Innovative gamification and outreach tools to raise awareness about antimicrobial resistance.

Since 2017, the SWICEU team has developed various informative actions and innovative gamification supports to educate and raise awareness about antimicrobial resistance (AMR) and the correct use of antibiotics among the general population especially among young people. This case study presents the results obtained in the last 5 years with the strategies carried out by this team, composed of students and professors of Health Sciences, Industrial Design Engineering, and Communication Sciences at CEU Cardenal Herrera University (CEU UCH) in Valencia (Spain). Over the past 5 years, playful educational supports have been developed to make the health problem of bacterial resistance and the action of antibiotics more understandable among young people. The dissemination media used, with the same objective of teaching and raising awareness about AMR in a creative and innovative way, have been selected according to the trends in digital communication and use of scientific and health content provided by the most recent studies carried out among the Spanish population. These strategies have included decalogues or "tips" with useful advice, infographics, YouTube videos, Twitter threads, online challenges on Kahoot, stories on Instagram, use of QR codes, etc. These actions have also obtained diffusion in the media and have been awarded by different national and international entities. The good results obtained in the case under study allow us to establish recommendations for the design of innovative educational gamification and dissemination supports on AMR, especially aimed at younger audiences.

Evaluation of knowledge about antibiotics and engagement with a research experience on antimicrobial resistance between pre-university and university students for five school years (2017-2021).

Antimicrobial resistance (AMR) remains a serious global health problem. Spain is the fifth country in Europe with the highest consumption of antibiotics, due in part to ignorance of the good use of these drugs and the problem of AMR. To avoid a post-antibiotic era, adequate training on this problem is key to create social awareness. This study aimed to evaluate the impact that the SWICEU project, an academic program about antibiotic discovery, has had on the knowledge of AMR and rational use of antimicrobials in pre-university students from seven schools in the province of Valencia during five academic years (2017-2021), as well as to evaluate the level of satisfaction of university and pre-university students who have participated in the project. For this study, a survey was carried out with multiple-choice questions with a single correct answer to evaluate the knowledge acquired by pre-university students before and after the project. A satisfaction survey was also designed with a Likert scale from the lowest to the highest level of satisfaction for the two groups of students after the project. Data on knowledge surveys indicated an increase in the mean number of correct answers after the sessions. In satisfaction surveys, we highlighted the issue that referred to the project's recommendation. The data obtained confirm this project as a valuable activity, as it allows learning about AMR and the rational use of antibiotics in a pleasing and attractive way for young pre-university and university students.

New Pharmacokinetic and Microbiological Prediction Equations to Be Used as Models for the Search of Antibacterial Drugs.

Currently, the development of resistance of Enterobacteriaceae bacteria is one of the most important health problems worldwide. Consequently, there is a growing urge for finding new compounds with antibacterial activity. Furthermore, it is very important to find antibacterial compounds with a good pharmacokinetic profile too, which will lead to more efficient and safer drugs. In this work, we have mathematically described a series of antibacterial quinolones by means of molecular topology. We have used molecular descriptors and related them to various pharmacological properties by using multilinear regression (MLR) analysis. The regression functions selected by presenting the best combination of a number of quality and validation metrics allowed for the reliable prediction of clearance (CL), and minimum inhibitory concentration 50 against Enterobacter aerogenes (MIC50Ea) and Proteus mirabilis (MIC50Pm). The obtained results clearly reveal that the combination of molecular topology methods and MLR provides an excellent tool for the prediction of pharmacokinetic properties and microbiological activities in both new and existing compounds with different pharmacological activities.

Virtual Combinatorial Chemistry and Pharmacological Screening: A Short Guide to Drug Design.

