The daily, weekly, and seasonal cycles of body temperature analyzed at large scale

Warming alters life-history traits and competition in a phage community

Host-parasite interactions are highly susceptible to changes in temperature due to mismatches in species thermal responses. In nature, parasites often exist in communities, and responses to temperature are expected to vary between host-parasite pairs. Temperature change thus has consequences for both host-parasite dynamics and parasite-parasite interactions. Here, we investigate the impact of warming (37°C, 40°C, and 42°C) on parasite life-history traits and competition using the opportunistic bacterial pathogen Pseudomonas aeruginosa (host) and a panel of three genetically diverse lytic bacteriophages (parasites). We show that phages vary in their responses to temperature. While 37°C and 40°C did not have a major effect on phage infectivity, infection by two phages was restricted at 42°C. This outcome was attributed to disruption of different phage life-history traits including host attachment and replication inside hosts. Furthermore, we show that temperature mediates competition between phages by altering their competitiveness. These results highlight phage trait variation across thermal regimes with the potential to drive community dynamics. Our results have important implications for eukaryotic viromes and the design of phage cocktail therapies.IMPORTANCEMammalian hosts often elevate their body temperatures through fevers to restrict the growth of bacterial infections. However, the extent to which fever temperatures affect the communities of phages with the ability to parasitize those bacteria remains unclear. In this study, we investigate the impact of warming across a fever temperature range (37°C, 40°C, and 42°C) on phage life-history traits and competition using a bacterium (host) and bacteriophage (parasite) system. We show that phages vary in their responses to temperature due to disruption of different phage life-history traits. Furthermore, we show that temperature can alter phage competitiveness and shape phage-phage competition outcomes. These results suggest that fever temperatures have the potential to restrict phage infectivity and drive phage community dynamics. We discuss implications for the role of temperature in shaping host-parasite interactions more widely.

Brain energy metabolism: A roadmap for future research

Although we have learned much about how the brain fuels its functions over the last decades, there remains much still to discover in an organ that is so complex. This article lays out major gaps in our knowledge of interrelationships between brain metabolism and brain function, including biochemical, cellular, and subcellular aspects of functional metabolism and its imaging in adult brain, as well as during development, aging, and disease. The focus is on unknowns in metabolism of major brain substrates and associated transporters, the roles of insulin and of lipid droplets, the emerging role of metabolism in microglia, mysteries about the major brain cofactor and signaling molecule NAD+, as well as unsolved problems underlying brain metabolism in pathologies such as traumatic brain injury, epilepsy, and metabolic downregulation during hibernation. It describes our current level of understanding of these facets of brain energy metabolism as well as a roadmap for future research.

The effect of physical barriers under a raised house on mosquito entry: an experimental study in rural Gambia

BACKGROUND

Anopheles gambiae, the major malaria mosquito in sub-Saharan Africa, feed largely indoors at night. Raising a house off the ground with no barriers underneath reduces mosquito-house entry. This experiment tested whether walling off the space under an elevated hut affects mosquito-hut entry.

METHODS

Four inhabited experimental huts, each of which could be moved up and down, were used in rural Gambia. Nightly collections of mosquitoes were made using light traps and temperature and carbon dioxide levels monitored indoors and outdoors using loggers. Each night, a reference hut was kept at ground level and three huts raised 2 m above the ground; with the space under the hut left open, walled with air-permeable walls or solid walls. Treatments were rotated every four nights using a randomized block design. The experiment was conducted for 32 nights. Primary measurements were mosquito numbers and indoor temperature in each hut.

RESULTS

A total of 1,259 female Anopheles gambiae sensu lato were collected in the hut at ground level, 655 in the hut with an open ground floor, 981 in the hut with air-permeable walls underneath and 873 in the hut with solid walls underneath. Multivariate analysis, adjusting for confounders, showed that a raised hut open underneath had 53% fewer mosquitoes (95% CI 47-58%), those with air-permeable walls underneath 24% fewer (95% CI 9-36%) and huts with solid walls underneath 31% fewer (95% CI 24-37%) compared with a hut on the ground. Similar results were found for Mansonia spp. and total number of female mosquitoes, but not for Culex mosquitoes where hut entry was unaffected by height or barriers. Indoor temperature and carbon dioxide levels were similar in all huts.

