Probiotic properties of ice creams produced with dietary fibres from by‐products of the food industry

The objective of this study was to investigate the effects of adding dietary fibre‐rich by‐products to probiotic ice creams. For this purpose, fruit (grape, apricot, apple)‐ and grain (rice, corn, sunflower, barley)‐based by‐products were added to ice cream. The viability of Lactobacillus acidophilus (ATCC 4357D‐5) and Bifidobacterium animalis subsp. lactis (ATCC 27536) was determined with microbial analyses at 1, 15, 30 and 60 days of storage. In conclusion, it was shown that dietary fibre‐rich by‐products could be used in ice cream with improved survival of the probiotic strains without any adverse effects on the physicochemical, microbiological and sensory properties of the ice cream.     

Determination of the quality and purity characteristics of olive oils obtained from different regions of Turkey,depending on climatic changes

Virgin olive oils (VOOs) obtained from olives grown in different regions of Turkey under changing climatic conditions sometimes show different sensory and chemical properties. This study was planned to determine whether these deviations are due to climatic changes or not. For this purpose, five different olive varieties (Ayvalık, Memecik, Gemlik, Nizip Yağlık, Kilis Yağlık) of commercial importance were harvested from the provinces/districts (four different region) where cultivation is intense during the 2017/2018–2020/2021 harvest years. Every year, olive samples were collected from 3 orchards from 13 provinces/districts. One hundred and fifty-six samples were subjected to the purity, quality and sensory analysis. Basic climatic values (average, minimum and maximum temperature, humidity and precipitation) were examined for four consecutive years. All of the examined olive oil samples were determined within the legal limits in terms of fatty acid composition and fatty acid ethyl ester values. However, delta-7-stigmastenol value from the sterol composition was found to be above 0.5% in some samples in all the years studied (total 21 samples). Delta-7-stigmastenol values of olive oil samples varied between 0.16% and 1.14%. Multiple linear regression analysis was applied using a genetic algorithm-based inverse least squares method to determine whether there is a relationship between climate data and delta-7-stigmastenol values. According to this result, it has been determined that the delta-7-stigmastenol value is high when the annual average relative humidity is low and the annual average temperature is high. There is an urgent need to make forward-looking plans due to climate change.     

Shear amplification of orientation in Nylon 11/clay nanocomposites during melt casting and resulting electrical properties

In this study, the effect of organically modified clay on the orientation enhancement in Nylon 11 in melt casting was investigated. Nylon 11 was mixed with 1 and 3 wt% Cloisite 20A using twin screw extrusion and they were cast into films with varying take-up speeds. The addition of clay in Nylon 11 helped increase orientation levels substantially in melt cast films, both as a function of clay concentration as well as take-up speeds. This was primarily due to shear amplification effect caused by the movement of adjacent clay nanoparticles due to the shear flow gradient within the die. At low clay concentrations, the sub-T_m stretchability, and electrical breakdown strength improve as the presence of clay reduces inter/intrachain hydrogen bonding. At higher clay concentrations, both orientation and electrical breakdown levels decrease. The latter is primarily caused by increased percolation path of charge carriers. Nevertheless, clay nanoplatelets were very effective in their role as melt processing aids, as they enhance orientation levels of Nylon 11 thin films by shear amplification effect where they increase local chain orientation of chains trapped between clay platelets while their orientation relaxation is suppressed.     

Process improvement and efficiency analysis using the Single-Minute Exchange of Dies method applied to the set-up and operation of screen-printing machines

Lean manufacturing methods are concerned with simplifying the production process and thus maximising efficiency and minimising wastage. All production processes contain several steps, which include sub-steps such as cleaning and changing devices and preparing the production areas for later steps. Most of these sub-steps require that machines are stopped and therefore they must be performed as quickly as possible. This downtime causes a decrease in efficiency, while increasing the costs and production time. Single-Minute Exchange of Dies (SMED) is a lean manufacturing strategy that has been applied successfully in many sectors to minimise excessive downtime. In this study, the SMED technique is applied in a textile screen-printing company for the case of changing the screens between each design. The steps are evaluated and designated as either external steps, which are performed without downtime, or internal steps, which take place during downtime. The number of external steps is increased while being decreased for internal steps. Also, the production time decreased by 54% and a 32% increase in efficiency was achieved during the screen-printing production of a sample t-shirt.     

Erlotinib-Modified BODIPY Photosensitizers for Targeted Photodynamic Therapy

Photodynamic therapy (PDT) is an innovative, non-invasive and highly selective therapeutic modality for tumours and non-malignant diseases. BODIPY based molecules can function as new generation photosensitizers (PSs) in various PDT applications. Despite numerous conjugated PS systems are available, BODIPYs containing erlotinib lagged behind other photosensitizer units. In this study, smart photosensitizers containing BODIPY, erlotinib and hydrophilic units were prepared for the first time, their physicochemical properties and PDT effects were investigated. Compared with non-halogenated compound, halogenated derivatives possessed much lower fluorescence profile as well as the good ROS generation ability under red light. In vitro PDT studies were performed on both healthy (PNT1a) and prostate cancerous cells (PC3) to determine the selectivity of the compounds on cancerous cells and their effects under light. The halogenated conjugates, exposed to low dose of light illumination exhibited potent activity on cancer cell viability and the calculated IC₅₀ values proved the high phototoxicity of the photosensitizers. It was also determined that the PSs have very low dark toxicity and that the light illumination and ROS formation are required for the initiation of the cell death mechanism. As a result, erlotinib modified BODIPYs could serve as promising agents in anticancer photodynamic therapy.     

Improving Brain Tumor Classification with Deep Learning UsingSyntheticData

Deep learning (DL) techniques, which do not need complex pre-processing and feature analysis, are used in many areas of medicine and achieve promising results. On the other hand, in medical studies, a limited dataset decreases the abstraction ability of the DL model. In this context, we aimed to produce synthetic brain images including three tumor types (glioma, meningioma, and pituitary), unlike traditional data augmentation methods, and classify them with DL. This study proposes a tumor classification model consisting of a Dense Convolutional Network (DenseNet121)-based DL model to prevent forgetting problems in deep networks and delay information flow between layers. By comparing models trained on two different datasets, we demonstrated the effect of synthetic images generated by Cycle Generative Adversarial Network (CycleGAN) on the generalization of DL. One model is trained only on the original dataset, while the other is trained on the combined dataset of synthetic and original images. Synthetic data generated by CycleGAN improved the best accuracy values for glioma, meningioma, and pituitary tumor classes from 0.9633, 0.9569, and 0.9904 to 0.9968, 0.9920, and 0.9952, respectively. The developed model using synthetic data obtained a higher accuracy value than the related studies in the literature. Additionally, except for pixel-level and affine transform data augmentation, synthetic data has been generated in the figshare brain dataset for the first time.