Ultrasound-based evaluation of loss of lean mass in patients with burns: A prospective longitudinal study.

OBJECTIVES: To evaluate the loss of lean mass in patients with burns using ultrasonography of the quadriceps muscle of the thigh. METHODS: A prospective longitudinal study was conducted using ultrasound of the quadriceps muscle of the thigh to assess the change in thickness in millimeters on days 1, 3 and 7 after study enrollment in 45 patients with burns who were admitted to a burn center (BTC) of a university hospital between April 2020 and September 2021. Patients burns on the thighs, which made it difficult to undertake examinations, were excluded. Depending on where they were admitted, patients were divided into ward and intensive care unit (ICU) patients. ICU patients were considered to have more severe injuries. The general data collected included age, sex, weight, height, area of body surface burn, burn degree and etiology, and airway injury. The data collected for all patients during hospitalization at the BTC were as follows: existence of chronic illness, requirement for mechanical ventilation, Simplified Acute Physiology Score 3 (SAPS 3) and Sequential Organ Failure Assessment (SOFA) on the first day of hospitalization in an intensive care bed in the burn treatment unit (BTU), health-related infection, feeding route, length of hospital stay, and time spent in the BTU. RESULTS: Loss of muscle thickness was observed in all patients between days 1 and 7. The median thickness for all patients on day 1 was 24.50 mm (ITQ 21.22-30.85) and on day 7 it was 18.80 (ITQ 16.07-23.62), with P = 0.0001. The variation in thigh quadricep muscle thickness between day 1 and day 3, a median of - 2.80 mm (ITQ - 3.52-2.02) was obtained for patients on the ward and - 2.50 mm (ITQ - 3.92 to - 1.47) for ICU patients. Between day 3 and day 7, the variation was - 2.55 mm (ITQ - 4.55 to - 1.25) for ward patients and - 2.10 mm (ITQ - 3.12 to - 1.15) for ICU patients. The median thickness variation assessed between day 1 and day 7 was - 4.95 mm (ITQ - 8.25 to - 3.70) for patients on the ward and - 4.40 mm (ITQ - 7, 35 to - 2.90) for ICU patients. A correlation was observed between the variation in muscle thickness in the interval between day 1 to day 3 and age (P = 0.035). CONCLUSIONS: Muscle loss occurred early and rapidly within the first seven days of hospitalization, reflecting the impact of burn injury on nutritional risk. An association was observed between muscle thickness loss and age, but no association was observed with the extent of burn, length of hospital stay, occurrence of health-related infections or mortality. These findings suggest the importance of monitoring muscle loss in these patients in planning nutritional therapy, early mobilization, and prevention of complications.

Bayesian spatiotemporal modeling on complex-valued fMRI signals via kernel convolutions.

We propose a model-based approach that combines Bayesian variable selection tools, a novel spatial kernel convolution structure, and autoregressive processes for detecting a subject's brain activation at the voxel level in complex-valued functional magnetic resonance imaging (CV-fMRI) data. A computationally efficient Markov chain Monte Carlo algorithm for posterior inference is developed by taking advantage of the dimension reduction of the kernel-based structure. The proposed spatiotemporal model leads to more accurate posterior probability activation maps and less false positives than alternative spatial approaches based on Gaussian process models, and other complex-valued models that do not incorporate spatial and/or temporal structure. This is illustrated in the analysis of simulated data and human task-related CV-fMRI data. In addition, we show that complex-valued approaches dominate magnitude-only approaches and that the kernel structure in our proposed model considerably improves sensitivity rates when detecting activation at the voxel level.

Screen Magnification for Readers with Low Vision: A Study on Usability and Performance.

We present a study with 20 participants with low vision who operated two types of screen magnification (lens and full) on a laptop computer to read two types of document (text and web page). Our purposes were to comparatively assess the two magnification modalities, and to obtain some insight into how people with low vision use the mouse to control the center of magnification. These observations may inform the design of systems for the automatic control of the center of magnification. Our results show that there were no significant differences in reading performances or in subjective preferences between the two magnification modes. However, when using the lens mode, our participants adopted more consistent and uniform mouse motion patterns, while longer and more frequent pauses and shorter overall path lengths were measured using the full mode. Analysis of the distribution of gaze points (as measured by a gaze tracker) using the full mode shows that, when reading a text document, most participants preferred to move the area of interest to a specific region of the screen.