Traditionally, drug development involved the individual synthesis and biological evaluation of hundreds to thousands of compounds with the intention of highlighting their biological activity, selectivity, and bioavailability, as well as their low toxicity. On average, this process of new drug development involved, in addition to high economic costs, a period of several years before hopefully finding a drug with suitable characteristics to drive its commercialization. Therefore, the chemical synthesis of new compounds became the limiting step in the process of searching for or optimizing leads for new drug development. This need for large chemical libraries led to the birth of high-throughput synthesis methods and combinatorial chemistry. Virtual combinatorial chemistry is based on the same principle as real chemistry-many different compounds can be generated from a few building blocks at once. The difference lies in its speed, as millions of compounds can be produced in a few seconds. On the other hand, many virtual screening methods, such as QSAR (Quantitative Sturcture-Activity Relationship), pharmacophore models, and molecular docking, have been developed to study these libraries. These models allow for the selection of molecules to be synthesized and tested with a high probability of success. The virtual combinatorial chemistry-virtual screening tandem has become a fundamental tool in the process of searching for and developing a drug, as it allows the process to be accelerated with extraordinary economic savings.

Molecular Topology for the Search of New Anti-MRSA Compounds.

The variability of methicillin-resistant Staphylococcus aureus (MRSA), its rapid adaptive response against environmental changes, and its continued acquisition of antibiotic resistance determinants have made it commonplace in hospitals, where it causes the problem of multidrug resistance. In this study, we used molecular topology to develop several discriminant equations capable of classifying compounds according to their anti-MRSA activity. Topological indices were used as structural descriptors and their relationship with anti-MRSA activity was determined by applying linear discriminant analysis (LDA) on a group of quinolones and quinolone-like compounds. Four extra equations were constructed, named DFMRSA1, DFMRSA2, DFMRSA3 and DFMRSA4 (DFMRSA was built in a previous study), all with good statistical parameters, such as Fisher-Snedecor F (>68 in all cases), Wilk's lambda (<0.13 in all cases), and percentage of correct classification (>94% in all cases), which allows a reliable extrapolation prediction of antibacterial activity in any organic compound. The results obtained clearly reveal the high efficiency of combining molecular topology with LDA for the prediction of anti-MRSA activity.

Evaluation of the Impact of the Tiny Earth Project on the Knowledge About Antibiotics of Pre-university Students in the Province of Valencia on Three Different School Years (2017-2020).

According to the World Health Organization (WHO), antibacterial resistance is a serious problem worldwide. In Spain, knowledge about the use of antibiotics is scarce, being the third country with the highest consumption of antibiotics in the world and the first in Europe. This problem is due, partly, to the abusive use of these drugs in human medicine, livestock, and agriculture. The objective of this study was to evaluate the impact that the Tiny Earth project has had on the antibiotic knowledge in pre-university students. To do this, a survey was conducted before and after the Tiny Earth project in three different school years (2017-2020) to 322 pre-university students belonging to seven schools in the province of Valencia. The survey consisted of 12 multiple-choice questions with a single valid answer. We observed 67.6% success at the beginning and 81.2% at the end. These data indicate that they correctly answered an average of 1.64 more questions after completing the project. In view of the results, we can affirm that the Tiny Earth project has contributed to an improvement in scientific knowledge and awareness of the correct use of antibiotics and the emergence of resistances by pre-university students, which could also be transmitted to their social environment, thus improving awareness global on these issues.

Molecular Topology for the Discovery of New Broad-Spectrum Antibacterial Drugs.

In this study, molecular topology was used to develop several discriminant equations capable of classifying compounds according to their antibacterial activity. Topological indices were used as structural descriptors and their relation to antibacterial activity was determined by applying linear discriminant analysis (LDA) on a group of quinolones and quinolone-like compounds. Four equations were constructed, named DF1, DF2, DF3, and DF4, all with good statistical parameters such as Fisher-Snedecor's F (over 25 in all cases), Wilk's lambda (below 0.36 in all cases) and percentage of correct classification (over 80% in all cases), which allows a reliable extrapolation prediction of antibacterial activity in any organic compound. From the four discriminant functions, it can be extracted that the presence of sp3 carbons, ramifications, and secondary amine groups in a molecule enhance antibacterial activity, whereas the presence of 5-member rings, sp2 carbons, and sp2 oxygens hinder it. The results obtained clearly reveal the high efficiency of combining molecular topology with LDA for the prediction of antibacterial activity.

