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An amendment to this paper has been published and can be accessed via the original article. [ABSTRACT FROM AUTHOR]

Community discovery is an important topic of network representation learning. Manifold learning has been widely applied to network representation learning. However, most manifold learning algorithms do not consider the asymmetry of edges which is not accord with the structure of social networks because the influence of nodes is not symmetrical. In this paper, a community discovery algorithm based on manifold graph embedding with structure information propagation mechanism is proposed. The proposed algorithm uses high order approximation matrix to obtain the local and global structure information of a graph, then low rank decomposition is introduced to obtain the node vectors and the context vectors. Finally, the node vectors can be adjusted by structure information. The proposed algorithm and comparison algorithms are conducted on the experimental data sets. The experimental results show that the proposed algorithm outperforms the comparison algorithms on the most experimental data sets. The experimental results prove that the proposed algorithm is an effective algorithm for community discovery. [ABSTRACT FROM AUTHOR]

Human body movements can convey a variety of emotions and even create advantages in some special life situations. However, how emotion is encoded in body movements has remained unclear. One reason is that there is a lack of public human body kinematic dataset regarding the expressing of various emotions. Therefore, we aimed to produce a comprehensive dataset to assist in recognizing cues from all parts of the body that indicate six basic emotions (happiness, sadness, anger, fear, disgust, surprise) and neutral expression. The present dataset was created using a portable wireless motion capture system. Twenty-two semi-professional actors (half male) completed performances according to the standardized guidance and preferred daily events. A total of 1402 recordings at 125 Hz were collected, consisting of the position and rotation data of 72 anatomical nodes. To our knowledge, this is now the largest emotional kinematic dataset of the human body. We hope this dataset will contribute to multiple fields of research and practice, including social neuroscience, psychiatry, computer vision, and biometric and information forensics. Measurement(s) body movement coordination trait • emotion/affect behavior trait Technology Type(s) motion capture system Factor Type(s) emotion category • sex Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12821150 [ABSTRACT FROM AUTHOR]

Background: Life of patients with uveal melanoma (UM) is largely threatened by liver metastasis. Little is known about the drivers of liver organotropic metastasis in UM. The elevated activity of transcription of oncogenes is presumably to drive aspects of tumors. We hypothesized that inhibition of transcription by cyclin-dependent kinase 7/9 (CDK7/9) inhibitor SNS-032 diminished liver metastasis by abrogating the putative oncogenes in charge of colonization, stemness, cell motility of UM cells in host liver microenvironment. Methods: The effects of SNS-032 on the expression of the relevant oncogenes were examined by qRT-PCR and Western blotting analysis. Proliferative activity, frequency of CSCs and liver metastasis were evaluated by using NOD-SCID mouse xenograft model and NOG mouse model, respectively. Results: The results showed that CDK7/9 were highly expressed in UM cells, and SNS-032 significantly suppressed the cellular proliferation, induced apoptosis, and inhibited the outgrowth of xenografted UM cells and PDX tumors in NOD-SCID mice, repressed the cancer stem-like cell (CSC) properties through transcriptional inhibition of stemness-related protein Krüppel-like factor 4 (KLF4), inhibited the invasive phonotypes of UM cells through matrix metalloproteinase 9 (MMP9). Mechanistically, SNS-032 repressed the c-Myc-dependent transcription of RhoA gene, and thereby lowered the RhoA GTPase activity and actin polymerization, and subsequently inhibited cell motility and liver metastasis. Conclusions: In conclusion, we validate a set of transcription factors which confer metastatic traits (e.g., KLF4 for CSCs, c-Myc for cell motility) in UM cells. Our results identify SNS-032 as a promising therapeutic agent, and warrant a clinical trial in patients with metastatic UM. [ABSTRACT FROM AUTHOR]

