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Background: Growth references play a crucial role in the screening, evaluation, and surveillance of children, aiding in the early identification of the requirement for diverse growth-promoting interventions. Variations in human growth across distinct ethnic cohorts arise from genetic disparities, lifestyle variances, nutritional diversity, and diverse social and environmental contexts. Consequently, the selection of growth references markedly influences the prevalence of developmental disorders and nutritional imbalances in children. The study aims to assess the growth percentile of children in the north-east of Iran and establish population-specific reference charts for length, weight, and head circumference spanning from birth to 24 months. Methods: This cross-sectional population-based research conducted in the north-east of Iran, from 2016 to 2023. The Data extracted from the electronic health records of Mashhad University of Medical Sciences. All apparently healthy children aged from birth to 24 months who were measured at least once by health staff at the ages of birth,1,2,4,6,7,9,12,15,18,24 months were included. The target population of the study were 479,089 children (96.21%), encompassing 233,565 girls (48.75%) and 245,524 boys (51.25%). Gender-specific percentile curves for length, weight, and head circumference concerning age, as well as weight concerning length, were derived using the GAMLSS approach. Results: From the anthropometric information of 479,089 children (245,524 boys and 233,565 girls), growth charts were constructed. In comparison to the standard WHO chart, Iranian neonates displayed lower weight across all percentiles during the first month after birth, exhibited decreased head circumference at the 3rd percentile, and boys showed reduced length across all percentiles. After this age, Iranian children demonstrated increased weight, length, and head circumference. Conclusions: This research introduces the inaugural large-scale endeavor for indigenous reference charts. Through the noted distinctions from the international reference, the utilization of this novel resource offers the potential to enhance the surveillance of children's growth within the area. Moreover, by accurately assessing growth anomalies such as underweight, stunting, and wasting, it expands the domain of impactful policies in this sphere. Simultaneously, it enables the exploration of the secular trend of children's growth in the forthcoming years. [ABSTRACT FROM AUTHOR]

Wild edible mushrooms are an important food source globally and have a crucial role in forest ecosystems. However, there is limited research on the growth characteristics and the contribution of agronomic traits to biomass, and the environmental factors affecting mushroom growth are limited. This study was conducted in the Qilian Mountains, China, and focused on investigating the growth patterns and agronomic traits of Lyophyllum decastes and Coprinus comatus. The results revealed that the growth of these mushrooms followed a logical growth curve. By calculating the model parameters, we obtained the maximum daily growth of height (PH), pileus diameter (PD), and cluster perimeter (CP) of L. decastes on the 5th, 7th, and 7th days, respectively, with values of 0.55 cm d−1, 0.54 cm d−1, and 4.54 cm d−1, respectively. However, the maximum daily growth of PH, pileus length (PL), and PD of the C. comatus appeared on the 3rd day, 2nd day, and 2nd day of the observation, respectively. This study identified near-surface relative humidity, air relative humidity, and rainfall as the primary factors influencing mushroom growth, as indicated by Pearson's correlation analysis, redundancy analysis (RDA), and multiple linear and stepwise regression. Additionally, land surface temperature and air temperature were also identified as important factors affecting mushroom growth. By utilizing random forest and stepwise regression analysis, this study identified PH and stipe diameter (SD) as the most crucial agronomic traits affecting mushroom biomass. Overall, this study offers insights for industrial mushroom cultivation and basic fungal research. [ABSTRACT FROM AUTHOR]

Background: The study of growth traits is of interest to many animal scientists, regardless of specialization, due to the economic importance of growth rate, mature weight and other related traits. Objective: This study aimed to compare six non‐linear models for describing the growth of Lori‐Bakhtiari sheep. Methods: In order to collect weight data, 85 lambs (41 males and 44 females) were reared from birth to 140 days of age, and their growth patterns were recorded by measuring their body weight at 10‐day intervals. Various mathematical functions, including the negative exponential, Brody, Gompertz, Logistic, Morgan–Mercer–Flodin (MMF) and Weibull, were used to model the relationship between body weight records and age. Results: The results showed that the MMF and Gompertz models provided the best fit to the body weight data, whereas the negative exponential model exhibited the worst fit. In all models, the asymptotic weight of male lambs was higher than females. The research also revealed differences in growth patterns between male and female lambs. Overall, females had a lower absolute growth rate than males, but they reached their peak growth at an earlier period, and their growth rate declined faster. Conclusions: The differences in growth patterns between males and females indicate the importance of analysing male and female data separately when describing growth. As a result, Gompertz model can be recommended to Lori‐Bakhtiari female and male lamb breeders to determine more accurate growth traits. In addition, it should be considered that feeding male and female lambs separately according to absolute growth rate values may increase growth performance. [ABSTRACT FROM AUTHOR]

Mathematical growth models are useful in describing the growth of livestock. The study was done to assess the predictive ability and accuracy of four three-parameter nonlinear mathematical models (namely: Gompertz, Gompertz-Laird, Logistic, and von Bertalanffy) and one four-parameter (namely: Richards) nonlinear mathematical model. Models were used to predict the body weight (BW) of commercial Ross broiler chickens adapted to tropical conditions (n = 1,286). Age-weight data were collected once every week for 6 weeks. The Gauss-Newton iterative process of the nonlinear procedure in SAS was employed to obtain the parameters for each model. In addition, each model's goodnessof-fit, residuals, and computational difficulty were estimated. Model parameters were evaluated using Akaike's information criterion (AIC), Bayesian information criterion (BIC), adjusted coefficient of determination (AdjR²) and root mean square error (RMSE). The AdjR² value for all five models was high; however, the highest value was observed in the Gompertz and Gompertz-Laird models. Furthermore, the lowest AIC, BIC and RMSE values were observed in the Gompertz models. Using a complimentary method (involving a subjective pairwise comparison of the observed and predicted BWs), the Logistic, Gompertz-Laird, von Bertalanffy, and Richards models fitted well for the data used. However, the best fitting was obtained in the Gompertz model. Some similarities were observed between the Logistic and Richards models. In conclusion, all five nonlinear mathematical models fitted the age weight data used in this study well, with the Gompertz model being the best. [ABSTRACT FROM AUTHOR]

Sheep were among the first animals domesticated by humans, and to this day, small ruminants are primarily raised for their meat, milk, and wool. This study evaluated the goodness of fit for growth curve models using observed age and weight data from crossbred lambs of various breeds based on the mean values between paired breeds. We employed a hybrid metaheuristic algorithm, combining a simulated annealing (SA) algorithm and a genetic algorithm (GA) called SAGAC, to determine the optimal parameter values for growth models, ensuring the best alignment between simulated and observed curves. The goodness of fit and model accuracy was assessed using the coefficient of determination (R2), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE). Errors were measured by comparing the criteria differences between simulated and observed data. Thirty crossbreed combinations were simulated, considering the average weight. Analysis of the observed and simulated growth curves indicated that specific crossbreeding scenarios produced promising results. This simulation approach is believed to assist geneticists in predicting potential crossbreeding outcomes, thereby saving time and financial resources in field research. [ABSTRACT FROM AUTHOR]

