Post-translational insertion of boron in proteins to probe and modulate function

Boron is absent in proteins, yet is a micronutrient. It possesses unique bonding that could expand biological function including modes of Lewis acidity not available to typical elements of life. Here we show that post-translational Cβ–Bγ bond formation provides mild, direct, site-selective access to the minimally sized residue boronoalanine (Bal) in proteins. Precise anchoring of boron within complex biomolecular systems allows dative bond-mediated, site-dependent protein Lewis acid–base-pairing (LABP) by Bal. Dynamic protein-LABP creates tunable inter- and intramolecular ligand–host interactions, while reactive protein-LABP reveals reactively accessible sites through migratory boron-to-oxygen Cβ–Oγ covalent bond formation. These modes of dative bonding can also generate de novo function, such as control of thermo- and proteolytic stability in a target protein, or observation of transient structural features via chemical exchange. These results indicate that controlled insertion of boron facilitates stability modulation, structure determination, de novo binding activities and redox-responsive ‘mutation’

Post-translational insertion of boron in proteins to probe and modulate function

Boron is absent in proteins, yet is a micronutrient. It possesses unique bonding that could expand biological function including modes of Lewis acidity not available to typical elements of life. Here we show that post-translational Cβ–Bγ bond formation provides mild, direct, site-selective access to the minimally sized residue boronoalanine (Bal) in proteins. Precise anchoring of boron within complex biomolecular systems allows dative bond-mediated, site-dependent protein Lewis acid–base-pairing (LABP) by Bal. Dynamic protein-LABP creates tunable inter- and intramolecular ligand–host interactions, while reactive protein-LABP reveals reactively accessible sites through migratory boron-to-oxygen Cβ–Oγ covalent bond formation. These modes of dative bonding can also generate de novo function, such as control of thermo- and proteolytic stability in a target protein, or observation of transient structural features via chemical exchange. These results indicate that controlled insertion of boron facilitates stability modulation, structure determination, de novo binding activities and redox-responsive ‘mutation’

A Repeated Measures Experiment of Green Exercise to Improve Self-Esteem in UK School Children

Exercising in natural, green environments creates greater improvements in adult's self-esteem than exercise undertaken in urban or indoor settings. No comparable data are available for children. The aim of this study was to determine whether so called 'green exercise' affected changes in self-esteem; enjoyment and perceived exertion in children differently to urban exercise. We assessed cardiorespiratory fitness (20 m shuttle-run) and self-reported physical activity (PAQ-A) in 11 and 12 year olds (n = 75). Each pupil completed two 1.5 mile timed runs, one in an urban and another in a rural environment. Trials were completed one week apart during scheduled physical education lessons allocated using a repeated measures design. Self-esteem was measured before and after each trial, ratings of perceived exertion (RPE) and enjoyment were assessed after completing each trial. We found a significant main effect (F (1,74), = 12.2, p<0.001), for the increase in self-esteem following exercise but there was no condition by exercise interaction (F (1,74), = 0.13, p = 0.72). There were no significant differences in perceived exertion or enjoyment between conditions. There was a negative correlation (r = -0.26, p = 0.04) between habitual physical activity and RPE during the control condition, which was not evident in the green exercise condition (r = -0.07, p = 0.55). Contrary to previous studies in adults, green exercise did not produce significantly greater increases in self-esteem than the urban exercise condition. Green exercise was enjoyed more equally by children with differing levels of habitual physical activity and has the potential to engage less active children in exercise. © 2013 Reed et al

When counting cattle is not enough: multiple perspectives in agricultural and veterinary research

A traditional approach in agricultural and veterinary research is focussing on the biological perspective where large cattle-databases are used to analyse the dairy herd. This approach has yielded valuable insights. However, recent research indicates that this knowledge-base can be further increased by examining agricultural and veterinary challenges from other perspectives. In this paper we suggest three perspectives that may supplement the biological perspective in agricultural and veterinary research; the economic-, the managerial-, and the social perspective. We review recent studies applying or combining these perspectives and discuss how multiple perspectives may improve our understanding and ability to handle cattle-health challenges

