International Workers' Day: Consumption Patterns of Morphine, Codeine, and Methamphetamine in Urban and Rural Areas Based on Wastewater-Based Epidemiology.

Wastewater-based epidemiology (WBE) is a reliable means to estimate drug consumption in a specific population. By measuring the concentration of drug residues or metabolites in wastewater, the consumption behavior pattern of a specific population can be deduced. Using the WBE method, the present study, for the first time, continuously monitored the differences in the consumption of morphine (MOR), codeine (CODE), and methamphetamine (METH) in three wastewater-treatment plants in a city and two surrounding villages in Xinjiang, China during International Workers' Day and the following week. The wastewater samples were pretreated by solid-phase extraction and then analyzed by high-performance liquid chromatography-tandem mass spectrometry. Methamphetamine was not detected in rural areas and was detected only on International Workers' Day in urban areas. According to the estimation of per capita consumption, the per capita consumption of MOR, CODE, and METH in urban inhabitants was 12.04 to 23.39, 10.44 to 16.39, and 1.31 mg/day/1000 inhabitants. The per capita consumption of MOR and CODE in rural areas was 5.19 to 8.35 and 2.56 to 3.52 mg/day/1000 inhabitants. The consumption of MOR in urban and rural areas was significantly higher than that of CODE and METH. During International Workers' Day, workdays, and weekends, the consumption of MOR and CODE in urban areas is significantly higher than that in rural areas. Compared with those on weekends, the consumption of urban MOR and CODE increased more during International Workers' Day. The consumption of MOR in urban areas showed a weekend effect. The present study can provide information for subsequent research and government departments. Environ Toxicol Chem 2024;00:1-9. © 2024 SETAC.

Modeling the population health impact of accurate and inaccurate perceptions of harm from nicotine.

BACKGROUND: Scientific evidence clearly demonstrates that inhaling the smoke from the combustion of cigarettes is responsible for most of the harm caused by smoking, and not the nicotine. However, a majority of U.S. adults who smoke inaccurately believe that nicotine causes cancer which may be a significant barrier, preventing switching to potentially reduced risk, non-combustible products like electronic nicotine delivery systems (ENDS) and smokeless tobacco (ST). We assessed the population health impact associated with nicotine perceptions. METHODS: Using a previously validated agent-based model to the U.S. population, we analyzed nationally representative data from the Population Assessment of Tobacco and Health (PATH) study to estimate base case rates of sustained (maintained over four waves) cessation and switching to non-combustible product use, by sex. Nicotine perception scenarios were determined from PATH data. The overall switch rate from smoking in Wave 4 to non-combustible product use in Wave 5 (3.94%) was stratified based on responses to the nicotine perception question "Do you believe nicotine is the chemical that causes most of the cancer caused by smoking cigarettes?", (four-item scale from "Definitely not" to "Definitely yes"). The relative percent change between the overall and stratified rates, corresponding to each item, was used to adjust the base case rates of switching, to determine the impact, if all adults who smoke exhibited switching behaviors based on responses to the nicotine perceptions question. The public health impact of nicotine perceptions was estimated as the difference in all-cause mortality between the base case and the four nicotine perception scenarios. RESULTS: Switch rates associated with those who responded, "Definitely not" (8.39%) resulted in a net benefit of preventing nearly 800,000 premature deaths over an 85-year period. Conversely switch rates reflective of those who responded, "Definitely yes" (2.59%) resulted in a net harm of nearly 300,000 additional premature deaths over the same period. CONCLUSIONS: Accurate knowledge regarding the role of nicotine is associated with higher switch rates and prevention of premature deaths. Our findings suggest that promoting public education to correct perceptions of harm from nicotine has the potential to benefit public health.

How Model Organisms and Model Uncertainty Impact Our Understanding of the Risk of Sublethal Impacts of Toxicants to Survival and Growth of Ecologically Relevant Species.