Background & Objective: This study aimed to assess maternal and neonatal outcomes in cases of Intrauterine Growth Restriction (IUGR). Understanding these outcomes is vital for early identification of potential adverse effects and facilitating prompt intervention and management. Materials & Methods: This retrospective cohort study focused on mothers whose fetuses experienced IUGR at Imam Khomeini Hospital in Ahvaz, Iran, between March 2021 and 2022. Data on neurodevelopmental and clinical aspects were collected periodically up to 24 months’ post-birth, encompassing various parameters such as infant age, gender, developmental and motor coordination disorders, neurodevelopmental status, medical and speech disorders, and maternal health during pregnancy. Results: Over a one-year period, 80 breastfed infants were studied. At 6, 12, and 24 months after birth, 30% of children showed growth disorders. Boys had a slightly higher percentage of growth arrest (76.4% vs. 63.2%, P>0.05). Growth retardation was present in 13.16% of girls, compared to none of the boys. The most common medical outcomes were asthma and orthopedic disorders (5% each). Developmental disorders and motor disorders were the most common neurological and developmental outcomes, each affecting 11.25% of children. During pregnancy, 16.25% had gestational diabetes, 17.5% had hypertension, and 10% had hypothyroidism, which decreased to 6.25%, 11.25%, and 3.75%, respectively, after childbirth. Conclusion: The present study indicates a significant prevalence of growth and developmental disorders, as well as medical outcomes such as asthma and orthopedic issues at the age of two in infants with IUGR. Mothers of these infants also faced significant postpartum issues, such as diabetes and hypertension. [ABSTRACT FROM AUTHOR]

This work presents a low-cost, open-source turbidimeter, the 'Erlenmeter', designed to monitor the growth of microorganisms in batch cultures. It is easy to build, based exclusively on inexpensive off-the-shelf electronic components and 3D-printed parts. The Erlenmeter allows measuring the optical density of cultures on standard Erlenmeyer flasks without the need to open the flasks to collect aliquots, ensuring speed, minimal use of consumables, and elimination of the risk of contamination. These features make it particularly well-suited not just for routine research assays but also for experimental teaching. Here we illustrate the use of the Erlenmeter turbidimeter to record the growth of the microalga Phaeodactylum tricornutum, of the bacterium Escherichia coli, and of the yeast Saccharomyces cerevisiae, model organisms that are widely used in research and teaching. The Erlenmeter allows a detailed characterization of the growth curves of all organisms, confirming its usefulness for studying microbial populations dynamics both for research purposes and in classroom settings. [ABSTRACT FROM AUTHOR]

Latent repeated measures ANOVA (L-RM-ANOVA) has recently been proposed as an alternative to traditional repeated measures ANOVA. L-RM-ANOVA builds upon structural equation modeling and enables researchers to investigate interindividual differences in main/interaction effects, examine custom contrasts, incorporate a measurement model, and account for missing data. However, L-RM-ANOVA uses maximum likelihood and thus cannot incorporate prior information and can have poor statistical properties in small samples. We show how L-RM-ANOVA can be used with Bayesian estimation to resolve the aforementioned issues. We demonstrate how to place informative priors on model parameters that constitute main and interaction effects. We further show how to place weakly informative priors on standardized parameters which can be used when no prior information is available. We conclude that Bayesian estimation can lower Type 1 error and bias, and increase power and efficiency when priors are chosen adequately. We demonstrate the approach using a real empirical example and guide the readers through specification of the model. We argue that ANOVA tables and incomplete descriptive statistics are not sufficient information to specify informative priors, and we identify which parameter estimates should be reported in future research; thereby promoting cumulative research. [ABSTRACT FROM AUTHOR]

Introduction: Angelman syndrome (AS) is a rare, genetic, neurodevelopmental disorder characterized by severe impairments in speech, cognition, and motor skills accompanied by unique behaviors, distinct facial features, and high prevalence of epilepsy and sleep problems. Despite some reports of short stature among AS patients, this feature is not included in the clinical criteria defined in 2005. We investigated growth patterns among AS patients with respect to mutation type, growth periods, family history, and endocrine abnormalities. Methods: Data were collected from patients' medical files in AS National Clinic. Mutation subtypes were divided to deletion and non-deletion. Four growth periods were defined: preschool, childhood, peak height velocity, and final height. Results: The cohort included 88 individuals (46 males), with 54 (61.4%) carrying deletion subtype. A median of 3 observations per individual produced 280 data points. Final height SDS was significantly lower compared to general population (−1.23 ± 1.26, p < 0.001), and in deletion group versus non-deletion (−1.67 ± 1.3 vs. −0.65 ± 0.96, p = 0.03). Final height SDS was significantly lower compared to height SDS in preschool period (−1.32 vs. −0.47, p = 0.007). Patient's final height SDS was significantly lower than the parents' (∆final-height SDS = 0.94 ± 0.99, p = 0.002). IGF1-SDS was significantly decreased compared to general population (−0.55 ± 1.61, p = 0.04), with lower values among deletion group (−0.70 ± 1.44, p = 0.01). Conclusions: AS patients demonstrate specific growth pattern with deceleration during childhood and adolescence, resulting in significantly decreased final height compared to normal population, and even lower among deletion subgroup, which could be attributed to reduced IGF1 levels. We propose adding short stature to the clinical criteria and developing adjusted growth curves for AS population. [ABSTRACT FROM AUTHOR]

A constrained multivariate linear model is a multivariate linear model with the columns of its coefficient matrix constrained to lie in a known subspace. This class of models includes those typically used to study growth curves and longitudinal data. Envelope methods have been proposed to improve the estimation efficiency in unconstrained multivariate linear models, but have not yet been developed for constrained models. We pursue that development in this article. We first compare the standard envelope estimator with the standard estimator arising from a constrained multivariate model in terms of bias and efficiency. To further improve efficiency, we propose a novel envelope estimator based on a constrained multivariate model. We show the advantage of our proposals by simulations and by studying the probiotic capacity to reduced Salmonella infection. [ABSTRACT FROM AUTHOR]

Background: The aim of the present study was to provide ocular biometry percentile values for Indian children between the ages of 6 and 12 and to validate the usefulness of centiles in predicting myopia development. Methods: The study was part of a longitudinal study—the Sankara Nethralaya Tamil Nadu Essilor Myopia Study (STEM), where objective refraction and ocular biometry were measured for children studying in grades 1, 4, and 6 at baseline (2019–2020). These data were used to generate ocular biometry percentile curves (both for axial length (AL) and AL/corneal curvature (AL/CR) ratios). The usefulness of percentile values in predicting myopia development was estimated from follow-up data (2022). Results: The total number of children in the three grades at baseline was 4514 (age range 6 to 12). Boys represented 54% (n = 2442) of the overall sample. The prevalence of myopia at baseline was 11.7% (95% CI from 10.8 to 12.7%) in these three grades. Both the AL and AL/CR ratio centiles showed a linear trend with an increase in AL and AL/CR with increasing grades (p < 0.001) for all percentiles (2, 5, 10, 25, 50, 75, 90, 95, 98, and 99) when stratified by sex. In the follow-up data (n = 377), the 75th and 50th percentiles of the AL/CR ratio had an area under the curve (AUC) of 0.79 and 0.72 to predict myopia onset for grade 4 and 6 children at baseline. Combining baseline AL with the centile shift in follow-up as a predictor increased the AUC to 0.83. Conclusions: The present study has provided centile values specific for Indian children between the ages of 6 and 12 to monitor and intervene where children are at a higher risk of myopia development. [ABSTRACT FROM AUTHOR]

Despite some progress in reducing income inequality between countries over the last two decades, there is evidence that income inequality is on the rise within nations. This article uses panel data compiled from multiple sources and a growth curve modeling approach to examine the relationship between foreign direct investment (FDI) and within-nation income inequality across two samples: one comprising 2,095 country-year observations nested in 141 countries from 1991 to 2018 to explore the broader FDI-income inequality relationship, and a second, more focused sample of 405 country-year observations nested in 61 countries from 2000 to 2018, designed to analyze effects of the sectoral distribution of FDI. The analyses find that the relationship between FDI and income inequality is positive and linear for non-OECD economies but follows an inverted U-shaped path for developed countries. Moreover, in this article, I have developed and introduced two new indices, the FDI Pluralism Index and FDI Sectoral Gini Coefficient, to measure the distribution of FDI among the sectors of the host economy. Results show that a concentration of FDI in one sector aggravates income inequality since foreign capital tends to flow into the most profitable industries, creating uneven growth between sectors and increasing between-sector income inequality. [ABSTRACT FROM AUTHOR]

