The Family Anesthesia Experience (FAX): Implementing a Social Support-Focused Wellness Programme Across Multiple Residency Programmes.

Introduction: Lack of social support negatively impacts medical trainees' wellness. Programmes to educate medical trainees and their support persons (SPs) have been developed to improve resident wellness, but implementation of these programmes at other institutions remains unclear. We aimed to demonstrate the feasibility of implementing the Family Anesthesia Experience (FAX) programme across multiple institutions and to assess the programme's utility.

Exploration of histone protein γ-H2AX as a prognostic factor in soft tissue sarcomas and its association with biological behavior, immune cell environment and survival in leiomyosarcoma.

This study evaluates the H2AX/γ-H2AX expression in soft tissue sarcomas (STS), its implications for biological behavior and immune environment, and its potential as a prognostic biomarker. RNA-Seq data from 237 STS were obtained from The Cancer Genome Atlas project. Patients were stratified by H2AX mRNA expression using a survival-associated cutoff.

Assessing the efficacy and safety of STOP (successful treatment for paranoia)-an app-based cognitive bias modification therapy for paranoia: a randomised clinical trial protocol.

Background: Paranoia, the belief that you are at risk of significant physical or emotional harm from others, is a common difficulty, which causes significant distress and impairment to daily functioning, including in psychosis-spectrum disorders. According to cognitive models of psychosis, paranoia may be partly maintained by cognitive processes, including interpretation biases. Cognitive bias modification for paranoia (CBM-pa) is an intervention targeting the bias towards interpreting ambiguous social scenarios in a way that is personally threatening.

On-site electronic consent in pediatrics using generic Informed Consent Service (gICS): Creating a specialized setup and collecting consent data.

Enrolling in a clinical trial or study requires informed consent. Furthermore, it is crucial to ensure proper consent when storing samples in biobanks for future research, as these samples may be used in studies beyond their initial purpose. For pediatric studies, consent must be obtained from both the child and their legal guardians, requiring the recording of multiple consents at once.

Balancing accuracy and Interpretability: An R package assessing complex relationships beyond the Cox model and applications to clinical prediction.

Background: Accurate and interpretable models are essential for clinical decision-making, where predictions can directly impact patient care. Machine learning (ML) survival methods can handle complex multidimensional data and achieve high accuracy but require post-hoc explanations. Traditional models such as the Cox Proportional Hazards Model (Cox-PH) are less flexible, but fast, stable, and intrinsically transparent.

Donning the : Enchanting the Ill and Pregnant Body in Art.

The hospital gown is a particularly charged article of clothing. For the chronically ill and disabled, the ritual of donning the gown signals a change of identity from "person" to "patient." This essay chronicles the metamorphosis of a standard hospital gown into a work of wearable art that showcases the glittering pregnant body.

Scans and Prints.

This essay reflects on occasions when images of the author's body stirred wonder and challenged the author's understanding of her relationship to her body. Wonder is not a sentimental or romantic feeling, but an intermingling of both admiration and fear. Wonder is perhaps closest to awe, which has connotations of both reverence and terror.

New horizons in prediction modelling using machine learning in older people's healthcare research.

Machine learning (ML) and prediction modelling have become increasingly influential in healthcare, providing critical insights and supporting clinical decisions, particularly in the age of big data. This paper serves as an introductory guide for health researchers and readers interested in prediction modelling and explores how these technologies support clinical decisions, particularly with big data, and covers all aspects of the development, assessment and reporting of a model using ML. The paper starts with the importance of prediction modelling for precision medicine.

Developing a process for assessing the safety of a digital mental health intervention and gaining regulatory approval: a case study and academic's guide.

Background: The field of digital mental health has followed an exponential growth trajectory in recent years. While the evidence base has increased significantly, its adoption within health and care services has been slowed by several challenges, including a lack of knowledge from researchers regarding how to navigate the pathway for mandatory regulatory approval. This paper details the steps that a team must take to achieve the required approvals to carry out a research study using a novel digital mental health intervention.

Origin of biogeographically distinct ecotypes during laboratory evolution.

Resource partitioning is central to the incredible productivity of microbial communities, including gigatons in annual methane emissions through syntrophic interactions. Previous work revealed how a sulfate reducer (Desulfovibrio vulgaris, Dv) and a methanogen (Methanococcus maripaludis, Mm) underwent evolutionary diversification in a planktonic context, improving stability, cooperativity, and productivity within 300-1000 generations. Here, we show that mutations in just 15 Dv and 7 Mm genes within a minimal assemblage of this evolved community gave rise to co-existing ecotypes that were spatially enriched within a few days of culturing in a fluidized bed reactor.

[Integration of Inventory Data from Cohort and Registry Studies into an Existing Research Network: National Pandemic Cohort Network (NAPKON)].

In the early phase of the COVID-19 pandemic, many local collections of clinical data on patients infected with SARS-CoV-2 were initiated in Germany. As part of the National Pandemic Cohort Network (NAPKON) of the University Medicine Network, the "Integration Core" was established to design the legal, technical and organisational requirements for the integration of inventory data into ongoing prospective data collections and to test the feasibility of the newly developed solutions using use cases (UCs). Detailed study documents of the data collections were obtained.

Reducing self-harm in adolescents: the RISA-IPD individual patient data meta-analysis and systematic review.

Background: Self-harm is common in adolescents and a major public health concern. Evidence for effective interventions is lacking. An individual patient data meta-analysis has the potential to provide more reliable estimates of the effects of therapeutic interventions for self-harm than conventional meta-analyses, to explore which treatments are best suited to certain groups.

