Decoupling of bird migration from the changing phenology of spring green-up.

The green-up of vegetation in spring brings a pulse of food resources that many animals track during migration. However, green-up phenology is changing with climate change, posing an immense challenge for species that time their migrations to coincide with these resource pulses. We evaluated changes in green-up phenology from 2002 to 2021 in relation to the migrations of 150 Western-Hemisphere bird species using eBird citizen science data. We found that green-up phenology has changed within bird migration routes, and yet the migrations of most species align more closely with long-term averages of green-up than with current conditions. Changing green-up strongly influenced phenological mismatches, especially for longer-distance migrants. These results reveal that bird migration may have limited flexibility to adjust to changing vegetation phenology and emphasize the mounting challenge migratory animals face in following en route resources in a changing climate.

Climate change causes declines and greater extremes in wetland inundation in a region important for wetland birds.

Wetland ecosystems are vital for maintaining global biodiversity, as they provide important stopover sites for many species of migrating wetland-associated birds. However, because weather determines their hydrologic cycles, wetlands are highly vulnerable to effects of climate change. Although changes in temperature and precipitation resulting from climate change are expected to reduce inundation of wetlands, few efforts have been made to quantify how these changes will influence the availability of stopover sites for migratory wetland birds. Additionally, few studies have evaluated how climate change will influence interannual variability or the frequency of extremes in wetland availability. For spring and fall bird migration in seven ecoregions in the south-central Great Plains of North America, we developed predictive models associating abundance of inundated wetlands with a suite of weather and land cover variables. We then used these models to generate predictions of wetland inundation at the end of the century (2069-2099) under future climate change scenarios. Climate models predicted the average number of inundated wetlands will likely decline during both spring and fall migration periods, with declines being greatest in the eastern ecoregions of the southern Great Plains. However, the magnitude of predicted declines varied considerably across climate models and ecoregions, with uncertainty among climate models being greatest in the High Plains ecoregion. Most ecoregions also were predicted to experience more-frequent extremely dry years (i.e., years with extremely low wetland abundances), but the projected change in interannual variability of wetland inundation was relatively small and varied across ecoregions and seasons. Because the south-central Great Plains represents an important link along the migratory routes of many wetland-dependent avian species, future declines in wetland inundation and more frequent periods of only a few wetlands being inundated will result in an uncertain future for migratory birds as they experience reduced availability of wetland stopover habitat across their migration pathways.

Avelumab Maintenance Therapy for Advanced or Metastatic Urothelial Carcinoma.

BACKGROUND: Platinum-based chemotherapy is standard-of-care first-line treatment for advanced urothelial carcinoma. However, progression-free survival and overall survival are limited by chemotherapy resistance. METHODS: In a phase 3 trial, we randomly assigned patients with unresectable locally advanced or metastatic urothelial cancer who did not have disease progression with first-line chemotherapy (four to six cycles of gemcitabine plus cisplatin or carboplatin) to receive best supportive care with or without maintenance avelumab. The primary end point was overall survival, assessed among all patients who underwent randomization (overall population) and among those with tumors positive for programmed cell death ligand 1 (PD-L1). Secondary end points included progression-free survival and safety. RESULTS: Among all 700 patients who underwent randomization, the addition of maintenance avelumab to best supportive care significantly prolonged overall survival as compared with best supportive care alone (control). Overall survival at 1 year was 71.3% in the avelumab group and 58.4% in the control group (median overall survival, 21.4 months vs. 14.3 months; hazard ratio for death, 0.69; 95% confidence interval [CI], 0.56 to 0.86; P = 0.001). Avelumab also significantly prolonged overall survival in the PD-L1-positive population; overall survival at 1 year was 79.1% in the avelumab group and 60.4% in the control group (hazard ratio, 0.56; 95% CI, 0.40 to 0.79; P<0.001). The median progression-free survival was 3.7 months in the avelumab group and 2.0 months in the control group in the overall population (hazard ratio for disease progression or death, 0.62; 95% CI, 0.52 to 0.75) and 5.7 months and 2.1 months, respectively, in the PD-L1-positive population (hazard ratio, 0.56; 95% CI, 0.43 to 0.73). The incidence of adverse events from any cause was 98.0% in the avelumab group and 77.7% in the control group; the incidence of adverse events of grade 3 or higher was 47.4% and 25.2%, respectively. CONCLUSIONS: Maintenance avelumab plus best supportive care significantly prolonged overall survival, as compared with best supportive care alone, among patients with urothelial cancer who had disease that had not progressed with first-line chemotherapy. (Funded by Pfizer and Merck [Darmstadt, Germany]; JAVELIN Bladder 100 ClinicalTrials.gov number, NCT02603432.).

