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Despite the common misconception of nearly static organisms, plants do interact continuously with the environment and with each other. It is fair to assume that during their evolution they developed particular features to overcome similar problems and to exploit possibilities from environment. In this paper we introduce various quantitative measures based on recent advancements in complex network theory that allow to measure the effective similarities of various species. By using this approach on the similarity in fruit-typology ecological traits we obtain a clear plant classification in a way similar to traditional taxonomic classification. This result is not trivial, since a similar analysis done on the basis of diaspore morphological properties do not provide any clear parameter to classify plants species. Complex network theory can then be used in order to determine which feature amongst many can be used to distinguish scope and possibly evolution of plants. Future uses of this approach range from functional classification to quantitative determination of plant communities in nature.
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http://dx.doi.org/10.1038/srep27077 | DOI Listing |
Med Teach
September 2025
NordSim, Center for Skills Training and Simulation, Aalborg University Hospital, Aalborg, Denmark.
Background: Assessing skills in simulated settings is resource-intensive and lacks validated metrics. Advances in AI offer the potential for automated competence assessment, addressing these limitations. This study aimed to develop and validate a machine learning AI model for automated evaluation during simulation-based thyroid ultrasound (US) training.
View Article and Find Full Text PDFJ Chem Inf Model
September 2025
Key Laboratory of Micro-nano Sensing and IoT of Wenzhou, Wenzhou Institute of Hangzhou Dianzi University, Wenzhou 325038, China.
Transcription factors (TFs) are essential proteins that regulate gene expression by specifically binding to transcription factor binding sites (TFBSs) within DNA sequences. Their ability to precisely control the transcription process is crucial for understanding gene regulatory networks, uncovering disease mechanisms, and designing synthetic biology tools. Accurate TFBS prediction, therefore, holds significant importance in advancing these areas of research.
View Article and Find Full Text PDFJ Food Sci
September 2025
College of Food and Bioengineering, Zhengzhou University of Light Industry, Zhengzhou, China.
Primary agricultural products are closely related to our daily lives, as they serve not only as raw materials for food processing but also as products directly purchased by consumers. These products face the issue of freshness decline and spoilage during both production and consumption. Freshness degradation induces sensory deterioration and nutritional loss and promotes harmful substance accumulation, causing gastrointestinal issues or even endangering life.
View Article and Find Full Text PDFUrol J
September 2025
Affiliated Hospital of Nantong University, Emergency Department, Nantong, 226000, Jiangsu, China.
Purpose: Urosepsis, a condition caused by a urinary tract infection spreading to the bloodstream, has a complex epigenetic behavior in its cellular and molecular pathophysiology. The objective of this study was to identify relevant genes and signaling pathways in adult urosepsis through a bioinformatic analysis of differentially expressed genes (DEGs).
Materials And Methods: In this in-silico study, the GSE69528 dataset, containing 138 total RNA blood samples from patients with sepsis and uninfected controls, was obtained from the Gene Expression Omnibus (GEO) database.
Talanta
September 2025
IRCCS Istituto delle Scienze Neurologiche di Bologna, Full Member of the European Reference Network for Rare and Complex Epilepsies (EpiCARE), Bologna, Italy.