Routine measurement of gastric residual volumes involves regularly aspirating the entire stomach contents to assess the volume and colour of the aspirate to inform feeding. This is an established practice in many United Kingdom and Australian neonatal units for preterm infants receiving gastric tube feeds. The rationale is to assess feed tolerance and to predict and potentially prevent necrotising enterocolitis, a serious gut condition. Routine measurement of gastric residual volumes may also be associated with adverse outcomes and harm, including delayed achievement of full enteral feeds and longer neonatal unit stay. Evidence to support the routine measurement of gastric residuals is poor, and previous small trials have not been generalisable to UK or Australian neonatal care. The aim of the neoGASTRIC trial is to test whether avoiding routine measurement of gastric residual volumes in preterm infants reduces the time taken for an infant to reach full enteral feeds without increasing necrotising enterocolitis. neoGASTRIC is an individually randomised controlled trial in neonatal units in the UK and Australia. A target of 7040 infants born before 34weeks' gestation will be randomly allocated, prior to receiving 24h of enteral feeds > 15ml/kg/day, on a 1:1 basis to have no routine gastric residual volumes measured, or to have gastric residual volumes measured routinely. Opt-out consent will be used with parent and staff views explored as part of an embedded process evaluation. The primary superiority outcome is time to reach full milk feeds ≥ 145ml/kg/day for three consecutive days. Bell's stage 2 or 3 necrotising enterocolitis following blinded adjudication will be the key secondary, non-inferiority safety outcome. Other neonatal core outcomes and health care resource use and costs prior to discharge will be evaluated. neoGASTRIC will address a research priority that affects more than 20,000 preterm infants in the United Kingdom and Australia annually. Even modest improvements in clinical outcomes and resource use could result in large clinical benefits and savings at a population level. ISRCTN 16710849. Prospectively registered on 8 February 2023.

To critically review recent findings related to the effects of omega-3 fatty acid supplementation on skeletal muscle, with a particular focus on skeletal muscle protein turnover and mitochondrial function. Evidence indicates that omega-3 fatty acids, particularly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), may support skeletal muscle health by influencing muscle protein synthesis (MPS), mitochondrial function, and redox balance. However, recent meta-analyses reveal inconsistent effects of omega-3 fatty acid supplementation on basal and stimulus-induced MPS, likely due to methodological variability. Omega-3 fatty acid supplementation is seemingly more beneficial in clinical cohorts and preclinical data suggests omega-3s may reduce oxidative stress. Omega-3 fatty acid supplementation is a promising nutritional strategy for supporting skeletal muscle health, via the modulation of MPS and mitochondrial function. However, large-scale trials in a variety of healthy and clinical populations using sustainable sources of omega-3 fatty acids are required before a consensus on efficacy can be made.

Purpose We are observing a significant transformation driven by the advancement of innovative technologies and their integration into consumer markets. Such developments have entailed changes to consumers' in-store shopping experiences, whereby showrooming activities have been reshaping their decision-making. Meanwhile, smart shopping affords consumers more accessible and productive decision-making, where commercial organizations facilitate timely business strategies to capture potential customers. This research draws on the innovation failure and knowledge management theories, investigating the impact of price perceptions and moral values on consumers' purchase intentions in showrooming. Design/methodology/approach Across four experimental studies with different consumer groups, we provide evidence for the joint effect of product price variation and consumers' morality on in-store purchase intentions. Findings We showed that price variation shapes consumers' purchase intentions to the extent that, increasingly, price variation is positively associated with out-of-store purchase intentions, but this influence varies in the presence of price matching. When a price-matching policy is offered, this joint effect is amplified as consumers' inferred motive is negative toward the retailer's policy. In the case of high price variation in the marketplace, price outweighs morality in forming a purchase decision. Originality/value In terms of consumer morality, when consumers recognize retailers' fair price policies, they reward those retailers by choosing them to complete their purchases in-store. We further support that consumers are likely to respond favorably to the salesperson's polite attitude. Our findings also contribute to the broader literature on dynamic capabilities by highlighting how retailers adapt pricing strategies in response to consumer morality and behavior. These insights align with innovation learning frameworks, where corrective pricing strategies serve as responses to prior mismatches in consumer expectations.

