Modelling competencies for computing education beyond 2020: a research based approach to defining competencies in the computing disciplines.

How might the content and outcomes of tertiary education programmes be described and analysed in order to understand how they are structured and function? To address this question we develop a framework for modelling graduate competencies linked to tertiary degree programmes in the computing disciplines. While the focus of our work is computing the framework is applicable to education more broadly. The work presented here draws upon the pioneering curricular document for information technology (IT2017), curricular competency frameworks, other related documents such as the software engineering competency model (SWECOM), the Skills Framework for the Information Age (SFIA), current research in competency models, and elicitation workshop results from recent computing conferences. The aim is to inform the ongoing Computing Curricula (CC2020) project, an endeavour supported by the Association for Computing Machinery (ACM) and the IEEE Computer Society. We develop the Competency Learning Framework (CoLeaF), providing an internationally relevant tool for describing competencies. We argue that this competency based approach is well suited for constructing learning environments and assists degree programme architects in dealing with the challenge of developing, describing and including competencies relevant to computer and IT professionals. In this paper we demonstrate how the CoLeaF competency framework can be applied in practice, and though a series of case studies demonstrate its effectiveness and analytical power as a tool for describing and comparing degree programmes in the international higher education landscape

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

Abstract: Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

Funder: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)Funder: National Center for Research Resources under award number 1 C06 RR12463-01, VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.Funder: Susan G Komen Foundation (CCR CCR18547966) and a Young Investigator Grant from the Breast Cancer Alliance.Funder: The Canadian Cancer SocietyFunder: Breast Cancer Research Foundation (BCRF), Grant No. 17-194Abstract: Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Funder: Breast Cancer Research Foundation (BCRF); doi: https://doi.org/10.13039/100001006Abstract: Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting

Retail Security Guards’ Experiences of, and Reactions to, Workplace Violence

Retail security guards (RSGs) are at particular risk of being assaulted at work. Even though incidents of workplace violence (WV) and the security industry are growing, little is known about how RSGs experience and react to assault. Consequently, this qualitatively-driven mixed-method research focuses on what the experience of WV and organisational support networks means for RSGs’ emotional well-being, on RSGs’ reactions to support and on how RSGs avoid future victimisation. To gain further insights into these phenomena, 488 questionnaires and 20 interviews were completed with a sample of contracted RSGs. Firstly, cognitive appraisal theory shows that differences in RSGs’ appraisals of both violent acts and a number of contextual factors contribute to the differences in RSGs’ emotional reactions to WV events. Secondly, drawing on elements of social exchange theory and organisational support theory reveals that the support source and the support action have a significant impact on RSGs’ emotional well-being and on the levels of loyalty and work motivation they feel towards the security company and the retail client. Thirdly, by applying the concept of functional and dysfunctional worry of crime, it is shown that different forms of worry can simultaneously facilitate and inhibit RSGs’ decisions to make use of proactive and inactive self-protection measures. Finally, this study uncovers that providing RSGs with appropriate support networks enhances their emotional well-being and their organisational commitment, whereas an absence of networks increases their desire to leave their jobs. It reveals that the provision of equipment, training and manpower increase RSGs’ feelings of safety which helps to decrease their need for undesirable self-protection measures. Ultimately, exploring RSGs’ emotional responses to WV and organisational support produced valuable insights into their occupational and behavioural reactions. This in turn might help to reduce WV-related turnover rates within the industry, improve training for RSGs and promote their protection

Security Guards as Victims of Violence: Using Organisational Support Theory to Understand How Support for Victims could have Positive Implications for the Security Industry.

Although it has been acknowledged that security guards are at high risk of becoming victims of violence, little previous research has considered (a) what support is provided for victims and (b) how a lack of adequate provision could have negative impacts on both security guards and the security industry. The paper focuses on data collected with retail security guards working in the United Kingdom through 488 online surveys and 20 face-to-face interviews. We outline the sources of support respondents would like to see and through the gaze of organisational support theory identify how inadequate support can generate negative emotions, a lack of loyalty towards employers and a lack of work motivation. We conclude that while international research across larger samples of security guards might help to build a more composite picture of the support needs of victimised security guards, the findings of this study have important implications for the security industry and pave the way for a potentially important body of research

Pneumomediastinum and Bilateral Pneumothoraces Causing Respiratory Failure after Thyroid Surgery

We report the first case of severe respiratory failure after thyroid surgery requiring venovenous extracorporeal membrane oxygenation (vvECMO). The patient was a 41-year-old woman with metastatic thyroid cancer. She underwent thyroidectomy, including left lateral and bilateral central neck dissection. During surgery, the patient developed pneumomediastinum with bilateral pneumothoraces. Despite early treatment with bilateral chest tubes and no evidence of a tracheal perforation, the patient developed severe respiratory failure after extubation on the intensive care unit. Because pneumothorax and pneumomediastinum might be more common than reported, and considering increasing cases of thyroid surgery, staff should remain vigilant of pulmonary complications after thyroid surgery

Explainable Boosting Machine approach identifies risk factors for acute renal failure

Abstract Background Risk stratification and outcome prediction are crucial for intensive care resource planning. In addressing the large data sets of intensive care unit (ICU) patients, we employed the Explainable Boosting Machine (EBM), a novel machine learning model, to identify determinants of acute kidney injury (AKI) in these patients. AKI significantly impacts outcomes in the critically ill. Methods An analysis of 3572 ICU patients was conducted. Variables such as average central venous pressure (CVP), mean arterial pressure (MAP), age, gender, and comorbidities were examined. This analysis combined traditional statistical methods with the EBM to gain a detailed understanding of AKI risk factors. Results Our analysis revealed chronic kidney disease, heart failure, arrhythmias, liver disease, and anemia as significant comorbidities influencing AKI risk, with liver disease and anemia being particularly impactful. Surgical factors were also key; lower GI surgery heightened AKI risk, while neurosurgery was associated with a reduced risk. EBM identified four crucial variables affecting AKI prediction: anemia, liver disease, and average CVP increased AKI risk, whereas neurosurgery decreased it. Age was a progressive risk factor, with risk escalating after the age of 50 years. Hemodynamic instability, marked by a MAP below 65 mmHg, was strongly linked to AKI, showcasing a threshold effect at 60 mmHg. Intriguingly, average CVP was a significant predictor, with a critical threshold at 10.7 mmHg. Conclusion Using an Explainable Boosting Machine enhance the precision in AKI risk factors in ICU patients, providing a more nuanced understanding of known AKI risks. This approach allows for refined predictive modeling of AKI, effectively overcoming the limitations of traditional statistical models