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  1. Article: Supporting self-management in women with pre-existing diabetes in pregnancy: a mixed-methods sequential comparative case study.

    Sushko, Katelyn / Strachan, Patricia / Butt, Michelle / Nerenberg, Kara / Sherifali, Diana

    BMC nursing

    2024  Volume 23, Issue 1, Page(s) 1

    Abstract: Introduction: Maternal glycemia is associated with pregnancy outcomes. Thus, supporting the self-management experiences and preferences of pregnant women with type 1 and type 2 diabetes is crucial to optimize glucose control and perinatal outcomes.: ... ...

    Abstract Introduction: Maternal glycemia is associated with pregnancy outcomes. Thus, supporting the self-management experiences and preferences of pregnant women with type 1 and type 2 diabetes is crucial to optimize glucose control and perinatal outcomes.
    Research design and methods: This paper describes the mixed methods integration of a sequential comparative case study. The objectives are threefold, as we integrated the quantitative and qualitative data within the overall mixed methods design: (1) to determine the predictors of glycemic control during pregnancy; (2) to understand the experience and diabetes self-management support needs during pregnancy among women with pre-existing diabetes; (3) to assess how self-management and support experiences helpe to explain glycemic control among women with pre-existing diabetes in pregnancy. The purpose of the mixing was to integrate the quantitative and qualitative data to develop rich descriptive cases of how diabetes self-management and support experiences and preferences in women with type 1 and type 2 diabetes during pregnancy help explain glucose control. A narrative approach was used to weave together the statistics and themes and the quantitative results were integrated visually alongside the qualitative themes to display the data integration.
    Results: The quantitative results found that women achieved "at target" glucose control (mean A1C of the cohort by the third visit: 6.36% [95% Confidence Interval 6.11%, 6.60%]). The qualitative findings revealed that feelings of fear resulted in an isolating and mentally exhausting pregnancy. The quantitative data also indicated that women reported high levels of self-efficacy that increased throughout pregnancy. Qualitative data revealed that women who had worked hard to optimize glycemia during pregnancy were confident in their self-management. However, they lacked support from their healthcare team, particularly around self-management of diabetes during labour and delivery.
    Conclusions: The achievement of optimal glycemia during pregnancy was motivated by fear of pregnancy complications and came at a cost to women's mental health. Mental health support, allowing women autonomy, and the provision of peer support may improve the experience of diabetes self-management during pregnancy. Future work should focus on developing, evaluating and implementing interventions that support these preferences.
    Language English
    Publishing date 2024-01-02
    Publishing country England
    Document type Journal Article
    ZDB-ID 2091496-9
    ISSN 1472-6955
    ISSN 1472-6955
    DOI 10.1186/s12912-023-01659-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Effects of carbon concentration on the local atomic structure of amorphous GST.

    Appleton, Robert J / McClure, Zachary D / Adams, David P / Strachan, Alejandro

    The Journal of chemical physics

    2024  Volume 160, Issue 17

    Abstract: Ge-Sb-Te (GST) alloys are leading phase-change materials for data storage due to the fast phase transition between amorphous and crystalline states. Ongoing research aims at improving the stability of the amorphous phase to improve retention. This can be ...

    Abstract Ge-Sb-Te (GST) alloys are leading phase-change materials for data storage due to the fast phase transition between amorphous and crystalline states. Ongoing research aims at improving the stability of the amorphous phase to improve retention. This can be accomplished by the introduction of carbon as a dopant to Ge2Sb2Te5, which is known to alter the short- and mid-range structure of the amorphous phase and form covalently bonded C clusters, both of which hinder crystallization. The relative importance of these processes as a function of C concentration is not known. We used molecular dynamics simulation based on density functional theory to study how carbon doping affects the atomic structure of GST-C. Carbon doping results in an increase in tetrahedral coordination, especially of Ge atoms, and this is known to stabilize the amorphous phase. We observe an unexpected, non-monotonous trend in the number of tetrahedral bonded Ge with the amount of carbon doping. Our simulations show an increase in the number of tetrahedral bonded Ge up to 5 at.% C, after which the number saturates and begins to decrease above 14 at.% C. The carbon atoms aggregate into clusters, mostly in the form of chains and graphene flakes, leaving less carbon to disrupt the GST matrix at higher carbon concentrations. Different degrees of carbon clustering can explain divergent experimental results for recrystallization temperature for carbon doped GST.
    Language English
    Publishing date 2024-05-15
    Publishing country United States
    Document type Journal Article
    ZDB-ID 3113-6
    ISSN 1089-7690 ; 0021-9606
    ISSN (online) 1089-7690
    ISSN 0021-9606
    DOI 10.1063/5.0203532
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Book: Davidson's principles and practice of medicine

    Davidson, Leybourne S. / Ralston, Stuart H. / Penman, Ian D. / Strachan, Mark WJ / Hobson, Richard P.

