Neutralizing antibody responses 300 days after SARS-CoV-2 infection and induction of high antibody titers after vaccination.

Neutralizing antibodies against SARS-CoV-2 are important to protect against infection and/or disease. Using an assay to detect antibodies directed against the receptor binding domain (RBD) of SARS-CoV-2 Spike, we identified individuals with SARS-CoV-2 infection after an outbreak at a local health institution. All but one COVID-19 patient developed detectable anti-RBD antibodies and 77% had virus neutralizing antibody titers of >1:25. Antibody levels declined slightly over time. However, we still detected virus neutralizing antibody titers in 64% of the COVID-19 patients at >300 days after infection, demonstrating durability of neutralizing antibody levels after infection. Importantly, full COVID-19 vaccination of these individuals resulted in higher antibody titers compared to fully vaccinated individuals in the absence of prior infection. These data demonstrate long-lived antibody-mediated immunity after SARS-CoV-2 infection, and a clear benefit of two vaccine doses for recovered individuals.

A modelling framework for local thermal comfort assessment related to bicycle helmet use.

Thermal discomfort due to accumulated sweat increasing head skin wettedness may contribute to low wearing rates of bicycle helmets. Using curated data on human head sweating and helmet thermal properties, a modelling framework for the thermal comfort assessment of bicycle helmet use is proposed. Local sweat rates (LSR) at the head were predicted as the ratio to the gross sweat rate (GSR) of the whole body or by sudomotor sensitivity (SUD), the change in LSR per change in body core temperature (Δtre). Combining those local models with Δtre and GSR output from thermoregulation models, we simulated head sweating depending on the characteristics of the thermal environment, clothing, activity, and exposure duration. Local thermal comfort thresholds for head skin wettedness were derived in relation to thermal properties of bicycle helmets. The modelling framework was supplemented by regression equations predicting the wind-related reductions in thermal insulation and evaporative resistance of the headgear and boundary air layer, respectively. Comparing the predictions of local models coupled with different thermoregulation models to LSR measured at the frontal, lateral and medial head under bicycle helmet use revealed a large spread in LSR predictions predominantly determined by the local models and the considered head region. SUD tended to overestimate frontal LSR but performed better for lateral and medial head regions, whereas predictions by LSR/GSR ratios were lower and agreed better with measured frontal LSR. However, even for the best models root mean squared prediction errors exceeded experimental SD by 18-30%. From the high correlation (R > 0.9) of skin wettedness comfort thresholds with local sweating sensitivity reported for different body regions, we derived a threshold value of 0.37 for head skin wettedness. We illustrate the application of the modelling framework using a commuter-cycling scenario, and discuss its potential as well as the needs for further research.

From Immunosenescence to Aging Types-Establishing Reference Intervals for Immune Age Biomarkers by Centile Estimation.

Immunological aging type definition requires establishing reference intervals from the distribution of immunosenescence biomarkers conditional on age. For 1605 individuals (18-97 years), we determined the comprehensive immune age index IMMAX from flow-cytometry-based blood cell sub-populations and identified age-specific centiles by fitting generalized additive models for location, scale, and shape. The centiles were uncorrelated with age and facilitated the categorization of individuals as immunologically slow or fast aging types. Using its 50th percentile as a reference, we rescaled the IMMAX to equivalent years of life (EYOL) and computed the immunological age gap as the difference between EYOL and chronological age. Applied to preliminary baseline and follow-up measurements from 53 participants of the Dortmund Vital Study (Clinical-Trials.gov Identifier: NCT05155397), the averaged changes in the IMMAX and EYOL conformed to the 5-year follow-up period, whereas no significant changes occurred concerning IMMAX centiles and age gap. This suggested that the participants immunologically adapted to aging and kept their relative positions within the cohort. Sex was non-significant. Methodical comparisons indicated that future confirmatory analyses with the completed follow-up examinations could rely on percentile curves estimated by simple linear quantile regression, while the selection of the immunosenescence biomarker will greatly influence the outcome, with IMMAX representing the preferable choice.

Sex differences in temperature-related all-cause mortality in the Netherlands.

