Scalable Visualization Methods for Modern Generalized Additive Models

Psilocybin increases optimistic engagement over time: computational modelling of behaviour in rats

Psilocybin has shown promise as a novel pharmacological intervention for treatment of depression, where post-acute effects of psilocybin treatment have been associated with increased positive mood and decreased pessimism. Although psilocybin is proving to be effective in clinical trials for treatment of psychiatric disorders, the information processing mechanisms affected by psilocybin are not well understood. Here, we fit active inference and reinforcement learning computational models to a novel two-armed bandit reversal learning task capable of capturing engagement behaviour in rats. The model revealed that after receiving psilocybin, rats achieve more rewards through increased task engagement, mediated by modification of forgetting rates and reduced loss aversion. These findings suggest that psilocybin may afford an optimism bias that arises through altered belief updating, with translational potential for clinical populations characterised by lack of optimism.

Use of long-term underwater camera surveillance to assess the effects of the largest Amazonian hydroelectric dam on fish communities

The increase in the construction of mega dams in tropical basins is considered a threat to freshwater fish diversity. Although difficult to detect in conventional monitoring programs, rheophilic species and those reliant on shallow habitats comprise a large proportion of fish diversity in tropical basins and are among the most sensitive species to hydropower impacts. We used Baited Remote Underwater Video (BRUV), an innovative, non-invasive sampling technique, to record the impacts caused by Belo Monte, the third largest hydropower project in the world, on fishes inhabiting fast waters in the Xingu River. BRUV were set in a river stretch of ~ 240 km for 7 years, 2 before and 5 after the Belo Monte operation. We explored the spatial and temporal variation in fish diversity (α, β, and γ) and abundance (MaxN) using generalized additive models. We also investigated the variation of environmental variables and tested how much information we gained by including them in the diversity and abundance models. Belo Monte altered the flow regime, water characteristics, and fishery yield in the Xingu, resulting in changes in the fish community structure. Temporally, we observed sharp declines in α diversity and abundance, far exceeding those from a previous study conducted with more conventional sampling methods (i.e., catch-based) in the region. γ-diversity was also significantly reduced, but we observed a non-expected increase in β diversity over time. The latter may be associated with a reduction in river connectivity and an increase in environmental heterogeneity among river sectors. Unexpected signs of recovery in diversity metrics were observed in the last years of monitoring, which may be associated with the maintenance of flow levels higher than those previously planned. These results showed that BRUV can be a useful and sensitive tool to monitor the impacts of dams and other enterprises on fish fauna from clear-water rivers. Moreover, this study enhances our comprehension of the temporal variations in freshwater fish diversity metrics and discusses the prevalent assumption that a linear continuum in fish-structure damage associated with dam impoundments may exhibit temporal non-linearity.

John M, Chau D, Clair C, Chan H, Holzman R, Martin CH. A multi-peak performance landscape for scale biting in an adaptive radiation of pupfishes

The physical interactions between organisms and their environment ultimately shape diversification rates, but the contributions of biomechanics to evolutionary divergence are frequently overlooked. Here, we estimated a performance landscape for biting in an adaptive radiation of Cyprinodon pupfishes, including scale-biting and molluscivore specialists, and compared performance peaks with previous estimates of the fitness landscape in this system. We used high-speed video to film feeding strikes on gelatin cubes by scale eater, molluscivore, generalist and hybrid pupfishes and measured bite dimensions. We then measured five kinematic variables from 227 strikes using the SLEAP machine-learning model. We found a complex performance landscape with two distinct peaks best predicted gel-biting performance, corresponding to a significant non-linear interaction between peak gape and peak jaw protrusion. Only scale eaters and their hybrids were able to perform strikes within the highest performance peak, characterized by larger peak gapes and greater jaw protrusion. A performance valley separated this peak from a lower performance peak accessible to all species, characterized by smaller peak gapes and less jaw protrusion. However, most individuals exhibited substantial variation in strike kinematics and species could not be reliably distinguished by their strikes, indicating many-to-many mapping of morphology to performance. The two performance peaks observed in the lab were partially consistent with estimates of a two-peak fitness landscape measured in the wild, with the exception of the new performance peak for scale eaters. We thus reveal a new bimodal non-linear biomechanical model that connects morphology to performance to fitness in a sympatric radiation of trophic niche specialists.

Night-to-night variability of objective sleep outcomes in youth Middle Eastern football players

OBJECTIVE

To describe components of night-to-night variation in objective measures of sleep.

METHODS

We conducted a secondary data analysis of consecutive and chronologically ordered actigraphy-based measurements for time in bed (min), time asleep (min), and wake-after-sleep onset (min). This investigation examined 575 individual night-based measures available for a sub-sample of fifty-two, male youth Middle Eastern football players tracked over a 14-day surveillance period (chronological age range: 12.1 to 16 years). Distinct multivariable-adjusted generalized additive models included each objective sleep outcome measure as dependent variable and disaggregated components of variation for night measurement-by-sleep period interaction, week part (weekday or weekend), and study participant random effects from within-subject night-to-night sleep variation.

RESULTS

The within-subject standard deviation (SD) of ±98 min (95% confidence interval [CI], 92 to 104 min) for time in bed, ±87 min (95%CI, 82 to 93 min) for time asleep, and ±23 min (95%CI, 22 to 25 min) for wake-after-sleep-onset overwhelmed other sources of variability and accounted for ∼44% to 53% of the overall night-to-night variation. The night measurement-by-fragmented sleep period interaction SD was ±83 min (95%CI, 44 to 156 min) for time in bed, ±67 min (95%CI, 34 to 131 min) for time asleep, and ±15 min (95%CI, 7 to 32 min) for wake-after-sleep-onset that accounted for ∼22% to 32% of each sleep outcome measure overall variability.

CONCLUSIONS

Substantial random night-to-night within-subject variability poses additional challenges for strategies aiming to mitigate problems of insufficient and inconsistent sleep that are detrimental to school learning and youth athlete development processes.

