371 research outputs found
Evaluation of structure specification in linear mixed models for modeling the spatial effects in tree height-diamater relationships
In recent years, linear mixed models (LMM) have become more popularto deal with spatial effects in forestry and ecological data. In this study, different structure specifications of linear mixed model were applied to model tree height-diameter relationships, including LMM with random blocks only (LMM-block), LMM with spatial covariance only (LMM-covariance), and the combination of the last two (LMM-block-covariance). Further, the between group heterogeneous variances were incorporated into LMM-covariance and LMM-block-covariance. The results indicated that, in general, LMM-covariance significantly reduced spatial autocorrelation in model residuals, while LMM-block was effective in dealing with spatial heterogeneity. LMM-blocktreated the blocks as random effects and avoided the estimation of parameters of the variogram model. Thus, it produced better model predictions than LMM-covariance. LMM-block-covariance took both block effects and spatial covariance into account, and significantly improve model fitting. However, it did not produce better model predictions due to the increase of model complexity and estimation of the local variogram within each block
Relationships between overstory species and community classification of the Sipsey Wilderness, Alabama
A total of 2314 trees was sampled from 170 randomly located plots to investigate ecological community relationships and species similarities of the vegetation covering the 12 000 ha Sipsey Wilderness in Alabama. Thirty-two tree species, 14 vegetation types and 10 landtypes were identi®ed. Within each plot, the species were ranked based on their basal area to determine the relative importance of the species. A variety of species including white oak (Quercus alba L.), post oak (Quercus stellata Wangenh.), chestnut oak (Quercus prinus L.), northern red oak (Quercus rubra L.), red maple (Acer rubrum L.), sugar maple (Acer saccharum Marsh.), loblolly pine (Pinus taeda L.), virginia pine (Pinus virginiana Mill.), pignut hickory (Carya glabra Sweet) and yellow poplar (Liriodendron tulipifera L.) were important species differentiating the ecological communities. Percent basal area (BA%) of each species in the plots was also computed. The vegetation-types and landtypes were characterized by average ranks and BA% of the species. Relationships between the vegetation-types were examined by cluster analysis
Simulation of Nondestructive Inspection of Nuclear Resonance Fluorescence Based on Electron Accelerator
Nuclear resonance fluorescence (NRF) is an emerging nondestructive active inspection technology. Specific isotopes can be identified by analyzing the characteristic energy recorded in the gamma spectrum. This technology plays an important role in the scanning inspection of small containers containing unknown explosives. In this paper, an NRF backscatter inspection scheme is optimized using Monte Carlo simulation program based on the X-ray source generated by electron accelerator bremsstrahlung radiation. After optimized design, X-ray leakage rate is reduced by 386 times, the beam asymmetry is less than 2%, the beam uniformity is more than 70%. The NRF characteristic energy spectrum of graphite samples and ammonium nitrate sample obtained by HPGe detector verifies the feasibility of the design scheme. The innovative application of importance sampling technique improves the simulation calculation efficiency of graphite sample by 72.23 times. The design scheme and calculation results provide technical support for the research and development of NRF based non-destructive nuclear detection system
Bifurcation in a Discrete Competition System
A new difference system is induced from a differential competition system by different discrete methods. We give theoretical analysis for local bifurcation of the fixed points and derive the conditions under which the local bifurcations such as flip occur at the fixed points. Furthermore, one- and two-dimensional diffusion systems are given when diffusion terms are added. We provide the Turing instability conditions by linearization method and inner product technique for the diffusion system with periodic boundary conditions. A series of numerical simulations are performed that not only verify the theoretical analysis, but also display some interesting dynamics
Tailoring Intermolecular Interactions Towards High‐Performance Thermoelectric Ionogels at Low Humidity
Development of ionic thermoelectric (iTE) materials is of immense interest for efficient heat-to-electricity conversion due to their giant ionic Seebeck coefficient (Si), but challenges remain in terms of relatively small Si at low humidity, poor stretchability, and ambiguous interaction mechanism in ionogels. Herein, a novel ionogel is reported consisting of polyethylene oxide (PEO), polyethylene oxide-polypropylene oxide-polyethylene oxide (P123), and 1-ethyl-3-methylimidazolium acetate (Emim:OAC). By delicately designing the interactions between ions and polymers, the migration of anions is restricted due to their strong binding with the hydroxyl groups of polymers, while the transport of cations is facilitated through segmental motions due to the increased amorphous regions, thereby leading to enlarged diffusion difference between the cations and anions. Moreover, the plasticizing effect of P123 and Emim:OAC can increase the elongation at break. As a consequence, the ionogel exhibits excellent properties including high Si (18 mV K−1 at relative humidity of 60%), good ionic conductivity (1.1 mS cm−1), superior stretchability (787%), and high stability (over 80% retention after 600 h). These findings show a promising strategy to obtain multifunctional iTE materials by engineering the intermolecular interactions and demonstrate the great potential of ionogels for harvesting low-grade heat in human-comfortable humidity environments
Anomaly data management and big data analytics: an application on disability datasets
Purpose - The disability datasets are the datasets that contain the information of disabled populations. By analyzing these datasets, professionals who work with disabled populations can have a better understanding of the inherent characteristics of the disabled populations, so that working plans and policies, which can effectively help the disabled populations, can be made accordingly. Design/methodology/approach - In this paper, the authors proposed a big data management and analytic approach for disability datasets. Findings - By using a set of data mining algorithms, the proposed approach can provide the following services. The data management scheme in the approach can improve the quality of disability data by estimating miss attribute values and detecting anomaly and low-quality data instances. The data mining scheme in the approach can explore useful patterns which reflect the correlation, association and interactional between the disability data attributes. Experiments based on real-world dataset are conducted at the end to prove the effectiveness of the approach. Originality/value - The proposed approach can enable data-driven decision-making for professionals who work with disabled populations
Braf d594a Mutation Defines a Unique Biological and Immuno-Modulatory Subgroup Associated With Functional CD8+ T Cell Infiltration in Colorectal Cancer
BACKGROUND: BRAF non-V600 mutation occupies a relatively small but critical subset in colorectal cancer (CRC). However, little is known about the biological functions and impacts of BRAF class III mutation in CRC. Here, we aim to explore how D594A mutation impacts on biological behaviors and immune related signatures in murine CRC cells.
