Nuclear magnetic resonance (NMR) is a non-destructive technique that can reveal the phase structure and dynamics of polymers at the molecular level. It is sensitive to polymer chain mobility and requires minimal special sample preparation. We investigated the phase structure and molecular dynamics of polyurethane rubber (PUR) based on the T₁-T₂^* relaxation correlation spectra, and analyzed the T₁-T₂^* data by multi modal decay. The T₁-T₂^* spectra showed three types of signals: rigid ¹H with the shortest T₂^* value, interphase ¹H with an intermediate T₂^* value, and mobile-amorphous ¹H with the longest T₂^* value. The three ¹H components exhibit the similar T₁ values in PUR, which decreased with increasing hardness or decreasing temperature. The integrals of these signals depend on the durometer hardness and temperature for PUR. They increase for the rigid phase but reduce for mobile-amorphous phase and interphase with an increase of PUR durometer hardness. The rigid ¹H component decreased and the mobile-amorphous ¹H component increased with increasing temperature, while the interphase ¹H component remained constant. In addition, the hard/soft ratio decreased with increasing temperature for PUR systems. These results indicated that T₁-T₂^* spectra can be used to characterize phase structure and dynamics of PUR.

In order to improve the reliability of two-dimensional nuclear magnetic resonance (2D NMR) measurement in shale oil reservoirs, the T₂-T₁ 2D NMR response characteristics and influencing factors of shale oil reservoirs were analyzed in three scenarios: laboratory core analysis, wellsite mobile full-diameter core scanning and logging. For different application scenarios, the optimization method of T₂-T₁ NMR measurement parameters for shale oil reservoirs were proposed. Laboratory core measurements require attention to the choice of echo interval time (T_E) and number of echo groups, in addition to the different magnetic field strengths and measurement sequences. When scanning full-diameter cores at the well site, it is necessary to focus on T_E and minimum waiting time (T_w). To ensure the convergence in T₁ dimension of quickly relaxed component, the minimum T_w should be set to at least 1 ms. NMR logging is limited by the acquisition conditions. It is necessary to focus on the distribution range and smoothing factor in data processing to interpret and modify data with different signal-to-noise ratios. A poor shale oil reservoir with NMR porosity less than 5% is difficult to ensure the accuracy of NMR results for its low signal-to-noise ratio. The systematic analysis of T₂-T₁ 2D NMR measurement parameters provides a reference for the optimization of 2D NMR detection methods for shale oil reservoirs, which helps to improve the accuracy of NMR measurements and obtain more reliable reservoir information.

Recently, multiple-cross polarization (multiCP) has attracted much interest owing to its favorable performance as a solid-state nuclear magnetic resonance quantitative method. Relating investigations revealed that the setup of multiCP parameters relies on the properties of the samples. Diverse types of samples require different parameters. To improve the tolerance to sample properties, an improved method named MLGCP-1 was proposed in this work, which employed Lee-Goldburg cross polarization technique. L-alanine, L-valine and their mixtures were chosen as model samples to evaluate the performance of MLGCP-1 method. multiCP experiments were also conducted for comparison. Based on the test of molecular group ratio, it was revealed that the range of contact time t_p of MLGCP-1 was larger than that of multiCP, which improved from 1.0~1.3 ms to 0.8~2.0 ms. Moreover, according to the study of L-valine and mixtures, it was revealed that the range of t_p was influenced by the difference of cross relaxation time T_CH. Large T_CH difference limited t_p range for quantification. This manner was in accordance with multiCP. However, the t_p range of MLGCP-1 was markedly enlarged in comparison with multiCP, presenting higher tolerance to the sample properties.

Proteins recognize partner proteins and take function through short-range interaction at a small interface area. Therefore, protein and its partner form a series of encounter complex ensembles on the pathway to simplify conformational searching and facilitate protein-protein association. The encounter complex is hard to detect by traditional structural-biology methods due to its short life and low population. This paper chose histidine phosphate carrier protein (HPr) and enzyme II (EIIA^Glc) complex as the research target, combining paramagnetic relaxation enhancement (PRE) with molecular dynamics simulation to characterize the encounter complex structure and dynamics. We found that the HPr first formed encounter complexes with EIIA^Glc in three directions, and then compelled the formation of the specific complex. The methods utilized in this paper can visualize the encounter complex ensembles, and help understand the mechanism of bio-molecule interaction and protein function pathway in cell.

