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Despite that deep learning methods have achieved remarkable performance in pathology image classification, they heavily rely on labeled data, demanding extensive human annotation efforts. In this study, we present a novel human annotation-free method for pathology image classification by leveraging pre-trained Vision-Language Models (VLMs). Without human annotation, pseudo labels of the training set are obtained by utilizing the zero-shot inference capabilities of VLM, which may contain a lot of noise due to the domain shift between the pre-training data and the target dataset. To address this issue, we introduce VLM-CPL, a novel approach based on consensus pseudo labels that integrates two noisy label filtering techniques with a semi-supervised learning strategy. Specifically, we first obtain prompt-based pseudo labels with uncertainty estimation by zero-shot inference with the VLM using multiple augmented views of an input. Then, by leveraging the feature representation ability of VLM, we obtain feature-based pseudo labels via sample clustering in the feature space. Prompt-feature consensus is introduced to select reliable samples based on the consensus between the two types of pseudo labels. By rejecting low-quality pseudo labels, we further propose High-confidence Cross Supervision (HCS) to learn from samples with reliable pseudo labels and the remaining unlabeled samples. Experimental results showed that our method obtained an accuracy of 87.1% and 95.1% on the HPH and LC25K datasets, respectively, and it largely outperformed existing zero-shot classification and noisy label learning methods. The code is available at https://github.com/lanfz2000/VLM-CPL., Comment: Under review

Deepfake videos are becoming increasingly realistic, showing few tampering traces on facial areasthat vary between frames. Consequently, existing Deepfake detection methods struggle to detect unknown domain Deepfake videos while accurately locating the tampered region. To address thislimitation, we propose Delocate, a novel Deepfake detection model that can both recognize andlocalize unknown domain Deepfake videos. Ourmethod consists of two stages named recoveringand localization. In the recovering stage, the modelrandomly masks regions of interest (ROIs) and reconstructs real faces without tampering traces, leading to a relatively good recovery effect for realfaces and a poor recovery effect for fake faces. Inthe localization stage, the output of the recoveryphase and the forgery ground truth mask serve assupervision to guide the forgery localization process. This process strategically emphasizes the recovery phase of fake faces with poor recovery, facilitating the localization of tampered regions. Ourextensive experiments on four widely used benchmark datasets demonstrate that Delocate not onlyexcels in localizing tampered areas but also enhances cross-domain detection performance., Comment: arXiv admin note: substantial text overlap with arXiv:2308.09921, arXiv:2305.05943

AI-generated content has accelerated the topic of media synthesis, particularly Deepfake, which can manipulate our portraits for positive or malicious purposes. Before releasing these threatening face images, one promising forensics solution is the injection of robust watermarks to track their own provenance. However, we argue that current watermarking models, originally devised for genuine images, may harm the deployed Deepfake detectors when directly applied to forged images, since the watermarks are prone to overlap with the forgery signals used for detection. To bridge this gap, we thus propose AdvMark, on behalf of proactive forensics, to exploit the adversarial vulnerability of passive detectors for good. Specifically, AdvMark serves as a plug-and-play procedure for fine-tuning any robust watermarking into adversarial watermarking, to enhance the forensic detectability of watermarked images; meanwhile, the watermarks can still be extracted for provenance tracking. Extensive experiments demonstrate the effectiveness of the proposed AdvMark, leveraging robust watermarking to fool Deepfake detectors, which can help improve the accuracy of downstream Deepfake detection without tuning the in-the-wild detectors. We believe this work will shed some light on the harmless proactive forensics against Deepfake., Comment: Accepted by IJCAI 2024

The misuse of deepfake technology by malicious actors poses a potential threat to nations, societies, and individuals. However, existing methods for detecting deepfakes primarily focus on uncompressed videos, such as noise characteristics, local textures, or frequency statistics. When applied to compressed videos, these methods experience a decrease in detection performance and are less suitable for real-world scenarios. In this paper, we propose a deepfake video detection method based on 3D spatiotemporal trajectories. Specifically, we utilize a robust 3D model to construct spatiotemporal motion features, integrating feature details from both 2D and 3D frames to mitigate the influence of large head rotation angles or insufficient lighting within frames. Furthermore, we separate facial expressions from head movements and design a sequential analysis method based on phase space motion trajectories to explore the feature differences between genuine and fake faces in deepfake videos. We conduct extensive experiments to validate the performance of our proposed method on several compressed deepfake benchmarks. The robustness of the well-designed features is verified by calculating the consistent distribution of facial landmarks before and after video compression.Our method yields satisfactory results and showcases its potential for practical applications.