Understanding how sublethal impacts of toxicants affect population-relevant outcomes for organisms is challenging. We tested the hypotheses that the well-known sublethal impacts of methylmercury (MeHg) and a polychlorinated biphenyl (PCB126) would have meaningful impacts on cohort growth and survival in yellow perch (Perca flavescens) and Atlantic killifish (Fundulus heteroclitus) populations, that inclusion of model uncertainty is important for understanding the sublethal impacts of toxicants, and that a model organism (zebrafish Danio rerio) is an appropriate substitute for ecologically relevant species (yellow perch, killifish). Our simulations showed that MeHg did not have meaningful impacts on growth or survival in a simulated environment except to increase survival and growth in low mercury exposures in yellow perch and killifish. For PCB126, the high level of exposure resulted in lower survival for killifish only. Uncertainty analyses increased the variability and lowered average survival estimates across all species and toxicants, providing a more conservative estimate of risk. We demonstrate that using a model organism instead of the species of interest does not necessarily give the same results, suggesting that using zebrafish as a surrogate for yellow perch and killifish may not be appropriate for predicting contaminant impacts on larval cohort growth and survival in ecologically relevant species. Our analysis also reinforces the notion that uncertainty analyses are necessary in any modeling assessment of the impacts of toxicants on a population because it provides a more conservative, and arguably realistic, estimate of impact. Environ Toxicol Chem 2024;43:2122-2133. © 2024 SETAC.

Morphological Stability for in silico Models of Avascular Tumors.

The landscape of computational modeling in cancer systems biology is diverse, offering a spectrum of models and frameworks, each with its own trade-offs and advantages. Ideally, models are meant to be useful in refining hypotheses, to sharpen experimental procedures and, in the longer run, even for applications in personalized medicine. One of the greatest challenges is to balance model realism and detail with experimental data to eventually produce useful data-driven models. We contribute to this quest by developing a transparent, highly parsimonious, first principle in silico model of a growing avascular tumor. We initially formulate the physiological considerations and the specific model within a stochastic cell-based framework. We next formulate a corresponding mean-field model using partial differential equations which is amenable to mathematical analysis. Despite a few notable differences between the two models, we are in this way able to successfully detail the impact of all parameters in the stability of the growth process and on the eventual tumor fate of the stochastic model. This facilitates the deduction of Bayesian priors for a given situation, but also provides important insights into the underlying mechanism of tumor growth and progression. Although the resulting model framework is relatively simple and transparent, it can still reproduce the full range of known emergent behavior. We identify a novel model instability arising from nutrient starvation and we also discuss additional insight concerning possible model additions and the effects of those. Thanks to the framework's flexibility, such additions can be readily included whenever the relevant data become available.

Modeling Full Life-Cycle Effects of Copper on Brook Trout (Salvelinus fontinalis) Populations.

Population models are increasingly used to predict population-level effects of chemicals. For trout, most toxicity data are available on early-life stages, but this may cause population models to miss true population-level effects. We predicted population-level effects of copper (Cu) on a brook trout (Salvelinus fontinalis) population based on individual-level effects observed in either a life-cycle study or an early-life stage study. We assessed the effect of Cu on predicted trout densities (both total and different age classes) and the importance of accounting for effects on the full life cycle compared with only early-life stage effects. Additionally, uncertainty about the death mechanism and growth effects was evaluated by comparing the effect of different implementation methods: individual tolerance (IT) versus stochastic death (SD) and continuous versus temporary growth effects. For the life-cycle study, the same population-level no-observed-effect concentration (NOECpop) was predicted as the lowest reported individual-level NOEC (NOECind; 9.5 µg/L) using IT. For SD, the NOECpop was predicted to be lower than the NOECind for young-of-the-year and 1-year-old trout (3.4 µg/L), but similar for older trout (9.5 µg/L). The implementation method for growth effects did not affect the NOECpop of the life-cycle study. Simulations based solely on the early-life stage effects within the life-cycle study predicted unbounded NOECpop values (≥32.5 µg/L), that is, >3.4 times higher than the NOECpop based on all life-cycle effects. For the early-life stage study, the NOECpop for both IT and SD were predicted to be >2.6 times higher than the lowest reported NOECind. Overall, we demonstrate that effects on trout populations can be underestimated if predictions are solely based on toxicity data with early-life stages. Environ Toxicol Chem 2024;43:1662-1676. © 2024 SETAC.

Tuning interdomain conjugation to enable in situ population modification in yeasts.

