Effectiveness of a Peer Mentoring on University Dropout and Academic Performance / La eficacia de un programa de mentoría en el abandono y el rendimiento académico

Mentoring programs have been proposed to reduce dropout and increase academic performance. We analyzed the effect of peer mentoring on university dropout and academic performance in the context of Spain. We applied a quasi-experimental posttest-only control group design with 3,774 students (mentees, n = 1,887; control, n = 1,887). Mentees had participated in a peer mentoring program. We apply the student’s t-test, Cohen’s d, phi statistic, and chi-square statistic. Mentees exhibited lower dropout than controls and showed higher academic performance regardless of the area of knowledge. Results support the implementation of mentoring programs in Spanish universities with the goal of reducing student dropout and increasing academic performance. The research provides empirical evidence for theory building in higher education studies, developmental relationships, and integration programs. (AU)

Se ha propuesto la aplicación de programas de mentoría para reducir la deserción universitaria y aumentar el rendimiento académico. En el artículo analizamos el efecto de la mentoría entre pares sobre el abandono universitario y el rendimiento académico en España. Aplicamos un diseño de grupo de control cuasiexperimental con medida post en una muestra de 3.774 estudiantes (mentorados, n = 1,887; control, n = 1,887). Los mentorados habían participado en un programa de mentoría entre pares. Aplicamos la prueba t de Student, la d de Cohen, el estadístico phi y el chi-cuadrado. Los mentorados presentaban un menor abandono que los controles y un mayor rendimiento académico independientemente del área de conocimiento. Los resultados avalan la implementación de programas de mentoría en las universidades españolas con el objetivo de reducir el abandono universitario y aumentar el rendimiento académico. La investigación proporciona evidencia empírica para la elaboración de teorías en estudios de educación superior, relaciones de desarrollo y programas de integración. (AU)

Wine yeasts identification by MALDI-TOF MS: Optimization of the preanalytical steps and development of an extensible open-source platform for processing and analysis of an in-house MS database.

Saccharomyces cerevisiae is the most important yeast species for the production of wine and other beverages. In addition, nowadays, researchers and winemakers are aware of the influence of non-Saccharomyces in wine aroma complexity. Due to the high microbial diversity associated to several agro-food processes, such as winemaking, developing fast and accurate methods for microbial identification is demanded. In this context, MALDI-TOF MS mass fingerprint provides reliable tool for fast biotyping and classification of microorganisms. However, there is no versatile and standardized method for fungi currently available. In this study, an optimized sample preparation protocol was devised for the biotyping of yeasts of oenological origin. Taking into account that commercially available reference databases comprise almost exclusively clinical microorganisms, most of them bacteria, in the present study a database of yeasts isolated from vineyards and wineries was created, and its accuracy was tested using industrial and laboratory yeast strains. In addition, the implementation of a program for MALDI-TOF MS spectra analysis has been developed as an extensible open-source platform for MALDI data processing and analysis with statistical techniques that has arisen from our previous experience working with MALDI data. The software integrates two R packages for raw MALDI data preprocessing: Continuous Wavelet Transform (CWT)-based algorithm and MassSpecWavelet. One of the advantages of the CWT is that it can be directly applied to a raw spectrum, without prior baseline correction. Mass fingerprints of 109 S. cerevisiae strains and 107 non-Saccharomyces isolates were generated by MALDI-TOF MS upon optimized sample preparation and instrument settings and analyzed for strain, species, and genus-level differentiation. As a reference method, for S. cerevisiae differentiation at strain level, the analysis of the polymorphism in the inter-delta region was chosen. The data revealed that MALDI-TOF MS can be used for the rapid and accurate identification of S. cerevisiae and non-Saccharomyces isolates at genus and species level. However, S. cerevisiae differentiation at strain level was not successfully achieved, and the differentiation among Metschnikowia species was also difficult.