Nocturnal blood pressure dipping in acute ischemic stroke.

OBJECTIVES: We aim to assess the impact of early nocturnal blood pressure (BP) variation in the functional outcome of patients after an acute ischemic stroke. MATERIALS AND METHODS: We included consecutive stroke patients treated with intravenous thrombolysis (IVrtPA) in a tertiary stroke center. BP measurements were performed at regular intervals throughout day and night during the first 48 h after stroke onset, and subjects were divided into four dipping categories (extreme dippers, dippers, non-dippers, and reverse dippers). Recanalization was assessed by transcranial color-coded Doppler and/or angiographic CT. Hemorrhagic transformation was evaluated at 24 h follow-up CT scan. Functional outcome was evaluated at 3 months after stroke using the modified Rankin Scale. RESULTS: A total of 304 patients were included, mean age 72.80 ± 11.10 years. After 24 h of systolic BP monitoring, 30.59% were classified as reverse dippers, 39.14% as non-dippers, 19.10% as dippers, and 11.18% as extreme dippers. Multivariate analysis did not show an independent association of any dipping class with 3-month functional outcome. Hemorrhagic transformation was not uniform between dipping classes: 25.81% for reverse dippers, 14.29% for non-dippers, 15.52% for dippers, and 5.88% for extreme dippers, P = 0.033. CONCLUSIONS: Nocturnal BP dipping pattern is not associated with functional outcome at 3 months in acute stroke patients treated with IVrtPA. Hemorrhagic transformation was more frequent in reverse dippers.

The Dependence of Crops for Pollinators and the Economic Value of Pollination in Brazil.

Food production is challenged by changes in climate and land use and expanding human population growth. Proper pollination can increase the production and quality of fruit, nut, oil, and fiber crops. We reviewed crop dependence on pollinators and estimated the economic value of pollination per year for each crop in Brazil. We analyzed 141 crops and found that 85 depend on pollinators. Almost one-third of these crops have an essential or great dependence on pollinators. The economic contribution of pollinators totals ∼30% (∼US$12 billion) of the total annual agricultural income of the dependent crops (totalizing almost US$45 billion). However, half of these figures includes soybean crop (US$5.7 billion of pollinators' contribution and US$22 billion of annual income). Soybean was considered as having a modest dependence on pollinators, but this remains controversial because pollinator dependence might vary among different varieties cultivated in Brazil. Moreover, we have no information about pollinator dependence regarding some important crops, showing the urgent need for basic research into reproductive biology and pollination ecology.

A new flexible regression model with application to recovery probability Covid-19 patients.

The aim of this study is to propose a generalized odd log-logistic Maxwell mixture model to analyze the effect of gender and age groups on lifetimes and on the recovery probabilities of Chinese individuals with COVID-19. We add new properties of the generalized Maxwell model. The coefficients of the regression and the recovered fraction are estimated by maximum likelihood and Bayesian methods. Further, some simulation studies are done to compare the regressions for different scenarios. Model-checking techniques based on the quantile residuals are addressed. The estimated survival functions for the patients are reported by age range and sex. The simulation study showed that mean squared errors decay toward zero and the average estimates converge to the true parameters when sample size increases. According to the fitted model, there is a significant difference only in the age group on the lifetime of individuals with COVID-19. Women have higher probability of recovering than men and individuals aged ≥60 years have lower recovered probabilities than those who aged <60 years. The findings suggest that the proposed model could be a good alternative to analyze censored lifetime of individuals with COVID-19.

Log-mean distribution: applications to medical data, survival regression, Bayesian and non-Bayesian discussion with MCMC algorithm.

We introduce a new family via the log mean of an underlying distribution and as baseline the proportional hazards model and derive some important properties. A special model is proposed by taking the Weibull for the baseline. We derive several properties of the sub-model such as moments, order statistics, hazard function, survival regression and certain characterization results. We estimate the parameters using frequentist and Bayesian approaches. Further, Bayes estimators, posterior risks, credible intervals and highest posterior density intervals are obtained under different symmetric and asymmetric loss functions. A Monte Carlo simulation study examines the biases and mean square errors of the maximum likelihood estimators. For the illustrative purposes, we consider heart transplant and bladder cancer data sets and investigate the efficiency of proposed model.