The ability to modify and control natural and engineered microbiomes is essential for biotechnology and biomedicine. Fungi are critical members of most microbiomes, yet technology for modifying the fungal members of a microbiome has lagged far behind that for bacteria. Interdomain conjugation (IDC) is a promising approach, as DNA transfer from bacterial cells to yeast enables in situ modification. While such genetic transfers have been known to naturally occur in a wide range of eukaryotes and are thought to contribute to their evolution, IDC has been understudied as a technique to control fungal or fungal-bacterial consortia. One major obstacle to the widespread use of IDC is its limited efficiency. In this work, we manipulated metabolic and physical interactions between genetically tractable Escherichia coli and Saccharomyces cerevisiae to control the incidence of IDC. We test the landscape of population interactions between the bacterial donors and yeast recipients to find that bacterial commensalism leads to maximized IDC, both in culture and in mixed colonies. We demonstrate the capacity of cell-to-cell binding via mannoproteins to assist both IDC incidence and bacterial commensalism in culture and model how these tunable controls can predictably yield a range of IDC outcomes. Furthermore, we demonstrate that these controls can be utilized to irreversibly alter a recipient yeast population, by both "rescuing" a poor-growing recipient population and collapsing a stable population via a novel IDC-mediated CRISPR/Cas9 system.IMPORTANCEFungi are important but often unaddressed members of most natural and synthetic microbial communities. This work highlights opportunities for modifying yeast microbiome populations through bacterial conjugation. While conjugation has been recognized for its capacity to deliver engineerable DNA to a range of cells, its dependence on cell contact has limited its efficiency. Here, we find "knobs" to control DNA transfer, by engineering the metabolic dependence between bacterial donors and yeast recipients and by changing their ability to physically adhere to each other. Importantly, we functionally validate these "knobs" by irreversibly altering yeast populations. We use these controls to "rescue" a failing yeast population, demonstrate the capacity of conjugated CRISPR/Cas9 to depress or collapse populations, and show that conjugation can be easily interrupted by disrupting cell-to-cell binding. These results offer building blocks toward in situ mycobiome editing, with significant implications for clinical treatments of fungal pathogens and other fungal system engineering.

Population pharmacokinetic, pharmacodynamic and efficacy modeling of SB12 (proposed eculizumab biosimilar) and reference eculizumab.

PURPOSE: To describe, compare similarity of pharmacokinetic (PK), pharmacodynamic (PD) and efficacy of SB12 and reference eculizumab (ECU) and find clinically significant covariate relationships. METHODS: The PK, PD (terminal complement activity) and efficacy (LDH) data of SB12 and ECU were obtained from 289 subjects from phase I and phase III studies. One- and two-compartment PK models with first-order elimination were evaluated for SB12 and ECU. For PD and efficacy, both direct and indirect models were tested. The impact of covariates on PK, PD and efficacy parameters was assessed. Relationship between PK/PD and PD/efficacy was characterized. This modeling was performed using NONMEM version 7.4 (Icon Development Solutions, Ellicott City, MD, USA). RESULTS: The two-compartment model adequately described the PK of SB12 and ECU, and the subject's weight was chosen as a clinically significant covariate affecting drugs' clearance and central volume of distribution. Treatment group was not a significant covariate affecting clearance. The direct response model using inhibitory sigmoid Emax and sigmoid Emax relationship well described the PK/PD relationship and PD/efficacy relationship of SB12 and ECU, respectively. Through this modeling, the relationships between PK, PD and efficacy were characterized. There were no differences in PK, PD and efficacy parameters between SB12 and ECU in pooled populations of healthy subjects and paroxysmal nocturnal haemoglobinuria (PNH) patients. CONCLUSION: The population modeling showed PK, PD and efficacy similarities between SB12 and ECU in pooled population of healthy subjects and PNH patients, supporting the totality of evidence on biosimilarity for SB12.

Camera trap surveys of Atlantic Forest mammals: A data set for analyses considering imperfect detection (2004-2020).

Camera traps became the main observational method of a myriad of species over large areas. Data sets from camera traps can be used to describe the patterns and monitor the occupancy, abundance, and richness of wildlife, essential information for conservation in times of rapid climate and land-cover changes. Habitat loss and poaching are responsible for historical population losses of mammals in the Atlantic Forest biodiversity hotspot, especially for medium to large-sized species. Here we present a data set from camera trap surveys of medium to large-sized native mammals (>1 kg) across the Atlantic Forest. We compiled data from 5380 ground-level camera trap deployments in 3046 locations, from 2004 to 2020, resulting in 43,068 records of 58 species. These data add to existing data sets of mammals in the Atlantic Forest by including dates of camera operation needed for analyses dealing with imperfect detection. We also included, when available, information on important predictors of detection, namely the camera brand and model, use of bait, and obstruction of camera viewshed that can be measured from example pictures at each camera location. Besides its application in studies on the patterns and mechanisms behind occupancy, relative abundance, richness, and detection, the data set presented here can be used to study species' daily activity patterns, activity levels, and spatiotemporal interactions between species. Moreover, data can be used combined with other data sources in the multiple and expanding uses of integrated population modeling. An R script is available to view summaries of the data set. We expect that this data set will be used to advance the knowledge of mammal assemblages and to inform evidence-based solutions for the conservation of the Atlantic Forest. The data are not copyright restricted; please cite this paper when using the data.

