A molecularly defined amygdala-independent tetra-synaptic forebrain-to-hindbrain pathway for odor-driven innate fear and anxiety.

Fear-related disorders (for example, phobias and anxiety) cause a substantial public health problem. To date, studies of the neural basis of fear have mostly focused on the amygdala. Here we identify a molecularly defined amygdala-independent tetra-synaptic pathway for olfaction-evoked innate fear and anxiety in male mice. This pathway starts with inputs from the olfactory bulb mitral and tufted cells to pyramidal neurons in the dorsal peduncular cortex that in turn connect to cholecystokinin-expressing (Cck+) neurons in the superior part of lateral parabrachial nucleus, which project to tachykinin 1-expressing (Tac1+) neurons in the parasubthalamic nucleus. Notably, the identified pathway is specifically involved in odor-driven innate fear. Selective activation of this pathway induces innate fear, while its inhibition suppresses odor-driven innate fear. In addition, the pathway is both necessary and sufficient for stress-induced anxiety-like behaviors. These findings reveal a forebrain-to-hindbrain neural substrate for sensory-triggered fear and anxiety that bypasses the amygdala.

Interactive Analysis of Epidemic Situations Based on a Spatiotemporal Information Knowledge Graph of COVID-19.

In view of the lack of data association in spatiotemporal information analysis and the lack of spatiotemporal situation analysis in knowledge graphs, this article combines the semantic web of the geographic knowledge graph with the visual analysis model of spatial information and puts forward the comprehensive utilization of the related technologies of the geographic knowledge graph and big data visual analysis. Then, it realizes the situational analysis of COVID-19 (Coronavirus Disease 2019) and the exploration of patient relationships through interactive collaborative analysis. The main contributions of the paper are as follows. (1) Based on the characteristics of the geographic knowledge graph, a patient entity model and an entity relationship type and knowledge representation method are proposed, and a knowledge graph of the spatiotemporal information of COVID-19 is constructed. (2) To analyse the COVID-19 patients' situations and explore their relationships, an analytical framework is designed. The framework, combining the semantic web of the geographic knowledge graph and the visual analysis model of geographic information, allows one to analyse the semantic web by using the node attribute similarity calculation, key stage mining, community prediction and other methods. (3)An efficient epidemic prevention and anti-epidemic method is proposed which is of referential significance. It is based on experiments and the collaborative analysis of the semantic web and spatial information, allowing for real-time situational understanding, the discovery of patients' relationships, the analysis of the spatiotemporal distribution of patients, super spreader mining, key node analysis, and the prevention and control of high-risk groups.

Media Reports about Violence against Medical Care Providers in China.

Improper, unprofessional, or misleading media reports about violence against medical care providers (typically doctors and nurses) may provoke copycat incidents. To examine whether media reports about violence against medical care providers in China follow professional journalism recommendations, we identified 10 influential incidents of violence against medical care providers in China through a systematic strategy and used standardized internet-based search techniques to retrieve media reports about these events from 2007-2017. Reports were evaluated independently by trained coders to assess adherence to professional journalism recommendations using a 14-item checklist. In total, 788 eligible media reports were considered. Of those, 50.5% and 47.3%, respectively, failed to mention the real and complete names of the writer and editor. Reports improperly mentioned specific details about the time, place, methods, and perpetrators of violence in 42.1%, 36.4%, 45.4%, and 54.6% of cases, respectively. Over 80% of reports excluded a suggestion to seek help from professional agencies or mediation by a third party and only 3.8% of reports mentioned the perspectives of all three key informants about an event: medical care providers, patients, and hospital administrators. Of those that mentioned medical care providers, patient, and/or hospital administrator perspectives, less than 20% indicated they had obtained the interviewee's consent to include their perspective. We concluded that most reports about violence against medical care providers in the Chinese media failed to strictly follow reporting recommendations from authoritative media bodies. Efforts are recommended to improve adherence to professional guidelines in media reports about violence against medical care providers in China, as adherence to those guidelines is likely to reduce future violent events against medical care providers like doctors and nurses.

Needs Analysis for a Parenting App to Prevent Unintentional Injury in Newborn Babies and Toddlers: Focus Group and Survey Study Among Chinese Caregivers.