John M, Chau D, Clair C, Chan H, Holzman R, Martin CH. Multiple performance peaks for scale-biting in an adaptive radiation of pupfishes

The physical interactions between organisms and their environment ultimately shape their rate of speciation and adaptive radiation, but the contributions of biomechanics to evolutionary divergence are frequently overlooked. Here we investigated an adaptive radiation of Cyprinodon pupfishes to measure the relationship between feeding kinematics and performance during adaptation to a novel trophic niche, lepidophagy, in which a predator removes only the scales, mucus, and sometimes tissue from their prey using scraping and biting attacks. We used high-speed video to film scale-biting strikes on gelatin cubes by scale-eater, molluscivore, generalist, and hybrid pupfishes and subsequently measured the dimensions of each bite. We then trained the SLEAP machine-learning animal tracking model to measure kinematic landmarks and automatically scored over 100,000 frames from 227 recorded strikes. Scale-eaters exhibited increased peak gape and greater bite length; however, substantial within-individual kinematic variation resulted in poor discrimination of strikes by species or strike type. Nonetheless, a complex performance landscape with two distinct peaks best predicted gel-biting performance, corresponding to a significant nonlinear interaction between peak gape and peak jaw protrusion in which scale-eaters and their hybrids occupied a second performance peak requiring larger peak gape and greater jaw protrusion. A bite performance valley separating scale-eaters from other species may have contributed to their rapid evolution and is consistent with multiple estimates of a multi-peak fitness landscape in the wild. We thus present an efficient deep-learning automated pipeline for kinematic analyses of feeding strikes and a new biomechanical model for understanding the performance and rapid evolution of a rare trophic niche.

Spatiotemporal and Individual Patterns of Domestic Cat (Felis catus) Hunting Behaviour in France

Domestic cats (Felis catus), one of the most popular pets, are widespread worldwide. This medium-sized carnivore has well-known negative effects on biodiversity, but there is still a need to better understand the approximate causes of their predation. Based on a citizen science project, we assessed the role of spatiotemporal (i.e., latitude, longitude, and seasons), climatic (i.e., rainfall), anthropogenic (i.e., human footprint, HFI), and individual (i.e., sex and age) variables on the number of preys returned home by cats in metropolitan France. Over the 5048 cats monitored between 2015 and 2022, prey from 12 different classes (n = 36,568) were returned home: 68% mammals, 21% birds, and 8% squamates. Shrews brought home by cats peaked during summer, while rodents were recorded during summer-autumn. Birds brought home by cats peaked in spring-summer and in autumn, and lizards peaked in spring and in late summer. Lower HFI was associated with more voles and mice brought home, and the opposite trend was observed for lizards and birds. Younger cats were more prone to bring home shrews, birds, and reptiles. Although environmental factors play a minor role in prey brought home by cats, some geographical characteristics of prey species distribution partly explains the hunting behaviour of cats.

Inconsistent Effect of Psychometric-Scale Familiarization on the Relationship Between Ratings of Perceived Exertion and External Load Measures in Elite Youth Soccer Players

OBJECTIVES

To examine the moderating effect of familiarization on the relationship between external load and ratings of perceived exertion (RPEs) in elite youth soccer players.

METHODS

Thirty-five elite male youth soccer players were monitored over a 31-week period. Players had no previous experience using the centiMax scale (arbitrary units [AU]). The final sample included familiarized (blackness test; n = 20) and nonfamiliarized players (n = 15) with the Borg centiMax scale. Players recorded a global RPE and differential RPEs (dRPE) for breathlessness (RPE-B) and leg-muscle exertion (RPE-L) 15 to 30 minutes following training sessions and competitive matches. Separate multivariable-adjusted random-effects generalized additive models with restricted maximum likelihood quantified familiarization versus no-familiarization differences in actual perceived exertion score (in AU) by number of accelerations, decelerations, and high-speed running distance (in meters) as predictor variables, respectively.

RESULTS

Players improved their blackness test score from 39% to 78%. For explorations by number of accelerations, familiarization effects were not practically relevant for the RPE and RPE-B variables. The width and sign of the effects for the RPE-L variable at 30 efforts of 10 AU (95% CI, 4-16 AU) suggested that scores were lower for players who underwent familiarization versus players who did not. Familiarization effects were not practically relevant for any RPE variable irrespective of the number of deceleration efforts and high-speed running distance covered.

CONCLUSION

Improved performance on the blackness test did not have a moderating effect on the relationship between proxy measures of external load and RPEs.

Ambulatory blood pressure as risk factor for long-term kidney function decline in the general population: a distributional regression approach

The results of randomized controlled trials are unclear about the long-term effect of blood pressure (BP) on kidney function assessed as the glomerular filtration rate (GFR) in persons without chronic kidney disease or diabetes. The limited duration of follow-up and use of imprecise methods for assessing BP and GFR are important reasons why this issue has not been settled. Since a long-term randomized trial is unlikely, we investigated the association between 24-h ambulatory BP (ABP) and measured GFR in a cohort study with a median follow-up of 11 years. The Renal Iohexol Clearance Survey (RENIS) cohort is a representative sample of persons aged 50 to 62 years without baseline cardiovascular disease, diabetes, or kidney disease from the general population of Tromsø in northern Norway. ABP was measured at baseline, and iohexol clearance at baseline and twice during follow-up. The study population comprised 1589 persons with 4127 GFR measurements. Baseline ABP or office BP components were not associated with the GFR change rate in multivariable adjusted conventional regression models. In generalized additive models for location, scale, and shape (GAMLSS), higher daytime systolic, diastolic, and mean arterial ABP were associated with a slight shift of the central part of the GFR distribution toward lower GFR and with higher probability of GFR < 60 mL/min/1.73 m2 during follow-up (p < 0.05). The use of a distributional regression method and precise methods for measuring exposure and outcome were necessary to detect an unfavorable association between BP and GFR in this study of the general population.

Citizen science data reveal regional heterogeneity in phenological response to climate in the large milkweed bug, Oncopeltus fasciatus

Regional populations of geographically widespread species may respond to different environmental factors across the species' range, generating divergent effects of climate change on life-history phenology. Using thousands of citizen science observations extracted from iNaturalist and associated with corresponding temperature, precipitation, elevation, and daylength information, we examined the drivers of adult mating and of nymphal phenology, development, and group size for populations of the large milkweed bug, Oncopeltus fasciatus, in different ecoregions. Research-grade iNaturalist images were correctly identified 98.3% of the time and yielded more than 3000 observations of nymphal groups and 1000 observations of mating adults spanning 18 years. Mating phenology showed distinct regional patterns, ranging from year-round mating in California to temporally restricted mating in the Great Lakes Northeastern Coast ecoregion. Relative temperature increases of 1°C for a given daylength expanded the mating season by more than a week in western ecoregions. While increases in relative temperature delayed mating phenology in all ecoregions, greater winter precipitation advanced mating in the California ecoregion. In the eastern ecoregions, nymphal phenology was delayed by increases in summer rainfall but was advanced by relative temperature increases, whereas in western regions, relative temperature increases delayed nymphal phenology. Furthermore, accumulated growing degree days (AGDD) was a poor predictor of developmental progression, as we found a positive but weak correlation between AGDD and age structure only for the Appalachian Southeast North America and the Great Lakes Northern Coast ecoregions. These complex phenological responses of O. fasciatus are just one example of how populations may be differentially susceptible to a diversity of climatic effects; using data across a species' whole distribution is critical for exposing regional variations, especially for species with large, continental-scale ranges. This study demonstrates the potential of photodocumented biodiversity data to aid in the monitoring of life history, host plant-insect interactions, and climate responsiveness.

