Clinically Applicable Assessment of Tisagenlecleucel CAR T Cell Treatment by Digital Droplet PCR for Copy Number Variant Assessment

Chimeric antigen receptor (CAR) T cell therapy is an innovative immunotherapy for treating cancers in both children and adults with proven utility in numerous clinical trials. Significantly, some CAR T cell therapies have now been approved by relevant national regulatory bodies across numerous countries for clinical therapeutic use outside of clinical trials. One such recently licensed product is tisagenlecleucel, a CAR T therapy approved for the treatment of B-cell acute lymphoblastic leukemia (B-ALL) using autologous T cells from the patient. The genetically engineered T cells target a protein called CD19, common to B cells, through a CAR incorporating a 4-1BB costimulatory domain to improve response. Since tisagenlecleucel is now a standard of care treatment for B-ALL, it is clinically essential to be able to accurately monitor these CAR T cells in patients. Assessment of the copy number variant (CNV) of the CAR T cell products allows this within a clinically acceptable timeframe for optimal patient benefit. However, no standardized method with high reproducibility and efficiency has been described within a routine clinical laboratory setting. Here, we demonstrated a novel digital droplet PCR (ddPCR)-based methodology for the study of CNV (ddPCR-CNV) in 4-1BB CD19-specific CAR T cells with universal applicability across clinical diagnostic laboratories.     

Tobacco particulate matter is more potent than nicotine at upregulating nicotinic receptors on SH-SY5Y cells.

The effect of total particulate matter (TPM) from cigarette smoke on the expression and binding properties of nicotinic acetylcholine receptors (nAChRs) was investigated using a human neuroblastoma cell line (SH-SY5Y). TPM but not nicotine on its own inhibited cell growth at nicotine concentrations above 5 microM. To examine effects on nAChR expression, intact cells were incubated with 3H-epibatidine, and a Bmax of 13 fmoles/10(5) cells (7.8 x 10(4) binding sites/cell) was measured in unexposed cells as well as in cells treated with 2 microM nicotine alone or with TPM containing 2 microM nicotine. Using Scatchard analysis, we measured a Kd of 0.3 nM for 3H-epibatidine binding to nAChRs. This Kd was increased to 1.3 nM by addition of nicotine or TPM extract, both at 2 microM nicotine. Bmax, however, was unaffected, suggesting competitive binding of nicotine to its receptor. Short-term and prolonged 3-day exposures of SH-SY5Y cells to either TPM or nicotine at nicotine concentrations ranging from 0.2 microM to 20 microM increased specific binding, suggesting upregulation of nAChR expression. Most significant, binding was consistently greater in cells pretreated with TPM than in cells pretreated with nicotine. We conclude that TPM contains compounds that are toxic to cells at high concentrations (cell growth inhibition) but that do not compete with nicotine for binding to nAChRs (Scatchard analysis). These non-nicotinic compounds are capable of increasing the expression of one or more of the nAChR subunits. Furthermore, our cell culture assay provides a useful in vitro model for assessing the relative addictiveness of different tobacco products, including that of non-nicotine components.     

Analyzing and automatically labelling the types of user issues that are raised in mobile app reviews

Mobile app reviews by users contain a wealth of information on the issues that users are experiencing. For example, a review might contain a feature request, a bug report, and/or a privacy complaint. Developers, users and app store owners (e.g. Apple, Blackberry, Google, Microsoft) can benefit from a better understanding of these issues – developers can better understand users’ concerns, app store owners can spot anomalous apps, and users can compare similar apps to decide which ones to download or purchase. However, user reviews are not labelled, e.g. we do not know which types of issues are raised in a review. Hence, one must sift through potentially thousands of reviews with slang and abbreviations to understand the various types of issues. Moreover, the unstructured and informal nature of reviews complicates the automated labelling of such reviews. In this paper, we study the multi-labelled nature of reviews from 20 mobile apps in the Google Play Store and Apple App Store. We find that up to 30 % of the reviews raise various types of issues in a single review (e.g. a review might contain a feature request and a bug report). We then propose an approach that can automatically assign multiple labels to reviews based on the raised issues with a precision of 66 % and recall of 65 %. Finally, we apply our approach to address three proof-of-concept analytics use case scenarios: (i) we compare competing apps to assist developers and users, (ii) we provide an overview of 601,221 reviews from 12,000 apps in the Google Play Store to assist app store owners and developers and (iii) we detect anomalous apps in the Google Play Store to assist app store owners and users.     

Managerial identity work in action: performative narratives and anecdotal stories of innovation

Innovation is invariably accepted as a central component of construction sector competitiveness. Yet, there remains a paucity of empirical research, which explores the gap between the way innovation is promoted in the policy discourse and how it is interpreted in practice. We follow the “narrative turn” in organization studies to explore the ways in which senior executives in the UK construction sector ascribe themselves with informal roles while advocating the cause of innovation. Empirical data is derived from narrative interviews with 32 senior executives who self-identify as “innovation champions”. When talking about innovation, the respondents were found to oscillate between performative narratives of innovation and more personalized stories derived from their own experience. The narratives were invariably pre-rehearsed often to the point of being monotonous. In contrast, the personalized stories tended to be engaging and emotionally laden. The tendency for senior executives to oscillate between narratives and stories is seen as an important means through which they search for meaning while at the same time legitimizing their self-identities as “innovation champions”. Of particular note is the way in which senior managers self-ascribe themselves with informal roles which are notably at odds with those described in more formalized narratives.     

A MODEL FOR SIMULATING RESIDENTIAL DEVELOPMENT

This article is the outgrowth of a long period of experimentation with models of residential and other development which focus on the individual decision-maker—the householder in search of a home, and the builder attempting to cater to his desires. The first part of the paper describes the means by which this process is simulated in a computer. Later parts of the paper indicate how this view of consumer behavior has led naturally into a consideration of households' activity patterns and into research on these patterns. In conclusion the author indicates by implication that the integration of these two approaches may lead in the direction of measurements of accessibility and of taking account of the competition fm desirable sites, of consequent increases in the intensity of utilization, and of the rents of these sites. Thus this article, in conjunction with others, illustrates a remarkable convergence between research starting at the level of individual decision units and coming to consider the larger framework, and research starting from gross changes in the metropolitan configuration and coming to give increasing consideration to the actual decision process.