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Qualitative evidence of service user experiences and perspectives on long-acting injectable buprenorphine for opioid treatment - a scoping review.

BACKGROUND: There is substantial literature on opioid treatment program (OTP) formulations and how they relate to the pharmacotherapy service user experience. As a newer formulation, less is known about service user experiences of long-acting injectable buprenorphine (LAIB). The aim of this scoping review is to map the qualitative evidence and gaps in the literature on service user experiences and perspectives of LAIB. METHODS: Our search strategy included Medline, Embase, PsycINFO, CINAHL, Scopus and Web Science, and citation chaining, from January 2016 to June 2025. Studies were included if reporting qualitative descriptions of LAIB service user experiences of treatment for opioid dependence, inclusive of qualitative, mixed methods (description of qualitative data only), case reports and English language. Articles were screened by two reviewers. A living experience first author led the analysis using inductive coding and thematic analysis, to produce a descriptive summary of synthesised findings alongside key study characteristics and quality appraisal, adhering to the Systematic reviews and Meta-Analysis for Scoping Reviews (PRISMA-ScR) checklist. RESULTS: After screening 838 titles/abstracts and reviewing 150 full texts, 40 studies met the eligibility criteria. All were conducted in high income countries, principally the US (n=12); Australia (n=10); and England and Wales (n=9). We identified five themes: Navigating LAIB treatment; Embodied and relational effects of LAIB; Impact and role of the service provider; Narratives of harm reduction and recovery; Stigma and criminalisation. LAIB was commonly experienced as increasing convenience, stability and freedom from daily supervised dosing, enabling improved work, travel, privacy and social participation. Reduced clinic/dosing contact often lessened enacted stigma and treatment burden. However, experiences were heterogenous. Some participants described injection-site discomfort, uncertainty about dose adequacy, reduced flexibility once injected, and ambivalence about LAIB effects. There was inconsistency in LAIB service user reports on service connection, isolation and psychosocial support. Treatment experiences were strongly shaped by provider practices. CONCLUSIONS: Findings underscore the need for integrated, flexible, harm-reduction oriented and person-centred LAIB treatment models that prioritise choice, autonomy and therapeutic relationships to maximise benefit for service users. However, evidence of LAIB service user experiences is concentrated in high-income countries, and the absence of perspectives from low- and middle-income country settings represents a substantial gap in the evidence base.

LAIB

Implementing a novel digital health platform for self-management of postmenopausal osteoporosis: A qualitative study of user experiences, perspectives and implementation outcomes.

BACKGROUND: Osteoporosis self-management requires scalable support, and digital health platforms may meet this need. This study aimed to characterise the experiences and perspectives of postmenopausal women who participated in a 12-month randomised controlled trial (RCT) of a digital voice assistant (DVA) delivered osteoporosis self-management intervention, and to assess key implementation outcomes. METHODS: This was a qualitative analysis of interviews with postmenopausal women from the intervention arm (DVA group) of the RCT. The DVA program broadcast education videos, medication reminders, home-based exercise, nutrition advice and monthly quizzes through a DVA device. Semi-structured interviews were recorded, transcribed and managed in NVivo through reflexive thematic analysis, guided by the Practical Planning for Implementation and Scale-Up and Proctor's implementation outcome taxonomy frameworks. Evidence weighting summarised participant coverage and code density. RESULTS: Twenty-two of 25 (88%) DVA group participants completed semi-structured interviews. Thematic analysis identified seven themes mapped to Proctor's implementation outcomes. Evidence weighting indicated strong support for the intervention's appropriateness and acceptability, moderate support for its adoption, fidelity, feasibility and sustainability, and limited support for costs. Participants valued clear audiovisual guidance, conversation-based interactions with natural language, and flexible home-based access to self-management. CONCLUSION: Digital health platforms for osteoporosis self-management appear feasible, acceptable and sustainable among postmenopausal women. Findings indicate that these platforms are approaching readiness for evaluation in implementation-focused settings, contingent on streamlined content, reliable delivery modalities, accessible user support, clear privacy regulations and pragmatic pricing models.

