Application of 3D-PCASL combined with t-ASL and MRA in the diagnosis of patients with isolated vertigo induced by posterior circulation ischemia.

OBJECTIVES: Isolated vertigo induced by posterior circulation ischemia (PCIV) can further progress into posterior circulation infarction. This study aimed to explore the diagnostic values of three-dimensional pseudo-continuous arterial spin labeling (3D-PCASL) combined with territorial arterial spin labeling (t-ASL) and magnetic resonance angiography (MRA) in visualizing and evaluating PCIV, seeking improved diagnostic tools for clinical guidance. METHODS: 28 PCIVs (11 males, 17 females, aged from 55 to 83 years, mean age: 69.68 ± 9.01 years) and 28 healthy controls (HCs, 12 male, 16 female, aged from 56 to 87 years, mean age: 66.75 ± 9.86 years) underwent conventional magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), MRA, 3D-PCASL, and t-ASL. We compared the incidence of anatomic variants of the posterior circle of Willis in MRA, cerebral blood flow (CBF) and anterior collateral blood flow on postprocessing maps obtained from 3D-PCASL and t-ASL sequence between PCIVs and HCs. Chi-square test and paired t-test were analyzed statistically with SPSS 24.0 software. RESULTS: 7 PCIVs (7/28, 25%) and 6 HCs (6/28, 21%) showed fetal posterior cerebral artery (FPCA) on MRA, including 1 HC, and 6 PCIVs with FPCA appeared hypoperfusion. 18 PCIVs (64%) and 2 HCs (7%) showed hypoperfusion in the posterior circulation (PC), including 1 HC and 7 PCIVs displayed anterior circulation collateral flow. Chi-square analyses demonstrated a difference in PC hypoperfusion between PCIVs and HCs, whether in the whole or FPCA-positive group assessment (P < 0.05). Paired t-test showed that the CBF values were significant difference for the bilateral PC asymmetrical perfusion in the PCIVs (P < 0.01). When compared to the bilateral PC symmetrical non-hypoperfusion area in the PCIVs and HCs, the CBF values were not significant (P > 0.05). The CBF values of the PC in PCIVs were lower than in HCs (P < 0.05). The reduction rate in the hypoperfusion side of the bilateral PC asymmetrical perfusion of the PCIVs ranged from 4% to 37%, while the HCs reduction rate was 7.7%. The average PC symmetrical perfusion average reduction rate of the PCIVs was 52.25%, while the HCs reduction rate was 42.75%. CONCLUSION: 3D-PCASL is a non-invasive and susceptible method for detecting hypoperfusion in PC, serving as a potential biomarker of PCIV. The suspected hypoperfusion in PC may be attributed to the emergence of FPCA and the manifestation of anterior collateral flow when combining t-ASL and MRA sequences. These findings demonstrated that 3D-PCASL combined with t-ASL and MRA sequences are the potential method to identify PCIV, leading to early diagnosis of PCIV and reducing the risk of progressing into infarction.

Molecular Characteristics of T Cell-Mediated Tumor Killing in Hepatocellular Carcinoma.

Background: Although checkpoint blockade is a promising approach for the treatment of hepatocellular carcinoma (HCC), subsets of patients expected to show a response have not been established. As T cell-mediated tumor killing (TTK) is the fundamental principle of immune checkpoint inhibitor therapy, we established subtypes based on genes related to the sensitivity to TKK and evaluated their prognostic value for HCC immunotherapies. Methods: Genes regulating the sensitivity of tumor cells to T cell-mediated killing (referred to as GSTTKs) showing differential expression in HCC and correlations with prognosis were identified by high-throughput screening assays. Unsupervised clustering was applied to classify patients with HCC into subtypes based on the GSTTKs. The tumor microenvironment, metabolic properties, and genetic variation were compared among the subgroups. A scoring algorithm based on the prognostic GSTTKs, referred to as the TCscore, was developed, and its clinical and predictive value for the response to immunotherapy were evaluated. Results: In total, 18 out of 641 GSTTKs simultaneously showed differential expression in HCC and were correlated with prognosis. Based on the 18 GSTTKs, patients were clustered into two subgroups, which reflected distinct TTK patterns in HCC. Tumor-infiltrating immune cells, immune-related gene expression, glycolipid metabolism, somatic mutations, and signaling pathways differed between the two subgroups. The TCscore effectively distinguished between populations with different responses to chemotherapeutics or immunotherapy and overall survival. Conclusions: TTK patterns played a nonnegligible role in formation of TME diversity and metabolic complexity. Evaluating the TTK patterns of individual tumor will contribute to enhancing our cognition of TME characterization, reflects differences in the functionality of T cells in HCC and guiding more effective therapy strategies.

