Hypoxia-inducible factor-1α contributes to the proliferation of cholesteatoma keratinocytes through regulating endothelin converting enzyme 1 expression.

Objective: Cholesteatoma is a hyperproliferative, pseudoneoplastic lesion of the middle ear characterized by aggressive growth and bone destruction. Hypoxia-inducible factor-1α (HIF-1α, also known as HIF1A) is a key transcription factor that enters the nucleus and upregulates many genes involved in cancer progression in the oxygen-free environment. This study is designed to explore the role and mechanism of HIF1A in the progression of cholesteatoma. Methods: HIF1A and endothelin converting enzyme 1 (ECE1) levels were determined using real-time quantitative polymerase chain reaction. The protein levels of HIF1A, Cyclin D1, proliferating cell nuclear antigen, and ECE1 were measured using western blot. Cell viability, proliferation, and cell cycle progression were analyzed using cell counting kit-8, Colony formation, 5-ethynyl-2'-deoxyuridine, and flow cytometry assays. Binding between HIF-1α and ECE1 promoter was predicted by Jaspar and verified using Chromatin immunoprecipitation and dual-luciferase reporter assays. Results: HIF1A and ECE1 were highly expressed in cholesteatoma patients and keratinocytes. Moreover, HIF1A knockdown might suppress the cell viability, proliferation, and cycle progression of cholesteatoma keratinocytes. Furthermore, HIF1A upregulated the transcription of ECE1 through binding to its promoter region. Conclusion: HIF1A might expedite cholesteatoma keratinocyte proliferation partly by increasing ECE1 expression, providing a possible therapeutic target for the cholesteatoma treatment.

Two New Compounds from the Endophytic Fungi of Dryopteris crassirhizoma and Their Antimicrobial Activities.

Two endophytic fungi Trichoderma afroharzianum (HP-3) and Alternaria alstroemeriae (HP-7) were isolated and purified from the fresh root of Dryopteris crassirhizoma. Chemical investigation of the two fungi resulted in the isolation of two new phenols 2,4-dihydroxy-3-farnesyl-5-methoxy benzoic acid (1) and 2-hydroxyphenethyl 2-phenylacetate (2), together with 22 known compounds. Their structures were elucidated by NMR, UV, IR, HRESIMS, and comparison to the literature data. Compounds 15 and 16 showed significant antibacterial activity against Micrococcus lysodeikticus with MIC value of 6.25 µg/mL, while 8 and 14 displayed moderate inhibitory activities against several plant pathogenic fungi and clinically important bacterial strains. This is the first study to report the isolation, identification, and antimicrobial properties of metabolites from endophytic fungi of D. crassirhizoma. Our findings may provide lead compounds for the development of new antibacterial agents.

Antimicrobial Acylphloroglucinol Meroterpenoids and Acylphloroglucinols from Dryopteris crassirhizoma.

Ten novel meroterpenoids, dryoptins/11″-epi-dryoptins A~E (1: ~10: ) with an unprecedented skeleton consisting of dimeric or trimeric acylphloroglucinols and dehydrotheonelline, two undescribed acylphloroglucinol-nerolidol meroterpenoids (11: ~12: ), and ten known acylphloroglucinol derivatives (13: ~22: ), were isolated from D. crassirhizoma. The novel structures including absolute configurations were established by comprehensive spectroscopic analyses and quantum chemical electronic circular dichroism (ECD) calculations. A biosynthetic pathway of 1: ~10: was assumed. The trimeric acylphloroglucinol meroterpenoids 7: /8: showed significant antifungal activity against standard Candida albicans with a MIC50 value of 1.61 µg/mL [fluconazole (FLC): 3.41 µg/mL], and when combined with FLC, the principal components 20: and 21: exhibited strong antifungal activities against FLC-resistant C. albicans with MIC50 values of 8.39 and 7.16 µg/mL (FLC: > 100 µg/mL), respectively. Moreover, compounds 2, 5: /6, 18, 19: , and 21: exhibited inhibitory effects against several pathogenic fungi and bacteria, with MIC50 values of 6.25 ~ 50 µg/mL.

