Advanced detection tools in food fraud: A systematic review for holistic and rational detection method based on research and patents

Modern food chain supply management necessitates the dire need for mitigating food fraud and adulterations. This holistic review addresses different advanced detection technologies coupled with chemometrics to identify various types of adulterated foods. The data on research, patent and systematic review analyses (2018-2023) revealed both destructive and non-destructive methods to demarcate a rational approach for food fraud detection in various countries. These intricate hygiene standards and AI-based technology are also summarized for further prospective research. Chemometrics or AI-based techniques for extensive food fraud detection are demanded. A systematic assessment reveals that various methods to detect food fraud involving multiple substances need to be simple, expeditious, precise, cost-effective, eco-friendly and non-intrusive. The scrutiny resulted in 39 relevant experimental data sets answering key questions. However, additional research is necessitated for an affirmative conclusion in food fraud detection system with modern AI and machine learning approaches.

A silent echo-planar spectroscopic imaging readout with high spectral bandwidth MRSI using an ultrasonic gradient axis

PURPOSE

We present a novel silent echo-planar spectroscopic imaging (EPSI) readout, which uses an ultrasonic gradient insert to accelerate MRSI while producing a high spectral bandwidth (20 kHz) and a low sound level.

METHODS

The ultrasonic gradient insert consisted of a single-axis (z-direction) plug-and-play gradient coil, powered by an audio amplifier, and produced 40 mT/m at 20 kHz. The silent EPSI readout was implemented in a phase-encoded MRSI acquisition. Here, the additional spatial encoding provided by this silent EPSI readout was used to reduce the number of phase-encoding steps. Spectroscopic acquisitions using phase-encoded MRSI, a conventional EPSI-readout, and the silent EPSI readout were performed on a phantom containing metabolites with resonance frequencies in the ppm range of brain metabolites (0-4 ppm). These acquisitions were used to determine sound levels, showcase the high spectral bandwidth of the silent EPSI readout, and determine the SNR efficiency and the scan efficiency.

RESULTS

The silent EPSI readout featured a 19-dB lower sound level than a conventional EPSI readout while featuring a high spectral bandwidth of 20 kHz without spectral ghosting artifacts. Compared with phase-encoded MRSI, the silent EPSI readout provided a 4.5-fold reduction in scan time. In addition, the scan efficiency of the silent EPSI readout was higher (82.5% vs. 51.5%) than the conventional EPSI readout.

CONCLUSIONS

We have for the first time demonstrated a silent spectroscopic imaging readout with a high spectral bandwidth and low sound level. This sound reduction provided by the silent readout is expected to have applications in sound-sensitive patient groups, whereas the high spectral bandwidth could benefit ultrahigh-field MR systems.

Myelin bilayer mapping in the human brain in vivo

PURPOSE

To quantitatively map the myelin lipid-protein bilayer in the live human brain.

METHODS

This goal was pursued by integrating a multi-TE acquisition approach targeting ultrashort T2 signals with voxel-wise fitting to a three-component signal model. Imaging was performed at 3 T in two healthy volunteers using high-performance RF and gradient hardware and the HYFI sequence. The design of a suitable imaging protocol faced substantial constraints concerning SNR, imaging volume, scan time, and RF power deposition. Model fitting to data acquired using the proposed protocol was made feasible through simulation-based optimization, and filtering was used to condition noise presentation and overall depiction fidelity.

RESULTS

A multi-TE protocol (11 TEs of 20-780 μs) for in vivo brain imaging was developed in adherence with applicable safety regulations and practical scan time limits. Data acquired using this protocol produced accurate model fitting results, validating the suitability of the protocol for this purpose. Structured, grainy texture of myelin bilayer maps was observed and determined to be a manifestation of correlated image noise resulting from the employed acquisition strategy. Map quality was significantly improved by filtering to uniformize the k-space noise distribution and simultaneously extending the k-space support. The final myelin bilayer maps provided selective depiction of myelin, reconciling competitive resolution (1.4 mm) with adequate SNR and benign noise texture.

CONCLUSION

Using the proposed technique, quantitative maps of the myelin bilayer can be obtained in vivo. These maps offer unique information content with potential applications in basic research, diagnosis, disease monitoring, and drug development.

Metallo-β-lactamase inhibitors: A continuing challenge for combating antibiotic resistance

β-lactam antibiotics are the most successful and commonly used antibacterial agents, but the emergence of resistance to these drugs has become a global health threat. The expression of β-lactamase enzymes produced by pathogens, which hydrolyze the amide bond of the β-lactam ring, is the major mechanism for bacterial resistance to β-lactams. In particular, among class A, B, C and D β-lactamases, metallo-β-lactamases (MBLs, class B β-lactamases) are considered crucial contributors to resistance in gram-negative bacteria. To combat β-lactamase-mediated resistance, great efforts have been made to develop β-lactamase inhibitors that restore the activity of β-lactams. Some β-lactamase inhibitors, such as diazabicyclooctanes (DBOs) and boronic acid derivatives, have also been approved by the FDA. Inhibitors used in the clinic can inactivate mostly serine-β-lactamases (SBLs, class A, C, and D β-lactamases) but have not been effective against MBLs until now. In order to develop new inhibitors particularly for MBLs, various attempts have been suggested. Based on structural and mechanical studies of MBL enzymes, several MBL inhibitor candidates, including taniborbactam in phase 3 and xeruborbactam in phase 1, have been introduced in recent years. However, designing potent inhibitors that are effective against all subclasses of MBLs is still extremely challenging. This review summarizes not only the types of β-lactamase and mechanisms by which β-lactam antibiotics are inactivated, but also the research finding on β-lactamase inhibitors targeting these enzymes. These detailed information on β-lactamases and their inhibitors could give valuable information for novel β-lactamase inhibitors design.

SCREENES: Enhancing non-uniform sampling reconstruction for symmetrical NMR spectroscopy

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.

SIGNIFICANCE

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.

Amination and crosslinking of acetone-fractionated hardwood kraft lignin using different amines and aldehydes for sustainable bio-based wood adhesives

Hardwood kraft lignin from the pulping industry is burned or discarded. Its valorization was conducted by subjecting fractionation, amination with ethylenediamine, diethylenetriamine, and monoethanolamine, and crosslinking with formaldehyde or glyoxal to obtain bio-based wood adhesives. Acetone-soluble and insoluble hardwood kraft lignin were prepared and subjected to amination and then crosslinking. Fourier transform infrared, 13C NMR, 15N NMR, and X-ray photoelectron spectroscopy results revealed successful amination with amide, imine, and ether bonds and crosslinking of all samples. Hardwood kraft lignin aminated with diethylenetriamine/ethylenediamine and crosslinked using glyoxal exhibited excellent results in comparison with samples crosslinked using formaldehyde. Acetone-insoluble hardwood kraft lignin aminated and crosslinked using diethylenetriamine and formaldehyde, respectively, exhibited excellent adhesion strength with plywood, satisfying the requirements of the Korean standards. The amination and crosslinking of industrial waste hardwood kraft lignin constitute a beneficial valorization method.

Low-field, not low quality: 1D simplification, selective detection, and heteronuclear 2D experiments for improving low-field NMR spectroscopy of environmental and biological samples

Understanding environmental change is challenging and requires molecular-level tools to explain the physicochemical phenomena behind complex processes. Nuclear magnetic resonance (NMR) spectroscopy is a key tool that provides information on both molecular structures and interactions but is underutilized in environmental research because standard "high-field" NMR is financially and physically inaccessible for many and can be overwhelming to those outside of disciplines that routinely use NMR. "Low-field" NMR is an accessible alternative but has reduced sensitivity and increased spectral overlap, which is especially problematic for natural, heterogeneous samples. Therefore, the goal of this study is to investigate and apply innovative experiments that could minimize these challenges and improve low-field NMR analysis of environmental and biological samples. Spectral simplification (JRES, PSYCHE, singlet-only, multiple quantum filters), selective detection (GEMSTONE, DREAMTIME), and heteronuclear (reverse and CH3/CH2/CH-only HSQCs) NMR experiments are tested on samples of increasing complexity (amino acids, spruce resin, and intact water fleas) at-high field (500 MHz) and at low-field (80 MHz). A novel experiment called Doubly Selective HSQC is also introduced, wherein 1H signals are selectively detected based on the 1H and 13C chemical shifts of 1H-13C J-coupled pairs. The most promising approaches identified are the selective techniques (namely for monitoring), and the reverse and CH3-only HSQCs. Findings ultimately demonstrate that low-field NMR holds great potential for biological and environmental research. The multitude of NMR experiments available makes NMR tailorable to nearly any research need, and low-field NMR is therefore anticipated to become a valuable and widely used analytical tool moving forward.

