It is known that sialyllactose (SL) in mammalians is a major source of sialic acid (Sia), which can further form cytidine monophosphate sialic acid (CMP-Sia), and the final product is polysialic acid (polySia) using polysialyltransferases (polySTs) on the neural cell adhesion molecule (NCAM). This process is called NCAM polysialylation. The overexpression of polysialylation is strongly related to cancer cell migration, invasion, and metastasis. In order to inhibit the overexpression of polysialylation, in this study, SL was selected as an inhibitor to test whether polysialylation could be inhibited. Our results suggest that the interactions between the polysialyltransferase domain (PSTD) in polyST and CMP-Siaand the PSTD and polySia could be inhibited when the 3\'-sialyllactose (3\'-SL) or 6\'-sialyllactose (6\'-SL) concentration is about 0.5 mM or 6\'-SL and 3 mM, respectively. The results also show that SLs (particularly for 3\'-SL) are the ideal inhibitors compared with another two inhibitors, low-molecular-weight heparin (LMWH) and cytidine monophosphate (CMP), because 3\'-SL can not only be used to inhibit NCAM polysialylation, but is also one of the best supplements for infant formula and the gut health system.

Pure shift NMR spectroscopy enables the robust probing on molecular structure and dynamics, benefiting from great resolution enhancements. Despite extensive application landscapes in various branches of chemistry, the long experimental times induced by the additional time dimension generally hinder its further developments and practical deployments, especially for multi-dimensional pure shift NMR. Herein, this study proposes and implements the fast, reliable, and robust reconstruction for accelerated pure shift NMR spectroscopy with lightweight attention-assisted deep neural network. This deep learning protocol allows one to regain high-resolution signals and suppress undersampling artifacts, as well as furnish high-fidelity signal intensities along with the accelerated pure shift acquisition, benefitting from the introduction of the attention mechanism to highlight the spectral feature and information of interest. Extensive results of simulated and experimental NMR data demonstrate that this attention-assisted deep learning protocol enables the effective recovery of weak signals that are almost drown in the serious undersampling artifacts, and the distinction and recognition of close chemical shifts even though using merely 5.4% data, highlighting its huge potentials on fast pure shift NMR spectroscopy. As a result, this study affords a promising paradigm for the AI-assisted NMR protocols toward broader applications in chemistry, biology, materials, and life sciences, and among others.

Disuse muscle atrophy (DMA) is a significant healthcare challenge characterized by progressive loss of muscle mass and function resulting from prolonged inactivity. The development of effective strategies for muscle recovery is essential. In this study, we established a DMA mouse model through hindlimb suspension to evaluate the therapeutic potential of lactate in alleviating the detrimental effects on the gastrocnemius muscle. Using NMR-based metabolomic analysis, we investigated the metabolic changes in DMA-injured gastrocnemius muscles compared to controls and evaluated the beneficial effects of lactate treatment. Our results show that lactate significantly reduced muscle mass loss and improved muscle function by downregulating Murf1 expression, decreasing protein ubiquitination and hydrolysis, and increasing myosin heavy chain levels. Crucially, lactate corrected perturbations in four key metabolic pathways in the DMA gastrocnemius: the biosynthesis of phenylalanine, tyrosine, and tryptophan; phenylalanine metabolism; histidine metabolism; and arginine and proline metabolism. In addition to phenylalanine-related pathways, lactate also plays a role in regulating branched-chain amino acid metabolism and energy metabolism. Notably, lactate treatment normalized the levels of eight essential metabolites in DMA mice, underscoring its potential as a therapeutic agent against the consequences of prolonged inactivity and muscle wasting. This study not only advances our understanding of the therapeutic benefits of lactate but also provides a foundation for novel treatment approaches aimed at metabolic restoration and muscle recovery in conditions of muscle wasting.

