Cooking without thinking: How understanding cooking as a practice can shed new light on inequalities in healthy eating.

In the UK the way we eat has become the biggest cause of preventable illness and death, placing a huge burden on our health system. Studies have found this is particularly true for those in more deprived areas. In the context of cheap ultra-processed foods, public health interventions to reduce this healthy eating gap often promote cooking 'from scratch' as a means of making increased fruit and vegetable consumption affordable on a tight budget. However the effectiveness of such healthy cooking interventions is debated. This research sought to address this problem by using practice theory to highlight previously overlooked non-cognitive factors involved in everyday cooking performances and consider how they might affect inequalities in healthy eating. Our findings are based on in-depth qualitative research with 25 mothers (including interviews and cooking observations) and a quantitative survey of 310 respondents. In the first section we build the case that cooking is better understood as a practice by outlining the different non-cognitive elements involved in mundane performances of cooking at home (focusing on materials, meanings and competencies). In the second section we focus on the complex relationships between social deprivation, diet and cooking practices, exploring the underexamined links between macro-scale social inequalities and the more micro-scale repeated performances of everyday activities. More specifically we show how social deprivation can impact upon the materials, meanings and competencies of cooking practices in ways that severely limit the capacity for those in more deprived areas to frequently cook with healthier unprocessed ingredients. Finally, we contend that by viewing cooking as a practice and by designing interventions based on this foundation it would be possible to achieve significant benefits to public health.

Predicting outcomes after blunt chest wall trauma: development and external validation of a new prognostic model.

INTRODUCTION: Blunt chest wall trauma accounts for over 15% of all trauma admissions to Emergency Departments worldwide. Reported mortality rates vary between 4 and 60%. Management of this patient group is challenging as a result of the delayed on-set of complications. The aim of this study was to develop and validate a prognostic model that can be used to assist in the management of blunt chest wall trauma. METHODS: There were two distinct phases to the overall study; the development and the validation phases. In the first study phase, the prognostic model was developed through the retrospective analysis of all blunt chest wall trauma patients (n = 274) presenting to the Emergency Department of a regional trauma centre in Wales (2009 to 2011). Multivariable logistic regression was used to develop the model and identify the significant predictors for the development of complications. The model's accuracy and predictive capabilities were assessed. In the second study phase, external validation of the model was completed in a multi-centre prospective study (n = 237) in 2012. The model's accuracy and predictive capabilities were re-assessed for the validation sample. A risk score was developed for use in the clinical setting. RESULTS: Significant predictors of the development of complications were age, number of rib fractures, chronic lung disease, use of pre-injury anticoagulants and oxygen saturation levels. The final model demonstrated an excellent c-index of 0.96 (95% confidence intervals: 0.93 to 0.98). CONCLUSIONS: In our two phase study, we have developed and validated a prognostic model that can be used to assist in the management of blunt chest wall trauma patients. The final risk score provides the clinician with the probability of the development of complications for each individual patient.

How can we mainstream mental health in research engaging the range of Sustainable Development Goals? A theory of change.

Mental health is a leading cause of ill-health worldwide, disproportionately affects low-and-middle-income countries and, increasingly, is considered relevant across the Sustainable Development Goals (SDGs). Hence, we ask: How can we mainstream mental health in research engaging the range of SDGs? We use the UK Research and Innovation Global Challenges Research Fund (GCRF) as a case study. In a previous scoping review, we purposefully sampled non-mental health focused GCRF grants for diversity from 2015 until May-end 2020 (N = 36). In the present study, the principal investigator of each grant in this sample was invited to interview (11 accepting). Snowballing, our networks, and returning to the funding archive secured a further 15 interviews sampled for diversity (Final sample: 13 UK researchers and 13 of their overseas collaborators). A thematic analysis of this data organised key information into a trajectory from the challenges of incorporating mental health impact, to how these challenges might be overcome and, finally, to support needs. This analysis was then organised into a Theory of Change designed to promote the mainstreaming of mental health in global challenges research. We outline the implications for global challenges researchers, mental health practitioners, and global challenge research funders. One important implication is that we provide evidence to encourage funders to engage with the desire of researchers to contribute more broadly to the wellbeing of the communities with whom they work.

Polish is quantitatively different on quartzite flakes used on different worked materials.

Metrology has been successfully used in the last decade to quantify use-wear on stone tools. Such techniques have been mostly applied to fine-grained rocks (chert), while studies on coarse-grained raw materials have been relatively infrequent. In this study, confocal microscopy was employed to investigate polished surfaces on a coarse-grained lithology, quartzite. Wear originating from contact with five different worked materials were classified in a data-driven approach using machine learning. Two different classifiers, a decision tree and a support-vector machine, were used to assign the different textures to a worked material based on a selected number of parameters (Mean density of furrows, Mean depth of furrows, Core material volume-Vmc). The method proved successful, presenting high scores for bone and hide (100%). The obtained classification rates are satisfactory for the other worked materials, with the only exception of cane, which shows overlaps with other materials. Although the results presented here are preliminary, they can be used to develop future studies on quartzite including enlarged sample sizes.