As armadilhas fotográficas tornaram­se o principal método de observação de muitas espécies em grandes áreas. Os dados obtidos com armadilhas fotográficas podem ser usados para descrever os padrões e monitorar a ocupação, abundância e riqueza da vida selvagem, informação essencial para a conservação em tempos de rápidas mudanças climáticas e de cobertura do solo. A perda de habitat e a caça furtiva são responsáveis pelas perdas populacionais históricas de mamíferos no hotspot de biodiversidade da Mata Atlântica, especialmente para espécies de médio e grande porte. Aqui apresentamos um conjunto de dados de levantamentos com armadilhas fotográficas de mamíferos de médio e grande porte (>1 kg) em toda a Mata Atlântica. Compilamos dados de 5.380 armadilhas fotográficas instaladas no nível do chão em 3.046 locais, de 2004 a 2020, resultando em 43.068 registros de 58 espécies. Esses dados acrescentam aos conjuntos de dados existentes de mamíferos na Mata Atlântica por incluir as datas de operação das câmeras, que são necessárias para análises que lidam com detecção imperfeita. Também incluímos, quando disponíveis, informações sobre importantes preditores de detecção, como marca e modelo da câmera, uso de isca e obstrução do visor da câmera que pode ser medido a partir de imagens de exemplo em cada local da câmera. Além de estudos sobre os padrões e mecanismos por trás da ocupação, abundância relativa, riqueza e detecção, o conjunto de dados aqui apresentado pode ser usado para estudar os padrões de atividade diária das espécies, nível de atividade e interações espaço­temporais entre as espécies. Além disso, os dados podem ser usados em combinação com outras fontes de dados em diversas análises com modelagem populacional integrada. Um script R está disponível para visualizar um resumo do conjunto de dados. Esperamos que este conjunto de dados seja usado para aumentar o conhecimento sobre as assembleias de mamíferos e usado para informar soluções baseadas em evidências para a conservação da Mata Atlântica. Os dados não são restritos por direitos autorais e, por favor, cite este documento ao usar os dados.

Restoring spatiotemporal variability to enhance the capacity for dispersal-limited species to track climate change.

Climate refugia are areas where species can persist through climate change with little to no movement. Among the factors associated with climate refugia are high spatial heterogeneity, such that there is only a short distance between current and future optimal climates, as well as biotic or abiotic environmental factors that buffer against variability in time. However, these types of climate refugia may be declining due to anthropogenic homogenization of environments and degradation of environmental buffers. To quantify the potential for restoration of refugia-like environmental conditions to increase population persistence under climate change, we simulated a population's capacity to track their temperature over space and time given different levels of spatial and temporal variability in temperature. To determine how species traits affected the efficacy of restoring heterogeneity, we explored an array of values for species' dispersal ability, thermal tolerance, and fecundity. We found that species were more likely to persist in environments with higher spatial heterogeneity and lower environmental stochasticity. When simulating a management action that increased the spatial heterogeneity of a previously homogenized environment, species were more likely to persist through climate change, and population sizes were generally higher, but there was little effect with mild temperature change. The benefits of heterogeneity restoration were greatest for species with limited dispersal ability. In contrast, species with longer dispersal but lower fecundity were more likely to benefit from a reduction in environmental stochasticity than an increase in spatial heterogeneity. Our results suggest that restoring environments to refugia-like conditions could promote species' persistence under the influence of climate change in addition to conservation strategies such as assisted migration, corridors, and increased protection.

Population pharmacokinetics of the dual endothelin receptor antagonist aprocitentan in subjects with or without essential or resistant hypertension.

