The value of a neural network based on multi-scale feature fusion to ultrasound images for the differentiation in thyroid follicular neoplasms.

OBJECTIVE: The objective of this research was to create a deep learning network that utilizes multiscale images for the classification of follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) through preoperative US. METHODS: This retrospective study involved the collection of ultrasound images from 279 patients at two tertiary level hospitals. To address the issue of false positives caused by small nodules, we introduced a multi-rescale fusion network (MRF-Net). Four different deep learning models, namely MobileNet V3, ResNet50, DenseNet121 and MRF-Net, were studied based on the feature information extracted from ultrasound images. The performance of each model was evaluated using various metrics, including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, F1 value, receiver operating curve (ROC), area under the curve (AUC), decision curve analysis (DCA), and confusion matrix. RESULTS: Out of the total nodules examined, 193 were identified as FTA and 86 were confirmed as FTC. Among the deep learning models evaluated, MRF-Net exhibited the highest accuracy and area under the curve (AUC) with values of 85.3% and 84.8%, respectively. Additionally, MRF-Net demonstrated superior sensitivity and specificity compared to other models. Notably, MRF-Net achieved an impressive F1 value of 83.08%. The curve of DCA revealed that MRF-Net consistently outperformed the other models, yielding higher net benefits across various decision thresholds. CONCLUSION: The utilization of MRF-Net enables more precise discrimination between benign and malignant thyroid follicular tumors utilizing preoperative US.

Nucleosome assembly protein 1 like 1 (NAP1L1) promotes cardiac fibrosis by inhibiting YAP1 ubiquitination and degradation.

Myocardial fibrosis post myocardial infarction (MI) is characterized by abnormal extracellular matrix (ECM) deposition and cardiac dysfunction could finally develop into serious heart disease, like heart failure. Lots of regulating factors involved in this pathological process have been reported while the specific mediators and underlying mechanisms remain to need to be further investigated. As part of the NAP1 family, Nucleosome assembly protein 1 like 1 (NAP1L1) is expressed in a wide variety of tissues. Here, we report that NAP1L1 is a significant regulator of cardiac fibrosis and is upregulated in ischemic cardiomyopathy patient hearts. Enhanced expression of NAP1L1 can promote cardiac fibroblasts (CFs) proliferation, migration, and differentiation into myofibroblasts. In contrast, loss of NAP1L1 decreased fibrosis-related mRNA and protein levels, inhibited the trans-differentiation, and blunted migration and proliferation of CFs after Transforming Growth Factorß1（TGF-ß1）stimulation. In vivo, NAP1L1 knockout mice enhanced cardiac function and reduced fibrosis area in response to MI stimuli. Mechanically, NAP1L1 binding to Yes-associated protein 1 (YAP1) protein influences its stability, and silencing NAP1L1 can inhibit YAP1 expression by promoting its ubiquitination and degradation in CFs. Collectively, NAP1L1 could potentially be a new therapeutic target for various cardiac disorders, including myocardial fibrosis.

Systematic analyses identify the anti-fibrotic role of lncRNA TP53TG1 in IPF.

Long non-coding RNA (lncRNA) was reported to be a critical regulator of cellular homeostasis, but poorly understood in idiopathic pulmonary fibrosis (IPF). Here, we systematically identified a crucial lncRNA, p53-induced long non-coding RNA TP53 target 1 (TP53TG1), which was the dysregulated hub gene in IPF regulatory network and one of the top degree genes and down-regulated in IPF-drived fibroblasts. Functional experiments revealed that overexpression of TP53TG1 attenuated the increased expression of fibronectin 1 (Fn1), Collagen 1α1, Collagen 3α1, ACTA2 mRNA, Fn1, and Collagen I protein level, excessive fibroblasts proliferation, migration and differentiation induced by TGF-ß1 in MRC-5 as well as PMLFs. In vivo assays identified that forced expression of TP53TG1 by adeno-associated virus 5 (AAV5) not only prevented BLM-induced experimental fibrosis but also reversed established lung fibrosis in the murine model. Mechanistically, TP53TG1 was found to bind to amount of tight junction proteins. Importantly, we found that TP53TG1 binds to the Myosin Heavy Chain 9 (MYH9) to inhibit its protein expression and thus the MYH9-mediated activation of fibroblasts. Collectively, we identified the TP53TG1 as a master suppressor of fibroblast activation and IPF, which could be a potential hub for targeting treatment of the disease.

Critical role of PAFR/YAP1 positive feedback loop in cardiac fibrosis.

Aberrant activation of cardiac fibroblasts is the main cause and character of cardiac fibrosis, and inhibition of cardiac fibrosis becomes a promising treatment for cardiac diseases. Platelet-activating factor (PAF) and Hippo pathway is recently recognized as key signaling mechanisms in cardiovascular diseases. In this study we explored the potential roles of PAF and Hippo signaling pathway in cardiac fibrosis. Myocardial infarction (MI) was induced in mice by left anterior descending artery ligation. After 28 days, the mice were sacrificed, and the hearts were collected for analyses. We showed that PAF receptor (PAFR) and yes-associated protein 1 (YAP1, a key effector in the Hippo pathway) were significantly increased in the heart of MI mice. Increased expression of PAFR and YAP1 was also observed in angiotensin II (Ang II)-treated mouse cardiac fibroblasts. In mouse cardiac fibroblasts, forced expression of YAP1 increased cell viability, resulted in collagen deposition and promoted fibroblast-myofibroblast transition. We showed that PAF induced fibrogenesis through activation of YAP1 and promoted its nuclear translocation via interacting with PAFR, while YAP1 promoted the expression of PAFR by binding to and activating transcription factor TEAD1. More importantly, silencing PAFR or YAP1 by shRNA, or using transgenic mice to induce the conditional deletion of YAP1 in cardiac fibroblasts, impeded cardiac fibrosis and improved cardiac function in MI mice. Taken together, this study elucidates the role and mechanisms of PAFR/YAP1 positive feedback loop in cardiac fibrosis, suggesting a potential role of this pathway as novel therapeutic targets in cardiac fibrosis.