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.

Differential impact of transfusion guidelines on blood transfusion practices within a health network

Whether clinical practice guidelines have a significant impact on practice is unclear. The effect of guideline recommendations on clinical practice often a lags behind the date of publication. We evaluated by means of a data-driven approach if and when the guidelines on red blood cell transfusions (RBCTs) issued by Swiss Smarter Medicine in 2016 had an impact on RBCTs practice within a hospital network, where awareness of guidelines was promoted mainly among internal medicine specialties. Data on RBCTs performed in a Swiss hospital network from January 2014 to April 2021 were analyzed by hospital site and specialty to assess whether guidelines led to a decrease in inappropriate RBCTs. RBCTs were defined as "inappropriate" if patients had a hemoglobin level ≥ 70 g/L without or ≥ 80 g/L with significant cardiovascular comorbidities. Changes in the rate of inappropriate transfusions were analyzed with an advanced statistical approach that included generalized additive models. Overall prior to March 2017 there were more inappropriate than appropriate RBCTs, but after October 2017 the opposite could be observed. A change-point in the time trend was estimated from transfusion data to occur in the time interval between March and October 2017. This change was mainly driven by practice changes in the medical wards, while no significant change was observed in the critical care, surgical and oncology wards. Change in practice varied by hospital site. In conclusion, our results show that a significant change in the RBCTs practice at the hospital level occurred approximately 18 months after national guidelines were issued.

Risk factors for, and prediction of, exertional heat illness in Thoroughbred racehorses at British racecourses

The development of exertional heat illness (EHI) is a health, welfare and performance concern for racehorses. However, there has been limited multivariable assessment of the possible risk factors for EHI in racehorses, despite such information being vital for regulators to effectively manage the condition. Consequently, this study aimed to identify the risk factors associated with the occurrence of EHI in Thoroughbred racehorses and assess the ability of the risk factor model to predict the occurrence of EHI in racehorses to assist in early identification. Runners at British racecourses recorded in the British Horseracing Authority database between 1st July 2010 and 30th April 2018 were used to model the probability that a horse would present with EHI as a function of a suite of environmental, horse level and race level factors. EHI was reported in 0.1% of runners. Race distance, wet bulb globe temperature, preceding 5-day temperature average, occurrence of a previous EHI incident, going, year and race off time were identified as risk factors for EHI. The model performed better than chance in classifying incidents with a mean area under the receiver operating characteristic curve score of 0.884 (SD = 0.02) but had a large number of false positives. The results provide vital evidence for industry on the need to provide appropriate cool down facilities, identify horses that have repeated EHI incidents for early intervention, and collect new data streams such as on course wet bulb globe temperature measurements. The results are especially relevant as the sport is operating in a changing climate and must mitigate against more extreme and longer spells of hot weather.

The impact of shape and attachment position of biologging devices in Northern Bald Ibises

Background

The impact of biologging devices on the aerodynamics or hydrodynamics of animals is still poorly understood. This stands in marked contrast to the ever more extensive use of such technologies in wild-living animals. Recently, increasing concerns have been raised about the impairing effects of these devices on the animals concerned. In the early days of biotelemetry, attention was focused solely on reducing weight, but now aerodynamic effects are also increasingly being considered. To investigate these effects, we trained Northern Bald Ibises to fly in a wind tunnel in which we measured heart rate and dynamic body acceleration (VeDBA) as proxies for energy expenditure in relation to different logger shapes and wind flow directions.

Results

Our data provide evidence that the position of biologging devices significantly influence the flight distances, and the shape of biologging devices has a considerable effect on heart rate and VeDBA, both of which have been used as proxies for energy expenditure. Unfavorable shape and positioning go beyond merely affecting the effort required during flapping flight. The energetically probably more important effect is that the devices impair the bird's ability to glide or soar and thus force them to perform the energetically much more demanding flapping flight more frequently. This effect was more pronounced in rising air than in horizontal airflow. A complementary study with wild Northern Bald Ibises during spring migration provides evidence that the position of the devices on the bird's back affects the length of the flight stages. Birds carrying the devices on the upper back, fixed by wing-loop harnesses, had significantly shorter flight stages compared to birds with a more caudally positioned device, fixed by leg-loop harnesses.

Conclusion

The attachment of biologging devices on birds affects their performance and behavior and thus may influence their fitness and mortality. Our results show that detrimental effects can be reduced with relatively little effort, in particular through a strictly aerodynamic design of the housing and increased consideration of aerodynamics when attaching the device to the body. In birds, the attachment of biologging devices via leg loops to the lower back is clearly preferable to the common attachment via wing loops on the upper back, even if this affects the efficiency of the solar panels. Nevertheless, the importance of drag reduction may vary between systems, as the benefits of having a biologging devices close to the center of gravity may outweigh the increase in drag that this involves. Overall, more research is required in this field. This is both in the interest of animal welfare and of avoiding biasing the quality of the collected data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40317-023-00322-5.

Adsorptive exchange of coccolith biominerals facilitates viral infection

Marine coccolithophores are globally distributed, unicellular phytoplankton that produce nanopatterned, calcite biominerals (coccoliths). These biominerals are synthesized internally, deposited into an extracellular coccosphere, and routinely released into the external medium, where they profoundly affect the global carbon cycle. The cellular costs and benefits of calcification remain unresolved. Here, we show observational and experimental evidence, supported by biophysical modeling, that free coccoliths are highly adsorptive biominerals that readily interact with cells to form chimeric coccospheres and with viruses to form "viroliths," which facilitate infection. Adsorption to cells is mediated by organic matter associated with the coccolith base plate and varies with biomineral morphology. Biomineral hitchhiking increases host-virus encounters by nearly an order of magnitude and can be the dominant mode of infection under stormy conditions, fundamentally altering how we view biomineral-cell-virus interactions in the environment.

