Growth Rate Trajectories Research Articles

A Preliminary Study of Anti‐TNFα Therapy for Symptomatic Dolichoectatic Vertebrobasilar Aneurysms

Background Dolichoectatic vertebrobasilar aneurysms (DVBAs) carry high morbidity, and treatment options are limited. The tumor necrosis factor α signaling cascade is implicated in DVBA growth and rupture, but the role of anti–tumor necrosis factor α therapy in DVBA has not been studied. Methods A retrospective, case–control study of DVBA at a single institution was performed. Two patients with DVBA were treated with infliximab (tumor necrosis factor α inhibitor) as part of routine therapy for rheumatoid arthritis. Three additional patients diagnosed with DVBA were studied as a control group. Routine brain magnetic resonance imaging/magnetic resonance angiography were measured by 2 blinded neuroradiologists to assess DVBA growth. Baseline comorbidities and clinical outcomes were assessed by chart review. Results The groups were similar with respect to baseline characteristics, and all patients were symptomatic at the time of DVBA diagnosis. One patient who started infliximab during the study period showed a reversal in DVBA growth rate trajectory, with a relative decrease in growth rate by 37% (0.49–0.18 mm 2 /day). Mean interval DVBA growth rates were lower during infliximab therapy than during noninfliximab observation intervals (0.13 versus 0.50 mm 2 /day; P = 0.09). Two patients in the control group died during the study period and 1 had a poor outcome (modified Rankin scale = 4). Both patients in the infliximab group had unchanged functional status (modified Rankin scale = 1) and no adverse events related to infliximab. Conclusion This study presents the first investigation of anti–tumor necrosis factor α therapy for DVBA. Infliximab was associated with low and decreasing DVBA growth trajectories with no treatment‐related adverse events. The effect of infliximab on clinical outcomes remains uncertain.

A repeatable CT protocol for quantifying caudal vena cava growth in medium and large breed dogs.

Developmental malformations can cause stunted or abnormal growth and clinical disease in dogs. In humans, measurements of the inferior vena cava are used as methods for detecting abnormal growth trajectories. The objectives of this retrospective, multicenter, analytical, cross-sectional study were to develop a repeatable protocol to measure the caudal vena cava (CVC) and generate growth curves in medium and large-breed dogs during development. Contrast-enhanced CT DICOM images from 438 normal dogs, aged from 1 to 18 months, from five specific breeds were included. A "best guess" measurement protocol was created. Dogs were stratified into medium or large breed groups based on growth rate trajectories. Linear regression models and logarithmic trend lines were used to evaluate the CVC growth over time. The CVC measurements were analyzed from four anatomical regions: thorax, diaphragm, intra-hepatic, and renal. The thoracic segment produced the most repeatable measurements with the highest explanatory power. The CVC thoracic circumference ranged from 2.5 to 4.9cm from 1 to 18 months of age. Medium and large breeds had similar CVC growth trajectories, with comparable estimated marginal means, however medium dogs reached 80% of predicted final CVC size approximately 4weeks earlier than large breed dogs. This new protocol provides a standardized technique for evaluation of the CVC circumference over time using contrast-enhanced CT and is most repeatable when taken at the thoracic level. This approach could be adapted for other vessels to predict their growth trajectories, generating healthy reference population data for comparison against patients with vascular anomalies.

OPT-ing out: Root-shoot dynamics are caused by local resource capture and biomass allocation, not optimal partitioning.

Combining plant growth analysis with a simple model of local resource capture and biomass allocation applied to exemplary experimental data, showed that dynamic changes in allocation to roots when nutrients are scarce is caused by disparities in growth rates between roots and shoots. Whole-plant growth rates also change but are not caused by an adaptive allocation response. Allocation and whole-plant growth rate are interdependent, not independent, traits. Following a switch in nutrient availability or partial biomass removal, convergence of allocation and growth rate trajectories does not reflect goal-seeking behaviour, but the constraints imposed by finite resource availability. Optimal root-shoot allocations are unnecessary to maximise whole-plant growth rate. Similar growth rates are attainable with different allocations. Changes in allocation cannot maintain or restore a superior whole-plant growth rate. Roots and shoots do not have to be tightly coordinated but can operate semiautonomously, as their modular construction permits. These findings question the plausibility of the prevailing general explanation of plants'root-shoot allocation responses, 'optimal partitioning theory' (OPT). Local allocation models, not OPT, explain the origins of variability in root-shoot trade-offs in individuals, the allocation of biomass at global and ecosystem scalesand inform selection for allocation plasticity in crop breeding.