Climate Change and Wetlands in the Southern Great Plains: How Are Managers Dealing with an Uncertain Future?

Little guidance is available to assist wetland managers in developing climate adaptation plans. To facilitate development of recommendations for adaptation strategies, it is essential to first determine if or how wetland managers are addressing these challenges. We used an online survey to solicit feedback from wetland managers and biologists in the Southern Great Plains of North America to gain information on perceptions of wetland managers regarding climate change; assess how the effects of climate change are being addressed through management; and identify barriers to implementing climate change adaptation. The majority of wetland managers (63%) agreed they are currently experiencing effects of climate change in wetlands, and most respondents (76%) reported that changes in the timing of water availability throughout the year was the most likely impact. Managers reported using a diversity of approaches in managing for changing precipitation, with management of native and invasive plant species being the two most common practices. Lack of funding and personnel were the most commonly identified factors limiting manager's response to changing precipitation patterns. In addition, >50% of managers indicated uncertainty about the effects of climate change on wetlands as a barrier to management, which may relate to limited access to peer-reviewed science. While most of the management practices reported were short-term measures and may not reflect long-term adaptation for climate change, the fact that many managers are considering climate change in their management suggests that there is considerable opportunities to continue developing capacity for climate change adaptation in the region.

Why did the chicken not cross the road? Anthropogenic development influences the movement of a grassland bird.

Movement and selection are inherently linked behaviors that form the foundation of a species' space-use patterns. Anthropogenic development in natural ecosystems can result in a variety of behavioral responses that can involve changes in either movement (speed or direction of travel) or selection (resources used), which in turn may cause population-level consequences including loss of landscape connectivity. Understanding how a species alters these different behaviors in response to human activity is essential for effective conservation. In this study, we investigated the effects of anthropogenic development such as roads, power lines and oil wells on the greater prairie-chicken (Tympanuchus cupido) movement and selection behaviors in the post-nesting and non-breeding season. Our first objective was to assess using integrated step selection analysis (iSSA) if greater prairie-chickens altered their movement behaviors or their selection patterns when encountering oil wells, power lines, or roads. Our second objective was to determine whether prairie-chickens avoided crossing linear features such as roads or power lines by comparing the number of crossing events in greater prairie-chicken movement tracks to the number of movements that crossed these features in simulated movement tracks. Based on the iSSA analysis, we found that greater prairie-chickens avoided oil wells, power lines, and roads in both seasons, and altered their rate of movement when near anthropogenic structures. However, changes in speed varied by season, with prairie-chickens increasing their movement rates in the post-nesting season when near to development and decreasing movement rates in the non-breeding season. Furthermore, prairie-chickens crossed roads and power lines at much lower rates than expected. These changes in behavior can result in habitat loss for greater prairie-chickens, as well as the potential loss of landscape connectivity. By considering both movement and selection, we were able to develop an ecological understanding of how increasing human activity may influence the space use of this species of conservation concern. Furthermore, this research provides insight into the decision-making processes by animals when they encounter anthropogenic development.

Role of the thermal environment in scaled quail (Callipepla squamata) nest site selection and survival.

