Reporting and transparent research practices in sports medicine and orthopaedic clinical trials: a meta-research study

Objectives: Transparent reporting of clinical trials is essential to assess the risk of bias and translate research findings into clinical practice. While existing studies have shown that deficiencies are common, detailed empirical and field-specific data are scarce. Therefore, this study aimed to examine current clinical trial reporting and transparent research practices in sports medicine and orthopaedics. Setting: Exploratory meta-research study on reporting quality and transparent research practices in orthopaedics and sports medicine clinical trials. Participants: The sample included clinical trials published in the top 25% of sports medicine and orthopaedics journals over 9 months. Primary and secondary outcome measures: Two independent reviewers assessed pre-registration, open data and criteria related to scientific rigour, like randomisation, blinding, and sample size calculations, as well as the study sample, and data analysis. Results: The sample included 163 clinical trials from 27 journals. While the majority of trials mentioned rigour criteria, essential details were often missing. Sixty per cent (95% confidence interval (CI) 53% to 68%) of trials reported sample size calculations, but only 32% (95% CI 25% to 39%) justified the expected effect size. Few trials indicated the blinding status of all main stakeholders (4%; 95% CI 1% to 7%). Only 18% (95% CI 12% to 24%) included information on randomisation type, method and concealed allocation. Most trials reported participants' sex/gender (95%; 95% CI 92% to 98%) and information on inclusion and exclusion criteria (78%; 95% CI 72% to 84%). Only 20% (95% CI 14% to 26%) of trials were pre-registered. No trials deposited data in open repositories. Conclusions: These results will aid the sports medicine and orthopaedics community in developing tailored interventions to improve reporting. While authors typically mention blinding, randomisation and other factors, essential details are often missing. Greater acceptance of open science practices, like pre-registration and open data, is needed. As these practices have been widely encouraged, we discuss systemic interventions that may improve clinical trial reporting

Dynamic Properties of Network Motifs Contribute to Biological Network Organization

Biological networks, such as those describing gene regulation, signal transduction, and neural synapses, are representations of large-scale dynamic systems. Discovery of organizing principles of biological networks can be enhanced by embracing the notion that there is a deep interplay between network structure and system dynamics. Recently, many structural characteristics of these non-random networks have been identified, but dynamical implications of the features have not been explored comprehensively. We demonstrate by exhaustive computational analysis that a dynamical property—stability or robustness to small perturbations—is highly correlated with the relative abundance of small subnetworks (network motifs) in several previously determined biological networks. We propose that robust dynamical stability is an influential property that can determine the non-random structure of biological networks

High variation among clinical studies in the assessment of physical function after knee replacement: a systematic review

PurposeThe purpose of this study was to summarise the current use of outcome measures for the assessment of physical function after knee joint replacement.MethodsA systematic approach following the PRISMA guidelines was used. Literature search was performed on MEDLINE database via PubMed and on Epistemonikos. Clinical trials (level of evidence I-II) on knee joint replacement reporting data on the 'physical function' domain published between January 2017 and June 2022 were included. Descriptive statistics were used to summarise the evidence.ResultsIn the 181 articles that met the inclusion criteria, 49 different outcome measurements were used to evaluate clinical outcomes after knee joint replacement. The most frequently adopted patient-reported outcome measures (PROMs) were the Knee Society Score (KSS) (78 studies; 43.1%), the Western Ontario and McMaster Universities (WOMAC) Arthritis Index (62 studies; 34.3%), the Oxford Knee Score (OKS) (51 studies; 28.2%) and the Knee Injury and Osteoarthritis Outcome Score (KOOS) (36 studies; 20%). The most frequently used performance-based outcome measures (PBOMs) were the Timed-Up-and-Go (TUG) test (30 studies; 16.6%) and the 6-min-walk test (6MWT) (21 studies; 11.6%). Among impairment-based outcome measures (IBOMs), range of motion (ROM) was the most used (74 studies; 40.9%).ConclusionThere is considerable variation among clinical studies regarding the assessment of the physical function of patients after knee joint replacement. PROMs were found to be the most commonly adopted outcome measures; however, no single PROM was used in more than half of the papers analysed

The influence of gluteal muscle strength deficits on dynamic knee valgus: a scoping review

