Toxicological effects of cadmium on deep-sea mussel Gigantidas platifrons revealed by a combined proteomic and metabolomic approach

IntroductionMarine metal contamination caused by deep-sea mining activities has elicited great concern from both social and scientific communities. Among the various metals deep-sea organisms might encounter, cadmium (Cd) is a widely detected metal that in very small amounts is nonetheless capable of severe toxicity. Yet due to both remoteness and technical challenges, insights into the effects of metal exposure resulting from mining activities upon deep-sea organisms are limited.MethodsHere, we investigated Cd’s toxicological effects on deep-sea mussels of Gigantidas platifrons exposed to 100 or 1000 g/L of Cd for 7 days; an integrated approach was used that incorporated proteomics and metabolomics along with traditional approaches (metal concentrations, metal subcellular distribution, and anti-oxidative and immune-related biochemical indexes).Results and DiscussionResults showed that Cd exposure caused significant Cd’s accumulation in mussel gills and redistribution of Cd among subcellular compartments, with cellular debris being the primary binding site. Although anti-oxidative enzymes activities (superoxide dismutase and catalase) were not significantly altered in mussel gills of both exposed groups, the markedly increased level of glutathione S-transferase detected via proteomic technique clearly evinced that deep-sea mussels suffered from oxidative stress under Cd exposure. Besides, altered activities of acid phosphatase and alkaline phosphatase assayed by traditional methods along with the predominant presence of largely altered immune-related proteins detected by proteomic data strongly revealed an immune response of deep-sea mussels elicited by Cd. In addition, results of proteomics combined with those of non-targeted metabolomics demonstrated that Cd could exert toxicity by disrupting cytoskeleton structure, ion homeostasis, and primary metabolisms of energy, lipid, and nucleotide in deep-sea mussels. As demonstrated in this study, proteomics and metabolomics can be used in tandem to provide valuable insights into the molecular mechanisms of deep-sea organisms’ response to Cd exposure and for helping to discover potential biomarkers for application during deep-sea mining assessments

Dissecting the roles and clinical potential of YY1 in the tumor microenvironment

Yin-Yang 1 (YY1) is a member of the GLI-Kruppel family of zinc finger proteins and plays a vital dual biological role in cancer as an oncogene or a tumor suppressor during tumorigenesis and tumor progression. The tumor microenvironment (TME) is identified as the “soil” of tumor that has a critical role in both tumor growth and metastasis. Many studies have found that YY1 is closely related to the remodeling and regulation of the TME. Herein, we reviewed the expression pattern of YY1 in tumors and summarized the function and mechanism of YY1 in regulating tumor angiogenesis, immune and metabolism. In addition, we discussed the potential value of YY1 in tumor diagnosis and treatment and provided a novel molecular strategy for the clinical diagnosis and treatment of tumors

Lineage tracing for multiple lung cancer by spatiotemporal heterogeneity using a multi-omics analysis method integrating genomic, transcriptomic, and immune-related features

IntroductionThe distinction between multiple primary lung cancer (MPLC) and intrapulmonary metastasis (IPM) holds clinical significance in staging, therapeutic intervention, and prognosis assessment for multiple lung cancer. Lineage tracing by clinicopathologic features alone remains a clinical challenge; thus, we aimed to develop a multi-omics analysis method delineating spatiotemporal heterogeneity based on tumor genomic profiling.MethodsBetween 2012 and 2022, 11 specimens were collected from two patients diagnosed with multiple lung cancer (LU1 and LU2) with synchronous/metachronous tumors. A novel multi-omics analysis method based on whole-exome sequencing, transcriptome sequencing (RNA-Seq), and tumor neoantigen prediction was developed to define the lineage. Traditional clinicopathologic reviews and an imaging-based algorithm were performed to verify the results.ResultsSeven tissue biopsies were collected from LU1. The multi-omics analysis method demonstrated that three synchronous tumors observed in 2018 (LU1B/C/D) had strong molecular heterogeneity, various RNA expression and immune microenvironment characteristics, and unique neoantigens. These results suggested that LU1B, LU1C, and LU1D were MPLC, consistent with traditional lineage tracing approaches. The high mutational landscape similarity score (75.1%), similar RNA expression features, and considerable shared neoantigens (n = 241) revealed the IPM relationship between LU1F and LU1G which were two samples detected simultaneously in 2021. Although the multi-omics analysis method aligned with the imaging-based algorithm, pathology and clinicopathologic approaches suggested MPLC owing to different histological types of LU1F/G. Moreover, controversial lineage or misclassification of LU2’s synchronous/metachronous samples (LU2B/D and LU2C/E) traced by traditional approaches might be corrected by the multi-omics analysis method. Spatiotemporal heterogeneity profiled by the multi-omics analysis method suggested that LU2D possibly had the same lineage as LU2B (similarity score, 12.9%; shared neoantigens, n = 71); gefitinib treatment and EGFR, TP53, and RB1 mutations suggested the possibility that LU2E might result from histology transformation of LU2C despite the lack of LU2C biopsy and its histology. By contrast, histological interpretation was indeterminate for LU2D, and LU2E was defined as a primary or progression lesion of LU2C by histological, clinicopathologic, or imaging-based approaches.ConclusionThis novel multi-omics analysis method improves the accuracy of lineage tracing by tracking the spatiotemporal heterogeneity of serial samples. Further validation is required for its clinical application in accurate diagnosis, disease management, and improving prognosis

