Maternal Reports of Preterm and Sick Term Infants' Settling, Sleeping and Feeding in the 9 Months after Discharge from Neonatal Nursery: An Observational Study.

The effects of preterm birth, neonatal morbidities and environmental influences on infant sleep development is an important yet under-researched topic, with little known about normative sleep for infants born sick or preterm. The aim of this prospective, observational longitudinal study was to evaluate maternal perceptions and degree of bother with infant sleep behaviours and feeding outcomes across the first 9 months after discharge for sick/preterm infants cared for in the neonatal intensive care unit (NICU) and for healthy term-born infants. This paper reports outcomes for the sick/preterm cohort (I = 94) that were recruited from two NICUs in Perth, Western Australia. Total bother scores were on average 20.2% higher at 9 months than at two weeks post-discharge (p < 0.001). Increased night waking frequency, evening settling duration and crying duration were all positively associated with total bother scores. Maternal confidence scores were negatively associated with maternal bother scores; with each unit increase in confidence, maternal bother decreased by 8.5% (p < 0.001). Covariates such as birth gestation, breastfeeding status and multiple births were not associated with maternal bother. Families may benefit from additional support when experiencing increased night waking frequency and crying and settling durations in the first 9 months after discharge from NICU.

Implementation of an Electronic Clinical Decision Support System for the Early Recognition and Management of Dysglycemia in an Inpatient Mental Health Setting Using CogStack: Protocol for a Pilot Hybrid Type 3 Effectiveness-Implementation Randomized Controlled Cluster Trial.

BACKGROUND: Severe mental illnesses (SMIs), including schizophrenia, bipolar affective disorder, and major depressive disorder, are associated with an increased risk of physical health comorbidities and premature mortality from conditions including cardiovascular disease and diabetes. Digital technologies such as electronic clinical decision support systems (eCDSSs) could play a crucial role in improving the clinician-led management of conditions such as dysglycemia (deranged blood sugar levels) and associated conditions such as diabetes in people with a diagnosis of SMI in mental health settings. OBJECTIVE: We have developed a real-time eCDSS using CogStack, an information retrieval and extraction platform, to automatically alert clinicians with National Health Service Trust-approved, guideline-based recommendations for dysglycemia monitoring and management in secondary mental health care. This novel system aims to improve the management of dysglycemia and associated conditions, such as diabetes, in SMI. This protocol describes a pilot study to explore the acceptability, feasibility, and evaluation of its implementation in a mental health inpatient setting. METHODS: This will be a pilot hybrid type 3 effectiveness-implementation randomized controlled cluster trial in inpatient mental health wards. A ward will be the unit of recruitment, where it will be randomly allocated to receive either access to the eCDSS plus usual care or usual care alone over a 4-month period. We will measure implementation outcomes, including the feasibility and acceptability of the eCDSS to clinicians, as primary outcomes, alongside secondary outcomes relating to the process of care measures such as dysglycemia screening rates. An evaluation of other implementation outcomes relating to the eCDSS will be conducted, identifying facilitators and barriers based on established implementation science frameworks. RESULTS: Enrollment of wards began in April 2022, after which clinical staff were recruited to take part in surveys and interviews. The intervention period of the trial began in February 2023, and subsequent data collection was completed in August 2023. Data are currently being analyzed, and results are expected to be available in June 2024. CONCLUSIONS: An eCDSS can have the potential to improve clinician-led management of dysglycemia in inpatient mental health settings. If found to be feasible and acceptable, then, in combination with the results of the implementation evaluation, the system can be refined and improved to support future successful implementation. A larger and more definitive effectiveness trial should then be conducted to assess its impact on clinical outcomes and to inform scalability and application to other conditions in wider mental health care settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT04792268; https://clinicaltrials.gov/study/NCT04792268. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/49548.

The NFκB Dif is required for behavioral and molecular correlates of sleep homeostasis in Drosophila.

