The diet of Antarctic toothfish (Dissostichus mawsoni) captured by bottom longlines on the Ross Sea continental shelf was examined during four consecutive summer research surveys (2012–2015) within the Ross Sea polynya. The surveys included three areas: south-west continental shelf (Core area), McMurdo Sound and Terra Nova Bay. Toothfish diet comprised mainly small notothens, especially Trematomus spp. (which accounted for 20–52% of total prey weight by area) and icefish (30–57% of total prey weight by area). Notothen prey were mainly Trematomus loennbergii, with Trematomus scotti regularly observed. The most important icefish prey were Chionodraco spp., of which Chionodraco hamatus was most frequently identified, and Neopagetopsis ionah. Dragonfish (Bathydraconidae) were rarely observed, except in 2012 when Gymnodraco acuticeps accounted for ~11% of prey weight. Antarctic silverfish (Pleuragramma antarcticum) were regularly observed but contributed little by weight (0.4–3.6% total prey weight by area). Invertebrates were a relatively small component of toothfish diet, with the prawn Notocrangon antarcticus and the amphipod Eusiris spp. found in ~3–24% and 0–9% of stomachs, respectively, but they were small and weighed little. Icefish (particularly Dacodraco hunteri) were more important than notothens in toothfish diet in Terra Nova Bay. The results indicate that D. mawsoni are predominantly benthic feeders, with no evidence of substantial feeding away from the seafloor in the days before they were caught. In contrast with previous McMurdo Sound diet studies, Antarctic silverfish were of relatively minor importance as a prey item for Antarctic toothfish in other areas of the Ross Sea shelf, which is consistent with a coastal and fast-ice distribution of silverfish and/or a seasonal change in the distribution of silverfish.

Objectives/Goals: We aim to understand how estradiol (E2) modulates proliferation and migration in distinct breast cancer subtypes within a collagen-based 3D platform that serves to better recapitulate human tissue architecture. This work seeks to bridge in vitro hormone biology with translational modeling of hormone-driven tumor behaviors. Methods/Study Population: MDA-MB-231 (triple-negative) and MCF-7 (hormone receptor-positive) breast cancer cells, tagged with red fluorescent protein, were exposed to varying E2 concentrations (0 to 10-4 M) in both 2D and 3D culture. In 2D, 2,000 cells/well were seeded in 96-well plates. Wells were imaged on Day 1 using confocal fluorescent microscopy, treated with E2, and reimaged on Day 5 to assess post-treatment counts. Normalized proliferation was calculated as Day 5/Day 1 cell count. In 3D, per well, 60,000 cells were embedded in a 12 µL base layer of 0.3% type I collagen, overlaid with 40 µL plain collagen, and topped with 150 µL E2-containing media. On Day 5, microscopy and a machine learning algorithm assessed cell counts and migration, defining migratory cells as those >1 standard deviation from the mean z-position of the tumor body. Results/Anticipated Results: In 2D, MCF-7 cells demonstrated significant dose-dependent proliferation to E2. Normalized cell counts increased progressively from 0 M to 10-10 M, at which point proliferation peaked, followed by a significant decline at higher concentrations. In contrast, MDA-MB-231 cells showed stable proliferation across the 0 to 10-6 M range, with a marked reduction in count at 10-4 M. In 3D, MDA-MB-231 cell proliferation remained stable across low and intermediate E2 doses, with a marked reduction at 10-4 M. MCF-7 cells, however, showed no significant differences in normalized proliferation across any E2 concentration in 3D. Quantitative migration analysis revealed that the percentage of migratory cells remained statistically unchanged across all E2 concentrations for both MCF-7 and MDA-MB-231 cells in the 3D matrix. Discussion/Significance of Impact: Dimensionality influences hormone responsiveness in breast cancer, highlighting limitations of 2D assays in modeling clinical behaviors and predicting outcomes. Advancing biomimetic 3D platforms like these may ultimately enable patient-specific screening of endocrine response and guide personalized therapy for hormone-sensitive cancers.

