Nondestructive Near-infrared Identification of Hawthorn Fruit Cultivars Based on Natural Language Processing

Hawthorn fruits of different varieties have varied nutritional composition, sensory properties etc., thus required for different processing for product development. Due to the limitations of traditional analytical methods of time-consuming, destructive sample preparation, and high cost ect., non-destructive techniques for variety identification are needed which would benefit for large scale production of foods with hawthorn fruits. In this study, a total of 240 hawthorn fruit samples from four different varieties were subjected for near-infrared spectroscopy analysis and the collected spectral data were pre-processed by different algorithms. In order to achieve non-destructive identification of hawthorn varieties, natural language processing (NLP) model was applied for data analysis, including long short-term memory (LSTM), gated recurrent unit (GRU) neural network, logistic regression, native Bayes, decision trees, and k-nearest neighbors. The results showed that the two deep learning models both had the best discrimination effect on the spectral preprocessed by principal component analysis (PCA) with the accuracy of the validation set and test set reached 99.46%±0.00% and 100%±0.00%. While, the logistic regression model showed excellent discrimination ability for hawthorn fruit spectra but poor discrimination ability for the difference of second order (D2) pretreatment spectra (accuracy of 96.65% in the validation set and 89.58% in the test set). The naive Bayes model also showed excellent discrimination effect on the spectra processed by PCA, and the accuracy of the validation set was 95.65%, and the accuracy of the test set was 95.83%. Results gained in this study confirmed the feasibility of applying NLP to the near-infrared non-destructive identification of hawthorn fruits

Continual Exposure to Cigarette Smoke Extracts Induces Tumor-Like Transformation of Human Nontumor Bronchial Epithelial Cells in a Microfluidic Chip

IntroductionHeavy cigarette smoking-related chronic obstructive pulmonary disease is an independent risk factor for lung squamous carcinoma. However, the mechanisms underlying the malignant transformation of bronchial epithelial cells are unclear.MethodsIn our study, human tumor-adjacent bronchial epithelial cells were obtained from 10 cases with smoking-related chronic obstructive pulmonary disease and lung squamous carcinoma and cultured in an established microfluidic chip for continual exposure to cigarette smoke extracts (CSE) to investigate the potential tumor-like transformation and mechanisms. The integrated microfluidic chip included upstream concentration gradient generator and downstream cell culture chambers supplied by flowing medium containing different concentrations of CSE.ResultsOur results showed that continual exposure to low doses of CSE promoted cell proliferation whereas to high doses of CSE triggered cell apoptosis. Continual exposure to CSE promoted reactive oxygen species production in human epithelial cells in a dose-dependent manner. More importantly, continual exposure to low dose of CSE promoted the epithelial-to-mesenchymal transition process and anchorage-independent growth, and increased chromosome instability in bronchial epithelial cells, accompanied by activating the GRP78, NF-κB, and PI3K pathways.ConclusionsThe established microfluidic chip is suitable for primary culture of human tumor-adjacent bronchial epithelial cells to investigate the malignant transformation. Continual exposure to low doses of CSE promoted tumor-like transformation of human nontumor bronchial epithelial cells by inducing reactive oxygen species production and activating the relevant signaling

Studies of Ionic Current Rectification Using Polyethyleneimines Coated Glass Nanopipettes

The modification of glass nanopipettes with polyethyleneimines (PEIs) has been successfully achieved by a relatively simple method, and the smallest tip opening is around 3 nm. Thus, in a much wider range of glass pipettes with radii from several nanometers to a few micrometers, the ion current rectification (ICR) phenomenon has been observed. The influences of different KCl concentrations, pH values, and tip radii on the ICR are investigated in detail. The sizes of PEIs have been determined by dynamic light scattering, and the effect of the sizes of PEIs for the modification, especially for a few nanometer-pipettes in radii, is also discussed. These findings systemically confirm and complement the theoretical model(7,18) and provide a platform for possible selectively molecular detection and mimic biological ion channels

Down-regulation of GRP78 is associated with the sensitivity of chemotherapy to VP-16 in small cell lung cancer NCI-H446 cells

<p>Abstract</p> <p>Background</p> <p>Chemotherapy resistance remains a major obstacle for the treatment of small cell lung cancer (SCLC). Glucose-regulated protein 78 (GRP78), an endoplasmic reticulum chaperone, plays a critical role in chemotherapy resistance in some cancers. However, whether the suppression of the chaperone can enhance the sensitivity of chemotherapy in SCLC is still unclear.</p> <p>Methods</p> <p>The SCLC NCI-H446 cells were divided into three groups: BAPTA-AM→A23187-treated group, A23187-treated group and control-group. Immunofluorescence, western blot and RT-PCR were used to assess the expression of GRP78 at both protein and mRNA levels. Cell apoptosis and the cell cycle distributions of the cells were analyzed by flow cytometry in order to evaluate the therapeutic sensitivity to VP-16.</p> <p>Results</p> <p>The expression of GRP78 at both protein and mRNA levels in the BAPTA-AM→A23187-treated cells dramatically decreased as compared to that in both A23187-treated and control groups. After treatment by VP-16, the percentage of apoptotic cells in BAPTA-AM→A23187-treated cells were: 33.4 ± 1.01%, 48.2 ± 1.77%, 53.0 ± 1.43%, 56.5 ± 2.13%, respectively, corresponding to the concentrations of BAPTA-AM 10, 15, 25, 40 μM, which was statistically significant high in comparison with the A23187-treated group and untreated-group (7.18 ± 1.03% and 27.8 ± 1.45%, respectively, p < 0.05). The results from analysis of cell cycle distribution showed that there was a significantly decreased in G₁phase and a dramatically increased in S phase for the BAPTA-AM→A23187-treated cells as compared with the untreated cells.</p> <p>Conclusion</p> <p>BAPTA-AM is a strong inhibitor of GRP78 in the NCI-H446 cell line, the down-regulation of GRP78 can significantly increase the sensitivity to VP-16. The suppression of GRP78 may offer a new surrogated therapeutic approach to the clinical management of lung cancer.</p