Temperature is increasingly recognized as an important component of wildlife habitat. Temperature is particularly important for avian nest sites, where extreme temperatures can influence adult behavior, embryonic development, and survival. For species inhabiting arid and semiarid climates, such as the scaled quail (Callipepla squamata), frequent exposure to extreme temperatures may increase the importance of the nest microclimate. Limited data suggest that scaled quail respond to temperature when selecting nest sites, and they are also known to respond to the presence of surface water and shrub cover on the landscape, two resources which may mitigate thermal stress. To better understand the role of temperature in nest site selection and survival, and to evaluate how other landscape resources may benefit nesting quail, we investigated nest site characteristics of scaled quail in southeastern New Mexico, USA. During the breeding seasons of 2018 and 2019 we located nests, monitored nest fate, and recorded thermal and vegetation characteristics at three spatial scales: the nest bowl, the nest microsite (area within 10 m of the nest bowl), and the landscape. We found that nest bowls moderated temperature relative to both the surrounding microsite and the broader landscape, remaining almost 5 °C cooler on average than the surrounding microsite at mid-day. Nest bowls also had taller, greater cover of vegetation compared to both the surrounding microsites and the landscape. Despite apparent selection for cooler temperatures and taller vegetation, these characteristics demonstrated a weak relationship with nest survival. Rather, nest survival was positively influenced by proximity to surface water and honey mesquite (Prosopis glandulosa), with survival decreasing with increasing distance from these features. Although the mechanism for this relationship is unclear, our results support the importance of temperature for nest site selection of ground-nesting birds in semiarid landscapes, and suggest further exploration of landscape-level sources of thermal mitigation.

Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data.

BACKGROUND: The ability to confidently predict health outcomes from gene expression would catalyze a revolution in molecular diagnostics. Yet, the goal of developing actionable, robust, and reproducible predictive signatures of phenotypes such as clinical outcome has not been attained in almost any disease area. Here, we report a comprehensive analysis spanning prediction tasks from ulcerative colitis, atopic dermatitis, diabetes, to many cancer subtypes for a total of 24 binary and multiclass prediction problems and 26 survival analysis tasks. We systematically investigate the influence of gene subsets, normalization methods and prediction algorithms. Crucially, we also explore the novel use of deep representation learning methods on large transcriptomics compendia, such as GTEx and TCGA, to boost the performance of state-of-the-art methods. The resources and findings in this work should serve as both an up-to-date reference on attainable performance, and as a benchmarking resource for further research. RESULTS: Approaches that combine large numbers of genes outperformed single gene methods consistently and with a significant margin, but neither unsupervised nor semi-supervised representation learning techniques yielded consistent improvements in out-of-sample performance across datasets. Our findings suggest that using l2-regularized regression methods applied to centered log-ratio transformed transcript abundances provide the best predictive analyses overall. CONCLUSIONS: Transcriptomics-based phenotype prediction benefits from proper normalization techniques and state-of-the-art regularized regression approaches. In our view, breakthrough performance is likely contingent on factors which are independent of normalization and general modeling techniques; these factors might include reduction of systematic errors in sequencing data, incorporation of other data types such as single-cell sequencing and proteomics, and improved use of prior knowledge.

Species-specific and temporal scale-dependent responses of birds to drought.

Global climate change is increasing the frequency and intensity of weather extremes, including severe droughts in many regions. Drought can impact organisms by inhibiting reproduction, reducing survival and abundance, and forcing range shifts. For birds, considering temporal scale by averaging drought-related variables over different time lengths (i.e., temporal grains) captures different hydrologic attributes which may uniquely influence food supplies, vegetation greenness/structure, and other factors affecting populations. However, studies examining drought impacts on birds often assess a single temporal grain without considering that different species have different life histories that likely determine the temporal grain of their drought response. Furthermore, while drought is known to influence bird abundance and drive between-year range shifts, less understood is whether it causes within-range changes in species distributions. Our objectives were to (a) determine which temporal grain of drought (if any) is most related to bird presence/absence and whether this response is species specific; and (b) assess whether drought alters bird distributions by quantifying probability of local colonization and extinction as a function of drought intensity. We used North American Breeding Bird Survey data collected over 16 years, generalized linear mixed models, and dynamic occupancy models to meet these objectives. Different bird species responded to drought at different temporal grains, with most showing the strongest signal at annual or near-annual grains. For all drought-responsive species, increased drought intensity at any temporal grain always correlated with decreased occupancy. Additionally, colonization/extinction analyses indicated that one species, the dickcissel (Spiza americana), is more likely to colonize novel areas within the southern/core portion of its range during drought. Considering drought at different temporal grains, along with hydrologic attributes captured by each grain, may better reveal mechanisms behind drought impacts on birds and other organisms, and therefore improve understanding of how global climate change impacts species and the landscapes they inhabit.

