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Sidechain structure-activity relationships of cyclobutane-based small molecule αvβ3 antagonists
Get PDFYesThe integrin family of cell surface extracellular matrix binding proteins are key to several physiological processes involved in tissue development, as well as cancer proliferation and dissemination. They are therefore attractive targets for drug discovery with cancer and non-cancer applications. We have developed a new integrin antagonist chemotype incorporating a functionalised cyclobutane ring as the central scaffold in an arginine–glycine–aspartic acid mimetic structure. Here, we report the synthesis of cyclobutanecarboxylic acids and cyclobutylamines with tetrahydronaphthyridine and aminopyridine arginine mimetic sidechains and masked carboxylic acid aspartic acid mimetic sidechains of varying length. Effective αvβ3 antagonists and new aspartic acid mimetics were identified in cell-based adhesion and invasion assays. A lead compound selected based on in vitro activity (IC50 80 minutes) and synthetic tractability was well-tolerated in vivo. These results show the promise of this synthetic approach for developing αvβ3 antagonists and provide a firm foundation to progress into advanced preclinical evaluation prior to progression towards the clinic. Additionally, they highlight the use of functionalised cyclobutanes as metabolically stable core structures and a straightforward and robust method for their synthesis. This important contribution to the medicinal chemists' toolbox paves the way for increased use of cyclobutanes in drug discovery.This work was funded by Yorkshire Cancer Research (Award reference number B002-PhD) and Prostate Cancer UK (Pilot Grant PA10-01)
The impact of carbon risk on the cost of debt in the listed firms in G7 economies: The role of the Paris agreement
Get PDFYesThe Paris Agreement, signed in 2015, sets ambitious goals for diminishing greenhouse gas emissions and
restricting the rise in global temperature to achieve a less carbon-intensive and climate-resilient global economy.
The Paris Agreement marked a defining moment in the worldwide response to global warming and has significantly
affected the financial sector. Given this background, this research explores the effects of carbon risk on
the cost of debt (CoD) in 1428 listed firms across seven economies from 2011 to 2020. The paper also reflects the
post-Paris Agreement’s involvement and the ESG factors’ moderating effect in the empirical models. The study
finds a significant impact of carbon risk on CoD following the implementation of the Paris Agreement. Notably,
companies with higher carbon risk face higher borrowing rates. However, the effect of ESG on moderating the
relationship between carbon risk and CoD is found to be insignificant. Further analyses confirm this finding, as
individual pillars of ESG (governance and social aspects) also show insignificant moderating effects
Mapping the migrant diagnostic radiographers in the UK: A national survey
Get PDFYesIntroduction: The international recruitment of healthcare workers remains a UK strategy to manage workforce gaps and maintain service delivery. Although not a new phenomenon, this has been exacerbated by chronic shortages. There is a need to profile the current international recruits and identify individual motivators to understand the opportunities for future recruitment and retention initiatives.
Method: A UK-wide electronic survey was conducted using the Jisc platform. The survey was promoted using social media and researcher networks. Eligibility criteria were diagnostic radiographers, internationally educated, and currently working in the UK.
Results: 226 responses were received. Most were working in England (90.7%) and 58.0% were under 35 years of age. The majority had migrated having moved to the UK since 2020 (63.7%) and the main drivers were career and/or training opportunities. Initial education was in 30 different countries, the highest number originating from Africa and Asia, with a median of 6 years post-qualification experience (IQR 4–11yrs). Despite experience, most were employed in band 5 (n = 72) or band 6 posts (n = 95). 56% had postgraduate qualifications on entry and a third had undertaken postgraduate study in the UK.
Conclusion: Based on the survey responses, the profile of internationally recruited diagnostic radiographers is relatively young but with pre-migration experience originating all over the globe. They are motivated to work in the UK particular for career progression opportunities.
Implications for practice: This study provides an insight into the motivations, demographics and employment patterns of internationally recruited radiographers working in the UK
3D numerical modelling and laboratory study of flow field induced by a group of submerged vegetations
Get PDFYesThe three-dimensional (3D) numerical modelling in an open channel flow field of a group of submerged vegetations using computational fluid dynamics (CFD) platform of FLOW-3D HYDRO was performed in this study. A set of acoustic Doppler velocimetry (ADV) measurements have been conducted as benchmark to validate the numerical model. A quantitative comparison was performed on several hydrodynamic variables that impacted the vegetated open channel flow, such as flow depth, streamwise water velocity, turbulent intensity, and Reynolds shear stress. In the numerical analysis, the flow turbulence was treated using the RANS approach (within RNG k-ε); while the Volume Of Fluid (VOF) method was used to track the air-water interface. Structured meshes with hexahedral elements were used to discretize the channel geometry. In the findings, the numerical model reasonably reproduced the flow field and presented corresponding agreement with the experimental turbulent structures. This study showed that the differences in results between various analyses were all less than 10% and concludes that the presented numerical approach can be utilised as an efficient tool for simulations of the flow field within a vegetation patch (i.e. by using the simplified RANS approach)
Multifactorial falls risk assessment and prevention in acute hospitals A practical guide for successful implementation
Get PDFYesNIHR - Health and Social Care Delivery Research (HSDR) programme (project number NIHR129488
The impact of energy diversification on firm performance: The moderating role of corporate social responsibility
Get PDFYesThis paper examines the impact of diverse consumption of energy sources on firm performance, focusing on the moderating role of corporate social responsibility (CSR). The paper uses 45,579 firm-level panel data samples across 56 developing and developed economies from 2002 to 2021. It is observed that the impact of energy diversification in improving firms' performance (measured by the return on assets, return on equity, sales growth, and Tobin's Q) is more potent in firms with higher CSR engagement. The moderating effect of CSR is also more pronounced among firms in high energy-consuming industries than in low energy-consuming ones. Finally, the moderating role of CSR activities is more substantial for firms in countries with individualistic and long-term-oriented cultures
Conversational assessment using artificial intelligence is as clinically useful as depression scales and preferred by users
No full textYesBackground: Depression is prevalent, chronic, and burdensome. Due to limited screening access, depression often remains undiagnosed. Artificial intelligence (AI) models based on spoken responses to interview questions may offer an effective, efficient alternative to other screening methods.