Sinomenine, an isoquinoline alkaloid extracted from the roots and stems of Sinomenium acutum, has been extensively studied for its derivatives as bioactive agents. This review concentrates on the research advancements in the biological activities and action mechanisms of sinomenine-related compounds until November 2023. The findings indicate a broad spectrum of pharmacological effects, including antitumor, anti-inflammation, neuroprotection, and immunosuppressive properties. These compounds are notably effective against breast, lung, liver, and prostate cancers, exhibiting IC50 values of approximately 121.4 nM against PC-3 and DU-145 cells, primarily through the PI3K/Akt/mTOR, NF-κB, MAPK, and JAK/STAT signaling pathways. Additionally, they manifest anti-inflammatory and analgesic effects predominantly via the NF-κB, MAPK, and Nrf2 signaling pathways. Utilized in treating rheumatic arthritis, these alkaloids also play a significant role in cardiovascular and cerebrovascular protection, as well as organ protection through the NF-κB, Nrf2, MAPK, and PI3K/Akt/mTOR signaling pathways. This review concludes with perspectives and insights on this topic, highlighting the potential of sinomenine-related compounds in clinical applications and the development of medications derived from natural products. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) play important roles in the occurrence and development of diseases. However, it is still challenging to identify the effective miRNA biomarkers for improving the disease diagnosis and prognosis. In this study, we proposed the miRNA data analysis method based on multi-view miRNA networks and reinforcement learning, miRMarker, to define the potential miRNA disease biomarkers. miRMarker constructs the cooperative regulation network and functional similarity network based on the expression data and known miRNA–disease relations, respectively. The cooperative regulation of miRNAs was evaluated by measuring the changes of relative expression. Natural language processing was introduced for calculating the miRNA functional similarity. Then, miRMarker integrates the multi-view miRNA networks and defines the informative miRNA modules through a reinforcement learning strategy. We compared miRMarker with eight efficient data analysis methods on nine transcriptomics datasets to show its superiority in disease sample discrimination. The comparison results suggested that miRMarker outperformed other data analysis methods in receiver operating characteristic analysis. Furthermore, the defined miRNA modules of miRMarker on colorectal cancer data not only show the excellent performance of cancer sample discrimination but also play significant roles in the cancer-related pathway disturbances. The experimental results indicate that miRMarker can build the robust miRNA interaction network by integrating the multi-view networks. Besides, exploring the miRNA interaction network using reinforcement learning favors defining the important miRNA modules. In summary, miRMarker can be a hopeful tool in biomarker identification for human diseases. [ABSTRACT FROM AUTHOR]

Clustering is an important data mining method to discover knowledge and patterns. Feature weighting is widely applied in high-dimensional data mining. In this paper, a multi-feature weighting neighborhood density clustering algorithm is proposed. It uses different dimension reduction algorithms to generate different features, and then, the weights of the features are determined by the discrimination ability. For the clustering algorithm, the center points can be selected by the upper approximation set and lower approximation set. At last, the final clustering result is from the fusion of multiple clustering results. The proposed algorithms and comparison algorithms are executed on the synthetic and real-world data sets. The test results show that the proposed algorithm outperforms the comparison algorithms on the most experimental data sets. The experimental results prove that the proposed algorithm is effective for data clustering. [ABSTRACT FROM AUTHOR]

As an important component of music information retrieval, music genre classification attracts great attentions these years. Benefitting from the outstanding performance of deep neural networks in computer vision, some researchers apply CNN on music genre classification tasks with audio spectrograms as input instead, which has similarities with RGB images. These methods are based on a latent assumption that spectrums with different temporal steps have equal importance. However, it goes against the theory of processing bottleneck in psychology as well as our observation from audio spectrograms. By considering the differences of spectrums, we propose a new model incorporating with attention mechanism based on Bidirectional Recurrent Neural Network. Furthermore, two attention-based models (serial attention and parallelized attention) are implemented in this paper. Comparing with serial attention, parallelized attention is more flexible and gets better results in our experiments. Especially, the CNN-based parallelized attention models with taking STFT spectrograms as input outperform the previous work. [ABSTRACT FROM AUTHOR]

In this study, a novel series of histone deacetylases 6 (HDAC6) inhibitors containing polycyclic aromatic rings were discovered and evaluated for their pharmacological activities. The most potent compound 10c exhibited high HDAC6 inhibitory activity (IC50 = 261 nM) and excellent HDAC6 selectivity (SI = 109 for HDAC6 over HDAC3). 10c also showed decent antiproliferative activity in vitro with IC50 of 7.37–21.84 μM against four cancer cell lines, comparable to that of tubastatin A (average IC50 = 6.10 μM). Further mechanism studies revealed that 10c efficiently induced apoptosis and S-phase arrest in B16-F10 cells. In addition, 10c markedly increased the expression of acetylated-α-tubulin both in vitro and in vivo, without affecting the levels of acetylated-H3 (marker of HDAC1 inhibition). Furthermore, 10c (80 mg/kg) exhibited moderate antitumor efficacy in a melanoma tumour model with a tumour growth inhibition (TGI) of 32.9%, comparable to that (TGI = 31.3%) of tubastatin A. Importantly, the combination of 10c with NP19 (a small molecule PD-L1 inhibitor discovered by us before) decreased tumour burden substantially (TGI% = 60.1%) as compared to monotherapy groups. Moreover, the combination of 10c with NP19 enhanced the anti-tumour immune response, mediated by a decrease of PD-L1 expression levels and increased infiltration of anti-tumour CD8+ T cells in tumour tissues. Collectively, 10c represents a novel HDAC6 inhibitor deserving further investigation as a potential anti-cancer agent. [ABSTRACT FROM AUTHOR]