Vaccine fake news: an analysis under the World Health Organization's 3Cs model. / Fake news sobre vacinas: uma análise sob o modelo dos 3Cs da Organização Mundial da Saúde.

OBJECTIVE: To analyze fake news about immunobiologicals using as reference vaccine hesitancy in the World Health Organization's 3Cs model (confidence, complacency and convenience). METHOD: This is an exploratory qualitative research that used content analysis to analyze fake news on three national news-checking sites. RESULTS: Twenty fake news related to immunobiologicals were analyzed, with 55% published in 2018 and 63% related to yellow fever vaccine. From analysis of results, two empirical categories have emerged: Immunobiologicals have a potential risk of death/sequel; Immunobiologicals are ineffective. CONCLUSION: Fake news have the potential to produce vaccine hesitancy based on the 3Cs model. Therefore, it is necessary to rethink communicative health practices that do not underestimate the asymmetries and inequities that characterize the unequal Brazilian society. Considering that nursing is the largest workforce in immunization rooms, there is a need for professionals' engagement as an active vehicle of truthful information in immunobiologicals for the population.

Fake news sobre vacinas: uma análise sob o modelo dos 3Cs da Organização Mundial da Saúde / Fake news sobre vacunas: un análisis bajo el modelo 3Cs de la Organización Mundial de la Salud / Vaccine fake news: an analysis under the World Health Organization's 3Cs model

RESUMO Objetivo Analisar as fake news sobre imunobiológicos tomando como referência a hesitação vacinal no modelo dos 3Cs (confiança, complacência e conveniência) da Organização Mundial da Saúde. Método Trata-se de uma pesquisa qualitativa de caráter exploratório que utilizou análise de conteúdo para analisar fake news em três sites de checagem de notícias nacionais. Resultados Foram analisadas 20 fake news relacionadas a imunobiológicos, sendo 55% publicadas em 2018 e 63% relacionadas à vacina contra febre amarela. A partir da análise dos resultados, duas categorias empíricas foram consideradas: Imunobiológicos têm potencial risco de morte/sequela e Imunobiológicos são ineficazes. Conclusão As fake news têm potencial para produzir hesitação vacinal baseado no modelo dos 3Cs. Sendo necessário, portanto, repensar práticas comunicativas em saúde que não subestimem as assimetrias e as iniquidades que caracterizam a desigual sociedade brasileira. Considerando que a enfermagem é a maior força de trabalho nas salas de vacinas, observa-se a necessidade do engajamento desses profissionais como veículo ativo de informações verídicas em imunobiológicos para a população.

RESUMEN Objetivo Analizar las fake news sobre inmunobiológicos tomando como referencia la vacilación vacunal en el modelo de las 3Cs (confianza, complacencia y conveniencia) de la Organización Mundial de la Salud. Método Es una investigación cualitativa exploratoria que utilizó el análisis de contenido para analizar fake news en tres sitios nacionales de verificación de noticias. Resultados Se analizaron veinte fake news relacionadas con inmunobiológicos, con un 55% publicadas en 2018 y un 63% relacionadas con la vacuna contra la fiebre amarilla. A partir del análisis de los resultados, se consideraron dos categorías empíricas: Los inmunobiológicos tienen un riesgo potencial de muerte/secuelas; Los inmunobiológicos son ineficaces. Conclusión Las fake news tienen el potencial de producir dudas sobre la vacuna según el modelo 3Cs. Por tanto, es necesario repensar prácticas de salud comunicativa que no subestimen las asimetrías e inequidades que caracterizan a la desigual sociedad brasileña. Considerando que la enfermería es la mayor fuerza laboral en las salas de vacunación, existe la necesidad de involucrar a estos profesionales como vehículo activo de información veraz en inmunobiológicos para la población.

ABSTRACT Objective To analyze fake news about immunobiologicals using as reference vaccine hesitancy in the World Health Organization's 3Cs model (confidence, complacency and convenience). Method This is an exploratory qualitative research that used content analysis to analyze fake news on three national news-checking sites. Results Twenty fake news related to immunobiologicals were analyzed, with 55% published in 2018 and 63% related to yellow fever vaccine. From analysis of results, two empirical categories have emerged: Immunobiologicals have a potential risk of death/sequel; Immunobiologicals are ineffective. Conclusion Fake news have the potential to produce vaccine hesitancy based on the 3Cs model. Therefore, it is necessary to rethink communicative health practices that do not underestimate the asymmetries and inequities that characterize the unequal Brazilian society. Considering that nursing is the largest workforce in immunization rooms, there is a need for professionals' engagement as an active vehicle of truthful information in immunobiologicals for the population.