Thermal refuge affects space use and movement of a large-bodied galliform.

Temperature affects every organism on Earth and has been argued to be one of the most critical factors influencing organisms' ecology and evolution. Most organisms are susceptible to landscape temperature ranges that exceed their thermal tolerance. As a result, the distribution of landscape features that mitigate thermal extremes can affect movement and space use of organisms. Using Rio Grande wild turkey (Meleagris gallopavo intermedia) as a model species, we measured black bulb temperature throughout the diurnal period and identified vegetation characteristics at wild turkey locations and random landscape locations. We observed that the thermal landscape was highly heterogeneous with temperature varying up to 52 °C at a given ambient temperature. Vegetation type strongly influenced temperature across space during daily peak heating, with taller vegetation types (woody vegetation >2 m) having mean temperatures up to 8.95 °C cooler than the remainder of the landscape. However, these cooler vegetation types were uncommon, only accounting for 8.2% of the landscape. Despite the rarity of tall woody cover, wild turkey showed strong selection for this vegetation type particularly during peak daily heating with 74.9% of locations within 18 m of tree cover. Not only did wild turkey alter space use across time relative to temperature variation, but they also altered movement. We found that on the hottest days (≥35 °C), wild turkeys decreased movement by three fold during peak heating, while movement on cooler days (<30 °C) was uniform. Collectively, our data provide evidence that space use and movement for large avian species can be influenced by the thermal environment, and that the thermal environment is an important component of habitat for a species.

Avian parental behavior and nest success influenced by temperature fluctuations.

Behavioral adjustments and parental decisions during reproduction can influence the thermal environment at nests, yet our understanding into how environmental factors (i.e., temperature and precipitation) constrain an adult's ability to balance self-maintenance and incubation demands is limited. To expand our understanding of how species respond to environmental factors, we investigated the reproductive ecology of two ground-nesting species (northern bobwhite [Colinus virginianus] and scaled quail [Callipepla squamata]) in a region (i.e., the Southern Great Plains) prone to thermal variability (i.e., extreme hot and cold temperatures). Specifically, our objective was to examine how temperature and precipitation directly influenced behavioral adjustments (i.e., off-bout duration, frequency, and nest attentiveness) and parental decisions (i.e., nest site selection), and indirectly influenced nest fate. Overall, we found that parents chose to nest in sites that were significantly cooler in temperature than randomly selected sites, and parents further altered the thermal environment experienced by embryos through incubation behavior. Daily precipitation and average ambient temperature and/or their interaction best predicted incubation behaviors, yet each species differed in the timing (i.e., morning vs. evening), frequency, and duration of off-bouts. Furthermore, successful nests were associated with cooler nest site temperatures for bobwhite and warmer nest site temperatures for scaled quail. Our finding of relatively stable (35.5 °C) incubation temperature for developing embryos of both species suggests that ground-nesting birds are able to regulate microclimate through behavioral adjustments and parental decisions even under extreme temperature fluctuations. Nevertheless, the ability for a ground-nesting species to effectively modify behavioral adjustments and decisions may be altered during long periods of enhanced physiological and environmental stress.

Extreme climatic events constrain space use and survival of a ground-nesting bird.

Two fundamental issues in ecology are understanding what influences the distribution and abundance of organisms through space and time. While it is well established that broad-scale patterns of abiotic and biotic conditions affect organisms' distributions and population fluctuations, discrete events may be important drivers of space use, survival, and persistence. These discrete extreme climatic events can constrain populations and space use at fine scales beyond that which is typically measured in ecological studies. Recently, a growing body of literature has identified thermal stress as a potential mechanism in determining space use and survival. We sought to determine how ambient temperature at fine temporal scales affected survival and space use for a ground-nesting quail species (Colinus virginianus; northern bobwhite). We modeled space use across an ambient temperature gradient (ranging from -20 to 38 °C) through a maxent algorithm. We also used Andersen-Gill proportional hazard models to assess the influence of ambient temperature-related variables on survival through time. Estimated available useable space ranged from 18.6% to 57.1% of the landscape depending on ambient temperature. The lowest and highest ambient temperature categories (<-15 °C and >35 °C, respectively) were associated with the least amount of estimated useable space (18.6% and 24.6%, respectively). Range overlap analysis indicated dissimilarity in areas where Colinus virginianus were restricted during times of thermal extremes (range overlap = 0.38). This suggests that habitat under a given condition is not necessarily a habitat under alternative conditions. Further, we found survival was most influenced by weekly minimum ambient temperatures. Our results demonstrate that ecological constraints can occur along a thermal gradient and that understanding the effects of these discrete events and how they change over time may be more important to conservation of organisms than are average and broad-scale conditions as typically measured in ecological studies.

