Search

Background: The key role of thrombospondin 1 (THBS1) in the pathogenesis of acute-on-chronic liver failure (ACLF) is unclear. Here, we present a transcriptome approach to evaluate THBS1 as a potential biomarker in ACLF disease pathogenesis. Methods: Biobanked peripheral blood mononuclear cells (PBMCs) from 330 subjects with hepatitis B virus (HBV)-related etiologies, including HBV-ACLF, liver cirrhosis (LC), and chronic hepatitis B (CHB), and normal controls (NC) randomly selected from the Chinese Group on the Study of Severe Hepatitis B (COSSH) prospective multicenter cohort underwent transcriptome analyses (ACLF = 20; LC = 10; CHB = 10; NC = 15); the findings were externally validated in participants from COSSH cohort, an ACLF rat model and hepatocyte-specific THBS1 knockout mice. Results: THBS1 was the top significantly differentially expressed gene in the PBMC transcriptome, with the most significant upregulation in ACLF, and quantitative polymerase chain reaction (ACLF = 110; LC = 60; CHB = 60; NC = 45) was used to verify that THBS1 expression corresponded to ACLF disease severity outcome, including inflammation and hepatocellular apoptosis. THBS1 showed good predictive ability for ACLF short-term mortality, with an area under the receiver operating characteristic curve (AUROC) of 0.8438 and 0.7778 at 28 and 90 days, respectively. Enzyme-linked immunosorbent assay validation of the plasma THBS1 using an expanded COSSH cohort subjects (ACLF = 198; LC = 50; CHB = 50; NC = 50) showed significant correlation between THBS1 with ALT and γ-GT (P = 0.01), and offered a similarly good prognostication predictive ability (AUROC = 0.7445 and 0.7175) at 28 and 90 days, respectively. ACLF patients with high-risk short-term mortality were identified based on plasma THBS1 optimal cut-off value (< 28 µg/ml). External validation in ACLF rat serum and livers confirmed the functional association between THBS1, the immune response and hepatocellular apoptosis. Hepatocyte-specific THBS1 knockout improved mouse survival, significantly repressed major inflammatory cytokines, enhanced the expression of several anti-inflammatory mediators and impeded hepatocellular apoptosis. Conclusions: THBS1 might be an ACLF disease development-related biomarker, promoting inflammatory responses and hepatocellular apoptosis, that could provide clinicians with a new molecular target for improving diagnostic and therapeutic strategies. [ABSTRACT FROM AUTHOR]

Purpose: Acute coronary syndrome (ACS) has a high incidence and mortality rate worldwide, which has a considerable negative impact on the global economy. This study aimed to identify a group of ACS patients at a high risk of recurrent adverse cardiac events using the plasma NLRP3 inflammasome. Patients and methods: ACS patients admitted to Liaocheng People's Hospital between June 2021 and March 2022 were enrolled in this study. Patients were divided into low (levels < 3.84 ng/mL) and high (levels ≥ 3.84 ng/mL) groups based on the median NLRP3 inflammasome levels. The patients were divided into three groups according to the Thrombolysis in Myocardial Infarction Risk Score for Secondary Prevention (TRS-2P): low (scores ≤ 2 points), intermediate (scores = 3 points), and high (score ≥ 4 points) risk. We investigated the relationship between NLRP3 inflammasome and laboratory indicators. Additionally, we examined whether the NLRP3 inflammasome was an independent predictor of high TRS-2P and explored the applicability of the plasma NLRP3 inflammasome for predicting high TRS-2P. Results: Logistic regression analysis revealed that NLRP3 inflammasome was an independent predictor of high TRS-2P (odds ratio [OR]:2.013; 95% confidence interval [CI]: 1.174– 3.452). The area under the receiver operating characteristic curve value of the NLRP3 inflammasome was 0.674 (95% CI: 0.611– 0.737; P < 0.001). Conclusion: NLRP3 inflammasome levels are an independent predictive factor for high TRS-2P levels, which indicates that the NLRP3 inflammasome may help predict the prognosis of ACS patients. [ABSTRACT FROM AUTHOR]

Image hashing is an efficient technique of many multimedia systems, such as image retrieval, image authentication and image copy detection. Classification between robustness and discrimination is one of the most important performances of image hashing. In this paper, we propose a robust image hashing with singular values of quaternion singular value decomposition (QSVD). The key contribution is the innovative use of QSVD, which can extract stable and discriminative image features from CIE L*a*b* color space. In addition, image features of a block are viewed as a point in the Cartesian coordinates and compressed by calculating the Euclidean distance between its point and a reference point. As the Euclidean distance requires smaller storage than the original block features, this technique helps to make a discriminative and compact hash. Experiments with three open image databases are conducted to validate efficiency of our image hashing. The results demonstrate that our image hashing can resist many digital operations and reaches a good discrimination. Receiver operating characteristic curve comparisons illustrate that our image hashing outperforms some state-of-the-art algorithms in classification performance. [ABSTRACT FROM AUTHOR]

Image hashing is a technique that represents an image as a short unidirectional sequence. In this study, we propose a robust color image hashing technique based on the quaternionic local ranking binary pattern (QLRBP). First, the values of the RGB color channels are expressed as a pure quaternion, and the texture image is generated using the phase difference of the Clifford translation quaternion as the source for local binary pattern (LBP) comparison data. Next, mean pooling is used to reduce the dimensionality of the image texture. For security, the pixels of the dimension-reduced image are randomly selected, and each pixel is quantized to obtain the final image hash. Experimental results showed that the proposed scheme resists a variety of ordinary image operations and achieves good balance between robustness and discrimination. In comparison with other state-of-the-art methods, the receiver operating characteristic (ROC) curves of our scheme demonstrate its superiority in terms of content identification. [ABSTRACT FROM AUTHOR]

