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Additional file 1: Supplementary material file 1. Extra information observational study (WP2) HORIZON2020 Palliative sedation.

Additional file 3: Supplementary Table S2. Interview guide for Health care professionals.

Additional file 2: Supplementary Table S1. Interview guide for bereaved relatives of the patient.

Background Where it has been determined that a resident in a nursing home living with dementia loses decisional capacity, nursing home staff must deliver care that is in the person's best interests. Ideally, decisions should be made involving those close to the person, typically a family carer and health and social care providers. The aim of the Family Carer Decisional Support intervention is to inform family carers on end-of-life care options for a person living with advanced dementia and enable them to contribute to advance care planning. This implementation study proposes to; 1) adopt and apply the intervention internationally; and, 2) train nursing home staff to deliver the family carer decision support intervention. Methods This study will employ a multiple case study design to allow an understanding of the implementation process and to identify the factors which determine how well the intervention will work as intended. We will enrol nursing homes from each country (Canada n = 2 Republic of Ireland = 2, three regions in the UK n = 2 each, The Netherlands n = 2, Italy n = 2 and the Czech Republic n = 2) to reflect the range of characteristics in each national and local context. The RE-AIM (reach, effectiveness, adoption, implementation, maintenance) framework will guide the evaluation of implementation of the training and information resources. Our mixed methods study design has three phases to (1) establish knowledge about the context of implementation, (2) participant baseline information and measures and (3) follow up evaluation. Discussion The use of a multiple case study design will enable evaluation of the intervention in different national, regional, cultural, clinical, social and organisational contexts, and we anticipate collecting rich and in-depth data. While it is hoped that the intervention resources will impact on policy and practice in the nursing homes that are recruited to the study, the development of implementation guidelines will ensure impact on wider national policy and practice. It is our aim that the resources will be sustainable beyond the duration of the study and this will enable the resources to have a longstanding relevance for future advance care planning practice for staff, family carers and residents with advanced dementia.

Background The C19-YRS is the literature's first condition-specific, validated scale for patient assessment and monitoring in Post-COVID-19 syndrome (PCS). The 22-item scale's subscales (scores) are symptom severity (0–100), functional disability (0–50), additional symptoms (0–60), and overall health (0–10). Objectives This study aimed to test the scale's psychometric properties using Rasch analysis and modify the scale based on analysis findings, emerging information on essential PCS symptoms, and feedback from a working group of patients and professionals. Methods Data from 370 PCS patients were assessed using a Rasch Measurement Theory framework to test model fit, local dependency, response category functioning, differential item functioning, targeting, reliability, and unidimensionality. The working group undertook iterative changes to the scale based on the psychometric results and including essential symptoms. Results Symptom severity and functional disability subscales showed good targeting and reliability. Post hoc rescoring suggested that a 4-point response category structure would be more appropriate than an 11-point response for both subscales. Symptoms with binary responses were placed in the other symptoms subscale. The overall health single-item subscale remained unchanged. Conclusion A 17-item C19-YRSm was developed with subscales (scores): symptom severity (0–30), functional disability (0–15), other symptoms (0–25), and overall health (0–10).

Objective Evaluate serum and urine biomarker panels for their capabilities in discriminating between individuals (13- to 34-years-olds) with healthy hips versus those with developmental dysplasia of the hip (DDH) prior to diagnosis of secondary hip osteoarthritis (OA). Design Urine and serum were collected from individuals (15-33 years old) with DDH, prior to and following diagnosis of hip OA, and from age-matched healthy-hip controls. Samples were analyzed for panels of protein biomarkers with potential for differentiation of hip status using receiver operator characteristic curve (area under curve [AUC]) assessments. Results Multiple urine and serum biomarker panels effectively differentiated individuals with DDH from healthy-hip controls in a population at risk for developing secondary hip OA with the best performing panel demonstrating an AUC of 0.959. The panel comprised of two serum and two urinary biomarkers provided the highest combined values for sensitivity, 0.85, and specificity, 1.00, while a panel of four serum biomarkers provided the highest sensitivity, 0.93, while maintaining adequate specificity, 0.71. Conclusion Results of this study indicate that panels of protein biomarkers measured in urine and serum may be able to differentiate young adults with DDH from young adults with healthy hips. These data suggest the potential for clinical application of a routine diagnostic method for cost-effective and timely screening for DDH in at-risk populations. Further development and validation of these biomarker panels may result in highly sensitive and specific tools for early diagnosis, staging, and prognostication of DDH, as well as treatment decision making and monitoring capabilities. Level of Evidence: III

