Based on the ring-down signal generation principle of nuclear magnetic resonance (NMR), we presented here a design scheme of transmitting and receiving separated short dead-time radio frequency (RF) coil composed of loop-gap resonator (LGR) coil and solenoid coil in low-field NMR system, to improve transmission efficiency by optimizing tuning and matching network. We also designed a fast RF switch and driver to fulfill the requirement of the RF coil. Based on the simulation results, the short dead-time RF coil was fabricated and applied to a self-developed 9.51 MHz portable low-field NMR spectrometer. The NMR experiments showed that the dead-time was reduced to less than 10 μs, which verified the feasibility of the design scheme.

The existing olfactory stimulator based on magnetic resonance measurement can provide different concentration of olfactory stimulation by adjusting the concentration of olfactory liquid. However, with the progress of the experiment, it is difficult to ensure the concentration stability of odorant gas delivered to the nasal cavity, due to the odorant volatilization and the change of experimental environments (temperature, humidity, air flow), thus affecting the experimental accuracy. In this research, we improved the olfactory stimulation device previously developed by our laboratory to achieve accurate quantification of gas concentration. The improved olfactory stimulator mainly consists of three parts: control system, feedback system and pneumatic system. The control system is mainly use to control gas delivery and adjust concentration of olfactory gas. The feedback system is responsible for measuring the gas concentration. In the pneumatic system, an activated carbon device is added to the original foundation to reduce interference of irrelevant factors. After the improvement, the switching response time between different pneumatic branches reached to 75.2 ms, which is nearly 1 s less than the original device, and effectively improves the accuracy of stimulus. The experimental results show that the olfactory gas concentration of ethanol, pyridine and amyl acetate decrease by 6.7%, 71.4%, and 79.2% respectively, within 300 s before adjusting the gas concentration. The odorant gas concentration changes significantly in a short time. The gas concentration regulation function can be realized by adjusting the voltage of air pump of the feedback system to change the ratio of odorant airflow and pure airflow. When the gas concentration drops to 90% of the target value, it took 13 s to adjust the odorant gas concentration to the target value for pyridine and amyl acetate.

With continuing breakthroughs in computational chemistry theory and substantial improvement of computation hardware performance, great progresses have been made in recent years in first principle-based prediction of ¹H and ¹³C chemical shifts of organic molecules. Some methods have even been gradually applied for accurate prediction in complex molecular systems. In this paper, a density functional theory-based high-precision on-line chemical shift prediction platform for organic molecules is established, which provides on-line interactive service of chemical shift prediction for molecules with a molecular weight less than 800. The platform accelerates the mapping between nuclear magnetic resonance (NMR) spectra and molecular structures, and provides a powerful tool for efficient assignment of NMR spectra and accurate analysis of organic molecular structure.

Due to its high sensitivity and resolution, the heteronuclear single quantum correlation (HSQC) experiment is widely used for nuclear magnetic resonance (NMR)-based structural elucidation and research on solution state macromolecules. However, optimizing instrument settings and experimental parameters in the HSQC experiments can be troublesome due to the complexity of the pulse sequence. In this work, we simulated HSQC spectra based on a quantum model. Through theoretical derivation and numerical calculation, the density matrix evolution of a two-spin ensemble with spin 1/2 (IS) was obtained after each pulse, which was then combined with the two-dimensional NMR sampling method to achieve spectral simulation of the HSQC experiment. For validation, the HSQC spectrum of ethanol was simulated. The simulation of HSQC experiment will be beneficial for spectrum prediction, and guide HSQC experimental setup to improve spectral quality.

In this work, an operando NMR method was used to investigate the interaction between water and methanol in photocatalytic methanol reforming process in a real solid-liquid environment. The existence of hydrogen bonding and proton exchange between water and methanol were proven. The experimental results demonstrated that, the interaction between methanol and water is affected by the type of catalyst, reaction temperature and light irradiation, which consequently influences the methanol reforming efficiency. It was also shown that selection of the appropriate temperature and catalyst could improve methanol reforming efficiency.

Differential diagnosis of meningioma and acoustic neuroma can be difficult because these two tumors have similar locations and appearances on medical images. To address this problem, mask region convolutional neural network (Mask RCNN) was used to classify and diagnose those two types of tumors. First, magnetic resonance images acquired with T₁-weighted spin-echo (T₁WI-SE) sequence of 89 meningioma and 218 acoustic neuroma patients were collected and preprocessed. Then the improved feature pyramid networks (FPN) algorithm was used for model network training. The effects of three different backbone feature extraction layers on classification and location were compared. It was demonstrated that Mask RCNN model with improved FPN and ResNet101 as backbone network is able to effectively classify and locate meningioma and acoustic neuroma, the values of precision, recall, specificity, and mean average precision (mAP) are 0.918 2, 0.856 9, 0.876 2, and 0.90, respectively.

