Standard Nuclear Magnetic Resonance Research Articles

Mediterranean Diet Adherence and Risk of All-Cause Mortality in Women

Higher adherence to the Mediterranean diet has been associated with reduced risk of all-cause mortality, but data on underlying molecular mechanisms over long follow-up are limited. To investigate Mediterranean diet adherence and risk of all-cause mortality and to examine the relative contribution of cardiometabolic factors to this risk reduction. This cohort study included initially healthy women from the Women's Health Study, who had provided blood samples, biomarker measurements, and dietary information. Baseline data included self-reported demographics and a validated food-frequency questionnaire. The data collection period was from April 1993 to January 1996, and data analysis took place from June 2018 to November 2023. Mediterranean diet score (range, 0-9) was computed based on 9 dietary components. Thirty-three blood biomarkers, including traditional and novel lipid, lipoprotein, apolipoprotein, inflammation, insulin resistance, and metabolism measurements, were evaluated at baseline using standard assays and nuclear magnetic resonance spectroscopy. Mortality and cause of death were determined from medical and death records. Cox proportional hazards regression was used to calculate hazard ratios (HRs) for Mediterranean diet adherence and mortality risk, and mediation analyses were used to calculate the mediated effect of different biomarkers in understanding this association. Among 25 315 participants, the mean (SD) baseline age was 54.6 (7.1) years, with 329 (1.3%) Asian women, 406 (1.6%) Black women, 240 (0.9%) Hispanic women, 24 036 (94.9%) White women, and 95 (0.4%) women with other race and ethnicity; the median (IQR) Mediterranean diet adherence score was 4.0 (3.0-5.0). Over a mean (SD) of 24.7 (4.8) years of follow-up, 3879 deaths occurred. Compared with low Mediterranean diet adherence (score 0-3), adjusted risk reductions were observed for middle (score 4-5) and upper (score 6-9) groups, with HRs of 0.84 (95% CI, 0.78-0.90) and 0.77 (95% CI, 0.70-0.84), respectively (P for trend < .001). Further adjusting for lifestyle factors attenuated the risk reductions, but they remained statistically significant (middle adherence group: HR, 0.92 [95% CI, 0.85-0.99]; upper adherence group: HR, 0.89 [95% CI, 0.82-0.98]; P for trend = .001). Of the biomarkers examined, small molecule metabolites and inflammatory biomarkers contributed most to the lower mortality risk (explaining 14.8% and 13.0%, respectively, of the association), followed by triglyceride-rich lipoproteins (10.2%), body mass index (10.2%), and insulin resistance (7.4%). Other pathways, including branched-chain amino acids, high-density lipoproteins, low-density lipoproteins, glycemic measures, and hypertension, had smaller contributions (<3%). In this cohort study, higher adherence to the Mediterranean diet was associated with 23% lower risk of all-cause mortality. This inverse association was partially explained by multiple cardiometabolic factors.

NOE analysis using dual injection DNP‐NMR for studies of solvent–solute interactions at low concentrations

AbstractDynamic nuclear polarization (DNP) offers significant signal enhancement compared to conventional nuclear magnetic resonance (NMR) in measuring the nuclear Overhauser effect. Owing to this enhancement, DNP enables the quantitative analysis of solvent–solute interactions, which are typically challenging to assess using standard NMR techniques. However, current experimental setups generally require the use of samples with relatively high solute concentrations because of large dilution factors. This limits the studies on solvent–solute interactions for bio‐related molecules, particularly those with low solubility. In such cases, the concentration of solute post‐dilution often falls below the detection limits. Herein, we introduce a novel dual injection system designed to considerably increase the dilution factor, thereby enabling the use of samples with lower solute concentrations while maintaining detectable signal levels. The effectiveness of this system was demonstrated in experiments using trifluoroacetic acid at concentrations 50 times lower than those used in the conventional method.

