Here, a novel macroporous hydrogel dressing is presented that can accelerate wound healing and guard against bacteria‐associated wound infection. Carboxymethyl agarose (CMA) is successfully prepared ...from agarose. The CMA molecular chains are cross‐linked by hydrogen bonding to form a supramolecular hydrogel, and the hydroxy groups in the CMA molecules complex with Ag+ to promote hydrogel formation. This hydrogel composite exhibits pH‐responsiveness and temperature‐responsiveness and releases Ag+, an antibacterial agent, over a prolonged period of time. Moreover, this hydrogel exhibits outstanding cytocompatibility and hemocompatibility. In vitro and in vivo investigations demonstrate that the hydrogel has enhanced antibacterial and anti‐inflammatory capabilities and can significantly accelerate skin tissue regeneration and wound closure. Astonishingly, the hydrogel can cause the inflammation process to occur earlier and for a shorter amount of time than in a normal process. Given its excellent antibacterial, anti‐inflammatory, and physicochemical properties, the broad application of this hydrogel in bacteria‐associated wound management is anticipated.
A macroporous hydrogel dressing with antibacterial and anti‐inflammatory properties is developed for accelerated wound healing. The hydrogel matrix is formed by hydrogen bonding and supramolecular complexation. The hydrogel shows outstanding biocompatibility and can significantly accelerate skin tissue regeneration and wound closure.
Noise causes unpleasant visual effects in low-light image/video enhancement. In this paper, we aim to make the enhancement model and method aware of noise in the whole process. To deal with heavy ...noise which is not handled in previous methods, we introduce a robust low-light enhancement approach, aiming at well enhancing low-light images/videos and suppressing intensive noise jointly. Our method is based on the proposed Low-Rank Regularized Retinex Model (LR3M), which is the first to inject low-rank prior into a Retinex decomposition process to suppress noise in the reflectance map. Our method estimates a piece-wise smoothed illumination and a noise-suppressed reflectance sequentially, avoiding remaining noise in the illumination and reflectance maps which are usually presented in alternative decomposition methods. After getting the estimated illumination and reflectance, we adjust the illumination layer and generate our enhancement result. Furthermore, we apply our LR3M to video low-light enhancement. We consider inter-frame coherence of illumination maps and find similar patches through reflectance maps of successive frames to form the low-rank prior to make use of temporal correspondence. Our method performs well for a wide variety of images and videos, and achieves better quality both in enhancing and denoising, compared with the state-of-the-art methods.
Purpose:
The major obstacles of radiofrequency ablation (RFA) heat treatments are nonuniform heating in the thermal lesion and heat sinks caused by large blood vessels during treatments which could ...lead to high tumor recurrence in patients. The objective of this study is to help comprehend RFA heat treatment through thermal lesion formation using computer simulation, and thus to provide helpful assistance in planning RFA.
Methods:
RFA heat treatment is a popular “minimally invasive” treatment method for both primary and metastatic liver tumors, and the heat treatment is studied by numerical calculation. A finite difference model is used to solve all partial differential equations for a simple three-dimensional cubic geometry model. Maximum tissue temperature is used as a critical index for reaching thermal lesion during RFA. Cylindrical RF cool-tip electrode is internally cooled at constant water temperature. RFA thermal lesion is studied at various impacts by single and countercurrent blood vessel(s) traversing the thermal lesion. Several factors are considered, such as location, diameter, and orientation of the blood vessel(s) to the electrode.
Results:
Results show the thermal lesion size decreases as the lesion blood perfusion rate increases. And, single large blood vessel which is orthogonal to RF electrode will cause less undercooled volume in the thermal lesion than one which is parallel to RF electrode. Furthermore, convective energy may easily damage parallel vessel and its surrounding normal tissues during RFA. Small blood vessels (or larger vessels with slow blood flow rate) during RFA could form “tail-like” thermal lesion formation, which could damage vessel downstream spots.
Conclusions:
Studies suggested that incomplete RF tumor ablation still exists within 1 cm distance between large blood vessel and RF electrode in a liver. This could have significant impact on local tumor recurrence rates. Second, if thermally significant vessel existed inevitably within the lesion, avoiding the RF cool-tip electrode placement next to the parallel large blood vessel would have a better heat treatment during RF heating. Additionally, reduced blood flow rate could help reduce significant cooling by large blood vessel.
