Initial Growth Rate Research Articles

​Circulating Cytokines in Myocardial Infarction Are Associated With Coronary Blood Flow.

BackgroundThe level of systemic inflammation correlates with the severity of the clinical course of acute myocardial infarction (AMI). It has been shown that circulating cytokines and endothelial dysfunction play an important role in the process of clot formation. The aim of our study was to assess the concentration of various circulating cytokines, endothelial function and blood clotting in AMI patients depending on the blood flow through the infarction-related artery (IRA).MethodsWe included 75 patients with AMI. 58 presented with ST-elevation myocardial infarction (STEMI) and 17 had non-ST-elevation myocardial infarction (non-STEMI). A flow-mediated dilation test (FMD test), thrombodynamics and rotational thromboelastometry as well as assessment of 14 serum cytokines using xMAP technology were performed.FindingsNon-STEMI-patients were characterized by higher levels of MDC, MIP-1β, TNF-α. Moreover, we observed that patients with impaired blood flow through the IRA (TIMI flow 0-1) had higher average and initial clot growth rates, earlier onset of spontaneous clots, C-reactive protein (CRP) and IL-10 compared to patients with preserved blood flow through the IRA (TIMI flow 2-3). Patients with TIMI 2-3 blood flow had higher level of IP-10. IL-10 correlated with CRP and pro-inflammatory cytokines levels, initial clot growth rate and clot lysis time in TIMI 0-1 patients. All these differences were statistically significant.InterpretationWe demonstrated that concentrations of the inflammatory cytokines correlate not only with the form of myocardial infarction (STEMI or non-STEMI), but also with the blood flow through the infarct-related artery. Inflammatory response, functional state of endothelium, and clot formation are closely linked with each other. A combination of these parameters affects the patency of the infarct-related artery.

Coarsening Dynamics of 2D Subaqueous Dunes

AbstractFluid flow over an initially flat granular bed leads to the formation of a surface‐wave instability. The sediment bed profile coarsens and increases in amplitude and wavelength as disturbances develop from ripples into dunes. We perform experiments and numerical simulations to quantify both the temporal evolution of bed properties and the relationship between the initial growth rate and the friction velocity u∗. Experimentally, we study underwater bedforms originating from a thin horizontal particle layer in a narrow and counter‐rotating annular flume. We investigate the role of flow speed, flow depth and initial bed thickness on dune evolution. Bedforms evolve from small, irregular disturbances on the bed surface to rapidly growing connected terraces (2D equivalent of transverse dunes) before splitting into discrete dunes. Throughout much of this process, growth is controlled by dune collisions which are observed to result in either coalescence or ejection (mass exchange). We quantify the coarsening process by tracking the temporal evolution of the bed amplitude and wavelength. Additionally, we perform Large Eddy Simulations (LES) of the fluid flow inside the flume to relate the experimental conditions to u∗. By combining the experimental observations with the LES results, we find that the initial dune growth rate scales approximately as . These results can motivate models of finite‐amplitude dune growth from thin sediment layers that are important in both natural and industrial settings.

Study of the contribution of active defense mechanisms to ciprofloxacin tolerance in Escherichia coli growing at different rates

Using rpoS, tolC, ompF, and recA knockouts, we investigated their effect on the physiological response and lethality of ciprofloxacin in E. coli growing at different rates on glucose, succinate or acetate. We have shown that, regardless of the strain, the degree of changes in respiration, membrane potential, NAD+/NADH ratio, ATP and glutathione (GSH) strongly depends on the initial growth rate and the degree of its inhibition. The deletion of the regulator of the general stress response RpoS, although it influenced the expression of antioxidant genes, did not significantly affect the tolerance to ciprofloxacin at all growth rates. The mutant lacking TolC, which is a component of many E. coli efflux pumps, showed the same sensitivity to ciprofloxacin as the parent. The absence of porin OmpF slowed down the entry of ciprofloxacin into cells, prolonged growth and shifted the optimal bactericidal concentration towards higher values. Deficiency of RecA, a regulator of the SOS response, dramatically altered the late phase of the SOS response (SOS-dependent cell death), preventing respiratory inhibition and a drop in membrane potential. The recA mutation inverted GSH fluxes across the membrane and abolished ciprofloxacin-induced H2S production. All studied mutants showed an inverse linear relationship between logCFU ml-1 and the specific growth rate. Mutations shifted the plot of this dependence relative to the parental strain according to their significance for ciprofloxacin tolerance. The crucial role of the SOS system is confirmed by dramatic shift down of this plot in the recA mutant.

