Lancaster City Council

There is now clear evidence, from a variety of studies, that galactic bars contribute to and/or accelerate processes which quench galaxies. However, bars have a variety of strengths and pattern speeds, and previous work has suggested that slow and strong bars impact their hosts the most. In this paper, we continue to investigate the impact of bar strength and bar speed on host galaxy evolution in a sample of barred galaxies identified via classifications from Galaxy Zoo. We perform a comprehensive assessment of star-formation tracers spanning a variety of timescales, based on spatially resolved spectroscopic information from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. Specifically, we examine the radial distributions of EW[Halpha], HdeltaA, Hbeta, and Dn4000; spectral data that trace star-formation on current, intermediate, and much longer timescales. We investigate how these star-formation tracers vary with respect to each other in diagnostic evolutionary planes for eight categories of barred galaxies (combinations of star forming or quenching; strong and weak; fast and slow). We continue to find that slow-strong bars drive the quenching of their hosts the most by triggering active star-formation throughout the barred region; however, we note some additional complexity: we observe that stronger bars boost star-formation at the bar centre while slower bars have increased star-formation along the bar. This work adds to the growing evidence that galactic bars have both global and local impacts on their host galaxies.

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Abstract Disclosure: R. Elangovan: None. K. Elangovan: None. J.R. Sethuraj: None. E. Krishnan: None. G. Palaniswamy: None. S. Nanduri: None. K. Sakalabaktula: None. U. Qureshi: None. F. Rahman: None. Z. Baloch: None. Z. Ahmed: None. S. Biswas: None. R. Muralidhar: None. C. Robert: None. K.J. Patel: None. G. Rajamani: None. N. Vora: None. S. Malapati: None. K. Noor: None. M. Kaur: None. A.S. Agrawal: None. A. Franklin Johnson: None. P. Uvaraj: None. T. Dontulwar: None. F. Madhumithaa Jagannathan: None. P.C. Sirait: None. M. Amro Alrouh: None. S. Tamma: None. S.S. Bhurchandi: None. S.K. Bhurchandi: None. Introduction: Endocrine cancers present critical challenges due to their systemic hormonal effects and intricate diagnostic profiles. With nearly 10 million cancer-related deaths annually, innovative solutions are imperative. Artificial intelligence (AI) is revolutionizing endocrinology by achieving unparalleled diagnostic precision in endocrine malignancies, offering scalable tools to reduce diagnostic errors and improve outcomes. AIM: This study aimed to develop and validate cutting-edge AI models for endocrine tumor evaluation, using multimodal data, ensuring their global generalizability, and deployment feasibility through a privacy-preserving, universally accessible application to promote equitable cancer care. Methods: Advanced deep learning architectures (EfficientNets and ResNets) were rigorously tested on anonymized multimodal datasets (CT, MRI, ultrasonography, cytopathology, and histopathology) from endocrine tumors in the thyroid, pancreas, pituitary gland, adrenal glands, and ovaries. Internal evaluations ensured model reliability, while external testing across diverse datasets from six continents validated generalizability. An online platform was developed, enabling users to test the models with their own data locally. Real-world applicability was confirmed through independent assessments by healthcare professionals worldwide. Results:EfficientNets and ResNets achieved exceptional diagnostic performance across multiple endocrine tumors (AUROC >99%) and robust generalizability. EfficientNetB0 excelled in treatment response monitoring (>97%). When deployed in an online application, EfficientNetB0 exhibited superior computational efficiency, while maintaining rapid processing speeds (<1 second/image) and diagnostic accuracy. Multi-national healthcare professionals validated the online platform’s reliability and usability, underscoring its global applicability. Conclusion: This study demonstrates the transformative impact of AI in endocrine oncology. Our findings illustrate a paradigm shift in biomedical AI, where minimal computational resources yield maximal diagnostic performance. This highlights the potential of AI-driven approaches to optimize diagnostic workflows, even with minimal computational resources, revolutionizing biomedical AI applications in cancer care. APPLICATION: The AI-powered application provides a privacy-preserving, scalable solution for endocrine tumor detection, classification, treatment monitoring, and advanced clinical decision-making. Validated multi-nationally by healthcare professionals, it ensures robust real-world applicability, fostering equitable cancer care globally. Its adaptability across platforms positions it as a universal tool for cancer care worldwide. Presentation: Sunday, July 13, 2025

Issue/ProblemThere are inequalities in children's oral health outcomes with a widening gap between the least and most deprived and the highest rates of dentinal decay in marginalised groups. Traditional public health messaging fails to resonate with community groups due to cultural and linguistic barriers. Community-based co-creative interventions used in practice deserve greater research attention to evidence effectiveness of complex interventions and translation into policy.Description of the problemThe project was conducted over a 1-year period by public health community officers addressing children's oral health inequalities in the most vulnerable communities. The methods used were co-creative storytelling to develop oral health messaging with cultural sensitivity. Academic evaluation focused on the impact on community of women involved and the subsequent role development into community health champions.ResultsA creative, collaborative storytelling intervention co-produced with the Southeast Asian and Pakistani community provided culturally sensitive oral health messaging that was positively received by children and families. It empowered the women involved to become community health champions.LessonsCommunity engagement using co-creation can have multiple outcomes as effective public health interventions as well as role formalisation through empowerment of marginalised women.Key messages• Creative, culturally sensitive methods like storytelling can bridge cultural gaps and improve health education.• Recognition of community champions through role formalisation is required to sustain public health benefits of community engagement.

