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It is increasingly recognized that Alzheimer’s disease (AD) exists before dementia is present and that shifts in amyloid beta occur long before clinical symptoms can be detected. Early detection of these molecular changes is a key aspect for the success of interventions aimed at slowing down rates of cognitive decline. Recent evidence indicates that of the two established methods for measuring amyloid, a decrease in cerebrospinal fluid (CSF) amyloid β1−42 (Aβ1−42) may be an earlier indicator of Alzheimer’s disease risk than measures of amyloid obtained from Positron Emission Tomography (PET). However, CSF collection is highly invasive and expensive. In contrast, blood collection is routinely performed, minimally invasive and cheap. In this work, we develop a blood-based signature that can provide a cheap and minimally invasive estimation of an individual’s CSF amyloid status using a machine learning approach. We show that a Random Forest model derived from plasma analytes can accurately predict subjects as having abnormal (low) CSF Aβ1−42 levels indicative of AD risk (0.84 AUC, 0.78 sensitivity, and 0.73 specificity). Refinement of the modeling indicates that only APOEε4 carrier status and four plasma analytes (CGA, Aβ1−42, Eotaxin 3, APOE) are required to achieve a high level of accuracy. Furthermore, we show across an independent validation cohort that individuals with predicted abnormal CSF Aβ1−42 levels transitioned to an AD diagnosis over 120 months significantly faster than those with predicted normal CSF Aβ1−42 levels and that the resulting model also validates reasonably across PET Aβ1−42 status (0.78 AUC). This is the first study to show that a machine learning approach, using plasma protein levels, age and APOEε4 carrier status, is able to predict CSF Aβ1−42 status, the earliest risk indicator for AD, with high accuracy.

This chapter calls for the endorsement of a ‘career perspective’ when theorizing identity in organizations. It argues that especially the concept of ‘career identity’ can be instructive for settling an ongoing controversy among scholars concerning temporal aspects of ‘continuity’ and ‘change’ in narrative identity construction. Since continuity and change are integral to the career notion, a career perspective helps to explain the under-explored coexistence of dynamic and at the same time stable dimensions of identity. This insight is particularly relevant in light of the changing relationships between organizations and their employees, where career paths are increasingly becoming more discontinuous and therefore unpredictable, protean, and boundaryless. Moreover, the chapter argues that a career perspective on identity helps to raise critical questions regarding how widely dispersed career imperatives influence people’s career choices, and how these imperatives can be resisted.

This chapter’s analysis of a New York Times op-ed article reveals how moral reasoning was undertaken in relation to three identities: the identity of Trump as an incumbent of the role of President, the identity of the writer, and, third, the identity of the collective group of Senior Officials. The moral accountability of Trump was articulated through a set of category predicates normatively associated with Presidents and category predicates normatively associated with Republicans. To have an identity is to be cast into a ‘typification’ or social type with an associated set of expectations about one’s role, relationships, and responsibilities within a culture or social structure. The chapter argues that the ethnomethodological approach underpinning membership categorization analysis (MCA) asks ‘How is identity done, managed, achieved and negotiated in situ?’ Indeed, MCA asks how people draw on and use social identities, in talk or text, in getting their everyday business done. This way of approaching the study of identity is different to other approaches that start with theories of self, or discourse, or power. To conclude, MCA enables us to analyse how, when a social category is used, the person being described is also being judged according to the set of normative expectations associated with that category.

De economische en financiële crisis, en de stijgende uitgaven in de zorg hebben de belangstelling voor het prestatiemanagement in de zorg vergroot. Jeremy Veillard onderzocht hoe het sturen op prestatie kan worden toegepast in de zorg op zowel internationaal en nationaal niveau, als op het niveau van een ziekenhuis. Hij concludeert dat het sturen op prestaties nauw moet aansluiten op de manier waarop de zorg wordt gemanaged. Ook stelt hij dat er goede hulpmiddelen moeten komen waarmee managers en politici het sturen op prestatie kunnen gebruiken.