Search PubMedSearch

SEARCH · Search PubMed

Results for “Aotearoa New Zealand”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

256 records · Page 3Linked to original sources

The cold case of state transition 7 (stt7) mutants of Chlamydomonas reinhardtii, solved by whole-genome sequencing.

The process of State Transitions (ST) corresponds to an STT7 kinase-driven redistribution of the transmembrane LHCII antenna proteins between Photosystem II (PSII) and Photosystem I (PSI), which results from changes in their phosphorylation state. For the past two decades, two LHCII-kinase mutants, stt7-1 and stt7-9, have been instrumental in the study of STs in Chlamydomonas reinhardtii, the former being a null mutant for the kinase but quasi-sterile in crosses, while the latter, although fertile, has a leaky phenotype. Using long-read sequencing, this study further characterized the genetic lesions of the stt7 mutant strains through whole-genome reconstruction and de novo chromosome assembly. In addition, two new stt7 null mutants were generated, one derived by crosses from the original stt7-1 and one obtained by Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated protein 9 (Cas9) technology. This work provides a comprehensive genomic characterization of the original stt7-1 null mutant, revealing extensive chromosomal rearrangements and high levels of aneuploidy, associated with increased cell size and meiotic dysfunction. Reassessment of their physiology and genetic backgrounds highlights the need for caution in interpreting genetic information. We thus produced more reliable null mutants for the LHCII-kinase, amenable to genetic crosses for the study of STs in a variety of genetic backgrounds.

Chlamydomonas reinhardtii

From fear to empowerment: the impact of employees AI awareness on workplace well-being - a new insight from the JD-R model.

PURPOSE: The primary purpose of the study was to explore the impact of health workers' awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in the literature. By examining this relationship through the lens of the Job demands-resources (JD-R) model, the study aimed to provide insights into how health workers' perceptions of AI integration in their jobs and careers could influence their informal learning behaviour and, consequently, their overall well-being in the workplace. The study's findings could inform strategies for supporting healthcare workers during technological transformations. DESIGN/METHODOLOGY/APPROACH: The study employed a quantitative research design using a survey methodology to collect data from 420 health workers across 10 hospitals in Ghana that have adopted AI technologies. The study was analysed using OLS and structural equation modelling. FINDINGS: The study findings revealed that health workers' AI awareness positively impacts their informal learning behaviour at the workplace. Again, informal learning behaviour positively impacts health workers' workplace well-being. Moreover, informal learning behaviour mediates the relationship between health workers' AI awareness and workplace wellbeing. Furthermore, employee learning orientation was found to strengthen the effect of AI awareness on informal learning behaviour. RESEARCH LIMITATIONS/IMPLICATIONS: While the study provides valuable insights, it is important to acknowledge its limitations. The study was conducted in a specific context (Ghanaian hospitals adopting AI), which may limit the generalizability of the findings to other healthcare settings or industries. Self-reported data from the questionnaires may be subject to response biases, and the study did not account for potential confounding factors that could influence the relationships between the variables. PRACTICAL IMPLICATIONS: The study offers practical implications for healthcare organizations navigating the digital transformation era. By understanding the positive impact of health workers' AI awareness on their informal learning behaviour and well-being, organizations can prioritize initiatives that foster a learning-oriented culture and provide opportunities for informal learning. This could include implementing mentorship programs, encouraging knowledge-sharing among employees and offering training and development resources to help workers adapt to AI-driven changes. Additionally, the findings highlight the importance of promoting employee learning orientation, which can enhance the effectiveness of such initiatives. ORIGINALITY/VALUE: The study contributes to the existing literature by addressing a relatively unexplored area - the impact of AI awareness on healthcare workers' well-being. While previous research has focused on the potential job displacement effects of AI, this study takes a unique perspective by examining how health workers' perceptions of AI integration can shape their informal learning behaviour and, subsequently, their workplace well-being. By drawing on the JD-R model and incorporating employee learning orientation as a moderator, the study offers a novel theoretical framework for understanding the implications of AI adoption in healthcare organizations.

