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A deep learning approach for classifying and predicting children's nutritional status in Ethiopia using LSTM-FC neural networks.
BioData Min
January 2025
Department of Statistics, College of Science, Bahir Dar University, P.O. Box 79, Bahir Dar, Ethiopia.
Background: This study employs a LSTM-FC neural networks to address the critical public health issue of child undernutrition in Ethiopia. By employing this method, the study aims classify children's nutritional status and predict transitions between different undernutrition states over time. This analysis is based on longitudinal data extracted from the Young Lives cohort study, which tracked 1,997 Ethiopian children across five survey rounds conducted from 2002 to 2016.
View Article and Find Full Text PDFAn eastern Congolian endemic, or widespread but secretive? New data on the recently described (Anura, Hyperoliidae) from the Democratic Republic of the Congo.
Zookeys
January 2025
Institute of Vertebrate Biology of the Czech Academy of Sciences, Brno, Czech Republic Institute of Vertebrate Biology of the Czech Academy of Sciences Brno Czech Republic.
The Great Lakes spiny reed frog () was recently described from transitional (submontane) forests at mid-elevations of the Albertine Rift mountains in the eastern Congolian region. Previously, because of its similarity, it had been understood to represent eastern populations of the unrelated , which is known mainly from Cameroon. Based on DNA barcoding, we document the westward extension of the known range of within lowland rainforests in the Northeastern and Central Congolian Lowland Forests.
View Article and Find Full Text PDFThe high compliance of the urinary bladder during filling is essential for its proper function, enabling it to accommodate significant volumetric increases with minimal rise in transmural pressure. This study aimed to elucidate the physical mechanisms underlying this phenomenon by analyzing the ex vivo filling process in rat from a fully voided state to complete distension, without preconditioning, using three complementary imaging modalities. High-resolution micro-CT at 10.
View Article and Find Full Text PDFGDFold2: A fast and parallelizable protein folding environment with freely defined objective functions.
Protein Sci
February 2025
MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing, China.
An important step of mainstream protein structure prediction is to model the 3D protein structure based on the predicted 2D inter-residue geometric information. This folding step has been integrated into a unified neural network to allow end-to-end training in state-of-the-art methods like AlphaFold2, but is separately implemented using the Rosetta folding environment in some traditional methods like trRosetta. Despite the inferiority in prediction accuracy, the conventional approach allows for the sampling of various protein conformations compatible with the predicted geometric constraints, partially capturing the dynamic information.
View Article and Find Full Text PDFQuantifying protein unfolding kinetics with a high-throughput microfluidic platform.
bioRxiv
January 2025
Department of Bioengineering, Stanford University, Stanford, CA 94305.
Even after folding, proteins transiently sample unfolded or partially unfolded intermediates, and these species are often at risk of irreversible alteration ( via proteolysis, aggregation, or post-translational modification). Kinetic stability, in addition to thermodynamic stability, can directly impact protein lifetime, abundance, and the formation of alternative, sometimes disruptive states. However, we have very few measurements of protein unfolding rates or how mutations alter these rates, largely due to technical challenges associated with their measurement.
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