Introductory Chemistry

Teaching and Learning resources for the 1st Year Introductory Chemistry course (Forensic Science). 30 credits. These are Open Educational Resources (OER), made available for re-use under a Creative Commons license

An Integrated Approach To Recruiting And Retaining Appalachian Engineering Students

Recruiting and retaining Appalachian engineering students is difficult for a variety of ecological and cultural reasons. At West Virginia University an NSF STEP grant1* has allowed the development specific interventions to evolve from an ecological model we describe here. The interventions include web-based, realistic engineering design exercises linked to state and federal content standards and objectives; a week-long residential summer camp addressing social and academic challenges for rural and minority students; a full set of retention efforts including "rescue courses" targeting struggling college freshmen in early stages of academic difficulty coupled with required study labs to underscore time management and persistence skills early in a freshman's academic career. Process and impact measures suggest that this package of interventions is effective in building interest in engineering not only in high school teachers but in the high school students themselves. While freshman retention has improved remarkably to an all time high of 84%, we conclude that it may take longer than five years to establish among youth in Appalachia an "engineering identity" as a cultural norm. We discuss the key aspects of our 5 year NSF project along with findings and conclusions

Chemistry.FM: the use of video clips produced by students in the teaching of chemistry

A novel approach proposed here is that we intend to use students as teachers in the video clips. Video material in all areas of chemistry and the evaluation obtained through student feedback and YouTube are also presented

Worlds Beyond: A Strategy for the Detection and Characterization of Exoplanets Executive Summary of a Report of the ExoPlanet Task Force Astronomy and Astrophysics Advisory Committee Washington, DC June 23, 2008

[No abstract

LHS6343C: A Transiting Field Brown Dwarf Discovered by the Kepler Mission

We report the discovery of a brown dwarf that transits one member of the M+M binary system LHS6343AB every 12.71 days. The transits were discovered using photometric data from the Kelper public data release. The LHS6343 stellar system was previously identified as a single high-proper-motion M dwarf. We use high-contrast imaging to resolve the system into two low-mass stars with masses 0.45 Msun and 0.36 Msun, respectively, and a projected separation of 55 arcsec. High-resolution spectroscopy shows that the more massive component undergoes Doppler variations consistent with Keplerian motion, with a period equal to the transit period and an amplitude consistent with a companion mass of M_C = 62.8 +/- 2.3 Mjup. Based on an analysis of the Kepler light curve we estimate the radius of the companion to be R_C = 0.832 +/- 0.021 Rjup, which is consistent with theoretical predictions of the radius of a > 1 Gyr brown dwarf.Comment: Our previous analysis neglected the dependence of the scaled semimajor axis, a/R, on the transit depth. By not correcting a/R for the third-light contamination, we overestimated the mass of Star A, which led to an overestimate the mass and radius of the LHS6343

Hypervelocity Planets and Transits Around Hypervelocity Stars

The disruption of a binary star system by the massive black hole at the Galactic Centre, SgrA*, can lead to the capture of one star around SgrA* and the ejection of its companion as a hypervelocity star (HVS). We consider the possibility that these stars may have planets and study the dynamics of these planets. Using a direct $N$-body integration code, we simulated a large number of different binary orbits around SgrA*. For some orbital parameters, a planet is ejected at a high speed. In other instances, a HVS is ejected with one or more planets orbiting around it. In these cases, it may be possible to observe the planet as it transits the face of the star. A planet may also collide with its host star. In such cases the atmosphere of the star will be enriched with metals. In other cases, a planet is tidally disrupted by SgrA*, leading to a bright flare.Comment: 8 pages, 5 figures, 2 tables, accepted for publication in MNRA

Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy.

MotivationMultiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia.ResultsWe performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified.Availability and implementationDatasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/.Supplementary informationSupplementary data are available at Bioinformatics online

An immune clock of human pregnancy

The maintenance of pregnancy relies on finely tuned immune adaptations. We demonstrate that these adaptations are precisely timed, reflecting an immune clock of pregnancy in women delivering at term. Using mass cytometry, the abundance and functional responses of all major immune cell subsets were quantified in serial blood samples collected throughout pregnancy. Cell signaling-based Elastic Net, a regularized regression method adapted from the elastic net algorithm, was developed to infer and prospectively validate a predictive model of interrelated immune events that accurately captures the chronology of pregnancy. Model components highlighted existing knowledge and revealed previously unreported biology, including a critical role for the interleukin-2-dependent STAT5ab signaling pathway in modulating T cell function during pregnancy. These findings unravel the precise timing of immunological events occurring during a term pregnancy and provide the analytical framework to identify immunological deviations implicated in pregnancy-related pathologies

Multiomic immune clockworks of pregnancy

Preterm birth is the leading cause of mortality in children under the age of five worldwide. Despite major efforts, we still lack the ability to accurately predict and effectively prevent preterm birth. While multiple factors contribute to preterm labor, dysregulations of immunological adaptations required for the maintenance of a healthy pregnancy is at its pathophysiological core. Consequently, a precise understanding of these chronologically paced immune adaptations and of the biological pacemakers that synchronize the pregnancy “immune clock” is a critical first step towards identifying deviations that are hallmarks of peterm birth. Here, we will review key elements of the fetal, placental, and maternal pacemakers that program the immune clock of pregnancy. We will then emphasize multiomic studies that enable a more integrated view of pregnancy-related immune adaptations. Such multiomic assessments can strengthen the biological plausibility of immunological findings and increase the power of biological signatures predictive of preterm birth

Multiomics Longitudinal Modeling of Preeclamptic Pregnancies

Preeclampsia is a complex disease of pregnancy whose physiopathology remains unclear and that poses a threat to both mothers and infants. Specific complex changes in women\u27s physiology precede a diagnosis of preeclampsia. Understanding multiple aspects of such a complex changes at different levels of biology, can be enabled by simultaneous application of multiple assays. We developed prediction models for preeclampsia risk by analyzing six omics datasets from a longitudinal cohort of pregnant women. A machine learning-based multiomics model had high accuracy (area under the receiver operating characteristics curve (AUC) of 0.94, 95% confidence intervals (CI):[0.90, 0.99]). A prediction model using only ten urine metabolites provided an accuracy of the whole metabolomic dataset and was validated using an independent cohort of 16 women (AUC= 0.87, 95% CI:[0.76, 0.99]). Integration with clinical variables further improved prediction accuracy of the urine metabolome model (AUC= 0.90, 95% CI:[0.80, 0.99], urine metabolome, validated). We identified several biological pathways to be associated with preeclampsia. The findings derived from models were integrated with immune system cytometry data, confirming known physiological alterations associated with preeclampsia and suggesting novel associations between the immune and proteomic dynamics. While further validation in larger populations is necessary, these encouraging results will serve as a basis for a simple, early diagnostic test for preeclampsia