BACKGROUND: With the growing popularity of mobile health technology, app-based interventions delivered by smartphone have become an increasingly important strategy toward injury prevention. OBJECTIVE: This study aimed to develop a framework supporting the design of an app-based intervention to prevent unintentional injury, targeted for caregivers of Chinese children aged 0 to 6 years. METHODS: A theory-based mixed-method study, including focus groups and Web-based quantitative survey, was performed. Adult caregivers who care for children aged 0 to 6 years and own a smartphone were recruited into 2 sequential stages of research. First, focus groups were conducted among the caregivers at community health care centers and preschools from December 2015 to March 2016. Focus groups (8-10 participants per group) explored awareness, experiences, and opinions of caregivers toward using an app to prevent unintentional injury among children. Second, based on the focus groups findings, a Web-based quantitative survey was designed and distributed to caregivers in November 2016; it collected information on specific needs for the app-based intervention. Thematic analysis and quantitative descriptive analyses were performed. RESULTS: In total, 12 focus groups were completed, involving 108 caregivers. Most participants expressed a strong desire to learn knowledge and skills about unintentional child injury prevention and held positive attitudes toward app-based interventions. Participants expressed multiple preferences concerning the app-based intervention, including their contents, functions, interactive styles, installation and registration logistics, and privacy protection and information security. Following the focus groups, 1505 caregivers completed a WeChat-based quantitative survey, which generated roughly similar results to those of focus groups and added numerical metrics concerning participants' preferences on what to learn, when to learn it, and how to learn it. A detailed framework was established involving 5 components: (1) content design, (2) functional design, (3) interactive style, (4) installation and registration logistics, and (5) privacy protection and information security, and 15 specific requirements. CONCLUSIONS: We developed a framework that can be used as a guide to design app-based interventions for parents and caregivers, specifically for unintentional injury prevention of children aged 0 to 6 years.

A new method to attribute differences in total deaths between groups to population size, age structure and age-specific mortality rate.

BACKGROUND: Two decomposition methods have been widely used to attribute death differences between two populations to population size, age structure of the population, and age-specific mortality rate (ASMR), but their properties remain uninvestigated. METHODS: We assess how the two established decomposition methods yield varying results with three-factor factorial experimental designs, illustrating that they are sensitive to the choice of the reference group. We then propose a novel decomposition method to obtain robust decomposition results and use three cases to demonstrate its advantage. RESULTS: The three decomposition methods differ fundamentally in their allocation of interactions to the contributions of the three factors. In comparison with the existing methods, the new method is robust to the choice of the reference group. Three case studies showed inconsistent attribution results for the two existing methods but robust results for the new method when the choice of the reference population changes. CONCLUSIONS: The proposed method offers robust and more justifiable attribution results compared to the two existing methods. This method could be generalized to attribution of group differences of other health indicators.

Comparative Effectiveness of Published Interventions for Elderly Fall Prevention: A Systematic Review and Network Meta-Analysis.

BACKGROUND: Falls are a major threat to older adults worldwide. Although various effective interventions have been developed, their comparative effectiveness remains unreported. METHODS: A systematic review and network meta-analysis was conducted to determine the most effective interventions to prevent falls in community-dwelling adults aged 60 and over. Combined odds ratio (OR) and 95% credible interval (95% CrI) were calculated. RESULTS: A total of 49 trials involving 27,740 participants and 9271 fallers were included. Compared to usual care, multifactorial interventions (MFI) demonstrated the greatest efficacy (OR: 0.64, 95% CrI: 0.53 to 0.77) followed by interventions combining education and exercise (EDU + EXC) (OR: 0.65, 95% CrI: 0.38 to 1.00) and interventions combining exercise and hazard assessment and modification (EXC + HAM) (OR: 0.66, 95% CrI: 0.40 to 1.04). The effect of medical care performed the worst (OR: 1.02, 95% CrI: 0.78 to 1.34). Model fit was good, inconsistency was low, and publication bias was considered absent. The overall quality of included trials was high. The pooled odds ratios and ranking probabilities remained relatively stable across all sensitivity analyses. CONCLUSIONS: MFI and exercise appear to be effective to reduce falls among older adults, and should be considered first as service delivery options. Further investigation is necessary to verify effectiveness and suitableness of the strategies to at-risk populations.