Anterior cruciate ligament (ACL) injuries are caused by both contact and non-contact injuries. However, it can be claimed that non-contact ones account approximately for 70% of all cases. Thus, several authors have emphasized the role of reduction of muscle strength as a modifable risk factor referred to non-contact ACL injury, with the latter being targeted by specifc training interventions. The present paper wants to review the available literature specifcally on the relationship between dynamic knee valgus, gluteal muscles (GM) strength, apart from the potential correlation regarding ACL injury. After a research based on MEDLINE via PubMed, Google scholar, and Web of Science, a total of 29 articles were collected and thus included. Additionally, this review highlights the crucial role of gluteal muscles in maintaining a correct knee position in the coronal plane during diferent exercises, namely walking, running, jumping and landin

Towards a Rigorous Assessment of Systems Biology Models: The DREAM3 Challenges

Background: Systems biology has embraced computational modeling in response to the quantitative nature and increasing scale of contemporary data sets. The onslaught of data is accelerating as molecular profiling technology evolves. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) is a community effort to catalyze discussion about the design, application, and assessment of systems biology models through annual reverse-engineering challenges. Methodology and Principal Findings: We describe our assessments of the four challenges associated with the third DREAM conference which came to be known as the DREAM3 challenges: signaling cascade identification, signaling response prediction, gene expression prediction, and the DREAM3 in silico network challenge. The challenges, based on anonymized data sets, tested participants in network inference and prediction of measurements. Forty teams submitted 413 predicted networks and measurement test sets. Overall, a handful of best-performer teams were identified, while a majority of teams made predictions that were equivalent to random. Counterintuitively, combining the predictions of multiple teams (including the weaker teams) can in some cases improve predictive power beyond that of any single method. Conclusions: DREAM provides valuable feedback to practitioners of systems biology modeling. Lessons learned from the predictions of the community provide much-needed context for interpreting claims of efficacy of algorithms described in the scientific literature

Petri Nets with Fuzzy Logic (PNFL): Reverse Engineering and Parametrization

Background: The recent DREAM4 blind assessment provided a particularly realistic and challenging setting for network reverse engineering methods. The in silico part of DREAM4 solicited the inference of cycle-rich gene regulatory networks from heterogeneous, noisy expression data including time courses as well as knockout, knockdown and multifactorial perturbations. Methodology and Principal Findings: We inferred and parametrized simulation models based on Petri Nets with Fuzzy Logic (PNFL). This completely automated approach correctly reconstructed networks with cycles as well as oscillating network motifs. PNFL was evaluated as the best performer on DREAM4 in silico networks of size 10 with an area under the precision-recall curve (AUPR) of 81%. Besides topology, we inferred a range of additional mechanistic details with good reliability, e.g. distinguishing activation from inhibition as well as dependent from independent regulation. Our models also performed well on new experimental conditions such as double knockout mutations that were not included in the provided datasets. Conclusions: The inference of biological networks substantially benefits from methods that are expressive enough to deal with diverse datasets in a unified way. At the same time, overly complex approaches could generate multiple different models that explain the data equally well. PNFL appears to strike the balance between expressive power and complexity. This also applies to the intuitive representation of PNFL models combining a straightforward graphical notation with colloquial fuzzy parameters

Norma DIN 476, su uso para desarrollar algunos temas de matemática de un programa de segundo año

Se presenta una propuesta de enseñanza, utilizando un material concreto que nos permite desarrollar algunos temas del programa de Matemática correspondiente al 2do año de la Escuela Industrial Superior de la ciudad de Santa Fe. La selección del material tiene que ver con una búsqueda de relaciones con otras asignaturas del mismo nivel (u otros) porque creemos que la enseñanza y aprendizaje de los contenidos de nuestra área tienen mejor recepción en los alumnos cuando se la contextualiza, cuando se evidencia su necesidad, valor o colaboración en otras áreas de estudio. El abordaje transdisciplinario requiere de mentes creativas, abiertas y capaces de resolver situaciones problemáticas específicas desde muchas perspectivas. Esto indica que el docente debe diseñar estrategias de enseñanza basadas en una concepción cognitiva del aprendizaje, favoreciendo el tratamiento de los contenidos disciplinares desde una perspectiva crítica y reflexiva; en la cual el joven pueda poner en juego sus propias capacidades y posibilidades para participar activamente del proceso y construir el conocimiento.Facultad de Humanidades y Ciencias de la Educació