The re-parameterized inverse Gaussian regression to model length of stay of COVID-19 patients in the public health care system of Piracicaba, Brazil.

Among the models applied to analyze survival data, a standout is the inverse Gaussian distribution, which belongs to the class of models to analyze positive asymmetric data. However, the variance of this distribution depends on two parameters, which prevents establishing a functional relation with a linear predictor when the assumption of constant variance does not hold. In this context, the aim of this paper is to re-parameterize the inverse Gaussian distribution to enable establishing an association between a linear predictor and the variance. We propose deviance residuals to verify the model assumptions. Some simulations indicate that the distribution of these residuals approaches the standard normal distribution and the mean squared errors of the estimators are small for large samples. Further, we fit the new model to hospitalization times of COVID-19 patients in Piracicaba (Brazil) which indicates that men spend more time hospitalized than women, and this pattern is more pronounced for individuals older than 60 years. The re-parameterized inverse Gaussian model proved to be a good alternative to analyze censored data with non-constant variance.

A random effect regression based on the odd log-logistic generalized inverse Gaussian distribution.

In recent decades, the use of regression models with random effects has made great progress. Among these models' attractions is the flexibility to analyze correlated data. In various situations, the distribution of the response variable presents asymmetry or bimodality. In these cases, it is possible to use the normal regression with random effect at the intercept. In light of these contexts, i.e. the desire to analyze correlated data in the presence of bimodality or asymmetry, in this paper we propose a regression model with random effect at the intercept based onthe generalized inverse Gaussian distribution model with correlated data. The maximum likelihood is adopted to estimate the parameters and various simulations are performed for correlated data. A type of residuals for the new regression is proposed whose empirical distribution is close to normal. The versatility of the new regression is demonstrated by estimating the average price per hectare of bare land in 10 municipalities in the state of São Paulo (Brazil). In this context, various databases are constantly emerging, requiring flexible modeling. Thus, it is likely to be of interest to data analysts, and can make a good contribution to the statistical literature.

Antioxidant, anti-inflammatory and anti-obesity effects of onion and its by-products in high-fat fed rodents: a systematic review.

The effects of onion and its by-products on metabolic changes induced by excessive consumption of a high fat diet have been the focus of many studies. The aim of this study was to systematically review the effects of onion and its by-products antioxidant, anti-inflammatory and anti-obesity in rats exposed to a high-fat diet. Five databases were used: Pubmed, EMBASE, Science Direct, Web of science and Scopus until June 2020 updated December 1, 2022. Research of the articles was carried out by two reviewers, searching and selecting studies after an initial reading of the titles and abstracts. In total, 2,448 papers were found and, after assessing against the inclusion and exclusion criteria, 18 papers were selected for this review. The findings of this review show the beneficial effects of onion and its by-products on inflammatory parameters, obesity, cardiovascular disease, thermogenesis and hepatic alterations generally associated with the consumption of a high-fat diet.

The semiparametric regression model for bimodal data with different penalized smoothers applied to climatology, ethanol and air quality data.

Semiparametric regressions can be used to model data when covariables and the response variable have a nonlinear relationship. In this work, we propose three flexible regression models for bimodal data called the additive, additive partial and semiparametric regressions, basing on the odd log-logistic generalized inverse Gaussian distribution under three types of penalized smoothers, where the main idea is not to confront the three forms of smoothings but to show the versatility of the distribution with three types of penalized smoothers. We present several Monte Carlo simulations carried out for different configurations of the parameters and some sample sizes to verify the precision of the penalized maximum-likelihood estimators. The usefulness of the proposed regressions is proved empirically through three applications to climatology, ethanol and air quality data.

Joint regression modeling of location and scale parameters of the skew t distribution with application in soil chemistry data.

In regression model applications, the errors may frequently present a symmetric shape. In such cases, the normal and Student t distributions are commonly used. In this paper, we shall be concerned only to model heavy-tailed, skewed errors and absence of variance homogeneity with two regression structures based on the skew t distribution. We consider a classic analysis for the parameters of the proposed model. We perform a diagnostic analysis based on global influence and quantile residuals. For different parameter settings and sample sizes, various simulation results are obtained and compared to evaluate the performance of the skew t regression. Further, we illustrate the usefulness of the new regression by means of a real data set (amount of potassium in different soil areas) from a study carried out at the Department of Soil Science of the Luiz de Queiroz School of Agriculture, University of São Paulo.