Humans

Efficient homologous replacement and deletion of large genomic fragments through template-jumping prime editing in rice.

Homologous replacement of genomic sequences with large DNA fragments (> 100 bp) holds great potential for crop breeding, yet an efficient method to achieve such edits is lacking in plants. Here, in rice, we developed template-jumping prime editing (TJ-PE), a recently reported PE strategy for large targeted insertion, as an efficient tool for homologous replacement with DNA fragments ranging from dozens to hundreds of base pairs, and using TJ-PE, we replaced genomic fragments of up to 340 bp with homologous fragments of the same length. In addition, our TJ-PE tool also enabled precise deletion of 944- to 2024-bp fragments in rice, with efficiencies of up to 34.6% for c. 2000-bp precise deletions. Collectively, this study expands the editing scope of PE in rice and establishes TJ-PE as a generalist tool for precise deletion and replacement of large DNA fragments.

Oryza

Predictive evolutionary genomics: principles, validation, and practice.

Climate change and habitat loss are driving rapid evolutionary responses in populations world-wide, which creates an urgent need for evolutionary forecasting in conservation and agriculture. Such forecasting can be categorized into three time scales: trait-based models that use multivariate quantitative genetic equations to project correlated phenotypic responses up to c. 20 generations, allele-based analyses that model allele frequency dynamics up to 100 generations, and composite adaptation scores that aggregate many small effects to yield predictions across longer horizons. However, these approaches have remained largely disconnected. Here, we present a Bayesian framework that integrates these three complementary approaches for evolutionary prediction. Our framework combines genomic, phenotypic, and environmental data to yield probabilistic predictions with explicit uncertainty. We show how predictive evolutionary forecasts can be validated with experimental evolution, field experimentation, historical specimens, and reciprocal transplants. These validated forecasts can help advance conservation and agricultural programmes by helping predict which populations are at risk of future extinction, optimizing breeding programmes for future climates, and planning ecosystem management under environmental change. By supporting a shift towards more predictive approaches in evolutionary biology, this framework may help improve our ability to manage biodiversity and food security in a changing world.

Genomics

Mul-PheG2P: decoupled learning and prediction-space fusion enables robust and interpretable multi-phenotype genomic prediction.

Genomic prediction of multiple phenotypes is crucial in modern plant breeding; however, existing methods struggle with negative transfer and lack interpretability, particularly across high-dimensional small-sample data and diverse species. To address this, we propose Mul-PheG2P, a novel paradigm based on decoupled learning and predictive space fusion. It employs a two-stage design: first training phenotype-specific encoders using genetic data, then decoupling phenotype-specific learning from cross-phenotype aggregation via an interpretable prediction layer. Mul-PheG2P outperforms existing methods across diverse crop datasets, including maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum). It provides a multi-scale interpretability chain: at the macro level, it quantifies phenotypic contributions via attention-based weighting; at the micro level, Integrated Gradients reveal the genetic basis of predictions. Notably, the model successfully identified the CCT (CONSTANS, CO-like, and TOC) motif regulating photoperiodism and the SQUAMOSA (SQUAMOSA promoter binding protein) promoter for inflorescence development, confirming its ability to capture functional biological mechanisms. These results highlight the high performance and interpretability of Mul-PheG2P, showcasing its value for low-cost, large-scale screening to advance precision breeding.

Phenotype

Integrated multi-omics analyses identify an RAS-SLC11A2-associated molecular framework linking iron metabolism with PCOS-related cardiometabolic risk.