Direct Observation of Polaritonic Chemistry by Nuclear Magnetic Resonance Spectroscopy

AbstractPolaritonic chemistry is emerging as a powerful approach to modifying the properties and reactivity of molecules and materials. However, probing how the electronics and dynamics of molecular systems change under strong coupling has been challenging due to the narrow range of spectroscopic techniques that can be applied in situ. Here we develop microfluidic optical cavities for vibrational strong coupling (VSC) that are compatible with nuclear magnetic resonance (NMR) spectroscopy using standard liquid NMR tubes. VSC is shown to influence the equilibrium between two conformations of a molecular balance sensitive to London dispersion forces, revealing an apparent change in the equilibrium constant under VSC. In all compounds studied, VSC does not induce detectable changes in chemical shifts, J‐couplings, or spin‐lattice relaxation times. This unexpected finding indicates that VSC does not substantially affect molecular electron density distributions, and in turn has profound implications for the possible mechanisms at play in polaritonic chemistry under VSC and suggests that the emergence of collective behavior is critical.

Direct Observation of Polaritonic Chemistry by Nuclear Magnetic Resonance Spectroscopy.

Polaritonic chemistry is emerging as a powerful approach to modifying the properties and reactivity of molecules and materials. However, probing how the electronics and dynamics of molecular systems change under strong coupling has been challenging due to the narrow range of spectroscopic techniques that can be applied in situ. Here we develop microfluidic optical cavities for vibrational strong coupling (VSC) that are compatible with nuclear magnetic resonance (NMR) spectroscopy using standard liquid NMR tubes. VSC is shown to influence the equilibrium between two conformations of a molecular balance sensitive to London dispersion forces, revealing an apparent change in the equilibrium constant under VSC. In all compounds studied, VSC does not induce detectable changes in chemical shifts, J-couplings, or spin-lattice relaxation times. This unexpected finding indicates that VSC does not substantially affect molecular electron density distributions, and in turn has profound implications for the possible mechanisms at play in polaritonic chemistry under VSC and suggests that the emergence of collective behavior is critical.

Cryogen-free 400-MHz nuclear magnetic resonance spectrometer as a versatile tool for pharmaceutical process analytical technology.

The discovery of new ceramic materials containing Ba-La-Cu oxides in 1986 that exhibited superconducting properties at high temperatures in the range of 35 K or higher, recognized with the Nobel Prize in Physics in 1987, opened a new world of opportunities for nuclear magnetic resonance (NMRs) and magnetic resonance imaging (MRIs) to move away from liquid cryogens. This discovery expands the application of high temperature superconducting (HTS) materials to fields beyond the chemical and medical industries, including electrical power grids, energy, and aerospace. The prototype 400-MHz cryofree HTS NMR spectrometer installed at Amgen's chemistry laboratory has been vital for a variety of applications such as structure analysis, reaction monitoring, and CASE-3D studies with RDCs. The spectrometer has been integrated with Amgen's chemistry and analytical workflows, providing pipeline project support in tandem with other Kinetic Analysis Platform technologies. The 400-MHz cryofree HTS NMR spectrometer, as the name implies, does not require liquid cryogens refills and has smaller footprint that facilitates installation into a chemistry laboratory fume hood, sharing the hood with a process chemistry reactor. Our evaluation of its performance for structural analysis with CASE-3D protocol and for reaction monitoring of Amgen's pipeline chemistry was successful. We envision that the HTS magnets would become part of the standard NMR and MRI spectrometers in the future. We believe that while the technology is being developed, there is room for all magnet options, including HTS, low temperature superconducting (LTS) magnets, and low field benchtop NMRs with permanent magnets, where utilization will be dependent on application type and costs.

Anisotropic NMR data acquisition with a prototype 400 MHz cryogen-free NMR spectrometer.

High-temperature superconducting (HTS) materials have recently been incorporated into the construction of HTS cryogen-free magnets for nuclear magnetic resonance (NMR) spectroscopy. These HTS NMR spectrometers do not require liquid cryogens, thereby providing significant cost savings and facilitating easy integration into chemistry laboratories. However, the optimal performance of these HTS magnets against standard cryogen NMR magnets must be evaluated, especially with demanding modern NMR applications such as NMR in anisotropic media. The stability of the HTS magnets over time and their performance with complex pulse sequence experiments are the main unknown factors of this new technology. In this study, we evaluate the utility of our prototype 400 MHz cryogen-free power-driven HTS NMR spectrometer, installed in the fumehood of a chemistry laboratory, for stereochemical analysis of three commercial natural products (artemisinin, artemether, and dihydroartemisinin) via measurement of anisotropic NMR data, in particular, residual dipolar couplings. The accuracy of measurement of the anisotropic NMR data with the HTS magnet spectrometer is evaluated through the CASE-3D fitting protocol, as implemented in the Mestrenova-StereoFitter software program.