CONCLUSION

Raising a house 2 m from the ground reduces the entry of An. gambiae and Mansonia mosquitoes, but not Culex species. The protective effect of height is reduced if the space underneath the hut is walled off.

Deciphering the relationship between temperature and immunity

Fever is a hallmark symptom of disease across the animal kingdom. Yet, despite the evidence linking temperature fluctuation and immune response, much remains to be discovered about the molecular mechanisms governing these interactions. In patients with rheumatoid arthritis, for instance, it is clinically accepted that joint temperature can predict disease progression. But it was only recently demonstrated that the mitochondria of stimulated T cells can rise to an extreme 50°C, potentially indicating a cellular source of these localized 'fevers'. A challenge to dissecting these mechanisms is a bidirectional interplay between temperature and immunity. Heat shock response is found in virtually all organisms, activating protective pathways when cells are exposed to elevated temperatures. However, the temperature threshold that activates these pathways can vary within the same organism, with human immune cells, in particular, demonstrating differential sensitivity to heat. Such inter-cellular variation may be clinically relevant given the small but significant temperature differences seen between tissues, ages, and sexes. Greater understanding of how such small temperature perturbations mediate immune responses may provide new explanations for persistent questions in disease such as sex disparity in disease prevalence. Notably, the prevalence and severity of many maladies are rising with climate change, suggesting temperature fluctuations can interact with disease on multiple levels. As global temperatures are rising, and our body temperatures are falling, questions regarding temperature-immune interactions are increasingly critical. Here, we review this aspect of environmental interplay to better understand temperature's role in immune variation and subsequent risk of disease.

Defining Usual Oral Temperature Ranges in Outpatients Using an Unsupervised Learning Algorithm

Importance

Although oral temperature is commonly assessed in medical examinations, the range of usual or "normal" temperature is poorly defined.

Objective

To determine normal oral temperature ranges by age, sex, height, weight, and time of day.

Design, Setting, and Participants

This cross-sectional study used clinical visit information from the divisions of Internal Medicine and Family Medicine in a single large medical care system. All adult outpatient encounters that included temperature measurements from April 28, 2008, through June 4, 2017, were eligible for inclusion. The LIMIT (Laboratory Information Mining for Individualized Thresholds) filtering algorithm was applied to iteratively remove encounters with primary diagnoses overrepresented in the tails of the temperature distribution, leaving only those diagnoses unrelated to temperature. Mixed-effects modeling was applied to the remaining temperature measurements to identify independent factors associated with normal oral temperature and to generate individualized normal temperature ranges. Data were analyzed from July 5, 2017, to June 23, 2023.

Exposures

Primary diagnoses and medications, age, sex, height, weight, time of day, and month, abstracted from each outpatient encounter.

Main Outcomes and Measures

Normal temperature ranges by age, sex, height, weight, and time of day.

Results

Of 618 306 patient encounters, 35.92% were removed by LIMIT because they included diagnoses or medications that fell disproportionately in the tails of the temperature distribution. The encounters removed due to overrepresentation in the upper tail were primarily linked to infectious diseases (76.81% of all removed encounters); type 2 diabetes was the only diagnosis removed for overrepresentation in the lower tail (15.71% of all removed encounters). The 396 195 encounters included in the analysis set consisted of 126 705 patients (57.35% women; mean [SD] age, 52.7 [15.9] years). Prior to running LIMIT, the mean (SD) overall oral temperature was 36.71 °C (0.43 °C); following LIMIT, the mean (SD) temperature was 36.64 °C (0.35 °C). Using mixed-effects modeling, age, sex, height, weight, and time of day accounted for 6.86% (overall) and up to 25.52% (per patient) of the observed variability in temperature. Mean normal oral temperature did not reach 37 °C for any subgroup; the upper 99th percentile ranged from 36.81 °C (a tall man with underweight aged 80 years at 8:00 am) to 37.88 °C (a short woman with obesity aged 20 years at 2:00 pm).