PURPOSE: Over the last few decades, a global increase in both cold and heat extremes has been observed with significant impacts on human mortality. Although it is well-identified that older individuals (> 65 years) are most prone to temperature-related mortality, there is no consensus on the effect of sex. The current study investigated if sex differences in temperature-related mortality exist in the Netherlands. METHODS: Twenty-three-year ambient temperature data of the Netherlands were combined with daily mortality data which were subdivided into sex and three age classes (< 65 years, 65-80 years, ≥ 80 years). Distributed lag non-linear models were used to analyze the effect of ambient temperature on mortality and determine sex differences in mortality attributable to the cold and heat, which is defined as mean daily temperatures below and above the Minimum Mortality Temperature, respectively. RESULTS: Attributable fractions in the heat were higher in females, especially in the oldest group under extreme heat (≥ 97.5th percentile), whilst no sex differences were found in the cold. Cold- and heat-related mortality was most prominent in the oldest age group (≥ 80 years) and to a smaller extent in the age group between 65-80 years. In the age group < 65 years temperature-related mortality was only significant for males in the heat. CONCLUSION: Mortality in the Netherlands represents the typical V- or hockey-stick shaped curve with a higher daily mortality in the cold and heat than at milder temperatures in both males and females, especially in the age group ≥ 80 years. Heat-related mortality was higher in females than in males, especially in the oldest age group (≥ 80 years) under extreme heat, whilst in the cold no sex differences were found. The underlying cause may be of physiological or behavioral nature, but more research is necessary.

Quantitative analysis of human NK cell reactivity using latex beads coated with defined amounts of antibodies.

Natural Killer (NK) cell responses are regulated by a variety of different surface receptors. While we can determine the overall positive or negative effect of a given receptor on NK cell functions, investigating NK cell regulation in a quantitative way is challenging. To quantitatively investigate individual receptors for their effect on NK cell activation, we chose to functionalize latex beads that have approximately the same size as lymphocytes with defined amounts of specific antibodies directed against distinct activating receptors. This enabled us to investigate NK cell reactivity in a defined, clean, and controllable system. Only CD16 and NKp30 could activate the degranulation of resting human NK cells. CD16, NKG2D, NKp30, NKp44, and NKp46 were able to activate cultured NK cells. NK cell activation resulted in the induction of polyfunctional cells that degranulated and produced IFN-γ and MIP-1ß. Interestingly, polyfunctional NK cells were only induced by triggering ITAM-coupled receptors. NKp44 showed a very sensitive response pattern, where a small increase in receptor stimulation caused maximal NK cell activity. In contrast, stimulation of 2B4 induced very little NK cell degranulation, while providing sufficient signal for NK cell adhesion. Our data demonstrate that activating receptors differ in their effectiveness to stimulate NK cells.

Impact of biometeorological conditions and air pollution on influenza-like illnesses incidence in Warsaw.

In order to assess the influence of atmospheric conditions and particulate matter (PM) on the seasonally varying incidence of influenza-like illnesses (ILI) in the capital of Poland-Warsaw, we analysed time series of ILI reported for the about 1.75 million residents in total and for different age groups in 288 approximately weekly periods, covering 6 years 2013-2018. Using Poisson regression, we predicted ILI by the Universal Thermal Climate Index (UTCI) as biometeorological indicator, and by PM2.5 and PM10, respectively, as air quality measures accounting for lagged effects spanning up to 3 weeks. Excess ILI incidence after adjusting for seasonal and annual trends was calculated by fitting generalized additive models. ILI morbidity increased with rising PM concentrations, for both PM2.5 and PM10, and with cooler atmospheric conditions as indicated by decreasing UTCI. While the PM effect focused on the actual reporting period, the atmospheric influence exhibited a more evenly distributed lagged effect pattern over the considered 3-week period. Though ILI incidence adjusted for population size significantly declined with age, age did not significantly modify the effect sizes of both PM and UTCI. These findings contribute to better understanding environmental conditionings of influenza seasonality in a temperate climate. This will be beneficial to forecasting future dynamics of ILI and to planning clinical and public health resources under climate change scenarios.

Estimated work ability in warm outdoor environments depends on the chosen heat stress assessment metric.

