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Erythrina velutina is a Brazilian native tree of the Caatinga (a unique semiarid biome). It is widely used in traditional medicine showing anti-inflammatory and central nervous system modulating activities. The species is a rich source of specialized metabolites, mostly alkaloids and flavonoids. To date, genomic information, biosynthesis, and regulation of flavonoids remain unknown in this woody plant. As part of a larger ongoing research goal to better understand specialized metabolism in plants inhabiting the harsh conditions of the Caatinga, the present study focused on this important class of bioactive phenolics. Leaves and seeds of plants growing in their natural habitat had their metabolic and proteomic profiles analyzed and integrated with transcriptome data. As a result, 96 metabolites (including 43 flavonoids) were annotated. Transcripts of the flavonoid pathway totaled 27, of which EvCHI, EvCHR, EvCHS, EvCYP75A and EvCYP75B1 were identified as putative main targets for modulating the accumulation of these metabolites. The highest correspondence of mRNA vs. protein was observed in the differentially expressed transcripts. In addition, 394 candidate transcripts encoding for transcription factors distributed among the bHLH, ERF, and MYB families were annotated. Based on interaction network analyses, several putative genes of the flavonoid pathway and transcription factors were related, particularly TFs of the MYB family. Expression patterns of transcripts involved in flavonoid biosynthesis and those involved in responses to biotic and abiotic stresses were discussed in detail. Overall, these findings provide a base for the understanding of molecular and metabolic responses in this medicinally important species. Moreover, the identification of key regulatory targets for future studies aiming at bioactive metabolite production will be facilitated., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Chacon, Santos, Bonilauri, Vilasboa, da Costa, da Silva, Torres, de Araújo, Roque, Pilon, Selegatto, Freire, Reginaldo, Voigt, Zuanazzi, Scortecci, Cavalheiro, Lopes, Ferreira, Santos, Fontes, Sousa, Carvalho, Fett-Neto and Giordani.)

To evaluate the diagnostic accuracy of caries and periapical lesions on a monitor with and without DICOM part 14: grayscale standard display function (DICOM-GSDF) calibration under different ambient light conditions. Forty digital bitewing radiographs were selected, with or without radiographic images of carious lesions and forty digital periapical radiographs with or without periapical lesions were selected from archives of the Radiology Department at the University Hospital of the Federal University of Sergipe. The gold standard radiographic images were determined through consensus between two radiologists with more than 15 and 30 years of experience. The selected radiographs were evaluated on a LG LED monitor with and without DICOM-GSDF calibration under different ambient light conditions: Lx1 (low ambient lighting), Lx2 (moderate ambient lighting) and Lx3 (high ambient lighting). Kappa (K w ) values determined that evaluator 1 showed almost perfect agreement for all devices, while evaluator 2 presented a substantial agreement for all devices. Monitors with and without DICOM-GSDF calibration have similar accuracy values. The three ambient light conditions analyzed have similar accuracy and can be used for caries lesions diagnosis (p > 0.05); however, the best diagnostic accuracy of periapical lesions was found in Lx 2. The displays with and without DICOM-GSDF calibration studied in this research have similar accuracy and can be used to evaluate digital radiographs without changing the diagnostic capacity. The different ambient lighting conditions did not influence the evaluation of caries lesions. The best diagnostic accuracy of periapical lesions was found in moderate ambient lighting., (© 2022. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.)

Introduction: Natural products of pharmaceutical interest often do not reach the drug market due to the associated low yields and difficult extraction. Knowledge of biosynthetic pathways is a key element in the development of biotechnological strategies for plant specialized metabolite production. Erythrina species are mainly used as central nervous system depressants in folk medicine and are important sources of bioactive tetracyclic benzylisoquinoline alkaloids (BIAs), which can act on several pathology-related biological targets., Objectives: In this sense, in an unprecedented approach used with a non-model Fabaceae species grown in its unique arid natural habitat, a combined transcriptome and metabolome analyses (seeds and leaves) is presented., Methods: The Next Generation Sequencing-based transcriptome ( de novo RNA sequencing) was carried out in a NextSeq 500 platform. Regarding metabolite profiling, the High-resolution Liquid Chromatography was coupled to DAD and a micrOTOF-QII mass spectrometer by using electrospray ionization (ESI) and Time of Flight (TOF) analyzer. The tandem MS/MS data were processed and analyzed through Molecular Networking approach., Results: This detailed macro and micromolecular approach applied to seeds and leaves of E. velutina revealed 42 alkaloids, several of them unique. Based on the combined evidence, 24 gene candidates were put together in a putative pathway leading to the singular alkaloid diversity of this species., Conclusion: Overall, these results could contribute by indicating potential biotechnological targets for modulation of erythrina alkaloids biosynthesis as well as improve molecular databases with omic data from a non-model medicinal plant, and reveal an interesting chemical diversity of Erythrina BIA harvested in Caatinga., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Authors. Published by Elsevier B.V. on behalf of Cairo University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