Zinc Deficiency as a General Feature of Cancer: a Review of the Literature

Trace elements are minerals that are present in very low concentrations in the human body and yet are crucial for a wide range of physiological functions. Zinc, the second most abundant trace element, is obtained primarily from the diet. After being taken up in the intestine, zinc is distributed to various target organs, where it plays key roles in processes such as immunity, protein folding, apoptosis, and antioxidant activity. Given the important role of zinc in a wide range of enzymatic reactions and physiological processes, zinc deficiency has been identified in a variety of diseases, notably cancer. In recent years, multiple meta-analyses and reviews looking at zinc levels in individual cancer types have been published, as have a plethora of primary studies demonstrating a link between low zinc levels and specific types of cancer. In this review, we summarize recent evidence implicating low zinc concentrations in serum or tissues as a characteristic in a wide range of cancers. We also discuss preliminary findings indicating that zinc level measurement could ultimately become a useful clinical tool for cancer diagnosis and predicting outcomes in patients with cancer. Finally, we suggest future directions for further elucidating the role of zinc deficiency in cancer development and progression.

Comparison of triple quantum (TQ) TPPI and inversion recovery TQ TPPI pulse sequences at 9.4 and 21.1 T

PURPOSE

Both sodium T1 triple quantum (TQ) signal and T1 relaxation pathways have a unique sensitivity to the sodium molecular environment. In this study an inversion recovery time proportional phase increment (IRTQTPPI) pulse sequence was investigated for simultaneous and reliable quantification of sodium TQ signal and bi-exponential T1 relaxation times.

METHODS

The IRTQTPPI sequence combines inversion recovery TQ filtering and time proportional phase increment. The reliable and reproducible results were achieved by the pulse sequence optimized in three ways: (1) optimization of the nonlinear fit for the determination of both T1-TQ signal and T1 relaxation times; (2) suppression of unwanted signals by assessment of four different phase cycles; (3) nonlinear sampling during evolution time for optimal scan time without any compromises in fit accuracy. The relaxation times T1 and T2 and the TQ signals from IRTQTPPI and TQTPPI were compared between 9.4 and 21.1 T. The motional environment of the sodium nuclei was evaluated by calculation of correlation times and nuclear quadrupole interaction strengths.

RESULTS

Reliable measurements of the T1-TQ signals and T1 bi-exponential relaxation times were demonstrated. The fit parameters for all four phase cycles were in good agreement with one another, with a negligible influence of unwanted signals. The agar samples yielded normalized T1-TQ signals from 3% to 16% relative to single quantum (SQ) signals at magnetic fields of both 9.4 and 21.1 T. In comparison, the normalized T2-TQ signal was in the range 15%-35%. The TQ/SQ signal ratio was decreased at 21.1 T as compared with 9.4 T for both T1 and T2 relaxation pathways. The bi-exponential T1 relaxation time separation ranged from 15 to 18 ms at 9.4 T and 15 to 21 ms at 21.1 T. The T2 relaxation time separation was larger, ranging from 28 to 35 ms at 9.4 T and 37 to 40 ms at 21.1 T.

CONCLUSION

The IRTQTPPI sequence, while providing a less intensive TQ signal than TQTPPI, allows a simultaneous and reliable quantification of both the T1-TQ signal and T1 relaxation times. The unique sensitivities of the T1 and T2 relaxation pathways to different types of molecular motion provide a deeper understanding of the sodium MR environment.

Contrast-agent-based perfusion MRI code repository and testing framework: ISMRM Open Science Initiative for Perfusion Imaging (OSIPI)

PURPOSE

Software has a substantial impact on quantitative perfusion MRI values. The lack of generally accepted implementations, code sharing and transparent testing reduces reproducibility, hindering the use of perfusion MRI in clinical trials. To address these issues, the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI) aimed to establish a community-led, centralized repository for sharing open-source code for processing contrast-based perfusion imaging, incorporating an open-source testing framework.

METHODS

A repository was established on the OSIPI GitHub website. Python was chosen as the target software language. Calls for code contributions were made to OSIPI members, the ISMRM Perfusion Study Group, and publicly via OSIPI websites. An automated unit-testing framework was implemented to evaluate the output of code contributions, including visual representation of the results.

RESULTS

The repository hosts 86 implementations of perfusion processing steps contributed by 12 individuals or teams. These cover all core aspects of DCE- and DSC-MRI processing, including multiple implementations of the same functionality. Tests were developed for 52 implementations, covering five analysis steps. For T1 mapping, signal-to-concentration conversion and population AIF functions, different implementations resulted in near-identical output values. For the five pharmacokinetic models tested (Tofts, extended Tofts-Kety, Patlak, two-compartment exchange, and two-compartment uptake), differences in output parameters were observed between contributions.

CONCLUSIONS

The OSIPI DCE-DSC code repository represents a novel community-led model for code sharing and testing. The repository facilitates the re-use of existing code and the benchmarking of new code, promoting enhanced reproducibility in quantitative perfusion imaging.

An Update on MR Spectroscopy in Cancer Management: Advances in Instrumentation, Acquisition, and Analysis

MR spectroscopy (MRS) is a noninvasive imaging method enabling chemical and molecular profiling of tissues in a localized, multiplexed, and nonionizing manner. As metabolic reprogramming is a hallmark of cancer, MRS provides valuable metabolic and molecular information for cancer diagnosis, prognosis, treatment monitoring, and patient management. This review provides an update on the use of MRS for clinical cancer management. The first section includes an overview of the principles of MRS, current methods, and conventional metabolites of interest. The remainder of the review is focused on three key areas: advances in instrumentation, specifically ultrahigh-field-strength MRI scanners and hybrid systems; emerging methods for acquisition, including deuterium imaging, hyperpolarized carbon 13 MRI and MRS, chemical exchange saturation transfer, diffusion-weighted MRS, MR fingerprinting, and fast acquisition; and analysis aided by artificial intelligence. The review concludes with future recommendations to facilitate routine use of MRS in cancer management. Keywords: MR Spectroscopy, Spectroscopic Imaging, Molecular Imaging in Oncology, Metabolic Reprogramming, Clinical Cancer Management © RSNA, 2024.

Polarization transfer methods for quantitative analysis of flowing mixtures with benchtop 13C NMR spectroscopy

Benchtop NMR spectroscopy is attractive for process monitoring; however, there are still drawbacks that often hamper its use, namely, the comparatively low spectral resolution in 1H NMR, as well as the low signal intensities and problems with the premagnetization of flowing samples in 13C NMR. We show here that all these problems can be overcome by using 1H-13C polarization transfer methods. Two ternary test mixtures (one with overlapping peaks in the 1H NMR spectrum and one with well-separated peaks, which was used as a reference) were studied with a 1 T benchtop NMR spectrometer using the polarization transfer sequence PENDANT (polarization enhancement that is nurtured during attached nucleus testing). The mixtures were analyzed quantitatively in stationary as well as in flow experiments by PENDANT enhanced 13C NMR experiments, and the results were compared with those from the gravimetric sample preparation and from standard 1H and 13C NMR spectroscopy. Furthermore, as a proxy for a process monitoring application, continuous dilution experiments were carried out, and the composition of the mixture was monitored in a flow setup by 13C NMR benchtop spectroscopy with PENDANT. The results demonstrate the high potential of polarization transfer methods for applications in quantitative process analysis with benchtop NMR instruments, in particular with flowing samples.

