Promises and Image Concerns

According to several psychological and economic studies, non-binding communication can be an effective tool to increase trust and enhance cooperation. This paper focuses on reasons why people stick to a given promise and analyzes to what extent image concerns of being perceived as a promise breaker play a role. In a controlled laboratory experiment, we vary the ex post observability of the promising party's action in order to test for social image concerns. We observe that slightly more promises are kept if the action is revealed than if it is not, yet the difference is not significant. However, a variation in the selection of pre-defined messages across treatments delivers another interesting finding. While most of the promises are kept, statements of intent tend to be broken

High PD-L1/CD274 Expression of Monocytes and Blood Dendritic Cells Is a Risk Factor in Lung Cancer Patients Undergoing Treatment with PD1 Inhibitor Therapy

The aim of this study was to investigate the expression of the coinhibitory molecule PD-L1/CD274 in monocytes and dendritic cells (DC) in the blood of lung cancer patients undergoing PD1 inhibitor therapy and to correlate data with patient’s outcome. PD-L1/CD274 expression of monocytes, CD1c+ myeloid DC (mDC) and CD303+ plasmacytoid DC (pDC) was determined by flow cytometry in peripheral blood at immunotherapy onset. The predictive value of the PD-L1/CD274-expression data was determined by patients’ survival analysis. Patients with a high PD-L1/CD274 expression of monocytes and blood DC subpopulations rarely responded to PD1 inhibitor therapy. Low PD-L1/CD274 expression of monocytes and DC correlated with prolonged progression-free survival (PFS) as well as overall survival (OS). The highest PD-L1/CD274 expression was found in CD14+HLA-DR++CD16+ intermediate monocytes. Whereas the PD-L1/CD274 expression of monocytes and DC showed a strong positive correlation, only the PD-L1/CD274 expression of DC inversely correlated with DC amounts and lymphocyte counts in peripheral blood. Our results implicate that a high PD-L1/CD274 expression of blood monocytes and DC subtypes is a risk factor for therapy response and for the survival of lung cancer patients undergoing PD1 inhibitor therapy

Monitoring Blood Immune Cells in Patients with Advanced Small Cell Lung Cancer Undergoing a Combined Immune Checkpoint Inhibitor/Chemotherapy

In this exploratory prospective observational study on 40 small cell lung cancer (SCLC) patients treated with a combination of chemotherapy and immune checkpoint inhibitors, blood immune cells were characterized by multi-color flow cytometry at the baseline and at the third therapy cycle. The numbers of neutrophils and of T-, B-, and NK cells, as well as the frequency of HLA-DRlow monocytes, 6-SulfoLacNAc (slan)+ non-classical monocytes and circulating dendritic cell (DC) subtypes were determined. The prognostic value of the parameters was evaluated by the patient’s survival analysis with overall survival (OS) as the primary endpoint. In addition, blood cell parameters from SCLC patients were compared to those from non-SCLC (NSCLC). The global median OS of patients was 10.4 ± 1.1 months. Disease progression (15% of patients) correlated with a higher baseline neutrophil/lymphocyte ratio (NLR), more HLA-DRlow monocytes, and lower NK cell and DC numbers. The risk factors for poor OS were the presence of brain/liver metastases, a baseline NLR ≥ 6.1, HLA-DRlow monocytes ≥ 21% of monocytes, slan+ non-classical monocytes < 0.12%, and/or CD1c+ myeloid DC < 0.05% of leukocytes. Lymphocytic subpopulations did not correlate with OS. When comparing biomarkers in SCLC versus NSCLC, SCLC had a higher frequency of brain/liver metastases, a higher NLR, the lowest DC frequencies, and lower NK cell numbers. Brain/liver metastases had a substantial impact on the survival of SCLC patients. At the baseline, 45% of SCLC patients, but only 24% of NSCLC patients, had between three and five risk factors. A high basal NLR, a high frequency of HLA-DRlow monocytes, and low levels of slan+ non-classical monocytes were associated with poor survival in all lung cancer histotypes. Thus, the blood immune cell signature might contribute to a better prediction of SCLC patient outcomes and may uncover the pathophysiological peculiarities of this tumor entity

Monitoring Blood Immune Cells in Patients with Advanced Small Cell Lung Cancer Undergoing a Combined Immune Checkpoint Inhibitor/Chemotherapy

In this exploratory prospective observational study on 40 small cell lung cancer (SCLC) patients treated with a combination of chemotherapy and immune checkpoint inhibitors, blood immune cells were characterized by multi-color flow cytometry at the baseline and at the third therapy cycle. The numbers of neutrophils and of T-, B-, and NK cells, as well as the frequency of HLA-DRlow monocytes, 6-SulfoLacNAc (slan)+ non-classical monocytes and circulating dendritic cell (DC) subtypes were determined. The prognostic value of the parameters was evaluated by the patient’s survival analysis with overall survival (OS) as the primary endpoint. In addition, blood cell parameters from SCLC patients were compared to those from non-SCLC (NSCLC). The global median OS of patients was 10.4 ± 1.1 months. Disease progression (15% of patients) correlated with a higher baseline neutrophil/lymphocyte ratio (NLR), more HLA-DRlow monocytes, and lower NK cell and DC numbers. The risk factors for poor OS were the presence of brain/liver metastases, a baseline NLR ≥ 6.1, HLA-DRlow monocytes ≥ 21% of monocytes, slan+ non-classical monocytes low monocytes, and low levels of slan+ non-classical monocytes were associated with poor survival in all lung cancer histotypes. Thus, the blood immune cell signature might contribute to a better prediction of SCLC patient outcomes and may uncover the pathophysiological peculiarities of this tumor entity

