The Transmission of Trauma from Mother to Infant: Radioactive Residues and Counter-Transference in the Case of a Haitian Mother and Her Two-Year-Old Son*

ABSTRACT

Close observation of the interactions between a traumatised mother and her infant son provides information on the modes of transmission of psychic trauma in the mother–infant dyad. Following the presentation of a current literature review on the theme, the subject of “radioactive residue” and counter-transference in the transmission of psychic trauma from mother to infant will be illustrated through a clinical case study that focuses on a Haitian mother and her two-year-old infant son who has been referred to a “transitional care nursery” in urban Paris. The encounter with this mother–infant dyad is analysed through observing the quality of the interactions that take place between the mother and infant in order to determine how a particularly traumatic narrative impacts the mother–infant relationship, in addition to relations with the clinician. Mother and infant respond to one another through the emission and reception of “radioactive residues” as hypothesized by Gampel. This clinical case study shows that there is a need to consider transcultural factors and collective experience and history when analysing traumatic events. Additionally, the case study shows that counter-transference can be an effective clinical tool for gaining access to an infant's experience as the recipient of a traumatic narrative.     

Changes in Quality of Health Care Delivery after Vertical Integration

ObjectivesTo fill an empirical gap in the literature by examining changes in quality of care measures occurring when multispecialty clinic systems were acquired by hospital-owned, vertically integrated health care delivery systems in the Twin Cities area.ConclusionsMoving a clinic system into a vertically integrated delivery system resulted in limited increases in quality of care indicators. Caution is warranted when the acquisition causes disruption in referral patterns.     

Rethinking PICO in the Machine Learning Era: ML-PICO

Background  Machine learning (ML) has captured the attention of many clinicians who may not have formal training in this area but are otherwise increasingly exposed to ML literature that may be relevant to their clinical specialties. ML papers that follow an outcomes-based research format can be assessed using clinical research appraisal frameworks such as PICO (Population, Intervention, Comparison, Outcome). However, the PICO frameworks strain when applied to ML papers that create new ML models, which are akin to diagnostic tests. There is a need for a new framework to help assess such papers. Objective  We propose a new framework to help clinicians systematically read and evaluate medical ML papers whose aim is to create a new ML model: ML-PICO (Machine Learning, Population, Identification, Crosscheck, Outcomes). We describe how the ML-PICO framework can be applied toward appraising literature describing ML models for health care. Conclusion  The relevance of ML to practitioners of clinical medicine is steadily increasing with a growing body of literature. Therefore, it is increasingly important for clinicians to be familiar with how to assess and best utilize these tools. In this paper we have described a practical framework on how to read ML papers that create a new ML model (or diagnostic test): ML-PICO. We hope that this can be used by clinicians to better evaluate the quality and utility of ML papers.     

IFN-alpha1,8 inhibits tumor-induced angiogenesis in murine angiosarcomas.

Interferon-alpha (IFN-alpha) has proved effective in the treatment of hemangiomas, hemangioblastomas, and Kaposi's sarcoma. To investigate the ability of IFNs to inhibit angiosarcoma, we used two transformed murine endothelial cell lines that form angiosarcomas in vivo. SVR and MS1-VEGF cell lines express oncogenic H-ras or vascular endothelial growth factor (VEGF), respectively. IFN-alpha1,8, which is active against murine and human cells, inhibited SVR and MS1-VEGF proliferation in vitro by 40% at 10(3) U/mL (p = 0.028). In vivo, IFN-alpha1,8 inhibited SVR tumor volume by 71% (p = 0.047) and MS1-VEGF volume by 79% (p = 0.003). Tumor-induced angiogenesis was decreased in SVR tumors by 52% (p = 0.005) and in MS1-VEGF tumors by 58% (p = 0.001). Sera from IFN-alpha1,8-treated mice bearing either SVR or MS1-VEGF tumors demonstrated a 5-fold increase in IP-10/CXCL10 (p = 0.001), an IFN-induced antiangiogenic protein. Both recombinant IP-10 and IFN-alpha1,8 inhibited human umbilical vein endothelial cell (HUVEC) vessel formation in the fibrin gel assay, a three-dimensional culture model of angiogenesis, by 56% at 25 ng/mL and 50% at 1.2 ng/mL, respectively (p < 0.001). An IP-10 blocking antibody restored vessel formation to 80% of untreated controls (p = 0.001). Given the magnitude of the in vivo response, these data suggested that the antitumor effects of IFN-alpha1,8 were likely mediated through angiogenesis inhibition rather than solely by direct inhibition of tumor cell proliferation.