Automated nuclear magnetic resonance fingerprinting of mixtures.

Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for qualitative and quantitative analysis. However, for complex mixtures, determining the speciation from NMR spectra can be tedious and sometimes even unfeasible. On the other hand, identifying and quantifying structural groups in a mixture from NMR spectra is much easier than doing the same for components. We call this group-based approach "NMR fingerprinting." In this work, we show that NMR fingerprinting can even be performed in an automated way, without expert knowledge, based only on standard NMR spectra, namely, 13C, 1H, and 13C DEPT NMR spectra. Our approach is based on the machine-learning method of support vector classification (SVC), which was trained here on thousands of labeled pure-component NMR spectra from open-source data banks. We demonstrate the applicability of the automated NMR fingerprinting using test mixtures, of which spectra were taken using a simple benchtop NMR spectrometer. The results from the NMR fingerprinting agree remarkably well with the ground truth, which was known from the gravimetric preparation of the samples. To facilitate the application of the method, we provide an interactive website (https://nmr-fingerprinting.de), where spectral information can be uploaded and which returns the NMR fingerprint. The NMR fingerprinting can be used in many ways, for example, for process monitoring or thermodynamic modeling using group-contribution methods-or simply as a first step in species analysis.

MagMet: A fully automated web server for targeted nuclear magnetic resonance metabolomics of plasma and serum.

Nuclear magnetic resonance (NMR) spectral analysis of biofluids can be a time-consuming process, requiring the expertise of a trained operator. With NMR becoming increasingly popular in the field of metabolomics, there is a growing need to change this paradigm and to automate the process. Here we introduce MagMet, an online web server, that automates the processing and quantification of 1D 1 H NMR spectra from biofluids-specifically, human serum/plasma metabolites, including those associated with inborn errors of metabolism (IEM). MagMet uses a highly efficient data processing procedure that performs automatic Fourier Transformation, phase correction, baseline optimization, chemical shift referencing, water signal removal, and peak picking/peak alignment. MagMet then uses the peak positions, linewidth information, and J-couplings from its own specially prepared standard metabolite reference spectral NMR library of 85 serum/plasma compounds to identify and quantify compounds from experimentally acquired NMR spectra of serum/plasma. MagMet employs linewidth adjustment for more consistent quantification of metabolites from higher field instruments and incorporates a highly efficient data processing procedure for more rapid and accurate detection and quantification of metabolites. This optimized algorithm allows the MagMet webserver to quickly detect and quantify 58 serum/plasma metabolites in 2.6 min per spectrum (when processing a dataset of 50-100 spectra). MagMet's performance was also assessed using spectra collected from defined mixtures (simulating other biofluids), with >100 previously measured plasma spectra, and from spiked serum/plasma samples simulating known IEMs. In all cases, MagMet performed with precision and accuracy matching the performance of human spectral profiling experts. MagMet is available at http://magmet.ca.

Rational method for defining and quantifying pseudo-components based on NMR spectroscopy.

Poorly specified mixtures, whose composition is unknown, are ubiquitous in chemical and biochemical engineering. In the present work, we propose a rational method for defining and quantifying pseudo-components in such mixtures that is free of ad hoc assumptions. The new method requires only standard nuclear magnetic resonance (NMR) experiments and can be fully automated. In the first step, the method analyzes the composition of the poorly specified mixture in terms of structural groups, which is much easier than obtaining the component speciation. The structural groups are then clustered into pseudo-components based on information on the self-diffusion coefficients measured by pulsed-field gradient (PFG) NMR spectroscopy. We demonstrate the performance of the new method on several aqueous mixtures. The method is broadly applicable and provides a sound basis for modeling and simulation of processes with poorly specified mixtures, without the need for tedious and expensive structure elucidation. It is also attractive for process monitoring.

Methods for Structure Determination of SH2 Domain-Phosphopeptide Complexes by NMR.

Nuclear magnetic resonance (NMR) spectroscopy is a powerful technique to solve the structure of biomolecular complexes at atomic resolution in solution. Small proteins such as Src-homology 2 (SH2) domains have fast tumbling rates and long-lived NMR signals, making them particularly suited to be studied by standard NMR methods. SH2 domains are modular proteins whose function is the recognition of sequences containing phosphotyrosines. In this chapter, we describe the application of NMR to assess the interaction between SH2 domains and phosphopeptides and determine the structure of the resulting complexes.