Objective: The primary aim was to use a demographically diverse sample to validate an AI model, previously trained on human-administered interviews, on novel bot-administered interviews, and to check for algorithmic biases related to age, sex, race, and ethnicity.
Methods: Using the Aiberry app, adults recruited via social media (N = 393) completed a brief bot-administered interview and a depression self-report form. An AI model was used to predict form scores based on interview responses alone. For all meaningful discrepancies between model inference and form score, clinicians performed a masked review to determine which one they preferred.
Results: There was strong concurrent validity between the model predictions and raw self-report scores (r = 0.73, MAE = 3.3). 90 % of AI predictions either agreed with self-report or with clinical expert opinion when AI contradicted self-report. There was no differential model performance across age, sex, race, or ethnicity.
Limitations: Limitations include access restrictions (English-speaking ability and access to smartphone or computer with broadband internet) and potential self-selection of participants more favorably predisposed toward AI technology.
Conclusion: The Aiberry model made accurate predictions of depression severity based on remotely collected spoken responses to a bot-administered interview. This study shows promising results for the use of AI as a mental health screening tool on par with self-report measures.Aiberry, Inc
stranger than fiction: that lying, conniving, disabled snitch … burn, burn, burn the witch!
No full textYesAll authors of this work are disabled scholars with varying experiences of learning disability, long-term illness, and chronic health conditions. All authors are neurodivergent. Three are currently unemployed, underemployed, and/or precariously employed. Two are from marginalised ethnic/racial groups. Two are the first in their generation to access higher education. Three have known severe poverty. Not all involved could be named on this publication, hence the inclusion of ghosts.
The lived experience of the authors is woven into a singular cautionary tale to provide an every-person understanding of career blocking within academia for disabled scholars. This artistic endeavour, inherently analytical in its documentation of the ‘identity work’ of our authors, draws on past experience (memory) weaved through imagination. The writing and publishing of this piece required a brutal honesty that lays us open, vulnerable and at risk. However, as you will read, the risk of silence could be greater still
Experimental investigation on the use of PCM heat exchangers in Geo-energy piles and walls
No full textYesThe current paper aims to experimentally investigate the thermal performance of geo-energy piles and walls fabricated with Phase Change heat exchangers. Four prototype concrete geo-energy structures (i.e., piles and walls) were tested using two distinct types of heat exchangers, including standard heat exchangers and PCM heat exchangers. The PCM heat exchangers utilized in the current study were filled up with two different types of Phase Change Materials (PCM) with melting points of 26 °C and 42 °C for geo-energy piles and walls, respectively. The thermal efficiency of the geo-energy piles/walls was experimentally assessed over 100 h of continuous operation under cycles of cooling and heating. The findings illustrated that using PCM heat exchangers led to enhancing the heat transfer efficiency of geo-energy piles by 75 % and 43 % in heating and cooling operations, respectively, compared to those achieved using a standard heat exchanger. Furthermore, the heat transfer performance of geo-energy walls with a PCM heat exchanger was enhanced by 43 % and 32 % in heating and cooling tests, respectively, compared to those achieved using a standard heat exchanger. Moreover, the findings indicated that the inclusion of PCM heat exchangers in geo-energy structures contributed to reducing: the impact on soil temperature and thermal interference radius as well as the potential structural damage due to thermal stress
Stochastic Expansion planning Model for a coordinated Natural gas and Electricity Networks Coupled with Gas-fired Generators, Power-to-Gas Facilities and Renewable Power
No full textYesThis paper presents a stochastic expansion planning model for coordinated natural gas and electricity networks, incorporating gas-fired generators, Power-to-Gas facilities, and renewable power sources. The primary objective is to minimize the total cost over the planning horizon, addressing the significant interdependencies between these networks which, if planned independently, can lead to higher overall costs. The originality of this work lies in its comprehensive integration of both systems, leveraging their synergies to optimize infrastructure investment and operational efficiency. Methodologically, the model employs mixed integer linear programming (MILP) within the General Algebraic Modelling System (GAMS), using a Scenario Tree concept to account for the stochastic nature of renewable energy sources (RESs) and load variations. Data from an adapted twenty-node Belgium gas network and a sixteen-bus UK electricity distribution system were utilized. Results demonstrate substantial cost savings and improved system performance with the integrated approach, validating the model's effectiveness.UKRI Knowledge Transfer Programme Partnership between the University of Bradford and U Energy (Yorkshire) Ltd., Huddersfield, UK. Grant KTP012748