Utilizing a Flipped Learning Model to Support Special Educators’ Mathematical Knowledge for Teaching

Flipped learning is a popular pedagogical approach in K-12 and in higher education (Graziano, 2017), however minimal research exists on the effectiveness of flipped learning in special education teacher preparation courses. Special education teacher candidates enrolled in five sections of a special education math methods course engaged with interactive, flipped “learning lessons” prior to class. During class, they participated in extension activities and lesson planning. The researchers utilized mixed methods to evaluate the impact of performance on and engagement with these learning lessons and found positive predictive relationships with student achievement on all individual summative assignments. Nearly all students agreed flipped learning was useful in helping them meet the course outcomes. Most students specifically credited the flipped lessons as a facilitator of their learning because they allowed them to interact with the content at their own pace and to utilize class time for more meaningful review and extension activities with the instructor\u27s support

Fine-tuned Sentiment Analysis of COVID-19 Vaccine-Related Social Media Data: Comparative Study

This study investigated and compared public sentiment related to COVID-19 vaccines expressed on two popular social media platforms, Reddit and Twitter, harvested from January 1, 2020, to March 1, 2022. To accomplish this task, we created a fine-tuned DistilRoBERTa model to predict sentiments of approximately 9.5 million Tweets and 70 thousand Reddit comments. To fine-tune our model, our team manually labeled the sentiment of 3600 Tweets and then augmented our dataset by the method of back-translation. Text sentiment for each social media platform was then classified with our fine-tuned model using Python and the Huggingface sentiment analysis pipeline. Our results determined that the average sentiment expressed on Twitter was more negative (52% positive) than positive and the sentiment expressed on Reddit was more positive than negative (53% positive). Though average sentiment was found to vary between these social media platforms, both displayed similar behavior related to sentiment shared at key vaccine-related developments during the pandemic. Considering this similar trend in shared sentiment demonstrated across social media platforms, Twitter and Reddit continue to be valuable data sources that public health officials can utilize to strengthen vaccine confidence and combat misinformation. As the spread of misinformation poses a range of psychological and psychosocial risks (anxiety, fear, etc.), there is an urgency in understanding the public perspective and attitude toward shared falsities. Comprehensive educational delivery systems tailored to the population's expressed sentiments that facilitate digital literacy, health information-seeking behavior, and precision health promotion could aid in clarifying such misinformation.Comment: 11 Pages, 5 Figures, and 1 Tabl

Emerging Role of miR-345 and Its Effective Delivery as a Potential Therapeutic Candidate in Pancreatic Cancer and Other Cancers

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with high mortality, poor prognosis, and palliative treatments, due to the rapid upregulation of alternative compensatory pathways and desmoplastic reaction. miRNAs, small non-coding RNAs, have been recently identified as key players regulating cancer pathogenesis. Dysregulated miRNAs are associated with molecular pathways involved in tumor development, metastasis, and chemoresistance in PDAC, as well as other cancers. Targeted treatment strategies that alter miRNA levels in cancers have promising potential as therapeutic interventions. miRNA-345 (miR-345) plays a critical role in tumor suppression and is differentially expressed in various cancers, including pancreatic cancer (PC). The underlying mechanism(s) and delivery strategies of miR-345 have been investigated by us previously. Here, we summarize the potential therapeutic roles of miR-345 in different cancers, with emphasis on PDAC, for miRNA drug discovery, development, status, and implications. Further, we focus on miRNA nanodelivery system(s), based on different materials and nanoformulations, specifically for the delivery of miR-345

Exploring celebrity influence on public attitude towards the COVID-19 pandemic: social media shared sentiment analysis

The COVID-19 pandemic has introduced new opportunities for health communication, including an increase in the public use of online outlets for health-related emotions. People have turned to social media networks to share sentiments related to the impacts of the COVID-19 pandemic. In this paper we examine the role of social messaging shared by Persons in the Public Eye (i.e. athletes, politicians, news personnel) in determining overall public discourse direction. We harvested approximately 13 million tweets ranging from 1 January 2020 to 1 March 2022. The sentiment was calculated for each tweet using a fine-tuned DistilRoBERTa model, which was used to compare COVID-19 vaccine-related Twitter posts (tweets) that co-occurred with mentions of People in the Public Eye. Our findings suggest the presence of consistent patterns of emotional content co-occurring with messaging shared by Persons in the Public Eye for the first two years of the COVID-19 pandemic influenced public opinion and largely stimulated online public discourse. We demonstrate that as the pandemic progressed, public sentiment shared on social networks was shaped by risk perceptions, political ideologies and health-protective behaviours shared by Persons in the Public Eye, often in a negative light.Comment: 7 Pages, 4 Figure