Experimental Study on Atomization Characteristics of Gas-Liquid Two-Phase Flow Nozzle and Its Dust Removal Effect.

An experimental study on the flow rate and atomization characteristics of a new gas–liquid two-phase flow nozzle was carried out to use high-concentration respirable dust in the workplace of high-efficiency sedimentation coal production based on the gas–liquid two-phase flow nozzle technology. The simulation roadway of dust fall in large coal mines was constructed, and the respirable rock dust produced by fully mechanized mining surfaces was chosen as the research object. The effects of humidity on the capture effect of respirable rock dust were analyzed in the experimental study. The results demonstrated that: (1) the distribution range of the particle size of fogdrops declines with the reduction in fogdrops D50, D[3,2] and D[4,3], which are produced by gas–liquid two-phase flow nozzles. (2) The initial ambient humidity in the simulated roadway was 64.8% RH. After the gas–liquid two-phase flow spray was started, the ambient humidity was elevated by 23.2 to 23.5% RH within 840s and tended to be stable and no longer grew after reaching 88.0–88.3% RH. The initial growth rate of the ambient humidity in the simulated roadway was high, and then was gradually slowed down. (3) Humidity is an important factor influencing the collection of respirable dust. The humidity at 10.0 m leeward of the dust-producing point was increased by 19.6% RH, and the sedimentation rate of respirable dust was increased by 6.73%; the two growth rates were 13.1% RH and 9.90% at 20.0 m; 16.4% RH and 15.42% at 30.0 m; 18.4% RH and 11.20% at 40.0 m. In practical applications of the gas–liquid two-phase flow nozzle in coal mining activities, attention shall be paid to not only the influences of its atomization characteristics on the capture effect of respirable dust but also the influences of the flow rate of the nozzle on the humidity of the working surface. Appropriate gas and water supply pressures shall be chosen according to the space and respirable dust concentration on the working surface to realize a better dust removal effect.

Estimation of optimal timing of early selection based on time trends of genetic parameters in Abies sachalinensis

Abstract Early selection is an imperative in ongoing forest tree breeding. This study estimated the optimal timing of early selection in Abies sachalinensis (F. Schmidt) Mast. based on time trends of genetic parameters obtained from two test sites. Tree height (Ht ) at 5, 10 (11), 15, 20, 30, and 40 years of age and diameter at breast height (DBH) at 20, 30, and 40 years of age were analyzed. The efficiency of early selection per year (E) for performing early indirect selection relative to performing direct selection at the earliest rotation age (40 years of age) was estimated based on narrow-sense heritability (h 2) and age–age genetic correlation (r). The h 2 of Ht peaked at 10 or 15 years of age (0.52–0.71), and that of DBH was the highest at 20 years of age (0.19 or 0.22). The age–age genetic correlation between tree heights or between tree height and DBH at different ages decreased with increasing differences between ages (regression coefficients were −0.011 and −0.007, respectively). The E values were highest at 10 or 15 years of age (0.84-1.74 and 1.42-2.24 for Ht and Ht -DBH, respectively), indicating the optimum selection timing. In Japapnese forestry, the initial growth rate is considered important for reducing weeding costs. Selection at 10 or 15 years of age had more than in >65 % indirect genetic gain relative to the direct genetic gain at 5 years of age; thus, selection at 10-15 years of age is appropriate considering the initial and mature phases of tree growth.

Stage duration distributions and intraspecific competition: a review of continuous stage-structured models.

