This study explored whether lifestyle therapy that promoted adherence to a Mediterranean-style diet as a treatment for depression led to environmental co-benefits. Participants (n 75 complete case) were Australian adults in the Curbing Anxiety and Depression using Lifestyle Medicine non-inferiority, randomised controlled trial, which showed that lifestyle therapy was non-inferior to psychotherapy in reducing depressive symptoms, when delivered in group format via video conferencing over an 8-week treatment period. In this secondary analysis, we hypothesised that the lifestyle arm would be superior to the psychotherapy arm in reducing the environmental impact of self-reported diet over time. Dietary intake derived from FFQ at baseline and 8 weeks was transformed into environmental impact scores by calculating global warming potential (GWP)*. GWP* was calculated for total dietary intake and distinct food groups (Australian Dietary Guidelines and NOVA classifications). Within-arm changes in GWP* over time were calculated using the median difference. Neither arm showed significant changes. Between-arm differences in percentage change in GWP* scores over time were analysed using generalised estimating equations models. No between-arm difference for total GWP* score was found (β = 11·06 (–7·04, 29·15)). When examining distinct food groups, results were mixed. These novel findings contribute to the sparse evidence base that has measured the environmental impact of diets in a clinical trial context. Whilst lifestyle therapy that reduced depressive symptoms did not have clear environmental benefits relative to psychotherapy, nutritional counselling that focuses on the environmental impact of food choices may drive more pronounced planetary co-benefits.

The central Maya lowlands (CML) display an uncommon demographic history—the absence of a millennial population rebound from its former occupational peak, about 800 CE. Here we postulate why the loss of a well-populated CML during the Late Classic-Terminal Classic periods failed to regain substantial occupation during the subsequent 700-800 years before the Spanish conquest of the Maya realm. Updating the narrative of stressful human-environmental conditions, shifts in trade routes, and long-term paucity of occupation in the CML, we examine push-pull factors that affected Postclassic Maya population geography. These factors include population pressures, environmental hazards, resource conditions, and livelihood standards that existed in the Postclassic Period between northern and coastal lowlands and the CML. The advantages that the CML maintained before Postclassic times, foremost regaining superior environmental conditions for agriculture, were insufficient pull factors given the low levels of push factors in the northern and coastal lowlands. We draw attention to the under-treated problem—the failure of a population rebound in the CML—and encourage improvements in systematic data and analytics to address it, including consideration of non-material, socio-cultural factors.

Network meta-analysis allows the synthesis of relative effects from several treatments. Two broad approaches are available to synthesize the data: arm-synthesis and contrast-synthesis, with several models that can be fitted within each. Limited evaluations comparing these approaches are available. We re-analyzed 118 networks of interventions with binary outcomes using three contrast-synthesis models (CSM; one fitted in a frequentist framework and two in a Bayesian framework) and two arm-synthesis models (ASM; both fitted in a Bayesian framework). We compared the estimated log odds ratios, their standard errors, ranking measures and the between-trial heterogeneity using the different models and investigated if differences in the results were modified by network characteristics. In general, we observed good agreement with respect to the odds ratios, their standard errors and the ranking metrics between the two Bayesian CSMs. However, differences were observed when comparing the frequentist CSM and the ASMs to each other and to the Bayesian CSMs. The network characteristics that we investigated, which represented the connectedness of the networks and rareness of events, were associated with the differences observed between models, but no single factor was associated with the differences across all of the metrics. In conclusion, we found that different models used to synthesize evidence in a network meta-analysis (NMA) can yield different estimates of odds ratios and standard errors that can impact the final ranking of the treatment options compared.