Non-uniform sampling to enhance the performance of compact NMR for characterizing new psychoactive substances

Efficient and robust analytical methods are needed to improve the identification and subsequent regulation of new psychoactive substances (NPS). NMR spectroscopy is a unique method able to determine the structure of small molecules such as NPS even in mixtures. However, high-field NMR analysis is associated with expensive purchase and maintenance costs. For more than a decade, compact NMR spectrometers have changed this paradigm. It was recently shown that a dedicated analytical workflow combining compact NMR and databases could identify the molecular structure of NPS, in spite of the lower spectral dispersion and sensitivity of compact spectrometers. This approach relies on 1H-13C HSQC to both recognize NPS and elucidate the structure of unknown substances. Still, its performance is limited by the need to compromise between resolution and experiment time. Here, we show that this strategy can be significantly improved by implementing non-uniform sampling (NUS) to improve spectral resolution in the 13C dimension of HSQC at no cost in terms of experiment time. Gains in the range of 3 to 4 in resolution are achieved for pure NPS and for a mixture. Finally, 2D HSQC with NUS was applied to improve the identification of NPS with the assistance of databases. The resulting method appears as a useful tool for the characterization of NPS in mixtures, which is essential for forensic laboratories.

Retrospectively gated ultrashort-echo-time MRI T1 mapping reveals compromised pulmonary microvascular NO-dependent function in a murine model of acute lung injury

This study sought to develop noninvasive, in vivo imaging schemes that allow for quantitative assessment of pulmonary microvascular functional status based on the combination of pulmonary T1 mapping and dynamic contrast-enhanced (DynCE) imaging. Ultrashort-echo-time (UTE) imaging at 9.4 T of lung parenchyma was performed. Retrospective gating was based on modulation of the first point in each recorded spoke. T1 maps were obtained using a series of five consecutive images with varying RF angles and analyzed with the variable flip angle approach. The obtained mean T1 lung value of 1078 ± 38 ms correlated well with previous reports. Improved intersession variability was observed, as evident from a decreased standard deviation of motion-resolved T1 mapping (F-test = 0.051). Animals received lipopolysaccharide (LPS) and were imaged at t = 2, 6, and 12 h after administration. The nitric oxide (NO)-dependent function was assessed according to changes in lung T1 after L-NAME injection, while microvascular perfusion and oxidant stress were assessed with contrast-enhanced imaging after injection of gadolinium or 3-carbamoyl-proxyl nitroxide radical, respectively. Retrospectivel gated UTE allowed robust, motion-compensated imaging that could be used for T1 mapping of lung parenchyma. Changes in lung T1 after L-NAME injection indicated that LPS induced overproduction of NO at t = 2 and 6 h after LPS, but NO-dependent microvascular function was impaired at t = 12 h after LPS. DynCE imaging at t = 6 h after LPS injection revealed decreased microvascular perfusion, with increased vascular permeability and oxidant stress. MRI allows to visualize and quantify lung microvascular NO-dependent function and its concomitant impairment during acute respiratory distress syndrome development with high sensitivity. UTE T1 mapping appears to be sensitive and useful in probing pulmonary microvascular functional status.

Determination of self-diffusion coefficients in mixtures with benchtop 13C NMR spectroscopy via polarization transfer

Nuclear magnetic resonance (NMR) is an established method to determine self-diffusion coefficients in liquids with high precision. The development of benchtop NMR spectrometers makes the method accessible to a wider community. In most cases, 1H NMR spectroscopy is used to determine self-diffusion coefficients due to its high sensitivity. However, especially when using benchtop NMR spectrometers for the investigation of complex mixtures, the signals in 1H NMR spectra can overlap, hindering the precise determination of self-diffusion coefficients. In 13C NMR spectroscopy, the signals of different compounds are generally well resolved. However, the sensitivity of 13C NMR is significantly lower than that of 1H NMR spectroscopy leading to very long measurement times, which makes diffusion coefficient measurements based on 13C NMR practically infeasible with benchtop NMR spectrometers. To circumvent this problem, we have combined two known pulse sequences, one for polarization transfer from 1H to the 13C nuclei (PENDANT) and one for the measurement of diffusion coefficients (PFG). The new method (PENPFG) was used to measure the self-diffusion coefficients of three pure solvents (acetonitrile, ethanol and 1-propanol) as well as in all their binary mixtures and the ternary mixture at various compositions. For comparison, also measurements of the same systems were carried out with a standard PFG-NMR routine on a high-field NMR instrument. The results are in good agreement and show that PENPFG is a useful tool for the measurement of the absolute value of the self-diffusion coefficients in complex liquid mixtures with benchtop NMR spectrometers.

Noninvasive Magnetic Resonance Imaging Measures of Glymphatic System Activity

The comprehension of the glymphatic system, a postulated mechanism responsible for the removal of interstitial solutes within the central nervous system (CNS), has witnessed substantial progress recently. While direct measurement techniques involving fluorescence and contrast agent tracers have demonstrated success in animal studies, their application in humans is invasive and presents challenges. Hence, exploring alternative noninvasive approaches that enable glymphatic research in humans is imperative. This review primarily focuses on several noninvasive magnetic resonance imaging (MRI) techniques, encompassing perivascular space (PVS) imaging, diffusion tensor image analysis along the PVS, arterial spin labeling, chemical exchange saturation transfer, and intravoxel incoherent motion. These methodologies provide valuable insights into the dynamics of interstitial fluid, water permeability across the blood-brain barrier, and cerebrospinal fluid flow within the cerebral parenchyma. Furthermore, the review elucidates the underlying concept and clinical applications of these noninvasive MRI techniques, highlighting their strengths and limitations. It addresses concerns about the relationship between glymphatic system activity and pathological alterations, emphasizing the necessity for further studies to establish correlations between noninvasive MRI measurements and pathological findings. Additionally, the challenges associated with conducting multisite studies, such as variability in MRI systems and acquisition parameters, are addressed, with a suggestion for the use of harmonization methods, such as the combined association test (COMBAT), to enhance standardization and statistical power. Current research gaps and future directions in noninvasive MRI techniques for assessing the glymphatic system are discussed, emphasizing the need for larger sample sizes, harmonization studies, and combined approaches. In conclusion, this review provides invaluable insights into the application of noninvasive MRI methods for monitoring glymphatic system activity in the CNS. It highlights their potential in advancing our understanding of the glymphatic system, facilitating clinical applications, and paving the way for future research endeavors in this field. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 5.

Myotubularin-related-protein-7 inhibits mutant (G12V) K-RAS by direct interaction

Inhibition of K-RAS effectors like B-RAF or MEK1/2 is accompanied by treatment resistance in cancer patients via re-activation of PI3K and Wnt signaling. We hypothesized that myotubularin-related-protein-7 (MTMR7), which inhibits PI3K and ERK1/2 signaling downstream of RAS, directly targets RAS and thereby prevents resistance. Using cell and structural biology combined with animal studies, we show that MTMR7 binds and inhibits RAS at cellular membranes. Overexpression of MTMR7 reduced RAS GTPase activities and protein levels, ERK1/2 phosphorylation, c-FOS transcription and cancer cell proliferation in vitro. We located the RAS-inhibitory activity of MTMR7 to its charged coiled coil (CC) region and demonstrate direct interaction with the gastrointestinal cancer-relevant K-RASG12V mutant, favouring its GDP-bound state. In mouse models of gastric and intestinal cancer, a cell-permeable MTMR7-CC mimicry peptide decreased tumour growth, Ki67 proliferation index and ERK1/2 nuclear positivity. Thus, MTMR7 mimicry peptide(s) could provide a novel strategy for targeting mutant K-RAS in cancers.