Attachment and antibiotic response of early-stage biofilms studied using resonant hyperspectral imaging.

Many bacterial species readily develop biofilms that act as a protective matrix against external challenge, e.g., from antimicrobial treatment. Therefore, biofilms are often responsible for persistent and recurring infections. Established methods for studying biofilms are either destructive or focus on the biofilm's surface. A non-destructive method that is sensitive to the underside of the biofilm is highly desirable, as it allows studying the penetration of antibiotics through the film. Here, we demonstrate that the high surface sensitivity of resonant hyperspectral imaging provides this capability. The method allows us to monitor the early stages of Escherichia coli biofilm formation, cell attachment and microcolony formation, in-situ and in real-time. We study the response of the biofilm to a number of different antibiotics and verify our observations using confocal microscopy. Based on this ability to closely monitor the surface-bound cells, resonant hyperspectral imaging gives new insights into the antimicrobial resistance of biofilms.

What influences student experience of Graduate Entry Medicine? Qualitative findings from Swansea School of Medicine.

BACKGROUND: The Graduate Entry Programme (GEP) in Medicine delivered by Swansea University (currently in collaboration with Cardiff University) accepts students from a diverse range of academic backgrounds with no restriction in relation to the field of first degree. There is a growing body of literature, predominantly quantitative in nature, regarding the influence of academic background on student achievement but little published information on students' views. AIM: To examine students' views regarding the extent to which previous higher education and wider life experience influence their student experience on the GEP course. METHOD: Recruitment from three student cohorts and group interview data followed by descriptive thematic analysis of anonymized data. RESULTS: Data themes were: (1) previous study experience and its impact on present student experience; (2) the impact of life experience; (3) the impact of the present study on life experience; (4) skills, status and difference; (5) characteristics and expectations of the course; (6) finances and (7) next steps. Previous study experience had little impact on present student experience. However, previous life experience, with time between first degree and GEP, clearly enhances the learning experience. Added maturity and early clinical contact enables students to manage the challenges of the course and the NHS environment despite financial strain and heavy coursework. CONCLUSIONS: Analysing students' views is informative and provides richer insight into experience and expectations than that accessible from quantitative data alone.

Multiparameter antibiotic resistance detection based on hydrodynamic trapping of individual E. coli.

There is an urgent need to develop novel methods for assessing the response of bacteria to antibiotics in a timely manner. Antibiotics are traditionally assessed via their effect on bacteria in a culture medium, which takes 24-48 h and exploits only a single parameter, i.e. growth. Here, we present a multiparameter approach at the single-cell level that takes approximately an hour from spiking the culture to correctly classify susceptible and resistant strains. By hydrodynamically trapping hundreds of bacteria, we simultaneously monitor the evolution of motility and morphology of individual bacteria upon drug administration. We show how this combined detection method provides insights into the activity of antimicrobials at the onset of their action which single parameter and traditional tests cannot offer. Our observations complement the current growth-based methods and highlight the need for future antimicrobial susceptibility tests to take multiple parameters into account.

Nasal Patches and Curves for Expression-Robust 3D Face Recognition.

The potential of the nasal region for expression robust 3D face recognition is thoroughly investigated by a novel five-step algorithm. First, the nose tip location is coarsely detected and the face is segmented, aligned and the nasal region cropped. Then, a very accurate and consistent nasal landmarking algorithm detects seven keypoints on the nasal region. In the third step, a feature extraction algorithm based on the surface normals of Gabor-wavelet filtered depth maps is utilised and, then, a set of spherical patches and curves are localised over the nasal region to provide the feature descriptors. The last step applies a genetic algorithm-based feature selector to detect the most stable patches and curves over different facial expressions. The algorithm provides the highest reported nasal region-based recognition ranks on the FRGC, Bosphorus and BU-3DFE datasets. The results are comparable with, and in many cases better than, many state-of-the-art 3D face recognition algorithms, which use the whole facial domain. The proposed method does not rely on sophisticated alignment or denoising steps, is very robust when only one sample per subject is used in the gallery, and does not require a training step for the landmarking algorithm.

A morphological gradient approach to color edge detection.

A new color edge detector based on vector differences is proposed. The basic technique gives as its output the maximum distance between the vectors within a mask. When applied to scalar-valued images, the method reduces to the classic morphological gradient. The technique is relatively computationally efficient and can also be readily applied to other vector-valued images. To improve the performance in the presence of noise, a novel pairwise outlier rejection scheme is employed. A quantitative evaluation using Pratt's figure of merit shows the new technique to outperform other recently proposed color edge detectors. In addition, application to real images demonstrates the approach to be highly effective despite its low complexity.

Altered clot microstructure detected in obstructive sleep apnoea hypopnoea syndrome.