The nuclear factor binding the κ light chain in B-cells (NFκB) is involved in a wide range of cellular processes including development, growth, innate immunity, and sleep. However, genetic studies of the role of specific NFκB transcription factors in sleep have been limited. Drosophila fruit flies carry three genes encoding NFκB transcription factors, Dorsal, Dorsal Immunity Factor (Dif), and Relish. We previously found that loss of the Relish gene from fat body suppressed daily nighttime sleep, and abolished infection-induced sleep. Here we show that Dif regulates daily sleep and recovery sleep following prolonged wakefulness. Mutants of Dif showed reduced daily sleep and suppressed recovery in response to sleep deprivation. Pan-neuronal knockdown of Dif strongly suppressed daily sleep, indicating that in contrast to Relish, Dif functions from the central nervous system to regulate sleep. Based on the unique expression pattern of a Dif- GAL4 driver, we hypothesized that its effects on sleep were mediated by the pars intercerebralis (PI). While RNAi knock-down of Dif in the PI reduced daily sleep, it had no effect on the recovery response to sleep deprivation. However, recovery sleep was suppressed when RNAi knock-down of Dif was distributed across a wider range of neurons. Induction of the nemuri (nur) antimicrobial peptide by sleep deprivation was reduced in Dif mutants and pan-neuronal overexpression of nur also suppressed the Dif mutant phenotype by significantly increasing sleep and reducing nighttime arousability. Together, these findings indicate that Dif functions from brain to target nemuri and to promote deep sleep.

Identification of a core transcriptional program driving the human renal mesenchymal-to-epithelial transition.

During kidney development, nephron epithelia arise de novo from fate-committed mesenchymal progenitors through a mesenchymal-to-epithelial transition (MET). Downstream of fate specification, transcriptional mechanisms that drive establishment of epithelial morphology are poorly understood. We used human iPSC-derived renal organoids, which recapitulate nephrogenesis, to investigate mechanisms controlling renal MET. Multi-ome profiling via snRNA-seq and ATAC-seq of organoids identified dynamic changes in gene expression and chromatin accessibility driven by activators and repressors throughout MET. CRISPR interference identified that paired box 8 (PAX8) is essential for initiation of MET in human renal organoids, contrary to in vivo mouse studies, likely by activating a cell-adhesion program. While Wnt/ß-catenin signaling specifies nephron fate, we find that it must be attenuated to allow hepatocyte nuclear factor 1-beta (HNF1B) and TEA-domain (TEAD) transcription factors to drive completion of MET. These results identify the interplay between fate commitment and morphogenesis in the developing human kidney, with implications for understanding both developmental kidney diseases and aberrant epithelial plasticity following adult renal tubular injury.

A systematic review of discrete choice experiments in stroke rehabilitation.

OBJECTIVES: Existing research qualitatively explores consumer preferences for stroke rehabilitation interventions. However, it remains unclear which intervention characteristics are most important to consumers, and how these preferences may influence uptake and participation. Discrete choice experiments (DCE) provide a unique way to quantitatively measure preferences for health and health care. This study aims to explore how DCEs have been used in stroke rehabilitation and to identify reported consumer preferences for rehabilitation interventions. MATERIAL AND METHODS: A systematic review of published stroke rehabilitation DCEs was completed (PROSPERO registration: CRD42021282578). Six databases (including CINAHL, MEDLINE, EconLIT) were searched from January 2000-March 2023. Data extracted included topic area, sample size, aim, attributes, design process, and preference outcomes. Descriptive and thematic analyses were conducted, and two methodological checklists applied to review quality. RESULTS: Of 2,446 studies screened, five were eligible. Studies focused on exercise preference (n = 3), the structure and delivery of community services (n = 1), and self-management programs (n = 1). All had small sample sizes (range 50-146) and were of moderate quality (average score of 77%). Results indicated people have strong preferences for one-to-one therapy (over group-based), light-moderate intensity of exercise, and delivery by qualified therapists (over volunteers). CONCLUSIONS: Few DCEs have been conducted in stroke rehabilitation, suggesting consumer preferences could be more rigorously explored. Included studies were narrow in the scope of attributes included, limiting their application to practice and policy. Further research is needed to assess the impact of differing service delivery models on uptake and participation.

Unbiased kidney-centric molecular categorization of chronic kidney disease as a step towards precision medicine.

