Deep-learning CT imaging algorithm to detect usual interstitial pneumonia pattern in patients with systemic sclerosis-associated interstitial lung disease: association with disease progression and survival.

OBJECTIVES: Interstitial lung disease (ILD) is the most common cause of death in patients with systemic sclerosis (SSc), although disease behavior is highly heterogeneous. While a usual interstitial pneumonia (UIP) pattern is associated with worse survival in other ILDs, its significance in SSc-ILD is unclear. We sought to assess the prognostic utility of a deep-learning HRCT algorithm of UIP probability in SSc-ILD. METHODS: Patients with SSc-ILD were included if HRCT images, concomitant lung function tests, and follow-up data were available. We used the Systematic Objective Fibrotic Imaging analysis Algorithm (SOFIA), a convolution neural network algorithm which provides probabilities of a UIP pattern on HRCT images. These were converted into the Prospective Investigation of Pulmonary Embolism Diagnosis (PIOPED)-based UIP probability categories. Decline in lung function was assessed by mixed-effect model analysis and relationship with survival by Cox proportional hazards analysis. RESULTS: 522 patients were included in the study. 19.5% were classified as UIP not in the differential, 53.5% as low probability of UIP, 25.7% as intermediate probability of UIP, and 1.3% as high probability of UIP. A higher likelihood of UIP probability expressed as PIOPED categories was associated with worse baseline FVC, as well as with decline in FVC (p= 0.008), and worse 15-year survival (p= 0.001), both independently of age, gender, ethnicity, smoking history, and baseline FVC or Goh et al. staging system. CONCLUSION: A higher probability of a SOFIA-determined UIP pattern is associated with more advanced ILD, disease progression, and worse survival, suggesting that it may be a useful prognostic marker in SSc-ILD.

Large-Kernel Attention for 3D Medical Image Segmentation.

Automated segmentation of multiple organs and tumors from 3D medical images such as magnetic resonance imaging (MRI) and computed tomography (CT) scans using deep learning methods can aid in diagnosing and treating cancer. However, organs often overlap and are complexly connected, characterized by extensive anatomical variation and low contrast. In addition, the diversity of tumor shape, location, and appearance, coupled with the dominance of background voxels, makes accurate 3D medical image segmentation difficult. In this paper, a novel 3D large-kernel (LK) attention module is proposed to address these problems to achieve accurate multi-organ segmentation and tumor segmentation. The advantages of biologically inspired self-attention and convolution are combined in the proposed LK attention module, including local contextual information, long-range dependencies, and channel adaptation. The module also decomposes the LK convolution to optimize the computational cost and can be easily incorporated into CNNs such as U-Net. Comprehensive ablation experiments demonstrated the feasibility of convolutional decomposition and explored the most efficient and effective network design. Among them, the best Mid-type 3D LK attention-based U-Net network was evaluated on CT-ORG and BraTS 2020 datasets, achieving state-of-the-art segmentation performance when compared to avant-garde CNN and Transformer-based methods for medical image segmentation. The performance improvement due to the proposed 3D LK attention module was statistically validated.

FDA Approval Summary: Fruquintinib for the Treatment of Refractory Metastatic Colorectal Cancer.

On November 8, 2023, the FDA approved fruquintinib, an inhibitor of vascular endothelial growth factor receptor (VEGFR)-1, -2, and -3, for the treatment of patients with metastatic colorectal cancer (mCRC) who have been previously treated with fluoropyrimidine-, oxaliplatin-, and irinotecan-based chemotherapy, an anti-VEGF therapy, and if RAS wild-type and medically appropriate, an anti-EGFR therapy. Approval was based on Study FRESCO-2, a globally conducted, double-blind, placebo-controlled randomized trial. The primary endpoint was overall survival (OS). The key secondary endpoint was progression-free survival. A total of 691 patients were randomly assigned (461 and 230 into the fruquintinib and placebo arms, respectively). Fruquintinib provided a statistically significant improvement in OS with a hazard ratio (HR) of 0.66 [95% confidence interval (CI), 0.55, 0.80; P < 0.001]. The median OS was 7.4 months (95% CI, 6.7, 8.2) in the fruquintinib arm and 4.8 months (95% CI, 4.0, 5.8) for the placebo arm. Adverse events observed were generally consistent with the known safety profile associated with the inhibition of VEGFR. The results of FRESCO-2 were supported by the FRESCO study, a double-blind, single-country, placebo-controlled, randomized trial in patients with refractory mCRC who have been previously treated with fluoropyrimidine-, oxaliplatin-, and irinotecan-based chemotherapy. In FRESCO, the OS HR was 0.65 (95% CI, 0.51, 0.83; P < 0.001). FDA concluded that the totality of the evidence from FRESCO-2 and FRESCO supported an indication for patients with mCRC with prior treatment with fluoropyrimidine, oxaliplatin-, and irinotecan-based chemotherapy, an anti-VEGF biological therapy, and if RAS wild-type and medically appropriate, an anti-EGFR therapy.