A new regression model for rates and proportions data with applications.

We propose a new continuous distribution in the interval ( 0 , 1 ) based on the generalized odd log-logistic-G family, whose density function can be symmetrical, asymmetric, unimodal and bimodal. The new model is implemented using the gamlss packages in R. We propose an extended regression based on this distribution which includes as sub-models some important regressions. We employ a frequentist and Bayesian analysis to estimate the parameters and adopt the non-parametric and parametric bootstrap methods to obtain better efficiency of the estimators. Some simulations are conducted to verify the empirical distribution of the maximum likelihood estimators. We compare the empirical distribution of the quantile residuals with the standard normal distribution. The extended regression can give more realistic fits than other regressions in the analysis of proportional data.

A new heteroscedastic regression to analyze mass loss of wood in civil construction in Brazil.

A heteroscedastic regression based on the odd log-logistic Marshall-Olkin normal (OLLMON) distribution is defined by extending previous models. Some structural properties of this distribution are presented. The estimation of the parameters is addressed by maximum likelihood. For different parameter settings, sample sizes and some scenarios, various simulations investigate the performance of the heteroscedastic OLLMON regression. We use residual analysis to detect influential observations and to check the model assumptions. The new regression explains the mass loss of different wood species in civil construction in Brazil.

Murinometric measurements and retroperitoneal adipose tissue in young rats exposed to the high-fat diet: Is there correlation?

AIM: This study aimed to verify the correlation between murine measurements and retroperitoneal adipose tissue in rats exposed to the high-fat diet. Material and methods: Wistar male adult rats, descendants of mothers who consumed a high-fat diet during pregnancy and lactation and fed the same diet after weaning were used. At 60 days of life, body weight, longitudinal axis and waist circumference (WC) were measured. The Body Mass Index (BMI) and the Lee Index were calculated for a posterior analysis of the correlation with the amount of retroperitoneal adipose tissue dissected on the same day. For analysis of the data, the Pearson correlation test was used, considering statistical significance for p <0.05. Results: Body weight had a weak correlation (r= 0.31; p= 0.38) with retroperitoneal adipose tissue. While the longitudinal correlated moderately and negative (r= -0.40; p= 0.25). Abdominal circumference (r= 0.62; p= 0.05), body mass index (r= 0.61; p= 0.03) and Lee (r= 0.69; p= 0.03) correlated moderately and positively with adipose tissue. Conclusion: Among the measured murine measurements, weight and longitudinal axis were not good indicators to represent accumulation of retroperitoneal adipose tissue in rats. However, Lee's index seems to be the best murine marker to diagnose the accumulation of retroperitoneal fat. BMI, CA and Lee index were murine parameters with higher correlation.

Perinatal exposure to a high-fat diet alters proopiomelanocortin, neuropeptide Y and dopaminergic receptors gene expression and the food preference in offspring adult rats.

Exposure to the hight-fat diet may alter the control of food intake promoting hyperphagia and obesity. The objective of this study was to investigate the effects of this diet on dopamine receptors (drd1 and drd2), proopiomelanocortin (pomc), neuropeptideY (npy) genes expression, and preference food in adult rats. Wistar female rats were fed a hight-fat or control diet during pregnancy and lactation. The offspring were allocated into groups: Lactation - Control (C) and High-fat (H). Post-weaning - Control Control (CC), offspring of mothers C, fed a control diet after weaning; Control Hight-fat (CH), offspring of mothers C, fed a hight-fat diet after weaning; Hight-fat Control (HC), offspring of mothers H, fed with control diet after weaning; and Hight-fat Hight-fat (HH), offspring of mothers H, fed a H diet after weaning. The groups CH and HH presented greater expression of drd1 in comparison to the CC. The drd2 of CH and HC presented higher gene expression than did CC. HH presented higher pomc expression in comparison to the other groups. HC also presented greater expression in comparison to CH. The npy of HH presented greater expression in relation to CH and HC. HH and HC have had a higher preference for a high-fat diet at 102º life's day. The high-fat diet altered the gene expression of the drd1, drd2, pomc and npy, and influencing the food preference for high-fat diet.