With a view to occupational effects of climate change, we performed a simulation study on the influence of different heat stress assessment metrics on estimated workability (WA) of labour in warm outdoor environments. Whole-day shifts with varying workloads were simulated using as input meteorological records for the hottest month from four cities with prevailing hot (Dallas, New Delhi) or warm-humid conditions (Managua, Osaka), respectively. In addition, we considered the effects of adaptive strategies like shielding against solar radiation and different work-rest schedules assuming an acclimated person wearing light work clothes (0.6 clo). We assessed WA according to Wet Bulb Globe Temperature (WBGT) by means of an empirical relation of worker performance from field studies (Hothaps), and as allowed work hours using safety threshold limits proposed by the corresponding standards. Using the physiological models Predicted Heat Strain (PHS) and Universal Thermal Climate Index (UTCI)-Fiala, we calculated WA as the percentage of working hours with body core temperature and cumulated sweat loss below standard limits (38 °C and 7.5% of body weight, respectively) recommended by ISO 7933 and below conservative (38 °C; 3%) and liberal (38.2 °C; 7.5%) limits in comparison. ANOVA results showed that the different metrics, workload, time of day and climate type determined the largest part of WA variance. WBGT-based metrics were highly correlated and indicated slightly more constrained WA for moderate workload, but were less restrictive with high workload and for afternoon work hours compared to PHS and UTCI-Fiala. Though PHS showed unrealistic dynamic responses to rest from work compared to UTCI-Fiala, differences in WA assessed by the physiological models largely depended on the applied limit criteria. In conclusion, our study showed that the choice of the heat stress assessment metric impacts notably on the estimated WA. Whereas PHS and UTCI-Fiala can account for cumulative physiological strain imposed by extended work hours when working heavily under high heat stress, the current WBGT standards do not include this. Advanced thermophysiological models might help developing alternatives, where not only modelling details but also the choice of physiological limit criteria will require attention. There is also an urgent need for suitable empirical data relating workplace heat exposure to workability.

Chronic Toxoplasma gondii Infection Modulates Hearing Ability across the Adult Life Span.

While several studies have shown associations between hearing disorders and congenital toxoplasmosis, the present study investigated the impact of chronic, latent Toxoplasma gondii (T. gondii) infection on hearing loss. We used a regression analysis to explore whether latent T. gondii infection modulates changes in hearing thresholds over an age range from 20 to 70 years. We analyzed audiometric data of 162 T. gondii IgG-positive and 430 T. gondii-negative participants, collected in the Dortmund Vital Study (DVS, ClinicalTrials.gov Identifier: NCT05155397), a prospective study on healthy cognitive aging. The regression analysis indicated that latent toxoplasmosis was associated with an accelerated development in hearing loss over the observed age range. Hearing loss was less frequent in IgG-positive than in IgG-negative participants up to the age of about 40 for a low (0.125-1 kHz)-frequency range. For high (2-8 kHz) frequencies, this pattern reversed for ages above 65 years. We discuss these findings on hearing function in the context of a recently proposed model, suggesting that latent toxoplasmosis can differentially affect brain functions across a lifespan.

The uncertainty of UTCI due to uncertainties in the determination of radiation fluxes derived from numerical weather prediction and regional climate model simulations.

In this study we examine the determination accuracy of both the mean radiant temperature (Tmrt) and the Universal Thermal Climate Index (UTCI) within the scope of numerical weather prediction (NWP), and global (GCM) and regional (RCM) climate model simulations. First, Tmrt is determined and the so-called UTCI-Fiala model is then used for the calculation of UTCI. Taking into account the uncertainties of NWP model (among others the HIgh Resolution Limited Area Model HIRLAM) output (temperature, downwelling short-wave and long-wave radiation) stated in the literature, we simulate and discuss the uncertainties of Tmrt and UTCI at three stations in different climatic regions of Europe. The results show that highest negative (positive) differences to reference cases (under assumed clear-sky conditions) of up to -21°C (9°C) for Tmrt and up to -6°C (3.5°C) for UTCI occur in summer (winter) due to cloudiness. In a second step, the uncertainties of RCM simulations are analyzed: three RCMs, namely ALADIN (Aire Limitée Adaptation dynamique Développement InterNational), RegCM (REGional Climate Model) and REMO (REgional MOdel) are nested into GCMs and used for the prediction of temperature and radiation fluxes in order to estimate Tmrt and UTCI. The inter-comparison of RCM output for the three selected locations shows that biases between 0.0 and ±17.7°C (between 0.0 and ±13.3°C) for Tmrt (UTCI), and RMSE between ±0.5 and ±17.8°C (between ±0.8 and ±13.4°C) for Tmrt (UTCI) may be expected. In general the study shows that uncertainties of UTCI, due to uncertainties arising from calculations of radiation fluxes (based on NWP models) required for the prediction of Tmrt, are well below ±2°C for clear-sky cases. However, significant higher uncertainties in UTCI of up to ±6°C are found, especially when prediction of cloudiness is wrong.