METHODS: BRAF V600E (class I), G469V (class II) and D594A (class III) mutant cell lines were established based on MC38 cells. The biological behaviors of cells were evaluated in respect of cell growth, cell proliferation, cell apoptosis, cell migration and invasion by the methods of colony-forming assay, CCK-8 assay, Annexin V/PI staining and transwell assay. The concentrations of soluble cytokines were detected by ELISA. The membrane expression of immuno-modulatory molecules and the pattern of tumor infiltrating lymphocyte were evaluated by flow cytometry. The molecular mechanism was explored by RNA sequencing. Immunohistochemistry (IHC) staining was used for the detection of CD8α in tumor tissues. qRT-PCR and western blot were performed to assess the mRNA and protein expression. Anti-PD-L1 treatment and cytokines neutralization experiments were conducted in in vivo models.
RESULTS: D594A mutant cells displayed lower grade malignancy characteristics than V600E (class I) and G469V (class II) mutant cells. Meanwhile, D594A mutation led to evident immuno-modulatory features including upregulation of MHC Class I and PD-L1. In vivo experiments displayed that the frequency of infiltrated CD8
CONCLUSIONS: D594A mutant CRC exhibited lower aggressiveness and immune-activated phenotype. ATF3-THBS1-CXCL9/CXCL10 axis mediated functional CD
CD1d-antibody fusion proteins target iNKT cells to the tumor and trigger long-term therapeutic responses
Despite the well-established antitumor activity of CD1d-restricted invariant natural killer T lymphocytes (iNKT), their use for cancer therapy has remained challenging. This appears to be due to their strong but short-lived activation followed by long-term anergy after a single administration of the CD1d agonist ligand alpha-galactosylceramide (αGC). As a promising alternative, we obtained sustained mouse iNKT cell responses associated with prolonged antitumor effects through repeated administrations of tumor-targeted recombinant sCD1d-antitumor scFv fusion proteins loaded with αGC. Here, we demonstrate that CD1d fusion proteins bound to tumor cells via the antibody fragment specific for a tumor-associated antigen, efficiently activate human iNKT cell lines leading to potent tumor cell lysis. The importance of CD1d tumor targeting was confirmed in tumor-bearing mice in which only the specific tumor-targeted CD1d fusion protein resulted in tumor inhibition of well-established aggressive tumor grafts. The therapeutic efficacy correlated with the repeated activation of iNKT and natural killer cells marked by their release of TH1 cytokines, despite the up-regulation of the co-inhibitory receptor PD-1. Our results demonstrate the superiority of providing the superagonist αGC loaded on recombinant CD1d proteins and support the use of αGC/sCD1d-antitumor fusion proteins to secure a sustained human and mouse iNKT cell activation, while targeting their cytotoxic activity and cytokine release to the tumor sit
High-level expression and purification of soluble recombinant FGF21 protein by SUMO fusion in Escherichia coli
<p>Abstract</p> <p>Background</p> <p>Fibroblast growth factor 21 (FGF21) is a promising drug candidate to combat metabolic diseases. However, high-level expression and purification of recombinant FGF21 (rFGF21) in <it>Escherichia coli (E. coli) </it>is difficult because rFGF21 forms inclusion bodies in the bacteria making it difficult to purify and obtain high concentrations of bioactive rFGF21. To overcome this problem, we fused the <it>FGF21 </it>with <it>SUMO </it>(Small ubiquitin-related modifier) by polymerase chain reaction (PCR), and expressed the fused gene in <it>E. coli </it>BL21(DE3).</p> <p>Results</p> <p>By inducing with IPTG, SUMO-FGF21 was expressed at a high level. Its concentration reached 30% of total protein, and exceeded 95% of all soluble proteins. The fused protein was purified by DEAE sepharose FF and Ni-NTA affinity chromatography. Once cleaved by the SUMO protease, the purity of rFGF21 by high performance liquid chromatography (HPLC) was shown to be higher than 96% with low endotoxin level (<1.0 EU/ml). The results of <it>in vivo </it>animal experiments showed that rFGF21 produced by using this method, could decrease the concentration of plasma glucose in diabetic rats by streptozotocin (STZ) injection.</p> <p>Conclusions</p> <p>This study demonstrated that SUMO, when fused with FGF21, was able to promote its soluble expression of the latter in <it>E. coli</it>, making it more convenient to purify rFGF21 than previously. This may be a better method to produce rFGF21 for pharmaceutical research and development.</p
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