Joint Bayesian Estimation of Voxel Activation and Inter-regional Connectivity in fMRI Experiments.

Brain activation and connectivity analyses in task-based functional magnetic resonance imaging (fMRI) experiments with multiple subjects are currently at the forefront of data-driven neuroscience. In such experiments, interest often lies in understanding activation of brain voxels due to external stimuli and strong association or connectivity between the measurements on a set of pre-specified groups of brain voxels, also known as regions of interest (ROI). This article proposes a joint Bayesian additive mixed modeling framework that simultaneously assesses brain activation and connectivity patterns from multiple subjects. In particular, fMRI measurements from each individual obtained in the form of a multi-dimensional array/tensor at each time are regressed on functions of the stimuli. We impose a low-rank parallel factorization decomposition on the tensor regression coefficients corresponding to the stimuli to achieve parsimony. Multiway stick-breaking shrinkage priors are employed to infer activation patterns and associated uncertainties in each voxel. Further, the model introduces region-specific random effects which are jointly modeled with a Bayesian Gaussian graphical prior to account for the connectivity among pairs of ROIs. Empirical investigations under various simulation studies demonstrate the effectiveness of the method as a tool to simultaneously assess brain activation and connectivity. The method is then applied to a multi-subject fMRI dataset from a balloon-analog risk-taking experiment, showing the effectiveness of the model in providing interpretable joint inference on voxel-level activations and inter-regional connectivity associated with how the brain processes risk. The proposed method is also validated through simulation studies and comparisons to other methods used within the neuroscience community.

Multistage treatment of almonds waste biomass: Characterization and assessment of the potential applications of raw material and products.

Almond shells are waste biomass generated in agro-industrial activities, which represent a resource that can be further valorized upon treatment. The purpose of this work was to assess new value-added products obtained through a novel multi-stage delignification process of almond shells. A comprehensive chemical characterization of the raw materials and products involved in each stage of the process was carried out. Moreover, an extensive mass balance was developed, providing a full understanding of the extraction process. The pulps produced did not display a significant cellulose loss and hence they could be exploited as cellulose-rich materials. On the other hand, the obtained lignins presented high purity values (≈90%) and a high reactivity, and their structures became more condensed and homogeneous after each extraction cycle. These features would allow their utilization as feedstock of renewable materials such bio-sourced phenolic resins.

Understanding the Impact of Stroke on Brain Motor Function: A Hierarchical Bayesian Approach.

Stroke is a disturbance in blood supply to the brain resulting in the loss of brain functions, particularly motor function. A study was conducted by the UCI Neurorehabilitation Lab to investigate the impact of stroke on motor-related brain regions. Functional MRI (fMRI) data were collected from stroke patients and healthy controls while the subjects performed a simple motor task. In addition to affecting local neuronal activation strength, stroke might also alter communications (i.e., connectivity) between brain regions. We develop a hierarchical Bayesian modeling approach for the analysis of multi-subject fMRI data that allows us to explore brain changes due to stroke. Our approach simultaneously estimates activation and condition-specific connectivity at the group level, and provides estimates for region/subject-specific hemodynamic response functions. Moreover, our model uses spike and slab priors to allow for direct posterior inference on the connectivity network. Our results indicate that motor-control regions show greater activation in the unaffected hemisphere and the midline surface in stroke patients than those same regions in healthy controls during the simple motor task. We also note increased connectivity within secondary motor regions in stroke subjects. These findings provide insight into altered neural correlates of movement in subjects who suffered a stroke.

Suitability of cytotoxicity endpoints and test microalgal species to disclose the toxic effect of common aquatic pollutants.