Temperature-Humidity-Dependent Wind Effects on Physiological Heat Strain of Moderately Exercising Individuals Reproduced by the Universal Thermal Climate Index (UTCI).

Increasing wind speed alleviates physiological heat strain; however, health policies have advised against using ventilators or fans under heat wave conditions with air temperatures above the typical skin temperature of 35 °C. Recent research, mostly with sedentary participants, suggests mitigating the effects of wind at even higher temperatures, depending on the humidity level. Our study aimed at exploring and quantifying whether such results are transferable to moderate exercise levels, and whether the Universal Thermal Climate Index (UTCI) reproduces those effects. We measured heart rates, core and skin temperatures, and sweat rates in 198 laboratory experiments completed by five young, semi-nude, heat-acclimated, moderately exercising males walking the treadmill at 4 km/h on the level for three hours under widely varying temperature-humidity combinations and two wind conditions. We quantified the cooling effect of increasing the wind speed from 0.3 to 2 m/s by fitting generalized additive models predicting the physiological heat stress responses depending on ambient temperature, humidity, and wind speed. We then compared the observed wind effects to the assessment performed by the UTCI. Increasing the wind speed lowered the physiological heat strain for air temperatures below 35 °C, but also for higher temperatures with humidity levels above 2 kPa water vapor pressure concerning heart rate and core temperature, and 3 kPa concerning skin temperature and sweat rate, respectively. The UTCI assessment of wind effects correlated positively with the observed changes in physiological responses, showing the closest agreement (r = 0.9) for skin temperature and sweat rate, where wind is known for elevating the relevant convective and evaporative heat transfer. These results demonstrate the potential of the UTCI for adequately assessing sustainable strategies for heat stress mitigation involving fans or ventilators, depending on temperature and humidity, for moderately exercising individuals.

Early expansion of activated adaptive but also exhausted NK cells during acute severe SARS-CoV-2 infection.

The analysis of immunological parameters during the course of a SARS-CoV-2 infection is of great importance, both to identify diagnostic markers for the risk of a severe course of COVID-19, and to better understand the role of the immune system during the infection. By using multicolor flow cytometry we compared the phenotype of Natural Killer (NK) cells from hospitalized COVID-19 patients during early SARS-CoV-2 infection with samples from recovered and SARS-CoV-2 naïve subjects. Unsupervised high-dimensional analysis of 28-color flow cytometric data revealed a strong enrichment of NKG2C expressing NK cells in response to the acute viral infection. In addition, we found an overrepresentation of highly activated NK cell subsets with an exhausted phenotype. Moreover, our data show long-lasting phenotypic changes within the NK cell compartment that did not completely reverse up to 2 months after recovery. This demonstrates that NK cells are involved in the early innate immune response against SARS-CoV-2.

A Systematic Analysis of Biological, Sociodemographic, Psychosocial, and Lifestyle Factors Contributing to Work Ability Across the Working Life Span: Cross-sectional Study.

