Social Media, Celebrity Endorsers and Effect on Purchasing Intentions of Young Adults

Through an online survey methodology, this study explored how the relationship between the three celebrity-based characteristics -- trustworthiness, attractiveness and expertise -- and Millennials\u27 social media usage influences Millennials\u27 purchasing intentions, or their likelihood to buy the product or brand being endorsed. Millennials were the focus of this study due to their involvement with social media, their pre-existing parasocial interactions with celebrities on social media and their increased likelihood of buying products endorsed by celebrities with the hope of being more like them.;The most significant finding revealed that the three celebrity-based characteristics -- expertise, trustworthiness and attractiveness -- are perceived differently by Millennials when compared to past research. Results showed that the respondents viewed the characteristics as one combined variable due to high correlations between the three. Millennial participants may have been affected by the halo effect and the cognitive consistency theory, which both work together to explain that Millennials who view celebrities as nice or positive will rate the rest of their characteristics positively. If a Millennial views the celebrity as negative, their characteristics will be rated negatively. Furthermore, the results indicated that Millennials\u27 social media usage has more of an impact on Millennials\u27 purchasing intentions, meaning that Millennials\u27 who have higher levels of social media use are more likely to purchase from the brand or buy the product being endorsed.;These findings highlight the differing perceptions of Millennials in regard the celebrity characteristic. Furthermore, the findings also show how Millennials\u27 social media use affects their purchasing intentions. With this change in perceptions, this study can help expand the knowledge and practices of brands and companies choosing celebrities to endorse their brand

Global control of host antiviral responses by rotavirus NSP1

Rotaviruses are a leading cause of severe, life-threatening diarrhea worldwide, primarily in infants and young children. Interferon induction is a key protective host defense mechanism triggered during viral infection, and to combat this response, rotaviruses encode the primary interferon antagonist non-structural protein 1 (NSP1). Expression of NSP1 proteins from diverse rotavirus strains is associated with a decrease in interferon induction, and depending on host species and virus strain, may achieve this result by facilitating the degradation of various host signaling proteins. Most human and porcine strains, including the rotavirus strain OSU, encode an NSP1 capable of facilitating the degradation of β-TrCP, a key regulator of NF-κB-mediated interferon induction. β-TrCP acts as a substrate adaptor protein of cellular E3 ubiquitin ligases, and by directing degradation of IκB (inhibitor of kappa B), allows NF-κB to translocate to the nucleus to induce interferon responses. β-TrCP recognizes and binds a phosphorylated degron (phosphodegron) motif (DSGϕxS) within IκB, and other cellular proteins, to facilitate degradation. The C-terminus of OSU NSP1 harbors a mimic of this motif (DSGIS) that allows for binding and sequestration of β-TrCP. In our studies, we have found that like IκB, NSP1 is phosphorylated and requires phosphorylation for β-TrCP engagement. Unlike IκB, NSP1 is a substrate of casein kinase II (CKII). NSP1 is a substrate adaptor protein of cullin-RING ligases (CRLs), and while NSP1 appears to engage cullin 3 via an N-terminal RING domain, C-terminal degron phosphorylation is required for NSP1 incorporation into CRLs. Interestingly, NSP1 proteins that engage interferon response factor (IRF) proteins are able to engage these substrates without phosphorylation. These data suggest that NSP1 proteins may inhibit interferon induction through binding and sequestration alone, without the specific need for degradation of substrates. Furthermore, many viruses are known to encode proteins that directly engage and direct β-TrCP activity. β-TrCP regulates stability of proteins involved in a number of pathways beyond simply interferon induction, including mTOR. Our studies indicate that OSU infection results in accumulation of DEPTOR, a β-TrCP substrate and negative regulator of mTOR complexes. Analysis of mTOR signaling cascades suggests that control of β-TrCP may result in a pro-viral cellular environment with benefits to viruses beyond promoting rotavirus replication

Mitigating Molecular Aggregation in Drug Discovery with Predictive Insights from Explainable AI