Collective Reactions to Epidemic Threat: Attachment and Cultural Orientations Predict Early COVID-19 Infection and Mortality Rates and Trajectories

Hypotheses on culture-level attachment and individualism/collectivism relationships with COVID-19 infection and death rates during a period at the beginning of the epidemic were tested in data from 53 countries and 50 U.S. states. Results from multilevel growth curve analyses showed group-average anxious attachment predicted a lower initial number of cases and deaths cross-culturally and in the United States, while avoidant attachment predicted a higher initial number of COVID-19 infections in the United States and a higher initial number of deaths in both studies. Yet, during this period, culture-level anxious attachment was associated with a higher growth rate of infections and deaths, while a lower growth rate of infections and deaths was observed in countries and U.S. states with higher individualism and avoidance. The research provides new insights into attachment and culture relationships and points to different mechanisms that may explain initial and growth rate trajectories at the beginning of the epidemic.

Model predictive control paradigms for fish growth reference tracking in precision aquaculture

In precision aquaculture, the primary goal is to maximize biomass production while minimizing production costs. This objective can be achieved by optimizing factors that have a strong influence on fish growth, such as feeding rate, temperature, and dissolved oxygen. This paper provides a comparative study of four model predictive control (MPC) strategies for fish growth reference tracking under a representative bioenergetic growth model in precision aquaculture. We propose to evaluate four candidate MPC formulations for fish growth reference tracking based on the receding horizon. The first MPC formulation tracks a desired fish growth trajectory while penalizing the feed ration, temperature, and dissolved oxygen. The second MPC optimization strategy directly optimizes the feed conversion ratio (FCR), which is the ratio between food quantity and fish weight gain at each sampling time. This FCR-like optimization strategy minimizes the feed while maximizing the predicted growth state’s deviation from the given reference growth trajectory. The third MPC formulation includes a tradeoff between the growth rate trajectory tracking, the dynamic energy, and food cost. The last MPC formulation aims to maximize the fish growth rate while minimizing the costs. Numerical simulations that integrate a realistic bioenergetic fish growth model of Nile tilapia (Oreochromis niloticus) are illustrated to examine the comparative performance of the four proposed optimal control strategies. A sensitivity analysis is conducted to study the robustness of these MPC strategies with respect to the effect of the prediction horizon, the regularization term, and the additive input disturbances to the process. The obtained results show great potential and flexibility to meet the fish farmers’ needs depending on the type of fish, selling price, culture duration, and feed cost.

Chemical cues of an invasive turtle reduce development time and size at metamorphosis in the common frog

In aquatic systems, chemical cues are one of the major sources of information through which animals can assess local predation risk. Non-native red-eared sliders (Trachemys scripta elegans) have the potential to disrupt aquatic ecosystems in Central Europe because of their superior competitive abilities and omnivorous diets. In this study, we examined whether continuous predator-borne cues are tied to changes in the developmental rates, growth rates and sizes at metamorphosis of common frog tadpoles (Rana temporaria). Our results show rather rarely documented types of amphibian prey responses to caged predators. The presence of turtles shortened the time at metamorphosis of tadpoles from 110 ± 11.7 days to 93 ± 13.0 days (mean ± S.D.). The first metamorphosed individuals were recorded on the 65th day and on the 80th day from hatching in the predator treatment and in the control group, respectively. The froglets were significantly smaller (12.8 ± 0.99 mm) in the presence of the predator than in the control treatment (15.2 ± 1.27 mm). The growth rate trajectories were similar between the predator treatment and the control. Thus, predator-induced tadpole defences were evident in higher developmental rates and smaller sizes at metamorphosis without significant changes in growth.

