cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5634934.v1
title: Vitamin D3 levels and NLRP3 expression in murine models of obese asthma: association with asthma outcomes

description: Vitamin D (25(OH)D3) is an essential nutrient that plays a role in the immune system. Serum 25(OH)D3 is found to be associated with asthma. However, the role of vitamin D in obese asthma remains unclear. Therefore, we investigated the association between vitamin D levels and asthma outcomes in a murine model of obese asthma. We also evaluated NLRP3 inflammasome activity in the pathogenesis of obese asthma. We divided 20 male Balb/c mice (3–4 weeks old) into 4 groups: normal control, asthma, obese, and obese asthma and developed an obese asthma mouse model. Airway hyperreactivity, cytokine concentrations, 25(OH)D3 levels, NLRP3 mRNA and IL-1β mRNA expressions were measured. Lung histology and bronchoalveolar lavage fluid (BALF) cell count were also determined. Obese asthma mice showed a significant increase in airway hyper-responsiveness, airway inflammation, pro-inflammatory cytokine levels and NLRP3 mRNA, IL-1β mRNA expression. Both asthma and obese groups had lower 25(OH)D3 levels. Vitamin D levels in obese asthma were the lowest among all groups. Vitamin D levels correlated negatively with body weight, lung resistance levels at 25 mg/mL of methacholine, total inflammatory cells, and IL-1β and IL-17 concentrations in BALF. These data demonstrated an association between serum vitamin D levels and outcomes of obese asthma, and indicated that NLRP3 inflammasome may play a role in this disorder.
DOI: 10.6084/m9.figshare.5634931
title: PREDICTION OF CONTENTS OF PHENOLIC COMPOUNDS AND FLAVONOIDS IN AERIAL PART OF Secale cereale L. Avena strigosa L. and Raphanus sativus L. WITH NEAR INFRARED SPECTROSCOPY (NIR)

description: Spectroscopy associated with chemometrics is a non-destructive method of the samples for the prediction of phenolic compounds. The objective of the work was to apply the near infrared spectroscopy (NIR) technique for the prediction of phenolic compounds and flavonoids in aerial part samples of cover crops plants Raphanus sativus L., Secale cereale L. and Avena strigosa L. Samples were collected at 60, 80 and 100 days after sowing (DAS) of the plants and, after lodging (DAA), at 15 and 30 days, in an experiment implanted in the field, in the city of Ituporanga, Santa Catarina. The samples were homogenized, identified, transported on dry ice, lyophilized, crushed, sieved and stored at -20 °C for analysis. For the calibration, 84 samples were used and for the validation 10 samples. The combination of NIR spectroscopy and multivariate analysis by partial least squares regression allowed the development of prediction models of phenolics and flavonoids with associated errors averaging 10%. NIR spectroscopy is recommended for the development of calibration models because it allows to non-destructive infer phenolic and total flavonoid contents, with high analytical frequency, without the use of reagents and other inputs required by the reference method, with results very close to those obtained in the laboratory.
DOI: 10.6084/m9.figshare.5634931.v1
title: PREDICTION OF CONTENTS OF PHENOLIC COMPOUNDS AND FLAVONOIDS IN AERIAL PART OF Secale cereale L. Avena strigosa L. and Raphanus sativus L. WITH NEAR INFRARED SPECTROSCOPY (NIR)

description: Spectroscopy associated with chemometrics is a non-destructive method of the samples for the prediction of phenolic compounds. The objective of the work was to apply the near infrared spectroscopy (NIR) technique for the prediction of phenolic compounds and flavonoids in aerial part samples of cover crops plants Raphanus sativus L., Secale cereale L. and Avena strigosa L. Samples were collected at 60, 80 and 100 days after sowing (DAS) of the plants and, after lodging (DAA), at 15 and 30 days, in an experiment implanted in the field, in the city of Ituporanga, Santa Catarina. The samples were homogenized, identified, transported on dry ice, lyophilized, crushed, sieved and stored at -20 °C for analysis. For the calibration, 84 samples were used and for the validation 10 samples. The combination of NIR spectroscopy and multivariate analysis by partial least squares regression allowed the development of prediction models of phenolics and flavonoids with associated errors averaging 10%. NIR spectroscopy is recommended for the development of calibration models because it allows to non-destructive infer phenolic and total flavonoid contents, with high analytical frequency, without the use of reagents and other inputs required by the reference method, with results very close to those obtained in the laboratory.
DOI: 10.6084/m9.figshare.5634928
title: Presumed Zika virus-related congenital brain malformations: the spectrum of CT and MRI findings in fetuses and newborns