Blood Immune Cell Biomarkers in Lung Cancer Patients Undergoing Treatment with a Combination of Chemotherapy and Immune Checkpoint Blockade

Although immune checkpoint inhibitor (ICI) therapies have improved the treatment of patients with advanced non-small cell lung cancer (NSCLC), several patients do not achieve durable clinical responses. Biomarkers for the prediction of therapy responses are urgently needed. To identify blood cell parameters correlating with patients’ survival, immune cells from 90 patients with NSCLC undergoing a combination of ICI and chemotherapy were prospectively monitored. At the time point of the first and third antibody administration, complete leukocyte blood count, the percentage of HLA-DRlow monocytes, the percentage of 6-Sulfo LacNAc (slan)+CD16+ non-classical monocytes, and the number of circulating dendritic cell (DC) subtypes, as well as T-, B-, and NK cells were determined by multi-color flow cytometry in peripheral blood. The prognostic value of the immune cell parameters investigated was evaluated by patients’ survival analysis, with progression-free survival (PFS) as the main criterion. A total of 67 patients (74.4%) showed a partial remission or a stable disease, and 35% of patients even survived 12 months and longer. Patients with a neutrophil-to-lymphocyte ratio (NLR) ≥6.1, a frequency of HLA-DRlow monocytes ≥22%, of slan+ non-classical monocytes <0.25% of leukocytes, and/or a sum of myeloid DC (MDC) and plasmacytoid DC (PDC) ≤0.14% of leukocytes had a poorer prognosis. The hazard ratio for PFS was 2.097 (1.208–3.640) for the NLR, 1.964 (1.046–3.688) for HLA-DRlow monocytes, 3.202 (1.712–5.99) for slan+ non-classical monocytes, and 2.596 (1.478–4.56) for the MDC/PDC sum. Patients without any of the four risk factors showed the best PFS. Furthermore, low NK cell counts correlated with shorter PFS (cutoff 200 cells/µL). Female patients had lower baseline NK cell counts and a shorter PFS. Our study confirms the usefulness of blood immune cells as biomarkers for clinical response and survival in NSCLC patients undergoing a combined ICI/chemotherapy

Gesprächsanalytisches Transkriptionssystem 2 (GAT 2)

Selting M, Auer P, Barth-Weingarten D, et al. Gesprächsanalytisches Transkriptionssystem 2 (GAT 2). Gesprächsforschung - Online-Zeitschrift zur verbalen Interaktion. 2009;10:353-402.This article presents a revised version of GAT, a transcription system first developed by a group of German conversation analysts and interactional linguists in 1998. GAT tries to follow as many principles and conventions of CA's Jeffersonstyle transcription as possible, yet proposes some conventions which are more compatible with linguistic and phonetic analyses of spoken language, especially for the representation of prosody in talk-in-interaction. After ten years of use by many reseachers in conversation and discourse analysis, it was time to revise the first version, against the background of past experience and in light of new necessities for the transcription of corpora arising from technological advances and methodological developments over recent years. This text presents the new GAT 2 transcription system with all its conventions. It gives detailed instructions on how to transcribe spoken talk on three levels of delicacy: minimal, basic and refined transcript versions. In addition, it briefly introduces a few tools that may be helpful for the user: the online tutorial GAT-TO and the transcription editing software FOLKER.Der Beitrag stellt eine aktualisierte Version des Gesprächsanalytischen Transkriptionssystems (GAT) dar. Nachdem GAT seit seiner Erstvorstellung im Jahr 1998 in der Gesprächsforschung eine breite Verwendung gefunden hat, war es nun an der Zeit, es aufgrund der bisherigen Erfahrungen und im Hinblick auf neue Anforderungen an Transkriptionen vorsichtig zu überarbeiten. Dieser Text stellt das aktualisierte GAT 2-Transkriptionssystem mit allen seinen alten und neuen Konventionen dar, versucht bekannte Zweifelsfälle zu klären und bekannte Schwächen der ersten Version zu beheben. GAT 2 gibt detaillierte Anweisungen zum Erstellen gesprächsanalytischer Transkriptionen auf drei Detailliertheitsstufen, dem Minimal-, Basis- und Feintranskript, sowie neue Vorschläge zur Darstellung komplexerer Phänomene in Sonderzeilen. Zudem wurden für GAT 2 einige zusätzliche Hilfsmittel entwickelt, die im Anhang kurz vorgestellt werden: das Online-Tutorial GAT-TO sowie der Transkriptionseditor FOLKER