Salmonella spp. in Domestic Ruminants, Evaluation of Antimicrobial Resistance Based on the One Health Approach-A Systematic Review and Meta-Analysis.

Salmonella spp. pose a global threat as a leading cause of foodborne illnesses, particularly prevalent in the European Union (EU), where it remains the second cause of foodborne outbreaks. The emergence of antimicrobial resistance (AMR) in Salmonella spp. has become a critical concern, complicating treatment strategies and escalating the risk of severe infections. The study focuses on large and small ruminants, identifying a prevalence of Salmonella spp. in slaughterhouses and revealing varied AMR rates across antimicrobial families throughout a meta-analysis. Also, comparison with AMR in human medicine was carried out by a systematic review. The results of the present meta-analysis displayed a prevalence of Salmonella spp. in large and small ruminants at slaughterhouses of 8.01% (8.31%, cattle; 7.04%, goats; 6.12%, sheep). According to the AMR of Salmonella spp., 20, 14, and 13 out of 62 antimicrobials studied were classified as low (<5%), high (>5% but <10%), and very high (>10%), respectively. Salmonella spp. did not display AMR against aztreonam, mezlocillin, ertapenem, meropenem, cefoxitin, ceftazidime, levofloxacin, tilmicosin, linezolid, fosfomycin, furazolidone, quinupristin, trimethoprim and spectinomycin. In contrast, a prevalence of 100% of AMR has been described against ofloxacin, lincomycin, and cloxacillin. In the context of the main antibiotics used in the treatment of human salmonellosis, azithromycin was shown to have the highest resistance among Salmonella spp. isolates from humans. Regarding cephalosporins, which are also used for the treatment of salmonellosis in humans, the prevalence of Salmonella spp. resistance to this class of antibiotics was similar in both human and animal samples. Concerning quinolones, despite a heightened resistance profile in Salmonella spp. isolates from ruminant samples, there appears to be no discernible compromise to the efficacy of salmonellosis treatment in humans since lower prevalences of AMR in Salmonella spp. isolated from human specimens were observed. Although the resistance of Salmonella spp. indicates some degree of concern, most antibiotics are not used in veterinary medicine. Thus, the contribution of cattle, sheep and goats to the rise of antibiotic resistance of Salmonella spp. and its potential impact on public health appears to be relatively insignificant, due to their low prevalence in carcasses and organs. Nevertheless, the observed low prevalence of Salmonella spp. in ruminants at slaughterhouse and the correspondingly low AMR rates of Salmonella spp. to key antibiotics employed in human medicine do not indicate that ruminant livestock poses a substantial public health risk concerning the transmission of AMR. Thus, the results observed in both the meta-analysis and systematic review suggests that AMR is not solely attributed to veterinary antibiotic use but is also influenced by factors such as animal health management (i.e., biosecurity measures, prophylactic schemes) and human medicine.

[Data sharing: Towards a more sustainable research]. / Compartir datos: hacia una investigación más sostenible.

In psychology, there is little tradition of sharing raw data from one's research. This lack of tradition, along with other circumstances, reflects some weaknesses of psychology as a science. The reasons for which this scarce willingness to share data and the counter-arguments in favour of the benefits that a change in attitude would involve are discussed in this article. Such a change would not only strengthen the scientific nature of psychology, but also result in a more sustainable development of the research, allowing practices such as recycling and secondary analyses of raw data. Some ways of action to facilitate this change are also suggested.

The small impact of p-hacking marginally significant results on the meta-analytic estimation of effect size / El pequeño impacto del haqueo de resultados marginalmente significativos sobre la estimación meta-analítica del tamaño del efecto

The label p-hacking (pH) refers to a set of opportunistic practices aimed at making statistically significant p values that should be non-significant. Some have argued that we should prevent and fight pH for several reasons, especially because of its potential harmful effects on the assessment of both primary research results and their meta-analytical synthesis. We focus here on the effect of a specific type of pH, focused on marginally significant studies, on the combined estimation of effect size in me-ta-analysis. We want to know how much we should be concerned with its biasing effect when assessing the results of a meta-analysis. We have calculated the bias in a range of situations that seem realistic in terms of the prevalence and the operational definition of pH. The results show that in most of the situations analyzed the bias is less than one hundredth (± 0.01), in terms of d or r. To reach a level of bias of five-hundredths (± 0.05), there would have to be a massive presence of this type of pH, which seems rather unrealistic. We must continue to fight pH for many good rea-sons, but our main conclusion is that among them is not that it has a big impact on the meta-analytical estimation of effect size

La etiqueta p-hacking (pH) se refiere a un conjunto de prácticas oportunistas destinadas a hacer que sean significativos algunos valores p que deberían ser no significativos. Algunos han argumentado que debemos prevenir y luchar contra el pH por varias razones, especialmente debido a sus posibles efectos nocivos en la evaluación de los resultados de la investigación primaria y su síntesis meta-analítica. Nos focalizamos aquí en el efecto de un tipo específico de pH, centrado en estudios marginalmente significativos, en la estimación combinada del tamaño del efecto en el meta-análisis. Queremos saber cuánto deberíamos preocuparnos por su efecto de sesgo al evaluar los resultados de un meta-análisis. Hemos calculado el sesgo en una variedad de situaciones que parecen realistas en términos de prevalencia y de la definición operativa del pH. Los resultados muestran que en la mayoría de las situaciones analizadas el sesgo es inferior a una centésima (± 0.01), en términos de d o r. Para alcanzar un nivel de sesgo de cinco centésimas (± 0.05), tendría que haber una presencia masiva de este tipo de pH, lo que parece poco realista. Hay muchas buenas razones para luchar contra el pH, pero nuestra conclusión principal es que entre esas razones no se incluye que tenga un gran impacto en la estimación meta-analítica del tamaño del efecto

Compartir datos: hacia una investigación más sostenible / Data sharing: towards a more sustainable research

En Psicología hay poca tradición de compartir los datos directos de nuestras investigaciones. Esta falta de tradición, más otras circunstancias, reflejan algunas debilidades de la psicología como ciencia. Se exponen las razones por las que hay poca disposición a compartir los datos y se presentan contra-argumentos para defender los beneficios que tendría un cambio en esta actitud. Aparte de fortalecer el carácter científico de la psicología, este cambio redundaría en un desarrollo más sostenible de la investigación, permitiendo prácticas como el análisis secundario y el reciclado de datos. Se proponen vías de actuación para facilitar este cambio (AU)

In psychology, there is little tradition of sharing raw data from one’s research. This lack of tradition, along with other circumstances, reflects some weaknesses of psychology as a science. The reasons for which this scarce willingness to share data and the counter-arguments in favour of the benefits that a change in attitude would involve are discussed in this article. Such a change would not only strengthen the scientific nature of psychology, but also result in a more sustainable development of the research, allowing practices such as recycling and secondary analyses of raw data. Some ways of action to facilitate this change are also suggested (AU)