Peanut is a critical food crop worldwide, and the development of high-throughput phenotyping techniques is essential for enhancing the crop's genetic gain rate. Given the obvious challenges of directly estimating peanut yields through remote sensing, an approach that utilizes above-ground phenotypes to estimate underground yield is necessary. To that end, this study leveraged unmanned aerial vehicles (UAVs) for high-throughput phenotyping of surface traits in peanut. Using a diverse set of peanut germplasm planted in 2021 and 2022, UAV flight missions were repeatedly conducted to capture image data thatwere used to construct high-resolution multitemporal sigmoidal growth curves based on apparent characteristics, such as canopy cover and canopy height. Latent phenotypes extracted from these growth curves and their first derivatives informed the development of advanced machine learning models, specifically random forest and eXtreme Gradient Boosting (XGBoost), to estimate yield in the peanut plots. The random forest model exhibited exceptional predictive accuracy (R2 = 0.93), while XGBoost was also reasonably effective (R2 = 0.88). When using confusion matrices to evaluate the classification abilities of each model, the two models proved valuable in a breeding pipeline, particularly for filtering out underperforming genotypes. In addition, the random forest model excelled in identifying top-performing material while minimizing Type I and Type II errors. Overall, these findings underscore the potential of machine learning models, especially random forests and XGBoost, in predicting peanut yield and improving the efficiency of peanut breeding programs. [ABSTRACT FROM AUTHOR]

Growth in individual body size amongst different species can to a greater or lesser extent depend on environmental factors such as resource availability. Individual growth curves can therefore be largely fixed or more plastic. Classic theory about phenotypic plasticity assumes that such plasticity has associated costs. In contrast, according to dynamic energy budget theory, maintaining a fixed growth rate in the face of variable resource availability would incur additional energetic costs. In this article, we explore the simultaneous evolution of the degree of plasticity in individual growth curves and the rate of non-plastic, environment-independent individual growth. We explore different relations between possible additional energetic costs and the degree of growth curve plasticity. To do so, we use adaptive dynamics to analyze a size-structured population model that is based on dynamic energy budget theory to account for the energetic trade-offs within an individual. We show that simultaneous evolution of the degree of growth curve plasticity and the rate of non-plastic individual growth will drive these traits to intermediate values at first. Afterwards, the degree of growth curve plasticity might evolve slowly towards extreme values depending on whether energetic costs increase or decrease with the degree of plasticity. In addition, the analysis shows that it is unlikely to encounter species in which individual growth is entirely fixed or entirely plastic, opposing general assumptions in dynamic energy budget theory. [ABSTRACT FROM AUTHOR]

Alpacas represent an exotic species for Italy, introduced no more than 20–30 years ago. Nevertheless, they are currently the most widespread camelid species reared in this country, highlighting the growing interest in breeding this species. So, it is useful to assess parameters on their growth in relation to the new environment. Thus, body weight and body measures were recorded on 49 healthy alpacas of Huacaya type (27 females, 22 males), along a period of 27 months. Overall, 111 individual observations were made. Data were analysed by ANOVA, as growth curves were estimated by applying the Gompertz's model. Multiple regression was finally used to estimate body weight from body measures. Body weight and linear measures, except for the distance between iliac crest and the length of the rump, were influenced by the category (calves, yearlings, adults) and by the age class within category (p < 0.05), while gender and interaction between gender and category were never significant (p > 0.05). Asymptotic weigh of males was 8.25% higher than females (p < 0.05). Moreover, males at maturity had higher withers (+0.96%), longer body (+2.70%) and chest measurements (+3.18%) than females. Asymptotic rump width (both at the ilium and at the ischium) was higher in females (respectively + 6.19%; +12.90%). According to our work, the best equation for the estimate of body weight from body measures was the following: 5.691 + 0.00005624 * chest circumference3 + 0.00002298 * trunk length3 − 1.155 * rump width between ischial tuberosities + 0.00001545 * height at rump3 (R2=0.957; SE of estimate = 4.36 kg), that is important for a better management of the species. Alpacas are the most widespread camelid species in Italy. Rump dimensions develop earlier than other body measures. It is possible to improve the management and welfare of animals by estimating the live weight starting from somatic measures. [ABSTRACT FROM AUTHOR]

Less variable than life history parameters (LHPs), it is life history ratios (LHRs) that define how taxa allocate energy between growth, maintenance and reproduction, and respond to fishing pressure. Limited by small samples, variable data quality, and a focus on LHP estimation, previous meta-analyses have failed to settle debate about the extent to which LHRs are relatively invariant across all taxa or characteristic of specific taxa. We collected de novo 1335 published studies and applying rigorous standardization and quality control procedures developed, and make available, a database of high-quality M / K and L m/ L ∞ estimates. We describe two parallel but independent meta-analyses: a cross-validation study of the predictability of M / K by taxonomic category and an evaluation of alternative relationships between the LHRs using Akaike information criteria. These analyses demonstrate that the LHRs are correlated and vary predictably by taxa, with aggregation to the level of family and genera having the most predictive power in our database. We postulate that the LHRs of taxa may relate to their stoichiometric niches, which could open up interesting lines for ecological research and provide new tools for predicting the LHRs of poorly studied taxa. [ABSTRACT FROM AUTHOR]

Evaluating the behavior of fruit width and length characters throughout the pepper crop cycle is essential for researchers in decision-making aimed at developing appropriate management techniques and harvesting fruits at proper growth stages. The Nonlinear Mixed-Effect Models (NLME) method is recommended to jointly model the residuals and the entire database, including group effects, to describe growth curves. This work compared four nonlinear equations (Gompertz, Logistic, Richards, and von Bertalanffy) by including groups (pepper and bell pepper) to describe the pepper genotypes' length and width growth. Of the eight genotypes used, three were bell pepper, and five were pepper. For each, fruit length and width were measured in 10 periods. According to the fit-quality measures studied, the best model for adjusting the length of the fruit was the Richards ( R a d j. 2 = 0.9960 ), while for the width, it was the Logistic ( R a d j. 2 = 0.9957 ). The estimated random effects showed that for asymptotic length and time to the inflection point presented a correlation of 0.75, indicating a positive association between these traits. For width, however, this result was different: −0.02. NLME adjustment allowed efficient prediction of values and efficient characterization of the studied genotypes, proving to be an efficient method for longitudinal data. [ABSTRACT FROM AUTHOR]

In this article, we compare two ways of modelling measures of fetal growth. The goal is to impute the missing information for certain ultrasound measurements that are observed at different times and with different numbers of observations. To analyze the effect that other variables have, such as environmental exposure to certain substances or diet, on fetal growth based on these data, we need to handle the information measured at the same instant of time for all the individuals under study, preferably in three time windows of pregnancy (first trimester, week 12; second trimester, week 20; third trimester, week 34). For this, data at these chosen times, in case they are not available, must be imputed from the available information using an appropriate statistical model. One option is to use a linear model, specifically a generalized least squares model that is fitted to the features shown in the data. The other option is to use diffusion processes, estimating their parameters based on the available information. In both options, missing data can be estimated with the unconditional fitted model, conditional on the previous available measurement, or conditional to the closest measurement. [ABSTRACT FROM AUTHOR]

