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  • Frontiers Media SA  (56)
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  • Frontiers Media SA  (56)
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  • 1
    Online Resource
    Online Resource
    Sleep quality and its associated factors among patients with tuberculosis: A cross-sectional study
    Frontiers Media SA ; 2023
    In:  Frontiers in Public Health Vol. 10 ( 2023-1-4)
    Details
    In: Frontiers in Public Health, Frontiers Media SA, Vol. 10 ( 2023-1-4)
    Abstract: Tuberculosis (TB) patients commonly suffer from sleep issues owing to various adverse drug reactions (ADRs), disease symptoms, and the contagious nature of their disease. These sleep issues negatively affect the treatment outcome and quality of life. However, the prevalence of sleep disturbance and its associated factors among TB patients have rarely been reported. Methods A total of 497 inpatients with TB from three hospitals in China were enrolled in this cross-sectional study to investigate their sleep quality using the Pittsburgh sleep quality index (PSQI). Clinical data, including demographic information, TB-related stigma, perceived stress, and nutrition- and immunity-related indicators, were also collected to explore the factors associated with sleep disturbance among the recruited patients. Results Approximately 70% of the recruited patients reported a sleep disturbance to varying degrees, presenting poorer global and subjective sleep qualities, longer sleep latency, shorter sleep duration, lower sleep efficiency, more frequent sleep disturbances, greater use of sleeping medication, and more severe daytime dysfunction. Furthermore, the body mass index (BMI), hemoglobin levels, albumin levels, and T lymphocyte count of the patients in the poor sleep quality group were significantly lower than those in the good sleep quality group ( p & lt; 0.05). Increasing age, higher income, drug resistance, higher stigma or stress perception, lower albumin levels, and lower CD4 levels were significantly associated with sleep disturbance among TB patients ( p & lt; 0.05). Conclusion Three-quarters of the participants were found to suffer from a probable sleep disturbance. And sleep problems are linked to biological traits that interact with psychological, cultural, and social factors in complex ways. It is therefore important to pay attention to the sleep quality of TB patients, especially those with the identified risk factors. Besides, taking care of these risk factors may prove to be an effective sleep management strategy.
    Type of Medium: Online Resource
    ISSN: 2296-2565
    URL: Article
    DOI: 10.3389/fpubh.2022.1047425
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2711781-9
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  • 2
    Online Resource
    Online Resource
    Constructing a prediction model of inflammatory bowel disease recurrence based on factors affecting the quality of life
    Frontiers Media SA ; 2023
    In:  Frontiers in Medicine Vol. 10 ( 2023-3-9)
    Details
    In: Frontiers in Medicine, Frontiers Media SA, Vol. 10 ( 2023-3-9)
    Abstract: This study aimed to determine the factors affecting the quality of life of patients with inflammatory bowel disease (IBD) and to construct a disease recurrence prediction model based on these influencing factors. Methods A prospective, single-center study in China was conducted between October 2020 and March 2021. The quality of life of patients was assessed using the Inflammatory Bowel Disease Questionnaire (IBDQ). Multiple stepwise regression analysis was used to analyze the factors influencing the quality of life of patients with IBD. The chi-square test and the point-biserial correlation analysis were performed to identify factors associated with clinical recurrence. A binary logistic regression model was constructed to predict the recurrence. The receiver operating characteristic curve was used to evaluate the prediction model. Patients with IBD from April 2021 to June 2021 were randomly included for model verification to evaluate the disease recurrence prediction model. Results The average IBDQ score of patients with IBD was 172.2 ± 35.0 (decreased by 23.2%). The scores of all dimensions of the IBDQ were decreased, especially emotional function and systemic symptoms. Disease activity, age, extraintestinal manifestations (EIMs), and annual household income were important factors influencing the IBDQ scores of patients with ulcerative colitis, and these accounted for ~57.0% of the factors affecting the quality of life. Disease activity, EIMs, and occupational stress were important factors influencing the IBDQ scores of patients with Crohn's disease, and they accounted for approximately 75.1% of the factors affecting the quality of life. Annual household income, occupational stress, and IBDQ scores were independent risk factors for recurrence. The area under the curve of the recurrence prediction model was 81.1%. The sensitivity and specificity were 81.7 and 71.7%, respectively. The Youden index of the model was 0.534. The established recurrence prediction model has good discriminant validity in the validation cohort. Conclusion The quality of life of patients with IBD was generally poor. The use of factors affecting the quality of life to predict disease recurrence has high predictive value and can support the management of IBD by selecting patients at a higher risk for relapse.