Modal engineering of electromagnetic circuits to achieve rapid settling times.

Inductive circuits and devices are ubiquitous and important design elements in many applications, such as magnetic drives, galvanometers, magnetic scanners, applying direct current (DC) magnetic fields to systems, radio frequency coils in nuclear magnetic resonance (NMR) systems, and a vast array of other applications. They are widely used to generate both DC and alternating current (AC) magnetic fields. Many of these applications require a rapid step and settling time, turning the DC or AC magnetic field on and off quickly. The inductive response normally makes this a challenging thing to do. In this article, we discuss open loop control algorithms for achieving rapid step and settling times in four general categories of applications: DC and AC systems where the system is either under- or over-damped. Each of these four categories requires a different algorithm, which we describe here. We show the operation of these drive methods using Simulink and Simscape modeling tools, analytical solutions to the underlying differential equations, and experimental results using an inductive magnetic coil and a Hall sensor. Finally, we demonstrate the application of these techniques to significantly reduce ringing in a standard NMR circuit. We intend this article to be practical, with useful, easy-to-apply algorithms and helpful tuning tricks.

Magnetic resonance imaging for non-invasive measurement of plastic ingestion in marine wildlife

Monitoring plastic ingestion by marine wildlife is important for both characterizing the extent of plastic pollution in the environment and understanding its effect on species and ecosystems. Current methods to detect plastic in the digestive system of animals are slow and invasive, such that the number of animals that can be screened is limited. In this article, magnetic resonance imaging (MRI) is investigated as a possible technology to perform rapid, non-invasive detection of plastic ingestion. Standard MRI methods were able to directly measure one type of plastic in a fulmar stomach and another type was able to be indirectly detected. In addition to MRI, other standard nuclear magnetic resonance (NMR) measurements were made. Different types of plastic were tested, and distinctive NMR signal characteristics were found in common for each type, allowing them to be distinguished from one another. The NMR results indicate specialized MRI sequences could be used to directly image several types of plastic. Although current commercial MRI technology is not suitable for field use, existing single-sided MRI research systems could be adapted for use outside the laboratory and become an important tool for future monitoring of wild animals.

Direct Detection of Glutathione Biosynthesis, Conjugation, Depletion and Recovery in Intact Hepatoma Cells.

Nuclear magnetic resonance (NMR) spectroscopy was used to monitor glutathione metabolism in alginate-encapsulated JM-1 hepatoma cells perfused with growth media containing [3,3′-13C2]-cystine. After 20 h of perfusion with labeled medium, the 13C NMR spectrum is dominated by the signal from the 13C-labeled glutathione. Once 13C-labeled, the high intensity of the glutathione resonance allows the acquisition of subsequent spectra in 1.2 min intervals. At this temporal resolution, the detailed kinetics of glutathione metabolism can be monitored as the thiol alkylating agent monobromobimane (mBBr) is added to the perfusate. The addition of a bolus dose of mBBr results in rapid diminution of the resonance for 13C-labeled glutathione due to a loss of this metabolite through alkylation by mBBr. As the glutathione resonance decreases, a new resonance due to the production of intracellular glutathione-bimane conjugate is detectable. After clearance of the mBBr dose from the cells, intracellular glutathione repletion is then observed by a restoration of the 13C-glutathione signal along with wash-out of the conjugate. These data demonstrate that standard NMR techniques can directly monitor intracellular processes such as glutathione depletion with a time resolution of approximately < 2 min.

DREAMTIME NMR Spectroscopy: Targeted Multi‐Compound Selection with Improved Detection Limits

AbstractNMR/MRI are critical tools for studying molecular structure and interactions but suffer from relatively low sensitivity and spectral overlap. Here, a Nuclear Magnetic Resonance (NMR) approach, termed DREAMTIME, is introduced that provides “a molecular window” inside complex systems, capable of showing only what the user desires, with complete molecular specificity. The user chooses a list of molecules of interest, and the approach detects only those targets while all other molecules are invisible. The approach is demonstrated in whole human blood and urine, small living aquatic organisms in 1D/2D NMR, and MRI. Finally, as proof‐of‐concept, once overlap is removed via DREAMTIME, a novel “multi‐focusing” approach can be used to increase sensitivity. In human blood and urine, sensitivity increases of 7–12 fold over standard 1H NMR are observed. Applicable even to unknowns, DREAMTIME has widespread application, from monitoring product formation in organic chemistry to monitoring/identifying suites of molecular targets in complex media or in vivo.

