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1.
Int J Mol Sci ; 22(6)2021 Mar 17.
Artículo en Inglés | MEDLINE | ID: mdl-33802822

RESUMEN

Future space missions will include a return to the Moon and long duration deep space roundtrip missions to Mars. Leaving the protection that Low Earth Orbit provides will unavoidably expose astronauts to higher cumulative doses of space radiation, in addition to other stressors, e.g., microgravity. Immune regulation is known to be impacted by both radiation and spaceflight and it remains to be seen whether prolonged effects that will be encountered in deep space can have an adverse impact on health. In this study, we investigated the effects in the overall metabolism of three different low dose radiation exposures (γ-rays, 16O, and 56Fe) in spleens from male C57BL/6 mice at 1, 2, and 4 months after exposure. Forty metabolites were identified with significant enrichment in purine metabolism, tricarboxylic acid cycle, fatty acids, acylcarnitines, and amino acids. Early perturbations were more prominent in the γ irradiated samples, while later responses shifted towards more prominent responses in groups with high energy particle irradiations. Regression analysis showed a positive correlation of the abundance of identified fatty acids with time and a negative association with γ-rays, while the degradation pathway of purines was positively associated with time. Taken together, there is a strong suggestion of mitochondrial implication and the possibility of long-term effects on DNA repair and nucleotide pools following radiation exposure.


Asunto(s)
Radiación Cósmica , Metaboloma/efectos de la radiación , Exposición a la Radiación , Bazo/metabolismo , Bazo/efectos de la radiación , Animales , Ciclo del Ácido Cítrico/efectos de la radiación , Relación Dosis-Respuesta en la Radiación , Modelos Lineales , Masculino , Ratones Endogámicos C57BL , Análisis Multivariante , Purinas/metabolismo
2.
BMC Bioinformatics ; 22(Suppl 2): 196, 2021 Apr 26.
Artículo en Inglés | MEDLINE | ID: mdl-33902443

RESUMEN

BACKGROUND: Linear regression models are important tools for learning regulatory networks from gene expression time series. A conventional assumption for non-homogeneous regulatory processes on a short time scale is that the network structure stays constant across time, while the network parameters are time-dependent. The objective is then to learn the network structure along with changepoints that divide the time series into time segments. An uncoupled model learns the parameters separately for each segment, while a coupled model enforces the parameters of any segment to stay similar to those of the previous segment. In this paper, we propose a new consensus model that infers for each individual time segment whether it is coupled to (or uncoupled from) the previous segment. RESULTS: The results show that the new consensus model is superior to the uncoupled and the coupled model, as well as superior to a recently proposed generalized coupled model. CONCLUSIONS: The newly proposed model has the uncoupled and the coupled model as limiting cases, and it is able to infer the best trade-off between them from the data.


Asunto(s)
Algoritmos , Redes Reguladoras de Genes , Teorema de Bayes , Modelos Lineales
3.
AAPS PharmSciTech ; 22(3): 132, 2021 Apr 13.
Artículo en Inglés | MEDLINE | ID: mdl-33851275

RESUMEN

The main objective of this study was to develop an in vivo predictive dissolution (IVPD) model for topiroxostat immediate-release (IR) formulation by the combination of mechanistic absorption model (MAM) deconvolution method with time shifting factor (TSF) adjustment. The in vitro dissolution profiles in different biorelevant dissolution media containing different concentrations of sodium lauryl sulfate (SLS) were obtained from dissolution testing with the paddle method of the US Pharmacopeia, while the human pharmacokinetic profile was taken from the published experimental results. The GastroPlus™ software was used to observe the linear relationship between in vitro drug dissolution and in vivo absorption. The pharmacokinetic profile of topiroxostat IR tablet was first deconvoluted through the MAM method to obtain the fraction absorbed in vivo. Next, Levy plot was constructed to estimate the TSF, and the time scale for both processes of dissolution and absorption was then adjusted to be superimposable. The IVPD modelling was subsequently established with data between in vitro dissolution profiles and fraction absorbed in vivo. Finally, the dissolution profiles of topiroxostat IR tablet were translated into a pharmacokinetic curve in terms of convolution method. The comparison between translated and observed pharmacokinetic data will validate the performance of the developed IVPD model. This new linear IVPD model with high predictive power for the tablet can predict the in vivo pharmacokinetic differences through in vitro dissolution data, and it can be utilized as a risk-control tool for the formulation development of the topiroxostat IR tablet and the quality control of product batches.