E-Commerce Brand Ranking Algorithm Based on User Evaluation and Sentiment Analysis.

Objective: Consumers often need to compare the same type of products from different merchants to determine their purchasing needs. Fully mining the product information on the website and applying it to e-commerce websites or product introduction websites can not only allow consumers to buy products that are more in line with their wishes, but also help merchants understand user needs and the advantages of each product. How to quantify the emotional tendency of evaluation information and how to recommend satisfactory products to consumers is the research purpose of this paper. Method: According to the analysis of the research object, this paper uses the Python crawler library to efficiently crawl the data required for research. By writing a custom program for crawling, the resulting data is more in line with the actual situation. This paper uses the BeautifulSoup library in Python web crawler technology for data acquisition. Then, in order to ensure high-quality data sets, the acquired data needs to be cleaned and deduplicated. Finally, preprocessing such as sentence segmentation, word segmentation, and semantic analysis is performed on the cleaned data, and the data format required by the subsequent model is output. For weightless network, the concept of node similarity is proposed, which is used to measure the degree of mutual influence between nodes. Combined with the LeaderRank algorithm, and fully considering the differences between nodes in the interaction, the SRank algorithm is proposed. Different from the classical node importance ranking method, the SRank algorithm fully considers the local and global characteristics of nodes, which is more in line with the actual network. Results/Discussion: This paper calculates the sentiment polarity of users' comments, obtains the final user influence ranking, and identifies opinion leaders. The final ranking results were compared and analyzed with the traditional PageRank algorithm and SRank ranking algorithm, and it was found that the opinion leaders identified by the opinion leader identification model integrating user activity and comment sentiment were more reasonable and objective. The algorithm in this paper improves the efficiency of operation to a certain extent, and at the same time solves the problem that sentiment analysis cannot be effectively used in social network analysis, and increases the accuracy of e-commerce brand ranking.

Research on E-Commerce Database Marketing Based on Machine Learning Algorithm.

From simple commercial relations to complex online transactions at this stage, it not only highlights the progress of science and technology, but also indirectly explains the diversified evolution of marketing methods and means. In marketing, database marketing has been favored by more marketers with its low cost and high efficiency and has become the "rookie" in marketing in recent years. However, as a kind of prediction and ferry, database marketing tends to be applied after simple data analysis in unpredictable market and in practice. In contrast, database marketing combined with machine learning algorithms has always been a depression in the marketing field. Therefore, this paper takes e-commerce as the research object and carries out database marketing research based on machine learning algorithm from four stages: theoretical preparation, status analysis, model construction, and results application. Firstly, the connotation, advantages, and specific operation procedures of database marketing are discussed. At the same time, four excellent machine learning algorithms including logistic regression, random forest, support vector machine, and gradient boosted decision tree (GBDT) are selected to explain the basic principles and algorithm introduction, respectively, laying a theoretical foundation for the model training chapter. Secondly, it analyzes the current situation of e-commerce from the distribution of marketing objects, the proportion of marketing channels, and the composition of marketing methods and finds new marketing ideas based on the main problems existing at the present stage of database marketing using machine learning algorithm. Thirdly, on the premise of marketing ideas, data acquisition, data processing, and positive and negative sample setting. At the same time, four machine learning algorithms are used to combine features from the perspectives of consumers, stores, and the relationship between consumers and stores. Finally, by substituting the predicted sample into the model for testing, the crowd whose predicted score is between 80 and 99 is selected to be put into the market as the model predicted crowd, and it is proposed that e-commerce should mainly adopt the database marketing method of model prediction. On the one hand, machine learning algorithm can solve the problem of uneven distribution of marketing objects, and on the other hand, it can effectively prevent the loss of potential consumers. In addition, the application strategy of optimizing other database marketing methods and assisting model prediction to improve marketing effect is also put forward.