As the importance of high-throughput screening (HTS) continues to grow due to its value in early stage drug discovery and data generation for training machine learning models, there is a growing need for robust methods for pre-screening compounds to identify and prevent false-positive hits. Small, colloidally aggregating molecules are one of the primary sources of false-positive hits in high-throughput screens, making them an ideal candidate to target for removal from libraries using predictive pre-screening tools. However, a lack of understanding of the causes of molecular aggregation introduces difficulty in the development of predictive tools for detecting aggregating molecules. Herein, we present an examination of the molecular features differentiating datasets of aggregating and non-aggregating molecules, as well as a machine learning approach to predicting molecular aggregation. Our method uses explainable graph neural networks and counterfactuals to reliably predict and explain aggregation, giving additional insights and design rules for future screening. The integration of this method in HTS approaches will help combat false positives, providing better lead molecules more rapidly and thus accelerating drug discovery cycles.Comment: 17 pages, plus S

Correleation of the SAGE III on ISS Thermal Models in Thermal Desktop

The Stratospheric Aerosol and Gas Experiment III (SAGE III) instrument is the fifth in a series of instruments developed for monitoring aerosols and gaseous constituents in the stratosphere and troposphere. SAGE III was launched on February 19, 2017 and mounted to the International Space Station (ISS) to begin its three-year mission. A detailed thermal model of the SAGE III payload, which consists of multiple subsystems, has been developed in Thermal Desktop (TD). Correlation of the thermal model is important since the payload will be expected to survive a three-year mission on ISS under varying thermal environments. Three major thermal vacuum (TVAC) tests were completed during the development of the SAGE III Instrument Payload (IP); two subsystem-level tests and a payload-level test. Additionally, a characterization TVAC test was performed in order to verify performance of a system of heater plates that was designed to allow the IP to achieve the required temperatures during payload-level testing; model correlation was performed for this test configuration as well as those including the SAGE III flight hardware. This document presents the methods that were used to correlate the SAGE III models to TVAC at the subsystem and IP level, including the approach for modeling the parts of the payload in the thermal chamber, generating pre-test predictions, and making adjustments to the model to align predictions with temperatures observed during testing. Model correlation quality will be presented and discussed, and lessons learned during the correlation process will be shared

Thermal Modeling Method Improvements for SAGE III on ISS

The Stratospheric Aerosol and Gas Experiment III (SAGE III) instrument is the fifth in a series of instruments developed for monitoring aerosols and gaseous constituents in the stratosphere and troposphere. SAGE III will be delivered to the International Space Station (ISS) via the SpaceX Dragon vehicle. A detailed thermal model of the SAGE III payload, which consists of multiple subsystems, has been developed in Thermal Desktop (TD). Many innovative analysis methods have been used in developing this model; these will be described in the paper. This paper builds on a paper presented at TFAWS 2013, which described some of the initial developments of efficient methods for SAGE III. The current paper describes additional improvements that have been made since that time. To expedite the correlation of the model to thermal vacuum (TVAC) testing, the chambers and GSE for both TVAC chambers at Langley used to test the payload were incorporated within the thermal model. This allowed the runs of TVAC predictions and correlations to be run within the flight model, thus eliminating the need for separate models for TVAC. In one TVAC test, radiant lamps were used which necessitated shooting rays from the lamps, and running in both solar and IR wavebands. A new Dragon model was incorporated which entailed a change in orientation; that change was made using an assembly, so that any potential additional new Dragon orbits could be added in the future without modification of the model. The Earth orbit parameters such as albedo and Earth infrared flux were incorporated as time-varying values that change over the course of the orbit; despite being required in one of the ISS documents, this had not been done before by any previous payload. All parameters such as initial temperature, heater voltage, and location of the payload are defined based on the case definition. For one component, testing was performed in both air and vacuum; incorporating the air convection in a submodel that was only built for the in-air cases allowed correlation of all testing to be done in a single model. These modeling improvements and more will be described and illustrated in the paper

Hyperprolactinemia Secondary to Paliperidone: Considerations for Women of Childbearing Age