Optimization of Simple Batch Crystallization Systems Considering Crystal Shape and Nucleation

Optimal control theory (OCT) is applied to derive nearly analytical solution to single- and multiobjective dynamic optimization problems for a two-dimensional batch crystallization system. Objective functions based on the product crystal aspect ratio, number of nuclei, and nucleated volume are studied. It is shown that applying a constant growth rate trajectory can minimize the product aspect ratio while early- and late-growth trajectories can minimize the nucleated number and volume, respectively. It is also found that there exists an optimal target aspect ratio between the maximum and minimum feasible values which permits a solution with the best single objective values for case of minimizing nucleated number or nucleated volume. Pareto-optimal fronts (PFs) for nucleated number and volume under different target aspect ratio are also plotted to understand the trade-off between objectives. The result suggests that the trade-off is stronger when the value of the aspect ratio constraint is near the midpoint of the feasible interval.

Pareto-Optimal Fronts for Simple Crystallization Systems Using Pontryagin’s Minimum Principle

Pontryagin’s minimum principle is applied to determine Pareto-optimal fronts for multiobjective optimization of seeded batch crystallization processes. For cases with two objectives, when both objectives are based on properties of the higher moments or lower moments of the crystal size distribution (for example, weight mean size and weight mean coefficient of variation), there is relatively little difference among the trajectories along the optimal front. By contrast, when one objective is based on the lower moments (e.g., minimizing the number of nuclei) and another objective is based on the higher moments (e.g., minimizing the nucleated mass), the difference in the shape of the trajectories along the front is more pronounced. In this case, a constant growth rate trajectory may represent a reasonable compromise between the competing objectives.

Associations between placental CpG methylation of metastable epialleles and childhood body mass index across ages one, two and ten in the Extremely Low Gestational Age Newborns (ELGAN) cohort

ABSTRACTThe Developmental Origins of Health and Disease (DOHaD) hypothesis posits that in utero and early life conditions can disrupt normal fetal development and program susceptibility to later-life disease. Metastable epialleles are genomic loci in which CpG methylation patterning is responsive to maternal diet and conserved across time and tissues. Thus, these sites could serve as ‘signatures’ of gestational environment conditions. Here, we sought to determine if methylation of metastable epialleles was associated with changes in childhood body mass index (BMI) z-scores across ages one, two and ten in the Extremely Low Gestational Age Newborns (ELGAN) cohort. CpG methylation of 250 probes (corresponding to 111 genes) within metastable epiallele regions was measured in placental tissue. Linear mixed effects models were fit to evaluate the overall and sex-stratified associations between methylation and changes in BMI z-score over time. In total, 26 probes were associated (p < 0.05) with changes in BMI z-score overall, including probes within Mesoderm Specific Transcript (MEST) and Histone Deacetylase 4 (HDAC4), which have previously been associated with childhood obesity and adipogenesis. Sex-stratified analyses revealed a significant association, after adjusting for multiple comparisons (q < 0.05), within female placentas for one probe annotated to the imprinted gene PLAG1 Like Zinc Finger 1 (PLAGL1). These findings suggest epigenetic marks may be involved in programming susceptibility to obesity in utero and highlight the potential to use placental tissues in predicting growth rate trajectories among premature infants.

Factors Affecting Bacterial Growth Constants

Bacterial population growth can largely, if not completely, be characterized by three fundamental growth constants: (1) Maximum Growth Rate, (2) Lag Time, and (3) Final Optical Density (OD). Due to their ability to capture growth dynamics, these fundamental growth constants have traditionally also been used as measurements of fitness. However, these metrics can be incredibly sensitive to the experimental choices in seemingly unintuitive ways. We quantified these fundamental growth constants in different growth conditions for B. subtilis and E. coli and extract the maximum growth rate, lag time, and final OD. Growing E. coli from different dilutions, we observe that the growth rate trajectory taken is dilution dependent. Moreover, the maximum growth rate is also initial OD or dilution dependent. Inoculating at a lower initial density allows the bacterial culture to have a higher maximum growth rate. In our model, simple nutrient depletion is able to recapitulate these experimental findings qualitatively. In addition to the initial inoculum size affecting the maximum growth rate, other factors such as the variable presence of glycerol can affect the robust measurement of lag. We observed that the presence of glycerol in day 1 of growth affects the lag times in day 2 for B. subtilis 168 dramatically. Traditionally this might not have been a problem in B. subtilis because most labs streak out cultures and start liquid culture from a colony, or inoculate into large volumes. However, for an experimental method that is tractable to working with libraries and high throughput measurements these solutions aren’t possible.

