James Cook University

This study examined nuanced preferences and unmet needs for bereavement care of mothers who experienced stillbirth or neonatal death. Cross-sectional survey. The Philippines. A total of 169 bereaved mothers aged 18 years or older who had experienced stillbirth or neonatal death on or after 30 January 2020 in the Philippines. Response patterns to nine self-administered questions about desired bereavement care and the care they received were analysed using latent class analysis. Measurement invariance was assessed across participant types and urbanicity. Multinomial logistic regression was used to examine the associations between latent classes, demographics and perinatal loss information. Desired type of bereavement care and unmet need for bereavement care. We identified three mutually exclusive stable latent classes related to desired care and unmet needs. For desired bereavement care, one class was characterised by a strong preference for seeing, holding, spending time with, and naming the baby, but low desire in memory making (25.1%). This preference was more common among mothers from urban areas (aOR = 3.04) and those who experienced stillbirth (aOR = 3.07), compared to those from rural areas and who experienced neonatal death, respectively. Regarding unmet need for bereavement care, one class reported unmet needs for memory making (28.3%), with preterm mothers (aOR = 3.11) three times more likely to belong to this class than those who delivered full-term. This study offers novel insights into the complex bereavement care preferences and needs of mothers who experienced perinatal loss. The findings can inform future frameworks and guide the development of culturally appropriate, context-specific interventions for mothers and families.

Microplastic (MP) pollution poses growing risks to marine ecosystems, yet the influence of physical and chemical characteristics of MP on ingestion and retention in tropical reef fish remains understudied. This study assessed how polymer type, shape, size, and colour influence MP ingestion preferences and gastrointestinal transit time (GTT) in juvenile damselfish Acanthochromis polyacanthus. Fish were exposed to non-biodegradable polystyrene (PS) and biodegradable polycaprolactone (PCL; considered an environmentally safer plastic alternative) of varying shapes (films and fragments), sizes (100-400μm diameter), and colours (transparent and blue). Ingestion was assessed after a 2h exposure, while GTT and depuration rate were monitored for 72h. Fish showed significant ingestion preference for larger, transparent fragments over films, irrespective of polymer type. Complete depuration of all MPs occurred within 48-72h with fragments depurated slower than films and size strongly influencing depuration. Depuration of PCL showed a non-linear size-dependent pattern, with intermediate-sized fragments clearing faster than both smaller and larger items, highlighting complex gastrointestinal transit dynamics. Importantly, biodegradable PCL persisted longer than PS MPs. These findings provide novel evidence that polymer-specific physical traits, rather than biodegradability alone, modulate ingestion and retention dynamics in reef fish. Furthermore, it highlights the need to consider ingestion preferences and retention in addition to degradability when evaluating and developing "safer plastic alternatives".

Face sketch synthesis is a technique aimed at converting face photos into sketches. Existing face sketch synthesis research mainly relies on training with numerous photo–sketch sample pairs from existing datasets. However, these large-scale discriminative learning methods will have to face problems, such as data scarcity and high human labor costs. Once the training data become scarce, their generative performance significantly degrades. In this article, we propose a one-shot face sketch synthesis method based on diffusion models. We optimize text instructions on a diffusion model using face photo–sketch image pairs. Then, the instructions derived through gradient-based optimization are used for inference. To simulate real-world scenarios more accurately and evaluate method effectiveness more comprehensively, we introduce a new benchmark named One-shot Face Sketch Dataset (OS-Sketch). The benchmark consists of 400 pairs of face photo–sketch images, including sketches with different styles and photos with different backgrounds, ages, sexes, expressions, illumination, and so on. For a solid out-of-distribution evaluation, we select only one pair of images for training at each time, with the rest used for inference. Extensive experiments demonstrate that the proposed method can convert various photos into realistic and highly consistent sketches in a one-shot context. Compared to other methods, our approach offers greater convenience and broader applicability. The dataset will be available at: https://github.com/HanWu3125/OS-Sketch .

Little attention has been paid to the gender difference in youth time use pre- and post-COVID-19 in Southeast Asia. This study applied data from two cohorts of youth (aged 16–21) in 2016 (pre-COVID-19) and 2023 (post-COVID-19) from a cross-national survey to examine youth time use in the Philippines and Indonesia. Gender, cohort and national differences were explored in the organization of youth’s lives – specifically how they allocate time across 11 domains covering aspects of daily routines, study, labor, and religious activities. Bivariate analysis suggests youth from the post-COVID-19 cohort spent significantly less time sleeping and more time on religious activities. In the pooled two-country sample, regression analysis highlights the persistently gendered time allocation pre- and post-COVID-19, that females spent more time on housework, more time studying outside of school, while males spent more time on family economic activities. The detailed results suggest nuanced processes differentiating the two country samples.

