Replicative senescence of human dermal fibroblasts affects structural and functional aspects of the Golgi apparatus

It is well recognized that the world population is ageing rapidly. Therefore, it is important to understand ageing processes at the cellular and molecular levels to predict the onset of age‐related diseases and prevent them. Recent research has focused on the identification of ageing biomarkers, including those associated with the properties of the Golgi apparatus. In this context, Golgi‐mediated glycosylation of proteins has been well characterized. Additionally, other studies show that the secretion of many compounds, including pro‐inflammatory cytokines and extracellular matrix–degrading enzymes, is modified during ageing, resulting in physical and functional skin degradation. Since the Golgi apparatus is a central organelle of the secretory pathway, we investigated its structural organization in senescent primary human dermal fibroblasts using confocal and electron microscopy. In addition, we monitored the expression of Golgi‐related genes in the same cells. Our data showed a marked alteration in the Golgi morphology during replicative senescence. In contrast to its small and compact structure in non‐senescent cells, the Golgi apparatus exhibited a large and expanded morphology in senescent fibroblasts. Our data also demonstrated that the expression of many genes related to Golgi structural integrity and function was significantly modified in senescent cells, suggesting a relationship between Golgi apparatus function and ageing.     

An ultrasonographic monitoring of skin condition in patients receiving radiotherapy for head and neck cancers

Radiodermatitis is one of the commonest side effects of radiotherapy. They are usually assessed by semi‐quantitative clinical scores, which are not validated and may be subject to inter‐observer variability. A few previous studies suggested that high‐frequency ultrasonography (HF‐USG) is useful in the assessment of the acute phase of radiation dermatitis in breast cancer patients. (a) To monitor skin changes by HF‐USG during the course of radiotherapy due to head and neck cancers, and (b) to determine whether there is any connection between skin sonograms and the skin scoring criteria. This prospective, observational study includes patients diagnosed with head and neck cancers, treated with radiotherapy or concomitant chemoradiation. The final analysis includes six patients. In every patient, the HF‐USG as well as dermatological assessment (target lesion score—TLS and CACE v. 4.0) were performed 4×: before, in the middle, day after, and 3 months after radiotherapy. There were significant differences between non‐irradiated skin thickness and thickness of skin with clinically obvious radiodermatitis (TLS grade 1‐4; P < .0001), as well as between irradiated, unchanged skin thickness (TLS grade 0) and thickness of skin with clinically obvious radiodermatitis (TLS grade 1‐4; P = .0002). There was no significant difference between non‐irradiated and irradiated, unchanged skin thickness (TLS grade 0; P = .9318). In four patients, we demonstrated subepidermal low echogenic band (SLEB). HF‐USG can be useful tool to noninvasive and objective assessment of skin changes during radiotherapy.     

Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure

BACKGROUND Postoperative liver failure is the most severe complication in cirrhotic patients with hepatocellular carcinoma(HCC) after major hepatectomy. Current available clinical indexes predicting postoperative residual liver function are not sufficiently accurate.AIM To determine a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting liver failure in cirrhotic patients with HCC after major hepatectomy.METHODS For this retrospective study, a radiomics-based model was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance images in 101 patients with HCC between June 2012 and June 2018. Sixty-one radiomic features were extracted from hepatobiliary phase images and selected by the least absolute shrinkage and selection operator method to construct a radiomics signature. A clinical prediction model, and radiomics-based model incorporating significant clinical indexes and radiomics signature were built using multivariable logistic regression analysis. The integrated radiomics-based model was presented as a radiomics nomogram. The performances of clinical prediction model, radiomics signature, and radiomics-based model for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve, and decision curve analyses.RESULTS Five radiomics features from hepatobiliary phase images were selected to construct the radiomics signature. The clinical prediction model, radiomics signature, and radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure(area under the curve: 0.809-0.894). The radiomics-based model achieved the highest performance for predicting liver failure(area under the curve: 0.894; 95%CI: 0.823-0.964). The integrated discrimination improvement analysis showed a significant improvement in the accuracy of liver failure prediction when radiomics signature was added to the clinical prediction model(integrated discrimination improvement = 0.117, P =0.002). The calibration curve and an insignificant Hosmer-Lemeshow test statistic(P = 0.841) demonstrated good calibration of the radiomics-based model. The decision curve analysis showed that patients would benefit more from a radiomics-based prediction model than from a clinical prediction model and radiomics signature alone.CONCLUSION A radiomics-based model of preoperative gadoxetic acid–enhanced MRI can be used to predict liver failure in cirrhotic patients with HCC after major hepatectomy.