Evaluations in the Moodle‑Mediated Music Teaching‑Learning Environment

This study presents the use of automated data analysis procedures in the teaching-learning process, mediated by telematics platforms. It is based on the application of the principles of virtual learning, the use of the Internet and the automation of data analysis of information collected in Moodle. The application of analysis procedures for the assessment of music competences is proposed based on the data collected in an exam administered at the end of the course. The sample of the study consists of 1327 students (n = 1327) in the first year of Compulsory Secondary Education in Spain and measures the level of acquisition of the key competences denominated “cultural and artistic”. The results are subjected to the K-means classification technique. This technique is used to obtain homogeneously distributed conglomerates which allow for an objective evaluation of the levels of acquisition of the key musical competences

Frequency of PCV-2 viremia in nursery piglets from a Spanish swine integration system in 2020 and 2022 considering PRRSV infection status

Background Porcine circovirus 2 (PCV‑2) poses a signifcant economic threat for the swine industry, causing a range of diseases collectively referred to as porcine circovirus diseases (PCVDs). Despite PCV‑2 vaccine efectiveness, the need for monitoring infectious pressure remains. PCV‑2 coinfection with other pathogens like porcine reproduc‑ tive and respiratory syndrome virus (PRRSV) can exacerbate disease severity and lead to PCV‑2‑systemic disease cases. Monitoring both PRRSV and PCV‑2 in co‑infected farms is crucial for an efective management and vaccination pro‑ grams. The present cross‑sectional study aimed to determine PCV‑2 antibody levels in piglets at weaning and PCV‑2 and PRRSV viremia in pooled serum samples at weaning (vaccination age) and at 6 and 9 weeks of age from a Spanish swine integration system in 2020 (48 farms) and in 2022 (28 out of the 48 analysed previously). Results The frequency of PCV‑2 detection in pools of piglet sera was 2.1% (2020) and 7.1% (2022) at vaccination age but increased at the end of the nursery period (10.4% in 2020 and 39.3% in 2022) in both years. Co‑infections between PCV‑2 and PRRSV were detected in a signifcant proportion of PRRSV positive farms (15% in 2020, and 60% in 2022). PCV‑2 antibody levels (ELISA S/P ratios) at weaning were lower in PCV‑2 qPCR positive farms at diferent sam‑ pling time‑points (0.361 in 2020 and 0.378 in 2022) compared to PCV‑2 qPCR negative ones (0.587 in 2020 and 0.541 in 2022). The 28 farms tested both years were classifed in four diferent epidemiological scenarios depending on their PCV‑2 virological status. Those PCV‑2 qPCR negative farms in 2020 that turned to be positive in 2022 had a statistically signifcant increase of PRRSV RT‑qPCR detection and a PCV‑2 antibody levels reduction, facts that were not observed in the rest of the scenarios. Conclusion This epidemiological study in farms from the same integration system determined the occurrence, in 2020 and in 2022, of PCV‑2 and PRRSV infections in piglets during the nursery period by using pooled serum samples.Mònica Sagrera is holder of an Industrial Doctorat grant from the Catalan Government (Spain), with the reference Nº. 2022 DI 56.info:eu-repo/semantics/publishedVersio

TransFlow: a modular framework for assembling and assessing accurate de novo transcriptomes in non-model organisms

[Background]: The advances in high-throughput sequencing technologies are allowing more and more de novo assembling of transcriptomes from many new organisms. Some degree of automation and evaluation is required to warrant reproducibility, repetitivity and the selection of the best possible transcriptome. Workflows and pipelines are becoming an absolute requirement for such a purpose, but the issue of assembling evaluation for de novo transcriptomes in organisms lacking a sequenced genome remains unsolved. An automated, reproducible and flexible framework called TransFlow to accomplish this task is described.[Results]: TransFlow with its five independent modules was designed to build different workflows depending on the nature of the original reads. This architecture enables different combinations of Illumina and Roche/454 sequencing data, and can be extended to other sequencing platforms. Its capabilities are illustrated with the selection of reliable plant reference transcriptomes and the assembling six transcriptomes (three case studies for grapevine leaves, olive tree pollen, and chestnut stem, and other three for haustorium, epiphytic structures and their combination for the phytopathogenic fungus Podosphaera xanthii). Arabidopsis and poplar transcriptomes revealed to be the best references. A common result regarding de novo assemblies is that Illumina paired-end reads of 100 nt in length assembled with OASES can provide reliable transcriptomes, while the contribution of longer reads is noticeable only when they complement a set of short, single-reads.[Conclusions]:TransFlow can handle up to 181 different assembling strategies. Evaluation based on principal component analyses allows its self-adaptation to different sets of reads to provide a suitable transcriptome for each combination of reads and assemblers. As a result, each case study has its own behaviour, prioritises evaluation parameters, and gives an objective and automated way for detecting the best transcriptome within a pool of them. Sequencing data type and quantity (preferably several hundred millions of 2×100 nt or longer), assemblers (OASES for Illumina, MIRA4 and EULER-SR reconciled with CAP3 for Roche/454) and strategy (preferably scaffolding with OASES, and probably merging with Roche/454 when available) arise as the most impacting factors.This work was supported by co-funding by the European Union through the European Regional Development Fund (ERDF) 2014-2020 “Programa Operativo de Crecimiento Inteligente” together with Spanish AEI “Agencia Estatal de Investigación” (BFU2016-77243-P, RTC-2015-4181-2, RTC-2016-4824-2, AGL2013-41939-R and AGL2016-76216-C2-1-R), AEI-INIA (RTA2013-00023-C02 and RTA2013-00068-C03), and Junta de Andalucía (P2011-CVI-7487), as well as CSIC grant 201540E065. PS received a postdoctoral fellowship from Junta de Andalucía linked to grant P10-CVI-6075. Publication costs were funded by the mentioned RTA2013-00068-C03 grant