Long-Term Monitoring of Polybrominated Diphenyl Ethers (PBDEs) in Indo-Pacific Humpback Dolphins (Sousa chinensis) from the Pearl River Estuary Reveals High Risks for Calves due to Maternal Exposure

Although many studies have documented the wide occurrence of polybrominated diphenyl ethers (PBDEs) in cetaceans, little evidence exists regarding the detrimental effects of PBDE exposure on calf death rates for free-ranging cetaceans. This study analyzed life-history-associated PBDE bioaccumulation patterns in 128 stranding Indo-Pacific humpback dolphin (Sousa chinensis) samples over an 18-year timespan from the Pearl River Estuary (PRE). In comparison to the records of PBDE levels in cetaceans worldwide, the median levels of PBDEs (median = 10600 ng g^-1 lw, range = 721-50900 ng g^-1 lw) in all samples were the highest to date. One-way analysis of variance (ANOVA) showed that adult males (median = 16100 ng g^-1 lw, range = 4070-50900 ng g^-1 lw) and calves (12000 ng g^-1 lw, range = 1250-35300 ng g^-1 lw) both had the highest levels of PBDEs compared to the rest of the age/sex groups (p < 0.05). Concentrations of PBDEs in noncalves significantly decreased over the studied period, while those in calves had a slightly increasing trend, which may be due to different exposure routes via fish or milk, respectively. A significant and positive relationship was found between annual calf stranding death rates and body-length-adjusted PBDE concentrations in calves (r = 0.62, p < 0.05), suggesting that maternal exposure of calves to elevated levels of PBDEs may have contributed to the high annual stranding death rates of calves in the last two decades.

Seasonal habitat preference and foraging behaviour of post-moult Weddell seals in the western Ross Sea

Weddell seals (Leptonychotes weddellii) are important predators in the Southern Ocean and are among the best-studied pinnipeds on Earth, yet much still needs to be learned about their year-round movements and foraging behaviour. Using biologgers, we tagged 62 post-moult Weddell seals in McMurdo Sound and vicinity between 2010 and 2012. Generalized additive mixed models were used to (i) explain and predict the probability of seal presence and foraging behaviour from eight environmental variables, and (ii) examine foraging behaviour in relation to dive metrics. Foraging probability was highest in winter and lowest in summer, and foraging occurred mostly in the water column or just above the bottom; across all seasons, seals preferentially exploited the shallow banks and deeper troughs of the Ross Sea, the latter providing a pathway for Circumpolar Deep Water to flow onto the shelf. In addition, the probability of Weddell seal occurrence and foraging increased with increasing bathymetric slope and where water depth was typically less than 600 m. Although the probability of occurrence was higher closer to the shelf break, foraging was higher in areas closer to shore and over banks. This study highlights the importance of overwinter foraging for recouping body mass lost during the previous summer.

Distributional regression modeling via generalized additive models for location, scale, and shape: An overview through a data set from learning analytics

The advent of technological developments is allowing to gather large amounts of data in several research fields. Learning analytics (LA)/educational data mining has access to big observational unstructured data captured from educational settings and relies mostly on unsupervised machine learning (ML) algorithms to make sense of such type of data. Generalized additive models for location, scale, and shape (GAMLSS) are a supervised statistical learning framework that allows modeling all the parameters of the distribution of the response variable with respect to the explanatory variables. This article overviews the power and flexibility of GAMLSS in relation to some ML techniques. Also, GAMLSS' capability to be tailored toward causality via causal regularization is briefly commented. This overview is illustrated via a data set from the field of LA. This article is categorized under:Application Areas > Education and LearningAlgorithmic Development > StatisticsTechnologies > Machine Learning.

Functional space expansion driven by transitions between energetically advantageous traits in the deep sea

Climate change is shifting community structure and biodiversity on a global scale, in part due to alterations of chemical and thermal energy availability. These changes may impact ecosystem functioning through their influence on functional diversity. We investigate patterns of functional diversity, functional niches, and functional traits in bivalve communities across the energetic gradient of the deep Atlantic Ocean. We use the functional traits feeding type, tiering, and motility level to define the axes of functional space and the unique combinations of these traits as functional niches. We find that increased energy affords new species, added into functional space through niche expansion rather than niche packing. Underlying this pattern are complex dynamics of gains and losses of individual functional niches, with few adapted to the low- and high-energy extremes, and most occurring at intermediate energy. Adaptive qualities of specific traits are evidenced by those functional niches occurring at energetic extremes. Tradeoffs between these traits within the intermediate energy zone underlie an increased coexistence of functional niches, which in turn drives a unimodal pattern of functional niches and expansion of used functional space. This work suggests that energy-limited communities may be especially vulnerable to continued shifts in food availability through the Anthropocene.

Competition for soil resources forces a trade-off between enhancing tree productivity and understorey species richness in managed beech forests

Traditionally focussed on maximising productivity, forest management increasingly has to consider other functions performed by the forest stands, such as biodiversity conservation. Terrestrial plant communities typically possess a hump-back relationship between biomass productivity and plant species richness. However, there is evidence of a reverse relationship in forests dominated by beech, one of the most competitive and widespread tree species in temperate Europe. To fully explore the tree productivity-species richness relationship, we investigated above- and below-ground drivers of understorey plant species richness. We focussed on managed beech forests growing along an elevation gradient in Central Europe. We found that the lowest understorey plant diversity was under conditions optimal for beech. Tree fine root mass, canopy openness, soil C/N ratio, the interaction between tree fine root mass and stoniness, and stand structural diversity explain the variation of understorey species richness. We show that the competition for soil resources is the main driver of plant species diversity in managed forests; maximising beech growth in optimal conditions may thus come at the expense of understorey plant richness.

Sex Differences in Age-Related Loss of Kidney Function

BACKGROUND

CKD is more prevalent in women, but more men receive kidney replacement therapy for kidney failure. This apparent contradiction is not well understood.

METHODS

We investigated sex differences in the loss of kidney function and whether any sex disparities could be explained by comorbidity or CKD risk factors. In the Renal Iohexol Clearance Survey (RENIS) in northern Europe, we recruited 1837 persons (53% women, aged 50-62 years) representative of the general population and without self-reported diabetes, CKD, or cardiovascular disease. Participants' GFR was measured by plasma iohexol clearance in 2007-2009 (n=1627), 2013-2015 (n=1324), and 2018-2020 (n=1384). At each study visit, healthy persons were defined as having no major chronic diseases or risk factors for CKD. We used generalized additive mixed models to assess age- and sex-specific GFR decline rates.