Background:Glucocorticoids (GCs) predispose individuals to fractures by reducing bone mineral density (BMD) and inducing adiposity. Emerging evidence highlights the harmful effects of adiposity on bone and increased fracture risk. This study aims to investigate GC-induced adiposity as a predictor of fragility fractures in a large population-based cohort.Methods:Data were collected from patients referred to a regional Dual-energy X-ray absorptiometry (DEXA) scanner in the northwest of England from 2004 to 2019 for their first DEXA scan. Patients underwent bilateral femoral and lumbar spine DEXA scans, providing fat percentage data for the abdomen (FPA), left hip (FPLH), right hip (FPRH), and partial body fat (PBF), as well as BMD data over the scanned areas. A questionnaire was administered to gather demographic variables, Fracture Risk Assessment (FRAX) risk factors, and self-reported history of fragility fractures (defined as a fall from standing height after the of age 50). Comparative statistics were conducted between GC and non-GC populations, with further analysis of fractured and non-fractured GC subgroups. A multivariate logistic regression modeled PBF, FPA, FPLH, and FPRH as predictors of non-spine fractures, adjusting for FRAX risk factors: age, sex, body mass index (BMI), smoking, excess alcohol use (defined as >3 units per day), rheumatoid arthritis, history of fracture, family history of fracture, and the left femoral T-score.Results:A total of 8023 GC and 23 523 non-GC patients were referred for scans. The mean age of GC patients was 67.3 years (SD 28.3) compared to 63.8 years (SD 13.7) for non-GC patients. Fractured GC patients had higher BMIs, weighed more, and had higher levels of adiposity than non-GC patients. In the GC population, only peripheral fat was significantly different between fractured and non-fractured groups. Partial body fat% (odds ratio [OR] 3.8, 95% CI 1.2-12.2), FPA% (OR 2.4, 95% CI 1.1-4.8), and FPLH% (OR 3.5, 95% CI 1.1-10.6) all predicted non-spine fractures.Conclusion:A key limitation of this study is the lack of data on the duration and dosage of glucocorticoid (GC) administration, which may have influenced the results. Despite this, GC-induced adiposity was a significant predictor of non-spine fractures, except for fractures in the Fat percentage at the right high (FPRH). High peripheral fat, particularly at the left hip, may indicate regional muscle loss, leading to instability and increased fracture risk. Further research is needed to investigate the relationship between GC dosage, timing, adiposity, and fracture risk, as well as to explore interventions aimed at reversing compositional changes in patients with a history of GC use to prevent fractures.

Abstract Background Cardiopulmonary exercise testing (CPET) is the gold standard for assessing physiological capacity before surgery and can predict postoperative outcomes. Socioeconomic status (SES) can impact surgical outcomes with patients from more deprived backgrounds having greater morbidity and mortality. This is the first study to analyse the relationship between SES and CPET measures in patients being considered for elective surgery. Methods Data from patients who underwent CPET between 2011 and 2024 was analysed. Patients were categorised into deprivation quintiles based on their postcode. Measures including baseline characteristics, V̇O₂ at anaerobic threshold (AT), peak V̇O₂, and VE/V̇CO₂ were compared across quintiles. Multivariable linear and logistic regression models were used to assess the effects of age, sex, BMI, Revised Cardiac Risk Index (RCRI), and deprivation quintile on CPET measures. Results A total of 3344 patients were included in the study (2476 male), who were being assessed prior to procedures in vascular (2006), colorectal (650), upper GI (267), urology (205), and other (216) surgical specialties. Lower socioeconomic status was associated with younger age (p<0.001), higher BMI (p=0.022), smoking prevalence (p<0.001), and RCRI ≥3 (p=0.013). CPET measures were less favourable in the most deprived quintile (Q1) compared to the least (Q5): mean AT was 11.0 vs. 11.5 ml·kg-1·min-1 and peak V̇O2 was 14.8 vs. 16.3 ml·kg-1·min-1 (p<0.05). Conclusion Patients from deprived areas exhibit risk factors for poor health and less favourable CPET measurements, highlighting the potential need for tailored optimisation strategies to help mitigate health disparities.