Commercial printers based on fused deposition modeling (FDM) are widely adopted for 3D printing applications. This method consists of the heating of polymeric filaments over the melting point followed by their deposition onto a solid base to create the desirable 3D structure. Prior investigation using chromatographic techniques has shown that chemical compounds (e.g. VOCs), which can be harmful to users, are emitted during the printing process, producing adverse effects to human health and contributing to indoor air pollution. In this study, we present a simple, inexpensive and disposable paper-based optoelectronic nose (i.e. colorimetric sensor array) to identify the gaseous emission fingerprint of five different types of thermoplastic filaments (ABS, TPU, PETG, TRITAN and PLA) in the indoor environment. The optoelectronic nose is comprised of selected 15 dyes with different chemical properties deposited onto a microfluidic paper-based device with spots of 5 mm in diameter each. Digital images were obtained from an ordinary flatbed scanner, and the RGB information collected before and after air exposure was extracted by using an automated routine designed in MATLAB, in which the color changes provide a unique fingerprint for each filament in 5 min of printing. Reproducibility was obtained in the range of 2.5-10% (RSD). Hierarchical clustering analysis (HCA) and principal component analysis (PCA) were successfully employed, showing suitable discrimination of all studied filaments and the non-polluted air. Besides, air spiked with vapors of the most representative VOCs were analyzed by the optoelectronic nose and visually compared to each filament. The described study shows the potential of the paper-based optoelectronic nose to monitor possible hazard emissions from 3D printers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Taurine is one of the most abundant amino acids in mammalian tissues. It is obtained from the diet and by de novo synthesis from cysteic acid or hypotaurine. Despite the discovery in 1954 that the oxygenation of hypotaurine produces taurine, the identification of an enzyme catalyzing this reaction has remained elusive. In large part, this is due to the incorrect assignment, in 1962, of the enzyme as an NAD-dependent hypotaurine dehydrogenase. For more than 55 years, the literature has continued to refer to this enzyme as such. Here we show, both in vivo and in vitro, that the enzyme that oxygenates hypotaurine to produce taurine is flavin-containing monooxygenase (FMO) 1. Metabolite analysis of the urine of Fmo1 -null mice by 1 H NMR spectroscopy revealed a buildup of hypotaurine and a deficit of taurine in comparison with the concentrations of these compounds in the urine of wild-type mice. In vitro assays confirmed that human FMO1 catalyzes the conversion of hypotaurine to taurine, utilizing either NADPH or NADH as cofactor. FMO1 has a wide substrate range and is best known as a xenobiotic- or drug-metabolizing enzyme. The identification that the endogenous molecule hypotaurine is a substrate for the FMO1-catalyzed production of taurine resolves a long-standing mystery. This finding should help establish the role FMO1 plays in a range of biologic processes in which taurine or its deficiency is implicated, including conjugation of bile acids, neurotransmitter, antioxidant and anti-inflammatory functions, and the pathogenesis of obesity and skeletal muscle disorders. SIGNIFICANCE STATEMENT: The identity of the enzyme that catalyzes the biosynthesis of taurine from hypotaurine has remained elusive. Here we show, both in vivo and in vitro, that flavin-containing monooxygenase 1 catalyzes the oxygenation of hypotaurine to produce taurine., (Copyright © 2020 by The American Society for Pharmacology and Experimental Therapeutics.)