INTRODUCTION: PCOS is a common endocrine disorder with elevated cardiometabolic risk, yet the role of the renin-angiotensin system (RAS)-iron metabolism axis in this comorbidity remains unclear. We explored its underlying mechanisms and evaluated the therapeutic potential of gentiopicroside. METHODS: Integrated multi-omics analyses combining transcriptomics, single-cell RNA sequencing, Mendelian randomization, machine learning, molecular docking, and in vitro functional assays were performed to identify shared molecular pathways and therapeutic targets across PCOS, hypertension, NAFLD, and T2DM. RESULTS: SLC11A2 was consistently dysregulated in PCOS transcriptomic datasets, and associated with iron metabolism, inflammatory response and oxidative stress pathways. Genetic analyses validated RAS-related regulation in hypertension susceptibility and revealed shared genetic architecture between PCOS and cardiometabolic traits. Network and single-cell analyses characterized SLC11A2-associated molecular patterns in disease-relevant cell types; machine learning identified disease-classifying molecular signatures. Gentiopicroside alleviated inflammatory and oxidative stress phenotypes, including reduced IL-6 expression and reactive oxygen species accumulation. CONCLUSION: This study defines an RAS-SLC11A2 molecular framework linking iron metabolism dysregulation to PCOS-related cardiometabolic risk, elucidating the mechanisms connecting ovarian dysfunction, inflammation, oxidative stress and hypertension, and supports gentiopicroside as a promising therapeutic candidate.

Humans

Domestication-associated reduction of methyl salicylate in tomato root and its significance for resistance to root-knot nematode.

Methyl salicylate (MeSA) plays diverse roles in the aerial parts of plants. By contrast, its biosynthesis and function in roots remain poorly understood. Here, we investigated root MeSA biosynthesis and function in tomato. Genome-wide association studies (GWAS) were performed using root MeSA levels as the phenotype in a diversity panel of 167 accessions to identify associated loci. Candidate genes were biochemically characterized, and the role of MeSA in defense against root-knot nematode (RKN, Meloidogyne incognita) was evaluated using transgenic plants. MeSA was identified as a major root volatile in tomato and showed a domestication-associated reduction. GWAS revealed multiple loci associated with natural variation in root MeSA, including a major locus on Chromosome 9 encoding the salicylic acid methyltransferase (SlSAMT). SlSAMT-overexpressing plants showed reduced resistance to RKNs, whereas SlSAMT-knockdown plants exhibited enhanced resistance. Our results suggest complex roles of MeSA and the salicylic acid (SA) signaling pathway in belowground plant defense. The SA signaling pathway likely plays critical roles in protecting roots against diverse natural enemies, including RKNs. Nevertheless, RKNs appear to have co-opted MeSA as a host-location signal, and the domestication-associated reduction of root MeSA in tomato has likely contributed to enhanced resistance against RKNs.

Solanum lycopersicum

Prophylactic folinic acid prevents pemetrexed myelosuppression: A randomized trial toward safer treatment with chemotherapy in non-small cell lung cancer.

Background Pemetrexed is a cornerstone in advanced non-small cell lung cancer treatment. Although generally well tolerated, severe myelosuppression occurs in 26% of patients. Preventing chemotherapy-associated toxicity has become increasingly important with the introduction of osimertinib combined with pemetrexed-based chemotherapy. Due to substantial toxicity, this regimen is often not administered to frail patients. Folinic acid prophylaxis can mitigate pemetrexed-induced toxicity, however its preventive use has not been routinely studied. We aimed to investigate the efficacy of folinic acid prophylaxis to reduce myelosuppression. Methods Fifty patients treated with pemetrexed were randomized (1:1) to receive pemetrexed with or without oral folinic acid prophylaxis on days 2-4 after each chemotherapy cycle. The primary endpoint was absolute neutrophil count (ANC) after the first chemotherapy cycle. Secondary endpoints included ANC after the second cycle, grade neutropenia, treatment efficacy, renal function and incidence of dose modifications. Results Twenty-four patients received folinic acid and twenty-six served as controls. Higher ANC were observed in the folinic acid group after the first cycle (median 3.79; IQR 2.22-4.93 vs. 1.85; IQR 1.43-3.78; p.

