Researchers led by Professor Jung-woo Chae of Chungnam National University developed a mathematical model designed to capture individual differences in growth response over time among children with ISS receiving growth hormone treatment. The work, made available online in the journal Value in Health on July 21, 2026, takes a deliberately different approach from many earlier attempts to predict treatment outcomes. Rather than measuring success simply as height gain in centimeters, the team analyzed changes in age- and sex-adjusted height percentiles. This distinction matters clinically. A child who grows six centimeters in a year may still fall further behind peers if those peers grew eight centimeters, whereas a child who climbs from the first percentile toward the tenth is genuinely catching up relative to children of the same age and sex. Percentile-based measures therefore provide a more intuitive and clinically meaningful picture of catch-up growth than absolute height gains alone.

The study itself was retrospective and single-center, drawing on medical records from 91 prepubertal Korean children with idiopathic short stature, 41 boys and 50 girls, who received recombinant human growth hormone, the formulation known as somatropin, between July 2020 and December 2023. The hormone was administered subcutaneously six to seven times per week, with doses adjusted during routine clinical care rather than under experimental conditions. This real-world treatment context is important, because it means the model was built on the kind of heterogeneous, individually tailored dosing patterns that pediatricians actually encounter in practice, rather than the rigid protocols of a controlled trial. The researchers collected demographic data, growth measurements, parental heights, laboratory values, and treatment information from the records, assembling a longitudinal dataset that could support sophisticated modeling of growth trajectories.

At the heart of the analysis was a Gompertz nonlinear mixed-effects model, a mathematical framework well suited to biological growth processes. The Gompertz function describes growth that is initially rapid and then progressively slows, a pattern that mirrors how children respond to growth hormone therapy, where early catch-up is often followed by diminishing gains. The mixed-effects structure allows the model to separate population-level trends from individual deviations, meaning it can characterize both the typical response across the study group and the substantial variation between individual children. Critically, the researchers incorporated cumulative growth hormone exposure into the model, so that the total dose a child received over time, not just the prescribed daily amount, could be linked to the observed trajectory of height percentile. Over a mean treatment period of 619 days with a standard deviation of 307 days, the mean height percentile in the cohort rose from 1.26 at baseline to 9.16 at follow-up, a striking illustration of what catch-up growth looks like on the percentile scale.

The model estimated a total growth-response parameter of approximately 17.2 percentile points, representing the potential shift in height percentile attributable to treatment under the fitted framework. Yet the more clinically valuable finding was not the average but the spread: responses differed substantially among patients, and the model identified baseline characteristics that predicted where an individual child was likely to fall within that range. According to Professor Chae, three baseline factors were associated with a greater predicted response: higher body mass index, lower levels of insulin-like growth factor-binding protein 3, known as IGFBP-3, and shorter paternal height. Of these, body mass index showed the strongest association with predicted response. Each of these variables is routinely available before therapy starts, which is precisely what makes the finding actionable. A pediatrician weighing whether to initiate growth hormone treatment can already measure a child’s BMI, order an IGFBP-3 assay, and record parental heights without any additional testing burden.

The biological logic behind these predictors is plausible, even though the study establishes association rather than mechanism. Higher BMI has been linked in prior pediatric endocrinology literature to greater growth hormone responsiveness, possibly reflecting differences in metabolism and hormone signaling in children with more adipose tissue. IGFBP-3 is the principal carrier protein for insulin-like growth factor 1, the mediator through which growth hormone exerts much of its effect on the growth plate, and lower circulating levels may indicate a state in which the growth axis has more room to respond to exogenous stimulation. Shorter paternal height, meanwhile, may serve as a proxy for the genetic height potential that treatment is working against, with children whose fathers are shorter having relatively more percentile ground to recover. The model does not prove these causal pathways, but it demonstrates that routinely collected clinical variables carry genuine predictive information about treatment response.

To translate the statistical framework into something usable at the point of care, the team also developed GrowCast, a web-based tool that generates individualized predicted height and percentile trajectories. The tool requires only seven inputs: the child’s age, sex, current height, weight, paternal height, IGFBP-3 level, and the intended growth hormone dose. From these, it produces modeled growth trajectories that clinicians can inspect, compare, and discuss. Professor Chae emphasized that GrowCast enables clinicians to compare modeled treatment scenarios and communicate potential growth trajectories with patients and families. This simulation capability addresses one of the most persistent communication gaps in pediatric endocrinology. Families often struggle to interpret statements about average response rates, and a visualized, individualized trajectory, complete with the uncertainty inherent in prediction, can ground conversations about what therapy realistically offers a particular child.

