Dietary Nutrient Intake and Obesity Prevalence Among Native American Adolescents

The prevalence of obesity among adolescent minority populations has been long recognized, but little research has been done on Native Americans adolescents. Using anthropometric measurements and dietary assessments, the findings within each study have shown to obtain baseline measures to determine the prevalence of obesity within the Sherman Indian High School's Native American adolescent population. Data of each assessment appear to be of use for predicting obesity and creating effective future interventions. Compiling data using the Harvard School of Public Health Youth/Adolescent Questionnaire (HSPH YAQ), a semi-quantitative food frequency questionnaire allowed significant data to be found between normal and obese weight students. Utilizing each finding allows more effective ways of targeting and reversing the inclining rate of obesity among Native American adolescents. Results show that antioxidants being examined on such as vitamin E and lycopene are beneficial in lowering the obesity rate among Native American adolescents. Levels of fiber, thiamin and folate consumption was significantly lower among the obese population in Sherman Indian High School's Native American adolescents. Moreover, dietary mineral intake was shown to be lower among obese Native American adolescents comparing with the normal weight group. The results suggested that dietary consumption of these nutrients might correlate and predict obesity and lead to the development of effective interventions for Native Americans. This study also found the effects of total fiber and vitamin B in diets with lifestyle intervention in prediabetic adults, showing that total fiber intake among the normal weight students is significantly higher than obese students, indicating that fiber and vitamin profile could be important determinants of the effect of dietary intervention

Evaluating Markers for Selecting a Patient\u27s Treatment

Selecting the best treatment for a patient\u27s disease may be facilitated by evaluating clinical characteristics or biomarker measurements at diagnosis. We consider how to evaluate the potential of such measurements to impact on treatment selection algorithms. For example, magnetic resonance neurographic imaging is potentially useful for deciding whether a patient should be treated surgically for carpal tunnel syndrome or if he/she should receive less invasive conservative therapy. We propose a graphical display, the selection impact (SI) curve, that shows the population response rate as a function of treatment selection criteria based on the marker. The curve can be useful for choosing a treatment policy that incorporates information on the patient\u27s marker value exceeding a threshold. The SI curve can be estimated using data from a comparative randomized trial conducted in the population as long as treatment assignment in the trial is independent of the predictive marker. Estimating the SI curve is therefore part of a post-hoc analysis to determine if the marker identifies patients that are more likely to benefit from one treatment over another. Nonparametric and parametric estimates of the SI curve are proposed in this paper. Asymptotic distribution theory is used to evaluate the relative efficiencies of the estimators. Simulation studies show that inference is straightforward with realistic sample sizes. We illustrate the SI curve and statistical inference for it with data motivated by an ongoing trial of surgery versus conservative therapy for carpal tunnel syndrome

Net Influence of an Internally Generated Guasi-biennial Oscillation on Modelled Stratospheric Climate and Chemistry

A Goddard Earth Observing System Chemistry- Climate Model (GEOSCCM) simulation with strong tropical non-orographic gravity wave drag (GWD) is compared to an otherwise identical simulation with near-zero tropical non-orographic GWD. The GEOSCCM generates a quasibiennial oscillation (QBO) zonal wind signal in response to a tropical peak in GWD that resembles the zonal and climatological mean precipitation field. The modelled QBO has a frequency and amplitude that closely resembles observations. As expected, the modelled QBO improves the simulation of tropical zonal winds and enhances tropical and subtropical stratospheric variability. Also, inclusion of the QBO slows the meridional overturning circulation, resulting in a generally older stratospheric mean age of air. Slowing of the overturning circulation, changes in stratospheric temperature and enhanced subtropical mixing all affect the annual mean distributions of ozone, methane and nitrous oxide. Furthermore, the modelled QBO enhances polar stratospheric variability in winter. Because tropical zonal winds are easterly in the simulation without a QBO, there is a relative increase in tropical zonal winds in the simulation with a QBO. Extratropical differences between the simulations with and without a QBO thus reflect the westerly shift in tropical zonal winds: a relative strengthening of the polar stratospheric jet, polar stratospheric cooling and a weak reduction in Arctic lower stratospheric ozone

Micro-Environment Causes Reversible Changes in DNA Methylation and mRNA Expression Profiles in Patient-Derived Glioma Stem Cells

In vitro and in vivo models are widely used in cancer research. Characterizing the similarities and differences between a patient\u27s tumor and corresponding in vitro and in vivo models is important for understanding the potential clinical relevance of experimental data generated with these models. Towards this aim, we analyzed the genomic aberrations, DNA methylation and transcriptome profiles of five parental tumors and their matched in vitro isolated glioma stem cell (GSC) lines and xenografts generated from these same GSCs using high-resolution platforms. We observed that the methylation and transcriptome profiles of in vitro GSCs were significantly different from their corresponding xenografts, which were actually more similar to their original parental tumors. This points to the potentially critical role of the brain microenvironment in influencing methylation and transcriptional patterns of GSCs. Consistent with this possibility, ex vivo cultured GSCs isolated from xenografts showed a tendency to return to their initial in vitro states even after a short time in culture, supporting a rapid dynamic adaptation to the in vitro microenvironment. These results show that methylation and transcriptome profiles are highly dependent on the microenvironment and growth in orthotopic sites partially reverse the changes caused by in vitro culturing