[Display omitted] • Paraffins and acid gases spontaneously enter the channel without electric fields. • Electric fields make water molecules occupy the channel in place of other gases. • Electric fields induce the ordered arrangements of water molecules. • The stable ice-like water structure formed is a key factor for dehumidification. • Dehumidification effect is not strictly dependent on channel diameters and surfaces. The existence of water in natural gas causes serious congestion and acid corrosion problems during exploitation and transport. Water must be removed. Here, we performed molecular dynamics simulations to investigate the effect of electric fields on natural gas dehydration through nanochannels. When the electric field is applied, only water molecules occupy the nanochannel in place of C 1 -C 3 paraffins, acid gases and N 2 molecules. The dominant mechanism is that the electric field and confinement of channels induce the ordered arrangements of water molecules, forming stable ice-like structures and restricting the entry of other components. Once removing the electric field, the water molecules will be released from the channel due to the relatively low water-channel interaction. Importantly, hydrophilic and hydrophobic channels both exhibit effective separation for water. The separation selectivity is not strictly dependent on channel diameters, avoiding the trade-off effect between adsorption capacity and selectivity based on the size sieving mechanism. [ABSTRACT FROM AUTHOR]

The life-cycle inspection of civil infrastructure can guide decisions on structural safety and reliability. This paper proposes a strategy for smartphone-based public participation in the life-cycle inspection of civil infrastructure (SPIC). The SPIC strategy consists of three parts: participants, Urban Brain, and Global View. Next, the feasibility of this strategy is verified by simulation experiments implemented in Unity3D. Civil infrastructure inspection modes include routine inspection, focus inspection, and emergency inspection. The activation and transition of the three inspection modes are tested. Test results show that routine inspection with public participation could timely identify pre-set damaged civil infrastructures. All abnormal civil infrastructures are observed by the Urban Brain. The focus inspection mode is activated when an abnormal civil infrastructure is detected, and the focus inspection provides a detailed and professional assessment of the abnormal civil infrastructure. Then, the inspection of all civil infrastructures in emergency inspection mode is completed in the test. Furthermore, this paper carries out a factor sensitivity analysis of this strategy. The proposed strategy establishes the mechanism for the assign-accept-feedback inspection task. In addition, the simulation performed in Unity3D is one of the next alternatives for large-scale urban disaster prevention and mitigation experiments in the real world. The SPIC strategy can effectively enhance the disaster prevention and mitigation capabilities of civil infrastructure. [ABSTRACT FROM AUTHOR]

[Display omitted] • The effects of crosslinking and branching degree on phenolic pyrolysis were studied. • The bimodal distribution of pyrolysis products was obtained. • The generation activation energy of low-boiling molecules was calculated. • The reaction kinetics path of phenolic pyrolysis was reasonably summarized. Based on the reactive force-field (ReaxFF) molecular dynamics, the thermostability of cross-linked and non-cross-linked phenolic was compared to study the effect of cross-linked and branched structures on the pyrolysis mechanism. The results show that during the pyrolysis process, phenolic tends to break into low-boiling molecules with less than 4 carbon atoms and polymerizes into macromolecules with more than 1500 carbon atoms. The results of residual carbon rate and products distribution confirm that carbon skeleton of phenolic resin with high degree of crosslinking and branching is better preserved and has better thermostability. The reaction kinetics path of phenolic pyrolysis was reasonably summarized, revealing the generation mechanism of low-boiling molecules with less than 4 carbon atoms and large carbon clusters, which is in good agreement with the experimental results of activation energy and chemical bond energy. The reaction kinetics data obtained in this work provide a reliable basis for multi-scale reaction simulation. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) is one of the most prevalent types of malignant tumours. Metastasis is the leading cause of cancer-related mortality, with lung metastases accounting for 32.9% of all metastatic CRCs. However, since the biological mechanism of lung metastatic CRC is poorly understood, limited therapeutic targets are available. In the present study, we aimed to identify the key genes and molecular processes involved in CRC lung metastasis. Methods: The differentially expressed genes (DEGs) between primary and lung metastatic CRC patients were obtained from the Gene Expression Omnibus (GEO) database via the GEO2R tool. The enriched biological processes and pathways modulated by the DEGs were determined with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome Gene Sets analyses. The search tool Retrieval of Interacting Genes (STRING) and Cytoscape were used to construct a protein–protein interaction (PPI) network among DEGs. Results: The DEGs were enriched in surfactant metabolism, cell–cell communication and chemokine signaling pathways. The defined hub genes were included CLU, SFTPD, CCL18, SPP1, APOE, BGN and MMP3. Among them, CLU, SFTPD and CCL18 might be associated with the specific lung tropism metastasis in CRC. In addition, the expression and prognostic values of the hub genes in CRC patients were verified in database of The Cancer Genome Atlas (TCGA) and GEO. Moreover, the protein levels of the hub genes were detected in primary and lung metastatic CRC cells, serum or tissues. Furthermore, SFTPD was confirmed to facilitate cellular proliferation and lung metastasis in CRC. Conclusion: This bioinformatics study may provide a better understanding of the candidate therapeutic targets and molecular mechanisms for CRC lung metastasis. [ABSTRACT FROM AUTHOR]