With increased access to advanced prenatal neuroimaging and genetic testing, neurological disorders such as brain malformations, brain injuries, and genetic disorders, are increasingly being diagnosed during pregnancy. In this review, we address neonatal neurocritical care considerations for the population with prenatally identified neurological disorders. We identify antenatal considerations, including planning location of delivery, as well as postnatal considerations, including clinical phenotyping, neuromonitoring, neuroimaging, and genetic testing. The importance of interdisciplinary collaboration between obstetrics, maternal-fetal medicine, neonatology, pediatric neurology, neuroradiology, genetics, palliative care, early intervention and habilitative services is emphasized. We outline high-priority research gaps, and highlight the need for large, multicenter studies that capture diverse geographies, populations, care practices and settings longitudinally. IMPACT: Fetal neurology is a rapidly evolving field owing to the increased prenatal diagnosis of neurological disorders; however, the natural history of many fetal neurological disorders is not well known. We identify interdisciplinary neonatal neurocritical care considerations for newborns with prenatally diagnosed neurological disorders, such as neuroimaging, neuromonitoring, and family support. We outline high-priority research gaps in fetal neurology relevant to neurocritical care, including the need to prioritize large-scale longitudinal studies on the etiologies, short- and long-term outcomes of fetal neurologic disorders across diverse geographies and populations to improve counseling and care.

Kappa free light chains (KFLCs) in the cerebrospinal fluid (CSF) have a similar performance to CSF-restricted oligoclonal bands (OCB) for multiple sclerosis (MS) diagnosis. To help with implementation, we set out to resolve several remaining uncertainties: (1) performance in a real-world cohort and the 2024 McDonald criteria; (2) equivalence to OCB in the specific clinical scenario when demonstration of intrathecal immunoglobulin synthesis is essential for MS diagnosis; (3) which KFLC metric has the best diagnostic performance. A retrospective study of 740 cases was conducted, categorised into three groups: MS (2024 McDonald criteria), other neuroinflammatory disorders and non-inflammatory groups. CSF and serum KFLC and albumin were assayed with immunoturbidimetry. OCB status was assessed using isoelectric focusing. Eight KFLC metrics were tested: CSF KFLC, KFLC index, three population-based models of the upper limit for the CSF/serum kappa quotient corrected for CSF/serum albumin quotient, and their corresponding intrathecal fractions. The KFLC index and the KFLC intrathecal fraction performed as well as OCB; no cases were missed when KFLC was mandatory to achieve a MS diagnosis. Intrathecal fraction computation improved the performance of the population-based models. In the setting of the 2024 McDonald criteria, KFLC metrics correcting for the CSF/serum albumin quotient were equivalent to OCBs. The intrathecal fraction provided no advantage over the KFLC index, which is simpler to compute. Importantly, the KFLC index can replace OCB when CSF positivity is essential for diagnosis. We provide an explanation for KFLC's comparable diagnostic performance despite its inability to identify CSF-only clones.

We consider the densest submatrix problem, which seeks the submatrix of fixed size of a given binary matrix that contains the most nonzero entries. This problem is a natural generalization of fundamental problems in combinatorial optimization, e.g., the densest subgraph, maximum clique, and maximum edge biclique problems, and has wide application the study of complex networks. Much recent research has focused on the development of sufficient conditions for exact solution of the densest submatrix problem via convex relaxation. The vast majority of these sufficient conditions establish identification of the densest submatrix within a graph containing exactly one large dense submatrix hidden by noise. The assumptions of these underlying models are not observed in real-world networks, where the data may correspond to a matrix containing many dense submatrices of varying sizes. We extend and generalize these results to the more realistic setting where the input matrix may contain \emph{many} large dense subgraphs. Specifically, we establish sufficient conditions under which we can expect to solve the densest submatrix problem in polynomial time for random input matrices sampled from a generalization of the stochastic block model. Moreover, we also provide sufficient conditions for perfect recovery under a deterministic adversarial. Numerical experiments involving randomly generated problem instances and real-world collaboration and communication networks are used empirically to verify the theoretical phase-transitions to perfect recovery given by these sufficient conditions.