description: ABSTRACT The new epidemic of Zika virus infection raises grave concerns, especially with the increasingly-recognized link between emerging cases of microcephaly and this infectious disease. Besides small cranial dimensions, there are striking morphologic anomalies in the fetal brain. Key anomalies include cortical developmental malformations and a peculiar distribution of pathologic calcifications. These potentially indicate a new pattern of congenital central nervous system infection. Methods: Eight women underwent fetal MRI. Four infants also underwent postnatal CT. Five of the women underwent amniocentesis. Results: All neonates were born with microcephaly. On fetal MRI, ventriculomegaly, marked reduction of white matter thickness, severe sylvian fissure simplification, abnormal sulcation, and diffuse volumetric loss of cerebellar hemispheres were consistently seen. On postnatal CT, diffuse subcortical and basal ganglia calcifications were observed. The Zika virus was detected in two amniocenteses by polymerase chain reaction assays. Conclusion: We hope to assist the medical community in recognizing the spectrum of encephalic changes related to congenital Zika virus infection.
DOI: 10.6084/m9.figshare.5634928.v1
title: Presumed Zika virus-related congenital brain malformations: the spectrum of CT and MRI findings in fetuses and newborns

description: ABSTRACT The new epidemic of Zika virus infection raises grave concerns, especially with the increasingly-recognized link between emerging cases of microcephaly and this infectious disease. Besides small cranial dimensions, there are striking morphologic anomalies in the fetal brain. Key anomalies include cortical developmental malformations and a peculiar distribution of pathologic calcifications. These potentially indicate a new pattern of congenital central nervous system infection. Methods: Eight women underwent fetal MRI. Four infants also underwent postnatal CT. Five of the women underwent amniocentesis. Results: All neonates were born with microcephaly. On fetal MRI, ventriculomegaly, marked reduction of white matter thickness, severe sylvian fissure simplification, abnormal sulcation, and diffuse volumetric loss of cerebellar hemispheres were consistently seen. On postnatal CT, diffuse subcortical and basal ganglia calcifications were observed. The Zika virus was detected in two amniocenteses by polymerase chain reaction assays. Conclusion: We hope to assist the medical community in recognizing the spectrum of encephalic changes related to congenital Zika virus infection.
DOI: 10.6084/m9.figshare.5634925
title: Genome-wide association for mapping QTLs linked to protein and oil contents in soybean

description: Abstract: The objective of this work was to identify single-nucleotide polymorphism (SNP) markers linked with quantitative trait loci (QTLs) associated with increased contents of protein and oil in soybean. A total of 169 Brazilian soybean varieties, genotyped with 6,000 SNP markers, were evaluated. Protein and oil contents were obtained with the near-infrared reflectance method. Correlation and multiple linear regression analyses were used to identify linkage disequilibrium between SNP markers and the QTLs associated with the two characteristics. Seven QTLs were found to be associated with protein content, on six chromosomes (2, 6, 11, 12, 13, and 16), explaining 60.9% of the variation in this trait. For oil content, eight QTLs were identified on six chromosomes (1, 4, 5, 6, 17, and 19), explaining 78.3% of the variation in the trait. The correlation between the number of loci containing favorable alleles and the evaluated characteristics was 0.49 for protein content and 0.60 for oil content. The molecular markers identified are mapped in genomic regions containing QTLs previously mapped for both characteristics, which reinforces the association between these regions and the genetic control of oil and protein contents in soybean.
DOI: 10.6084/m9.figshare.5634925.v1
title: Genome-wide association for mapping QTLs linked to protein and oil contents in soybean

