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Soil characteristics and bacterial community characteristics of shelterbelts of different tree species in black soil region of China
Abstract To understand how surface soil characteristics and bacterial communities are affected by the establishment of farmland shelterbelts. Five types of shelterbelts in the mid-west of Heilongjiang Province China were selected for the study. The physicochemical characteristics and bacterial diversity of Populus×xiaohei monoculture (X), Larix gmelinii monoculture (L), Pinus sylvestris monoculture (Z), Pinus sylvestris and Larix gmelinii mixed forest (ZL), and Fraxinus mandshurica and Larix gmelinii mixed forest (SL), as well as in fallow land (CK), were measured and analyzed, respectively. Soil physicochemical characteristics and bacterial diversity (via high-throughput sequencing) were analyzed across 0–20 cm depths. Results showed that shelterbelts significantly altered soil characteristics: X increased moisture, ammonium nitrogen, and microbial biomass nitrogen but reduced aeration. ZL exhibited the highest bacterial richness and enhanced water-holding capacity, aeration, and nutrient retention (total organic carbon, nitrogen, phosphorus). ZL outperformed monocultures in promoting soil health, with available potassium (0–10 cm) and pH (10–20 cm) identified as key drivers of bacterial community variation. Unique genera like Krasilnikovia and Rubrobacter dominated shelterbelt soils, reflecting species-specific effects. Shelterbelts induced surface accumulation of nitrate-nitrogen, potassium, and microbial biomass carbon. Overall, Pinus sylvestris and Larix gmelinii mixed forests optimized soil structure, microbial diversity, and nutrient cycling, underscoring their ecological benefits for sustainable agroforestry. This study highlights the critical role of mixed forest shelterbelts in enhancing soil health and microbial biodiversity, which are essential for sustainable land management practices in the black soil region of China.
Study on the predictive value of preoperative CT features for the mitotic index of GIST based on the nomogram
Study on the law of stress distribution in the presence of remaining coal pillar in a close-distance coal seam and the reasonable location of the roadway
ELTIRADS framework for thyroid nodule classification integrating elastography, TIRADS, and radiomics with interpretable machine learning
Metabolomics insights into the protective molecular mechanism of Vaccinium myrtillus against oxidative stress in intestinal cells
Abstract Blueberry (Vaccinium myrtillus L.) is a rich source of secondary metabolites known for their potent antioxidant, anti-inflammatory, and cytoprotective properties. These compounds are essential in neutralizing reactive oxygen species (ROS), which are implicated in oxidative stress-related diseases. In this study, we induced oxidative stress in IEC-6 small intestine cells using hydrogen peroxide (H2O2), creating a cellular model to investigate the biochemical response. The obtained results showed that a blueberry extract (BLUBE) significantly exhibited strong antioxidant capacity, as evidenced by DPPH, FRAP and ABTS in vitro tests. Additionally, BLUBE effectively inhibited the release of reactive species in cells and enhanced cytoprotective response, as indicated by improved wound healing and clonogenic potential reduction of stress fibers rearrangement and apoptosis. Metabolomic analysis, specifically High-Resolution Mass Spectrometry (HR-MS), was employed to elucidate the metabolic alterations associated with the protective activity of BLUBE against oxidative stress in IEC-6 cells. Chemometric approaches were applied to preprocess the data, explore variability, and identify systematic biases, ensuring the removal of batch effects and other experimental artifacts. A Partial Least Squares Discriminant Analysis classification model confirmed clear group stratifications with high accuracy (98.75 ± 2.31%), sensitivity, and specificity, aiding in the identification of significant metabolites for pathway enrichment analysis. Key metabolic pathways, including sphingolipid metabolism, taurine and hypotaurine metabolism, glycerophospholipid metabolism, and cysteine and methionine metabolism, were significantly modulated, supporting the biochemical basis of BLUBE’s protective effects. In fact, BLUBE was able to partially reverse the downregulation of these pathways, effectively reducing oxidative stress and promoting cell survival. This study highlights the power of HR-MS-based metabolomics in uncovering the mechanisms of nutraceuticals and emphasizes the potential of BLUBE as a protective agent for oxidative stress-related diseases. It also underscores the growing significance of metabolomics in the food and pharmaceutical industries.