Preoperative anemia: impact on short- and long-term outcomes following curative-intent resection of gastroenteropancreatic neuroendocrine tumors.

BACKGROUND: The effect of preoperative anemia on clinical outcomes of patients undergoing resection of gastroenteropancreatic neuroendocrine tumors (GEP-NETs) has not been previously investigated. This study aimed to characterize how preoperative anemia affected short- and long-term outcomes of patients undergoing curative-intent resection of GEP-NETs. METHODS: Patients who underwent curative-intent resection for GEP-NETs between January 1990 and December 2020 were identified from 8 major institutions. The last preoperative hemoglobin level was recorded; anemia was defined as <13.5 g/dL in males or <12.0 g/dL in females based on the guides of the American Society of Hematology. The effect of anemia on postoperative outcomes was assessed on uni- and multivariate analyses. RESULTS: Among 1559 patients, the median age was 58 years (IQR, 48-66), and roughly one-half of the cohort was male (796 [51.1%]). Most patients had a pancreatic tumor (1040 [66.7%]), followed by small bowel (259 [16.6%]), duodenum (103 [6.6%]), stomach (66 [4.2%]), appendix (53 [3.4%]), and other locations (38 [2.6%]). The median preoperative hemoglobin level was 13.4 g/dL (IQR, 12.2-14.5). Overall, 101 (6.7%) and 119 (8.5%) patients received an intra- or postoperative packed red blood cell (pRBC) transfusion, respectively. A total of 972 patients (44.5%) experienced a postoperative complication. Although the overall incidence of complications was no different among patients who did (anemic: 48.7%) vs patients who did not (nonanemic: 47.3%) have anemia (P = .597), patients with preoperative anemia were more likely to develop a major (Clavien-Dindo grade ≥IIIa: 48.9% [anemic] vs 38.0% [nonanemic]; P = .006) and multiple (≥3 types of complications: 32.2% [anemic] vs 19.7% [anemic]; P < .001) complications. Of note, 1-, 3-, and 5-year overall survival (OS) rates were 96.7%, 90.5%, and 86.6%, respectively. On multivariable analysis, anemia (hazard ratio, 2.0; 95% CI, 1.2-3.2; P = .006) remained associated with worse OS; postoperative pRBC transfusion was associated with an OS (5-year OS: 75.0% vs 87.7%; P = .017) and recurrence-free survival (RFS; 5-year RFS: 66.9% vs 76.5%; P = .047). CONCLUSION: Preoperative anemia was commonly identified in roughly 1 in 3 patients who underwent curative-intent resection for GEP-NETs. Preoperative anemia was strongly associated with a higher risk of postoperative morbidity and worse long-term outcomes.

IKBKE promotes the ZEB2-mediated EMT process by phosphorylating HMGA1a in glioblastoma.

IKBKE (Inhibitor of Nuclear Factor Kappa-B Kinase Subunit Epsilon) is an important oncogenic protein in a variety of tumors, which can promote tumor growth, proliferation, invasion and drug resistance, and plays a critical regulatory role in the occurrence and progression of malignant tumors. HMGA1a (High Mobility Group AT-hook 1a) functions as a cofactor for proper transcriptional regulation and is highly expressed in multiple types of tumors. ZEB2 (Zinc finger E-box Binding homeobox 2) exerts active functions in epithelial mesenchymal transformation (EMT). In our current study, we confirmed that IKBKE can increase the proliferation, invasion and migration of glioblastoma cells. We then found that IKBKE can phosphorylate HMGA1a at Ser 36 and/or Ser 44 sites and inhibit the degradation process of HMGA1a, and regulate the nuclear translocation of HMGA1a. Crucially, we observed that HMGA1a can regulate ZEB2 gene expression by interacting with ZEB2 promoter region. Hence, HMGA1a was found to promote the ZEB2-related metastasis. Consequently, we demonstrated that IKBKE can exert its oncogenic functions via the IKBKE/HMGA1a/ZEB2 signalling axis, and IKBKE may be a prominent biomarker for the treatment of glioblastoma in the future.