Stage structured models, by grouping individuals with similar demographic characteristics together, have proven useful in describing population dynamics. This manuscript starts from reviewing two widely used modeling frameworks that are in the form of integral equations and age-structured partial differential equations. Both modeling frameworks can be reduced to the same differential equation structures with/without time delays by applying Dirac and gamma distributions for the stage durations. Each framework has its advantages and inherent limitations. The net reproduction number and initial growth rate can be easily defined from the integral equation. However, it becomes challenging to integrate the density-dependent regulations on the stage distribution and survival probabilities in an integral equation, which may be suitably incorporated into partial differential equations. Further recent modeling studies, in particular those by Stephen A. Gourley and collaborators, are reviewed under the conditions of the stage duration distribution and survival probability being regulated by population density.

Characterization and Evolution of a Digital Economy Ecosystem Based on an Interspecies Competition Model

This paper provides an in‐depth study and analysis of the characterization of the digital economy ecosystem and the mechanism of eye‐flowering through the method of interspecies competition. The evolutionary game model of symbiotic decision‐making in the entrepreneurial ecosystem is constructed, the evolutionary process of symbiotic decision‐making of subjects is analyzed through mathematical derivation, and the symbiotic decision‐making process of subjects is simulated through computer simulation to answer how the subjects of the entrepreneurial ecosystem make symbiotic decisions and explore the mechanism of symbiotic formation of the entrepreneurial ecosystem. Then, based on the ecological perspective, the symbiotic evolution model of entrepreneurial ecosystem subjects is constructed from the subject level, the equilibrium point of the evolution of entrepreneurial ecosystem subjects, the stability conditions, and the relationship between the equilibrium point and the symbiosis model are analyzed, and the symbiotic evolution paths of entrepreneurial ecosystem subjects under different symbiosis modes, initial population size, maximum size, and natural growth rate are presented with simulation experiments, respectively. The main characteristics and manifestations of the dynamic evolution of the platform ecosystem are analyzed, and the key competitive factors that determine the dynamic evolution of the platform ecosystem are depicted. Then, according to the inherent characteristic laws of the platform ecosystem, the complex network approach is applied to construct a dynamic evolution model with originality and wide applicability for the change of bilateral user scale. Based on the dynamic evolution process, the relationship between model parameters and business performance is explored, and the trajectory of bilateral user size change over time and the range of parameters are derived by numerical calculation. Finally, using Monte Carlo simulation methods, the dynamic evolution model is used to predict the future operating conditions of platform enterprises, providing a valuation basis for investors to make investment decisions and helping platform managers to formulate business strategies.

Supporting Growth and Transpiration of Newly Planted Street Trees With Passive Irrigation Systems

AbstractSolutions that use stormwater runoff to rapidly establish tree canopy cover in cities have received significant attention. Passive irrigation systems that direct stormwater to trees have the potential to increase growth and transpiration and may limit drought stress. However, little data from the field demonstrates this, and we lack robust and reliable designs which achieve it. Here, we quantified growth and transpiration for trees: (a) in infiltration pits receiving stormwater, with a raised underdrain and internal water storage (drained), (b) next to infiltration pits receiving stormwater but without an underdrain and internal water storage (adjacent), and (c) planted in standard pits, not receiving stormwater (control). Trees in drained pits grew twice as fast as control trees in the first 2 years, but fast initial growth rates were not sustained in years three and four. Trees outgrowing the small infiltration pits, rather than a lack of water, was most likely responsible for growth rates slowing down. Despite this, rapid initial growth for trees in drained pits meant trees were larger by year three and transpired more than twice as much (5.1 L d−1) as trees adjacent to pits (2.4 L d−1) or control trees (2.3 L d−1). No trees showed drought stress during the study. However, some trees planted adjacent to infiltration pits showed waterlogging stress, suggesting caution installing infiltration pits adjacent to establishing trees in fine‐textured soils. Overall, our results suggest passive irrigation systems can substantially increase initial tree growth, thereby facilitating greater cooling and runoff reduction through increased transpiration.

