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Depression and anxiety are major global health burdens. Although SSRIs targeting the serotonergic system are prescribed over 200 million times annually, they have variable therapeutic efficacy and side effects, and mechanisms of action remain incompletely understood. Here, we comprehensively characterise the molecular landscape of gene regulatory changes associated with fluoxetine, a widely-used SSRI. We performed multimodal analysis of SSRI response in 27 mammalian brain regions using 310 bulk RNA-seq and H3K27ac ChIP-seq datasets, followed by in-depth characterisation of two hippocampal regions using single-cell RNA-seq (20 datasets). Remarkably, fluoxetine induced profound region-specific shifts in gene expression and chromatin state, including in the nucleus accumbens shell, locus coeruleus and septal areas, as well as in more well-studied regions such as the raphe and hippocampal dentate gyrus. Expression changes were strongly enriched at GWAS loci for depression and antidepressant drug response, stressing the relevance to human phenotypes. We observed differential expression at dozens of signalling receptors and pathways, many of which are previously unknown. Single-cell analysis revealed stark differences in fluoxetine response between the dorsal and ventral hippocampal dentate gyri, particularly in oligodendrocytes, mossy cells and inhibitory neurons. Across diverse brain regions, integrative omics analysis consistently suggested increased energy metabolism via oxidative phosphorylation and mitochondrial changes, which we corroborated in vitro; this may thus constitute a shared mechanism of action of fluoxetine. Similarly, we observed pervasive chromatin remodelling signatures across the brain. Our study reveals unexpected regional and cell type-specific heterogeneity in SSRI action, highlights under-studied brain regions that may play a major role in antidepressant response, and provides a rich resource of candidate cell types, genes, gene regulatory elements and pathways for mechanistic analysis and identifying new therapeutic targets for depression and anxiety.

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Background Mealtimes are embedded routines of residents living in residential aged care facilities (RACFs) that directly impact their health and quality of life. Little is known about how mealtime experiences are informed and affected by structures such as government and organisational policies and processes. This scoping review used Giddens’ (The constitution of society: outline of the theory of structuration, 1984) Structuration Theory to investigate how governance structures related to mealtime practices inform residents’ mealtime experiences. Methods Using Arksey and O’Malley’s (Int J Soc Res Methodol 8:19–32, 2005) scoping review framework, a systematic database, grey literature and policy search was completed in May 2020 and updated in July 2021. From 2725 identified articles, 137 articles were included in data charting and deductive analysis, and 76 additional Australian government policy papers were used interpretatively. Results Data charting identified that the included studies were prominently situated in Western countries, with a progressive increase in publication rate over the past two decades. Qualitative findings captured structures that guide RACF mealtimes, how these relate to person-centred mealtime practices, and how these facilitate residents to enact choice and control. Conclusions Current policies lack specificity to inform the specific structures and practices of RACF mealtimes. Staff, residents, organisational and governance representatives possess different signification, legitimation and domination structures, and lack a shared understanding of policy, and how this influences processes and practices that comprise mealtimes.

Background Heatwaves, air pollution and their effects on children’s health can vary temporally and spatially. With the emergence of advanced methods such as machine learning, there is an opportunity to improve prediction of children’s health events associated with those exposures. Methods Daily records on emergency department attendances (EDA) for children Results RF was the best model with the lowest root mean squared error (MSE). The best RF validation model had an r-squared (R2) =0.95. The percentage increase in MSE indicated that PM10 and PM2.5 were important predictors of EDA for all children. Number of burns was more important in 5-9 year age group than other groups. GRF models (R2 0.90-0.98) showed that heatwave and PM2.5 were the important predictors in southern part of the study area for all age groups. Conclusions The importance of risk factors to predict EDA was varied by age groups and locations. Such differences are important when developing targeted health promotion strategies tailored to age groups and geographical locations. Key messages RF predicted EDA better than other models. Evaluation of spatial variation of heatwave and air quality effects on EDA for children by GRF modelling is useful to identify at risk geographical locations.