The Hippoboscidae are ectoparasites of birds and mammals, which, as a group, are known to vector multiple diseases. Avipoxvirus (APV) is mechanically vectored by various arthropods and causes seasonal disease in wild birds in the United Kingdom (UK). Signs of APV and the presence of louse flies (Hippoboscidae) on Dunnocks Prunella modularis were recorded over a 16·5-year period in a rural garden in Somerset, UK. Louse flies collected from this site and other sites in England were tested for the presence of APV DNA and RNA sequences. Louse flies on Dunnocks were seen to peak seasonally three weeks prior to the peak of APV lesions, an interval consistent with the previously estimated incubation period of APV in Dunnocks. APV DNA was detected on 13/25 louse flies, Ornithomya avicularia and Ornithomya fringillina, taken from Dunnocks, both with and without lesions consistent with APV, at multiple sites in England. Collectively these data support the premise that louse flies may vector APV. The detection of APV in louse flies, from apparently healthy birds, and from sites where disease has not been observed in any host species, suggests that the Hippoboscidae could provide a non-invasive and relatively cheap method of monitoring avian diseases. This could provide advanced warnings of disease, including zoonoses, before they become clinically apparent.

In low- and middle-income countries, fewer than 1 in 10 people with mental health conditions are estimated to be accurately diagnosed in primary care. This is despite more than 90 countries providing mental health training for primary healthcare workers in the past two decades. The lack of accurate diagnoses is a major bottleneck to reducing the global mental health treatment gap. In this commentary, we argue that current research practices are insufficient to generate the evidence needed to improve diagnostic accuracy. Research studies commonly determine accurate diagnosis by relying on self-report tools such as the Patient Health Questionnaire-9. This is problematic because self-report tools often overestimate prevalence, primarily due to their high rates of false positives. Moreover, nearly all studies on detection focus solely on depression, not taking into account the spectrum of conditions on which primary healthcare workers are being trained. Single condition self-report tools fail to discriminate among different types of mental health conditions, leading to a heterogeneous group of conditions masked under a single scale. As an alternative path forward, we propose improving research on diagnostic accuracy to better evaluate the reach of mental health service delivery in primary care. We recommend evaluating multiple conditions, statistically adjusting prevalence estimates generated from self-report tools, and consistently using structured clinical interviews as a gold standard. We propose clinically meaningful detection as ‘good-enough’ diagnoses incorporating multiple conditions accounting for context, health system and types of interventions available. Clinically meaningful identification can be operationalized differently across settings based on what level of diagnostic specificity is needed to select from available treatments. Rethinking research strategies to evaluate accuracy of diagnosis is vital to improve training, supervision and delivery of mental health services around the world.

Translational research needs to show value through impact on measures that matter to the public, including health and societal benefits. To this end, the Translational Science Benefits Model (TSBM) identified four categories of impact: Clinical, Community, Economic, and Policy. However, TSBM offers limited guidance on how these areas of impact relate to equity. Central to the structure of our Center for American Indian and Alaska Native Diabetes Translation Research are seven regional, independent Satellite Centers dedicated to community-engaged research. Drawing on our collective experience, we provide empirical evidence about how TSBM applies to equity-focused research that centers community partnerships and recognizes Indigenous knowledge. For this special issue – “Advancing Understanding and Use of Impact Measures in Implementation Science” – our objective is to describe and critically evaluate gaps in the fit of TSBM as an evaluation approach with sensitivity to health equity issues. Accordingly, we suggest refinements to the original TSBM Logic model to add: 1) community representation as an indicator of providing community partners “a seat at the table” across the research life cycle to generate solutions (innovations) that influence equity and to prioritize what to evaluate, and 2) assessments of the representativeness of the measured outcomes and benefits.

Contact tracing for COVID-19 in England operated from May 2020 to February 2022. The clinical, demographic and exposure information collected on cases and their contacts offered a unique opportunity to study secondary transmission. We aimed to quantify the relative impact of host factors and exposure settings on secondary COVID-19 transmission risk using 550,000 sampled transmission links between cases and their contacts. Links, or ‘contact episodes’, were established where a contact subsequently became a case, using an algorithm accounting for incubation period, setting, and contact date. A mixed-effects logistic regression model was used to estimate adjusted odds of transmission. Of sampled episodes, 8.7% resulted in secondary cases. Living with a case (71% episodes) was the most significant risk factor (aOR = 2.6, CI = 1.9–3.6). Other risk factors included unvaccinated status (aOR = 1.2, CI = 1.2–1.3), symptoms, and older age (66–79 years; aOR = 1.4, CI = 1.4–1.5). Whilst global COVID-19 strategies emphasized protection outside the home, including education, travel, and gathering restrictions, this study evidences the relative importance of household transmission. There is a need to reconsider the contribution of household transmission to future control strategies and the requirement for effective infection control within households.