Prognostic and clinicopathological significance of miR-638 in cancer patients: A meta-analysis.

INTRODUCTION: MiR-638 is believed to be involved in human cancers. However, the prognostic value of miR-638 in human carcinomas is controversial and inconclusive. Therefore, we conducted this meta-analysis to investigate the association between miR-638 expression and clinical outcomes in the patients with various cancers. METHODS: We searched Pubmed, Embase, Wanfang, and the China National Knowledge Infrastructure (CNKI) up to September 1, 2020 to identify relevant studies. Hazard ratios (HRs) and odds ratios (ORs) with 95% confidence intervals (CIs) were used to correlate expression of miR-638 with prognosis and clinicopathological features. RESULTS: A total of 18 studies involving 1886 patients were included in the meta-analysis. The results revealed that low miR-638 expression was significantly correlated with poor overall survival (OS) (HR = 2.09, 95% CI: 1.46-2.98, P < .001), but not with disease-free survival (DFS) (HR = 1.71, 95% CI: 0.31-9.56, P = .540). Subgroup analysis found that low miR-638 expression was associated with worse OS in patients with digestive system cancer (HR = 2.47, 95% CI: 1.85-3.30, P < .001), the reported directly from articles group (HR = 2.12, 95% CI: 1.34-3.33, P < .001), survival curves group (HR = 2.02, 95% CI: 1.07-3.80, P = .029), in studies with sample size ≥100 (HR = 2.12, 95% CI: 1.34-3.35, P = .001), and in studies with sample size <100 (HR = 2.02, 95%CI: 1.09-3.75, P = .025). Moreover, cancer patients with low miR-638 expression were prone to tumor size (OR = 1.47, 95% CI: 1.03-2.09, P = .035), earlier lymph node metastasis (present vs absent, OR = 2.26, 95% CI: 1.63-3.14, P < .001), earlier distant metastasis (present vs absent, OR = 2.60, 95% CI: 1.45-4.67, P < .001), TNM stage (III-IV vs I-II, OR = 2.01, 95% CI: 1.35-2.99, P = .001), and portal vein invasion (present vs absent, OR = 4.39, 95% CI:2.23-8.64, P < .001), but not associated with age, gender, tumor differentiation, and vascular invasion. CONCLUSIONS: MiR-638 may serve as a promising indicator in the prediction of prognosis and clinicopathological features in patients with different kinds of cancers.

Prognostic and clinicopathological significance of MicroRNA-153 in human cancers: A meta-analysis.

BACKGROUND: Several studies have explored the prognostic value of MicroRNA-153 (miR-153) in various cancers, but obtained inconsistent results. Thus, we conducted a meta-analysis to assess the prognostic significance of miR-153 for patients with cancer. METHODS: Eligible studies were identified by searching the online databases Pubmed, Embase, Web of Science, Medline,and the China National Knowledge Infrastructure (CNKI) up to March 2020. Hazard ratios (HRs) with 95% CIs and were calculated to clarify the correlation between miR-153 expression and prognosis of different cancers. Odds ratios (ORs) with 95% CI were selected to appraise the correlation between miR-153 with clinicopathological characteristics of cancer patients. RESULTS: In total, 933 patients from 11 articles were enrolled in our meta-analysis. The results revealed that low miR-153 expression was significantly correlated with poor overall survival (OS) (HR = 2.45, 95% CI = 1.66-3.63, P < .001), but not with disease-free survival (DFS) (HR = 1.67, 95% CI = 0.45-6.19, P = .442). Subgroup analysis found that low miR-153 expression was associated with worse OS in the reported directly from articles group (HR = 2.67, 95% CI: 1.32-5.37, P = .006), survival curves group (HR = 2.10, 95% CI: 1.56-2.84, P < .001), digestive system tumor (HR = 2.76, 95% CI: 1.73-4.41, P < .001), and breast cancer (HR = 4.01, 95% CI: 1.46-11.04, P = .007).Moreover, cancer patients with low miR-153 expression were prone to poor tumor differentiation(poor vs well+moderate, OR = 2.41, 95% CI = 1.52-3.82, P < .001), earlier lymph node metastasis (present vs absent, OR = 2.19, 95% CI = 1.12-4.25, P = .021) and earlier distant metastasis (present vs absent,OR = 8.24, 95% CI = 2.93-23.21, P < .001), but not associated with age,gender and TNM stage. CONCLUSIONS: This meta-analysis indicated that low miR-153 expression is associated with poor prognosis. miR-153 may serve as an effective predictive biomarker for tumor prognosis, especially for digestive system tumor and breast cancer.