The two-year simulations built into the study illustrate just how wide the range of predicted outcomes can be. Depending on a child’s body mass index, IGFBP-3 level, paternal height, and cumulative growth hormone exposure, median predicted height percentiles ranged from 4.0 percent in lower-response profiles to 31.0 percent in higher-response profiles. In other words, two children who look superficially similar at the start of treatment could be headed toward very different destinations on the growth chart. This heterogeneity is exactly why a one-size-fits-all description of growth hormone benefit has served families poorly, and why the researchers argue that individual characteristics should be considered when assessing the expected response to therapy. The simulations also allow exploration of different dosage regimens, showing how predicted trajectories shift under various treatment scenarios before any commitment to a particular plan is made.

The researchers are careful about the limits of what they have built. GrowCast is not yet a validated dosing-prescription tool, and the study’s retrospective, single-center design, with its cohort of 91 Korean children, means the model must be tested in larger, prospective, multicenter studies before it can be implemented routinely in clinical practice. Cohort-specific factors, local treatment conventions, and population differences in growth patterns all warrant verification in independent datasets. Nevertheless, the study offers a promising framework for more personalized growth hormone treatment in idiopathic short stature. By combining routinely available baseline characteristics with cumulative growth hormone exposure in a rigorous nonlinear mixed-effects model, the approach may help clinicians estimate individual growth trajectories, support more informed treatment planning, and move pediatric growth hormone therapy away from a trial-and-error enterprise toward genuine personalized medicine.

Subject of Research: Predictive modeling of growth hormone therapy response in children with idiopathic short stature

Article Title: Chungnam National University researchers develop model for predicting growth hormone therapy responses in children with short stature

Article References: Chungnam National University researchers develop model for predicting growth hormone therapy responses in children with short stature. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: idiopathic short stature, growth hormone therapy, Gompertz model, nonlinear mixed-effects modeling, height percentile, pediatric endocrinology, IGFBP-3, body mass index, personalized medicine, pharmacometrics, GrowCast, Value in Health

The research, led by Dhomas Indiwara Prana Jhouhanggir and colleagues working with the Environmental Agency of Bantul Regency in Yogyakarta, Indonesia, began with a sobering field assessment. Monthly monitoring of the centralized activated sludge treatment plant serving ten leather tanning industries revealed persistent compliance failures. Ammonia concentrations in the treated effluent ranged from 2.24 to 11.10 milligrams per liter throughout 2025, consistently exceeding the local discharge limit of 0.5 milligrams per liter. BOD5 and COD also spiked dramatically in some months, peaking at 225 and 487 milligrams per liter respectively in August, far above the regulatory thresholds of 50 and 110 milligrams per liter.

These failures are not surprising. Activated sludge systems depend on delicate microbial communities whose nitrifying bacteria are highly sensitive to the wild fluctuations in flow, salinity, pH, and toxic load that characterize tannery wastewater. Influent flow at the Bantul plant nearly doubled between January and February 2025, swinging from 437 to 868 cubic meters per month. During a three-day field assessment conducted alongside the laboratory experiments, the full-scale system removed only about 26 percent of influent ammonia, leaving 15.64 milligrams per liter in the effluent, and achieved just 24 percent removal of total dissolved solids, which remained far above the 2000 milligram per liter limit.

To address these weaknesses, the team turned to microalgae, organisms that photosynthesize, assimilate nitrogen and phosphorus directly into their cells, and tolerate environmental variability better than bacterial consortia. The researchers obtained a Chlorella vulgaris culture from the Jepara Brackishwater Aquaculture Fisheries Center and verified its identity twice over. Light microscopy showed the characteristic unicellular, spherical cells averaging 6.33 micrometers in diameter, while PCR amplification and sequencing of the 18S rRNA gene returned 100 percent query coverage and 100 percent sequence identity against reference strains in the NCBI GenBank database. A phylogenetic tree placed the isolate firmly within the authenticated C. vulgaris clade, closest to strains from South Korea, Cape Verde, and Malaysia, confirming a globally conserved genetic profile for this species.

The experimental heart of the study was a two-stage cultivation design. Tannery effluent collected from the equalization tank of the centralized plant was centrifuged to reduce turbidity and sterilized before inoculation with three different proportions of algal culture: 10, 20, and 30 percent by volume, each supplemented with Walne medium. Each stage lasted seven days at 24 degrees Celsius under continuous illumination of 5000 lux with aeration. Growth was tracked daily by optical density and fitted to the Gompertz kinetic model, which achieved coefficients of determination between 0.9906 and 0.9966 across all treatments, indicating an excellent fit to the observed growth dynamics.