In vivo magnetic resonance vessel size imaging at 7 T high field was used to explore the changes in cerebral vascular plasticity after spinal cord hemisection injury in rats. Region of interest (ROI) analysis showed that four weeks after injury, mean vessel diameter (mVD), microvascular density (Density) and vessel size index (VSI) values were significantly increased in the contralateral side compared with the ipsilateral pyramid of the injury site, suggesting angiogenesis or vascular activation in the white matter region of the contralateral corticospinal tract (CST). Immunofluorescence results showed that the intensity of staining for platelet endothelial cell adhesion molecule 1 (CD31) and glial fibrillary acidic protein (GFAP) also increased significantly in the contralateral pyramid four weeks after injury. These results suggested that magnetic resonance vessel size imaging could provide valuable information on neovascularization in brain after spinal cord injury and may be a novel tool to diagnose brain vascular pathologies in spinal cord injury patients.

ATPase family AAA domain-containing protein 2 (ATAD2) is a chromatin regulator, also known as an oncogenic transcription cofactor. Its abnormal expression is closely related to the occurrence and development of various malignant tumors. ATAD2 consists of two domains: the ATPase domain and the bromodomain. The bromodomain can specifically recognize and interact with the acetylated lysines in proteins, which regulates the refactoring and transcription of chromosomes. In this work, we found that ATAD2 bromodomains are aggregated under normal solution conditions. Considering the possible impact of aggregation on the interaction between ATAD2 bromodomain and acetylated histone tail, we preliminarily investigated the aggregation of ATAD2 bromodomains mainly by nuclear magnetic resonance (NMR) and circular dichroism (CD) spectra. The results suggested that the aggregation is accompanied with structure alteration and possibly related to the physiological functions of cells. This study may provide new clues for the development of ATAD2 bromodomain inhibitors.

In order to improve the signal-to-noise ratio of magnetic resonance imaging signal acquisition and reduce the interference in signal transmission, the popular technical solution is to place the signal acquisition device in a shielded room, close to the receiving coil. In response to the previous scheme, this paper proposed an optical fiber data transmission scheme based on SerialLite II protocol to solve the problem of parameter configuration of signal acquisition and high-speed transmission of echo data. The circuit takes field programmable gate array (FPGA) device and small form pluggable (SFP) optical fiber module as the core of new instrument and realizes the download of configuration parameters of signal acquisition and the upload of echo data based on SerialLite II protocol. In order to facilitate programming, a NIOS II soft-core processor is constructed in FPGA to complete the sending, receiving and configuration of the parameters of the signal acquisition module. An experimental prototype was developed, and data transmission was tested. The results showed that this scheme can achieve high-speed data transmission. It takes only about 364.2 μs to transmit 64 K bytes of data through a 30-meter optical fiber. The scheme is reliable and has low-delay.

Due to its sensitivity to the local geometries and chemical environments, solid-state nuclear magnetic resonance (NMR) is widely applied to investigate the host-guest interactions between metal-organic frameworks (MOFs) and guest molecules in the studies of gas adsorption and chemical separation. Multi-nuclear, multi-dimensional and variable temperature solid-state NMR is employed to investigate the adsorption behavior, primary adsorption sites, dynamic property, and self-diffusion coefficients of light hydrocarbons and carbon dioxide inside the MOFs channels. Moreover, solid-state NMR spectroscopy is utilized to determine the adsorption selectivity, visualize the preferential adsorption and uncover the separation mechanism of light alkane/alkene mixtures inside MOFs. Furthermore, solid-state NMR is used to explore the detailed host-guest interaction mechanism between common chemicals and MOFs adsorbents. All these findings provide insights into deep understanding of the structure-property relationship for the application of functional MOFs in gas adsorption and chemical separation.

Magnetic resonance fingerprinting (MRF) is a revolutionary new technique for rapid quantitative magnetic resonance imaging. We reviewed the imaging technology and clinical application of MRF in an all-round way. We focus on three technical aspects: data collection, dictionary generation, and pattern recognition from traditional quantitative framework to deep learning quantitative framework. We also analyzed the technical challenges and limitations of MRF. The clinical applications of MRF in various human body regions were summarized, and the current status of MRF technology verification in terms of repeatability and reproducibility was introduced. Finally, we discussed the potential barriers and opportunities for MRF to enter clinical application and envision the future development direction of MRF technology.

As global aging worsens and deep learning advances, the imaging classification of Alzheimer’s disease (AD) based on deep learning has become a hot topic of research. This paper reviewed the common deep learning models, evaluation criteria and public datasets in AD imaging classification tasks, discussed the application of different image modalities in AD imaging classification. The content was focused on the improvement of deep learning models applied to AD imaging classification. The studies of model interpretability were also introduced. Finally, the paper summarized and compared the classification models mentioned, identified the brain regions related to AD image classification, and outlined the future research directions in this field.