Existing image inpainting methods have achieved remarkable accomplishments in generating visually appealing results, often accompanied by a trend toward creating more intricate structural textures. However, while these models excel at creating more realistic image content, they often leave noticeable traces of tampering, posing a significant threat to security. In this work, we take the anti-forensic capabilities into consideration, firstly proposing an end-to-end training framework for anti-forensic image inpainting named SafePaint. Specifically, we innovatively formulated image inpainting as two major tasks: semantically plausible content completion and region-wise optimization. The former is similar to current inpainting methods that aim to restore the missing regions of corrupted images. The latter, through domain adaptation, endeavors to reconcile the discrepancies between the inpainted region and the unaltered area to achieve anti-forensic goals. Through comprehensive theoretical analysis, we validate the effectiveness of domain adaptation for anti-forensic performance. Furthermore, we meticulously crafted a region-wise separated attention (RWSA) module, which not only aligns with our objective of anti-forensics but also enhances the performance of the model. Extensive qualitative and quantitative evaluations show our approach achieves comparable results to existing image inpainting methods while offering anti-forensic capabilities not available in other methods.

With the rapid development of engineered nanomaterials (ENMs) in biomedical applications, their biocompatibility and cytotoxicity need to be evaluated properly. Recently, it has been demonstrated that inflammasome activation may be a vital contributing factor for the development of biological responses induced by ENMs. Among the inflammasome family, NLRP3 inflammasome has received the most attention because it directly interacts with ENMs to cause the inflammatory effects. However, the pathways that link ENMs to NLRP3 inflammasome have not been thoroughly summarized. Thus, we reviewed recent findings on the role of major ENMs properties in modulating NLRP3 inflammasome activation, both in vitro and in vivo, to provide a better understanding of the underlying mechanisms. In addition, the interactions between ENMs and NLRP3 inflammasome activation are summarized, which may advance our understanding of safer designs of nanomaterials and ENM-induced adverse health effects.

Deepfake techniques have been widely used for malicious purposes, prompting extensive research interest in developing Deepfake detection methods. Deepfake manipulations typically involve tampering with facial parts, which can result in inconsistencies across different parts of the face. For instance, Deepfake techniques may change smiling lips to an upset lip, while the eyes remain smiling. Existing detection methods depend on specific indicators of forgery, which tend to disappear as the forgery patterns are improved. To address the limitation, we propose Mover, a new Deepfake detection model that exploits unspecific facial part inconsistencies, which are inevitable weaknesses of Deepfake videos. Mover randomly masks regions of interest (ROIs) and recovers faces to learn unspecific features, which makes it difficult for fake faces to be recovered, while real faces can be easily recovered. Specifically, given a real face image, we first pretrain a masked autoencoder to learn facial part consistency by dividing faces into three parts and randomly masking ROIs, which are then recovered based on the unmasked facial parts. Furthermore, to maximize the discrepancy between real and fake videos, we propose a novel model with dual networks that utilize the pretrained encoder and masked autoencoder, respectively. 1) The pretrained encoder is finetuned for capturing the encoding of inconsistent information in the given video. 2) The pretrained masked autoencoder is utilized for mapping faces and distinguishing real and fake videos. Our extensive experiments on standard benchmarks demonstrate that Mover is highly effective.

Segmentation of pathological images is a crucial step for accurate cancer diagnosis. However, acquiring dense annotations of such images for training is labor-intensive and time-consuming. To address this issue, Semi-Supervised Learning (SSL) has the potential for reducing the annotation cost, but it is challenged by a large number of unlabeled training images. In this paper, we propose a novel SSL method based on Cross Distillation of Multiple Attentions (CDMA) to effectively leverage unlabeled images. Firstly, we propose a Multi-attention Tri-branch Network (MTNet) that consists of an encoder and a three-branch decoder, with each branch using a different attention mechanism that calibrates features in different aspects to generate diverse outputs. Secondly, we introduce Cross Decoder Knowledge Distillation (CDKD) between the three decoder branches, allowing them to learn from each other's soft labels to mitigate the negative impact of incorrect pseudo labels in training. Additionally, uncertainty minimization is applied to the average prediction of the three branches, which further regularizes predictions on unlabeled images and encourages inter-branch consistency. Our proposed CDMA was compared with eight state-of-the-art SSL methods on the public DigestPath dataset, and the experimental results showed that our method outperforms the other approaches under different annotation ratios. The code is available at \href{https://github.com/HiLab-git/CDMA}{https://github.com/HiLab-git/CDMA.}, Comment: Provisional Accepted by MICCAI 2023