Quantitative assessment of articular cartilage degeneration using 3D ultrashort echo time cones adiabatic T1ρ (3D UTE-Cones-AdiabT1ρ) imaging.

OBJECTIVES: To evaluate articular cartilage degeneration using quantitative three-dimensional ultrashort-echo-time cones adiabatic-T1ρ (3D UTE-Cones-AdiabT1ρ) imaging. METHODS: Sixty-six human subjects were recruited for this study. Kellgren-Lawrence (KL) grade and Whole-Organ Magnetic-Resonance-Imaging Score (WORMS) were evaluated by two musculoskeletal radiologists. The human subjects were categorized into three groups, namely normal controls (KL0), doubtful-minimal osteoarthritis (OA) (KL1-2), and moderate-severe OA (KL3-4). WORMS were regrouped to encompass the extent of lesions and the depth of lesions. The UTE-Cones-AdiabT1ρ values were obtained using 3D UTE-Cones data acquisitions preceded by seven paired adiabatic full passage pulses that corresponded to seven spin-locking times (TSLs) of 0, 12, 24, 36, 48, 72, and 96 ms. The performance of the UTE-Cones-AdiabT1ρ technique in evaluating the degeneration of knee cartilage was assessed via the ANOVA comparisons with subregional analysis and Spearman's correlation coefficient as well as the receiver-operating-characteristic (ROC) curve. RESULTS: UTE-Cones-AdiabT1ρ showed significant positive correlations with KL grade (r = 0.15, p < 0.05) and WORMS (r = 0.57, p < 0.05). Higher UTE-Cones-AdiabT1ρ values were observed in both larger and deeper lesions in the cartilage. The differences in UTE-Cones-AdiabT1ρ values among different extent and depth groups of cartilage lesions were all statistically significant (p < 0.05). Subregional analyses showed that the correlations between UTE-Cones-AdiabT1ρ and WORMS varied with the location of cartilage. The AUC value of UTE-Cones-AdiabT1ρ for mild cartilage degeneration (WORMS=1) was 0.8. The diagnostic threshold value of UTE-Cones-AdiabT1ρ for mild cartilage degeneration was 39.4 ms with 80.8% sensitivity. CONCLUSIONS: The 3D UTE-Cones-AdiabT1ρ sequence can be useful in quantitative evaluation of articular cartilage degeneration. KEY POINTS: • The 3D UTE-Cones-AdiabT1ρ sequence can distinguish mild cartilage degeneration from normal cartilage with a diagnostic threshold value of 39.4 ms for mild cartilage degeneration with 80.8% sensitivity. • Higher UTE-Cones-AdiabT1ρ values were observed in both larger and deeper lesions in the articular cartilage. • UTE-Cones-AdiabT1ρ is a promising biomarker for quantitative evaluation of early cartilage degeneration.

Intervertebral disc degeneration associated with vertebral marrow fat, assessed using quantitative magnetic resonance imaging.

OBJECTIVE: To investigate the potential clinical application of quantitative MRI in assessing the correlation between lumbar vertebrae bone marrow fat deposition and intervertebral disc degeneration. MATERIALS AND METHODS: A total of 104 chronic lower-back pain volunteers underwent 3.0-T MRI with T2-weighted imaging, T2 mapping, and iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL-IQ) between August 2018 and June 2019. Each disc was assessed with T2 value by T2 mapping, and the L1-S1 vertebral bone marrow fat fraction was assessed by IDEAL-IQ. The differences and relationship between T2 value and the adjacent vertebral bone marrow fat fraction values within the five Pfirrmann groups, five age groups, and five lumbar levels were statistically analyzed. RESULTS: The vertebral bone marrow fat fraction had a significant negative correlation with T2 values of nucleus pulposus' T2 values (p < 0.001). However, the significant negative correlation was only found between T2 values of nucleus pulposus and adjacent vertebral bone marrow fat in Pfirrmann II-III, L1/2-L5/S1 level, and 40-49 years' age groups. Pfirrmann grades of the intervertebral disc were positively correlated with adjacent vertebrae bone marrow fat fraction (p < 0.05). CONCLUSION: Lumbar bone marrow fat deposition significantly increases during the early stages of intervertebral disc degeneration. Quantitative measurements of bone marrow fat deposition and water content of intervertebral discs have a predictive value and are an important supplement to the qualitative traditional classification strategies for the early stages of intervertebral disc degeneration.

Immune-related prognosis biomarkers associated with osteosarcoma microenvironment.