Direct Measurement of 8OG Syn-Anti Flips in Mutagenic 8OG·A and Long-Range Damage-Dependent Hoogsteen Breathing Dynamics Using 1H CEST NMR

Elucidating how damage impacts DNA dynamics is essential for understanding the mechanisms of damage recognition and repair. Many DNA lesions alter their propensities to form low-populated and short-lived conformational states. However, NMR methods to measure these dynamics require isotopic enrichment, which is difficult for damaged nucleotides. Here, we demonstrate the utility of the 1H chemical exchange saturation transfer (CEST) NMR experiment in measuring the dynamics of oxidatively damaged 8-oxoguanine (8OG) in the mutagenic 8OGsyn·Aanti mismatch. Using 8OG-H7 as an NMR probe of the damaged base, we directly measured 8OG syn-anti flips to form a lowly populated (pop. ∼ 5%) and short-lived (lifetime ∼50 ms) nonmutagenic 8OGanti·Aanti. These exchange parameters were in quantitative agreement with values from 13C off-resonance R1ρ and CEST on the labeled partner adenine. The Watson-Crick-like 8OGsyn·Aanti mismatch also rescued the kinetics of Hoogsteen motions at distant A-T base pairs, which the G·A mismatch had slowed down. The results lend further support for 8OGanti·Aanti as a minor conformational state of 8OG·A, reveal that 8OG damage can impact Hoogsteen dynamics at a distance, and demonstrate the utility of 1H CEST for measuring damage-dependent dynamics in unlabeled DNA.

In-Cell 19F NMR of Proteins: Recent Progress and Future Opportunities

In vitro, 19F NMR methodology is preferably selected as a complementary and straightforward method for unveiling the conformations, dynamics, and interactions of biological molecules. Its effectiveness in vivo has seen continuous improvement, addressing challenges faced by conventional heteronuclear NMR experiments on structured proteins, such as severe line broadening, low signal-to-noise ratio, and background signals. Herein, we summarize the distinctive advantages of 19F NMR, along with recent progress in sample preparation and applications within the realm of in-cell NMR. Additionally, we offer insights into the future directions and prospects of this methodology based on our understanding.

Evolution of a Combined UV/Vis and NMR Setup with Fixed Pathlengths for Mass-limited Samples

The investigation of reaction mechanisms is a complex task that usually requires the use of several techniques. To obtain as much information as possible on the reaction and any intermediates - possibly invisible to one technique - the combination of techniques is a solution. In this work we present a new setup for combined UV/Vis and NMR spectroscopy and compare it to an established alternative. The presented approach allows a versatile usage of different commercially-available components like mirrors and fiber bundles as well as different fixed pathlengths according to double transmission or single transmission measurements. While a previous approach is based on a dip-probe setup for conventional NMR probes, the new one is based on a micro-Helmholtz coil array (LiquidVoxel™). This makes the use of rectangular cuvettes possible, which ensure well-defined pathlengths allowing for quantification of species. Additionally, very low quantities of compound can be analyzed due to the microfabrication and small cuvette size used. As proof-of-principle this new setup for combined UV/Vis and NMR spectroscopy is used to examine a well-studied photochromic system of the dithienylethene compound class. A thorough comparison of the pros and cons of the two setups for combined UV/Vis and NMR measurements is performed.

Characterizing Prion-Like Protein Aggregation: Emerging Nanopore-Based Approaches

Prion-like protein aggregation is characteristic of numerous neurodegenerative diseases, such as Alzheimer's and Parkinson's diseases. This process involves the formation of aggregates ranging from small and potentially neurotoxic oligomers to highly structured self-propagating amyloid fibrils. Various approaches are used to study protein aggregation, but they do not always provide continuous information on the polymorphic, transient, and heterogeneous species formed. This review provides an updated state-of-the-art approach to the detection and characterization of a wide range of protein aggregates using nanopore technology. For each type of nanopore, biological, solid-state polymer, and nanopipette, discuss the main achievements for the detection of protein aggregates as well as the significant contributions to the understanding of protein aggregation and diagnostics.

Range and sensitivity of 17O nuclear spin-lattice relaxation as a probe of aqueous electrolyte dynamics

The study of electrolytic solutions is of relevance in many research fields, ranging from biophysics, materials, and colloid science to catalysis and electrochemistry. The dependence of solution dynamics on the nature of electrolytes and their concentrations has been the subject of many experimental and computational studies, yet it remains challenging to obtain a full understanding of the factors that govern solution behavior. Here, we provide additional insights into the behavior of aqueous solutions of alkali chlorides by combining 17O relaxation data with diffusion and viscosity data and contrast their behavior with 1H nuclear magnetic resonance relaxation data. The main findings are that 17O relaxation correlates well with viscosity data but not with diffusion data, while 1H relaxation correlates with neither. Certain ionic trends match known ion-specific series behavior, especially at high concentrations. Notably, we also examine the ranges of the interactions and conclude that the majority of the effects are tied to local water reorientation dynamics.

Solution NMR chemical shift assignment of apo and molybdate-bound ModA at two pHs

ModA is a soluble periplasmic molybdate-binding protein found in most gram-negative bacteria. It is part of the ABC transporter complex ModABC that moves molybdenum into the cytoplasm, to be used by enzymes that carry out various redox reactions. Since there is no clear analog for ModA in humans, this protein could be a good target for antibacterial drug design. Backbone 1H, 13C and 15N chemical shifts of apo and molybdate-bound ModA from E. coli were assigned at pHs 6.0 and 4.5. In addition, side chain atoms were assigned for apo ModA at pH 6.0. When comparing apo and molybdate-bound ModA at pH 6.0, large chemical shift perturbations are observed, not only in areas near the bound metal, but also in regions that are distant from the metal-binding site. Given the significant conformational change between apo and holo ModA, we might expect the large chemical shift changes to be more widespread; however, since they are limited to specific regions, the residues with large perturbations may reveal allosteric sites that could ultimately be important for the design of antibiotics that target ModA.

Elucidating Structural Configuration of Lipid Assemblies for mRNA Delivery Systems

The development of mRNA delivery systems utilizing lipid-based assemblies holds immense potential for precise control of gene expression and targeted therapeutic interventions. Despite advancements in lipid-based gene delivery systems, a critical knowledge gap remains in understanding how the biophysical characteristics of lipid assemblies and mRNA complexes influence these systems. Herein, we investigate the biophysical properties of cationic liposomes and their role in shaping mRNA lipoplexes by comparing various fabrication methods. Notably, an innovative fabrication technique called the liposome under cryo-assembly (LUCA) cycle, involving a precisely controlled freeze-thaw-vortex process, produces distinctive onion-like concentric multilamellar structures in cationic DOTAP/DOPE liposomes, in contrast to a conventional extrusion method that yields unilamellar liposomes. The inclusion of short-chain DHPC lipids further modulates the structure of cationic liposomes, transforming them from multilamellar to unilamellar structures during the LUCA cycle. Furthermore, the biophysical and biological evaluations of mRNA lipoplexes unveil that the optimal N/P charge ratio in the lipoplex can vary depending on the structure of initial cationic liposomes. Cryo-EM structural analysis demonstrates that multilamellar cationic liposomes induce two distinct interlamellar spacings in cationic lipoplexes, emphasizing the significant impact of the liposome structures on the final structure of mRNA lipoplexes. Taken together, our results provide an intriguing insight into the relationship between lipid assembly structures and the biophysical characteristics of the resulting lipoplexes. These relationships may open the door for advancing lipid-based mRNA delivery systems through more streamlined manufacturing processes.

Multiparametric MRI for characterization of the tumour microenvironment

Our understanding of tumour biology has evolved over the past decades and cancer is now viewed as a complex ecosystem with interactions between various cellular and non-cellular components within the tumour microenvironment (TME) at multiple scales. However, morphological imaging remains the mainstay of tumour staging and assessment of response to therapy, and the characterization of the TME with non-invasive imaging has not yet entered routine clinical practice. By combining multiple MRI sequences, each providing different but complementary information about the TME, multiparametric MRI (mpMRI) enables non-invasive assessment of molecular and cellular features within the TME, including their spatial and temporal heterogeneity. With an increasing number of advanced MRI techniques bridging the gap between preclinical and clinical applications, mpMRI could ultimately guide the selection of treatment approaches, precisely tailored to each individual patient, tumour and therapeutic modality. In this Review, we describe the evolving role of mpMRI in the non-invasive characterization of the TME, outline its applications for cancer detection, staging and assessment of response to therapy, and discuss considerations and challenges for its use in future medical applications, including personalized integrated diagnostics.