Simple Summary: Following the growth of a fattening animal is an important aspect since farmers aim to maximize their profits by improving their slaughter weight. Growth models can fit the age–weight data into biologically interpretable parameters that provide a growth curve for monitoring animal growth, thus identifying the growth declining point during the fattening period. In this study, we aimed to define the best fitting growth model for describing Kivircik lamb growth. While the Gompertz model was identified as the best fitting growth model, it was determined that male lambs, twin lambs, and winter-born lambs had a higher mature weight. Even though they may be lighter at birth, the proportion of their prospective weight gain was found to be higher compared to female, single-born, and spring-born lambs. Our results showed that the estimation error of the Gompertz model ranged between −0.43 kg to 0.60 kg. In conclusion, according to the Gompertz model's estimation, Kivircik lambs reached 40.7% of their slaughter weight at weaning and had a 66.3% degree of maturity at the slaughter age, which indicated inappropriate management. The Kivircik is an indigenous sheep breed from Turkey, and it has superior meat quality compared to other indigenous breeds. Therefore, farmers prioritize Kivircik lamb fattening instead of milk production. Here, we aimed to determine the best nonlinear growth model, i.e., Gompertz, Logistic, Von Bertalanffy, and Brody, to describe the growth curve of Kivircik lambs. The body weight data from birth until 150 days of age belonging to 612 lambs were used as the material of this study. The best fitting model was selected by considering the adjusted coefficient of determination (R2adj), residual mean square, and Akaike's (AIC) and Bayesian information criteria (BIC). Even though the Brody model had a better statistical fit, considering its biological interpretation, the Gompertz model was identified as an appropriate model for describing Kivircik lamb growth. Male lambs, twin lambs, and lambs born in winter had higher mature live weights (44.2 kg, 71.2 kg, and 38.5 kg, respectively) and rate of weight gain (2.1, 2.6, and 2.0, respectively). However, our subgroups revealed a similar rate of maturity (0.01). Growth models are important tools for deciding the optimal slaughter age and they provide valuable information on the management practices of both sexes, birth types, and birth seasons. These results can be applied to breeding programs for early selection, enabling intervention strategies when needed. [ABSTRACT FROM AUTHOR]

Objectives: The literature regarding the effectiveness of long‐term psychological interventions delivered in tertiary care is scarce. This study sought to quantify and evaluate outcomes delivered in a UK tertiary care psychotherapy service against equivalent service benchmarks. Design: A retrospective analysis of outcomes on the Outcome Questionnaire‐45 (OQ‐45) over a 10‐year period in a tertiary care psychotherapy service. The modalities evaluated were cognitive‐behavioural, cognitive‐analytic, and psychoanalytic psychotherapies. Methods: Effectiveness was calculated at the service level and for each modality using pre‐post‐effect sizes and recovery rates. Benchmarking included a random‐effects meta‐analysis. Trajectories of change for each modality were examined using growth curve models. Results: Baseline distress on the OQ‐45 was higher than comparative norms (M = 102.57, SD = 22.79, N = 364). The average number of sessions was 48.68 (SD = 42.14, range = 5–335). There was a moderate pre‐post‐treatment effect (d =.46, 95% CI =.37–.55) which was lower than available benchmarks. The modalities differed in duration but were largely equivalent in terms of outcome. The reliable improvement rate was 29.95%, and the recovery rate was 10.16%, and change over time was best explained using a nonlinear (cubic) time trend. Conclusions: The elevated distress at baseline appears to create the conditions for relatively lengthy interventions and attenuated clinical outcomes. Suggestions are made regarding the clinical role, function, and evaluation of tertiary care psychotherapy services. [ABSTRACT FROM AUTHOR]

Breed-specific growth curves (GCs) are needed for neonatal puppies, but breed-specific data may be insufficient. We investigated an unsupervised clustering methodology for modeling GCs by augmenting breed-specific data with data from breeds having similar growth profiles. Puppy breeds were grouped by median growth profiles (bodyweights between birth and Day 20) using hierarchical clustering on principal components. Median bodyweights for breeds in a cluster were centered to that cluster's median and used to model cluster GCs by Generalized Additive Models for Location, Shape and Scale. These were centered back to breed growth profiles to produce cluster-scale breed GCs. The accuracy of breed-scale GCs modeled with breed-specific data only and cluster-scale breed GCs were compared when modeled from diminishing sample sizes. A complete dataset of Labrador Retriever bodyweights (birth to Day 20) was split into training (410 puppies) and test (460 puppies) datasets. Cluster-scale breed and breed-scale GCs were modelled from defined sample sizes from the training dataset. Quality criteria were the percentages of observed data in the test dataset outside the target growth centiles of simulations. Accuracy of cluster-scale breed GCs remained consistently high down to sampling sizes of three. They slightly overestimated breed variability, but centile curves were smooth and consistent with breed-scale GCs modeled from the complete Labrador Retriever dataset. At sampling sizes ≤ 20, the quality of breed-scale GCs reduced notably. In conclusion, GCs for neonatal puppies generated using a breed-cluster hybrid methodology can be more satisfactory than GCs at purely the breed level when sample sizes are small. [ABSTRACT FROM AUTHOR]

Following the completion of an adaptive evolution experiment, fitness evaluations are routinely conducted to assess the magnitude of adaptation. In doing so, proper consideration should be given when determining the appropriate methods as trade-offs may exist between accuracy and throughput. Here, we present three instances in which small changes in the framework or execution of fitness evaluations significantly impacted the outcomes. The first case illustrates that discrepancies in fitness conclusions can arise depending on the approach to evaluating fitness, the culture vessel used, and the sampling method. The second case reveals that variations in environmental conditions can occur associated with culture vessel material. Specifically, these subtle changes can greatly affect microbial physiology leading to changes in the culture pH and distorting fitness measurements. Finally, the last case reports that heterogeneity in CFU formation time can result in inaccurate fitness conclusions. Based on each case, considerations and recommendations are presented for future adaptive evolution experiments. [ABSTRACT FROM AUTHOR]

Research shows that the quality of mother‐child interactions is a robust antecedent of child socioemotional functioning. Yet, relatively little is known about the evolution of this relational quality over time, and even less about how changes in relational quality may bear on child adjustment. This study aimed to describe the trajectory of quality of mother‐child interactions between ages 2 and 7 and to investigate associations between individual differences in this trajectory and child socioemotional functioning at age 8. In a sample of 233 mother‐child dyads primarily comprised of White French‐Canadian mothers, the quality of interactions was assessed during 10‐min play sequences when children were aged 2, 4, and 7 years. Child internalizing, externalizing, and prosocial behaviors were reported by a subsample of 171 teachers at age 8. The results showed that on average, quality of mother‐child interactions decreased over time. In terms of individual differences, children who experienced a slower decrease in the quality of interactions with their mother from 2 to 7 years showed less internalizing behavior at age 8, over and above initial quality at 2 years. Children involved in higher quality interactions with their mother at 2 years showed more prosocial and less externalizing behavior at age 8, independent of the subsequent decrease in the quality of those interactions. The findings suggest that initial levels and subsequent changes in the quality of mother‐child interactions are two distinct indicators of their relationship with potentially different implications for child adjustment. [ABSTRACT FROM AUTHOR]

Maternal exposure to childhood maltreatment (CM) is associated with offspring behavioral problems; however, little work has examined these associations longitudinally across child development. This study examined the effects of maternal history of CM on trajectories of child internalizing and externalizing behavior measured from toddlerhood to preschool, and the role of maternal depressive symptoms and parenting behavior as potential mediators. Participants included 115 mother–child dyads recruited from a hospital maternity ward. Maternal CM was measured at 3-months postpartum. At 18, 36, and 60 months, maternal depressive symptoms and child behavior were assessed via maternal report and parenting behavior was assessed through direct observation. Findings indicated that children of mothers exposed to CM demonstrated poorer trajectories of problem behavior across early childhood. Maternal depressive symptoms mediated the relation between CM and children's internalizing problems. Findings highlight the importance of screening for maternal depressive symptoms and early intervention for maternal and child mental health. [ABSTRACT FROM AUTHOR]