Aprocitentan is a novel, potent, dual endothelin receptor antagonist that recently demonstrated efficacy in the treatment of difficult-to-treat (resistant) hypertension. The aim of this study was to develop a population pharmacokinetic (PK) model describing aprocitentan plasma concentration over time, to investigate relationships between subject-specific factors (covariates) and model parameters, and to quantify the influence of the identified covariates on the exposure to aprocitentan via model-based simulations, enabling judgment about the clinical relevance of the covariates.PK data from 902 subjects in ten Phase 1, one Phase 2, and one Phase 3 study were pooled to develop a joint population PK model. The concentration-time course of aprocitentan was described by a two-compartment model with absorption lag time, first-order absorption and elimination, and reduced relative bioavailability following very high doses of 300 and 600 mg.The population PK model described the observed data well. Volume and clearance parameters were associated with body weight. Renal function as reflected by estimated glomerular filtration rate (eGFR), hepatic impairment, and sex were identified as relevant covariates on clearance.The subject-specific characteristics of body weight, eGFR, hepatic impairment, and sex were shown to influence exposure parameters area under the concentration-time curve and maximum concentration in steady state to a limited extent, i.e., not more than 25% different from a reference subject, and therefore do not warrant dose adjustments.

Wildlife ecological risk assessment in the 21st century: Promising technologies to assess toxicological effects.

Despite advances in toxicity testing and the development of new approach methodologies (NAMs) for hazard assessment, the ecological risk assessment (ERA) framework for terrestrial wildlife (i.e., air-breathing amphibians, reptiles, birds, and mammals) has remained unchanged for decades. While survival, growth, and reproductive endpoints derived from whole-animal toxicity tests are central to hazard assessment, nonstandard measures of biological effects at multiple levels of biological organization (e.g., molecular, cellular, tissue, organ, organism, population, community, ecosystem) have the potential to enhance the relevance of prospective and retrospective wildlife ERAs. Other factors (e.g., indirect effects of contaminants on food supplies and infectious disease processes) are influenced by toxicants at individual, population, and community levels, and need to be factored into chemically based risk assessments to enhance the "eco" component of ERAs. Regulatory and logistical challenges often relegate such nonstandard endpoints and indirect effects to postregistration evaluations of pesticides and industrial chemicals and contaminated site evaluations. While NAMs are being developed, to date, their applications in ERAs focused on wildlife have been limited. No single magic tool or model will address all uncertainties in hazard assessment. Modernizing wildlife ERAs will likely entail combinations of laboratory- and field-derived data at multiple levels of biological organization, knowledge collection solutions (e.g., systematic review, adverse outcome pathway frameworks), and inferential methods that facilitate integrations and risk estimations focused on species, populations, interspecific extrapolations, and ecosystem services modeling, with less dependence on whole-animal data and simple hazard ratios. Integr Environ Assess Manag 2024;20:725-748. © 2023 His Majesty the King in Right of Canada and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). Reproduced with the permission of the Minister of Environment and Climate Change Canada. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

A multidisciplinary approach to estimating wolf population size for long-term conservation.

The wolf (Canis lupus) is among the most controversial of wildlife species. Abundance estimates are required to inform public debate and policy decisions, but obtaining them at biologically relevant scales is challenging. We developed a system for comprehensive population estimation across the Italian alpine region (100,000 km2 ), involving 1513 trained operators representing 160 institutions. This extensive network allowed for coordinated genetic sample collection and landscape-level spatial capture-recapture analyses that transcended administrative boundaries to produce the first estimates of key parameters for wolf population status assessment. Wolf abundance was estimated at 952 individuals (95% credible interval 816-1120) and 135 reproductive units (i.e., packs) (95% credible interval 112-165). We also estimated that mature individuals accounted for 33-45% of the entire population. The monitoring effort was spatially estimated thereby overcoming an important limitation of citizen science data. This is an important approach for promoting wolf-human coexistence based on wolf abundance monitoring and an endorsement of large-scale harmonized conservation practices.

Una estrategia multidisciplinaria para la estimación del tamaño poblacional de los lobos para la conservación a largo plazo Resumen El lobo (Canis lupus) está entre las especies de fauna más controversiales. Se requieren estimaciones de abundancia para informar al debate público y las decisiones políticas, pero es un reto obtenerlos en escalas con relevancia biológica. Desarrollamos un sistema para la estimación completa de la población en la región alpina de Italia (100,000 km2 ), con la participación de 1,513 operadores entrenados que representan a 160 instituciones. Esta red extensa permitió una colecta coordinada de muestras genéticas y análisis de captura-recaptura espacial que trascendieron las fronteras administrativas para así producir las primeras estimaciones de los parámetros clave para la evaluación del estado de la población de los lobos. Se estimó la abundancia en 952 individuos (95% intervalo de confianza 816-1120) y 135 unidades reproductivas (es decir, manadas) (95% intervalo de confianza 112-165). También estimamos que los individuos maduros representaban el 33-45% de toda la población. El esfuerzo de monitoreo se estimó espacialmente, por lo que sobrepasó una limitación importante de la ciencia ciudadana. Esta estrategia es importante para promover la coexistencia entre lobos y humanos con base en el monitoreo de la abundancia y el apoyo a las prácticas armonizadas de conservación a gran escala.