Humans

Associations between smart infusion pump-electronic health record interoperability and healthcare outcomes: A systematic review.

OBJECTIVE: This study synthesized available evidence on the associations between smart infusion pump-electronic health record (EHR) interoperability and healthcare outcomes. METHODS: A systematic review of PubMed, CINAHL, Embase, and Scopus databases identified 901 records, which were imported into Rayyan® for duplicate removal, independent screening by three reviewers, and resolution of discrepancies. Eligible studies were peer-reviewed, data-driven, and reported associations between smart infusion pump-EHR interoperability and healthcare outcomes. Studies focused solely on technical validation or interoperability prototypes were excluded. A backward citation search identified additional studies. Two reviewers independently extracted and cross-validated study characteristics using standardized templates. Methodological quality was assessed with the Joanna Briggs Institute Critical Appraisal Tools. RESULTS: Twenty records of 14 full-text studies and 6 conference proceedings were included. Most records reported positive associations between smart infusion pump-EHR interoperability and outcomes related to safety (e.g., medication administration errors, safety-reported events, pump alerts, and compliance with interoperability and drug library), operational efficiency (e.g., programming and documentation time and technical issues), financial performance (e.g., charges captured, and cost avoided), and user experience domains. Most studies used observational designs, reflecting real-world interoperability implementations, where controlling confounding factors is challenging. Limited reporting of baseline characteristics, pump type, and sample sizes limited comparability across studies. CONCLUSIONS: Smart infusion pump-EHR interoperability was associated with improvements in patient safety, efficiency, charge capture, and user experience, with variable findings across studies. Future research should use rigorous methodologies and standardized measures, examine relationships across outcome domains, assess limitations of pump-EHR interoperability, and evaluate underexplored outcomes, including team communication, cognitive workload, and AI-enabled pumps. IMPLICATIONS FOR CLINICAL PRACTICE: Interoperability should be viewed as a component of a broader sociotechnical system, in which technology, user, workflow, clinical content, and organizational practices collectively determine overall effectiveness.

Humans

A framework for delivering real-time, instrument-relative navigation in transoral robotic surgery.

Transoral robotic surgery (TORS) is a minimally invasive, inside-out technique that, compared with traditional open approaches, provides fewer post-operative complications, shorter hospital stays, and improved survival for early-stage head and neck cancer. However, TORS is limited by its steep learning curve and poor visualization of deep tumor margins. This randomized crossover study evaluated a surgical navigation system's potential to enhance accuracy and user experience with real-time, instrument-relative feedback. Seven Teflon beads (d = 2.381 mm) were embedded at the tongue base of a porcine pharynx-and-larynx model. Tongue blade compression and retraction were applied to the model to mimic intraoperative tissue deformation, reproducing the anatomical shifts that occur relative to preoperative imaging. Eight participants used the da Vinci Surgical system to localize the beads by placing pins under two conditions: (a) preoperative computed tomography with no navigation; (b) model-based visual navigation with quantitative instrument-to-target metrics. Surgical accuracy was determined by calculating the target localization error (TLE, pin-to-bead Euclidean distance) and the angular error (AE, pin axis trajectory to bead). Accounting for training level and bead depth, surgical navigation reduced TLE by 5.44 mm (95% CI, 4.02-6.86 mm; p = 2.00e-11) and AE by 8.47 degrees (95% CI, 6.21-10.72 degrees; p = 5.17e-11). Impressions of the system were generally favorable using a 5-point Likert survey and task duration (p = 0.26) or cognitive workload via the NASA-Task Load Index (p = 0.22) were not significantly affected. The navigation system demonstrated translational promise, offering improved target localization accuracy and more consistent performance across experience levels, two critical determinants of surgical quality in TORS.

Robotic Surgical Procedures

Outcomes and effectiveness of decision aids for families affected by hereditary cancer syndromes: A scoping review.

