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Background Recording and analyzing microbial growth is a routine task in the life sciences. Microplate readers that record dozens to hundreds of growth curves simultaneously are increasingly used for this task raising the demand for their rapid and reliable analysis. Results Here, we present Dashing Growth Curves, an interactive web application ( http://dashing-growth-curves.ethz.ch/ ) that enables researchers to quickly visualize and analyze growth curves without the requirement for coding knowledge and independent of operating system. Growth curves can be fitted with parametric and non-parametric models or manually. The application extracts maximum growth rates as well as other features such as lag time, length of exponential growth phase and maximum population size among others. Furthermore, Dashing Growth Curves automatically groups replicate samples and generates downloadable summary plots for of all growth parameters. Conclusions Dashing Growth Curves is an open-source web application that reduces the time required to analyze microbial growth curves from hours to minutes.

Background Characterization of microbial growth is of both fundamental and applied interest. Modern platforms can automate collection of high-throughput microbial growth curves, necessitating the development of computational tools to handle and analyze these data to produce insights. Results To address this need, here I present a newly-developed R package: gcplyr. gcplyr can flexibly import growth curve data in common tabular formats, and reshapes it under a tidy framework that is flexible and extendable, enabling users to design custom analyses or plot data with popular visualization packages. gcplyr can also incorporate metadata and generate or import experimental designs to merge with data. Finally, gcplyr carries out model-free (non-parametric) analyses. These analyses do not require mathematical assumptions about microbial growth dynamics, and gcplyr is able to extract a broad range of important traits, including growth rate, doubling time, lag time, maximum density and carrying capacity, diauxie, area under the curve, extinction time, and more. Conclusions gcplyr makes scripted analyses of growth curve data in R straightforward, streamlines common data wrangling and analysis steps, and easily integrates with common visualization and statistical analyses.

Background Achondroplasia is the most common genetic skeletal disorder causing disproportionate short stature/dwarfism. Common additional features include spinal stenosis, midface retrusion, macrocephaly and a generalized spondylometaphyseal dysplasia which manifest as spinal cord compression, sleep disordered breathing, delayed motor skill acquisition and genu varus with musculoskeletal pain. To better understand the interactions and health outcomes of these potential complications, we embarked on a multi-center, natural history study entitled CLARITY (achondroplasia natural history study). One of the CLARITY objectives was to develop growth curves (length/height, weight, head circumference, weight-for-height) and corresponding reference tables of mean and standard deviations at 1 month increments from birth through 18 years for clinical use and research for achondroplasia patients. Methods All available retrospective anthropometry data including length/height, weight and head circumference from achondroplasia patients were collected at 4 US skeletal dysplasia centers (Johns Hopkins University, AI DuPont Hospital for Children, McGovern Medical School University of Texas Health, University of Wisconsin School of Medicine and Public Health). Weight-for-age values beyond 3 SD above the mean were excluded from the weight-for-height and weight-for-age curves to create a stricter tool for weight assessment in this population. Results Over 37,000 length/height, weight and head circumference measures from 1374 patients with achondroplasia from birth through 75 years of age were compiled in a REDCap database. Stature and weight data from birth through 18 years of age and head circumference from birth through 5 years of age were utilized to construct new length/height-for-age, weight-for-age, head circumference-for-age and weight-for-height curves. Conclusion Achondroplasia-specific growth curves are essential for clinical care of growing infants and children with this condition. In an effort to provide prescriptive, rather than purely descriptive, references for weight in this population, extreme weight values were omitted from the weight-for-age and weight-for-height curves. This well-phenotyped cohort may be studied with other global achondroplasia populations (e.g. Europe, Argentina, Australia, Japan) to gain further insight into environmental or ethnic influences on growth.

