Magnetic Resonance Spectroscopy Research Articles

Structural Characterization of APSN from Astragalus membranaceus and Its Potential Therapeutic Effect on Immune Dysregulation and Tissue Damage.

Addressing the global health impact of inflammatory and immune-mediated diseases, this study focused on purifying and characterizing a neutral polysaccharide, APSN, from the Astragalus membranaceus. Employing high-performance gel permeation chromatography (HPGPC), Fourier-transform infrared spectroscopy (FTIR), and nuclear magnetic resonance (NMR) spectroscopy, we elucidated APSN's structural features, revealing a highly branched glucan with a 1,4-α-d-glucopyranosyl main chain and side chains at the O-6 position. Separately, we assessed APSN's biological activity, finding that it significantly modulates immune responses by inhibiting the NF-κB pathway in RAW264.7 macrophages and promotes endothelial cell proliferation and angiogenesis-related gene expression in HUVECs. These results position APSN as a potential therapeutic for diseases characterized by immune dysregulation and tissue damage, warranting further investigation of its mechanisms and clinical efficacy.

Dual-catalyst effect on the molecular weight enhancement of polyfurfuryl alcohol resin and stability

This study advances furan chemistry by synthesising high-molecular-weight polyfurfuryl alcohol (PFA) resin (Mw = 118,959 g/mol) from furfuryl alcohol (FA) using a co-catalytic system, compared to conventional single-catalytic methods. Unlike traditional single-catalyst approaches, our method significantly increases the molecular weight of the resulting PFA, as confirmed by gel permeation chromatography (GPC), which shows a molecular weight increase of up to 60%. The dual-catalyst system also enhances the thermal stability of the resin, with thermogravimetric analysis (TGA) revealing a higher decomposition temperature (over 100 °C) compared to PFA synthesised using a single catalyst. Fourier-transform infrared (FTIR) and nuclear magnetic resonance (NMR) spectroscopy further corroborate the structural integrity and successful polymerisation of furfuryl alcohol under these conditions. The co-catalytic approach uses acetic acid as the catalytic precursor and hydrochloric acid (HCl) as the primary catalyst, allowing controlled polymerisation and achieving higher molecular weight while maintaining processability. Comprehensive characterisation reveals that the resulting PFA resin has a highly irregular chain structure with increased chain packing, enhancing its properties. The synthesised PFA shows excellent shelf life, remaining stable for over six months without forming a hard, insoluble solid when stored at room temperature. The higher molecular weight significantly improves the PFA resin’s mechanical properties, thermal stability, and chemical resistance, making it suitable for standalone moulded materials, composites, coatings, adhesives, and nanostructured carbons. The co-catalytic system elevates molecular weight and simplifies the synthesis process, making it more practical and reproducible. By leveraging furans' unique properties, this study opens new avenues for developing polymeric systems with superior attributes, contributing to sustainability and defossilisation in material science.

Pre-Diagnostic Plasma Metabolites are Associated with Incident Hepatocellular Carcinoma: A Prospective Analysis.

Despite increasing incidence of hepatocellular carcinoma (HCC) in vulnerable populations, accurate early detection tools are lacking. We aimed to investigate the associations between pre-diagnostic plasma metabolites and incident HCC in a diverse population. In a prospective, nested case-control study within the Southern Community Cohort Study (SCCS), we conducted pre-diagnostic liquid chromatography-mass spectrometry metabolomics profiling in 150 incident HCC cases (median time to diagnosis 7.9 years) and 100 controls with cirrhosis. Logistic regression assessed metabolite associations with HCC risk. Metabolite set enrichment analysis identified enriched pathways, and random forest classifier was used for risk classification models. Candidate metabolites were validated in the UK Biobank (N=12 incident HCC cases and 24 cirrhosis controls). In logistic regression analysis, seven metabolites were associated with incident HCC (Meff p<0.0004), including N-acetylmethionine (OR=0.46, 95% CI=0.31-0.66). Multiple pathways were enriched in HCC, including histidine and coenzyme A metabolism (FDR p<0.001). Random forest classifier identified ten metabolites for inclusion in HCC risk classification models, which improved HCC risk classification compared to clinical covariates alone (AUC=0.66 for covariates vs. 0.88 for 10 metabolites plus covariates; p<0.0001). Findings were consistent in the UK Biobank (AUC=0.72 for covariates vs. 0.88 for four analogous metabolites plus covariates; p=0.04), assessed via nuclear magnetic resonance spectroscopy. Pre-diagnostic metabolites, primarily amino acid and sphingolipid derivatives, are associated with HCC risk and improve HCC risk classification beyond clinical covariates. These metabolite profiles, detectable years before diagnosis, could serve as early biomarkers for HCC detection and risk stratification if validated in larger studies.

