Lactate can provide a large amount of energy to the body to maintain the stability of the cellular nervous system. In medicine, lactate is often used as a signaling molecule to monitor the health level of the body in a timely manner. Accurately and efficiently detecting changes in the content of lactate in living tissues can provide important information about the physiological functions and health status of the organism, and also has certain significance for the early diagnosis of diseases. Several methods for detecting lactate using magnetic resonance spectroscopy techniques have been reported in literature, including long TE filtering technology and multiple quantum filtering technology, which have certain limitations in signal selectivity and efficiency. Here we propose a new method for selectively filtering lactate signals, which uses optimized control pulses to specifically transform the four hydrogen protons on the methyl and methine of lactate molecules into a two-spin Zeeman order, achieving efficient and highly selective detection of the methyl signal of lactate. Using this pulse sequence method, we have successively achieved selective detection of the signals of lactate or similar chemical groups in mixtures and polymer samples. This study provides new ideas and methods for efficiently selecting the signals of lactate in complex systems.

In situ solid-state nuclear magnetic resonance (NMR) serves as a powerful means to study catalytic reactions under operating conditions. Standard solid-state NMR rotors typically struggle to match the pressure and temperature of active reactions during sampling. Here, we introduce specialized inserts for commercial solid-state NMR rotors capable of withstanding pressures from atmospheric to 618.3 kPa and temperatures ranging from room temperature up to 433 K. With this innovative design, we examine the isomerization of dihydroxyacetone (DHA) on Sn-MFI zeolite catalyst using in situ ¹H MAS NMR, revealing the presence of a gem-diols-type intermediate during the transformation of DHA into glyceraldehyde.

In the present study, a systematic investigation of photoexcited fluorine supersensitization is carried out using in situ nuclear magnetic resonance (NMR) technique in combination with a newly designed photoresponsive device, and the validity of the photoresponsive device is confirmed. The reaction device consists of a light source, a light path, a coaxial collimating connector, and a solution mixing system, and the combination of nine fluorinated aromatic compounds with six photosensitizers is tested by the standard signal-to-noise (S/N) formula. In addition, the device's suitability is further verified by continuously monitoring the photopromoted open-loop reaction. The results show that the photoreactor can be well adapted to the commercially available NMR spectrometer for photochemical reaction detection and research.

In this work, the hyphenated liquid chromatography-diode array detector-solid phase extraction-nuclear magnetic resonance/mass spectrometry (LC-DAD-SPE-NMR/MS) technique is employed to characterize a novel degradation impurity with an approximate content of 0.3%~0.4% in cabazitaxel injection. In LC analysis, the impurity is co-eluted with tween-80, an important excipient contained in cabazitaxel injection, which poses a great challenge for high-purity degradation impurity isolation and further structure elucidation. Based on LC-DAD-SPE-NMR/MS hyphenation, automatic SPE is performed to trap and concentrate the impurity, and extensive NMR analysis was performed to characterize the structure of the impurity. In the ¹H NMR spectrum, partial peaks of the impurity are overlaid with co-eluted tween-80. To navigate the complexity, ¹H-¹H, ¹H-¹³C correlations, ¹H and ¹³C chemical shifts are extracted from the interfering peaks of tween-80 based on extensive analysis of 2D NMR spectra. Finally, the structure of the impurity is elucidated to be a cabazitaxel isomer with a rearranged taxane skeleton. The elucidation is completed in less than 48 h, showcasing a successful application of LC-DAD-SPE-NMR/MS hyphenation in determining the structure of an unknown trace impurity in pharmaceutical drugs, which evidences its capability and application prospects in the pharmaceutical industry.

3/4/5-O-feruloylquinic acids (3/4/5-O-FQA) have antioxidant activity, which is beneficial to disease prevention and human health maintenance, however, their exact 3D structures are still unknown. In the present work, the structures of 3/4/5-O-FQA in gas phase, D₂O solution and DMSO-d₆ solution are investigated respectively using ¹H nuclear magnetic resonance (NMR) spectroscopy combined with quantum chemistry calculation. We observed a difference of 4.147° in dihedral angle τ (H3C3O1C9) on the esterification site H-3 for 3-O-FQA in D₂O and DMSO-d₆ solutions, which can explain the difference on ¹H NMR spectra for H-3 atom of 3-O-FQA in the two solutions. This work presents the 3D structures of 3/4/5-O-FQA, offering valuable insights for further studies on their properties and potential applications.