    2018  

    Title variant Principles and practice of medicine
    Author's details edited by Stuart H Ralston, Ian D Penman, Mark WJ Strachan, Richard P Hobson
    Subject code 616
    Language English
    Size xx, 1417 Seiten, Illustrationen, Diagramme, 27 cm
    Edition 23rd edition
    Publisher Elsevier
    Publishing place Edinburgh
    Publishing country Great Britain
    Document type Book
    Note Zugang zur Online-Ausgabe über Code
    HBZ-ID HT019728731
    ISBN 978-0-7020-7028-0 ; 978-0-7020-7027-3 ; 0-7020-7028-9 ; 0-7020-7027-0
    Database Catalogue ZB MED Medicine, Health

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  4. Article ; Online: Interpretable Performance Models for Energetic Materials using Parsimonious Neural Networks.

    Appleton, Robert J / Salek, Peter / Casey, Alex D / Barnes, Brian C / Son, Steven F / Strachan, Alejandro

    The journal of physical chemistry. A

    2024  Volume 128, Issue 6, Page(s) 1142–1153

    Abstract: Predictive models for the performance of explosives and propellants are important for their design, optimization, and safety. Thermochemical codes can predict some of these properties from fundamental quantities such as density and formation energies ... ...

    Abstract Predictive models for the performance of explosives and propellants are important for their design, optimization, and safety. Thermochemical codes can predict some of these properties from fundamental quantities such as density and formation energies that can be obtained from first principles. Models that are simpler to evaluate are desirable for efficient, rapid screening of material screening. In addition, interpretable models can provide insight into the physics and chemistry of these materials that could be useful to direct new synthesis. Current state-of-the-art performance models are based on either the parametrization of physics-based expressions or data-driven approaches with minimal interpretability. We use parsimonious neural networks (PNNs) to discover interpretable models for the specific impulse of propellants and detonation velocity and pressure for explosives using data collected from the open literature. A combination of evolutionary optimization with custom neural networks explores and trains models with objective functions that balance accuracy and complexity. For all three properties of interest, we find interpretable models that are Pareto optimal in the accuracy and simplicity space.
    Language English
    Publishing date 2024-01-31
    Publishing country United States
    Document type Journal Article
    ISSN 1520-5215
    ISSN (online) 1520-5215
    DOI 10.1021/acs.jpca.3c06159
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Neoadjuvant tyrosine kinase inhibitor therapy in locally advanced differentiated thyroid cancer: a single centre case series.

    Yeo, J J Y / Stewart, K / Maniam, P / Arman, S / Srinivasan, D / Wall, L / MacNeill, M / Strachan, M / Nixon, I

    The Journal of laryngology and otology

    2023  Volume 137, Issue 11, Page(s) 1237–1243

    Abstract: Objective: Primary surgical resection remains the mainstay of management in locally advanced differentiated thyroid cancer. Tyrosine kinase inhibitors have recently shown promising results in patients with recurrent locally advanced differentiated ... ...

    Abstract Objective: Primary surgical resection remains the mainstay of management in locally advanced differentiated thyroid cancer. Tyrosine kinase inhibitors have recently shown promising results in patients with recurrent locally advanced differentiated thyroid cancer. This study discussed four patients with locally advanced differentiated thyroid cancer managed with tyrosine kinase inhibitors used prior to surgery in the 'neoadjuvant' setting.
    Method: Prospective data collection through a local thyroid database from February 2016 identified four patients with locally advanced differentiated thyroid cancer unsuitable for primary surgical resection commenced on neoadjuvant tyrosine kinase inhibitor therapy.
    Results: All cases had T
    Conclusion: Neoadjuvant tyrosine kinase inhibitors in locally advanced differentiated thyroid cancer can be effective in reducing primary tumour extent to potentially facilitate a more limited surgical resection for local disease control.
    MeSH term(s) Humans ; Thyroid Neoplasms/surgery ; Tyrosine Kinase Inhibitors ; Neoadjuvant Therapy ; Iodine Radioisotopes ; Adenocarcinoma
    Chemical Substances Tyrosine Kinase Inhibitors ; Iodine Radioisotopes
    Language English
    Publishing date 2023-03-22
    Publishing country England
    Document type Journal Article
    ZDB-ID 218299-3
    ISSN 1748-5460 ; 0022-2151
    ISSN (online) 1748-5460
    ISSN 0022-2151
    DOI 10.1017/S0022215123000506
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Understanding the self-management experiences and support needs during pregnancy among women with pre-existing diabetes: a qualitative descriptive study.

