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Dehydration rapidly induces expression of NCED genes from a single subclade in diverse eudicots.
Planta
January 2025
School of Natural Sciences, University of Tasmania, Private Bag 55, Hobart, TAS, 7001, Australia.
A gene within a single subclade of NCED genes is triggered in response to both, short- and long-term dehydration treatments, in three model dicot species. During dehydration, some plants can rapidly synthesise the stress hormone abscisic acid (ABA) in leaves within 20 min, triggering the closure of stomata and limiting further water loss. This response is associated with significant transcriptional upregulation of Nine-cis-Epoxycarotenoid Dioxygenase (NCED) genes, which encode the enzyme considered to be rate-limiting in ABA biosynthesis.
View Article and Find Full Text PDFPrivacy-preserving approach for IoT networks using statistical learning with optimization algorithm on high-dimensional big data environment.
Sci Rep
January 2025
Department of Artificial Intelligence and Data Science, College of Computer Science and Engineering, University of Hail, Hail, Saudi Arabia.
In the present digital scenario, the explosion of Internet of Things (IoT) devices makes massive volumes of high-dimensional data, presenting significant data and privacy security challenges. As IoT networks enlarge, certifying sensitive data privacy while still employing data analytics authority is vital. In the period of big data, statistical learning has seen fast progressions in methodological practical and innovation applications.
View Article and Find Full Text PDFHigh-Precision prediction of curling trajectory multivariate time series using the novel CasLSTM approach.
Sci Rep
January 2025
Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China.
As a multivariate time series, the prediction of curling trajectories is crucial for athletes to devise game strategies. However, the wide prediction range and complex data correlations present significant challenges to this task. This paper puts forward an innovative deep learning approach, CasLSTM, by introducing integrated inter-layer memory, and establishes an encoder-predictor curling trajectory forecasting model accordingly.
View Article and Find Full Text PDFUnsupervised data imputation with multiple importance sampling variational autoencoders.
Sci Rep
January 2025
School of Mathematics and Statistics, Shaoguan University, Shaoguan, 512005, China.
Recently, deep latent variable models have made significant progress in dealing with missing data problems, benefiting from their ability to capture intricate and non-linear relationships within the data. In this work, we further investigate the potential of Variational Autoencoders (VAEs) in addressing the uncertainty associated with missing data via a multiple importance sampling strategy. We propose a Missing data Multiple Importance Sampling Variational Auto-Encoder (MMISVAE) method to effectively model incomplete data.
View Article and Find Full Text PDFTransient lymphocyte count decrease correlates with oncolytic adenovirus efficacy in humans: mechanistic and biomarker findings from TUNIMO phase I trial.
J Immunother Cancer
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Cancer Gene Therapy Group, Translational Immunology Research Program, University of Helsinki, Helsinki, Finland
Background: Oncolytic viruses (OVs) are promising immunotherapeutics to treat immunologically cold tumors. However, research on the mechanism of action of OVs in humans and clinically relevant biomarkers is still sparse. To induce strong T-cell responses against solid tumors, TILT-123 (Ad5/3-E2F-d24-hTNFa-IRES-hIL2, igrelimogene litadenorepvec) was developed.
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