Conclusions and Relevance

The findings of this cross-sectional study suggest that normal oral temperature varies in an expected manner based on sex, age, height, weight, and time of day, allowing individualized normal temperature ranges to be established. The clinical significance of a value outside of the usual range is an area for future study.

Understanding temporal changes and seasonal variations in glycemic trends using wearable data

Seasonal variations in glycemic trends remain largely unstudied despite the growing prevalence of diabetes. To address this gap, our objective is to investigate temporal changes in glycemic trends by analyzing intensively sampled blood glucose data from 137 patients (ages 2 to 76, primarily type 1 diabetes) over the course of 9 months to 4.5 years. From over 91,000 days of continuous glucose monitor data, we found that glycemic control decreases significantly around the holidays, with the largest decline observed on New Year's Day among the patients with already poor glycemic control (i.e., <55% time in the target range). We also observed seasonal variations in glycemic trends, with patients having worse glycemic control in the months of November to February (i.e., mid-fall and winter, in the United States), and better control in the months of April to August (i.e., mid-spring and summer). These insights are critical to inform targeted interventions that can improve diabetes outcomes.

Infradian Rhythms in Cerebrovascular Oxygenation and Blood Volume in Humans at Rest: A 5-Year Study

BACKGROUND

All parameters of human physiology show chronobiological variability. While circadian (cycle length ~ 24 h) rhythms of the neuronal, hemodynamic and metabolic aspects of human brain activity are increasingly being explored, infradian (cycle length > 24 h) rhythms are largely unexplored.

AIM

We investigated if cerebrovascular oxygen saturation (StO2) and blood volume ([tHb]) values measured over many years in many subjects during resting show infradian rhythmicity.

SUBJECTS AND METHODS

 Absolute StO2 and [tHb] values (median over a 5 min resting-phase while sitting) were measured in 220 healthy subjects (age: 24.7 ± 3.6 years, 87 males, 133 females) 2-4 times on different days over the right and left frontal lobe (FL) and occipital lobe (OL) by employing frequency-domain NIRS as part of different systemic physiology augmented functional near-infrared spectroscopy, SPA-fNIRS, studies. The data set consisted of 708 single measurements performed over a timespan of 5 years (2017-2021). General additive models (GAM) and cosinor modelling were used to analyze the data.

RESULTS

 The GAM analysis revealed (i) a non-linear trend in the StO2 and [tHb] values over the 5-year span, (ii) a circannual (cycle length ~ 12 months) rhythm in StO2 at the FL (amplitude (A): 3.4%, acrophase (φ): June) and OL (A: 1.5%, φ: May) as well as in [tHb] at the OL (A: 1.2 μM, bathyphase (θ): June), and (iii) a circasemiannual (cycle length ~ 6 months) rhythm in [tHb] at the FL (A: 2.7 μM, φ: March and September, respectively). Furthermore, the circannual oscillations of StO2 (at the FL) and [tHb] (at the OL) were statistically significantly correlated with the day length, outdoor temperature, humidity and air pressure.

DISCUSSION AND CONCLUSION

 We conclude that absolute values of StO2 and [tHb] show chronobiological variability on the group-level with a long-term nonlinear trend as well as circannual/circasemiannual rhythmicity. These rhythms need to be taken into account when defining reference values for StO2 and [tHb] and may correlate with the variability of cerebrovascular disease incidents over the year.

