SPIRIT-DEFINE explanation and elaboration: recommendations for enhancing quality and impact of early phase dose-finding clinical trials protocols.

Unlabelled: Transparent and accurate reporting in early phase dose-finding (EPDF) clinical trials is crucial for informing subsequent larger trials. The SPIRIT statement, designed for trial protocol content, does not adequately cover the distinctive features of EPDF trials. Recent findings indicate that the protocol contents in past EPDF trials frequently lacked completeness and clarity.

CONSORT-DEFINE explanation and elaboration: recommendations for enhancing reporting quality and impact of early phase dose-finding clinical trials.

Unlabelled: Early phase dose-finding (EPDF) trials are key in the development of novel therapies, with their findings directly informing subsequent clinical development phases and providing valuable insights for reverse translation. Comprehensive and transparent reporting of these studies is critical for their accurate and critical interpretation, which may improve and expedite therapeutic development. However, quality of reporting of design characteristics and results from EPDF trials is often variable and incomplete.

Testing an Electronic Patient-Reported Outcome Platform in the Context of Traumatic Brain Injury: PRiORiTy Usability Study.

Background: Traumatic brain injury (TBI) is a significant public health issue and a leading cause of death and disability globally. Advances in clinical care have improved survival rates, leading to a growing population living with long-term effects of TBI, which can impact physical, cognitive, and emotional health. These effects often require continuous management and individualized care.

Novel high-content and open-source image analysis tools for profiling mitochondrial morphology in neurological cell models.

Mitochondria undergo dynamic morphological changes depending on cellular cues, stress, genetic factors, or disease. The structural complexity and disease-relevance of mitochondria have stimulated efforts to generate image analysis tools for describing mitochondrial morphology for therapeutic development. Using high-content analysis, we measured multiple morphological parameters and employed unbiased feature clustering to identify the most robust pair of texture metrics that described mitochondrial state.