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Videos de Conceptos Relacionados

NMR Spectrometers: Resolution and Error Correction01:14

NMR Spectrometers: Resolution and Error Correction

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When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
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¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

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When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
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Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
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Physics-embedded CycleGAN for robust metabolite mapping in short-readout deuterium metabolic imaging.

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Video Experimental Relacionado

Updated: Jan 13, 2026

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
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Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Published on: November 29, 2024

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Modelo de Fase Impulsado por Aprendizaje Profundo para Corrección de Fase Robusta en Metabolómica Basada en RMN de

Chuanwen Zhao1, Gang Chen1,2, Caixiang Liu1,2

  • 1State Key Laboratory of Magnetic Resonance Spectroscopy and Imaging, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430071, China.

The journal of physical chemistry letters
|January 9, 2026
PubMed
Resumen

Un nuevo método de aprendizaje profundo, Red de Atención Residual Impulsada por Modelo de Fase (PD-RAN), corrige con precisión la fase en metabolómica RMN de alto rendimiento. Esta técnica robusta garantiza un análisis espectral confiable para grandes conjuntos de datos de muestras biológicas.

Área de la Ciencia:

  • Química Analítica
  • Bioquímica
  • Biología Computacional
Palabras clave:
MetabolómicaRMNCorrección de faseAprendizaje profundoPD-RANAnálisis espectralAlto rendimiento

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Last Updated: Jan 13, 2026

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Conclusiones:

  • PD-RAN ofrece un avance significativo en el procesamiento de datos de metabolómica RMN, proporcionando una corrección de fase precisa y eficiente.
  • El enfoque de aprendizaje profundo informado físicamente mejora la confiabilidad del análisis cuantitativo de metabolómica.
  • Este método se adapta bien a las demandas de la metabolómica RMN de alto rendimiento, facilitando la caracterización escalable y consistente de muestras biológicas.