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The Fourth Industrial Revolution (4IR) is an era of enormous technical progress that has impacted professionals across industries, including Chartered Accountants (CAs). This study explored how CAs view the impact of the 4IR on their profession, focusing on the shifting roles, competencies, and challenges they face during this transitional period. The research adopted a qualitative approach to data collecting, including 14 semi-structured interviews with participants from various CA backgrounds. This research provides a thorough knowledge of the 4IR’s consequences for the profession and the perceptions of CA’s of the 4IR. Rapid task automation via technologies such as AI is posing a challenge to traditional CA roles, forcing a change towards more analytical thinking and strategic insight. CAs need to develop critical thinking abilities and data analysis ability. Older generations might need support to adapt to the technological changes. Despite fears about job loss due to technology, members were largely optimistic about the 4IR’s professional development potential. Conclusions are drawn and recommendations are given.

Introduction Cell repair dynamics are crucial in optimizing anti-cancer therapies. Various assays (eg, comet assay and γ-H2AX) assess post-radiation repair kinetics, but interpreting such data is challenging and model-based data analyses are required. However, ambiguities in parameter calibration remain an unsolved challenge. To address this, we propose combining survival dose-rate effects with computer simulations to gain knowledge about repair kinetics. Methods After a literature review, theoretical discriminators based on common fractionation/dose-rate-related effects were defined to discard unrealistic model dynamics. The Multi-Hit Repair (MHR) model was calibrated with canine osteosarcoma Abrams cell line data to study the discriminators’ efficacy in scenarios with limited survival data. Additionally, survival dose-rate-dependent data from the human SiHa cervical cancer cell line were used to illustrate the survival behavior at diverse dose-rates and the capability of the MHR to model these data. Results SiHa data confirmed the validity of the proposed discriminators. The discriminators filtered 99% of parameter sets, improving the calibration of Abrams cells data. Furthermore, results from both cell lines may hint universal aspects of cellular repair. Conclusions Dose-rate theoretical discrimination criteria are an effective method to understand repair kinetics and improve radiobiological model calibration. Moreover, this methodology may be used to analyze diverse biological data using dynamic models in-silico .

Over the past decade, ecological connectivity has entered the political agenda, especially within the European transnational context. This evolution has driven the development of structural ecological connectivity and landscape permeability methodologies, such as the Continuum Suitability Index (CSI) presented here, which considers a range of anthropogenic factors that impact ecosystems. Numerous international and national projects have adopted the CSI to assess terrestrial landscape permeability on the macro-regional scale and prioritize areas for the implementation of ecological conservation and restoration measures. Although the CSI methodology has been applied several times, its sensitivity to individual factors, plausibility and ability to maintain consistency and robustness across different data sources and levels of spatial data precision have remained largely unexplored. Here, we presented the conceptual aspects of the CSI methodology, incorporating the outcomes from a literature review and expert workshops, and examined the CSI results for three projects spanning the Alps and Dinaric Mountains. Five key factors—namely, land use, population pressure, landscape fragmentation, environmental protection and topography—were identified as pivotal for analyzing landscape permeability and thus ecological connectivity. Notably, among these factors, population pressure exhibited the highest sensitivity, while fragmentation exerted the least influence on CSI outcomes. When comparing the CSI factors with data on the presence of red-listed species, the environmental protection indicator emerged as the most influential factor. Furthermore, our investigation comparing the different projects indicated that the chosen level of detail and data sources had minimal impact on the CSI results. Collectively, these analyses highlight CSI's adaptability and considerable potential as a versatile and straightforward applicable tool for an initial assessment of ecological connectivity at the macro-regional scale.

Surgery remains an essential element of the multimodality radical treatment of patients with early-stage nonsmall cell lung cancer. In addition, thoracic surgery is one of the key specialties involved in the lung cancer tumour board. The importance of the surgeon in the setting of a multidisciplinary panel is ever-increasing in light of the crucial concept of resectability, which is at the base of patient selection for neoadjuvant/adjuvant treatments within trials and in real-world practice. This review covers some of the topics which are relevant in the daily practice of a thoracic oncological surgeon and should also be known by the nonsurgical members of the tumour board. It covers the following topics: the pre-operative selection of the surgical candidate in terms of fitness in light of the ever-improving nonsurgical treatment alternatives unfit patients may benefit from; the definition of resectability, which is so important to include patients into trials and to select the most appropriate radical treatment; the impact of surgical access and surgical extension with the evolving role of minimally invasive surgery, sublobar resections and parenchymal-sparing sleeve resections to avoid pneumonectomy.

