A compact microfluidic platform for rapid multiplex detection of respiratory viruses via centrifugal polar-absorbance spectroscopy.

Nucleic acid detection technology has become a crucial tool in cutting-edge research within the life sciences and clinical diagnosis domains. Its significance is particularly highlighted during the respiratory virus pandemic, where nucleic acid testing plays a pivotal role in accurately detecting the virus. Isothermal amplification technologies have been developed and offer advantages such as rapidity, mild reaction conditions and excellent stability.

Rapid and multi-target genotyping of Helicobacter pylori with digital microfluidics.

Helicobacter pylori (H. pylori) infection correlates closely with gastric diseases such as gastritis, ulcers, and cancer, influencing more than half of the world's population. Establishing a rapid, precise, and automated platform for H.

Discrepancies in breast cancer guideline recommendations despite similar Cochrane systematic review conclusions.

Aim: This study aims to describe the citation patterns of Cochrane systematic reviews (CSR) in guidelines for managing breast cancer.

Methods: We searched for systematic reviews on breast cancer in The Cochrane Library from the date of inception to November 15, 2023, and identified guidelines that cited them. We described how systematic reviews were cited by the guidelines in each database and each year.

[Ferroptosis inducer IKE ameliorate pulmonary fibrosis in collagen-induced arthritis (CIA) mice via decreasing the expression of IL-6, CCL5 and CXCL9].

Objective To investigate the impact of imidazole ketone erastin (IKE), a ferroptosis inducer, on pulmonary fibrosis progression in mice with collagen-induced arthritis (CIA), and to understand its potential mechanism. Methods Chick type II collagen emulsified in complete Freund's adjuvant (CFA) was injected into DBA/1 mice, aged 8 to 10 weeks, to induce CIA. Fourteen days later, type II collagen emulsified in incomplete Freund's adjuvant (IFA) was administered to the mice.

iPiDA-SWGCN: Identification of piRNA-disease associations based on Supplementarily Weighted Graph Convolutional Network.

Accurately identifying potential piRNA-disease associations is of great importance in uncovering the pathogenesis of diseases. Recently, several machine-learning-based methods have been proposed for piRNA-disease association detection. However, they are suffering from the high sparsity of piRNA-disease association network and the Boolean representation of piRNA-disease associations ignoring the confidence coefficients.

iPiDA-GCN: Identification of piRNA-disease associations based on Graph Convolutional Network.

Motivation: Piwi-interacting RNAs (piRNAs) play a critical role in the progression of various diseases. Accurately identifying the associations between piRNAs and diseases is important for diagnosing and prognosticating diseases. Although some computational methods have been proposed to detect piRNA-disease associations, it is challenging for these methods to effectively capture nonlinear and complex relationships between piRNAs and diseases because of the limited training data and insufficient association representation.

iPiDA-LTR: Identifying piwi-interacting RNA-disease associations based on Learning to Rank.

Piwi-interacting RNAs (piRNAs) are regarded as drug targets and biomarkers for the diagnosis and therapy of diseases. However, biological experiments cost substantial time and resources, and the existing computational methods only focus on identifying missing associations between known piRNAs and diseases. With the fast development of biological experiments, more and more piRNAs are detected.