Microplastic Diversity as a Potential Driver of Soil Denitrification Shifts.

Microplastics (MPs) are raising significant global concerns due to their environmental impacts. While most studies have focused on the effects of individual MP types, MPs in natural environments typically coexist as multiple types, and their combined effects remain poorly understood. In this study, we conducted a microcosm experiment with four levels of MP diversity (0, 1, 3, and 5 types) to investigate the effects of MP diversity on soil ecosystem functions using metagenomic sequencing.

Unique plastisphere viromes with habitat-dependent potential for modulating global methane cycle.

Plastispheres, novel niches in the Anthropocene, harbor microbial communities with unique functional signatures. As the most abundant biological entity on Earth, viruses are key regulators of microbial community composition and metabolism. However, little is known about viral communities and their functions in the plastisphere.

Increasing pesticide diversity impairs soil microbial functions.

Pesticide application is essential for stabilizing agricultural production. However, the effects of increasing pesticide diversity on soil microbial functions remain unclear, particularly under varying nitrogen (N) fertilizer management practices. In this study, we investigated the stochasticity of soil microbes and multitrophic networks through amplicon sequencing, assessed soil community functions related to carbon (C), N, phosphorus (P), and sulfur (S) cycling, and characterized the dominant bacterial life history strategies via metagenomics along a gradient of increasing pesticide diversity under two N addition levels.

Selective enrichment of virulence factor genes in the plastisphere under antibiotic and heavy metal pressures.

The growing accumulation of plastic waste in the environment has created novel habitats known as the "plastisphere", where microorganisms can thrive. Concerns are rising about the potential for pathogenic microorganisms to proliferate in the plastisphere, posing risks to human health. However, our knowledge regarding the virulence and pathogenic potential of these microorganisms in the plastisphere remains limited.

Effects of heavy metal and disinfectant on antibiotic resistance genes and virulence factor genes in the plastisphere from diverse soil ecosystems.

Antibiotic-resistance genes (ARGs) are world-wide contaminants posing potential health risks. Quaternary ammonium compounds (QACs) and heavy metals can apply selective pressure on antibiotic resistance. However, there is a lack of evidence regarding their coupled effect on changes in ARGs and virulence factor genes (VFGs) in various soil types and their plastispheres.

Evolutionary extreme learning machine with sparse cost matrix for imbalanced learning.

Extreme learning machine is a popular machine learning technique for single hidden layer feed-forward neural network. However, due to the assumption of equal misclassification cost, the conventional extreme learning machine fails to properly learn the characteristics of the data with skewed category distribution. In this paper, to enhance the representation of few-shot cases, we break down that assumption by assigning penalty factors to different classes, and minimizing the cumulative classification cost.

Effects of TLR-2/NF-κB signaling pathway on the occurrence of degenerative knee osteoarthritis: an in vivo and in vitro study.

The study aims to explore the effects of TLR-2/NF-κB signaling pathway on the occurrence of degenerative knee osteoarthritis (OA). Degenerative knee OA and normal cartilage samples were collected from patients with degenerative knee OA receiving total knee arthroplasty and amputation. Expressions of TLR-2, NF-κB and MMP-13 were determined by qRT-PCR and immunochemistry.