    Sushko, Katelyn / Strachan, Patricia / Butt, Michelle / Nerenberg, Kara A / Sherifali, Diana

    BMC pregnancy and childbirth

    2023  Volume 23, Issue 1, Page(s) 309

    Abstract: Background: With the increasing prevalence of pre-existing type 1 and type 2 diabetes in pregnancy and their associated perinatal risks, there is a need to focus on interventions to achieve optimal maternal glycemia to improve pregnancy outcomes. One ... ...

    Abstract Background: With the increasing prevalence of pre-existing type 1 and type 2 diabetes in pregnancy and their associated perinatal risks, there is a need to focus on interventions to achieve optimal maternal glycemia to improve pregnancy outcomes. One strategy focuses on improving diabetes self-management education and support for expectant mothers with diabetes. This study's objective is to describe the experience of managing diabetes during pregnancy and identify the diabetes self-management education and support needs during pregnancy among women with type 1 and type 2 diabetes.
    Methods: Using a qualitative descriptive study design, we conducted semi-structured interviews with 12 women with pre-existing type 1 or 2 diabetes in pregnancy (type 1 diabetes, n = 6; type 2 diabetes, n = 6). We employed conventional content analyses to derive codes and categories directly from the data.
    Results: Four themes were identified that related to the experiences of managing pre-existing diabetes in pregnancy; four others were related to the self-management support needs in this population. Women with diabetes described their experiences of pregnancy as terrifying, isolating, mentally exhausting and accompanied by a loss of control. Self-management support needs reported included healthcare that is individualized, inclusive of mental health support and support from peers and the healthcare team.
    Conclusions: Women with diabetes in pregnancy experience feelings of fear, isolation and a loss of control, which may be improved through personalized management protocols that avoid "painting everybody with the same brush" as well as peer support. Further examination of these simple interventions may yield important impacts on women's experience and sense of connection.
    MeSH term(s) Pregnancy ; Female ; Humans ; Diabetes Mellitus, Type 2/therapy ; Self-Management ; Qualitative Research ; Diabetes Mellitus, Type 1 ; Pregnancy Outcome
    Language English
    Publishing date 2023-05-02
    Publishing country England
    Document type Journal Article
    ZDB-ID 2059869-5
    ISSN 1471-2393 ; 1471-2393
    ISSN (online) 1471-2393
    ISSN 1471-2393
    DOI 10.1186/s12884-023-05542-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Communication skills training for nurses: Is it time for a standardised nursing model?

    Kerr, Debra / Martin, Peter / Furber, Lynn / Winterburn, Sandra / Milnes, Sharyn / Nielsen, Annegrethe / Strachan, Patricia

    Patient education and counseling

    2022  Volume 105, Issue 7, Page(s) 1970–1975

    MeSH term(s) Clinical Competence ; Communication ; Humans ; Models, Nursing ; Nurse-Patient Relations
    Language English
    Publishing date 2022-03-12
    Publishing country Ireland
    Document type Journal Article
    ZDB-ID 605590-4
    ISSN 1873-5134 ; 0738-3991
    ISSN (online) 1873-5134
    ISSN 0738-3991
    DOI 10.1016/j.pec.2022.03.008
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: The Nottingham Ischaemic Cardiovascular Magnetic Resonance resource (NotIs CMR): a prospective paired clinical and imaging scar database-protocol.

    Jathanna, Nikesh / Strachan, Kevin / Erhayiem, Bara / Kamaruddin, Hazlyna / Swoboda, Peter / Auer, Dorothee / Chen, Xin / Jamil-Copley, Shahnaz

    Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance

    2023  Volume 25, Issue 1, Page(s) 69

    Abstract: Introduction: Research utilising artificial intelligence (AI) and cardiovascular magnetic resonance (CMR) is rapidly evolving with various objectives, however AI model development, generalisation and performance may be hindered by availability of robust ...