Traditionally, the screening of metabolites in microbial matrices is performed by monocultures. Nonetheless, the absence of biotic and abiotic interactions generally observed in nature still limit the chemical diversity and leads to "poorer" chemical profiles. Nowadays, several methods have been developed to determine the conditions under which cryptic genes are activated, in an attempt to induce these silenced biosynthetic pathways. Among those, the one strain, many compounds (OSMAC) strategy has been applied to enhance metabolic production by a systematic variation of growth parameters. The complexity of the chemical profiles from OSMAC experiments has required increasingly robust and accurate techniques. In this sense, deconvolution-based 1 HNMR quantification have emerged as a promising methodology to decrease complexity and provide a comprehensive perspective for metabolomics studies. Our present work shows an integrated strategy for the increased production and rapid quantification of compounds from microbial sources. Specifically, an OSMAC design of experiments (DoE) was used to optimize the microbial production of bioactive fusaric acid, cytochalasin D and 3-nitropropionic acid, and Global Spectral Deconvolution (GSD)-based 1 HNMR quantification was carried out for their measurement. The results showed that OSMAC increased the production of the metabolites by up to 33% and that GSD was able to extract accurate NMR integrals even in heavily coalescence spectral regions. Moreover, GSD- 1 HNMR quantification was reproducible for all species and exhibited validated results that were more selective and accurate than comparative methods. Overall, this strategy up-regulated important metabolites using a reduced number of experiments and provided fast analyte monitor directly in raw extracts., (© 2019 John Wiley & Sons, Ltd.)

Introduction: The increase in multidrug resistance and lack of efficacy in malaria therapy has propelled the urgent discovery of new antiplasmodial drugs, reviving the screening of secondary metabolites from traditional medicine. In plant metabolomics, NMR-based strategies are considered a golden method providing both a holistic view of the chemical profiles and a correlation between the metabolome and bioactivity, becoming a corner stone of drug development from natural products., Objective: Create a multivariate model to identify antiplasmodial metabolites from 1 H NMR data of two African medicinal plants, Keetia leucantha and K. venosa., Methods: The extracts of twigs and leaves of Keetia species were measured by 1 H NMR and the spectra were submitted to orthogonal partial least squares (OPLS) for antiplasmodial correlation., Results: Unsupervised 1 H NMR analysis showed that the effect of tissues was higher than species and that triterpenoids signals were more associated to Keetia twigs than leaves. OPLS-DA based on Keetia species correlated triterpene signals to K. leucantha, exhibiting a higher concentration of triterpenoids and phenylpropanoid-conjugated triterpenes than K. venosa. In vitro antiplasmodial correlation by OPLS, validated for all Keetia samples, revealed that phenylpropanoid-conjugated triterpenes were highly correlated to the bioactivity, while the acyclic squalene was found as the major metabolite in low bioactivity samples., Conclusion: NMR-based metabolomics combined with supervised multivariate data analysis is a powerful strategy for the identification of bioactive metabolites in plant extracts. Moreover, combination of statistical total correlation spectroscopy with 2D NMR allowed a detailed analysis of different triterpenes, overcoming the challenge posed by their structure similarity and coalescence in the aliphatic region.

The intrinsic value of biodiversity extends beyond species diversity, genetic heritage, ecosystem variability and ecological services, such as climate regulation, water quality, nutrient cycling and the provision of reproductive habitats it is also an inexhaustible source of molecules and products beneficial to human well-being. To uncover the chemistry of Brazilian natural products, the Nuclei of Bioassays, Ecophysiology and Biosynthesis of Natural Products Database (NuBBE DB ) was created as the first natural product library from Brazilian biodiversity. Since its launch in 2013, the NuBBE DB has proven to be an important resource for new drug design and dereplication studies. Consequently, continuous efforts have been made to expand its contents and include a greater diversity of natural sources to establish it as a comprehensive compendium of available biogeochemical information about Brazilian biodiversity. The content in the NuBBE DB is freely accessible online (https://nubbe.iq.unesp.br/portal/nubbedb.html) and provides validated multidisciplinary information, chemical descriptors, species sources, geographic locations, spectroscopic data (NMR) and pharmacological properties. Herein, we report the latest advancements concerning the interface, content and functionality of the NuBBE DB . We also present a preliminary study on the current profile of the compounds present in Brazilian territory.