The Splicing Factor RBM4 Controls Apoptosis, Proliferation, and Migration to Suppress Tumor Progression

Splicing dysregulation is one of the molecular hallmarks of cancer. However, the underlying molecular mechanisms remain poorly defined. Here we report the splicing factor RBM4 suppresses proliferation and migration of various cancer cells by specifically controlling cancer-related splicing. Particularly, RBM4 regulates Bcl-x splicing to induce apoptosis, and co-expression of Bcl-xL partially reverses the RBM4-mediated tumor suppression. Moreover, RBM4 antagonizes an oncogenic splicing factor, SRSF1, to inhibit mTOR activation. Strikingly, RBM4 expression is dramatically decreased in cancer patients, and RBM4 level is positively correlated with improved survival. In addition to providing mechanistic insights of cancer-related splicing dysregulation, this study establishes RBM4 as a tumor suppressor with therapeutic potentials and clinical values as a prognostic factor

A Lightweight Convolutional Neural Network Based on Visual Attention for SAR Image Target Classification

With the continuous development of the convolutional neural network (CNN) concept and other deep learning technologies, target recognition in Synthetic Aperture Radar (SAR) images has entered a new stage. At present, shallow CNNs with simple structure are mostly applied in SAR image target recognition, even though their feature extraction ability is limited to a large extent. What&rsquo;s more, research on improving SAR image target recognition efficiency and imbalanced data processing is relatively scarce. Thus, a lightweight CNN model for target recognition in SAR image is designed in this paper. First, based on visual attention mechanism, the channel attention by-pass and spatial attention by-pass are introduced to the network to enhance the feature extraction ability. Then, the depthwise separable convolution is used to replace the standard convolution to reduce the computation cost and heighten the recognition efficiency. Finally, a new weighted distance measure loss function is introduced to weaken the adverse effect of data imbalance on the recognition accuracy of minority class. A series of recognition experiments based on two open data sets of MSTAR and OpenSARShip are implemented. Experimental results show that compared with four advanced networks recently proposed, our network can greatly diminish the model size and iteration time while guaranteeing the recognition accuracy, and it can effectively alleviate the adverse effects of data imbalance on recognition results

Upconversion and Downconversion Fluorescent Graphene Quantum Dots: Ultrasonic Preparation and Photocatalysis

A facile ultrasonic route for the fabrication of graphene quantum dots (GQDs) with upconverted emission is presented. The as-prepared GQDs exhibit an excitation-independent downconversion and upconversion photoluminescent (PL) behavior, and the complex photocatalysts (rutile TiO₂/GQD and anatase TiO₂/GQD systems) were designed to harness the visible spectrum of sunlight. It is interesting that the photocatalytic rate of the rutile TiO₂/GQD complex system is <i>ca.</i> 9 times larger than that of the anatase TiO₂/GQD complex under visible light (λ > 420 nm) irradiation in the degradation of methylene blue

Wnt signaling in castration-resistant prostate cancer: implications for therapy.

Increasing evidence has indicated that Wnt signaling plays complex roles in castration resistant prostate cancer (CRPC). Although not all data were consistent, β-catenin nuclear localization and its co-localization with androgen receptor (AR) were more frequently observed in CRPC compared to hormone naïve prostate cancer. This direct interaction between AR and β-catenin seemed to elicit a specific expression of a set of target genes in low androgen conditions in CRPC. Paracrine Wnt signaling also was shown to aid resistance to chemotherapy and androgen deprivation therapy. Results from the next generation sequencing studies (i.e. RNA-seq and whole exosome sequcing) of CRPC specimens have identified the Wnt pathway as one of the top signaling pathways with significant genomic alterations in CRPC, whereas, Wnt pathway alterations were virtually absent in hormone naïve primary prostate cancer. Furthermore, Wnt signaling has been suggested to play an important role in cancer stem cell functions in prostate cancer recurrence and resistance to androgen deprivation therapy. Therefore, in this review we have summarized existing knowledge regarding potential roles of Wnt signaling in CRPC and underline Wnt signaling as a potential therapeutic target for CRPC. Further understanding of Wnt signaling in castration resistance may eventually contribute new insights into possible treatment options for this incurable disease