Models considered in the current special issue represent valuable additions to the statistical toolbox of prevention researchers for many types of research questions and designs. Their appropriate use, however, depends on critical evaluation relative to previously existing techniques. This evaluation includes (a.) model choice involving "right-sizing" of the model relative to the amount and quality of data at hand, (b.) examination of the external validity of identified associations relative to observed or latent subgroups, (c.) confirmation of the reasonableness of the functional form assumed by the model, and (d.) identification of influential or outlying observations which unduly affect model fit or parameter estimates. Models in this issue allow for testing of new types of hypotheses in prevention research, and can constitute counterarguments to existing statistical practice. These models may, however, in turn be the object of critical examination of counterarguments a reasonable skeptic may offer. [ABSTRACT FROM AUTHOR]

Child growth measurements are critical vital signs to track, with every individual child growth curve potentially revealing a story about a child's health and well‐being. Simply put, every baby born requires basic building blocks to grow and thrive: proper nutrition, love and care, and medical health. To ensure that every child who is missing one of these vital aspects is identified, growth is traditionally measured at birth and each well‐child visit. While the blue and pink growth curves appear omnipresent in pediatric clinics, it is surprising to realize that their use only became standard of care in 1977 when the National Center for Health Statistics (NCHS) adopted the growth curve as a clinical tool for health. Behind this practice lies a socioeconomically, culturally, and politically complex interplay of individuals and institutions around the world. In this review, we highlight the often forgotten past, current state of practice, and future potential of this powerful clinical tool: the growth reference chart, with a particular focus on clinical genetics practice. The goal of this article is to understand ongoing work in the field of anthropometry (the scientific study of human measurements) and its direct impact on modern pediatric and genetic patient care. [ABSTRACT FROM AUTHOR]

BACKGROUND: When the human population increases, so does the need to explore a wider range of feedstocks and biomasses, such as cyanobacteria. However, a deeper understanding of the growth patterns and pigment production is required to support the selection of the most beneficial species and conditions for industrial production. The growth and pigment production (i.e., chlorophyll a and C‐phycocyanin) of three cyanobacterium species were evaluated following a three‐fold aim. The first goal was to compare among a species commonly selected for exploitation (Arthrospira platensis) and two alternative species (Anabaena cylindrica and Nostoc muscorum). The second goal was analyzing pigment production in the long‐term. The last goal involved comparing different methods (spectrophotometry and fluorimetry) to understand whether there is an appropriate proxy of biomass increase and pigment production that can be used for monitoring purposes. RESULTS: All species showed high longevity and proved capable of growing for more than 100 days without any additional supplementation. However, the maximum quantum yield of PS II (Fv /Fm) revealed that their photosynthetic efficiency varied over time with a clear decrease after 2 months. Pigment analysis showed a heterogeneous pattern during the growth periods of all three species that could only be captured by the parameter Fv /Fm, but the pattern was only present for A. cylindrica and N. muscorum in some stages of the culture period. CONCLUSION: N. muscorum was found to be the best chlorophyll a and C‐phycocyanin producer, with the production peaking for all species at defined time periods within the growth profile. © 2022 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI). [ABSTRACT FROM AUTHOR]

Opuntia joconostle is a semi-wild cactus cultivated for its fruit. However, the cladodes are often discarded, wasting the potentially useful mucilage in them. The mucilage is composed primarily of heteropolysaccharides, characterized by their molar mass distribution, monosaccharide composition, structural features (by vibrational spectroscopy, FT IR, and atomic force microscopy, AFM), and fermentability by known saccharolytic commensal members of the gut microbiota. After fractionation with ion exchange chromatography, four polysaccharides were found: one neutral (composed mainly of galactose, arabinose, and xylose) and three acidic, with a galacturonic acid content from 10 to 35%mol. Their average molar masses ranged from 1.8 × 105 to 2.8 × 105 g·mol−1. Distinct structural features such as galactan, arabinan, xylan, and galacturonan motifs were present in the FT IR spectra. The intra- and intermolecular interactions of the polysaccharides, and their effect on the aggregation behavior, were shown by AFM. The composition and structural features of these polysaccharides were reflected in their prebiotic potential. Lactobacilli and Bifidobacteria were not able to utilize them, whereas members of Bacteroidetes showed utilization capacity. The obtained data suggest a high economic potential for this Opuntia species, with potential uses such as animal feed in arid areas, precise prebiotic, and symbiotic formulations, or as the carbon skeleton source in a green refinery. Our methodology can be used to evaluate the saccharides as the phenotype of interest, helping to guide the breeding strategy. [ABSTRACT FROM AUTHOR]

Featured Application: A better understanding of mold growth on wood and the parameters on which this growth depends will lead to improved calculation models for predicting mold occurrence in buildings and building components. The possible influence of anatomical sections of wood on mold growth was investigated by means of a laboratory experiment. The selected fungi, Aspergillus sp., Penicillium sp., and Alternaria sp. were inoculated by spraying on the surface of wood specimens prepared from pine (Pinus sylvestris) and spruce (Picea abies). The incubation was carried out under stable environmental conditions (temperature of 22 °C, relative humidity of 75, 87, and 95%) over three months. Mold growth was evaluated based on regular microscopic and macroscopic observations. The recorded mold coverage fractions and the qualitative indicators of mold development were later expressed by a dimensionless mold index. The differences in mold growth in the anatomical sections of wood were found to be relatively insignificant. In contrast, comparison of measured data with other experimental studies showed large differences, especially in the initial growth phase. The discrepancy is probably related to differences among the experimental protocols. It is concluded that laboratory mold growth studies would be improved if a common standardized methodology was developed and followed. [ABSTRACT FROM AUTHOR]

Background Randomized trials reported no difference whether induction or expectant management is performed in non-diabetic women with large for gestational age babies but no tool has been validated for the prediction of high risk cases. Aim Assessing the performance of different growth curves in the prediction of complications. Methods Data from 1066 consecutive non-diabetic women who delivered babies ≥4000 g were collected. Logistic regression analysis was used to analyze the impact of the maternal variables on: instrumental delivery, shoulder dystocia (SD), perineal tears, cesarean section (CS), and postpartum hemorrhage. Intergrowth21 curves and customized Gardosi’s curves were compared in terms of prediction of adverse outcomes. Findings Induction of labor was performed in 23.1% cases. The rate of CS was 17%. Hemorrhage, fetal distress, and SD occurred in 2%, 1.3%, and 2.7% of cases, respectively. Induction was significantly associated with instrumental delivery (p < .001), CS (p = .001), third and fourth degree perineal tears (p = .031), and post-partum hemorrhage (p = .02). The cutoff of 90th percentile according to Intergrowth21 did not show significant performance in predicting CS, while the same cutoff according to the Gardosi curves showed an OR 1.92 (CI 1.30–2.84) (p = .0009). Discussion Gardosi curves showed a better performance in predicting the risk of CS versus Intergrowth curves. Induction is significantly associated with adverse outcome in non-diabetic women with LGA babies. [ABSTRACT FROM AUTHOR]