PURPOSE: In the past 15 years, numerous decision aids (DAs) have been developed to assist families affected by hereditary cancer syndromes in decision-making for managing inheritance and cancer risk. We identified the range and characteristics of DAs, focusing on their development stage according to guideline recommendations, their outcomes, and effectiveness. METHODS: A comprehensive search was conducted in MEDLINE, EMBASE, Cochrane, CINAHL, and PsycINFO, along with manual searches. Eligible articles reported DAs for supporting families affected by hereditary cancer syndromes, published in English from inception to July 2024. Quality was assessed using the Mixed-Methods Appraisal Tool. RESULTS: From 15,066 records, 32 studies with a moderate risk of bias, reporting 23 unique DAs, were identified. Most DAs targeted women (69.6%) with hereditary breast and ovarian cancer syndrome (73.9%) in North America and Europe (81.3%), primarily supporting decisions on cancer risk-reduction strategies (56.5%) and genetic testing/counseling (47.8%). Only 4 DAs were consistent with guideline-recommended development process, including prototype development, alpha- and beta-testing. Development and alpha-testing outcomes included user experience, understandability, and psychological impact. Beta-testing evaluated decision-making capacity, quality of the decision-making process, psychological impact, and impact on decisions. DAs consistently improved decision-making capacity and quality of the decision-making process but showed variable effects on psychological outcomes and actual decision in risk management. CONCLUSION: DAs are underdeveloped for genetic, racial, or gender minorities, according to guideline-recommended development process. Future research should develop DAs for broader populations and clarify their effectiveness, particularly regarding psychological outcomes.

Humans

Cost-Effectiveness of Electronic Patient-Reported Outcome Measure Interventions in Cancer: Systematic Review and Parameter Extraction for Economic Modeling.

BACKGROUND: Complex digital interventions that integrate electronic patient-reported outcome measures (ePROM) into clinical practice in cancer have the potential to improve quality of life, increase survival, and reduce health resource use and costs. Such systems can help patients with cancer self-manage chemotherapy symptoms, reduce clinicians' workloads through automated decision support, and resolve problems earlier. However, more research on the cost-effectiveness of ePROM monitoring is needed. OBJECTIVE: This paper comprises two complementary components: (1) a systematic literature review summarizing and evaluating the quantitative and qualitative evidence related to the cost-effectiveness of ePROM monitoring and (2) a health economic model parameter extraction. We also conducted supplementary targeted searches and scoping to provide context to our findings. METHODS: We searched Ovid (including MEDLINE and Embase), Scopus, and the International Health Technology Assessment Database for original English-language papers published on or before March 2025 using search strings that combined terms related to ePROMs, health economics, and cancer/oncology. We included papers reporting health economic-related outcomes for ePROM interventions designed for adult cancer populations and excluded screening tools and conference abstracts. RESULTS: We included 34 publications from 27 unique studies and identified and analyzed 26 ePROM-integrated interventions within these. Most (23/26) of the included interventions explicitly described some form of alert handling and automated decision support based on remote ePROM monitoring. Of the 34 publications, 5 presented full cost-effectiveness analysis results, of which 3 were highly uncertain and lacked clear differences in costs and health outcomes between ePROMs and standard care; conversely, 2 presented strong evidence of cost-effectiveness due to quality-of-life improvements, reduced hospitalizations, and potentially more autonomy in health-related travel (eg, ePROM-monitored patients can drive or walk to the hospital instead of using taxis or ambulances). A further 5 publications reported partial health economic results (eg, cost-consequence and budget impact), of which 1 detected no difference in strategies; in contrast, 4 reported lower health resource use and costs of ePROMs, mainly due to hospitalization reductions. Overall, 12 of the 27 studies included a qualitative component but mostly focused on user experience and design-related themes; only 2 of these addressed economic-specific themes (eg, changes in workflow and resource use due to ePROM implementation and integration), indicating some potential for time saving due to ePROM monitoring. CONCLUSIONS: Some ePROM-integrated interventions demonstrated cost-effectiveness in cancer care, but the evidence base remains limited. Where evidence does exist, cost-effectiveness appears driven by reduced hospitalization and improved quality of life. Qualitative research within the included studies rarely addressed economic questions. We provide a detailed parameter extraction for use in future economic modeling and recommend research priorities, including quantitative mapping of ePROM symptom data onto health resource use patterns, and qualitative work exploring how ePROM implementation affects clinical workloads and patient-perspective costs.