Do Electrostatics Control the Diffusive Dynamics of Solitary Water? NMR and MD Studies of Water Translation and Rotation in Dipolar and Ionic Solvents

NMR-based measurements of the diffusion coefficients and rotation times of solitary water and benzene at 300 K are reported in a diverse collection of 13 conventional organic solvents and 10 imidazolium ionic liquids. Proton chemical shifts of water are found to be correlated to water OH-stretching frequencies, confirming the importance of electrostatic interactions in these shifts. However, the influence of magnetic interactions in aromatic solvents renders chemical shifts a less reliable indicator of electrostatics. Diffusion coefficients (DB) and rotational correlation times (τB) of benzene in the solvents examined are accurately described as functions of viscosity (η) by DB ∝ η-0.81 and τB ∝ η0.64. Literature values of DB and τB in alkane and normal alcohols, which were not included among the solvents studied here, are systematically faster than predicted by these correlations, indicating that factors beyond solvent viscosity play a role in determining the friction on benzene. In contrast to benzene, water diffusion and rotation are poorly described in terms of viscosity alone, even in the dipolar and ionic solvents measured here. The present data and the substantial literature data already available on dilute water diffusion show a systematic dependence of DW on solvent polarity among isoviscous solvents. The aspect of solvent polarity most relevant to water dynamics is the ability of a solvent to accept hydrogen bonds from water, as conveniently quantified by the frequency of water's OH stretching band, ΔνOH. The friction on translation, ζtr = kBT/DW, and rotation, ζrot = kBTτW, are both well correlated by functions of the form ζ(η, ΔνOH) = a1ηa2 exp (a3ΔνOH), where the ai are adjustable parameters. Molecular dynamics simulations reveal a strong coupling between electrostatic and nonelectrostatic water-solvent interactions, which makes it impossible to dissect the friction on water into additive dielectric and hydrodynamic components. Simulations also provide a tentative explanation for the unusual form of the correlating function ζ(η, ΔνOH), at least in the case of ζrot.

17O Solid-State NMR Spectroscopy of Lipid Membranes

Despite the limitations posed by poor sensitivity, studies have reported the unique advantages of 17O based NMR spectroscopy to study systems existing in liquid, solid, or semisolid states. 17O NMR studies have exploited the remarkable sensitivity of quadrupole coupling and chemical shift anisotropy tensors to the local environment in the characterization of a variety of intra- and intermolecular interactions and motion. Recent studies have considerably expanded the use of 17O NMR to study dynamic intermolecular interactions associated with some of the challenging biological systems under magic angle spinning (MAS) and aligned conditions. The very fast relaxing nature of 17O has been well utilized in cellular and in vivo MRS (magnetic resonance spectroscopy) and MRI (magnetic resonance imaging) applications. The main focus of this Review is to highlight the new developments in the biological solids with a detailed discussion for a few selected examples including membrane proteins and nanodiscs. In addition to the unique benefits and limitations, the remaining challenges to overcome, and the impacts of higher magnetic fields and sensitivity enhancement techniques are discussed.

A new preparation method of covalent annular nanodiscs based on MTGase

The preservation of the native conformation and functionality of membrane proteins has posed considerable challenges. While detergents and liposome reconstitution have been traditional approaches, nanodiscs (NDs) offer a promising solution by embedding membrane proteins in phospholipids encircled by an amphipathic helical protein MSP belt. Nevertheless, a drawback of commonly used NDs is their limited homogeneity and stability. In this study, we present a novel approach to construct covalent annular nanodiscs (cNDs) by leveraging microbial transglutaminase (MTGase) to catalyze isopeptide bond formation between the side chains of terminal amino acids, specifically Lysine (K) and Glutamine (Q). This methodology significantly enhances the homogeneity and stability of NDs. Characterization of cNDs and the assembly of membrane proteins within them validate the successful reconstitution of membrane proteins with improved homogeneity and stability. Our findings suggest that cNDs represent a more suitable tool for investigating interactions between membrane proteins and lipids, as well as for analyzing membrane protein structures.

Spatiotemporal encoding MRI in a portable low-field system

PURPOSE

Demonstrate the potential of spatiotemporal encoding (SPEN) MRI to deliver largely undistorted 2D, 3D, and diffusion weighted images on a 110 mT portable system.

METHODS

SPEN's quadratic phase modulation was used to subsample the low-bandwidth dimension of echo planar acquisitions, delivering alias-free images with an enhanced immunity to image distortions in a laboratory-built, low-field, portable MRI system lacking multiple receivers.

RESULTS

Healthy brain images with different SPEN time-bandwidth products and subsampling factors were collected. These compared favorably to EPI acquisitions including topup corrections. Robust 3D and diffusion weighted SPEN images of diagnostic value were demonstrated, with 2.5 mm isotropic resolutions achieved in 3 min scans. This performance took advantage of the low specific absorption rate and relative long TEs associated with low-field MRI.

CONCLUSION

SPEN MRI provides a robust and advantageous fast acquisition approach to obtain faithful 3D images and DWI data in low-cost, portable, low-field systems without parallel acceleration.

Efficient Access to Elusive 1D 13C NMR Spectra through Highly Resolved 1H, 13C-Long-Range Correlation Spectroscopy

A method for obtaining 1D 13C NMR spectra from natural products or metabolites using proton detection is described. The approach delivers singlets for every 13C signal without conducting any broadband 1H decoupling (CPD) and is based on calculating 13C projections from constant-time HMBC and conventional HSQC experiments, recorded at high digital resolution and processed to pure phases. Paramount to the proposed method is the implication of nonuniform sampling and echo processing. The echo processing produces phase-sensitive 2D CT-HMBC spectra with narrow 13C signal line shapes. Two simple HMBC pulse sequences are utilized with the suppression of homo- and heteronuclear couplings. Due to the removal of the 1H multiplet structure in F1 (no tilt at higher digital resolution), 13C singlets arise. An overall increase in 13C signal-to-noise (SINO) for all types of carbon multiplicities is observed, making the proposed technique superior compared to direct 13C excitation. For otherwise difficult-to-measure quaternary carbon atoms, a SINO enhancement of up to 6 and 12 depending on F1 resolution (3 and 6 Hz/point) is reported. Echo/anti-Echo signal detection cleans up the spectrum. Nonuniform sampling (NUS) lays the groundwork to significantly reduce the total acquisition time. Final 1D 13C projections are obtained by combining the 13C projection from CT HMBC and conventional HSQC. This orthogonal concept of combining the 13C projections from different spectra inherently minimizes the risk of missing 13C cross-peaks by inappropriate setting of long-range nJHC coupling delays and the shortcoming of T2 relaxations. The advantages and some limitations of the concept are discussed.