RESULTS

Women had a lower GFR than men at baseline (mean [SD], 90.0 [14.0] versus 98.0 [13.7] ml/min per 1.73 m2; P<0.001). The mean GFR change rate was -0.96 (95% confidence interval [CI], -0.88 to -1.04) ml/min per 1.73 m2 per year in women and -1.20 (95% confidence interval [CI], -1.12 to -1.28) in men. Although the relationship between age and GFR was very close to linear in women, it was curvilinear in men, with steeper GFR slopes at older ages (nonlinear effect; P<0.001). Healthy persons had a slower GFR decline, but health status did not explain the sex difference in the GFR decline.

CONCLUSION

Among middle-aged and elderly individuals in the general population, decline in the mean GFR in women was slower than in men, independent of health status.

Task-related, intrinsic oscillatory and aperiodic neural activity predict performance in naturalistic team-based training scenarios

Effective teams are essential for optimally functioning societies. However, little is known regarding the neural basis of two or more individuals engaging cooperatively in real-world tasks, such as in operational training environments. In this exploratory study, we recruited forty individuals paired as twenty dyads and recorded dual-EEG at rest and during realistic training scenarios of increasing complexity using virtual simulation systems. We estimated markers of intrinsic brain activity (i.e., individual alpha frequency and aperiodic activity), as well as task-related theta and alpha oscillations. Using nonlinear modelling and a logistic regression machine learning model, we found that resting-state EEG predicts performance and can also reliably differentiate between members within a dyad. Task-related theta and alpha activity during easy training tasks predicted later performance on complex training to a greater extent than prior behaviour. These findings complement laboratory-based research on both oscillatory and aperiodic activity in higher-order cognition and provide evidence that theta and alpha activity play a critical role in complex task performance in team environments.

Air pollution in Delhi, India: It’s status and association with respiratory diseases

The policymakers need research studies indicating the role of different pollutants with morbidity for polluted cities to install a strategic air quality management system. This study critically assessed the air pollution of Delhi for 2016–18 to found out the role of air pollutants in respiratory morbidity under the ICD-10, J00-J99. The critical assessment of Delhi air pollution was done using various approaches. The mean PM_2.5 and PM₁₀ concentrations during the measurement period exceeded both national and international standards by a wide margin. Time series charts indicated the interdependence of PM_2.5 and PM₁₀ and connection with hospital visits due to respiratory diseases. Violin plots showed that daily respiratory disease hospital visits increased during the winter and autumn seasons. The winter season was the worst from the city’s air pollution point of view, as revealed by frequency analyses. The single and multi-pollutant GAM models indicated that short-term exposure to PM₁₀ and SO₂ led to increased hospital visits due to respiratory diseases. Per 10 units increase in concentrations of PM₁₀ brought the highest increase in hospital visits of 0.21% (RR: 1.00, 95% CI: 1.001, 1.002) at lag0-6 days. This study found the robust effect of SO₂ persisted in Delhi from lag0 to lag4 days and lag01 to lag06 days for single and cumulative lag day effects, respectively. While every 10 μg m^-3 increase of SO₂ concentrations on the same day (lag0) led to 32.59% (RR: 1.33, 95% CI: 1.09, 1.61) rise of hospital visits, the cumulative concentration of lag0-1 led to 37.21% (RR: 1.37, 95% CI:1.11, 1.70) rise in hospital visits which further increased to even 83.33% (RR: 1.83, 95% CI:1.35, 2.49) rise at a lag0-6 cumulative concentration in Delhi. The role of SO₂ in inducing respiratory diseases is worrying as India is now the largest anthropogenic SO₂ emitter in the world.

Relative Skeletal Maturity and Performance Test Outcomes in Elite Youth Middle Eastern Soccer Players

PURPOSE

This study aimed to explore the influence of differences in relative skeletal maturity on performance test outcomes in elite youth soccer players from the Middle East.

METHODS

We integrated skeletal age and performance assessments using mixed-longitudinal data available for 199 outfield players (chronological age range, 11.7 to 17.8 yr) enrolled as academy student-athletes (annual screening range, 1 to 5 visits). Skeletal age was determined as per the Tanner-Whitehouse II protocol. Relative maturity was calculated as the difference (∆) between Tanner-Whitehouse II skeletal age minus chronological age. Performance test outcomes of interest were 10-m sprinting, 40-m sprinting, countermovement jump height, and maximal aerobic speed. Separate random-effects generalized additive models quantified differences in performance test outcomes by relative skeletal maturity. Estimated differences were deemed practically relevant based on the location of the confidence interval (95% CI) against minimal detectable change values for each performance test outcome.

RESULTS

For 40-m sprinting, differences of +0.51 s (95% CI, +0.35 to +0.67 s) and +0.62 s (95% CI, +0.45 to +0.78 s) were practically relevant for relative maturity status of ∆ = -1.5 yr versus ∆ = +0.5 and ∆ = +1 yr, respectively. For countermovement jump height, a difference of -8 cm (95% CI, -10 to -5 cm) was practically relevant for ∆ = -1.5 yr versus ∆ = +1 yr relative maturity status comparison. Effects for 10-m sprinting and maximal aerobic speed were unclear.

CONCLUSIONS

Integration of skeletal age and performance assessments indicated that conventional maturity status classification criteria were inconsistent to inform player development processes in our sample. Between-player differences in test performance may depend on a substantial delay in skeletal maturation (∆ ≤ -1.5 yr) and the performance outcome measure.

Past and recent farming degrades aquatic insect genetic diversity

Recent declines in once-common species are triggering concern that an environmental crisis point has been reached. Yet, the lack of long abundance time series data for most species can make it difficult to attribute these changes to anthropogenic causes, and to separate them from normal cycles. Genetic diversity, on the other hand, is sensitive to past and recent environmental changes, and reflects a measure of a populations' potential to adapt to future stressors. Here, we consider whether patterns of genetic diversity among aquatic insects can be linked to historical and recent patterns of land use change. We collated mitochondrial cytochrome c oxidase subunit I (COI) variation for >700 aquatic insect species across the United States, where patterns of agricultural expansion and intensification have been documented since the 1800s. We found that genetic diversity was lowest in regions where cropland was historically (pre-1950) most extensive, suggesting a legacy of past environmental harm. Genetic diversity further declined where cropland has since expanded, even after accounting for climate and sampling effects. Notably though, genetic diversity also appeared to rebound where cropland has diminished. Our study suggests that genetic diversity at the community level can be a powerful tool to infer potential population declines and rebounds over longer time spans than is typically possible with ecological data. For the aquatic insects that we considered, patterns of land use many decades ago appear to have left long-lasting damage to genetic diversity that could threaten evolutionary responses to rapid global change.