Reproductive plasticity and landscape heterogeneity benefit a ground-nesting bird in a fire-prone ecosystem.

Disturbance is critical for the conservation of rangeland ecosystems worldwide and many of these systems are fire dependent. Although it is well established that restoring fire as an ecological process can lead to increased biodiversity in grasslands and shrublands, the underlying mechanisms driving community patterns are poorly understood for fauna in fire-prone landscapes. Much of this uncertainty stems from the paucity of studies that examine the effects of fire at scales relevant to organism life histories. We assessed the response of a non-migratory ground-dwelling bird to disturbance (i.e., prescribed fire) and environmental stochasticity over the course of a 4-yr period, which spanned years of historic drought and record rainfall. Specifically, we investigated the nesting ecology of Northern Bobwhite (Colinus virginianus; hereafter Bobwhite) to illuminate possible avenues by which individuals respond to dynamic landscape patterns during a critical reproductive stage (i.e., nesting) in a mixed-grass shrubland in western Oklahoma, USA. We found that Bobwhites exhibited extreme plasticity in nest substrate use among time since fire categories (TSF) and subsequently maintained high nest survival (e.g., 57-70%). Bobwhites were opportunistic in nest substrate use among TSF categories (i.e., 72% of nest sites in shrubs in 0-12 months post fire compared to 71% in herbaceous vegetation in >36 months post fire), yet nesting decisions were first filtered by similar structural components (i.e., vertical and horizontal cover) within the vicinity of nest sites regardless of TSF category. Despite being a non-migratory and comparatively less mobile ground-nesting bird species, Bobwhites adjusted to dynamic vegetation mosaics on a fire-prone landscape under stochastic climatic conditions that culminated in stable and high nest survival. Broadly, our findings provide a unique depiction of organism response strategies to fire at scales relevant to a critical life-stage, a topic that has been previously understudied and poorly understood. We also demonstrate how doing so can better inform conservation practices aimed at restoring fire regimes on grassland and shrubland landscapes.

Restoring fire to grasslands is critical for migrating shorebird populations.

Fire is a disturbance process that maintains the structure and function of grassland ecosystems while sustaining grassland biodiversity. Conversion of grasslands to other land uses coupled with altered disturbance regimes has greatly diminished the habitat available to many grassland-dependent species. These changes have been linked to declines in breeding bird populations, but may also be critical for migrating bird populations such as those shorebird species that depend on mesic grasslands during migration. We examined migratory shorebird use of burned grasslands in the southern Great Plains of North America using DISTANCE sampling to estimate and compare bird densities across recently burned and not recently burned landscapes (1-5 yr post fire). We conducted two surveys per week for 8-10 weeks along a 54-km route starting at the end of March and concluding in mid-May during 2014-2015. We encountered 2,509 total shorebirds in recently burned areas compared to 130 individuals in areas that were unburned. Fire was a major attractant for our three focal species with American Golden-plover (Pluvialis dominica), Upland Sandpiper (Bartramia longicauda), and Killdeer (Charadrius vociferus) densities of 20.48, 11.09, and 26.09 birds/km2 in burned areas compared with 0.00, 1.27, and 0.92 birds/km2 in unburned areas, respectively. This research illustrates the importance of burned grassland for migrating shorebirds, a phenomenon that has largely gone unreported previously. Generally, these findings add to a body of knowledge that demonstrates the value of managing grasslands with historic disturbances that vary over space and time. The application of these findings should improve decision-making for shorebird conservation and provides evidence that prescribed fire planning should include consideration for breeding, transient, and non-breeding populations that vary in their temporal use of the landscape.

