Emergency action for calculating stock size and reference points in case of massive data deficiency (BREFdata)

This EMFF-project “Emergency action for calculating stock size and reference points in case of massive data deficiency” has delivered the tasks specified in the project description.This project was a timely response to the easily predictable gaps in data caused by the corona pandemic. The project has developed and implemented statistical rigorous methods for dealing with such data gaps. One consequence of gaps in the data series is that the uncertainties become larger --- even when the gaps are handled in the best way possible. The project has also developed methods to calculate reference points within the assessment model because that ensures that the (now larger) uncertainties are propagated correctly to all the results used by managers.The SAM model, which is used for more than 30 analytical assessments in ICES, is now capable of handling data situations where individual observations are becoming more uncertain (due to partially impacted data collection) and situations where individual observations are completely missing. This works for all types of observations (even of biological parameters) and for partially observed observations it works when the larger uncertainty is a known quantity and when it is unknown and needs to be estimated by the model. The SAM model can now also estimate a range of different reference points (e.g. Fmsy, Fmax, Fspr, Fb0, Fext, and Flim) internally and these can be based on wide selection of stock-recruitment relationships (e.g. Ricker, Beverton-Holt, hockey, spline, Shepherd, power, and Hassel/Deriso). Internal estimation of these reference points ensures that they are calculated consistently with the assessment model. In combination, this gives the working groups the tools needed to correctly handle data gaps in assessment and management.The project has thoroughly validated the implemented methods to study their performance and to strengthen confidence that they have been implemented correctly. The project has documented the developed methods in clear text, code examples, and mathematical formulas and further made them easily available in software (R package https://github.com/fishfollower/SAM) and online platform normally used to conduct such assessments (http://stockassessment.org). The project has presented these methods and helped apply them at all relevant expert and benchmark working groups.In the initial stages of the project, it was found that data gaps were also frequently caused by other factors than a covid pandemic, so this project turned out to be even more useful and applicable than anticipated. The combination of the techniques from this project and a previous project on treating biological quantities (e.g. weights and maturities) as observations gave the added benefit of being able to predict biological quantities where they are missing. Finally, the ability to predict any observation opens a lot of possibilities of using prediction-validation or cross-validation to compare the performance of models

Cm-p5 Peptide Dimers Inhibit Biofilms of <i>Candida albicans</i> Clinical Isolates, <i>C. parapsilosis</i> and Fluconazole-Resistant Mutants of <i>C. auris</i>

Antimicrobial peptides (AMPs) represent a promising class of therapeutic biomolecules that show antimicrobial activity against a broad range of microorganisms, including life-threatening pathogens. In contrast to classic AMPs with membrane-disrupting activities, new peptides with a specific anti-biofilm effect are gaining in importance since biofilms could be the most important way of life, especially for pathogens, as the interaction with host tissues is crucial for the full development of their virulence in the event of infection. Therefore, in a previous study, two synthetic dimeric derivatives (parallel Dimer 1 and antiparallel Dimer 2) of the AMP Cm-p5 showed specific inhibition of the formation of Candida auris biofilms. Here we show that these derivatives are also dose-dependently effective against de novo biofilms that are formed by the widespread pathogenic yeasts C. albicans and C. parapsilosis. Moreover, the activity of the peptides was demonstrated even against two fluconazole-resistant strains of C. auris

Communication, Coordination, and Security for People with Multiple Sclerosis (COCOS-MS): a randomised phase II clinical trial protocol

INTRODUCTION: Patients with multiple sclerosis (MS) have complex needs that range from organising one’s everyday life to measures of disease-specific therapy monitoring to palliative care. Patients with MS are likely to depend on multiple healthcare providers and various authorities, which are often difficult to coordinate. Thus, they will probably benefit from comprehensive cross-sectoral coordination of services provided by care and case management (CCM). Though studies have shown that case management improves quality of life (QoL), functional status and reduces service use, such benefits have not yet been investigated in severely affected patients with MS. In this explorative phase ll clinical trial, we evaluated a CCM with long-term, cross-sectoral and outreaching services and, in addition, considered the unit of care (patients and caregivers). METHODS AND ANALYSIS: Eighty patients with MS and their caregivers will be randomly assigned to either the control (standard care) or the intervention group (standard care plus CCM (for 12 months)). Regular data assessments will be done at baseline and then at 3-month intervals. As primary outcome, we will evaluate patients’ QoL. Secondary outcomes are patients’ treatment-related risk perception, palliative care needs, anxiety/depression, use of healthcare services, caregivers’ burden and QoL, meeting patients’ and caregivers’ needs, and evaluating the CCM intervention. We will also evaluate CCM through individual interviews and focus groups. The sample size calculation is based on a standardised effect of 0.5, and one baseline and four follow-up assessments (with correlation 0.5). Linear mixed models for repeated measures will be applied to analyse changes in quantitative outcomes over time. Multiple imputation approaches are taken to assess the robustness of the results. The explorative approach (phase ll clinical trial) with embedded qualitative research will allow for the development of a final design for a confirmative phase lll trial. ETHICS AND DISSEMINATION: The trial will be conducted under the Declaration of Helsinki and has been approved by the Ethics Commission of Cologne University’s Faculty of Medicine. Trial results will be published in an open-access scientific journal and presented at conferences. TRIAL REGISTRATION NUMBER: German Register for Clinical Studies (DRKS) (DRKS00022771)