Regulation of interstitial fluid flow in adventitia along vasculature by heartbeat and respiration.

Converging studies showed interstitial fluid (ISF) adjacent to blood vessels flows in adventitia along vasculature into heart and lungs. We aim to reveal circulatory pathways and regulatory mechanism of such adventitial ISF flow in rat model. By MRI, real-time fluorescent imaging, micro-CT, and histological analysis, ISF was found to flow in adventitial matrix surrounded by fascia and along systemic vessels into heart, then flow into lungs via pulmonary arteries and back to heart via pulmonary veins, which was neither perivascular tissues nor blood or lymphatic vessels. Under physiological conditions, speckle-like adventitial ISF flow rate was positively correlated with heart rate, increased when holding breath, became pulsative during heavy breathing. During cardiac or respiratory cycle, each dilation or contraction of heart or lungs can generate to-and-fro adventitial ISF flow along femoral veins. Discovered regulatory mechanisms of adventitial ISF flow along vasculature by heart and lungs will revolutionize understanding of cardiovascular system.

SUMF1 overexpression promotes tumorous cell growth and migration and is correlated with the immune status of patients with glioma.

BACKGROUND: Glioma is a prevalent type of malignant tumor. To date, there is a lack of literature reports that have examined the association between sulfatase modifying factor 1 (SUMF1) and glioma. METHODS: The levels of SUMF1 were examined, and their relationships with the diagnosis, prognosis, and immune microenvironment of patients with glioma were investigated. Cox and Lasso regression analysis were employed to construct nomograms and risk models associated with SUMF1. The functions and mechanisms of SUMF1 were explored and verified using gene ontology, cell counting kit-8, wound healing, western blotting, and transwell experiments. RESULTS: SUMF1 expression tended to increase in glioma tissues. SUMF1 overexpression was linked to the diagnosis of cancer, survival events, isocitrate dehydrogenase status, age, and histological subtype and was positively correlated with poor prognosis in patients with glioma. SUMF1 overexpression was an independent risk factor for poor prognosis. SUMF1-related nomograms and high-risk scores could predict the outcome of patients with glioma. SUMF1 co-expressed genes were involved in cytokine, T-cell activation, and lymphocyte proliferation. Inhibiting the expression of SUMF1 could deter the proliferation, migration, and invasion of glioma cells through epithelial mesenchymal transition. SUMF1 overexpression was significantly associated with the stromal score, immune cells (such as macrophages, neutrophils, activated dendritic cells), estimate score, immune score, and the expression of the programmed cell death 1, cytotoxic T-lymphocyte associated protein 4, CD79A and other immune cell marker. CONCLUSION: SUMF1 overexpression was found to be correlated with adverse prognosis, cancer detection, and immune status in patients with glioma. Inhibiting the expression of SUMF1 was observed to deter the proliferation, migration, and invasion of cancer cells. The nomograms and risk models associated with SUMF1 could predict the prognosis of patients with glioma.

LA-Net: layer attention network for 3D-to-2D retinal vessel segmentation in OCTA images.

Objective.Retinal vessel segmentation from optical coherence tomography angiography (OCTA) volumes is significant in analyzing blood supply structures and the diagnosing ophthalmic diseases. However, accurate retinal vessel segmentation in 3D OCTA remains challenging due to the interference of choroidal blood flow signals and the variations in retinal vessel structure.Approach.This paper proposes a layer attention network (LA-Net) for 3D-to-2D retinal vessel segmentation. The network comprises a 3D projection path and a 2D segmentation path. The key component in the 3D path is the proposed multi-scale layer attention module, which effectively learns the layer features of OCT and OCTA to attend to the retinal vessel layer while suppressing the choroidal vessel layer. This module also efficiently captures 3D multi-scale information for improved semantic understanding during projection. In the 2D path, a reverse boundary attention module is introduced to explore and preserve boundary and shape features of retinal vessels by focusing on non-salient regions in deep features.Main results.Experimental results in two subsets of the OCTA-500 dataset showed that our method achieves advanced segmentation performance with Dice similarity coefficients of 93.04% and 89.74%, respectively.Significance.The proposed network provides reliable 3D-to-2D segmentation of retinal vessels, with potential for application in various segmentation tasks that involve projecting the input image. Implementation code:https://github.com/y8421036/LA-Net.