Light/Dark and Temperature Cycling Modulate Metabolic Electron Flow in Pseudomonas aeruginosa Biofilms

Sunlight drives phototrophic metabolism, which affects redox conditions and produces substrates for nonphototrophs. These environmental parameters fluctuate daily due to Earth’s rotation, and nonphototrophic organisms can therefore benefit from the ability to respond to, or even anticipate, such changes. Circadian rhythms, such as daily changes in body temperature, in host organisms can also affect local conditions for colonizing bacteria. Here, we investigated the effects of light/dark and temperature cycling on biofilms of the opportunistic pathogen Pseudomonas aeruginosa PA14. We grew biofilms in the presence of a respiratory indicator dye and found that enhanced dye reduction occurred in biofilm zones that formed during dark intervals and at lower temperatures. This pattern formation occurred with cycling of blue, red, or far-red light, and a screen of mutants representing potential sensory proteins identified two with defects in pattern formation, specifically under red light cycling. We also found that the physiological states of biofilm subzones formed under specific light and temperature conditions were retained during subsequent condition cycling. Light/dark and temperature cycling affected expression of genes involved in primary metabolic pathways and redox homeostasis, including those encoding electron transport chain components. Consistent with this, we found that cbb₃-type oxidases contribute to dye reduction under light/dark cycling conditions. Together, our results indicate that cyclic changes in light exposure and temperature have lasting effects on redox metabolism in biofilms formed by a nonphototrophic, pathogenic bacterium.

Measurement of intraocular temperature in glaucoma: week-day and seasonal fluctuations

PURPOSE

To evaluate long-term intraocular temperature (IOT) variations in eyes with primary open-angle glaucoma (POAG) using an intraocular telemetric sensor.

METHODS

This prospective, open-label, multicentre observational study analysed the IOT variations in 22 eyes of 22 patients with POAG. All enrolled patients underwent implantation of an intraocular pressure (IOP) sensor during cataract surgery. The telemetric system uses a built-in temperature sensor to control measured IOP for temperature. Each time a patient measures their IOP, both the IOP and IOT are recorded in the reader device. Patients were instructed to self-measure their IOP as often as desired, but at least four times daily. Recorded readings were retrieved and analysed using mixed effect models and pairwise comparisons using Bonferroni correction to assess the statistical significance of average IOT variations between each individual weekday and calendar month.

RESULTS

The mean age of patients was 67.8±6.8 years and 36.4% were women. A total of 132 745 readings over 21 102 measurement-days were obtained. On average, IOT was significantly higher on Sundays (34.57°C; 95% CI 34.37 to 34.78) than on any other day of the week (p<0.001). Mean IOT on other weekdays ranged from 34.48°C to 34.51°C. Over the year, IOT followed a clear seasonal pattern, reaching its maximum in July (34.8°C; 95% CI 34.56 to 34.97) and its minimum in January (34.4°C; 95% CI 34.15 to 34.56; p<0.001).

CONCLUSIONS

This study demonstrates the feasibility of continual and long-term measurement of IOT using intraocular sensors. The results show significant short-term and long-term fluctuations of IOT. Research is warranted to understand the impact of IOT variations on IOP, ocular perfusion and glaucoma progression.

Dynamics of temperature change during experimental respiratory virus challenge: Relationships with symptoms, stress hormones, and inflammation

Thermoregulation is a complex, dynamic process involving coordination between multiple autonomic, endocrine, and behavioral mechanisms. In the context of infection, this intricate machinery generates fever, a process believed to serve vital functions in the body's defense against pathogens. In addition to increasing core temperature, infection can lead to changes in the dynamic fluctuations in body temperature over time. The patterns of these deviations may convey information about the health of the body and the course of illness. Here, we utilized dynamic structural equation modeling to explore patterns of body temperature change following an experimental respiratory virus challenge in an aggregated, archival dataset of human participants (N = 1,412). We also examined whether temperature dynamics during infection were related to symptom severity, as well as individual differences in biomarkers of inflammation and stress. We found that individuals meeting the criteria for infection exhibited higher but less stable body temperatures over time compared to those not meeting criteria of infection. While temperature parameters did not reliably predict symptom severity, higher levels of nasal proinflammatory cytokines were associated with lower, more consistent temperatures during the study period. Further, levels of salivary cortisol and urinary catecholamines measured at the beginning of the study appeared to have disparate effects on temperature change. In sum, this research highlights the utility of dynamic time series modeling as a framework for studying body temperature change and lends novel insights into how stress may interact with infection to influence patterns of thermoregulation.

