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The therapeutic effect of EZH2 inhibitors in targeting human papillomavirus associated cervical cancer
Get PDFHigh-risk human papillomavirus (HPV) is a crucial risk factor in the development of cervical cancer, where epigenetic modifications and epithelial–mesenchymal transition (EMT) processes have been implicated in cancer progression and metastasis. Enhancer of zeste homolog 2 (EZH2), a histone methyltransferase, is frequently overexpressed in HPV-associated cervical cancers and has been linked to tumour progression. However, there is still no consensus on the mechanisms of their action and their effectiveness on HPV-associated cancers. This study aimed to investigate whether EZH2 inhibitors (EPZ6438 and ZLD1039) can be effective in managing cervical cancer with less toxic effects than the conventional chemotherapeutic drug cisplatin. Proliferation assay and flow cytometry results showed that EZH2 inhibitors effectively induced apoptosis and arrested cells in G0/G1 phase in both HPV+ and HPV- cervical cancer cells. Both inhibitors downregulated the expression of EZH2 and HPV16 E6/E7 at mRNA and protein levels whilst upregulating expressions of p53 and Rb and epithelial markers. In summary, both EZH2 inhibitors showed therapeutic potential in comparison to cisplatin based on cellular and molecular readouts. Additionally, EPZ6438 showed a greater efficacy and higher sensitivity towards HPV+ cells, which was further supported by preliminary in vivo results from the chorioallantoic membrane assay
Towards a global human rights court
No full textSince the UN was founded there have been calls to establish a global human rights court. However, this has never gained much momentum. Rather suddenly, the International Court of Justice has taken up a large number of human rights cases becoming, in effect, this global human rights court. The article discusses the recent developments
Formalizing federated learning and differential privacy for GIS systems in IIIf
No full textGIS systems, like Google maps or ArcGIS, are a ubiquitous central application but are highly privacy critical. In many GIS systems, inputs from various and diverse sensors potentially expose private information. However, in particular, in the context of public safety, the sensor inputs are crucial to provide timely information for example for weather related warning systems. The notion of Differential Privacy (DP) has become an ad hoc standard, most notably adopted for the US census. Federated Learning (FL) facilitates machine learning for mobile distributed scenarios. This paper proposes a notion of DP for FL for infrastructures with actors and policies formalized in the Isabelle Insider and Infrastructure framework (IIIf). To illustrate this extension of the IIIf by FL and DP on a practical example, we apply the extended framework to a case study from GIS systems for extreme weather warning to control privacy
A little history of mathematics
No full textA lively, accessible history of mathematics throughout the ages and across the globe Mathematics is fundamental to our daily lives. Science, computing, economics—all aspects of modern life rely on some kind of maths. But how did our ancestors think about numbers? How did they use mathematics to explain and understand the world around them? Where do numbers even come from? In this Little History, Snezana Lawrence traces the fascinating history of mathematics, from the Egyptians and Babylonians to Renaissance masters and enigma codebreakers. Like literature, music, or philosophy, mathematics has a rich history of breakthroughs, creativity and experimentation. And its story is a global one. We see Chinese Mathematical Art from 200 BCE, the invention of algebra in Baghdad's House of Wisdom, and sangaku geometrical theorems at Japanese shrines. Lawrence goes beyond the familiar names of Newton and Pascal, exploring the prominent role women have played in the history of maths, including Emmy Noether and Maryam Mirzakhani
Development of machine learning-aided rapid CFD prediction for optimal urban wind environment design
No full textThis paper presents a Machine Learning (ML) model based on Computational Fluid Dynamics (CFD), developed to quickly and accurately predict the impact of buildings on the urban wind environment. While CFD simulations are effective for wind studies, such as analyzing wind loads, pedestrian comfort, and pollution dispersion, they require significant computational resources and time. Recently, Machine Learning has demonstrated strong potential in providing accurate and immediate predictions by learning from datasets. By training on CFD-generated data, the ML model can quickly produce accurate and physically consistent results, addressing the limitations of CFD methods. The Reynolds-Averaged Navier-Stokes (RANS) turbulence model was chosen for CFD simulations, which were validated against experimental data, with mesh sensitivity analyzed at a wind speed of 3 m/s. A dataset of 300 cases, involving 100 hypothetical buildings and three wind speeds (3, 4, and 5 m/s), was generated to train the ML model. A multi-output regression model was proposed to effectively predict key parameters—wind velocity, turbulence intensity, and CO₂ mass fraction—in the selected urban domain. The Random Forest algorithm, which best represented the CFD results, was selected for model development. The ML model demonstrated high efficiency on new data, achieving 88-96% accuracy. This work offers a fast and precise prediction tool, valuable for urban design and related applications