Contour attention network for cerebrovascular segmentation from TOF-MRA volumetric images.

BACKGROUND: Cerebrovascular segmentation is a crucial step in the computer-assisted diagnosis of cerebrovascular pathologies. However, accurate extraction of cerebral vessels from time-of-flight magnetic resonance angiography (TOF-MRA) data is still challenging due to the complex topology and slender shape. PURPOSE: The existing deep learning-based approaches pay more attention to the skeleton and ignore the contour, which limits the segmentation performance of the cerebrovascular structure. We aim to weight the contour of brain vessels in shallow features when concatenating with deep features. It helps to obtain more accurate cerebrovascular details and narrows the semantic gap between multilevel features. METHODS: This work proposes a novel framework for priority extraction of contours in cerebrovascular structures. We first design a neighborhood-based algorithm to generate the ground truth of the cerebrovascular contour from original annotations, which can introduce useful shape information for the segmentation network. Moreover, We propose an encoder-dual decoder-based contour attention network (CA-Net), which consists of the dilated asymmetry convolution block (DACB) and the Contour Attention Module (CAM). The ancillary decoder uses the DACB to obtain cerebrovascular contour features under the supervision of contour annotations. The CAM transforms these features into a spatial attention map to increase the weight of the contour voxels in main decoder to better restored the vessel contour details. RESULTS: The CA-Net is thoroughly validated using two publicly available datasets, and the experimental results demonstrate that our network outperforms the competitors for cerebrovascular segmentation. We achieved the average dice similarity coefficient ( D S C $DSC$ ) of 68.15 and 99.92% in natural and synthetic datasets. Our method segments cerebrovascular structures with better completeness. CONCLUSIONS: We propose a new framework containing contour annotation generation and cerebrovascular segmentation network that better captures the tiny vessels and improve vessel connectivity.

Identification of FEZ2 as a potential oncogene in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is one of the common malignant tumors with high lethal rate and poor prognosis. Dysregulation of many genes have been reported to be involved in the occurrence and development of PDAC. However, as a highly conserved gene in eukaryotes, the role of Fasciculation and Elongation protein Zeta 2 (FEZ2) in pancreatic cancer progression is not clear. In this study, we identified the oncogenic effect of FEZ2 on PDAC. By mining of The Cancer Genome Atlas (TCGA) database, we found that FEZ2 was upregulated in PDAC tissues and FEZ2 expression was negatively regulated by its methylation. Moreover, high expression and low methylation of FEZ2 correlated with poor prognosis in PDAC patients. Besides, we found that FEZ2 could promote PDAC cells proliferation, migration and 5-FU resistance in vitro. Furthermore, Gene pathway enrichment analysis demonstrated a positive correlation between Wnt signaling activation and FEZ2 expression in PDAC patients. Western blot showed that FEZ2 knockdown significantly suppressed ß-catenin expression. Collectively, our finding revealed that FEZ2 functioned as a potential oncogene on PDAC progression and migration, and the expression of FEZ2 had guidance value for the treatment and chemotherapy program of PDAC patients.

Risk factors and risk nomogram model of reoperation for hemorrhages after severe traumatic brain injury craniotomy.