With the development of 5G technology, Internet of Things (IoT) is proliferating and deeply integrated with our daily lives and industry productions. IoT applications in the 5G era generate massive connections, and this would bring about many security issues. In this paper, we first analyze security risks for massive IoT in the 5G era, then summarize related security policies and standards. Furthermore, we propose security requirements and measures for various layers, including sensor control equipment and IoT card, IoT network and transmission exchange, IoT business application and service, and IoT security management and operation. Next, we introduce the case of the cyber security monitoring platform, explain the security technology based on edge computing, and point out the related standards. Finally, we put forward suggestions on IoT security technology and standardization work, so as to promote the secure development of IoT in the 5G era. [ABSTRACT FROM AUTHOR]

Due to boundary ambiguity and over-segmentation issues, identifying all the frames in long untrimmed videos is still challenging. To address these problems, we present the Efficient Two-Step Network (ETSN) with two components. The first step of ETSN is Efficient Temporal Series Pyramid Networks (ETSPNet) that capture both local and global frame-level features and provide accurate predictions of segmentation boundaries. The second step is a novel unsupervised approach called Local Burr Suppression (LBS), which significantly reduces the over-segmentation errors. Our empirical evaluations on the benchmarks including 50Salads, GTEA and Breakfast dataset demonstrate that ETSN outperforms the current state-of-the-art methods by a large margin. [ABSTRACT FROM AUTHOR]

Facial landmark tracking often adopts static models to generically fit per frame of video. This is considered inappropriate since such models ignore the informative correlation between previous and current frames. Moreover, most of these methods fail to balance the speed and accuracy for video-based facial landmark tracking simultaneously. In this paper, we propose an efficient online framework for video-based face alignment, named Incrementally Cascaded Broad Learning framework (ICBL). ICBL aims to continuously enhance the prediction capability of tracking model for sequential data. It is capable of learning the spatial appearance on specific-person statistics from continuous facial frames and using such knowledge to incrementally tune a cascade of regressors in parallel. To achieve this goal, we approximate the facial shape space by sampling from a dynamic distribution which is continuously updated by person-specific statistics from the tracked facial frames. This dramatically facilitates cascade regression to incrementally update all cascade-regressors in parallel, thus allowing a fast update of the whole model. Furthermore, we successfully incorporate both the linear and non-linear mappings into our parallel cascade framework and introduce Broad Learning (BL) algorithm as a solution for them simultaneously. Experimental results on the most popular and large-scale benchmark for facial landmark tracking show highly competitive performance of proposed ICBL in comparisons with the state-of-the-arts. The code of our ICBL framework has been available from https://github.com/CaifengLiu/Facial-landmark-tracking-by-ICBL. [ABSTRACT FROM AUTHOR]

Clustering analysis is an important data mining method for data stream. In this paper, a self-adaption neighborhood density clustering method for mixed data stream is proposed. The method uses a significant metric criteria to make categorical attribute values become numeric and then the dimension of data is reduced by a nonlinear dimensionality reduction method. In the clustering method, each point is evaluated by neighborhood density. The k points are selected from the data set with maximum mutual distance after k is determined according to rough set. In addition, a new similarity measure based on neighborhood entropy is presented. The data points can be partitioned into the nearest cluster and the algorithm adaptively adjusts the clustering center points by clustering error. The experimental results show that the proposed method can obtain better clustering results than the comparison algorithms on the most data sets and the experimental results prove that the proposed algorithm is effective for data stream clustering. [ABSTRACT FROM AUTHOR]

Direct finite element analysis that takes stamping dimensional deviations into account was achieved based on coupled electro-thermo-mechanical method and reverse engineering in the current research. The two continuous resistance spot welding processes of the reverse established back side panel were simulated. Its residual stresses and deformation were compared with those of the ideal back side panel. Large distortion presents in the reverse back side panel while only slight deformation exists in the ideal one. The former is validated to be closer to the deformation of the actual welded back side panel. The peak residual stresses after processes 1 and 2 remain almost unchanged in the reverse back side panel while those in the ideal one show an increasing trend. The final residual stresses of the reverse and the ideal back side panel are both high but the former is lower than the later. The stamping dimensional deviations are responsible for these differences. They lead to obvious attenuation of geometric features and large assembly clearances in the reverse back side panel. These assembly clearances allow large deformations of the stamping parts during the welding process. Meanwhile, these clearances make it relatively freer for the heated sheet metal to expand thermally in the thickness direction, resulting in less or even no residual stress in this direction. These clearances also promote the release of the thickness-direction component of the tensile residual stress in the extension direction of sheet by allowing deformation in the thickness direction. [ABSTRACT FROM AUTHOR]

