Walking Step Monitoring with a Millimeter-Wave Radar in Real-Life Environment for Disease and Fall Prevention for the Elderly

We studied the use of a millimeter-wave frequency-modulated continuous wave radar for gait analysis in a real-life environment, with a focus on the measurement of the step time. A method was developed for the successful extraction of gait patterns for different test cases. The quantitative investigation carried out in a lab corridor showed the excellent reliability of the proposed method for the step time measurement, with an average accuracy of 96%. In addition, a comparison test between the millimeter-wave radar and a continuous-wave radar working at 2.45 GHz was performed, and the results suggest that the millimeter-wave radar is more capable of capturing instantaneous gait features, which enables the timely detection of small gait changes appearing at the early stage of cognitive disorders

A novel yeast hybrid modeling framework integrating Boolean and enzyme-constrained networks enables exploration of the interplay between signaling and metabolism

The interplay between nutrient-induced signaling and metabolism plays an important role in maintaining homeostasis and its malfunction has been implicated in many different human diseases such as obesity, type 2 diabetes, cancer, and neurological disorders. Therefore, unraveling the role of nutrients as signaling molecules and metabolites together with their interconnectivity may provide a deeper understanding of how these conditions occur. Both signaling and metabolism have been extensively studied using various systems biology approaches. However, they are mainly studied individually and in addition, current models lack both the complexity of the dynamics and the effects of the crosstalk in the signaling system. To gain a better understanding of the interconnectivity between nutrient signaling and metabolism in yeast cells, we developed a hybrid model, combining a Boolean module, describing the main pathways of glucose and nitrogen signaling, and an enzyme-constrained model accounting for the central carbon metabolism of Saccharomyces cerevisiae, using a regulatory network as a link. The resulting hybrid model was able to capture a diverse utalization of isoenzymes and to our knowledge outperforms constraint-based models in the prediction of individual enzymes for both respiratory and mixed metabolism. The model showed that during fermentation, enzyme utilization has a major contribution in governing protein allocation, while in low glucose conditions robustness and control are prioritized. In addition, the model was capable of reproducing the regulatory effects that are associated with the Crabtree effect and glucose repression, as well as regulatory effects associated with lifespan increase during caloric restriction. Overall, we show that our hybrid model provides a comprehensive framework for the study of the non-trivial effects of the interplay between signaling and metabolism, suggesting connections between the Snf1 signaling pathways and processes that have been related to chronological lifespan of yeast cells

Azufre elemental como corrector del pH y la fertilidad de algunos suelos de la III y IV Regi\uf3n de Chile

Soils containing calcite are common in Northern Chile, and this condition decreases the availability of nutrients for plants. The effect of the application of elemental sulphur (S\ub0) was evaluated on soil pH, electrical conductivity and the available micronutrients content in six soils of the III and IV Regions of Chile. This was applied in doses of 500 and 1000 mg S\ub0 kg-1 and the soils were incubated for periods of 60 and 120 days at 80% of field capacity and 26\ub0C. The experimental design was completely randomized with a factorial design and the treatments included soil, doses of elemental sulphur and times of incubation. The soil characteristics having the greatest influence on acidification by sulphur addition were the CaCO3, organic matter and sand contents. A highly significant reduction of soil pH occured in those soils with a smaller buffering capacity, as a consequence of lower CaCO3 and organic matter contents. Electrical conductivity increased by the application of elemental sulphur as a result of the rise of soluble salts in the soil. When the pH diminished significantly, the levels of Fe, Mn and Cu micronutrients increased in the soils; Mn was the most strongly influenced by the acidification. This information is useful for the application of amendment programs for the calcareous soils of Northern ChileEn los suelos de la zona norte de Chile existen suelos con carbonatos, situaci\uf3n que influye sobre la disponibilidad de nutrientes para los cultivos. En el presente experimento se evalu\uf3 en condiciones de laboratorio, el efecto de la aplicaci\uf3n de azufre elemental sobre el pH, conductividad el\ue9ctrica y micronutrientes en seis suelos de la III y IV Regi\uf3n, Chile. El azufre se aplic\uf3 en dosis de 500 y 1000 mg S\ub0 kg-1, y el suelo se incub\uf3 por per\uedodos de 60 y 120 d\uedas a 80% de su capacidad de campo a 25\ub0C. El experimento se estableci\uf3 con un dise\ue3o de tratamientos completamente al azar con arreglo factorial, donde los factores fueron: suelo, dosis de azufre elemental y tiempo de incubaci\uf3n. Los recipientes en incubaci\uf3n se distribuyeron de acuerdo a un dise\ue3o completamente al azar. Las caracter\uedsticas de los suelos que m\ue1s influyeron sobre la magnitud del efecto acidificante del azufre elemental fueron los contenidos de CaCO3, materia org\ue1nica y arena. Las reducciones de pH significativas se presentaron en los suelos con una menor capacidad tamp\uf3n, como consecuencia del menor contenido de CaCO3 y materia org\ue1nica. La conductividad el\ue9ctrica se increment\uf3 por la aplicaci\uf3n del azufre elemental, debido al aumento de sales solubles en el suelo. Los niveles de los micronutrientes Fe, Mn y Cu se incrementaron en los suelos cuyos pH disminuyeron significativamente, siendo el Mn el m\ue1s influenciado por la acidificaci\uf3n. Esta informaci\uf3n es de utilidad para establecer programas de aplicaci\uf3n de enmiendas en suelos calc\ue1reos de la zona norte de Chile