Asunto(s)
Simulación por Computador , Modelos Biológicos , Nitrilos/química , Nitrilos/farmacocinética , Piridinas/química , Piridinas/farmacocinética , Adulto , Liberación de Fármacos/fisiología , Inhibidores Enzimáticos/química , Inhibidores Enzimáticos/farmacocinética , Femenino , Predicción , Humanos , Modelos Lineales , Masculino , Persona de Mediana Edad , Comprimidos , Adulto Joven
4.
Rev Bras Epidemiol ; 24(suppl 1): e210017, 2021.
Artículo en Inglés, Portugués | MEDLINE | ID: mdl-33886890

RESUMEN

OBJECTIVE: The main objective of this paper was to analyze the relation between GDP and three variables linked to traffic accidents in Brazilian municipalities: traffic accident mortality, deaths per vehicle; and vehicles per inhabitant. METHODS: 2005, 2010 and 2015 traffic accident (TA) mortality rates were estimated using a three-year moving average and were standardized; then, we applied the empirical Bayes estimator (EBE). Fatality rates (deaths per vehicle) were also based on EBE. The variable vehicles per inhabitant considered the ratio between the fleet and the population at municipal level. For every studied year, we estimated linear regression models between GDP and the interest variables. RESULTS: The variables distribution indicates that, between 2005 and 2015, GDP and vehicles per inhabitant kept the same rising relationship. Fatality rates show a decreasing association with GDP. The distribution of mortality by TA had an inverted U-shaped pattern. The model coefficients practically did not change for the vehicle per inhabitant. Estimated association between deaths per vehicle and GDP kept the same sign, but diminished between 2005 and 2015. Model coefficient sign changed in 2015 for TA mortality. CONCLUSION: Similar to what was observed in developed countries, the relation between mortality by traffic accidents and GDP changed in the analyzed period.


Asunto(s)
Accidentes de Tránsito , Teorema de Bayes , Brasil/epidemiología , Ciudades/epidemiología , Humanos , Modelos Lineales
5.
Sensors (Basel) ; 21(6)2021 Mar 17.
Artículo en Inglés | MEDLINE | ID: mdl-33803032

RESUMEN

Saturation effects limit the application of vegetation indices (VIs) in dense vegetation areas. The possibility to mitigate them by adopting a negative soil adjustment factor X is addressed. Two leaf area index (LAI) data sets are analyzed using the Google Earth Engine (GEE) for validation. The first one is derived from observations of MODerate resolution Imaging Spectroradiometer (MODIS) from 16 April 2013, to 21 October 2020, in the Apiacás area. Its corresponding VIs are calculated from a combination of Sentinel-2 and Landsat-8 surface reflectance products. The second one is a global LAI dataset with VIs calculated from Landsat-5 surface reflectance products. A linear regression model is applied to both datasets to evaluate four VIs that are commonly used to estimate LAI: normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), transformed SAVI (TSAVI), and enhanced vegetation index (EVI). The optimal soil adjustment factor of SAVI for LAI estimation is determined using an exhaustive search. The Dickey-Fuller test indicates that the time series of LAI data are stable with a confidence level of 99%. The linear regression results stress significant saturation effects in all VIs. Finally, the exhaustive searching results show that a negative soil adjustment factor of SAVI can mitigate the SAVIs' saturation in the Apiacás area (i.e., X = -0.148 for mean LAI = 5.35), and more generally in areas with large LAI values (e.g., X = -0.183 for mean LAI = 6.72). Our study further confirms that the lower boundary of the soil adjustment factor can be negative and that using a negative soil adjustment factor improves the computation of time series of LAI.


Asunto(s)
Hojas de la Planta , Suelo , Modelos Lineales , Imágenes Satelitales
6.
Sensors (Basel) ; 21(9)2021 Apr 28.
Artículo en Inglés | MEDLINE | ID: mdl-33925152

RESUMEN

Leaf pigment content retrieval is an essential research field in remote sensing. However, retrieval studies on anthocyanins are quite rare compared to those on chlorophylls and carotenoids. Given the critical physiological significance of anthocyanins, this situation should be improved. In this study, using the reflectance, partial least squares regression (PLSR) and Gaussian process regression (GPR) were sought to retrieve the leaf anthocyanin content. To our knowledge, this is the first time that PLSR and GPR have been employed in such studies. The results showed that, based on the logarithmic transformation of the reflectance (log(1/R)) with 564 and 705 nm, the GPR model performed the best (R2/RMSE (nmol/cm2): 0.93/2.18 in the calibration, and 0.93/2.20 in the validation) of all the investigated methods. The PLSR model involved four wavelengths and achieved relatively low accuracy (R2/RMSE (nmol/cm2): 0.87/2.88 in calibration, and 0.88/2.89 in validation). GPR apparently outperformed PLSR. The reason was likely that the non-linear property made GPR more effective than the linear PLSR in characterizing the relationship for the absorbance vs. content of anthocyanins. For GPR, selected wavelengths around the green peak and red edge region (one from each) were promising to build simple and accurate two-wavelength models with R2 > 0.90.


