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The cost of treatment of antibiotic-resistant pathogens is on the level of tens of billions of dollars at the moment. It is of special interest to reduce or solve this problem using antimicrobial coatings, especially in hospitals or other healthcare facilities. The bacteria can transfer from medical staff or contaminated surfaces to patients. In this paper, we focused our attention on the antibacterial and antibiofouling activities of two types of photodynamic polyurethane composite films doped with carbon polymerized dots (CPDs) and fullerene C60. Detailed atomic force, electrostatic force and viscoelastic microscopy revealed topology, nanoelectrical and nanomechanical properties of used fillers and composites. A relationship between the electronic structure of the nanocarbon fillers and the antibacterial and antibiofouling activities of the composites was established. Thorough spectroscopic analysis of reactive oxygen species (ROS) generation was conducted for both composite films, and it was found that both of them were potent antibacterial agents against nosocomial bacteria (Klebsiela pneumoniae, Proteus mirabilis, Salmonela enterica, Enterococcus faecalis, Enterococcus epidermis and Pseudomonas aeruginosa). Antibiofouling testing of composite films indicated that the CPDs/PU composite films eradicated almost completely the biofilms of Pseudomonas aeruginosa and Staphylococcus aureus and about 50% of Escherichia coli biofilms.

In order to better predict the high aerosol concentrations associated with air pollution and climate change, a machine learning model was developed using transfer learning and the segmentation process of global satellite images. The main concept of transfer learning lies on convolutional neural networks and works by initializing the already trained model weights to better adapt the weights when the network is trained on a different dataset. The transfer learning technique was tested with the ResNet3D-101 model pre-trained from a 2D ImageNet dataset. This model has performed well for contrail detection to assess climate impact. Aerosol distributions can be monitored via satellite remote sensing. Satellites can monitor some aerosol optical properties like aerosol optical thickness. Aerosol optical thickness snapshots were the input dataset for the model and were obtained from NASA’s Terra-Modis satellite; the output images were segmented by comparing the pixel values with a threshold value of 0.8 for aerosol optical thickness. Hyperparameter optimization finds a tuple of hyperparameters that yields an optimal model that minimizes a predefined loss function on given independent data. The model structure was adjusted in order to improve the performance of the model by applying methods and hyperparameter optimization techniques such as grid search, batch size, threshold, and input length. According to the criteria defined by the authors, the distance domain criterion and time domain criterion, the developed model is capable of generating adequate data and finding patterns in the time domain. As observed from the comparison of relative coefficients for the criteria metrics proposed by the authors, ddc and dtc, the deep learning model based on ConvLSTM layers developed in our previous studies has better performance than the model developed in this study with transfer learning.

In this study, nanochitosan dots (ChiDs) were synthesized using gamma rays and encapsulated in bacterial cellulose (BC) polymer matrix for antibiofilm potential in photodynamic therapy. The composites were analyzed for structural changes using SEM, AFM, FTIR, XRD, EPR, and porosity measurements. Additionally, ChiD release was assessed. The results showed that the chemical composition remained unaltered, but ChiD agglomerates embedded in BC changed shape (1.5–2.5 µm). Bacterial cellulose fibers became deformed and interconnected, with increased surface roughness and porosity and decreased crystallinity. No singlet oxygen formation was observed, and the total amount of released ChiD was up to 16.10%. Antibiofilm activity was higher under green light, with reductions ranging from 48 to 57% under blue light and 78 to 85% under green light. Methicillin-resistant Staphylococcus aureus was the most sensitive strain. The new photoactive composite hydrogels show promising potential for combating biofilm-related infections.

Graphene quantum dots (GQDs) attract huge scientific attention ever since they were discovered. They are the only 0-dimensional, water-dispersible graphene-based nanomaterial. They show (i) excellent biocompatibility; (ii) stable and tunable photoluminescence in the visible part of the spectrum resistive to photobleaching; (iii) large surface area; (iv) good solubility in water and polar organic solvents. Their astonishing properties stem from the structure: graphene in the core and a vast number of different oxygen-containing functional groups such as carboxyl, carbonyl, epoxy, hydroxyl, and lactone. Their lateral size is below 100 nm, and the height is from 0.5 to a few nm. Thanks to different oxygen groups, they have very reach chemistry; they can be easily processed, modified, and functionalized. GQDs can be modified after their synthesis using different chemical reactions, which lead to changes in oxygen content, the addition of heteroatoms, binding of target molecules. Heteroatoms can be built-in GQDs structure during the process of synthesis and usually, N, S, and P are selected. They can be produced in many different ways and starting materials and all of them are dived into two main groups: bottom-up and top-down methods. Due to a large number of diverse functional groups and high surface area, GQDs create complexes with ions, cations, biomolecules, organic molecules, etc. Thanks to this feature, GQDs are studied for the application in sensing heavy metal ions, selected anions, proteins, metabolites, hormones, enzymes, pesticides, organic colors, etc. Another exciting feature of GQDs is their ability to produce reactive oxygen species under visible light.

This research explores the synthesis, characterization, and biological activities of silver nanoparticles (AgNPs) derived from acetone (AgNPs-acetone) and aqueous (AgNPs-H2O) extracts of Agrimonia eupatoria. The nanoparticles exhibit isometric morphology and uniform size distribution, as elucidated through Transmission Electron Microscopy (TEM) and high-resolution TEM (HRTEM) analyses. The utilization of Scanning Transmission Microscopy (STEM) with High-Angle Annular Dark-Field (HAADF) imaging and energy dispersive spectrometry (EDS) confirms the crystalline nature of AgNPs. Fourier Transform Infrared (FTIR) analysis reveals identical functional groups in the plant extracts and their corresponding AgNPs, suggesting the involvement of phytochemicals in the reduction of silver ions. Spectrophotometric monitoring of the synthesis process, influenced by various parameters, provides insights into the kinetics and optimal conditions for AgNP formation. The antioxidant activities of the plant extracts and synthesized AgNPs are evaluated through DPPH and ABTS methods, highlighting AgNPs-acetone as a potent antioxidant. Third-instar larvae exposed to the extracts have differential effects on DNA damage, with the acetone extract demonstrating antigenotoxic properties. Similarly, biosynthesized AgNPs-acetone displays antigenotoxic effects against EMS-induced DNA damage. The genotoxic effect of water extract and AgNPs-acetone was dose-dependent. Hemolytic potential is assessed on rat erythrocytes, revealing that low concentrations of AgNPs-acetone and AgNPs-H2O had a nontoxic effect on erythrocytes. Cytotoxicity assays demonstrate time-dependent and dose-dependent effects, with AgNPs-acetone exhibiting superior cytotoxicity. Proapoptotic activity is confirmed through apoptosis induction, emphasizing the potential therapeutic applications of AgNPs. The antimicrobial activity of AgNPs reveals concentration-dependent effects. AgNPs-H2O display better antibacterial activity, while

Coumarin derivates possess several biological effects, including anti-inflammatory, antioxidant, anticoagulant, antitumor, insecticidal, anthelminthic, hypnotic, antifungal, and HIV protease inhibition properties [1,2]. Due to their solubility in organic solvents and insolubility in water and body fluids, their bioavailability is significantlylow. Thus, they can be encapsulated intoliposomal particles with the aim of overcoming the mentioned disadvan-tage[3]. Hence, in the present study, coumarin derivate was encapsulated in phospholipid liposomes and their stability was monitored for 60 days in terms of vesicle size, polydispersity index (PDI), zeta potential, and mobility.