Bridging the gap: challenges and solutions in the transition to practice from midwifery education to clinical practice
No full textA conference presentation at the Midwifery and Maternity Festival to present the findings of phase 2 of my Professional Doctorate
Exploring how digital communication influences consumer sustainable consumption and wellbeing
No full textClimate change, a major 21st-century challenge, poses as a great environmental risk, which includes temperature changes, extreme weather events, and increasing greenhouse gas emissions. The 2016 Paris Agreement highlights the need to adopt sustainable practices. Transportation, is a major source of environmental emission, with car manufacturers developing eco-friendly substitutes like electric vehicles (EVs) to restraint global carbon footprint. Limited research exists on applying digital communications strategies explicitly to EVs. The purpose of this study is to explore how digital communication strategies, particularly, firm generated content and opinion leadership, promotes pro-environmental behaviours like adopting electric vehicles and its impact on consumer well-being. The literature underscores the transformative potential of digital communications in promoting EVs, provided strategies are culturally nuanced, risk-aware, and inclusive.
A mixed-methods approach was applied, engaging the use of semi-structured interviews (n = 30) via Zoom, following quota sampling. Respondents were categorized into EV owners, non-EV owners, and prospective vehicle buyers to capture diverse market opinions. Thematic analysis was done on the interview data to classify and define the presented data by recognising underlying themes. To collective quantitative insights an online survey (n = 550) was completed. Amos 28 was employed to create a structural equation model, confirming the validity and reliability of the data. Data collection was conducted from September 1 to November 2, 2023, collecting 620 responses via Survey Monkey. Data was collected from 620 UK participants over two months, with 550 completing the survey. The survey data were examined by means of Structural Equation Modelling to recognise relations between digital communication strategies, emotions, moral obligations, and EV adoption intents.
The findings from qualitative data analysis through semi-structured interviews point to psychological factors, predominantly an inclination towards being risk aversive, and it acts as a deterrent for consumer behaviour in the EV market. Risk-averse individuals tend to view electric vehicles as carrying higher uncertainty compared to conventional gasoline-powered vehicles. This research underscores the importance of psychological factors, contrasting with prior studies that focused on external factors like cost and infrastructure. Addressing the concerns of risk-averse consumers is essential for accelerating EV adoption and achieving environmental goals. The results from the interviews also showed that positive emotions were a stronger indicator of pro-environmental behaviour along with social norms. The participants were more encouraged when their friends, family and neighbours took part in pro-environmental behaviour as opposed to just relying on their own. The participants felt a sense of satisfaction and happiness when partaking in any environmentally friendly actions. The participants also mentioned that by taking part in pro-environmental behaviour it has a positive effect on their consumer well-being. Notably, how using an EV makes them feel less stressed about pollution and creates a sense of satisfaction and mental ease that they are doing the right thing.
This study further analysed proposed hypothesised relations between major constructs, with the use of structural equation modelling. This helped to form the findings from the online survey which was used to collect quantitative data. The findings from the hypothesis testing reveal that all proposed relationships involving the variables are statistically important. Digital communication strategies (opinion leadership and firm-generated content) revealed a strong positive impact on moral obligations incorporating subjective social norms and personal norms and a moderate influence on emotions. Moral obligations developed as the strongest predictor of responsible behaviour, highlighting their impact in driving pro-environmental behaviour like EV adoption. Emotions further supported responsible behaviour, emphasizing their role. Risk aversion displayed a considerable positive impact on responsible behaviour. The model displayed strong validity and reliability, confirming the theoretical consistency of incorporating second-order constructs.