Asunto(s)
Antocianinas , Hojas de la Planta , Clorofila , Análisis de los Mínimos Cuadrados , Modelos Lineales
7.
J Environ Manage ; 289: 112437, 2021 Jul 01.
Artículo en Inglés | MEDLINE | ID: mdl-33812149

RESUMEN

Low-density polyethylene (LDPE) passive sampling is very attractive for use in determining chemicals concentrations. Crucial to the measurement is the coefficient (KPE) describing partitioning between LDPE and environmental matrices. 255, 117 and 190 compounds were collected for the development of datasets in three different matrices, i.e., water, air and seawater, respectively. Further, 3 pp-LFER models and 9 QSPR models based on classical multiple linear regression (MLR) coupled with prevalent nonlinear algorithms (artificial neural network, ANN and support vector machine, SVM) were performed to predict LDPE-water (KPE-W), LDPE-air (KPE-A) and LDPE-seawater (KPE-SW) partition coefficients. These developed models have satisfying predictability (R2adj: 0.805-0.966, 0.963-0.991 and 0.817-0.941; RMSEtra: 0.233-0.565, 0.200-0.406 and 0.260-0.459) and robustness (Q2ext: 0.840-0.943, 0.968-0.984 and 0.797-0.842; RMSEext: 0.308-0.514, 0.299-0.426 and 0.407-0.462) in three datasets (water, air and seawater), respectively. In particular, the reasonable mechanism interpretations revealed that the molecular size, hydrophobicity, polarizability, ionization potential, and molecular stability were the most relevant properties, for governing chemicals partitioning between LDPE and environmental matrices. The application domains (ADs) assessed here exhibited the satisfactory applicability. As such, the derived models can act as intelligent tools to predict unknown KPE values and fill the experimental gaps, which was further beneficial for the construction of enormous and reliable database to facilitate a distinct understanding of the distribution for organic contaminants in total environment.


Asunto(s)
Polietileno , Agua , Simulación por Computador , Interacciones Hidrofóbicas e Hidrofílicas , Modelos Lineales
8.
J Environ Manage ; 289: 112509, 2021 Jul 01.
Artículo en Inglés | MEDLINE | ID: mdl-33836439

RESUMEN

Rural land valuation plays an important role in the development of land use policies for agricultural purposes. The advance of computational software and machine learning methods has enhanced mass appraisal methodologies for modeling and predicting economic values. New machine learning methods, like tree-based regression models, have been proposed as an alternative to linear regression to predict economic values from ancillary variables, since these algorithms are able to handle non-normality and non-linearity in the data. However, regression trees are commonly estimated assuming independent rather than spatially correlated data. This study aims to build a tree-based regression model that will help to tackle methodological problems related to the determination of prices of rural lands. The Quantile Regression Forest (QRF) algorithm was used to provide a regression model to predict and assess the uncertainty associated with model-derived predictions. However, the classical QRF ignores the autocorrelation underlying spatialized land values. The objective of this work was to develop, implement, and evaluate a spatial version of QRF, named sQRF, for computer-assisted mass appraisal of rural land values accounting for information from neighboring sites. We compared predictions of land values from sQRF with those obtained from spatial random forest, kriging regression, and linear regression models. sQRF performed well in predicting rural land values; indeed, it performed better than multiple linear regression. An important feature of sQRF is its ability to produce a direct uncertainty measure to assess the goodness of the predictions. Land values reflect a complex mix of agricultural returns, localization, and access to markets, which can be predicted from ancillary environmental variables. Good predictive models are essential to determine land values for multiple purposes including territorial taxation.


Asunto(s)
Monitoreo del Ambiente , Aprendizaje Automático , Algoritmos , Modelos Lineales , Análisis Espacial
9.
Front Public Health ; 9: 641253, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33898377

RESUMEN

Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century post-the Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, which is responsible for Covid-19. It emerged from the city of Wuhan (China) in December 2019, and within a few months, the virus propagated itself globally now resulting more than 50 million cases with over 1 million deaths. The high infection rates coupled with dynamic population movement demands for tools, especially within a Brazilian context, that will support health managers to develop policies for controlling and combating the new virus. Methods: In this work, we propose a tool for real-time spatio-temporal analysis using a machine learning approach. The COVID-SGIS system brings together routinely collected health data on Covid-19 distributed across public health systems in Brazil, as well as taking to under consideration the geographic and time-dependent features of Covid-19 so as to make spatio-temporal predictions. The data are sub-divided by federative unit and municipality. In our case study, we made spatio-temporal predictions of the distribution of cases and deaths in Brazil and in each federative unit. Four regression methods were investigated: linear regression, support vector machines (polynomial kernels and RBF), multilayer perceptrons, and random forests. We use the percentage RMSE and the correlation coefficient as quality metrics. Results: For qualitative evaluation, we made spatio-temporal predictions for the period from 25 to 27 May 2020. Considering qualitatively and quantitatively the case of the State of Pernambuco and Brazil as a whole, linear regression presented the best prediction results (thematic maps with good data distribution, correlation coefficient >0.99 and RMSE (%) <4% for Pernambuco and around 5% for Brazil) with low training time: [0.00; 0.04 ms], CI 95%. Conclusion: Spatio-temporal analysis provided a broader assessment of those in the regions where the accumulated confirmed cases of Covid-19 were concentrated. It was possible to differentiate in the thematic maps the regions with the highest concentration of cases from the regions with low concentration and regions in the transition range. This approach is fundamental to support health managers and epidemiologists to elaborate policies and plans to control the Covid-19 pandemics.