Humans

Surveilled subjectivation: narratives of drug policing among people who use prohibited drugs in Sweden.

In Sweden, possession and personal use of drugs are criminalized since 1988, resulting in police work being directed towards minor drug offenses. Despite this, police and other authorities are encouraged to protect the health and wellbeing of people who use prohibited drugs (PWUPD). Knowledge is scarce on how this drug policy plays out in practice. This study therefore analyzes interviews with 20 PWUPD who visited harm reduction services and interacted with policing agents in Stockholm, Sweden. The analysis is based on the participants' narratives of drug policing, and it concerns how they produced themselves as subjects through relations between materiality and discourse. We utilize the concept of surveilled subjectivation to elucidate what the participants could do, what they knew and who they could be or become under drug policing. Four themes were identified illustrating the link between discourse and materiality in PWUPD's surveilled subjectivation: "Material aspects of surveillance"; "Resisting the 'drug abuser' identity"; "Fighting power with power"; and "Crossing boundaries and becoming-other". The participants described nonstop efforts to prevent their bodies, activities, belongings and environments from being enfolded by drug law enforcement, which otherwise would fuel even more surveillance. They therefore disassociated themselves from the "drug abuser" identity, and managed encounters with policing agents by keeping a low profile or acting compliantly. While the study highlights the skills and knowledges the participants deployed to navigate omnipresent drug policing, we conclude that their production of autonomous and empowered subjectivities would be facilitated if possession and use of drugs were no longer criminalized.

Humans

The Soundtrack of Everyday Life: Real-world Music Listening Habits of Adult Cochlear Implant Users.

OBJECTIVE: Characterize real-world patterns of music listening and reward sensitivity among adult cochlear implant (CI) users compared with normal-hearing (NH) listeners. STUDY DESIGN: Cross-sectional observational study. SETTING: Online. PATIENTS: Adults (&#x2265;18&#xa0;y) with a CI or NH who used a music-streaming platform as their primary listening method. INTERVENTIONS: None. MAIN OUTCOME MEASURES: Objective measures included platform-derived audio features (acousticness, danceability, energy, tempo, and valence), listening volume, unique-song ratio, and decade preferences. Self-reported measures included listening habits and the Barcelona Music Reward Questionnaire (BMRQ). Group comparisons used ANCOVAs and mixed-effect models adjusting for age and gender; within-CI analyses compared prelingual versus postlingual deafness. RESULTS: Among 16 CI users (69% male, 39.0&#xb1;15.6&#xa0;y) and 29 NH listeners (38% male, 32.2&#xb1;11.3&#xa0;y), CI users demonstrated a higher unique-song ratio (&#x3b2;=-0.157, CI as reference; 95%CI [-0.281, -0.034]; P =0.014) and stronger preference for older music (Pillai trace=0.537; F8,35 =5.07; P <0.001), adjusting for age. No significant group differences were observed in weekly listening time, listening volume, audio features, or BMRQ scores (total and subscores). Equivalence was confirmed for Emotion Evocation and Sensory-Motor subscales. There were no statistically significant differences in listening environments after Holm correction. No statistically detectable differences were observed between pre- and postlingually deafened CI users. CONCLUSIONS: Musically active CI users showed no significant differences in listening volume or overall music-reward sensitivity compared with NH peers, but demonstrated higher unique-song ratios and a bias toward older music. Findings highlight the value of ecologically valid data in understanding real-world music experiences among CI users.

Adult

From complexity to clarity: Building dashboards for hit selection in high throughput screens.