Region-based evidential deep learning to quantify uncertainty and improve robustness of brain tumor segmentation.

Despite recent advances in the accuracy of brain tumor segmentation, the results still suffer from low reliability and robustness. Uncertainty estimation is an efficient solution to this problem, as it provides a measure of confidence in the segmentation results. The current uncertainty estimation methods based on quantile regression, Bayesian neural network, ensemble, and Monte Carlo dropout are limited by their high computational cost and inconsistency. In order to overcome these challenges, Evidential Deep Learning (EDL) was developed in recent work but primarily for natural image classification and showed inferior segmentation results. In this paper, we proposed a region-based EDL segmentation framework that can generate reliable uncertainty maps and accurate segmentation results, which is robust to noise and image corruption. We used the Theory of Evidence to interpret the output of a neural network as evidence values gathered from input features. Following Subjective Logic, evidence was parameterized as a Dirichlet distribution, and predicted probabilities were treated as subjective opinions. To evaluate the performance of our model on segmentation and uncertainty estimation, we conducted quantitative and qualitative experiments on the BraTS 2020 dataset. The results demonstrated the top performance of the proposed method in quantifying segmentation uncertainty and robustly segmenting tumors. Furthermore, our proposed new framework maintained the advantages of low computational cost and easy implementation and showed the potential for clinical application.

Fuzzy Attention Neural Network to Tackle Discontinuity in Airway Segmentation.

Airway segmentation is crucial for the examination, diagnosis, and prognosis of lung diseases, while its manual delineation is unduly burdensome. To alleviate this time-consuming and potentially subjective manual procedure, researchers have proposed methods to automatically segment airways from computerized tomography (CT) images. However, some small-sized airway branches (e.g., bronchus and terminal bronchioles) significantly aggravate the difficulty of automatic segmentation by machine learning models. In particular, the variance of voxel values and the severe data imbalance in airway branches make the computational module prone to discontinuous and false-negative predictions, especially for cohorts with different lung diseases. The attention mechanism has shown the capacity to segment complex structures, while fuzzy logic can reduce the uncertainty in feature representations. Therefore, the integration of deep attention networks and fuzzy theory, given by the fuzzy attention layer, should be an escalated solution for better generalization and robustness. This article presents an efficient method for airway segmentation, comprising a novel fuzzy attention neural network (FANN) and a comprehensive loss function to enhance the spatial continuity of airway segmentation. The deep fuzzy set is formulated by a set of voxels in the feature map and a learnable Gaussian membership function. Different from the existing attention mechanism, the proposed channel-specific fuzzy attention addresses the issue of heterogeneous features in different channels. Furthermore, a novel evaluation metric is proposed to assess both the continuity and completeness of airway structures. The efficiency, generalization, and robustness of the proposed method have been proved by training on normal lung disease while testing on datasets of lung cancer, COVID-19, and pulmonary fibrosis.

Fluorinated Siloxane Modified Layered Double Hydroxide Sealing Film to Enhance the Corrosion Resistance of Anodic Oxide Film of Fricition Stir Welding Joint of Aluminum Alloys.

Aluminum alloys and their welding structures have been widely used in aviation, aerospace, automobiles, ships, and other industrial fields. The non-uniform nature of welding structures of aluminum alloys causes intractable corrosion problems. Anodizing and subsequent sealing processes are common and effective methods to improve the corrosion resistance of welding structures. However, traditional sealing processes like hot water sealing and potassium dichromate sealing are criticized due to energy consumption or toxicity. In this work, a layered double hydroxide (LDH) sealing process with subsequent fluorinated siloxane modification is proposed to improve the corrosion resistance of the anodic oxide film of friction stir welding joints of typical aluminum alloys. The obtained sealing film with typical lamelliform structures of LDH grows well at the defects of oxidation film and also smoothens the sample surface. The hydrophobicity of the film can separate the corrosive medium from the sample surface and further enhance corrosion resistance. As a result, the corrosion current of the welded sample in 3.5 wt.% NaCl solution plummets about 3~4 orders of magnitude compared to the initial state without anodizing, indicating superior corrosion resistance brought by this method.