COVID-19 transmission risk factors

ABSTRACT We analyze risk factors correlated with the initial transmission growth rate of the recent COVID-19 pandemic in different countries. The number of cases follows in its early stages an almost exponential expansion; we chose as a starting point in each country the first day with 30 cases and we fitted for 12 days, capturing thus the early exponential growth. We looked then for linear correlations of the exponents with other variables, for a sample of 126 countries. We find a positive correlation, i.e. faster spread of COVID-19, with high confidence level with the following variables, with respective -value: low Temperature (), high ratio of old vs. working-age people (), life expectancy (), number of international tourists (), earlier epidemic starting date (), high level of physical contact in greeting habits (), lung cancer prevalence (), obesity in males (), share of population in urban areas (), cancer prevalence (), alcohol consumption (), daily smoking prevalence (), and UV index (, 73 countries). We also find a correlation with low Vitamin D serum levels (), but on a smaller sample, countries, to be confirmed on a larger sample. There is highly significant correlation also with blood types: positive correlation with types RH- () and A+ (), negative correlation with B+ (). We also find positive correlation with moderate confidence level (-value of ) with: CO2/SO emissions, type-1 diabetes in children, low vaccination coverage for Tuberculosis (BCG). Several of the above variables are correlated with each other, and so they are likely to have common interpretations. We thus performed a Principal Component Analysis, to find the significant independent linear combinations of such variables. The variables with loadings of at least 0.3 on the significant PCA are: greeting habits, urbanization, epidemic starting date, number of international tourists, temperature, lung cancer, smoking, and obesity in males. We also analyzed the possible existence of a bias: countries with low GDP-per capita might have less intense testing, and we discuss correlation with the above variables.

Unraveling Fe(II)-Oxidizing Mechanisms in a Facultative Fe(II) Oxidizer, Sideroxydans lithotrophicus Strain ES-1, via Culturing, Transcriptomics, and Reverse Transcription-Quantitative PCR.

ABSTRACTSideroxydans lithotrophicus ES-1 grows autotrophically either by Fe(II) oxidation or by thiosulfate oxidation, in contrast to most other isolates of neutrophilic Fe(II)-oxidizing bacteria (FeOB). This provides a unique opportunity to explore the physiology of a facultative FeOB and constrain the genes specific to Fe(II) oxidation. We compared the growth of S. lithotrophicus ES-1 on Fe(II), thiosulfate, and both substrates together. While initial growth rates were similar, thiosulfate-grown cultures had higher yield with or without Fe(II) present, which may give ES-1 an advantage over obligate FeOB. To investigate the Fe(II) and S oxidation pathways, we conducted transcriptomics experiments, validated with reverse transcription-quantitative PCR (RT-qPCR). We explored the long-term gene expression response at different growth phases (over days to a week) and expression changes during a short-term switch from thiosulfate to Fe(II) (90 min). The dsr and sox sulfur oxidation genes were upregulated in thiosulfate cultures. The Fe(II) oxidase gene cyc2 was among the top expressed genes during both Fe(II) and thiosulfate oxidation, and addition of Fe(II) to thiosulfate-grown cells caused an increase in cyc2 expression. These results support the role of Cyc2 as the Fe(II) oxidase and suggest that ES-1 maintains readiness to oxidize Fe(II), even in the absence of Fe(II). We used gene expression profiles to further constrain the ES-1 Fe(II) oxidation pathway. Notably, among the most highly upregulated genes during Fe(II) oxidation were genes for alternative complex III, reverse electron transport, and carbon fixation. This implies a direct connection between Fe(II) oxidation and carbon fixation, suggesting that CO2 is an important electron sink for Fe(II) oxidation.IMPORTANCE Neutrophilic FeOB are increasingly observed in various environments, but knowledge of their ecophysiology and Fe(II) oxidation mechanisms is still relatively limited. Sideroxydans isolates are widely observed in aquifers, wetlands, and sediments, and genome analysis suggests metabolic flexibility contributes to their success. The type strain ES-1 is unusual among neutrophilic FeOB isolates, as it can grow on either Fe(II) or a non-Fe(II) substrate, thiosulfate. Almost all our knowledge of neutrophilic Fe(II) oxidation pathways comes from genome analyses, with some work on metatranscriptomes. This study used culture-based experiments to test the genes specific to Fe(II) oxidation in a facultative FeOB and refine our model of the Fe(II) oxidation pathway. We gained insight into how facultative FeOB like ES-1 connect Fe, S, and C biogeochemical cycling in the environment and suggest a multigene indicator would improve understanding of Fe(II) oxidation activity in environments with facultative FeOB.

