Definition, detection, and tracking of nanowaste in foods: Challenges and perspectives.

Commercial applications of nanotechnology in the food industry are rapidly increasing. Accordingly, there is a simultaneous increase in the amount and diversity of nanowaste, which arise as byproducts in the production, use, disposal, or recycling processes of nanomaterials utilized in the food industry. The potential risks of this nanowaste to human health and the environment are alarming. It is of crucial significance to establish analytical methods and monitoring systems for nanowaste to ensure food safety. This review provides comprehensive information on nanowaste in foods as well as comparative material on existing and new analytical methods for the detection of nanowaste. The article is specifically focused on nanowaste in food systems. Moreover, the current techniques, challenges as well as potential use of new and progressive methods are underlined, further highlighting advances in technology, collaborative efforts, as well as future perspectives for effective nanowaste detection and tracking. Such detection and tracking of nanowaste are required in order to effectively manage this type ofwasted in foods. Although there are devices that utilize spectroscopy, spectrometry, microscopy/imaging, chromatography, separation/fractionation, light scattering, diffraction, optical, adsorption, diffusion, and centrifugation methods for this purpose, there are challenges to be overcome in relation to nanowaste as well as food matrix and method characteristics. New technologies such as radio-frequency identification, Internet of things, blockchain, data analytics, and machine learning are promising. However, the cooperation of international organizations, food sector, research, and political organizations is needed for effectively managing nanowaste. Future research efforts should be focused on addressing knowledge gaps and potential strategies for optimizing nanowaste detection and tracking processes.

Machine Learning Analysis of the Impact of Silver Nitrate and Silver Nanoparticles on Wheat (Triticum aestivum L.): Callus Induction, Plant Regeneration, and DNA Methylation.

The objective of this study was to comprehend the efficiency of wheat regeneration, callus induction, and DNA methylation through the application of mathematical frameworks and artificial intelligence (AI)-based models. This research aimed to explore the impact of treatments with AgNO3 and Ag-NPs on various parameters. The study specifically concentrated on analyzing RAPD profiles and modeling regeneration parameters. The treatments and molecular findings served as input variables in the modeling process. It included the use of AgNO3 and Ag-NPs at different concentrations (0, 2, 4, 6, and 8 mg L-1). The in vitro and epigenetic characteristics were analyzed using several machine learning (ML) methods, including support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), k-nearest neighbor classifier (KNN), and Gaussian processes classifier (GP) methods. This study's results revealed that the highest values for callus induction (CI%) and embryogenic callus induction (EC%) occurred at a concentration of 2 mg L-1 of Ag-NPs. Additionally, the regeneration efficiency (RE) parameter reached its peak at a concentration of 8 mg L-1 of AgNO3. Taking an epigenetic approach, AgNO3 at a concentration of 2 mg L-1 demonstrated the highest levels of genomic template stability (GTS), at 79.3%. There was a positive correlation seen between increased levels of AgNO3 and DNA hypermethylation. Conversely, elevated levels of Ag-NPs were associated with DNA hypomethylation. The models were used to estimate the relationships between the input elements, including treatments, concentration, GTS rates, and Msp I and Hpa II polymorphism, and the in vitro output parameters. The findings suggested that the XGBoost model exhibited superior performance scores for callus induction (CI), as evidenced by an R2 score of 51.5%, which explained the variances. Additionally, the RF model explained 71.9% of the total variance and showed superior efficacy in terms of EC%. Furthermore, the GP model, which provided the most robust statistics for RE, yielded an R2 value of 52.5%, signifying its ability to account for a substantial portion of the total variance present in the data. This study exemplifies the application of various machine learning models in the cultivation of mature wheat embryos under the influence of treatments and concentrations involving AgNO3 and Ag-NPs.

α-tocopherol ameliorates copper II oxide nanoparticles-induced cytotoxic, biochemical, apoptotic, and genotoxic damages in the rainbow trout gonad cells-2 (RTG-2) culture.

We investigated the effects of α-tocopherol on oxidative stress-caused damage caused by copper II oxide nanoparticles (CuO NPs) on Oncorhynchus mykiss gonadal cells (RTG-2) for 24 and 48 h. α-Tocopherol reversed the cell death and alterations in the expressions of genes such as sod1, gpx1a, gpx4b, and igf2 caused by CuO NPs; it also supported the expressions of cat, igf1, and gapdh genes caused by CuO NPs for 24 h and promoted alterations in the expressions of the sod2, gh1, and igf1 genes for 48 h. Additionally, α-tocopherol reversed the caspase 3/7 activity increased by CuO NPs for 24 h and supported it's decrease for 48 h. α-Tocopherol supported the increase in tail DNA (%) affected by CuO NPs for 24 h and reversed it for 48 h. Therefore, α-tocopherol may have the potential to protect against cellular alterations induced by CuO NPs in a time-dependent manner.