Due to its position at the air-sea interface, the sea-surface microlayer (SML) modulates the exchange of gases, including the deposition of ozone to the ocean. While ozone deposition to the ocean is a large sink of ozone from the troposphere, the processes involved are not well understood. Previous work has focussed on seawater iodide as a driver of ozone uptake to the ocean, however the SML contains a complex mixture of organic material, which could also impact ozone uptake. The contribution of this organic material to ozone uptake remains particularly unclear.During this project, ozone uptake to seawater was measured by eddy covariance from coastal towers near Penlee Point (Plymouth, UK) and Tudor Hill (Bermuda), and at sea aboard the RV Atlantic Explorer, operating at and around the Bermuda Atlantic Time-series Study site in the Sargasso Sea. Additionally, the chemical component of ozone uptake to seawater was measured using a flow reactor during a trans-Atlantic cruise. This suite of observations has been combined to investigate the driving forces of oceanic ozone uptake. We present data that demonstrate that iodide was not a strong predictor of ozone uptake, despite its fast chemical reaction with ozone and the ubiquitous presence of iodide in the surface ocean.Organic compounds in the SML are of interest to this work because some organic compounds have ozone-reactive functional groups. An example of this is carbon-carbon double bonds, present in some oceanic fatty acids. By increasing chemical reactivity, organic material can therefore augment ozone uptake to the ocean. The contribution of chemical reactions between ozone and organic material to ozone uptake was investigated using the kinetic multilayer model of surface and bulk chemistry (KM-SUB). A simplified system of a monolayer of an unsaturated fatty acid (oleic acid) over seawater was modelled and demonstrated that a monolayer of ozone-reactive surfactants on the ocean surface could contribute substantially more to ozone uptake, compared to environmental levels of aqueous iodide.This work indicates that the commonly applied iodide-based parameterisation for ozone uptake to seawater may not accurately represent the chemical processes involved in ozone deposition to the sea surface. This has implications not only for predicted spatial and temporal variations in the magnitude of ozone deposition, but also for the chemical profile of oxidised gases emitted from the sea surface to the remote marine troposphere.

In deep-inelastic positron-proton scattering, the lepton-jet azimuthal angular asymmetry is measured using data collected with the H1 detector at HERA. When the average transverse momentum of the lepton-jet system, $\lvert \vec{P}_\perp \rvert $, is much larger than the total transverse momentum of the system, $\lvert \vec{q}_\perp \rvert$, the asymmetry between parallel and antiparallel configurations, $\vec{P}_\perp$ and $\vec{q}_\perp$, is expected to be generated by initial and final state soft gluon radiation and can be predicted using perturbation theory. Quantifying the angular properties of the asymmetry therefore provides an additional test of the strong force. Studying the asymmetry is important for future measurements of intrinsic asymmetries generated by the proton's constituents through Transverse Momentum Dependent (TMD) Parton Distribution Functions (PDFs), where this asymmetry constitutes a dominant background. Moments of the azimuthal asymmetries are measured using a machine learning method for unfolding that does not require binning.

Nurse retention remains a pivotal issue, necessitating urgent strategies aimed at the recruitment and retention of highly qualified nurses. However, there is limited knowledge regarding the influence of nurses' personal and professional values, along with work environment, on predicting intent to leave an organization. Utilizing a secondary analysis approach, this study employed logistic regression to predict intent to leave among registered nurses (n=671) using results from the Short Schwartz's Value Survey, the Nurses Professional Values Scale-3, and the Practice Environment Scale of the Nursing Work Index. Regression analysis indicates that the work environment including "Participation in Hospital Affairs" (B=-.665, odds ratio=.514), "Nurse Manager Ability, Leadership, and Support" (B=-.448, odds ratio=.639), and "Staffing and Resource Adequacy" (B=-.589, odds ratio=.555) are significant predictors of nurses' intentions to leave. Establishing and maintaining supportive work environments is essential for retention, highlighting the importance of effective leadership.

A woman in her 60s initially presented with rapid-onset left-sided hemiparesis with later development of slurred speech and left-sided facial droop. Despite ruling out common causes, her condition rapidly progressed with the development of bilateral proximal weakness, ophthalmoplegia, ataxia, and pyramidal signs eventually leading to a cardiorespiratory arrest. Extensive investigations, including computerised tomography (CT), magnetic resonance imaging (MRI), and lumbar puncture (LP), were negative for infectious or vascular aetiologies. Nerve conduction studies (NCS) revealed severe peripheral nerve damage, and despite a provisional diagnosis of Guillain-Barré Syndrome (GBS), the clinical picture aligned more with Bickerstaff Brainstem Encephalitis (BBE) given the central nervous system (CNS) involvement, despite negative anti-GM1 and anti-GQ1b autoantibodies. Treatment involved ventilatory support, immunoglobulins, and steroids. This case report describes a rare and challenging presentation of BBE and reminds clinicians to have a systematic approach to a patient presenting with rapid onset neurological symptoms and that BBE is a clinical diagnosis.