Many traditional fermented foods and beverages in both eastern and western countries are produced with the addition of starter cultures. Daqu is the undefined starter used for Chinese liquor, which ...contributed many fermentation functional fungal and bacterial communities to liquor fermentation process. However, the sources of these microbial communities and how these microorganisms formed in Daqu are still unclear. In this study, high-throughput sequencing combined with microbial source tracking analysis were applied to analyze the sources of the microbial communities in Daqu. We found fungal communities in Daqu were mainly originated from Daqu making environments (mainly tools and indoor ground), including Saccharomycopsis fibuligera, Pichia kudriavzevii, Rhizopus oryzae, Sterigmatomyces elviae, Aspergillus flavus/oryzae, Hyphopichia burtonii and Lichtheimia corymbifera. Meanwhile, most of bacterial communities in Daqu were from raw materials, including Gammaproteobacteria, Alphaproteobacteria and Bacilli. During Daqu-making process, the abundance of Gammaproteobacteria and Alphaproteobacteria that were not beneficial to liquor fermentation declined, but the abundance of the fermentation functional yeasts and Bacilli increased. Moreover, network analysis showed the bacteria in Daqu might be the drivers for the microbial succession during the Daqu-making process. This study shows that the Daqu production technology is a good way to screen fermentation functional microorganisms from complex environmental microbial communities.
•Raw materials were the main sources of bacteria in Daqu.•Daqu-making environment was the main source of fungi in Daqu.•Bacteria drove the microbial succession during Daqu-making process.
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•A fully automatic system for abdominal organ segmentation is presented.•Regional convolutional neural networks are used for organwise segmentation.•State-of-the-art results on ...abdominal organ segmentation challenge.
A fully automatic system for abdominal organ segmentation is presented. As a first step, an organ localization is obtained via a robust and efficient feature registration method where the center of the organ is estimated together with a region of interest surrounding the center. Then, a convolutional neural network performing voxelwise classification is applied. Two convolutional neural networks of different architecture are compared. The first one has a structure similar to networks used for classification and is applied using a sliding window approach. The second one has a structure allowing it to be applied in a fully convolutional manner reducing computation time. Despite limited training data, our experimental results are on par with state-of-the-art approaches that have been developed over many years. More specifically the method is applied to the MICCAI2015 challenge “Multi-Atlas Labeling Beyond the Cranial Vault” in the free competition for organ segmentation in the abdomen. The method performed well for both types of convolutional neural networks. For the fully convolutional network a mean Dice coefficient of 0.767 was achieved, for the network applied with sliding window this number was 0.757.
Meteorological and soil drought is disastrous to natural and social systems. It is expected that the occurrence of meteorological and soil drought compound events will become more frequent and ...extreme in the future. The propagation process of meteorological drought to soil drought plays an essential role in the occurrence of drought. However, the drought propagation process is not clear, especially the quantification of drought characteristic propagation process is rarely realized. This study constructs drought intensity propagation index (DIP) and drought duration propagation index (DDP), and then puts forward drought propagation partition in China. Furthermore, this study preliminarily discussed the driving factors of drought propagation and the relationship between land‐atmosphere interaction and main drought propagation partition (arid type drought propagation area, peer‐to‐peer type drought propagation area, and humid type drought propagation area). The results show that DDP and DIP are significantly negatively correlated in China from 1981 to 2020. From southeast to northwest, the propagation of drought intensity from meteorological drought to soil drought gradually increased and the propagation of drought duration gradually decreased. We further concluded that 68% of regions with similar intensity and duration of meteorological drought and soil drought (peer‐to‐peer type drought propagation area) are concentrated in semiarid and dry subhumid, which is exactly the area with strong land‐atmosphere interaction. In all land use types, grasslands are most prone to peer‐to‐peer propagation of drought. This study further reveals the law and mechanism of drought propagation and provides a new idea and attempt to clarify the drought propagation process.
