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Neurometabolites Alteration in the Acute Phase of Mild Traumatic Brain Injury (mTBI): An In Vivo Proton Magnetic Resonance Spectroscopy (1H-MRS) Study

Veeramuthu V, Seow P, Narayanan V, Wong JHD, Tan LK, Hernowo AT, et al.

Acad Radiol, 2018 09;25(9):1167-1177.
PMID: 29449141 DOI: 10.1016/j.acra.2018.01.005

RATIONALE AND OBJECTIVES: Magnetic resonance spectroscopy is a noninvasive imaging technique that allows for reliable assessment of microscopic changes in brain cytoarchitecture, neuronal injuries, and neurochemical changes resultant from traumatic insults. We aimed to evaluate the acute alteration of neurometabolites in complicated and uncomplicated mild traumatic brain injury (mTBI) patients in comparison to control subjects using proton magnetic resonance spectroscopy (1H magnetic resonance spectroscopy).
MATERIAL AND METHODS: Forty-eight subjects (23 complicated mTBI [cmTBI] patients, 12 uncomplicated mTBI [umTBI] patients, and 13 controls) underwent magnetic resonance imaging scan with additional single voxel spectroscopy sequence. Magnetic resonance imaging scans for patients were done at an average of 10 hours (standard deviation 4.26) post injury. The single voxel spectroscopy adjacent to side of injury and noninjury regions were analysed to obtain absolute concentrations and ratio relative to creatine of the neurometabolites. One-way analysis of variance was performed to compare neurometabolite concentrations of the three groups, and a correlation study was done between the neurometabolite concentration and Glasgow Coma Scale.
RESULTS: Significant difference was found in ratio of N-acetylaspartate to creatine (NAA/Cr + PCr) (χ2(2) = 0.22, P

Matched MeSH terms: Dipeptides/metabolism*
Fulltext A novel sequence-based predictor for identifying and characterizing thermophilic proteins using estimated propensity scores of dipeptides

Charoenkwan P, Chotpatiwetchkul W, Lee VS, Nantasenamat C, Shoombuatong W

Sci Rep, 2021 Dec 10;11(1):23782.
PMID: 34893688 DOI: 10.1038/s41598-021-03293-w

Owing to their ability to maintain a thermodynamically stable fold at extremely high temperatures, thermophilic proteins (TTPs) play a critical role in basic research and a variety of applications in the food industry. As a result, the development of computation models for rapidly and accurately identifying novel TTPs from a large number of uncharacterized protein sequences is desirable. In spite of existing computational models that have already been developed for characterizing thermophilic proteins, their performance and interpretability remain unsatisfactory. We present a novel sequence-based thermophilic protein predictor, termed SCMTPP, for improving model predictability and interpretability. First, an up-to-date and high-quality dataset consisting of 1853 TPPs and 3233 non-TPPs was compiled from published literature. Second, the SCMTPP predictor was created by combining the scoring card method (SCM) with estimated propensity scores of g-gap dipeptides. Benchmarking experiments revealed that SCMTPP had a cross-validation accuracy of 0.883, which was comparable to that of a support vector machine-based predictor (0.906-0.910) and 2-17% higher than that of commonly used machine learning models. Furthermore, SCMTPP outperformed the state-of-the-art approach (ThermoPred) on the independent test dataset, with accuracy and MCC of 0.865 and 0.731, respectively. Finally, the SCMTPP-derived propensity scores were used to elucidate the critical physicochemical properties for protein thermostability enhancement. In terms of interpretability and generalizability, comparative results showed that SCMTPP was effective for identifying and characterizing TPPs. We had implemented the proposed predictor as a user-friendly online web server at http://pmlabstack.pythonanywhere.com/SCMTPP in order to allow easy access to the model. SCMTPP is expected to be a powerful tool for facilitating community-wide efforts to identify TPPs on a large scale and guiding experimental characterization of TPPs.

Matched MeSH terms: Dipeptides/metabolism
In-vitro digestibility and amino acid composition of soy protein isolate cross-linked with microbial transglutaminase followed by heating with ribose

Gan CY, Cheng LH, Azahari B, Easa AM

Int J Food Sci Nutr, 2009;60 Suppl 7:99-108.
PMID: 19194813 DOI: 10.1080/09637480802635090

Cross-linked soy protein isolate (SPI) gels were produced via single-treatment of SPI with microbial transglutaminase (MTG) for 5 h or 24 h, or with ribose for 2 h, or via combined-treatments of SPI with MTG followed by heating with ribose. Assessment of gel strength and solubility concluded that measures which increased protein cross-links resulted in improved gel strength; however, in most cases the digestibility and amino acid content of the gels were reduced. The combined treated gel of SPI/MTG for 24 h/ribose was more easily digested by digestive enzymes and retained higher amounts of amino acids compared with the control Maillard gels of SPI with ribose. MTG consumed lysine and glutamine and reduced the availability of amino acids for the Maillard reaction with ribose. MTG was able to preserve the nutritional value of SPI against the destructive effect of the Maillard reaction and cross-links.

Matched MeSH terms: Dipeptides/metabolism

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