3D cine-magnetic resonance imaging using spatial and temporal implicit neural representation learning (STINR-MR)

Objective. 3D cine-magnetic resonance imaging (cine-MRI) can capture images of the human body volume with high spatial and temporal resolutions to study anatomical dynamics. However, the reconstruction of 3D cine-MRI is challenged by highly under-sampled k-space data in each dynamic (cine) frame, due to the slow speed of MR signal acquisition. We proposed a machine learning-based framework, spatial and temporal implicit neural representation learning (STINR-MR), for accurate 3D cine-MRI reconstruction from highly under-sampled data.Approach. STINR-MR used a joint reconstruction and deformable registration approach to achieve a high acceleration factor for cine volumetric imaging. It addressed the ill-posed spatiotemporal reconstruction problem by solving a reference-frame 3D MR image and a corresponding motion model that deforms the reference frame to each cine frame. The reference-frame 3D MR image was reconstructed as a spatial implicit neural representation (INR) network, which learns the mapping from input 3D spatial coordinates to corresponding MR values. The dynamic motion model was constructed via a temporal INR, as well as basis deformation vector fields (DVFs) extracted from prior/onboard 4D-MRIs using principal component analysis. The learned temporal INR encodes input time points and outputs corresponding weighting factors to combine the basis DVFs into time-resolved motion fields that represent cine-frame-specific dynamics. STINR-MR was evaluated using MR data simulated from the 4D extended cardiac-torso (XCAT) digital phantom, as well as two MR datasets acquired clinically from human subjects. Its reconstruction accuracy was also compared with that of the model-based non-rigid motion estimation method (MR-MOTUS) and a deep learning-based method (TEMPEST).Main results. STINR-MR can reconstruct 3D cine-MR images with high temporal (<100 ms) and spatial (3 mm) resolutions. Compared with MR-MOTUS and TEMPEST, STINR-MR consistently reconstructed images with better image quality and fewer artifacts and achieved superior tumor localization accuracy via the solved dynamic DVFs. For the XCAT study, STINR reconstructed the tumors to a mean ± SD center-of-mass error of 0.9 ± 0.4 mm, compared to 3.4 ± 1.0 mm of the MR-MOTUS method. The high-frame-rate reconstruction capability of STINR-MR allows different irregular motion patterns to be accurately captured.Significance. STINR-MR provides a lightweight and efficient framework for accurate 3D cine-MRI reconstruction. It is a 'one-shot' method that does not require external data for pre-training, allowing it to avoid generalizability issues typically encountered in deep learning-based methods.

Ultra-clean pure shift NMR with optimal water suppression for analysis of aqueous pharmaceutical samples

Pure shift NMR experiments greatly enhance spectral resolution by collapsing multiplet structures into singlets and, with water suppression, can be used for aqueous samples. Here, we combine ultra-clean pure-shift NMR (SAPPHIRE) with two different internally encoded water suppression schemes to achieve optimal performance for small molecule and macrocyclic peptide pharmaceuticals in water and acetonitrile-water mixtures.

Identification of potential serum biomarkers associated with HbA1c levels in Indian type 2 diabetic subjects using NMR-based metabolomics

BACKGROUND

The prevalence of type 2 diabetes mellitus (T2DM), a progressive metabolic disorder characterized by chronic hyperglycemia and the development of insulin resistance, has increased globally, with worrying statistics coming from children, adolescents, and young adults from developing countries like India. Here, we investigated unique circulating metabolic signatures associated with prediabetes and T2DM in an Indian cohort using NMR-based metabolomics.

MATERIALS AND METHODS

The study subjects included healthy volunteers (N = 101), prediabetic subjects (N = 75), and T2DM patients (N = 108). Serum metabolic profiling was performed using 1H NMR spectroscopy and major perturbed metabolites were identified by multivariate analysis and receiver operating characteristic (ROC) modules.

RESULTS

Of the 36 aqueous abundant metabolites, 24 showed a statistically significant difference between healthy volunteers, prediabetics, and established T2DM subjects. On performing multivariate ROC curve analysis with 5 commonly dysregulated metabolites (namely, glucose, pyroglutamate, o-phosphocholine, serine, and methionine) in prediabetes and T2DM, AUC values obtained were 0.96 (95 % confidence interval (CI) = 0.93, 0.98) for T2DM; and 0.88 (95 % CI = 0.81, 0.93) for prediabetic subjects, respectively.

CONCLUSION

We propose that the identified metabolite panel can be used in the future as a biomarker for clinical diagnosis, patient surveillance, and for predicting individuals at risk for developing diabetes.

Delving into theoretical and computational considerations for accurate calculation of chemical shifts in paramagnetic transition metal systems using quantum chemical methods

The chemical shielding tensor for a paramagnetic system has been derived from the macroscopically observed magnetization using the perturbation theory. An approach to calculate the paramagnetic chemical shifts in transition metal systems based on the spin-only magnetic susceptibility directly evaluated from the ab initio Hilbert space of the electronic Zeeman Hamiltonian has been discussed. Computationally, several advantages are associated with this approach: (a) it includes the state-specific paramagnetic Curie (first-order) and Van Vleck (second-order) contributions of the paramagnetic ion to the paramagnetic chemical shifts; (b) thus it avoids the system-specific modeling and evaluating effectively in terms of the electron paramagnetic resonance (EPR) spin Hamiltonian parameters of the magnetic moment of the paramagnetic ion formulated previously; (c) it can be utilized both in the point-dipole (PD) approximation (in the long-range) and with the quantum chemical (QC) method based the hyperfine tensors (in the short-range). Additionally, we have examined the predictive performance of various density functional theory (DFT) functionals of different families and commonly used core-augmented basis sets for nuclear magnetic resonance (NMR) chemical shifts. A selection of transition metal ion complexes with and without first-order orbital contributions, namely the [M(AcPyOx)3(BPh)]+ complexes of M = Mn2+, Ni2+ and Co2+ ions and CoTp2 complex and their reported NMR chemical shifts are studied from QC methods for illustration.

Collective long-lived zero-quantum coherences in aliphatic chains

In nuclear magnetic resonance, long-lived coherences constitute a class of zero-quantum (ZQ) coherences that have lifetimes that can be longer than the relaxation lifetimes T2 of transverse magnetization. So far, such coherences have been observed in systems with two coupled spins with spin quantum numbers I = 1/2, where a term S0T0+T0S0 in the density operator corresponds to a coherent superposition between the singlet S0 and the central triplet T0 state. Here, we report on the excitation and detection of collective long-lived coherences in AA'MM'XX' spin systems in molecules containing a chain of at least three methylene (-CH2-) groups. Several variants of excitation by polychromatic spin-lock induced crossing (poly-SLIC) are introduced that can excite a non-uniform distribution of the amplitudes of terms such as S0S0T0S0S0T0, S0T0S0S0T0S0, and T0S0S0T0S0S0. Once the radio frequency fields are switched off, these are not eigenstates, leading to ZQ precession involving all six protons, a process that can be understood as a propagation of spin order along the chain of CH2 groups before the reconversion into observable magnetization by a second poly-SLIC pulse that can be applied to any one or several of the CH2 groups. In the resulting 2D spectra, the ω2 domain shows SQ spectra with the chemical shifts of the CH2 groups irradiated during the reconversion, while the ω1 dimension shows ZQ signals in absorption mode with linewidths on the order of 0.1 Hz that are not affected by the inhomogeneity of the static magnetic field but can be broadened by chemical exchange as occurs in drug screening. The ZQ frequencies are primarily determined by differences ΔJ between vicinal J-couplings.

Dynamic of binary molecular systems-Advantages and limitations of NMR relaxometry

1H spin-lattice relaxation studies have been performed for binary systems, including glycerol as the first component and alanine, glycine, and aspartic acid (with different levels of deuteration) as the second one. The relaxation studies have been performed in the frequency range from 10 kHz to 10 MHz vs temperature. A theoretical framework, including all relevant 1H-1H and 1H-2H relaxation pathways, has been formulated. The theory has been exploited for a thorough interpretation of a large set of the experimental data. The importance of the 1H-2H relaxation contributions has been discussed, and the possibility of revealing dynamical properties of individual liquid components in binary liquids has been carefully investigated. As far as the dynamical properties of the specific binary liquids, chosen as an example, are considered, it has been shown that in the presence of the second component (alanine, glycine, and aspartic acid), both molecular fractions undergo dynamics similar to that of glycerol in bulk.

Results of the 2023 ISBI challenge to reduce GABA-edited MRS acquisition time

PURPOSE

Use a conference challenge format to compare machine learning-based gamma-aminobutyric acid (GABA)-edited magnetic resonance spectroscopy (MRS) reconstruction models using one-quarter of the transients typically acquired during a complete scan.

METHODS

There were three tracks: Track 1: simulated data, Track 2: identical acquisition parameters with in vivo data, and Track 3: different acquisition parameters with in vivo data. The mean squared error, signal-to-noise ratio, linewidth, and a proposed shape score metric were used to quantify model performance. Challenge organizers provided open access to a baseline model, simulated noise-free data, guides for adding synthetic noise, and in vivo data.