Forward Modeling Steady-State Free Precession in Surface NMR

In efforts to map water at depth, steady-state free-precession (SSFP) sequences promise to rapidly increase data acquisition rates in the practice of surface nuclear magnetic resonance (NMR). Unlike conventional surface NMR excitation schemes, pulses in SSFP are transmitted so frequently that the nuclear magnetization of hydrogen in water can not return to its natural alignment with the earth’s ambient magnetic field, and instead achieve a steady-state; a dynamic equilibrium between pulses. Unfortunately, the traditional formulations of SSFP sequences and the full surface NMR forward models are not immediately compatible with each other. Firstly, the traditional analysis of SSFP sequences assume that relaxation during pulse (RDP) effects are negligible, which is not always valid in surface NMR. Secondly, even for single pulse measurements, the surface NMR forward model can be computationally demanding; this challenge scales with the number of pulses. Here we investigate the incorporation of RDP effects on the dynamic equilibrium of SSFP measurements. This is then incorporated into the full surface NMR forward model by deriving analytical expressions to directly predict processed surface NMR data. The model is validated by jointly inverting an extensive and diverse suite of SSFP measurements; 12 distinct sequences each with 16 pulse moments. The inverted model has a data misfit of 0.99 and is consistent with models derived from standard NMR data. The ability of our forward model to reproduce diverse signals and jointly invert them is a strong indication of its validity.

Particles and corrected particles of LDL and non-HDL are stronger predicters of coronary lesion in postmenopausal women

BackgroundThe optimum lipid indexes, predicting the coronary lesion in postmenopausal women are not clear.ObjectiveTo evaluate the optimum lipid predicter for coronary lesion in routine and advanced lipid tests.Method300 postmenopausal women were enrolled and assigned into coronary heart disease (CHD) Group (242), and non-CHD Group (58). Routine and advanced lipid indexes were measured with standard laboratory test and nuclear magnetic resonance (NMR) spectroscopy. The correlation and predictivities for CHD of routine and advanced lipid indexes were performed with Logistic regression, Spearman correlation analysis and receiver operating characteristic (ROC).ResultsAge (hazard ratio (HR) 2.58, 95% confidence interval (CI) 1.08–5.86, P = 0.03), apolipoprotein B (ApoB) (HR 1.35, 95% CI 1.15–1.59, P < 0.001), corrected particles of low-density lipoprotein (LDL-p-corr) (HR 1.05, 95% CI 1.03–1.06, P < 0.001) and corrected particles of non-high-density lipoprotein (non-HDL-p-corr) (HR 1.02, 95% CI 1.01–1.03, P < 0.001) were the risk factors of CHD. LDL cholesterol (LDL-C), LDL-p, LDL-p-corr, HDL cholesterol (HDL-C), non-HDL cholesterol (non-HDL-C), non-HDL-p and non-HDL-p-corr were in linear correlation with Gensini score. Advanced lipid indexes LDL-p (area under curve (AUC) = 0.750, P = 0.02), LDL-p-corr (AUC = 0.759, P = 0.02), non-HDL-p (AUC = 0.693, P = 0.03) and non-HDL-p-corr (AUC = 0.699, P = 0.03) were more predictive for CHD than the routine ones (LDL-C and non-HDL-C).ConclusionIn postmenopausal women, age, ApoB, LDL-p-corr and non-HDL-p-corr were risk factors of CHD. Compared with traditional lipid items, LDL-p, LDL-p-corr, non-HDL-p and non-HDL-p-corr may be better lipid indexes for CHD in postmenopausal women.

Substrate quality of drained organic soils—Implications for carbon dioxide fluxes