Systematic pan­cancer analysis identifies CDC45 as having an oncogenic role in human cancers.

Cell division cycle 45 (CDC45) is an essential protein required for the initiation of DNA replication. In the present study, the role of CDC45 across 33 cancers was systematically investigated. It was observed that the expression of CDC45 was significantly upregulated in most cancers, exhibiting a marked negative correlation with the overall survival. Next, there was no significant difference in prognosis between the genomically altered and unaltered groups with respect to clinical outcomes. A decreased level of CDC45 at the DNA promoter region was also identified in several cancers. Furthermore, CDC45 expression was associated with the levels of tumor­infiltrating immune cells in some specific cancer types. In addition, CDC45 was associated with m6A methylation, and CDC45 expression was primarily positively correlated with 'writers' and 'readers' in various cancers, particularly HNRNPC, RBM15 and YTHDC1. Gene enrichment analysis was also performed. In addition, the AUC of each cancer with respect to its 1­, 3­, and 5­year survival rates were explored. Finally, CCK­8 assays, EdU assays and cell cycle analysis were conducted. In conclusion, the present study demonstrated that CDC45 may be a potential biomarker and target for cancer treatment.

Bioinformatics analysis of potential glioblastoma circular RNA sponge network.

Background: Circular RNA is emerging functional molecule for glioblastoma. However, the function and regulatory of circular RNA (circRNA) remains unclear. In this study, the circRNA sequencing and array data of glioblastoma were analyzed by multiple bioinformatics methods to establish a potential molecular sponge mechanism regulation network. Methods: Gene Expression Omnibus datasets were used to extract circRNAs. CircInteractome was used to predict microRNAs binding to circRNAs. Chinese Glioma Gene Atlas database was used to screen the microRNAs with expression and survival trends. MiRabel database was used to predict potential gene targets of microRNAs. The Cancer Genome Atlas database was used to screen the gene targets of sponge network. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis were to explain the gene targets functions. R software, Cytoscape software and Bioinformatics website were used to establish the network and visualize the results. Results: Hsa_circ_0000219, hsa_circ_0001073 and hsa_circ_0070700 were selected from more than 2000 differentially expressed circRNAs of Gene Expression Omnibus Series (GSE) GSE146463, GSE92322 and GSE86202 datasets. Hsa-miR-1248 and hsa-miR-1290 were up regulated and related to glioblastoma poor prognosis. Targets of these microRNAs including ARHGEF7, CELA2b, RNF11, YPEL1 and ZNF37a were also screened via expression and survival data. Gene targets function were mainly enriched in signal transduction, cell plasma membrane, ATP binding and calcium signaling pathway. Conclusions: A circRNA molecular sponge regulatory network including hsa-miR-1248 and hsa-miR-1290 has been established. In this network, hsa_circ_0001073, hsa_circ_0070700, hsa_circ_0000219, hsa-miR-1248, hsa-miR-1290, and RNF11 may have the potential being emerging glioblastoma therapeutic targets. However, their function and significance for glioblastoma need further experiments to verify.

Pathogenesis of Liver Fibrosis and Its TCM Therapeutic Perspectives.

Liver fibrosis is a pathological process of abnormal tissue proliferation in the liver caused by various pathogenic factors, which will further develop into cirrhosis or even hepatocellular carcinoma if liver injury is not intervened in time. As a diffuse progressive liver disease, its clinical manifestations are mostly excessive deposition of collagen-rich extracellular matrix resulting in scar formation due to liver injury. Hepatic fibrosis can be caused by hepatitis B and C, fatty liver, alcohol, and rare diseases such as hemochromatosis. As the metabolic center of the body, the liver regulates various vital activities. During the development of fibrosis, it is influenced by many other factors in addition to the central event of hepatic stellate cell activation. Currently, with the increasing understanding of TCM, the advantages of TCM with multiple components, pathways, and targets have been demonstrated. In this review, we will describe the factors influencing liver fibrosis, focusing on the effects of cells, intestinal flora, iron death, signaling pathways, autophagy and angiogenesis on liver fibrosis, and the therapeutic effects of herbal medicine on liver fibrosis.