High throughput screening produces large, complex datasets that are difficult to interrogate without programming expertise, making hit selection time-consuming and inflexible. While instrument software and commercial tools offer partial solutions, they often lack adaptability or require costly infrastructure. Interactive dashboards provide an effective alternative by enabling dynamic filtering and integrated visualization within a single interface. Here, we present simple R Markdown-based templates for creating customizable, modular dashboards for screen data analysis. Built using the flexdashboard and crosstalk R packages, and HTML widgets, these lightweight, easy-to-build HTML dashboards require no complex installation process or installation of licensed software. They support linked visualizations, threshold-based filtering (e.g., Z-score, p-value, fold change), and interactive data exploration and are shared as a standalone HTML file. This framework enables rapid, flexible hit selection across diverse high throughput screening applications and is designed for users with basic R experience.

High-Throughput Screening Assays

scSNViz: visualization and analysis of cell-specific expressed SNVs.

MOTIVATION: Accurately characterizing expressed genetic variation at the single-cell level is essential for understanding transcriptional heterogeneity, allelic regulation, and mutational dynamics within complex tissues. However, few tools enable comprehensive visualization and quantitative analysis of expressed variants across individual cells. RESULTS: scSNViz is an R package for the exploration, quantification, and visualization of expressed single-nucleotide variants (SNVs) from cell-barcoded single-cell RNA sequencing (scRNA-seq) data. The software supports estimation of variant allele fractions, clustering of SNV expression profiles, and 2D and 3D visualization of individual SNVs or user-defined SNV groups. Beyond visualization, scSNViz facilitates investigation of cell-, cluster-, or lineage-specific variant expression patterns, as well as allelic dynamics including imprinting, random allele inactivation, and transcriptional bursting. It interoperates seamlessly with established single-cell frameworks-Seurat for clustering, Slingshot for trajectory inference, scType for cell-type annotation, and CopyKat for copy-number profiling-enabling integrative multi-omic analyses of expressed variation. AVAILABILITY AND IMPLEMENTATION: scSNViz is implemented in R and freely available at https://github.com/HorvathLab/scSNViz (DOI: 10.5281/zenodo.17307516). The package includes comprehensive documentation and example workflows designed for users with limited bioinformatics experience.

Software

PYRAMA: an open-source tool for advanced meta-analysis of genome wide association studies.

MOTIVATION: Genome-wide association study (GWAS) meta-analysis tools are essential for integrating summary statistics across multiple cohorts, thereby increasing statistical power and validating genetic associations. Widely cited tools, such as METAL, PLINK, and GWAMA, have facilitated numerous significant discoveries in the field of GWAS. Nevertheless, these tools offer a limited set of meta-analysis methods and typically require users to have prior experience with command-line tools to be executed. RESULTS: We present here PYRAMA, an open-source tool which is designed for meta-analysis of genome wide association studies. This work introduces an easy-to-use software package that includes several meta-analysis methods that are absent in similar software packages. PYRAMA is faster compared to other tools, supports robust methods for analysis and meta-analysis, fixed-effects, random-effects and Bayesian meta-analysis and it is currently the only tool that supports meta-analysis with imputation of summary statistics. It is available both as a standalone tool and as a freely available web server. AVAILABILITY AND IMPLEMENTATION: https://github.com/pbagos/PYRAMA, https://doi.org/10.5281/zenodo.17830449.

Genome-Wide Association Study

AutoPVPrimer: A comprehensive AI-Enhanced pipeline for efficient plant virus primer design and assessment.

Plant viruses pose a significant threat to global agriculture and require efficient tools for their timely detection. We present AutoPVPrimer, an innovative pipeline that integrates artificial intelligence (AI) and machine learning to accelerate the development of plant virus primers. The pipeline uses Biopython to automatically retrieve different genomic sequences from the NCBI database to increase the robustness of the subsequent primer design. The design_primers_with_tuning module uses a random forest classifier that optimizes parameters and provides flexibility for different experimental conditions. Quality control measures, including the evaluation of poly-X content and melting temperature, increase primer reliability. Unique to AutoPVPrimer is the visualize_primer_dimer module, which supports the visual evaluation of primer dimers-a feature missing in other tools. Primer specificity is validated via primer BLAST, which contributes to the overall efficiency of the pipeline. AutoPVPrimer has been successfully applied to the tomato mosaic virus, proving its adaptability and efficiency. The modular design allows customization by the user and extends the applicability to different plant viruses and experimental scenarios. The pipeline represents a significant advance in primer design and provides researchers with an effective tool to accelerate molecular biology experiments. Future developments aim to extend compatibility and incorporate user feedback to consolidate AutoPVPrimer as an innovative contribution to the bioinformatics toolbox and a promising resource for the advancement of plant virology research.