Flame Describing Function analysis of spinning and standing modes in an annular combustor and comparison with experiments

This article reports a numerical analysis of combustion instabilities coupled by a spinning mode or a standing mode in an annular combustor. The method combines an iterative algorithm involving a Helmholtz solver with the Flame Describing Function (FDF) framework. This is applied to azimuthal acoustic coupling with combustion dynamics and is used to perform a weakly nonlinear stability analysis yielding the system response trajectory in the frequency-growth rate plane until a limit cycle condition is reached. Two scenarios for mode type selection are tentatively proposed. The first is based on an analysis of the frequency growth rate trajectories of the system for different initial solutions. The second considers the stability of the solutions at limit cycle. It is concluded that a criterion combining the stability analysis at the limit cycle with the trajectory analysis might best define the mode type at the limit cycle. Simulations are compared with experiments carried out on the MICCA test facility equipped with 16 matrix burners. Each burner response is represented by means of a global FDF and it is considered that the spacing between burners is such that coupling with the mode takes place without mutual interactions between adjacent burning regions. Depending on the nature of the mode being considered, two hypotheses are made for the FDFs of the burners. When instabilities are coupled by a spinning mode, each burner features the same velocity fluctuation level implying that the complex FDF values are the same for all burners. In case of a standing mode, the sixteen burners feature different velocity fluctuation amplitudes depending on their relative position with respect to the pressure nodal line. Simulations retrieve the spinning or standing nature of the self-sustained mode that were identified in the experiments both in the plenum and in the combustion chamber. The frequency and amplitude of velocity fluctuations predicted at limit cycle are used to reconstruct time resolved pressure fluctuations in the plenum and chamber and heat release rate fluctuations at two locations. For the pressure fluctuations, the analysis provides a suitable estimate of the limit cycle oscillation and suitably retrieves experimental data recorded in the MICCA setup and in particular reflects the difference in amplitude levels observed in these two cavities. Differences in measured and predicted amplitudes appear for the heat release rate fluctuations. Their amplitude is found to be directly linked to the rapid change in the FDF gain as the velocity fluctuation level reaches large amplitudes corresponding to the limit cycle, underlying the need of FDF information at high modulation amplitudes.

Predicting Compensatory Growth and Reproduction in Agricultural Weeds Using a Plant’s Growth Rate Trajectory: A Test with Defoliation of Abutilon theophrasti

Predicting Compensatory Growth and Reproduction in Agricultural Weeds Using a Plant’s Growth Rate Trajectory: A Test with Defoliation of Abutilon theophrasti

Dynamic Models of Learning that Characterize Parent-Child Exchanges Predict Vocabulary Growth

Cumulative vocabulary models for infants and toddlers were developed from models of learning that predict trajectories associated with low, average, and high vocabulary growth rates (14 to 46 months). It was hypothesized that models derived from rates of learning mirror the type of exchanges provided to infants and toddlers by parents and caregivers. Slow and rapid growth models assume that rates of acquiring new vocabulary are proportional to (a) the child's current vocabulary and (b) the difference between maximum achievable vocabulary and the child's current vocabulary. These models produce (a) exponential growth and (b) bounded exponential growth, respectively. The third model (interactive engagement) results from the interaction of the two previous models and describes vocabulary growth trajectories with a logistic function. It describes the three empirical growth trajectories for average, slow, and rapid growth in the 14 to 46 month study, and for percentile growth rate trajectories of infants and toddlers between 16 and 30 months in a second study. A substantive outcome to the interactive engagement model is that it provided physically meaningful predictions when it was extended forward in time to 60 months and backward in time to 10 months. Although meaningful predictions of achievement can be made based on polynomial growth models (quadratic, and cubic) that fit empirical data, physically meaningful growth trajectories are obtained for logistic-model predictions beyond the empirical data. Excellent agreement between empirical data and model predictions provide evidence that additional birth through age three exchanges by parents and caregivers will narrow socioeconomic status gaps.