Molecular effects of clinically relevant chemotherapeutic agents on choline phospholipid metabolism in triple negative breast cancer cells.

Triple-negative breast cancer (TNBC) is the most lethal breast cancer subtype, leading to poor patient outcomes despite aggressive treatment with surgery, radiation, and chemotherapy. There are currently no clinical tests available which measure early on whether TNBC patients respond to the selected chemotherapy treatment regimen. The magnetic resonance spectroscopy (MRS)-detected total choline (tCho) signal was shown to be a promising biomarker for assessing the response to chemotherapy treatment early on, as breast tumor tCho decreases after the first treatment cycle in patients who respond to chemotherapy cocktails. We sought to further investigate these clinical observations at the molecular level by combining metabolic and transcriptomic studies in two human TNBC cell lines treated with six different chemotherapeutic agents. Overall, our findings show that the glycerophosphocholine-to-phosphocholine ratio (GPC/PC) was a more sensitive and more broadly applicable measure of TNBC response to various chemotherapeutic agents than tCho. Specific chemotherapeutic drugs, including 5-fluorouracil and melphalan, resulted in the most significant effects on choline phospholipid metabolism, while other drugs did not significantly alter choline phospholipid metabolism. Overall, several of the six tested chemotherapeutic drugs mainly affected the expression levels of phosphatidylcholine (PtdC)-specific phospholipases and lysophospholipases, leading to the observed GPC/PC and tCho changes following treatment with the chemotherapeutic agents that altered choline phospholipid metabolism. The presented metabolic and transcriptomic findings support that the GPC/PC ratio and PtdC-phospholipases and -lysophospholipases could be further developed for assessing the response to chemotherapy treatment in TNBC patients. Statement of Significance: We show that the glycerophosphocholine-to-phosphocholine ratio and phosphatidylcholine-specific-phospholipases and -lysophospholipases are reliable markers for assessing the response to several chemotherapeutic agents, which could help with selecting correct treatments for TNBC patients.

Untargeted Metabolomics and Liquid Biopsy Investigation of Circulating Biomarkers in Soft Tissue Sarcoma

Background: Soft tissue sarcomas (STSs) are rare, highly malignant mesenchymal tumours, comprising approximately 1% of all adult cancers and about 15% of paediatric solid tumours. STSs exhibit considerable genomic complexity with diverse subtypes, posing significant clinical challenges. Objectives: This study aims to characterise the molecular signature of primary STS through liquid biopsies and the untargeted metabolomic profiling of 75 patients, providing deep insights into cellular processes and potential therapeutic targets. Methods: This study analysed serum samples using nuclear magnetic resonance (NMR) spectroscopy for metabolomic profiling. Multivariate data analysis and machine learning classifiers were employed to identify biomarkers. Results: A panel of eleven significant deregulated metabolites were discovered in serum samples of patients with STS, with potential implications for cancer diagnosis and treatment. Conclusions: Choline decrease emerged as a marker for cancer progression, highlighting the potential of targeting its metabolism for therapeutic approaches in STS. The NMR analysis protocol proved effective for determining circulating biomarkers from liquid biopsies, making it suitable for rare disease research.

Identification of Three Novel Tetrahydrocannabinol Analogs in the European Market.