Metaproteomics-informed stoichiometric modeling reveals the responses of wetland microbial communities to oxygen and sulfate exposure.

Climate changes significantly impact greenhouse gas emissions from wetland soil. Specifically, wetland soil may be exposed to oxygen (O) during droughts, or to sulfate (SO) as a result of sea level rise. How these stressors - separately and together - impact microbial food webs driving carbon cycling in the wetlands is still not understood.

A precise performance-based reimbursement model for the multi-centre NAPKON cohorts - development and evaluation.

Fair allocation of funding in multi-centre clinical studies is challenging. Models commonly used in Germany - the case fees ("fixed-rate model", FRM) and up-front staffing and consumables ("up-front allocation model", UFAM) lack transparency and fail to suitably accommodate variations in centre performance. We developed a performance-based reimbursement model (PBRM) with automated calculation of conducted activities and applied it to the cohorts of the National Pandemic Cohort Network (NAPKON) within the Network of University Medicine (NUM).

Dynamic and Transdiagnostic Risk Calculator Based on Natural Language Processing for the Prediction of Psychosis in Secondary Mental Health Care: Development and Internal-External Validation Cohort Study.

Background: Automatic transdiagnostic risk calculators can improve the detection of individuals at risk of psychosis. However, they rely on assessment at a single point in time and can be refined with dynamic modeling techniques that account for changes in risk over time.

Methods: We included 158,139 patients (5007 events) who received a first index diagnosis of a nonorganic and nonpsychotic mental disorder within electronic health records from the South London and Maudsley National Health Service Foundation Trust between January 1, 2008, and October 8, 2021.

Bridging the gap from medical to psychological safety assessment: consensus study in a digital mental health context.

Background: Digital Mental Health Interventions (DMHIs) that meet the definition of a medical device are regulated by the Medicines and Healthcare products Regulatory Agency (MHRA) in the UK. The MHRA uses procedures that were originally developed for pharmaceuticals to assess the safety of DMHIs. There is recognition that this may not be ideal, as is evident by an ongoing consultation for reform led by the MHRA and the National Institute for Health and Care Excellence.

The diversity and ecological significance of microbial traits potentially involved in B biosynthesis in the global ocean.

Cobalamin (B), an essential nutrient and growth cofactor for many living organisms on Earth, can be fully synthesized only by selected prokaryotes in nature. Therefore, microbial communities related to B biosynthesis could serve as an example subsystem to disentangle the underlying ecological mechanisms balancing the function and taxonomic make-up of complex functional assemblages. By anchoring microbial traits potentially involved in B biosynthesis, we depict the biogeographic patterns of B biosynthesis genes and the taxa harboring them in the global ocean, despite the limitations of detecting de novo B synthesizers via metagenomes alone.

A transdiagnostic prodrome for severe mental disorders: an electronic health record study.

Effective prevention of severe mental disorders (SMD), including non-psychotic unipolar mood disorders (UMD), non-psychotic bipolar mood disorders (BMD), and psychotic disorders (PSY), rely on accurate knowledge of the duration, first presentation, time course and transdiagnosticity of their prodromal stages. Here we present a retrospective, real-world, cohort study using electronic health records, adhering to RECORD guidelines. Natural language processing algorithms were used to extract monthly occurrences of 65 prodromal features (symptoms and substance use), grouped into eight prodromal clusters.

An integrated evaluation of bioenhanced in situ LNAPL dissolution.

Performance evaluation of in situ bioremediation processes in the field is difficult due to uncertainty created by matrix and contaminant heterogeneity, inaccessibility to direct observation, expense of sampling, and limitations of some measurements. The goal of this research was to develop a strategy for evaluating in situ bioremediation of light nonaqueous-phase liquid (LNAPL) contamination and demonstrating the occurrence of bioenhanced LNAPL dissolution by: (1) integrating a suite of analyses into a rational evaluation strategy; and (2) demonstrating the strategy's application in intermediate-scale flow-cell (ISFC) experiments simulating an aquifer contaminated with a pool of LNAPL (naphthalene dissolved in dodecane). Two ISFCs were operated to evaluate how the monitored parameters changed between a "no bioremediation" scenario and an "intrinsic in situ bioremediation" scenario.

Genomic and environmental controls on Castellaniella biogeography in an anthropogenically disturbed subsurface.

Castellaniella species have been isolated from a variety of mixed-waste environments including the nitrate and multiple metal-contaminated subsurface at the Oak Ridge Reservation (ORR). Previous studies examining microbial community composition and nitrate removal at ORR during biostimulation efforts reported increased abundances of members of the Castellaniella genus concurrent with increased denitrification rates. Thus, we asked how genomic and abiotic factors control the Castellaniella biogeography at the site to understand how these factors may influence nitrate transformation in an anthropogenically impacted setting.

Contribution of Microorganisms with the Clade II Nitrous Oxide Reductase to Suppression of Surface Emissions of Nitrous Oxide.

The sources and sinks of nitrous oxide, as control emissions to the atmosphere, are generally poorly constrained for most environmental systems. Initial depth-resolved analysis of nitrous oxide flux from observation wells and the proximal surface within a nitrate contaminated aquifer system revealed high subsurface production but little escape from the surface. To better understand the environmental controls of production and emission at this site, we used a combination of isotopic, geochemical, and molecular analyses to show that chemodenitrification and bacterial denitrification are major sources of nitrous oxide in this subsurface, where low DO, low pH, and high nitrate are correlated with significant nitrous oxide production.