Comparative Genomics and Functional Genomics Analysis in Plants

Comparative genomics and functional genomics are two basic branches of plant genomics [...

A meta-analytic investigation of the psychometric evidence of language-based machine learning personality assessment

This paper presents a meta-analytic review of the multidimensional psychometric evidence of language-based machine learning (ML) supported personality assessment, examining the reliability and construct validity, specifically convergent and discriminant validity, of the extracted scores for the big five personality domains derived from ML natural language processing (NLP) techniques. Moreover, factors that may potentially moderate the effect size correlations between traditional personality judgment using self-reports and machine-generated judgment from NLP algorithms, such as types of language data source, types of algorithms, and types of personality scales used. This study uncovered that personality scores derived from textual data using ML and NLP approaches are only partially consistent with those from traditional personality assessment, and that much psychometric evidence is lacking in existing language-based ML personality assessment applications

AutoEdge-CCP: A novel approach for predicting cancer-associated circRNAs and drugs based on automated edge embedding.

The unique expression patterns of circRNAs linked to the advancement and prognosis of cancer underscore their considerable potential as valuable biomarkers. Repurposing existing drugs for new indications can significantly reduce the cost of cancer treatment. Computational prediction of circRNA-cancer and drug-cancer relationships is crucial for precise cancer therapy. However, prior computational methods fail to analyze the interaction between circRNAs, drugs, and cancer at the systematic level. It is essential to propose a method that uncover more valuable information for achieving cancer-centered multi-association prediction. In this paper, we present a novel computational method, AutoEdge-CCP, to unveil cancer-associated circRNAs and drugs. We abstract the complex relationships between circRNAs, drugs, and cancer into a multi-source heterogeneous network. In this network, each molecule is represented by two types information, one is the intrinsic attribute information of molecular features, and the other is the link information explicitly modeled by autoGNN, which searches information from both intra-layer and inter-layer of message passing neural network. The significant performance on multi-scenario applications and case studies establishes AutoEdge-CCP as a potent and promising association prediction tool

2H-azirines as potential bifunctional chemical linkers of cysteine residues in bioconjugate technology

2H-Azirine-2-caboxamides have been designed to perform as a new type of bifunctional thiol linker under very mild reaction conditions. The cleavage of a C-N double bond of 2H-azirine furnishes an amino amide functional group in situ through a thiol addition and ring-opening process. It works with a broad scope of thiols and 2H-azirines in the absence of any catalysts at room temperature. Cysteine-containing peptides have also been demonstrated to work efficiently in a completely water solution.We gratefully acknowledge funding from the National Natural Science Foundation of China (21971112), Jiangsu Province Funds Surface Project (BK 20161541), and the Starting Funding of Research (39837107) from Nanjing Tech Universit

Quorum Sensing Inhibitors from Marine Microorganisms and Their Synthetic Derivatives

Quorum sensing inhibitors (QSIs) present a promising alternative or potent adjuvants of conventional antibiotics for the treatment of antibiotic-resistant bacterial strains, since they could disrupt bacterial pathogenicity without imposing selective pressure involved in antibacterial treatments. This review covers a series of molecules showing quorum sensing (QS) inhibitory activity that are isolated from marine microorganisms, including bacteria, actinomycetes and fungi, and chemically synthesized based on QSIs derived from marine microorganisms. This is the first comprehensive overview of QSIs derived from marine microorganisms and their synthetic analogues with QS inhibitory activity