Humans

Context matters: coordinated transcriptional regulation and root plasticity under multinutrient conditions.

Plants often encounter simultaneous imbalances in multiple nutrients, but the regulatory logic coordinating their responses remains poorly understood. We aimed to uncover shared transcriptional programs and regulatory nodes underpinning multinutrient adaptation in Arabidopsis thaliana roots. We analyzed publicly available RNA-seq datasets spanning 15 nutrient and beneficial element conditions using differential expression, co-expression network (WGCNA), and gene regulatory network analysis. Selected transcription factors (TFs) were validated via root phenotyping, suberin staining, and ionomic profiling under two-nutrient stress conditions. We identified a core set of 2050 genes responsive to multiple nutrient treatments, enriched for suberin biosynthesis, and structured into modular co-expression clusters. Eight prioritized candidate TFs (ARR10, GBF3, HHO5, NAC32, NF-YA3, NF-YB2, SARD1, and WRKY33) were shown to modulate root system architecture under specific nutrient combinations. WRKY33 and NF-YB2, in particular, regulated nutrient-responsive suberin deposition and ionomic plasticity. These findings reveal suberin remodeling as a shared downstream process in multinutrient responses and suggest that plasticity is not a fixed trait but a modular, polygenic, and context-dependent outcome. Repurposed TFs with pleiotropic functions coordinate structural and physiological traits, providing regulatory entry points for improving nutrient resilience.

Plant Roots

Maize ZmMYB59 inhibits post-germinative shoot and root elongation through ZmGA2ox3/10-mediated gibberellin catabolism.

Gibberellin (GA) promotes seed germination, but sustained or excessive GA signaling after germination can lead to aberrant root and shoot elongation. How GA homeostasis is transcriptionally restrained during post-germinative seedling development remains unclear. Using overexpression and gene-edited maize materials, we demonstrate that ZmMYB59 inhibits root and shoot elongation during post-germinative growth. Integrated RNA-Seq and CUT&Tag analyses identified the GA catabolism genes ZmGA2ox3 and ZmGA2ox10 as candidate direct targets of ZmMYB59. Hormone profiling analysis showed elevated bioactive GA1 and GA4 levels in the scutellum and aleurone layer cells of zmmyb59 mutants. Dual-luciferase assays, electrophoretic mobility shift assays, and ChIP-qPCR further confirmed that ZmMYB59 directly binds AC8 cis-elements in the ZmGA2ox3/10 promoters and activates their transcription. The zmga2ox3/10 double mutant, but neither single mutant, exhibited enhanced root and shoot elongation, accompanied by GA4 accumulation. This phenotype was suppressed by exogenous application of the GA biosynthesis inhibitor uniconazole. Transcriptomic and biochemical analyses further revealed enhanced starch degradation, reduced starch content, and increased soluble sugar accumulation in the double mutant. Taken together, these findings reveal that the ZmMYB59-ZmGA2ox3/10 module restrains GA accumulation and starch mobilization after germination, thereby coordinating reserve utilization with post-germinative root and shoot growth in maize.

Gibberellins

A cooperative regulatory module between TAGL2 and JMJC1 activates specific defense genes against root-knot nematodes in tomato.