Multilevel Longitudinal Analysis of Sex Differences in Height Gain and Growth Rate Changes in Japanese School-Aged Children

BackgroundDetermining standard pubertal growth patterns using longitudinal anthropometric measures is important in growth assessment. We used an appropriate repeated-measurements method to identify height growth patterns in Japanese school-aged girls and boys.MethodsThe participants were children born during the period from 1991 through 1999 who had entered the first grade of elementary school in the Enzan district in Koshu City, Japan. This study was part of the Project Koshu cohort study. Height was measured annually in April from the first grade of elementary school (age, 6–7 years) to the third grade of junior middle school (age, 14–15 years). Height gain and growth rate trajectories in boys and girls were constructed using multilevel analysis.ResultsIn total, 1984 children (1036 boys and 948 girls) were included in this study. Height in boys and girls was similar at age 6.5 to 9.5 years. Girls subsequently grew faster and were taller than boys at age 10.5 to 11.5 years. Starting at age 12.5 years, male height caught up and exceeded female height. Height gain trajectories showed that annual height gain among girls increased slowly and peaked during age 9.5 to 11.5 years, while male height gains declined slightly at first and peaked at age 11.5 to 12.5 years. Sex differences in height gains were significant during the period from age 7.5 to 14.5 years (P < 0.0001). Growth rate and height gain trajectories were similar between sexes.ConclusionsSex differences in growth trajectory were significant, and female height gain peaked approximately 2 years earlier than male height gain.

Computer programs for modeling mammalian cell batch and fed-batch cultures using logistic equations

A MATLAB(®) toolbox was developed for applying the logistic modeling approach to mammalian cell batch and fed-batch cultures. The programs in the toolbox encompass sensitivity analyses and simulations of the logistic equations in addition to cell specific rate estimation. The toolbox was first used to generate time courses of the sensitivity equations for characterizing the relationship between the logistic variable and the model parameters. Subsequently, the toolbox was used to describe CHO cell data from batch and fed-batch mammalian cell cultures. Cell density, product, glucose, lactate, glutamine, and ammonia data were analyzed for the batch culture while fed-batch analysis included cell density and product concentration. In all instances, experimental data were well described by the logistic equations and the resulting specific rate profiles were representative of the underlying cell physiology. The 6-variable batch culture data set was also used to compare the logistic specific rates with those from polynomial fitting and discrete derivative methods. The polynomial specific rates grossly misrepresented cell behavior in the initial and final stages of culture while those based on discrete derivatives had high variability due to computational artifacts. The utility of logistic specific rates to guide process development activities was demonstrated using specific protein productivity versus growth rate trajectories for the 3 cultures examined in this study. Overall, the computer programs developed in this study enable rapid and robust analysis of data from mammalian cell batch and fed-batch cultures which can help process development and metabolic flux estimation.

A new framework and a simpler method for the development of batch crystallization recipes

AbstractWe use a new generalized dimensionless model of a seeded batch crystallization process to compare results from four crystal growth rate/concentration trajectories: a numerically‐computed optimal trajectory, a constant growth rate trajectory, a trajectory proposed by Mullin and Nyvlt [Chem Eng Sci. 1971;26:369–377] that can be calculated without a kinetic model, and a linear concentration‐time trajectory. Because the model is generalized and dimensionless it is not specific to any particular solute–solvent system. We show that if seed properties are good, all trajectories achieve a good result, whereas if seed properties are poor all trajectories achieve a poor result. If seed properties are intermediate, the linear concentration trajectory performs much worse than the other trajectories. On the basis of this, we conclude: (1) Linear trajectories and natural cooling trajectories are poor and should be avoided. When evaluating the benefit derived from an optimization of a temperature/saturation concentration trajectory, the appropriate benchmark should be the Mullin‐Nyvlt trajectory, which typically performs much better than the linear trajectory and can be calculated knowing only the mass of seeds at the beginning of the batch. (2) Changing seed properties is more likely to improve batch crystallizer performance than optimizing the growth/saturation concentration trajectory. (3) For rapid process development, the most reasonable approach is to use the Mullin‐Nyvlt trajectory and seek to improve process performance by adjusting seed properties. © 2010 American Institute of Chemical Engineers AIChE J, 2011