RESULTS

Three submissions were compared. A covariance matrix convolutional neural network model was most successful for Track 1. A vision transformer model operating on a spectrogram data representation was most successful for Tracks 2 and 3. Deep learning (DL) reconstructions with 80 transients achieved equivalent or better SNR, linewidth and fit error compared to conventional 320 transient reconstructions. However, some DL models optimized linewidth and SNR without actually improving overall spectral quality, indicating a need for more robust metrics.

CONCLUSION

DL-based reconstruction pipelines have the promise to reduce the number of transients required for GABA-edited MRS.

Towards a unified picture of polarization transfer - pulsed DNP and chemically equivalent PHIP

Nuclear spin hyperpolarization techniques, such as dynamic nuclear polarization (DNP) and parahydrogen-induced polarization (PHIP), have revolutionized nuclear magnetic resonance and magnetic resonance imaging. In these methods, a readily available source of high spin order, either electron spins in DNP or singlet states in hydrogen for PHIP, is brought into close proximity with nuclear spin targets, enabling efficient transfer of spin order under external quantum control. Despite vast disparities in energy scales and interaction mechanisms between electron spins in DNP and nuclear singlet states in PHIP, a pseudo-spin formalism allows us to establish an intriguing equivalence. As a result, the important low-field polarization transfer regime of PHIP can be mapped onto an analogous system equivalent to pulsed-DNP. This establishes a correspondence between key polarization transfer sequences in PHIP and DNP, facilitating the transfer of sequence development concepts. This promises fresh insights and significant cross-pollination between DNP and PHIP polarization sequence developers.

Systematic Review of Cerebrospinal Fluid Biomarker Discovery in Neuro-Oncology: A Roadmap to Standardization and Clinical Application

Effective diagnosis, prognostication, and management of CNS malignancies traditionally involves invasive brain biopsies that pose significant risk to the patient. Sampling and molecular profiling of cerebrospinal fluid (CSF) is a safer, rapid, and noninvasive alternative that offers a snapshot of the intracranial milieu while overcoming the challenge of sampling error that plagues conventional brain biopsy. Although numerous biomarkers have been identified, translational challenges remain, and standardization of protocols is necessary. Here, we systematically reviewed 141 studies (Medline, SCOPUS, and Biosis databases; between January 2000 and September 29, 2022) that molecularly profiled CSF from adults with brain malignancies including glioma, brain metastasis, and primary and secondary CNS lymphomas. We provide an overview of promising CSF biomarkers, propose CSF reporting guidelines, and discuss the various considerations that go into biomarker discovery, including the influence of blood-brain barrier disruption, cell of origin, and site of CSF acquisition (eg, lumbar and ventricular). We also performed a meta-analysis of proteomic data sets, identifying biomarkers in CNS malignancies and establishing a resource for the research community.

Comparison of the Backbone Dynamics of Dehaloperoxidase-Hemoglobin Isoenzymes

Dehaloperoxidase (DHP) is a multifunctional hemeprotein with a functional switch generally regulated by the chemical class of the substrate. Its two isoforms, DHP-A and DHP-B, differ by only five amino acids and have an almost identical protein fold. However, the catalytic efficiency of DHP-B for oxidation by a peroxidase mechanism ranges from 2- to 6-fold greater than that of DHP-A depending on the conditions. X-ray crystallography has shown that many substrates and ligands have nearly identical binding in the two isoenzymes, suggesting that the difference in catalytic efficiency could be due to differences in the conformational dynamics. We compared the backbone dynamics of the DHP isoenzymes at pH 7 through heteronuclear relaxation dynamics at 11.75, 16.45, and 19.97 T in combination with four 300 ns MD simulations. While the overall dynamics of the isoenzymes are similar, there are specific local differences in functional regions of each protein. In DHP-A, Phe35 undergoes a slow chemical exchange between two conformational states likely coupled to a swinging motion of Tyr34. Moreover, Asn37 undergoes fast chemical exchange in DHP-A. Given that Phe35 and Asn37 are adjacent to Tyr34 and Tyr38, it is possible that their dynamics modulate the formation and migration of the active tyrosyl radicals in DHP-A at pH 7. Another significant difference is that both distal and proximal histidines have a 15-18% smaller S2 value in DHP-B, thus their greater flexibility could account for the higher catalytic activity. The distal histidine grants substrate access to the distal pocket. The greater flexibility of the proximal histidine could also accelerate H2O2 activation at the heme Fe by increased coupling of an amino acid charge relay to stabilize the ferryl Fe(IV) oxidation state in a Poulos-Kraut "push-pull"-type peroxidase mechanism.

Fuzzy recognition by the prokaryotic transcription factor HigA2 from Vibrio cholerae

Disordered protein sequences can exhibit different binding modes, ranging from well-ordered folding-upon-binding to highly dynamic fuzzy binding. The primary function of the intrinsically disordered region of the antitoxin HigA2 from Vibrio cholerae is to neutralize HigB2 toxin through ultra-high-affinity folding-upon-binding interaction. Here, we show that the same intrinsically disordered region can also mediate fuzzy interactions with its operator DNA and, through interplay with the folded helix-turn-helix domain, regulates transcription from the higBA2 operon. NMR, SAXS, ITC and in vivo experiments converge towards a consistent picture where a specific set of residues in the intrinsically disordered region mediate electrostatic and hydrophobic interactions while "hovering" over the DNA operator. Sensitivity of the intrinsically disordered region to scrambling the sequence, position-specific contacts and absence of redundant, multivalent interactions, point towards a more specific type of fuzzy binding. Our work demonstrates how a bacterial regulator achieves dual functionality by utilizing two distinct interaction modes within the same disordered sequence.

Speciation of Lanthanide Metal Ion Dopants in Microcrystalline All-Inorganic Halide Perovskite CsPbCl3

Lanthanides are versatile modulators of optoelectronic properties owing to their narrow optical emission spectra across the visible and near-infrared range. Their use in metal halide perovskites (MHPs) has recently gained prominence, although their fate in these materials has not yet been established at the atomic level. We use cesium-133 solid-state NMR to establish the speciation of all nonradioactive lanthanide ions (La3+, Ce3+, Pr3+, Nd3+, Sm3+, Sm2+, Eu3+, Eu2+, Gd3+, Tb3+, Dy3+, Ho3+, Er3+, Tm3+, Yb3+, Lu3+) in microcrystalline CsPbCl3. Our results show that all lanthanides incorporate into the perovskite structure of CsPbCl3 regardless of their oxidation state (+2, +3).

Can Adipokine FAM19A5 Be a Biomarker of Metabolic Disorders?

Aim

One of the most critical functions of adipose tissue is the production of adipokines, ie, numerous active substances that regulate metabolism. One is the newly discovered FAM19A5, whose older name is TAFA-5.

Purpose

The study aimed to review the literature on the FAM19A5 protein.

Methods

The review was conducted in December 2023 using the PubMed (Medline) search engine. Sixty-four papers were included in the review.

Results

This protein exhibits the characteristics of an adipokine with positive features for maintaining homeostasis. The results showed that FAM19A5 was highly expressed in adipose tissue, with mild to moderate expression in the brain and ovary. FAM19A5 may also inhibit vascular smooth muscle cell proliferation and migration through the perivascular adipose tissue paracrine pathway. Serum levels of FAM19A5 were decreased in obese children compared with healthy controls. There are negative correlations between FAM19A5, body mass index, and fasting insulin. Serum FAM19A5 level is correlated with type 2 diabetes, waist circumference, waist-to-hip ratio, glutamic pyruvic transferase, fasting plasma glucose, HbA1c, and mean shoulder pulse wave velocity. FAM19A5 expression was reduced in mice with obesity. However, the data available needs to be clarified or contradictory.

Conclusion

Considering today's knowledge about FAM19A5, we cannot consider this protein as a biomarker of the metabolic syndrome. According to current knowledge, FAM19A5 cannot be considered a marker of metabolic disorders because the results of studies conducted in this area are unclear.