The stochastic dynamics of early epidemics: probability of establishment, initial growth rate, and infection cluster size at first detection.

Emerging epidemics and local infection clusters are initially prone to stochastic effects that can substantially impact the early epidemic trajectory. While numerous studies are devoted to the deterministic regime of an established epidemic, mathematical descriptions of the initial phase of epidemic growth are comparatively rarer. Here, we review existing mathematical results on the size of the epidemic over time, and derive new results to elucidate the early dynamics of an infection cluster started by a single infected individual. We show that the initial growth of epidemics that eventually take off is accelerated by stochasticity. As an application, we compute the distribution of the first detection time of an infected individual in an infection cluster depending on testing effort, and estimate that the SARS-CoV-2 variant of concern Alpha detected in September 2020 first appeared in the UK early August 2020. We also compute a minimal testing frequency to detect clusters before they exceed a given threshold size. These results improve our theoretical understanding of early epidemics and will be useful for the study and control of local infectious disease clusters.

Invasions of ecological communities: Hints of impacts in the invader's growth rate

Abstract Theory in ecology and evolution often relies on the analysis of invasion processes, and general approaches exist to understand the early stages of an invasion. However, predicting the long‐term transformations of communities following an invasion remains a challenging endeavour. We propose a general analytical method that uses both resident community and invader dynamical features to predict whether an invasion causes large long‐term impacts on the invaded community. This approach reveals a direction in which classic invasion analysis, based on initial invasion growth rate, can be extended. Indeed, we explain how the density dependence of invasion growth, if properly defined, synthetically encodes the long‐term biotic transformations caused by an invasion, and therefore predicts its ultimate outcome. This approach further clarifies how the density dependence of the invasion growth rate is as much a property of the invading population as it is one of the invaded community. Our theory applies to any stable community model, and directs us towards new questions that may enrich the toolset of invasion analysis, and suggests that indirect interactions and dynamical stability are key determinants of invasion outcomes.

ANALYSIS OF DIESEL SPILL BIOREMEDIATION BY BACTERIAL ISOLATES IN BATCH CULTURE USING MONOD AND HALDANE KINETIC MODEL

The unintended oil spills from oil tankers, transportation and storage facilities, leads to petroleum hydrocarbon pollution that causes adverse effects on the air, water and soil environment. Bioremediation using indigenous microorganisms has become a promising tool for effective mineralization of toxic contaminants into harmless end products. In this study, bioremediation of petroleum contaminated soil was carried out in a batch scale using Staphylococcus, Pseudomonas, Micrococcus, Escherichia, Acinetobacter, Bacillus, Corynebacterium, Salmonella and Klebsiella species, all isolated from petroleum hydrocarbon contaminated soil. The effect of 1 to 10% v/v diesel concentrations on the growth and biodegradation rate of all selected nine isolates was studied and specific growth rates (μh -1) were calculated. The initial rate of growth and biodegradation of nine isolates increased correspondingly with the diesel concentration up to 5% (v/v), but further increase in diesel concentration resulted in a slight decrease in the rate of biodegradation. Diesel is known to be an inhibitory substrate. Both Monod and Haldane kinetic models were useful for the evaluation of the growth kinetic parameters (μmax, Ks, Ki). It was found that the Monod model was able to express the growth parameters up to 5% v/v diesel. However, Haldane model effortlessly fitted with the experimental data for increase in the diesel i.e. over 6 % v/v diesel. These results showed that the diesel oil degraders were able to utilize a considerably high concentration of diesel and could be very effective in diesel biodegradation for restoration of contaminated sites.

It doesn't always pay to be fit: success landscapes.

Landscapes play an important role in many areas of biology, in which biological lives are deeply entangled. Here we discuss a form of landscape in evolutionary biology which takes into account (1) initial growth rates, (2) mutation rates, (3) resource consumption by organisms, and (4) cyclic changes in the resources with time. The long-term equilibrium number of surviving organisms as a function of these four parameters forms what we call a success landscape, a landscape we would claim is qualitatively different from fitness landscapes which commonly do not include mutations or resource consumption/changes in mapping genomes to the final number of survivors. Although our analysis is purely theoretical, we believe the results have possibly strong connections to how we might treat diseases such as cancer in the future with a deeper understanding of the interplay between resource degradation, mutation, and uncontrolled cell growth.