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts.

A major challenge in metabolomic studies is how to extract and analyze an entire metabolome. So far, no single method was able to clearly complete this task in an efficient and reproducible way. In this work we proposed a sequential strategy for the extraction and chromatographic separation of metabolites from leaves Jatropha gossypifolia using a design of experiments and partial least square model. The effect of 14 different solvents on extraction process was evaluated and an optimized separation condition on liquid chromatography was estimated considering mobile phase composition and analysis time. The initial conditions of extraction using methanol and separation in 30 min between 5 and 100% water/methanol (1:1 v/v) with 0.1% of acetic acid, 20 μL sample volume, 3.0 mL min(-1) flow rate and 25°C column temperature led to 107 chromatographic peaks. After the optimization strategy using i-propanol/chloroform (1:1 v/v) for extraction, linear gradient elution of 60 min between 5 and 100% water/(acetonitrile/methanol 68:32 v/v with 0.1% of acetic acid), 30 μL sample volume, 2.0 mL min(-1) flow rate, and 30°C column temperature, we detected 140 chromatographic peaks, 30.84% more peaks compared to initial method. This is a reliable strategy using a limited number of experiments for metabolomics protocols., (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The bicritical properties of the three-dimensional classical anisotropic Heisenberg model in a crystal field are investigated through extensive Monte Carlo simulations on a simple cubic lattice, using Metropolis and Wolff algorithms. Field-mixing and multidimensional histogram techniques were employed in order to compute the probability distribution function of the extensive conjugate variables of interest and, using finite-size scaling analysis, the first-order transition line of the model was precisely located. The fourth-order cumulant of the order parameter was then calculated along this line and the bicritical point located with good precision from the cumulant crossings. The bicritical properties of this point were further investigated through the measurement of the universal probability distribution function of the order parameter. The results lead us to conclude that the studied bicritical point belongs in fact to the three-dimensional Heisenberg universality class.

A version of the Vector Blume-Emery-Griffiths model with three-dimensional spins was studied on a simple cubic lattice by Monte Carlo simulations. We obtained the phase diagram, which reproduces, for a range of the parameters of the model, the topology of the one observed for bulk mixtures of 3He--4He. The phase diagram displays a superfluid, 4He-rich phase which undergoes a phase transition to a normal phase. This transition is first or second order, depending on the region of the phase diagram examined. One of the main features of this diagram is the existence of a tricritical point, which, for some values of the parameters of the model, decomposes into a critical endpoint and a double critical endpoint. These points were located with reasonable precision. This study provides the basis for the subsequent study of dynamic properties of 3He--4He mixtures.

Using a single microscope objective lens to optically trap, illuminate, and collect backscattered light of a dielectric microsphere, we measure the temporal-intensity-autocorrelation functions (ACFs), and intensity profiles to obtain the trap stiffness and friction coefficient of the bead. This is an interesting study of an harmonically bound Brownian particle, with nanometer resolution. We extend the work of Bar-Ziv et al. [Phys. Rev. Lett. 78, 154 (1997)] to more general situations allowing for the use of our simpler geometry in other applications. As examples, we present measurements of the parallel Stokes friction coefficient on the trapped bead as a function of its distance from a surface and the entropic force of a single lambda-DNA molecule.

Hydrolysis of D-valyl-L-leucyl-L-arginine p-nitroanilide (D-Val-Leu-Arg-Nan) at five different concentrations (10-20 microM) by human urinary kallikrein was studied in the absence and in the presence of increasing concentrations of basic pancreatic trypsin inhibitor (BPTI) (1.35-9.15 nM). The data indicate that the inhibition of human urinary kallikrein by BPTI is not a simple competitive inhibition as reported by others, but that it is a competitive inhibition of the parabolic type, with two inhibitor molecules binding to one enzyme molecule, with the formation of a ternary enzymatic complex. Statistical analysis of the experimental data supports the kinetic model proposed. The calculated values of the constants Ki and Kii were 16.20 nM and 1.10 nM, respectively. It is noteworthy that the Kii < Ki, i.e., the second BPTI molecule binds to the enzyme with a larger affinity suggesting that this second binding site was probably created or positively modulated as a consequence of the binding of the first BPTI molecule.