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Su-Jun Sun,1 Peng Deng,1 Chun-E Peng,1 Hai-Yu Ji,2 Long-Fei Mao,1 Li-Zeng Peng1 1Key Laboratory of Agro-Products Processing Technology of Shandong Province, Key Laboratory of Novel Food Resources Processing Ministry of Agriculture, Institute of Agro-Food Science and Technology, Shandong Academy of Agricultural Sciences, Jinan, People’s Republic of China; 2Center for Mitochondria and Healthy Aging, College of Life Sciences, Yantai University, Yantai, People’s Republic of ChinaCorrespondence: Li-Zeng Peng, Tel +86-159-5412-8918, Email penglizeng@sdnu.edu.cnIntroduction: Chitosan is the product of the natural polysaccharide chitin removing part of the acetyl group, and exhibits various physiological and bioactive functions. Selenium modification has been proved to further enhance the chitosan bioactivities, and has been a hot topic recently.Methods: The present study aimed to investigate the potential inhibitory mechanism of selenium-modified chitosan (SMC) on HepG2 cells through MTT assays, morphological observation, annexin V–FITC/PI double staining, mitochondrial membrane potential determination, cell-cycle detection, Western blotting, and two-dimensional gel electrophoresis (2-DE).Results: The results indicated that SMC can induce HepG2 cell apoptosis with the cell cycle arrested in the S and G2/M phases and gradual disruption of mitochondrial membrane potential, reduce the expression of Bcl2, and improve the expression of Bax, cytochrome C, cleaved caspase 9, and cleaved caspase 3. Also, 2-DE results showed that tubulin α1 B chain, myosin regulatory light chain 12A, calmodulin, UPF0568 protein chromosome 14 open reading frame 166, and the cytochrome C oxidase subunit 5B of HepG2 cells were downregulated in HepG2 cells after SMC treatment.Discussion: These data suggested that HepG2 cells induced apoptosis after SMC treatment via blocking the cell cycle in the S and G2/M phases, which might be mediated through the mitochondrial apoptotic pathway. These results could be of benefit to future practical applications of SMC in the food and drug fields.Keywords: selenium-modified chitosan, antihepatoma activity, mitochondrial apoptotic pathway, differential protein analysis

With continuous development of artificial intelligence, text classification has gradually changed from a knowledge-based method to a method based on statistics and machine learning. Among them, it is a very important and efficient way to classify text based on the convolutional neural network (CNN) model. Text data are a kind of sequence data, while time sequentiality of the general text data is relatively weak, so text classification is usually less relevant to the sequential structure of the full text. Therefore, CNN-based text classification has gradually become a research hotspot when dealing with issues of text classification. For machine learning, especially deep learning, model interpretability has increasingly become the focus of academic research and industrial applications, and also become a key issue for further development and application of deep learning technology. Therefore, we recommend using the backtracking analysis method to conduct in-depth research on deep learning models. This paper proposes an analysis method for interpretability of a CNN text classification model. The method proposed by us can perform multi-angle analysis on the discriminant results of multi-classified text and multi-label classification tasks through backtracking analysis on model prediction results. Finally, the analysis results of the model can be displayed using visualization technology from multiple dimensions based on interpretability. The representative data set IMDB (Internet Movie Database) in text classification is verified by examples, and the results show that the model can be effectively analyzed when using our method.

A mild alkaline treatment with the assistance of surfactants has proved to be an effective way to introduce uniform mesopores into zeolites, yielding hierarchical materials with superior catalytic performance. Accelerating this process may open new opportunities in the scale-up of this new class of materials. In this study, we present an ultrafast surfactant-templating (UST) approach achieved within only a few minutes for the fast production of mesoporous ultra-stable Y (USY) zeolites by combining several favorable factors including high treating temperature, reactors featuring fast heating, and optimized reagent composition. Temperatures in the range of 150–220 °C yielded high quality materials, while too high temperatures (260–280 °C) produced inferior samples. The use of a flow reactor allowed for completing the UST in just one minute, which evidences the remarkable structural flexibility of zeolites that can reorganize in such a short time to accommodate a large amount of intracrystalline mesoporosity, without compromising their integrity or main properties. [ABSTRACT FROM AUTHOR]