Fermentation parameters, especially the duration, are important in imparting a peculiar taste and flavor to soy sauce. The main purpose of this research was to monitor metabolic changes occurring during the various time intervals of the fermentation process. NMR-based metabolomics was used to monitor the compositional changes in soy sauce during fermentation. The 1H-NMR spectra of the soy sauce samples taken from the fermentation tanks at 0 to 8 months were analyzed using 1H-NMR spectroscopy, and the obtained spectra were analyzed by multivariate statistical analysis. The Principal Component Analysis (PCA) and Partial Least Square Discriminate analysis (PLSDA) revealed the separation of samples fermented for various time durations under identical conditions. Key metabolites shown by corresponding loading plots exhibited variations in amino acids (lysine, threonine, isoleucine, etc.), acetate, glucose, fructose, sucrose, ethanol, glycerol, and others. The levels of ethanol in soy sauce increased with longer fermentation durations, which can be influenced by both natural fermentation and the intentional addition of ethanol as a preservative. The study shows that the variation in metabolite can be very efficiently monitored using 1H-NMR-based metabolomics, thus suggestion to optimize the time duration to get the soy sauce product with the desired taste and flavor.

The expression of polysialic acid (polySia) on the neuronal cell adhesion molecule (NCAM) is called NCAM-polysialylation, which is strongly related to the migration and invasion of tumor cells and aggressive clinical status. Thus, it is important to select a proper drug to block tumor cell migration during clinical treatment. In this study, we proposed that lactoferrin (LFcinB11) may be a better candidate for inhibiting NCAM polysialylation when compared with CMP and low-molecular-weight heparin (LMWH), which were determined based on our NMR studies. Furthermore, neutrophil extracellular traps (NETs) represent the most dramatic stage in the cell death process, and the release of NETs is related to the pathogenesis of autoimmune and inflammatory disorders, with proposed involvement in glomerulonephritis, chronic lung disease, sepsis, and vascular disorders. In this study, the molecular mechanisms involved in the inhibition of NET release using LFcinB11 as an inhibitor were also determined. Based on these results, LFcinB11 is proposed as being a bifunctional inhibitor for inhibiting both NCAM polysialylation and the release of NETs.

Excessive exposure to light is a global issue. Artificial light pollution has been shown to disrupt the body\'s natural circadian rhythm. To investigate the impacts of light on metabolism, we studied Sprague-Dawley rats chronically exposed to red or blue light during daytime or nighttime. Rats in the experimental group were exposed to extended light for 4 hours during daytime or nighttime to simulate the effects of excessive light usage. Strikingly, we found systemic metabolic alterations only induced by blue light during daytime. Furthermore, we conducted metabolomic analyses of the cerebrospinal fluid, serum, heart, liver, spleen, adrenal, cerebellum, pituitary, prostate, spermatophore, hypothalamus and kidney from rats in the control and blue light exposure during daytime. Significant changes in metabolites have been observed in cerebrospinal fluid, serum, hypothalamus and kidney of rats exposed to blue light during daytime. Metabolic alterations observed in rats encompassing pyruvate metabolism, glutathione metabolism homocysteine degradation, phosphatidylethanolamine biosynthesis, and phospholipid biosynthesis, exhibit analogous patterns to those inherent in specific physiological processes, notably neurodevelopment, cellular injury, oxidative stress, and autophagic pathways. Our study provides insights into tissue-specific metabolic changes in rats exposed to blue light during the daytime and may help explain potential mechanisms of photopathogenesis.

The quantitative measurement of adsorbed guest species within metal-organic framework (MOF) pores is of fundamental importance for evaluating the adsorption performance of MOFs. However, routine analytic techniques such as thermogravimetric analysis cannot distinguish the contribution from species adsorbed within pores, species adsorbed on the surface, and gas phase or liquid phase encapsulated in the inter-crystalline space. Herein, we developed a new quantification method based on the cross-polarization (CP) solid-state nuclear magnetic resonance (ssNMR) technique, in which only the species within MOF pores are selectively probed due to the dramatically reduced mobility. Using the commercialized MOF α-Mg3(HCOO)6 as an example, a good linear correlation between Areaguest/Areaframework (i. e., the integrated area of guest and framework 13C NMR signals) and guest loading can be observed for several representative molecules such as benzene, tetrahydrofuran (THF), and 1,4-dioxane, clearly revealing the feasibility of CP quantification approach. The effects of guest molecule and corresponding residual mobility on the CP quantification are further discussed by varying the geometry and size of guest molecules. This methodology thus provides an effective and irreplaceable route to evaluate the adsorption performance of porous materials in-depth, especially for liquid-phase adsorption and gas-phase adsorption in which the capillary condensation is not negligible.