Image representation and ranking are crucial parts in image retrieval. These two steps are independently constructed in most retrieval models, but the compatibility between descriptors and ranking algorithms play an important role. Inspired by human vision perception and manifold learning, we propose a novel image retrieval framework in this paper. We first propose an image representation called texton uniform descriptor, and then illustrate the preservation of the intrinsic manifold structure through visualizing the distribution of image representations on the two-dimensional manifold. This characteristic provides the foundation for subsequent manifold-based ranking. To further improve the efficiency in image retrieval, we propose modified manifold ranking (MMR) which aims at selecting small-scale images randomly as landmarks to propagate adjacent similarity among images iteratively. The extensive experiments in four public datasets demonstrate that our framework has better performance than other state-of-the-art methods in image retrieval. [ABSTRACT FROM AUTHOR]

Metastasis remains the principal cause of cancer-related lethality despite advancements in cancer treatment. Dysfunctional epigenetic alterations are crucial in the metastatic cascade. Among these, super-enhancers (SEs), emerging as new epigenetic regulators, consist of large clusters of regulatory elements that drive the high-level expression of genes essential for the oncogenic process, upon which cancer cells develop a profound dependency. These SE-driven oncogenes play an important role in regulating various facets of metastasis, including the promotion of tumor proliferation in primary and distal metastatic organs, facilitating cellular migration and invasion into the vasculature, triggering epithelial-mesenchymal transition, enhancing cancer stem cell-like properties, circumventing immune detection, and adapting to the heterogeneity of metastatic niches. This heavy reliance on SE-mediated transcription delineates a vulnerable target for therapeutic intervention in cancer cells. In this article, we review current insights into the characteristics, identification methodologies, formation, and activation mechanisms of SEs. We also elaborate the oncogenic roles and regulatory functions of SEs in the context of cancer metastasis. Ultimately, we discuss the potential of SEs as novel therapeutic targets and their implications in clinical oncology, offering insights into future directions for innovative cancer treatment strategies., (© 2024. The Author(s).)

Manifold learning now plays an important role in machine learning and many relevant applications. In spite of the superior performance of manifold learning techniques in dealing with nonlinear data distribution, their performance would drop when facing the problem of data sparsity. It is hard to obtain satisfactory embeddings when sparsely sampled high-dimensional data are mapped into the observation space. To address this issue, in this article, we propose hierarchical neighbors embedding (HNE), which enhances the local connections through hierarchical combination of neighbors. And three different HNE-based implementations are derived by further analyzing the topological connection and reconstruction performance. The experimental results on both the synthetic and real-world datasets illustrate that our HNE-based methods could obtain more faithful embeddings with better topological and geometrical properties. From the view of embedding quality, HNE develops the outstanding advantages in dealing with data of general distributions. Furthermore, comparing with other state-of-the-art manifold learning methods, HNE shows its superiority in dealing with sparsely sampled data and weak-connected manifolds.

In this study, permanganate combined with bisulfite (PM/BS), a novel advanced oxidation process, was used for rapidly removing sulfamethoxazole (SMX) from contaminated water. The results showed that 80% SMX was removed within 10 s in the PM/BS system, while no obvious SMX degradation was observed in the PM or BS alone system within 300 s. Reactive manganese species (RMnS, Mn(III), Mn(V) and Mn(VI)), sulfate radical (SO 4 •- ) and hydroxyl radical (HO • ) formed in the PM/BS system all played a role in accelerated degradation of SMX. Due to the loss of RMnS, SMX degradation was significantly inhibited with the increase in pH. The best [BS]:[PM] ratio for SMX removal was 7.5:1-10:1. The presence of Cl - , HCO 3 - or natural organic matter (NOM) significantly inhibited the degradation of SMX, while SO 4 2- and NO 3 - had little impact on SMX removal. Based on the detected transformation products, two degradation pathways of SMX by PM/BS, namely N-S bond cleavage and amino oxidation, were proposed.

