Effect of Apple Polyphenols on the Antioxidant Activity and Structure of Three-Dimensional Printed Processed Cheese.

Additives can influence the processability and quality of three-dimensional (3D)-printed foods. Herein, the effects of apple polyphenols on the antioxidant activity and structure of 3D-printed processed cheese were investigated. The antioxidant activities of processed cheese samples with different contents of apple polyphenols (0%, 0.4%, 0.8%, 1.2%, or 1.6%) were evaluated using 2,2'-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) and 2,2-di(4-tert-octylphenyl)-1-picrylhydrazyl (DPPH) assays. In addition, the rheological properties and structural characteristics of the processed cheeses were investigated using rheometry, Fourier transform infrared spectroscopy, and fluorescence spectroscopy. Then, the final printed products were analyzed for comparative molding effects and dimensional characteristics. it was found that apple polyphenols can significantly improve the antioxidant activity of processed cheese. When the amount of apple polyphenols added was 0.8%, the 3D shaping effect was optimal with a porosity rate of 4.1%. Apple polyphenols can be used as a good antioxidant additive, and the moderate addition of apple polyphenols can effectively improve the antioxidant and structural stability of 3D-printed processed cheese.

Production and evaluation of enzyme-modified cheese adding protease or lipase to improve quality properties.

Enzyme-modified cheese (EMC) produced by enzyme hydrolysis is a natural, cost-effective, and flexible alternative to using natural cheese in industrial applications. The modification of cheese by enzymes can increase their benefits for consumer acceptance and health, and intensify the specific cheese flavor. We evaluated the properties of cheese with added protease (Ep) or lipase (El), including texture, sensory, organic acids, volatile compounds, and free amino acids. As results, the hardness and gumminess of the cheese reached their maximum values when the concentration of protease and lipase was 0.1% and 0.6%, respectively. Interestingly, the bitterness and astringency of the cheese was reduced. The highest scores for odor, taste, and overall acceptability were observed on 0.08% protease in Ep and 0.8% lipase in El. Compared with the anchor cheese, eight new compounds were produced after the addition of protease and nine new compounds were produced after the addition of lipase. Irrespective of the type of enzyme, the content of free amino acids decreased slightly with the increase in enzyme content. From the point of view of adding enzyme species, the free amino acids content of Ep was generally higher than that of El, and glutamic acid and proline contents were high. Acetic acid concentrations (aroma-active compounds) of enzyme-modified cheese using protease and lipase were 482-931 mg/100 g and 30-36 mg/100 g, respectively, which were significantly increased. According to the results obtained in this study, a cheese with higher sensorial and textural acceptability was obtained by adding the appropriate protease or lipase.

HMGA2 Synergizes with EZH2 to Mediate Epithelial Cell Inflammation and Apoptosis in Septic Lung Dysfunction.

OBJECTIVE: High mobility group AT-hook 2 (HMGA2) has been increasingly acknowledged to be significantly expressed in malignant tumors. However, it has been discovered to serve as a pro-inflammatory factor in several diseases. This study aimed to investigate the involvement of HMGA2 in septic lung injury. METHODS: Human pulmonary alveolar epithelial cells were subjected to lipopolysaccharide (LPS) to construct models. The effects of HMGA2 knockdown on cell viability, inflammation, and apoptosis were evaluated. Following the verification of the association between HMGA2 and Enhancer of Zeste homolog 2 (EZH2), the impacts of EZH2 on HMGA2 regulation were determined. RESULTS: The levels of HMGA2 in the LPS-treated cells were all significantly elevated. HMGA2 knockdown alleviated damage caused by LPS in cellular viability, and reduced inflammation and apoptosis. Whereas EZH2 overexpression reversed the impacts of HMGA2 knockdown on these aspects, indicating EZH2 participated in the regulation of HMGA2 on cells. CONCLUSION: HMGA2 could synergize with EZH2 to induce lung epithelial cell destruction in septic lung injury. Herein, targets for treatment have been investigated, which involves suppressing pro-inflammatory factors to reduce the body's inflammatory response.

lncRNA RPPH1 promotes non-small cell lung cancer progression through the miR-326/WNT2B axis.

