AIMC Topic: Magnetic Resonance Spectroscopy

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Synthesis, identification and in vitro biological evaluation of some novel quinoline incorporated 1,3-thiazinan-4-one derivatives.

Bioorganic & medicinal chemistry letters
The present study describes the synthesis of two new series of 3-hydroxy-N-(4-oxo-2-phenyl-1,3-thiazinan-3-yl)-8-(trifluoromethyl)quinoline-2-carboxamide derivatives (4a-j) and 3-((7-chloroquinolin-4-ylamino)methyl)-2-phenyl-1,3-thiazinan-4-one deriv...

Machine learning methods for the classification of gliomas: Initial results using features extracted from MR spectroscopy.

The neuroradiology journal
CONTEXT: With the advent of new imaging modalities, radiologists are faced with handling increasing volumes of data for diagnosis and treatment planning. The use of automated and intelligent systems is becoming essential in such a scenario. Machine l...

Exploring microbial natural products through NMR-based metabolomics.

Natural product reports
Covering: 2000. 01 to 2025. 03The soaring demand for novel drugs has led to an increase in the requirement for smart methods to aid in the exploration of microbial natural products (NPs). Cutting-edge metabolomics excels at prompt identification of c...

A machine learning-based nuclear magnetic resonance profiling model to authenticate 'Jerez-Xérès-Sherry' wines.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Traditionally, wine quality and certification have been assessed through sensory analysis by trained tasters. However, this method has the limitation of relying on highly specialized individuals who are typically trained to evaluate only specific typ...

Accurate Paediatric Brain Tumour Classification Through Improved Quantitative Analysis of H MR Imaging and Spectroscopy.

NMR in biomedicine
Multimodality imaging is an emerging research topic in neuro-oncology for its potential of being able to demonstrate tumours in a more comprehensive manner. Diffusion-weighted magnetic resonance imaging (dMRI) and proton magnetic resonance spectrosco...

Artificial Intelligence Applied to Honey C NMR Data: A New Path for Honey Recognition.

Journal of agricultural and food chemistry
Besides food authentication control based on acknowledged analytical methods, nowadays there is a continuous attempt to develop new approaches for unambiguously differentiating distinct food commodities. In this regard, current tendencies involve Art...

Next generation technologies for protein structure determination: challenges and breakthroughs in plant biology applications.

Journal of plant physiology
Advancements in structural biology have significantly deepened our understanding of plant proteins, which are central to critical biological functions such as photosynthesis, metabolism, signal transduction, and structural architechture. Gaining insi...

NMR Pure Shift Spectroscopy and Its Potential Applications in the Pharmaceutical Industry.

Chembiochem : a European journal of chemical biology
H nuclear magnetic resonance (NMR) spectroscopy plays an important role in the pharmaceutical industry, but for complex substances, spectral analysis is challenging due to the narrow chemical shift range and signal splitting caused by scalar coupling...

WAND: Wavelet Analysis-Based Neural Decomposition of MRS Signals for Artifact Removal.

NMR in biomedicine
Accurate quantification of metabolites in magnetic resonance spectroscopy (MRS) is challenged by low signal-to-noise ratio (SNR), overlapping metabolites, and various artifacts. Particularly, unknown and unparameterized baseline effects obscure the q...

NNFit: A Self-Supervised Deep Learning Method for Accelerated Quantification of High-Resolution Short-Echo-Time MR Spectroscopy Datasets.

Radiology. Artificial intelligence
Purpose To develop and evaluate the performance of NNFit, a self-supervised deep learning method for quantification of high-resolution short-echo-time (TE) echo-planar spectroscopic imaging (EPSI) datasets, with the goal of addressing the computation...