BACKGROUND: Osteosarcoma is a highly aggressive bone tumor that most commonly affects children and adolescents. Treatment and outcomes for osteosarcoma have remained unchanged over the past 30 years. The relationship between osteosarcoma and the immune microenvironment may represent a key to its undoing. METHODS: We calculated the immune and stromal scores of osteosarcoma cases from the Target database using the ESTIMATE algorithm. Then we used the CIBERSORT algorithm to explore the tumor microenvironment and analyze immune infiltration of osteosarcoma. Differentially expressed genes (DEGs) were identified based on immune scores and stromal scores. Search Tool for the Retrieval of Interacting Genes Database (STRING) was utilized to assess protein-protein interaction (PPI) information, and Molecular Complex Detection (MCODE) plugin was used to screen hub modules of PPI network in Cytoscape. The prognostic value of the gene signature was validated in an independent GSE39058 cohort. Gene set enrichment analysis (GSEA) was performed to study the hub genes in signaling pathways. RESULTS: From 83 samples of osteosarcoma obtained from the Target dataset, 137 DEGs were identified, including 134 upregulated genes and three downregulated genes. Functional enrichment analysis and PPI networks demonstrated that these genes were mainly involved in neutrophil degranulation and neutrophil activation involved in immune response, and participated in neuroactive ligand-receptor interaction and staphylococcus aureus infection. CONCLUSIONS: Our study established an immune-related gene signature to predict outcomes of osteosarcoma, which may be important targets for individual treatment.

Genome-wide profiling of prognosis-related alternative splicing signatures in sarcoma.

BACKGROUND: Sarcomas (SARCs) are rare malignant tumors with poor prognosis. Increasing evidence has suggested that aberrant alternative splicing (AS) is strongly associated with tumor initiation and progression. We considered whether survival-related AS events might serve as prognosis predictors and underlying targeted molecules in SARC treatment. METHODS: RNA-Seq data of the SARC cohort were downloaded from The Cancer Genome Atlas (TCGA) database. Survival-related AS events were selected by univariate and multivariate Cox regression analyses. Metascape was used for constructing a gene interaction network and performing functional enrichment analysis. Then, prognosis predictors were established based on statistically significant survival-related AS events and evaluated by receiver operator characteristic (ROC) curve analysis. Finally, the potential regulatory network was analyzed via Pearson's correlation between survival-related AS events and splicing factors (SFs). RESULTS: A total of 3,610 AS events and 2,291 genes were found to be prognosis-related in 261 SARC samples. The focal adhesion pathway was identified as the most critical molecular mechanism corresponding to poor prognosis. Notably, several prognosis predictors based on survival-related AS events showed excellent performance in prognosis prediction. The area under the curve of the ROC of the risk score was 0.85 in the integrated predictor. The splicing network proved complicated regulation between prognosis-related SFs and AS events. Also, driver gene mutations were significantly associated with AS in SARC patients. CONCLUSIONS: Survival-related AS events may become ideal indictors for the prognosis prediction of SARCs. Corresponding splicing regulatory mechanisms are worth further exploration.

[PROMOTION EFFECT OF CHONDROITIN SULFATE ON PROLIFERATION OF MYOBLASTS].

OBJECTIVE: To research the effect of chondroitin sulfate (CS) on the proliferation of myoblasts and the formation of myotube. METHODS: The myoblasts at passage 5 were used to prepare the cells suspension (1×108 cells/mL), and the experiment was divided into 4 groups based on CS concentration in the medium:group A (0 µg/mL), group B (50 µg/mL), group C (100 µg/mL), and group D (200 µg/mL). The cell morphology and myotube formation were observed by inverted microscope at 4, 5, and 8 days after treatment; MTT was used to detect the cell proliferation at 6 days, and the number of myotube was calculated by HE staining at 8 days. RESULTS: Cells showed spindle shape after adherent, with ovoid nuclei and dense cytoplasm under inverted microscope. When the cell adherent rate was 90%, cells arranged in whorls swirled and showed long fusiform adherent growth; and then nuclei fusion resulted in formation of multincleated myotubes. At 8 days, most myoblasts fused to form myotube in group A, but less myotube was observed in groups B and C, and the least myotube in group D. The absorbance (A) values of groups A, B, C, and D were 0.045 2±0.004 4, 0.540 4±0.096 7, 0.660 9±0.143 4, and 1.069 0±0.039 0 respectively, showing significant difference between other groups (P<0.05) except between groups B and C P>0.05). HE staining observation showed that most myoblasts fused to form myotube in group A, but less myotube in groups B and C, and the least myotube in group D. The number of myotube of groups A, B, C, and D were 222.01±30.02, 193.13±42.46, 170.26±11.96, and 136.88±16.78 respectively, showing no significant difference among groups (F=1.658, P=0.252). CONCLUSIONS: CS can significantly promote the proliferation of myoblast, the promotion is the biggest when CS concentration is 200 µg/mL.