Current classification of chronic kidney disease (CKD) into stages using indirect systemic measures (estimated glomerular filtration rate (eGFR) and albuminuria) is agnostic to the heterogeneity of underlying molecular processes in the kidney thereby limiting precision medicine approaches. To generate a novel CKD categorization that directly reflects within kidney disease drivers we analyzed publicly available transcriptomic data from kidney biopsy tissue. A Self-Organizing Maps unsupervised artificial neural network machine-learning algorithm was used to stratify a total of 369 patients with CKD and 46 living kidney donors as healthy controls. Unbiased stratification of the discovery cohort resulted in identification of four novel molecular categories of disease termed CKD-Blue, CKD-Gold, CKD-Olive, CKD-Plum that were replicated in independent CKD and diabetic kidney disease datasets and can be further tested on any external data at kidneyclass.org. Each molecular category spanned across CKD stages and histopathological diagnoses and represented transcriptional activation of distinct biological pathways. Disease progression rates were highly significantly different between the molecular categories. CKD-Gold displayed rapid progression, with significant eGFR-adjusted Cox regression hazard ratio of 5.6 [1.01-31.3] for kidney failure and hazard ratio of 4.7 [1.3-16.5] for composite of kidney failure or a 40% or more eGFR decline. Urine proteomics revealed distinct patterns between the molecular categories, and a 25-protein signature was identified to distinguish CKD-Gold from other molecular categories. Thus, patient stratification based on kidney tissue omics offers a gateway to non-invasive biomarker-driven categorization and the potential for future clinical implementation, as a key step towards precision medicine in CKD.

Alzheimer's disease-associated P460L variant of EphA1 dysregulates receptor activity and blood-brain barrier function.

INTRODUCTION: Genome-wide association studies link susceptibility to late-onset Alzheimer's disease (LOAD) with EphA1. Sequencing identified a non-synonymous substitution P460L as a LOAD risk variant. Other Ephs regulate vascular permeability and immune cell recruitment. We hypothesized that P460L dysregulates EphA1 receptor activity and impacts neuroinflammation. METHODS: EphA1/P460L receptor activity was assayed in isogenic Human Embryonic Kidney (HEK) cells. Soluble EphA1/P460L (sEphA1/sP460L) reverse signaling in brain endothelial cells was assessed by T-cell recruitment and barrier function assays. RESULTS: EphA1 and P460L were expressed in HEK cells, but membrane and soluble P460L were significantly reduced. Ligand engagement induced Y781 phosphorylation of EphA1 but not P460L. sEphA1 primed brain endothelial cells for increased T-cell recruitment; however, sP460L was less effective. sEphA1 decreased the integrity of the brain endothelial barrier, while sP460L had no effect. DISCUSSION: These findings suggest that P460L alters EphA1-dependent forward and reverse signaling, which may impact blood-brain barrier function in LOAD. HIGHLIGHTS: EphA1-dependent reverse signaling controls recruitment of T cells by brain endothelial cells. EphA1-dependent reverse signaling remodels brain endothelial cell contacts. LOAD-associated P460L variant of EphA1 shows reduced membrane expression and reduced ligand responses. LOAD-associated P460L variant of EphA1 fails to reverse signal to brain endothelial cells.

Prospective study design and data analysis in UK Biobank.

Population-based prospective studies, such as UK Biobank, are valuable for generating and testing hypotheses about the potential causes of human disease. We describe how UK Biobank's study design, data access policies, and approaches to statistical analysis can help to minimize error and improve the interpretability of research findings, with implications for other population-based prospective studies being established worldwide.

Exploring the Use of Digital Interventions by People with Severe Mental Illness to Support Their Physical Health: A Mixed Methods Study.

People with severe mental illness (SMI) are more likely to experience physical health conditions than the general population. Little is known about the experience of people with SMI using digital health interventions (DHIs) to support their physical health. We explored how people with SMI use DHIs to support their physical health, the acceptability, factors affecting use, and impact on physical health. This was a three-stage mixed methods study (1) online survey of people with SMI; (2) interviews with a subsample of participants from Stage 1; (3) stakeholder workshops. Participants were generally satisfied with the DHIs they used. The most popular DHIs were targeted at diet, exercise, and weight management. Factors that encouraged use included simplicity and data-linkage. Concerns included costs, data security, and reliability of information. Positive impacts included accountability and tangible physical health benefits. Mental health impacted engagement with DHIs. DHIs were seen as a useful tool to monitor physical health but could not replace contact with clinical services. DHIs were considered useful and acceptable by people with SMI and may be used as an extension of clinical care. The specific needs and priorities of people with SMI should be considered both in developing and recommending interventions.