Asunto(s)
/epidemiología , Monitoreo Epidemiológico , Brasil/epidemiología , Predicción , Humanos , Modelos Lineales , Redes Neurales de la Computación , Análisis Espacio-Temporal , Máquina de Vectores de Soporte
10.
Front Public Health ; 9: 643640, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33898378

RESUMEN

Background: The COVID-19 pandemic hit Brazil in a scenario of substantial socioeconomic and health inequalities. It is unknown the immediate impact of social restriction recommendations (i.e., lockdown, stay-at-home) on the life-space mobility of older people. Objective: To investigate the immediate impact of COVID-19 pandemic on life-space mobility of community-dwelling Brazilian older adults and examine the social determinants of health associated with change in life-space mobility. Design: Baseline data from a prospective cohort study (REMOBILIZE Study). Setting: Community. Subject: A convenience snowball sample of participants aged 60 and older (n = 1,482) living in 22 states in Brazil. Methods: We conducted an online and phone survey using an adapted version of the Life-Space Assessment (LSA). Linear regression models were used to investigate social determinants of health on the change in LSA score. Results: Regardless of their gender and social determinants of health, participants showed a significant reduction in life-space mobility since COVID-19 pandemic outbreak. Life-space mobility reduction was higher among black individuals, those living alone and aged between 70 and 79. Other variables associated with change in life-space mobility, to a lesser extent, were sex, education and income. Conclusion: Social restriction measures due to pandemic caused substantial reduction in older adults' life-space mobility in Brazil. Social inequalities strongly affected vulnerable groups. Concerted actions should be put in place to overcome the deterioration in life-pace mobility amongst these groups. Failure in minimizing health inequalities amplified by the pandemic may jeopardize the desired achievements of the Decade of Healthy Aging.


Asunto(s)
Pandemias , Determinantes Sociales de la Salud , Anciano , Anciano de 80 o más Años , Brasil/epidemiología , Control de Enfermedades Transmisibles , Femenino , Disparidades en el Estado de Salud , Humanos , Modelos Lineales , Masculino , Persona de Mediana Edad , Estudios Prospectivos , Factores Socioeconómicos , Encuestas y Cuestionarios
11.
Artículo en Chino | MEDLINE | ID: mdl-33910293

RESUMEN

Objective: To determine hydrazine quantitatively in workplace air by gas chromatography with large bore capillary column. Methods: In October 2019, hydrazine in the air was adsorbed by acid silica gel tube sampling and desorped using sulfuric acid solution. After derivatization with furfural and extraction, the content of hydrazine was determined by DM-FFAP capillary column gas chromatography with flame ionization detector. Results: The linear regression equation was y=353.8x+21.2 (r=0.9998) between 0.1-2.0 µg/ml of target concentration. The detection limit was 0.030 µg/ml. The lower limit of quantification was 0.100 µg/ml. If 15 L air sample was collected, the minimum detection concentration was 0.004 mg/m(3) and the minimum quantitative concentration was 0.013 mg/m(3) respectively. The average desorption efficiency was 86.5%-89.4%. The recovery was 94.4%-97.1%. The relative standard deviation was 1.6%-4.9%. Hydrazine and furfural derivative was 2-furaldehyde hydrazine. Conclusion: The method has symmetrical peak shape of hydrazine derivatives chromatographic peaks, short analysis time, easy operation, and is suitable for the determination of the concentration of hydrazine in the air in the workplace.


Asunto(s)
Contaminantes Ocupacionales del Aire , Lugar de Trabajo , Contaminantes Ocupacionales del Aire/análisis , Cromatografía de Gases , Hidrazinas , Modelos Lineales
12.
Nat Commun ; 12(1): 2003, 2021 03 31.
Artículo en Inglés | MEDLINE | ID: mdl-33790282

RESUMEN

Understanding how activity of visual neurons represents distinct components of attention and their dynamics that account for improved visual performance remains elusive because single-unit experiments have not isolated the intensive aspect of attention from attentional selectivity. We isolated attentional intensity and its single trial dynamics as determined by spatially non-selective attentional performance in an orientation discrimination task while recording from neurons in monkey visual area V4. We found that attentional intensity is a distinct cognitive signal that can be distinguished from spatial selectivity, reward expectations and motor actions. V4 spiking on single trials encodes a combination of sensory and cognitive signals on different time scales. Attentional intensity and the detection of behaviorally relevant sensory signals are well represented, but immediate reward expectation and behavioral choices are poorly represented in V4 spiking. These results provide a detailed representation of perceptual and cognitive signals in V4 that are crucial for attentional performance.