Synthetic cannabinoids, known as Spice or K2, emerged in Europe and the United States between 2005 and 2008, peaking in incidents by 2015 with severe health implications. In 2021, the identification of hexahydrocannabinol (HHC), a semisynthetic cannabinoid (SSC), led to regulatory control in more than 20 countries in Europe, several US states, and other jurisdictions. A 2024 study in the United States highlighted the diversity of semisynthetic cannabinoids in the US market. New entries of SSCs are increasingly available in the European market, often found as blends in consumer products. This highlights the growing complexity of their regulation and the potential public health risks due to limited toxicological data. The major ingredients, isolated from "CB9", "tresconol",and "CBx", were subjected to mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. The major isolated ingredient of "CB9" was identified as [2-(E)-propen-1-yl]-Δ8-tetrahydrocannabinol-acetate. The major ingredient of "tresconol" was identified as [2-propen-2-yl]-Δ9-tetrahydrocannabinol, and the major ingredient of "CBx" was identified as [2-propen-2-yl]-Δ8-tetrahydrocannabinol. These compounds have no available spectroscopic or chromatographic data, have never been identified in Cannabis plants, and cannot be identified by standard chromatographic forensic analytical methods, without the use of spectroscopic techniques due to the lack of reference standards. The products were complex mixtures of previously unknown synthetic cannabinoids lacking established safety profiles. These findings highlight the potential public health risks associated with unregulated SSCs, similar to the concerns raised during the 2015 Spice outbreak. The presence of these novel substances requires careful monitoring to prevent future health crises.

New Polyketides From Trichoderma harzianum and Their Antifungal Activity.

Chemical investigation of the marine-derived fungus Trichoderma harzianum ZN-4 led to the isolation and identification of seven new secondary metabolites, harzianolides K-Q (1-7). The complete structures of seven new compounds were determined by high-resolution mass spectrometry and nuclear magnetic resonance spectroscopic analyses coupled with electronic circular dichroism calculations. The seven isolates were inactive as antibacterial and antitumor agents. However, harzianolides K (1), L (2), M (3) and O (5) exhibited weak to moderate anti-Pestalotiopsis theae activity with minimum inhibitory concentration values at the range of 25-100µg/mL.

WAND: A multi-modal dataset integrating advanced MRI, MEG, and TMS for multi-scale brain analysis

This paper introduces the Welsh Advanced Neuroimaging Database (WAND), a multi-scale, multi-modal imaging dataset comprising in vivo brain data from 170 healthy volunteers (aged 18–63 years), including 3 Tesla (3 T) magnetic resonance imaging (MRI) with ultra-strong (300 mT/m) magnetic field gradients, structural and functional MRI and nuclear magnetic resonance spectroscopy at 3 T and 7 T, magnetoencephalography (MEG), and transcranial magnetic stimulation (TMS), together with trait questionnaire and cognitive data. Data are organised using the Brain Imaging Data Structure (BIDS). In addition to raw data, we provide brain-extracted T1-weighted images, and quality reports for diffusion, T1- and T2-weighted structural data, and blood-oxygen level dependent functional tasks. Reasons for participant exclusion are also included. Data are available for download through our GIN repository, a data access management system designed to reduce storage requirements. Users can interact with and retrieve data as needed, without downloading the complete dataset. Given the depth of neuroimaging phenotyping, leveraging ultra-high-gradient, high-field MRI, MEG and TMS, this dataset will facilitate multi-scale and multi-modal investigations of the healthy human brain.

Revealing the Potential of a Chimaera: a Peptide-Peptide Nucleic Acid Molecule Designed To Interact with the SARS-CoV-2 Nucleocapsid Protein.

Numerous RNA-binding proteins have modular structures with folded domains and intrinsically disordered regions, making their atomic characterization difficult. This severely limits the investigation of their modalities of interaction as well as the evaluation of possible ways to interfere with this process. We report herein a rational strategy for the design and synthesis of a ligand able to interfere with the protein function, monitoring the interaction through solution nuclear magnetic resonance spectroscopy. Our approach employs a chimaera composed of two different fragments, a peptide and a peptide-nucleic acid, allowing to incorporate in the resulting molecule key features to address RNA-protein interactions. Focusing on two constructs of the N protein from SARS-CoV-2, the globular N-terminal domain and a more extended one comprising also two flanking intrinsically disordered regions, we demonstrate the enhanced affinity of the designed peptide-peptide nucleic acid chimaera for the protein compared to a related peptide lacking π-π stacking contributions within the chain. Furthermore, we emphasize the increasingly recognized relevant and synergistic role of the intrinsically disordered regions in protein-ligand interaction.

Synthesis, Structural Analysis and Antibacterial Properties of a Novel β-Aminoenone.