description: Abstract: The objective of this work was to identify single-nucleotide polymorphism (SNP) markers linked with quantitative trait loci (QTLs) associated with increased contents of protein and oil in soybean. A total of 169 Brazilian soybean varieties, genotyped with 6,000 SNP markers, were evaluated. Protein and oil contents were obtained with the near-infrared reflectance method. Correlation and multiple linear regression analyses were used to identify linkage disequilibrium between SNP markers and the QTLs associated with the two characteristics. Seven QTLs were found to be associated with protein content, on six chromosomes (2, 6, 11, 12, 13, and 16), explaining 60.9% of the variation in this trait. For oil content, eight QTLs were identified on six chromosomes (1, 4, 5, 6, 17, and 19), explaining 78.3% of the variation in the trait. The correlation between the number of loci containing favorable alleles and the evaluated characteristics was 0.49 for protein content and 0.60 for oil content. The molecular markers identified are mapped in genomic regions containing QTLs previously mapped for both characteristics, which reinforces the association between these regions and the genetic control of oil and protein contents in soybean.
DOI: 10.6084/m9.figshare.5634922
title: Straw production and agronomic performance of soybean intercropped with forage species in no-tillage system

description: Abstract: The objective of this work was to evaluate the straw production and the agronomic performance of soybean intercropped with oversown forage species, in no-tillage system. A randomized complete block design was carried out with four replicates, in a 5×2+2 factorial arrangement, as follows: five forage species - Urochloa brizantha 'Marandu', Urochloa ruziziensis, Panicum maximum 'Mombaça', Panicum maximum 'Massai', and Pennisetum americanum -, intercropped with soybean over two crop years (2013/2014 and 2014/2015), plus two controls, with P. americanum sowed in succession to soybean or with soybean monocropping followed by winter fallow (traditional cultivation). Soybean yield components and forage straw yield were evaluated. None of the intercropping systems reduced soybean grain yield, compared with monocropped soybean. The oversown species can significantly improve soybean productivity, as is the case for soybean intercropped with P.maximum 'Mombaça', compared with soybean monocropping, followed or not by millet. Panicum maximum 'Mombaça' is the most effective forage species for dry matter accumulation in the fall/spring period.
DOI: 10.6084/m9.figshare.5634922.v1
title: Straw production and agronomic performance of soybean intercropped with forage species in no-tillage system

description: Abstract: The objective of this work was to evaluate the straw production and the agronomic performance of soybean intercropped with oversown forage species, in no-tillage system. A randomized complete block design was carried out with four replicates, in a 5×2+2 factorial arrangement, as follows: five forage species - Urochloa brizantha 'Marandu', Urochloa ruziziensis, Panicum maximum 'Mombaça', Panicum maximum 'Massai', and Pennisetum americanum -, intercropped with soybean over two crop years (2013/2014 and 2014/2015), plus two controls, with P. americanum sowed in succession to soybean or with soybean monocropping followed by winter fallow (traditional cultivation). Soybean yield components and forage straw yield were evaluated. None of the intercropping systems reduced soybean grain yield, compared with monocropped soybean. The oversown species can significantly improve soybean productivity, as is the case for soybean intercropped with P.maximum 'Mombaça', compared with soybean monocropping, followed or not by millet. Panicum maximum 'Mombaça' is the most effective forage species for dry matter accumulation in the fall/spring period.
DOI: 10.6084/m9.figshare.5634919
title: Agronomic performance of 'Cabernet Sauvignon' with leaf removal management in a high-altitude region of Southern Brazil

description: Abstract: The objective of this work was to compare the effect of different times of leaf removal on the vegetative-productive efficiency and on the chemical and physical characteristics of 'Cabernet Sauvignon' clusters in a high-altitude region of the state of Santa Catarina, Brazil. The experiment was conducted in the 2015 and 2016 vintages, in a commercial vineyard, located in the municipality of São Joaquim, in the state of Santa Catarina, at 1,230-m altitude. The treatments consisted of different times leaf removal in the cluster zone, in the following phenological stages: full bloom, buckshot berries, pea-sized berries, veraison, and 15 days after veraison, besides a control without leaf removal. The evaluated variables were subjected to the analysis of variance and compared with the Scott-Knott test, at 5% probability. In a high-altitude region, leaf removal provides more adequate indices for plant vegetative:yield balance. It also increases yield when performed during the pea-sized berry and veraison stages, increases the fertility index when performed during the pea-sized berry stage, and improves the chemical composition of 'Cabernet Sauvignon' grape when performed up to the pea-sized berry stage. The obtained results show the importance of early leaf removal to obtain must with potential for the production of quality wines.
DOI: 10.6084/m9.figshare.5634919.v1
title: Agronomic performance of 'Cabernet Sauvignon' with leaf removal management in a high-altitude region of Southern Brazil

