LaTeX: Language Pattern-aware Triggering Event Detection for Adverse Experience during Pandemics

The COVID-19 pandemic has accentuated socioeconomic disparities across various racial and ethnic groups in the United States. While previous studies have utilized traditional survey methods like the Household Pulse Survey (HPS) to elucidate these disparities, this paper explores the role of social media platforms in both highlighting and addressing these challenges. Drawing from real-time data sourced from Twitter, we analyzed language patterns related to four major types of adverse experiences: loss of employment income (LI), food scarcity (FS), housing insecurity (HI), and unmet needs for mental health services (UM). We first formulate a sparsity optimization problem that extracts low-level language features from social media data sources. Second, we propose novel constraints on feature similarity exploiting prior knowledge about the similarity of the language patterns among the adverse experiences. The proposed problem is challenging to solve due to the non-convexity objective and non-smoothness penalties. We develop an algorithm based on the alternating direction method of multipliers (ADMM) framework to solve the proposed formulation. Extensive experiments and comparisons to other models on real-world social media and the detection of adverse experiences justify the efficacy of our model.Comment: arXiv admin note: text overlap with arXiv:1911.0868

Social media use among American Indians in South Dakota: Preferences and perceptions

Social media use data is widely being used in health, psychology, and marketing research to analyze human behavior. However, we have very limited knowledge on social media use among American Indians. In this context, this study was designed to assess preferences and perceptions of social media use among American Indians during COVID-19. We collected data from American Indians in South Dakota using online survey. Results show that Facebook, YouTube, TikTok, Instagram and Snapchat are the most preferred social media platforms. Most of the participants reported that the use of social media increased tremendously during COVID-19 and had perceptions of more negative effects than positive effects. Hate/harassment/extremism, misinformation/made up news, and people getting one point of view were the top reasons for negative effects.Comment: 20 pages, 6 figures, 2 Tables, Appendix Tables (7

Analysis of Ultra Low Genome Conservation in Clostridium difficile

Microarray-based comparative genome hybridisations (CGH) and genome sequencing of Clostridium difficile isolates have shown that the genomes of this species are highly variable. To further characterize their genome variation, we employed integration of data from CGH, genome sequencing and putative cellular pathways. Transcontinental strain comparison using CGH data confirmed the emergence of a human-specific hypervirulent cluster. However, there was no correlation between total toxin production and hypervirulent phenotype, indicating the possibility of involvement of additional factors towards hypervirulence. Calculation of C. difficile core and pan genome size using CGH and sequence data estimated that the core genome is composed of 947 to 1,033 genes and a pan genome comprised of 9,640 genes. The reconstruction, annotation and analysis of cellular pathways revealed highly conserved pathways despite large genome variation. However, few pathways such as tetrahydrofolate biosynthesis were found to be variable and could be contributing to adaptation towards virulence such as antibiotic resistance

MiR-214 promotes renal fibrosis in diabetic nephropathy via targeting SOCS1

Purpose: To elucidate how miR-214 regulates the pathogenesis of diabetic nephropathy (DN). Methods: The extent of fibrosis in DN mice kidneys was examined using Masson’s staining. Quantitative polymerase chain reaction (qPCR) was used to determine the levels of miR-214. Dual luciferase reporter assay was used to identify the target of miR-214. The expression of fibrosis marker proteins of high glucose-stimulated NRK-52E cells transfected with miR-214 was determined using western blotting. Results: Fibrosis in renal tissue of DN mice was significantly increased and miR-214 was upregulated (p < 0.001). Suppressor of cytokine signaling 1 protein (SOCS1) was the target gene of miR-214, and overexpression of miR-214 promoted fibrosis (p < 0.05, p < 0.001). On the other hand, overexpression of SOCS1 inhibited this process, indicating that miR-214 promoted fibrosis via targeting SOCS1 (p < 0.001). Finally, inhibition of miR-214 c ameliorated renal fibrosis in DN mice (p < 0.01, p < 0.001). Conclusions: MiR-214 is upregulated in db/db DN mice kidney tissue; miR-214 regulates renal fibrosis in DN mice by targeting SOCS1

Analysis of crucial molecules involved in herniated discs and degenerative disc disease

OBJECTIVES: Herniated discs and degenerative disc disease are major health problems worldwide. However, their pathogenesis remains obscure. This study aimed to explore the molecular mechanisms of these ailments and to identify underlying therapeutic targets. MATERIAL AND METHODS: Using the GSE23130 microarray datasets downloaded from the Gene Expression Omnibus database, differentially co-expressed genes and links were identified using the differentially co-expressed gene and link method with a false discovery rate ,0.25 as a significant threshold. Subsequently, the underlying molecular mechanisms of the differential co-expression of these genes were investigated using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. In addition, the transcriptional regulatory relationship was also investigated. RESULTS: Through the analysis of the gene expression profiles of different specimens from patients with these diseases, 539 differentially co-expressed genes were identified for these ailments. The ten most significant signaling pathways involving the differentially co-expressed genes were identified by enrichment analysis. Among these pathways, apoptosis and extracellular matrix-receptor interaction pathways have been reported to be related to these diseases. A total of 62 pairs of regulatory relationships between transcription factors and their target genes were identified as critical for the pathogenesis of these diseases. CONCLUSION: The results of our study will help to identify the mechanisms responsible for herniated discs and degenerative disc disease and provides a theoretical basis for further therapeutic study

Multimodal N-of-1 trials: A Novel Personalized Healthcare Design

N-of-1 trials aim to estimate treatment effects on the individual level and can be applied to personalize a wide range of physical and digital interventions in mHealth. In this study, we propose and apply a framework for multimodal N-of-1 trials in order to allow the inclusion of health outcomes assessed through images, audio or videos. We illustrate the framework in a series of N-of-1 trials that investigate the effect of acne creams on acne severity assessed through pictures. For the analysis, we compare an expert-based manual labelling approach with different deep learning-based pipelines where in a first step, we train and fine-tune convolutional neural networks (CNN) on the images. Then, we use a linear mixed model on the scores obtained in the first step in order to test the effectiveness of the treatment. The results show that the CNN-based test on the images provides a similar conclusion as tests based on manual expert ratings of the images, and identifies a treatment effect in one individual. This illustrates that multimodal N-of-1 trials can provide a powerful way to identify individual treatment effects and can enable large-scale studies of a large variety of health outcomes that can be actively and passively assessed using technological advances in order to personalized health interventions