i-aging cosmetic formulations with enhanced skin permeation properties.Resolution plays an essential role in oral imaging for periodontal disease assessment. Nevertheless, due to limitations in acquisition tools, a considerable number of oral examinations have low resolution, making the evaluation of this kind of lesion difficult. Recently, the use of deep-learning methods for image resolution improvement has seen an increase in the literature. In this work, we performed two studies to evaluate the effects of using different resolution improvement methods (nearest, bilinear, bicubic, Lanczos, SRCNN, and SRGAN). In the first one, specialized dentists visually analyzed the quality of images treated with these techniques. In the second study, we used those methods as different pre-processing steps for inputs of convolutional neural network (CNN) classifiers (Inception and ResNet) and evaluated whether this process leads to better results. The deep-learning methods lead to a substantial improvement in the visual quality of images but do not necessarily promote better classifier performance.The approval of two mRNA vaccines as urgent prophylactic treatments against Covid-19 made them a realistic alternative to conventional vaccination methods. However, naked mRNA is rapidly degraded by the body and cannot effectively penetrate cells. Vectors capable of addressing these issues while allowing endosomal escape are therefore needed. To date, the most widely used vectors for this purpose have been lipid-based vectors. Thus, we have designed an innovative vector called LipoParticles (LP) consisting of poly(lactic) acid (PLA) nanoparticles coated with a 15/85 mol/mol DSPC/DOTAP lipid membrane. An in vitro investigation was carried out to examine whether the incorporation of a solid core offered added value compared to liposomes alone. To that end, a formulation strategy that we have named particulate layer-by-layer (pLbL) was used. This method permitted the adsorption of nucleic acids on the surface of LP (mainly by means of electrostatic interactions through the addition of LAH4-L1 peptide), allowing an interesting strategy-essentially reducing the peptide intake to limit its cytotoxicity while maintaining a relevant transfection efficiency.The course of periodontal disease is affected by many factors; however, the most significant are the dysbiotic microflora, showing different pathogenicity levels. Rapid colonization in the subgingival environment can radically change the clinical state of the periodontium. This systematic review aims to present an innovative technique of loop-mediated isothermal amplification for rapid panel identification of bacteria in periodontal diseases. The decisive advantage of the loop-mediated isothermal amplification (LAMP) technique in relation to molecular methods based on the identification of nucleic acids (such as polymerase chain reaction (PCR or qPCR) is the ability to determine more pathogens simultaneously, as well as with higher sensitivity. In comparison with classical microbiological seeding techniques, the use of the LAMP method shortens a few days waiting time to a few minutes, reducing the time necessary to identify the species and determine the number of microorganisms. The LAMP technology requires only a small hardware base; hence it is possible to use it in outpatient settings. The developed technique provides the possibility of almost immediate assessment of periodontal status and, above all, risk assessment of complications during the treatment (uncontrolled spread of inflammation), which can certainly be of key importance in clinical work.Most conventional water treatment plants are not sufficiently equipped to treat both intracellular and extracellular Microcystins in drinking water. However, the effectiveness of sodium hypochlorite in removing Microcystin in containers at the point-of-use is not yet known. This study aimed to assess point-of-use water container treatment using bleach or sodium hypochlorite (NaOCl) and to assess the health problems associated with microcystins. Thirty-nine percent (29 of 74) of the total selected households were randomly selected to receive and treat their stored container water with sodium hypochlorite. The level of microcystin in the container water was measured after 30 min of contact with sodium hypochlorite. Microcystin concentrations in both the blooming and decaying seasons were higher (mean 1.10, 95% CI 0.46-1.67 µg/L and mean 1.14, 95% CI 0.65-1.63 µg/L, respectively) than the acceptable limit of 1 µg/L in households that did not treat their water with NaOCl, whilst in those that did, there was a significant reduction in the microcystin concentration (mean 0.07, 95% CI 0.00-0.16 µg/L and mean 0.18, 95% CI 0.00-0.45 µg/L). In conclusion, sodium hypochlorite treatment decreased microcystin s to an acceptable level and reduced the related health problems.Traditional authentication techniques, such as cryptographic solutions, are vulnerable to various attacks occurring on session keys and data. Physical unclonable functions (PUFs) such as dynamic random access memory (DRAM)-based PUFs are introduced as promising security blocks to enable cryptography and authentication services. However, PUFs are often sensitive to internal and external noises, which cause reliability issues. see more The requirement of additional robustness and reliability leads to the involvement of error-reduction methods such as error correction codes (ECCs) and pre-selection schemes that cause considerable extra overheads. In this paper, we propose deep PUF a deep convolutional neural network (CNN)-based scheme using the latency-based DRAM PUFs without the need for any additional error correction technique. The proposed framework provides a higher number of challenge-response pairs (CRPs) by eliminating the pre-selection and filtering mechanisms. The entire complexity of device identification is moved to the server side that enables the authentication of resource-constrained nodes. The experimental results from a 1Gb DDR3 show that the responses under varying conditions can be classified with at least a 94.9% accuracy rate by using CNN. After applying the proposed authentication steps to the classification results, we show that the probability of identification error can be drastically reduced, which leads to a highly reliable authentication.