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This study aimed to evaluate the compositional changes and bioaccessibility of phenolics and antioxidants in propolis during in vitro digestion as well as the cytotoxic effects of digested propolis on various cancer cell lines.

Six propolis samples were obtained and subjected to in vitro oral, gastric and intestinal digestion. Both digested and undigested samples were analyzed for their total phenolic, flavonoid and antioxidant activities. Additionally, changes in phenolic composition in the in vitro digestion system were revealed by the HPLC-DAD system. The cytotoxic effects of the digested samples were assessed on lung (A549, H1299), skin (A431), liver (Hep-G2) and colon (Caco-2) cancer cells as well as on fibroblast (Bj) cells.

The mean bioaccessibility values of phenolic and flavonoid compounds were found to be less than 35 and 24%, respectively, while the TEAC and CUPRAC antioxidant results ranged between 225.08–649.04 and 398.68–1552.28 µmol TE/g, respectively. The release of p-coumaric, ferulic, 3,4-dimethoxycinnamic acids, naringenin, pinocembrin and chrysin increased progressively from the oral to the intestinal stage. The cytotoxic effects of samples on cell lines were ranked, based on IC50 results, as A431 > Hep-G2 > Caco-2 > A549 > H1299 > Bj.

Propolis has been recognized for centuries as a natural remedy, and numerous studies have explored its bioactive components. However, no studies have previously examined the changes in the phenolic compositions of propolis samples during digestion or their cytotoxic effects on cancer cells. Therefore, this study provides novel insights and an approach to the existing literature on this topic.

This study aims to examine the relationship between the chemical composition of juices obtained from fruits of autochthonous wild pomegranate (Punica granatum L.) grown in Montenegro and their cytotoxic effects on cancer cells.

To explore the potential value of wild pomegranate fruits, in vitro biological assays were carried out with juices whose composition was analyzed in detail for sugars, organic acids, vitamin C and phenolic compounds. The effect of juices on survival was determined in human lung A549, cervical HeLa and breast MCF-7 carcinoma cells by MTT assay. As a control, the cytotoxicity against normal fetal lung fibroblasts (MRC-5) was monitored.

Among cancer cell lines, considering the IC50 related to total phenolics, the lowest value – 13 µg/mL was found for the A549. The strongest effect on lung cells was assumed due to the favorable contribution of ellagitannins to total phenolics in juice as well as the given combination of anthocyanins and their synergistic action. For HeLa cells, the lowest IC50 value was obtained at 88 µg/mL, and the cytotoxicity could be matched with the effects of anthocyanins and catechin. For MCF-7 cells, the lowest IC50 was 504 µg/mL, and the elevated levels of vitamin C and ellagic acid derivatives should have a noticeable effect on these cells.

This study provides an important contribution to the knowledge on the effect of phytochemicals from wild pomegranate juice on lung, cervical and breast cancer cells, in vitro. The present observations suggest that the juice of wild pomegranate has the potential in the fight against cancer.

This paper aims to deal with intra and inter-cell layout problems in cellular manufacturing systems. The model is organized to minimize the total handling cost, i.e. intra and inter-cell handling costs in a continuous environment.

The research was conducted by developing a mixed integer mathematical model. Due to the complexity and NP-hard nature of the cellular manufacturing layout problem, which mostly originated from binary variables, a “graph-pair” representation is used for every machine set and cells each of which manipulates the relative locations of the machines and cells both in left-right and below-up direction. This approach results in a linear model as the binary variables are eliminated and the relative locations of the machines and cells are determined. Moreover, a genetic algorithm as an efficient meta-heuristic algorithm is embedded in the resulting linear programming model after graph-pair construction.

Various numerical examples in both small and large sizes are implemented to verify the efficiency of the linear programming embedded genetic algorithm.

Considering the machine and cell layout problem simultaneously within the shop floor under a static environment enabled managers to use this concept to develop the models with high efficiency.

Monocytes are a leukocytes’ subset that plays an important role in immunity. Protein kinase B (AKT) is involved in monocytes' survival, proliferation and differentiation. Using phorbol 12-myristate 13-acetate (PMA) as an inducer for cell line U937 differentiation into macrophage-like cells may be used as a model for cancer cell therapy or other biomedical research studies. The authors investigated the Akt1 signaling pathway's involvement with PMA as a differentiating agent and survival in the U937 cell line.

PMA was utilized to stimulate the differentiation of the U937 cell line into macrophage-like cells at a concentration of 10 nM. Akt1-phosphorylated Serine 473, Bad-phosphorylated Serine 136 and Caspase9-phosphorylated Serine 196 were tested by flow cytometry for the involvement of the Akt1 signaling pathway during differentiation in addition to the expression of CD14, CD206 and CD83. DNA cell cycle variation analysis was done using PI staining and cell viability and apoptosis detection using Annexin V and PI flow cytometry.

There was a decrease in phosphorylated Akt1 and Bad activation and an increase in Caspase9 activation, with an increase in surface markers CD14, CD206 and CD83 acquired by PMA-differentiated cells. DNA cell cycle analysis revealed cell accumulation in the G2/M phase and fewer cells in the S phase of PMA-induced U937. Apoptosis induction for Ly294002 or Wortmannin-inhibited cells and part of PMA-induced cells were detected.

These results may be used to create a model for biomedical research studies and advance the understanding of the mechanism involving differentiation of the U937 cell line.

The heterogeneous character of Industry 4.0 opens opportunities for studies to understand the difficulties and challenges found in the transformation process of manufacturers. This article aims to present a critical analysis of the modernization process of an Industry 3.0 automated cell into a fully autonomous cell of Industry 4.0. The objective is to elucidate the difficulties found in this transition process and the possible ways to overcome the challenges, focusing on the management perspective.

For this, the needed steps for the technology transition were defined and the main I4.0 enabling technologies were applied, such as the application of machine learning algorithms to control quality parameters in milling.

The main challenges found were related to the obsolescence of the equipment present in the cell, challenges in data integration and communication protocols, in addition to the training of people who work actively in the project team. The difficulties faced were discussed based on similar studies in the literature and possible solutions for each challenge.

This understanding of possible barriers in the modernization process, and the step-by-step defined for this transition, can be important references for professionals working in manufacturing industries and researchers who aim to deepen their studies in this important and disruptive stage of world industrialization.

Acrylamide (AA) is predominantly used as a synthetic substance within various industries. However, AA is also recognized as a carcinogen. Zinc oxide nanoparticles (ZnO-NPs) are becoming increasingly attractive as medical agents. However, to the knowledge, the effects of ZnO-NPs on preventing cytotoxicity with AA have not been reported. Therefore, this study aims to determine the protective effects of ZnO-NPs against the cytotoxicity caused by AA.

MTT assay was used to determine the cytotoxicity. Reactive oxygen species (ROS) formation, carbonyl protein, malondialdehyde (MDA) and glutathione (GSH) were measured and analyzed statistically.

The findings observed that the presence of 200 µM AA led to a substantial reduction in cell viability (p < 0.001). However, ZnO-NPs restored cell viability at 50 and 100 µM concentrations (p = 0.0121 and p = 0.0011, respectively). The levels of ROS were significantly reduced (p = 0.001 and p = < 0.001) to 518 ± 47.57 and 364 ± 47.79, respectively, compared to the AA group. The levels of GSH were significantly increased (p = 0.004 and p = 0.002) to 16.9 ± 1.3 and 17.6 ± 0.5, respectively, compared to the AA group. The levels of MDA were significantly decreased (p = 0.005, p < 0.001 and p < 0.001) when compared to the AA group, as were the levels of carbonyl protein (p = 0.009 and p < 0.002) in comparison to the AA group.

In summary, the outcomes of this research indicate that ZnO-NPs played a role in inhibiting AA-induced oxidative stress and cytotoxicity.

Estimation of solar cell parameters, mathematical modeling and the actual performance analysis of photovoltaic (PV) cells at various ecological conditions are very important in the design and analysis of maximum power point trackers and power converters. This study aims to propose the analysis and modeling of a simplified three-diode model based on the manufacturer’s performance data.

A novel technique is presented to evaluate the PV cell constraints and simplify the existing equation using analytical and iterative methods. To examine the current equation, this study focuses on three crucial operational points: open circuit, short circuit and maximum operating points. The number of parameters needed to estimate these built-in models is decreased from nine to five by an effective iteration method, considerably reducing computational requirements.

The proposed model, in contrast to the previous complex nine-parameter three-diode model, simplifies the modeling and analysis process by requiring only five parameters. To ensure the reliability and accuracy of this proposed model, its results were carefully compared with datasheet values under standard test conditions (STC). This model was implemented using MATLAB/Simulink and validated using a polycrystalline solar cell under STC conditions.

The proposed three-diode model clearly outperforms the earlier existing two-diode model in terms of accuracy and performance, especially in lower irradiance settings, according to the results and comparison analysis.

This study aims to design and implement a multimaterial system for printing multifunctional specimens suitable for various sectors, with a particular focus on biomedical applications such as addressing mandibular bone loss.

To enhance both the mechanical and biological properties of scaffolds, an automatic multimaterial setup using vat photopolymerization was developed. This setup features a linear system with two resin vats and one ultrasonic cleaning tank, facilitating the integration of diverse materials and structures to optimize scaffold composition. Such versatility allows for the simultaneous achievement of various characteristics in scaffold design.

The printed multimaterial scaffolds, featuring 20 Wt.% hydroxylapatite (HA) on the interior and poly-L-lactic acid (PLLA) with 1 Wt.% graphene oxide (GO) on the exterior, exhibited favorable mechanical and biological properties at the optimum postcuring and heat-treatment time. Using an edited triply periodic minimal surface (TPMS) lattice structure further enhanced these properties. Various multimaterial specimens were successfully printed and evaluated, showcasing the capability of the setup to ensure functionality, cleanliness and adequate interface bonding. Additionally, a novel Gyroid TPMS scaffold with a nominal porosity of 50% was developed and experimentally validated.

This study demonstrates the successful fabrication of multimaterial components with minimal contaminations and suitable mechanical and biological properties. By combining PLLA-HA and PLLA-GO, this innovative technique holds significant promise for enhancing the effectiveness of regenerative procedures, particularly in the realm of dentistry.

This paper presents a Monotonic Unbounded Schemes Transformer (MUST) approach to bound/monotonize (remove undershoots and overshoots) unbounded spatial differencing schemes automatically, and naturally. Automatically means the approach (1) captures the critical cell Peclet number when an unbounded scheme starts to produce physically unrealistic solution automatically, and (2) removes the undershoots and overshoots as part of the formulation without requiring human interventions. Naturally implies, all the terms in the discretization equation of the unbounded spatial differencing scheme are retained.

The authors do not formulate new higher-order scheme. MUST transforms an unbounded higher-order scheme into a bounded higher-order scheme.

The solutions obtained with MUST are identical to those without MUST when the cell Peclet number is smaller than the critical cell Peclet number. For cell Peclet numbers larger than the critical cell Peclet numbers, MUST sets the nodal values to the limiter value which can be derived for the problem at-hand. The authors propose a way to derive the limiter value. The authors tested MUST on the central differencing scheme, the second-order upwind differencing scheme and the QUICK differencing scheme. In all cases tested, MUST is able to (1) capture the critical cell Peclet numbers; the exact locations when overshoots and undershoots occur, and (2) limit the nodal value to the value of the limiter values. These are achieved by retaining all the discretization terms of the respective differencing schemes naturally and accomplished automatically as part of the discretization process. The authors demonstrated MUST using one-dimensional problems. Results for a two-dimensional convection–diffusion problem are shown in Appendix to show generality of MUST.

The authors present an original approach to convert any unbounded scheme to bounded scheme while retaining all the terms in the original discretization equation.

This paper aims to construct positivity-preserving finite volume schemes for the three-dimensional convection–diffusion equation that are applicable to arbitrary polyhedral grids.

The cell vertices are used to define the auxiliary unknowns, and the primary unknowns are defined at cell centers. The diffusion flux is discretized by the classical nonlinear two-point flux approximation. To ensure the fully discrete scheme has positivity-preserving property, an improved discretization method for the convection flux was presented. Besides, a new positivity-preserving vertex interpolation method is derived from the linear reconstruction in the discretization of convection flux. Moreover, the Picard iteration method may have slow convergence in solving the nonlinear system. Thus, the Anderson acceleration of Picard iteration method is used to solve the nonlinear system. A condition number monitor of matrix is employed in the Anderson acceleration method to achieve better robustness.

The new scheme is applicable to arbitrary polyhedral grids and has a second-order accuracy. The results of numerical experiments also confirm the positivity-preserving of the discretization scheme.

1. This article presents a new positivity-preserving finite volume scheme for the 3D convection–diffusion equation. 2. The new discretization scheme of convection flux is constructed. 3. A new second-order interpolation algorithm is given to eliminate the auxiliary unknowns in flux expressions. 4. An improved Anderson acceleration method is applied to accelerate the convergence of Picard iterations. 5. This scheme can solve the convection–diffusion equation on the distorted meshes with second-order accuracy.