Abstract
Tuning metal–support interaction has been considered as an effective approach to modulate the electronic structure and catalytic activity of supported metal catalysts. At the atomic level, ...the understanding of the structure–activity relationship still remains obscure in heterogeneous catalysis, such as the conversion of water (alkaline) or hydronium ions (acid) to hydrogen (hydrogen evolution reaction, HER). Here, we reveal that the fine control over the oxidation states of single-atom Pt catalysts through electronic metal–support interaction significantly modulates the catalytic activities in either acidic or alkaline HER. Combined with detailed spectroscopic and electrochemical characterizations, the structure–activity relationship is established by correlating the acidic/alkaline HER activity with the average oxidation state of single-atom Pt and the Pt–H/Pt–OH interaction. This study sheds light on the atomic-level mechanistic understanding of acidic and alkaline HER, and further provides guidelines for the rational design of high-performance single-atom catalysts.
Nonalcoholic fatty liver disease (NAFLD) is a serious liver disorder associated with the accumulation of fat and inflammation. The objective of this study was to determine the gut microbiota ...composition that might influence the progression of NAFLD. Germ-free mice were inoculated with feces from patients with nonalcoholic steatohepatitis (NASH) or from healthy persons (HL) and then fed a standard diet (STD) or high-fat diet (HFD). We found that the epididymal fat weight, hepatic steatosis, multifocal necrosis, and inflammatory cell infiltration significantly increased in the NASH-HFD group. These findings were consistent with markedly elevated serum levels of alanine transaminase, aspartate transaminase, endotoxin, interleukin 6 (IL-6), monocyte chemotactic protein 1 (Mcp1), and hepatic triglycerides. In addition, the mRNA expression levels of Toll-like receptor 2
), Toll-like receptor 4
, tumor necrosis factor alpha (
),
, and peroxisome proliferator-activated receptor gamma (
) significantly increased. Only abundant lipid accumulation and a few inflammatory reactions were observed in group HL-HFD. Relative abundance of
and
shifted in the HFD-fed mice. Furthermore, the relative abundance of
was the highest in group NASH-HFD. Nevertheless, obesity-related
were significantly upregulated in HL-HFD mice. Our results revealed that the gut microbiota from NASH Patients aggravated hepatic steatosis and inflammation. These findings might partially explain the NAFLD progress distinctly was related to different compositions of gut microbiota.
This paper employs quantile regression to analyze the determinants of household electricity consumption in Taiwan over the period 1981–2011. Our results show that the effects of demographic, ...socioeconomic, and household dwelling characteristics on household electricity consumption may differ across quantiles and may change over time. We found that household income and household size were significant in all quantiles for each year. We identify the characteristics of high-electricity-consuming households. Households with higher income, larger household size, and more elderly members consumed more electricity. In terms of dwelling attributes, larger housing areas, homes with more appliances, and owner-occupied, business-used, and multi-floor houses contributed to higher household electricity consumption. Strategies for reducing electricity consumption should focus on specific groups that tend to exhibit higher electricity use. However, we also found that the low-income and small-size households may have higher electricity consumption on a per capita basis. Thus, as household size decreased, the increase of per capita electricity demand driven by the change of household size should be a matter of concern.
•We analyze the determinants of household electricity use between 1981 and 2011.•We identify the characteristics of high-electricity-consuming households.•The effects of predictor variables differ across quantiles and change over time.•Income variable and household size were significant in all quantiles for each year.•Strategies for reducing electricity use should focus on high electricity users.
In regenerative medicine applications, the differentiation stage of implanted stem cells must be optimized to control cell fate and enhance therapeutic efficacy. We investigated the therapeutic ...potential of human induced pluripotent stem cell (iPSC)-derived cells at two differentiation stages on peripheral nerve regeneration. Neural crest stem cells (NCSCs) and Schwann cells (NCSC-SCs) derived from iPSCs were used to construct a tissue-engineered nerve conduit that was applied to bridge injured nerves in a rat sciatic nerve transection model. Upon nerve conduit implantation, the NCSC group showed significantly higher electrophysiological recovery at 1 month as well as better gastrocnemius muscle recovery at 5 months than the acellular group, but the NCSC-SC group didn't. Both transplanted NCSCs and NCSC-SCs interacted with newly-growing host axons, while NCSCs showed better survival rate and distribution. The transplanted NCSCs mainly differentiated into Schwann cells with no teratoma formation, and they secreted higher concentrations of brain-derived neurotrophic factor and nerve growth factor than NCSC-SCs. In conclusion, transplantation of iPSC-NCSCs accelerated functional nerve recovery with the involvement of stem cell differentiation and paracrine signaling. This study unravels the in vivo performance of stem cells during tissue regeneration, and provides a rationale of using appropriate stem cells for regenerative medicine.
