Rexinoids Induce Differential Gene Expression in Human Glioblastoma Cells and Protein-Protein Interactions in a Yeast Two-Hybrid System.

Rexinoids are compounds that bind to the rexinoid X receptor (RXR) to modulate gene expression and have been proposed as a new class of therapeutics to treat Alzheimer's disease. Different rexinoids will initiate downstream effects that can be quite marked even though such compounds can be structurally similar and have comparable RXR binding affinities. RXR can both homo- and heterodimerize, and these protein-protein interactions and subsequent transactivating potential lead to differential gene expression, depending on the RXR dimeric partner, additional cofactors recruited, and downstream transcription factors that are up- or downregulated. Expression analysis was performed in the U87 human glioblastoma cell line treated with a panel of rexinoids, and our analysis demonstrated that rexinoids with similar RXR EC50 values can have pronounced differences in differential gene expression. Rexinoid binding likely leads to distinctive RXR conformations that cause major downstream gene expression alterations via modulation of RXR interacting proteins. Yeast two-hybrid analysis of RXR bait with two RXR interacting partners demonstrates that rexinoids drive differential binding of RXR to distinctive protein partners. Physiochemical analysis of the rexinoids reveals that the molecules cluster similarly to their gene expression patterns. Thus, rexinoids with similar RXR binding affinities drive differential gene expression by stimulating additional binding patterns in RXR and its homo- and heteropartners, driven by the physicochemical characteristics of these molecules.

New Validated Tool to Diagnose Breastfeeding Dysfunction.

BACKGROUND: Breastfeeding behaviors and experiences exist on a continuum. What differentiates normal from dysfunctional is defined by frequency and severity. No current validated tool addresses the subjective experience of dyads with a predictive score that can be followed over time. RESEARCH AIM: To create and validate a self-report tool to assess breastfeeding and evaluate its ability to predict risk of breastfeeding dysfunction. METHODS: This study used a cross-sectional design to determine the validity of a novel instrument to assess breastfeeding dysfunction. We gave the initial questionnaire to 2085 breastfeeding dyads. We assessed content validity by comparison with other tools. We used exploratory factor analysis with varimax rotation for concept identification and Cronbach's alpha for internal consistency. We employed logistic regression to assess the tool's ability to differentiate between normal breastfeeding and breastfeeding dysfunction. RESULTS: Factor analysis mapped 17 questions to four concepts to create a score (FLIP; flow, latch, injury [to the nipple], and post-feed behavior). Internal consistency and reliability of the scores in these concepts were acceptable (Cronbach's alpha ≥ 0.087 for all measures). A logistic regression model that controlled for infant age, with a breastfeeding dysfunction risk classification threshold of 60%, yielded a correct classification of 88.7%, with 93.1% sensitivity, 64.6% specificity, and a 6.5% false positive rate. CONCLUSIONS: The FLIP score was determined to be a valid and reliable instrument for quantifying the severity of breastfeeding dysfunction in children under 1 year old. Further studies will assess its usefulness in the management of breastfeeding dysfunction.

Microbes in fingerprints: A source for dating crime evidence?

Interest in the human microbiome has grown in recent years because of increasing applications to biomedicine and forensic science. However, the potential for dating evidence at a crime scene based upon time-dependent changes in microbial signatures has not been established, despite a relatively straightforward scientific process for isolating the microbiome. We hypothesize that modifications in microbial diversity, abundance, and succession can provide estimates of the time a surface was touched for investigative purposes. In this proof-of-concept research, the sequencing and analysis of the 16 S rRNA gene from microbes present in fresh and aged latent fingerprints deposited by three donors with pre- and post-washed hands is reported. The stability of major microbial phyla is confirmed while the dynamics of less abundant groups is described up to 21 days post-deposition. Most importantly, a phylum is suggested as the source for possible biological markers to date fingerprints: Deinococcus-Thermus.

Winter Rains Support Butterfly Diversity, but Summer Monsoon Rainfall Drives Post-Monsoon Butterfly Abundance in the Arid Southwest of the US.

Butterfly populations are declining worldwide, reflecting our current global biodiversity crisis. Because butterflies are a popular and accurate indicator of insect populations, these declines reflect an even more widespread threat to insects and the food webs upon which they rely. As small ectotherms, insects have a narrow range of habitable conditions; hence, extreme fluctuations and shifts caused by climate change may increase insects' risk of extinction. We evaluated trends of butterfly richness and abundance and their relationship with relevant climate variables in Arizona, U.S.A., using the past 40 years of community science data. We focused on precipitation and temperature as they are known to be influential for insect survival, particularly in arid areas like southwestern U.S.A. We found that preceding winter precipitation is a driver of both spring and summer/fall butterfly richness and spring butterfly abundance. In contrast, summer/fall butterfly abundance was driven by summer monsoon precipitations. The statistically significant declines over the 40-year period were summer/fall butterfly abundance and spring butterfly richness. When controlling for the other variables in the model, there was an average annual 1.81% decline in summer/fall season butterfly abundance and an average annual decline of 2.13 species in the spring season. As climate change continues to negatively impact winter precipitation patterns in this arid region, we anticipate the loss of butterfly species in this region and must consider individual butterfly species trends and additional management and conservation needs.

Partitioned GMM logistic regression models for longitudinal data.