Combining multi-dimensional molecular fingerprints to predict the hERG cardiotoxicity of compounds.

Recently, drug toxicity has become a critical problem with heavy medical and economic burdens. Acquired long QT syndrome (acLQTS) is an acquired cardiac ion channel disease caused by drugs blocking the hERG channel. Therefore, it is necessary to avoid cardiotoxicity in drug design, and computer models have been widely used to fix this predicament. In this study, we collected a hERG inhibitor dataset containing 8671 compounds, and then, these compounds were featurized by traditional molecular fingerprints (including Baseline2D, ECFP4, PropertyFP, and 3DFP) and the newly proposed molecular dynamics fingerprint (MDFP). Subsequently, regression prediction models were established by using four machine learning algorithms based on these fingerprints and the combined multi-dimensional molecular fingerprints (MultiFP). After cross-validation and independent test dataset validation, the results show that the best model was built by the consensus of four algorithms with MultiFP, and this model bests recently published methods in terms of hERG cardiotoxicity prediction with a RMSE of 0.531 and a R2 of 0.653 on the test dataset. Feature importance analysis and correlation analysis identified some novel structural features and molecular dynamics features that are highly associated with the hERG inhibition of compounds. Our findings provide new insight into multi-dimensional molecular fingerprints and consensus models for hERG cardiotoxicity prediction.

The function of natural compounds in important anticancer mechanisms.

The existence of malignant tumors has been a threat to human life, health, and safety. Although the rapid development of radiotherapy, drug therapy, surgery, and local therapy has improved the quality of life of tumor patients, there are still some risks. Natural compounds are widely used in cancer because they are easy to obtain, have a good curative effects and have no obvious side effects, and play a vital role in the prevention and treatment of various cancers. Phenolic, flavonoids, terpenoids, alkaloids, and other natural components of traditional Chinese medicine have certain anti-tumor activities, which can promote apoptosis, anti-proliferation, anti-metastasis, inhibit angiogenesis, change the morphology of cancer cells and regulate immune function, etc., and have positive effects on breast cancer, liver cancer, lung cancer, gastric cancer, rectal cancer and so on. To better understand the effects of natural compounds on cancer, this paper screened out four important pathways closely related to cancer, including cell death and immunogenic cell death, immune cells in the tumor microenvironment, inflammation and related pathways and tumor metastasis, and systematically elaborated the effects of natural compounds on cancer.

CBX2 Induces Glioma Cell Proliferation and Invasion Through the Akt/PI3K Pathway.

Glioma is the most common primary intracranial tumor. Abnormal expression of CBX2 (ChromoBox2) is associated with tumorigenesis and tumor development. TCGA data in UALCAN showed that CBX2 was overexpressed in glioma tissue. To confirm the role of CBX2 in glioma, we regulated the level of CBX2 and conducted colony formation, Transwell, and CCK-8 assays to verify the effect of CBX2. The results showed that CBX2 knockdown reduced glioma cell proliferation and invasion and that the cells were less tumorigenic. CBX2 overexpression induced glioma cell proliferation and invasion and glioma stem cell self-renewal. The animal experiments showed that CBX2 knockdown inhibited glioma growth and improved survival time. CBX2 knockdown inhibited activation of the Akt/PI3K pathway. epidermal growth factor rescued the effects of CBX2. CBX2 could induce the growth and invasion of glioma cells via the Akt/PI3K pathway.

Pan-cancer analysis indicates that MYBL2 is associated with the prognosis and immunotherapy of multiple cancers as an oncogene.

MYBL2 has been demonstrated to be an oncogene in some cancers, but there is no pan-cancer analysis at the macro level. We used multiple online or offline bioinformatic tools to examine the effects of MYBL2 in human cancers. We first identified that MYBL2 was highly expressed and related to the stage and grade of most cancers. The results of survival analysis from two databases showed that high MYBL2 expression was positively correlated with a poor prognosis for most cancer patients. We observed a significant difference in the promoter methylation level of MYBL2 in cancers such as colon adenocarcinoma and liver hepatocellular carcinoma versus normal controls. We found that MYBL2 can affect the tumor immune microenvironment by influencing the immune infiltration level and expression level of CD4+ T cells, CD8+ T cells, cancer-associated fibroblasts (CAFs) and immune checkpoint-associated cells. Functional enrichment analysis of MYBL2 identified that MYBL2 can play a crucial role in cancers by regulating spliceosomes, DNA replication and the cell cycle. Moreover, we verified the function of MYBL2 in three cancer cells of glioma, breast cancers and liver cancers, and the results showed that MYBL2 can regulate the cell cycle and proliferation ability of cancers.

miRNA-451 regulates the NF-κB signaling pathway by targeting IKKß to inhibit glioma cell growth.