BACKGROUND: As employees age, their physical and mental abilities decline and work ability decreases, enhancing the risk for long-term sick leave or even premature retirement. However, the relative impact of biological and environmental determinants on work ability with increasing age is poorly understood in terms of their complexity. OBJECTIVE: Previous research has shown relationships between work ability and job and individual resources, as well as specific demographic and lifestyle-related variables. However, other potentially important predictors of work ability remain unexplored, such as personality traits and biological determinants, including cardiovascular, metabolic, immunological, and cognitive abilities or psychosocial factors. Our aim was to systematically evaluate a wide range of factors to extract the most crucial predictors of low and high work ability across the working life span. METHODS: As part of the Dortmund Vital Study, 494 participants from different occupational sectors, aged between 20 and 69 years, completed the Work Ability Index (WAI) assessing employee's mental and physical resources. A total of 30 sociodemographic variables were grouped into 4 categories (social relationships, nutrition and stimulants, education and lifestyle, and work related), and 80 biological and environmental variables were grouped into 8 domains (anthropometric, cardiovascular, metabolic, immunologic, personality, cognitive, stress related, and quality of life) and have been related to the WAI. RESULTS: Using the analyses, we extracted important sociodemographic factors influencing work ability, such as education, social activities, or sleep quality, and identified age-dependent and age-independent determinants of work ability. Regression models explained up to 52% of the WAI variance. Negative predictors of work ability were chronological and immunological age, immunological inefficiency, BMI, neuroticism, psychosocial stress, emotional exhaustion, demands from work, daily cognitive failures, subclinical depression, and burnout symptoms. Positive predictors were maximum heart rate during ergometry, normal blood pressure, hemoglobin and monocyte concentration, weekly physical activity, commitment to the company, pressure to succeed, and good quality of life. CONCLUSIONS: The identified biological and environmental risk factors allowed us to evaluate work ability in its complexity. Policy makers, employers, and occupational safety and health personnel should consider the modifiable risk factors we identified to promote healthy aging at work through focused physical, dietary, cognitive, and stress-reduced preventive programs, in addition to well-balanced working conditions. This may also increase the quality of life, commitment to the job, and motivation to succeed, which are important factors to maintain or even enhance work ability in the aging workforce and to prevent early retirement. TRIAL REGISTRATION: ClinicalTrials.gov NCT05155397; https://clinicaltrials.gov/ct2/show/NCT05155397. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/32352.

Physiological responses to temperature and humidity compared to the assessment by UTCI, WGBT and PHS.

In COST Action 730, a multi-segmental thermophysiological model was used to describe physiological strain reactions for different climatic conditions in order to develop a 'Universal Thermal Climate Index' (UTCI). UTCI predictions for warm climates were compared with empirical data from the laboratory tests. The comparison was performed by means of equivalence lines within a psychrometric chart so that the combined influence of air temperature and humidity on physiological strain may be assessed. Within a reasonable regime of air temperatures and relative humidities (RH), the differences between simulated and measured values were as follows: for rectal temperatures below 0.3°C, for skin temperatures below 1.5°C, for sweat rates below 200 g/h and for heart rates (estimated from relative cardiac output) below 30 min(-1). This characterises the validity of the model with respect to the description of the influence of heat and humidity on physiological strain. The same comparison to physiological data was also conducted for the equivalent temperature calculated for UTCI. In order to compare UTCI with other thermal indices used in occupational health, the physiological data have also been compared to equivalence lines of WBGT (Wet Bulb Globe Temperature) and PHS (Predicted Heat Strain) indices.

UTCI-Fiala multi-node model of human heat transfer and temperature regulation.

The UTCI-Fiala mathematical model of human temperature regulation forms the basis of the new Universal Thermal Climate Index (UTC). Following extensive validation tests, adaptations and extensions, such as the inclusion of an adaptive clothing model, the model was used to predict human temperature and regulatory responses for combinations of the prevailing outdoor climate conditions. This paper provides an overview of the underlying algorithms and methods that constitute the multi-node dynamic UTCI-Fiala model of human thermal physiology and comfort. Treated topics include modelling heat and mass transfer within the body, numerical techniques, modelling environmental heat exchanges, thermoregulatory reactions of the central nervous system, and perceptual responses. Other contributions of this special issue describe the validation of the UTCI-Fiala model against measured data and the development of the adaptive clothing model for outdoor climates.

Predicting urban outdoor thermal comfort by the Universal Thermal Climate Index UTCI--a case study in Southern Brazil.

Recognising that modifications to the physical attributes of urban space are able to promote improved thermal outdoor conditions and thus positively influence the use of open spaces, a survey to define optimal thermal comfort ranges for passers-by in pedestrian streets was conducted in Curitiba, Brazil. We applied general additive models to study the impact of temperature, humidity, and wind, as well as long-wave and short-wave radiant heat fluxes as summarised by the recently developed Universal Thermal Climate Index (UTCI) on the choice of clothing insulation by fitting LOESS smoothers to observations from 944 males and 710 females aged from 13 to 91 years. We further analysed votes of thermal sensation compared to predictions of UTCI. The results showed that females chose less insulating clothing in warm conditions compared to males and that observed values of clothing insulation depended on temperature, but also on season and potentially on solar radiation. The overall pattern of clothing choice was well reflected by UTCI, which also provided for good predictions of thermal sensation votes depending on the meteorological conditions. Analysing subgroups indicated that the goodness-of-fit of the UTCI was independent of gender and age, and with only limited influence of season and body composition as assessed by body mass index. This suggests that UTCI can serve as a suitable planning tool for urban thermal comfort in sub-tropical regions.