Analysis of the influence of clinical and demographic factors on the understanding of cataract informed consent / Análisis de la influencia de factores clínicos y demográficos en la comprensión del consentimiento informado de cataratas / Análise da influência de fatores clínicos e demográficos na compreensão do consentimento informado para cirurgia de catarata

PURPOSE: To estimate the influence of clinical and demographical information in the understanding of cataract surgery informed consent, identifying less understandable areas. To assess informed consent document concept. METHODS: Multiple-choice questionnaire was designed to collect information and to evaluate the understanding of cataract surgery and informed consent. An ordinary regression model was adjusted to express the effect of clinical and demographic variables to the questionnaire score. RESULTS: The study comprised 180 patients. Sex (female, p=0.404), non-ophthalmologist source of information (p=0.397), previous surgical history (p=0.571), not having a companion (p=0.396) nor the days since the signing of informed consent form (p=0.535) had no influence in the understanding of cataract surgery informed consent. Age (r=-0.083, p<0.001) and educational level (secondary studies r=1.845, p<0.001; tertiary studies r=4.289, p<0.001) showed statistical significance with greater strength of association educational level (OR secondary studies = 6.33, OR tertiary studies = 72.86) than age had (OR = 0.92). CONCLUSION: Patient's knowledge about cataract informed consent is influenced by age and educational level. The purpose and the risks, consequences of not performing surgery and postoperative indications are the least understood topics. Informed consent is seen as a forced legal obligation.

OBJETIVOS: estimar la influencia de la información clínica y demográfica en la comprensión del consentimiento informado de la cirugía de cataratas, identificando áreas menos comprensibles. Evaluar el concepto de "documento de consentimiento informad". MÉTODOS: el cuestionario de opción múltiple se diseñó para reunir información y evaluar la comprensión de la cirugía de cataratas y el consentimiento informado. Se ajustó un modelo de regresión ordinario para expresar el efecto de las variables clínicas y demográficas en la puntuación del cuestionario. RESULTADOS: El estudio abarcó 180 pacientes. Sexo (femenino, p = 0.404); fuente de información no oftalmológica (p = 0.397); historial quirúrgico previo (p = 0.571); no tener acompañante (p = 0.396), y los días desde la firma del formulario de consentimiento informado (p = 0,535), que no tuvo influencia en la comprensión del consentimiento informado en la cirugía de cataratas. La edad (r = -0.083, p <0.001) y el nivel educativo (estudios secundarios r = 1.845, p <0.001; estudios terciarios r = 4.289, p <0.001) mostraron significación estadística con una mayor fuerza del nivel educativo de asociación (OR estudios secundarios = 6.33, OR estudios terciarios = 72.86) que la edad (OR = 0.92). CONCLUSIÓN: El conocimiento del paciente sobre el consentimiento informado en cirugía de cataratas está influenciado por la edad y el nivel educativo. Los temas menos entendidos son el propósito y los riesgos, las consecuencias de no realizar la cirugía y las indicaciones postoperatorias. El consentimiento informado se considera una obligación legal forzada.

OBJETIVO: Estimar a influência de informações clínicas e demográficas na compreensão do consentimento informado para cirurgia de catarata, identificando áreas menos compreensíveis. Avaliar o conceito do documento de consentimento informado. MÉTODOS: Um questionário de múltipla escolha foi desenvolvido para coletar informações e avaliar a compreensão sobre cirurgia de catarata e de consentimento informado. Um modelo de regressão ordinária foi ajustado para expressar o efeito das variáveis clínicas e demográficas no escore do questionário. RESULTADOS: O estudo envolveu 180 pacientes. Sexo (feminino, p=0,404), fonte de informações não oftalmológica (p=0,397), história cirúrgica prévia (p=0,571), não ter um/a companheiro/a (p=0,396) nem os dias desde a assinatura do formulário de consentimento informado (p=0,535) tiveram influência na compreensão do consentimento informado para cirurgia de catarata. Idade (r=-0,083, p<0,001) e nível educacional (estudos secundários r=1,845, p<0,001; estudos terciários r=4,289, p<0,001) mostraram significância estatística, com maior força de associação para o nível educacional (OR estudos secundários = 6,33, OR estudos terciários = 72,86) que para a idade (OR = 0,92). CONCLUSÃO: O conhecimento do paciente sobre o consentimento informado para cirurgia de catarata é influenciado pela idade e nível educacional. O objetivo e os riscos, consequências, de não fazer a cirurgia e as indicações pós-operatórias são os tópicos menos compreensíveis. O consentimento informado é visto como uma obrigação legal compulsória.