(Z)-3-butylamino-4,4,4-trifluoro-1-(2-hydroxyphenyl)but-2-en-1-one (1), a new β-aminoenone, has been investigated in terms of its intra- and intermolecular interactions. Vibrational, electronic and nuclear magnetic resonance spectroscopies were used for the characterization, while X-ray diffraction methods afforded the determination of the crystal structure. The compound is arranged in the crystal lattice as centre-symmetric H-bonded dimeric aggregates (C2/c monoclinic space group). Both experimental (infrared, Raman, ultraviolet-visible transitions and X-ray diffraction data) and theoretical (Quantum Theory of Atoms in Molecules and Natural Bond Orbital approaches, calculated spectra and conformational analysis) methods were used to obtain a deep insight into the intra- and intermolecular contacts. The interactions were quali- and quantitatively analysed and the data compared with closely related compounds. In vitro experiments were carried out in this work to evaluate the antibacterial activity of 1 against Gram-positive and Gram-negative bacteria, particularly Pseudomonas aeruginosa (ATCC 27853) and Staphylococcus aureus (6538). Compound 1 demonstrated a discernible suppression of biofilm formation and quorum sensing of both bacterial strains, indicating that it may be developed as an antibacterial candidate to reduce bacterial resistance and persistence on surfaces across a range of industries.

UV‐Curable Polyester Oligomers Containing Triptycene Segments

ABSTRACTA series of UV‐curable polyesters containing triptycene segments were synthesized via the melt polycondensation of 1,4‐cyclohexanedicarboxylic acid, triptycene‐1,4‐hydroquinone‐bis(2‐hydroxyethyl) ether, and various comonomer diols including 1,6‐hexanediol, neopentyl glycol, and 1,4‐cyclohexanedimethanol. The polyesters were characterized by 1H nuclear magnetic resonance spectroscopy, Fourier‐transform infrared spectroscopy, gel‐permeation chromatography, and differential scanning calorimetry. Thin films were prepared by solvent casting and were cured via exposure to UV‐light at elevated temperature. The crosslinked films were subsequently analyzed by differential scanning calorimetry, dynamic mechanical analysis, Soxhlet extractions, and tensile tests. Most of the samples that contained a high concentration of the triptycene monomer resulted in brittle materials with relatively high moduli and tensile strengths, but poor extensibilities. However, the 1,6‐hexanediol/1,4‐cyclohexanedicarboxylic acid polyester with 30 mol% of triptycene‐1,4‐hydroquinone‐bis(2‐hydroxyethyl) ether exhibited a Tg above room temperature, a relatively high modulus (~1.1 GPa) and tensile strength (~25 MPa), and ductility (144% elongation‐at‐break). These unique properties were attributed to the triptycene monomer, which is capable of threading polymer chains through its V‐shaped cavities to reinforce the polymer network. When these polyesters were formulated into UV‐curable coatings, the coatings displayed excellent impact resistance and substrate adhesion.

Targeting the G-quadruplex as a novel strategy for developing antibiotics against hypervirulent drug-resistant Staphylococcus aureus

BackgroundThe rapid emergence of multiple drug-resistant (MDR) bacterial pathogens and the lack of a novel antibiotic pipeline pose a serious threat to global healthcare. The limited number of established targets further restricts the identification of novel antibiotics to treat life-threatening MDR infections caused by Staphylococcus aureus strains. Therefore, novel targets for developing antibiotics are urgently required. In this study, we hypothesized that the G-quadruplex (G4)-binding ligands can be used as novel antibiotics as their binding can possibly downregulate/block the expression of vital genes.MethodsTo test this, first we screened the antibiotic properties of representative G4-binding ligands against hypervirulent and MDR S. aureus USA300 and determined the in vitro and in vivo antibacterial activity; and proposed the mechanism of action by applying various microbiological, infection, microscopic, and biophysicochemical techniques.ResultsHerein, among screened G4-binding ligands, N-methyl mesoporphyrin IX (NMM) showed the highest antibacterial activity against S. aureus USA300. NMM exhibited a minimum inhibitory concentration (MIC) of 5 μM against S. aureus USA300, impacting cell division and the cell wall by repressing the expressions of genes in the division cell wall (dcw) gene cluster. Genome-wide bioinformatics analysis of G4 motifs and their mapping on S. aureus genome, identified the presence of G4-motif in the promoter of mraZ, a conserved master regulator of the dcw cluster regulating the coordinated cell division and cell wall synthesis. Physicochemical assessments using UV–visible, circular dichroism, and nuclear magnetic resonance spectroscopy confirmed that the G4-motif present in the mraZ promoter formed an intramolecular parallel G4 structure, interacting with NMM. In vivo reporter followed by coupled in vitro transcription/translation (IVT) assays confirmed the role of mraZ G4 as a target interacting NMM to impose extreme antibacterial activity against both the gram-positive and -negative bacteria. In-cell and in vivo validation of NMM using RAW264.7 cells and Galleria mellonella; respectively, demonstrated that NMM exhibited superior antibiotic activity compared to well-established antibiotics, with no observed cytotoxicity.ConclusionsIn summary, the current study identified NMM as a broad-spectrum potent antibacterial agent and elucidated its plausible mechanism of action primarily by targeting G4-motif in the mraZ promoter of the dcw gene cluster.