Correlation is inherent in longitudinal studies due to the repeated measurements on subjects, as well as due to time-dependent covariates in the study. In the National Longitudinal Study of Adolescent to Adult Health (Add Health), data were repeatedly collected on children in grades 7-12 across four waves. Thus, observations obtained on the same adolescent were correlated, while predictors were correlated with current and future outcomes such as obesity status, among other health issues. Previous methods, such as the generalized method of moments (GMM) approach have been proposed to estimate regression coefficients for time-dependent covariates. However, these approaches combined all valid moment conditions to produce an averaged parameter estimate for each covariate and thus assumed that the effect of each covariate on the response was constant across time. This assumption is not necessarily optimal in applications such as Add Health or health-related data. Thus, we depart from this assumption and instead use the Partitioned GMM approach to estimate multiple coefficients for the data based on different time periods. These extra regression coefficients are obtained using a partitioning of the moment conditions pertaining to each respective relationship. This approach offers a deeper understanding and appreciation into the effect of each covariate on the response. We conduct simulation studies, as well as analyses of obesity in Add Health, rehospitalization in Medicare data, and depression scores in a clinical study. The Partitioned GMM methods exhibit benefits over previously proposed models with improved insight into the nonconstant relationships realized when analyzing longitudinal data.

Comparison of trailside degradation across a gradient of trail use in the Sonoran Desert.

As recreational visitation to the Sonoran Desert increases, the concern of scientists, managers and advocates who manage its natural resources deepens. Although many studies have been conducted on trampling of undisturbed vegetation and the effects of trails on adjacent plant and soil communities, little such research has been conducted in the arid southwest. We sampled nine 450-m trail segments with different visitation levels in Scottsdale's McDowell Sonoran Preserve over three years to understand the effects of visitation on soil erosion, trailside soil crusts and plant communities. Soil crust was reduced by 27-34% near medium and high use trails (an estimated peak rate of 13-70 visitors per hour) compared with control plots, but there was less than 1% reduction near low use trails (peak rate of two to four visitors per hour). We did not detect soil erosion in the center 80% of the trampled area of any of the trails. The number of perennial plant species dropped by less than one plant species on average, but perennial plant cover decreased by 7.5% in trailside plots compared with control plots 6 m off-trail. At the current levels of visitation, the primary management focus should be keeping people on the originally constructed trail tread surface to reduce impact to adjacent soil crusts.

Ridge Width Correlations between Inked Prints and Powdered Latent Fingerprints.

A methodology to estimate the time of latent fingerprint deposition would be of great value to law enforcement and courts. It has been observed that ridge topography changes as latent prints age, including the widths of ridges that could be measured as a function of time. Crime suspects are commonly identified using fingerprint databases that contain reference inked tenprints (flat and rolled impressions). These can be of interest in aging studies as they provide baseline information relating to the original (nonaged) ridges' widths. In practice, the age of latent fingerprints could be estimated following a comparison process between the evidentiary aged print and the corresponding reference inked print. The present article explores possible correlations between inked and fresh latent fingerprints deposited on different substrates and visualized with TiO2 . The results indicate that the ridge width of flat inked prints is most similar to fresh latent fingerprints, and these should be used as the comparison standard for future aging studies.

Mitigating Chinese-Indian rhesus macaque (Macaca mulatta) hybridity at the California National Primate Research Center (CNPRC).

The effectiveness of abating hybridity in a rhesus breeding colony was evaluated. STR data from the 2006 to 2015 newborns were analyzed. Hybridity decreased over successive years. Birth cohorts retained high genetic variability without signs of inbreeding and differentiation. Hybridity was minimized without compromising overall genetic variability.

Variability in capsaicinoid content and Scoville heat ratings of commercially grown Jalapeño, Habanero and Bhut Jolokia peppers.

The variability of capsaicinoid content of three common, commercially-available hot pepper varieties, namely Jalapeño, Habanero and Bhut Jolokia, was investigated. For each variety tested, ten peppers were acquired from each of ten different suppliers resulting in 100 peppers per variety that were individually analyzed. The results showed that different pepper varieties had different distribution types. The Habanero peppers showed a normal distribution; the Bhut Jolokia showed a skewed distribution and the Jalapeño peppers showed a very skewed distribution. The source of variability was also different; the Habaneros were very consistent within a given pepper supplier so most of the overall variation resulted from differences between suppliers. The Jalapeño peppers were the exact opposite with a very high degree of variability within a given supplier and relatively low variation between suppliers. A bootstrap statistical simulation was conducted on the data to suggest a minimum number of peppers to analyze to characterize the variation in a population. The simulations indicated that small sample sizes are effective at estimating the mean concentrations, but a sample size of ten or more is necessary to describe the population and capture the high-end tail of the distributions, which are the very hottest peppers.

National projections of time, cost and failure in implantable device identification: Consideration of unique device identification use.

BACKGROUND: U.S. health care is responding to significant regulation and meaningful incentives for higher quality care, patient safety, electronic documentation and data exchange. FDA's Unique Device Identification (UDI) Rule, a relatively new regulation aligned with these goals, requires standard labeling of medical devices by manufacturers. This lays the foundation for UDI scanning and documentation in the electronic health record, expected to change the landscape of medical device identification and postmarket surveillance. METHODS: We developed national projections for time, cost and failure in implant identification prior to revision total hip and knee arthroplasty (THA/TKA) using American Association of Hip and Knee Surgeons 2012 membership survey data, Nationwide Inpatient Sample 2011 data and THA/TKA demand projection data. RESULTS: Our projections suggest that cumulative surgeon time spent identifying failed implants could reach 133,000 h in 2030, representing opportunity to perform over 500,000 15 min established patient office visits. Staff time could reach 220,000 h with a cost of $3.3m. Failed implants that cannot be identified may be greater than 50,000 preoperatively and 25,000 intraoperatively in 2030. CONCLUSION: Study projections indicate significant time, cost and inability to identify failed implants, supporting need for improvement of implant documentation. FDA's UDI Rule sets the foundation for UDI scanning and documentation in the electronic health record, a process poised to serve as the standard system for device documentation.