Cereal-legume intercropping stimulates straw decomposition and promotes soil organic carbon stability.

Increasing carbon (C) sequestration and stability in agricultural soils is a key strategy to mitigate climate change towards C neutrality. Crop diversification is an initiative to increase C sequestration in fields, but it is unclear how legume-based crop diversification impacts the functional components of soil organic carbon (SOC) in dryland, including the formation and transformation of particulate organic carbon (POC) and mineral-associated organic carbon (MAOC). We investigated the decomposition of straw residues, the fate of photosynthesized C, as well as the formation of MAOC and POC fractions using an in situC labeling technique in the soybean-wheat intercropping, soybean-maize intercropping and their respective monocropping systems, with and without cover crops.

Enhanced fibrotic potential of COL1A1NR4A1 fibroblasts in ischemic heart revealed by transcriptional dynamics heterogeneity analysis at both bulk and single-cell levels.

Background: Fibroblasts in the fibrotic heart exhibit a heterogeneous biological behavior. The specific subsets of fibroblasts that contribute to progressive cardiac fibrosis remain unrevealed. Our aim is to identify the heart fibroblast (FB) subsets that most significantly promote fibrosis and the related critical genes as biomarkers for ischemic heart disease.

Chronic implantable flexible serpentine probe reveals impaired spatial coding of place cells in epilepsy.

The development of minimally invasive and reliable electrode probes for neural signal recording is crucial for advancing neuroscience and treating major brain disorders. Flexible neural probes offer superior long-term recording capabilities over traditional rigid probes. This study introduces a parylene-based serpentine electrode probe for stable, long-term neural monitoring.

Explicit relation between thin film chromatography and column chromatography conditions from statistics and machine learning.

In chemistry, empirical paradigms prevail, especially within the realm of chromatography, where the selection of separation conditions frequently relies on the chemist's experience. However, the underlying rationale for such experiential knowledge has not been established or analysed. This study explicitly elucidates how chemists use thin-layer chromatography (TLC) to determine column chromatography (CC) conditions, employing statistical analysis and machine learning techniques.

Locally repulsive coupling-induced tunable oscillations.

The precise amplitude and period of neuronal oscillations are crucial for the functioning of neuronal networks. We propose a chain model featuring a repulsive coupling at the first node, followed by attractive couplings at subsequent nodes. This model allows for the simultaneous regulation of both quantities.