SummaryExisting computational methods that use single-cell RNA-sequencing for cell fate prediction either summarize observations of cell states and their couplings without modeling the underlying differentiation process, or are limited in their capacity to model complex differentiation landscapes. Thus, contemporary methods cannot predict how cells evolve stochastically and in physical time from an arbitrary starting expression state, nor can they model the cell fate consequences of gene expression perturbations. We introduce PRESCIENT (Potential eneRgy undErlying Single Cell gradIENTs), a generative modeling framework that learns an underlying differentiation landscape from single-cell time-series gene expression data. Our generative model framework provides insight into the process of differentiation and can simulate differentiation trajectories for arbitrary gene expression progenitor states. We validate our method on a recently published experimental lineage tracing dataset that provides observed trajectories. We show that this model is able to predict the fate biases of progenitor cells in neutrophil/macrophage lineages when accounting for cell proliferation, improving upon the best-performing existing method. We also show how a model can predict trajectories for cells not found in the model’s training set, including cells in which genes or sets of genes have been perturbed. PRESCIENT is able to accommodate complex perturbations of multiple genes, at different time points and from different starting cell populations. PRESCIENT models are able to recover the expected effects of known modulators of cell fate in hematopoiesis and pancreatic β cell differentiation.

This paper presents a novel spatial market segmentation method to determine key user groups of a train station (such as gender, age and access mode), based on the size and shape of the station catchment area of each group. Two new indices – area ratio and composite ratio – are developed to quantify the importance of user groups for a train station. This method is applied to identify key user groups at seven train stations in Perth, Western Australia. The study offers a new way to explore the travel behaviour of train users and provides insights for rail transport planning and marketing.

This study aims to produce renewable diesel and biopriviliged chemicals from microalgae that can thrive in wastewater environment. Spirulina (SP) was converted into biocrude oil at 300ºC for a 30-minute reaction time via hydrothermal liquefaction (HTL). Next, fractional distillation was used to separate SP-derived biocrude oil into different distillates. It was found that 62% of the viscous SP-derived biocrude oil can be separated into liquids at about 270ºC (steam temperature of the distillation). Physicochemical characterizations, including density, viscosity, acidity, elemental compositions, higher heating values and chemical compositions, were carried out with the distillates separated from SP-derived biocrude oil. These analyses showed that 15% distillates could be used as renewable diesel because they have similar heating values (43-46 MJ/kg) and carbon numbers (ranging from C8 to C18) to petroleum diesel. The Van Krevelan diagram of the distillates suggests that deoxygenation was effectively achieved by fractional distillation. In addition, GC-MS analysis indicates that some distillates contain biopriviliged chemicals like aromatics, phenols and fatty nitriles that can be used as commodity chemicals. An algal biorefinery roadmap was proposed based on the analyses of different distillates from the SP-derived biocrude oil. Finally, the fuel specification analysis was conducted with the drop-in renewable diesel, which was prepared with 10 vol.% (HTL10) distillates and 90 vol.% petroleum diesel. According to the fuel specification analysis, HTL10 exhibited a qualified lubricity (6 hr), as well as a comparable net heat of combustion (1% lower), ash content (29% lower) and viscosity (17% lower) to those of petroleum diesel. Ultimately, it is expected that this study can provide insights for potential application of algal biocrude oil converted via HTL.

As the frequency, intensity, and duration of heatwaves increases, emergency health serviceutilization, including ambulance service, has correspondingly increased across the world. The negative effects of air pollution on health complicate these adverse health effects. This research work is the first known study to analyze the joint effects of heatwaves and air quality on the ambulance service in Western Australia (WA). The main objective is to investigate the potential joint effects of heatwaves and air quality on the ambulance service for vulnerable populations in the Perth metropolitan area. A time series design was used. Daily data on ambulance callouts, temperature and air pollutants (CO, SO2, NO2, O3, PM10 and PM2.5) were collected for the Perth metropolitan area, WA from 2006 to 2015. Poisson regression modeling was used to assess the association between heatwaves, air quality, and ambulance callouts. Risk assessments on age, gender, socio-economic status (SES), and joint effects between heatwaves and air quality on ambulance callouts were conducted. The ambulance callout rate was higher during heatwave days (14.20/100,000/day) compared to non-heatwave days (13.95/100,000/day) with a rate ratio of 1.017 (95% confidence interval 1.012, 1.023). The ambulance callout rate was higher in males, people over 60 years old, people with low SES, and those living in coastal areas during period of heatwaves. Exposure to CO, SO2, O3 and PM2.5 increased risk on ambulance callouts and exposure to NO2 showed joint effect with heatwave and increased risk of ambulance callouts by 3% after adjustment of all other risk factors. Ambulance callouts are an important indicator for evaluating heatwave-related emergency morbidity in WA. As the median concentrations of air pollutants in WA were lower than the Australian National Standards, the interactive effects of heatwaves and air quality on ambulance service need to be further examined, especially when air pollutants exceed the standards.