The Fourth Industrial Revolution (4IR) is an era of enormous technical progress that has impacted professionals across industries, including Chartered Accountants (CAs). This study explored how CAs view the impact of the 4IR on their profession, focusing on the shifting roles, competencies, and challenges they face during this transitional period. The research adopted a qualitative approach to data collecting, including 14 semi-structured interviews with participants from various CA backgrounds. This research provides a thorough knowledge of the 4IR’s consequences for the profession and the perceptions of CA’s of the 4IR. Rapid task automation via technologies such as AI is posing a challenge to traditional CA roles, forcing a change towards more analytical thinking and strategic insight. CAs need to develop critical thinking abilities and data analysis ability. Older generations might need support to adapt to the technological changes. Despite fears about job loss due to technology, members were largely optimistic about the 4IR’s professional development potential. Conclusions are drawn and recommendations are given. [ABSTRACT FROM AUTHOR]

Introduction: Cell repair dynamics are crucial in optimizing anti-cancer therapies. Various assays (eg, comet assay and γ-H2AX) assess post-radiation repair kinetics, but interpreting such data is challenging and model-based data analyses are required. However, ambiguities in parameter calibration remain an unsolved challenge. To address this, we propose combining survival dose-rate effects with computer simulations to gain knowledge about repair kinetics. Methods: After a literature review, theoretical discriminators based on common fractionation/dose-rate-related effects were defined to discard unrealistic model dynamics. The Multi-Hit Repair (MHR) model was calibrated with canine osteosarcoma Abrams cell line data to study the discriminators' efficacy in scenarios with limited survival data. Additionally, survival dose-rate-dependent data from the human SiHa cervical cancer cell line were used to illustrate the survival behavior at diverse dose-rates and the capability of the MHR to model these data. Results: SiHa data confirmed the validity of the proposed discriminators. The discriminators filtered 99% of parameter sets, improving the calibration of Abrams cells data. Furthermore, results from both cell lines may hint universal aspects of cellular repair. Conclusions: Dose-rate theoretical discrimination criteria are an effective method to understand repair kinetics and improve radiobiological model calibration. Moreover, this methodology may be used to analyze diverse biological data using dynamic models in-silico. [ABSTRACT FROM AUTHOR]

Colloidal dispersions composed of polymethylmetacrylate particles dispersed in a mixture of cyclohexyl bromide and decalin find widespread use as model systems in optical microscopy experiments. While the system allows simultaneous density and refractive index matching, preparing particles with hard potentials remains challenging, and strong variations in the physical parameters of samples prepared in the same manner are commonly observed. Here, we present data on the measurement of forces between individual pairs of particles in highly diluted dispersions over the course of tens of days using the blinking optical tweezers method. Our results show that the variations in the particle properties are indeed caused by a temporal evolution of the particles' charging. Additional measurements of the influence of the addition of tetrabutylammonium bromide (TBAB) to the dispersions show that already small concentrations of added TBAB salt drastically decrease the electrostatic forces between colloidal particles. However, small, non-negligible contact potentials remain even at the highest TBAB concentrations added.

Background: Hospital readmission rates are used for quality and pay-for-performance initiatives. To identify readmissions from administrative data, two commonly employed methods are focusing either on unplanned readmissions (used by the Centers for Medicare & Medicaid Services, CMS) or potentially avoidable readmissions (used by commercial vendors such as SQLape or 3 M). However, it is not known which of these methods has higher criterion validity and can more accurately identify actually avoidable readmissions., Objectives: A manual record review based on data from seven hospitals was used to compare the validity of the methods by CMS and SQLape., Methods: Seven independent reviewers reviewed 738 single inpatient stays. The sensitivity, specificity, positive predictive value (PPV), and F1 score were examined to characterize the ability of an original CMS method, an adapted version of the CMS method, and the SQLape method to identify unplanned, potentially avoidable, and actually avoidable readmissions., Results: Both versions of the CMS method had greater sensitivity (92/86% vs. 62%) and a higher PPV (84/91% vs. 71%) than the SQLape method, in terms of identifying their outcomes of interest (unplanned vs. potentially avoidable readmissions, respectively). To distinguish actually avoidable readmissions, the two versions of the CMS method again displayed higher sensitivity (90/85% vs. 66%), although the PPV did not differ significantly between the different methods., Conclusions: Thus, the CMS method has both higher criterion validity and greater sensitivity for identifying actually avoidable readmissions, compared with the SQLape method. Consequently, the CMS method should primarily be used for quality initiatives., (© 2024 The Author(s). Journal of Hospital Medicine published by Wiley Periodicals LLC on behalf of Society of Hospital Medicine.)