    Type of Medium: Online Resource
    ISSN: 2296-858X
    URL: Article
    DOI: 10.3389/fmed.2023.1041505
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2775999-4
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  • 3
    Online Resource
    Online Resource
    β2-Adrenergic Receptor-Mediated HIF-1α Upregulation Mediates Blood Brain Barrier Damage in Acute Cerebral Ischemia
    Frontiers Media SA ; 2017
    In:  Frontiers in Molecular Neuroscience Vol. 10 ( 2017-08-14)
    Details
    In: Frontiers in Molecular Neuroscience, Frontiers Media SA, Vol. 10 ( 2017-08-14)
    Type of Medium: Online Resource
    ISSN: 1662-5099
    URL: Article
    DOI: 10.3389/fnmol.2017.00257
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2017
    detail.hit.zdb_id: 2452967-9
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  • 4
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    Online Resource
    A Leaf Modeling and Multi-Scale Remeshing Method for Visual Computation via Hierarchical Parametric Vein and Margin Representation
    Frontiers Media SA ; 2018
    In:  Frontiers in Plant Science Vol. 9 ( 2018-6-26)
    Details
    In: Frontiers in Plant Science, Frontiers Media SA, Vol. 9 ( 2018-6-26)
    Type of Medium: Online Resource
    ISSN: 1664-462X
    URL: Article
    DOI: 10.3389/fpls.2018.00783
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2018
    detail.hit.zdb_id: 2687947-5
    detail.hit.zdb_id: 2613694-6
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  • 5
    Online Resource
    Online Resource
    Table_2.xlsx
    Frontiers Media SA ; 2023
    In:  Frontiers in Plant Science Vol. 14 ( 2023-6-9)
    Details
    In: Frontiers in Plant Science, Frontiers Media SA, Vol. 14 ( 2023-6-9)
    Abstract: Xinjiang is the largest grape-producing region in China and the main grape cultivation area in the world. The Eurasian grape resources grown in Xinjiang are very rich in diversity. The sugar composition and content are the main factors that determine the quality of berries. However, there are currently no systematic reports on the types and contents of sugars in grapes grown in Xinjiang region. In this research, we evaluated the appearance and fruit maturity indicators of 18 grape varieties during fruit ripening and determined their sugar content using GC-MS. All cultivars primarily contained glucose, D-fructose, and sucrose. The glucose content in varieties varied from 42.13% to 46.80% of the total sugar, whereas the fructose and sucrose contents varied from 42.68% to 50.95% and 6.17% to 12.69%, respectively. The content of trace sugar identified in grape varieties varied from 0.6 to 2.3 mg/g. The comprehensive assessment by principal component analysis revealed strong positive correlations between some sugar components. A comprehensive study on the content and types of sugar will provide the foundation to determine the quality of grape cultivars and effective ways to utilize resources to improve sugar content through breeding.
    Type of Medium: Online Resource
    ISSN: 1664-462X
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fpls.2023.1200071
    DOI: 10.3389/fpls.2023.1200071.s001
    DOI: 10.3389/fpls.2023.1200071.s002
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2687947-5
    detail.hit.zdb_id: 2613694-6
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  • 6
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    Online Resource
    Table_1.xlsx
    Frontiers Media SA ; 2023
    In:  Frontiers in Plant Science Vol. 14 ( 2023-8-28)
    Details
    In: Frontiers in Plant Science, Frontiers Media SA, Vol. 14 ( 2023-8-28)
    Abstract: The morphology of maize ears plays a critical role in the breeding of new varieties and increasing yield. However, the study of traditional ear-related traits alone can no longer meet the requirements of breeding. In this study, 20 ear-related traits, including size, shape, number, and color, were obtained in 407 maize inbred lines at two sites using a high-throughput phenotypic measurement method and system. Significant correlations were found among these traits, particularly the novel trait ear shape (ES), which was correlated with traditional traits: kernel number per row and kernel number per ear. Pairwise comparison tests revealed that the inbred lines of tropical-subtropical were significantly different from other subpopulations in row numbers per ear, kernel numbers per ear, and ear color. A genome-wide association study identified 275, 434, and 362 Single nucleotide polymorphisms (SNPs) for Beijing, Sanya, and best linear unbiased prediction scenarios, respectively, explaining 3.78% to 24.17% of the phenotypic variance. Furthermore, 58 candidate genes with detailed functional descriptions common to more than two scenarios were discovered, with 40 genes being associated with color traits on chromosome 1. After analysis of haplotypes, gene expression, and annotated information, several candidate genes with high reliability were identified, including Zm00001d051328 for ear perimeter and width, zma-MIR159f for ear shape, Zm00001d053080 for kernel width and row number per ear, and Zm00001d048373 for the blue color channel of maize kernels in the red-green-blue color model. This study emphasizes the importance of researching novel phenotypic traits in maize by utilizing high-throughput phenotypic measurements. The identified genetic loci enrich the existing genetic studies related to maize ears.
