Double-target self-supervised clustering with multi-feature fusion for medical question texts.

Background: To make the question text represent more information and construct an end-to-end text clustering model, we propose a double-target self-supervised clustering with multi-feature fusion (MF-DSC) for texts which describe questions related to the medical field. Since medical question-and-answer data are unstructured texts and characterized by short characters and irregular language use, the features extracted by a single model cannot fully characterize the text content.

Methods: Firstly, word weights were obtained based on term frequency, and word vectors were generated according to lexical semantic information.

Insight into the molecular mechanism of phosphine toxicity provided by functional analysis of cytochrome b5 fatty acid desaturase and dihydrolipoamide dehydrogenase in the red flour beetle, Tribolium castaneum.

Phosphine is the dominant chemical used in postharvest pest control. Widespread and highly frequent use of phosphine has been selected for pest insects, including Tribolium castaneum, which is highly resistant. Lipid peroxidation and reactive oxygen species (ROS) are two major factors determining phosphine toxicity; however, the mechanisms of production of these two factors in phosphine toxicity are still unknown.

Amplification refractory mutation system based real-time PCR (ARMS-qPCR) for rapid resistance characterization of Tribolium castaneum to phosphine.

Resistance of Tribolium castaneum to phosphine is related to point mutations in DNA code corresponding to amino acid changes associated with a core metabolic enzyme dihydrolipoamide dehydrogenase (DLD), but the mutation patterns vary among different resistant populations. Thus, there is a great need to develop a cost-effective method to detect core mutations in T. castaneum, which would be the key factor to understand the molecular basis of phosphine resistance.

Prenatal diagnosis of fetal congenital mesoblastic nephroma by ultrasonography combined with MR imaging: A case report and literature review.

Rationale: Fetal congenital mesoblastic nephroma (CMN) is a rare renal tumor, characterized by polyhydramnios, premature birth, and neonatal hypertension. In the prenatal stage, it is particularly difficult to diagnose CMN either by ultrasonography or magnetic resonance imaging (MRI). Thus, CMN is frequently detected in the third trimester in the clinical scenario.