Evaluating and Explaining the Variability of Honey Bee Field Studies across Europe Using BEEHAVE.

To assess the effect of plant protection products on pollinator colonies, the higher tier of environmental risk assessment (ERA), for managed honey bee colonies and other pollinators, is in need of a mechanistic effect model. Such models are seen as a promising solution to the shortcomings, which empirical risk assessment can only overcome to a certain degree. A recent assessment of 40 models conducted by the European Food Safety Authority (EFSA) revealed that BEEHAVE is currently the only publicly available mechanistic honey bee model that has the potential to be accepted for ERA purposes. A concern in the use of this model is a lack of model validation against empirical data, spanning field studies conducted in different regions of Europe and covering the variability in colony and environmental conditions. We filled this gap with a BEEHAVE validation study against 66 control colonies of field studies conducted across Germany, Hungary, and the United Kingdom. Our study implements realistic initial colony size and landscape structure to consider foraging options. Overall, the temporal pattern of colony strength is predicted well. Some discrepancies between experimental data and prediction outcomes are explained by assumptions made for model parameterization. Complementary to the recent EFSA study using BEEHAVE, our validation covers a large variability in colony conditions and environmental impacts representing the Northern and Central European Regulatory Zones. Thus we believe that BEEHAVE can be used to serve the development of specific protection goals as well as the development of simulation scenarios for the European Regulatory Zone. Subsequently, the model can be applied as a standard tool for higher tier ERA of managed honey bees using the mechanistic ecotoxicological module for BEEHAVE, BEEHAVEecotox . Environ Toxicol Chem 2023;42:1839-1850. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Comparing the effectiveness of different insecticide application orders for suppressing Drosophila suzukii Matsumura (Diptera: Drosophilidae) infestation: experimental and modeling approaches.

Drosophila suzukii Matsumura (Diptera: Drosophilidae) is a key pest of soft-skinned fruit such as blackberry and blueberry. Differing seasonal spray regimes are expected to have variable effects on D. suzukii populations. Semi-field cage trials were performed at three locations in the United States (Georgia, Oregon, and North Carolina) on blueberry and blackberry crops to evaluate this hypothesis. Insecticides with different efficacy rates (ZC - zeta-cypermethrin, SPI - spinetoram, CYAN - cyantraniliprole) were applied during field experiments conducted within large cages. Treatment schedules consisted of two insecticide applications which performed over three weeks. Seasonal treatment schedules were applied in the following order: ZC-CYAN and CYAN-ZC in rabbiteye and highbush blueberry with the addition of a ZC-SPI treatment applied in blackberry. In addition, a population model was applied to simulate the relative efficacy of the insecticide schedules in Oregon on D. suzukii population model based on previously published efficacy, biological, and weather parameters. Overall, all schedules resulted in reduced D. suzukii infestation compared to untreated control (UTC) treatments, with statistical differences in all three locations. The numerically lower infestation was found in some cases in ZC-CYAN schedule. Population modeling conducted exclusively for blueberry, and the simulations indicated no discernible differences between the two respective schedules (ZC-CYAN vs CYAN-ZC). The present study demonstrates that seasonal infestation of D. suzukii could be suppressed irrespective of application order. Additional research is required to assess the optimal timing and sequence of insecticide applications for controlling seasonal populations of D. suzukii in fruit crops. Such information could be invaluable for growers who are seeking to strategize their insecticide applications.

Comparison of Compartmental and Non-Compartmental Analysis to Detect Biopharmaceutical Similarity of Intravenous Nanomaterial-Based Rifabutin Formulations.

