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Background: Studies using machine learning to identify the target characteristics and develop predictive models for coronary artery disease severity in patients with premature myocardial infarction (PMI) are limited.

Methods: In this observational study, 1111 PMI patients (≤55 years) at Tianjin Chest Hospital from 2017 to 2022 were selected and divided according to their SYNTAX scores into a low-risk group (≤22) and medium-high-risk group (>22). These groups were further randomly assigned to a training or test set in a ratio of 7:3.

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Enhancing the Optically Detected Magnetic Resonance Signal of Organic Molecular Qubits.

ACS Cent Sci

January 2025

Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States.

In quantum information science and sensing, electron spins are often purified into a specific polarization through an optical-spin interface, a process known as optically detected magnetic resonance (ODMR). Diamond-NV centers and transition metals are both excellent platforms for these so-called color centers, while metal-free molecular analogues are also gaining popularity for their extended polarization lifetimes, milder environmental impacts, and reduced costs. In our earlier attempt at designing such organic high-spin π-diradicals, we proposed to spin-polarize by shelving triplet = ±1 populations as singlets.

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Hydroxylation, an extensive post-translational modification on proline, is critical for the modulation of protein structures, further dominating their functions in life systems. However, current mass spectrometry-based identification, could hardly distinguish hydroxylation from neighboring oxidation due to the same mass shifts, as well as challenges posed by low abundance and exogenous oxidation during sample preparation. To address these, an engineered nanopore was designed, capable of discriminating single hydroxyl group, to achieve the identification of proline hydroxylation on individual native peptides directly in the mixture.

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Introduction: The occurrence of Gleason grade group upgrading (GGU) significantly impacts both treatment strategy development. We aim to develop an optimal predictive model to assess the risk of GGU in patients with localized prostate cancer (PCa), by comparing traditional logistic regression (LR) with seven machine learning algorithms.

Methods: A retrospective collection of clinical data was conducted on patients who underwent RP at Wuhan Central Hospital (January 2017 to December 2023, n=177) and Jiangxi Cancer Hospital (July 2019 to February 2024, n=87).

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Slopes influenced by multiple faults are prone to large-scale landslides triggered by multi-regional failures. Understanding the failure process and sequence is essential for the sustainable development of mining operations. This paper presents a method combining InSAR monitoring and numerical simulation to analyze the failure processes of slopes affected by multiple faults.

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