Evaluation of the Effects of Di-(2-ethylhexyl) phthalate (DEHP) on Caenorhabditis elegans Survival and Fertility.

Di-2-ethylhexyl (DEHP), which is widely used in industrial products, is produced annually in excess of 2 million tons worldwide. DEHP is an endocrine disruptor and one of the major environmental pollutant chemicals (EDCs) in nature. There is some information about the effects of these products, which provide great advantages in every respect, on human health and the environment. In this study, C. elegans organism was used to evaluate the health and environmental risks of DEHP. The survival and fertility effects of DEHP on the C. elegans organism were examined and the results were evaluated. In the study, it was determined that DEHP not only shortened the survival time of C. elegans but also caused a decrease in fertility. DEHP (0.625 mM and 10 mM) caused a 23.2-30.6% decrease in fertility. Additionally, the LC50 (50% lethal concentration) value of DEHP was found to be 321 µg/mL.

Antimicrobial, Antioxidant and Cytotoxic Effects of Essential Oil, Fatty Acids and Bioactive Compounds of Beta vulgaris var. crassa (Fodder Beet).

Beta vulgaris var. crassa is undoubtedly a very important plant that is not used enough in the world. In this study, it was aimed to determine the cytotoxic activities of the components (essential oils, fatty acids, total phenol and flavonoid) found in the leaf parts of Beta vulgaris var. crassa against PC-3, MCF-7 and HeLa cancer cell lines. In addition, the effectiveness of these ingredients against bacteria and fungi that can cause serious health problems in humans was tested. In experiments, three tumor cell lines were exposed to various plant extract concentrations (31.25, 62.5, 125, 250, 500 and 1000 µg/mL) for 72 h. It was found that plant extracts showed high (SI: 2.14 > 2) cytotoxicity to PC-3 cells, moderate (SI: 1.62 < 2) to HeLa cells, and low (SI: 0.93 < 2) cytotoxicity to MCF-7 cells. Also, different plant extract concentrations were found to cause an inhibition rate of 16.3-22.3% in Staphylococcus aureus, 16.8-23.5% in Streptococcus pyogenes and 12-16.2% in Cutibacterium acnes. Similarly, inhibition rates were determined between 9.5-20.7% for Candida albicans, 3.5-7.7% for Candida auris, and 5.5-15.1% for Candida glabrata. The results showed that the plant extract exhibited a concentration-dependent cytotoxic and antimicrobial effect against both cancer cell lines and microbial pathogens. Supplementary Information: The online version contains supplementary material available at 10.1007/s12088-024-01269-8.

Evaluation of the effects of zinc oxide (ZnO NPs) nanoparticles synthesized by green synthesis on Caenorhabditis elegans.

In recent years, the rapid development of nanotechnology has caused the products obtained with this technology to be used more daily. Information on the effects of these products, which provide great advantages in every respect, on human health and the environment is insufficient. It has been suggested that these nanoparticles may have toxic effects on living things, mostly in animal experiments and cell cultures. In this paper, the organism Caenorhabditis elegans (C. elegans), which contains a genome and biochemical ways highly similar to humans, is used to understand and reveal the metabolism of Zinc oxide nanoparticles (ZnO NPs) toxicological effects. The toxicological effects of ZnO NPs on C. elegans organisms were investigated and the results were evaluated in terms of environment and human health. C. elegans was exposed to commercial ZnO NPs and green synthesized ZnO NPs from Olea europaea (olive tree, OLE). LC50 values were determined by probit analysis (green synthesized ZnO NP LC5024h = 84.97 mg/L, LC5072h = 33.27 mg/L, commercial ZnO NPs LC5024h = 5.75 mg/L, LC5072h = 1.91 mg/L). When the survival times of C. elegans were evaluated by the Kaplan-Meier method, it was seen that commercial ZnO NPs were more toxic than green synthesized ZnO NPs. In MTT tests, it was clearly seen that commercial ZnO NPs and green synthesized ZnO NPs entered the cell and caused different cytotoxicity. While there was a difference between control and 0.5, 2.5, 5, 10, 25, and 50 mg/L doses in commercial ZnO NP applications, there were significant differences between control and 25, 50 mg/L concentrations in green synthesized ZnO NP applications.

Herbicides widely used in the world: an investigation of toxic effects on Caenorhabditis elegans.

Dicamba, paraquat, picloram, clopyralid and linuron are herbicides widely used in agriculture. The aim of the present study is to evaluate the toxicity effects of the herbicides used on survival, fertility and length of Caenorhabditis elegans. Kaplan-Meier Survival Analysis method was used to identify the toxicity effect of herbicides on survival, and ANOVA and Post Hoc tests were used to determine the toxicity effects on fertility and length. In the study, C. elegans was exposed to 5 different concentrations (62.5, 125, 250, 500, 1000 µM) of each herbicide. When the results were evaluated, it was observed that survival (life span) and length (physical growth) were more affected, respectively, by paraquat, dicamba, linuron, picloram and clopyralid herbicides, fertility (egg productivity) were more affected, respectively, by paraquat, linuron, dicamba, picloram and clopyralid herbicides. As a result, it was determined that increasing the dose amounts of herbicides caused many toxic reactions on C. elegans, affecting survival, egg productivity and length.

Machine learning approach for predicting the antifungal effect of gilaburu (Viburnum opulus) fruit extracts on Fusarium spp. isolated from diseased potato tubers.

This work addresses the mathematical model building to detect the diameter of the inhibition zone of gilaburu (Viburnum opulus L.) extract against eight different Fusarium strains isolated from diseased potato tubers. Gilaburu extracts were obtained with acetone, ethanol or methanol. The isolated Fusarium strains were: F. solani, F. oxysporum, F. sambucinum, F. graminearum, F. coeruleum, F. sulphureum, F. auneaceum and F. culmorum. In general, it was observed that ethanolic extracts showed highest antifungal activity. The antifungal activity of extracts was evaluated with machine learning (ML) methods. Several ML methods (classification and regression trees (CART), support vector machines (SVM), k-Nearest Neighbors (k-NN), artificial neural network (ANN), ensemble algorithms (EA), AdaBoost (AB) algorithm, gradient boosting (GBM) algorithm, random forests (RF) bagging algorithm and extra trees (ET)) were applied and compared for modeling fungal growth. From this research, it is clear that ML methods have the lowest error level. As a result, ML methods are reliable, fast, and cheap tools for predicting the antifungal activity of gilaburu extracts. These encouraging results will attract more research efforts to implement ML into the field of food microbiology instead of traditional methods.