Pulse discharges of chemicals to aquatic environments may lead to high concentrations of them in surface waters for short periods of time, but enough to induce toxic effects on aquatic organisms; however, no many methods allow an early warning of toxicity of these agents. Acute effects of one representative chemical from each of three of the main groups of aquatic pollutants (pesticides, metals and pharmaceuticals) are studied on two green microalgal species (Chlamydomonas moewusii and Chlorella vulgaris). Flow cytometry protocols were used to detect the potential application of chlorophyll a fluorescent emission, cell viability, metabolic activity and membrane potential as cytotoxicity endpoints, besides an epifluorescence microscopy protocol for comet assay to detect genotoxicity level of cells. Obtained results confirm the suitability of them for the prospective assessment of the potential cytotoxicity of these aquatic pollutants. The two microalgal species analysed could be used as indicators in toxicity bioassays, being C. moewusii more sensitive than C. vulgaris. Among cell parameters assayed, the metabolic activity and the primary DNA damage stood out as sensitive cytotoxicity endpoints.

Spectral decompositions of multiple time series: a Bayesian non-parametric approach.

We consider spectral decompositions of multiple time series that arise in studies where the interest lies in assessing the influence of two or more factors. We write the spectral density of each time series as a sum of the spectral densities associated to the different levels of the factors. We then use Whittle's approximation to the likelihood function and follow a Bayesian non-parametric approach to obtain posterior inference on the spectral densities based on Bernstein-Dirichlet prior distributions. The prior is strategically important as it carries identifiability conditions for the models and allows us to quantify our degree of confidence in such conditions. A Markov chain Monte Carlo (MCMC) algorithm for posterior inference within this class of frequency-domain models is presented.We illustrate the approach by analyzing simulated and real data via spectral one-way and two-way models. In particular, we present an analysis of functional magnetic resonance imaging (fMRI) brain responses measured in individuals who participated in a designed experiment to study pain perception in humans.

Effect of the photocatalytic activity of TiO2 on lignin depolymerization.

Lignin is a good candidate for photocatalytic cracking due to the presence of hydroxyl groups. The photocatalytic cracking reaction involves TiO2 as heterogeneous catalyst. In the present work lignin obtained by two different pulping methods is treated under photocatalytic conditions to be depolimerized. Different exposure times to UV radiation were carried out. The results of GS-MS revealed the degradation products of the hemicelluloses contained in the lignin samples. 1h of exposure to UV radiation shows the best yield in the obtaining of lignin degradation derived compounds; the main products obtained are syringaldehyde, pyrocatechol and raspberryketone, the concentration of syringaldehyde increases 20% and vanillin 30%.

Bayesian factor models in characterizing molecular adaptation.

Assessing the selective influence of amino acid properties is important in understanding evolution at the molecular level. A collection of methods and models has been developed in recent years to determine if amino acid sites in a given DNA sequence alignment display substitutions that are altering or conserving a prespecified set of amino acid properties. Residues showing an elevated number of substitutions that favorably alter a physicochemical property are considered targets of positive natural selection. Such approaches usually perform independent analyses for each amino acid property under consideration, without taking into account the fact that some of the properties may be highly correlated. We propose a Bayesian hierarchical regression model with latent factor structure that allows us to determine which sites display substitutions that conserve or radically change a set of amino acid properties, while accounting for the correlation structure that may be present across such properties. We illustrate our approach by analyzing simulated data sets and an alignment of lysin sperm DNA.

Bayesian semiparametric regression models to characterize molecular evolution.

BACKGROUND: Statistical models and methods that associate changes in the physicochemical properties of amino acids with natural selection at the molecular level typically do not take into account the correlations between such properties. We propose a Bayesian hierarchical regression model with a generalization of the Dirichlet process prior on the distribution of the regression coefficients that describes the relationship between the changes in amino acid distances and natural selection in protein-coding DNA sequence alignments. RESULTS: The Bayesian semiparametric approach is illustrated with simulated data and the abalone lysin sperm data. Our method identifies groups of properties which, for this particular dataset, have a similar effect on evolution. The model also provides nonparametric site-specific estimates for the strength of conservation of these properties. CONCLUSIONS: The model described here is distinguished by its ability to handle a large number of amino acid properties simultaneously, while taking into account that such data can be correlated. The multi-level clustering ability of the model allows for appealing interpretations of the results in terms of properties that are roughly equivalent from the standpoint of molecular evolution.

Screening acute cytotoxicity biomarkers using a microalga as test organism.

