Consequences of altered Cacna1c and Cacna1d expression levels on CaV1.2 and CaV1.3 activity

HonorsUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/162634/1/jlmcmaho.pd

Reactions to Supporters of the 2016 Presidential Candidates

Two experiments were carried out to explore responses to supporters of 2016 Presidential candidates. In Study 1, a field experiment was carried out on the effect of political affiliation on an individual’s willingness to reciprocate a smile. The prediction that more participants (90 females, 90 males) on the SHU campus would return a smile to confederates wearing Trump vs. Clinton vs. a Neutral t-shirt was not supported. In Study 2, 253 participants volunteered to participate in a social perception experiment in which they rated confederates wearing a neutral, Trump, or Clinton for President t-shirt. In line with the hypothesis, MANOVA results showed that Trump supporters were perceived as more prejudiced (p \u3c .003) and Clinton supporters as more liberal (p \u3c .000)

Sequential Photoperiodic Programing of Serotonin Neurons, Signaling and Behaviors During Prenatal and Postnatal Development

Early life stimuli during critical developmental time frames have been linked to increased risk for neurodevelopmental disorders later in life. The serotonergic system of the brain is implicated in mood disorders and is impacted by the duration of daylight, or photoperiod. Here we sought to investigate sensitive periods of prenatal and postnatal development for photoperiodic programming of DRN serotonin neurons, midbrain serotonin and metabolite levels along with affective behaviors in adolescence (P30) or adulthood (P50). To address these questions we restricted the interval of exposure to prenatal development (E0-P0) for Long summer-like photoperiods (LD 16:8), or Short winter-like photoperiods (LD 8:16) with postnatal development and maturation then occurring under the opposing photoperiod. Prenatal exposure alone to Long photoperiods was sufficient to fully program increased excitability of DRN serotonin neurons into adolescence and adulthood, similar to maintained exposure to Long photoperiods throughout development. Interestingly, Long photoperiod exposure can elevate serotonin and its’ corresponding metabolite levels along with reducing affective behavior, which appear to have both pre and postnatal origins. Thus, exposure to Long photoperiods prenatally programs increased DRN serotonin neuronal excitability, but this step is insufficient to program serotonin signaling and affective behavior. Continuing influence of Long photoperiods during postnatal development then modulates serotonergic content and has protective effects for depressive-like behavior. Photoperiodic programing of serotonin function in mice appears to be a sequential process with programing of neuronal excitability as a first step occurring prenatally, while programing of circuit level serotonin signaling and behavior extends into the postnatal period

Qualitative Analysis of Reflective Narratives of Physical Therapy Students Attempting to Implement Biopsychosocial Approaches to Care

Purpose: To examine the learning process of physical therapy students attempting to apply BPS principles to clinical treatment during both an initial training period under mentorship, and during clinical rotations

Noble gas signatures constrain oil-field water as the carrier phase of hydrocarbons occurring in shallow aquifers in the San Joaquin Basin, USA

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Karolyte, R., Barry, P. H., Hunt, A. G., Kulongoski, J. T., Tyne, R. L., Davis, T. A., Wright, M. T., McMahon, P. B., & Ballentine, C. J. Noble gas signatures constrain oil-field water as the carrier phase of hydrocarbons occurring in shallow aquifers in the San Joaquin Basin, USA. Chemical Geology, 584, (2021): 120491, https://doi.org/10.1016/j.chemgeo.2021.120491.Noble gases record fluid interactions in multiphase subsurface environments through fractionation processes during fluid equilibration. Water in the presence of hydrocarbons at the subsurface acquires a distinct elemental signature due to the difference in solubility between these two fluids. We find the atmospheric noble gas signature in produced water is partially preserved after hydrocarbons production and water disposal to unlined ponds at the surface. This signature is distinct from meteoric water and can be used to trace oil-field water seepage into groundwater aquifers. We analyse groundwater (n = 30) and fluid disposal pond (n = 2) samples from areas overlying or adjacent to the Fruitvale, Lost Hills, and South Belridge Oil Fields in the San Joaquin Basin, California, USA. Methane (2.8 × 10−7 to 3 × 10−2 cm3 STP/cm3) was detected in 27 of 30 groundwater samples. Using atmospheric noble gas signatures, the presence of oil-field water was identified in 3 samples, which had equilibrated with thermogenic hydrocarbons in the reservoir. Two (of the three) samples also had a shallow microbial methane component, acquired when produced water was deposited in a disposal pond at the surface. An additional 6 samples contained benzene and toluene, indicative of interaction with oil-field water; however, the noble gas signatures of these samples are not anomalous. Based on low tritium and 14C contents (≤ 0.3 TU and 0.87–6.9 pcm, respectively), the source of oil-field water is likely deep, which could include both anthropogenic and natural processes. Incorporating noble gas analytical techniques into the groundwater monitoring programme allows us to 1) differentiate between thermogenic and microbial hydrocarbon gas sources in instances when methane isotope data are unavailable, 2) identify the carrier phase of oil-field constituents in the aquifer (gas, oil-field water, or a combination), and 3) differentiate between leakage from a surface source (disposal ponds) and from the hydrocarbon reservoir (either along natural or anthropogenic pathways such as faulty wells).This work was supported by the U.S. Geological Survey as part of the California State Water Resources Control Board's Oil and Gas Regional Monitoring Program