Feasibility and effectiveness of daily temperature screening to detect COVID-19 in a prospective cohort at a large public university

BACKGROUND

Many persons with active SARS-CoV-2 infection experience mild or no symptoms, presenting barriers to COVID-19 prevention. Regular temperature screening is nonetheless used in some settings, including university campuses, to reduce transmission potential. We evaluated the potential impact of this strategy using a prospective university-affiliated cohort.

METHODS

Between June and August 2020, 2912 participants were enrolled and tested for SARS-CoV-2 by PCR at least once (median: 3, range: 1-9). Participants reported temperature and symptoms daily via electronic survey using a previously owned or study-provided thermometer. We assessed feasibility and acceptability of daily temperature monitoring, calculated sensitivity and specificity of various fever-based strategies for restricting campus access to reduce transmission, and estimated the association between measured temperature and SARS-CoV-2 test positivity using a longitudinal binomial mixed model.

RESULTS

Most participants (70.2%) did not initially have a thermometer for taking their temperature daily. Across 5481 total person months, the average daily completion rate of temperature values was 61.6% (median: 67.6%, IQR: 41.8-86.2%). Sensitivity for SARS-CoV-2 ranged from 0% (95% CI 0-9.7%) to 40.5% (95% CI 25.6-56.7%) across all strategies for self-report of possible COVID-19 symptoms on day of specimen collection, with corresponding specificity of 99.9% (95% CI 99.8-100%) to 95.3% (95% CI 94.7-95.9%). An increase of 0.1 °F in individual mean body temperature on the same day as specimen collection was associated with 1.11 increased odds of SARS-CoV-2 positivity (95% CI 1.06-1.17).

CONCLUSIONS

Our study is the first, to our knowledge, that examines the feasibility, acceptability, and effectiveness of daily temperature screening in a prospective cohort during an infectious disease outbreak, and the only study to assess these strategies in a university population. Daily temperature monitoring was feasible and acceptable; however, the majority of potentially infectious individuals were not detected by temperature monitoring, suggesting that temperature screening is insufficient as a primary means of detection to reduce transmission of SARS-CoV-2.

Forecasting Seizure Likelihood With Wearable Technology

The unpredictability of epileptic seizures exposes people with epilepsy to potential physical harm, restricts day-to-day activities, and impacts mental well-being. Accurate seizure forecasters would reduce the uncertainty associated with seizures but need to be feasible and accessible in the long-term. Wearable devices are perfect candidates to develop non-invasive, accessible forecasts but are yet to be investigated in long-term studies. We hypothesized that machine learning models could utilize heart rate as a biomarker for well-established cycles of seizures and epileptic activity, in addition to other wearable signals, to forecast high and low risk seizure periods. This feasibility study tracked participants' (n = 11) heart rates, sleep, and step counts using wearable smartwatches and seizure occurrence using smartphone seizure diaries for at least 6 months (mean = 14.6 months, SD = 3.8 months). Eligible participants had a diagnosis of refractory epilepsy and reported at least 20 seizures (mean = 135, SD = 123) during the recording period. An ensembled machine learning and neural network model estimated seizure risk either daily or hourly, with retraining occurring on a weekly basis as additional data was collected. Performance was evaluated retrospectively against a rate-matched random forecast using the area under the receiver operating curve. A pseudo-prospective evaluation was also conducted on a held-out dataset. Of the 11 participants, seizures were predicted above chance in all (100%) participants using an hourly forecast and in ten (91%) participants using a daily forecast. The average time spent in high risk (prediction time) before a seizure occurred was 37 min in the hourly forecast and 3 days in the daily forecast. Cyclic features added the most predictive value to the forecasts, particularly circadian and multiday heart rate cycles. Wearable devices can be used to produce patient-specific seizure forecasts, particularly when biomarkers of seizure and epileptic activity cycles are utilized.