Research on Copyright Infringement of Network Remixes Short Video

The new economic model and the development of the Internet and media technology have bred the network mixed clip video. This new video type not only enriches people’s spiritual and cultural life, but also brings about copyright infringement problems. This article focuses on the copyright issue of Network remixes short video, and also focuses on the issues of whether the Network remixes short video belong to the “Works” stipulated in the Copyright Law of The People’s Republic of China and whether the use of other people’s works in the Network remixes short video can be regarded as reasonable, and hopes to put forward some suggestions for the prevention, solution or regulation of related problems

Quantum Particle Swarm Optimization Extraction Algorithm Based on Quantum Chaos Encryption

Considering the highly complex structure of quantum chaos and the nonstationary characteristics of speech signals, this paper proposes a quantum chaotic encryption and quantum particle swarm extraction method based on an underdetermined model. The proposed method first uses quantum chaos to encrypt the speech signal and then uses the local mean decomposition (LMD) method to construct a virtual receiving array and convert the underdetermined model to a positive definite model. Finally, the signal is extracted using the Levi flight strategy based on kurtosis and the quantum particle swarm optimization optimized by the greedy algorithm (KLG-QPSO). The bit error rate and similarity coefficient of the voice signal are extracted by testing the source voice signal SA1, SA2, and SI943 under different SNR, and the similarity coefficient, uncertainty, and disorder of the observed signal and the source voice signal SA1, SA2, and SI943 verify the effectiveness of the proposed speech signal extraction method and the security of quantum chaos used in speech signal encryption

An Image Compression Encryption Algorithm Based on Chaos and ZUC Stream Cipher

In order to improve the transmission efficiency and security of image encryption, we combined a ZUC stream cipher and chaotic compressed sensing to perform image encryption. The parallel compressed sensing method is adopted to ensure the encryption and decryption efficiency. The ZUC stream cipher is used to sample the one-dimensional chaotic map to reduce the correlation between elements and improve the randomness of the chaotic sequence. The compressed sensing measurement matrix is constructed by using the sampled chaotic sequence to improve the image restoration effect. In order to reduce the block effect after the parallel compressed sensing operation, we also propose a method of a random block of images. Simulation analysis shows that the algorithm demonstrated better encryption and compression performance

An Efficient Convolutional Blind Source Separation Algorithm for Speech Signals under Chaotic Masking

As the main method of information transmission, it is particularly important to ensure the security of speech communication. Considering the more complex multipath channel transmission situation in the wireless communication of speech signals and separating or extracting the source signal from the convolutional signal are crucial steps in obtaining source information. In this paper, chaotic masking technology is used to guarantee the transmission safety of speech signals, and a fast fixed-point independent vector analysis algorithm is used to solve the problem of convolutional blind source separation. First, the chaotic masking is performed before the speech signal is sent, and the convolutional mixing process of multiple signals is simulated by impulse response filter. Then, the observed signal is transformed to the frequency domain by short-time Fourier transform, and instantaneous blind source separation is performed using a fast fixed-point independent vector analysis algorithm. The algorithm can preserve the high-order statistical correlation between frequencies to solve the permutation ambiguity problem in independent component analysis. Simulation experiments show that this algorithm can efficiently complete the blind extraction of convolutional signals, and the quality of recovered speech signals is better. It provides a solution for the secure transmission and effective separation of speech signals in multipath transmission channels

Microstructure and mechanical property of high power laser powder bed fusion AlSi10Mg alloy before and after T6 heat treatment

This paper focuses on the microstructure and mechanical property of the high power laser powder bed fusion AlSi10Mg alloy before and after T6 heat treatment. The results demonstrate that the as-printed sample presents a columnar grain structure along the build direction and a strong texture. Inside the columnar α-Al grains, there are cellular dendrites decorated with network eutectic Si. Both the α-Al matrix and eutectic Si have high-density dislocations. Besides, nano-twins and stacking faults are observed in eutectic Si. After T6 treatment, although the α-Al matrix still exhibits a columnar solidification feature, the cellular dendrites disappear and the proportion of equiaxed grains increase. And the eutectic Si presents as separate plates or nanoscale particles, in which nano-twins and stacking faults are not found. The tensile property anisotropy decreases and the strength-ductility balance improves after T6 treatment. The evolution mechanisms of the microstructure and tensile property are revealed

Visual Secure Image Encryption Scheme Based on Compressed Sensing and Regional Energy

The network security transmission of digital images needs to solve the dual security problems of content and appearance. In this paper, a visually secure image compression and encryption scheme is proposed by combining compressed sensing (CS) and regional energy. The plain image is compressed and encrypted into a secret image by CS and zigzag confusion. Then, according to the regional energy, the secret image is embedded into a carrier image to obtain the final visual secure cipher image. A method of hour hand printing (HHP) scrambling is proposed to increase the pixel irrelevance. Regional energy embedding reduce the damage to the visual quality of carrier image, and the different embedding positions between images greatly enhances the security of the encryption algorithm. Furthermore, the hyperchaotic multi-character system (MCS) is utilized to construct measurement matrix and control pixels. Simulation results and security analyses demonstrate the effectiveness, security and robustness of the propose algorithm