OPLS-DA score and loadinig S-plots of the HR-MAS MR spectra for predicting pathologic response to NAC.

<p>(A) pCR vs. PR (B) pCR vs. SD (C) PR vs. SD. pCR: pathologic complete response; PR: partial response; SD: stable disease.</p

Pattern Recognition Analysis for Hepatotoxicity Induced by Acetaminophen Using Plasma and Urinary ¹H NMR-Based Metabolomics in Humans

Drug-induced liver injury (DILI) is currently an increasingly relevant health issue. However, available biomarkers do not reliably detect or quantify DILI risk. Therefore, the purpose of this study was to comparatively evaluate plasma and urinary biomarkers obtained from humans treated with acetaminophen (APAP) using a metabolomics approach and a proton nuclear magnetic resonance (NMR) platform. APAP (3 g/day, two 500 mg tablets every 8 h) was administered to 20 healthy Korean males (age, 20–29 years) for 7 days. Urine was collected daily before and during dosing and 6 days after the final dose. NMR spectra of these urine samples were analyzed using principal component analysis (PCA) and partial least-squares-discrimination analysis. Although the activities of aspartate aminotransferase and lactate dehydrogenase were significantly increased 7 days post-APAP treatment, serum biochemical parameters of aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, total bilirubin, γ-glutamyl transpeptidase, and lactate dehydrogenase were within normal range of hepatic function. However, urine and plasma ¹H NMR spectroscopy revealed different clustering between predosing and after APAP treatment for global metabolomic profiling through PCA. Urinary endogenous metabolites of trimethylamine-N-oxide, citrate, 3-chlorotyrosine, phenylalanine, glycine, hippurate, and glutarate as well as plasma endogenous metabolites such as lactate, glucose, 3-hydroxyisovalerate, isoleucine, acetylglycine, acetone, acetate, glutamine, ethanol, and isobutyrate responded significantly to APAP dosing in humans. Urinary and plasma endogenous metabolites were more sensitive than serum biochemical parameters. These results might be applied to predict or screen potential hepatotoxicity caused by other drugs using urinary and plasma ¹H NMR analyses

Metabolomics of Breast Cancer Using High-Resolution Magic Angle Spinning Magnetic Resonance Spectroscopy: Correlations with 18F-FDG Positron Emission Tomography-Computed Tomography, Dynamic Contrast-Enhanced and Diffusion-Weighted Imaging MRI

<div><p>Purpose</p><p>Our goal in this study was to find correlations between breast cancer metabolites and conventional quantitative imaging parameters using high-resolution magic angle spinning (HR-MAS) magnetic resonance spectroscopy (MRS) and to find breast cancer subgroups that show high correlations between metabolites and imaging parameters.</p><p>Materials and methods</p><p>Between August 2010 and December 2013, we included 53 female patients (mean age 49.6 years; age range 32–75 years) with a total of 53 breast lesions assessed by the Breast Imaging Reporting and Data System. They were enrolled under the following criteria: breast lesions larger than 1 cm in diameter which 1) were suspicious for malignancy on mammography or ultrasound (US), 2) were pathologically confirmed to be breast cancer with US-guided core-needle biopsy (CNB) 3) underwent 3 Tesla MRI with dynamic contrast-enhanced (DCE) and diffusion-weighted imaging (DWI) and positron emission tomography-computed tomography (PET-CT), and 4) had an attainable immunohistochemistry profile from CNB. We acquired spectral data by HR-MAS MRS with CNB specimens and expressed the data as relative metabolite concentrations. We compared the metabolites with the signal enhancement ratio (SER), maximum standardized FDG uptake value (SUV max), apparent diffusion coefficient (ADC), and histopathologic prognostic factors for correlation. We calculated Spearman correlations and performed a partial least squares-discriminant analysis (PLS-DA) to further classify patient groups into subgroups to find correlation differences between HR-MAS spectroscopic values and conventional imaging parameters.</p><p>Results</p><p>In a multivariate analysis, the PLS-DA models built with HR-MAS MRS metabolic profiles showed visible discrimination between high and low SER, SUV, and ADC. In luminal subtype breast cancer, compared to all cases, high SER, ADV, and SUV were more closely clustered by visual assessment. Multiple metabolites were correlated with SER and SUV in all cases. Multiple metabolites showed correlations with SER and SUV in the ER positive, HER2 negative, and Ki-67 negative groups.</p><p>Conclusion</p><p>High levels of PC, choline, and glycine acquired from HR-MAS MRS using CNB specimens were noted in the high SER group via DCE MRI and the high SUV group via PET-CT, with significant correlations between choline and SER and between PC and SUV. Further studies should investigate whether HR-MAS MRS using CNB specimens can provide similar or more prognostic information than conventional quantitative imaging parameters.</p></div