Glioblastoma multiforme (GBM) is associated with a poor prognosis, and effective treatments are lacking. Our previous studies have shown that miRNA-451 is closely related to the development and progression of glioma. miRNA-451 is a tumor suppressor whose expression is negatively correlated with the WHO grades of gliomas, but its specific mechanism is still unclear. Research shows that NF-κB is highly expressed in early malignant glioma, and thus, the NF-κB signaling pathway has become an important target for the treatment of malignant glioma. Activation of IKK is a critical step in the activation of the classical NF-κB pathway. By performing a bioinformatics analysis, we found that IKKß is a potential direct target of miRNA-451 in glioma. In this study, we transfected lentivirus expressing miRNA-451 to test the effect of miRNA-451 overexpression on malignant glioma cell lines and confirmed that IKKß is a target gene of miRNA-451 by luciferase assay. By targeting IKKß, MTT, cell invasion and wound-healing assays showed that cell proliferation, cell invasion and migration were significantly suppressed in the LV-miRNA-451 group. Western blotting results showed that the expression levels of IKKß, p-p65, MMP-2, MMP-9, Cyclin D1, p16 and PCNA were significantly decreased in the LV-miRNA-451 group. In vivo, miRNA-451 significantly decreased glioma cell growth, and the survival of BALB/c-A nude mice was significantly prolonged. Immunohistochemistry showed that p-p65, Cyclin D1 and Ki67 expression was significantly reduced in the LV-miRNA-451 group. Taken together, these results suggest that miRNA-451 could regulate the NF-κB signaling pathway by targeting IKKß, which inhibits glioma cell growth in vitro and in vivo. Therefore, this study may provide novel insight into miRNA-451-targeted therapy for glioma.

Production of Margarines Rich in Unsaturated Fatty Acids Using Oxidative-stable Vitamin C-Loaded Oleogel.

Vitamin C (VC)-loaded oleogel (VCOG) with corn oil and monoglyceride stearate was used to replace lipid phase of margarine completely. The oxidative stability of VCOG was evaluated at 60±1°C in a lightproof oven for 18 days and the result showed that VCOG peroxide (> 6 days) and p-anisidine value (> 4 days) was significantly lower than that of bulk oil and VC-free oleogel (p < 0.05). Then, the margarine containing 79.70% VCOG (VCOGM) was in comparison with four commercial butter in sensory and physical characteristic. Results showed that firmness, solid fat content and trans fatty acid of VCOGM were in the lowest values while unsaturated fatty acid and adhesiveness of VCOGM was in the highest values. Furthermore, VCOGM presented the similar springiness, cohesiveness, gumminess, score appearance, texture, taste and overall impression to some/all commercial butters selected in this research (p > 0.05). These results implied that VC-loaded oleogel was an excellent alternative of lipid phase in margarine which confirmed by 55% "definitely buy" and 25% "try once-then decide".

Feature Pyramid Nonlocal Network With Transform Modal Ensemble Learning for Breast Tumor Segmentation in Ultrasound Images.

Automated breast ultrasound image segmentation is essential in a computer-aided diagnosis (CAD) system for breast tumors. In this article, we present a feature pyramid nonlocal network (FPNN) with transform modal ensemble learning (TMEL) for accurate breast tumor segmentation in ultrasound images. Specifically, the FPNN fuses multilevel features under special consideration of long-range dependencies by combining the nonlocal module and feature pyramid network. Additionally, the TMEL is introduced to guide two iFPNNs to extract different tumor details. Two publicly available datasets, i.e., the Dataset-Cairo University and Dataset-Merge, were used for evaluation. The proposed FPNN-TMEL achieves a Dice score of 84.70% ± 0.53%, Jaccard Index (Jac) of 78.10% ± 0.48% and Hausdorff distance (HD) of 2.815 ± 0.016 mm on the Dataset-Cairo University, and Dice of 87.00% ± 0.41%, Jac of 79.16% ± 0.56%, and HD of 2.781±0.035 mm on the Dataset-Merge. Qualitative and quantitative experiments show that our method outperforms other state-of-the-art methods for breast tumor segmentation in ultrasound images. Our code is available at https://github.com/pixixiaonaogou/FPNN-TMEL.

