Article in Journal of proteome research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
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.
2 · The registry
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.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
10 authors.
Andong ZhuAustralian National Phenome Centre and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth WA 6150, Australia.
Reika MasudaAustralian National Phenome Centre and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth WA 6150, Australia.
Philipp NitschkeAustralian National Phenome Centre and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth WA 6150, Australia.ORCID 0000-0002-5814-7529
Gengjie JiaShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Shenzhen Key Laboratory of Agricultural Synthetic Biology, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China.
Jianbin YanShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Shenzhen Key Laboratory of Agricultural Synthetic Biology, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China.
Elaine HolmesAustralian National Phenome Centre and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth WA 6150, Australia.ORCID 0000-0002-0556-8389
Jeremy K NicholsonNutrition Research, Department of Metabolism, Nutrition and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, London SW7 2AZ, U.K.ORCID 0000-0002-8123-8349
Julien WistAustralian National Phenome Centre and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth WA 6150, Australia.ORCID 0000-0002-3416-2572
Andres BernalAustralian National Phenome Centre and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth WA 6150, Australia.ORCID 0000-0003-1668-7225
Ruey Leng LooAustralian National Phenome Centre and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth WA 6150, Australia.ORCID 0000-0001-5307-5709
Funding
No grant is acknowledged in the PubMed record.
6 · The paper itself
Abstract
Nuclear magnetic resonance (NMR) spectroscopy is increasingly employed in research to quantify lipoprotein subfractions, offering potential utility in clinical diagnostics, particularly for cardiovascular risk assessment. However, the independent validation of proprietary NMR-based lipoprotein profiling methods is crucial for verifying clinical accuracy and reliability. This study presents a posthoc evaluation of concordance between the NMR-based B.I.LISA method and standard enzymatic assays for total cholesterol (TC), triglycerides (TGs), and high-density lipoprotein cholesterol (HDL-C), measured in 620 plasma samples from the OMNI-Heart study, focusing on their performance in evaluating the dietary intervention outcomes. Despite involving independently acquired data not designed for an intermethod validation, the comparison showed a high correlation between methods (
Indexed as
LipoproteinsProton Magnetic Resonance SpectroscopyAdultAgedCardiovascular DiseasesCholesterolCholesterol, HDLDietFemaleHumansMagnetic Resonance SpectroscopyMaleMiddle AgedReproducibility of ResultsTriglyceridesCholesterolCholesterol, HDLLipoproteinsTriglyceridesaccuracyenzymatic assaysHDL cholesterolLDL cholesterollipoproteins subfractionsNMRtriglycerides
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.