Pharmacometric analysis is often used to quantify the differences and similarities between formulation prototypes. In the regulatory framework, it plays a significant role in the evaluation of bioequivalence. While non-compartmental analysis provides an unbiased data evaluation, mechanistic compartmental models such as the physiologically-based nanocarrier biopharmaceutics model promise improved sensitivity and resolution for the underlying causes of inequivalence. In the present investigation, both techniques were applied to two nanomaterial-based formulations for intravenous injection, namely, albumin-stabilized rifabutin nanoparticles and rifabutin-loaded PLGA nanoparticles. The antibiotic rifabutin holds great potential for the treatment of severe and acute infections of patients co-infected with human immunodeficiency virus and tuberculosis. The formulations differ significantly in their formulation and material attributes, resulting in an altered biodistribution pattern as confirmed in a biodistribution study in rats. The albumin-stabilized delivery system further undergoes a dose-dependent change in particle size which leads to a small yet significant change in the in vivo performance. A second analysis was conducted comparing the dose fraction-scaled pharmacokinetic profiles of three dose levels of albumin-stabilized rifabutin nanoparticles. The dose strength affects both the nanomaterial-related absorption and biodistribution of the carrier as well as the drug-related distribution and elimination parameters, increasing the background noise and difficulty of detecting inequivalence. Depending on the pharmacokinetic parameter (e.g., AUC, Cmax, Clobs), the relative (percentage) difference from the average observed using non-compartmental modeling ranged from 85% to 5.2%. A change in the formulation type (PLGA nanoparticles vs. albumin-stabilized rifabutin nanoparticles) resulted in a similar level of inequivalence as compared to a change in the dose strength. A mechanistic compartmental analysis using the physiologically-based nanocarrier biopharmaceutics model led to an average difference of 152.46% between the two formulation prototypes. Albumin-stabilized rifabutin nanoparticles tested at different dose levels led to a 128.30% difference, potentially due to changes in particle size. A comparison of different dose strengths of PLGA nanoparticles, on average, led to a 3.87% difference. This study impressively illustrates the superior sensitivity of mechanistic compartmental analysis when dealing with nanomedicines.

Comparison of sequential and joint nonlinear mixed effects modeling of tumor kinetics and survival following Durvalumab treatment in patients with metastatic urothelial carcinoma.

Standard endpoints such as objective response rate are usually poorly correlated with overall survival (OS) for treatment with immune checkpoint inhibitors. Longitudinal tumor size may serve as a more useful predictor of OS, and establishing a quantitative relationship between tumor kinetics (TK) and OS is a crucial step for successfully predicting OS based on limited tumor size measurements. This study aims to develop a population TK model in combination with a parametric survival model by sequential and joint modeling approaches to characterize durvalumab phase I/II data from patients with metastatic urothelial cancer, and to evaluate and compare the performance of the two modeling approaches in terms of parameter estimates, TK and survival predictions, and covariate identification. The tumor growth rate constant was estimated to be greater for patients with OS ≤ 16 weeks as compared to that for patients with OS > 16 weeks with the joint modeling approach (kg= 0.130 vs. 0.0551 week-1, p-value < 0.0001), but similar for both groups (kg = 0.0624 vs.0.0563 week-1, p-value = 0.37) with the sequential modeling approach. The predicted TK profiles by joint modeling appeared better aligned with clinical observations. Joint modeling also predicted OS more accurately than the sequential approach according to concordance index and Brier score. The sequential and joint modeling approaches were also compared using additional simulated datasets, and survival was predicted better by joint modeling in the case of a strong association between TK and OS. In conclusion, joint modeling enabled the establishment of a robust association between TK and OS and may represent a better choice for parametric survival analyses over the sequential approach.

Penetration of Vancomycin into Noninfected Bone in Patients Undergoing Total Joint Arthroplasty Evaluated by a Minimal Physiologically Based Population Pharmacokinetic Modeling Approach.

Arthroplasty is a healthcare priority and represents high volume, high cost surgery. Periprosthetic joint infection (PJI) results in significant mortality, thus it is vital that the risk for PJI is minimized. Vancomycin is recommended for surgical prophylaxis in total joint arthroplasty (TJA) by current clinical practice guidelines endorsed by the Infectious Diseases Society of America. This study aimed to develop a new assay to determine vancomycin concentrations in serum and bone, and a minimal physiologically based population PK (mPBPK) model to evaluate vancomycin bone penetration in noninfected patients. Eleven patients undergoing TJA received 0.5-2.0 g intravenous vancomycin over 12-150 min before surgery. Excised bone specimens and four blood samples were collected per patient. Bone samples were pulverized under liquid nitrogen using a cryogenic mill. Vancomycin concentrations in serum and bone were analyzed by liquid chromatography-tandem mass spectrometry and subjected to mPBPK modeling. Vancomycin serum and bone concentrations ranged from 9.30 to 86.6 mg/L, and 1.94-37.0 mg/L, respectively. Average bone to serum concentration ratio was 0.41 (0.16-1.0) based on the collected samples. The population mean total body clearance was 2.12L/h/kg0.75. Inclusion of total body weight as a covariate substantially decreased interindividual variability in clearance. The bone/blood partition coefficient (Kpbone) was estimated at 0.635, reflecting the average bone/blood concentration ratio at steady-state. The model predicted median ratio of vancomycin area under the curve (AUC) for bone/AUC for serum was 44%. Observed vancomycin concentrations in bone were overall consistent with perfusion-limited distribution from blood to bone. An mPBPK model overall well described vancomycin concentrations in serum and bone.