Technology has a major impact on the way nurses work. Data-driven technologies, such as artificial intelligence (AI), have particularly strong potential to support nurses in their work. However, their use also introduces ambiguities. An example of such a technology is AI-driven lifestyle monitoring in long-term care for older adults, based on data collected from ambient sensors in an older adult's home. Designing and implementing this technology in such an intimate setting requires collaboration with nurses experienced in long-term and older adult care. This viewpoint paper emphasizes the need to incorporate nurses and the nursing perspective into every stage of designing, using, and implementing AI-driven lifestyle monitoring in long-term care settings. It is argued that the technology will not replace nurses, but rather act as a new digital colleague, complementing the humane qualities of nurses and seamlessly integrating into nursing workflows. Several advantages of such a collaboration between nurses and technology are highlighted, as are potential risks such as decreased patient empowerment, depersonalization, lack of transparency, and loss of human contact. Finally, practical suggestions are offered to move forward with integrating the digital colleague., (©Sjors Groeneveld, Gaya Bin Noon, Marjolein E M den Ouden, Harmieke van Os-Medendorp, J E W C van Gemert-Pijnen, Rudolf M Verdaasdonk, Plinio Pelegrini Morita. Originally published in JMIR Nursing (https://nursing.jmir.org), 23.05.2024.)

Competing Interests: The authors declare that they do not have any conflicts of interest.

Introduction: Hyperthermia (HT) induces various cellular biological processes, such as repair impairment and direct HT cell killing. In this context, in-silico biophysical models that translate deviations in the treatment conditions into clinical outcome variations may be used to study the extent of such processes and their influence on combined hyperthermia plus radiotherapy (HT + RT) treatments under varying conditions., Methods: An extended linear-quadratic model calibrated for SiHa and HeLa cell lines (cervical cancer) was used to theoretically study the impact of varying HT treatment conditions on radiosensitization and direct HT cell killing effect. Simulated patients were generated to compute the Tumor Control Probability (TCP) under different HT conditions (number of HT sessions, temperature and time interval), which were randomly selected within margins based on reported patient data., Results: Under the studied conditions, model-based simulations suggested a treatment improvement with a total CEM43 thermal dose of approximately 10 min. Additionally, for a given thermal dose, TCP increased with the number of HT sessions. Furthermore, in the simulations, we showed that the TCP dependence on the temperature/time interval is more correlated with the mean value than with the minimum/maximum value and that comparing the treatment outcome with the mean temperature can be an excellent strategy for studying the time interval effect., Conclusion: The use of thermoradiobiological models allows us to theoretically study the impact of varying thermal conditions on HT + RT treatment outcomes. This approach can be used to optimize HT treatments, design clinical trials, and interpret patient data.

Introduction: There is an ongoing scientific discussion, that anti-cancer effects induced by radiofrequency (RF)-hyperthermia might not be solely attributable to subsequent temperature elevations at the tumor site but also to non-temperature-induced effects. The exact molecular mechanisms behind said potential non-thermal RF effects remain largely elusive, however, limiting their therapeutical targetability., Objective: Therefore, we aim to provide an overview of the current literature on potential non-temperature-induced molecular effects within cancer cells in response to RF-electromagnetic fields (RF-EMF)., Material and Methods: This literature review was conducted following the PRISMA guidelines. For this purpose, a MeSH-term-defined literature search on MEDLINE (PubMed) and Scopus (Elsevier) was conducted on March 23 rd , 2024. Essential criteria herein included the continuous wave RF-EMF nature (3 kHz - 300 GHz) of the source, the securing of temperature-controlled circumstances within the trials, and the preclinical nature of the trials., Results: Analysis of the data processed in this review suggests that RF-EMF radiation of various frequencies seems to be able to induce significant non-temperature-induced anti-cancer effects. These effects span from mitotic arrest and growth inhibition to cancer cell death in the form of autophagy and apoptosis and appear to be mostly exclusive to cancer cells. Several cellular mechanisms were identified through which RF-EMF radiation potentially imposes its anti-cancer effects. Among those, by reviewing the included publications, we identified RF-EMF-induced ion channel activation, altered gene expression, altered membrane potentials, membrane oscillations, and blebbing, as well as changes in cytoskeletal structure and cell morphology., Conclusion: The existent literature points toward a yet untapped therapeutic potential of RF-EMF treatment, which might aid in damaging cancer cells through bio-electrical and electro-mechanical molecular mechanisms while minimizing adverse effects on healthy tissue cells. Further research is imperative to definitively confirm non-thermal EMF effects as well as to determine optimal cancer-type-specific RF-EMF frequencies, field intensities, and exposure intervals.