Plant-parasitic nematodes (PPNs) threaten global food security. Although epigenetic modifications are crucial for plant immunity, how histone modifiers contribute to root-knot nematodes (RKNs, Meloidogyne incognita) resistance remains unclear. Here, using genetic, molecular and biochemical approaches, we investigated the epigenetic and transcriptional mechanisms underlying RKN resistance mediated by the histone demethylase (HDM) JMJC1 and the MADS-box transcription factor TAGL2 in tomato (Solanum lycopersicum). We identified JMJC1 as an RKN-induced positive defense regulator targeting H3K9me3 and H3K27me3 histone marks. JMJC1 physically interacts with TAGL2, which also positively regulates RKN resistance. Transcriptomic analysis indicated that TAGL2 regulates multiple layers of the plant defense network, transcriptionally activating representative genes from distinct pathways (including PUB10, bHLH98, CCaMK, and SAUR3), which we validated as positive regulators of RKN resistance via virus-induced gene silencing (VIGS). At the chromatin level, TAGL2 and JMJC1 co-regulate these loci, associating with localized H3K9me3 and H3K27me3 reduction. Furthermore, TAGL2 directly activates JMJC1 transcription, establishing a positive feedback loop that amplifies immune signaling. Our findings reveal a cooperative model wherein a HDM and a transcription factor coordinate at specific loci to fine-tune multiple defense layers at both epigenetic and transcriptional levels, providing insights for breeding durable nematode-resistant plants.

Solanum lycopersicum

The combination of morphogenic regulators BABY BOOM and GRF-GIF improves maize transformation efficiency and promotes leaf regeneration.

Transformation is an indispensable tool for plant genetics and functional genomics. Although stable transformation in maize is no longer a major obstacle, there remains a need for accessible and efficient methods for academic laboratories. Here, we present the GGB system, a rapid and efficient approach optimized for immature embryo transformation in B104 and other maize lines. This system combines two distinct morphogenetic regulators, the wheat GRF4-GIF1 chimera and the maize BABY BOOM (BBM) transcription factor (hence the name "GGB") with a modified QuickCorn protocol, enabling regeneration of transformed maize plantlets in c. 2 months with an efficiency 7-fold higher than when compared to either morphogenic factor used in isolation. Expression of both regulators did not significantly affect development, eliminating the need to excise them after regeneration. However, transmission of the transgenic GGB construct through pollen was significantly reduced, potentially aiding transgenic line containment. We show that the GGB system is adaptable for CRISPR-Cas9 editing and reporter line generation. Furthermore, stable GGB transformants exhibited high leaf regeneration capacity via somatic embryogenesis. RNA-seq time-course profiling of GGB leaf cultures identified additional factors that could promote regeneration and led to the discovery of asparagine and trehalose as additional media components that significantly enhanced leaf regeneration.

Zea mays

Pre-treatment polyfunctionality percentage (PFA) of CD8+ T cells is associated with development of immune-related adverse events (irAEs) in patients receiving immune checkpoint inhibitors (ICIs).

INTRODUCTION: Immune checkpoint inhibitors (ICIs) have improved cancer survival, but immune-related adverse events (irAEs) occur frequently and can have devastating consequences. There are no validated methods to evaluate risk of irAEs prior to initiation of ICIs. MATERIALS AND METHODS: We conducted a pilot study evaluating the ability of blood-based, single-cell secretomic analysis to characterize irAEs. A total of 10 patients with thoracic malignancies who were scheduled to receive ICIs were enrolled. Each patient had a pre-ICI blood sample drawn as well as a sample at the time of irAE development or 12 weeks after ICI initiation, whichever came first. Utilizing IsoPlexis's IsoLight system, polyfunctionality percentages (PFAs) and strength indices (PSIs) were analyzed for CD4+ and CD8+ T cells. RESULTS: Five patients developed irAEs and 5 patients did not develop irAEs. Pre- and post-ICI CD8+ T cell PFA was significantly elevated in patients who developed irAEs compared with those who did not (p = 0.017 and p = 0.014, respectively). CONCLUSIONS: In this pilot study, pre-ICI CD8+ T cell PFA was associated with development of irAEs. While this is a pilot study, this is a first step toward developing a blood-based, streamlined assay to assess risk of irAEs prior to initiation of ICIs. Validation in larger cohorts is warranted.

Humans

Plant species identification by genome skimming across the vascular plant tree of life.