A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios

[EN] Ecuador is worldwide considered as one of the main natural flower producers and exporters ¿being roses the most salient ones. Such a fact has naturally led the emergence of small and medium sized companies devoted to the production of quality roses in the Ecuadorian highlands, which intrinsically entails resource usage optimization. One of the first steps towards optimizing the use of resources is to forecast demand, since it enables a fair perspective of the future, in such a manner that the in-advance raw materials supply can be previewed against eventualities, resources usage can be properly planned, as well as the misuse can be avoided. Within this approach, the problem of forecasting the supply of roses was solved into two phases: the first phase consists of the macro-forecast of the total amount to be exported by the Ecuadorian flower sector by the year 2020, using multi-layer neural networks. In the second phase, the monthly demand for the main rose varieties offered by the study company was micro-forecasted by testing seven models. In addition, a Bayesian network model is designed, which takes into consideration macroeconomic aspects, the level of employability in Ecuador and weather-related aspects. This Bayesian network provided satisfactory results without the need for a large amount of historical data and at a low-computational cost.Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS ¿Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems¿ (www.ruc-aps.eu), funded by the European Union under their funding scheme H2020-MSCA-RISE-2015. In addition, the authors are greatly grateful by the support given by the SDAS Research Group (www.sdas-group.com)Herrera-Granda, ID.; Lorente-Leyva, LL.; Peluffo-Ordóñez, DH.; Alemany Díaz, MDM. (2021). A Forecasting Model to Predict the Demand of Roses in an Ecuadorian Small Business Under Uncertain Scenarios. Lecture Notes in Computer Science. 12566:245-258. https://doi.org/10.1007/978-3-030-64580-9_21S24525812566Asociación de Productores y Exportadores de Flores: Inicio – Expoflores. https://expoflores.com/Palacios, J., Rosero, D.: Análisis de las condiciones climáticas registradas en el Ecuador continental en el año 2013 y su impacto en el sector agrícola. Estud. e Investig. meteorológicas. Ina. Inst. Nac. Meteorol. e Hidrol. Ecuador, 28, p. (2014)Hidalgo-Proaño, M.: Variabilidad climática interanual sobre el Ecuador asociada a ENOS. CienciAmérica 6, 42–47 (2017)Ritchie, J.W., Abawi, G.Y., Dutta, S.C., Harris, T.R., Bange, M.: Risk management strategies using seasonal climate forecasting in irrigated cotton production: a tale of stochastic dominance. Aust. J. Agric. Resour. 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Syst. 106, 33–45 (2012). https://doi.org/10.1016/j.agsy.2011.10.005Scott, S.L., Varian, H.R.: Predicting the present with bayesian structural time series. Available SSRN 2304426 (2013)Prudhomme, C., Shaffrey, L., Woollings, T., Jackson, C., Fowler, H., Anderson, B.: IMPETUS: Improving predictions of drought for user decision-making. International Conference on Drought: Research and Science-Policy Interfacing, 2015. pp. 273–278. CRC Press/Balkema, Centre for Ecology and Hydrology, Wallingford, Oxfordshire, United Kingdom (2015)Wiles, P., Enke, D.: A hybrid neuro-fuzzy model to forecast the Soybean complex. International Annual Conference of the American Society for Engineering Management 2015, ASEM 2015. pp. 1–5. American Society for Engineering Management, Missouri University of Science and Technology, Engineering Management and Systems Engineering Department, United States (2015)Hansen, B.G., Li, Y.: An analysis of past world market prices of feed and milk and predictions for the future. Agribusiness 33, 175–193 (2017). https://doi.org/10.1002/agr.21474Johnson, M.D., Hsieh, W.W., Cannon, A.J., Davidson, A., Bedard, F.: Crop yield forecasting on the Canadian Prairies by remotely sensed vegetation indices and machine learning methods. Agric. For. Meteorol. 218, 74–84 (2016). https://doi.org/10.1016/j.agrformet.2015.11.003Chen, J., Yang, J., Zhao, J., Xu, F., Shen, Z., Zhang, L.: Energy demand forecasting of the greenhouses using nonlinear models based on model optimized prediction method. 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Sustain. 11 (2019). https://doi.org/10.3390/su11164457Kusunose, Y., Ma, L., Van Sanford, D.: User responses to imperfect forecasts: findings from an experiment with Kentucky wheat farmers. Weather. Clim. Soc. 11, 791–808 (2019). https://doi.org/10.1175/wcas-d-18-0135.1Kadigi, I.L., et al.: Forecasting yields, prices and net returns for main cereal crops in Tanzania as probability distributions: a multivariate empirical (MVE) approach. Agric. Syst. 180 (2020). https://doi.org/10.1016/j.agsy.2019.102693McGrath, G., Rao, P.S.C., Mellander, P.-E., Kennedy, I., Rose, M., van Zwieten, L.: Real-time forecasting of pesticide concentrations in soil. Sci. Total Environ. 663, 709–717 (2019). https://doi.org/10.1016/j.scitotenv.2019.01.401Yang, B., Xie, L.: Bayesian network modelling for “direct farm” mode based agricultural supply chain risk. Ekoloji 28, 2361–2368 (2019)Zaporozhtseva, L.A., Sabetova, T. 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Modelling diverse root density dynamics and deep nitrogen uptake — a simple approach

