Circulating Fibroblast Growth Factor 21 Levels Are Closely Associated with Hepatic Fat Content: A Cross-Sectional Study

BACKGROUND AND AIMS: Fibroblasts growth factor 21 (FGF21), a liver-secreted endocrine factor involved in regulating glucose and lipid metabolism, has been shown to be elevated in patients with non-alcoholic fatty liver disease (NAFLD). This study aimed to evaluate the quantitative correlation between serum FGF21 level and hepatic fat content. METHODS: A total of 138 subjects (72 male and 66 female) aged from 18 to 65 years with abnormal glucose metabolism and B-ultrasonography diagnosed fatty liver were enrolled in the study. Serum FGF21 levels were determined by an in-house chemiluminescence immunoassay and hepatic fat contents were measured by proton magnetic resonance spectroscopy. RESULTS: Serum FGF21 increased progressively with the increase of hepatic fat content, but when hepatic fat content increased to the fourth quartile, FGF21 tended to decline. Serum FGF21 concentrations were positively correlated with hepatic fat content especially in subjects with mild/moderate hepatic steatosis (r = 0.276, p = 0.009). Within the range of hepatic steatosis from the first to third quartile, FGF21 was superior to any other traditional clinical markers including ALT to reflect hepatic fat content. When the patients with severe hepatic steatosis (the fourth quartile) were included, the quantitative correlation between FGF21 and hepatic fat content was weakened. CONCLUSIONS: Serum FGF21 was a potential biomarker to reflect the hepatic fat content in patients with mild or moderate NAFLD. In severe NAFLD patients, FGF21 concentration might decrease due to liver inflammation or injury

Presentation_1_Esophageal cancer detection via non-contrast CT and deep learning.PPTX

BackgroundEsophageal cancer is the seventh most frequently diagnosed cancer with a high mortality rate and the sixth leading cause of cancer deaths in the world. Early detection of esophageal cancer is very vital for the patients. Traditionally, contrast computed tomography (CT) was used to detect esophageal carcinomas, but with the development of deep learning (DL) technology, it may now be possible for non-contrast CT to detect esophageal carcinomas. In this study, we aimed to establish a DL-based diagnostic system to stage esophageal cancer from non-contrast chest CT images.MethodsIn this retrospective dual-center study, we included 397 primary esophageal cancer patients with pathologically confirmed non-contrast chest CT images, as well as 250 healthy individuals without esophageal tumors, confirmed through endoscopic examination. The images of these participants were treated as the training data. Additionally, images from 100 esophageal cancer patients and 100 healthy individuals were enrolled for model validation. The esophagus segmentation was performed using the no-new-Net (nnU-Net) model; based on the segmentation result and feature extraction, a decision tree was employed to classify whether cancer is present or not. We compared the diagnostic efficacy of the DL-based method with the performance of radiologists with various levels of experience. Meanwhile, a diagnostic performance comparison of radiologists with and without the aid of the DL-based method was also conducted.ResultsIn this study, the DL-based method demonstrated a high level of diagnostic efficacy in the detection of esophageal cancer, with a performance of AUC of 0.890, sensitivity of 0.900, specificity of 0.880, accuracy of 0.882, and F-score of 0.891. Furthermore, the incorporation of the DL-based method resulted in a significant improvement of the AUC values w.r.t. of three radiologists from 0.855/0.820/0.930 to 0.910/0.955/0.965 (p = 0.0004/ConclusionThe DL-based method shows a satisfactory performance of sensitivity and specificity for detecting esophageal cancers from non-contrast chest CT images. With the aid of the DL-based method, radiologists can attain better diagnostic workup for esophageal cancer and minimize the chance of missing esophageal cancers in reading the CT scans acquired for health check-up purposes.</p

Enrichment of short mutant cell-free DNA fragments enhanced detection of pancreatic cancerResearch in context