Asunto(s)
Algoritmos , Atención/fisiología , Macaca mulatta/fisiología , Neuronas/fisiología , Corteza Visual/fisiología , Percepción Visual/fisiología , Animales , Fenómenos Electrofisiológicos , Modelos Lineales , Masculino , Estimulación Luminosa/métodos , Pupila/fisiología , Corteza Visual/citología
13.
Med Educ Online ; 26(1): 1913785, 2021 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-33849405

RESUMEN

Coronavirus disease 2019 (COVID-19) pandemic has brought unprecedented challenges to medical education systems and medical students. The aim of this study was to investigate the effects of COVID-19 pandemic on medical career and specialty choices among medical students. An online cross-sectional survey of Chinese medical students was conducted during the COVID-19 pandemic from February to April 2020. The students' willingness to be a doctor before and after the COVID-19 pandemic and changed willingness to specialize in respiratory medicine and infectious diseases were investigated. Multiple linear regression and binary logistic regression was used to explore factors that were associated with changes of willingness. A total of 1,837 medical students, including 1,227 females (66.8%), with a median age of 21.0 years, were recruited. Of the participants, 10.6% and 6.9% showed increased and decreased willingness to be a doctor after the COVID-19 outbreak, respectively. Moreover, 11.7% showed increased willingness and 9.5% showed decreased willingness to major in respiratory medicine and infectious diseases. Students with younger age, lower household income, fewer depressive symptoms, less exposure to negative pandemic information and more satisfaction with their own major after the pandemic were associated with increased willingness to be a doctor. Students who engaged in regular exercise, were males and undergraduate level, were interested in medicine, paid more attention to positive information, were satisfied with their majors, and had increased willingness to be a doctor after the pandemic were more likely to choose to specialize in respiratory medicine and infectious disease. However, the severity of anxiety symptoms was associated with decreased willingness to work in the specialties of respiratory medicine and infectious diseases. Psychological problems and professional satisfaction appear to be independent factors that affect medial career and specialty choices. The impacts of the COVID-19 pandemic on medical students require further research.


Asunto(s)
Selección de Profesión , Especialización , Estudiantes de Medicina , Ansiedad/epidemiología , China/epidemiología , Estudios Transversales , Femenino , Humanos , Modelos Lineales , Masculino , Pandemias , Estudiantes de Medicina/psicología , Encuestas y Cuestionarios , Adulto Joven
14.
J Chromatogr A ; 1645: 462108, 2021 May 24.
Artículo en Inglés | MEDLINE | ID: mdl-33857674

RESUMEN

The solvation parameter model affords a useful tool to model distribution properties of neutral compounds in biphasic separation systems. Common applications include column characterization and method development in gas chromatography; reversed-phase, micellar and hydrophilic interaction liquid chromatography; supercritical fluid chromatography; and micellar electrokinetic chromatography. The characterization of the distribution properties of liquid-liquid partition systems is another major application of this model. This tutorial is aimed at establishing good practices for the application of the model to separation systems. Suitable experimental protocols to determine system constants by multiple linear regression analysis and descriptors by the Solver method are presented; statistical tools to evaluate model quality are discussed; and model-specific data analysis tools based on system maps and correlation diagrams are described.


Asunto(s)
Cromatografía de Gases , Cromatografía Liquida , Extracción Líquido-Líquido , Modelos Químicos , Modelos Lineales
15.
Int J Mol Sci ; 22(5)2021 Mar 06.
Artículo en Inglés | MEDLINE | ID: mdl-33800928

RESUMEN

Long non-coding RNAs (lncRNAs) play important roles in multiple biological processes including ovarian follicular development. Here we aimed to gain novel information regarding lncRNAs transcriptome profiles in porcine granulosa cells of advanced atretic antral (AA) and healthy antral (HA) follicles using RNA-seq. A total of 11,321 lncRNAs including 10,813 novel and 508 annotated lncRNAs were identified, of which 173 lncRNAs were differentially expressed (DE-lncRNAs); ten of these were confirmed by qRT-PCR. Gene Ontology indicated that DE-lncRNAs associated with developmental processes were highly enriched. Pathway analysis demonstrated predicted cis- and trans-targets of DE-lncRNAs. Potential mRNA targets of up-regulated DE-lncRNAs were mainly enriched in apoptosis related pathways, while targeted genes of downregulated DE-lncRNAs were primarily enriched in metabolism and ovarian steroidogenesis pathways. Linear regression analyses showed that expression of upregulated DE-lncRNAs was significantly associated with apoptosis related genes. NOVEL_00001850 is the most-downregulated DE-lncRNA (FDR = 0.04, FC = -6.53), of which miRNA binding sites were predicted. KEGG analysis of its downregulated target genes revealed that ovarian steroidogenesis was the second most highlighted pathway. qRT-PCR and linear regression analysis confirmed the expression and correlation of its potential targeted gene, CYP19A1, a key gene involved in estradiol synthesis. Our results indicate that lncRNAs may participate in granulosa cells apoptosis and thus antral follicular atresia.