We present a 2-D model for simulation of root density and plant nitrogen (N) uptake for crops grown in agricultural systems, based on a modification of the root density equation originally proposed by Gerwitz and Page in J Appl Ecol 11:773–781, (1974). A root system form parameter was introduced to describe the distribution of root length vertically and horizontally in the soil profile. The form parameter can vary from 0 where root density is evenly distributed through the soil profile, to 8 where practically all roots are found near the surface. The root model has other components describing root features, such as specific root length and plant N uptake kinetics. The same approach is used to distribute root length horizontally, allowing simulation of root growth and plant N uptake in row crops. The rooting depth penetration rate and depth distribution of root density were found to be the most important parameters controlling crop N uptake from deeper soil layers. The validity of the root distribution model was tested with field data for white cabbage, red beet, and leek. The model was able to simulate very different root distributions, but it was not able to simulate increasing root density with depth as seen in the experimental results for white cabbage. The model was able to simulate N depletion in different soil layers in two field studies. One included vegetable crops with very different rooting depths and the other compared effects of spring wheat and winter wheat. In both experiments variation in spring soil N availability and depth distribution was varied by the use of cover crops. This shows the model sensitivity to the form parameter value and the ability of the model to reproduce N depletion in soil layers. This work shows that the relatively simple root model developed, driven by degree days and simulated crop growth, can be used to simulate crop soil N uptake and depletion appropriately in low N input crop production systems, with a requirement of few measured parameters

Next-generation sequencing using microfluidic PCR enrichment for molecular autopsy.

BACKGROUND: We aimed to determine the mutation yield and clinical applicability of "molecular autopsy" following sudden arrhythmic death syndrome (SADS) by validating and utilizing low-cost high-throughput technologies: Fluidigm Access Array PCR-enrichment with Illumina HiSeq 2000 next generation sequencing (NGS). METHODS: We validated and optimized the NGS platform with a subset of 46 patients by comparison with Sanger sequencing of coding exons of major arrhythmia risk-genes (KCNQ1, KCNH2, SCN5A, KCNE1, KCNE2, RYR2). A combined large multi-ethnic international SADS cohort was sequenced utilizing the NGS platform to determine overall molecular yield; rare variants identified by NGS were subsequently reconfirmed by Sanger sequencing. RESULTS: The NGS platform demonstrated 100% sensitivity for pathogenic variants as well as 87.20% sensitivity and 99.99% specificity for all substitutions (optimization subset, n = 46). The positive predictive value (PPV) for NGS for rare substitutions was 16.0% (27 confirmed rare variants of 169 positive NGS calls in 151 additional cases). The overall molecular yield in 197 multi-ethnic SADS cases (mean age 22.6 ± 14.4 years, 68% male) was 5.1% (95% confidence interval 2.0-8.1%), representing 10 cases carrying pathogenic or likely pathogenic risk-mutations. CONCLUSIONS: Molecular autopsy with Fluidigm Access Array and Illumina HiSeq NGS utilizing a selected panel of LQTS/BrS and CPVT risk-genes offers moderate diagnostic yield, albeit requiring confirmatory Sanger-sequencing of mutational variants

miR-132/212 knockout mice reveal roles for these miRNAs in regulating cortical synaptic transmission and plasticity