Objectives/Goals: We aim to develop new tissue-engineered ear tissue that more closely mimics native elastic cartilage and maintains its topographic form for reconstructive auricular surgery. By integrating decellularized cartilage (DCM) into chondrocyte-seeded collagen matrices, we seek to improve structural stability to support future clinical translation. Methods/Study Population: Bovine auricular chondrocytes were isolated via enzymatic digestion, expanded to passage 3, and encapsulated at 25 million cells/mL into four construct formulations composed of 1% type I collagen mixed with varying amounts of DCM: (1) 100% collagen, (2) 70% collagen + 30% DCM, (3) 40% collagen + 60% DCM, and (4) 10% collagen + 90% DCM. DCM was prepared by zesting ovine rib cartilage into ~0.5 mm³ flakes, followed by chemical and enzymatic decellularization. Constructs were packed into 3D-printed scaffolds and cultured for 0, 1, or 2 months. At each timepoint, constructs were assessed for gross volume, volume retention (normalized to baseline), and angle at the dome–base interface as a geometric surrogate for shape retention. Histology evaluated cell distribution and cartilage-specific matrix deposition. Results/Anticipated Results: At baseline, volumes were comparable across groups. By 1 and 2 months, constructs with higher DCM content yielded significantly greater volume retention. At 2 months, mean retention in the 90% DCM group was 94.0%±6.2%, compared to 64.7%±4.1% in 30% DCM (p<0.01) and 74.7%±5.9% in 0% DCM (p<0.05). Angle analysis likewise showed that higher DCM preserved sharper dome–base curvature. Mean angle change at 2 months was 3.0°±3.6° in 90% DCM versus 17.6°±5.7° (70% DCM, p<0.01), 16.3°±5.7° (30% DCM, p<0.05), and 21.6°±8.1° (0% DCM, p<0.001). In all groups, histology confirmed chondrocyte viability, and inclusion of DCM did not hinder cell distribution in collagen. These findings suggest DCM reinforces construct stability, and we anticipate similar volume and shape retention in upcoming in vivo rat studies. Discussion/Significance of Impact: Incorporating DCM improves in vitro form retention in bioengineered ear cartilage without impeding cell viability, suggesting DCM can act as an internal rebar to resist contraction and preserve geometry. By continuing to advance this construct translationally, next in vivo, we aim to enable its eventual use in clinical ear reconstruction.

Almost 12 % of the human population have insufficient access to food and hence are at risk from nutrient deficiencies and related conditions, such as anaemia and stunting. Ruminant meat and milk are rich in protein and micronutrients, making them a highly nutritious food source for human consumption. Conversely, ruminant production contributes to methane (CH4) emissions, a greenhouse gas (GHG) with a global warming potential (GWP) 27–30 times greater than that of carbon dioxide (CO2). Nonetheless, ruminant production plays a crucial role in the circular bioeconomy in terms of upcycling agricultural products that cannot be consumed by humans, into valuable and nutritional food, whilst delivering important ecosystem services. Taking on board the complexities of ruminant production and the need to improve both human and planetary health, there is increasing emphasis on developing innovative solutions to achieve sustainable ruminant production within the ‘One Health’ framework. Specifically, research and innovation will undoubtedly continue to focus on (1) Genetics and Breeding; (2) Animal nutrition and (3) Animal Health, to achieve food security and human health, whilst limiting environmental impact. Implementation of resultant innovations within the agri-food sector will require several enablers, including large-scale investment, multi-actor partnerships, scaling, regulatory approval and importantly social acceptability. This review outlines the grand challenges of achieving sustainable ruminant production and likely research and innovation landscape over the next 15 years and beyond, specifically outlining the pathways and enablers required to achieve sustainable ruminant production within the One Health framework.

