LINC00978 regulates metabolic rewiring to promote the malignancy of glioblastoma through AKR1B1.

Glioma is a fatal primary brain tumor. Improved glioma treatment effectiveness depends on a better understanding of its underlying mechanisms. Glioblastoma (GBM), was classified as high-grade glioma with the most lethality and therapeutic resistance. Herein, we reported LINC00978 overexpressed in high-grade gliomas. Down-regulation of LINC00978 in glioblastoma cells inhibited cell proliferation, invasion, migration, and induced apoptosis. In vivo experiments confirmed that the CamK-A siRNA of LINC00978 could effectively inhibit the proliferation of glioblastoma cells. The main pathway and genes regulated by LINC00978 were detected using RNA sequencing to elucidate the molecular mechanism. The results suggest that LINC00978 regulates the expression of genes related to metabolic pathways, including aldo-keto reductase family 1 member B (AKR1B1), which mediates the cytotoxicity of 2-deoxyglucose. LINC00978 positively regulated AKR1B1 expression, and 2-deoxyglucose induced AKR1B1 expression via a LINC00978-dependent mechanism. This research has revealed that LINC00978 promotes the sensitivity of glioblastoma cells to 2DG. LINC00978 is highly expressed in most high-grade glioma patients. Thus, understanding the anticancer mechanism identified in this study may contribute to treating the majority of glioma patients. This study clarified the function and molecular mechanism of LINC00978 in glioblastoma and provided a study basis for LINC00978 to guide the clinical treatment of glioblastoma.

Comparing the clinical utility of single-shot, readout-segmented and zoomit echo-planar imaging in diffusion-weighted imaging of the kidney at 3 T.

We compared the clinical utility of single-shot echo-planar imaging (SS-EPI) using different breathing schemes, readout-segmented EPI and zoomit EPI in the repeatability of apparent diffusion coefficient (ADC) measurements, cortico-medullary contrast to noise ratio (c-mCNR) and image quality. In this institutional review board-approved prospective study, some common clinically applicable diffusion-weighted imaging (b = 50, 400, 800 s/mm2) of kidney on 3.0 T MRI were performed on 22 volunteers using SS-EPI with breath-hold diffusion-weighted imaging (BH-DWI), free-breathing (FB-DWI), navigator-triggered (NT-DWI) and respiratory-triggered (RT-DWI), readout-segmented DWI (RS-DWI), and Zoomit DWI (Z-DWI). ADC and c-mCNR were measured in 12 anatomic locations (the upper, middle, and lower pole of the renal cortex and medulla), and image quality was assessed on these DWI sequences. A DWI with the optimal clinical utility was decided by systematically assessing the ADC repeatability, c-mCNR and image quality among the DWIs. For ADC measurements, Z-DWI had an excellent intra-observer agreement (intra-class correlation coefficients (ICCs): 0.876-0.944) and good inter-observer agreement (inter-class ICCs: 0.798-0.856) in six DWI sequences. Z-DWI had the highest ADC repeatability in most of the 12 anatomic locations of the kidneys (mean ADC absolute difference: 0.070-0.111 × 10-3 mm2/s, limit of agreement: 0.031-0.056 × 10-3 mm2/s). In all DWIs, Z-DWI yielded a slightly higher c-mCNR than other DWIs in most representative locations (P > 0.05), which was significantly higher than BH-DWI and FB-DWI in the middle pole of both kidneys and the upper pole of the left kidney (P < 0.05). In addition, Z-DWI yielded image quality that was similar to RT-DWI and NT-DWI (P > 0.05) and superior to BH-DWI, FB-DWI and RS-DWI (P < 0.05). Our results suggest that Z-DWI provides the highest ADC reproducibility, better c-mCNR and good image quality on 3.0 T MRI, making it the recommended sequence for clinical DWI of the kidney.

Preoperative Magnetic Resonance Imaging Radiomics for Predicting Early Recurrence of Glioblastoma.

PURPOSE: Early recurrence of glioblastoma after standard treatment makes patient care challenging. This study aimed to assess preoperative magnetic resonance imaging (MRI) radiomics for predicting early recurrence of glioblastoma. PATIENTS AND METHODS: A total of 122 patients (training cohort: n = 86; validation cohort: n = 36) with pathologically confirmed glioblastoma were included in this retrospective study. Preoperative brain MRI images were analyzed for both radiomics and the Visually Accessible Rembrandt Image (VASARI) features of glioblastoma. Models incorporating MRI radiomics, the VASARI parameters, and clinical variables were developed and presented in a nomogram. Performance was assessed based on calibration, discrimination, and clinical usefulness. RESULTS: The nomogram consisting of the radiomic signatures, the VASARI parameters, and blood urea nitrogen (BUN) values showed good discrimination between the patients with early recurrence and those with later recurrence, with an area under the curve of 0.85 (95% CI, 0.77-0.94) in the training cohort and 0.84 [95% CI, 0.71-0.97] in the validation cohort. Decision curve analysis demonstrated favorable clinical application of the nomogram. CONCLUSION: This study showed the potential usefulness of preoperative brain MRI radiomics in predicting the early recurrence of glioblastoma, which should be helpful in personalized management of glioblastoma.