Accurate species identification is essential for biodiversity conservation and sustainable use, yet standard plant DNA barcoding often fails to achieve species-level resolution. We present a large-scale empirical evaluation of genome skimming as a tool to improve plant species discrimination. Using standardised data from 1969 individuals representing 475 species from 32 genera across major lineages of the vascular plant tree of life, we compare conventional plastid + internal transcribed spacer (ITS) barcodes with genome skimming approaches. Standard barcoding using rbcL, matK, trnH-psbA and ITS resolved about half of species (49.3%), with six genera showing <&#x2009;25% species discrimination. By contrast, genome skimming enabled the recovery of complete plastid genomes, yielding 57.6% species discrimination. It also generated sufficient nuclear genomic data for additional resolution from k-mer analysis, achieving 66.8% species discrimination - an average gain of 17.5% over standard barcodes - while eliminating cases of extreme failure (<&#x2009;25% resolution). The recovery of complete plastomes and ribosomal DNAs from genome skims also ensures backward compatibility with existing barcode datasets. Our results demonstrate that genome skimming provides data that substantially improves species-level resolution across diverse plant lineages and offers a scalable, high-throughput approach for building comprehensive reference resources to support global biodiversity initiatives.

DNA Barcoding, Taxonomic

Divergent trajectories of genome architecture and chromosome evolution in ferns and angiosperms.

Ferns and angiosperms represent the two largest vascular plant lineages but exhibit striking genomic and ecological contrasts. We investigated whether differences in genome size, chromosome architecture, GC content, and stomatal traits reveal divergent evolutionary trajectories between these lineages. We assembled the most comprehensive dataset to date, integrating genome size, chromosome number and size, GC content, and stomatal traits for over 1100 fern species and compared it with an extensive angiosperm dataset. Ferns exhibited markedly lower variability and c. 16-fold slower rates of chromosome size evolution than angiosperms. A persistent positive relationship between genome size and chromosome number in ferns suggests limited cytological post-polyploid diploidization. While ferns generally possess larger stomata, this difference disappears after accounting for genome size, indicating that nucleotypic constraints, rather than lineage-specific physiology, dictate stomatal dimensions. Both groups share a unimodal GC-genome size relationship peaking at c. 14 Gbp. Larger fern chromosomes imply lower genome-wide recombination rates, potentially limiting genetic reshuffling and adaptive potential. Our results highlight fundamentally divergent evolutionary trajectories, likely shaped by meiotic symmetry in ferns and meiotic asymmetry, possibly centromere drive, and post-polyploid diploidization in angiosperms, defining the functional and genomic landscapes of these lineages across deep evolutionary timescales.

Genome, Plant

Decoding tumor immune microenvironment heterogeneity by single-cell and spatial multi-omics: From immunotherapy resistance to translational biomarkers.

Immune checkpoint blockade has transformed cancer therapy, yet primary and acquired resistance remain major clinical challenges. Increasing evidence indicates that immunotherapy resistance cannot be fully explained by tumor-intrinsic alterations or conventional biomarkers such as PD-L1 expression, tumor mutational burden, or microsatellite instability. Instead, therapeutic response is shaped by the tumor immune microenvironment (TIME) as a heterogeneous, spatially organized, and dynamically evolving ecosystem. Single-cell omics has revealed diverse immune and stromal cell states, including progenitor and terminally exhausted T cells, suppressive myeloid programs, B-cell/TLS-associated immune-reactive states, and CAF-mediated exclusion phenotypes. Spatial transcriptomics, spatial proteomics, and imaging-based approaches further demonstrate that these cell states assemble into distinct immune niches, including immune-inflamed, T-cell-excluded, myeloid-suppressive, metabolic/hypoxic, and TLS-associated niches. These spatial ecosystems determine whether antitumor immune cells can access malignant cells, receive antigen-presenting support, or become restrained by stromal, vascular, metabolic, and myeloid barriers. In this review, we summarize how single-cell and spatial multi-omics redefine TIME heterogeneity in immunotherapy resistance, highlight ligand-receptor communication networks linking cell states to spatial immune dysfunction, and discuss emerging translational biomarkers for patient stratification. We further propose that future immunotherapy biomarkers should evolve from static single-marker assays toward longitudinal, spatially resolved, and interpretable multi-omics models that guide precision combination immunotherapy.