Deriving the operational procedure for the Universal Thermal Climate Index (UTCI).

The Universal Thermal Climate Index (UTCI) aimed for a one-dimensional quantity adequately reflecting the human physiological reaction to the multi-dimensionally defined actual outdoor thermal environment. The human reaction was simulated by the UTCI-Fiala multi-node model of human thermoregulation, which was integrated with an adaptive clothing model. Following the concept of an equivalent temperature, UTCI for a given combination of wind speed, radiation, humidity and air temperature was defined as the air temperature of the reference environment, which according to the model produces an equivalent dynamic physiological response. Operationalising this concept involved (1) the definition of a reference environment with 50% relative humidity (but vapour pressure capped at 20 hPa), with calm air and radiant temperature equalling air temperature and (2) the development of a one-dimensional representation of the multivariate model output at different exposure times. The latter was achieved by principal component analyses showing that the linear combination of 7 parameters of thermophysiological strain (core, mean and facial skin temperatures, sweat production, skin wettedness, skin blood flow, shivering) after 30 and 120 min exposure time accounted for two-thirds of the total variation in the multi-dimensional dynamic physiological response. The operational procedure was completed by a scale categorising UTCI equivalent temperature values in terms of thermal stress, and by providing simplified routines for fast but sufficiently accurate calculation, which included look-up tables of pre-calculated UTCI values for a grid of all relevant combinations of climate parameters and polynomial regression equations predicting UTCI over the same grid. The analyses of the sensitivity of UTCI to humidity, radiation and wind speed showed plausible reactions in the heat as well as in the cold, and indicate that UTCI may in this regard be universally useable in the major areas of research and application in human biometeorology.

The UTCI-clothing model.

The Universal Thermal Climate Index (UTCI) was conceived as a thermal index covering the whole climate range from heat to cold. This would be impossible without considering clothing as the interface between the person (here, the physiological model of thermoregulation) and the environment. It was decided to develop a clothing model for this application in which the following three factors were considered: (1) typical dressing behaviour in different temperatures, as observed in the field, resulting in a model of the distribution of clothing over the different body segments in relation to the ambient temperature, (2) the changes in clothing insulation and vapour resistance caused by wind and body movement, and (3) the change in wind speed in relation to the height above ground. The outcome was a clothing model that defines in detail the effective clothing insulation and vapour resistance for each of the thermo-physiological model's body segments over a wide range of climatic conditions. This paper details this model's conception and documents its definitions.

Calibrating a Comprehensive Immune Age Metric to Analyze the Cross Sectional Age-Related Decline in Cardiorespiratory Fitness.

Cardiorespiratory fitness (CRF) is essential for sustained work ability in good health, but declines with aging, as does the functionality of the immune system, the latter process commonly referred to as immunosenescence. This study aimed to compare the capacity of immunosenescence biomarkers with chronological age for predicting low CRF in a cross-sectional sample recruited from the regional working population. CRF was determined by submaximal bicycle ergometer testing in a cross-sectional sample of 597 volunteers aged 20-70 years from the 'Dortmund Vital Study' (DVS, ClinicalTrials.gov Identifier: NCT05155397). Low CRF was scored if the ergometer test was not completed due to medical reasons or if the power output projected to a heart rate of 130 bpm divided by body mass was below sex-specific reference values of 1.25 W/kg for females and 1.5 W/kg for males, respectively. In addition to established biomarkers of immunosenescence, we calibrated a comprehensive metric of immune age to our data and compared its predictive capacity for low CRF to chronological age, while adjusting our analysis for the influence of sex, obesity, and the level of regular physical activity, by applying univariate and multiple logistic regression. While obesity, low physical activity, chronological and immune age were all associated with increased probability for low CRF in univariate analyses, multiple logistic regression revealed that obesity and physical activity together with immune age, but not chronological age, were statistically significant predictors of low CRF outcome. Sex was non-significant due to the applied sex-specific reference values. These results demonstrate that biological age assessed by our immunological metric can outperform chronological age as a predictor for CRF and indicate a potential role for immunosenescence in explaining the inter-individual variability of the age-related decline in cardiorespiratory fitness.