Synthesizing insights from a dynamic capability perspective and social network theory, this study identifies the factors influencing green innovation and examines the relationships between ...influencing factors, green innovation, and performance. This study uses structural equation modeling to test the research hypotheses. The results indicate that dynamic capability, coordination capability, and social reciprocity are significant drivers of green innovation, including green product innovation and green process innovation. Green product and process innovation have positive effects on environmental performance and organizational performance. These findings are relevant to firms in quest of green management and innovation.
Abstract Objectives Due to the inconsistent definitions, reporting methods and study characteristics, prevalences of peri-implant diseases significantly varied in studies. This study aimed to ...systematically analyze implant-based and subject-based prevalences of peri-implant diseases and assess clinical variables potentially affecting the prevalence. Sources Electronic search of studies was conducted using MEDLINE (PubMed), EMBASE and Web of Science. Publication screening, data extraction, and quality assessment were performed. Study selection Clinical studies having an at least average three-year follow-up period were selected. The numbers of subjects and implants in the studies had to be equal to or more than thirty. Data Forty seven studies were selected and prevalences of peri-implant diseases were analyzed. Since heterogeneity existed in each outcome (I2 = 94.7, 95.7, 95.3, and 99.3 for implant-based and subject-based peri-implantitis and peri-implant mucositis, respectively), the random-effects model based on the DerSimonian and Laird method, which incorporate an estimate of heterogeneity in the weighting, was applied to obtain the pooled prevalence. Weighted mean implant-based and subject-based peri-implantitis prevalences were 9.25% (95% Confidence Interval (CI): 7.57, 10.93) and 19.83% (CI 15.38, 24.27) respectively. Weighted mean implant-based and subject-based peri-implant mucositis prevalences were 29.48% (CI: 22.65, 36.32) and 46.83% (CI: 38.30, 55.36) respectively. Functional time and implant to subject ratio were associated with subject-based peri-implantitis prevalence, but not peri-implant mucositis prevalences. Conclusions Peri-implant diseases were prevalent and prevalence of peri-implantitis increased over time. Prevalences of peri-implantitis and peri-implant mucositis might not be highly associated since the prevalences were influenced by distinct variables. The results should be carefully interpreted because of data heterogeneity. Clinical significance Peri-implant diseases affect a significant number of dental implants and patients. It is important to understand the difficulties in diagnosis of these diseases and risk factors which may be modified to reduce the potential for disease occurrence or progression.
Feature selection becomes prominent, especially in the data sets with many variables and features. It will eliminate unimportant variables and improve the accuracy as well as the performance of ...classification. Random Forest has emerged as a quite useful algorithm that can handle the feature selection issue even with a higher number of variables. In this paper, we use three popular datasets with a higher number of variables (Bank Marketing, Car Evaluation Database, Human Activity Recognition Using Smartphones) to conduct the experiment. There are four main reasons why feature selection is essential. First, to simplify the model by reducing the number of parameters, next to decrease the training time, to reduce overfilling by enhancing generalization, and to avoid the curse of dimensionality. Besides, we evaluate and compare each accuracy and performance of the classification model, such as Random Forest (RF), Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and Linear Discriminant Analysis (LDA). The highest accuracy of the model is the best classifier. Practically, this paper adopts Random Forest to select the important feature in classification. Our experiments clearly show the comparative study of the RF algorithm from different perspectives. Furthermore, we compare the result of the dataset with and without essential features selection by RF methods
varImp(),
Boruta, and Recursive Feature Elimination (RFE) to get the best percentage accuracy and kappa. Experimental results demonstrate that Random Forest achieves a better performance in all experiment groups.
PDF