The multinomial logistic regression model for predicting the discharge status after liver transplantation: estimation and diagnostics analysis.

The multinomial logistic regression model (MLRM) can be interpreted as a natural extension of the binomial model with logit link function to situations where the response variable can have three or more possible outcomes. In addition, when the categories of the response variable are nominal, the MLRM can be expressed in terms of two or more logistic models and analyzed in both frequentist and Bayesian approaches. However, few discussions about post modeling in categorical data models are found in the literature, and they mainly use Bayesian inference. The objective of this work is to present classic and Bayesian diagnostic measures for categorical data models. These measures are applied to a dataset (status) of patients undergoing kidney transplantation.

Comprehensive investigation of pesticides in Brazilian surface water by high resolution mass spectrometry screening and gas chromatography-mass spectrometry quantitative analysis.

In this work, a comprehensive investigation on the occurrence of pesticides in the Paraná 3 hydrographic basin of Paraná State, Brazil, was made by application of wide-scope screening based on ultra-high performance liquid chromatography (LC) and gas chromatography (GC) both coupled to quadrupole time-of-flight mass spectrometry (QTOF MS). The use of two complementary techniques, such as GC-QTOF MS and LC-QTOF MS, allowed screening a large number of compounds with different polarity and volatility. This screening approach was applied to 17 samples, enabling the detection of fifty-two pesticides and six metabolites. In a second step, an specific research was made on the herbicide atrazine, one of the most frequent compounds in samples, and its major transformation products (TPs), which were quantitatively analyzed by dispersive liquid-liquid microextraction (DLLME) followed by GC-MS measurement. Twenty-one agricultural streams from the Paraná 3 hydrographic basin were sampled twice in 2017, each time along six successive weeks. Additional samples were also collected after rain events exceeding 10 mm. In total, 407 samples were quantitatively analyzed by DLLME/GC-MS. Atrazine concentrations did not exceed the maximum permitted concentration of 2 µg L-1 according to Brazilian legislation, and only one surface water sample, collected after precipitation events, was slightly above this value (2.89 µg L-1). The maximum concentrations for the TPs desethylatrazine and deisopropylatrazine were 0.80 and 1.22 µg L-1, respectively. Based on the quantification results, a map was produced showing the occurrence of atrazine and its TPs in the area under study. This is the first time that the presence of agrochemicals is evaluated in the Paraná 3 hydrographic basin.

Influence of mother nutrition during pregnancy and/or lactation on offspring food preference in experimental models.

INTRODUCTION: Understanding associations between food preferences and maternal nutrition during pregnancy and lactation could inform efforts to understanding the obesity mechanisms and provide insight to prevent it. Objective: To identify studies that investigated the effects of nutritional interventions during the pregnancy and lactation on the food preferences of offspring. Method: The review was conducted with search for articles in the databases: Scopus, Pubmed, Medline, LILACS, Scielo and Science Direct. Exclusion criteria were used: reviews, human studies, studies with drugs or other substances not related to food. Results: At the end of the search in the databases, 176 references were found. After use the exclusion criteria, reading the titles, abstracts and full articles, were selected 11 articles to compose the review. Conclusion: The selected studies suggested that unbalanced nutrition in early life alters the food preference and neural components related to the consumption of fatty and sugary foods in offspring rodents.

Effects of maternal high fat intake during pregnancy and lactation on total cholesterol and adipose tissue in neonatal rats.

AIM: Obesity during pregnancy is one of the most established risk factors for negative long-term programming. The aim of the present study was to investigate the effects of maternal consumption of a high-fat diet during pregnancy and lactation on the weight gain, visceral adipose tissue and cholesterolemia in neonatal rats. METHODS: Wistar rats were divided into two groups according to the mother's diet during pregnancy and lactation: Control group (CG, n = 12) were the offspring of rats fed a standard diet (4% lipid) and the Test group (TG, n = 12) were pups rats fed on a high fat diet (23% lipid). The weight of the animals was measured on alternate days until the 22nd day of life, when collected visceral adipose tissue and blood were collected for biochemical analysis. For statistical analysis the Student t test, Sidak´s teste and two way ANOVA was used, with p <0.05. RESULTS: the test group showed differences in weight gain, visceral adipose tissue and higher cholesterol. CONCLUSION: a maternal exposure to a high-fat diet during pregnancy and lactation can promote changes in weight gain, hypercholesterolemia and an increase in adipose tissue in neonatal rats.