Adaptable Pectin Extraction and Functional Group Impact on Electrolytes Suitable for Energy Storage Applications

Abstract An alkaline de-esterification method was developed to modify the functional properties of pectin extracted from soybean hull waste. The process yielded pectin with degrees of esterification (DE) ranging from 40 to 0.40, which was then incorporated into symmetrical supercapacitors using carbon active material derived from in-situ resource utilization (ISRU) methods for space exploration applications. Physical characterization via Fourier transform infrared spectroscopy, H1 nuclear magnetic resonance spectroscopy, and static light scattering revealed that precipitation pH significantly influenced DE, molecular weight, and yield. In electrochemical testing using coin cells with blocking electrodes, pectin with 27 DE demonstrated superior ionic conductivity of 17.51 S m-1, substantially higher than reported biopolymer alternatives. While initial supercapacitor cells using ISRU carbon showed modest capacity (~1 F g-1) and specific energy (~0.1-1 Wh kg-1), devices incorporating commercial carbon electrodes achieved markedly improved performance (2-5 Wh kg-1). The pectin-based hydrogel electrolytes exhibited promising characteristics including high specific power (1,000-11,000 W kg-1) and exceptional stability over 10,000 galvanostatic charge-discharge cycles with maintained coulombic efficiency, establishing their potential for future energy storage applications.

Analysis of the Generation of Harmful Aldehydes in Edible Oils During Sunlight Exposure and Deep-Frying Using High-Field Proton Nuclear Magnetic Resonance Spectroscopy

Edible oils are essential dietary components that provide crucial micronutrients. However, their quality can deteriorate during frying—a common cooking method—and with prolonged light exposure due to chemical reactions such as hydrolysis, oxidation, and polymerization. These processes lead to the formation of harmful compounds, particularly aldehydes. This study investigates how thermal and light exposure impact the chemical composition of five widely used edible oils: olive, rapeseed, sunflower, sesame, and peanut oils. For the thermal treatment, the oils were heated to 190 ± 5 °C in a commercial fryer, with samples taken at the start and after 10 min and 60 min of heating, while intermittently frying chicken nuggets to simulate typical frying conditions. For the light exposure treatment, the oil samples were exposed to direct sunlight for 3 and 8 h, with control samples being collected beforehand. The oil composition was analyzed using an advanced 800 MHz nuclear magnetic resonance (NMR) instrument with a triple-resonance inverse cryoprobe, providing high sensitivity and resolution. The results revealed a significant increase in various aldehyde compounds in all oils under both thermal and light exposure conditions. Notably, this study identified the generation of genotoxic and cytotoxic α,β-unsaturated aldehydes, including 4-hydroperoxy-(E)-2-alkenals, 4-hydroxy-(E)-2-alkenals, and 4,5-epoxy-(E)-2-alkenals. Given the established association of aldehydes with health risks, including cancer, Alzheimer’s, and Parkinson’s diseases, these findings highlight the importance of monitoring oil degradation during cooking and the appropriate storage of oils to minimize light exposure to reduce potential health risks.

Diagnostic value and efficacy of multimodal magnetic resonance imaging in differentiating radiation necrosis from tumor recurrence in glioblastomas.

