Warped Vacuum Statistics

We consider the effect of warping on the distribution of type IIB flux vacua constructed with Calabi-Yau orientifolds. We derive an analytical form of the distribution that incorporates warping and find close agreement with the results of a Monte Carlo enumeration of vacua. Compared with calculations that neglect warping, we find that for any finite volume compactification, the density of vacua is highly diluted in close proximity to the conifold point, with a steep drop-off within a critical distance.Comment: 30 pages, 2 figure

DNA methylation partially mediates antidiabetic effects of metformin on HbA1c levels in individuals with type 2 diabetes

Aims: Despite metformin being used as first-line pharmacological therapy for type 2 diabetes, its underlying mechanisms remain unclear. We aimed to determine whether metformin altered DNA methylation in newlydiagnosed individuals with type 2 diabetes. Methods and Results: We found that metformin therapy is associated with altered methylation of 26 sites in blood from Scandinavian discovery and replication cohorts (FDR < 0.05), using MethylationEPIC arrays. The majority (88%) of these 26 sites were hypermethylated in patients taking metformin for ~ 3 months compared to controls, who had diabetes but had not taken any diabetes medication. Two of these blood-based methylation markers mirrored the epigenetic pattern in muscle and adipose tissue (FDR < 0.05). Four type 2 diabetes-associated SNPs were annotated to genes with differential methylation between metformin cases and controls, e.g., GRB10, RPTOR, SLC22A18AS and TH2LCRR. Methylation correlated with expression in human islets for two of these genes. Three metformin-associated methylation sites (PKNOX2, WDTC1 and MICB) partially mediate effects of metformin on follow-up HbA1c levels. When combining methylation of these three sites into a score, which was used in a causal mediation analysis, methylation was suggested to mediate up to 32% of metformin’s effects on HbA1c. Conclusion: Metformin-associated alterations in DNA methylation partially mediates metformin’s antidiabetic effects on HbA1c in newly-diagnosed individuals with type 2 diabetes

Key factors supporting implementation of a training program for neonatal family- centered care - a qualitative study

BackgroundTraditionally, the care of infants in neonatal care units has been professionally centered, paying less attention to family support. In recent years, many interventions have been developed to improve family-centered care and thereby parent and infant outcomes. Understanding the key factors of implementation of these interventions would help improve clinical practice. The aim of this study was to describe the staff's perceptions of the implementation of the Close Collaboration with Parents Training Program and to identify the barriers and facilitators of the implementation.MethodsA descriptive qualitative interview study was conducted in eight neonatal intensive care units in Finland. Nineteen unit managers and 32 nurses were interviewed after their unit had finished the 1.5-year training program. Data were analyzed using thematic content analysis.ResultsKey factors facilitating the implementation of the training program were multidisciplinary commitment and the staff's motivation to change their professional role to work as the parents' facilitator. Observable benefits promoted the implementation, as well as experiential learning as a facilitation method. The role of mentor was remarkable as a facilitator. In addition, contextual elements such as support from leadership and proper timing were important.ConclusionsImplementation of family-centered care is facilitated by staff who is prepared to accept parents as partners and adopt a new professional role. Enough time for preparation, readiness for the change, solid support from the leadership, and a multidisciplinary approach are needed as well. Mentoring was found to be one of the key factors facilitating the change.</p

An educational intervention for NICU staff decreased maternal postpartum depression