MicroRNAs (miRNAs) play important roles in the occurrence and development of diseases. However, it is still challenging to identify the effective miRNA biomarkers for improving the disease diagnosis and prognosis. In this study, we proposed the miRNA data analysis method based on multi-view miRNA networks and reinforcement learning, miRMarker, to define the potential miRNA disease biomarkers. miRMarker constructs the cooperative regulation network and functional similarity network based on the expression data and known miRNA-disease relations, respectively. The cooperative regulation of miRNAs was evaluated by measuring the changes of relative expression. Natural language processing was introduced for calculating the miRNA functional similarity. Then, miRMarker integrates the multi-view miRNA networks and defines the informative miRNA modules through a reinforcement learning strategy. We compared miRMarker with eight efficient data analysis methods on nine transcriptomics datasets to show its superiority in disease sample discrimination. The comparison results suggested that miRMarker outperformed other data analysis methods in receiver operating characteristic analysis. Furthermore, the defined miRNA modules of miRMarker on colorectal cancer data not only show the excellent performance of cancer sample discrimination but also play significant roles in the cancer-related pathway disturbances. The experimental results indicate that miRMarker can build the robust miRNA interaction network by integrating the multi-view networks. Besides, exploring the miRNA interaction network using reinforcement learning favors defining the important miRNA modules. In summary, miRMarker can be a hopeful tool in biomarker identification for human diseases., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Human body expressions convey emotional shifts and intentions of action and, in some cases, are even more effective than other emotion models. Despite many datasets of body expressions incorporating motion capture available, there is a lack of more widely distributed datasets regarding naturalized body expressions based on the 2D video. In this paper, therefore, we report the multi-view emotional expressions dataset (MEED) using 2D pose estimation. Twenty-two actors presented six emotional (anger, disgust, fear, happiness, sadness, surprise) and neutral body movements from three viewpoints (left, front, right). A total of 4102 videos were captured. The MEED consists of the corresponding pose estimation results (i.e., 397,809 PNG files and 397,809 JSON files). The size of MEED exceeds 150 GB. We believe this dataset will benefit the research in various fields, including affective computing, human-computer interaction, social neuroscience, and psychiatry., (© 2023. Springer Nature Limited.)

Colorectal cancer (CRC) is the second most common cause of cancer-related mortality and lies third in terms of morbidity due to the limited number of effective druggable targets. Since cancer stem cells (CSCs) are considered to be one of the roots of tumorigenesis, outgrowth and metastasis, targeting CSCs may be a promising strategy to reverse the malignant phenotypes of CRC. Cyclin-dependent kinase 12 (CDK12) has been reported to be involved in the self-renewal of CSCs in various cancers, rendering it an attractive potential target against CSCs to consequently limit the malignant phenotypes in CRC. In the present study, we aimed to investigate whether CDK12 can be a potential therapeutic target for patients with CRC and clarify its underlying mechanism. We found that CDK12, but not CDK13 is required for CRC survival. CDK12 was found to drive tumor initiation according to the colitis-associated colorectal cancer mouse model. In addition, CDK12 promoted CRC outgrowth and hepatic metastasis in the subcutaneous allograft and liver metastasis mouse models, respectively. In particular, CDK12 was able to induce the self-renewal of CRC CSCs. Mechanistically, the activation of Wnt/β-catenin signaling mediated by CDK12 was implicated in stemness regulation and malignant phenotype maintenance. These findings indicate that CDK12 is a candidate druggable target in CRC. Therefore, the CDK12 inhibitor SR-4835 warrants clinical trial testing in patients with CRC., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Colorectal cancer (CRC) is the leading cause of cancer-related mortality worldwide, which makes it urgent to identify novel therapeutic targets for CRC treatment. In this study, DHX9 was filtered out as the prominent proliferation promoters of CRC by siRNA screening. Moreover, DHX9 was overexpressed in CRC cell lines, clinical CRC tissues and colitis-associated colorectal cancer (CAC) mouse model. The upregulation of DHX9 was positively correlated with poor prognosis in patients with CRC. Through gain- and loss-of function experiments, we found that DHX9 promoted CRC cell proliferation, colony formation, apoptosis resistance, migration and invasion in vitro. Furthermore, a xenograft mouse model and a hepatic metastasis mouse model were utilized to confirm that forced overexpression of DHX9 enhanced CRC outgrowth and metastasis in vivo, while DHX9 ablation produced the opposite effect. Mechanistically, from one aspect, DHX9 enhances p65 phosphorylation, promotes p65 nuclear translocation to facilitate NF-κB-mediated transcriptional activity. From another aspect, DHX9 interacts with p65 and RNA polymerase II (RNA Pol II) to enhance the downstream targets of NF-κB (e.g., Survivin, Snail) expression to potentiate the malignant phenotypes of CRC. Together, our results suggest that DHX9 may be a potential therapeutic target for prevention and treatment of CRC patients., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Colonization is believed a rate-limiting step of metastasis cascade. However, its underlying mechanism is not well understood. Uveal melanoma (UM), which is featured with single organ liver metastasis, may provide a simplified model for realizing the complicated colonization process. Because DDR1 was identified to be overexpressed in UM cell lines and specimens, and abundant pathological deposition of extracellular matrix collagen, a type of DDR1 ligand, was noted in the microenvironment of liver in metastatic patients with UM, we postulated the hypothesis that DDR1 and its ligand might ignite the interaction between UM cells and their surrounding niche of liver thereby conferring strengthened survival, proliferation, stemness and eventually promoting metastatic colonization in liver. We tested this hypothesis and found that DDR1 promoted these malignant cellular phenotypes and facilitated metastatic colonization of UM in liver. Mechanistically, UM cells secreted TGF-β1 which induced quiescent hepatic stellate cells (qHSCs) into activated HSCs (aHSCs) which secreted collagen type I. Such a remodeling of extracellular matrix, in turn, activated DDR1, strengthening survival through upregulating STAT3-dependent Mcl-1 expression, enhancing stemness via upregulating STAT3-dependent SOX2, and promoting clonogenicity in cancer cells. Targeting DDR1 by using 7rh, a specific inhibitor, repressed proliferation and survival in vitro and in vivo outgrowth. More importantly, targeting cancer cells by pharmacological inactivation of DDR1 or targeting microenvironmental TGF-β1-collagen I loop exhibited a prominent anti-metastasis effect in mice. In conclusion, targeting DDR1 signaling and TGF-β signaling may be a novel approach to diminish hepatic metastasis in UM.

