Complete characterization of spin chains with two Ising symmetries

Spin chains with two Ising symmetries are the Jordan-Wigner duals of one-dimensional interacting fermions with particle-hole and time-reversal symmetry. From earlier works on Majorana chains, it is known that this class of models has 10 distinct topological phases. In this paper, we analyze the physical properties of the correspondent 10 phases of the spin model. In particular, thanks to a set of two non-commuting dualities, we determine the local and non-local order parameters of the phases. We find that 4 phases are topologically protected by the Ising symmetries, while the other 6 break at least one symmetry. Our study highlights the non-trivial relation between the topological classifications of interacting bosons and fermions.Comment: 7 page

The arogenate dehydratase ADT2 is essential for seed development in Arabidopsis

Phenylalanine (Phe) biosynthesis in plants is a key process, as Phe serves as precursor of proteins and phenylpropanoids. The prephenate pathway connects chorismate, final product of the shikimate pathway, with the biosynthesis of Phe and Tyr. Two alternative routes of Phe biosynthesis have been reported: one depending of arogenate, and the other of phenylpyruvate. Whereas the arogenate pathway is considered the main route, the role of the phenylpyruvate pathway remains unclear. Here, we report that the deficiency in ADT2, a bifunctional arogenate dehydratase (ADT)/ prephenate dehydratase (PDT) enzyme, causes embryo arrest and seed abortion. This result makes a clear distinction between the essential role of ADT2 and the five remaining ADTs from Arabidopsis, which display mostly overlapping functions. We have found that PHA2, a monofunctional PDT from yeast, restores the adt2 phenotype when is targeted within the plastids, but not when is expressed in the cytosol. Similar results can be obtained by expressing ADT3, a monofunctional ADT. These results suggest that Phe can be synthesized from phenylpyruvate or arogenate when the bifunctional ADT2 is replaced by other ADT or PDT enzymes during seed formation, highlighting the importance of Phe for embryo development, and providing further insights into the plasticity of Phe biosynthesis.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Biochemical regulation of arginine biosynthesis in plants

Arginine plays a relevant role in plant metabolism due to its importance as building block of proteins but also as precursor of multiple secondary metabolites, polyamines and nitric oxide. Importantly, arginine frequently plays an essential role as a major nitrogen storage form in seeds and other vegetative tissues and its mobilization provides an efficient flux of nitrogen for different physiological processes [1][2][3]. Despite its importance, the biochemical regulation and kinetics of the enzymes involved in arginine biosynthesis remains poorly characterized in plants. In this work, we provide new knowledge about the biochemical regulation of the three enzymes involved in the last steps of the arginine pathway: ornithine transcarbamoylase (OTC), argininosuccinate synthetase (ASSY), and argininosuccinate lyase (ASL). Our results indicate that these enzymes are regulated by the concentration of different amino acids and metabolites, including arginine, suggesting that feedback regulatory loops could play and important role in the homeostasis of this amino acid. Besides, these regulatory mechanisms seem to have been subjected to a progressive refinement during the evolution of land plants, pointing towards a coevolution with the higher requirements of arginine in seed plants.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Applying artificial intelligence models for the automatic forest fire detection

Throughout the past decade, the development of Artificial Intelligence-based devices for the automatic detection of early stage forest fires has been a growing focus. Computer Vision techniques are well-suited for this problem due to the distinctive visual characteristics of forest fires. The effectiveness of several Artificial Intelligence algorithms in a binary classification problem involving fire/ non-fire images was assessed by comparing them using a publicly available dataset. The benchmark dataset was used to both train and evaluate the models. An optimization method was employed to train the Artificial Intelligence algorithms, resulting in a higher performance than that previously achieved by studies on the same dataset

The wildfire dataset: enhancing deep learning-based forest fire detection with a diverse evolving open-source dataset focused on data representativeness and a novel multi-task learning approach

This study explores the potential of RGB image data for forest fire detection using deep learning models, evaluating their advantages and limitations, and discussing potential integration within a multi-modal data context. The research introduces a uniquely comprehensive wildfire dataset, capturing a broad array of environmental conditions, forest types, geographical regions, and confounding elements, aiming to reduce high false alarm rates in fire detection systems. To ensure integrity, only public domain images were included, and a detailed description of the dataset’s attributes, URL sources, and image resolutions is provided. The study also introduces a novel multi-task learning approach, integrating multi-class confounding elements within the framework. A pioneering strategy in the field of forest fire detection, this method aims to enhance the model’s discriminatory ability and decrease false positives. When tested against the wildfire dataset, the multi-task learning approach demonstrated significantly superior performance in key metrics and lower false alarm rates compared to traditional binary classification methods. This emphasizes the effectiveness of the proposed methodology and the potential to address confounding elements. Recognizing the need for practical solutions, the study stresses the importance of future work to increase the representativeness of training and testing datasets. The evolving and publicly available wildfire dataset is anticipated to inspire innovative solutions, marking a substantial contribution to the fieldPostprint (published version

Fingerprinting Hysteresis

We test the predictive power of first-oder reversal curve (FORC) diagrams using simulations of random magnets. In particular, we compute a histogram of the switching fields of the underlying microscopic switching units along the major hysteresis loop, and compare to the corresponding FORC diagram. We find qualitative agreement between the switching-field histogram and the FORC diagram, yet differences are noticeable. We discuss possible sources for these differences and present results for frustrated systems where the discrepancies are more pronounced.Comment: 4 pages, 5 figure