DNA Primers

Plotgardener App: a graphical interface for publication-ready genomic visualization.

SUMMARY: Plotgardener is an R package used for generating high-quality genomic visualizations. Despite its broad range of functions and versatility, its reliance on code presents a barrier for many potential users. To address this, we developed a macOS desktop application version of Plotgardener that enables users to create publication-ready genomic plots with no programming experience. The application employs a modular architecture comprising an Electron.js backend, a React frontend, and a Python parser that dynamically analyzes the Plotgardener package to ensure interface fields remain synchronized with package updates. By lowering the technical barrier to advanced genomic visualization, the Plotgardener desktop application broadens access to powerful visualization workflows for researchers and clinicians. AVAILABILITY: The current release of the Plotgardener App is an open source macOS desktop application built with Electron (Node.js), featuring a React frontend and a Python-based parser. The download link is available at https://phanstiellab.github.io/plotgardener/articles/guides/plotgardenerApp.html and on Zenodo (doi: https://doi.org/10.5281/zenodo.21684228). The source code is hosted on GitHub at https://github.com/rishabhsvemuri/ThePlotgardenerApp.

Genomics

CountASAP: a lightweight, easy to use python package for processing ASAPseq data.

BACKGROUND: Declining sequencing costs coupled with the increasing availability of easy-to-use kits for the isolation of DNA and RNA transcripts from single cells have driven a rapid proliferation of studies centered around genomic and transcriptomic data. Simultaneously, a wealth of new techniques have been developed that utilize single cell technologies to interrogate a broad range of cell-biological processes. One recently developed technique, transposase-accessible chromatin with sequencing (ATAC) with select antigen profiling by sequencing (ASAPseq), provides a combination of chromatin accessibility assessments with measurements of cell-surface marker expression levels. While software exists for the characterization of these datasets, there currently exists no tool explicitly designed to reformat ASAP surface marker FASTQ data into a count matrix which can then be used for these downstream analyses. RESULTS: To address this lack of a dedicated tool for ASAPseq data processing, we created CountASAP, an easy-to-use Python package purposefully designed to transform FASTQ files from ASAP experiments into count matrices compatible with commonly-used downstream bioinformatic analysis packages. CountASAP takes advantage of the independence of the relevant data structures to perform fully parallelized matches of each sequenced read to user-supplied input ASAP oligos and unique cell-identifier sequences. We directly compare the performance and user-friendliness of CountASAP to existing tools using similarly-structured data from a more common sequencing experiment: cellular indexing of transcriptomes and epitopes by sequencing (CITEseq). Further benchmarking against existing tools helps to identify proper defaults for CountASAP and assess the agreement of outputs from all tested software. A final test using a novel ASAPseq dataset provides evidence that CountASAP can generate biologically meaningful results that correlate well with paired chromatin accessibility data. CONCLUSIONS: CountASAP shows good agreement with existing, well-tested data processing tools in the analysis of similarly-structured benchmarking data. CountASAP runs efficiently on a standard laptop, has user-friendly documentation, a one-step installation, and represents the first and only tool designed specifically for the processing of ASAPseq data.

Software

RNAcare: integrating clinical data with transcriptomic evidence using rheumatoid arthritis as a case study.

