Application and validation of a biotic ligand model for calculating acute toxicity of lead to Moina dubia in lakes of Hanoi, Vietnam.

It is increasingly being recognized that biotic ligand models (BLMs) can successfully predict the toxicity of divalent metals toward aquatic biota applied to temperate freshwater ecosystems. However, studies on the eutrophic lakes in tropical regions toward native tropical organisms, including Moina, are relatively limited. In this study, Moina dubia, the native organism of the Hanoi eutrophic urban lakes, were used in toxicological studies of lead (Pb); 24-h EC50 value of Pb was 523.19 µg/L under optimal living conditions for M. dubia in the laboratory. The constant binding of Pb2+ on M. dubia surface sites (log KPbBL = 2.38) was significantly low. Other stability constants were obtained under experiments as logKCaBL = 2.48, logKMgBL = 2.80, logKNaBL = 2.35, logKKBL = 2.49, and logKHBL = 3.026. A BLM was developed to calculate the acute toxicity (EC50-24 h) of lead on M. dubia based on the condition of the urban lakes of Hanoi. Validation with toxicity data in synthetic medium showed a coefficient determination of 79.16% and a mean absolute percentage error (MAPE) of 10.2%, while the validation with the toxicity data with natural water medium from 11 Hanoi lakes showed a coefficient determination of 73.7% and a MAPE of 13.66%. The BLM worked well with water at a pH of 7.0 to 8.0, but failed with water at a pH above 8.0. Eutrophic conditions proved to have a significant effect on the toxicity of lead on local zooplankton.

Development and Validation of Clinical Diagnostic Model for Girls with Central Precocious Puberty: Machine-learning Approaches.

BACKGROUND: A brief gonadotropin-releasing hormone analogues (GnRHa) stimulation test which solely focused on LH 30-minute post-stimulation was considered to identify girls with central precocious puberty (CPP). However, it was tested using traditional statistical methods. With advanced computer science, we aimed to develop a machine learning-based diagnostic model that processed baseline CPP-related variables and a brief GnRHa stimulation test for CPP diagnosis. METHODS: We recruited girls suspected of precocious puberty and underwent a GnRHa stimulation test at Children Hospital 2, Vietnam, and Cathay General Hospital, Taiwan. Clinical data, bone age measurement, and 30-min post-stimulation blood test were used to build up the predictive model. The candidate model was developed by different machine learning algorithms that were mainly evaluated by sensitivity, specificity, the area under the receiver operator characteristic curve (AUC), and F1-score in internal and external validation data to classify girls as CPP and non-CPP at different time-points (0-min, 30-min, 60-min, and 120-min post-stimulation). RESULTS: Among the 614 girls diagnosed with PP, 524 (85.3%) had CPP. The random forest algorithm yielded the highest value of F1-score (0.976), specificity (0.893), positive predicted value (0.987), and relatively high value of AUC (0.972) that contributed to high probability to identify CPP. The performance metrics of the 30-min post-stimulation diagnostic model including sensitivity and specificity surpassed those of the 0-minute model (0-min) and were equivalent to those of the model obtained 60-min and 120-min post-stimulation. Hence, our machine learning-based model helps shorten the stimulation test to 30 minutes after GnRHa injection, in general, it requires 120 minutes for a completed GnRHa stimulation test. CONCLUSIONS: We developed a diagnostic model based on clinical features and a single sample 30-minute post-stimulation to identify CPP in girls that can reduce distress for children caused by multiple blood samplings.

Characterization of Solanum melongena Thioesterases Related to Tomato Methylketone Synthase 2.

2-Methylketones are involved in plant defense and fragrance and have industrial applications as flavor additives and for biofuel production. We isolated three genes from the crop plant Solanum melongena (eggplant) and investigated these as candidates for methylketone production. The wild tomato methylketone synthase 2 (ShMKS2), which hydrolyzes ß-ketoacyl-acyl carrier proteins (ACP) to release ß-ketoacids in the penultimate step of methylketone synthesis, was used as a query to identify three homologs from S. melongena: SmMKS2-1, SmMKS2-2, and SmMKS2-3. Expression and functional characterization of SmMKS2s in E. coli showed that SmMKS2-1 and SmMKS2-2 exhibited the thioesterase activity against different ß-ketoacyl-ACP substrates to generate the corresponding saturated and unsaturated ß-ketoacids, which can undergo decarboxylation to form their respective 2-methylketone products, whereas SmMKS2-3 showed no activity. SmMKS2-1 was expressed at high level in leaves, stems, roots, flowers, and fruits, whereas expression of SmMKS2-2 and SmMKS2-3 was mainly in flowers and fruits, respectively. Expression of SmMKS2-1 was induced in leaves by mechanical wounding, and by methyl jasmonate or methyl salicylate, but SmMKS2-2 and SmMKS2-3 genes were not induced. SmMKS2-1 is a candidate for methylketone-based defense in eggplant, and both SmMKS2-1 and SmMKS2-2 are novel MKS2 enzymes for biosynthesis of methylketones as feedstocks to biofuel production.