The irregular morphology of cerebral aneurysms, especially the presence of a daughter sac, is a crucial risk factor for aneurysm rupture. Clinical assessment of daughter sac relies mainly on image reconstruction by time of flight-magnetic resonance angiography (TOF-MRA) and judgment based on physicians' vision and experience, which limits the efficiency and accuracy of diagnosis. In this paper, we propose an improved parallel multiscale fusion attention network (PMAF-Net) based on 3D ResNet50 for classification. PMAF-Net uses multi-scale convolution and weighted fusion channel and spatial attention weights to enhance the feature extraction capability. The experiment used 291 cases of TOF-MRA data, including 128 cases in the training set, 32 cases in the validation set, and 131 cases in the test set. Compared with other classification networks, PMAF-Net performs best on the test set, with the accuracy of 83.97%, recall of 84.48%, precision of 80.33%, and F1-score of 0.823 5, and the receiver operating characteristic curve (ROC) also reflects the model's optimal classification performance (AUC of 0.900 8). The results show that the network can identify daughter sac type aneurysms more accurately, which is expected to support the assessment and quantification of the risk of aneurysm rupture.

In diffusion magnetic resonance imaging (dMRI), conventional multi-shell constrained spherical deconvolution (CSD) methods usually model white matter microstructure as anisotropic and gray matter microstructure as isotropic. Nonetheless, investigations using high-resolution dMRI and histology have demonstrated that the diffusion process in gray matter exhibits clear anisotropic features. To better disclose the microstructural aspects of gray matter, this research suggests a gray matter multi-shell restricted spherical deconvolution method based on the SANDI (Soma And Neurite Density Imaging) model. We first simulate the signal of grey matter using the SpinDoctor with real neuronal data and then reconstruct the fibers in the grey matter portion of real brain data. Experimental results demonstrate that our algorithm effectively captures the anisotropic features of grey matter regions and estimates grey matter fiber orientations with greater accuracy, closely reflecting real-world scenarios.

Magnetic resonance logging plays a pivotal role in petroleum exploration. The magnet system serves as a crucial component of the magnetic resonance logging sensor. However, current designs of magnet systems often rely on empirical structures and lack theoretical research on optimal configurations. This paper proposes a design method for the magnetic core structure of a single-side magnetic resonance logging sensor based on topology optimization using the variable density method. The design domain of the magnetic core in the two-dimensional cross-section model of the logging probe is divided into N small units with densities ranging from 0 to 1. The moving asymptote method of gradient descent is employed to update the density based on gradient information from the objective function, leading to an iterative approach for achieving an optimal solution. Based on these optimization results, a scaled-down prototype of the magnetic resonance sensor is fabricated for experimental verification. With an external radius of 2.5 cm, this sensor can generate a static magnetic field with intensities ranging from 641.0 G (1 G=10^-4 T) to 1108.6 G and gradients from 303.0 G/cm to 683.6 G/cm within the remote region of interest (ROI). The measured data regarding magnetic field distribution aligns with simulation-based optimization results. Subsequently, water mode measurement experiments are conducted using this designed magnetic resonance logging sensor, yielding a signal-to-noise ratio of 23.5.

Many quartz tubes are used in electron paramagnetic resonance (EPR) experiments. These tubes are long and thin, and difficult to clean. To address the problem, an automated washing instrument for EPR sample tubes is designed. The whole instrument mainly includes a water purification machine, water storage tank, booster pump, air compressor, controller, solenoid valve pipeline, and washing rack. Fully automatic washing and drying of EPR sample tubes is achieved by controlling the solenoid valve and the motor/lifter through a Raspberry Pi computer, relay extension module, and Python Graphical User Interface (GUI) program. The instrument is used to clean EPR sample tubes that had contained solid and viscous liquid. The results demonstrate that the instrument has excellent cleaning performance (no impurity signals under low-temperature conditions of T =2 K) and high efficiency (completing a cleaning and drying cycle within 5 min), showcasing significant practical application value.

Vapor cell rubidium atomic clock is widely used in the fields of satellite navigation and communication with advantages including small size, light weight, low power and maintenance cost. The high-performance vapor cell rubidium atomic clocks in BDS-3 (Beidou-3 Navigation Satellite System) demonstrate exceptional stability, achieving 5E-13/ \sqrt{\tau }within 1~10 000 s and exceeding 3E-15 at one day. However, in atmospheric environment, due to environmental factors, particularly the influence of atmospheric pressure, the long-term stability deteriorates by 1 to 2 orders of magnitude after 1 000 s. This paper proposes a high-precision pressure compensation method by analyzing noise introduced from compensation algorithm and conducting sufficient experimental verification. After compensation, the long-term stability at 10 000 s of ground-type rubidium atomic clock is improved by approximately one order of magnitude, reaching a frequency stability better than 6.5E-15.