The Primordial Inflation Polarization Explorer (PIPER)

The Primordial Inflation Polarization Explorer (PIPER) is a balloon-borne cosmic microwave background (CMB) polarimeter designed to search for evidence of inflation by measuring the large-angular scale CMB polarization signal. BICEP2 recently reported a detection of B-mode power corresponding to the tensor-to-scalar ratio r = 0.2 on ~2 degree scales. If the BICEP2 signal is caused by inflationary gravitational waves (IGWs), then there should be a corresponding increase in B-mode power on angular scales larger than 18 degrees. PIPER is currently the only suborbital instrument capable of fully testing and extending the BICEP2 results by measuring the B-mode power spectrum on angular scales $\theta$ = ~0.6 deg to 90 deg, covering both the reionization bump and recombination peak, with sensitivity to measure the tensor-to-scalar ratio down to r = 0.007, and four frequency bands to distinguish foregrounds. PIPER will accomplish this by mapping 85% of the sky in four frequency bands (200, 270, 350, 600 GHz) over a series of 8 conventional balloon flights from the northern and southern hemispheres. The instrument has background-limited sensitivity provided by fully cryogenic (1.5 K) optics focusing the sky signal onto four 32x40-pixel arrays of time-domain multiplexed Transition-Edge Sensor (TES) bolometers held at 140 mK. Polarization sensitivity and systematic control are provided by front-end Variable-delay Polarization Modulators (VPMs), which rapidly modulate only the polarized sky signal at 3 Hz and allow PIPER to instantaneously measure the full Stokes vector (I, Q, U, V) for each pointing. We describe the PIPER instrument and progress towards its first flight.Comment: 11 pages, 7 figures. To be published in Proceedings of SPIE Volume 9153. Presented at SPIE Astronomical Telescopes + Instrumentation 2014, conference 915

Malaria surveillance from both ends: concurrent detection of Plasmodium falciparum in saliva and excreta harvested from Anopheles mosquitoes

Background: Malaria is the most important vector-borne disease in the world. Epidemiological and ecological studies of malaria traditionally utilize detection of Plasmodium sporozoites in whole mosquitoes or salivary glands by microscopy or serological or molecular assays. However, these methods are labor-intensive, and can over- or underestimate mosquito transmission potential. To overcome these limitations, alternative sample types have been evaluated for the study of malaria. It was recently shown that Plasmodium could be detected in saliva expectorated on honey-soaked cards by Anopheles stephensi, providing a better estimate of transmission risk. We evaluated whether excretion of Plasmodium falciparum nucleic acid by An. stephensi correlates with expectoration of parasites in saliva, thus providing an additional sample type for estimating transmission potential. Mosquitoes were exposed to infectious blood meals containing cultured gametocytes, and excreta collected at different time points post-exposure. Saliva was collected on honey-soaked filter paper cards, and salivary glands were dissected and examined microscopically for sporozoites. Excreta and saliva samples were tested by real time polymerase chain reaction (RT-rtPCR). Results: Plasmodium falciparum RNA was detected in mosquito excreta as early as four days after ingesting a bloodmeal containing gametocytes. Once sporogony (the development of sporozoites) occurred, P. falciparum RNA was detected concurrently in both excreta and saliva samples. In the majority of cases, no difference was observed between the Ct values obtained from matched excreta and saliva samples, suggesting that both samples provide equally sensitive results. A positive association was observed between the molecular detection of the parasites in both samples and the proportion of mosquitoes with sporozoites in their salivary glands from each container. No distinguishable parasites were observed when excreta samples were stained and microscopically analyzed. Conclusions: Mosquito saliva and excreta are easily collected and are promising for surveillance of malaria-causing parasites, especially in low transmission settings or in places where arboviruses co-circulate