Pollination of Campomanesia phaea (Myrtaceae) by night-active bees: a new nocturnal pollination system mediated by floral scent.

Bees are the most important diurnal pollinators of angiosperms. In several groups of bees a nocturnal/crepuscular habit developed, yet little is known about their role in pollination and whether some plants are adapted specifically to these bees. We used a multidisciplinary approach to investigate the reproductive biology and to understand the role of nocturnal/crepuscular bees in pollination of Campomanesia phaea (Myrtaceae), popularly named cambuci. We studied the floral biology and breeding system of C. phaea. We collected the floral visitors and tested the pollinators' effectiveness. We also determined the floral scents released at night and during daytime, and studied behavioural responses of crepuscular/nocturnal bees towards these scents. The flowers of cambuci were self-incompatible and had pollen as the only resource for flower visitors. Anthesis lasted around 14 h, beginning at 04:30 h at night. The flowers released 14 volatile compounds, mainly aliphatic and aromatic compounds. We collected 52 species of floral visitors, mainly bees. Nocturnal and crepuscular bees (four species) were among the most frequent species and the only effective pollinators. In field bioassays performed at night, nocturnal/crepuscular bees were attracted by a synthetic scent blend consisting of the six most abundant compounds. This study describes the first scent-mediated pollination system between a plant and its nocturnal bee pollinators. Further, C. phaea has several floral traits that do not allow classification into other nocturnal pollination syndromes (e.g. pollinator attraction already before sunrise, with pollen as the only reward), instead it is a plant specifically adapted to nocturnal bees.

Perinatal exposure to a high-fat diet alters proopiomelanocortin, neuropeptide Y and dopaminergic receptors gene expression and the food preference in offspring adult rats / Exposição perinatal a uma dieta hiperlipídica altera a expressão gênica de proopiomelanocortina, neuropepitídeo Y e receptores dopaminérgicos e a preferência alimentar em ratos adultos descendentes

Exposure to the hight-fat diet may alter the control of food intake promoting hyperphagia and obesity. The objective of this study was to investigate the effects of this diet on dopamine receptors (drd1 and drd2), proopiomelanocortin (pomc), neuropeptideY (npy) genes expression, and preference food in adult rats. Wistar female rats were fed a hight-fat or control diet during pregnancy and lactation. The offspring were allocated into groups: Lactation - Control (C) and High-fat (H). Post-weaning ­ Control Control (CC), offspring of mothers C, fed a control diet after weaning; Control Hight-fat (CH), offspring of mothers C, fed a hight-fat diet after weaning; Hight-fat Control (HC), offspring of mothers H, fed with control diet after weaning; and Hight-fat Hight-fat (HH), offspring of mothers H, fed a H diet after weaning. The groups CH and HH presented greater expression of drd1 in comparison to the CC. The drd2 of CH and HC presented higher gene expression than did CC. HH presented higher pomc expression in comparison to the other groups. HC also presented greater expression in comparison to CH. The npy of HH presented greater expression in relation to CH and HC. HH and HC have had a higher preference for a high-fat diet at 102º life's day. The high-fat diet altered the gene expression of the drd1, drd2, pomc and npy, and influencing the food preference for high-fat diet.

A exposição à dieta hiperlipídica pode alterar o controle da ingestão de alimentos, promovendo hiperfagia e obesidade. O objetivo deste estudo foi investigar os efeitos dessa dieta sobre a expressão gênica dos receptores de dopamina (drd1 e drd2), da proopiomelanocortina (pomc) e neuropeptídeo Y (npy), e preferência alimentar em ratos adultos. Ratas Wistar foram alimentadas com uma dieta hiperlipídica ou controle durante a gestação e lactação. Os descendentes foram alocados em grupos: Lactação ­ Controle (C) e Hiperlipídica (H). Pós-desmame - Controle Controle (CC), descendentes das genitoras do grupo controle e alimentados com dieta controle após o desmame; Controle Hiperlipídica (CH), descendentes das genitoras do grupo controle e alimentados com dieta hiperlipídica após o desmame; Hiperlipídica Controle (HC), descendentes das genitoras do grupo hiperlipídica e alimentados com dieta controle após o desmame; Hiperlipídica Hiperlipídica (HH), descendentes das genitoras do grupo hiperlipídica e alimentados com dieta hiperlipídica após o desmame. Os grupos CH e HH apresentaram maior expressão de drd1 em comparação ao CC. O drd2 de CH e HC apresentou maior expressão gênica que o CC. HH apresentou maior expressão de pomc em comparação com os outros grupos. O HC também apresentou maior expressão de pomc em comparação ao CH. O npy do HH apresentou maior expressão em relação ao CH e HC. HH e HC tiveram uma preferência maior por uma dieta rica em gordura no 102º dia de vida. A dieta hiperlipídica alterou a expressão gênica dos drd1, drd2, pomc e npy e influenciou na preferência alimentar pela dieta hiperlipídica.