Benchmarking accuracy and precision of intensity-based absolute quantification of protein abundances in Saccharomyces cerevisiae

Protein quantification via label-free mass spectrometry (MS) has become an increasingly popular method for predicting genome-wide absolute protein abundances. A known caveat of this approach, however, is the poor technical reproducibility, that is, how consistent predictions are when the same sample is measured repeatedly. Here, we measured proteomics data for Saccharomyces cerevisiae with both biological and inter-batch technical triplicates, to analyze both accuracy and precision of protein quantification via MS. Moreover, we analyzed how these metrics vary when applying different methods for converting MS intensities to absolute protein abundances. We demonstrate that our simple normalization and rescaling approach can perform as accurately, yet more precisely, than methods which rely on external standards. Additionally, we show that inter-batch reproducibility is worse than biological reproducibility for all evaluated methods. These results offer a new benchmark for assessing MS data quality for protein quantification, while also underscoring current limitations in this approach

Identification of a novel gene required for competitive growth at high temperature in the thermotolerant yeast Kluyveromyces marxianus

It is important to understand the basis of thermotolerance in yeasts to broaden their application in industrial biotechnology. The capacity to run bioprocesses at temperatures above 40 \ub0C is of great interest but this is beyond the growth range of most of the commonly used yeast species. In contrast, some industrial yeasts such as Kluyveromyces marxianus can grow at temperatures of 45 \ub0C or higher. Such species are valuable for direct use in industrial biotechnology and as a vehicle to study the genetic and physiological basis of yeast thermotolerance. In previous work, we reported that evolutionarily young genes disproportionately changed expression when yeast were growing under stressful conditions and postulated that such genes could be important for long-term adaptation to stress. Here, we tested this hypothesis in K. marxianus by identifying and studying species-specific genes that showed increased expression during high-temperature growth. Twelve such genes were identified and 11 were successfully inactivated using CRISPR-mediated mutagenesis. One gene, KLMX_70384, is required for competitive growth at high temperature, supporting the hypothesis that evolutionary young genes could play roles in adaptation to harsh environments. KLMX_70384 is predicted to encode an 83 aa peptide, and RNA sequencing and ribo-sequencing were used to confirm transcription and translation of the gene. The precise function of KLMX_70384 remains unknown but some features are suggestive of RNA-binding activity. The gene is located in what was previously considered an intergenic region of the genome, which lacks homologues in other yeasts or in databases. Overall, the data support the hypothesis that genes that arose de novo in K. marxianus after the speciation event that separated K. marxianus and K. lactis contribute to some of its unique traits

Yeast metabolic innovations emerged via expanded metabolic network and gene positive selection

Yeasts are known to have versatile metabolic traits, while how these metabolic traits have evolved has not been elucidated systematically. We performed integrative evolution analysis to investigate how genomic evolution determines trait generation by reconstructing genome-scale metabolic models (GEMs) for 332 yeasts. These GEMs could comprehensively characterize trait diversity and predict enzyme functionality, thereby signifying that sequence-level evolution has shaped reaction networks towards new metabolic functions. Strikingly, using GEMs, we can mechanistically map different evolutionary events, e.g. horizontal gene transfer and gene duplication, onto relevant subpathways to explain metabolic plasticity. This demonstrates that gene family expansion and enzyme promiscuity are prominent mechanisms for metabolic trait gains, while GEM simulations reveal that additional factors, such as gene loss from distant pathways, contribute to trait losses. Furthermore, our analysis could pinpoint to specific genes and pathways that have been under positive selection and relevant for the formulation of complex metabolic traits, i.e. thermotolerance and the Crabtree effect. Our findings illustrate how multidimensional evolution in both metabolic network structure and individual enzymes drives phenotypic variations