The present study checked the suitability of the integration of flow cytometry (FCM) as technique and a freshwater microalga (Chlamydomonas moewusii) as cell system model for ecotoxicological studies, looking for sensitive biomarkers of acute cytotoxicity of potential contaminants in aquatic systems. The detection of the potential acute toxicity of a pollutant is of interest because pulse discharges of contaminants to natural waters could lead to high concentrations of these substances that are only present for short periods of time but can affect aquatic organisms such as microalgae. Physiological alterations in C. moewusii cells were analysed after 1h of exposure to different concentrations of the herbicide paraquat. Cell viability was not affected, but the acute toxicity of paraquat was evident at other levels of cell physiology. Herbicide-treated cells showed lower autofluorescence and higher size and internal complexity, lower esterase activity and lower mitochondrial membrane potential. Paraquat induced the depolarisation of the plasma membrane and the increase of intracellular free calcium level and cytosolic pH in a concentration-dependent percentage of cells. All these effects can be related to the oxidative stress induced by the herbicide, as revealed the significantly increased intracellular levels of reactive oxygen species in cultures exposed to paraquat concentrations which induced the physiological alterations mentioned above. Excluding cell viability and mitochondrial membrane potential, these cytotoxicity endpoints could be considered sensitive biomarkers for the short-term exposure to pollutants such as herbicides.

Flow cytometric analysis to evaluate physiological alterations in herbicide-exposed Chlamydomonas moewusii cells.

Investigation of herbicide toxicology in non-target aquatic primary producers such as microalgae is of great importance from an ecological point of view. In order to study the toxicity of the widely used herbicide paraquat on freshwater green microalga Chlamydomonas moewusii, physiological changes associated with 96 h-exposures to this pollutant were monitored using flow cytometry (FCM) technique. Intracellular reactive oxygen species concentration, cytoplasmic membrane potential, metabolic activity and cell protein content were monitored to evaluate the toxicological impact of paraquat on algal physiology. Results showed that herbicide paraquat induced oxidative stress in C. moewusii cells, as it indicated the increase of both superoxide anion and hydrogen peroxide levels observed in non-chlorotic cells of cultures exposed to increasing herbicide concentrations. Furthermore, a progressive increase in the percentage of depolarised cells and a decrease in the metabolic activity level were observed in response to paraquat when non-chlorotic cells were analysed. Chlorotic cells were probably non-viable cells, based on the cytoplasmic membrane depolarisation, its metabolically non-active state and its drastically reduced protein content. In view of the obtained results, we have concluded that a range of significant physiological alterations, detected by flow cytometry, occur when C. moewusii, an ubiquitous microalga in freshwater environments, is challenged with environmentally relevant concentrations of the herbicide paraquat.

Characterization of cell response in Chlamydomonas moewusii cultures exposed to the herbicide paraquat: Induction of chlorosis.

The use of herbicides constitutes the principal method of weed control, but the introduction of these compounds into the aquatic environment can provoke severe consequences for non-target organisms such as microalgae. Effects of the widely used herbicide paraquat were assessed on the green freshwater microalga Chlamydomonas moewusii by means of the analysis of its photosynthetic pigment content, using a traditional spectrophotometric technique that provides population bulk measurements, and by means of flow cytometry, which allowed characterizing the microalgal response at a single-cell level. Results obtained reveal that paraquat concentrations above 50nM induce chlorosis in a percentage of microalgal cells depending on herbicide concentration and exposure time, as reflected by a reduced cell chlorophyll autofluorescence and pigment content of the biomass. Cell viability in these cultures was also reduced in a concentration dependent way. The possibility of analysing chlorotic and non-chlorotic subpopulations separately allowed the study of morphological properties and physiological status of both cell types, leading to the conclusion that chlorotic cells are non-viable cells, based on their reduced size and complexity and their inability to be stained in the fluorescein diacetate assay. In the case of non-chlorotic cells, cell viability was reduced with the increase of paraquat concentration. Non-chlorotic cells in these cultures showed an increased size and complexity in comparison with control cells, probably due to a growth inhibition. Chlorophyll fluorescence was the most sensitive parameter since even cells exposed to the lowest concentration assayed, 50nM, although not chlorotic, showed a significantly reduced chlorophyll fluorescence with respect to control cells, reflected also by a reduced chlorophyll content of the biomass.