Distinguishing radiation necrosis (RN) from recurrent tumor (RT) in patients with gliomas treated with radiation therapy presents an important clinical dilemma. To evaluate the diagnostic performance of multiparametric magnetic resonance imaging (MRI) techniques in distinguishing RN from RT in patients with histologically confirmed glioma treated previously with radiotherapy and chemotherapy or without chemotherapy using a combination of dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion MRI, diffusion tensor imaging (DTI), and MR spectroscopy (MRS). Patients with glioma who developed a new enhancing mass after standard treatment were retrospectively evaluated. Conventional MRI, DTI, DSC, and MRS were performed. The region of interest (ROI) was manually drawn in the enhancing lesions, peri-lesional white matter edema, and the contralateral normal-appearing white matter. Apparent diffusion coefficient (ADC), fractional anisotropy (FA), relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), N-acetylaspartate (NAA), choline (Cho), creatine (Cr), NAA/Cr, Cho/NAA, and Cho/Cr were calculated. Two-tailed t-test and receiver operating characteristic (ROC) curve analysis were performed. In total, 34 patients with RT and 25 with RN met our inclusion criteria. FA, rCBF, rCBV, Cho/NAA, Cho/Cr were statistically significant between the two groups (P < 0.05). The sensitivity and specificity of FA, rCBF, rCBV, Cho/NAA, and Cho/Cr in the diagnosis of RT were 70.6%, 97.1%, 91.2%, 91.2%, and 82.4% and 64%, 100%, 100%, 96%, and 72% respectively. DTI, DSC, and MRS are of great value in the differential diagnosis of RN and RT of glioma. The diagnostic performance of DSC is better than DTI and MRS.

Role of Hepatic Glycogen on Nocturnal Gluconeogenesis in Type 2 Diabetes Mellitus.

Higher gluconeogenesis (GNG) contributes to higher nocturnal endogenous glucose production (EGP) in type 2 diabetes (T2D). Studies using 13C Magnetic Resonance Spectroscopy (MRS) have confirmed lower hepatic glycogen content in T2D than in subjects without diabetes (ND). We determined the role of glycogen loading vs non-glycogen loading on contribution of GNG to nocturnal EGP in T2D. 14 T2D and 15 matched ND subjects were studied on two occasions, with glycogen loaded (GL: 60% carbohydrate) vs non-glycogen loaded (NGL: 40% carbohydrate) isocaloric meals for 3 days, in random order in the overnight state. [6,6-2H2] Glucose was infused to measure EGP, deuterium labelled water was used to measure GNG and 13C MRS scans were performed in fed and fasted state to measure hepatic glycogen content. Hepatic glycogen content and nocturnal EGP were higher (p<0.05) in GL vs NGL in both cohorts. % GNG to EGP averaged ∼50% in ND throughout the night after both meals. In contrast, % GNG to nocturnal EGP in T2D was lower with GL vs NGL and matched the pattern observed in ND with GL lowering overnight rates of GNG in T2D. Selective targeting of GNG at night with appropriate medications could reduce nocturnal and early morning fasting hyperglycemia and hepatic insulin resistance in people with T2D.

Pharmacophore Recombination Design, Synthesis, and Bioactivity of Ester-Substituted Pyrazole Purine Derivatives as Herbicide Safeners.

Mesosulfuron-methyl, an acetolactate synthase (ALS) inhibitor primarily applied to wheat and rye, can injure or even kill wheat crops. Herbicide safeners can improve the herbicide resistance of crops without reducing the herbicidal effect on targeted weed species. Herein, we present a series of pyrazole purine derivatives with the primary structure of the natural product cytokinin and commercialized safener mefenpyridyl, designed using the pharmacophore recombination method. The title compounds were synthesized and characterized using infrared spectroscopy, 1H and 13C nuclear magnetic resonance spectroscopy, and high-resolution mass spectrometry. A bioactivity assay proved that most of the target compounds can reduce the wheat phytotoxicity of mesosulfuron-methyl. Measurements of chlorophyll and glutathione contents, along with other enzyme activity assays, confirmed that compounds I-15 and I-13 exhibit higher safety activities compared with the mefenpyr-diethyl safener. Molecular structure comparisons demonstrated that I-15 is more readily absorbed and disseminated through the crop than the commercialized safener mefenpyr-diethyl. Molecular docking models and molecular dynamics simulations elucidated the protective mechanism of safeners; specifically, compound I-15 competitively binds to the ALS active site with mesosulfuron-methyl. The current study reveals the potential of pyrazole purine derivatives in the future discovery of novel herbicide safeners.

Chemical shift and relaxation regularization improve the accuracy of 1H MR spectroscopy analysis.

