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Screening and identification of evaluation indicators of low phosphorus tolerant germplasm in Gleditsia sinensis Lam.

Sci Rep

December 2024

Institute for Forest Resources and Environment of Guizhou, College of Forestry, Guizhou University, Guiyang, 550025, Guizhou, China.

This study aims to explore the low phosphorus (P) tolerance of saplings from different Gleditsia sinensis Lam. families. It also seeks to screen for Gleditsia sinensis families with strong low P tolerance and identify key indicators for evaluating their tolerance.

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Cancer, characterized by uncontrolled growth and spread of abnormal cells potentially influencing almost all tissues in the body, is one of the most devastating and lethal diseases throughout the world. Chemotherapy is one of the principal approaches for cancer treatment, but multidrug resistance and severe side effects represent the main barriers to the success of therapy, creating a vital need to develop novel chemotherapeutic agents. The 1,2,3-triazole moiety can be conveniently constructed by "click chemistry" and could exert diverse noncovalent interactions with various enzymes in cancer cells.

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Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder and its underlying neuroanatomical mechanisms still remain unclear. The scaled subprofile model of principal component analysis (SSM-PCA) is a data-driven multivariate technique for capturing stable disease-related spatial covariance pattern. Here, SSM-PCA is innovatively applied to obtain robust ASD-related gray matter volume pattern associated with clinical symptoms.

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Background: The lack of clearly defined neuromodulation targets has contributed to the inconsistent results of real-time fMRI-based neurofeedback (rt-fMRI-NF) for the treatment of chronic pain. Functional neurosurgery (funcSurg) approaches have shown more consistent effects in reducing pain in patients with severe chronic pain.

Objective: This study aims to redefine rt-fMRI-NF targets for chronic pain management informed by funcSurg studies.

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Introduction: The wearable cyborg Hybrid Assistive Limb (HAL) is a therapeutic exoskeletal device that provides voluntary gait assistance using kinematic/kinetic gait data and bioelectrical signals. By utilizing the gait data automatically measured by HAL, we are developing a system to analyze the wearer's gait during the intervention, unlike conventional evaluations that compare pre- and post-treatment gait test results. Despite the potential use of the gait data from the HAL's sensor information, there is still a lack of analysis using such gait data and knowledge of gait patterns during HAL use.

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