Cardio protective role of wogonin loaded nanoparticle against isoproterenol induced myocardial infarction by moderating oxidative stress and inflammation.

Wogonin, one of the main active ingredients of Scutellaria radix, is a kind of flavonoid compound. In the present study, we report that wogonin nanoparticles (Wog np) protect Isoproterenol (ISO) induced Myocardial Infarction (MI) rats. Nanoparticles of sizes less than 200 nm with spherical shape were prepared using Polylactic-co-glycolic acid (PLGA) and Polyvinyl alcohol (PVA) respectively as polymer and stabilizer. Male Wistar rats were divided into 4 groups. Group 1 as a control group administered with physiological saline solution with 0.5 % carboxymethylcellulose (1 mL/day). Group 2 served as toxic group; rats received physiological saline solution with 0.5 % carboxymethylcellulose (1 mL/day) orally for 21 days Groups 3 and 4 received Wog np (25 and 50 mg/kg/day) orally for 21 days and on the 20th and 21 st days group 2, 3, and 4 were administered with ISO (85 mg/kg) through s.c. route at 24 h interval. pre-treatment with Wog np (25 and 50 mg/kg) could significantly reduce the cardiac infarct size, serum cardiac markers, lipid peroxidation product (MDA) and inflammatory markers as well as markedly upregulated the protein expression of nuclear factor erythroid 2-related factor (Nrf2)and heme oxygenase-1 (HO-1) to confer its strong cardioprotective activity against ISO induced myocardial damage.

Circular RNA-100219 promotes breast cancer progression by binding to microRNA-485-3p.

PURPOSE: To investigate whether circ-100219 could promote the proliferation and migration of breast cancer cells by upregulating NTRK3 after binding to microRNA-485-3p, thus participating in the development of breast cancer. METHODS: Breast cancer cell lines MCF-7, MDA-MB-231, MDA-MB-549 and human mammary epithelial cells were cultured. The expression levels of circ-100219, microRNA-485-3p and NTRK3 in breast cancer and paracancer tissues were determined using real-time quantitative polymerase chain reaction (RT-qPCR). The regulatory effects of circ-100219, microRNA-485-3p and NTRK3 on the proliferative and migratory capacities of breast cancer cells were assessed using cell counting kit-8 (CCK-8) and Transwell assay, respectively. Dual-luciferase reporter gene assay was conducted to determine the binding condition among circ-100219, microRNA-485-3p and NTRK3. Rescue experiments were performed in co-transfected breast cancer cells. RESULTS: RT-qPCR data showed that circ-100219 and NTRK3 were highly expressed, whereas microRNA-485-3p was lowly expressed in breast cancer tissues than those of paracancer tissues. Knockdown of circ-100219 in MCF-7 and MDA-MB-231 cells inhibited their proliferative and migratory capacities. On the contrary, microRNA-485-3p knockdown improved the proliferative and migratory capacities. Dual-luciferase reporter gene assay revealed that circ-100219 could bind to microRNA-485-3p and NTRK3 was the target gene of microRNA-485-3p. Western blot results elucidated that circ-100219 stabilized NTRK3 expression, whereas microRNA-485-3p degraded NTRK3 expression. Rescue experiments demonstrated that overexpression of NTRK3 could partially reverse the inhibited proliferative and migratory capacities induced by circ-100219 knockdown in MCF-7 and MDA-MB-231 cells. CONCLUSIONS: Overexpression of circ-10021 promotes the proliferative and migratory capacities of breast cancer cells by sponging microRNA-485-3p to upregulate the NTRK3 expression.

Direct formation of InN-codoped p-ZnO/n-GaN heterojunction diode by solgel spin-coating scheme.