Background: Uveal melanoma (UM) is the most common primary intraocular tumor. Hepatic metastasis is the major and direct death-related reason in UM patients. Given that cancer stem-like cells (CSCs) are roots of metastasis, targeting CSCs may be a promising strategy to overcome hepatic metastasis in UM. Salinomycin, which has been identified as a selective inhibitor of CSCs in multiple types of cancer, may be an attractive agent against CSCs thereby restrain hepatic metastasis in UM. The objective of the study is to explore the antitumor activity of salinomycin against UM and clarify its underlying mechanism., Methods: UM cells were treated with salinomycin, and its effects on cell proliferation, apoptosis, migration, invasion, CSCs population, and the related signal transduction pathways were determined. The in vivo antitumor activity of salinomycin was evaluated in the NOD/SCID UM xenograft model and intrasplenic transplantation liver metastasis mouse model., Results: We found that salinomycin remarkably obviated growth and survival in UM cell lines and in a UM xenograft mouse model. Meanwhile, salinomycin significantly eliminated CSCs and efficiently hampered hepatic metastasis in UM liver metastasis mouse model. Mechanistically, Twist1 was fundamental for the salinomycin-enabled CSCs elimination and migration/invasion blockage in UM cells., Conclusions: Our findings suggest that targeting UM CSCs by salinomycin is a promising therapeutic strategy to hamper hepatic metastasis in UM. These results provide the first pre-clinical evidence for further testing of salinomycin for its antitumor efficacy in UM patients with hepatic metastasis.

Objective: To evaluate skin irritation, acute toxicity, and allergy of medical ozone oil for clinical application.
 Methods: In contrast to their left and right side irritation, one or more skin irritation tests were performed on the intact and damaged skins of guinea pigs. With the maximum concentration, acute skin toxicity test was applied on the intact and damaged skins of rats.Active cutaneous anaphylaxis was applied to the guinea pigs.
 Results: High concentration (ozone consumption: 150 g/L) of medical ozone oil showed a slight irritation on the broken skin of guinea pigs, while low concentrations did not show skin irritation.Medical ozone oil had no obvious acute toxicity to rats. The medical ozone oil and base oil showed mildallergy for the skin of guinea pig.
 Conclusion: The irritation of medical ozone oil is related to its concentration. With appropriateconcentration and duration of treatment, medical ozone oil is safe.

Background and Objective: The clinical presentations and disease courses of patients hospitalized with either influenza A virus subtype H7N9 (H7N9) or 2009 pandemic H1N1 influenza virus were compared in a recent report, but associated cardiac complications remain unclear. The present retrospective study investigated whether cardiac complications in critically ill patients with H7N9 infections differed from those infected with the pandemic H1N1 influenza virus strain., Methods: Suspect cases were confirmed by reverse transcription polymerase chain reaction assays with specific confirmation of the pandemic H1N1 strain at the Centers for Disease Control and Prevention. Comparisons were conducted at the individual-level data of critically ill patients hospitalized with H7N9 (n=24) or pandemic H1N1 influenza virus (n=22) infections in Suzhou, China. Changes in cardiac biochemical markers, echocardiography, and electrocardiography during hospitalization in the intensive care unit were considered signs of cardiac complications., Results: The following findings were more common among the H7N9 group relative to the pandemic H1N1 influenza virus group: greater tricuspid regurgitation pressure gradient, sinus tachycardia (heartbeat≥130bpm), ST segment depression, right ventricular dysfunction, and elevated cardiac biochemical markers. Pericardial effusion was more often found among pandemic H1N1 influenza virus patients than in the H7N9 group. In both groups, most of the cardiac complications were detected from day 6 to 14 after the onset of influenza symptoms. Those who developed cardiac complications were especially vulnerable during the first four days after initiation of mechanical ventilation. Cardiac complications were reversible in the vast majority of discharged H7N9 patients., Conclusions: Critically ill hospitalized H7N9 patients experienced a higher rate of cardiac complications than did patients with 2009 pandemic H1N1 influenza virus infections, with the exception of pericardial effusion. This study may help in the prevention, identification, and treatment of influenza-induced cardiac complications in both pandemic H1N1 influenza virus and H7N9 infections., (Copyright © 2016 Sociedade Brasileira de Infectologia. Published by Elsevier Editora Ltda. All rights reserved.)