Bitter taste perception plays a dual role in human nutrition and evolutionary biology; being identifiable in nutrient-dense foods such as cruciferous vegetables and historically signalled toxic compounds. The TAS2R38 gene, part of the taste 2 receptor family, is central to individual differences in bitter taste perception(1). While genetic variations are influential, dietary habits and food preparation also impact taste perception. However, research investigating the interplay between these factors and genetic variations in influencing bitter taste sensitivity and food intake is limited. This study aimed to elucidate the relationship between bitter taste sensitivity and TAS2R38 haplotype variations in the context of bitter food consumption among Australian adults. A cross-sectional, mixed-methods study was conducted. Healthy adults who had maintained a stable diet for at least three months were eligible. Data collection was via an online survey (REDCap), capturing self-reported demographics, dietary patterns specific to bitter foods including metrics of bitter food avoidance, frequency, liking and perceived healthfulness, alongside a Dietary Quality Index (DQI) derived from a food frequency questionnaire(2). Bitter taste sensitivity was assessed using self-reported intensity perceptions of 6-n-propylthiouracil (PROP) taste strips(3). Genotyping was conducted via TaqMan qPCR assays on DNA extracted from buccal swabs to ascertain TAS2R38 haplotypes. Data analysis utilised Analysis of Covariance (ANCOVA) and regression models, with all tests adjusted for confounding variables such as gender, age, and smoking status. A total of 222 participants (47.5 ± 17.7 years; 86% female; BMI 27.3 ± 7.1 kg/m2) completed the study. PROP sensitivity was strongly correlated with TAS2R38 haplotype, with supertasters predominantly having PAV/PAV, medium tasters with PAV/AVI, and non-tasters with AVI/AVI (p = 0.002). However, no relationship was observed between PROP sensitivity and either the frequency, liking, or avoidance of bitter foods (p>0.05). DQI was significantly related to bitter food consumption; individuals in the lowest DQI quintile consumed bitter foods more frequently than those in the third (p = 0.007) and top quintiles (p = 0.001). The perceived healthfulness of bitter foods was significantly higher in those with AVI/AVI haplotypes (non-tasters) compared to those with PAV/AVI (medium tasters) (p = 0.001). Counterintuitively, participants who reported greater enjoyment of bitter tastes consumed bitter foods less frequently (p<0.001). Our study confirms that TAS2R38 variants are predictive of PROP taste sensitivity, consistent with literature that identifies PAV/PAV individuals as supertasters. However, neither PROP sensitivity nor TAS2R38 haplotype influenced bitter food frequency or preference consumption patterns. Interestingly, those with lower Dietary Quality Index scores and less enjoyment of bitter taste consumed bitter foods more often. These observations highlight the need to investigate other factors influencing bitter food intake, such as additional sensory characteristics or psychological and behavioural aspects.

Behavioural treatments are recommended first-line for insomnia, but long-term benzodiazepine receptor agonist (BZRA) use remains common and engaging patients in a deprescribing consultation is challenging. Few deprescribing interventions directly target patients. Prescribers’ support of patient-targeted interventions may facilitate their uptake. Recently assessed in the Your Answers When Needing Sleep in New Brunswick (YAWNS NB) study, Sleepwell (mysleepwell.ca) was developed as a direct-to-patient behaviour change intervention promoting BZRA deprescribing and non-pharmacological insomnia management. BZRA prescribers of YAWNS NB participants were invited to complete an online survey assessing the acceptability of Sleepwell as a direct-to-patient intervention. The survey was developed using the seven construct components of the theoretical framework of acceptability (TFA) framework. Respondents (40/250, 17.2%) indicated high acceptability, with positive responses per TFA construct averaging 32.3/40 (80.7%). Perceived as an ethical, credible, and useful tool, Sleepwell also promoted prescriber–patient BZRA deprescribing engagements (11/19, 58%). Prescribers were accepting of Sleepwell and supported its application as a direct-to-patient intervention.