    Type of Medium: Online Resource
    ISSN: 1664-462X
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fpls.2023.1248446
    DOI: 10.3389/fpls.2023.1248446.s001
    DOI: 10.3389/fpls.2023.1248446.s002
    DOI: 10.3389/fpls.2023.1248446.s003
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2687947-5
    detail.hit.zdb_id: 2613694-6
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  • 7
    Online Resource
    Online Resource
    Video_1.MP4
    Frontiers Media SA ; 2022
    In:  Frontiers in Plant Science Vol. 13 ( 2022-8-18)
    Details
    In: Frontiers in Plant Science, Frontiers Media SA, Vol. 13 ( 2022-8-18)
    Abstract: Canopy photosynthesis integrates leaf functional and structural traits in space and time and correlates positively with yield formation. Many models with different levels of architectural details ranging from zero-dimensional (0D) to three-dimensional (3D) have been developed to simulate canopy light interception and photosynthesis. Based on these models, a crop growth model can be used to assess crop yield in response to genetic improvement, optimized practices, and environmental change. However, to what extent do architectural details influence light interception, photosynthetic production, and grain yield remains unknown. Here, we show that a crop growth model with high-resolution upscaling approach in space reduces the departure of predicted yield from actual yield and refines the simulation of canopy photosynthetic production. We found crop yield predictions decreased by 12.0–48.5% with increasing the resolution of light simulation, suggesting that a crop growth model without architectural details may result in a considerable departure from the actual photosynthetic production. A dramatic difference in light interception and photosynthetic production of canopy between cultivars was captured by the proposed 3D model rather than the 0D, 1D, and 2D models. Furthermore, we found that the overestimation of crop yield by the 0D model is caused by the overestimation of canopy photosynthetically active radiation (PAR) interception and the RUE and that by the 1D and 2D model is caused by the overestimated canopy photosynthesis rate that is possibly related to higher predicted PAR and fraction of sunlit leaves. Overall, this study confirms the necessity of taking detailed architecture traits into consideration when evaluating the strategies of genetic improvement and canopy configuration in improving crop yield by crop modeling.
    Type of Medium: Online Resource
    ISSN: 1664-462X
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fpls.2022.735981
    DOI: 10.3389/fpls.2022.735981.s001
    DOI: 10.3389/fpls.2022.735981.s002
    DOI: 10.3389/fpls.2022.735981.s003
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2687947-5
    detail.hit.zdb_id: 2613694-6
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  • 8
    Online Resource
    Online Resource
    DataSheet_1.zip
    Frontiers Media SA ; 2022
    In:  Frontiers in Plant Science Vol. 13 ( 2022-12-1)
    Details
    In: Frontiers in Plant Science, Frontiers Media SA, Vol. 13 ( 2022-12-1)
    Abstract: The spatial morphological structure of plant leaves is an important index to evaluate crop ideotype. In this study, we characterized the three-dimensional (3D) data of the ear leaf midrib of maize at the grain-filling stage using the 3D digitization technology and obtained the phenotypic values of 15 traits covering four different dimensions of the ear leaf midrib, of which 13 phenotypic traits were firstly proposed for featuring plant leaf spatial structure. Cluster analysis results showed that the 13 traits could be divided into four groups, Group I, -II, -III and -IV. Group I contains HorizontalLength, OutwardGrowthMeasure, LeafAngle and DeviationTip; Group II contains DeviationAngle, MaxCurvature and CurvaturePos; Group III contains LeafLength and ProjectionArea; Group IV contains TipTop, VerticalHeight, UpwardGrowthMeasure, and CurvatureRatio. To investigate the genetic basis of the ear leaf midrib curve, 13 traits with high repeatability were subjected to genome-wide association study (GWAS) analysis. A total of 828 significantly related SNPs were identified and 1365 candidate genes were annotated. Among these, 29 candidate genes with the highest significant and multi-method validation were regarded as the key findings. In addition, pathway enrichment analysis was performed on the candidate genes of traits to explore the potential genetic mechanism of leaf midrib curve phenotype formation. These results not only contribute to further understanding of maize leaf spatial structure traits but also provide new genetic loci for maize leaf spatial structure to improve the plant type of maize varieties.