BACKGROUND: Gene expression analysis is a crucial tool for uncovering the biological mechanisms that underlie differences between patient subgroups, offering insights that can inform clinical decisions. However, despite its potential, gene expression analysis remains challenging for clinicians due to the specialised skills required to access, integrate, and analyse large datasets. Existing tools primarily focus on RNA-Seq data analysis, providing user-friendly interfaces but often falling short in several critical areas: they typically do not integrate clinical data, lack support for patient-specific analyses, and offer limited flexibility in exploring relationships between gene expression and clinical outcomes in disease cohorts. Users, including clinicians with a general knowledge of transcriptomics, however, who may have limited programming experience, are increasingly seeking tools that go beyond traditional analysis. To overcome these issues, computational tools must incorporate advanced techniques, such as machine learning, to better understand how gene expression correlates with patient symptoms of interest. RESULTS: Our RNAcare platform, addresses these limitations by offering an interactive and reproducible solution specifically designed for analysing transcriptomic data from patient samples in a clinical context. This enables researchers to directly integrate gene expression data with clinical features, perform exploratory data analysis, and identify patterns among patients with similar diseases. By enabling users to integrate transcriptomic and clinical data, and customise the target label, the platform facilitates the analysis of the relationships between gene expression and clinical symptoms like pain and fatigue. This allows users to generate hypotheses and illustrative visualisations/reports to support their research. As proof of concept, we use RNAcare to link inflammation-related genes to pain and fatigue in rheumatoid arthritis (RA) and detect signatures in the drug response group, confirming previous findings. CONCLUSION: We present a novel computational platform allowing the interpretation of clinical and transcriptomics data in real-time. The platform can be used for data generated by the user, such as the patient data presented here or using published datasets. The platform is available at https://rna-care.mvls.gla.ac.uk/ , and its source code is https://github.com/sii-scRNA-Seq/RNAcare/ .

Humans

Multichannel genomic recording of biological information with ENGRAM.

Molecular recording is an emerging paradigm for measuring biology over time. Enhancer-mediated genomic recording of activity in multiplex (ENGRAM) is a recently described synthetic biology circuit architecture that converts the transient activity of cis-regulatory elements (CREs) into stable genomic records that can be retrospectively recovered via DNA sequencing. Here we provide a step-by-step protocol for conducting ENGRAM experiments and analyzing the resulting data. We also describe key design considerations for ENGRAM recorders, summarize the strengths and limitations of ENGRAM, and highlight applications, including multiplex signal recording and high-throughput CRE screening. In contrast to other systems for DNA-based recording in mammalian systems, ENGRAM relies on prime editing-mediated insertions to record the activity of a given CRE, such that it is inherently multiplexable-for example, four-base-pair insertions can represent the activities of up to 256 distinct CREs. A further contrast lies with ENGRAM's compatibility with DNA Typewriter, which facilitates the capture of signal order. For users with basic skills in molecular biology, mammalian cell culture and DNA sequencing analysis, ENGRAM experiments can typically be completed within 5-6 weeks.

Genomics

Open Dialogue versus treatment as usual for adults presenting in crisis to mental health services in England (the ODDESSI Trial): a multisite cluster-randomised trial.