Odd Radio Circles (ORCs) are a class of low surface brightness, circular objects approximately one arcminute in diameter. ORCs were recently discovered in the Australian Square Kilometre Array Pathfinder (ASKAP) data and subsequently confirmed with follow-up observations on other instruments, yet their origins remain uncertain. In this paper, we suggest that ORCs could be remnant lobes of powerful radio galaxies, re-energised by the passage of a shock. Using relativistic hydrodynamic simulations with synchrotron emission calculated in post-processing, we show that buoyant evolution of remnant radio lobes is alone too slow to produce the observed ORC morphology. However, the passage of a shock can produce both filled and edge-brightnened ORC-like morphologies for a wide variety of shock and observing orientations. Circular ORCs are predicted to have host galaxies near the geometric centre of the radio emission, consistent with observations of these objects. Significantly offset hosts are possible for elliptical ORCs, potentially causing challenges for accurate host galaxy identification. Observed ORC number counts are broadly consistent with a paradigm in which moderately powerful radio galaxies are their progenitors.

To investigate the symptoms of SARS-CoV-2 infection, their dynamics and their discriminatory power for the disease using longitudinally, prospectively collected information reported at the time of their occurrence. We have analysed data from a large phase 3 clinical UK COVID-19 vaccine trial. The alpha variant was the predominant strain. Participants were assessed for SARS-CoV-2 infection via nasal/throat PCR at recruitment, vaccination appointments, and when symptomatic. Statistical techniques were implemented to infer estimates representative of the UK population, accounting for multiple symptomatic episodes associated with one individual. An optimal diagnostic model for SARS-CoV-2 infection was derived. The 4-month prevalence of SARS-CoV-2 was 2.1%; increasing to 19.4% (16.0%–22.7%) in participants reporting loss of appetite and 31.9% (27.1%–36.8%) in those with anosmia/ageusia. The model identified anosmia and/or ageusia, fever, congestion, and cough to be significantly associated with SARS-CoV-2 infection. Symptoms’ dynamics were vastly different in the two groups; after a slow start peaking later and lasting longer in PCR+ participants, whilst exhibiting a consistent decline in PCR- participants, with, on average, fewer than 3 days of symptoms reported. Anosmia/ageusia peaked late in confirmed SARS-CoV-2 infection (day 12), indicating a low discrimination power for early disease diagnosis.

Gestational diabetes is treated with medical nutrition therapy, delivered by healthcare professionals; however, the optimal diet for affected women is unknown. Randomised controlled trials, such as the DiGest (Dietary Intervention in Gestational Diabetes) trial, will address this knowledge gap, but the acceptability of whole-diet interventions in pregnancy is unclear. Whole-diet approaches reduce bias but require high levels of participant commitment and long intervention periods to generate meaningful clinical outcomes. We aimed to assess healthcare professionals’ views on the acceptability of the DiGest dietbox intervention for women with gestational diabetes and to identify any barriers to adherence which could be addressed to support good recruitment and retention to the DiGest trial. Female healthcare professionals (n 16) were randomly allocated to receive a DiGest dietbox containing 1200 or 2000 kcal/d including at least one weeks’ food. A semi-structured interview was conducted to explore participants’ experience of the intervention. Interviews were audio-recorded, transcribed verbatim and analysed thematically using NVivo software. Based on the findings of qualitative interviews, modifications were made to the dietboxes. Participants found the dietboxes convenient and enjoyed the variety and taste of the meals. Factors which facilitated adherence included participants having a good understanding of study aims and sufficient organisational skills to facilitate weekly meal planning in advance. Barriers to adherence included peer pressure during social occasions and feelings of deprivation or hunger (affecting both standard and reduced calorie groups). Healthcare professionals considered random allocation to a whole-diet replacement intervention to be acceptable and feasible in a clinical environment and offered benefits to participants including convenience.