AMPK agonist AICAR ameliorates maternal hepatic lipid metabolism disorder, inflammation, and fibrosis caused by PM2.5 exposure during pregnancy
Publisher Correction: Enhancing black mulberry storage with sodium caseinate and gum tragacanth edible films
Causal analysis of PM2.5 propagation characteristics during the winters of 2015 to 2023 in Hubei Province, China
Effects of seamless care in the perioperative management of laparoscopic pancreatoduodenectomy on patients’ quality of life and postoperative complications
Attention-enhanced and integrated deep learning approach for fishing vessel classification based on multiple features
A robust deep learning approach for segmenting cortical and trabecular bone from 3D high resolution µCT scans of mouse bone
Abstract Recent advancements in deep learning have significantly enhanced the segmentation of high-resolution microcomputed tomography (µCT) bone scans. In this paper, we present the dual-branch attention-based hybrid network (DBAHNet), a deep learning architecture designed for automatically segmenting the cortical and trabecular compartments in 3D µCT scans of mouse tibiae. DBAHNet’s hierarchical structure combines transformers and convolutional neural networks to capture long-range dependencies and local features for improved contextual representation. We trained DBAHNet on a limited dataset of 3D µCT scans of mouse tibiae and evaluated its performance on a diverse dataset collected from seven different research studies. This evaluation covered variations in resolutions, ages, mouse strains, drug treatments, surgical procedures, and mechanical loading. DBAHNet demonstrated excellent performance, achieving high accuracy, particularly in challenging scenarios with significantly altered bone morphology. The model’s robustness and generalization capabilities were rigorously tested under diverse and unseen conditions, confirming its effectiveness in the automated segmentation of high-resolution µCT mouse tibia scans. Our findings highlight DBAHNet’s potential to provide reliable and accurate 3D µCT mouse tibia segmentation, thereby enhancing and accelerating preclinical bone studies in drug development. The model and code are available at https://github.com/bigfahma/DBAHNet .
Explaining trunk strength variation and improvement following resistance training in people with chronic low back pain: clinical and performance-based outcomes analysis
Abstract A multitude of variables contribute to the variation of trunk strength in individuals with chronic low back pain (CLBP). This study investigated a range of variables to determine which variables contribute most to variation in trunk isometric strength and gains in strength following resistance training in people with CLBP. Outcome measures were recorded from 20 participants with CLBP both at baseline and following resistance training. Regression analyses were applied with the average trunk maximum voluntary isometric torque as the dependent variable. Variance in baseline trunk flexion strength (R 2 = .66) was explained by demographic covariates and a measure of trunk muscle co-activation. The baseline trunk extension strength variance (R 2 = .65) was explained by demographic covariates and lumbar erector spinae (LES) activity during a maximum trunk extension contraction. Demographic variables, trunk muscle co-activation, baseline trunk flexion strength, level of physical function, and pain intensity over the past week influenced the change in trunk flexion strength after training (R 2 = .93). Demographic variables and LES muscle activity explained the variance in trunk extension strength at follow-up (R 2 = .64). This study supports the major influence of sex, physical function and baseline strength and muscle activity, on the variation in maximum trunk strength in participants with CLBP at baseline and gains in trunk muscle strength following progressive resistance training.
Immature forms of low density granulocytes are increased in acute myeloid leukemia and myelodysplastic syndromes
Acrolein exposure associated with kidney damage: a cross‑sectional study
Asymmetry in centrosome maturation revealed through AIR-1 dynamics in the early Caenorhabditis elegans embryo
Feature refinement and rethinking attention for remote sensing image captioning
Methane oxidation to ethanol by a molecular junction photocatalyst
Abstract Methane, the main component of natural and shale gas, is a significant carbon source for chemical synthesis. The direct partial oxidation of methane to liquid oxygenates under mild conditions1–3 is an attractive pathway, but the inertness of the molecule makes it challenging to achieve simultaneously high conversion and high selectivity towards a single target product. This difficulty is amplified when aiming for more valuable products that require C–C coupling4,5. Whereas selective partial methane oxidation processes1–3,6–9 have thus typically generated C1 oxygenates6,7, recent reports have documented photocatalytic methane conversion to the C2 oxygenate ethanol with low conversions but good-to-high selectivities4,5,8–12. Here we show that the intramolecular junction photocatalyst covalent triazine-based framework-1 with alternating benzene and triazine motifs13,14 drives methane coupling and oxidation to ethanol with a high selectivity and significantly improved conversion. The heterojunction architecture not only enables efficient and long-lived separation of charges after their generation, but also preferential adsorption of H2O and O2 to the triazine and benzene units, respectively. This dual-site feature separates C–C coupling to form ethane intermediates from the sites where •OH radicals are formed, thereby avoiding over-oxidation. When loaded with Pt to further boost performance, the molecular heterojunction photocatalyst generates ethanol in a packed-bed flow reactor with greatly improved conversion that results in an apparent quantum efficiency of 9.4%. We anticipate that further developing the ‘intramolecular junction’ approach will deliver efficient and selective catalysts for C–C coupling, pertaining, but not limited, to methane conversion to C2+ chemicals.