The two-stage strategy proved decisive. In the first stage, the raw effluent’s high pollutant load, turbidity, and toxic constituents such as chromium and sulfide suppressed growth, particularly at lower inoculum densities where longer lag phases reflected slower acclimatization and greater sensitivity to ammonia inhibition. By the second stage, however, the first round of algal treatment had already removed much of the inhibitory load and clarified the medium, allowing better light penetration and faster growth. The maximum specific growth rate in stage two rose to 0.0765 cells per milliliter per day for the 30 percent treatment, statistically comparable to pure culture growth, and the lag phase shortened to just over half a day, indicating rapid adaptation.

Pollutant removal followed the same trajectory of improvement. Under the best-performing condition, CVG 30 percent, the two-stage system achieved 92.94 percent removal of BOD5, 91.60 percent removal of COD, 99.74 percent removal of total chromium, 93.31 percent removal of total nitrogen, and a striking 99.80 percent removal of ammonia. Sulfide removal exceeded 99.99 percent in every treatment, and total suspended solids fell by up to 97.60 percent. Critically, the final concentrations of chromium, BOD5, COD, and ammonia all fell within the applicable regulatory discharge limits, a feat the existing full-scale activated sludge system could not match for most of these parameters during the same period. Only total dissolved solids remained above the limit, at 3740 milligrams per liter, reflecting the inherent difficulty of biologically removing dissolved inorganic ions such as chloride, sodium, and sulfate.

The authors attribute this performance to the complementary mechanisms of phycoremediation. Dissolved pollutants first adhere to the algal cell surface through biosorption, involving adsorption, ion exchange, surface complexation, precipitation, and electrostatic interactions. Living cells then transport selected nutrients and contaminants intracellularly, where nitrogen from ammonia is incorporated into amino acids, proteins, and nucleic acids, directly linking pollutant removal to biomass production. Meanwhile, photosynthetic oxygen generation supports aerobic degradation of organic matter by associated microorganisms, and enzymatic transformations break down complex organics both outside and inside the cells. This metabolic flexibility explains why microalgae outperformed conventional biological treatment on the very pollutants, especially ammonia, that most plague activated sludge operations.

Beyond water cleaning, the study adds a waste-to-resource dimension by characterizing the fatty acid methyl ester profile of the biomass harvested from the best treatment. The lipid composition proved remarkably balanced: 28.41 percent saturated fatty acids, 35.17 percent monounsaturated fatty acids, and 36.41 percent polyunsaturated fatty acids. Methyl palmitate dominated the saturated fraction at 22.40 percent, a hallmark of biodiesel feedstocks. Methyl cis-11-eicosenoate, a long-chain monounsaturated ester with potential lubricity and even immunostimulatory pharmaceutical applications, reached 16.67 percent, an unusually high level that suggests wastewater cultivation may enhance long-chain monounsaturated lipid synthesis. Most notably, methyl linoleate accounted for 26.36 percent of the total, and the biomass also contained gamma-linolenic acid, eicosapentaenoic acid, and docosahexaenoic acid, omega fatty acids associated with cardiovascular protection, anti-inflammatory effects, and neurological development.

The researchers caution that fatty acid composition alone does not establish a specific commercial application, and that pilot and full-scale trials will be needed to evaluate long-term stability, energy requirements, and economic feasibility when the algal process is integrated with existing infrastructure. Because dissolved solids resist biological removal, a membrane polishing step such as ultrafiltration or reverse osmosis may still be required to meet the TDS standard. Nevertheless, the integrated assessment, spanning molecular strain verification, kinetic growth modeling, pollutant removal, field benchmarking against a real treatment plant, and biochemical biomass characterization, provides one of the most comprehensive demonstrations to date that two-stage microalgal cultivation can transform tannery effluent from a regulatory liability into a feedstock, closing the loop in one of the world’s most polluting industries.

Subject of Research: Two-stage microalgae cultivation for tannery industrial effluent treatment and biomass valorization

Article Title: Two-stage cultivation of microalgae C. vulgaris for tannery industrial effluent treatment: strain verification, growth performance, pollutant removal, and fame characterization

Article References: Jhouhanggir, D. I. P., Pertiwiningrum, A., Kollia, C., Dardavila, M. M., Lymperopoulou, T., Fitriyanto, N. A., Suyono, E. A., Abidin, M. Z., & Widiastuti, I. (2026). Two-stage cultivation of microalgae C. vulgaris for tannery industrial effluent treatment: strain verification, growth performance, pollutant removal, and FAME characterization. Case Studies in Chemical and Environmental Engineering, 14, Article 101476. https://doi.org/10.1016/j.cscee.2026.101476

Image Credits: AI Generated

DOI: 10.1016/j.cscee.2026.101476

Keywords: Chlorella vulgaris, tannery wastewater, phycoremediation, ammonia removal, chromium removal, two-stage cultivation, Gompertz model, FAME profile, biodiesel, activated sludge, wastewater treatment, biomass valorization