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Unsaturated polyester resin (UPR) is one of the first commercialized polymer matrices for composites reinforced with glass fibers, but has remained popular to this day. To reduce their environmental impact, natural fibers have been used as reinforcements. Researchers all over the world are still interested in these composites, and numerous papers have been published in the last four decades. Using bibliometric analysis, this work provides compiled, structured, and relevant information about the evolution and current state of these materials. This first study on UPR biocomposites based on bibliometric analysis examined 531 published papers identified in the Scopus database from 1982 to July 2022. An analysis of the most active states, leading institutions, and leading authors is followed by the identification of key areas such as the most common natural fibers used as reinforcements, fiber treatments, and composite design parameters such as processing techniques; recently, composite testing; and technological applications. The findings emphasize the importance of staying active in this global field and provide information on novel promising topics for future research.

Nanosystems are gaining momentum in pharmaceutical sciences because of the wide variety of possibilities for designing these systems to have specific functions. Specifically, studies of new cancer cotherapy drug-vitamin release nanosystems (DVRNs) including anticancer compounds and vitamins or vitamin derivatives have revealed encouraging results. However, the number of possible combinations of design and synthesis conditions is remarkably high. In addition, a large number of anticancer and vitamin derivatives have been already assayed, but a notably less number of cases of DVRNs were assayed as a whole (with the anticancer compound and the vitamin linked to them). Our approach combines with the perturbation theory and machine learning (PTML) model to predict the probability of obtaining an interesting DVRN by changing the anticancer compound and/or the vitamin present in a DVRN that is already tested for other anticancer compounds or vitamins that have not been tested yet as part of a DVRN. In a previous work, we built a linear PTML model useful for the design of these nanosystems. In doing so, we used information fusion (IF) techniques to carry out data enrichment of DVRN data compiled from the literature with the data for preclinical assays of vitamins from the ChEMBL database. The design features of DVRNs and the assay conditions of nanoparticles (NPs) and vitamins were included as multiplicative PT operators (PTOs) to the system, which indicates the importance of these variables. However, the previous work omitted experiments with nonlinear ML techniques and different types of PTOs such as metric-based PTOs. More importantly, the previous work does not consider the structure of the anticancer drug to be included in the new DVRNs. In this work, we are going to accomplish three main objectives (tasks). In the first task, we found a new model, alternative to the one published before, for the rational design of DVRNs using metric-based PTOs. The most accurate PTML

Nanoparticles (NPs) decorated with coating agents (polymers, gels, proteins, etc.) form Nanoparticle Drug Delivery Systems (DDNS), which are of high interest in nanotechnology and biomaterials science. There have been increasing reports of experimental data sets of biological activity, toxicity, and delivery properties of DDNS. However, these data sets are still dispersed and not as large as the datasets of DDNS components (NP and drugs). This has prompted researchers to train Machine Learning (ML) algorithms that are able to design new DDNS based on the properties of their components. However, most ML models reported up to date predictions of the specific activities of NP or drugs over a determined target or cell line. In this paper, we combine Perturbation Theory and Machine Learning (PTML algorithm) to train a model that is able to predict the best components (NP, coating agent, and drug) for DDNS design. In so doing, we downloaded a dataset of >30 000 preclinical assays of drugs from ChEMBL. We also downloaded an NP data set formed by preclinical assays of coated Metal Oxide Nanoparticles (MONPs) from public sources. Both the drugs and NP datasets of preclinical assays cover multiple conditions of assays that can be listed as two arrays, namely, cjdrug and cjNP. The cjdrug array includes >504 biological activity parameters (c0drug), >340 target proteins (c1drug), >650 types of cells (c2drug), >120 assay organisms (c3drug), and >60 assay strains (c4drug). On the other hand, the cjNP array includes 3 biological activity parameters (c0NP), 40 types of proteins (c1NP), 10 shapes of nanoparticles (c2NP), 6 assay media (c3NP), and 12 coating agents (c4NP). After downloading, we pre-processed both the data sets by separate calculation PT operators that are able to account for changes (perturbations) in the drug, coating agents, and NP chemical structure and/or physicochemical properties as well as for the assay conditions. Next, we carry out an information fusion proce

Strawberry (Fragaria ananassa), blackberry (Rubus glaucus), Peruvian cherry (Physalis peruviana L.) and purple passion fruit (Passiflora edulis Sims) are important fruit crops in Colombia, due to their organoleptic properties and nutritional qualities, making them attractive for international markets. This study was undertaken to characterize the physicochemical properties of these four fruits and to present an alternative for their use. To achieve this goal, the moisture, pH, soluble solids, acidity, color, iron and vitamin C concentration were determined, and a fortified mixed fruit drink was developed. All of the fruits can be classified as high acidity products dueto the acidity results. Purple passion fruit and Peruvian cherry presented the highest content of soluble solids, while blackberry, purple passion fruit and Peruvian cherry did not exhibit statistically significant differences in their iron contents, and strawberry exhibited the highest contribution of vitamin C., La fresa (Fragaria ananassa), la mora (Rubus glaucus), la uchuva (Physalis peruviana L.)y la gulupa (Passiflora edulis Sims)son cultivos frutales importantes en Colombia por sus propiedades organolépticas y nutritivas. Este estudio se realizó para caracterizar las propiedades fisicoquímicas de estos cuatro frutos y presentar una alternativa para su uso. Para lograr este objetivo, se caracterizaron las cuatro frutas determinando humedad, pH, sólidos solubles, acidez, color, contenido de hierro y la concentración de vitamina C. Posteriormente se desarrolló una bebida fortificada de frutas. De acuerdo a los resultados de acidez, todos losfrutos se pueden clasificar como productos de alta acidez. La gulupa y la uchuva, presentaron el mayor contenido de sólidos solubles, mientras que la mora, la gulupa y la uchuva, no presentaron diferencias estadísticamente significativas en su contenido de hierro. La fresa presentó la mayor contribución de la vitamina C.

Polymer biomaterials have had an unfavourable image due to their association with pollution. However, they are important in biomedicine. Polymers are versatile materials, they can be obtained in several chemical configurations and mixtures to generate composite materials with synergistic properties. In this research, a scientific and technological analysis of the biomedical application of polymeric biomaterials was performed, along with the compilation of their applications, production, mechanical properties and important features for the biomedical industry. Polymeric biomaterials area cutting-edge topic, as reflected in the number of scientific articles and patents. Nowadays, these biomaterials canreplace, reinforce or fulfil a specific function in the human body. However, due to the complexity of biological systems, immune reactions are still present,preventingthe development of tissues and functional organs in laboratory scale., Los materiales poliméricos han tenido una imagen desfavorable, ya que son asociados con contaminación. Sin embargo,estos son de gran importancia para la biomedicina. Los polímeros son materiales muy versátiles, se pueden obtener de múltiples configuraciones químicas y mezclaspara generar materiales compuestos conpropiedades sinérgicas. En esta investigaciónse realizó un análisis científico y tecnológico de las aplicaciones biomédicas de biomateriales poliméricos y se recopila algunas de sus aplicaciones, propiedades mecánicas y características importantes para la industria biomédica. Los biomateriales poliméricos sonuna temática de punta como se refleja en el número de artículos científicios y de patentes. En la actualidad, estos biomateriales pueden llegar a reemplazar, reforzar o cumplir una función específica en el cuerpo humano. No obstante, debido a la complejidad de los sistemas biológicos aún se siguen presentando reacciones inmunes,que evitan el desarrollo de tejidos u órganos funcionales a escala de laboratorio.