Determination of freedom-from-rabies for small Indian mongoose populations in the United States Virgin Islands, 2019–2020

Mongooses, a nonnative species, are a known reservoir of rabies virus in the Caribbean region. A cross-sectional study of mongooses at 41 field sites on the US Virgin Islands of St. Croix, St. John, and St. Thomas captured 312 mongooses (32% capture rate). We determined the absence of rabies virus by antigen testing and rabies virus exposure by antibody testing in mongoose populations on all three islands. USVI is the first Caribbean state to determine freedom-from-rabies for its mongoose populations with a scientifically-led robust cross-sectional study. Ongoing surveillance activities will determine if other domestic and wildlife populations in USVI are rabies-free

Mongooses (\u3ci\u3eUrva auropunctata\u3c/i\u3e) as reservoir hosts of leptospira species in the United States Virgin Islands, 2019–2020

During 2019–2020, the Virgin Islands Department of Health investigated potential animal reservoirs of Leptospira spp., the bacteria that cause leptospirosis. In this cross-sectional study, we investigated Leptospira spp. exposure and carriage in the small Indian mongoose (Urva auropunctata, syn: Herpestes auropunctatus), an invasive animal species. This study was conducted across the three main islands of the U.S. Virgin Islands (USVI), which are St. Croix, St. Thomas, and St. John. We used the microscopic agglutination test (MAT), fluorescent antibody test (FAT), real-time polymerase chain reaction (lipl32 rt-PCR), and bacterial culture to evaluate serum and kidney specimens and compared the sensitivity, specificity, positive predictive value, and negative predictive value of these laboratory meth-ods. Mongooses (n = 274) were live-trapped at 31 field sites in ten regions across USVI and humanely euthanized for Leptospira spp. testing. Bacterial isolates were sequenced and evaluated for species and phylogenetic analysis using the ppk gene. Anti-Leptospira spp. antibodies were detected in 34% (87/256) of mongooses. Reactions were observed with the following serogroups: Sejroe, Icterohaemorrhagiae, Pyrogenes, Mini, Cynopteri, Australis, Hebdomadis, Autumnalis, Mankarso, Pomona, and Ballum. Of the kidney specimens exam-ined, 5.8% (16/270) were FAT-positive, 10% (27/274) were culture-positive, and 12.4% (34/ 274) were positive by rt-PCR. Of the Leptospira spp. isolated from mongooses, 25 were L. borgpetersenii, one was L. interrogans, and one was L. kirschneri. Positive predictive values of FAT and rt-PCR testing for predicting successful isolation of Leptospira by culture were 88% and 65%, respectively. The isolation and identification of Leptospira spp. in mongooses highlights the potential role of mongooses as a wildlife reservoir of leptospirosis; mongooses could be a source of Leptospira spp. infections for other wildlife, domestic animals, and humans

Ethical, legal and social aspects of human cerebral organoids and their governance in Germany, the United Kingdom and the United States

Human cerebral organoids (HCOs) are model systems that enable researchers to investigate the human brain in ways that had previously been impossible. The emergence of HCOs was accompanied by both expert and layperson discussions concerning the possibility of these novel entities developing sentience or consciousness. Such concerns are reflected in deliberations about how to handle and regulate their use. This perspective article resulted from an international and interdisciplinary research retreat “Ethical, Legal and Social Aspects of Human Cerebral Organoids and their Governance in Germany, the United Kingdom and the United States”, which took place in Tübingen, Germany, in August 2022. The retreat focused on whether HCO research requires new ethical and regulatory approaches. It addressed epistemic issues around the detection and theorisation of consciousness, ethical concerns around moral status and research conduct, difficulties for legislation and guidelines managing these entities, and public engagement

International Olympic Committee consensus statement on pain management in elite athletes