A randomized phase II non-comparative study of PF-04691502 and gedatolisib (PF-05212384) in patients with recurrent endometrial cancer.

OBJECTIVE: PF-04691502 and gedatolisib (PF-05212384) are potent, dual PI3K/mTOR inhibitors. This phase II study (B1271004) was conducted in patients with recurrent endometrial cancer following platinum-containing chemotherapy. The primary endpoint was to assess clinical benefit response (complete or partial response, or stable disease for ≥16weeks) following treatment with PF-04691502 or gedatolisib. METHODS: The main study consisted of four independent arms based on a Simon two-stage design. Patients were assigned to putative PI3K-basal (PF-04691502 or gedatolisib) or PI3K-activated (PF-04691502 or gedatolisib) arms based on stathmin-low or stathmin-high tumor expression, respectively. Japanese patients were also enrolled in a separate lead-in cohort. RESULTS: In stage 1 (main study), eighteen patients were randomized to PF-04691502 and 40 to gedatolisib. The two PF-04691502 arms were discontinued early due to unacceptable toxicity, including pneumonia and pneumonitis. The most common treatment-related adverse events associated with gedatolisib were nausea (53%), mucosal inflammation (50%), decreased appetite (40%), diarrhea (38%), fatigue (35%), and dysgeusia and vomiting (each 30%). Clinical benefit response rate was 53% (10/19) in the gedatolisib/stathmin-low arm and 26% (5/19) in the gedatolisib/stathmin-high arm. Safety profile and pharmacokinetic characteristics of both drugs in the Japanese lead-in cohort were comparable to the Western population. CONCLUSIONS: Gedatolisib administered by weekly intravenous infusion demonstrated acceptable tolerability and moderate activity in patients with recurrent endometrial cancer. PF-04691502 daily oral dosing was not well tolerated. Clinical benefit response criteria for proceeding to stage 2 were only met in the gedatolisib/stathmin-low arm. Stathmin-high expression did not correlate with greater treatment efficacy. ClinicalTrials.gov registration ID: NCT01420081.

Modeling Nonlinear Adsorption with a Single Chemical Parameter: Predicting Chemical Median Langmuir Binding Constants.

Procedures for accurately predicting linear partition coefficients onto various sorbents (e.g., organic carbon, soils, clay) are reliable and well established. However, similar procedures for the prediction of sorption parameters of nonlinear isotherm models are not. The purpose of this paper is to present a procedure for predicting nonlinear isotherm parameters, specifically the median Langmuir binding constants, K̃L, obtained utilizing the single-chemical parameter log-normal Langmuir isotherm developed in the accompanying work. A reduced poly parameter linear free energy relationship (pp-LFER) is able to predict median Langmuir binding constants for graphite, charcoal, and Darco granular activated carbon (GAC) adsorption data. For the larger F400 GAC data set, a single pp-LFER model was insufficient, as a plateau is observed for the median Langmuir binding constants of larger molecular volume sorbates. This volumetric cutoff occurs in proximity to the median pore diameter for F400 GAC. A log-linear relationship exists between the aqueous solubility of these large compounds and their median Langmuir binding constants. Using this relationship for the chemicals above the volumetric cutoff and the pp-LFER below the cutoff, the median Langmuir binding constants can be predicted with a root-mean square error for graphite (n = 13), charcoal (n = 11), Darco GAC (n = 14), and F400 GAC (n = 44) of 0.129, 0.307, 0.407, and 0.424, respectively.

Modeling Nonlinear Adsorption to Carbon with a Single Chemical Parameter: A Lognormal Langmuir Isotherm.

