death Index. Multivariable-adjusted hazard ratios (HRs) for the relationship between fat intake and ASCVD risk were computed using Cox regression models. ResultsThe mean age was 61 years, 88% were males. A total of 11,771 ASCVD events were identified during the follow-up. When compared with the lowest quintile, participants in the highest quintile of dietary trans-monounsaturated fats and conjugated linoleic acids had an increased risk (HR [95% CI]) of ASCVD events: 1.10 (1.04, 1.17) and 1.11 (1.05, 1.18), respectively. When compared with low consumers, participants in the highest quintile of total cis-polyunsaturated fatty acid intake had a lower risk of experiencing an ASCVD event 0.93 (0.87, 0.99). ConclusionAlthough higher intakes of specific trans-fatty acids and conjugated linoleic were associated with an increased risk of ASCVD, the same cannot be said for all other fat classes. This work suggests that care must be taken when drawing general conclusions regarding the health effects of dietary individual fatty acids.

This meta-analysis synthesized the findings of experimental and quasi-experimental studies to determine the efficacy of math interventions for enhancing the word problem-solving accuracy of students with mathematics difficulties in Grades 4 to 12. Further, we identified intervention and design characteristics that moderate the effectiveness of interventions. We appraised study quality using Council for Exceptional Children (CEC's) evidence standards. We also used random-effects meta-regression models with robust variance estimation (RVE) to compute the overall weighted treatment effect and investigate the moderating impact of 15 variables. Results from 36 intervention studies published between 1989 and 2020 reveal a relatively large and positive mean effect size (g = 0.71; SE = 0.11, 95% CI [0.49, 0.92]) across 88 outcomes, suggesting the examined interventions were effective. The moderator analyses' findings showed the treatment efficacy varied as a function of five intervention characteristics, including intervention model, interventionist, grade level, math topic, and intervention duration. None of the design features we examined led to significant moderator effects. We discuss findings and limitations and provide directions for future research and practice.

As the evidence linking test scores to long-run student outcomes has grown, standardized assessments have become a widely used management tool in education including addressing the racial education gap. One of the concerns with the use of standards tests is the perverse incentive for teachers to alter test scores. The consequences for educators found cheating can be substantial, although little is known about how students are impacted by cheating. Using an 11-year panel of individual-level data on students and teachers from a predominantly Black urban school district where widespread test-score manipulation occurred, we investigated the impact of teacher cheating on subsequent student test scores. To access the impact, we used school-grade and classroom fixed effects as well as measure potential omitted variable bias (OVB). We found that for each additional wrong-to-right altered test question it is associated with a reduced future achievement of between 0.003 and 0.014 standard deviations depending on the specification. Although the evidence from OVB analysis does not suggest that test-score manipulation itself harmed or benefited students. Our evidence also contributes to a growing literature on the importance of sensitivity tests for OVB. We show how failure to conduct such tests could lead to erroneous findings.

POGIL (Process Oriented Guided Inquiry Learning) is based on the principle that students learn more when they construct their own understanding. Instead of attending lecture, student teams work through POGIL activities to discover concepts on their own, while instructors circulate and facilitate learning. Students learn the material better, and this constructivist approach also teaches them important process skills, including critical thinking, team work, and leadership. In this special session, SIGCSE attendees will experience a POGIL activity for themselves, learn about the structure of POGIL activities (through a POGIL meta-activity), and hear perspectives from teachers who recently adopted POGIL activities available at http://cspogil.org. We will share classroom-tested guided inquiry activities and discuss how POGIL can transform CS classes at all levels, from high school to graduate-level classes, from small schools to large universities.