LncRNA HAS2-AS1 Promotes Glioblastoma Proliferation by Sponging miR-137.

GBM (Glioblastoma multiform) is the most malignant tumor type of the central nervous system and has poor diagnostic and clinical outcomes. LncRNAs (Long non-coding RNAs) have been reported to participate in multiple biological and pathological processes, but their underlying mechanism remains poorly understood. Here, we aimed to explore the role of the lncRNA HAS2-AS1 (HAS2 antisense RNA 1) in GBM. GSE103227 was analyzed, and qRT-PCR was performed to measure the expression of HAS2-AS1 in GBM. FISH (Fluorescence in situ hybridization) was performed to verify the localization of HAS2-AS1. The interaction between HAS2-AS1 and miR-137 (microRNA-137) was predicted by LncBook and miRcode followed by dual-luciferase reporter assays, and the relationships among HAS2-AS1, miR-137 and LSD1 (lysine-specific demethylase 1) were assessed by WB (western blot) and qRT-PCR. Colony formation and CCK-8 (cell counting kit-8) assays were performed as functional tests. In vivo, nude mice were used to confirm the function of HAS2-AS1. HAS2-AS1 expression was upregulated in GBM cell lines, and HAS2-AS1 was localized mainly in the cytoplasm. In vitro, high HAS2-AS1 expression promoted proliferation, and knockdown of HAS2-AS1 significantly inhibited proliferation. Furthermore, HAS2-AS1 functioned as a ceRNA (competing endogenous RNA) of miR-137, leading to the disinhibition of its downstream target LSD1. The miR-137 level was downregulated by HAS2-AS1 overexpression and upregulated by HAS2-AS1 knockdown. In a subsequent study, LSD1 expression was negatively regulated by miR-137, while miR-137 reversed the LSD1 expression levels caused by HAS2-AS1. These results were further supported by the nude mouse tumorigenesis experiment; compared with xenografts with high HAS2-AS1 expression, the group with low levels of HAS2-AS1 exhibited suppressed proliferation and better survival. We conclude that lncRNA HAS2-AS1 promotes proliferation by functioning as a miR-137 decoy to increase LSD1 levels and thus might be a possible biomarker for GBM.

[Pollution Characteristics and Risk Assessment of Nitro Polycyclic Aromatic Hydrocarbons in PM2.5 of Nanjing, China].

Nitro polycyclic aromatic hydrocarbons (NPAHs) are important pollutants with carcinogenic effects present in PM2.5. To analyze the pollution characteristics and sources of NPAHs, 14 samples of PM2.5 were collected in Nanjing from November 2017 to March 2018. The results showed that, 2,8-dinitrodibenzothiophene (743 pg·m-3), 2, 7-dinitrofluorene (331 pg·m-3), 9-nitroanthracene (326 pg·m-3), 3-nitrofluoranthene (217 pg·m-3), and 1,8-dinitropyrene (193 pg·m-3) were dominant, and the detection concentrations notably varied between seasons; the highest concentrations occurred in winter (3082 pg·m-3) followed by autumn (1553 pg·m-3) and spring (1218 pg·m-3). The ratio of nitrofluoranthene and 1-nitropyrene concentrations, and 9-nitroanthracene and 1-nitropyrene concentrations, indicated that the main sources of NPAHs in the PM2.5 of Nanjing were photooxidation of polycyclic aromatic hydrocarbons and biomass burning. NPAHs were more typically associated with smaller particles, which further indicated that secondary formation is an important source. The current carcinogenic risk of NPAHs in PM2.5 in Nanjing is controllable, and dinitro-polycyclic aromatic hydrocarbons represent the highest level of risk. The data presented in this study provide important baseline information that can inform the management of risks associated with NPAHs in PM2.5 in Nanjing.