Privacy by Projection: Federated Population Density Estimation by Projecting on Random Features.

We consider the problem of population density estimation based on location data crowdsourced from mobile devices, using kernel density estimation (KDE). In a conventional, centralized setting, KDE requires mobile users to upload their location data to a server, thus raising privacy concerns. Here, we propose a Federated KDE framework for estimating the user population density, which not only keeps location data on the devices but also provides probabilistic privacy guarantees against a malicious server that tries to infer users' location. Our approach Federated random Fourier feature (RFF) KDE leverages a random feature representation of the KDE solution, in which each user's information is irreversibly projected onto a small number of spatially delocalized basis functions, making precise localization impossible while still allowing population density estimation. We evaluate our method on both synthetic and real-world datasets, and we show that it achieves a better utility (estimation performance)-vs-privacy (distance between inferred and true locations) tradeoff, compared to state-of-the-art baselines (e.g., GeoInd). We also vary the number of basis functions per user, to further improve the privacy-utility trade-off, and we provide analytical bounds on localization as a function of areal unit size and kernel bandwidth.

Sensitivity Analysis of Cardiac Alternans and Tachyarrhythmia to Ion Channel Conductance Using Population Modeling.

Action potential duration (APD) alternans, an alternating phenomenon between action potentials in cardiomyocytes, causes heart arrhythmia when the heart rate is high. However, some of the APD alternans observed in clinical trials occurs under slow heart rate conditions of 100 to 120 bpm, increasing the likelihood of heart arrhythmias such as atrial fibrillation. Advanced studies have identified the occurrence of this type of APD alternans in terms of electrophysiological ion channel currents in cells. However, they only identified physiological phenomena, such as action potential due to random changes in a particular ion channel's conductivity through ion models specializing in specific ion channel currents. In this study, we performed parameter sensitivity analysis via population modeling using a validated human ventricular physiology model to check the sensitivity of APD alternans to ion channel conductances. Through population modeling, we expressed the changes in alternans onset cycle length (AOCL) and mean APD in AOCL (AO meanAPD) according to the variations in ion channel conductance. Finally, we identified the ion channel that maximally affected the occurrence of APD alternans. AOCL and AO meanAPD were sensitive to changes in the plateau Ca2+ current. Accordingly, it was expected that APD alternans would be vulnerable to changes in intracellular calcium concentration.

Inequalities of spatial primary healthcare accessibility in China.

A key step to the establishment of a tiered healthcare system is equitable access to basic primary healthcare services for all. However, no quantitative research on the national status quo of primary healthcare accessibility in China exists. We filled this gap by estimating spatial accessibility to primary healthcare centers (PHCs) and mapping its inequality across the mainland China. Four national datasets during 2015-2018, including administrative boundaries, residential communities, points-of-interest (including PHCs), and road networks, were collected to calculate the distance to the nearest PHC for each community. Five other national datasets including census, elevation, land use, vegetation, and nightlight, were collected to model 100m × 100 m population grids, based on which geographical modeling was used to calculate PHC accessibility of each community. Inequalities in PHC accessibility across China were described with concentration indices. About 44% of communities across China representing approximately 30% of the overall population had no access to PHCs within their 6-km catchment areas; about 78% of communities across China representing approximately 68.4% of the overall population had no access to PHCs within their 1.5-km catchment areas. Some municipalities/provinces like Shanghai, Beijing, Tianjin, Jiangsu, Shandong, and Zhejiang generally had higher proximity to the nearest PHCs, while others like Tibet, Guizhou, and Guangxi had lower proximity to the nearest PHCs. However, assuming similar basic service capacity across all PHCs, Shanghai, Tianjin, and Chongqing showed the lowest PHC accessibility due to high population density. Variations in PHC accessibility existed, with more inequalities observed in the north and northeastern provinces and less inequalities in southwestern and south-central provinces. This study demonstrates primary healthcare accessibility and inequality at province and city levels, and identifies communities with lower proximity and accessibility to PHCs in China. It would serve as a starting point to facilitate precise healthcare planning and preparedness for health emergencies in China.