Asunto(s)
Apoptosis/genética , Células de la Granulosa/metabolismo , Folículo Ovárico/metabolismo , ARN Largo no Codificante/genética , Animales , Ciclo Estral/genética , Femenino , Regulación de la Expresión Génica , Ontología de Genes , Modelos Lineales , MicroARNs/genética , MicroARNs/metabolismo , ARN Circular/genética , Reacción en Cadena en Tiempo Real de la Polimerasa , Porcinos , Transcriptoma , Regulación hacia Arriba
16.
Int. j. clin. health psychol. (Internet) ; 21(1): 191-191, ene.-abr. 2021. tab
Artículo en Inglés | IBECS | ID: ibc-200209

RESUMEN

BACKGROUND/OBJECTIVE: Most studies have evaluated victimization at a single time point, making it difficult to determine the impact of the time during which an individual is victimized. This longitudinal study aims to examine the differences in the levels of social status (social preference and perceived popularity) and friendship in peer victimization trajectories, and to analyse if there were changes over time in the levels of social status and friendship in each trajectory. METHOD: The final sample was composed of 1,239 students (49% girls) with ages between 9 and 18 (M = 12.23, SD = 1.73), from 22 schools in southern Spain. Peer nominations were collected. RESULTS: The General Linear Model results associated the highest levels of social preference, perceived popularity and friendship with the sporadic victimization profile and the lowest levels of these dimensions with the stable profile. CONCLUSIONS: The results are discussed based on important personal aspects of stable victimization that confirms social rejection, unpopularity, and the low social support that victimization causes. This contribution is discussed in terms of health and social welfare in adolescence


ANTECEDENTES/OBJETIVO: La mayoría de los estudios han evaluado la victimización en un único momento temporal, lo que impide determinar el impacto del tiempo durante el que un individuo es victimizado. Este estudio longitudinal pretende examinar las diferencias en los niveles de estatus social (preferencia social y popularidad percibida) y amistad entre las diferentes trayectorias de las víctimas de iguales en función de su trayectoria de victimización, y explorar si existen cambios con el paso del tiempo en los niveles de estatus social y amistad de cada trayectoria. MÉTODO: La muestra se compuso por 1.239 estudiantes (49% chicas) entre 9 y 18 años (M = 12,23, DT = 1,73), pertenecientes a 22 centros educativos del sur de España. Se utilizaron las hetero-nominaciones de sus iguales dentro del grupo de clase. RESULTADOS: Los resultados del Modelo Lineal General asociaron los niveles más altos de preferencia social, popularidad percibida y amistad a la victimización esporádica, y los niveles más bajos de estas dimensiones a la trayectoria estable. CONCLUSIONES: Los resultados se discuten en base al rechazo social, la impopularidad y los escasos apoyos sociales que provoca la victimización. Se valora esta aportación a nivel de salud y bienestar social adolescente


Asunto(s)
Humanos , Masculino , Femenino , Niño , Adolescente , Clase Social , Amigos/psicología , Víctimas de Crimen/psicología , Influencia de los Compañeros , Estudios Longitudinales , Conducta del Adolescente/psicología , Estudiantes/psicología , Factores Sexuales , Modelos Lineales
17.
Int. j. clin. health psychol. (Internet) ; 21(1): 200-200, ene.-abr. 2021. tab, graf
Artículo en Inglés | IBECS | ID: ibc-200212

RESUMEN

BACKGROUND/OBJECTIVE: The aim was to evaluate the evolution of depressive symptoms and to explore the influence of physical activity (PA) practice during the home confinement due to the COVID-19 outbreak in Spain. METHOD: Information was collected from 595 confined participants who reported personal and contextual information, depressive symptoms and PA levels at four time points. RESULTS: The changes in depressive symptoms were analyzed using a linear mixed model with cubic splines. Results showed a significant increase, with a significant rise between T1 and T2 (OR = 2.38, 95% CI = 1.83-3.10). It continued growing until T4 (OR = 2.93, 95% CI = 1.97-4.38). A negative relationship was observed between the increase in depressive symptoms and moderate-to-vigorous physical activity (MVPA) levels, with a significant slope up to 4 hours of MVPA per week (OR = 0.51, 95% CI = 0.29-0.90) that tended to increase until 16 hours per week of MVPA (OR = 0.41, 95% CI = 0.20-0.87). CONCLUSIONS: Results from a partition model showed that moderate intensity of PA could be enough to prevent an increase of depressive symptoms during home isolation


