RESUMEN
In this study, we utilized ontology and machine learning methods to analyze the current results on vaccine adverse events. With the VAERS (Vaccine Adverse Event Reporting System) Database, the side effects of COVID-19 vaccines are summarized, and a relational/graph database was implemented for further applications and analysis. The adverse effects of COVID-19 vaccines up to March 2022 were utilized in the study. With the built network of the adverse effects of COVID-19 vaccines, the API can help provide a visualized interface for patients, healthcare providers and healthcare officers to quickly find the information of a certain patient and the potential relationships of side effects of a certain vaccine. In the meantime, the model was further applied to predict the key feature symptoms that contribute to hospitalization and treatment following receipt of a COVID-19 vaccine and the performance was evaluated with a confusion matrix method. Overall, our study built a user-friendly visualized interface of the side effects of vaccines and provided insight on potential adverse effects with ontology and machine learning approaches. The interface and methods can be expanded to all FDA (Food and Drug Administration)-approved vaccines.
RESUMEN
All-inorganic CsPbX3 (X = Cl, Br, I) perovskite quantum dots (QDs) have become a kind of optoelectronic material with huge application prospects due to their excellent physical and optical properties. However, their poor structural stability to the external environment, especially polar solvents, seriously hinder further development in practical applications. Considering whether polar solvents have the same effects on perovskites QDs, few studies have been investigated in this area presently. In order to find out the effect of different polar solvents on all-inorganic perovskite QDs, in this work, we select 12 kinds of polar solvents of methanol, ethanol, isopropanol, 1-butanol, 1-pentanol, 1-octanol, N,N-dimethylformamide (DMF), tetramethylethylenediamine (TMEDA), ethyl acetate, n-butyl acetate, dibutyl phthalate and acetone for a specific analysis. The characterization of their morphology, optical and physicochemical properties shows that different polar solvents have different effects on all-inorganic perovskite QDs, but their effects are regular. Polar solvents act on the ligands preferentially, and the effects can be divided into: reducing the concentration of ligands; substituting ligands partially; completely destroying the surface ligands; polar solvents with the same functional group, as the polarity of the solvent increases, the impact on all-inorganic perovskite QDs is greater. We believe that this discovery has important implications for improving the stability of all-inorganic perovskite QDs.
RESUMEN
Nonhepatic delivery of small interfering RNAs (siRNAs) remains a challenge for development of RNA interference-based therapeutics. We report a noncationic vector wherein linear poly(ethylene glycol) (PEG), a polymer generally considered as inert and safe biologically but ineffective as a vector, is transformed into a bottlebrush architecture. This topology provides covalently embedded siRNA with augmented nuclease stability and cellular uptake. Consisting almost entirely of PEG and siRNA, the conjugates exhibit a ~25-fold increase in blood elimination half-life and a ~19-fold increase in the area under the curve compared with unmodified siRNA. The improved pharmacokinetics results in greater tumor uptake and diminished liver capture. Despite the structural simplicity these conjugates efficiently knock down target genes in vivo without apparent toxic and immunogenic reactions. Given the benign biological nature of PEG and its widespread precedence in biopharmaceuticals, we anticipate the brush polymer-based technology to have a significant impact on siRNA therapeutics.