Long non-coding RNAs (lncRNAs) serve important regulatory roles in human tumors. The aim of the present study was to examine the role of ribonuclease P RNA component H1 (RPPH1) in non-small cell lung cancer (NSCLC). RPPH1 expression was assessed in datasets from The Cancer Genome Atlas, as well as lung cancer cell lines and patients with NSCLC. RPPH1 was significantly upregulated in NSCLC cell lines, compared with a normal lung epithelial cell line. Moreover, high RPPH1 expression was associated with poor overall survival and disease progression. RPPH1 was knocked down in A549 and H1299 cells using short hairpin (sh) RNA constructs, and the expressions of target genes and proteins were determined by reverse transcription-quantitative PCR and western blotting. Cell invasion potential was also determined using Transwell Matrigel assays. Compared with the negative control, RPPH1 silencing significantly reduced the number of invading cells, increased E-cadherin expression and reduced vimentin protein expression. Cell resistance to cisplatin/cis-diamminedichloridoplatinum (CDDP) was also evaluated using Cell Counting Kit-8 and colony formation assays. RPPH1 overexpression increased the resistance of A549 and H1299 cells to CDDP. Moreover, the potential interactions between RPPH1, microRNA (miR)-326 and Wnt family member 2B (WNT2B) were investigated using luciferase reporter assays and co-transfection experiments. MiR-326 expression was directly inhibited by RPPH1. In A549 cells co-transfected with shRPPH1 and miR-326 inhibitor, the invading cell number significantly increased compared with cells transfected with shRPPH1 alone. In addition, E-cadherin expression levels were reduced, and vimentin was upregulated. MiR-326 overexpression partially reduced the resistance of A549 cells to CDDP induced by RPPH1 overexpression. WNT2B expression was directly suppressed using miR-326. A549 cells co-transfected with a miR-326 mimic and a WNT2B overexpression vector demonstrated increased invasion potential, reduced E-cadherin and increased vimentin protein expression levels, compared with cells transfected with the mimic alone. miR-326 overexpression reduced CDDP resistance in A549 cells. However, co-transfection with WNT2B partially enhanced CDDP resistance, compared with the mimic alone. In conclusion, RPPH1 promoted NSCLC progression and lung cancer cell resistance to CDDP through miR-326 and WNT2B.

Dynamin-related protein-1 promotes lung cancer A549 cells apoptosis through the F-actin/bax signaling pathway.

Dynamin-related protein-1 (Drp1) has been found to be associated with cell death. The role of Drp1 in A549 cells death has not been explored. In this study, adenovirus-mediated Drp1 overexpression was used to investigate the influence of Drp1 on A549 cell viability with a focus on F-actin and Bax. Cell viability, protein expression, oxygen consumption, energy metabolism, and growth rate were measured through ELISA, qPCR, western blots and pathway analysis. Our results indicated that Drp1 overexpression promoted A549 cell death through apoptosis. Mechanistically, cytoskeletal F-actin was impaired and Bax expression was elevated in response to Drp1 overexpression. Besides, energy metabolism was reduced and oxygen consumption was interrupted. Therefore, our results demonstrated that A549 cell viability, apoptosis and growth were regulated by the Drp1/F-actin/Bax signaling pathways. These data explain a new role played by Drp1 in regulating cell viability and also provide a potential target to affect the progression of lung cancer through induction of cell death.

MARCKSL1 promotes the proliferation, migration and invasion of lung adenocarcinoma cells.

Lung cancer is the most common cancer in males and females and ~40% of lung cancer cases are adenocarcinomas. Previous studies have demonstrated that myristoylated alanine rich protein kinase C substrate (MARCKS) is upregulated in several types of cancer and is associated with poor prognosis in patients with breast cancer. However, its expression level and role in lung adenocarcinoma remain unknown. Therefore, the aim of the present study was to investigate the expression level and biological functions of MARCKS like 1 (MARCKSL1), a member of the MARCKS family, in lung adenocarcinoma. The expression level of MARCKSL1 was examined in human lung adenocarcinoma tissues and cell lines. MARCKSL1-specific small interfering RNAs effectively suppressed its expression level and significantly inhibited the proliferation, migration and invasion of lung adenocarcinoma cells. Additionally, the role of MARCKSLI in the regulation of metastasis was examined. Silencing MARCKSL1 decreased the expression of the epithelial-mesenchymal transition (EMT)-associated proteins E-cadherin, N-cadherin, vimentin and snail family transcriptional repressor 2, and decreased the phosphorylation level of AKT. The results obtained in the current study suggested that MARCKSL1 promoted the progression of lung adenocarcinoma by regulating EMT. MARCKSLI may have prognostic value and serve as a novel therapeutic target in lung adenocarcinoma.

