A nuclear magnetic resonance method of analysis for glycosaminoglycans in general, and of heparins and low molecular weight heparins and their derivatives in particular, is provided. The method allows for their identification and for relative quantification of respective characteristic signals by .sup.1H-NMR and/or .sup.1H-.sup.13C HSQC.

An analytical method employing nuclear magnetic resonance of glycosaminoglycans in general, and of heparins and low molecular weight heparins and their derivatives in particular, is provided. The method is used for identification and the relative quantification of characteristic signals by .sup.1H-NMR and/or .sup.1H-.sup.13C HSQC.

Disclosed herein are methods of preparing a composition comprising crystalline biomolecules, for example, crystalline antibodies. In exemplary embodiments, the method comprises forming a fluidized bed of crystalline biomolecules using, for example, a counter-flow centrifuge to exchange buffer and/or to concentrate the crystalline biomolecules in a solution. Also provided are methods of detecting crystalline biomolecules and/or amorphous biomolecules in a sample.

A method for processing two-dimensional (2D) nuclear magnetic resonance (NMR) Diffusion Ordered Spectroscopy (DOSY) based on deep learning comprises constructing a simulated dataset by generating simulated data using a mathematical model based on signal characteristics of the 2D NMR DOSY, generating labels for training a deep learning network model, wherein the labels comprise a first two-dimensional matrix, and two dimensions of the first two-dimensional matrix comprise chemical shift and diffusion coefficients, constructing the deep learning network model and setting training parameters of the deep learning network model, training the deep learning network model using the simulated dataset, and testing the deep learning network model.

The invention provides methods for processing nuclear magnetic resonance (NMR) spectroscopic data to assign resonance peaks in an NMR spectrum of a molecule to atomic nuclei in said molecule, based on graph-theoretical principles. In particular, the methods of the invention may be employed in the assignment of data obtained from methyl-TROSY spectroscopy of proteins.

A sensor including a fluorinated receptor can be used to identify an analyte through shift in .sup.19F NMR resonance of the receptor when the receptor interacts with the analyte.

In a general aspect, a magnetic resonance system includes a primary magnet system configured to generate a principal magnetic field in a sample region. The magnetic resonance system also includes a field source device. The field source device includes a substrate and first and second conductor layers on the substrate. The first conductor layer includes a constriction configured to generate a radio frequency magnetic field in the sample region. The second conductor layer is vertically centered above the first conductor layer, and includes gradient coils configured to generate first, second, and third magnetic field gradients along respective first, second and third mutually-orthogonal spatial dimensions in the sample region.

The present invention discloses a method of obtaining reproducible quantitative magnetic resonance data about a sample to be analyzed, which allows for the rapid collection of a large amount of data that is well suited for quantitative analysis. In some embodiments, the method comprises performing a nulling sequence, where the nulling sequence comprises a series of applied changes to the magnetic field of the sample, which reduces all components of the magnetization in the sample to near zero or zero magnitude, within measurable limits; and performing at least one excitation step, where each excitation step comprises applying an excitation (radio frequency) pulse to the sample, followed by a measurement of magnetic resonance data.

Disclosed are fibers which contain identification fibers. The identification fibers can contain a one or more of chemical markers and one or more distinct features, or taggants, which may vary among the fibers or be incorporated throughout all of the fibers. The chemical markers and distinct features can be representative of specific supply chain information. The supply chain information can be used to track the fibers from manufacturing through intermediaries, conversion to final product, and/or the consumer. The disclosed embodiments also relate to the method for making and characterizing the fibers. Characterization of the fibers can include identifying chemical markers and distinct features and correlating the chemical markers and distinct features to manufacturer-specific taggants to determine supply chain information.

An electron diffraction apparatus measures an overall structure of a crystal of a specimen by electron diffraction. An NMR apparatus measures a local structure of the crystal by NMR measurement. An analysis apparatus combines the overall structure and the local structure to specify a structure of the crystal.