The findings help to develop theoretical frameworks by integrating psychological factors into electric vehicle adoption. Furthermore, the data collected in this study have wider influences towards the theoretical understanding of green technology and sustainability and their use and adoption. Practically speaking, managers can focus on applying strategies which can help to reduce any observed risks which are predominantly seen when it comes to owning EVs. Companies can handle consumer risks through steps such as providing better warranties, along with user friendly features, creating educational information that can focus on EV durability, and partnering with credible influencers in order to build trust. Government policymakers are also encouraged to support initiatives such as EV specific driving courses which can help to improve driver confidence. The research mainly highlights the need to attend any psychological barriers which are present in EV adoption, while suggesting approaches which are relevant to industry stakeholders while providing wider applications for sustainable technology adoption
Bridging the gap: findings from focus groups on challenges and solutions in the transition from midwifery education to clinical practice
Get PDFTo explore the experiences of student midwives as they transition into clinical practice. This study, conducted as part of a Professional Doctorate, aims to enhance support, supervision and training by identifying the factors that facilitate or hinder a successful transition during their programme.
A qualitative approach, using purposeful recruitment to select participants who can provide in-depth insights into the challenges and experiences faced during this critical phase. Data were collected through focus group discussions, transcribed verbatim, and thematic analysis was conducted to identify key themes and patterns within the data. Ethical consent was obtained through the university's Middlesex Online Research Ethics (MORE) form.
The transition from education to clinical practice in midwifery is marked by several consistent themes across all three focus groups. Participants commonly faced a discrepancy between their expectations and the realities of clinical practice, primarily due to inconsistent mentorship and varying levels of support. The lack of hands-on practical training, exacerbated by the COVID-19 pandemic, was a significant challenge, highlighting gaps in their education. Emotional resilience and personal motivation were crucial for navigating these challenges, with participants relying on their passion for midwifery to persevere.
Suggestions for improvement included better integration of practical training with theoretical learning, more consistent mentorship and early placement experiences in less intense environments to build foundational skills. Overall, the themes underscore the need for a more supportive structure and a hands-on approach to midwifery education and training, to better prepare students for the demands of clinical practice
Der ROPO-Effekt im B2B-Umfeld – Eine Analyse anhand eines Multichannel-Unternehmens im Produktgeschäft des deutschen Maschinenbaus
No full textThis dissertation analyses the occurrence of the ROPO effect in B2B. ROPO stands for Re-search Online Purchase Offline and describes a purchasing behaviour where the online chan-nel is used for research purposes while the order is placed offline. ROPO is a common buying behaviour among consumers and is well known in B2C. The problem of the ROPO effect lies in the missing gross sales of the online channel, which is a serious problem for pure online re-tailers, but also for retailers that use both channels (multichannel retailers) due to the process costs caused by manually processed orders.
The aim of this dissertation is to analyse the reasons for ROPO behaviour in B2B, focusing on the product business of multichannel companies. This is where the research gap lies. The ROPO effect has been well analysed within B2C, but research has not yet considered B2B and organisational purchasing processes.
As this is a new area of research that needs to be explored, qualitative methods are used. The research takes the form of a case study in which qualitative interviews are conducted with experts from several companies in the German engineering sector.
The results show that the reasons for the ROPO effect in B2B can be found in different ele-ments of the purchasing process. Responsibilities and constraints within an organisational pur-chasing process are part of it, while psychological factors, perceived benefits of different chan-nels for search and purchase, situational, product-related factors and the risk of the purchas-ing situation itself also play an important role. An important finding is that these factors influ-ence each other, so that they cannot be seen and treated as separate factors.
This dissertation extends the ROPO research by organisational buying behaviour and the re-search of the organisational buying decision process by channel decision. Furthermore, these results enable companies to analyse their own situation with regard to the ROPO effect and provide a valid basis for the development of strategies to avoid the ROPO effect