Abstract
Supported metal nanoparticles are of universal importance in many industrial catalytic processes. Unfortunately, deactivation of supported metal catalysts via thermally induced sintering is ...a major concern especially for high-temperature reactions. Here, we demonstrate that the particle distance as an inherent parameter plays a pivotal role in catalyst sintering. We employ carbon black supported platinum for the model study, in which the particle distance is well controlled by changing platinum loading and carbon black supports with varied surface areas. Accordingly, we quantify a critical particle distance of platinum nanoparticles on carbon supports, over which the sintering can be mitigated greatly up to 900 °C. Based on in-situ aberration-corrected high-angle annular dark-field scanning transmission electron and theoretical studies, we find that enlarging particle distance to over the critical distance suppress the particle coalescence, and the critical particle distance itself depends sensitively on the strength of metal-support interactions.
Cancer is still presenting a serious threat to human health worldwide. The understanding of the complex biology of cancer and the development of oncotherapy have led to increasing treatment ...approaches such as targeted therapy and immunotherapy. Chinese medicinal herbs have attracted considerable attention due to their potential anticancer effects. Some natural products or formulae from Chinese medicinal herbs with directly or indirectly anticancer effects have been reported. In this article, we summarized the current progression on development of anticancer drugs from Chinese medicinal herbs, toward providing ideas for further development and application of Chinese medicinal herbs in cancer therapy.
Objective Congenital hypothyroidism (CH), the most common neonatal metabolic disorder, is characterized by impaired neurodevelopment. Although several candidate genes have been associated with CH, ...comprehensive screening of causative genes has been limited. Design and methods One hundred ten patients with primary CH were recruited in this study. All exons and exon–intron boundaries of 21 candidate genes for CH were analyzed by next-generation sequencing. And the inheritance pattern of causative genes was analyzed by the study of family pedigrees. Results Our results showed that 57 patients (51.82%) carried biallelic mutations (containing compound heterozygous mutations and homozygous mutations) in six genes (DUOX2, DUOXA2, DUOXA1, TG, TPO and TSHR) involved in thyroid hormone synthesis. Autosomal recessive inheritance of CH caused by mutations in DUOX2, DUOXA2, TG and TPO was confirmed by analysis of 22 family pedigrees. Notably, eight mutations in four genes (FOXE1, NKX2-1, PAX8 and HHEX) that lead to thyroid dysgenesis were identified in eight probands. These mutations were heterozygous in all cases and hypothyroidism was not observed in parents of these probands. Conclusions Most cases of congenital hypothyroidism in China were caused by thyroid dyshormonogenesis rather than thyroid dysgenesis. This study identified previously reported causative genes for 57/110 Chinese patients and revealed DUOX2 was the most frequently mutated gene in these patients. Our study expanded the mutation spectrum of CH in Chinese patients, which was significantly different from Western countries.
Bacterial cellulose (BC) is well known as a high-performance dietary fiber. This study investigates the adsorption capacity of BC for cholesterol, sodium cholate, unsaturated oil, and heavy metal ...ions in vitro. Further, a hyperlipidemia mouse model was constructed to investigate the effects of BC on lipid metabolism, antioxidant levels, and intestinal microflora. The results showed that the maximum adsorption capacities of BC for cholesterol, sodium cholate, Pb
and Cr
were 11.910, 16.149, 238.337, 1.525 and 1.809 mg/g, respectively. Additionally, BC reduced the blood lipid levels, regulated the peroxide levels, and ameliorated the liver injury in hyperlipidemia mice. Analysis of the intestinal flora revealed that BC improved the bacterial community of intestinal microflora in hyperlipidemia mice. It was found that the abundance of
was increased, while the abundance of
and
was decreased at the phylum level. In addition, increased abundance of
and decreased abundance of
and
were obtained at the genus level. These changes were supposed to be beneficial to the activities of intestinal microflora. To conclude, the findings prove the role of BC in improving lipid metabolism in hyperlipidemia mice and provide a theoretical basis for the utilization of BC in functional food.
