skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: A Case Study Using Accelerometers to Identify Illness in Ewes following Unintentional Exposure to Mold-Contaminated Feed
Sensor technologies can identify modified animal activity indicating changes in health status. This study investigated sheep behavior before and after illness caused by mold-contaminated feed using tri-axial accelerometers. Ten ewes were fitted with HerdDogg biometric accelerometers. Five ewes were concurrently fitted with Axivity AX3 accelerometers. The flock was exposed to mold-contaminated feed following an unexpected ration change, and observed symptomatic ewes were treated with a veterinarian-directed protocol. Accelerometer data were evaluated 4 days before exposure (d −4 to −1); the day of ration change (d 0); and 4 days post exposure (d 1 to 4). Herddogg activity index correlated to the variability of minimum and standard deviation of motion intensity monitored by the Axivity accelerometer. Herddogg activity index was lower (p < 0.05) during the mornings (0800 to 1100 h) of days 2 to 4 and the evening of day 1 than days −4 to 0. Symptomatic ewes had lower activity levels in the morning and higher levels at night. After accounting for symptoms, activity levels during days 1 to 4 were lower (p < 0.05) than days −4 to 0 the morning after exposure. Results suggest real-time or near-real time accelerometers have potential to detect illness in ewes.  more » « less
Award ID(s):
2151254
PAR ID:
10398490
Author(s) / Creator(s):
; ; ; ; ; ; ;
Date Published:
Journal Name:
Animals
Volume:
12
Issue:
3
ISSN:
2076-2615
Page Range / eLocation ID:
266
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract We examined the effects of dietary supplementation of a blend of mannan and glucan on the growth performance, energy status, and whole-blood immune gene expression of newly weaned beef steers during a 42-d receiving period. Forty-eight newly weaned Angus crossbred steers (2-d post-weaning; 199 ± 13 kg of initial body weight [BW]) from a single source were stratified by BW and randomly assigned to one of the two treatments: basal diet with no additive (CON; n = 24) or a basal diet top-dressed with 5 g of a blend of mannan and glucan (MANGLU; n = 24). Average daily gain (ADG) and feed efficiency (FE) from days 1 to 14, 15 to 42, and 1 to 42 were calculated from daily dry matter intake (DMI) and weekly BW. Blood samples were collected on days 0, 14, and 42 for measurement of plasma glucose and nonesterified fatty acids (NEFA). Blood samples collected on days 14 and 42 were composited for each steer for untargeted carbonyl-metabolome analysis (measurement of carbonyl-containing metabolites). Expression of 84 immune-related genes was analyzed on blood samples collected on day 42. Beginning on days 37 to 42, total mixed ration, refusals, and fecal samples were collected once daily to determine apparent total tract digestibility of DM, CP, NDF, and ADF using indigestible NDF as an internal marker. Over the 42-d feeding trial, supplemental MANGLU tended to increase final BW (P = 0.07) and ADG (P = 0.06). Compared to CON, beef steers fed supplemental MANGLU had greater (P = 0.01) DMI during the first 14 d, greater DM digestibility (P = 0.03), and tended to have greater NDF digestibility (P = 0.09). No treatment effects (P > 0.10) on plasma glucose and NEFA on days 14 and 42 were detected; however, carbonyl-metabolome analysis revealed increased (FDR ≤ 0.05) plasma concentrations of galactose and glyceraldehydes, and altered (FDR ≤ 0.05) concentrations of some microbiome-derived metabolites in beef steers fed MANGLU. Compared with CON, MANGLU increased (P ≤ 0.05) the expression of five immune-related genes involved in recognition of and mounting immune defense against microbial pathogens. In conclusion, the results of this study demonstrated that supplemental MANGLU enhances beef cattle immunocompetence and productivity during feedlot receiving period. 
    more » « less
  2. ABSTRACT Seasonal changes in sleep/wake cycles and behaviors related to reproduction often co‐occur with seasonal fluctuations in sex hormones. Experimental studies have established that fluctuations in circulating testosterone mediate circadian rhythms. However, most studies are performed under constant lighting conditions and fail to investigate the effects of testosterone on the phenotypic output of circadian rhythms, that is, chronotype (daily activity patterns under light:dark cycles). Here, we experimentally elevated testosterone with implants during short nonbreeding daylengths in male house sparrows (Passer domesticus) to test if observed seasonal changes in chronotype are directly in response to photoperiod or to testosterone. We fitted individuals with accelerometers to track activity across treatment periods. Birds experienced three treatments periods: short day photoperiods before manipulation (SD), followed by testosterone implants while still on short days (SD + T). Implants were then removed. After a decrease in cloacal protuberance size, an indicator of low testosterone levels, birds were then photostimulated on long days (LD). Blood samples were collected at night, when testosterone peaks, to compare testosterone levels to daily onset/offset activity for experimental periods. Our results indicate that experimentally elevated testosterone under short nonbreeding photoperiods significantly advanced daily onset of activity and total daily activity relative to daylength. This suggests that testosterone, independent of photoperiod, is responsible for seasonal shifts in chronotypes and daily activity rhythms. These findings suggest that sex steroid hormone actions regulate timing of daily behaviors, likely coordinating expression of reproductive behaviors to appropriate times of the day. 
