A novel weighted pseudo-labeling framework based on matrix factorization for adverse drug reaction prediction.

Adverse drug reactions (ADRs) are among the global public health events that seriously endanger human life and cause high economic burdens. Therefore, predicting the possibility of their occurrence and taking early and effective response measures is of great significance. Constructing a correlation matrix between drugs and their adverse reactions, followed by effective correlation data mining, is one of the current strategies to predict ADRs using accessible public data.

Plasma Circulating Cell-Free DNA Facilitated the Detection of an Alveolar Echinococcosis Patient Initially Misdiagnosed as Cystic Echinococcosis: A Case Report.

Echinococcosis, especially alveolar echinococcosis (AE), is becoming an emerging/re-emerging disease with a growing number of cases reported globally. The diagnosis of echinococcosis is based mainly on imaging, which may be challenging when the image presentation is atypical. We reported one patient with suspected cystic echinococcosis (CE) by imaging.

SubGE-DDI: A new prediction model for drug-drug interaction established through biomedical texts and drug-pairs knowledge subgraph enhancement.

Biomedical texts provide important data for investigating drug-drug interactions (DDIs) in the field of pharmacovigilance. Although researchers have attempted to investigate DDIs from biomedical texts and predict unknown DDIs, the lack of accurate manual annotations significantly hinders the performance of machine learning algorithms. In this study, a new DDI prediction framework, Subgraph Enhance model, was developed for DDI (SubGE-DDI) to improve the performance of machine learning algorithms.

Michler's ethylketone as a novel negative-ion matrix for the enhancement of lipid MALDI tissue imaging.

Michler's ethylketone (MEK, 4,4'-bis(diethylamino)benzophenone), commonly-known as an intermediate in the synthesis of dyes and pigments, was successfully screened and optimized as a novel matrix for the enhancement of lipid detection and imaging in tissues by MALDI-MSI. The results show several properties of MEK as a powerful MALDI matrix, including strong UV absorption, µm-sized crystals and uniform matrix-coating, super high vacuum chemical stability, low matrix-related ion interference, super soft ionization, and high lipid ionization efficiency.