Cross-network interaction for diagnosis of major depressive disorder based on resting state functional connectivity.

Previous studies have suggested that resting-state functional connectivity plays a central role in the physiopathology of major depressive disorder (MDD). However, the individualized diagnosis of MDD based on resting-state functional connectivity is still unclear, especially in first episode drug-naive patients with MDD. Resting state functional magnetic resonance imaging was enrolled from 30 first episode drug-naive patients with MDD and age- and gender-matched 31 healthy controls. Whole brain functional connectivity was computed and viewed as classification features. Multivariate pattern analysis (MVPA) was performed to discriminate patients with MDD from controls. The experimental results exhibited a correct classification rate of 82.25% (p < 0.001) with sensitivity of 83.87% and specificity of 80.64%. Almost all of the consensus connections (125/128) were cross-network interaction among default mode network (DMN), salience network (SN), central executive network (CEN), visual cortex network (VN), Cerebellum and Other. Moreover, the supramarginal gyrus exhibited high discriminative power in classification. Our findings suggested cross-network interaction can be used as an effective biomarker for MDD clinical diagnosis, which may reveal the potential pathological mechanism for major depression. The current study further confirmed reliable application of MVPA in discriminating MDD patients from healthy controls.

Application of magnetic resonance 3D-SPACE sequence combined image fusion technique in preoperative evaluation of pituitary macroadenoma. / ç£å ±æŒ¯3D-SPACEåºåˆ—ç»“åˆå›¾åƒèžåˆæŠ€æœ¯åœ¨åž‚ä½“å¤§è ºç˜¤æœ¯å‰è¯„ä¼°ä¸­çš„åº”ç”¨ä»·å€¼.

OBJECTIVES: To evaluate the image quality of magnetic resonance 3D-sampling perfection with application-optimized contrasts by using different filp angle evolutions (3D-SPACE) sequence combined with different fusion methods in image fusion technology and the application value of fusion technology in preoperative evaluation of pituitary macroadenoma. METHODS: We collected MRI data of 43 patients with pituitary macroadenoma confirmed by Xiangya Hospital of Central South University, including collecting conventional MRI scan+enhancement, 3D-SPACE T2WI, and 3D-SPACE T1WI+C image data. 3D-SPACE sequence fusion was used in 6 combinations of 3D-SPACE T2WI/3D-SPACE T1WI+C, which were normal phase+normal phase, reverse phase+normal phase, normal phase+reverse phase, reverse phase+reverse phase, and normal phase pseudo color+normal phase, normal phase+normal phase pseudo color. Two senior radiologists used semi-quantitative methods to evaluate and compare the image quality of different combinations to obtain the best fusion mode. According to the degree of tumor invasion of the optic chiasma, oculomotor nerve, and cavernous sinus vessels, the MRI enhancement, 3D-SPACE T2WI, 3D-SPACE T1WI+C, and 2 3D-SPACE sequence fusion images were performed according to a three-level score system. Taking the intraoperative observation as the gold standard, Fisher probability exact method was used to compare different sequences to show the difference between the degree of invasion of the pituitary macroadenoma to the surrounding tissue and the intraoperative results. RESULTS: The Kruskal-Wallis H rank sum test showed that among the 6 image fusion modes, 3D-SPACE T1WI+C normal phase pseudo-color and 3D-SPACE T2WI normal phase fusion images had the best quality (P<0.05). No significance was observed among the 4 groups in the evaluation of consistency between the intraoperative findings and the graphically displayed extent of tumor invasion into oculomotor nerve (both level I, II, and III, P>0.05). The 3D-SPACE T2WI/3D-SPACE T1WI+C fusion images and the 3D-SPACE T2WI images showed better performance in the evaluation of consistency between the intraoperative findings and the graphically displayed extent of tumor invasion into optic chiasma (level II and III) than that in other two kinds of imaging data of the MRI enhancement group and 3D-SPACE T1WI+C group (P<0.01, P<0.05, respectively), with no significance being observed in level I. The 3D-SPACE T2WI/3D-SPACE T1WI+C fusion images and the 3D-SPACE T1WI+C images showed better performance in the evaluation of consistency between the intraoperative findings and the graphically displayed extent of tumor invasion into cavernous sinus vessels (level II) than that in other two kinds of imaging data of the MRI enhancement group and 3D-SPACE T2WI group (P<0.01, P<0.05, respectively), with no significance being observed in level I and III. CONCLUSIONS: Magnetic resonance 3D-SPACE sequence combined with image fusion technology is better than conventional magnetic resonance sequence for showing pituitary macroadenoma invasion of skull base vascular nerves. The invasion is better than the 3D-SPACE sequence alone, showing that the relationship between tumor and cavernous sinus vascular grade II better than the 3D-SPACE sequence alone. It has good application prospects for preoperative risk assessment and surgical plan.