An aspect of the present disclosure is a bioderived polymer that includes a first repeat unit that includes

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where n is an integer between 1 and 1000, and R.sup.1 is a first hydrocarbon group.

A method is offered which permits NMR measurements of integer spin nuclei to be performed at higher sensitivity than heretofore. In particular, the method enables high-resolution multidimensional correlation NMR measurements on integer spin nucleus S having integer spin S and nucleus I of other spin species. The method starts with applying an RF magnetic field having a frequency that is n times (where n is an integer equal to or greater than 2) the Larmor frequency of the integer spin nucleus S to the spin S. Magnetization transfer is effected between the nucleus I and the integer spin nucleus S.

Provided is a stable isotope-labeled aliphatic amino acid enabling the assignment of the signal of an amino acid residue side chain by increasing to the maximum the observation sensitivity to an NMR signal of the same amino acid residue side chain, and allowing NOE (nuclear Overhauser effect) between protons in the amino acid residue to be observed. The stable isotope-labeled aliphatic amino acid is for constituting a protein and satisfies all of the following conditions (1) to (3): (1) two or more carbon atoms are labeled with .sup.13C; (2) of two or more carbon atoms labeled with .sup.13C, a carbon atom other than a carbon atom of a methyl group, which is capable of bonding to a hydrogen atom, has one .sup.1H directly bonded thereto, while the carbon atom of the methyl group has at least one .sup.1H directly bonded thereto; and (3) other carbon atoms adjacent to all the .sup.13C are all .sup.12C.

Systems and methods employing spin editing techniques to improve magnetic resonance spectroscopy (MRS) and magnetic resonance spectroscopic imaging (MRSI) are discussed. Using these spin editing techniques, magnetic resonance signals of one or more non-target chemicals (chemicals whose signals are to be filtered out or suppressed) chemicals can be suppressed, so that the signal(s) of a set of target chemicals can be obtained without signals from the one or more non-target chemicals. Information about and differences between the molecular topologies of the first set of chemicals and the one or more unwanted chemicals can be used to design a sequence that suppresses the one or more unwanted chemicals while allowing acquisition of signal(s) from the first set of chemicals. These techniques can be employed to recover sharp peaks despite magnetic field inhomogeneities and susceptibility effects.

An NMR method and apparatus for analyzing a sample of interest applies a static magnetic field together with RF pulses of oscillating magnetic field across a sample volume that encompasses the sample of interest. The RF pulses are defined by a pulse sequence that includes a plurality of measurement segments configured to characterize a plurality of relaxation parameters related to relaxation of nuclear magnetization of the sample of interest. Signals induced by the RF pulses are detected in order to derive the relaxation parameters. The measurement segments of the pulse sequence include at least one first-type measurement segment configured to characterize relaxation of spin-lattice interaction between nuclei of the sample of interest in a rotating frame (T.sub.1ρ) at a predefined frequency. The T.sub.1ρ parameter can be measured in conjunction with the measurement of other relaxation and/or diffusion parameters as part of multidimensional NMR experiments.

A new method for reconstructing a full spectrum from under-sampled magnetic resonance spectrum data by using a deep learning network. First, the exponential function is used to generate a time-domain signal of the magnetic resonance spectrum, and a zero-filling time-domain signal is obtained after the under-sampled operation is completed in the time domain. The zero-filling time-domain signal and the full spectrum corresponding to the full sampling are combined to form a training data set. Then, a data verification convolutional neural network model is established for magnetic resonance spectrum reconstruction, where the training data set is used to train neural network parameters to form a trained neural network. Finally, the under-sampled magnetic resonance time-domain signal is input to the trained data verification convolutional neural network, and the full magnetic resonance spectrum is reconstructed.

Methods of fingerprinting a specific molecule in a composition using nuclear magnetic resonance (NMR) is disclosed. The disclosed NMR methods provide several modifications and improvements over existing NMR techniques. In some embodiments, the methods include applying a cycle of signal processing steps, including applying a radio frequency (RF) pulse, applying a gradient pulse having a pulse length less than or equal to 1000 μs, and applying a water suppression technique (WET). In some embodiments, the methods further include repeating the cycle for at least 3 times to acquire an enhanced signal of the composition. In some embodiments, the methods further include fingerprinting the specific molecule based on the enhanced signal of the composition

An integrated MRI and MRS system includes a plurality of different classifiers for detecting the likelihood of the new data to be one of the different diseases/conditions in different body organs, and even the progression of the disease, disease state and condition within that organ. An interface module receives information on the individual including region of the body and potential disease/condition; and provides this information to a data analysis unit which automatically dictates which coil, the scanning protocol and classifier.

The present invention relates to an MRS 1D or 2D method and system for obtaining spectral data of the brain of a subject and using neurochemical markers to enable whether a subject is experiencing acute pain, and providing the capacity to monitor response to therapy on an individual basis. The markers can be an increase of Fuc II, III, IV, VII and lactate.

Systems and methods for analyzing metabolite concentration in a subject using a medical imaging system are provided. The method includes, using a nuclear magnetic resonance (NMR] system, acquiring data from a subject during multiple acquisitions using different echo times for the multiple acquisitions to create a chemical shift domain. The method also includes, using the chemical shift domain, identifying metabolites by at least two chemical shifts and generating a report indicating the metabolites.