    Type of Medium: Online Resource
    ISSN: 1664-462X
    URL: Article
    URL: Article
    DOI: 10.3389/fpls.2022.1063056
    DOI: 10.3389/fpls.2022.1063056.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2687947-5
    detail.hit.zdb_id: 2613694-6
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  • 9
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    Online Resource
    Data_Sheet_1.docx
    Frontiers Media SA ; 2022
    In:  Frontiers in Plant Science Vol. 13 ( 2022-6-30)
    Details
    In: Frontiers in Plant Science, Frontiers Media SA, Vol. 13 ( 2022-6-30)
    Abstract: The currently available methods for evaluating most biochemical traits of plant phenotyping are destructive and have extremely low throughput. However, hyperspectral techniques can non-destructively obtain the spectral reflectance characteristics of plants, which can provide abundant biophysical and biochemical information. Therefore, plant spectra combined with machine learning algorithms can be used to predict plant phenotyping traits. However, the raw spectral reflectance characteristics contain noise and redundant information, thus can easily affect the robustness of the models developed via multivariate analysis methods. In this study, two end-to-end deep learning models were developed based on 2D convolutional neural networks (2DCNN) and fully connected neural networks (FCNN; Deep2D and DeepFC, respectively) to rapidly and non-destructively predict the phenotyping traits of lettuces from spectral reflectance. Three linear and two nonlinear multivariate analysis methods were used to develop models to weigh the performance of the deep learning models. The models based on multivariate analysis methods require a series of manual feature extractions, such as pretreatment and wavelength selection, while the proposed models can automatically extract the features in relation to phenotyping traits. A visible near-infrared hyperspectral camera was used to image lettuce plants growing in the field, and the spectra extracted from the images were used to train the network. The proposed models achieved good performance with a determination coefficient of prediction ( R p 2 ) of 0.9030 and 0.8490 using Deep2D for soluble solids content and DeepFC for pH, respectively. The performance of the deep learning models was compared with five multivariate analysis method. The quantitative analysis showed that the deep learning models had higher R p 2 than all the multivariate analysis methods, indicating better performance. Also, wavelength selection and different pretreatment methods had different effects on different multivariate analysis methods, and the selection of appropriate multivariate analysis methods and pretreatment methods increased more time and computational cost. Unlike multivariate analysis methods, the proposed deep learning models did not require any pretreatment or dimensionality reduction and thus are more suitable for application in high-throughput plant phenotyping platforms. These results indicate that the deep learning models can better predict phenotyping traits of plants using spectral reflectance.
    Type of Medium: Online Resource
    ISSN: 1664-462X
    URL: Article
    URL: Article
    DOI: 10.3389/fpls.2022.927832
    DOI: 10.3389/fpls.2022.927832.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2687947-5
    detail.hit.zdb_id: 2613694-6
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  • 10
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    Online Resource
    Structural and Functional Brain Abnormalities in Internet Gaming Disorder and Attention-Deficit/Hyperactivity Disorder: A Comparative Meta-Analysis
    Frontiers Media SA ; 2021
    In:  Frontiers in Psychiatry Vol. 12 ( 2021-7-1)
    Details
    In: Frontiers in Psychiatry, Frontiers Media SA, Vol. 12 ( 2021-7-1)
    Abstract: Background: Patients with Internet gaming disorder (IGD) and attention-deficit/hyperactivity disorder (ADHD) have high comorbidity but it is still unknown whether these disorders have shared and distinctive neuroimage alterations. Objective: The aim of this meta-analysis was to identify shared and disorder-specific structural, functional, and multimodal abnormalities between IGD and ADHD. Methods: A systematic literature search was conducted for whole-brain voxel-based morphometry (VBM) and functional magnetic resonance imaging (fMRI) studies comparing people with IGD or ADHD with healthy controls. Regional gray matter volume (GMV) and fMRI differences were compared over the patient groups and then a quantitative comparison was performed to find abnormalities (relative to controls) between IGD and ADHD using seed-based d mapping meta-analytic methods. Result: The meta-analysis contained 14 IGD VBM studies (contrasts covering 333 IGDs and 335 HCs), 26 ADHD VBM studies (1,051 patients with ADHD and 887 controls), 30 IGD fMRI studies (603 patients with IGD and 564 controls), and 29 ADHD fMRI studies (878 patients with ADHD and 803 controls). Structurally, VBM analysis showed disorder-specific GMV abnormality in the putamen among IGD subjects and orbitofrontal cortex in ADHD and shared GMV in the prefrontal cortex. Functionally, fMRI analysis discovered that IGD-differentiating increased activation in the precuneus and shared abnormal activation in anterior cingulate cortex, insular, and striatum. Conclusion: IGD and ADHD have shared and special structural and functional alterations. IGD has disorder-differentiating structural alterations in the putamen and ADHD has alterations in the orbitofrontal cortex. Disorder-differentiating fMRI activations were predominantly observed in the precuneus among IGD subjects and shared impairing function connection was in the rewards circuit (including ACC, OFC, and striatum).
    Type of Medium: Online Resource
    ISSN: 1664-0640
    URL: Article
    DOI: 10.3389/fpsyt.2021.679437
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2564218-2
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