5,961 research outputs found
Histological and Biomechanical Evaluation of the Preserved Degenerative Dermis in Rat Autologous Skin Transplant Models after a Deep Second Degree Burn
To describe the histological and biomechanical changes of the preserved degenerative dermis in rat autologous skin transplant models after a deep second-degree burn. 50 SD rats were divided into 5 groups randomly of 10 rats of each: 7-days group, 9-days group, 14-days group, 21-days group, and 60-days group. Deep second-degree burn wounds were prepared on the back of rats sized 3.5cm×3.5cm. Super tangential excision was performed on the burn wound to preserve the degenerative dermis. Then, autologous epidermis was grafted on the wound. After that, the histological changes of the preserved degenerative dermis tissues and the graft areas were observed by macroscopic, light microscope and electron microscope in the 7, 9, 14, 21, 60 days after the operation. Moreover, the tensile properties of healing deeply burned rat skin were also tested for each group at the same time points mentioned above. Results: (1) According to the macroscopic observation, 7 days after the operation, the grafted skin was fused with the area of burn wound; A few hairs were growing out on the skin at the 14th day; the injured skin recovered to normality by the 60th day. (2) Hyaline change occurred in the preserved degenerative dermis tissues based on the observation by light microscope. At the 7th day after operation, the dermis papillae and reticular layer could be discerned; by the 21st day, the thickness, structures and morphology of grafted skin were similar to the normal tissues. (3) 7 days after operation, ballooning changes were observed by the electron microscope in the mitochondria and endoplasmic reticulum of damaged cells and the number of the ribosomes was obviously reduced. The subcellular wound improved continuously and approached normality by the 21st day. (4) 9 days after the operation, the tensible strength and maximal strain of the grafting rat skin approached 70% and 90% of natural skin, respectively. (5) 60 days after the operation, the tensile performance of the healing rat skin recovered to the natural level. Conclusion: The histological and biomechanical changes of the denatured dermis of a deep second degree burn wound may gradually recover to normality after being covered by autologous skin.
Development of beam arrangement design for tunable diode laser absorption tomography reconstruction based on Tikhonov regularization parameter matrix
Improving Text Matching in E-Commerce Search with A Rationalizable, Intervenable and Fast Entity-Based Relevance Model
Discovering the intended items of user queries from a massive repository of
items is one of the main goals of an e-commerce search system. Relevance
prediction is essential to the search system since it helps improve
performance. When online serving a relevance model, the model is required to
perform fast and accurate inference. Currently, the widely used models such as
Bi-encoder and Cross-encoder have their limitations in accuracy or inference
speed respectively. In this work, we propose a novel model called the
Entity-Based Relevance Model (EBRM). We identify the entities contained in an
item and decompose the QI (query-item) relevance problem into multiple QE
(query-entity) relevance problems; we then aggregate their results to form the
QI prediction using a soft logic formulation. The decomposition allows us to
use a Cross-encoder QE relevance module for high accuracy as well as cache QE
predictions for fast online inference. Utilizing soft logic makes the
prediction procedure interpretable and intervenable. We also show that
pretraining the QE module with auto-generated QE data from user logs can
further improve the overall performance. The proposed method is evaluated on
labeled data from e-commerce websites. Empirical results show that it achieves
promising improvements with computation efficiency
A data analysis method for isochronous mass spectrometry using two time-of-flight detectors at CSRe
The concept of isochronous mass spectrometry (IMS) applying two
time-of-flight (TOF) detectors originated many years ago at GSI. However, the
corresponding method for data analysis has never been discussed in detail.
Recently, two TOF detectors have been installed at CSRe and the new working
mode of the ring is under test. In this paper, a data analysis method for this
mode is introduced and tested with a series of simulations. The results show
that the new IMS method can significantly improve mass resolving power via the
additional velocity information of stored ions. This improvement is especially
important for nuclides with Lorentz factor -value far away from the
transition point of the storage ring CSRe.Comment: published in Chinese Physics C Vol. 39, No. 10 (2015) 10620
First evidence on different transportation modes of arsenic and phosphorus in arsenic hyperaccumulator Pteris vittata
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A Versatile Surface Bioengineering Strategy Based on Mussel-Inspired and Bioclickable Peptide Mimic
In this work, we present a versatile surface engineering strategy by the combination of mussel adhesive peptide mimicking and bioorthogonal click chemistry. The main idea reflected in this work derived from a novel mussel-inspired peptide mimic with a bioclickable azide group (i.e., DOPA4-azide). Similar to the adhesion mechanism of the mussel foot protein (i.e., covalent/noncovalent comediated surface adhesion), the bioinspired and bioclickable peptide mimic DOPA4-azide enables stable binding on a broad range of materials, such as metallic, inorganic, and organic polymer substrates. In addition to the material universality, the azide residues of DOPA4-azide are also capable of a specific conjugation of dibenzylcyclooctyne- (DBCO-) modified bioactive ligands through bioorthogonal click reaction in a second step. To demonstrate the applicability of this strategy for diversified biofunctionalization, we bioorthogonally conjugated several typical bioactive molecules with DBCO functionalization on different substrates to fabricate functional surfaces which fulfil essential requirements of biomedically used implants. For instance, antibiofouling, antibacterial, and antithrombogenic properties could be easily applied to the relevant biomaterial surfaces, by grafting antifouling polymer, antibacterial peptide, and NO-generating catalyst, respectively. Overall, the novel surface bioengineering strategy has shown broad applicability for both the types of substrate materials and the expected biofunctionalities. Conceivably, the “clean” molecular modification of bioorthogonal chemistry and the universality of mussel-inspired surface adhesion may synergically provide a versatile surface bioengineering strategy for a wide range of biomedical materials
XCloud-VIP: Virtual Peak Enables Highly Accelerated NMR Spectroscopy and Faithful Quantitative Measures
Background: Nuclear Magnetic Resonance (NMR) spectroscopy is an important
bio-engineering tool to determine the metabolic concentrations, molecule
structures and so on. The data acquisition time, however, is very long in
multi-dimensional NMR. To accelerate data acquisition, non-uniformly sampling
is an effective way but may encounter severe spectral distortions and
unfaithful quantitative measures when the acceleration factor is high.
Objective: To reconstruct high fidelity spectra from highly accelerated NMR and
achieve much better quantitative measures. Methods: A virtual peak (VIP)
approach is proposed to self-learn the prior spectral information, such as the
central frequency and peak lineshape, and then feed these information into the
reconstruction. The proposed method is further implemented with cloud computing
to facilitate online, open, and easy access. Results: Results on synthetic and
experimental data demonstrate that, compared with the state-of-the-art method,
the new approach provides much better reconstruction of low-intensity peaks and
significantly improves the quantitative measures, including the regression of
peak intensity, the distances between nuclear pairs, and concentrations of
metabolics in mixtures. Conclusion: Self-learning prior peak information can
improve the reconstruction and quantitative measures of spectra. Significance:
This approach enables highly accelerated NMR and may promote time-consuming
applications such as quantitative and time-resolved NMR experiments
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