ANTECEDENTES/OBJETIVO: El objetivo fue evaluar la evolución de los síntomas depresivos y explorar la influencia de la práctica de actividad física (AF) durante la fase de confinamiento domiciliario de la población española como consecuencia de la enfermedad del coronavirus 2019 (COVID-19). MÉTODO: Participaron 595 personas confinadas que informaron de su situación personal, los síntomas depresivos y la AF en cuatro momentos de medida. RESULTADOS: Los cambios en los síntomas depresivos analizados con splines cúbicos a partir de modelos lineales mixtos, mostraron un incremento significativo, con una subida importante entre el T1 y el T2 (OR = 2,38, 95% CI = 1,83-3,10), para luego seguir incrementándose de manera más lenta hasta el T4 (OR = 2,93, 95% CI = 1,97-4,38). Se observó una relación inversa entre el incremento de los síntomas depresivos y los niveles de actividad física moderada-vigorosa (AFMV) semanal, con una pendiente importante hasta las cuatro horas de AFMV a la semana (OR = 0,51, 95% CI = 0,29-0,90) que tiende a disminuir hasta las 16 horas/semana AFMV (OR = 0,41, 95% CI = 0,20-0,87). CONCLUSIONES: Se probó un modelo de partición que mostró que la AF de intensidad moderada podría ser suficiente para prevenir un incremento de los síntomas depresivos en situación de confinamiento


Asunto(s)
Humanos , Masculino , Femenino , Adolescente , Adulto Joven , Adulto , Persona de Mediana Edad , Anciano , Anciano de 80 o más Años , Depresión/prevención & control , Depresión/psicología , Ejercicio Físico/psicología , Cuarentena/psicología , Estudios Transversales , Encuestas y Cuestionarios , Infecciones por Coronavirus/prevención & control , Factores de Riesgo , Modelos Lineales , Factores de Tiempo , España/epidemiología , Pandemias
18.
Int. j. clin. health psychol. (Internet) ; 21(1): 201-201, ene.-abr. 2021. graf, tab
Artículo en Inglés | IBECS | ID: ibc-200213

RESUMEN

BACKGROUND/OBJECTIVE: Long-term childhood cancer survivors (CCS) are at risk for adverse late effects. However, not all of them are well understood. The present study addressed loneliness, a previously under-researched mental health risk in cancer survivor populations. We assessed the prevalence of loneliness and its impact on psychological symptoms over time. METHOD: A registry-based sample of N=633 adult long-term CCS underwent medical and psychological assessments and took part in a follow-up survey 2.5 years later. Psychological symptoms (somatic, anxiety, depression symptoms, and suicidal ideation) were measured using the Patient Health Questionnaire. We calculated linear regression models of symptoms at follow-up to investigate the impact of loneliness over time (controlling for symptoms at baseline and relevant confounders). RESULTS: Loneliness was reported by 17.70% of CCS. In multivariate linear regression analyses, loneliness was still predictive of more severe anxiety symptoms and suicidal ideation over two years later. Loneliness did not predict somatic and depression symptoms at follow-up (which increased with age). CONCLUSIONS: Loneliness affected a significant number of CCS and was a risk factor for persistent anxiety symptoms and suicidal ideation. The extent to which young cancer patients' re-integration into society is successful could thus have important implications for well-being in adulthood


ANTECEDENTE/OBJETIVO: Los sobrevivientes a largo plazo de cáncer infantil (SCI) están en riesgo de sufrir efectos tardíos. Evaluamos la prevalencia de la soledad y su impacto en los síntomas psicológicos a lo largo del tiempo. MÉTODO: Una muestra de N=633 adultos con un pasado de SCI se sometió a evaluaciones médicas y psicológicas y participó en una encuesta de seguimiento 2,5 años después. Los síntomas psicológicos se midieron mediante el Patient Health Questionnaire. Calculamos modelos de regresión lineal de síntomas en el seguimiento para investigar el impacto de la soledad a lo largo del tiempo (controlando los síntomas al inicio y los factores de confusión relevantes). RESULTADOS: La soledad fue reportada por el 17,70% de SCI. La soledad seguía siendo predictiva de síntomas de ansiedad más graves e ideación suicida dos años después. La soledad no predijo los síntomas somáticos y de depresión durante el seguimiento (que aumentaron con la edad). CONCLUSIONES: La soledad fue un factor de riesgo para síntomas de ansiedad persistente e ideación suicida. La medida en que la reintegración de los pacientes jóvenes con cáncer en la sociedad tenga éxito podría tener importantes implicaciones para el bienestar en la edad adulta