Key Points
Drought intensity propagation index and drought duration propagation index for quantifying drought propagation characteristics are proposed
Dividing drought propagation partition
Discovery of drought propagation close peer‐to‐peer in areas with strongest land‐atmosphere coupling
Tumor cells reside in a highly complex and heterogeneous tumor microenvironment (TME), which is composed of a myriad of genetically stable non-cancer cells, including fibroblasts, immune cells, ...endothelial cells, and epithelial cells, and a tumor-specific extracellular matrix (ECM). Cancer-associated fibroblasts (CAFs), as an abundant and active stromal cell population in the TME, function as the signaling center and remodeling machine to aid the creation of a desmoplastic tumor niche. Although there is no denial that the TME and CAFs may have anti-tumor effects as well, a great deal of findings reported in recent years have convincingly revealed the tumor-promoting effects of CAFs and CAF-derived ECM proteins, enzymes, chemical factors and other downstream effectors. While there is growing enthusiasm for the development of CAF-targeting therapies, a better understanding of the complexities of CAF-ECM and CAF-cancer cell interactions is necessary before novel therapeutic strategies targeting the malignant tumor "soil" can be successfully implemented in the clinic.
In this work, silver nanoparticles (AgNPs)/reduced graphene oxide (rGO) nanocomposites were electrodeposited on glassy carbon electrodes (GCE) to construct electrochemical sensors for the detection ...of hydrogen peroxide (H
O
) and dopamine (DA). The AgNPs were synthesized on graphene oxide (GO) by the hydrothermal method, followed by the reduction of the GO during the electrodeposition process, resulting in the formation of the nanocomposites on the surface of the electrodes. The generation of AgNPs on the graphene sheets was verified by scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS). The AgNPs/rGO/GCE showed a linear response to H
O
in the range of 5 μM to 620 μM, with a sensitivity of 49 μA mM
cm
and a limit of detection (LOD) of 3.19 μA. The linear response of the AgNPs/rGO/GCE to DA ranged from 1 μM to 276 μM, the sensitivity was 7.86 μA mM
cm
, and the LOD was 0.18 μM. Furthermore, DA and H
O
were detected simultaneously in the same solution without interferences, and the sensors displayed good stability over time. The preparation method for the sensors is relatively eco-friendly, convenient, and efficient, exhibiting great potential for sensitive detection of DA and H
O
.
We developed a system for computer-assisted diagnosis (CAD) for real-time automated diagnosis of precancerous lesions and early esophageal squamous cell carcinomas (ESCCs) to assist the diagnosis of ...esophageal cancer.
A total of 6473 narrow-band imaging (NBI) images, including precancerous lesions, early ESCCs, and noncancerous lesions, were used to train the CAD system. We validated the CAD system using both endoscopic images and video datasets. The receiver operating characteristic curve of the CAD system was generated based on image datasets. An artificial intelligence probability heat map was generated for each input of endoscopic images. The yellow color indicated high possibility of cancerous lesion, and the blue color indicated noncancerous lesions on the probability heat map. When the CAD system detected any precancerous lesion or early ESCCs, the lesion of interest was masked with color.
The image datasets contained 1480 malignant NBI images from 59 consecutive cancerous cases (sensitivity, 98.04%) and 5191 noncancerous NBI images from 2004 cases (specificity, 95.03%). The area under curve was 0.989. The video datasets of precancerous lesions or early ESCCs included 27 nonmagnifying videos (per-frame sensitivity 60.8%, per-lesion sensitivity, 100%) and 20 magnifying videos (per-frame sensitivity 96.1%, per-lesion sensitivity, 100%). Unaltered full-range normal esophagus videos included 33 videos (per-frame specificity 99.9%, per-case specificity, 90.9%).
A deep learning model demonstrated high sensitivity and specificity for both endoscopic images and video datasets. The real-time CAD system has a promising potential in the near future to assist endoscopists in diagnosing precancerous lesions and ESCCs.
In this study, a cationic amphiphilic self-assembling peptide (SAP) Z23 was designed, and a simple bisphenol a (BPA) sensor, based on SAP Z23/multiwalled carbon nanotubes (Z23/MWCNTs) composite, was ...successfully fabricated on the surface of a glassy carbon electrode (GCE). The composite material was formed by π-π stacking interaction between the aromatic group on the hydrophobic side of Z23 and the side-wall of MWCNTs, with the charged hydrophilic group of Z23 exposed. During the electrocatalytic process of BPA, a synergistic effect was observed between Z23 and MWCNTs. The current response of the sensor based on composite material was 3.24 times that of the MWCNTs-modified electrode, which was much higher than that of the peptide-based electrode. Differential pulse voltammetry (DPV) was used to optimize the experimental conditions affecting the analytical performance of the modified electrode. Under optimal conditions, the linear range of the sensor was from 10 nM to 100 μM by amperometric measurement with sensitivity and limit of detection (LOD) at 6.569 μAμM
cm
and 1.28 nM (S/N = 3), respectively. Consequently, the sensor has excellent electrochemical performance and is easy to fabricate, making it a good prospect in the field of electrochemical detection in the future.