Calcium phosphate crystals, as the main component of dentin and enamel, have been widely used for the occlusion of dentinal tubules. However, the low bond strength and poor sealing effect limit their clinical practicality. In this study, a collagen/calcium dual-affinitive peptide E8DS (EEEEEEEEDSpESpSpEEDR) and nano-hydroxyapatite (nano-HAp) flocculi were developed to seal dentin tubules for reducing dentin hypersensitivity, whereas the E8DS peptides were pre-applied to improve the adhesion of occlusive hydroxyapatite coating on dentin collagen matrix for the long-lasting sealing effect and relief from hypersensitivity. Our study showed that E8DS peptides had a strong affinity with dentin collageneous matrix that almost 43.7% of initial E8DS peptides immobilized on exposed dentin samples remained detained after continuous washing by distilled water for four weeks at a rate of 1 mL/min. Nano-HAp flocculi were obtained by re-neutralization of HAp-HCl solution and then brushed onto the surfaces of pre-treated human dentin disks with E8DS peptides, which showed a perfect occlusion of exposed dentinal tubules, as compared with Nano-HAp only and a commercial desensitizer, Green Or. With only around 10-min E8DS peptide pre-treatment, the occlusive mineral layers remained intact against consecutively stirred washing in phosphate-buffered saline or coke for 15 min, and 6 min of tooth-brushing, which implied that our E8DS peptide could comparatively improve the durability of sealant-dentin interface bonds for long-lasting dentine desensitization. [ABSTRACT FROM AUTHOR]

Aim:Spiking activities and neuronal network oscillations in the theta frequency range have been found in many cortical areas during information processing. The aim of this study is to determine whether nicotinic acetylcholine receptors (nAChRs) mediate neuronal network activity in rat medial septum diagonal band Broca (MSDB) slices.Methods:Extracellular field potentials were recorded in the slices using an Axoprobe 1A amplifier. Data analysis was performed off-line. Spike sorting and local field potential (LFP) analyses were performed using Spike2 software. The role of spiking activity in the generation of LFP oscillations in the slices was determined by analyzing the phase-time relationship between the spikes and LFP oscillations. Circular statistic analysis based on the Rayleigh test was used to determine the significance of phase relationships between the spikes and LFP oscillations. The timing relationship was examined by quantifying the spike-field coherence (SFC).Results:Application of nicotine (250 nmol/L) induced prominent LFP oscillations in the theta frequency band and both small- and large-amplitude population spiking activity in the slices. These spikes were phase-locked to theta oscillations at specific phases. The Rayleigh test showed a statistically significant relationship in phase-locking between the spikes and theta oscillations. Larger changes in the SFC were observed for large-amplitude spikes, indicating an accurate timing relationship between this type of spike and LFP oscillations. The nicotine-induced spiking activity (large-amplitude population spikes) was suppressed by the nAChR antagonist dihydro-β-erythroidine (0.3 μmol/L).Conclusion:The results demonstrate that large-amplitude spikes are phase-locked to theta oscillations and have a high spike-timing accuracy, which are likely a main contributor to the theta oscillations generated in MSDB during nicotine receptor activation. [ABSTRACT FROM AUTHOR]

Non-Intrusive Load Monitoring (NILM) increases awareness on user energy usage patterns. In this paper, an efficient and highly accurate NILM method is proposed featuring condensed representation, super-state and fusion of two deep learning based models. Condensed representation helps the two models perform more efficiently and preserve longer-term information, while super-state helps the model to learn correlations between appliances. The first model is a deep user model that learns user appliances usage patterns to predict the next appliance usage behavior based on past behaviors by capturing the dynamics of user behaviors history and appliances usage habits. The second model is a deep appliance group model that learns the characteristics of appliances with temporal and electrical information. These two models are then fused to perform NILM. The case study based on REFIT datasets demonstrates that the proposed NILM method outperforms two state-of-the-art benchmark methods. [ABSTRACT FROM AUTHOR]

