Infodemiology of Influenza-like Illness: Utilizing Google Trends' Big Data for Epidemic Surveillance.

Background: Influenza-like illness (ILI) encompasses symptoms similar to influenza, affecting population health. Surveillance, including Google Trends (GT), offers insights into epidemic patterns. Methods: This study used multiple regression models to analyze the correlation between ILI incidents, GT keyword searches, and climate variables during influenza outbreaks. It compared the predictive capabilities of time-series and deep learning models against ILI emergency incidents. Results: The GT searches for "fever" and "cough" were significantly associated with ILI cases (p < 0.05). Temperature had a more substantial impact on ILI incidence than humidity. Among the tested models, ARIMA provided the best predictive power. Conclusions: GT and climate data can forecast ILI trends, aiding governmental decision making. Temperature is a crucial predictor, and ARIMA models excel in forecasting ILI incidences.

Mutational analysis of epidermolysis bullosa in Taiwan by whole-exome sequencing complemented by RNA sequencing: a series of 77 patients.

BACKGROUND: Epidermolysis bullosa (EB) is a heterogeneous group of hereditary skin diseases characterized by skin fragility. Primary data on Taiwanese population remain scarce. METHODS: We gathered clinical information from EB patients at National Cheng Kung University Hospital from January, 2012, to June, 2021. Diagnostic tests including transmission electron microscopy, immunofluorescence studies, and whole-exome sequencing (WES) were performed. The pathogenicity of novel splice-site mutations was determined through reverse transcriptase-PCR of skin mRNA followed by Sanger and/or RNA sequencing. RESULTS: Seventy-seven EB patients from 45 families were included: 19 EB simplex, six junctional EB, and 52 dystrophic EB. Pathogenic variants were identified in 37 of 38 families (97.4%), in which WES was used as a first-line tool for mutational analysis; RNA sequencing determined pathogenic variants in the remaining one family. A total of 60 mutations in EB-related genes were identified, including 22 novel mutations. The mutations involved KRT5, KRT14, PLEC, COL17A1, LAMB3, LAMA3, ITGB4, and COL7A1. Over one-quarter of DEB patients had EB pruriginosa. CONCLUSIONS: The distinct clinical presentation and molecular pathology of EB in Taiwan expand our understanding of this disorder. WES was an effective first-line diagnostic tool for identifying EB-associated variants. RNA sequencing complemented WES when multiple potentially pathogenic splice-site mutations were found.

Continuous lipid extraction of microalgae using high-pressure carbon dioxide.

Sequestering carbon, purifying water, and creating biofuel materials using microalgae are of global interest in the R&D field. However, extracting algal oil consumes a high amount of energy, which is an obstacle for the biofuel market. Nontoxic and recyclable high-pressure CO2 extraction processes are being developed by numerous researchers; however, most of these processes use batch operations mixed with a large amount of co-solvent and require improvement. We fabricated a continuous high-pressure CO2 extraction system, evaluating the optimal parameters for the extraction process. The various parameter tests included temperature, pressure, pretreatment methods, ratio, and the species of co-solvent. We integrated the optimal parameters from previous tests, using a 5-d continuous operation. Compared with traditional solvent extraction, a 90.56% extraction yield ratio was achieved using this continuous extraction method. This shows the stable, high extraction yields of this continuous high-pressure CO2 extraction system.