Natural and anthropogenic influences on benthic cyanobacteria in streams of the northeastern United States

Benthic cyanobacteria are widespread in streams and rivers and have the potential to release toxins. In large numbers, these microorganisms and their toxins present a risk to human health. Cyanobacterial abundance in stream biofilms is typically related to single or a limited set of environmental factors, mainly light availability, water temperature, and nutrient concentrations. However, these factors may act synergistically with watershed characteristics and other stressors, such as anthropogenic pollutants, to affect cyanobacteria. We investigated the influence of multiple regional and local variables on the abundance of benthic cyanobacterial genera in streams using all subsets generalized additive modeling. We examined watershed factors (topography, geology, and climate) alongside in-stream factors (geomorphology, hydrology, pH, specific conductance, nutrients, organic contaminants, and dissolved metals) from 76 sites along an urban gradient in the northeast United States. Each genus responded to a distinct combination of environmental variables, demonstrating strong intergeneric variation in environmental selection of realized niches. Four of the 7 potentially toxigenic genera that we modeled were positively influenced by water temperature or nutrients. Nonetheless, watershed characteristics, streamflow, and/or other water quality pollutants were equally or more influential for the potentially toxigenic genera. Additionally, the relationships between cyanobacterial abundance and environmental factors varied in shape and direction across many genera. In particular, with increasing concentrations of herbicides, polychlorinated biphenyls, or metals, the abundance of roughly half of the affected genera decreased, while the others increased. These results likely demonstrate novel toxic effects of the pollutants on cyanobacterial genera in the environment, while indicating that unmeasured biotic interactions may lead to positive responses for other genera. Our results emphasize the need to consider variables beyond those that are most frequently measured or implicated (e.g., water temperature and nutrients) to more fully understand the environmental conditions that influence the distributions and abundance of potentially harmful cyanobacteria.

Empirical Evidence for Energy Efficiency Using Intermittent Gliding Flight in Northern Bald Ibises

Birds face exceptionally high energy demands during their flight. One visible feature of some species is alternating between flapping and gliding, which should allow them to save energy. To date, there is no empirical evidence of an energetic benefit to this. To understand the physiology behind the strategy, we equipped hand-raised Northern Bald Ibises (Geronticus eremita) with data loggers during human-guided migration. We monitored the position of the birds, wingbeats, overall dynamic body acceleration (ODBA), and heart rates as a proxy for energy expenditure. The energy expenditure was significantly affected by the length of flapping and gliding bouts. A pronounced decrease in heart rate was measured after already 1 s of gliding. Additionally, the heart rate at flapping bouts up to 30 s increased steadily but stabilized thereafter. The gilding proportion during intermittent flight affected the energy saving compared to continuous flapping. At a gliding proportion of about 20%, we measured a maximum of 11% saving based on heart rate measurement. At higher gliding proportions, the additional energy saving was negligible. Furthermore, as during flight, not all energy is used for mechanical work, we found a greater decrease rate of ODBA at different gliding proportions compared to heart rate. Nevertheless, the combination of the two methods is essential to determine birds’ movement and energy expenditure. This study provides empirical evidence that intermittent flight is energetically beneficial and can reduce the high costs of flights.

Oscillatory and Aperiodic Neural Activity Jointly Predict Language Learning

Memory formation involves the synchronous firing of neurons in task-relevant networks, with recent models postulating that a decrease in low-frequency oscillatory activity underlies successful memory encoding and retrieval. However, to date, this relationship has been investigated primarily with face and image stimuli; considerably less is known about the oscillatory correlates of complex rule learning, as in language. Furthermore, recent work has shown that nonoscillatory (1/ƒ) activity is functionally relevant to cognition, yet its interaction with oscillatory activity during complex rule learning remains unknown. Using spectral decomposition and power-law exponent estimation of human EEG data (17 females, 18 males), we show for the first time that 1/ƒ and oscillatory activity jointly influence the learning of word order rules of a miniature artificial language system. Flexible word-order rules were associated with a steeper 1/ƒ slope, whereas fixed word-order rules were associated with a shallower slope. We also show that increased theta and alpha power predicts fixed relative to flexible word-order rule learning and behavioral performance. Together, these results suggest that 1/ƒ activity plays an important role in higher-order cognition, including language processing, and that grammar learning is modulated by different word-order permutations, which manifest in distinct oscillatory profiles.

Blubber Cortisol-Based Approach to Explore the Endocrine Responses of Indo-Pacific Humpback Dolphins (Sousa chinensis) to Diet Shifts and Contaminant Exposure

The detrimental effects of contaminant exposure and changes in the availability of food resources are still of concern for Indo-Pacific humpback dolphins (Sousa chinensis) of the Pearl River Estuary (PRE). Here, we validated and applied a blubber cortisol biomarker approach to assess the physiological responses of PRE dolphins to various pollutants and diet changes during 2008-2018 (n = 70). For calves, generalized additive models (GAMs) revealed that cortisol levels varied significantly by month and were positively correlated with the body length, owing to significant maternal transfer of hormones. The significantly positive correlation between length-adjusted cortisol levels in calf and the annual calf mortality ratios suggested that during years of high calf mortality, these animals were highly stressed before they die. For noncalves, blubber cortisol levels in diseased animals were significantly higher than those in "healthy" ones. Chromium (Cr) and dichlorodiphenyltrichloroethanes displayed a significant and positive relationship with blubber cortisol levels, suggesting that contaminant-mediated endocrine disruption effects may have occurred in noncalves. The GAMs indicated a decreasing trend of noncalf's blubber cortisol levels over an 11-year span, which can be explained by their declining contaminant accumulation levels due to a significant dietary shift from eating highly contaminated fishes to less polluted ones.