Magnetic resonance imaging (MRI) studies have documented that there were structural abnormalities in acquired immune deficiency syndrome (AIDS) patients. Although the long-term survival rate of AIDS patients can be improved by the combined antiretroviral therapy (cART), little is known about the effect of cART on brain structural alterations in AIDS patients. In this study, three-dimensional high-resolution brain structure MRI and voxel-based morphometric methods were used to explore the effects of cART on brain gray matter volume in AIDS patients. The results indicate that cART may effectively mitigate the occurrence of abnormal brain structure in AIDS patients, emphasizing the importance of early initiation of cART.

Some studies have shown that the cognitive state in Alzheimer's disease (AD) patients is related to the changes of the temporal characteristics of dynamic functional connection. Persistent homology index analysis method provides a deeper insight into the property of dynamic brain networks. However, current research mainly focused on spatial evolution, while there is little research on time-varying brain network evolution. Based on resting state-functional magnetic resonance imaging (rs-fMRI) data, this paper analyzed the static functional connectivity network in AD patients and normal controls (NC), as well as the dynamic brain networks constructed by sliding windows. The analysis method based on persistent homology was compared with the ones based on graph theory, and the temporal characteristics were analyzed with k-means clustering. The results demonstrated that there were more significant differences between the AD patients and NC subjects, when the index based on persistent homology was used. Compared with the analysis of static brain networks, the dynamic brain network evolution analysis based on persistent homology provides new ideas for the detection of functional brain network biomarkers.

Alzheimer's disease has become more prevalent in our lives as the population ages. Accurate diagnosis and positive intervention can effectively delay the progress of early-stage Alzheimer’s disease. Accurate diagnosis of Alzheimer’s disease requires the combination of information from multiple regions of interest (ROIs), because the use of one single ROI may lose the connection and impact among multiple brain regions. In this paper, we firstly proposed a three-input convolutional neural network (CNN) to comprehensively utilize the information from three ROIs, hippocampus, other gray matter (without hippocampus) and white matter. In addition, as the neural network deepens, important feature information of original image will be partially lost. Therefore, we proposed a multi-output 3D CNN, which increases the connection and output of middle layers, shortens the distance between input and output, enhances feature propagation and reduces the loss of feature information. The results showed that the accuracy rate, precision rate, sensitivity, specificity and F1-score of the test set diagnosis obtained by multi-output 3D CNN model were 90.5%, 91.0%, 90.4%, 95.2% and 90.5%, respectively. The diagnostic performance was better than that of the single-output 3D CNN model.

Two new β-dihydroagrofuran compounds, 1β,2β,15-triacetoxy-8α-(α-methyl)-butanoyloy-9β-benzoxy-4α,6α- dihydroxy-β-dihydroagrofuran (compound I) and 1β,15-diacetoxy-8α-(α-methyl)-propionyloxy-2β,9β-dibenzoxy-4α,6α- dihydroxy-β-dihydroagrofuran (compound II), were isolated from Celastrus angulatus Maxim. The chemical shifts of the two new compounds were assigned by one- and two-dimensional nuclear magnetic resonance (NMR) techniques. Their structures were elucidated.

Manidipine hydrochloride is the third generation of new synthetic antihypertensive drugs. The structure of manidipine hydrochloride was confirmed with 1D and 2D nuclear magnetic resonance (NMR) techniques, such as ¹H NMR, ¹³C NMR, DEPT-135, ¹H-¹H COSY, ¹H-¹H NOESY, ¹H-¹³C HSQC, and ¹H-¹³C HMBC. Some abnormal signals in ¹H NMR and ¹³C NMR spectra were further discussed.

¹H nucleus is the most commonly used nucleus for magnetic resonance imaging (MRI) due to its high natural abundance in organisms and high MR sensitivity. However, other nuclei are distinctive in physiological processes, such as ³¹P that is important in the energy metabolisms. The development of high-field MRI allows for MRI research based on ³¹P nucleus, while high-quality ¹H/³¹P dual-tuned radio frequency (RF) coil is essential for such applications. This article summarized the researches and applications of various ¹H/³¹P dual-tuned RF coils, and presented in vivo ¹H MRI and ³¹P MR spectra of mouse brain at 9.4 T. Potential applications of ¹H/³¹P dual-tuned RF coil for high field were discussed.

The performance of gradient and shim coils affect the quality of magnetic resonance imaging (MRI) directly. Conventional gradient/shim coils have some inherent disadvantages, such as the state of produced magnetic field is single and inflexible, many types of coils are required and the structure is complex, while the matrix gradient coils are able to overcome those problems. This paper introduces the concept and characteristics of matrix gradient coil, and reviews the current progresses in this research topic according to the structure and function of the gradient coil. The development tendency of matrix gradient coil in the future is proposed. In addition, the preliminary research on matrix gradient coil is presented.