Abnormal clot microstructure plays a pivotal role in the pathophysiology of thromboembolic diseases. Assessing the viscoelastic properties of clot microstructure using novel parameters, Time to Gel Point (T GP ), Fractal Dimension (d f ) and clot elasticity (G׳ GP ) could explain the increased cardiovascular and thromboembolic events in patients with Obstructive Sleep Apnoea Hypopnea Syndrome (OSAHS). We wanted to compare T GP , d f , and G׳ GP and their diurnal variation in OSAHS and symptomatic comparators. thirty six patients attending a sleep disturbed breathing clinic with symptoms of OSAHS were recruited. T GP , d f and G׳ GP were measured alongside standard coagulation screening, thrombin generation assays, and platelet aggregometry at 16:00 h and immediately after an in-patient sleep study at 07:30 h. OSAHS group had significantly lower afternoon d f than comparators (1.705±0.033 vs. 1.731±0.031, p<0.05). d f showed diurnal variation and only in the OSAHS group, being significantly lower in the afternoon than morning (p<0.05). Diurnal changes in d f correlated with 4% DR, even after controlling for BMI (r=0.37, p=0.02). The lower d f in the afternoon in OSAHS suggests a partial compensatory change that may make up for other pro-clotting abnormalities/hypertension during the night. The change to the thrombotic tendency in the afternoon is biggest in severe OSAHS. d f Shows promise as a new microstructural indicator for abnormal haemostasis in OSAHS.

Technological Analysis of the World's Earliest Shamanic Costume: A Multi-Scalar, Experimental Study of a Red Deer Headdress from the Early Holocene Site of Star Carr, North Yorkshire, UK.

Shamanic belief systems represent the first form of religious practice visible within the global archaeological record. Here we report on the earliest known evidence of shamanic costume: modified red deer crania headdresses from the Early Holocene site of Star Carr (c. 11 kya). More than 90% of the examples from prehistoric Europe come from this one site, establishing it as a place of outstanding shamanistic/cosmological significance. Our work, involving a programme of experimental replication, analysis of macroscopic traces, organic residue analysis and 3D image acquisition, metrology and visualisation, represents the first attempt to understand the manufacturing processes used to create these artefacts. The results produced were unexpected--rather than being carefully crafted objects, elements of their production can only be described as expedient.

New method development in prehistoric stone tool research: evaluating use duration and data analysis protocols.

Lithic microwear is a research field of prehistoric stone tool (lithic) analysis that has been developed with the aim to identify how stone tools were used. It has been shown that laser scanning confocal microscopy has the potential to be a useful quantitative tool in the study of prehistoric stone tool function. In this paper, two important lines of inquiry are investigated: (1) whether the texture of worn surfaces is constant under varying durations of tool use, and (2) the development of rapid objective data analysis protocols. This study reports on the attempt to further develop these areas of study and results in a better understanding of the complexities underlying the development of flexible analytical algorithms for surface analysis. The results show that when sampling is optimised, surface texture may be linked to contact material type, independent of use duration. Further research is needed to validate this finding and test an expanded range of contact materials. The use of automated analytical protocols has shown promise but is only reliable if sampling location and scale are defined. Results suggest that the sampling protocol reports on the degree of worn surface invasiveness, complicating the ability to investigate duration related textural characterisation.

Anaesthesia for serial whole-lung lavage in a patient with severe pulmonary alveolar proteinosis: a case report.

INTRODUCTION: Pulmonary alveolar proteinosis is a rare condition that requires treatment by whole-lung lavage. We report a case of severe pulmonary alveolar proteinosis and discuss a safe and effective strategy for the anaesthetic management of patients undergoing this complex procedure. CASE PRESENTATION: A 34-year-old Caucasian man was diagnosed with severe pulmonary alveolar proteinosis. He developed severe respiratory failure and subsequently underwent serial whole-lung lavage. Our anaesthetic technique included the use of pre-oxygenation, complete lung separation with a left-sided double-lumen endotracheal tube, one-lung ventilation with positive end-expiratory pressure, appropriate ventilatory monitoring, cautious use of positional manoeuvres and single-lumen endotracheal tube exchange for short-term postoperative ventilation. CONCLUSION: Patients with pulmonary alveolar proteinosis may present with severe respiratory failure and require urgent whole-lung lavage. We have described a safe and effective strategy for anaesthesia for whole-lung lavage. We recommend our anaesthetic technique for patients undergoing this complex and uncommon procedure.

Relationships between personal values and reported behavior on ethical scenarios for law students.

Lawyers' values might be considered to play some role in the decisions that are made in everyday legal practice. This study aimed to explore the effects of personal value hierarchies on ethical decision making within the context of several ethical dilemmas. A questionnaire was administered utilizing hypothetical situations presented in 11 ethical scenarios and including the Rokeach Value Survey. Logistic regression results suggested that different personal values were significant predictors of reported behavioral choices on respective ethical scenarios. However, the most important values associated with behavior consistent with ethical conduct in scenarios were 'honesty' and 'equality'. The implications of results are discussed in the contexts of ethics education in a tertiary educational environment and in relation to regulation for the professions.