Background Randomized trials reported no difference whether induction or expectant management is performed in non-diabetic women with large for gestational age babies but no tool has been validated for the prediction of high risk cases. Aim Assessing the performance of different growth curves in the prediction of complications. Methods Data from 1066 consecutive non-diabetic women who delivered babies ≥4000 g were collected. Logistic regression analysis was used to analyze the impact of the maternal variables on: instrumental delivery, shoulder dystocia (SD), perineal tears, cesarean section (CS), and postpartum hemorrhage. Intergrowth21 curves and customized Gardosi’s curves were compared in terms of prediction of adverse outcomes. Findings Induction of labor was performed in 23.1% cases. The rate of CS was 17%. Hemorrhage, fetal distress, and SD occurred in 2%, 1.3%, and 2.7% of cases, respectively. Induction was significantly associated with instrumental delivery (p < .001), CS (p = .001), third and fourth degree perineal tears (p = .031), and post-partum hemorrhage (p = .02). The cutoff of 90th percentile according to Intergrowth21 did not show significant performance in predicting CS, while the same cutoff according to the Gardosi curves showed an OR 1.92 (CI 1.30–2.84) (p = .0009). Discussion Gardosi curves showed a better performance in predicting the risk of CS versus Intergrowth curves. Induction is significantly associated with adverse outcome in non-diabetic women with LGA babies. [ABSTRACT FROM AUTHOR]

The objective of this study was to assess the possibility of using two nonlinear models, i.e. the von Bertalanffy and Gompertz functions, for fitting growth curves of Popielno White and New Zealand White rabbits. The study was conducted using 37 Popielno White (21 male and 16 female) and 55 New Zealand White (28 male and 27 female) rabbits. The nonlinear regression procedure (NLIN) in SAS 9.4 software was used to model the rabbits’ growth curves from birth to 12 weeks of age. To see how rabbit growth might progress in subsequent weeks, we extrapolated the weights of the rabbits up to the age of 30 weeks. Six criteria were used to compare models: mean error, mean squared error, mean absolute error, quotient between the error sum of squares and observed sum of squares, corrected Akaike information criterion, and Bayesian information criterion. The shape of all curves was sigmoid, and both models fitted well to the data from birth to 12 weeks of age, i.e. during the interpolation process. A problem with the fit occurred later, during the extrapolation process, i.e. when the models were used to predict the animals’ course of growth in subsequent weeks. When body weight was extrapolated in later weeks of life, the fitting of the von Bertalanffy model was slightly worse, and asymptotic body weight was overestimated. To predict the further course of rabbit growth in practice, the Gompertz function would be a better choice. The Gompertz model could also be a helpful tool for breeders to describe the growth process of rabbits and to select a more economically profitable breed. [ABSTRACT FROM AUTHOR]

Information on age and growth is essential to modern stock assessment and the development of management plans for fish resources. To provide quality otolith-based estimates of growth parameters, this study performed five types of analyses on the two important croakers that were under high fishing pressure in southwestern Taiwan: Pennahia macrocephalus (big-head pennah croaker) and Atrobucca nibe (blackmouth croaker): (1) Estimation of length–weight relationships (LWR) with discussion on the differences with previous studies; (2) validation of the periodicity of ring formation using edge analysis; (3) examination of three age determination methods (integral, quartile and back-calculation methods) and selection of the most appropriate one using a k-fold cross-validation simulation; (4) determination of the representative growth models from four candidate models using a multimodel inference approach; and, (5) compilation of growth parameters for all Pennahia and Atrobucca species published globally for reviewing the clusters of estimates using auximetric plots of logged growth parameters. The study observed that features of samples affected the LWR estimates. Edge analysis supported the growth rings were formed annually, and the cross-validation study supported the quartile method (age was determined as the number of opaque bands on otolith plus the quartile of the width of the marginal translucent band) provided more appropriate estimates of age. The multimodel inference approach suggested the von Bertalanffy growth model as the optimal model for P. macrocephalus and logistic growth model for A. nibe, with asymptotic lengths and relative growth rates of 18.0 cm TL and 0.789 year−1 and 55.21 cm, 0.374 year−1, respectively. Auximetric plots of global estimates showed a downward trend with clusters by species. Growth rates of the two species were higher than in previous studies using the same aging structure (otolith) and from similar locations conducted a decade ago, suggesting a possible effect of increased fishing pressure and the need to establish a management framework. This study adds updated information to the global literature and provides an overview of growth parameters for the two important croakers. [ABSTRACT FROM AUTHOR]

SATB2‐associated syndrome (SAS) is an autosomal dominant multisystemic disorder caused by alterations in the SATB2 gene. In addition to a predominant neurodevelopmental phenotype, individuals with SAS often present with feeding difficulties and growth retardation that persist past infancy. In this study, we present growth and measurement data from 211 individuals (53.6% male, 46.4% female) with SAS due to different molecular mechanisms. To delineate growth in this population, we constructed SAS‐specific growth charts by sex from birth to 10 years of age. Smoothed SAS percentiles were superimposed with normative percentiles from WHO (birth to <24 months) and CDC (24 months to 10 years) growth charts. Individuals with SAS tend to display slower postnatal growth with 22.2% (32/144), 19.0% (26/137), and 21.6% having at least one weight, height, or weight‐for‐length /body mass index (BMI) measurement below −2 standard deviations, respectively. The SAS 50th centile BMI was consistently below the normative data 50th centile and negative mean Z‐scores were seen across almost all age groups analyzed for both genders. Individuals with chromosomal abnormalities displayed significantly lower weight for age Z‐score, height for age Z‐scores, occipitofrontal head circumference for age Z‐scores, and BMI for age Z‐scores compared to either missense or null variants. [ABSTRACT FROM AUTHOR]

Growth centiles and growth curves are two ways to present child anthropometry; however, they differ in the type of data used, the method of analysis, the biological parameters fitted and the form of interpretation. To fit and compare height growth centiles and curves in Indian children. 1468 children (796 boys) from Pune India aged 6–18 years with longitudinal data on age and height (n = 7781) were analysed using GAMLSS (Generalised Additive Models for Location Scale and Shape) for growth centiles, and SITAR (SuperImposition by Rotation and Translation) for growth curves. SITAR explained 98.7% and 98.8% of the height variance in boys and girls, with mean age at peak height velocity 13.1 and 11.0 years, and mean peak velocity 9.0 and 8.0 cm/year, respectively. GAMLSS (Box-Cox Cole Green model) also captured the pubertal growth spurt but the centiles were shallower than the SITAR mean curve. Boys showed a mid-growth spurt at age 8 years. GAMLSS displays the distribution of height in the population by age and sex, while SITAR effectively and parsimoniously summarises the pattern of height growth in individual children. The two approaches provide distinct, useful information about child growth. [ABSTRACT FROM AUTHOR]

Monitoring the growth of bacterial cultures is one of the most common techniques in microbiology. This is usually achieved by using expensive and bulky spectrophotometric plate readers which periodically measure the optical density of bacterial cultures during the incubation period. In this study, we present a completely novel way of obtaining bacterial growth curves based on the classification of scanned images of cultures rather than using spectrophotometric measurements. We trained a deep learning model with images of bacterial broths contained in microplates, and we integrated it into a custommade software application that triggers a flatbed scanner to timely capture images, automatically processes the images, and represents all growth curves. The developed tool, ScanGrow, is presented as a low-cost and high-throughput alternative to plate readers, and it only requires a computer connected to a flatbed scanner and equipped with our open-source ScanGrow application. In addition, this application also assists in the pre-processing of data to create and evaluate new models, having the potential to facilitate many routine microbiological techniques. [ABSTRACT FROM AUTHOR]

