1,652 research outputs found
Chemical weathering of monsoonal eastern China: implications from major elements of topsoil
Major element compositions of 36 bulk samples and 41 clay samples, which were obtained from 47 topsoils collected in monsoonal eastern China, were investigated with conventional wet chemistry and X-ray fluorescence (XRF) spectrometry, respectively. Based on major element analyses, the mobility of major elements and latitudinal distributions of SiO2/Al2O3 ratio, chemical index of alteration (CIA), chemical index of weathering (CIW) and weathering index of Parker (WIP) were analyzed. Meanwhile, the suitability of these chemical weathering indices to topsoils in monsoonal eastern China and its controls were discussed. These investigations indicate that Na, K, Ca, Mg, and Si are relatively depleted, while Mn, P, Fe and Ti are relatively enriched in topsoils of the study area by comparison with their contents in the upper continent crust (UCC), and that alkali metal (Na, K) and alkaline earth metal (Ca, Mg) elements are generally easier to be depleted from their parent materials than other major elements during chemical weathering. The latitudinal distributions of CIA, CIW and WIP show that they are suitable to both bulk and clay samples, but SiO2/Al2O3 is only suitable to clay samples, not suitable in bulk ones. All these investigations indicate a significant dependence of grain-size in major element abundance and latitudinal distributions of SiO2/Al2O3, CIA, CIW and WIP, but parent rock type has little effect on them, except its impact on the latitudinal distribution of WIP in clay samples. The significant grain-size dependence probably indicates the presence of unaltered minerals in bulk samples, thus we suggest that clay samples are more suitable to investigating chemical weathering of sediments on continents than bulk samples. The trivial effect of parent rock type probably indicates a relatively uniform chemical weathering on various parent rocks. Correlation analyses indicate that climate is the dominant control of chemical weathering of topsoils in the study area, and the significant latitude effect indicated by the spatial distributions of chemical weathering indices actually reflect the climate control on chemical weathering of topsoils. Chemical weathering indices actually reflect the integrated weathering history in the study area. Besides the dominant control of climate, other factors like tectonics, parent rock, biology, landform and soil depth and age might also have some effect on the chemical weathering of topsoils in the study area, which needs further research. (C) 2013 Elsevier Ltd. All rights reserved.National Basic Research Program of China [2010CB833405]; National Natural Science Foundation of China [40872111, 40930106
Transiently Impaired Endothelial Function During Thyroid Hormone Withdrawal in Differentiated Thyroid Cancer Patients
PURPOSE: Endothelial dysfunction, which was associated with chronic hypothyroidism, was an early event in atherosclerosis. Whether short-term hypothyroidism following thyroxine withdrawal during radioiodine (RAI) therapy was associated with endothelial dysfunction in patients with differentiated thyroid cancer (DTC) was unclear. Aim of the study was to assess whether short-term hypothyroidism could impair endothelial function and the accompanied metabolic changes in the whole process of RAI therapy.
METHODS: We recruited fifty-one patients who underwent total thyroidectomy surgery and would accept RAI therapy for DTC. We analyzed thyroid function, endothelial function and serum lipids levels of the patients at three time points: the day before thyroxine withdrawal(P
RESULTS: We analyzed the changes of FMD, thyroid function and lipids at three time points. FMD(P
CONCLUSION: Endothelial function was transiently impaired in DTC patients at short-term hypothyroidism state during the RAI therapy, and immediately returned to the initial state after restoring TSH suppression therapy
Reciprocal facilitation between annual plants and burrowing crabs:Implications for the restoration of degraded saltmarshes
Increasing evidence shows that facilitative interactions between species play an essential role in coastal wetland ecosystems. However, there is a lack of understanding of how such interactions can be used for restoration purposes in saltmarsh ecosystems. We therefore studied the mechanisms of reciprocal facilitative interactions between native annual plants, Suaeda salsa, and burrowing crabs, Helice tientsinensis, in a middle-elevation saltmarsh (with generally high plant density and moderate tides) in the Yellow River Delta of China. We investigated the relationship between the densities of the plants and crab burrows in different seasons. Then, we tested whether and how saltmarsh plants and crabs indeed facilitate each other in a series of field and laboratory experiments. Finally, we applied the results by creating a field-scale artificial approach for microtopographic modification to restore a degraded saltmarsh. We found that the density of plant seedlings in spring was positively correlated with the density of crab burrows in the previous autumn; moreover, the density of crab burrows was correlated with the density of plants in summer. The concave-convex surface microtopography created by crabs promoted seed retention and seedling establishment of