Acanthopanax senticosus (AS), previously classified as Eleutherococcus senticosus, is one of the most commonly used herbs in the Chinese materia medica. However, there is currently no comprehensive ...review summarising advances in AS research. AS has been used as a functional food and in various preparations since ancient times, to invigorate the liver and kidneys, replenish vitality, strengthen the bones, stimulate appetite, and improve memory. It is widely used in countries such as China, Korea, Japan, and Russia, for specific pharmacologic effects, although it contains various chemical components that ensure its broad-spectrum effect. Its chemical constituents mainly include glycosides and flavonoids. Over the past several decades, researchers worldwide have conducted systematic investigations on this herb. AS has positive pharmacological effects on the cardiovascular, central nervous, and immune systems. Representative pathways stimulated by AS are related to neuroactive ligand-receptor interactions, cancer, and phosphatidylinositol 3 kinase/protein kinase B signalling. Importantly, AS is safe and exerts no significant adverse effects at normal doses.
To provide comprehensive insights into the ethnobotany, medicinal uses, chemical composition, pharmacological activity, and toxicology of AS to aid its future development and utilisation.
Information about AS was collected from various sources, including classic books about Chinese herbal medicine and scientific databases including scientific journals, books, and pharmacopoeia. We discuss the ethnopharmacology of AS from 1965 to 2020 and summarise the knowledge of AS phytochemicals, pharmacological activity, quality control, and toxicology.
From the current literature, we conclude that AS is a promising dietary Chinese herb with various potential applications owing to its multiple therapeutic effects.
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•A review on Acanthopanax senticosus (AS) was performed.•This review provides comprehensive insights into the toxicology of AS.•The medicinal use, phytochemicals, and pharmacological activity of AS are discussed.•Our findings will help in the further development and utilisation of AS resources.
In this paper, we propose an adaptive locality weighted multisource joint sparse representation classification (ALWMJ-SRC) model for the classification of multisource remote sensing data. Although ...the notion of multitask joint sparsity has been recently developed for data fusion and has shown to be effective for various applications, in this paper, we suggest that there are important limitations stemming from the assumptions in such a framework. We propose a formulation that is inspired by this approach yet addresses some of the key shortcomings (e.g., uniform weights and unstable estimation of coefficients), resulting in a more robust formulation for data fusion. Specifically, we impose an adaptive locality weight to constrain the sparse coefficients, which not only considers the locality information between the test sample and the atoms in the dictionary but also helps ensure that the coefficients are adaptively penalized, reducing estimation bias. The adaptive locality weight is calculated for each source, which ensures that complementary information is employed from different sources for fusion. The optimization problem is solved using an alternating-direction-methods-of-multipliers formulation. In addition, the proposed algorithm is extended to the kernel space. The efficacy of the proposed algorithm is validated via experiments for two fusion scenarios-spectral-spatial classification and hyperspectral-LiDAR sensor fusion. The experimental results demonstrate that ALWMJ-SRC consistently performs better than state-of-the-art classification approaches.
Distributed generation and demand-side management are expected to play a more prominent role in future power systems. However, the increased number of generations and load demands pose new challenges ...to optimal energy management in a microgrid. In this paper, an economic dispatch model for microgrids considering Traditional Generators (TGs), energy storage units, wind turbines (WTs), and flexible loads is established. To tackle the Economic Dispatch Problem (EDP) over directed communication networks, a fully distributed algorithm developed by leveraging a two-step state information exchange mechanism is proposed. In addition, by employing a fixed stepsize, the proposed algorithm demonstrates rapid convergence. Furthermore, our algorithm is well-suited for nonquadratic convex cost functions. Subsequently, we extend our algorithm to address imperfect communication scenarios. Even in the presence of arbitrarily large yet bounded time delays, our algorithm exhibits robustness. Finally, several numerical examples are given to verify the correctness and effectiveness of the developed results.
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