Threatening processes, such as disease, can drive major changes in population demographics of the host. Chytridiomycosis, caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd), has led to the decline of at least 500 amphibian species across the globe and has been shown to truncate host age structure by lowering adult survival rates. This results in heavy reliance on annual recruitment and the inability to recover in the event of periodic recruitment failure. We used skeletochronology to determine the age structure, growth, and survival rates of populations of an endangered amphibian, Litoria raniformis, with endemic chytridiomycosis, across two climatically disparate regions in south‐eastern Australia: semi‐arid and temperate. Contrary to predictions, populations in the semi‐arid region (in which chytrid prevalence is substantially lower due to high temperatures) displayed a more truncated age structure than populations in the temperate study regions. Maximum recorded age was only two years in the semi‐arid region compared with up to four years in the temperate region. Wetland hydroperiod and average seasonal air temperature were correlated with age, and males had a slightly higher survival rate than females (0.31 for males and 0.27 for females). Despite the previously documented differences in chytrid prevalence between the two climatic regions, water availability and wetland hydroperiods appear the over‐riding determinants of the age structure and survival rates of L. raniformis. Targeted management which ensures water availability and improves survival of 1‐year‐old frogs into their second and third breeding season would reduce the impact of stochastic events on L. raniformis, and this may be true for numerous frog species susceptible to chytridiomycosis. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study is to determine a healthy fetal growth pattern of twins from a Polish population based on an outcome-dependent growth curve.Methods: The fetal growth data of live-born twin pregnancies between 25th and 40th week gestation in the period of 1 January 2005 to 31 March 2018 from the database of a tertiary care women's hospital in Western Poland was used to calculate birth weight percentiles. The growth curves of singletons from the same database were used as comparison. Because this study aimed for an outcome-dependent approach for the calculation of fetal growth curves, all babies born that may have high risk of unfavorable outcome were excluded. After application of all exclusion criteria, 1317 records referring to 2634 children were included in our analysis. Growth curves of singletons from the same database were used as reference for this study.Results: A linear relationship between 10th, 50th, and 90th percentiles and gestational age were found for twins but not for singletons suggesting the different mechanisms of intrauterine growth between singleton and twin pregnancies. Week-to-week weight gain equal to or higher than 150 g in twins also predict a favorable outcome in absence of other pathologies.Conclusion: The calculated outcome-dependent fetal growth curves for twins in this study may help in the accurate diagnosis of small or large twin fetuses for their gestational age in this Western Poland population. [ABSTRACT FROM AUTHOR]

Background/introduction: In the absence of evidence‐based findings for Saxonian Chicken (SaChi) and German Langshan bantam (GLB), which are indigenous endangered German fancy chicken breeds, the objective of the present study was to characterise their growth performance and meat potential in an extensive free‐range system Methods: A total of 340 hatching eggs from SaChi and 439 eggs from GLB were provided by private breeders, from which 263 SaChi (77.3%) and 174 GLB (39.6%) hatched (p < 0.001) Results: By week 20, SaChi reached body weights of 2362.3 ± 315.3 g (mean ± SD; roosters) and 1624.7 ± 158.9 g (hens), while GLB weighed 1089.7 ± 148.3 g (roosters) and 820.4 ± 89.5 g (hens). Fitting the non‐linear regression of growth data to the Gompertz function estimated asymptotic body weights of 3131.4, 2363.9, 1359.2 and 1107.3 g, with inflection point times of 10.5, 10.3, 9.2 and 9.3 weeks in male SaChi, female SaChi, male GLB and female GLB, respectively. Moderate plumage damage was observed on days 18, 35, 53, 70 and 105 in SaChi and on days 53, 70 and 105 in GLB, while all birds presented completely intact plumage on day 140. Using a binary logistic regression model, breed, age and sex were shown to affect the plumage condition (p < 0.001 each). Roosters were slaughtered in week 20. No breed effects were detected in the carcass yield (SaChi: 68.8 ± 1.7%, GLB: 69.7 ± 1.8%) (p = 0.135) or abdominal fat share (SaChi: 0.89 ± 0.15%, GLB: 1.08 ± 0.14%) (p = 0.281). The percentage of valuable cuts (breast fillets and legs) in the carcass was 43.8 ± 1.9% for SaChi and 43.1 ± 3.0% for GLB (p = 0.490) Discussion/conclusions: In conclusion, this study provides insights into the performance traits and welfare indicators during the rearing of two endangered German chicken breeds. [ABSTRACT FROM AUTHOR]

The objectives of this study were a) to compare growth functions for describing the early growth curve of Romane sheep based on weighing records, b) to estimate the heritability of the growth curve parameters, and c) to estimate genetic parameters for 90-days-old bodyweight utilizing the data of earlier age. The raw data included 662 lambs (316 males and 346 females) bred at the Romane Sheep Research Center, INRAE, France. The studied trait was the bodyweight of lambs at birth, 15, 21, 35, 60, and 90 days of age. The number of measurements was approximately six for each animal. Dataset after mining consisted of 3261 weight records of 574 lambs. We applied four non-linear growth functions, including Gompertz, Brody, Logistic, and Richards. The goodness of fit for each equation was compared using the Akaike information criterion (AIC), coefficient of determination (R2 ) and residual mean square (MSE). Predicting abilities of the included models were evaluated by comparing the predicted and observed phenotypes until 90 days of age. Genetic parameters of the non-linear functions were obtained using a specific two steps approach; in first step, the parameters of the different functions were estimated, and in the second, the parameters were considered as observations and we analyzed them using a multiple trait animal models. Residual mean square and R2 for the models of Brody, Gompertz, Logistic and Richards were 106.71 and 0.37, 4.79 and 0.94, 7.41 and 0.88, and 9.04 and 0.88, respectively. The Logistic function had the smallest AIC and MSE values, and also had the highest R2 value, indicating the best fit. The estimated heritability of the parameters in the logistic function were low (ranging from 0.007 to 0.017). In our study, the correlation between BV90 and BV35 was 0.54 with a confidence interval of 0.47-0.61. Since BV90 and BV35 have a positive genetic correlation, BV35 could be used to select the lambs for best growth until the slaughter age of Romane using the Logistic model. [ABSTRACT FROM AUTHOR]

The South African spearfishery targets a variety of data-deficient species, which are consequently poorly managed. This study aimed to describe the age and growth of one of these species, the Cape knifejaw, Oplegnathus conwayi, which is endemic to the southern and eastern coasts of South Africa. Monthly biological samples were collected through research spearfishing (n = 170) and augmented by recreational spearfishers' catches (n = 135). The results indicated that the O. conwayi population sex ratio was skewed towards males (1M:0.6F). The length- and age-frequency distributions were similar between sexes. Oplegnathus conwayi is a relatively slow-growing species, with a maximum-recorded age of 27 years. No significant differences were observed between male and female growth, with the overall population growth curve being best described as L(t) = 697.15(1 − e−0.06(t−6.30)). The slow growth observed in this species is characteristic of a species that is vulnerable to overexploitation, and accordingly a precautionary approach to future management is recommended. [ABSTRACT FROM AUTHOR]