Occurrence and sources of radium in groundwater associated with oil fields in the southern San Joaquin Valley, California

Author Posting. © American Chemical Society, 2019. This is an open access article published under an ACS AuthorChoice License. The definitive version was published in Environmental Science and Technology 53(16), (2019): 9398-9406, doi:10.1021/acs.est.9b02395.Geochemical data from 40 water wells were used to examine the occurrence and sources of radium (Ra) in groundwater associated with three oil fields in California (Fruitvale, Lost Hills, South Belridge). 226Ra+228Ra activities (range = 0.010–0.51 Bq/L) exceeded the 0.185 Bq/L drinking-water standard in 18% of the wells (not drinking-water wells). Radium activities were correlated with TDS concentrations (p < 0.001, ρ = 0.90, range = 145–15,900 mg/L), Mn + Fe concentrations (p < 0.001, ρ = 0.82, range = <0.005–18.5 mg/L), and pH (p < 0.001, ρ = −0.67, range = 6.2–9.2), indicating Ra in groundwater was influenced by salinity, redox, and pH. Ra-rich groundwater was mixed with up to 45% oil-field water at some locations, primarily infiltrating through unlined disposal ponds, based on Cl, Li, noble-gas, and other data. Yet 228Ra/226Ra ratios in pond-impacted groundwater (median = 3.1) differed from those in oil-field water (median = 0.51). PHREEQC mixing calculations and spatial geochemical variations suggest that the Ra in the oil-field water was removed by coprecipitation with secondary barite and adsorption on Mn–Fe precipitates in the near-pond environment. The saline, organic-rich oil-field water subsequently mobilized Ra from downgradient aquifer sediments via Ra-desorption and Mn/Fe-reduction processes. This study demonstrates that infiltration of oil-field water may leach Ra into groundwater by changing salinity and redox conditions in the subsurface rather than by mixing with a high-Ra source.This article was improved by the reviews of John Izbicki and anonymous reviewers for the journal. This work was funded by the California State Water Resources Control Board’s Regional Groundwater Monitoring in Areas of Oil and Gas Production Program and the USGS Cooperative Water Program. A.V., A.J.K., and Z.W were supported by USDA-NIFA grant (#2017-68007-26308). Any use of trade, firm, or product names is for description purposes only and does not imply endorsement by the U.S. Government

Simulation Intelligence: Towards a New Generation of Scientific Methods

The original "Seven Motifs" set forth a roadmap of essential methods for the field of scientific computing, where a motif is an algorithmic method that captures a pattern of computation and data movement. We present the "Nine Motifs of Simulation Intelligence", a roadmap for the development and integration of the essential algorithms necessary for a merger of scientific computing, scientific simulation, and artificial intelligence. We call this merger simulation intelligence (SI), for short. We argue the motifs of simulation intelligence are interconnected and interdependent, much like the components within the layers of an operating system. Using this metaphor, we explore the nature of each layer of the simulation intelligence operating system stack (SI-stack) and the motifs therein: (1) Multi-physics and multi-scale modeling; (2) Surrogate modeling and emulation; (3) Simulation-based inference; (4) Causal modeling and inference; (5) Agent-based modeling; (6) Probabilistic programming; (7) Differentiable programming; (8) Open-ended optimization; (9) Machine programming. We believe coordinated efforts between motifs offers immense opportunity to accelerate scientific discovery, from solving inverse problems in synthetic biology and climate science, to directing nuclear energy experiments and predicting emergent behavior in socioeconomic settings. We elaborate on each layer of the SI-stack, detailing the state-of-art methods, presenting examples to highlight challenges and opportunities, and advocating for specific ways to advance the motifs and the synergies from their combinations. Advancing and integrating these technologies can enable a robust and efficient hypothesis-simulation-analysis type of scientific method, which we introduce with several use-cases for human-machine teaming and automated science