Characterizing molecular adaptation: a hierarchical approach to assess the selective influence of amino acid properties.

MOTIVATION: A number of methods for detecting positive selection in protein coding DNA sequences are based on whether each site/region has a non-synonymous to synonymous substitution rates ratio ω greater than one. However, a site/region may show a relatively large number of non-synonymous mutations that conserve a particular property. Recent methods have proposed to consider as evidence for molecular adaptations how conserving, or radically different, non-synonymous mutations are with respect to some key amino acid properties. While such methods have been useful in providing a qualitative assessment of molecular adaptation, they rely on independent statistical analyses for each amino acid property and typically do not properly adjust for multiple comparisons when selection needs to be assessed at several sites. RESULTS: We consider a Bayesian hierarchical model that allows us to jointly determine if a set of amino acid properties are being conserved or radically changed while simultaneously adjusting for multiple comparisons at the codon level. We illustrate how this model can be used to characterize molecular adaptation in two datasets: an alignment from six class I alleles of the human major histocompatibility complex and a sperm lysin alignment from 25 abalone species. We compare the results obtained with the proposed hierarchical models to those obtained with alternative methods. Our analyses indicate that a more complete quantitative and qualitative characterization of molecular adaptation is achieved by taking into account changes in amino acid properties. AVAILABILITY: The R code for implementing the hierarchical models is freely available at http://www.ams.ucsc.edu/∼raquel/software/.

Ring test for whole-sediment toxicity assay with -a- benthic marine diatom.

This work presents the results of an interlaboratory proficiency exercise for whole-sediment toxicity assays with the benthic marine diatom Cylindrotheca closterium. An assay protocol was established and followed by all participating laboratories. Cell growth after 72 h exposure was the endpoint used. Four sediment samples of unknown toxicity were assayed. The main problem encountered during this exercise was the differences in the cell growth of algae exposed to reference sediment. Those differences may be associated with changes in the physiological status of the initial culture due to temperature changes during transport to the other laboratories. In general, the method proposed presented good replicability (precision between replicates) and reproducibility (interlaboratory precision). Around 80% (17 out of 21) of results obtained were classified as satisfactory (Z-scores <2). The whole-sediment assay with C. closterium presented here can be considered sufficiently successful for possible use as a standard toxicity test. The assay is simple to perform, the proposed species is ecologically relevant as an integral component of microphytobenthos, and is widely distributed around the world. These positive factors suggest that the whole-sediment assay with the benthic marine diatom C. closterium can be used as a reliable tool in marine sediment quality assessment.

Cell proliferation alterations in Chlorella cells under stress conditions.

Very little is known about growth and proliferation in relation to the cell cycle regulation of algae. The lack of knowledge is even greater when referring to the potential toxic effects of pollutants on microalgal cell division. To assess the effect of terbutryn, a triazine herbicide, on the proliferation of the freshwater microalga Chlorella vulgaris three flow cytometric approaches were used: (1) in vivo cell division using 5-,6-carboxyfluorescein diacetate succinimidyl ester (CFSE) staining was measured, (2) the growth kinetics were determined by cytometric cell counting and (3) cell viability was evaluated with the membrane-impermeable double-stranded nucleic acid stain propidium iodide (PI). The results obtained in the growth kinetics study using CFSE to identify the microalgal cell progeny were consistent with those determined by cytometric cell counting. In all C. vulgaris cultures, each mother cell had undergone only one round of division through the 96 h of assay and the cell division occurred during the dark period. Cell division of the cultures exposed to the herbicide was asynchronous. Terbutryn altered the normal number of daughter cells (4 autospores) obtained from each mother cell. The number was only two in the cultures treated with 250 nM. The duration of the lag phase after the exposure to terbutryn could be dependent on the existence of a critical cell size to activate cytoplasmic division. Cell size, complexity and fluorescence of chlorophyll a of the microalgal cells presented a marked light/dark (day/night) cycle, except in the non-dividing 500 nM cultures, where terbutryn arrested cell division at the beginning of the cycle. Viability results showed that terbutryn has an algastatic effect in C. vulgaris cells at this concentration. The rapid and precise determination of cell proliferation by CFSE staining has allowed us to develop a model for assessing both the cell cycle of C. vulgaris and the in vivo effects of pollutants on growth and reproduction at microalgal cell level.