Is being born in spring significantly associated with early-onset bipolar affective disorder? A case-control study

Few studies have investigated relationships between birth season and early-onset bipolar affective disorder (BAD) in young adults. In the current study, birth season was compared in patients with early-onset BAD and in sex-matched and age-matched controls. A total of 957 patients aged <25 years of age from three hospitals in the North China Plain region were enrolled in the study. Sex-matched and age-matched control group data were collected in universities and schools via questionnaires. The R*C chi-square test was used to assess distributional differences in season of birth both in the patient and control group. A binary logistic regression model adjusted for age and sex was used to evaluate associations between season of birth and BAD. Using spring as the reference season, BAD patients showed significantly lower odds ratios of being born in any other season. There were associations between birth season and early-onset BAD, and early-onset BAD patients were more likely to have been born in spring. These data have implications for future disease prevention strategies and future research.

The relationship between house height and mosquito house entry: an experimental study in rural Gambia

Most malaria infections in sub-Saharan Africa are acquired indoors, thus finding effective ways of preventing mosquito house entry should reduce transmission. Since most malaria mosquitoes fly less than 1 m from the ground, we tested whether raising buildings off the ground would prevent the entry of Anopheles gambiae, the principal African malaria vector, in rural Gambia. Nightly collections of mosquitoes were made using light traps from four inhabited experimental huts, each of which could be moved up or down. Mosquito house entry declined with increasing height, with a hut at 3 m reducing An. gambiae house entry by 84% when compared with huts on the ground. A propensity for malaria vectors to fly close to the ground and reduced levels of carbon dioxide, a major mosquito attractant, in elevated huts, may explain our findings. Raised buildings may help reduce malaria transmission in Africa.

A Tangled Threesome: Circadian Rhythm, Body Temperature Variations, and the Immune System

Simple Summary

In mammals, including humans, the body temperature displays a circadian rhythm and is maintained within a narrow range to facilitate the optimal functioning of physiological processes. Body temperature increases during the daytime and decreases during the nighttime thus influencing the expression of the molecular clock and the clock-control genes such as immune genes. An increase in body temperature (daytime, or fever) also prepares the organism to fight aggression by promoting the activation, function, and delivery of immune cells. Many factors may affect body temperature level and rhythm, including environment, age, hormones, or treatment. The disruption of the body temperature is associated with many kinds of diseases and their severity, thus supporting the assumed association between body temperature rhythm and immune functions. Recent studies using complex analysis suggest that circadian rhythm may change in all aspects (level, period, amplitude) and may be predictive of good or poor outcomes. The monitoring of body temperature is an easy tool to predict outcomes and maybe guide future studies in chronotherapy.

Abstract

The circadian rhythm of the body temperature (CRBT) is a marker of the central biological clock that results from multiple complex biological processes. In mammals, including humans, the body temperature displays a strict circadian rhythm and has to be maintained within a narrow range to allow optimal physiological functions. There is nowadays growing evidence on the role of the temperature circadian rhythm on the expression of the molecular clock. The CRBT likely participates in the phase coordination of circadian timekeepers in peripheral tissues, thus guaranteeing the proper functioning of the immune system. The disruption of the CRBT, such as fever, has been repeatedly described in diseases and likely reflects a physiological process to activate the molecular clock and trigger the immune response. On the other hand, temperature circadian disruption has also been described as associated with disease severity and thus may mirror or contribute to immune dysfunction. The present review aims to characterize the potential implication of the temperature circadian rhythm on the immune response, from molecular pathways to diseases. The origin of CRBT and physiological changes in body temperature will be mentioned. We further review the immune biological effects of temperature rhythmicity in hosts, vectors, and pathogens. Finally, we discuss the relationship between circadian disruption of the body temperature and diseases and highlight the emerging evidence that CRBT monitoring would be an easy tool to predict outcomes and guide future studies in chronotherapy.