Clinicopathologic data of 34 patients with 36 malignant breast lesions in this study.

<p>N/A: not available.</p

Synthesis of a Zr-Based Metal–Organic Framework with Spirobifluorenetetrabenzoic Acid for the Effective Removal of Nerve Agent Simulants

A new microporous Zr­(IV)-based metal–organic framework (MOF) containing 4,4′,4″,4‴-(9,9′-spirobi­[fluorene]-2,2′,7,7′-tetrayl)­tetrabenzoic acid (Spirof-MOF) was synthesized, characterized, and size-controlled for the adsorption and decomposition of a nerve agent simulant, dimethyl 4-nitrophenylphosphate (DMNP). Spirof-MOF showed a hydrolysis half-life (<i>t</i>_1/2) of 7.5 min to DMNP, which was confirmed by using in situ ³¹P NMR spectroscopy. Additionally, size-controlled Spirof-MOFb (∼1 μm) exhibited a half-life of 1.8 min and 99% removal within 18 min for DMNP. The results show that Spirof-MOF is a new active material in removing nerve agent simulants by adsorption and hydrolytic decomposition

Correlation between histopathologic parameters and HR-MAS MR spectroscopy values.

*<p>Other NMR values (GPC/Cho, GPC/PC, PC/Cho) were not significantly different by histopathologic parameters.</p><p><b>Bold</b> indicates statistical significance (<i>P</i><0.05).</p

HR-MAS MR spectroscopy values for 36 breast cancer specimens.

<p>Data represent the mean ± standard deviation (median).</p><p>Cho: choline, PC: phosphocholine, GPC: glycerophosphocholine, tCho: total choline (the sum of Cho, PC, and GPC), Cr: creatine, Tau: taurine, Gly: glycine, m-Ins: myo-inositol, s-Ins: scyllo-inositol, Ala: alanine, Suc: succinate.</p

A 38-year-old woman with invasive ductal carcinoma (tumor size 37 mm, triple negative, strongly positive Ki-67).

<p>The HR-MAS MR spectrum (11.7T) obtained using the core needle biopsy specimen shows peaks of each choline metabolite. The tCho concentration measured with HR-MAS MR spectroscopy was 6.5 mmol/kg. Note. Lac, lactate; Ala, alanine; Glu, glutamate; Cr, creatine; Cho, free choline; GPC, glycerophosphocholine; PC, phosphocholine; tCho, total choline, sum of Cho, PC, and GPC; Tau, taurine; m-Ins, myo-inositol; Gly, glycine.</p

Correlation between conventional quantitative parameters (SER, ADC, SUV) and HR-MAS MR spectroscopy values in the 53 breast cancer specimens.

<p>Correlation between conventional quantitative parameters (SER, ADC, SUV) and HR-MAS MR spectroscopy values in the 53 breast cancer specimens.</p

Partial Least Squares-Discriminant Analysis (PLS-DA) score plot and loadings S plot for (A,B) SER, (C,D) ADC, and (E,F) SUV of all cases.

<p>Partial Least Squares-Discriminant Analysis (PLS-DA) score plot and loadings S plot for (A,B) SER, (C,D) ADC, and (E,F) SUV of all cases.</p