miR-132 and miR-212 are two closely related miRNAs encoded in the same intron of a small non-coding gene, which have been suggested to play roles in both immune and neuronal function. We describe here the generation and initial characterisation of a miR-132/212 double knockout mouse. These mice were viable and fertile with no overt adverse phenotype. Analysis of innate immune responses, including TLR-induced cytokine production and IFNβ induction in response to viral infection of primary fibroblasts did not reveal any phenotype in the knockouts. In contrast, the loss of miR-132 and miR-212, while not overtly affecting neuronal morphology, did affect synaptic function. In both hippocampal and neocortical slices miR-132/212 knockout reduced basal synaptic transmission, without affecting paired-pulse facilitation. Hippocampal long-term potentiation (LTP) induced by tetanic stimulation was not affected by miR-132/212 deletion, whilst theta burst LTP was enhanced. In contrast, neocortical theta burst-induced LTP was inhibited by loss of miR-132/212. Together these results indicate that miR-132 and/or miR-212 play a significant role in synaptic function, possibly by regulating the number of postsynaptic AMPA receptors under basal conditions and during activity-dependent synaptic plasticity

Involvement of a Natural Fusion of a Cytochrome P450 and a Hydrolase in Mycophenolic Acid Biosynthesis

Mycophenolic acid (MPA) is a fungal secondary metabolite and the active component in several immunosuppressive pharmaceuticals. The gene cluster coding for the MPA biosynthetic pathway has recently been discovered in Penicillium brevicompactum, demonstrating that the first step is catalyzed by MpaC, a polyketide synthase producing 5-methylorsellinic acid (5-MOA). However, the biochemical role of the enzymes encoded by the remaining genes in the MPA gene cluster is still unknown. Based on bioinformatic analysis of the MPA gene cluster, we hypothesized that the step following 5-MOA production in the pathway is carried out by a natural fusion enzyme MpaDE, consisting of a cytochrome P450 (MpaD) in the N-terminal region and a hydrolase (MpaE) in the C-terminal region. We verified that the fusion gene is indeed expressed in P. brevicompactum by obtaining full-length sequence of the mpaDE cDNA prepared from the extracted RNA. Heterologous coexpression of mpaC and the fusion gene mpaDE in the MPA-nonproducer Aspergillus nidulans resulted in the production of 5,7-dihydroxy-4-methylphthalide (DHMP), the second intermediate in MPA biosynthesis. Analysis of the strain coexpressing mpaC and the mpaD part of mpaDE shows that the P450 catalyzes hydroxylation of 5-MOA to 4,6-dihydroxy-2-(hydroxymethyl)-3-methylbenzoic acid (DHMB). DHMB is then converted to DHMP, and our results suggest that the hydrolase domain aids this second step by acting as a lactone synthase that catalyzes the ring closure. Overall, the chimeric enzyme MpaDE provides insight into the genetic organization of the MPA biosynthesis pathway

Evolutionary and pulsational properties of white dwarf stars

Abridged. White dwarf stars are the final evolutionary stage of the vast majority of stars, including our Sun. The study of white dwarfs has potential applications to different fields of astrophysics. In particular, they can be used as independent reliable cosmic clocks, and can also provide valuable information about the fundamental parameters of a wide variety of stellar populations, like our Galaxy and open and globular clusters. In addition, the high densities and temperatures characterizing white dwarfs allow to use these stars as cosmic laboratories for studying physical processes under extreme conditions that cannot be achieved in terrestrial laboratories. They can be used to constrain fundamental properties of elementary particles such as axions and neutrinos, and to study problems related to the variation of fundamental constants. In this work, we review the essentials of the physics of white dwarf stars. Special emphasis is placed on the physical processes that lead to the formation of white dwarfs as well as on the different energy sources and processes responsible for chemical abundance changes that occur along their evolution. Moreover, in the course of their lives, white dwarfs cross different pulsational instability strips. The existence of these instability strips provides astronomers with an unique opportunity to peer into their internal structure that would otherwise remain hidden from observers. We will show that this allows to measure with unprecedented precision the stellar masses and to infer their envelope thicknesses, to probe the core chemical stratification, and to detect rotation rates and magnetic fields. Consequently, in this work, we also review the pulsational properties of white dwarfs and the most recent applications of white dwarf asteroseismology.Comment: 85 pages, 28 figures. To be published in The Astronomy and Astrophysics Revie