Medium-chain esters are versatile chemicals with broad applications as flavors, fragrances, solvents, and potential drop-in biofuels. Currently, these esters are largely produced by the conventional chemical process that uses harsh operating conditions and requires high energy input. Alternatively, the microbial conversion route has recently emerged as a promising platform for sustainable and renewable ester production. The ester biosynthesis pathways can utilize either lipases or alcohol acyltransferase (AAT), but the AAT-dependent pathway is more thermodynamically favorable in an aqueous fermentation environment. Even though a cellulolytic thermophile Clostridium thermocellum harboring an AAT-dependent pathway has recently been engineered for direct conversion of lignocellulosic biomass into esters, the production is not efficient. One potential bottleneck is the ester degradation caused by the endogenous carbohydrate esterases (CEs) whose functional roles are poorly understood. The challenge is to identify and disrupt CEs that can alleviate ester degradation while not negatively affecting the efficient and robust capability of C. thermocellum for lignocellulosic biomass deconstruction. In this study, by using bioinformatics, comparative genomics, and enzymatic analysis to screen a library of CEs, we identified and disrupted the two most critical CEs, Clo1313_0613 and Clo1313_0693, that significantly contribute to isobutyl acetate degradation in C. thermocellum. We demonstrated that an engineered esterase-deficient C. thermocellum strain not only reduced ester hydrolysis but also improved isobutyl acetate production while maintaining effective cellulose assimilation.

Background Missing data are common in end-of-life care studies, but there is still relatively little exploration of which is the best method to deal with them, and, in particular, if the missing at random (MAR) assumption is valid or missing not at random (MNAR) mechanisms should be assumed. In this paper we investigated this issue through a sensitivity analysis within the ACTION study, a multicenter cluster randomized controlled trial testing advance care planning in patients with advanced lung or colorectal cancer. Methods Multiple imputation procedures under MAR and MNAR assumptions were implemented. Possible violation of the MAR assumption was addressed with reference to variables measuring quality of life and symptoms. The MNAR model assumed that patients with worse health were more likely to have missing questionnaires, making a distinction between single missing items, which were assumed to satisfy the MAR assumption, and missing values due to completely missing questionnaire for which a MNAR mechanism was hypothesized. We explored the sensitivity to possible departures from MAR on gender differences between key indicators and on simple correlations. Results Up to 39% of follow-up data were missing. Results under MAR reflected that missingness was related to poorer health status. Correlations between variables, although very small, changed according to the imputation method, as well as the differences in scores by gender, indicating a certain sensitivity of the results to the violation of the MAR assumption. Conclusions The findings confirmed the importance of undertaking this kind of analysis in end-of-life care studies.

Purpose To provide an initial characterization of relevant bacterial DNA profiles for patients undergoing closed-fracture fixation or total joint arthroplasties. Patients and methods Swabs were collected and analyzed using Polymerase Chain Reaction from adult patients undergoing closed-fracture fixation or total shoulder, knee, or hip arthroplasties. Results Bacterial DNA profiles varied across the different orthopaedic patient populations, and produced uncharacteristic profile shifts with direct relevance to each clinical infection. Conclusion Findings provide a foundational dataset regarding bacterial colonization of relevant anatomic sites that can act as sources of surgical site infections for patients.

Non-overlapping cell populations within dorsomedial prefrontal cortex (dmPFC), defined by gene expression or projection target, control dissociable aspects of reward seeking through unique activity patterns. However, even within these defined cell populations, considerable cell-to-cell variability is found, suggesting that greater resolution is needed to understand information processing in dmPFC. Here, we use two-photon calcium imaging in awake, behaving mice to monitor the activity of dmPFC excitatory neurons throughout Pavlovian reward conditioning. We characterize five unique neuronal ensembles that each encodes specialized information related to a sucrose reward, reward-predictive cues, and behavioral responses to those cues. The ensembles differentially emerge across daily training sessions – and stabilize after learning – in a manner that improves the predictive validity of dmPFC activity dynamics for deciphering variables related to behavioral conditioning. Our results characterize the complex dmPFC neuronal ensemble dynamics that stably predict reward availability and initiation of conditioned reward seeking following cue-reward learning.