Epistasis, aneuploidy, and functional mutations underlie evolution of resistance to induced microtubule depolymerization.

Cells with blocked microtubule polymerization are delayed in mitosis, but eventually manage to proliferate despite substantial chromosome missegregation. While several studies have analyzed the first cell division after microtubule depolymerization, we have asked how cells cope long-term with microtubule impairment. We allowed 24 clonal populations of yeast cells with beta-tubulin mutations preventing proper microtubule polymerization, to evolve for ˜150 generations. At the end of the laboratory evolution experiment, cells had regained the ability to form microtubules and were less sensitive to microtubule-depolymerizing drugs. Whole-genome sequencing identified recurrently mutated genes, in particular for tubulins and kinesins, as well as pervasive duplication of chromosome VIII. Recreating these mutations and chromosome VIII disomy prior to evolution confirmed that they allow cells to compensate for the original mutation in beta-tubulin. Most of the identified mutations did not abolish function, but rather restored microtubule functionality. Analysis of the temporal order of resistance development in independent populations repeatedly revealed the same series of events: disomy of chromosome VIII followed by a single additional adaptive mutation in either tubulins or kinesins. Since tubulins are highly conserved among eukaryotes, our results have implications for understanding resistance to microtubule-targeting drugs widely used in cancer therapy.

Development of biotesting method for water quality control

The article presents a method for biotesting natural waters based on the rate of growth of nasturtium pollen tubes on a nutrient medium prepared using tested water samples; pollen tubes of flowering plants are used as an indicator; the waters of a large water-transport artery Moscow Canal and the Klyazminskoye Reservoir are subject to biotesting. For the research, pollen of nasturtium plants, which has convenient for observation sizes of pollen grains and a high initial growth rate of pollen tubes, was selected. Within the process of research, the factors influencing the development of pollen tubes were identified and optimal conditions for germination were proposed. As well, the article attempts to indicate the state of water in the Moscow Canal during the season using the proposed method.

A rumor spreading pairwise model on weighted networks

The heterogeneity in edge weights plays a crucial role in the spread of a rumor on networks. To investigate the effects of weight distribution on a rumor spreading, we employ an ISR pairwise model on weighted regular random networks in this paper. The basic reproductive ratio of this model is derived, and it indicates that the heterogeneity in transmission rate leads to a fall in the basic reproductive ratio when the average transmission rate is fixed. Besides, by assuming that the transmission rate is a linear function of the edge weight, numerical simulation results of the model on networks with a bimodal weight distribution show that weight heterogeneity has a complex impact on the dynamics of a rumor. When we fix the proportions of two weights but vary their values to keep a constant average weight, increasing the heterogeneity in weight distribution slows down the initial growth rate, the final size and the maximum influence of a rumor, but increases the duration for rumor spreading. However, if we change both the values and proportions of two weights, only the mean and variance of the weight distribution are not able to provide sufficient information to predict the dynamics of a rumor. Moreover, we get similar simulation results in the case of nonlinear transmission rate.

The growth rates of solitary gallbladder polyps compared to multi-polyps: A quantitative analysis.

Several studies suggest solitary gallbladder polyps (GBPs) have an increased malignancy risk compared to multi-polyps. Furthermore, some malignant GBPs possessed faster growth rates compared to benign GBPs. To our knowledge, no study has established a relationship between GBP number and growth rates. Hence, this study aims to: (i) determine whether there is a statistical significance in growth rates between solitary GBPs versus multi-polyps; (ii) determine, in a four-year period, the proportion of GBPs in this study's total cohort that exhibit growth compared to previous studies. A retrospective, quantitative, cohort study was implemented utilising 100 consecutive patient records from three private radiology clinics. These were assessed against the eligibility criteria and allocated into the solitary or multi-polyp study group, depending on number of GBPs detected on initial and follow-up ultrasound examinations conducted 6-48 months later. Patient age, GBP sizes, time interval between initial and follow-up ultrasound examinations and GBP growth rates were compared between the study groups utilising Student's t tests. No statistically significant difference was found between the study groups according to gender, age, GBP size and time between ultrasound examinations. Furthermore, there was no statistically significant difference between the growth rates of solitary and multi-polyp groups (P = 0.77). Most GBPs [92/100 (92%)] grew <2 mm in maximal diameter, while 8/100 (8%) of GBPs grew ≥2 mm in maximal diameter at follow-up. The large majority of GBPs maintained size stability at follow-up. On average, solitary GBPs did not grow faster than multi-polyps, although further research is recommended to reinforce this.