Impact of Biological and Lifestyle Factors on Cognitive Aging and Work Ability in the Dortmund Vital Study: Protocol of an Interdisciplinary, Cross-sectional, and Longitudinal Study.

BACKGROUND: Previous research revealed several biological and environmental factors modulating cognitive functioning over a human's lifespan. However, the relationships and interactions between biological factors (eg, genetic polymorphisms, immunological parameters, metabolic products, or infectious diseases) and environmental factors (eg, lifestyle, physical activity, nutrition, and work type or stress at work) as well as their impact on cognitive functions across the lifespan are still poorly understood with respect to their complexity. OBJECTIVE: The goal of the Dortmund Vital Study is to validate previous hypotheses as well as generate and validate new hypotheses about the relationships among aging, working conditions, genetic makeup, stress, metabolic functions, the cardiovascular system, the immune system, and mental performance over the human lifespan with a focus on healthy working adults. The Dortmund Vital Study is a multidisciplinary study involving the Departments of Ergonomics, Immunology, Psychology and Neurosciences, and Toxicology at the Leibniz Research Centre for Working Environment and Human Factors at the Technical University of Dortmund (IfADo) in Germany, as well as several national and international partners. METHODS: The Dortmund Vital Study is designed as a combined cross-sectional and longitudinal study. Approximately 600 healthy subjects aged between 20 and 70 years will participate. A wide range of demographic, psychological, behavioral, sensory, cardiovascular, immunological, and biochemical data, a comprehensive electroencephalography (EEG)-based cognitive test battery as well as structural and functional magnetic resonance imaging (MRI) have been included in the study. RESULTS: The study was approved by the Ethics Committee of IfADo in October 2015. The baseline testing was conducted between 2016 and 2021 and will be repeated every 5 years (3 follow-up measures until 2035). As of March 2020 (until the outbreak of the COVID-19 pandemic), 593 participants have been enrolled. Some results from the cross-sectional part of the study were already published, further results will be published soon. Longitudinal data will be analyzed and published by 2025. CONCLUSIONS: We anticipate that the study will shed light on sources of interindividual differences in the alterations of cognitive functioning with increasing age and reveal biological and lifestyle markers contributing to work ability, longevity, and healthy aging on the one hand, and to risk factors for cognitive decline, mild cognitive impairment, or even dementia on the other hand. TRIAL REGISTRATION: ClinicalTrials.gov NCT05155397; https://clinicaltrials.gov/ct2/show/NCT05155397. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/32352.

Indicators to assess physiological heat strain - Part 1: Systematic review.

In a series of three companion papers published in this Journal, we identify and validate the available thermal stress indicators (TSIs). In this first paper of the series, we conducted a systematic review (registration: INPLASY202090088) to identify all TSIs and provide reliable information regarding their use (funded by EU Horizon 2020; HEAT-SHIELD). Eight databases (PubMed, Agricultural and Environmental Science Collection, Web of Science, Scopus, Embase, Russian Science Citation Index, MEDLINE, and Google Scholar) were searched from database inception to 15 April 2020. No restrictions on language or study design were applied. Of the 879 publications identified, 232 records were considered for further analysis. This search identified 340 instruments and indicators developed between 200 BC and 2019 AD. Of these, 153 are nomograms, instruments, and/or require detailed non-meteorological information, while 187 can be mathematically calculated utilizing only meteorological data. Of these meteorology-based TSIs, 127 were developed for people who are physically active, and 61 of those are eligible for use in occupational settings. Information regarding the equation, operating range, interpretation categories, required input data, as well as a free software to calculate all 187 meteorology-based TSIs is provided. The information presented in this systematic review should be adopted by those interested in performing on-site monitoring and/or big data analytics for climate services to ensure appropriate use of the meteorology-based TSIs. Studies two and three in this series of companion papers present guidance on the application and validation of these TSIs, to guide end users of these indicators for more effective use.