ReviewNMR in biomedicine2017
Applications of high-resolution magic angle spinning MRS in biomedical studies II-Human diseases.
Review in NMR in biomedicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 34 citations in OpenAlex.
- Urine metabolic analysis as a non-invasive method to predict biochemical recurrence in prostate cancer.Translational andrology and urology · 2025Article
- NMR and Metabolomics-A Roadmap for the Future.Metabolites · 2022Review
- Placental metabolite profiles in late gestation for healthy mice.Metabolomics : Official journal of the Metabolomic Society · 2022Article
- Multiplatform Metabolomics Studies of Human Cancers With NMR and Mass Spectrometry Imaging.Frontiers in molecular biosciences · 2022Article
- Dysregulated Alanine as a Potential Predictive Marker of Glioma-An Insight from Untargeted HRMAS-NMR and Machine Learning Data.Metabolites · 2021Article
- NMR-Based Metabolomics.Advances in experimental medicine and biology · 2021Article
- Spatially-resolved metabolic profiling of living Drosophila in neurodegenerative conditions usingScientific reports · 2020Article
- Metabolomic Profiling of Wildtype and TransgenicMetabolites · 2020Article
- Characterization of Brain Metabolism by Nuclear Magnetic Resonance.Chemphyschem : a European journal of chemical physics and physical chemistry · 2019Review
- Evaluation of Enzyme Substrate Radiotracers as PET/MRS Hybrid Imaging Agents.ACS medicinal chemistry letters · 2018Article
- Promises and pitfalls of untargeted metabolomics.Journal of inherited metabolic disease · 2018Review
- Metabolite Profile of Alzheimer's Disease in the Frontal Cortex as Analyzed by HRMASFrontiers in aging neuroscience · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 3 institutions in 4 countries.
Funding
Abstract
High-resolution magic angle spinning (HRMAS) MRS is a powerful method for gaining insight into the physiological and pathological processes of cellular metabolism. Given its ability to obtain high-resolution spectra of non-liquid biological samples, while preserving tissue architecture for subsequent histopathological analysis, the technique has become invaluable for biochemical and biomedical studies. Using HRMAS MRS, alterations in measured metabolites, metabolic ratios, and metabolomic profiles present the possibility to improve identification and prognostication of various diseases and decipher the metabolomic impact of drug therapies. In this review, we evaluate HRMAS MRS results on human tissue specimens from malignancies and non-localized diseases reported in the literature since the inception of the technique in 1996. We present the diverse applications of the technique in understanding pathological processes of different anatomical origins, correlations with in vivo imaging, effectiveness of therapies, and progress in the HRMAS methodology.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.