BACKGROUND: Open Dialogue is a person-centred, transdiagnostic model of mental health care that emphasises continuity, therapeutic relationships, and collaboration with the service user's social network. Open Dialogue is a service-wide approach to care involving network meetings with the service user, members of their social network, and usually two practitioners who support the network throughout the duration of care. In this cluster-randomised trial, we aimed to evaluate the clinical effectiveness of Open Dialogue versus treatment as usual for adults presenting in crisis to community mental health services in England. METHODS: This multicentre, parallel two-arm, cluster-randomised, controlled superiority trial was conducted in mental health services in five National Health Service trusts in London and the South of England. Clusters were defined at the level of primary care practices within service catchment areas. Participants were adults aged 18 years or older presenting in crisis to mental health services and registered with a practice within trial clusters. Randomisation was done at the cluster level (1:1), stratified by catchment area, and balanced on average general practice (GP) list size and Index of Multiple Deprivation (2015). The chief investigator, senior statistician, and assessors of the primary outcome were masked in the study. Participants either received Open Dialogue or treatment as usual, which refers to the functional team model currently implemented throughout English mental health services. The primary outcome was time (days) to first relapse following initial recovery from the index crisis censored at the end of the 2-year follow-up period. Participant-reported secondary outcomes were EuroQol Visual Analogue Scale, Social Provisions Scale, Lubben Social Network Scale, Questionnaire about the Process of Recovery, and the Client Satisfaction Questionnaire, measured at five timepoints over 2 years, and clinical measures were extracted from electronic health records. People with relevant lived experience were involved in the design and execution of the study. Fidelity to the model of care in Open Dialogue and treatment as usual, and adherence to the delivery of Open Dialogue, were measured prior to each site starting participant recruitment, then every 6 months thereafter until the final participant follow-up in that site. The trial was retrospectively registered (ISRCTN52653325) and is complete. FINDINGS: 185 general practices associated with six mental health Trusts across England were identified for screening. 105 practices were excluded, and 80 were included in cluster formation, forming 32 clusters that were randomly assigned (16 to treatment as usual and 16 to the Open Dialogue intervention). One mental health trust (two clusters) withdrew, resulting in five mental health trusts (30 clusters) participating in the trial. Between June 25, 2019, and Dec 9, 2021, 494 participants (266 [54%] female gender, 221 [45%] male gender, 341 [69%] White British) with a mean age of 38&#xb7;1 years (SD 13&#xb7;4) provided consent for study inclusion (223 in the treatment as usual group and 271 in the Open Dialogue group). Of these, 174 (78%) in the treatment as usual group and 225 (83%) in the Open Dialogue group recovered and had data enabling relapse determination; there was no significant difference between groups on the primary outcome of time to relapse following initial recovery (marginal hazard ratio 0&#xb7;95 [95% CI 0&#xb7;67-1&#xb7;32]). For secondary outcomes, Open Dialogue was associated with significantly lower probabilities of psychiatric inpatient admission and re-referral to crisis care or secondary mental health services, and with improvements in self-rated recovery, health-related quality of life, and satisfaction with services. There were no significant differences in social network quality or size. There were 386 serious adverse events (281 in the treatment as usual group and 105 in the Open Dialogue group); 376 (97%) were deemed to be unrelated to the intervention. INTERPRETATION: Open Dialogue did not reduce time to first relapse compared with treatment as usual, the primary outcome, but it reduced acute inpatient bed use, improved service user reported outcomes and experience, and there were no significant safety concerns. Further investigation is required to determine whether Open Dialogue can enhance the effectiveness and acceptability of crisis care and continuing care in community mental health services. FUNDING: National Institute for Health Research.

Humans

A method for authenticating the fidelity of Cryptococcus neoformans knockout collections.

Gene knockout (KO) strain collections are important tools for discovery in microbiology. Cryptococcus neoformans, a human fungal pathogen, has an available genome-wide gene deletion collection that is widely used by the research community. We uncovered mix-ups in the assembly of the commercially available C. neoformans deletion collection of ~4,700 unique strains acquired by our laboratory. Evidence supporting a mix-up includes RNAseq analysis that identified transcripts for the gene listed as the KO. The mystery was soon solved as this same KO strain lacked RNA transcripts for a different KO strain gene found in the same plate position in an earlier partial KO collection, suggesting a plate swap between two KO collections. Therefore, we developed a quick PCR assay to distinguish the two KO collections based on the size differences between their nourseothricin (NAT)-resistance cassettes, confirmed by genome sequencing. Here, we report that nine of the first 15 plates of the 42-plate our KN99&#x251; KO collection had been replaced with the corresponding plates from an earlier partial KO collection. We provide additional evidence that the remaining plates are correct, and the simple authentication method presented here serves as a quick check to identify similar mix-ups in the KO collections.IMPORTANCEGene KO strain collections are important tools for discovery in microbiology. The human fungal pathogen Cryptococcus neoformans has an available genome-wide deletion collection that is widely used by the research community. Here, we report that our KN99&#x251; collection is comprised of mixed plates from two independent KO libraries and present a simple authentication method that other investigators can use to distinguish the identities of these KO collections. Above all, this article serves as a reminder to users of the 2015 KO library collection to screen the plates before undertaking large phenotyping experiments.

Cryptococcus neoformans