Exploration of PM mass, source, and component-related factors that might explain heterogeneity in daily PM2.5-mortality associations across the United States

Multi-city epidemiologic studies examining short-term (daily) differences in fine particulate matter (PM2.5) provide evidence of substantial spatial heterogeneity in city-specific mortality risk estimates across the United States. Because PM2.5 is a mixture of particles, both directly emitted from sources or formed through atmospheric reactions, some of this heterogeneity may be due to regional variations in PM2.5 toxicity. Using inverse variance weighted linear regression, we examined change in percent change in mortality in association with 24 "exposure" determinants representing three basic groupings based on potential explanations for differences in PM toxicity - size, source, and composition. Percent changes in mortality for the PM2.5-mortality association for 313 core-based statistical areas and their metropolitan divisions over 1999-2005 were used as the outcome. Several determinants were identified as potential contributors to heterogeneity: all mass fraction determinants, vehicle miles traveled (VMT) for diesel total, VMT gas per capita, PM2.5 ammonium, PM2.5 nitrate, and PM2.5 sulfate. In multivariable models, only daily correlation of PM2.5 with PM10 and long-term average PM2.5 mass concentration were retained, explaining approximately 10% of total variability. The results of this analysis contribute to the growing body of literature specifically focusing on assessing the underlying basis of the observed spatial heterogeneity in PM2.5-mortality effect estimates, continuing to demonstrate that this heterogeneity is multifactorial and not attributable to a single aspect of PM.

A doubling of stony coral cover on shallow forereefs at Carrie Bow Cay, Belize from 2014 to 2019

To better understand the decline of one of earth’s most biodiverse habitats, coral reefs, many survey programs employ regular photographs of the benthos. An emerging challenge is the time required to annotate the large volume of digital imagery generated by these surveys. Here, we leverage existing machine-learning tools (CoralNet) and develop new fit-to-purpose programs to process and score benthic photoquadrats using five years of data from the Smithsonian MarineGEO Network’s biodiversity monitoring program at Carrie Bow Cay, Belize. Our analysis shows that scleractinian coral cover on forereef sites (at depths of 3–10 m) along our surveyed transects increased significantly from 6 to 13% during this period. More modest changes in macroalgae, turf algae, and sponge cover were also observed. Community-wide analysis confirmed a significant shift in benthic structure, and follow-up in situ surveys of coral demographics in 2019 revealed that the emerging coral communities are dominated by fast-recruiting and growing coral species belonging to the genera Agaricia and Porites. While the positive trajectory reported here is promising, Belizean reefs face persistent challenges related to overfishing and climate change. Open-source computational toolkits offer promise for increasing the efficiency of reef monitoring, and therefore our ability to assess the future of coral reefs in the face of rapid environmental change.

Sportive lemurs elevate their metabolic rate during challenging seasons and do not enter regular heterothermy

Animals experience seasonal changes of environmental and ecological conditions in most habitats. Fluctuations in ambient temperature have a strong influence on thermoregulation, particularly on small endothermic mammals. However, different mammalian species cope differently with these changes. Understanding the physiological responses of organisms to different seasons and analysing the mechanisms that account for intra- and inter-specific differences and the ecological consequences of these variations is important to predict species responses to climatic changes. Consequences of climatic changes will be most pronounced in climatically already challenging habitats, such as the dry regions of western Madagascar. We aimed to identify the seasonal responses and adaptive possibilities in energy budgeting of Lepilemur edwardsi, a small primate of this habitat, by measuring metabolic rate (MR; open-flow respiratory) and skin temperature in the field during different seasons. Resting metabolism was generally low, but our study did not detect any signs of regular heterothermic episodes, despite the fact that these are known in other sympatrically living lemurs with a similar lifestyle. Surprisingly, L. edwardsi responded by elevating its resting MR in the poor-resourced dry season, compared to the better-resourced wet season, presumably to master detoxification of their increasingly toxic diet. As body mass decreased over this time, this strategy is obviously not energetically balanced on the long term. This is cause for concern, as it suggests that L. edwardsi has a very small leeway to adjust to changing conditions as experienced due to climate change, as dry season are expected to become longer and hotter, straining water budgets and food quality even more. Moreover, our findings highlight the importance of studying physiological parameters directly in the field and under differing climatic conditions.

Species and Phenotypic Distribution Models Reveal Population Differentiation in Ethiopian Indigenous Chickens

Smallholder poultry production dominated by indigenous chickens is an important source of livelihoods for most rural households in Ethiopia. The long history of domestication and the presence of diverse agroecologies in Ethiopia create unique opportunities to study the effect of environmental selective pressures. Species distribution models (SDMs) and Phenotypic distribution models (PDMs) can be applied to investigate the relationship between environmental variation and phenotypic differentiation in wild animals and domestic populations. In the present study we used SDMs and PDMs to detect environmental variables related with habitat suitability and phenotypic differentiation among nondescript Ethiopian indigenous chicken populations. 34 environmental variables (climatic, soil, and vegetation) and 19 quantitative traits were analyzed for 513 adult chickens from 26 populations. To have high variation in the dataset for phenotypic and ecological parameters, animals were sampled from four spatial gradients (each represented by six to seven populations), located in different climatic zones and geographies. Three different ecotypes are proposed based on correlation test between habitat suitability maps and phenotypic clustering of sample populations. These specific ecotypes show phenotypic differentiation, likely in response to environmental selective pressures. Nine environmental variables with the highest contribution to habitat suitability are identified. The relationship between quantitative traits and a few of the environmental variables associated with habitat suitability is non-linear. Our results highlight the benefits of integrating species and phenotypic distribution modeling approaches in characterization of livestock populations, delineation of suitable habitats for specific breeds, and understanding of the relationship between ecological variables and quantitative traits, and underlying evolutionary processes.

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.

Be still my heart: Cardiac regulation as a mode of uncertainty reduction

Decreased heart rate (HR) and variability (HRV) are well-established correlates of attention; however, the functional significance of these dynamics remains unclear. Here, we investigate whether attention-related cardiac modulation is sensitive to different varieties of uncertainty. Thirty-nine adults performed a binocular rivalry-replay task in which changes in visual perception were driven either internally (in response to constant, conflicting stimuli; rivalry) or externally (in response to physically alternating stimuli; replay). Tonic HR and high-frequency HRV linearly decreased as participants progressed from resting-state baseline (minimal visual uncertainty) through replay (temporal uncertainty) to rivalry (temporal uncertainty and ambiguity). Time-resolved frequency estimates revealed that cardiac deceleration was sustained throughout the trial period and modulated by ambiguity, novelty, and switch rate. These findings suggest cardiac regulation during active attention may play an instrumental role in uncertainty reduction.