Predictive models for linear sorption of solutes onto various media, e.g., soil organic carbon, are well-established; however, methods for predicting parameters for nonlinear isotherm models, e.g., Freundlich and Langmuir models, are not. Predicting nonlinear partition coefficients is complicated by the number of model parameters to fit n isotherms (e.g., Freundlich (2n) or Polanyi-Manes (3n)). The purpose of this paper is to present a nonlinear adsorption model with only one chemically specific parameter. To accomplish this, several simplifications to a log-normal Langmuir (LNL) isotherm model with 3n parameters were explored. A single sorbate-specific binding constant, the median Langmuir binding constant, and two global sorbent parameters; the total site density and the standard deviation of the Langmuir binding constant were employed. This single-solute specific (ss-LNL) model (2 + n parameters) was demonstrated to fit adsorption data as well as the 2n parameter Freundlich model. The LNL isotherm model is fit to four data sets composed of various chemicals sorbed to graphite, charcoal, and activated carbon. The RMS errors for the 3-, 2-, and 1-chemical specific parameter models were 0.066, 0.068, 0.069, and 0.113, respectively. The median logarithmic parameter standard errors for the four models were 1.070, 0.4537, 0.382, and 0.201 respectively. Further, the single-parameter model was the only model for which there were no standard errors of estimated parameters greater than a factor of 3 (0.50 log units). The surprising result is that very little decrease in RMSE occurs when two of the three parameters, σκ and qmax, are sorbate independent. However, the large standard errors present in the other models are significantly reduced. This remarkable simplification yields the single sorbate-specific parameter (ss-LNL) model.

Acellular pertussis vaccine effectiveness for children during the 2009-2010 pertussis epidemic in Queensland.

UNLABELLED: OBJECTIVES To assess the effectiveness of three, four and five doses of acellular pertussis vaccine against pertussis notification for children aged 1 - < 4 years and 5 - < 12 years, and the effectiveness of three doses of acellular pertussis vaccine against pertussis hospitalisation for children aged 1 - < 4 years. DESIGN, SETTING AND PARTICIPANTS: A population-based retrospective study of children aged 1 - < 12 years residing in Queensland, Australia, during 2009 and 2010. Routinely collected notification, hospitalisation, testing and vaccination data were used to describe notification rates and testing patterns and to assess vaccine effectiveness (VE) by the screening method. MAIN OUTCOME MEASURES: VE against pertussis notification for children aged 1 - < 4 years and 5 - < 12 years, by birth year, and VE against pertussis hospitalisation for children aged 1 - < 4 years. RESULTS: 1961 notifications and 29 hospitalisations were included in the VE calculations. VE point estimates against pertussis notification and hospitalisation in children aged 1 - < 4 years were similar in 2009 and 2010, and ranged between 83.5% and 89.4%. VE point estimates against notification among children aged 5 - < 12 years were between 71.2% and 87.7% in 2009, and between 34.7% and 70.3% in 2010. The numbers of pertussis tests performed for children, particularly polymerase chain reaction (PCR) tests, increased between 2009 and 2010. CONCLUSIONS: Acellular pertussis vaccine provided good protection within the first years of priming, but this waned as age increased. Changes in pertussis testing behaviour, because of increases in PCR use and awareness, may have contributed to increased pertussis notification rates and lower estimates of VE against notification owing to identification of milder disease.

In Silico Acute Aquatic Hazard Assessment and Prioritization Using a Grouped Target Site Model: A Case Study of Organic Substances Reported in Permian Basin Hydraulic Fracturing Operations.

Hydraulic fracturing (HF) is commonly used to enhance onshore recovery of oil and gas during production. This process involves the use of a variety of chemicals to support the physical extraction of oil and gas, maintain appropriate conditions downhole (e.g., redox conditions, pH), and limit microbial growth. The diversity of chemicals used in HF presents a significant challenge for risk assessment. The objective of the present study is to establish a transparent, reproducible procedure for estimating 5th percentile acute aquatic hazard concentrations (e.g., acute hazard concentration 5th percentiles [HC5s]) for these substances and validating against existing toxicity data. A simplified, grouped target site model (gTSM) was developed using a database (n = 1696) of diverse compounds with known mode of action (MoA) information. Statistical significance testing was employed to reduce model complexity by combining 11 discrete MoAs into three general hazard groups. The new model was trained and validated using an 80:20 allocation of the experimental database. The gTSM predicts toxicity using a combination of target site water partition coefficients and hazard group-based critical target site concentrations. Model performance was comparable to the original TSM using 40% fewer parameters. Model predictions were judged to be sufficiently reliable and the gTSM was further used to prioritize a subset of reported Permian Basin HF substances for risk evaluation. The gTSM was applied to predict hazard groups, species acute toxicity, and acute HC5s for 186 organic compounds (neutral and ionic). Toxicity predictions and acute HC5 estimates were validated against measured acute toxicity data compiled for HF substances. This case study supports the gTSM as an efficient, cost-effective computational tool for rapid aquatic hazard assessment of diverse organic chemicals. Environ Toxicol Chem 2024;43:1161-1172. © 2024 ExxonMobil Petroleum and Chemical BV. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