BackgroundStrains from a collection of Drosophila GFP protein trap lines express GFP in the normal tissues where the endogenous protein is present. This collection can be used to screen for proteins distributed in the nucleus in a non-uniform pattern.Methodology/Principal FindingsWe analyzed four lines that show peripheral or punctate nuclear staining. One of these lines affects an uncharacterized gene named CG11138. The CG11138 protein shows a punctate distribution in the nuclear periphery similar to that of Drosophila insulator proteins but does not co-localize with known insulators. Interestingly, mutations in Lamin proteins result in alterations in CG11138 localization, suggesting that this protein may be a novel component of the nuclear lamina. A second line affects the Decondensation factor 31 (Df31) gene, which encodes a protein with a unique nuclear distribution that appears to segment the nucleus into four different compartments. The X-chromosome of males is confined to one of these compartments. We also find that Drosophila Nucleoplasmin (dNlp) is present in regions of active transcription. Heat shock leads to loss of dNlp from previously transcribed regions of polytene chromosome without redistribution to the heat shock genes. Analysis of Stonewall (Stwl), a protein previously found to be necessary for the maintenance of germline stem cells, shows that Stwl is present in a punctate pattern in the nucleus that partially overlaps with that of known insulator proteins. Finally we show that Stwl, dNlp, and Df31 form part of a highly interactive network. The properties of other components of this network may help understand the role of these proteins in nuclear biology.Conclusions/SignificanceThese results establish screening of GFP protein trap alleles as a strategy to identify factors with novel cellular functions. Information gained from the analysis of CG11138 Stwl, dNlp, and Df31 sets the stage for future studies of these proteins.

Imaging mass spectrometry is a method for understanding the molecular distribution in a two-dimensional sample. This method is effective for a wide range of molecules, but generates a large amount of data. It is difficult to extract important information from these large datasets manually and automated methods for discovering important spatial and spectral features are needed. Independent component analysis and non-negative matrix factorization are explained and explored as tools for identifying underlying factors in the data. These techniques are compared and contrasted with principle component analysis, the more standard analysis tool. Independent component analysis and non-negative matrix factorization are found to be more effective analysis methods. A mouse cerebellum dataset is used for testing.

Students who are deaf or hard of hearing typically lack descriptors in their written expression. Visual tools are often used in the classroom with this population, without empirical support. This study used a single-subject changing criterion design in an attempt to fill the gap between practice and research. The purpose was to test the use of a visual tool with deaf or hard of hearing students in writing a response to age-appropriate action pictures. Three adolescent students who were deaf or hard of hearing were taught how to write a response to a series of questions using a visual tool and were guided through an experience of modeled, shared, guided, and independent attempts. The use of a visual tool in the practice of writing, along with faded teacher support, helped each student involved in the study increase the descriptiveness of his or her writing, as measured by the number of adjectives in his or her writing samples. However, while the number of adjectives increased, the number of action words and story grammar elements decreased. Further research is needed to address how to help students increase descriptiveness while maintaining action and story grammar.

We used a one‐dimensional (1‐D) cloud parcel model to assess the impact of biomass‐burning aerosol on cloud properties in the Amazon Basin and to identify the physical and chemical properties of the aerosol that influence droplet growth. Cloud condensation nuclei (CCN) measurements were performed between 0.15% and 1.5% supersaturation at ground‐based sites in the states of Amazonas and Rondônia, Brazil during several field campaigns in 1998 and 1999 as part of the Large‐Scale Biosphere–Atmosphere (LBA) Experiment in Amazonia. CCN concentrations measured during the wet season were low and resembled concentrations more typical of marine conditions than most continental sites. During the dry season, smoke aerosol from biomass burning dramatically increased CCN concentrations. The modification of cloud properties, such as cloud droplet effective radius and maximum supersaturation, is most sensitive at low CCN concentrations. Hence, we could expect larger interannual variation of cloud properties during the wet season that the dry season. We found that differences between CCN spectra from forested and deforested regions during the wet season are modest and result in modifications of cloud properties that are small compared to those between wet and dry seasons. Our study suggests that the differences in surface albedo, rather than cloud albedo, between forested and deforested regions may dominate the impact of deforestation on the hydrological cycle and convective activity during the wet season. During the dry season, on the other hand, cloud droplet concentrations may increase by up to 7 times, which leads to a model‐predicted decrease in cloud effective radius by a factor of 2. This could imply a maximum indirect radiative forcing due to aerosol as high as ca. −27 W m−2 for a nonabsorbing cloud. Light‐absorbing substances in smoke darken the Amazonian clouds and reduce the net radiative forcing, and a comparison of the Advanced Very High Resolution Radiometer (AVHRR) analysis and our modeling studies suggests that absorption of sunlight due to smoke aerosol may compensate for about half of the maximum aerosol effect. Sensitivity tests show that complete characterization of the aerosol is necessary when kinetic growth limitations become important. Subtle differences in the chemical and physical makeup are shown to be particularly influential in the activation and growth behavior of the aerosol. Knowledge of the CCN spectrum alone is not sufficient to fully capture the climatic influence of biomass burning.