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  • 1
    In: Frontiers in Psychology, Frontiers Media SA, Vol. 12 ( 2021-8-26)
    Abstract: Resilience has been defined as the maintenance or quick recovery of mental health during and after times of adversity. How to operationalize resilience and to determine the factors and processes that lead to good long-term mental health outcomes in stressor-exposed individuals is a matter of ongoing debate and of critical importance for the advancement of the field. One of the biggest challenges for implementing an outcome-based definition of resilience in longitudinal observational study designs lies in the fact that real-life adversity is usually unpredictable and that its substantial qualitative as well as temporal variability between subjects often precludes defining circumscribed time windows of inter-individually comparable stressor exposure relative to which the maintenance or recovery of mental health can be determined. To address this pertinent issue, we propose to frequently and regularly monitor stressor exposure (E) and mental health problems (P) throughout a study's observation period [Frequent Stressor and Mental Health Monitoring (FRESHMO)-paradigm]. On this basis, a subject's deviation at any single monitoring time point from the study sample's normative E–P relationship (the regression residual) can be used to calculate that subject's current mental health reactivity to stressor exposure (“stressor reactivity,” SR). The SR score takes into account the individual extent of experienced adversity and is comparable between and within subjects. Individual SR time courses across monitoring time points reflect intra-individual temporal variability in SR, where periods of under-reactivity (negative SR score) are associated with accumulation of fewer mental health problems than is normal for the sample. If FRESHMO is accompanied by regular measurement of potential resilience factors, temporal changes in resilience factors can be used to predict SR time courses. An increase in a resilience factor measurement explaining a lagged decrease in SR can then be considered to index a process of adaptation to stressor exposure that promotes a resilient outcome (an allostatic resilience process). This design principle allows resilience research to move beyond merely determining baseline predictors of resilience outcomes, which cannot inform about how individuals successfully adjust and adapt when confronted with adversity. Hence, FRESHMO plus regular resilience factor monitoring incorporates a dynamic-systems perspective into resilience research.
    Type of Medium: Online Resource
    ISSN: 1664-1078
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2563826-9
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  • 2
    In: Frontiers in Immunology, Frontiers Media SA, Vol. 12 ( 2021-11-16)
    Abstract: Treatment of advanced melanoma with combined immune checkpoint inhibitor (ICI) therapy is complicated in up to 50% of cases by immune-related adverse events (irAE) that commonly include hepatitis, colitis and skin reactions. We previously reported that pre-therapy expansion of cytomegalovirus (CMV)-reactive CD4 + effector memory T cells (T EM ) predicts ICI-related hepatitis in a subset of patients with Stage IV melanoma given αPD-1 and αCTLA-4. Here, we develop and validate a 10-color flow cytometry panel for reliably quantifying CD4 + T EM cells and other biomarkers of irAE risk in peripheral blood samples. Compared to previous methods, our new panel performs equally well in measuring CD4 + T EM cells (agreement = 98%) and is superior in resolving CD4 + CD197 + CD45RA - central memory T cells (T CM ) from CD4 + CD197 + CD45RA + naive T cells (T naive ). It also enables us to precisely quantify CD14 + monocytes (CV = 6.6%). Our new “monocyte and T cell” (MoT) assay predicts immune-related hepatitis with a positive predictive value (PPV) of 83% and negative predictive value (NPV) of 80%. Our essential improvements open the possibility of sharing our predictive methods with other clinical centers. Furthermore, condensing measurements of monocyte and memory T cell subsets into a single assay simplifies our workflows and facilitates computational analyses.
    Type of Medium: Online Resource
    ISSN: 1664-3224
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2606827-8
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