Topological index Nclass as a factor determining the antibacterial activity of quinolones against Escherichia coli.

Aim: Due to antibiotic resistance and the lack of investment in antimicrobial R&D, quantitative structure-activity relationship (SAR) methods appear as an ideal approach for the discovery of new antibiotics. Result & methodology: Molecular topology and linear discriminant analysis were used to construct a model to predict activity against Escherichia coli. This model establishes new SARs, of which, molecular size and complexity (Nclass), stand out for their discriminant power. This model was used for the virtual screening of the Index Merck database, with results showing a high success rate as well as a moderate restriction. Conclusion: The model efficiently finds new active compounds. The topological index Nclass can act as a filter in other quantitative structure-activity relationship models predicting activity against E. coli.

Obtaining Microbiological and Pharmacokinetic Highly Predictive Equations.

In this paper, a Multilinear Regression (MLR) analysis has been carried out in order to accurately predict physicochemical properties and biological activities of a group of antibacterial quinolones by means of a set of structural descriptors called topological indices. The aim of this work is to develop prediction equations for these properties after collecting the maximum number of data from the literature on antibacterial quinolones. The five regression functions selected by presenting the best combination of various statistical parameters, subsequently validated by means of internal validation (intercorrelation, Y-randomization and leave-one-out cross-validation tests), allowed the reliable prediction of minimum inhibitory concentration 50 versus Staphylococcus aureus (MIC50Sa), Streptococcus pyogenes (MIC50Spy) and Bacteroides fragilis (MIC50Bf), Mean Residence Time (MRT) after oral administration and volume of distribution (VD). We conclude that the combination of molecular topology methods and MLR provides an excellent tool for the prediction of pharmacological properties.

Topological pattern for the search of new active drugs against methicillin resistant Staphylococcus aureus.

Molecular topology was used to develop a mathematical model capable of classifying compounds according to antimicrobial activity against methicillin resistant Staphylococcus aureus (MRSA). Topological indices were used as structural descriptors and their relation to antimicrobial activity was determined by using linear discriminant analysis. This topological model establishes new structure activity relationships which show that the presence of cyclopropyl, chlorine and ramification pairs at a distance of two bonds favor this activity, while the presence of tertiary amines decreases it. This model was applied to a combinatorial library of a thousand and one 6-fluoroquinolones, from which 117 theoretical active molecules were obtained. The compound 10 and five new quinolones were tested against MRSA. They all showed some activity against MRSA, although compounds 6, 8 and 9 showed anti-MRSA activity similar to ciprofloxacin. This model was also applied to 263 theoretical antibacterial agents described by us in a previous work, from which 34 were predicted as theoretically active. Anti-MRSA activity was found bibliographically in 9 of them (ensuring at least 26% of success), and from the rest, 3 compounds were randomly chosen and tested, finding mitomycin C to be more active than ciprofloxacin. The results demonstrate the utility of the molecular topology approaches for identifying new drugs active against MRSA.

Topological Model for the Search of New Antibacterial Drugs. 158 Theoretical Candidates.

In this paper, molecular topology was used to develop a mathematical model capable of classifying compounds according to their antibacterial activity. Topological indices were used as structural descriptors and their relation to antibacterial activity was determined by applying linear discriminant analysis (LDA) on a group of quinolones, widely used nowadays because of their broad spectrum of activity, well tolerance profile and advantageous pharmacokinetic properties. The topological model of activity obtained included two discriminant functions, selected by a combination of various statistical paremeters such as Fisher-Snedecor F and Wilk's lambda, and allows the reliable prediction of antibacterial activity in any organic compound. After a virtual pharmacological screening on a library of 6375 compounds, the model has selected 263 as active compounds, from which 40% have proven antibacterial activity. The results obtained clearly reveal the high efficiency of molecular topology for the prediction of pharmacological activities. These models are very helpful in the discovery of new applications of natural and synthetic molecules with different chemical or biological properties. Therefore, we finally present 158 strong candidates to be developed as novel antibacterials.