Two-dimensional (2D) J-resolved spectroscopy provides valuable information on J-coupling constants for molecular structure analysis by resolving one-dimensional (1D) spectra. However, it is challenging to decipher the J-coupling connectivity in 2D J-resolved spectra because the J-coupling connectivity cannot be directly provided. In addition, 2D homonuclear correlation spectroscopy (COSY) can directly elucidate molecular structures by tracking the J-coupling connectivity between protons. However, this method is limited by the problem of spectral peak crowding and is only suitable for simple sample systems. To fully understand the intuitive coupling relationship and coupling constant information, we propose a three-dimensional (3D) COSY method called CTCOSY-JRES (Constant-Time COrrelation SpectroscopY and J-REsolved Spectroscopy) in this paper. By combining the J-resolved spectrum with the constant-time COSY technique, a doubly decoupled COSY spectrum can be provided while preserving the J-coupling constant along an additional dimension, ensuring high-resolution analysis of J-coupling connectivity and J-coupling information. Moreover, compression sensing and fold-over correction techniques are introduced to accelerate experimental acquisition. The CTCOSY-JRES method has been successfully validated in a variety of sample systems, including industrial, agricultural, and biopharmaceutical samples, revealing complex coupling interactions and providing deeper insights into the resolution of molecular structures.

BACKGROUND: Symmetrical NMR spectroscopy, such as Total Correlation Spectroscopy (TOCSY) and other homonuclear spectroscopy, displays symmetry in chemical shift but are generally not symmetrical in terms of intensity, which constitutes a pivotal branch of multidimensional NMR spectroscopy and offers a robust tool for elucidating the structures and dynamics of complex samples, particularly in the context of biological macromolecules. Non-Uniform Sampling (NUS) stands as a critical technique for accelerating multidimensional NMR experiments. However, symmetrical NMR spectroscopy inherently presents dynamic peak intensities, where cross peaks tend to be substantially weaker compared to diagonal peaks. Recovering these weaker cross peaks from NUS data poses a significant challenge, often resulting in compromised data quality.
RESULTS: We enhance the reconstruction quality of NUS symmetrical NMR spectroscopy based on the assumption that the asymmetry in intensity is mild. Regarding the sampling schedule, we employ the symmetrical sampling structure integrated with Poisson sampling schedule to enhance the efficiency of data acquisition. In term of the reconstruction algorithm, we propose the new method by incorporating hard and soft symmetrical constraints into our recently developed L1-norm-based Compressed Sensing (CS) method known as Sparse Complex-valued REconstruction Enabled by Newton method (SCREEN). Additionally, we propose a two-step reconstruction strategy that separately addresses diagonal and cross peaks. In this two-step strategy, cross peaks are effectively reconstructed by excluding the stronger diagonal peaks. Extensive experimental results validate the effectiveness of our proposed methodology.
CONCLUSIONS: This method enhances the overall quality of the reconstructed NUS symmetrical NMR spectra, especially in terms of cross peaks, thereby enriching the interpretation of spectral information. Furthermore, it boosts the robustness towards regularization parameters, facilitating a user-friendly experience.

Cytotoxic T-lymphocyte antigen 4 (CTLA-4) is a pivotal immune checkpoint receptor, playing a crucial role in modulating T-cell activation. In this study, we delved into the underlying mechanism by which a common mutation, G199R, in the cytoplasmic domain of CTLA-4 impacts its inhibitory function. Utilizing nuclear magnetic resonance (NMR) spectroscopy and biochemical techniques, we mapped the conformational changes induced by this mutation and investigated its role in CTLA-4 activity. Our findings reveal that this mutation leads to a distinct conformational alteration, enhancing protein-membrane interactions. Moreover, functional assays demonstrated an improved capacity of the G199R mutant to downregulate T-cell activation, underscoring its potential role in immune-related disorders. These results not only enhance our understanding of CTLA-4 regulatory mechanisms but also provide insights for targeted therapeutic strategies addressing immune dysregulation linked to CTLA-4 mutations.