Exploring the potential relationship between indoor air quality and the concentration of airborne culturable fungi: a combined experimental and neural network modeling study.

Indoor airborne culturable fungi exposure has been closely linked to occupants' health. However, conventional measurement of indoor airborne fungal concentration is complicated and usually requires around one week for fungi incubation in laboratory. To provide an ultra-fast solution, here, for the first time, a knowledge-based machine learning model is developed with the inputs of indoor air quality data for estimating the concentration of indoor airborne culturable fungi. To construct a database for statistical analysis and model training, 249 data groups of air quality indicators (concentration of indoor airborne culturable fungi, indoor/outdoor PM2.5 and PM10 concentrations, indoor temperature, indoor relative humidity, and indoor CO2 concentration) were measured from 85 residential buildings of Baoding (China) during the period of 2016.11.15-2017.03.15. Our results show that artificial neural network (ANN) with one hidden layer has good prediction performances, compared to a support vector machine (SVM). With the tolerance of ± 30%, the prediction accuracy of the ANN model with ten hidden nodes can at highest reach 83.33% in the testing set. Most importantly, we here provide a quick method for estimating the concentration of indoor airborne fungi that can be applied to real-time evaluation.

Extreme learning machine: a new alternative for measuring heat collection rate and heat loss coefficient of water-in-glass evacuated tube solar water heaters.

BACKGROUND: Heat collection rate and heat loss coefficient are crucial indicators for the evaluation of in service water-in-glass evacuated tube solar water heaters. However, the direct determination requires complex detection devices and a series of standard experiments, wasting too much time and manpower. FINDINGS: To address this problem, we previously used artificial neural networks and support vector machine to develop precise knowledge-based models for predicting the heat collection rates and heat loss coefficients of water-in-glass evacuated tube solar water heaters, setting the properties measured by "portable test instruments" as the independent variables. A robust software for determination was also developed. However, in previous results, the prediction accuracy of heat loss coefficients can still be improved compared to those of heat collection rates. Also, in practical applications, even a small reduction in root mean square errors (RMSEs) can sometimes significantly improve the evaluation and business processes. CONCLUSIONS: As a further study, in this short report, we show that using a novel and fast machine learning algorithm-extreme learning machine can generate better predicted results for heat loss coefficient, which reduces the average RMSEs to 0.67 in testing.

Artificial Neural Networks-Based Software for Measuring Heat Collection Rate and Heat Loss Coefficient of Water-in-Glass Evacuated Tube Solar Water Heaters.

Measurements of heat collection rate and heat loss coefficient are crucial for the evaluation of in service water-in-glass evacuated tube solar water heaters. However, conventional measurement requires expensive detection devices and undergoes a series of complicated procedures. To simplify the measurement and reduce the cost, software based on artificial neural networks for measuring heat collection rate and heat loss coefficient of water-in-glass evacuated tube solar water heaters was developed. Using multilayer feed-forward neural networks with back-propagation algorithm, we developed and tested our program on the basis of 915 measured samples of water-in-glass evacuated tube solar water heaters. This artificial neural networks-based software program automatically obtained accurate heat collection rate and heat loss coefficient using simply "portable test instruments" acquired parameters, including tube length, number of tubes, tube center distance, heat water mass in tank, collector area, angle between tubes and ground and final temperature. Our results show that this software (on both personal computer and Android platforms) is efficient and convenient to predict the heat collection rate and heat loss coefficient due to it slow root mean square errors in prediction. The software now can be downloaded from http://t.cn/RLPKF08.