ABSTRACT This article reports on multiple case studies exploring how five Chinese-speaking sojourners demonstrate transcultural abilities and awareness by mediating their linguistic and sociocultural strategies while interacting with non-Chinese-speaking social networks at a UK university. Data are gathered through five participant observations conducted across three social settings, followed by five retrospective interviews. This study expands research on language learning strategies by investigating strategic practices associated with transcultural abilities in authentic second-language social contexts. These strategies can be incorporated into educational programmes to enhance sojourners’ transversal competences during their mobility journey in an increasingly transnational world.

Abstract Introduction and aims Adiposity in early life has been associated with an increased risk of infantile and childhood atopic eczema but evidence for this has been inconsistent. Examining this association can help identify mechanisms which influence the risk of developing atopic eczema and point to measures that may help prevent or control the condition. The aim of this study was to examine the association between adiposity and atopic eczema through infancy and early childhood. Methods Within the Southampton Women Survey, infant/child total body fat was assessed using dual-energy X-ray absorptiometry (DXA) as means of evaluating body composition at birth (n = 933), 4 years (n = 797) and 6 years (n = 1141). Atopic eczema was ascertained using the UK Working Party Diagnostic Criteria at ages 6 months (n = 154/1679, 12 months (n = 174/1655), 3 years (n = 233/1583) and 6 years (n = 217/1427). A directed acyclic graph determined confounders, which were: maternal body mass index, education, smoking during pregnancy, maternal history of eczema in the last 12 months, parity and infant sex. Analyses also adjusted for infant gestational age and age of DXA scan as they directly impact total body fat. Logistic regressions examined the associations between total body fat and atopic eczema at the various timepoints. Results Total body fat at birth, 4 years and 6 years were not related to atopic eczema in infancy or early childhood. However, total body fat > 80th centile at age 4 years was associated with a higher risk of atopic eczema at age 6 years and remained significant after adjusting for confounders (adjusted odds ratio 1.69, 95% confidence interval 1.03–2.77; P = 0.04). Conclusions These findings suggest that excess total body fat > 80th centile in early childhood is associated with a higher risk of childhood atopic eczema. Further research is needed to establish the mechanisms that link excess adiposity at age 4 years and atopic eczema in childhood.

Abstract Introduction and aims Psoriasis is an inflammatory skin disorder affecting > 1 million people in the UK. Machine learning has become an important tool for image processing tasks within dermatology. An emerging technique within this field includes generative artificial intelligence (AI). The aim of this study was to train a generative adversarial network (GAN) to create personalized, AI digital twin images of psoriasis. Methods Overall, 1664 photographs of psoriasis and surrounding normal skin were taken from 57 participants. A total of 375 images from 20 individuals were used to train a GAN (StyleGAN) to generate ‘fake’ but realistic images of psoriasis. In total, 464 of these images were assessed and scored by three dermatologists who graded the images using the erythema and scaling components of the Psoriasis Area and Severity Index; mean erythema and scaling scores were 1.97 ± 0.011 and 1.71 ± 0.021, respectively, for images of moderate psoriasis, and 3.07 ± 0.018 and 3.00 ± 0.025, respectively, for images of severe psoriasis. Results In total, 210 real patient images were subsequently embedded into the latent space of the GAN allowing us to transform clinical photographs into digital twin images, replicating the unique psoriatic lesions of individual patients. Furthermore, comparison of images of different severity by the GAN enabled the identification of treatment and size vectors. Application of these vectors to the digital twin images allows us to observe a prediction for the changes that would be expected following treatment in the clinical setting, i.e. reduction in erythema and scaling with minimal reduction in size of psoriatic lesion. We are currently evaluating the accuracy of the personalized GAN images in predicting improvement in patients’ psoriasis undergoing treatment with ultraviolet. Conclusions This study shows that generative AI, using the StyleGan network, could be used to illustrate a predicted treatment response with antipsoriatic therapy for patients with psoriasis in a clinical setting.