Female genital schistosomiasis (FGS) is a chronic disease manifestation of the waterborne parasitic infection Schistosoma haematobium that affects up to 56 million women and girls, predominantly in sub-Saharan Africa. Starting from early childhood, this stigmatizing gynaecological condition is caused by the presence of Schistosoma eggs and associated toxins within the genital tract. Schistosoma haematobium typically causes debilitating urogenital symptoms, mostly as a consequence of inflammation, which includes bleeding, discharge and lower abdominal pelvic pain. Chronic complications of FGS include adverse sexual and reproductive health and rights outcomes such as infertility, ectopic pregnancy and miscarriage. FGS is associated with prevalent human immunodeficiency virus and may increase the susceptibility of women to high-risk human papillomavirus infection. Across SSA, and even in clinics outside endemic areas, the lack of awareness and available resources among both healthcare professionals and the public means FGS is underreported, misdiagnosed and inadequately treated. Several studies have highlighted research needs and priorities in FGS, including better training, accessible and accurate diagnostic tools, and treatment guidelines. On 6 September, 2024, LifeArc, the Global Schistosomiasis Alliance and partners from the BILGENSA Research Network (Genital Bilharzia in Southern Africa) convened a consultative, collaborative and translational workshop: ‘Female Genital Schistosomiasis: Translational Challenges and Opportunities’. Its ambition was to identify practical solutions that could address these research needs and drive appropriate actions towards progress in tackling FGS. Here, we present the outcomes of that workshop – a series of discrete translational actions to better galvanize the community and research funders.

Interpersonal psychotherapy (IPT) and antidepressant medications are both first-line interventions for adult depression, but their relative efficacy in the long term and on outcome measures other than depressive symptomatology is unknown. Individual participant data (IPD) meta-analyses can provide more precise effect estimates than conventional meta-analyses. This IPD meta-analysis compared the efficacy of IPT and antidepressants on various outcomes at post-treatment and follow-up (PROSPERO: CRD42020219891). A systematic literature search conducted May 1st, 2023 identified randomized trials comparing IPT and antidepressants in acute-phase treatment of adults with depression. Anonymized IPD were requested and analyzed using mixed-effects models. The prespecified primary outcome was post-treatment depression symptom severity. Secondary outcomes were all post-treatment and follow-up measures assessed in at least two studies. IPD were obtained from 9 of 15 studies identified (N = 1536/1948, 78.9%). No significant comparative treatment effects were found on post-treatment measures of depression (d = 0.088, p = 0.103, N = 1530) and social functioning (d = 0.026, p = 0.624, N = 1213). In smaller samples, antidepressants performed slightly better than IPT on post-treatment measures of general psychopathology (d = 0.276, p = 0.023, N = 307) and dysfunctional attitudes (d = 0.249, p = 0.029, N = 231), but not on any other secondary outcomes, nor at follow-up. This IPD meta-analysis is the first to examine the acute and longer-term efficacy of IPT v. antidepressants on a broad range of outcomes. Depression treatment trials should routinely include multiple outcome measures and follow-up assessments.

We discuss the applicability of quasilinear-type approximations for a turbulent system with a large range of spatial and temporal scales. We consider a paradigm fluid system of rotating convection with vertical and horizontal temperature gradients. In particular, the interaction of rotation with the horizontal temperature gradient drives a ‘thermal wind’ shear flow whose strength is controlled by the horizontal temperature gradient. Varying this parameter therefore systematically alters the ordering of the shearing time scale, the convective time scale and the correlation time scale. We demonstrate that quasilinear-type approximations work well when the shearing time scale or the correlation time scale is sufficiently short. In all cases, the generalised quasilinear approximation systematically outperforms the quasilinear approximation. We discuss the consequences for statistical theories of turbulence interacting with mean gradients.

Throughout the COVID-19 pandemic, many areas in the United States experienced healthcare personnel (HCP) shortages tied to a variety of factors. Infection prevention programs, in particular, faced increasing workload demands with little opportunity to delegate tasks to others without specific infectious diseases or infection control expertise. Shortages of clinicians providing inpatient care to critically ill patients during the early phase of the pandemic were multifactorial, largely attributed to increasing demands on hospitals to provide care to patients hospitalized with COVID-19 and furloughs.1 HCP shortages and challenges during later surges, including the Omicron variant-associated surges, were largely attributed to HCP infections and associated work restrictions during isolation periods and the need to care for family members, particularly children, with COVID-19. Additionally, the detrimental physical and mental health impact of COVID-19 on HCP has led to attrition, which further exacerbates shortages.2 Demands increased in post-acute and long-term care (PALTC) settings, which already faced critical staffing challenges difficulty with recruitment, and high rates of turnover. Although individual healthcare organizations and state and federal governments have taken actions to mitigate recurring shortages, additional work and innovation are needed to develop longer-term solutions to improve healthcare workforce resiliency. The critical role of those with specialized training in infection prevention, including healthcare epidemiologists, was well-demonstrated in pandemic preparedness and response. The COVID-19 pandemic underscored the need to support growth in these fields.3 This commentary outlines the need to develop the US healthcare workforce in preparation for future pandemics.