Influences of l-ascorbic acid on cytotoxic, biochemical, and genotoxic damages caused by copper II oxide nanoparticles in the rainbow trout gonad cells-2.

In parallel with the raising use of copper oxide nanoparticles (CuO NPs) in various industrial and commercial practices, scientific reports on their release to the environment and toxicity are increasing. The toxicity of CuO NPs is mostly based on their oxidative stress. Therefore, it is necessary to investigate the efficacy of well-known therapeutic agents as antioxidants against CuO NPs damage. This study aimed to investigate the mechanism of this damage and to display whether l-ascorbic acid could preserve against the cell toxicities induced by CuO NPs in the rainbow trout gonad cells-2 (RTG-2). While CuO NPs treatment significantly diminished cell viability, the l-ascorbic acid supplement reversed this. l-ascorbic acid treatment reversed the changes in expressions of sod1, sod2, gpx1a, and gpx4b genes while playing a supportive role in the changes in the expression of the cat gene induced by CuO NPs treatment. Moreover, CuO NPs treatment caused an upregulation in the expressions of growth-related genes (gh1, igf1, and igf2) and l-ascorbic acid treatment further increased these effects. CuO NPs treatment significantly up-regulated the expression of the gapdh gene (glycolytic enzyme gene) compared to the control group, and l-ascorbic acid treatment significantly down-regulated the expression of the gapdh gene compared to CuO NPs treatment. The genotoxicity test demonstrated that l-ascorbic acid treatment increased the genotoxic effect caused by CuO NPs by acting as a co-mutagen. Based on the findings, l-ascorbic acid has the potential to be sometimes inhibitory and sometimes supportive of cellular mechanisms caused by CuO NPs.

Nanotechnology-based preservation approaches for aquatic food products: A review with the current knowledge.

Aquatic food products (AFPs) are primarily preferred by consumers due to their high-quality protein content, omega 3 fatty acids, vitamins, minerals, and low calories. However, AFPs are easily degraded by microbial, enzymatic, and chemical reactions. The cold storage, freezing, chemical preservation, salting as well as vacuum packaging systems are the major preservation techniques. However, they are insufficient to extend the shelf life of AFPs. Therefore, researchers have focused on the availability of nanotechnology to be used in AFPs in line with the changing consumer demands. Studies on the effectiveness of nanoemulsion, nanoparticle, and nanofiber forms to increment the shelf life of AFPs are rapidly increasing. In this review, the degradation mechanisms of AFPs, the nano-preservation approaches, and possible mechanisms of action are reviewed with the current knowledge. The article highlights that nano-preservation approaches in AFPs have better microbial and physicochemical parameters such as total volatile basic nitrogen (TVBN), thiobarbituric acid (TBA), peroxide value (PV), free fatty acid (FFA), pH as well as the shelf life extension compared to the conventional methods. The antimicrobial activity of nanostructures reduces the microbial load of AFPs and delays the onset of oxidative degradation. Consequently, researchers suggest that nano-approaches may have great potential in extending the shelf life of AFPs.

Removing Trypan blue dye using nano-Zn modified Luffa sponge.

This study has presented specific features that are examined to remove the Trypan blue dye from the waste using Luffa sponge (LS) and modified Luffa sponge with zinc nanoparticles (ZnNPs). Peroxidase enzyme was obtained from Euphorbia amygdaloides plant and it was used with the green synthesis of Zn nanoparticles. Luffa sponge was used to be a support material for immobilized nanoparticles and it also used in remediation work. The obtained membrane forms, fibrous materials, (LS, ZnNPs-LS) were characterized with SEM and XRD. LS and ZnNPs-LS were employed as adsorbent to be used for the removal of Trypan blue dye from aqueous via batch studies. Measurements were made for the equilibrium, pH, temperature, concentration of dye with UV-visible spectrometer (590nm; for Trypan blue dye). The optimum removal of Trypan blue dye was found at pH7, the equilibrium was attained within 30min. The thermodynamic properties ΔG0, ΔH0, and ΔS0 showed that adsorption of Trypan blue dye onto LS and ZnNPs-LS were spontaneous and endothermic. The equilibrium isotherm data were analyzed using Langmuir and Freundlich models and the sorption process was described by the Langmuir isotherm with maximum monolayer adsorption capacity of 45.32 and 47.3mg/g for LS and LS-ZnNPs at 303±1°K, respectively.