Determination of Molecular Structures of HIV Envelope Glycoproteins using Cryo-Electron Tomography and Automated Sub-tomogram Averaging

Since its discovery nearly 30 years ago, more than 60 million people have been infected with the human immunodeficiency virus (HIV) (www.usaid.gov). The virus infects and destroys CD4+ T-cells thereby crippling the immune system, and causing an acquired immunodeficiency syndrome (AIDS) 2. Infection begins when the HIV Envelope glycoprotein "spike" makes contact with the CD4 receptor on the surface of the CD4+ T-cell. This interaction induces a conformational change in the spike, which promotes interaction with a second cell surface co-receptor 5,9. The significance of these protein interactions in the HIV infection pathway makes them of profound importance in fundamental HIV research, and in the pursuit of an HIV vaccine

Triplet lifetime in gaseous argon

MiniCLEAN is a single-phase liquid argon dark matter experiment. During the initial cooling phase, impurities within the cold gas ($<$140 K) were monitored by measuring the scintillation light triplet lifetime, and ultimately a triplet lifetime of 3.480 $\pm$ 0.001 (stat.) $\pm$ 0.064 (sys.) $\mu$s was obtained, indicating ultra-pure argon. This is the longest argon triplet time constant ever reported. The effect of quenching of separate components of the scintillation light is also investigated

Defining Natural History: Assessment of the Ability of College Students to Aid in Characterizing Clinical Progression of Niemann-Pick Disease, Type C

Niemann-Pick Disease, type C (NPC) is a fatal, neurodegenerative, lysosomal storage disorder. It is a rare disease with broad phenotypic spectrum and variable age of onset. These issues make it difficult to develop a universally accepted clinical outcome measure to assess urgently needed therapies. To this end, clinical investigators have defined emerging, disease severity scales. The average time from initial symptom to diagnosis is approximately 4 years. Further, some patients may not travel to specialized clinical centers even after diagnosis. We were therefore interested in investigating whether appropriately trained, community-based assessment of patient records could assist in defining disease progression using clinical severity scores. In this study we evolved a secure, step wise process to show that pre-existing medical records may be correctly assessed by non-clinical practitioners trained to quantify disease progression. Sixty-four undergraduate students at the University of Notre Dame were expertly trained in clinical disease assessment and recognition of major and minor symptoms of NPC. Seven clinical records, randomly selected from a total of thirty seven used to establish a leading clinical severity scale, were correctly assessed to show expected characteristics of linear disease progression. Student assessment of two new records donated by NPC families to our study also revealed linear progression of disease, but both showed accelerated disease progression, relative to the current severity scale, especially at the later stages. Together, these data suggest that college students may be trained in assessment of patient records, and thus provide insight into the natural history of a disease

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Nucleophilicity of Neutral versus Cationic Magnesium Silyl Compounds

Charge and ancillary ligands affect the reactivity of monomeric tris(trimethylsilyl)silyl magnesium compounds. Diamine-coordinated (tmeda)Mg{Si(SiMe3)3}Me (tmeda = tetramethylethylenediamine; 2-tmeda) and (dpe)Mg{Si(SiMe3)3}Me (dpe =1,2-N,N-dipyrrolidenylethane; 2-dpe) are synthesized by salt elimination reactions of L2MgMeBr and KSi(SiMe3)3. Compounds 2-tmeda or 2-dpe react with MeI or MeOTf to give MeSi(SiMe3)3 as the product of Si–C bond formation. In contrast, 2-tmeda and 2-dpe undergo exclusively reaction at the magnesium methyl group with electrophiles such as Me3SiI, B(C6F5)3, HB(C6F5)2, and [Ph3C][B(C6F5)4]. These reactions provide a series of neutral, zwitterionic, and cationic magnesium silyl compounds, and from this series we have found that silyl group transfer is less effective with cationic magnesium compounds than neutral complexes