Throughout history, pandemics and their aftereffects have spurred society to make substantial improvements in healthcare. After the Black Death in 14th century Europe, changes were made to elevate standards of care and nutrition that resulted in improved life expectancy.1 The 1918 influenza pandemic spurred a movement that emphasized public health surveillance and detection of future outbreaks and eventually led to the creation of the World Health Organization Global Influenza Surveillance Network.2 In the present, the COVID-19 pandemic exposed many of the pre-existing problems within the US healthcare system, which included (1) a lack of capacity to manage a large influx of contagious patients while simultaneously maintaining routine and emergency care to non-COVID patients; (2) a “just in time” supply network that led to shortages and competition among hospitals, nursing homes, and other care sites for essential supplies; and (3) longstanding inequities in the distribution of healthcare and the healthcare workforce. The decades-long shift from domestic manufacturing to a reliance on global supply chains has compounded ongoing gaps in preparedness for supplies such as personal protective equipment and ventilators. Inequities in racial and socioeconomic outcomes highlighted during the pandemic have accelerated the call to focus on diversity, equity, and inclusion (DEI) within our communities. The pandemic accelerated cooperation between government entities and the healthcare system, resulting in swift implementation of mitigation measures, new therapies and vaccinations at unprecedented speeds, despite our fragmented healthcare delivery system and political divisions. Still, widespread misinformation or disinformation and political divisions contributed to eroded trust in the public health system and prevented an even uptake of mitigation measures, vaccines and therapeutics, impeding our ability to contain the spread of the virus in this country.3 Ultimately, the lessons of COVID-19 illustrate the need to better prepare for the next pandemic. Rising microbial resistance, emerging and re-emerging pathogens, increased globalization, an aging population, and climate change are all factors that increase the likelihood of another pandemic.4

The Society for Healthcare Epidemiology in America (SHEA) strongly supports modernization of data collection processes and the creation of publicly available data repositories that include a wide variety of data elements and mechanisms for securely storing both cleaned and uncleaned data sets that can be curated as clinical and research needs arise. These elements can be used for clinical research and quality monitoring and to evaluate the impacts of different policies on different outcomes. Achieving these goals will require dedicated, sustained and long-term funding to support data science teams and the creation of central data repositories that include data sets that can be “linked” via a variety of different mechanisms and also data sets that include institutional and state and local policies and procedures. A team-based approach to data science is strongly encouraged and supported to achieve the goal of a sustainable, adaptable national shared data resource.

We present radio observations of the galaxy cluster Abell S1136 at 888 MHz, using the Australian Square Kilometre Array Pathfinder radio telescope, as part of the Evolutionary Map of the Universe Early Science program. We compare these findings with data from the Murchison Widefield Array, XMM-Newton, the Wide-field Infrared Survey Explorer, the Digitised Sky Survey, and the Australia Telescope Compact Array. Our analysis shows the X-ray and radio emission in Abell S1136 are closely aligned and centered on the Brightest Cluster Galaxy, while the X-ray temperature profile shows a relaxed cluster with no evidence of a cool core. We find that the diffuse radio emission in the centre of the cluster shows more structure than seen in previous low-resolution observations of this source, which appeared formerly as an amorphous radio blob, similar in appearance to a radio halo; our observations show the diffuse emission in the Abell S1136 galaxy cluster contains three narrow filamentary structures visible at 888 MHz, between $\sim$80 and 140 kpc in length; however, the properties of the diffuse emission do not fully match that of a radio (mini-)halo or (fossil) tailed radio source.