ST40 electromagnetic predictive studies supported by machine learning applied to experimental database.

Nuclear fusion is entering the era of power plant-scale devices, which are now undergoing extensive studies to support the design phase. Plasma disruptions pose a high risk to these classes of devices because of the large stored thermal and magnetic energy which might jeopardize machine integrity and availability. Therefore, disruptions within these devices must be virtually eliminated, and any disruptions which do happen must be highly mitigated.

Analysis of the PEBP gene family and identification of a novel FLOWERING LOCUS T orthologue in sugarcane.

Sugarcane (Saccharum spp.) is an important economic crop for both sugar and biomass, the yields of which are negatively affected by flowering. The molecular mechanisms controlling flowering in sugarcane are nevertheless poorly understood.

Transcriptomic Analysis of Changes in Gene Expression During Flowering Induction in Sugarcane Under Controlled Photoperiodic Conditions.

Flowering is of utmost relevance for the agricultural productivity of the sugarcane bioeconomy, but data and knowledge of the genetic mechanisms underlying its photoperiodic induction are still scarce. An understanding of the molecular mechanisms that regulate the transition from vegetative to reproductive growth in sugarcane could provide better control of flowering for breeding. This study aimed to investigate the transcriptome of +1 mature leaves of a sugarcane cultivar subjected to florally inductive and non-inductive photoperiodic treatments to identify gene expression patterns and molecular regulatory modules.

Selection and validation of reference genes by RT-qPCR under photoperiodic induction of flowering in sugarcane (Saccharum spp.).

Although reference genes have previously been used in the expression analysis of genes involved in sugarcane flowering they had not been experimentally validated for stability and consistency of expression between different samples over a wide range of experimental conditions. Here we report the analysis of candidate reference genes in different tissue types, at different temporal time-points, in both short and long day photoperiodic treatments. The stability of the candidate reference genes in all conditions was evaluated with NormFinder, BestKeeper, and RefFinder algorithms that complement each other for a more robust analysis.