In this work p-ZnO/n-GaN heterojunction diodes were directly formed on the Si substrate by a combination of cost-effective solgel spin-coating and thermal annealing treatment. Spin-coated n-ZnO films on InN/GaN/Si wafers were converted to p-type polarity after thermal treatment of proper annealing durations. X-ray diffraction (XRD) analysis reveals that InN-codoped ZnO films have grown as the standard hexagonal wurtzite structure with a preferential orientation in the (002) direction. The intensity of the (002) peak decreases for a further extended annealing duration, indicating the greater incorporation of dopants, also confirmed by x-ray photoelectron spectroscopy and low-temperature photoluminescence. Hall and resistivity measurements validate that our p-type ZnO film has a high carrier concentration of 3.73×10¹7 cm⁻³, a high mobility of 210 cm²/Vs, and a low resistivity of 0.079 Ωcm. As a result, the proposed p-ZnO/n-GaN heterojunction diode displays a well-behaving current rectification of a typical p-n junction, and the measured current versus voltage (I-V) characteristic is hence well described by the modified Shockley equation. The research on the fabrication of p-ZnO/n-GaN heterojunctions shown here generates useful advances in the production of cost-effective ZnO-based optoelectronic devices.

The spiral ganglion degeneration and the expression of EFR3A in the cochlea of the deaf mice induced by co-administration of kanamycin and furosemide / 中华耳鼻咽喉头颈外科杂志

<p><b>OBJECTIVE</b>To investigate the spiral ganglion degeneration and the expression of EFR3A in the cochlea of the deaf mice induced by co-administration of kanamycin and furosemide.</p><p><b>METHODS</b>Eight weeks old C57BL/6J mice were administered with a single dose of kanamycin followed by furosemide, then fluorescent immunohistochemistry staining and transmission electron microscopy were applied to observe the SGNs' degeneration process and extent characteristics at 1, 5, 15, 30 and 60 days following treatment. We detected the expression of EFR3A during the degeneration of SGNs via fluorescent immunohistochemistry and western blotting.</p><p><b>RESULTS</b>Co-administration of kanamycin and furosemide quickly induced cochlear hair cell death in mice, and then caused progressive degeneration of SGNs. Our results showed that the abnormal morphology of SGNs occurredat day 5 following administration, and the number of SGNs began to decrease at day 15. Compared to the control group, it was found the remarkable increase of the EFR3A protein at the fifth day after co-administration, then decreased to the nearly normal at 15 days following treatment, and no further significant changes thereafter.</p><p><b>CONCLUSION</b>The changes of the EFR3A protein expression in the spiral ganglion of the cochlea in mice are coincidence with the time of the SGNs degeneration to happen, which imply that EFR3A may play an important role in the occurrence of the SGNs' degeneration in the cochlea in mice following hair cells loss.</p>

Analysis of the related risk factors of diabetic peripheral neuropathy / 中华实验和临床病毒学杂志

<p><b>OBJECTIVE</b>To explore the risk factors of diabetic peripheral neuropathy (DPN) and the relationship between DPN and diabetic retinopathy (DR).</p><p><b>METHODS</b>The data of the in-patients with type 2 diabetes mellitus (T2 DM) were retrospectively studied. A total of 200 T2 DM patients were divided into DPN group (n = 136) and non-DPN group (n = 64) according to peripheral neuropathy. The basic clinical data and the incidence rate of DR were compared between two groups. Logistic regression analysis was used to study the risk factors of DPN.</p><p><b>RESULTS</b>The course of disease, the level of BMI, glycosylated hemoglobin (HbA1c), 2 hour postprandial blood glucose (2 hPG), 2 hour glucose C peptide (2 hC-P) and the incidence rate of the DR were significantly different between two groups (P < 0.01). Logistic regression analysis showed that significant differences were observed in T2 DM complicated by DR (P = 0.023), the course of disease (P = 0.008), the level of HbA1c (P = 0.006), BMI (P = 0.000) and 2 hC-P (P = 0.065).</p><p><b>CONCLUSION</b>Diabetic retinopathy, the course of disease, the level of BMI,HbA1c and 2 hC-P are the risk factors for type 2 diabetic peripheral neuropathy. Diabetic peripheral neuropathy is positive correlated with diabetic retinopathy.</p>