    Abstract Introduction: Research utilising artificial intelligence (AI) and cardiovascular magnetic resonance (CMR) is rapidly evolving with various objectives, however AI model development, generalisation and performance may be hindered by availability of robust training datasets including contrast enhanced images.
    Methods: NotIs CMR is a large UK, prospective, multicentre, observational cohort study to guide the development of a biventricular AI scar model. Patients with ischaemic heart disease undergoing clinically indicated contrast-enhanced cardiac magnetic resonance imaging will be recruited at Nottingham University Hospitals NHS Trust and Mid-Yorkshire Hospital NHS Trust. Baseline assessment will include cardiac magnetic resonance imaging, demographic data, medical history, electrocardiographic and serum biomarkers. Participants will undergo monitoring for a minimum of 5 years to document any major cardiovascular adverse events. The main objectives include (1) AI training, validation and testing to improve the performance, applicability and adaptability of an AI biventricular scar segmentation model being developed by the authors and (2) develop a curated, disease-specific imaging database to support future research and collaborations and, (3) to explore associations in clinical outcome for future risk prediction modelling studies.
    Conclusion: NotIs CMR will collect and curate disease-specific, paired imaging and clinical datasets to develop an AI biventricular scar model whilst providing a database to support future research and collaboration in Artificial Intelligence and ischaemic heart disease.
    MeSH term(s) Humans ; Cicatrix/diagnostic imaging ; Cicatrix/etiology ; Cicatrix/pathology ; Artificial Intelligence ; Prospective Studies ; Contrast Media ; Predictive Value of Tests ; Magnetic Resonance Imaging/methods ; Myocardial Ischemia/diagnostic imaging ; Coronary Artery Disease ; Magnetic Resonance Spectroscopy ; Magnetic Resonance Imaging, Cine ; Observational Studies as Topic
    Chemical Substances Contrast Media
    Language English
    Publishing date 2023-11-27
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1458034-2
    ISSN 1532-429X ; 1097-6647
    ISSN (online) 1532-429X
    ISSN 1097-6647
    DOI 10.1186/s12968-023-00978-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Book ; Online: Conformal prediction under ambiguous ground truth

    Stutz, David / Roy, Abhijit Guha / Matejovicova, Tatiana / Strachan, Patricia / Cemgil, Ali Taylan / Doucet, Arnaud

    2023  

    Abstract: In safety-critical classification tasks, conformal prediction allows to perform rigorous uncertainty quantification by providing confidence sets including the true class with a user-specified probability. This generally assumes the availability of a held- ...

    Abstract In safety-critical classification tasks, conformal prediction allows to perform rigorous uncertainty quantification by providing confidence sets including the true class with a user-specified probability. This generally assumes the availability of a held-out calibration set with access to ground truth labels. Unfortunately, in many domains, such labels are difficult to obtain and usually approximated by aggregating expert opinions. In fact, this holds true for almost all datasets, including well-known ones such as CIFAR and ImageNet. Applying conformal prediction using such labels underestimates uncertainty. Indeed, when expert opinions are not resolvable, there is inherent ambiguity present in the labels. That is, we do not have ``crisp'', definitive ground truth labels and this uncertainty should be taken into account during calibration. In this paper, we develop a conformal prediction framework for such ambiguous ground truth settings which relies on an approximation of the underlying posterior distribution of labels given inputs. We demonstrate our methodology on synthetic and real datasets, including a case study of skin condition classification in dermatology.
    Keywords Computer Science - Machine Learning ; Computer Science - Computer Vision and Pattern Recognition ; Statistics - Methodology ; Statistics - Machine Learning
    Subject code 006
    Publishing date 2023-07-18
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: Design of Atomic Ordering in Mo

    Wyatt, Brian C / Thakur, Anupma / Nykiel, Kat / Hood, Zachary D / Adhikari, Shiba P / Pulley, Krista K / Highland, Wyatt J / Strachan, Alejandro / Anasori, Babak

    Nano letters

    2023  Volume 23, Issue 3, Page(s) 931–938

    Abstract: The need for novel materials for energy storage and generation calls for chemical control at the atomic scale in nanomaterials. Ordered double-transition-metal MXenes expanded the chemical diversity of the family of atomically layered 2D materials since ... ...

    Abstract The need for novel materials for energy storage and generation calls for chemical control at the atomic scale in nanomaterials. Ordered double-transition-metal MXenes expanded the chemical diversity of the family of atomically layered 2D materials since their discovery in 2015. However, atomistic tunability of ordered MXenes to achieve ideal composition-property relationships has not been yet possible. In this study, we demonstrate the synthesis of Mo
    Language English
    Publishing date 2023-01-26
    Publishing country United States
    Document type Journal Article
    ISSN 1530-6992
    ISSN (online) 1530-6992
    DOI 10.1021/acs.nanolett.2c04287
    Database MEDical Literature Analysis and Retrieval System OnLINE

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