Multidisciplinary teaching of Biotechnology and Omics sciences

In the last years, there was a great boom in the Omics fields that have developed as multidisciplinary sciences. They use laboratory techniques related to Biology and Chemistry but also Bioinformatics tools. However, the developmental progress of these disciplines has led that much of undergraduate studies related to Biology have curricula that become outdated. From this point of view, it is necessary to focus the students to the fundamentals and techniques of complementary disciplines that will be essentials for the understanding of the Omics sciences. In the present work, we have developed a new teaching approach for Biochemistry, Biology and Bioinformatics students. They formed interdisciplinary working groups. These groups have prepared and presented communications about different techniques or methods in Molecular Biology, Omics or Bioinformatics participating in a technical meeting. This learning strategy “I do and I learn” has enabled to the students a first contact with the scientific communication including the approach to the scientific literature to acquire technical knowledge. The cooperation between students from different disciplines has enriched their point of view and even has been used in some practical master’s works.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Maritime pine PpMYB8 directly co-regulates secondary cell wall architecture and the associated Phe-biosynthesis pathway

Plants rely on the biosynthesis of L-Phenylalanine as building block for the synthesis of proteins but also as precursor for a tremendous range of plant-derived compounds essential for its grown, development and defense. Polymerization of secondary cell wall in trees involves the massive biosynthesis, among others, of the Phe-derived compound lignin. Thus, these plants require an accurate metabolic coordination between Phe and lignin biosynthesis to ensure its normal development. We have here identified that the pine arogenate dehydratase, whose enzyme activity limits the biosynthesis of Phe in plants, is transcriptionally regulated through direct interaction with PpMyb8. We have also shown that this transcription factor is directly involve in secondary cell wall biogenesis and cell death processes. Together these results indicate that a single transcription factor coordinates lignin accumulation and the proper biosynthesis of its essential precursor L-Phe.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Metabolic channeling of phe for lignin biosynthesis in maritime pine

Phenylalanine (Phe) is the main precursor of phenylpropanoids biosynthesis in plants. This vast family of Phe-derived compounds can represent more than 30% of captured photosynthetic carbon, playing essential roles in plants such as cell wall components, defense molecules, pigments and flavors. In addition to its physiological importance, phenylpropanoids and particularly lignin, a component of wood, are targets in plant biotechnology. The arogenate pathway has been proposed as the main pathway for Phe biosynthesis in plants (Maeda et al., 2010). The final step in Phe biosynthesis, catalyzed by the enzyme arogenate dehydratase (ADT), has been considered as a key regulatory point in Phe biosynthesis, due to its key branch position in the pathway, the multiple isoenzymes identified in plants and the existence of a feedback inhibition mechanism by Phe. So far, the regulatory mechanisms underlying ADT genes expression have been poorly characterized, although a strong regulation of the Phe metabolic flux should be expected depending on its alternative use for protein biosynthesis versus phenylpropanoid biosynthesis. This second fate involves a massive carbon flux compared to the first one. Here we report our current research activities in the transcriptional regulation of ADT genes by MYB transcription factors in Pinus pinaster. The conifers channels massive amounts of photosynthetic carbon for phenylpropanoid biosynthesis during wood formation. We have identified the complete ADT gene family in maritime pine (El-Azaz et al., 2016) and a set of ADT isoforms specifically related with the lignification process. The potential control of transcription factors previously reported as key regulators in pine wood formation (Craven-Bartle et al., 2013) will be presented.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Phenylalanine biosynthesis: the role and evolution of arogenate dehydratase gene family in c

In plants, arogenate dehydratase activity (ADT, EC 4.2.1.91) is responsible for the last step in the main pathway for phenylalanine biosynthesis, known as the arogenate pathway, which consist in two steps: the conversion of prephenate to arogenate in a reaction catalyzed by the enzyme prephenate aminotransferase (PAT, EC 2.6.1.78) and the decarboxylation of arogenate to render phenylalanine catalyzed by ADT. The arogenate pathway results of particular interest according to the important role of phenylalanine in plant metabolism, acting as the main gate of entry to phenylpropanoids biosynthesis, that constitute up to 30 to 45% of plant organic matter (Razal et al., 1996). This is particularly relevant in perennial woody plants, in which lignification process and resultant biomass acumulation through plant life cycle are notably important. Despite of the high importance of phenylalanine biosynthesis and derived phenylpropanoids in plants biology, the arogenate pathway still remains poorly characterized, particularly in woody plants. Very recently, two independent publications reported physiological evidences suggesting an alternative arogenate-independent pathway for phenylalanine biosynthesis in plants (Yoo et al., 2013; De la Torre et al., 2014), as described previously in fungi and bacteria. This pathway is dependent of a prephenate dehydratase enzyme (PDT, EC 4.2.1.51) catalyzing the conversion of prephenate to phenylpyruvate, being subsequently converted into phenylalanine through a transamination reaction. It has been reported that ADT and PDT activities are housed in the same proteins in plants (Cho et al., 2007). Here we present preliminary results focused on the characterization of the ADT/PDT gene family in maritime pine (Pinus pinaster Ait.), a conifer tree of ecological and commercial interest. Our results demonstrate the existence of at least 9 ADT-like genes in the P. pinaster transcriptome, showing organ- and developmentspecific mRNA and protein expression profiles. Moreover, 3 of those 9 candidate genes present a distinctive phylogenetic clustering, forming a conifer-characteristic group of ADT-like genes differenced from the remaining ADT sequences. These findings highlights the potential importance of ADT/PDT activities in conifer metabolism, suggesting the existence of a singular and highly-specialized prephenate-related metabolism in conifers. Cho MH, Corea OR, Yang H, Bedgar DL, Laskar DD, Anterola AM, Moog-Anterola FA, Hood RL, Kohalmi SE, Bernards MA, Kang C, Davin LB and Lewis NG. (2007) Phenylalanine biosynthesis in Arabidopsis thaliana. Identification and characterization of arogenate dehydratases. J Biol Chem. 282(42):30827-35.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech