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5 result(s) for "Keyvan, Erhan"
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Ethanolic extract of Turkish bee pollen and propolis: phenolic composition, antiradical, antiproliferative and antibacterial activities
Bee pollen and propolis are considered as health-promoting foods with many therapeutic (antibacterial, antifungal and antioxidant) activities. This study analyzed the phenolic profile and the antioxidant properties of Turkish bee pollen and propolis ethanolic extracts and assayed their antiproliferative effect on myeloma cells and in vitro antibacterial activity against Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa. The antibacterial activity assays included agar well diffusion and microdilution methods. The phenolic profile and several aromatic compounds of the extracts were determined by high-performance liquid chromatography with diode-array detection (HPLC-DAD). The antiproliferative activity on myeloma cells was determined by MTT test. The propolis extract had higher total phenolic content (TPC), free-radical scavenging activity (DPPH) and half-maximal inhibitory concentration (IC 50 ) than the pollen ethanolic extract. Benzoic and cinnamic acid were the most abundant aromatic substances in the pollen and propolis extracts, respectively. The IC 50 values of pollen and propolis extracts on myeloma cells were 1.49% and 2.88%, respectively. The propolis extract was active against S. aureus and E. coli, but not P. aeruginosa. The pollen extract presented no detectable inhibition zone against the three bacterial strains. The minimum inhibitory concentration (MIC) of both extracts for S. aureus and E. coli was 0.63% (w/v). The minimum bactericidal concentration (MBC) of the propolis extract was 1.25% for S. aureus and E. coli. MIC could not be determined for the pollen extract in the tested bacteria. The pollen and propolis extracts did not exert antimicrobial activity against P. aeruginosa up to 2.5% concentration.
Novel Photodynamic Inactivation Strategy for Salmonella Enteritidis PT4 on Eggshells: Exploiting the Antimicrobial Potential of Curcumin and Carvacrol
Photodynamic inactivation (PDI) is a new and promising strategy for eliminating foodborne pathogenic bacteria in food preservation, reducing associated health risks for consumers. This study aimed to develop an innovative PDI‐based system to inactivate Salmonella Enteritidis PT4 on eggshells. The system includes 405 nm light‐emitting diodes (LEDs) and the application of curcumin or carvacrol as photosensitizers. The antibacterial activity of the system was investigated in eggshells inoculated with S. Enteritidis PT4 at different temperatures (4, 25, and 37°C) and exposure times (15, 30, and 45 min). Carvacrol + LEDs application was completely inhibited S. Enteritdis PT4 at 4 (after 30 min), 25, and 37°C at the 45th min. Curcumin + LED completely inhibited bacterial growth after 45 min at 4 and 25°C. The results showed that simultaneous use of carvacrol or curcumin with LEDs at various temperatures exhibited significant antibacterial activity against the bacteria depending on the exposure time. The application of curcumin or carvacrol sourced via PDI in the originally developed system resulted in any significant changes in egg quality parameters and sensory properties. This study demonstrated that PDI‐based system using curcumin or carvacrol as photosensitizers could be a potential tool for decontamination of eggs contaminated with S. Enteritidis PT4. Photodynamic inactivation (PDI) is an innovative approach to control foodborne pathogens. This study focuses on utilizing PDI to eliminate Salmonella Enteritidis PT4 on eggshells using 405 nm LEDs paired with curcumin or carvacrol as photosensitizers. At 4, 25, and 37°C, significant antibacterial effects were achieved within 45 min.
Inactivation of Listeria monocytogenes in ready-to-consume liquid infant milk treated with Ohmic Heating
Ohmic heating is a promising alternative method to conventional heating for microbial inactivation. This study aimed to inactivate Listeria monocytogenes and assess some quality parameters in ready-to-consume liquid infant milk treated with different voltage gradients of ohmic heating. Different ohmic heating voltage gradients (5, 10, and 20V cm-1) were applied to the samples inoculated with Listeria monocytogenes (ATCC 13932) for 5 minutes. The application of 20 V cm-1 ohmic heating induced inactivation of Listeria monocytogenes at 4 minutes and resulted in approximately 5.34 log reduction; however, there was no significant reduction for the 5 and 10V cm-1 groups. Moreover, 20V cm-1 ohmic heating application did not cause any changes in pH, L*, and b* values. A significant decrease in a* value and an increase in hydroxymethylfurfural value was noted in this group.  In conclusion, the effectiveness of ohmic heating in pathogen inactivation depends on the applied electric field intensity and the application time. As a result, the ohmic heating conditions must be carefully determined for the infant milk to inactivate pathogens and ensure public health protection. The results of this study contain significant and beneficial data that can be disposed of the listeriosis risk associated with the consumption of infant milk in infants.
Optimization of Phenolic and Flavonoid Extraction From Bee Bread Using Response Surface Methodology and Central Composite Design, and Evaluation of Antimicrobial Activity
Bee bread is a remarkable apicultural product recognized for its abundant proteins, minerals, vitamins, and phenolic compounds, which enhance its notable biological activity. This study aimed to optimize the extraction conditions to maximize the total phenolic content (TPC), total flavonoid content (TFC), and antioxidant capacity (DPPH) with conventional extraction of bee bread using response surface methodology (RSM) with Central Composite Design (CCD). The phenolic profile of the optimal extract was evaluated by high‐performance liquid chromatography (HPLC). Antibacterial activity of the optimal extract was evaluated against Staphylococcus aureus, Escherichia coli, and Salmonella Enteritidis by using the microdilution method. The optimal conditions were determined to be 30°C temperature, 40 mL/g solvent–solid ratio, 66.729% solvent concentration, and 19.996 h time. The TPC, TFC, and DPPH results of the optimal extract were found to be 26.860 ± 1.08 mg GAE/g, 2.300 ± 0.46 mg QE/g, and 3.043 ± 0.26 mg AAE/g, respectively. HPLC analysis showed that quercetin, kaempferol, and hesperidin are the main phenolic compounds of the optimal extract. The optimal extract had minimum inhibition concentration (MIC) values of 12.5 mg/mL against S. Enteritidis, 25 mg/mL against E. coli, and > 25 mg/mL against S. aureus. In conclusion, this study demonstrated that the recovery of antioxidant and phenolic compounds from bee bread can be significantly enhanced by RSM. This study successfully optimized the extraction parameters for Turkish bee bread using Response Surface Methodology (RSM) with a Central Composite Design (CCD). Under optimized conditions (30°C, 40 mL/g ratio, 66.7% ethanol, 20 h), the recovery of total phenolics (26.86 mg GAE/g) and flavonoids was maximized. HPLC‐DAD characterization identified Quercetin, Kaempferol, and Hesperidin as the primary bioactive markers. The resulting optimal extract demonstrated potent antibacterial efficacy, particularly against Salmonella Enteritidis with a Minimum Inhibitory Concentration (MIC) of 12.5 mg/mL, validating the effectiveness of the multivariate optimization approach for functional food development.
GPL-SLAM: A Laser SLAM Framework with Gaussian Process Based Extended Landmarks
We present a novel Simultaneous Localization and Mapping (SLAM) method that employs Gaussian Process (GP) based landmark (object) representations. Instead of conventional grid maps or point cloud registration, we model the environment on a per object basis using GP based contour representations. These contours are updated online through a recursive scheme, enabling efficient memory usage. The SLAM problem is formulated within a fully Bayesian framework, allowing joint inference over the robot pose and object based map. This representation provides semantic information such as the number of objects and their areas, while also supporting probabilistic measurement to object associations. Furthermore, the GP based contours yield confidence bounds on object shapes, offering valuable information for downstream tasks like safe navigation and exploration. We validate our method on synthetic and real world experiments, and show that it delivers accurate localization and mapping performance across diverse structured environments.