Rapid isolation of therapeutic bacteriophages from environmental sources is essential for personalized phage therapy, particularly when appropriate phages are unavailable in existing banks. However, comprehensive characterization of all candidate phages is resource-intensive, especially when plaque morphologies are similar and fail to discriminate between distinct phages. Here, we present an upstream screening approach that utilizes co-culture growth curve analysis to rapidly triage phage isolates during the early isolation process. We extracted seven biologically meaningful features that capture lysis kinetics, lysis efficiency, and post-lysis dynamics from bacterial growth curves and applied unsupervised clustering algorithms for phage discrimination. Validation using T-phages at a multiplicity of infection of 0.01 demonstrated superior clustering performance (Adjusted Rand Index = 0.881 ± 0.057) compared to established metrics including the Virulence Index and Centroid Index. Application to phages isolated from sewage successfully identified all three genomically distinct species present (sampling score = 1.0), enabling targeted selection of representative phages for downstream characterization. This approach reduced candidates requiring detailed analysis by two-thirds (from 21 to 7 isolates) while maintaining complete species coverage, thereby providing an efficient and scalable screening tool that reduces workload for downstream analyses and accelerates discovery of novel therapeutic phages for clinical applications.

Brain development from 1 to 6 years of age anchors a wide range of functional capabilities and carries early signs of neurodevelopmental disorders. However, quantitative models for depicting brain morphology changes and making individualized inferences are lacking, preventing the identification of early brain atypicality during this period. With a sample size of 285, we characterized the age dependence of the cortical thickness and subcortical volume in neurologically normal children and constructed quantitative growth charts of all brain regions for preschool children. While the cortical thickness of most brain regions decreased with age, the entorhinal and parahippocampal regions displayed an inverted-U shape of age dependence. Compared to the cortical thickness, the normalized volume of subcortical regions exhibited more divergent trends, with some regions increasing, some decreasing, and some displaying inverted-U-shaped trends. The growth curve models for all brain regions demonstrated utilities in identifying brain atypicality. The percentile measures derived from the growth curves facilitate the identification of children with developmental speech and language disorders with an accuracy of 0.875 (area under the receiver operating characteristic curve: 0.943). Our results fill the knowledge gap in brain morphometrics in a critical development period and provide an avenue for individualized brain developmental status evaluation with demonstrated sensitivity. The brain growth charts are shared with the public (http://phi-group.top/resources.html). [Display omitted]

The identification of somatic growth, through reference curves, can be used to create strategies and public policies to reduce public health problems such as malnutrition and obesity and to identify underweight, overweight and obesity. The purpose of this systematic review was to identify studies providing reference growth curves for weight status in children and adolescents. A systematic search was conducted in eight databases and in gray literature (Google scholar). To assess the risk of bias/methodological quality of studies, the National Institutes of Health (NIH) Quality Assessment Tool for Observational Cohort and Cross-sectional Studies (NHLBI) was used. Overall, 86 studies that met the inclusion criteria were included. Through the values   of reference growth curves for the identification of underweight, overweight and obesity, it was possible to verify that there is great variability among percentiles for the identification of underweight, overweight and obesity. The most prevalent percentiles for underweight were P3 and P5; for overweight, the most prevalent was P85 and the most prevalent percentiles for obesity were P95 and P97. The most prevalent anthropometric indicators were Body Mass Index (BMI), Waist Circumference (WC), Body Mass (BM) for age and height for age. Conclusion: Such data can demonstrate that the optimal growth must be reached, through the standard growth curves, but that the reference curves demonstrate a cut of the population growth, raising possible variables that can influence the optimal growth, such as an increase in the practice of physical activities and an awareness of proper nutrition.

Abstract Context We characterized linear growth in infants and children with X-linked hypophosphatemia (XLH). Objective Provide linear growth curves for children with XLH from birth to early adolescence. Design Data from 4 prior studies of XLH were pooled to construct growth curves. UX023-CL002 was an observational, retrospective chart review. Pretreatment data were collected from 3 interventional trials: two phase 2 trials (UX023-CL201, UX023-CL205) and a phase 3 trial (UX023-CL301). Setting Medical centers with expertise in treating XLH. Patients Children with XLH, 1-14 years of age. Intervention None. Main Outcome Measure Height-for-age linear growth curves, including values for the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles for children with XLH compared to population norms. Results A total of 228 patients (132 girls, 96 boys) with 2381 height measurements were included. Nearly all subjects (> 99%) reported prior management with supplementation therapy. Compared to the Center for Disease Control and Prevention growth curves, boys at age 3 months, 6 months, 9 months, 1 year, and 2 years had median height percentiles of 46%, 37%, 26%, 18%, and 5%, respectively; for girls the median height percentiles were 52%, 37%, 25%, 18%, and 7%, respectively. Annual growth in children with XLH fell below that of healthy children near 1 year of age and progressively declined during early childhood, with all median height percentiles < 8% between 2 and 12 years old. Conclusion Children with XLH show decreased height gain by 1 year of age and remain below population norms thereafter. These data will help evaluate therapeutic interventions on linear growth for pediatric XLH.