Perinatal exposure to a high-fat diet alters proopiomelanocortin, neuropeptide Y and dopaminergic receptors gene expression and the food preference in offspring adult rats / Exposição perinatal a uma dieta hiperlipídica altera a expressão gênica de proopiomelanocortina, neuropepitídeo Y e receptores dopaminérgicos e a preferência alimentar em ratos adultos descendentes

Exposure to the hight-fat diet may alter the control of food intake promoting hyperphagia and obesity. The objective of this study was to investigate the effects of this diet on dopamine receptors (drd1 and drd2), proopiomelanocortin (pomc), neuropeptideY (npy) genes expression, and preference food in adult rats. Wistar female rats were fed a hight-fat or control diet during pregnancy and lactation. The offspring were allocated into groups: Lactation – Control (C) and High-fat (H). Post- weaning – Control Control (CC), offspring of mothers C, fed a control diet after weaning; Control Hight-fat (CH), offspring of mothers C, fed a hight-fat diet after weaning; Hight-fat Control (HC), offspring of mothers H, fed with control diet after weaning; and Hight-fat Hight-fat (HH), offspring of mothers H, fed a H diet after weaning. The groups CH and HH presented greater expression of drd1 in comparison to the CC. The drd2 of CH and HC presented higher gene expression than did CC. HH presented higher pomc expression in comparison to the other groups. HC also presented greater expression in comparison to CH. The npy of HH presented greater expression in relation to CH and HC. HH and HC have had a higher preference for a high-fat diet at 102º life’s day. The high-fat diet altered the gene expression of the drd1, drd2, pomc and npy, and influencing the food preference for high-fat diet.

A exposição à dieta hiperlipídica pode alterar o controle da ingestão de alimentos, promovendo hiperfagia e obesidade. O objetivo deste estudo foi investigar os efeitos dessa dieta sobre a expressão gênica dos receptores de dopamina (drd1 e drd2), da proopiomelanocortina (pomc) e neuropeptídeo Y (npy), e preferência alimentar em ratos adultos. Ratas Wistar foram alimentadas com uma dieta hiperlipídica ou controle durante a gestação e lactação. Os descendentes foram alocados em grupos: Lactação – Controle (C) e Hiperlipídica (H). Pós-desmame – Controle Controle (CC), descendentes das genitoras do grupo controle e alimentados com dieta controle após o desmame; Controle Hiperlipídica (CH), descendentes das genitoras do grupo controle e alimentados com dieta hiperlipídica após o desmame; Hiperlipídica Controle (HC), descendentes das genitoras do grupo hiperlipídica e alimentados com dieta controle após o desmame; Hiperlipídica Hiperlipídica (HH), descendentes das genitoras do grupo hiperlipídica e alimentados com dieta hiperlipídica após o desmame. Os grupos CH e HH apresentaram maior expressão de drd1 em comparação ao CC. O drd2 de CH e HC apresentou maior expressão gênica que o CC. HH apresentou maior expressão de pomc em comparação com os outros grupos. O HC também apresentou maior expressão de pomc em comparação ao CH. O npy do HH apresentou maior expressão em relação ao CH e HC. HH e HC tiveram uma preferência maior por uma dieta rica em gordura no 102º dia de vida. A dieta hiperlipídica alterou a expressão gênica dos drd1, drd2, pomc e npy e influenciou na preferência alimentar pela dieta hiperlipídica.