Analysis of genetic diversity in the Oryza officinalis complex

The genetic relationships among 34 accessions of wild rice from Asia, Africa, America and Australia were analysed using RFLP technique. After southern blotting, DNA digestion pattern was hybridised with a highly repetitive DNA sequence of a retrotransposon from a gypsy family of mobile elements. A dendrogram was constructed from RFLP data in which the species clustered according to their genome designation (CC, BB, BBCC and CCDD genomes). Some species did not appear in the same group, for example, O. eichingeri from Africa and Sri Lanka clustered separately from each other. The same situation was observed for the accessions from China of O. officinalis, which cluster together showing a close relationship with O. rhizomatis, and O. eichingeri (both of CC genome). Also, the tetraploid BBCC from India of O. officinalis appears in the same cluster of O. eichingeri and O. punctata (both from Africa) suggesting close phylogenetic relationship with the African genomes BB, CC and BBCC

Stress-induced expression is enriched for evolutionarily young genes in diverse budding yeasts

The Saccharomycotina subphylum (budding yeasts) spans 400 million years of evolution and includes species that thrive in diverse environments. To study niche-adaptation, we identify changes in gene expression in three divergent yeasts grown in the presence of various stressors. Duplicated and non-conserved genes are significantly more likely to respond to stress than genes that are conserved as single-copy orthologs. Next, we develop a sorting method that considers evolutionary origin and duplication timing to assign an evolutionary age to each gene. Subsequent analysis reveals that genes that emerged in recent evolutionary time are enriched amongst stress-responsive genes for each species. This gene expression pattern suggests that budding yeasts share a stress adaptation mechanism, whereby selective pressure leads to functionalization of young genes to improve growth in adverse conditions. Further characterization of young genes from species that thrive in harsh environments can inform the design of more robust strains for biotechnology

Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0

Genome-scale metabolic models (GEMs) have been widely used for quantitative exploration of the relation between genotype and phenotype. Streamlined integration of enzyme constraints and proteomics data into such models was first enabled by the GECKO toolbox, allowing the study of phenotypes constrained by protein limitations. Here, we upgrade the toolbox in order to enhance models with enzyme and proteomics constraints for any organism with a compatible GEM reconstruction. With this, enzyme-constrained models for the budding yeasts Saccharomyces cerevisiae, Yarrowia lipolytica and Kluyveromyces marxianus are generated to study their long-term adaptation to several stress factors by incorporation of proteomics data. Predictions reveal that upregulation and high saturation of enzymes in amino acid metabolism are common across organisms and conditions, suggesting the relevance of metabolic robustness in contrast to optimal protein utilization as a cellular objective for microbial growth under stress and nutrient-limited conditions. The functionality of GECKO is expanded with an automated framework for continuous and version-controlled update of enzyme-constrained GEMs, also producing such models for Escherichia coli and Homo sapiens. In this work, we facilitate the utilization of enzyme-constrained GEMs in basic science, metabolic engineering and synthetic biology purposes

Electrically Controlled Spin Injection from Giant Rashba Spin-Orbit Conductor BiTeBr

Ferromagnetic materials are the widely used source of spin-polarized electrons in spintronic devices, which are controlled by external magnetic fields or spin-transfer torque methods. However, with increasing demand for smaller and faster spintronic components utilization of spin-orbit phenomena provides promising alternatives. New materials with unique spin textures are highly desirable since all-electric creation and control of spin polarization is expected where the strength, as well as an arbitrary orientation of the polarization, can be defined without the use of a magnetic field. In this work, we use a novel spin-orbit crystal BiTeBr for this purpose. Because of its giant Rashba spin splitting, bulk spin polarization is created at room temperature by an electric current. Integrating BiTeBr crystal into graphene-based spin valve devices, we demonstrate for the first time that it acts as a current-controlled spin injector, opening new avenues for future spintronic applications in integrated circuits