AbstractBackgroundPeatlands only cover a minor fraction of the global terrestrial surface, but due to drainage, they are major contributors to carbon dioxide (CO2) emissions from soils. Previous studies have shown that hydrological conditions, nutrient availability and anthropogenic disturbance play an important role in the mineralisation of organic matter. Furthermore, microbial turnover depends on peat quality, which is determined by its botanical origin and degree of transformation under natural conditions.AimsThe objective of this study was to shed light on the interdependence between mineralisation rates, secondary transformation of peat and chemical composition by examining the differences between bog and fen peat and between strongly degraded topsoil and well‐preserved subsoil.MethodsBog and fen peat from ten different peatlands under grassland use in Germany were analysed for their chemical composition using standard 13C nuclear magnetic resonance (NMR) spectroscopy and wet chemical extractions for fibre analysis. The radiocarbon age was determined as well. The results were combined with CO2 fluxes from a previous incubation study.ResultsTopsoils had higher shares of proteins and lipids, and lower shares of carbohydrates and aromatics than subsoils. Bog peat subsoils were characterised by higher shares of carbohydrates and lower shares of aromatics than fen peat subsoils. Topsoils were more similar to each other in their chemical composition than the subsoils. Considering all samples, aromatics and phenolics were negatively correlated with CO2 fluxes. Measured CO2 fluxes from topsoils were significantly higher than from subsoils. However, no influences of chemical composition on CO2 fluxes were detected when examining topsoils and subsoils separately. Even though aromatics and phenolics showed positive relationships with radiocarbon age, differences in age alone were unable to explain the higher amounts of these compounds in the subsoil.ConclusionsThe results imply that chemical composition of topsoil peat is not the reason for higher mineralisation rates compared to subsoil peat, but rather a consequence of decomposition and transformation. Thus, peat mineralisation of drained organic soils under agriculture might not slow down over time due to gradually decreasing peat quality but could increase further.

Quantitative Analysis of Porous Silicon Nanoparticles Functionalization by 1H NMR.

Porous silicon (PSi) nanoparticles have been applied in various fields, such as catalysis, imaging, and biomedical applications, because of their large specific surface area, easily modifiable surface chemistry, biocompatibility, and biodegradability. For biomedical applications, it is important to precisely control the surface modification of PSi-based materials and quantify the functionalization density, which determines the nanoparticle’s behavior in the biological system. Therefore, we propose here an optimized solution to quantify the functionalization groups on PSi, based on the nuclear magnetic resonance (NMR) method by combining the hydrolysis with standard 1H NMR experiments. We optimized the hydrolysis conditions to degrade the PSi, providing mobility to the molecules for NMR detection. The NMR parameters were also optimized by relaxation delay and the number of scans to provide reliable NMR spectra. With an internal standard, we quantitatively analyzed the surficial amine groups and their sequential modification of polyethylene glycol. Our investigation provides a reliable, fast, and straightforward method in quantitative analysis of the surficial modification characterization of PSi requiring a small amount of sample.

The Field-Frequency Lock for Fast Field Cycling Magnetic Resonance: From NMR to MRI

Magnetic field stability plays a fundamental role in Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI) experiments, guaranteeing accuracy and reproducibility of results. While high levels of stabilization can be achieved for standard NMR techniques, this task becomes particularly challenging for Fast Field Cycling (FFC) NMR and MRI, where the main magnetic field is switched to higher or lower levels during the pulse sequence, and field stabilization must be guaranteed within a very short time after switching. Recent works have addressed the problem with rigorous tools from control system theory, proposing a model based approach for the synthesis of magnetic field controllers for FFC-NMR. While an experimental proof of concept has underlined the correctness of the approach for a complete FFC-NMR setup, the application of the novel, model based Field-Frequency Lock (FFL) system to a FFC-MRI scanner requires proper handling of field encoding gradients. Furthermore, the proof of concept work has also stressed how further advances in the hardware and firmware could improve the overall performances of the magnetic field control loop. The main aim of this perspective paper is then discussing the key challenges that arise in the development of the FFL system suitable for a complete MRI scanner, as well as defining possible research directions by means of preliminary, simulated experiments, with the final goal of favoring the development of a novel, model based FFL system for FFC-MRI.

Two States of Water Converge to One State below 215 K.

Anomalies of water have been explained by the two-state water model. In the model, water becomes one state upon supercooling. However, water crystallizes completely below 235 K ("no man's land"). The structural origin of the anomalous of the water is hidden in the "no man's land". To understand the properties of water, the spectroscopic experiment in "Norman's land" is inevitable. Hence, we proposed a new soft-confinement method for standard nuclear magnetic resonance spectroscopy to explore the "no man's land". We found the singularity temperature (215 K) at ambient pressure. Water exists in one state below 215 K. Above 215 K, the two states of water are supercritical states of the liquid-liquid critical point. The current study provides a perspective to determine the liquid-liquid critical point of water existing in a high-pressure condition.