Objective: This study aimed to explore the risk factors associated with reoperation for postoperative hemorrhages after severe traumatic brain injury (sTBI) craniotomy and establish a risk nomogram model. Methods: A retrospective case-control study was performed. Overall, 367 patients who were diagnosed with sTBI and fulfilled the inclusion criteria were enrolled from the Department of Neurosurgery of the Affiliated Hospital of Zunyi Medical University between January 2015 and December 2020. They were divided into a reoperation group and a non-reoperation group according to whether they underwent reoperation for hemorrhages. Using univariate binary logistic regression analysis, the possible risk factors were screened. Subsequently, the independent risk factors of reoperation for postoperative hemorrhages were screened using the forward step method of multivariate binary logistic regression analysis, and a corresponding nomogram model was constructed. The receiver operative characteristic (ROC) curve was used to evaluate the reliability of the model. Finally, 30% of the data were randomly selected for internal verification of the model. Results: The reoperation rate for hemorrhage after sTBI emergency craniotomy was 14.71% (54/367); multivariate logistic regression analysis showed that multiple hemorrhages (odds ratio [OR] = 4.38, 95% confidence interval [CI]: 1.815-10.587, p = 0.001), day or night surgery (OR = 0.26, 95% CI: 0.119-0.547, p < 0.001), operation duration (OR = 0.74, 95% CI: 0.119-0.547, p < 0.025), and abnormal intraoperative blood pressure fluctuation (OR = 4.15, 95% CI: 2.090-8.245, p < 0.001) were statistically significant. The sensitivity and specificity of the nomogram model were 0.815 and 0.661, respectively, and the area under ROC curve was 0.76 (95% CI: 0.705-0.833). Internal verification showed that the area under the ROC curve was 0.783 (95% CI: 0.683-0.883). Conclusions: Taken together, the results of our study reveal that multiple preoperative intracranial hemorrhages, day and night operation, operation duration, and abnormal fluctuation of intraoperative blood pressure were independent risk factors for postoperative bleeding and reoperation for sTBI. Through the analysis of the influencing factors, a prediction model for the risk of bleeding and reoperation after craniocerebral trauma was developed. Compared with other relevant studies, this prediction model has good prediction efficiency and can be used to predict the occurrence of bleeding and reoperation after sTBI in patients.

Development and validation of a ferroptosis-related prognostic model in pancreatic cancer.

BACKGROUND: The purpose of this study was to identify ferroptosis-related genes (FRGs) associated with the prognosis of pancreatic cancer and to construct a prognostic model based on FRGs. METHODS: Based on pancreatic cancer data obtained from The Cancer Genome Atlas database, we established a prognostic model from 232 FRGs. A nomogram was constructed by combining the prognostic model and clinicopathological features. Gene Expression Omnibus datasets and tissue samples obtained from our center were utilized to validate the model. The relationship between risk score and immune cell infiltration was explored by CIBERSORT and TIMER. RESULTS: The prognostic model was established based on four FRGs (ENPP2, ATG4D, SLC2A1 and MAP3K5), and the risk score was demonstrated to be an independent risk factor in pancreatic cancer (HR 1.648, 95% CI 1.335-2.035, p < 0.001). Based on the median risk score, patients were divided into a high-risk group and a low-risk group. The low-risk group had a better prognosis than the high-risk group. In the high-risk group, patients treated with chemotherapy had a better prognosis. The nomogram showed that the model was the most important element. Gene set enrichment analysis identified three key pathways, namely, TGFß signaling, HIF signaling pathway and the adherens junction. The prognostic model may be associated with infiltration of immune cells such as M0 macrophages, M1 macrophages, CD4 + T cells and CD8 + T cells. CONCLUSION: The ferroptosis-related prognostic model can be employed to predict the prognosis of pancreatic cancer. Ferroptosis is an important marker, and immunotherapy may be a potential therapeutic target for pancreatic cancer.

Effect of fibulin-5 on aldosterone-induced apoptosis in human ascending aortic smooth muscle cells.

The aim of the current study was to investigate the effect of aldosterone on apoptosis in human aortic smooth muscle cells (HA-VSMC) and to determine the role of fibulin-5 in the aldosterone-induced apoptosis of HA-VSMC cells. Through the construction of a fibulin-5 eukaryotic overexpression vector and a short hairpin RNA interference plasmid, fibulin-5 was overexpressed and silenced, respectively. The role of fibulin-5 in the aldosterone-induced apoptosis of HA-VSMC was subsequently determined. The overexpression of fibulin-5 inhibited the apoptosis of cells, particularly at low concentrations of aldosterone; a smaller effect on apoptosis was induced by high concentrations of aldosterone. fibulin-5 knockdown promoted the apoptosis of cells induced by high concentrations of aldosterone but had a smaller effect on the apoptosis of cells induced by low concentrations of aldosterone. Therefore, the results of the current study indicate that fibulin-5 inhibits the aldosterone-induced apoptosis of HA-VSMC cells and that this effect may be altered by changing the aldosterone concentration.