    more » « less
  3. Background Research has shown the feasibility of human activity recognition using wearable accelerometer devices. Different studies have used varying numbers and placements for data collection using sensors. Objective This study aims to compare accuracy performance between multiple and variable placements of accelerometer devices in categorizing the type of physical activity and corresponding energy expenditure in older adults. Methods In total, 93 participants (mean age 72.2 years, SD 7.1) completed a total of 32 activities of daily life in a laboratory setting. Activities were classified as sedentary versus nonsedentary, locomotion versus nonlocomotion, and lifestyle versus nonlifestyle activities (eg, leisure walk vs computer work). A portable metabolic unit was worn during each activity to measure metabolic equivalents (METs). Accelerometers were placed on 5 different body positions: wrist, hip, ankle, upper arm, and thigh. Accelerometer data from each body position and combinations of positions were used to develop random forest models to assess activity category recognition accuracy and MET estimation. Results Model performance for both MET estimation and activity category recognition were strengthened with the use of additional accelerometer devices. However, a single accelerometer on the ankle, upper arm, hip, thigh, or wrist had only a 0.03-0.09 MET increase in prediction error compared with wearing all 5 devices. Balanced accuracy showed similar trends with slight decreases in balanced accuracy for the detection of locomotion (balanced accuracy decrease range 0-0.01), sedentary (balanced accuracy decrease range 0.05-0.13), and lifestyle activities (balanced accuracy decrease range 0.04-0.08) compared with all 5 placements. The accuracy of recognizing activity categories increased with additional placements (accuracy decrease range 0.15-0.29). Notably, the hip was the best single body position for MET estimation and activity category recognition. Conclusions Additional accelerometer devices slightly enhance activity recognition accuracy and MET estimation in older adults. However, given the extra burden of wearing additional devices, single accelerometers with appropriate placement appear to be sufficient for estimating energy expenditure and activity category recognition in older adults. 
    more » « less
  4. Abstract This study investigates bidirectional associations between adolescents’ daily experiences of victimization and aggression perpetration within friendships. We investigated (a) across‐day associations between victimization and aggression perpetration; (b) morning cortisol activity as a moderator of cross‐day victimization and aggression links; and (c) potential sex differences in these patterns. For 4 consecutive days, 99 adolescents (Mage = 18.06,SD = 1.09, 46 females) reported whether they were victimized by or aggressive toward their friends. On three of these days, adolescents provided three morning saliva samples. Multilevel path analyses showed that across days, victimization and aggression were bidirectionally linked, but only for male adolescents. Additionally, for male adolescents, morning cortisol output (but not morning cortisol increase) moderated the association between victimization and next‐day aggression; victimization predicted greater next‐day aggression for boys with low, but not high, morning cortisol output. Findings implicate a physiological factor that may modify daily links between victimization and aggression in male adolescent friendships. 
    more » « less
  5. ABSTRACT Understanding clinical trajectories of sepsis patients is crucial for prognostication, resource planning, and to inform digital twin models of critical illness. This study aims to identify common clinical trajectories based on dynamic assessment of cardiorespiratory support using a validated electronic health record data that covers retrospective cohort of 19,177 patients with sepsis admitted to intensive care units (ICUs) of Mayo Clinic Hospitals over 8-year period. Patient trajectories were modeled from ICU admission up to 14 days using an unsupervised machine learning two-stage clustering method based on cardiorespiratory support in ICU and hospital discharge status. Of 19,177 patients, 42% were female with a median age of 65 (interquartile range [IQR], 55–76) years, The Acute Physiology, Age, and Chronic Health Evaluation III score of 70 (IQR, 56–87), hospital length of stay (LOS) of 7 (IQR, 4–12) days, and ICU LOS of 2 (IQR, 1–4) days. Four distinct trajectories were identified: fast recovery (27% with a mortality rate of 3.5% and median hospital LOS of 3 (IQR, 2–15) days), slow recovery (62% with a mortality rate of 3.6% and hospital LOS of 8 (IQR, 6–13) days), fast decline (4% with a mortality rate of 99.7% and hospital LOS of 1 (IQR, 0–1) day), and delayed decline (7% with a mortality rate of 97.9% and hospital LOS of 5 (IQR, 3–8) days). Distinct trajectories remained robust and were distinguished by Charlson Comorbidity Index, The Acute Physiology, Age, and Chronic Health Evaluation III scores, as well as day 1 and day 3 SOFA (P< 0.001 ANOVA). These findings provide a foundation for developing prediction models and digital twin decision support tools, improving both shared decision making and resource planning. 
    more » « less