BackgroundMothers of preterm infants are at increased risk for postpartum depression, which may disturb parenting and child development. Strategies for prevention are needed. Therefore, we evaluated how an educational intervention for neonatal staff affected depression symptoms among mothers of preterm infants.MethodsThe Close Collaboration with Parents intervention was implemented in the NICU at Turku University Hospital in Finland. Maternal depression was compared between the pre-intervention and post-intervention cohorts using the Edinburgh Postnatal Depression Scale. The eligible infants were born ≤1500 g without major anomalies and survived. Data were available from 145 and 93 mothers in the pre-intervention and post-intervention cohorts, respectively, at 4 and/or 6 months of corrected age.ResultsThe depression scores were significantly lower in the post-intervention cohort than in the pre-intervention cohort; the estimated difference was 2.54 points (95% CI, 1.24–3.83), p p = 0.066.ConclusionThe Close Collaboration with Parents intervention decreased depression symptoms among the mothers of very preterm infants. Systematic educational intervention targeted to the whole NICU staff can potentially prevent postnatal depression among mothers of preterm infants.</p

Translating land cover/land use classifications to habitat taxonomies for landscape monitoring: A Mediterranean assessment

Periodic monitoring of biodiversity changes at a landscape scale constitutes a key issue for conservation managers. Earth observation (EO) data offer a potential solution, through direct or indirect mapping of species or habitats. Most national and international programs rely on the use of land cover (LC) and/or land use (LU) classification systems. Yet, these are not as clearly relatable to biodiversity in comparison to habitat classifications, and provide less scope for monitoring. While a conversion from LC/LU classification to habitat classification can be of great utility, differences in definitions and criteria have so far limited the establishment of a unified approach for such translation between these two classification systems. Focusing on five Mediterranean NATURA 2000 sites, this paper considers the scope for three of the most commonly used global LC/LU taxonomies—CORINE Land Cover, the Food and Agricultural Organisation (FAO) land cover classification system (LCCS) and the International Geosphere-Biosphere Programme to be translated to habitat taxonomies. Through both quantitative and expert knowledge based qualitative analysis of selected taxonomies, FAO-LCCS turns out to be the best candidate to cope with the complexity of habitat description and provides a framework for EO and in situ data integration for habitat mapping, reducing uncertainties and class overlaps and bridging the gap between LC/LU and habitats domains for landscape monitoring—a major issue for conservation. This study also highlights the need to modify the FAO-LCCS hierarchical class description process to permit the addition of attributes based on class-specific expert knowledge to select multi-temporal (seasonal) EO data and improve classification. An application of LC/LU to habitat mapping is provided for a coastal Natura 2000 site with high classification accuracy as a result

Validated respiratory drug deposition predictions from 2D and 3D medical images with statistical shape models and convolutional neural networks

37 pages main text (including frontmatter). 9 figures. Additional supplementary material. [v1] Thu, 2 Mar 2023 07:47:07 UTC (14,131 KB). The file archived on this institutional repository is an arXiv preprint. It may not have been certified by peer review.For the one billion sufferers of respiratory disease, managing their disease with inhalers crucially influences their quality of life. Generic treatment plans could be improved with the aid of computational models that account for patient-specific features such as breathing pattern, lung pathology and morphology. Therefore, we aim to develop and validate an automated computational framework for patient-specific deposition modelling. To that end, an image processing approach is proposed that could produce 3D patient respiratory geometries from 2D chest X-rays and 3D CT images. We evaluated the airway and lung morphology produced by our image processing framework, and assessed deposition compared to in vivo data. The 2D-to-3D image processing reproduces airway diameter to 9% median error compared to ground truth segmentations, but is sensitive to outliers of up to 33% due to lung outline noise. Predicted regional deposition gave 5% median error compared to in vivo measurements. The proposed framework is capable of providing patient-specific deposition measurements for varying treatments, to determine which treatment would best satisfy the needs imposed by each patient (such as disease and lung/airway morphology). Integration of patient-specific modelling into clinical practice as an additional decision-making tool could optimise treatment plans and lower the burden of respiratory diseases.Simulations reported in this study were performed on Oracle cloud computing platform, funded by Open Clouds Research Environments (OCRE) ‘Cloud Funding for Research’. JW was funded by a 2019 PhD Scholarship from the Carnegie-Trust for the Universities of Scotland. The in vivo deposition data used in this study was obtained from a project sponsored by Air Liquide