Nonlinear model-based control of the Czochralski process I: Motivation, modeling and feedback controller design

This paper presents a new approach for model-based control of the Czochralski process. The main idea is not to rely on a complex mathematical model of the overall process. Such a model usually suffers from many unknown parameters, boundary and initial conditions making the control system not robust. Instead, only those parts of the process are modeled the parameters of which are known with sufficient accuracy and the structure of which is sufficiently precise. From this model a nonlinear model-based controller is derived as the core of the proposed control system. It is used in combination with conventional PID controllers. Doing so, tracking of crystal diameter and growth rate trajectories is realized with a lot of model knowledge included in the control system. Thus, its performance is improved greatly. The usefulness of the approach is proven by several experimental results from growth of gallium-arsenide (GaAs) and indium-phosphide (InP) crystals.

Model Based Control of Large Scale Fed-Batch Baker's Yeast Fermentation

Two different control methods are applied to the technical scale (25 m 3 ) fed-batch baker's yeast fermentation. Feedback linearizing control design is used to manipulate the substrate feeding rate in order to maximize the biomass yield and minimizing the production of ethanol. Firstly, the specific growth rate controller is developed and applied to maintain the specific growth rate at specified trajectory. Secondly, the minimal ethanol controller is developed to maximize biomass productivity, by controlling specific growth rate just above the maximum oxidative growth rate by controlling ethanol concentration. The both controllers worked successfully and can be combined to follow required specific growth rate trajectory and respond successfully to disturbances in overflow fermentations such as Saccharomyces cerevisiae .

In This Issue/Abstract Thinking: Critical Periods

This month's editorial by Feldman (p. 233) discusses the potentially critical periods that occur during fetal development. The editorial highlights the interplay of the intrauterine environment, later temperamental characteristics, and the imposition of the environment on behavior, further detailed in three original articles appearing in this month's Journal. To begin, the Generation R study reported by Roza et al. (p. 265) examines the influence of intrauterine growth on temperamental difficulties in 3,792 infants. Growth size and growth rate trajectories were followed in utero, and infant temperamental dimensions were measured at 6 months of age. However, after correcting for maternal variations, temperamental difficulties were not found to be associated to the measured growth parameters, in contrast to several previous studies. Linking the role of temperament to risk of psychopathology, Rettew et al. (p. 274) measured temperament characteristics using latent profile analysis with respect to psychopathology and wellness in children. They define several temperamental phenotypes, thereby adding dimension to the influence of temperament on positive and negative outcomes.

New haemoglobin genotypes in Atlantic cod, Gadus morhua: Possible relation with growth

In a preliminary study, 121 individually tagged juvenile Atlantic cod (Gadus morhua) were classified according to their haemoglobin genotypes into four groups, i.e., two main haemoglobin genotypes [Hb-I(1/2), Hb-I(2/2)] and two sub-types [Hb-I(1/2b), Hb-I(2/2b)], and reared for 3 months at 10 degrees C, 13 degrees C and T-step (fish reared at 16 degrees C and then subsequently moved to 13 and later to 10 degrees C). Overall growth rates across temperatures were 10% and 19% higher in the Hb-I(2/2b), Hb-I(1/2b) sub-types compared to corresponding Hb-I(2/2) and Hb-I(1/2) main types, respectively. Individual growth rate trajectories varied between the genotypes at all temperatures studied. Our study indicates that under certain environmental conditions higher growth in the two sub-types compared to the main genotypes could be expected. This may indicate difference in other physiological characters not studied here, but seen in previous studies, i.e., oxygen affinity and competitive performance.