Identification of an immune-responsive mesolimbocortical serotonergic system: potential role in regulation of emotional behavior

Peripheral immune activation can have profound physiological and behavioral effects including induction of fever and sickness behavior. One mechanism through which immune activation or immunomodulation may affect physiology and behavior is via actions on brainstem neuromodulatory systems, such as serotonergic systems. We have found that peripheral immune activation with antigens derived from the nonpathogenic, saprophytic bacterium, Mycobacterium vaccae, activated a specific subset of serotonergic neurons in the interfascicular part of the dorsal raphe nucleus (DRI) of mice, as measured by quantification of c-Fos expression following intratracheal (12 h) or s.c. (6 h) administration of heat-killed, ultrasonically disrupted M. vaccae, or heat-killed, intact M. vaccae, respectively. These effects were apparent after immune activation by M. vaccae or its components but not by ovalbumin, which induces a qualitatively different immune response. The effects of immune activation were associated with increases in serotonin metabolism within the ventromedial prefrontal cortex, consistent with an effect of immune activation on mesolimbocortical serotonergic systems. The effects of M. vaccae administration on serotonergic systems were temporally associated with reductions in immobility in the forced swim test, consistent with the hypothesis that the stimulation of mesolimbocortical serotonergic systems by peripheral immune activation alters stress-related emotional behavior. These findings suggest that the immune-responsive subpopulation of serotonergic neurons in the DRI is likely to play an important role in the neural mechanisms underlying regulation of the physiological and pathophysiological responses to both acute and chronic immune activation, including regulation of mood during health and disease states. Together with previous studies, these findings also raise the possibility that immune stimulation activates a functionally and anatomically distinct subset of serotonergic neurons, different from the subset of serotonergic neurons activated by anxiogenic stimuli or uncontrollable stressors. Consequently, selective activation of specific subsets of serotonergic neurons may have distinct behavioral outcomes.     

Cannabinoids and the Microbiota–Gut–Brain Axis: Emerging Effects of Cannabidiol and Potential Applications to Alcohol Use Disorders

The endocannabinoid system (ECS) has emerged in recent years as a potential treatment target for alcohol use disorders (AUD). In particular, the nonpsychoactive cannabinoid cannabidiol (CBD) has shown preclinical promise in ameliorating numerous clinical symptoms of AUD. There are several proposed mechanism(s) through which cannabinoids (and CBD in particular) may confer beneficial effects in the context of AUD. First, CBD may directly impact specific brain mechanisms underlying AUD to influence alcohol consumption and the clinical features of AUD. Second, CBD may influence AUD symptoms through its actions across the digestive, immune, and central nervous systems, collectively known as the microbiota–gut–brain axis (MGBA). Notably, emerging work suggests that alcohol and cannabinoids exert opposing effects on the MGBA. Alcohol is linked to immune dysfunction (e.g., chronic systemic inflammation in the brain and periphery) as well as disturbances in gut microbial species (microbiota) and increased intestinal permeability. These MGBA disruptions have been associated with AUD symptoms such as craving and impaired cognitive control. Conversely, existing preclinical data suggest that cannabinoids may confer beneficial effects on the gastrointestinal and immune system, such as reducing intestinal permeability, regulating gut bacteria, and reducing inflammation. Thus, cannabinoids may exert AUD harm-reduction effects, at least in part, through their beneficial actions across the MGBA. This review will provide a brief introduction to the ECS and the MGBA, discuss the effects of cannabinoids (particularly CBD) and alcohol in the brain, gut, and immune system (i.e., across the MGBA), and put forth a theoretical framework to inform future research questions.     

Concerns about analgesics among patients and family caregivers in a hospice setting

Patients receiving curative treatment for cancer have concerns about reporting pain and using analgesics. These concerns are associated with underutilization of analgesics. To extend knowledge about such concerns to the context of palliative care, the concerns of hospice patients and family caregivers were compared. Within 5 days of admission to hospice, 35 patients with cancer and their caregivers each completed a measure of eight concerns such as fear of addiction, worry about tolerance, and worry about side effects. There was no correlation between caregiver and patient concerns and means for the two groups were similar, indicating that within a given dyad either the patient or the caregiver may have greater concerns. The findings highlight the need for patient and caregiver education about reporting pain and using analgesics. © 1996 John Wiley & Sons, Inc.     

Using cognitive models to develop quality multiple-choice questions

With the recent interest in competency-based education, educators are being challenged to develop more assessment opportunities. As such, there is increased demand for exam content development, which can be a very labor-intense process. An innovative solution to this challenge has been the use of automatic item generation (AIG) to develop multiple-choice questions (MCQs). In AIG, computer technology is used to generate test items from cognitive models (i.e. representations of the knowledge and skills that are required to solve a problem). The main advantage yielded by AIG is the efficiency in generating items. Although technology for AIG relies on a linear programming approach, the same principles can also be used to improve traditional committee-based processes used in the development of MCQs. Using this approach, content experts deconstruct their clinical reasoning process to develop a cognitive model which, in turn, is used to create MCQs. This approach is appealing because it: (1) is efficient; (2) has been shown to produce items with psychometric properties comparable to those generated using a traditional approach; and (3) can be used to assess higher order skills (i.e. application of knowledge). The purpose of this article is to provide a novel framework for the development of high-quality MCQs using cognitive models.