Formerly degenerate seventh zinc finger domain from transcription factor ZNF711 rehabilitated by experimental NMR structure

Domain Z7 of nuclear transcription factor ZNF711 has the consensus last metal-ligand H23 found in odd-numbered zinc-fingers of this protein replaced by a phenylalanine. Ever since the discovery of ZNF711 it has been thought that Z7 is probably non-functional because of the H23F substitution. The presence of H26 three positions downstream prompted us to examine if this histidine could substitute as the last metal ligand. The Z7 domain adopts a stable tertiary structure upon metal binding. The NMR structure of Zn 2+ -bound Z7 shows the classical ββα-fold of CCHH zinc fingers. Mutagenesis and pH titration experiments indicate that H26 is not involved in metal binding and that Z7 has a tridentate metal-binding site comprised of only residues C3, C6, and H19. By contrast, an F23H mutation that introduces a histidine in the consensus position forms a tetradentate ligand. The structure of the WT Z7 is stable causing restricted ring-flipping of phenyalanines 10 and 23. Dynamics are increased with either the H26A or F23H substitutions and aromatic ring rotation is no longer hindered in the two mutants. The mutations have only small effects on the K d values for Zn 2+ and Co 2+ and retain the high thermal stability of the WT domain above 80 °C. Like two previously reported designed zinc fingers with the last ligand replaced by water, the WT Z7 domain is catalytically active, hydrolyzing 4-nitophenyl acetate. We discuss the implications of naturally occurring tridentate zinc fingers for cancer mutations and drug targeting of notoriously undruggable transcription factors. Our findings that Z7 can fold with only a subset of three metal ligands suggests the recent view that most everything about protein structure can be predicted through homology modeling might be premature for at least the resilient and versatile zinc-finger motif.

Initial Primer Synthesis of a DNA Primase Monitored by Real-Time NMR Spectroscopy

Primases are crucial enzymes for DNA replication, as they synthesize a short primer required for initiating DNA replication. We herein present time-resolved nuclear magnetic resonance (NMR) spectroscopy in solution and in the solid state to study the initial dinucleotide formation reaction of archaeal pRN1 primase. Our findings show that the helix-bundle domain (HBD) of pRN1 primase prepares the two substrates and then hands them over to the catalytic domain to initiate the reaction. By using nucleotide triphosphate analogues, the reaction is substantially slowed down, allowing us to study the initial dinucleotide formation in real time. We show that the sedimented protein-DNA complex remains active in the solid-state NMR rotor and that time-resolved 31P-detected cross-polarization experiments allow monitoring the kinetics of dinucleotide formation. The kinetics in the sedimented protein sample are comparable to those determined by solution-state NMR. Protein conformational changes during primer synthesis are observed in time-resolved 1H-detected experiments at fast magic-angle spinning frequencies (100 kHz). A significant number of spectral changes cluster in the HBD pointing to the importance of the HBD for positioning the nucleotides and the dinucleotide.

Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments

Investigating protein-protein interactions is crucial for understanding cellular biological processes because proteins often function within molecular complexes rather than in isolation. While experimental and computational methods have provided valuable insights into these interactions, they often overlook a critical factor: the crowded cellular environment. This environment significantly impacts protein behavior, including structural stability, diffusion, and ultimately the nature of binding. In this review, we discuss theoretical and computational approaches that allow the modeling of biological systems to guide and complement experiments and can thus significantly advance the investigation, and possibly the predictions, of protein-protein interactions in the crowded environment of cell cytoplasm. We explore topics such as statistical mechanics for lattice simulations, hydrodynamic interactions, diffusion processes in high-viscosity environments, and several methods based on molecular dynamics simulations. By synergistically leveraging methods from biophysics and computational biology, we review the state of the art of computational methods to study the impact of molecular crowding on protein-protein interactions and discuss its potential revolutionizing effects on the characterization of the human interactome.

Understanding Sorption of Aqueous Electrolytes in Porous Carbon by NMR Spectroscopy

Ion adsorption at solid-water interfaces is crucial for many electrochemical processes involving aqueous electrolytes including energy storage, electrochemical separations, and electrocatalysis. However, the impact of the hydronium (H3O+) and hydroxide (OH-) ions on the ion adsorption and surface charge distributions remains poorly understood. Many fundamental studies of supercapacitors focus on non-aqueous electrolytes to avoid addressing the role of functional groups and electrolyte pH in altering ion uptake. Achieving microscopic level characterization of interfacial mixed ion adsorption is particularly challenging due to the complex ion dynamics, disordered structures, and hierarchical porosity of the carbon electrodes. This work addresses these challenges starting with pH measurements to quantify the adsorbed H3O+ concentrations, which reveal the basic nature of the activated carbon YP-50F commonly used in supercapacitors. Solid-state NMR spectroscopy is used to study the uptake of lithium bis(trifluoromethanesulfonyl)-imide (LiTFSI) aqueous electrolyte in the YP-50F carbon across the full pH range. The NMR data analysis highlights the importance of including the fast ion-exchange processes for accurate quantification of the adsorbed ions. Under acidic conditions, more TFSI- ions are adsorbed in the carbon pores than Li+ ions, with charge compensation also occurring via H3O+ adsorption. Under neutral and basic conditions, when the carbon's surface charge is close to zero, the Li+ and TFSI- ions exhibit similar but lower affinities toward the carbon pores. Our experimental approach and evidence of H3O+ uptake in pores provide a methodology to relate the local structure to the function and performance in a wide range of materials for energy applications and beyond.

Unravelling the structure of CO2 in silica adsorbents: an NMR and computational perspective

This comprehensive review describes recent advancements in the use of solid-state NMR-assisted methods and computational modeling strategies to unravel gas adsorption mechanisms and CO2 speciation in porous CO2-adsorbent silica materials at the atomic scale. This work provides new perspectives for the innovative modifications of these materials rendering them more amenable to the use of advanced NMR methods.

Recommendations for quantitative cerebral perfusion MRI using multi-timepoint arterial spin labeling: Acquisition, quantification, and clinical applications

Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision-making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi-timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post-labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi-timepoint data can be acquired in the same scan time as single-PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single-PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi-timepoint ASL and provides robust recommendations for acquiring high-quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi-timepoint ASL data. Furthermore, we review the potential clinical applications where multi-timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article.

Dual-space high-frequency learning for transformer-based MRI super-resolution

BACKGROUND AND OBJECTIVE

Magnetic resonance imaging (MRI) can provide rich and detailed high-contrast information of soft tissues, while the scanning of MRI is time-consuming. To accelerate MR imaging, a variety of Transformer-based single image super-resolution methods are proposed in recent years, achieving promising results thanks to their superior capability of capturing long-range dependencies. Nevertheless, most existing works prioritize the design of transformer attention blocks to capture global information. The local high-frequency details, which are pivotal to faithful MRI restoration, are unfortunately neglected.

METHODS

In this work, we propose a high-frequency enhanced learning scheme to effectively improve the awareness of high frequency information in current Transformer-based MRI single image super-resolution methods. Specifically, we present two entirely plug-and-play modules designed to equip Transformer-based networks with the ability to recover high-frequency details from dual spaces: 1) in the feature space, we design a high-frequency block (Hi-Fe block) paralleled with Transformer-based attention layers to extract rich high-frequency features; while 2) in the image intensity space, we tailor a high-frequency amplification module (HFA) to further refine the high-frequency details. By fully exploiting the merits of the two modules, our framework can recover abundant and diverse high-frequency information, rendering faithful MRI super-resolved results with fine details.

RESULTS

We integrated our modules with six Transformer-based models and conducted experiments across three datasets. The results indicate that our plug-and-play modules can enhance the super-resolution performance of all foundational models to varying degrees, surpassing the capabilities of existing state-of-the-art single image super-resolution networks.

CONCLUSION

Comprehensive comparison of super-resolution images and high-frequency maps from various methods, clearly demonstrating that our module possesses the capability to restore high-frequency information, showing huge potential in clinical practice for accelerated MRI reconstruction.