Background: Analysis of cell-free DNA (cfDNA) is promising for broad applications in clinical settings, but with significant bias towards late-stage cancers. Although recent studies have discussed the diverse and degraded nature of cfDNA molecules, little is known about its impact on the practice of cfDNA analysis. Methods: We developed single-strand library preparation and hybrid-capture-based cfDNA sequencing (SLHC-seq) to analysis degraded cfDNA fragments. Next we used SLHC-seq to perform cfDNA profiling in 112 pancreatic cancer patients, and the results were compared with 13 previous reports. Extensive analysis was performed in terms of cfDNA fragments to explore the reasons for higher detection rate of KRAS mutations in the circulation of pancreatic cancers. Findings: By applying the new approach, we achieved higher efficiency in analysis of mutations than previously reported using other detection assays. 791 cancer-specific mutations were detected in plasma of 88% patients with KRAS hotspots detected in 70% of all patients. Only 8 mutations were detected in 28 healthy controls without any known oncogenic or truncating alleles. cfDNA profiling by SLHC-seq was largely consistent with results of tissue-based sequencing. SLHC-seq rescued short or damaged cfDNA fragments along to increase the sensitivity and accuracy of circulating-tumour DNA detection. Interpretation: We found that the small mutant fragments are prevalent in early-stage patients, which provides strong evidence for fragment size-based detection of pancreatic cancer. The new pipeline enhanced our understanding of cfDNA biology and provide new insights for liquid biopsy. Keywords: Pancreatic cancer, Cell-free DNA, Fragmentation, Tissue biopsy, Diagnosis and prognosi

Hypoxic Preconditioning with Cobalt of Bone Marrow Mesenchymal Stem Cells Improves Cell Migration and Enhances Therapy for Treatment of Ischemic Acute Kidney Injury

<div><p>Mesenchymal stem cell (MSC) administration is known to enhance the recovery of the kidney following injury. Here we tested the potential of hypoxic-preconditioned-MSC transplantation to enhance the efficacy of cell therapy on acute kidney injury (AKI) by improving MSC migration to the injured kidney. Cobalt was used as hypoxia mimetic preconditioning (HMP). MSC were subjected to HMP through 24 h culture in 200 µmol/L cobalt. Compared to normoxia cultured MSC (NP-MSC), HMP significantly increased the expression of HIF-1α and CXCR4 in MSC and enhanced the migration of MSC <i>in vitro</i>. This effect was lost when MSC were treated with siRNA targeting HIF-1α or CXCR4 antagonist. SPIO labeled MSC were administered to rats with I/R injury followed immediately by magnetic resonance imaging. Imaging clearly showed that HMP-MSC exhibited greater migration and a longer retention time in the ischemic kidney than NP-MSC. Histological evaluation showed more HMP-MSC in the glomerular capillaries of ischemic kidneys than in the kidneys receiving NP-MSC. Occasional tubules showed iron labeling in the HMP group, while no tubules had iron labeling in NP group, indicating the possibility of tubular transdifferentiation after HMP. These results were also confirmed by fluorescence microscopy study using CM-DiI labeling. The increased recruitment of HMP-MSC was associated with reduced kidney injury and enhanced functional recovery. This effect was also related to the increased paracrine action by HMP-MSC. Thus we suggest that by enhancing MSC migration and prolonging kidney retention, hypoxic preconditioning of MSC may be a useful approach for developing AKI cell therapy.</p></div

Quantitative perfusion imaging of neoplastic liver lesions: A multi-institution study

Abstract We describe multi-institutional experience using free-breathing, 3D Spiral GRAPPA-based quantitative perfusion MRI in characterizing neoplastic liver masses. 45 patients (age: 48–72 years) were prospectively recruited at University Hospitals, Cleveland, USA on a 3 Tesla (T) MRI, and at Zhongshan Hospital, Shanghai, China on a 1.5 T MRI. Contrast-enhanced volumetric T1-weighted images were acquired and a dual-input single-compartment model used to derive arterial fraction (AF), distribution volume (DV) and mean transit time (MTT) for the lesions and normal parenchyma. The measurements were compared using two-tailed Student’s t-test, with Bonferroni correction applied for multiple-comparison testing. 28 hepatocellular carcinoma (HCC) and 17 metastatic lesions were evaluated. No significant difference was noted in perfusion parameters of normal liver parenchyma and neoplastic masses at two centers (p = 0.62 for AF, 0.015 for DV, 0.42 for MTT for HCC, p = 0.13 for AF, 0.97 for DV, 0.78 for MTT for metastases). There was statistically significant difference in AF, DV, and MTT of metastases and AF and DV of HCC compared to normal liver parenchyma (p < 0.5/9 = 0.0055). A statistically significant difference was noted in the MTT of metastases compared to hepatocellular carcinoma (p < 0.001*10-5). In conclusion, 3D Spiral-GRAPPA enabled quantitative free-breathing perfusion MRI exam provides robust perfusion parameters