Video hashing is a novel technique of multimedia processing and finds applications in video retrieval, video copy detection, anti-piracy search and video authentication. In this paper, we propose a robust video hashing based on discrete cosine transform (DCT) and non-negative matrix decomposition (NMF). The proposed video hashing extracts secure features from a normalized video via random partition and dominant DCT coefficients, and exploits NMF to learn a compact representation from the secure features. Experiments with 2050 videos are carried out to validate efficiency of the proposed video hashing. The results show that the proposed video hashing is robust to many digital operations and reaches good discrimination. Receiver operating characteristic (ROC) curve comparisons illustrate that the proposed video hashing outperforms some state-of-the-art algorithms in classification between robustness and discrimination. [ABSTRACT FROM AUTHOR]

Image hashing is an efficient technology for processing digital images and has been successfully used in image copy detection, image retrieval, image authentication, image quality assessment, and so on. In this paper, we design a new image hashing with compressed sensing (CS) and ordinal measures. This hashing method uses a visual attention model called Itti model and Canny operator to construct an image representation, and exploits CS to extract compact features from the representation. Finally, the CS-based compact features are quantized via ordinal measures. L2 norm is used to judge similarity of hashes produced by the proposed hashing method. Experiments about robustness validation, discrimination test, block size discussion, selection of visual attention model, selection of quantization scheme, and effectiveness of the use of ordinal measures are conducted to verify performances of the proposed hashing method. Comparisons with some state-of-the-art algorithms are also carried out. The results illustrate that the proposed hashing method outperforms some compared algorithms in classification according to ROC (receiver operating characteristic) graph. [ABSTRACT FROM AUTHOR]

Currently, the reported image hashing schemes cannot perform satisfactorily in some aspects, such as rotation robustness. To this end, a perceptual color image hashing scheme is proposed. First, the original image is normalized and smoothed by Gaussian low-pass filter. The obtained secondary image is divided into a series of ring-ribbons with different radii and the same number of pixels. Then, textural and color features are extracted in local and global manners. Specifically, local textural features are extracted on luminance values of the ring-ribbons using quadtree decomposition, and global textural features are extracted by gray level co-occurrence matrix. Local color features of significant corner points are extracted on outer boundaries of ring-ribbons through color vector angles, and global color features are extracted by low-order moments. The extracted features are concatenated after quantization and permutation to generate the final hash. Receiver operating characteristic curves verified the effectiveness of our scheme, including robustness, discrimination, and security, which can be effectively applied in content authentication and tampering detection. [ABSTRACT FROM AUTHOR]

The study aimed to determine whether high sensitivity C-reactive protein to prealbumin (hs-CRP/PAB) ratio could be used to predict in-hospital major adverse cardiac events (MACE) in patients with acute coronary syndrome (ACS). A total of 659 patients with ACS were included in the study. Patients were divided into two groups: high hs-CRP/PAB ratio group (hs-CRP/PAB ≥0.010) and low hs-CRP/PAB ratio group (hs-CRP/PAB <0.010). MACE was defined as death, cardiogenic shock, re-infarction and acute heart failure. Logistic regression was performed and the receiver operating characteristic curve (ROC) was generated to evaluate the correlation of hs-CRP/PAB ratio and MACE in patients with ACS. The occurrence rate of MACE was significantly higher in high hs-CRP/PAB ratio group when compared with that in low hs-CRP/PAB ratio group (P < 0.001). Multivariable analysis determined that hs-CRP/PAB ratio was an independent predictor of MACE (adjusted odds ratio: 1.276, 95% confidence interval: 1.106–1.471, P = 0.001). Moreover, the area under the curve value of hs-CRP/PAB ratio for predicting MACE was higher than hs-CRP and equal to PAB. High hs-CRP/PAB ratio was considered as a prognostic parameter of MACE in ACS patients, with the predictive power equal to PAB but greater than hs-CRP. [ABSTRACT FROM AUTHOR]

In recent decades, numerous perceptual authentication hashing schemes have been proposed for image content authentication. However, most of these schemes are based on a single spatial or transform domain, and they fail to provide satisfactory robustness and discrimination capability when facing complex image manipulations in real scenarios. In this work, we present a perceptual authentication hashing scheme based on Convolutional Neural Network (CNN) that leverages both spatial and frequency domains. Specifically, we construct two separate streams for spatial and transform domains. Then, we introduce a feature fusion module to merge the features of these two domains to generate a hash sequence. Besides, we design a frequency domain channel filter and a frequency attention module for the frequency domain, and introduce a frequency domain loss function to optimize model training. Based on large-scale testing datasets, our scheme demonstrates superior performance compared to state-of-the-art schemes, as evidenced by Receiver Operating Characteristic (ROC) curves. • A new robust perceptual hashing scheme for image authentication is proposed. • Multi-domain feature fusion strategy is exploited for hash sequence generation. • The channel filter and attention module are designed in frequency domain. • An integrated loss function including hash loss and frequency loss is introduced. • Theoretical analysis and experiments are given to show the superiority of our scheme. [ABSTRACT FROM AUTHOR]