Humans

Status of dementia care among healthcare practitioners in Nigerian tertiary hospitals: a cross-sectional study.

BACKGROUND/OBJECTIVES: Dementia is an escalating public health concern globally. This study evaluated the knowledge, attitudes, practices, and perceived barriers to dementia care among healthcare practitioners in Nigerian tertiary hospitals, aiming to identify practitioner-related sociodemographic predictors and systemic barriers affecting dementia care delivery. METHODS: We collected data from May 2024 to May 2025 for this cross-sectional study in 12 purposively selected tertiary hospitals across Nigeria's six geopolitical zones. Participants included physicians, nurses, pharmacists, and other professionals involved in geriatric psychiatric care. Using multistage and convenience sampling, 394 respondents were recruited (response rate: 99.5%). Data were collected via a validated Dementia Care Practice Questionnaire (Cronbach's &#x3b1; = 0.84) and analyzed with SPSS v22. Descriptive statistics, Chi-square tests, and odds ratios (ORs) identified associations (significance: p &#x2264; 0.05). RESULTS: Of 394 respondents, 51.5% were aged &#x2265;40 years, and 54.8% were female. While 62.9% demonstrated adequate knowledge, negative perceptions (51.3%) and attitudes (56.9%) were common. Despite this, 71.3% reported engagement in dementia care, and 75.6% demonstrated appropriate professional help-seeking behaviour when confronted with dementia care challenges. Practitioner-reported barriers included limited training opportunities, geographical barriers affecting patient access to dementia services, and inadequate staffing. Predictors of desirable care practices among healthcare practitioners included age &#x2265;40 years, female gender, Christian affiliation, and &#x2265;5 years of professional experience. CONCLUSION: Although many healthcare practitioners are involved in dementia care, gaps in perceptions, attitudes, and structural support persist. Interventions should focus on targeted training, system strengthening, and policy reform to improve dementia care outcomes.

Barriers to care

The feasibility and efficacy of weighted blankets as a sleep intervention for people with behavioural and psychological symptoms of dementia: a pilot randomised crossover trial.

Sleep disturbances contribute to disease progression in dementia and result in reduced quality of life. Non-pharmacological interventions are recommended for the management of sleep and other behavioural and psychological symptoms of dementia (BPSD), although these interventions can be challenging to implement. This pilot study assessed the feasibility and efficacy of weighted blankets as a sleep intervention for people with BPSD in a neurobehavioural unit. Fourteen residents, serving as their own control, slept two weeks with a weighted blanket and two weeks with usual bedding in a crossover trial. The primary outcomes were sleep duration and efficiency, measured via a Withing's sleep analyser and sleep disordered behaviours, measured by the sleep disorder inventory (SDI). Secondary outcomes included responsive behaviours, measured by the Neuropsychiatric index (NPI), falls incidents, restrictive practice incidents and use of pro re nata psychotropic medications. Generalised Estimation Equation (GEE) method was used for analysis. There was no statistical evidence that weighted blankets improved sleep or behavioural outcomes for people with BPSD, however fewer fall incidents, wakings and restrictive practices were reported during weighted blanket use. Weighted blankets were considered feasible and acceptable with high recruitment rates, nil participant withdrawals and no adverse outcomes, however there was variable compliance to the intervention protocol and the Withings did not adequately measure sleep. Whilst there is insufficient effectiveness evidence for further trials, weighted blankets can be offered to people living with dementia as a low risk sleep intervention option, with the caveat that there is currently no effectiveness evidence.

Behavioural Symptoms