Diet Shifts Explain Temporal Trends of Pollutant Levels in Indo-Pacific Humpback Dolphins (Sousa chinensis) from the Pearl River Estuary, China

We examined spatiotemporal trends of diet compositions and their relationship with pollutant accumulation levels in 46 weaning Indo-Pacific humpback dolphins (n = 46) from 2004 to 2017 in the Pearl River Estuary (PRE) based on blubber fatty acid signatures using quantitative fatty acid signature analysis in R (QFASAR). Fifty-one potential prey species were tested, among which 13 had a mean relative proportion greater than 1% in dolphin diets. Bombay duck was the predominant prey species, followed by Dussumier's thryssa and mullet, whereas other prey species were present at considerably reduced proportions in diets. The proportion of larger fishes (Bombay duck and mullet) in the diet has exhibited a significant decreasing trend in recent years, whereas the smaller fish (Dussumier's thryssa) steadily increased over the whole period, possibly due to the severe impacts of climate change and other human stressors on large fishes in estuarine waters. The proportions of Bombay duck in the diet were significantly and positively correlated with hepatic Cr levels in dolphins, whereas the temporal change in Bombay duck consumption mirrored that in the hepatic levels of several per- and polyfluoroalkyl substances, because Bombay duck was the most contaminated species among all the prey fishes.

Avian responses to extreme weather across functional traits and temporal scales

Extreme weather, including heat waves, droughts, and high rainfall, is becoming more common and affecting a diversity of species and taxa. However, researchers lack a framework that can anticipate how diverse species will respond to weather extremes spanning weeks to months. Here we used high-resolution occurrence data from eBird, a global citizen science initiative, and dynamic species distribution models to examine how 109 North American bird species ranging in migration distance, diet, body size, habitat preference, and prevalence (commonness) respond to extreme heat, drought, and rainfall across a wide range of temporal scales. Across species, temperature influenced species' distributions more than precipitation at weekly and monthly scales, while precipitation was more important at seasonal scales. Phylogenetically controlled multivariate models revealed that migration distance was the most important factor mediating responses to extremely hot or dry weeks; residents and short-distance migrants occurred less often following extreme heat. At monthly or seasonal scales, less common birds experienced decreases in occurrence following drought-like conditions, while widespread species were unaffected. Spatial predictions demonstrated variation in responses to extreme weather across species' ranges, with predicted decreases in occurrence up to 40% in parts of ranges. Our results highlight that extreme weather has variable and potentially strong implications for birds at different time scales, but these responses are mediated by life-history characteristics. As weather once considered extreme occurs more frequently, researchers and managers require a better understanding of how diverse species respond to extreme conditions.

GFR in Healthy Aging: an Individual Participant Data Meta-Analysis of Iohexol Clearance in European Population-Based Cohorts

BACKGROUND

Population mean GFR is lower in older age, but it is unknown whether healthy aging is associated with preserved rather than lower GFR in some individuals.

METHODS

We investigated the cross-sectional association between measured GFR, age, and health in persons aged 50-97 years in the general population through a meta-analysis of iohexol clearance measurements in three large European population-based cohorts. We defined a healthy person as having no major chronic disease or risk factors for CKD and all others as unhealthy. We used a generalized additive model to study GFR distribution by age according to health status.

RESULTS

There were 935 (22%) GFR measurements in persons who were healthy and 3274 (78%) in persons who were unhealthy. The mean GFR was lower in older age by -0.72 ml/min per 1.73 m² per year (95% confidence interval [95% CI], -0.96 to -0.48) for men who were healthy versus -1.03 ml/min per 1.73 m² per year (95% CI, -1.25 to -0.80) for men who were unhealthy, and by -0.92 ml/min per 1.73 m² per year (95% CI, -1.14 to -0.70) for women who were healthy versus -1.22 ml/min per 1.73 m² per year (95% CI, -1.43 to -1.02) for women who were unhealthy. For healthy and unhealthy people of both sexes, both the 97.5th and 2.5th GFR percentiles exhibited a negative linear association with age.

CONCLUSIONS

Healthy aging is associated with a higher mean GFR compared with unhealthy aging. However, both the mean and 97.5 percentiles of the GFR distribution are lower in older persons who are healthy than in middle-aged persons who are healthy. This suggests that healthy aging is not associated with preserved GFR in old age.

Hot water pretreatment of lignocellulosic biomass: Modeling the effects of temperature, enzyme and biomass loadings on sugar yield

Experimental conditions of liquid hot water (LHW) pretreatment were tested for two dedicated energy crops, Napiergrass (Pennisetum purpureum) and Energycane (Saccharum officinarum × Saccharum robustum). Both crops showed differential resistance to temperature during pretreatment and differences in response to biomass and enzyme loadings during subsequent enzymatic hydrolysis. Sugar response surfaces, for both glucose release per g pretreated biomass and as percent yield of glucose present in the initial biomass, were estimated using a General Additive Model (GAM) in R to compare non-linear sugar release as temperature, and biomass and enzyme loadings were manipulated. Compared to Napiergrass, more structural glucose is estimated to be recovered from Energycane per g of pretreated biomass under relatively less harsh pretreatment conditions, however, Napiergrass had the highest measured glucose yield. Sugar degradation products (furfural and hydroxymethylfurfural), pH, and biomass recovery differed significantly between crops across pretreatment temperatures, which could adversely affect downstream biochemical processes.

Niche separation within aerobic methanotrophic bacteria across lakes and its link to methane oxidation rates

Lake methane (CH₄ ) emissions are largely controlled by aerobic methane-oxidizing bacteria (MOB) which mostly belong to the classes Alpha- and Gammaproteobacteria (Alpha- and Gamma-MOB). Despite the known metabolic and ecological differences between the two MOB groups, their main environmental drivers and their relative contribution to CH₄ oxidation rates across lakes remain unknown. Here, we quantified the two MOB groups through CARD-FISH along the water column of six temperate lakes and during incubations in which we measured ambient CH₄ oxidation rates. We found a clear niche separation of Alpha- and Gamma-MOB across lake water columns, which is mostly driven by oxygen concentration. Gamma-MOB appears to dominate methanotrophy throughout the water column, but Alpha-MOB may also be an important player particularly in well-oxygenated bottom waters. The inclusion of Gamma-MOB cell abundance improved environmental models of CH₄ oxidation rate, explaining part of the variation that could not be explained by environmental factors alone. Altogether, our results show that MOB composition is linked to CH₄ oxidation rates in lakes and that information on the MOB community can help predict CH₄ oxidation rates and thus emissions from lakes.