saltmarsh plants in winter and spring. These plants in turn facilitated crabs by inhibiting predators, providing food and reducing physical stresses for crabs in summer and autumn. The experimental removal of saltmarsh plants decreased crab burrow density, while both transplanting and simulating plants in bare patches promoted crabs. The microtopographic modification, inspired by our new understanding of the interactions between saltmarsh plants and crabs, showed that these degraded saltmarsh ecosystems can be restored by a single ploughing intervention. Synthesis. Our results suggest a reciprocal facilitation between annual plants and burrowing crabs in a middle-elevation saltmarsh ecosystem. This knowledge yielded new restoration options for degraded coastal saltmarshes through the one-time ploughing initiation of microtopographic variation, which could promote the re-establishment of ecosystem engineers and lead to the efficient recovery of pioneer coastal vegetation and associated fauna
Chip-Scale Plasmonic Sum Frequency Generation
Plasmonics provides a promising candidate for nonlinear optical interactions because of its ability to enable extreme light concentration at the nanoscale. We demonstrate on-chip plasmonic sum frequency generation (SFG) with a metal-dielectric-metal nanostructure. The two cross-polarized pumps (800 and 1500 nm) are designed to match the two resonances of this plasmonic nanostructure to make the most of the electric field enhancement and spatial overlapping of the modes. Since these two resonances are predominantly determined by the sizes of the top metallic nanostructures in the same direction, the SFG (521 nm) can be independently controlled by each pump via changing these sizes. This study exerts the full strength of plasmonic resonance induced field enhancement, thereby paving a way toward using nanoplasmonics for future nonlinear nanophotonics applications, such as optical information processing, imaging, and spectroscopy
A Two-stage Method with a Shared 3D U-Net for Left Atrial Segmentation of Late Gadolinium-Enhanced MRI Images
Objective: This study was aimed at validating the accuracy of a proposed algorithm for fully automatic 3D left atrial segmentation and to compare its performance with existing deep learning algorithms. Methods: A two-stage method with a shared 3D U-Net was proposed to segment the 3D left atrium. In this architecture, the 3D U-Net was used to extract 3D features, a two-stage strategy was used to decrease segmentation error caused by the class imbalance problem, and the shared network was designed to decrease model complexity. Model performance was evaluated with the DICE score, Jaccard index and Hausdorff distance. Results: Algorithm development and evaluation were performed with a set of 100 late gadolinium-enhanced cardiovascular magnetic resonance images. Our method achieved a DICE score of 0.918, a Jaccard index of 0.848 and a Hausdorff distance of 1.211, thus, outperforming existing deep learning algorithms. The best performance of the proposed model (DICE: 0.851; Jaccard: 0.750; Hausdorff distance: 4.382) was also achieved on a publicly available 2013 image data set. Conclusion: The proposed two-stage method with a shared 3D U-Net is an efficient algorithm for fully automatic 3D left atrial segmentation. This study provides a solution for processing large datasets in resource-constrained applications. Significance Statement: Studying atrial structure directly is crucial for comprehending and managing atrial fibrillation (AF). Accurate reconstruction and measurement of atrial geometry for clinical purposes remains challenging, despite potential improvements in the visibility of AF-associated structures with late gadolinium-enhanced magnetic resonance imaging. This difficulty arises from the varying intensities caused by increased tissue enhancement and artifacts, as well as variability in image quality. Therefore, an efficient algorithm for fully automatic 3D left atrial segmentation is proposed in the present study
Time series canopy phenotyping enables the identification of genetic variants controlling dynamic phenotypes in soybean
Advances in plant phenotyping technologies are dramatically reducing the marginal costs of collecting multiple phenotypic measurements across several time points. Yet, most current approaches and best statistical practices implemented to link genetic and phenotypic variation in plants have been developed in an era of single-time-point data. Here, we used time-series phenotypic data collected with an unmanned aircraft system for a large panel of soybean (Glycine max (L.) Merr.) varieties to identify previously uncharacterized loci. Specifically, we focused on the dissection of canopy coverage (CC) variation from this rich data set. We also inferred the speed of canopy closure, an additional dimension of CC, from the time-series data, as it may represent an important trait for weed control. Genome-wide association studies (GWASs) identified 35 loci exhibiting dynamic associations with CC across developmental stages. The time-series data enabled the identification of 10 known flowering time and plant height quantitative trait loci (QTLs) detected in previous studies of adult plants and the identification of novel QTLs influencing CC. These novel QTLs were disproportionately likely to act earlier in development, which may explain why they were missed in previous single-time-point studies. Moreover, this time-series data set contributed to the high accuracy of the GWASs, which we evaluated by permutation tests, as evidenced by the repeated identification of loci across multiple time points. Two novel loci showed evidence of adaptive selection during domestication, with different genotypes/haplotypes favored in different geographic regions. In summary, the time-series data, with soybean CC as an example, improved the accuracy and statistical power to dissect the genetic basis of traits and offered a promising opportunity for crop breeding with quantitative growth curves