Fever Incidence Is Much Lower in the Morning than the Evening: Boston and US National Triage Data

INTRODUCTION

In this observational study, we evaluated time-of-day variation in the incidence of fever that is seen at triage. The observed incidence of fever could change greatly over the day because body temperatures generally rise and fall in a daily cycle, yet fever is identified using a temperature threshold that is unchanging, such as ≥38.0° Celsius (C) (≥100.4° Fahrenheit [F]).

METHODS

We analyzed 93,225 triage temperature measurements from a Boston emergency department (ED) (2009-2012) and 264,617 triage temperature measurements from the National Hospital Ambulatory Medical Care Survey (NHAMCS, 2002-2010), making this the largest study of body temperature since the mid-1800s. Boston data were investigated exploratorily, while NHAMCS was used to corroborate Boston findings and check whether they generalized. NHAMCS results are nationally representative of United States EDs. Analyses focused on adults.

RESULTS

In the Boston ED, the proportion of patients with triage temperatures in the fever range (≥38.0°C, ≥100.4°F) increased 2.5-fold from morning to evening (7:00-8:59 PM vs 7:00-8:59 AM: risk ratio [RR] 2.5, 95% confidence interval [CI], 2.0-3.3). Similar time-of-day changes were observed when investigating alternative definitions of fever: temperatures ≥39.0°C (≥102.2°F) and ≥40.0°C (≥104.0°F) increased 2.4- and 3.6-fold from morning to evening (7:00-8:59 PM vs 7:00-8:59 AM: RRs [95% CIs] 2.4 [1.5-4.3] and 3.6 [1.5-17.7], respectively). Analyses of adult NHAMCS patients provided confirmation, showing mostly similar increases for the same fever definitions and times of day (RRs [95% CIs] 1.8 [1.6-2.1], 1.9 [1.4-2.5], and 2.8 [0.8-9.3], respectively), including after adjusting for 12 potential confounders using multivariable regression (adjusted RRs [95% CIs] 1.8 [1.5-2.1], 1.8 [1.3-2.4], and 2.7 [0.8-9.2], respectively), in age-group analyses (18-64 vs 65+ years), and in several sensitivity analyses. The patterns observed for fever mirror the circadian rhythm of body temperature, which reaches its highest and lowest points at similar times.

CONCLUSION

Fever incidence is lower at morning triages than at evening triages. High fevers are especially rare at morning triage and may warrant special consideration for this reason. Studies should examine whether fever-causing diseases are missed or underappreciated during mornings, especially for sepsis cases and during screenings for infectious disease outbreaks. The daily cycling of fever incidence may result from the circadian rhythm.

TRPV1 is crucial for thermal homeostasis in the mouse by heat loss behaviors under warm ambient temperature

Thermal homeostasis in mammalians is a self-regulating process by which biological systems maintain an internal thermal stability, even under different temperature conditions; however, the molecular mechanisms involved under warm ambient temperature remain unclear. Here, we aimed to clarify functional significance of transient receptor potential vanilloid receptor 1 (TRPV1) under warm ambient temperature. TRPV1 KO mice exhibited transient hyperthermia when exposed to 30.0 and 32.5 °C, whereas wild-type (WT) mice did not. TRPV1 KO mice exhibited prolonged and prominent hyperthermia upon exposure to 35.0 °C, whereas WT mice showed transient hyperthermia. Hyperthermia also occurs in WT mice that received intracerebroventricular injection of TRPV1 antagonist AMG9810 upon exposure to 35.0 °C. Heat loss behaviors, sleeping and body licking, were deficient in TRPV1 KO mice exposed to warm temperatures. Therefore, the present results indicate that central TRPV1 is crucial for maintaining a constant body temperature via the initiation of heat loss behaviors under warm ambient temperature.