Immune responses of alcoholics are often compromised, placing them at increased risk for frequent and severe infections. We demonstrate, using a murine model that parallels human alcoholism, that ethanol consumption polarizes adaptive immune responses by CD4+ T helper lymphocytes (Th). Alcohol impairs Th1-regulated cell-mediated, although Th2-regulated humoral responses are largely unimpaired and may be enhanced. Ethanol's effect is most pronounced during the early or cognitive phase of the immune response, when antigen-presenting cells (APC) interact with T cells. We find that alcohol does not act directly upon T cells, but upon APC. Consequences of this interaction of alcohol with APC in vivo are diminished Th1-mediated delayed hypersensitivity (DTH) reactions, while at the same time increased Th2-regulated serum IgE levels are seen. Further ethanol consumption leads to decrease affinity of the IgG2a and IgG2b Th1-regulated antibody isotypes.

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The development of an ontology facilitates the organization of the variety of concepts used to describe different terms in different resources. The proposed ontology will facilitate the study of cardiothoracic surgical education and data analytics in electronic medical records (EMR) with the standard vocabulary.

Background Acquiring proficiency for the repair of a cerebrospinal fluid (CSF) leak is challenging in great part due to its relative rarity, which offers a finite number of training opportunities. Objective The purpose of this study was to evaluates the use of a 3-dimensional (3D) printed, anatomically accurate model to simulate CSF leak closure. Methods Volunteer participants completed two simulation sessions. Questionnaires to assess their professional qualifications and a standardized 5-point Likert scale to estimate the level of confidence, were completed before and after each session. Participants were also queried on the overall educational utility of the simulation. Results Thirteen otolaryngologists and 11 neurosurgeons, met the inclusion criteria. A successful repair of the CSF leak was achieved by 20/24 (83.33%), and 24/24 (100%) during the first and second simulation sessions respectively (average time 04:04 ± 1.39 and 02:10 ± 01:11). Time-to-close-the-CSF-leak during the second session was significantly shorter than the first (p < 0.001). Confidence scores increased across the training sessions (3.3 ± 1.0, before the simulation, 3.7 ± 0.6 after the first simulation, and 4.2 ± 0.4 after the second simulation; p < 0.001). All participants reported an increase in confidence and believed that the model represented a valuable training tool. Conclusions Despite significant differences with varying clinical scenarios, 3D printed models for cerebrospinal leak repair offer a feasible simulation for the training of residents and novice surgeons outside the constrictions of a clinical environment.

Introduction: Cerebral Small Vessel Disease (CSVD) impacts the functional outcome of acute ischemic stroke (AIS) patients. The majority of the available tools to quantify its burden relies on visual categorical scales, which is labor intensive and subject to inter- and intra-reader variability. Fully automated tools are rare and mostly focus on white matter hyperintensity (WMH) as a surrogate for CSVD. We aimed to develop a novel software that simulates the clinicians’ rational to detect lacunes on clinical MRI scans of patients presenting with acute AIS or transient ischemic attack (TIA). Methods: Patients presenting with symptoms of acute AIS or TIA were prospectively recruited. Lacunes were scored on the first brain MRI collected within 24 hours of hospital admission by a board-certified neuro-intensivist/vascular neurologist according to the Neuroimaging Standards for Research into Small Vessel Disease (STRIVE) criteria. Following standard skull stripping and co-registration, automated software was developed in Matlab by calculating maximal intensity difference of co-registered voxels on FLAIR and T2 MRI sequences. Cerebrospinal fluid was removed by seed-based growing approach and lacunes were subsequently detected based on their size (3-15 mm) and morphological features. Results: 30 subjects were included (age 61.6±16.1, 30% females); 6 of which had TIA and 23 had AIS (10 acute lacunar stroke, 3 cardioembolic, 10 cryptogenic and 1 stroke of other determined etiology). There were 24 lacunes detected in 12 subjects by the human reader. The automated system accurately identified subjects with lacunes in 91.6% of the cases with 75% specificity. Negative predictive value for subjects without lacunes was 93.7%. At the lesion level, the paradigm identified 62.5% of all lacunes in all subjects with positive predictive value of 78.9%; 67.0% of the missed lacunes were in close proximity to the ventricles. Conclusions: Automated identification of lacunes is feasible on clinical MRI scans of patients with acute AIS or TIA. Lacunes closer to the ventricles are challenging and may require a separate approach.