description: Abstract: The objective of this work was to compare the effect of different times of leaf removal on the vegetative-productive efficiency and on the chemical and physical characteristics of 'Cabernet Sauvignon' clusters in a high-altitude region of the state of Santa Catarina, Brazil. The experiment was conducted in the 2015 and 2016 vintages, in a commercial vineyard, located in the municipality of São Joaquim, in the state of Santa Catarina, at 1,230-m altitude. The treatments consisted of different times leaf removal in the cluster zone, in the following phenological stages: full bloom, buckshot berries, pea-sized berries, veraison, and 15 days after veraison, besides a control without leaf removal. The evaluated variables were subjected to the analysis of variance and compared with the Scott-Knott test, at 5% probability. In a high-altitude region, leaf removal provides more adequate indices for plant vegetative:yield balance. It also increases yield when performed during the pea-sized berry and veraison stages, increases the fertility index when performed during the pea-sized berry stage, and improves the chemical composition of 'Cabernet Sauvignon' grape when performed up to the pea-sized berry stage. The obtained results show the importance of early leaf removal to obtain must with potential for the production of quality wines.
DOI: 10.6084/m9.figshare.5634916
title: BAMLSS: Bayesian Additive Models for Location, Scale, and Shape (and Beyond)

description: Bayesian analysis provides a convenient setting for the estimation of complex generalized additive regression models (GAMs). Since computational power has tremendously increased in the past decade, it is now possible to tackle complicated inferential problems, for example, with Markov chain Monte Carlo simulation, on virtually any modern computer. This is one of the reasons why Bayesian methods have become increasingly popular, leading to a number of highly specialized and optimized estimation engines and with attention shifting from conditional mean models to probabilistic distributional models capturing location, scale, shape (and other aspects) of the response distribution. To embed many different approaches suggested in literature and software, a unified modeling architecture for distributional GAMs is established that exploits distributions, estimation techniques (posterior mode or posterior mean), and model terms (fixed, random, smooth, spatial,…). It is shown that within this framework implementing algorithms for complex regression problems, as well as the integration of already existing software, is relatively straightforward. The usefulness is emphasized with two complex and computationally demanding application case studies: a large daily precipitation climatology, as well as a Cox model for continuous time with space-time interactions. Supplementary material for this article is available online.
DOI: 10.6084/m9.figshare.5634916.v2
title: BAMLSS: Bayesian Additive Models for Location, Scale, and Shape (and Beyond)

description: Bayesian analysis provides a convenient setting for the estimation of complex generalized additive regression models (GAMs). Since computational power has tremendously increased in the past decade, it is now possible to tackle complicated inferential problems, for example, with Markov chain Monte Carlo simulation, on virtually any modern computer. This is one of the reasons why Bayesian methods have become increasingly popular, leading to a number of highly specialized and optimized estimation engines and with attention shifting from conditional mean models to probabilistic distributional models capturing location, scale, shape (and other aspects) of the response distribution. To embed many different approaches suggested in literature and software, a unified modeling architecture for distributional GAMs is established that exploits distributions, estimation techniques (posterior mode or posterior mean), and model terms (fixed, random, smooth, spatial,…). It is shown that within this framework implementing algorithms for complex regression problems, as well as the integration of already existing software, is relatively straightforward. The usefulness is emphasized with two complex and computationally demanding application case studies: a large daily precipitation climatology, as well as a Cox model for continuous time with space-time interactions. Supplementary material for this article is available online.
DOI: 10.6084/m9.figshare.5634916.v1
title: BAMLSS: Bayesian Additive Models for Location, Scale and Shape (and Beyond)