Objective: To provide new information about androgen insensitivity syndrome (AIS), we studied growth patterns in Chinese children with AIS. Subjects: Data are from 118 untreated AIS patients who were admitted to eight pediatric endocrine centers from January 2010 to December 2019. Methods: In this retrospective cohort study, clinical data were collected from a multicenter database. We compared physical assessment data among AIS patients and standard growth charts for Chinese pediatric population. Results: 1. Children with AIS grew slightly less than the mean before 6 months of age, and then, height gradually increased before 12 years of age, from the median to +1 standard deviation (SD), according to the standard reference for Chinese pediatric population. After 12 years of age, height showed differently in profiles: The mean height in AIS patients gradually decreased from the mean to −1 SD, according to the standard for Chinese boys, and increased from the mean to +2 SD, according to the standard for Chinese girls. 2. The weights of children with AIS were greater than the mean standards of Chinese pediatric population from newborn to 11 years of age. From 12–16 years of age, the mean weight of children with AIS showed different profiles, from the mean to −1 SD, according to the standard for Chinese boys and from the mean to +1.5 SD, according to the standard for Chinese girls. 3. Weight standard deviation (WtSDS) and target height (THt) in northern Chinese AIS patients were significantly higher than those from the southern region (p = 0.035, 0.005, respectively). Age in northern Chinese AIS patients was significantly younger than those from the southern region (p = 0.034). No difference was found among birth weight (BW), birth length (BL), height standard deviation (HtSDS) and body mass index (BMI) in AIS patients from different regions (p > 0.05). 4. HtSDS and WtSDS in complete AIS (CAIS) patients were higher than those in partial AIS (PAIS) patients without significant difference (p > 0.05). Conclusions: Growth of children with AIS varied to different degrees. AIS patients seemed not to experience a puberty growth spurt. CAIS and PAIS patients show little difference in their growth. Regional differences have no effect on the height but influence the weight of AIS patients. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The NIA Long Life Family Study (LLFS) is a longitudinal, multicenter, multinational, population-based multigenerational family study of the genetic and nongenetic determinants of exceptional longevity and healthy aging. The Visit 1 in-person evaluation (2006-2009) recruited 4 953 individuals from 539 two-generation families, selected from the upper 1% tail of the Family Longevity Selection Score (FLoSS, which quantifies the degree of familial clustering of longevity). Demographic, anthropometric, cognitive, activities of daily living, ankle-brachial index, blood pressure, physical performance, and pulmonary function, along with serum, plasma, lymphocytes, red cells, and DNA, were collected. A Genome Wide Association Scan (GWAS) (Ilumina Omni 2.5M chip) followed by imputation was conducted. Visit 2 (2014-2017) repeated all Visit 1 protocols and added carotid ultrasonography of atherosclerotic plaque and wall thickness, additional cognitive testing, and perceived fatigability. On average, LLFS families show healthier aging profiles than reference populations, such as the Framingham Heart Study, at all age/sex groups, for many critical healthy aging phenotypes. However, participants are not uniformly protected. There is considerable heterogeneity among the pedigrees, with some showing exceptional cognition, others showing exceptional grip strength, others exceptional pulmonary function, etc. with little overlap in these families. There is strong heritability for key healthy aging phenotypes, both cross-sectionally and longitudinally, suggesting that at least some of this protection may be genetic. Little of the variance in these heritable phenotypes is explained by the common genome (GWAS + Imputation), which may indicate that rare protective variants for specific phenotypes may be running in selected families. [ABSTRACT FROM AUTHOR]

We present the results of a prospective, observational, descriptive, cross‐sectional study performed on a Mexican population of 1867 children, aged 0–18 years, with Down syndrome (DS), observed between 2013 and 2019. A total of 9968 measurements of height, weight, and head circumference, as well as calculation of body mass index (BMI) were used to create growth charts and tables of percentiles. Growth curves were elaborated using Cole's LMS method. The mean weight and length at birth did not differ by sex: the weight was 2750 g for boys and 2710 g for girls (p > 0.05), and the length was 48.2 cm for boys and 47.9 cm for girls (p > 0.05). The mean final height at 18 years was different by sex: 149.6 cm for boys and 141.2 cm for girls. The average BMI at 18 years was 24.2 kg/m2 for boys and 21.9 kg/m2 for girls. In a comparison with U.S. growth charts, we find that the Mexican population has lower height and weight. These are the first growth curves for the Mexican population with DS. They can be used by health care providers to optimize preventive care by monitoring children with DS for the early identification of factors that affect individual growth. [ABSTRACT FROM AUTHOR]

Large datasets of detailed anthropometric measurements are scarce in children. The Japanese Standard Association 1978–1981 survey provides a rare opportunity to use high quality data from Japanese children. To construct inside leg length (ILL) and inside leg length to stature ratio (ILL/S) reference centile curves for Japanese children. The study sample consisted of 14,825 boys and 14,577 girls age 0–18 years for stature and weight measurements, and 9064 boys and 8796 girls age 0–12 years for ILL measurements, who participated in the 1978–1981 national survey on body sizes. LMS method was used to construct the reference centile curves. The reference centile curves for stature, weight, ILL, and ILL/S were compared to those of British children. The L, M, and S reference values for Japanese children are presented for stature, weight, ILL, and ILL/S. Compared with British children of 0–12 years of age, Japanese children of 0–12 years of age had shorter median stature, shorter median ILL, and shorter median ILL/S. We present the first reference values for ILL and ILL/S in Japanese children. Japanese children had relatively shorter legs compared to British children from infancy. [ABSTRACT FROM AUTHOR]

The measurement of fungal cell growth in submerged culture systems containing insoluble compounds is essential yet difficult due to the interferences from the insoluble compounds like biopolymers. Here, we developed a fluorescent strategy based on chitosan-modified fluorescein isothiocyanate (GC-FITC) to monitor the cell growth of lignocellulosic fungi cultivated on biopolymers. GC-FITC could stain only lignocellulosic fungi (Tricoderma reesei, Penicillium oxalicum, Aspergillus nidulans , and Neurospora crassa), but not biopolymers (cellulose, xylan, pectin, or lignin), excluding the interferences from these insoluble biopolymer. Moreover, a linear relationship was observed between the fluorescence intensity of GC-FITC absorbed by lignocellulosic fungi and the biomass of lignocellulosic fungi. Therefore, GC-FITC was leveraged to monitor the cell growth of lignocellulosic fungi when using biopolymers like cellulose as the carbon sources, which is faster, more convenient, time-saving, and cost-effective than the existing methods using protein/DNA content measurement. GC-FITC offers a powerful tool to detect fungal growth in culture systems with insoluble materials. [ABSTRACT FROM AUTHOR]

Copyright of Atatürk University Journal of Agricultural Faculty is the property of Ataturk University Coordinatorship of Scientific Journals and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: The growth curve has a significant role in understanding the growth trajectories over time and examining the mathematical relationship between the outcome variable and time. Study design: A longitudinal prospective cohort study. Methods: This study aimed to identify a nonlinear growth curve that best represents the growth trajectories in children's physical growth from ages 1 to 15 years. The data were obtained from the Young Lives study conducted in Ethiopia, India, Peru, and Vietnam. Nonlinear growth curves were studied through the families of three-parameter nonlinear mixed-effects models. Results: The study examined the performances of different three-parameter nonlinear growth curves for the growth trajectory analysis, and the Logistic curve was chosen for the trajectory analysis. Gender and country differences had significant effects on the child's growth. Females reached asymptotic height earlier and shorter than males. The mean height values at the end of the growth stage for children in Ethiopia, India, Peru, and Vietnam were 171.78, 170.37, 171.30, 174.31cm, respectively. Children in Ethiopia approached adult height earlier than those in India but later than children in Peru. However, no significant growth change was observed between children in Ethiopia and Vietnam. This indicates that children in Ethiopia and Vietnam have no significant differences regarding approaching adult height. Conclusion: The study concludes that the Logistic curve was found to be the best growth curve to describe the growth trajectories. Children in all four countries exhibited different growth parameters. [ABSTRACT FROM AUTHOR]

Latent growth curve models tested associations among age, four sources of religious doubt and emotional wellbeing. Adults (N = 179, men age = 37.9 yrs) completed three waves of data collection over a two-year period. Older age was associated with lower initial levels of life satisfaction (b = -.103) and lower initial positive affect (b = -.047) and faster decline in positive affect (b =.028). Age was not significantly associated with initial levels of negative affect. Higher doubts related to the benevolence of God affected initial levels of life satisfaction and positive affect. Only doubts related to felt pressures from one's religious community influenced initial levels and rates of increase over time in negative affect. Drawing on Socioemotional Selectivity Theory and gerotranscendence theory, findings suggest that age and sources religious doubt differentially influence a range of wellbeing outcomes, exacerbating negative affect. [ABSTRACT FROM AUTHOR]