Store-operated Ca 2+ entry (SOCE) is an important mechanism of extracellular Ca 2+ entry into cells. It has been proved that SOCE is involved in many pathologic and physiological processes. Two key participants of SOCE, stromal interaction molecule1 (STIM1) and Orai1, have been identified. But their function in cardiac fibroblasts remains elusive. In present study, our findings suggested the expression of STIM1 and Orai1 were increased followed by angiotensin II (Ang II) stimulation in vivo and in vitro. In cultured adult rat cardiac fibroblasts, Ang II led to STIM1 interact with Orai1 and Ca 2+ release from intracellular calcium store. In addition, the upregulation of fibronectin (FN), connective tissue growth factor (CTGF) and smooth muscle α-actin (α-SMA) induced by Ang II were attenuated by SOCE inhibitor SKF-96365, similar results were observed by knocking down STIM1 and Orai1. Furthermore, we found that silencing Orai1 by RNA interference also suppressed the translocation of Nuclear Factor of Activated T-cells (NFAT) Isoforms NFATc4 and decreased the phosphorylation of Smad2 and Smad3 induced by Ang II. These results unraveled a novel role of SOCE as a key modulator in the Ang II-induced cardiac fibrosis by mediating Ca 2+ influx., (Copyright © 2016 The Authors. Production and hosting by Elsevier B.V. All rights reserved.)

Objective: To evaluate the efficacy and safety of dexmedetomidine for post-operative elder patients on mechanical ventilation (MV)., Methods: For this randomized controlled trial, 108 cases of post-operative patients on MV were enrolled and assigned into either dexmedetomidine group (n = 54) or propofol group (n = 54) for sedation. And propofol was used for rescue. The dose of sedation was regulated by Ramsay score for maintaining a sedative score of 3-4. In both groups, fentanyl was provided intravenously continually for analgesia. The amount of fentanyl was adjusted according to the numerical rating scale (NRS) score for maintaining an analgesic score of 0-3. The average Ramsay score, the frequency of propofol, the highest score of NRS, the total dosage of fentanyl and recovery time were compared. Additional outcomes included duration of mechanical ventilation and intensive care unit (ICU) length. And the incidence of delirium and cardiovascular adverse events were compared for two groups., Results: No significant inter-group difference existed in the effectiveness of sedation. Compare with propofol group, the highest score of NRS decreased (1.8 ± 1.12 vs 3.1 ± 1.24, P < 0.05), the total dosage of fentanyl significantly decreased (427.6 ± 14.1 vs 658.4 ± 27.3 µg, P < 0.05) and recovery time became significantly shortened (0.3 ± 0.02 h vs 1.1 ± 0.3 h, P < 0.05) in dexmedetomidine group. Median duration of mechanical ventilation in dexmedetomidine group (21.0 h, 95%CI: 18.6-21.4 h) was significantly shorter than that in propofol group (28.0 h, 95%CI: 25.6-30.4 h) (P < 0.05). No inter-group differences existed in the ICU length of stay and the incidence of delirium. Two cases in dexmedetomidine group developed bradycardia while hypotension occurred in two cases of propofol group., Conclusion: Sedative effects of dexmedetomidine are safe and effective for post-operative elder patients on MV. And it offers a better efficacy of analgesia and shorter durations of MV and recovery time. But dexmedetomidine had no significant influence on the ICU length of stay or the incidence of delirium.

Protected cyclohexanol and cyclohex-2-enol substrates, containing benzyl ether and benzoate ester moieties, were designed to fit into the active site of the Tyr96Ala mutant of cytochrome P450cam. The protected cyclohexanol substrates were efficiently and selectively hydroxylated by the mutant enzyme at the trans C-H bond of C-4 on the cyclohexyl ring. The selectivity of oxidation of the benzoate ester protected cyclohexanol could be altered by making alternative amino acid substitutions in the P450cam active site. The addition of the double bond in the cyclohexyl ring of the benzoate ester protected cyclohex-2-enol has a debilitative effect on the activity of the Tyr96Ala mutant with this substrate. However, the Phe87Ala/Tyr96Phe double mutant, which introduces space at a different location in the active site than the Tyr96Ala mutant, was able to efficiently hydroxylate the C-H bonds of 1-cyclohex-2-enyl benzoate at the allylic C-4 position. Mutations at Phe87 improved the selectivity of the oxidation of 1-phenyl-1-cyclohexylethylene to trans-4-phenyl-ethenylcyclohexanol (92%) when compared to single mutants at Tyr96 of P450cam.