Dataset Information

Comparative data on emotional (psychotic) aggressive biting behavior in mice of ddY strain measured by using two devices; Aggressive response meter and powerlab-compatible type aggressive response meter.

ABSTRACT: The Aggressive Response Meter (ARM) has been validated for measuring emotional (psychotic) aggression triggered by mental irritation in mice. In the present article, we newly developed a device, pARM (PowerLab-compatible type ARM). We collected on the aggressive biting behavior (ABB) intensity and ABB frequency of 20 male and female mice of ddY strain studied over a period of 6 days by using pARM and the former ARM. We calculated Pearson's correlation between the values of pARM and those of ARM. The accumulated data can be referred as a basis for demonstrating the consistence of pARM and the former ARM, and used in future research to augment the understanding of stress-induced emotional aggression in mice.

SUBMITTER: Igarashi K

PROVIDER: S-EPMC10294006 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Comparative data on emotional (psychotic) aggressive biting behavior in mice of ddY strain measured by using two devices; Aggressive response meter and powerlab-compatible type aggressive response meter.

Igarashi Kento K Kuchiiwa Satoshi S Kuchiiwa Toshiko T Tomita Kazuo K Sato Tomoaki T

Data in brief 20230512

The Aggressive Response Meter (ARM) has been validated for measuring emotional (psychotic) aggression triggered by mental irritation in mice. In the present article, we newly developed a device, pARM (PowerLab-compatible type ARM). We collected on the aggressive biting behavior (ABB) intensity and ABB frequency of 20 male and female mice of ddY strain studied over a period of 6 days by using pARM and the former ARM. We calculated Pearson's correlation between the values of pARM and those of ARM. ...[more]

PMID: 37383814

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Project description:BackgroundThe Pfizer-BioNTech COVID-19 vaccine uses a novel messenger RNA technology to elicit a protective immune response. Short-term physiologic responses to the vaccine have not been studied using wearable devices.ObjectiveWe aim to characterize physiologic changes in response to COVID-19 vaccination in a small cohort of participants using a wearable device (WHOOP Strap 3.0). This is a proof of concept for using consumer-grade wearable devices to monitor response to COVID-19 vaccines.MethodsIn this prospective observational study, physiologic data from 19 internal medicine residents at a single institution that received both doses of the Pfizer-BioNTech COVID-19 vaccine was collected using the WHOOP Strap 3.0. The primary outcomes were percent change from baseline in heart rate variability (HRV), resting heart rate (RHR), and respiratory rate (RR). Secondary outcomes were percent change from baseline in total, rapid eye movement, and deep sleep. Exploratory outcomes included local and systemic reactogenicity following each dose and prophylactic analgesic use.ResultsIn 19 individuals (mean age 28.8, SD 2.2 years; n=10, 53% female), HRV was decreased on day 1 following administration of the first vaccine dose (mean -13.44%, SD 13.62%) and second vaccine dose (mean -9.25%, SD 22.6%). RHR and RR showed no change from baseline after either vaccine dose. Sleep duration was increased up to 4 days post vaccination, after an initial decrease on day 1. Increased sleep duration prior to vaccination was associated with a greater change in HRV. Local and systemic reactogenicity was more severe after dose two.ConclusionsThis is the first observational study of the physiologic response to any of the novel COVID-19 vaccines as measured using wearable devices. Using this relatively small healthy cohort, we provide evidence that HRV decreases in response to both vaccine doses, with no significant changes in RHR or RR. Sleep duration initially decreased following each dose with a subsequent increase thereafter. Future studies with a larger sample size and comparison to other inflammatory and immune biomarkers such as antibody response will be needed to determine the true utility of this type of continuous wearable monitoring in regards to vaccine responses. Our data raises the possibility that increased sleep prior to vaccination may impact physiologic responses and may be a modifiable way to increase vaccine response. These results may inform future studies using wearables for monitoring vaccine responses.Trial registrationClinicalTrials.gov NCT04304703; https://www.clinicaltrials.gov/ct2/show/NCT04304703.

Project description:BackgroundEarable devices are novel, wearable Internet of Things devices that are user-friendly and have potential applications in mobile health care. The position of the ear is advantageous for assessing vital status and detecting diseases through reliable and comfortable sensing devices.ObjectiveOur study aimed to review the utility of health-related indicators derived from earable devices and propose an improved definition of disease prevention. We also proposed future directions for research on the health care applications of earable devices.MethodsA systematic review was conducted of the PubMed, Embase, and Web of Science databases. Keywords were used to identify studies on earable devices published between 2015 and 2020. The earable devices were described in terms of target health outcomes, biomarkers, sensor types and positions, and their utility for disease prevention.ResultsA total of 51 articles met the inclusion criteria and were reviewed, and the frequency of 5 health-related characteristics of earable devices was described. The most frequent target health outcomes were diet-related outcomes (9/51, 18%), brain status (7/51, 14%), and cardiovascular disease (CVD) and central nervous system disease (5/51, 10% each). The most frequent biomarkers were electroencephalography (11/51, 22%), body movements (6/51, 12%), and body temperature (5/51, 10%). As for sensor types and sensor positions, electrical sensors (19/51, 37%) and the ear canal (26/51, 51%) were the most common, respectively. Moreover, the most frequent prevention stages were secondary prevention (35/51, 69%), primary prevention (12/51, 24%), and tertiary prevention (4/51, 8%). Combinations of ≥2 target health outcomes were the most frequent in secondary prevention (8/35, 23%) followed by brain status and CVD (5/35, 14% each) and by central nervous system disease and head injury (4/35, 11% each).ConclusionsEarable devices can provide biomarkers for various health outcomes. Brain status, healthy diet status, and CVDs were the most frequently targeted outcomes among the studies. Earable devices were mostly used for secondary prevention via monitoring of health or disease status. The potential utility of earable devices for primary and tertiary prevention needs to be investigated further. Earable devices connected to smartphones or tablets through cloud servers will guarantee user access to personal health information and facilitate comfortable wearing.

Dataset Information

Comparative data on emotional (psychotic) aggressive biting behavior in mice of ddY strain measured by using two devices; Aggressive response meter and powerlab-compatible type aggressive response meter.

Publications

Comparative data on emotional (psychotic) aggressive biting behavior in mice of ddY strain measured by using two devices; Aggressive response meter and powerlab-compatible type aggressive response meter.

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