description: Bayesian analysis provides a convenient setting for the estimation of complex generalized additive regression models (GAMs). Since computational power has tremendously increased in the past decade it is now possible to tackle complicated inferential problems, e.g., with Markov chain Monte Carlo simulation, on virtually any modern computer. This is one of the reasons why Bayesian methods have become increasingly popular, leading to a number of highly specialized and optimized estimation engines and with attention shifting from conditional mean models to probabilistic distributional models capturing location, scale, shape (and other aspects) of the response distribution. In order to embed many different approaches suggested in literature and software, a unified modeling architecture for distributional GAMs is established that exploits distributions, estimation techniques (posterior mode or posterior mean), and model terms (fixed, random, smooth, spatial, …). It is shown that within this framework implementing algorithms for complex regression problems, as well as the integration of already existing software, is relatively straightforward. The usefulness is emphasized with two complex and computationally demanding application case studies: a large daily precipitation climatology, as well as a Cox model for continuous time with space-time interactions.
DOI: 10.6084/m9.figshare.5634910
title: A novel de novo COL1A1 mutation in a Thai boy with osteogenesis imperfecta born to consanguineous parents

description: Abstract Osteogenesis imperfecta (OI) is genetically heterogeneous. Mutations in COL1A1 and COL1A2 are responsible for at least 90% of the cases, which are transmitted in an autosomal dominant manner or are de novo events. We identified a Thai boy with OI whose parents were first cousins. Because the proband was the product of a consanguineous marriage, we hypothesized that he might be homozygous for a mutation in a known gene causing a recessive form of OI. Using whole exome sequencing (WES), we did not find any pathogenic mutations in any known gene responsible for an autosomal recessive form of OI. Instead, we identified a COL1A1 frameshift mutation, c.1290delG (p.Gly431Valfs*110) in heterozygosis. By Sanger sequencing, the mutation was confirmed in the proband, and not detected in his parents, indicating that it was a de novo mutation. These findings had implication for genetic counseling. In conclusion, we expanded the mutational spectrum of COL1A1 and provided another example of a de novo pathogenic mutation in heterozygosis in a patient born to consanguineous parents.
DOI: 10.6084/m9.figshare.5634910.v1
title: A novel de novo COL1A1 mutation in a Thai boy with osteogenesis imperfecta born to consanguineous parents

description: Abstract Osteogenesis imperfecta (OI) is genetically heterogeneous. Mutations in COL1A1 and COL1A2 are responsible for at least 90% of the cases, which are transmitted in an autosomal dominant manner or are de novo events. We identified a Thai boy with OI whose parents were first cousins. Because the proband was the product of a consanguineous marriage, we hypothesized that he might be homozygous for a mutation in a known gene causing a recessive form of OI. Using whole exome sequencing (WES), we did not find any pathogenic mutations in any known gene responsible for an autosomal recessive form of OI. Instead, we identified a COL1A1 frameshift mutation, c.1290delG (p.Gly431Valfs*110) in heterozygosis. By Sanger sequencing, the mutation was confirmed in the proband, and not detected in his parents, indicating that it was a de novo mutation. These findings had implication for genetic counseling. In conclusion, we expanded the mutational spectrum of COL1A1 and provided another example of a de novo pathogenic mutation in heterozygosis in a patient born to consanguineous parents.
DOI: 10.6084/m9.figshare.5634901
title: ELEMENTARY CHARACTERIZATION OF RICE HUSK AND THEIR ASHES BY MIP OES AFTER ACID DECOMPOSITION WITH REFLUX SYSTEM

description: This paper describes the optimization of a sample preparation method using response surface methodology for Al, Cd, Cu, Fe, Mg, Mn, Mo, Na, Ni and Ti determinations in samples of rice husk and rice husk ash by MIP OES. Sample preparation was performed using a reflux system adapted to the digestion tubes. This system allowed the decomposition of the samples without the necessity of replacement of the acids during this step without any loss of volatile elements. The decompositions were performed with 3.6 mL of HNO3 and 1.4 mL of H2SO4 for 205 min in a digester block at 225 ºC. The detection limit for determination of respective analytes in both samples were satisfactory. The RSDs for the analytes were less than 10%. Moreover, the accuracy of the method can be verified by recovery tests, whose values ranged from 82 to 115% for husk samples and 82 to 120% for ashes. The proposed method was presented as a simple, safe and low cost procedure being suitable for sample preparation and subsequent determination of metals by MIP OES.