Pain is a common problem among elite athletes and is frequently associated with sport injury. Both pain and injury interfere with the performance of elite athletes. There are currently no evidence-based or consensus-based guidelines for the management of pain in elite athletes. Typically, pain management consists of the provision of analgesics, rest and physical therapy. More appropriately, a treatment strategy should address all contributors to pain including underlying pathophysiology, biomechanical abnormalities and psychosocial issues, and should employ therapies providing optimal benefit and minimal harm. To advance the development of a more standardised, evidence-informed approach to pain management in elite athletes, an IOC Consensus Group critically evaluated the current state of the science and practice of pain management in sport and prepared recommendations for a more unified approach to this important topic

Profound Chemopreventative Effects of a Hydrogen Sulfide-Releasing NSAID in the APC(Min/+) Mouse Model of Intestinal Tumorigenesis

Canadian Institutes of Health Research grant to JL

Good Advice is Beyond All Price, but What if it Comes from a Machine?

As nonhuman agents become integrated into the workforce, the question becomes whether humans are willing to consider their advice, and to what extent advice-seeking depends on the perceived agent-task fit. To examine this, participants performed social and analytical tasks and received advice from human, robot, and computer agents in two conditions: in the Agent First condition, participants were first asked to choose advisors and were then informed which task to perform; in the Task First condition, they were first informed about the task and then asked to choose advisors. In the Agent First condition, we expected participants to prefer human to non-human advisors, and to subsequently trust their advice more if they were assigned the social as opposed to the analytical task. In the Task First condition, we expected advisor choices to be guided by stereotypical assumptions regarding the agents’ expertise for the tasks, accompanied by higher trust in their suggestions. The findings indicate that in the Agent First condition, the human was chosen significantly more often than the machines, while in the Task First condition advisor choices were calibrated based on perceived agent-task fit. Trust was higher in the social task, but only showed variations with the human partner

Under Pressure: Examining Social Conformity with Computer and Robot Groups

Objective: To investigate whether non-human agents, such as computers or social robots, produce a social conformity effect within human operators and to what extent potential conformist behavior varies as a function of the human-likeness of the group members and the type of task that had to be performed. Background: People conform due to normative and/or informational motivations in human-human interactions, and conformist behavior is modulated by factors related to the individual, as well as factors associated with the group, context and culture. Studies have yet to examine whether non-human agents also induce social conformity. Method: Participants were assigned to a computer, robot, or human group and completed both a social and analytical task with the respective group. Results: Conformity measures (percentage of times participants answered in line with agents on critical trials) subjected to a 3 x 2 mixed ANOVA showed significantly higher conformity rates for the analytical versus the social task, as well as a modulation of conformity depending of the perceived agent-task fit. Conclusion: Findings indicate that non-human agents were able to exert a general conformity effect and that informational influence associated with the group’s expertise for a given task had a stronger impact on conformity than normative motivations associated with its human-likeness. Application: Results suggest that users may react differently to suggestions of non-human versus human agent groups with the potential of under-reliance on social tasks

Good Advice is Beyond All Price, but What if it Comes from a Machine?

As nonhuman agents become integrated into the workforce, the question becomes whether humans are willing to consider their advice, and to what extent advice-seeking depends on the perceived agent-task fit. To examine this, participants performed social and analytical tasks and received advice from human, robot, and computer agents in two conditions: in the Agent First condition, participants were first asked to choose advisors and were then informed which task to perform; in the Task First condition, they were first informed about the task and then asked to choose advisors. In the Agent First condition, we expected participants to prefer human to non-human advisors, and to subsequently trust their advice more if they were assigned the social as opposed to the analytical task. In the Task First condition, we expected advisor choices to be guided by stereotypical assumptions regarding the agents’ expertise for the tasks, accompanied by higher trust in their suggestions. The findings indicate that in the Agent First condition, the human was chosen significantly more often than the machines, while in the Task First condition advisor choices were calibrated based on perceived agent-task fit. Trust was higher in the social task, but only showed variations with the human partner