Interactive Metal Mixture Toxicity to Daphnia magna Populations as an Emergent Property in a Dynamic Energy Budget Individual-Based Model.

Environmental risk assessment of metal mixtures is challenging due to the large number of possible mixtures and interactions. Mixture toxicity data cannot realistically be generated for all relevant scenarios. Therefore, methods for prediction of mixture toxicity from single-metal toxicity data are needed. We tested how well toxicity of Cu-Ni-Zn mixtures to Daphnia magna populations can be predicted based on the Dynamic Energy Budget theory with an individual-based model (DEB-IBM), assuming non-interactivity of metals on the physiological level. We exposed D. magna populations to Cu, Ni, and Zn and their mixture at a fixed concentration ratio. We calibrated the DEB-IBM with single-metal data and generated blind predictions of mixture toxicity (population size over time), with account for uncertainty. We compared the predictive performance of the DEB-IBM with respect to mixture effects on population density and population growth rates with that of two reference models applied on the population level, independent action and concentration addition. Our inferred physiological modes of action (pMoA) differed from literature-reported pMoAs, raising the question of whether this is a result of different model selection approaches, intraspecific variability, or whether different pMoAs might actually drive toxicity in a population context. Observed mixture effects were concentration- and endpoint-dependent. The independent action was overall more accurate than the concentration addition but concentration addition-predicted effects on population growth rate were slightly better. The DEB-IBM most accurately predicted effects on 6-week density, including antagonistic effects at high concentrations, which emerged from non-interactivity at the physiological level. Mixture effects on initial population growth rate appear to be more difficult to predict. To explain why model accuracy is endpoint-dependent, relationships between individual-level and population-level endpoints should be illuminated. Environ Toxicol Chem 2021;40:3034-3048. © 2021 SETAC.

Effects of nitrogen regulation and strip intercropping on faba bean biomass, nitrogen accumulation and distribution, and interspecific interactions

AbstractEffects of nitrogen fertilization on the accumulation and distribution of biomass and plant nitrogen content in intercropped faba beans, together with its impact on the interspecific interactions between faba bean and wheat has not been well studied. Here, we have used a logistic model to analyze the cropping systems (i.e., monocropped faba bean, monocropped wheat, and faba bean intercropped with wheat) by evaluating the effects of different levels of nitrogen application on the dynamic changes in biomass and nitrogen accumulation, along with the interspecific interaction. Using monocropped and intercropped faba beans in field experiments spanning two years, we found that nitrogen application increased both monocropped and intercropped faba bean yields. The yield of intercropped faba beans was greatest at the lower nitrogen input for two consecutive years. Nitrogen application increased the biomass and nitrogen accumulation in both monocropped and intercropped faba beans. The simulation parameters that increased were maximum nitrogen accumulation (A') and maximum accumulation rate (R'max) while the initial cumulative rate (r') decreased. Compared with monocropping, intercropped faba bean–wheat showed increased yield and biomass accumulation, along with a significantly increased initial growth rate (r) and a maximum instantaneous growth rate (Rmax). Intercropping reduced stem and leaf biomass and the nitrogen distribution ratio while increasing the pod content. In the early intercropped faba bean growth stage, there was no competition for nutrients or any kind of yield advantage, while in the later stages, the nutrient competitiveness of intercropping was stronger than the intraspecific competition, showing the advantages of intercropping on biomass and yield (i.e., relative crowding coefficient [K] &gt;1, relative interspecific competitiveness [RC] &gt;0, and relative competition intensity [RCI] &lt;0). In summary, nitrogen application of 45 kg ha–1 could be the desired amount that maximizes the nutrient competition and interspecific advantages in the middle and late stages of faba bean growth when intercropped, thus contributing to the yield.