Fagopyrum dibotrys (F. dibotrys) (D.Don) H.Hara is a well-known edible herbal medicine in Asian countries. It has been widely used for the treatment of lung diseases, swelling, etc., and is also an ...important part of many Chinese medicine prescriptions. At present, more than 100 compounds have been isolated and identified from F. dibotrys, and these compounds can be primarily divided into flavonoids, phenols, terpenes, steroids, and fatty acids. Flavonoids and phenolic compounds are considered to be the main active ingredients of F. dibotrys. Previous pharmacological studies have shown that F. dibotrys possesses anti-inflammatory, anti-cancer, anti-oxidant, anti-bacterial, and anti-diabetic activities. Additional studies on functional genes have led to a better understanding of the metabolic pathways and regulatory factors related with the flavonoid active ingredients in F. dibotrys. In this paper, we systemically reviewed the research advances on the phytochemistry and pharmacology of F. dibotrys, as well as the functional genes related to the synthesis of active ingredients, aiming to promote the development and utilization of F. dibotrys. Keywords: Fagopyrum dibotrys, Phytochemistry, Pharmacology, Functional genes, Active ingredients
Element partition coefficients play key roles in understanding various geological processes and are typically measured by performing high-temperature-pressure (HTP) experiments. In HTP experiments, ...samples are usually enclosed in capsules made of noble metals. Previous studies have shown that Fe, Ni, and Cu readily alloy with noble metals, resulting in significant loss of these elements from the experimental samples. The loss of elements could severely undermine phase equilibrium and compromise the validity and accuracy of the obtained partition coefficients. However, it remains unclear if other elements (in addition to Fe, Ni, and Cu) will also be lost from samples during HTP experiments, and how to minimize such losses. We performed a series of experiments at 1 GPa and 1400°C to investigate which elements will be lost from samples and explore the influence of capsule materials and oxygen fugacity (fO2) on the loss behavior of elements. The starting material is a synthesized basaltic glass consisting of 8 major elements and 37 trace elements. The sample capsules included platinum (Pt), graphite-lined Pt, and rhenium-lined Pt, and the experimental oxygen fugacity (fO2) was buffered from <FMQ-2 to ∼FMQ+5. Results show that: (1) 15 elements (V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, Ge, Cd, In, Sn, W, and Mo) were lost from the sample due to direct contacting and alloying with Pt under graphite-buffered conditions; (2) graphite and Re lining can physically isolate the starting material from Pt and prevent the loss of V, Cr, Mn, Fe, Zn, Ga, Ge, Cd, In, Sn, W, and Mo, but only slightly reduce the loss of Ni and Cu; and (3) element loss can be significantly reduced under oxidizing conditions, and all elements except Cu were retained in the samples under Ru-RuO2 buffered conditions. These findings provide several viable capsule assemblies that are capable of preventing or reducing element loss, which may prove useful in determining accurate partition coefficients in HTP experiments.
Deep neural network-based methods have recently achieved excellent performance in visual tracking task. As very few training samples are available in visual tracking task, those approaches rely ...heavily on extremely large auxiliary dataset such as ImageNet to pretrain the model. In order to address the discrepancy between the source domain (the auxiliary data) and the target domain (the object being tracked), they need to be finetuned during the tracking process. However, those methods suffer from sensitivity to the hyper-parameters such as learning rate, maximum number of epochs, size of mini-batch, and so on. Thus, it is worthy to investigate whether pretraining and fine tuning through conventional back-prop is essential for visual tracking. In this paper, we shed light on this line of research by proposing convolutional random vector functional link (CRVFL) neural network, which can be regarded as a marriage of the convolutional neural network and random vector functional link network, to simplify the visual tracking system. The parameters in the convolutional layer are randomly initialized and kept fixed. Only the parameters in the fully connected layer need to be learned. We further propose an elegant approach to update the tracker. In the widely used visual tracking benchmark, without any auxiliary data, a single CRVFL model achieves 79.0% with a threshold of 20 pixels for the precision plot. Moreover, an ensemble of CRVFL yields comparatively the best result of 86.3%.
As a powerful tool for data regression and classification, neural networks have received considerable attention from researchers in fields such as machine learning, statistics, computer vision and so ...on. There exists a large body of research work on network training, among which most of them tune the parameters iteratively. Such methods often suffer from local minima and slow convergence. It has been shown that randomization based training methods can significantly boost the performance or efficiency of neural networks. Among these methods, most approaches use randomization either to change the data distributions, and/or to fix a part of the parameters or network configurations. This article presents a comprehensive survey of the earliest work and recent advances as well as some suggestions for future research.
•Functional foods play an important role in preventing metabolic diseases.•Metabolomics reveals the changes of bioactive compounds during processing and storage.•Metabolomics reflects the changes of ...small molecular metabolites in the body.•Metabolomics technology becomes an important research tool in the fields of food science.
Metabolomics is an important branch of systems biology, which can detect changes in the body's metabolism before and after the intervention of functional foods, identify effective metabolites, and predict the interventional effects and the mechanism. This review summarizes the latest research outcomes regarding interventional effects of functional foods on metabolic diseases via metabolomics analysis. Since metabolomics approaches are powerful strategies for revealing the changes in bioactive compounds of functional foods during processing and storage, we also discussed the effects of these parameters on functional food metabolites using metabolomics approaches. To date, a number of endogenous metabolites related to the metabolic diseases after functional foods intervention have been discovered. Unfortunately, the mechanisms of metabolic disease-related molecules are still unclear and require further studies. The combination of metabolomics with other omics technologies could further promote its ability to fully understand the precise biological processes of functional food intervention on metabolic diseases.
It′s just a phase: The title reaction sequence of para‐quinone methides (p‐QMs) has been developed with malonates under phase‐transfer catalysis. The reaction also offers an alternative route to ...asymmetric construction of diarylmethine stereocenters in excellent enantioselectivities and high yields.
PDF
