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This scientific article aims to evaluate the efficacy of the drug Doxorubicin for treating hepatocellular carcinoma (HCC) in Egypt. The study analyzes data from patients referred to a multi-disciplinary consultation at the National Cancer Institute, Cairo University. The study includes 40 intermediate-stage HCC patients who underwent treatment with either Doxorubicin-Lipiodol or Doxorubicin-loaded drug-eluting beads-trans-arterial chemoembolization (DEB-TACE).

Patients referred to a multi-disciplinary consultation at the National Cancer Institute, Cairo University with a possible diagnosis of HCC in the intermediate stage were eligible for the study.

The study finds that the plasma peak concentration of Doxorubicin is significantly higher in patients treated with Lipiodol compared to those treated with DEB-TACE. The median plasma peak concentration of patients treated with Lipiodol was significantly higher 424 (202.5–731) than the peak level of patients treated with beads 84.95 (26.6–156.5) with p-value = 0.036. However, there is no significant difference in other pharmacokinetic parameters between the two treatment groups. The research article also investigates the genetic polymorphisms in HCC patients treated with Doxorubicin-Lipiodol and Doxorubicin-loaded DEB-TACE. It identifies a significant association between the ABCB1 gene (C3435T) and the concentration of Doxorubicin in plasma. Patients with the CCand computed tomography (CT) genotypes of ABCB1 have higher concentrations of Doxorubicin compared to those with the TT genotype. Furthermore, the study examines the progression-free survival rates and tumour response in the two treatment groups. It demonstrates that DEB-TACE patients have a higher progression-free survival rate compared to cTACE patients. DEB-TACE also leads to better tumour regression.

The current study helps to increase the understanding of the genetic factors that may contribute to HCC susceptibility in the Egyptian population. However, it is essential to consider that genetic polymorphism is just one aspect of HCC risk, and other factors such as environment, lifestyle and viral infections also play crucial roles. Further research is needed to elucidate the complex interactions between genetic and environmental factors in HCC development among Egyptians.

Digital transformation is a foundational change in how firms operate and deliver value to customers by using digital technologies to create new business opportunities. The purpose of this study is to offer a conceptual framework by reorganizing the elements of digital transformation, including resources, technology, capabilities and performance, into a workable process and investigating how firms integrate these resources, build new capabilities and transform them into enhanced performance.

This framework builds three blocks: resource integration, organizational capabilities and outcomes, exploring the impact of resource integration on outcomes through organizational capabilities. For resource integration, this study adopts a resource-based view (RBV) and service-dominant logic (SDL) to integrate organizational resources, including information technology (IT)-based resources, which play a role in moderating the effect of resource integration. Moreover, the author argues that firms’ capabilities have two levels: higher-order capabilities and lower-order capabilities, which will convert these resources through the capabilities into organizational performance.

This framework is built to understand the process of digital transformation and its antecedents for firms’ performance in business environments. Drawing on RBV, it provides a more holistic perspective that has been linked to resource integration, organizational capabilities and outcomes at the firm level. In this way, the theoretical basis for diminishing implicitness associated with the current perspective of digital transformation can be strengthened.

This paper offers a coherent discussion of digital transformation and explains the process of digital transformation, thus advancing prior work. The major contribution is connecting the process of digital transformation through which firms integrate resources, i.e. digital technologies and valuable, rare, inimitable and nonsubstitutable (VRIN) and nonVRIN resources as well, to build organizational dynamic capabilities based on RBV and SDL.

In the wine industry, maintaining superior quality standards is crucial to meet the expectations of both producers and consumers. Traditional approaches to assessing wine quality involve labor-intensive processes and rely on the expertise of connoisseurs proficient in identifying taste profiles and key quality factors. In this research, we introduce an innovative and efficient approach centered on the analysis of volatile organic compounds (VOCs) signals using an electronic nose, thereby empowering nonexperts to accurately assess wine quality.

To devise an optimal algorithm for this purpose, we conducted four computational experiments, culminating in the development of a specialized deep learning network. This network seamlessly integrates 1D-convolutional and long-short-term memory layers, tailor-made for the intricate task at hand. Rigorous validation ensued, employing a leave-one-out cross-validation methodology to scrutinize the efficacy of our design.

The outcomes of these e-demonstrates were subjected to meticulous evaluation and analysis, which unequivocally demonstrate that our proposed architecture consistently attains promising recognition accuracies, ranging impressively from 87.8% to an astonishing 99.41%. All this is achieved within a remarkably brief timeframe of a mere 4 seconds. These compelling findings have far-reaching implications, promising to revolutionize the assessment and tracking of wine quality, ultimately affording substantial benefits to the wine industry and all its stakeholders, with a particular focus on the critical aspect of VOCs signal analysis.

This research has not been published anywhere else.

The purpose of this paper is to explore leadership succession in families in business. Although there is a vast amount of research on leadership succession, no attempt has been made to understand this phenomenon by using an intergenerational learning approach. By applying the Double ABC–X model, the authors discuss how resilience is developed through intergenerational learning during family leadership succession in business.

Based on a single case, the authors define pre- and post-event parameters of the business family under study and use the Double ABC–X Model as an analytical framework. Individual and pair interviews, as well as a family firm workshop, were undertaken following an action research approach using multiple interventions. The qualitative data were collected by reflective journals, field notes and observation protocols. Finally, the authors analyze the data according to a circular deconstruction strategy.

The authors find specific pre-event stressor parameters related to mutual mistrust, independent decision making and non-strategic transmission of power, knowledge and responsibility from predecessor to successor. The intervention based on the intergenerational approach during the post-crisis phase focuses on problem solving and coping within the new situation of co-habitation among the two generations. The intergenerational learning approach based on pile-up of demands, adaptive resources and perception is the source of family adaptation. Additionally, the power of the narrative to reflect past events and project the future seems to the point where the family starts developing resilience.

The way family businesses deal with critical and stressful events during leadership succession may lead to intergenerational learning, which is a source of resilient families. The authors apply the Double ABC–X model to understand family leadership succession in business and further develop it to explain how families develop resilience.