Abstract Offspring survival is a central component in understanding the life-history of species. With sea turtles, estimates of hatchling survival to adulthood can be traced back to theoretical considerations made over 50 years ago and before key parameters needed in the hatchling survival calculation had been quantified. Here, using up-to-date figures for adult survival rates and hence adult longevity and lifetime reproductive output, we show that the survival rate of hatchlings to adulthood will generally lie between 1 in 400 and 1 in 2000. We show that this survival rate probably varies across populations and species in line with variations in adult survival rates, remigration intervals and clutch frequency and will likely be impacted by factors such as local management, resource availability and bycatch pressures. Popular articles that tend to quote this survival rate as 1 in 1000 are broadly comparable with our estimates, although the survival rate likely varies appreciably across populations. We identify the key parameters that need to be measured for this value to be determined accurately for individual populations around the world. This approach of using values for adult reproductive output to estimate offspring survival rates to adulthood likely has broad utility across reptiles and other taxa.

Genetic nephrology has emerged as a distinct subspecialty within nephrology with growing evidence supporting its clinical utility and cost-effectiveness across diagnostic, prognostic, and management pathways. Yet significant implementation gaps such as undefined clinic models and outcomes, limited use of implementation science frameworks, ad hoc strategy development, and a narrow focus on diagnostic yield and clinical utility hinder its routine adoption and integration. This research programme aims to systematically design, implement, and evaluate a multidisciplinary kidney genetics clinic model, using a theory-informed and stakeholder-engaged implementation science approach, to translate genomic advances into improved service, patient-reported, and implementation outcomes, and to inform sustainable and scalable kidney genomics care policy. Using a interconnected four-part, mixed-methods, multi-frameworks design underpinned by implementation science theory, the research programme will (1) review global kidney genetics clinic models, outcomes, determinants of successful implementation, and implementation strategies; (2) assess local stakeholder perceptions, priorities and contextual determinants using Consolidated Framework for Implementation Research (CFIR)-guided qualitative inquiry; (3) co-design and refine tailored implementation strategies via Consolidated Framework for Implementation Research-Expert Recommendations for Implementing Change (CFIR-ERIC) mapping and hybrid participatory methods; and (4) evaluate the clinic’s service, patients, and implementation outcomes in a prospective effectiveness-implementation hybrid type 2 quasi-experimental interrupted time-series study design. Outcomes assessed include (1) service outcomes (diagnostic yield, clinical utility, and timeliness of care); (2) patient-reported outcomes (personal utility, patient-reported outcome measures); and (3) Proctor-defined implementation outcomes (acceptability, appropriateness, readiness, feasibility, and fidelity, and penetration). We will measure outcomes longitudinally across pre-implementation, implementation, and post-implementation phases, and analyse data using segmented regression analysis to assess changes in outcomes over time. The Implementation Research Logic Model (IRLM) will guide evaluation and adaptation throughout. This programme is designed to address critical implementation gaps between genomic evidence and clinical practice. Through four sequential studies, the programme will generate standardised kidney genetics clinic models and care pathways, evidence-informed implementation determinants, and context-tailored, co-designed implementation strategies. Taken together, this programme will establish a policy-relevant genetic nephrology care model with improved service, patient-reported, and implementation outcomes for the benefit of patients and families living with genetic kidney disease.

Multi-omics in combination with advanced computational methodologies synthesizes diverse omics data to provide deeper insights into molecular interactions and offers transformative potential for unravelling phenomenon behind disease complexities, improving diagnostics, disease prevention, and personalized treatments. This integrative strategy enables our understanding of gene-environment relationships, chronic disease progression, and the intricate molecular pathways involved in health. Effective multi-omics analyses require robust data sharing, accessibility, interoperability, and governance, which are critical for linking genomic elements to phenotypic traits. The Global Alliance for Genomics and Health advocates for responsible data-sharing practices, by promoting key principles such as transparency and equity. By emphasizing a collaborative approach to data utilization, our proposed framework seeks to advance improved disease prevention and treatment strategies. Multi-disciplinary collaboration, encompassing researchers, clinicians, policy makers, and patient representatives, is pivotal for driving innovation and addressing rare disease diagnostics. The success of multi-omics applications hinges on the establishment of comprehensive datasets, understanding the functional implications of multi-omic variation, adherence to findable, accessible, interoperable, reusable (FAIR) and Collective Benefit, Authority to Control, Responsibility, and Ethics (CARE) principles, and the strengthening of global genomic commons, benefiting scientific research, drug development, and broader health initiatives. Our review highlights essential components of multi-omics integration, underscoring its potential to transform the landscape of precision medicine and improved patient outcomes worldwide.