Accurate analysis of metabolite levels from 1H MRS data is a significant challenge, typically requiring the estimation of approximately 100 parameters from a single spectrum. Signal overlap, spectral noise, and common artifacts further complicate the analysis, leading to instability and reports of poor agreement between different analysis approaches. One inconsistently used method to improve analysis stability is known as regularization, where poorly determined parameters are partially constrained to take a predefined value. In this study, we examine how regularization of frequency and linewidth parameters influences analysis accuracy. The accuracy of three MRS analysis methods was compared: (1) ABfit, (2) ABfit-reg, and (3) LCModel, where ABfit-reg is a modified version of ABfit incorporating regularization. Accuracy was assessed on synthetic MRS data generated with random variability in the frequency shift and linewidth parameters applied to each basis signal. Spectra ( ) were generated across a range of SNR values (10, 30, 60, 100) to evaluate the impact of variable data quality. Comparison between ABfit and ABfit-reg demonstrates a statistically significant (p < 0.0005) improvement in accuracy associated with regularization for each SNR regime. An approximately 10% reduction in the mean squared metabolite errors was found for ABfit-reg compared to LCModel for SNR >10 (p < 0.0005). Furthermore, Bland-Altman analysis shows that incorporating regularization into ABfit enhances its agreement with LCModel. Regularization is beneficial for MRS fitting and accurate characterization of the frequency and linewidth variability in vivo may yield further improvements.

A novel multifrequency-tuned transceiver array for human-brain 31P-MRSI at 7 T.

Phosphorus-31 (31P) MR spectroscopy imaging (MRSI) at 7 T is a powerful tool for investigating high-energy phosphate metabolism in human brains with significantly improved signal-to-noise ratio (SNR) and spectral resolution. However, this imaging technique requires dual-frequency radiofrequency coil for performing brain anatomical imaging and B0 shimming at proton (1H) operation frequency, and 31P MRSI at lower operation frequency. Herein, we introduce a novel 31P-1H dual-frequency radiofrequency coil design using a double-tuned and double-matched (DODO) coil that does not require complex circuitry or two coil layers and exhibits similar imaging performance as to single-frequency control coils for both 31P and 1H imaging operations. We constructed an eight-element 31P-1H dual-frequency DODO transceiver array and compared its performance with a quadrature-driven dual-tuned eight-element 31P and eight-element 1H transverse electromagnetic volume coil for both phantom and in vivo human-brain 31P-MRSI studies at 7 T. The DODO transceiver array achieved high spatiotemporal resolution 31P MRSI with 2.5-cc nominal voxel size and 22-min scan time covering the entire human brain, showing excellent SNR for mapping cerebral phosphorous metabolites such as phosphocreatine, adenosine triphosphate, and other low-concentration metabolites. Compared with the transverse electromagnetic volume coil, the DODO array demonstrated large improvements in 31P-MRSI SNR in both phantom and human brain studies, with over 5-fold SNR gain in peripheral regions and over 2-fold SNR gain in central brain regions. This simple and cost-effective array design and excellent performance can greatly benefit human-brain 31P-MRSI applications at 7 T.

Radiomics in glioma: emerging trends and challenges.

Radiomics is a promising neuroimaging technique for extracting and analyzing quantitative glioma features. This review discusses the application, emerging trends, and challenges associated with using radiomics in glioma. Integrating deep learning algorithms enhances various radiomics components, including image normalization, region of interest segmentation, feature extraction, feature selection, and model construction and can potentially improve model accuracy and performance. Moreover, investigating specific tumor habitats of glioblastomas aids in a better understanding of glioblastoma aggressiveness and the development of effective treatment strategies. Additionally, advanced imaging techniques, such as diffusion-weighted imaging, perfusion-weighted imaging, magnetic resonance spectroscopy, magnetic resonance fingerprinting, functional MRI, and positron emission tomography, can provide supplementary information for tumor characterization and classification. Furthermore, radiomics analysis helps understand the glioma immune microenvironment by predicting immune-related biomarkers and characterizing immune responses within tumors. Integrating multi-omics data, such as genomics, transcriptomics, proteomics, and pathomics, with radiomics, aids the understanding of the biological significance of the underlying radiomics features and improves the prediction of genetic mutations, prognosis, and treatment response in patients with glioma. Addressing challenges, such as model reproducibility, model generalizability, model interpretability, and multi-omics data integration, is crucial for the clinical translation of radiomics in glioma.