CASE DESCRIPTION: A 27 year old female with past medical history significant for schizoaffective disorder, borderline personality disorder, major depressive disorder, and catatonia was admitted following a suicide attempt. During her admission, she revealed that she has had a persistent delusion of believing she was pregnant despite not being sexually active in several months and having multiple negative pregnancy tests. After the patient was started on paliperidone, she stopped menstruating, further perpetuating this delusion. The patient also expressed concerns for infertility in the future. CONCLUSION: Paliperidone has a high incidence of hyperprolactinemia which can lead to reproductive concerns including menstrual irregularity and infertility. These side-effects highlight the critical need for shared decision making in discussions about fertility in patients with psychotic disorders. Further complicating this issue is the significant increase in psychosis risk during the perinatal period. There are other alternatives that exist and may be better options for some patients but changing medications to oral options should be balanced with medication adherence needs. CLINICAL SIGNIFICANCE: Through shared decision-making, the selection of antipsychotic maintenance therapy should consider a variety of patient and physician goals. A younger age of initial psychotic break has strong indications for reproductive counseling, which should remain consistent with patients’ goals and be reassessed as goals evolve throughout their lifetime. Patients who struggle with medication adherence may benefit from long acting injectable antipsychotic medications. However, some of these injections, like paliperidone, can cause hyperprolactinemia and contribute to infertility. Prolactin levels can be monitored and lowering medication doses can be effective for mitigating hyperprolactinemia. There are oral medications available that have a lower chance of causing hyperprolactinemia. However, oral only medication options must be balanced with patient medication adherence concerns

Development and Implementation of Efficiency-Improving Analysis Methods for the SAGE III on ISS Thermal Model Originating

The Stratospheric Aerosol and Gas Experiment III (SAGE III) instrument is the fifth in a series of instruments developed for monitoring aerosols and gaseous constituents in the stratosphere and troposphere. SAGE III will be delivered to the International Space Station (ISS) via the SpaceX Dragon vehicle in 2015. A detailed thermal model of the SAGE III payload has been developed in Thermal Desktop (TD). Several novel methods have been implemented to facilitate efficient payload-level thermal analysis, including the use of a design of experiments (DOE) methodology to determine the worst-case orbits for SAGE III while on ISS, use of TD assemblies to move payloads from the Dragon trunk to the Enhanced Operational Transfer Platform (EOTP) to its final home on the Expedite the Processing of Experiments to Space Station (ExPRESS) Logistics Carrier (ELC)-4, incorporation of older models in varying unit sets, ability to change units easily (including hardcoded logic blocks), case-based logic to facilitate activating heaters and active elements for varying scenarios within a single model, incorporation of several coordinate frames to easily map to structural models with differing geometries and locations, and streamlined results processing using an Excel-based text file plotter developed in-house at LaRC. This document presents an overview of the SAGE III thermal model and describes the development and implementation of these efficiency-improving analysis methods

Eristalis flower flies can be mechanical vectors of the common trypanosome bee parasite, Crithidia bombi

Flowers can be transmission platforms for parasites that impact bee health, yet bees share floral resources with other pollinator taxa, such as flies, that may be hosts or non-host vectors (i.e., mechanical vectors) of parasites. Here, we assessed whether the fecal-orally transmitted gut parasite of bees, Crithidia bombi, can infect Eristalis tenax flower flies. We also investigated the potential for two confirmed solitary bee hosts of C. bombi, Osmia lignaria and Megachile rotundata, as well as two flower fly species, Eristalis arbustorum and E. tenax, to transmit the parasite at flowers. We found that C. bombi did not replicate (i.e., cause an active infection) in E. tenax flies. However, 93% of inoculated flies defecated live C. bombi in their first fecal event, and all contaminated fecal events contained C. bombi at concentrations sufficient to infect bumble bees. Flies and bees defecated inside the corolla (flower) more frequently than other plant locations, and flies defecated at volumes comparable to or greater than bees. Our results demonstrate that Eristalis flower flies are not hosts of C. bombi, but they may be mechanical vectors of this parasite at flowers. Thus, flower flies may amplify or dilute C. bombi in bee communities, though current theoretical work suggests that unless present in large populations, the effects of mechanical vectors will be smaller than hosts