Bioinformatics and system biology approach to identify the influences among COVID-19, influenza, and HIV on the regulation of gene expression
BackgroundCoronavirus disease (COVID-19), caused by SARS-CoV-2, has emerged as a infectious disease, coexisting with widespread seasonal and sporadic influenza epidemics globally. Individuals living with HIV, characterized by compromised immune systems, face an elevated risk of severe outcomes and increased mortality when affected by COVID-19. Despite this connection, the molecular intricacies linking COVID-19, influenza, and HIV remain unclear. Our research endeavors to elucidate the shared pathways and molecular markers in individuals with HIV concurrently infected with COVID-19 and influenza. Furthermore, we aim to identify potential medications that may prove beneficial in managing these three interconnected illnesses.MethodsSequencing data for COVID-19 (GSE157103), influenza (GSE185576), and HIV (GSE195434) were retrieved from the GEO database. Commonly expressed differentially expressed genes (DEGs) were identified across the three datasets, followed by immune infiltration analysis and diagnostic ROC analysis on the DEGs. Functional enrichment analysis was performed using GO/KEGG and Gene Set Enrichment Analysis (GSEA). Hub genes were screened through a Protein-Protein Interaction networks (PPIs) analysis among DEGs. Analysis of miRNAs, transcription factors, drug chemicals, diseases, and RNA-binding proteins was conducted based on the identified hub genes. Finally, quantitative PCR (qPCR) expression verification was undertaken for selected hub genes.ResultsThe analysis of the three datasets revealed a total of 22 shared DEGs, with the majority exhibiting an area under the curve value exceeding 0.7. Functional enrichment analysis with GO/KEGG and GSEA primarily highlighted signaling pathways associated with ribosomes and tumors. The ten identified hub genes included IFI44L, IFI44, RSAD2, ISG15, IFIT3, OAS1, EIF2AK2, IFI27, OASL, and EPSTI1. Additionally, five crucial miRNAs (hsa-miR-8060, hsa-miR-6890-5p, hsa-miR-5003-3p, hsa-miR-6893-3p, and hsa-miR-6069), five essential transcription factors (CREB1, CEBPB, EGR1, EP300, and IRF1), and the top ten significant drug chemicals (estradiol, progesterone, tretinoin, calcitriol, fluorouracil, methotrexate, lipopolysaccharide, valproic acid, silicon dioxide, cyclosporine) were identified.ConclusionThis research provides valuable insights into shared molecular targets, signaling pathways, drug chemicals, and potential biomarkers for individuals facing the complex intersection of COVID-19, influenza, and HIV. These findings hold promise for enhancing the precision of diagnosis and treatment for individuals with HIV co-infected with COVID-19 and influenza
The LAMOST Complete Spectroscopic Survey of Pointing Area (LaCoSSPAr) in the Southern Galactic Cap I. The Spectroscopic Redshift Catalog
We present a spectroscopic redshift catalog from the LAMOST Complete
Spectroscopic Survey of Pointing Area (LaCoSSPAr) in the Southern Galactic Cap
(SGC), which is designed to observe all sources (Galactic and extra-galactic)
by using repeating observations with a limiting magnitude of in
two fields. The project is mainly focusing on the completeness of
LAMOST ExtraGAlactic Surveys (LEGAS) in the SGC, the deficiencies of source
selection methods and the basic performance parameters of LAMOST telescope. In
both fields, more than 95% of galaxies have been observed. A post-processing
has been applied to LAMOST 1D spectrum to remove the majority of remaining sky
background residuals. More than 10,000 spectra have been visually inspected to
measure the redshift by using combinations of different emission/absorption
features with uncertainty of . In total, there are 1528
redshifts (623 absorption and 905 emission line galaxies) in Field A and 1570
redshifts (569 absorption and 1001 emission line galaxies) in Field B have been
measured. The results show that it is possible to derive redshift from low SNR
galaxies with our post-processing and visual inspection. Our analysis also
indicates that up to 1/4 of the input targets for a typical extra-galactic
spectroscopic survey might be unreliable. The multi-wavelength data analysis
shows that the majority of mid-infrared-detected absorption (91.3%) and
emission line galaxies (93.3%) can be well separated by an empirical criterion
of . Meanwhile, a fainter sequence paralleled to the main population
of galaxies has been witnessed both in / and /
diagrams, which could be the population of luminous dwarf galaxies but
contaminated by the edge-on/highly inclined galaxies ().Comment: 19 pages, 14 figures, 2 MRT, accepted by ApJ
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