The ethanol precipitation method has been widely-used for Dendrobium officinale polysaccharides preparation. However, the alcohol-soluble fractions have always been ignored, which causes significant wastes of resources and energies. In this study, the extraction, physicochemical properties, and immune regulation activity of an edible D. officinale polysaccharide (DOPs) isolated from the supernatant after 75% ethanol precipitation were systematically investigated. The structural characteristics determination results showed that DOPs was mainly composed of glucose and mannose at a molar ratio of 1.00:5.78 with an average molecular weight of 4.56 × 10 3 Da, which was made up of α-(1,3)-Glc p as the main skeleton, and the α-(1,4)-Glc p and β-(1,4)-Man p as the branches. Subsequently, the cyclophosphamide (CTX)-induced immunosuppressive mice model was established, and the results demonstrated that DOPs could dose-dependently protect the immune organs against CTX damage, improve the immune cells activities, and promote the immune-related cytokines (IL-2, IFN-γ and TNF-α) secretions. Furthermore, DOPs treatment also effectively enhanced the antioxidant enzymes levels (SOD, GSH-Px) in sera and livers, therefore weakening the oxidative damage of CTX-treated mice. Considering these above data, DOPs presented great potential to be explored as a natural antioxidant and supplement for functional foods.

The occlusion of dentinal tubules is considered to be an effective strategy to treat dentin hypersensitivity. This in vitro study introduced mesoporous silica nanoparticles (MSNs) for tubular occlusion to achieve deeper sealing. Further, MSNs with independently encapsulated calcium and phosphates (as calcium and phosphate sources) (Ca(2+)/PO₄(3-)@MSNs) were introduced to achieve improved efficacy of tubular occlusion and remineralization. MSNs or Ca(2+)/PO₄(3-)@MSNs were proportionally mixed with distilled water to make their respective desensitizing slurries, which were used to treat dentin surfaces. The efficacy of tubular occlusion was evaluated using scanning electron microscopy (SEM) images and an image analyzer, and compared with that achieved with Green-Or -a commonly used densitizer. The results demonstrated that both MSNs and Ca(2+)/PO₄(3-)@MSNs almost completely occluded dentinal tubules and formed a deeper seal which penetrated about 105 μm deep into the dentinal tubules. Significant differences in tubular occlusion were observed between Green-Or densitizer and MSNs or Ca(2+)/PO₄(3-)@MSNs. The novel MSNs-based nanomaterials showed great potential as a treatment option for dentin hypersensitivity.

Acoustic analysis is one of the important branches of biometric recognition technology widely used now. The mainly aim of the technology is to recognize the identity of person and judge the content of speech or diagnose the illness automatically according to the features extracted from the speaker's waveforms. All these features are related with the characteristics of speaker's physiological, pathological and psychological action. Speaker recognition study has its 50-year old history already, but acoustic analysis in diagnosing disease has been founded since 1970s. This paper introduces the main concept and research background of this diagnosing system generally and discusses the problems generated during processing. At last the prospect for the applications of acoustic analysis is forecasted.

This paper proposed a support vector machine (SVM) based classification method to identify diversified pathological voices. Sound signals were sampled from the pronunciation of a vowel "a" vocalized by 214 subjects, including 181 patients suffered from various dysphonias (such as polypoid degeneration, adductor spasmodic dysphonia, vocal fatigue, vocal tremor, vocal fold edema, hyperfunction, and erythema), and 33 healthy subjects. 25 acoustic parameters were calculated from the sampled data for each subject. The original acoustic dataset was first transformed via principal component analysis (PCA) method into a new feature space. To learn the identification boundary for healthy and pathological voices, a soft-margin SVM and three kinds of kernels were examined. The results under different combination of parameters and kernels were investigated. The effectiveness of SVM-based approach seems to be promising in the application of pathological voice identification.