Grapes are considered a crucial fruit crop with extensive uses globally. Cluster compactness is an undesirable trait for the productivity of Yaghooti grape, and it reduces its desirability among consumers. The RNA-Seq data were analyzed in three stages of cluster development using the FEELnc software, leading to the identification of 849 lncRNAs. 183 lncRNAs were differentially expressed during cluster development stages. The GO and KEGG enrichment analyses of these lncRNAs revealed that they target 1,814 genes, including CKX, PG, PME, NPC2, and UGT. The analysis demonstrated a relationship between these lncRNAs and key processes such as grape growth and development, secondary metabolite synthesis, and resistance to both biotic and abiotic stresses. These findings, combined with molecular experiments on lncRNA interactions with other regulatory factors, could enhance Yaghooti grape quality and decrease cluster compactness.
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http://dx.doi.org/10.1016/j.gene.2024.149029 | DOI Listing |
Sensors (Basel)
December 2024
B-DAT and CICAEET, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Existing learning-based remote sensing change detection (RSCD) commonly uses semantic-agnostic binary masks as supervision, which hinders their ability to distinguish between different semantic types of changes, resulting in a noisy change mask prediction. To address this issue, this paper presents a Language-guided semantic clustering framework that can effectively transfer the rich semantic information from the contrastive language-image pretraining (CLIP) model for RSCD, dubbed LSC-CD. The LSC-CD considers the strong zero-shot generalization of the CLIP, which makes it easy to transfer the semantic knowledge from the CLIP into the CD model under semantic-agnostic binary mask supervision.
View Article and Find Full Text PDFMicroorganisms
December 2024
Applied Biotechnology Department, University of Technology and Applied Sciences, P.O. Box 411, Sur 411, Oman.
Determining the microbial quality and safety of meat is crucial because of its high potential to harbor pathogens. To address the critical knowledge gap and shed light on potential contamination risk in the meat supply chain, this study aimed to assess the underexplored microbial quality and safety of marketed beef meat in Oman. Thirty-three beef meat samples from six hypermarkets were analyzed for Aerobic Plate Count (APC), Psychrotrophic Bacteria Count (PBC), and coliform and counts.
View Article and Find Full Text PDFBrain Sci
December 2024
Neuroinformatics Laboratory (NiLab), Bruno Kessler Foundation (FBK), 39123 Trento, Italy.
In glioma surgery, maximizing the extent of resection while preserving cognitive functions requires an understanding of the unique architecture of the white matter (WM) pathways of the single patient and of their spatial relationship with the tumor. Tractography enables the reconstruction of WM pathways, and bundle segmentation allows the identification of critical connections for functional preservation. This study evaluates the effectiveness of a streamline-based approach for bundle segmentation on a clinical dataset as compared to the traditional ROI-based approach.
View Article and Find Full Text PDFJ Hazard Mater
December 2024
School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China; Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China. Electronic address:
Understanding the behavior and fate of microplastics (MPs) in aquatic environment is crucial for assessing their potential risks. This study investigated the heteroaggregation behaviors of MPs with representative 2D nanosheets, MoS and graphene oxide (GO), under various conditions, focusing on the transport behavior of the resulting aggregates. It was found that the destabilization capabilities of 2D nanosheets are notably stronger than those of well-reported nanoparticles.
View Article and Find Full Text PDFNat Genet
January 2025
Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
Identifying gene expression differences in heterogeneous tissues across conditions is a fundamental biological task, enabled by multi-condition single-cell RNA sequencing (RNA-seq). Current data analysis approaches divide the constituent cells into clusters meant to represent cell types, but such discrete categorization tends to be an unsatisfactory model of the underlying biology. Here, we introduce latent embedding multivariate regression (LEMUR), a model that operates without, or before, commitment to discrete categorization.
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