The sex-specific differences in the growth and population characteristics of the high-commercial-value sand crab Ovalipes punctatus were investigated in Korea. The estimated allometric growth between the sexes showed significant differences in all morphometric measurements. In the classification of growth types, carapace width-chela length exhibited positive and negative allometric growth in males and females, respectively. Carapace width-abdominal width showed positive relative growth in both sexes, and orbital spine width exhibited negative relative growth in both sexes. Consequently, sexual dimorphism was evident in all measured traits. Growth parameters estimated using the ELEFAN function of the FiSAT II program indicated higher values in males compared to females. Asymptotic length (CW ∞ ) for males was estimated at 139.2 mm, whereas for females it was 116.6 mm. Additionally, the growth coefficient (K) was higher in males (0.65) than in females (0.54), suggesting faster growth in males. The winter point (WP) was 1 for males and 0.7 for females, indicating slower growth in males during the colder December and slower growth in females during the spawning period in August. The modified von Bertalanffy growth curves indicated asymptotic growth in all sexes, and the growth performance index (φ') showed higher values in males (4.10) compared to females (3.87), reflecting differences in growth curves. The steady increase in recruitment rates from July to September was associated with the appearance of larvae and their subsequent growth into juveniles, leading to their recruitment into the population during this period. Therefore, O. punctatus exhibited sex-specific differences in growth parameters, suggesting distinct growth strategies between the sexes.

Modeling and analysis of biological growth curves are an age-old study area in which much effort has been dedicated to developing new growth equations. Recent efforts focus on identifying the correct model from a large number of equations. The relative growth rate (RGR), developed by Fisher (1921), has largely been used in the statistical inference of biological growth curve models. It is convenient to express growth equations using RGR, where RGR can be expressed as functions of size or time. Even though RGR is model invariant, it has limitations when it comes to identifying actual growth patterns. By proposing interval-specific rate parameters (ISRPs), Pal et al. (2018) appeared to solve this problem. The ISRP is based on the mathematical structure of the growth equations. Therefore, it is not model invariant. The current effort is to develop a measure of growth that is model invariant like RGR and shares the advantages of ISRP. We propose a new measure of growth, which we call instantaneous maturity rate (IMR). IMR is model invariant, which allows it to distinguish growth patterns more clearly than RGR. IMR is also scale-invariant and can take several forms including increasing, decreasing, constant, sigmoidal, bell-shaped, and bathtub. A wide range of possible IMR shapes makes it possible to identify different growth curves. The estimation procedure of IMR under a stochastic setup has been developed. Statistical properties of empirical IMR estimators have also been investigated in detail. In addition to extensive simulation studies, real data sets have been analyzed to prove the utility of IMR.

A twin-based chart of birth weight was useful to avoid overdiagnosis of small for gestational age (SGA) or large for gestational age (LGA) in twins comparing to the singleton-based chart. Several twin-based charts of birth weight were reported based on large data from nationwide, multiple cities or local regions in China. However, these twin-based charts showed inconsistent ranges across gestational age (GA) and not well-consistent growth trajectories, and may require further integration. We aimed to develop a set of smoothed percentile growth curves of twin birth weight in Chinese neonates that allows for continuous use from extremely preterm to full-term. We collected twin birth weight data through a procedure of systematic review by searching PubMed, Scopus, Web of science, Chinese national knowledge infrastructure (CNKI), and Wanfang from their inception to April 30, 2025. Finally, five studies that met the inclusion criteria were included in this present study. We used a two-stage proportionally weighted approach to generate initial integrated percentile data of twin birth weight, and then employed polynomial regression equation and the LMS method to establish the P 3 , P 10 , P 25 , P 50 , P 75 , P 90 , and P 97 reference values of twin birth weight that allowed for continuous use from GA of 22 to 42 weeks in Chinese male and female twins. Our established twin-based growth curves illustrated a distinct pattern comparing to the singleton-based growth curves in China. In conclusion, our established twin-based birth weight percentile references could be preferred over the use of singleton references when diagnosing SGA or LGA in twin newborns or monitoring the growth of twin newborns in China.