Asunto(s)
Humanos , Masculino , Femenino , Adulto , Adultos Sobrevivientes de Eventos Adversos Infantiles/psicología , Supervivientes de Cáncer/psicología , Soledad/psicología , Ideación Suicida , Ansiedad/psicología , Factores de Riesgo , Encuestas y Cuestionarios , Factores Socioeconómicos , Modelos Lineales , Escalas de Valoración Psiquiátrica , Alemania/epidemiología
19.
J Chromatogr A ; 1642: 462036, 2021 Apr 12.
Artículo en Inglés | MEDLINE | ID: mdl-33714770

RESUMEN

Biomonitoring is a potent tool to control the health risk of people occupationally and non-occupationally exposed. The latest trend in bioanalytical chemistry is to develop quick, cheap, easy, safe and reliable green analytical procedures to analyse a large number of chemicals in easily accessible biomatrices such as urine. In this paper, a new dispersive liquid-liquid microextraction (DLLME) procedure, conceived to treat urine samples and based on the use of a low transition temperature mixture (LTTM), was developed and validated to analyse twenty pesticides commonly used in farm practises. The LTTM was composed of choline chloride and sesamol in molar ratio 1:3 (ChCl:Ses 1:3); its characterization via differential scanning calorimetry identified it as an LTTM and not as a deep eutectic solvent due to the occurrence of a glass transition at -71 °C. The prepared mixture was used as the extraction solvent in the DLLME procedure, while ethyl acetate as the dispersing solvent. The salting out effect (50 mg mL-1 of NaCl in a diluted urine sample) improved the separation phase and the analyte transfer to the extractant. Due to the high ionic strength and despite the density of ChCl:Ses 1:3 (1.25 g mL-1), the LTTM layer floated on the top of the sample solution after centrifugation. All extracts were analysed by high-performance liquid chromatography coupled to mass spectrometry. After optimization and validation of the whole method, lower limits of quantitation were in the range of 0.02 - 0.76 µg  L-1. Extraction recoveries spanned from 50 to 101 % depending on the spike level and analytes. Precision and accuracy ranges were 3-18% and 5-20%, respectively. The extraction procedure was also compared with other methods, showing to be advantageous for rapidity, simplicity, efficiency, and low cost. Finally, urine samples from ten volunteers were effectively analysed using the developed method.


Asunto(s)
Cromatografía Líquida de Alta Presión , Frío , Microextracción en Fase Líquida/métodos , Espectrometría de Masas , Plaguicidas/orina , Temperatura de Transición , Adulto , Rastreo Diferencial de Calorimetría , Femenino , Humanos , Límite de Detección , Modelos Lineales , Masculino , Persona de Mediana Edad , Concentración Osmolar , Solventes/química , Factores de Tiempo , Adulto Joven
20.
Br J Surg ; 108(2): 220-227, 2021 03 12.
Artículo en Inglés | MEDLINE | ID: mdl-33711143

RESUMEN

BACKGROUND: Postoperative infection is one of the most frequent and important complications after surgery. The epidemiology of infection following elective surgery remains poorly described. METHODS: This was a prospective analysis of the International Surgical Outcomes Study (ISOS) describing infection by 30 days after elective surgery. Associations between postoperative infection (primary outcome) and baseline demographic, surgical, and anaesthetic risk factors were assessed. Analyses were carried out using logistic and linear regression models. Secondary outcomes were 30-day mortality and duration of hospital stay. Treatments received by patients after different types of infection were evaluated. RESULTS: Some 44 814 patients were included in the analysis, with a total of 4032 infections occurring in 2927 patients (6.5 per cent). Overall, 206 patients died, of whom 99 of 2927 (3.4 per cent) had infection. Some 737 of 4032 infections (18.3 per cent) were severe; the most frequent types were superficial surgical-site infection (1320, 32.7 per cent), pneumonia (708, 17.6 per cent), and urinary tract infection (681, 16.9 per cent). Excluding missing data, antimicrobials were used in 2126 of 2749 infections (77.3 per cent), and 522 of 2164 patients (24.1 per cent) required admission to critical care. Factors associated with an increased incidence of infection in adjusted analyses were: age, male sex, ASA grade, co-morbid disease, preoperative anaemia, anaesthetic technique, surgical category, surgical severity, and cancer surgery. Infection significantly increased the risk of death (odds ratio 4.68, 95 per cent c.i. 3.39 to 6.47; P < 0.001), and duration of hospital stay by on average 6.45 (6.23 to 6.66) days (P < 0.001). CONCLUSION: Infection is a common complication after elective surgery. Recognition of modifiable risk factors will help inform appropriate prevention strategies.


Asunto(s)
Procedimientos Quirúrgicos Electivos/efectos adversos , Infección de la Herida Quirúrgica/epidemiología , Adulto , Anciano , Procedimientos Quirúrgicos Electivos/mortalidad , Femenino , Humanos , Tiempo de Internación/estadística & datos numéricos , Modelos Lineales , Modelos Logísticos , Masculino , Persona de Mediana Edad , Estudios Prospectivos , Factores de Riesgo
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