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Algal biofuel research aims to make a renewable, carbon-neutral biofuel by using oil-producing microalgae. The freshwater microalga Botryococcus braunii has received much attention due to its ability to accumulate large amounts of petroleum-like hydrocarbons but suffers from slow growth. We performed a large-scale screening of fast-growing strains with 180 strains isolated from 22 ponds located in a wide geographic range from the tropics to cool-temperate. A fast-growing strain, Showa, which recorded the highest productivities of algal hydrocarbons to date, was used as a benchmark. The initial screening was performed by monitoring optical densities in glass tubes and identified 9 wild strains with faster or equivalent growth rates to Showa. The biomass-based assessments showed that biomass and hydrocarbon productivities of these strains were 12-37% and 11-88% higher than that of Showa, respectively. One strain, OIT-678 established a new record of the fastest growth rate in the race B strains with a doubling time of 1.2 days. The OIT-678 had 36% higher biomass productivity, 34% higher hydrocarbon productivity, and 20% higher biomass density than Showa at the same cultivation conditions, suggesting the potential of the new strain to break the record for the highest productivities of hydrocarbons.
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http://dx.doi.org/10.1038/s41598-021-86760-8 | DOI Listing |
PLoS Comput Biol
September 2025
Department of Mathematical and Computational Methods, National Laboratory for Scientific Computing, Petrópolis, Brazil.
Understanding cerebral circulation is crucial for early diagnosis and patient-oriented therapies for brain conditions. However, blood flow simulations at the organ scale have been limited. This work introduces a framework for modeling extensive vascular networks in the human cerebral cortex and conducting pulsatile blood flow simulations.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
September 2025
Significant progress has been made in applying deep learning for the automatic diagnosis of skin lesions. However, most models remain unexplainable, which severely hinders their application in clinical settings. Concept-based ante-hoc interpretable models have the potential to clarify the decision-making process of diagnosis by learning high-level, human-understandable concepts, while they can only provide numerical values of conceptual contributions.
View Article and Find Full Text PDFChild Psychiatry Hum Dev
September 2025
Department of Psychology, University of California, Los Angeles, CA, USA.
Youth anxiety and depression are rising rapidly worldwide, highlighting the need for efficient school-based assessment tools across sociocultural contexts. The Revised Child Anxiety and Depression Scale (RCADS) is one of the most widely used screening measures, with demonstrated cross-cultural applicability. However, its psychometric properties have rarely been evaluated in Chinese populations.
View Article and Find Full Text PDFACS Appl Mater Interfaces
September 2025
National Key Laboratory of Advanced Micro and Nano Manufacture Technology, Shanghai Jiao Tong University, Shanghai 200240, China.
Integrating surface-enhanced fluorescence (SEF) and surface-enhanced Raman spectroscopy (SERS) into a single probe is a natural step forward for plasmon-enhanced spectroscopy (PES), as SEF enables enhanced fluorescent imaging for fast screening of targets, while SERS allows ultrasensitive trace molecular characterization with specificity. However, many challenges remain, e.g.
View Article and Find Full Text PDFFront Mol Biosci
August 2025
Department of Urology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Recent advances in artificial intelligence (AI) are reshaping the diagnostic and therapeutic of primary aldosteronism (PA). For screening, machine learning models integrate multidimensional data to improve the efficiency of PA detection, facilitating large-scale population screening. For diagnosis, AI-driven algorithms have further enhanced the specificity of PA identification.
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