Magnetic resonance spectroscopy (MRS) is the only biomedical imaging method that can noninvasively detect endogenous signals from the neurotransmitter γ-aminobutyric acid (GABA) in the human brain. Its increasing popularity has been aided by improvements in scanner hardware and acquisition methodology, as well as by broader access to pulse sequences that can selectively detect GABA, in particular J-difference spectral editing sequences. Nevertheless, implementations of GABA-edited MRS remain diverse across research sites, making comparisons between studies challenging. This large-scale multi-vendor, multi-site study seeks to better understand the factors that impact measurement outcomes of GABA-edited MRS. An international consortium of 24 research sites was formed. Data from 272 healthy adults were acquired on scanners from the three major MRI vendors and analyzed using the Gannet processing pipeline. MRS data were acquired in the medial parietal lobe with standard GABA+ and macromolecule- (MM-) suppressed GABA editing. The coefficient of variation across the entire cohort was 12% for GABA+ measurements and 28% for MM-suppressed GABA measurements. A multilevel analysis revealed that most of the variance (72%) in the GABA+ data was accounted for by differences between participants within-site, while site-level differences accounted for comparatively more variance (20%) than vendor-level differences (8%). For MM-suppressed GABA data, the variance was distributed equally between site- (50%) and participant-level (50%) differences. The findings show that GABA+ measurements exhibit strong agreement when implemented with a standard protocol. There is, however, increased variability for MM-suppressed GABA measurements that is attributed in part to differences in site-to-site data acquisition. This study’s protocol establishes a framework for future methodological standardization of GABA-edited MRS, while the results provide valuable benchmarks for the MRS community.

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Abstract

Accurate and reliable quantification of brain metabolites measured in vivo using 1 H magnetic resonance spectroscopy (MRS) is a topic of continued interest in the field. Aside from differences in the basic approach to quantification, the quantification of metabolite data acquired at different sites and on different platforms poses an additional methodological challenge. In this study, we analyze spectrally edited -aminobutyric acid (GABA) MRS data and quantify GABA levels relative to an internal tissue water reference. Data from 284 volunteers scanned across 25 research sites were collected using standard GABA+ editing. Unsuppressed water acquisitions from the same volume of interest were acquired for signal referencing. Whole-brain T1-weighted structural images were acquired and tissue-segmented to determine gray matter, white matter and cerebrospinal fluid voxel tissue fractions. Water-referenced GABA+ measurements were fully corrected for tissue-dependent signal relaxation and water visibility effects. The cohort-wide coefficient of variation was 17%, which was largely driven by vendor-related differences according to a linear mixed-effects analysis. The mean within-site coefficient of variation was 9%. Vendor differences contributed 53% to the total variance in the data, while the remaining variance was attributed to site-(11%) and participant-level (36%) effects. Results from an exploratory analysis suggested that the vendor differences were related to the water signal acquisition. Discounting the observed vendor-specific effects, water-referenced GABA+ measurements exhibit levels of variance similar to creatine-referenced GABA+ measurements. It is concluded that quantification using internal tissue water referencing remains a viable and reliable method for the in vivo quantification of GABA+ levels.

The aim of the present study was to clarify the activation of ferroptosis in different breast cancer cells by sulfasalazine (SAS) and to explore the relationship between the estrogen receptor (ER) and the transferrin receptor (TFRC). MDA-MB-231 and T47D cells were treated with SAS for 24 h. Changes in cell morphology were observed under a microscope. CCK-8 was used to detect the proliferation inhibition rate and determine the IC 50 values. Western blotting was used to detect the expression of glutathione peroxidase 4 (GPX4) and xCT. Flow cytometry was used to identify changes in the production of reactive oxygen species (ROS). Mitochondrial morphological changes in T47D were observed using transmission electron microscopy. Changes in the mitochondrial membrane potential (MMP) were observed using confocal fluorescence microscopy. RT-PCR was used to detect the mRNA expression levels of TFRC and divalent metal transporter 1 (DMT1). Bioinformatics analysis was performed on TFRC expression in 1,208 breast cancer samples and its relationship with ER. TFRC expression was detected in various breast cancer tissues using immunohistochemistry and in various breast cancer cells using western blotting. Small interfering RNA (siRNA) knocked down ER expression in T47D cells, and changes in the TFRC mRNA and protein levels were observed. RT-PCR was used to detect TFRC expression in 87 clinical specimens. The results of the present study revealed that SAS could inhibit breast cancer cell viability, which was accompanied by an abnormal increase in ROS and a depletion of GPX4 and system x c-. Liproxstatin-1 reversed the SAS-induced increase in ROS. The cells treated with SAS had shrunken mitochondria and decreased MMP. SAS upregulated TFRC and DMT1. Knockdown of the ER increased TFRC expression in breast cancer cells. Immunohistochemistry indicated that TFRC expression was lower in ER + tissues than in ERtissues. After confirmation with RT-PCR in 87 clinical specimens, TFRC expression in ERtissue was revealed to be significantly higher than that of ER + tissue. In conclusion SAS could trigger ferroptosis in breast cancer cells, especially in cells with low ER expression. Therefore, SAS is a potential agent for breast cancer treatment.