The dose-response characteristics of four NTCP models: using a novel CT-based radiomic method to quantify radiation-induced lung density changes.

Multiple competing normal tissue complication probability (NTCP) models have been proposed for predicting symptomatic radiation-induced lung injury in human. In this paper we tested the efficacy of four common NTCP models applied quantitatively to sub-clinical X-ray computed tomography (CT)-density changes in the lung following radiotherapy. Radiotherapy planning datasets and follow-up chest CTs were obtained in eight patients treated for targets within the lung or hilar region. Image pixel-wise radiation dose exposure versus change in observable CT Hounsfield units was recorded for early (2-5 months) and late (6-9 months) time-points. Four NTCP models, Lyman, Logistic, Weibull and Poisson, were fit to the population data. The quality of fits was assessed by five statistical criteria. All four models fit the data significantly (p < 0.05) well at early, late and cumulative time points. The Lyman model fitted best for early effects while the Weibull Model fitted best for late effects. No significant difference was found between the fits of the models and with respect to parameters D50 and γ50. The D50 estimates were more robust than γ50 to image registration error. For analyzing population-based sub-clinical CT pixel intensity-based dose response, all four models performed well.

Educational Case: Opportunistic Infections of the Central Nervous System.

The following fictional case is intended as a learning tool within the Pathology Competencies for Medical Education (PCME), a set of national standards for teaching pathology. These are divided into three basic competencies: Disease Mechanisms and Processes, Organ System Pathology, and Diagnostic Medicine and Therapeutic Pathology. For additional information, and a full list of learning objectives for all three competencies, see http://journals.sagepub.com/doi/10.1177/2374289517715040.1.

Educational Case: Etiologies, Mechanisms, and Treatment of Stroke.

The following fictional case is intended as a learning tool within the Pathology Competencies for Medical Education (PCME), a set of national standards for teaching pathology. These are divided into three basic competencies: Disease Mechanisms and Processes, Organ System Pathology, and Diagnostic Medicine and Therapeutic Pathology. For additional information, and a full list of learning objectives for all three competencies, see http://journals.sagepub.com/doi/10.1177/2374289517715040.1.

A Gastrointestinal PCR Panel Improves Clinical Management and Lowers Health Care Costs.

Conventional methods for the identification of gastrointestinal pathogens are time-consuming and expensive and have limited sensitivity. The aim of this study was to determine the clinical impact of a comprehensive molecular test, the BioFire FilmArray gastrointestinal (GI) panel, which tests for many of the most common agents of infectious diarrhea in approximately 1 h. Patients with stool cultures submitted were tested on the GI panel (n = 241) and were compared with control patients (n = 594) from the year prior. The most common organisms detected by the GI panel were enteropathogenic Escherichia coli (EPEC, n = 21), norovirus (n = 21), rotavirus (n = 15), sapovirus (n = 9), and Salmonella (n = 8). Patients tested on the GI panel had an average of 0.58 other infectious stool tests compared with 3.02 in the control group (P = 0.0001). The numbers of days on antibiotic(s) per patient were 1.73 in the cases and 2.12 in the controls (P = 0.06). Patients with the GI panel had 0.18 abdomen and/or pelvic imaging studies per patient compared with 0.39 (P = 0.0002) in the controls. The average length of time from stool culture collection to discharge was 3.4 days in the GI panel group versus 3.9 days in the controls (P = 0.04). The overall health care cost could have decreased by $293.61 per patient tested. The GI panel improved patient care by rapidly identifying a broad range of pathogens which may not have otherwise been detected, reducing the need for other diagnostic tests, reducing unnecessary use of antibiotics, and leading to a reduction in hospital length of stay.

Disease signatures for schizophrenia and bipolar disorder using patient-derived induced pluripotent stem cells.

Schizophrenia and bipolar disorder are complex psychiatric disorders that present unique challenges in the study of disease biology. There are no objective biological phenotypes for these disorders, which are characterized by complex genetics and prominent roles for gene-environment interactions. The study of the neurobiology underlying these severe psychiatric disorders has been hindered by the lack of access to the tissue of interest - neurons from patients. The advent of reprogramming methods that enable generation of induced pluripotent stem cells (iPSCs) from patient fibroblasts and peripheral blood mononuclear cells has opened possibilities for new approaches to study relevant disease biology using iPSC-derived neurons. While early studies with patient iPSCs have led to promising and intriguing leads, significant hurdles remain in our attempts to capture the complexity of these disorders in vitro. We present here an overview of studies to date of schizophrenia and bipolar disorder using iPSC-derived neuronal cells and discuss potential future directions that can result in the identification of robust and valid cellular phenotypes that in turn can lay the groundwork for meaningful clinical advances.