The Impact of Warm Pool El Nino Events on Antarctic Ozone

Warm pool El Nino (WPEN) events are characterized by positive sea surface temperature (SST) anomalies in the central equatorial Pacific in austral spring and summer. Previous work found an enhancement in planetary wave activity in the South Pacific in austral spring, and a warming of 3-5 K in the Antarctic lower stratosphere during austral summer, in WPEN events as compared with ENSO neutral. In this presentation, we show that weakening of the Antarctic vortex during WPEN affects the structure and magnitude of high-latitude total ozone. We use total ozone data from TOMS and OMI, as well as station data from Argentina and Antarctica, to identify shifts in the longitudinal location of the springtime ozone minimum from its climatological position. In addition, we examine the sensitivity of the WPEN-related ozone response to the phase of the quasi-biennial oscillation (QBO). We then compare the observed response to WPEN events with Goddard Earth Observing System chemistry-climate model, version 2 (GEOS V2 CCM) simulations. Two, 50-year time-slice simulations are forced by annually repeating SST and sea ice climatologies, one set representing observed WPEN events and the second set representing neutral ENSO events, in a present-day climate. By comparing the two simulations, we isolate the impact of WPEN events on lower stratospheric ozone, and furthermore, examine the sensitivity of the WPEN ozone response to the phase of the QBO

FALLING RESULTS IN VARIABLES ASSOCIATED WITH DECREASED ACL LOADING DURING LANDINGS AFTER MID-FLIGHT TRUNK PERTURBATION

Trunk contact is commonly observed near the time of anterior cruciate ligament (ACL) injuries. Soft landings and falling after landing are suggested to decrease ACL injury risk. The purpose was to assess the effect of natural landing, soft landing, and falling techniques on variables associated with ACL loading, including knee flexion, impact forces, knee abduction angles and moments during single-leg landings with or without mid-flight medial-lateral external upper-trunk perturbation. Twenty-eight participants performed single-leg landings using the three landing techniques with or without mid-flight perturbation. Falling resulted in variables associated with decreased ACL loading compared to natural and soft landings, especially for perturbation conditions. Falling techniques are suggested to modify variables associated with ACL loading when the sports environment allows

Patient and family communication during consultation visits: The effects of a decision aid for treatment decision-making for localized prostate cancer

To analyze the effects of a decision aid on improving patients’ and family members’ information giving and question asking during consultations for prostate cancer treatment decision-making

High-spatial-resolution imaging of thermal emission from debris disks

We have obtained sub-arcsec mid-IR images of a sample of debris disks within 100 pc. For our sample of nineteen A-type debris disk candidates chosen for their IR excess, we have resolved, for the first time, five sources plus the previously resolved disk around HD 141569. Two other sources in our sample have been ruled out as debris disks since the time of sample selection. Three of the six resolved sources have inferred radii of 1-4 AU (HD 38678, HD 71155, and HD 181869), and one source has an inferred radius ~10-30 AU (HD 141569). Among the resolved sources with detections of excess IR emission, HD 71155 appears to be comparable in size (r~2 AU) to the solar system's asteroid belt, thus joining Zeta Lep (HD 38678, reported previously) to comprise the only two resolved sources of that class. Two additional sources (HD 95418 and HD 139006) show spatial extent that implies disk radii of ~1-3 AU, although the excess IR fluxes are not formally detected with better than 2-sigma significance. For the unresolved sources, the upper limits on the maximum radii of mid-IR disk emission are in the range ~1-20 AU, four of which are comparable in radius to the asteroid belt. We have compared the global color temperatures of the dust to that expected for the dust in radiative equilibrium at the distances corresponding to the observed sizes or limits on the sizes. In most cases, the temperatures estimated via these two methods are comparable, and therefore, we see a generally consistent picture of the inferred morphology and the global mid-IR emission. Finally, while our sample size is not statistically significant, we notice that the older sources (>200 Myr) host much warmer dust (T > 400 K) than younger sources (in the 10s of Myr).Comment: 46 pages, 12 figure

Advances in geocomputation and geospatial artificial intelligence (GeoAI) for mapping

Geocomputation and geospatial artificial intelligence (GeoAI) have essential roles in advancing geographic information science (GIS) and Earth observation to a new stage. GeoAI has enhanced traditional geospatial analysis and mapping, altering the methods for understanding and managing complex human–natural systems. However, there are still challenges in various aspects of geospatial applications related to natural, built, and social environments, and in integrating unique geospatial features into GeoAI models. Meanwhile, geospatial and Earth data are critical components in geocomputation and GeoAI studies, as they can effectively reveal geospatial patterns, factors, relationships, and decision-making processes. This editorial provides a comprehensive overview of geocomputation and GeoAI applications in mapping, classifying them into four categories: (i) buildings and infrastructure, (ii) land use analysis, (iii) natural environment and hazards, and (iv) social issues and human activities. In addition, the editorial summarizes geospatial and Earth data in case studies into seven categories, including in-situ data, geospatial datasets, crowdsourced geospatial data (i.e., geospatial big data), remote sensing data, photogrammetry data, LiDAR, and statistical data. Finally, the editorial presents challenges and opportunities for future research