US and international per- and polyfluoroalkyl substances surface water quality criteria: A review of the status, challenges, and implications for use in chemical management and risk assessment.

Regulation of per- and polyfluorinated substances (PFAS) in surface water is a work-in-progress with relatively few criteria promulgated in the United States and internationally. Surface water quality criteria (SWQC) or screening values derived for perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) by Australia, Canada, the European Union (EU), and four US states (Florida, Michigan, Minnesota, and Wisconsin), and the San Francisco Bay Regional Water Quality Control Board (SFB RWQCB; California) were compared. Across these eight jurisdictions, promulgated numeric criteria for the same compound and receptor span over five orders of magnitude as a result of different approaches and data interpretations. Human health criteria for PFOS range from 0.0047 to 600 ng/L depending on route of exposure (e.g., fish consumption or drinking water) and are lower than most ecological criteria for protection of aquatic and wildlife receptors. Data gaps and uncertainty in chronic toxicity and bioaccumulation of PFOS and PFOA, as well as the use of conservative assumptions regarding intake and exposure, have resulted in some criteria falling at or below ambient background concentrations and current analytical detection limits (around 1 ng/L for commercial laboratories). Some jurisdictions (e.g., Australia, Canada) have deemed uncertainty in quantifying water-fish bioaccumulation too great and set fish tissue action levels in lieu of water criteria. Current dynamics associated with the emerging and evolving science of PFAS toxicity, exposure, and environmental fate (i.e., data gaps and uncertainty), as well as the continuous release of scientific updates, pose a challenge to setting regulatory limits. Integr Environ Assess Manag 2024;20:36-58. © 2023 AECOM Technical Services, Inc and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Predicting Hydrocarbon Primary Biodegradation in Soil and Sediment Systems Using System Parameterization and Machine Learning.

Technical complexity associated with biodegradation testing, particularly for substances of unknown or variable composition, complex reaction products, or biological materials (UVCB), necessitates the advancement of non-testing methods such as quantitative structure-property relationships (QSPRs). Models for describing the biodegradation of petroleum hydrocarbons (HCs) have been previously developed. A critical limitation of available models is their inability to capture the variability in biodegradation rates associated with variable test systems and environmental conditions. Recently, the Hydrocarbon Biodegradation System Integrated Model (HC-BioSIM) was developed to characterize the biodegradation of HCs in aquatic systems with the inclusion of key test system variables. The present study further expands the HC-BioSIM methodology to soil and sediment systems using a database of 2195 half-life (i.e., degradation time [DT]50) entries for HCs in soil and sediment. Relevance and reliability criteria were defined based on similarity to standard testing guidelines for biodegradation testing and applied to all entries in the database. The HC-BioSIM soil and sediment models significantly outperformed the existing biodegradation HC half-life (BioHCWin) and virtual evaluation of chemical properties and toxicities (VEGA) quantitative Mario Negri Institute for Pharmacological Research (IRFMN) models in soil and sediment. Average errors in predicted DT50s were reduced by up to 6.3- and 8.7-fold for soil and sediment, respectively. No significant bias as a function of HC class, carbon number, or test system parameters was observed. Model diagnostics demonstrated low variability in performance and high consistency of parameter usage/importance and rule structure, supporting the generalizability and stability of the models for application to external data sets. The HC-BioSIM provides improved accuracy of Persistence categorization, with correct classification rates of 83.9%, and 90.6% for soil and sediment, respectively, demonstrating a significant improvement over the existing BioHCWin (70.7% and 58.6%) and VEGA (59.5% and 18.5%) models. Environ Toxicol Chem 2024;43:1352-1363. © 2024 Concawe. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.