Unlike hiding bit-level messages, hiding image-level messages is more challenging, which requires large capacity, high imperceptibility, and high security. Although recent advances in hiding image-level messages have been remarkable, existing schemes are limited to lossless spatial images as covers and cannot be directly applied to JPEG images, the ubiquitous lossy format images in daily life. The difficulties of migration are caused by the lack of targeted design and the loss of details due to lossy decompression and re-compression. Considering that taking DCT densely on $8\times8$ image patches is the core of the JPEG compression standard, we design a novel model called \textsf{EFDR}, which can comprehensively \underline{E}xploit \underline{F}ine-grained \underline{D}CT \underline{R}epresentations and embed the secret image into quantized DCT coefficients to avoid the lossy process. Specifically, we transform the JPEG cover image and hidden secret image into fine-grained DCT representations that compact the frequency and are associated with the inter-block and intra-block correlations. Subsequently, the fine-grained DCT representations are further enhanced by a sub-band features enhancement module. Afterward, a transformer-based invertibility module is designed to fuse enhanced sub-band features. Such a design enables a fine-grained self-attention on each sub-band and captures long-range dependencies while maintaining excellent reversibility for hiding and recovery. To our best knowledge, this is the first attempt to embed a color image of equal size in a color JPEG image. Extensive experiments demonstrate the effectiveness of our \textsf{EFDR} with superior performance., Comment: ACM Multimedia 23 submitted by Xin Liao (https://xin-liao.github.io/)

Malicious Deepfakes have led to a sharp conflict over distinguishing between genuine and forged faces. Although many countermeasures have been developed to detect Deepfakes ex-post, undoubtedly, passive forensics has not considered any preventive measures for the pristine face before foreseeable manipulations. To complete this forensics ecosystem, we thus put forward the proactive solution dubbed SepMark, which provides a unified framework for source tracing and Deepfake detection. SepMark originates from encoder-decoder-based deep watermarking but with two separable decoders. For the first time the deep separable watermarking, SepMark brings a new paradigm to the established study of deep watermarking, where a single encoder embeds one watermark elegantly, while two decoders can extract the watermark separately at different levels of robustness. The robust decoder termed Tracer that resists various distortions may have an overly high level of robustness, allowing the watermark to survive both before and after Deepfake. The semi-robust one termed Detector is selectively sensitive to malicious distortions, making the watermark disappear after Deepfake. Only SepMark comprising of Tracer and Detector can reliably trace the trusted source of the marked face and detect whether it has been altered since being marked; neither of the two alone can achieve this. Extensive experiments demonstrate the effectiveness of the proposed SepMark on typical Deepfakes, including face swapping, expression reenactment, and attribute editing., Comment: Accepted by ACM MM 2023

In Intelligent Transportation Systems, images are the main data sources to be analyzed for providing intelligent and precision cognitive services. Therefore, how to protect the privacy of sensitive images in the process of information transmission has become an important research issue, especially in future no non-private data era. In this article, we design the Rearrangement-Arnold Cat Map (R-ACM) to disturb the relationship between adjacent pixels and further propose an efficient Bit-level Image Encryption Algorithm(Bl-IEA) based on R-ACM. Experiments show that the correlation coefficients of two adjacent pixels are 0.0022 in the horizontal direction, -0.0105 in the vertical direction, and -0.0035 in the diagonal direction respectively, which are obviously weaker than that of the original image with high correlations of adjacent pixels. What's more, the NPCR is 0.996120172, and the UACI is 0.334613406, which indicate that Bl-IEA has stronger ability to resist different attacks compared with other solutions. Especially, the lower time complexity and only one round permutation make it particularly suitable to be used in the time-limited intelligent transportation field.

The exploitation of Deepfake techniques for malicious intentions has driven significant research interest in Deepfake detection. Deepfake manipulations frequently introduce random tampered traces, leading to unpredictable outcomes in different facial regions. However, existing detection methods heavily rely on specific forgery indicators, and as the forgery mode improves, these traces become increasingly randomized, resulting in a decline in the detection performance of methods reliant on specific forgery traces. To address the limitation, we propose Recap, a novel Deepfake detection model that exposes unspecific facial part inconsistencies by recovering faces and enlarges the differences between real and fake by mapping recovered faces. In the recovering stage, the model focuses on randomly masking regions of interest (ROIs) and reconstructing real faces without unpredictable tampered traces, resulting in a relatively good recovery effect for real faces while a poor recovery effect for fake faces. In the mapping stage, the output of the recovery phase serves as supervision to guide the facial mapping process. This mapping process strategically emphasizes the mapping of fake faces with poor recovery, leading to a further deterioration in their representation, while enhancing and refining the mapping of real faces with good representation. As a result, this approach significantly amplifies the discrepancies between real and fake videos. Our extensive experiments on standard benchmarks demonstrate that Recap is effective in multiple scenarios., Comment: arXiv admin note: substantial text overlap with arXiv:2305.05943

Due to the progression of information technology in recent years, document images have been widely disseminated on social networks. With the help of powerful image editing tools, document images are easily forged without leaving visible manipulation traces, which leads to severe issues if significant information is falsified for malicious use. Therefore, the research of document image forensics is worth further exploring. In this paper, we propose a Character Texture Perception Network (CTP-Net) to localize the forged regions in document images. Specifically, considering the characters with semantics in a document image are highly vulnerable, capturing the forgery traces is the key to localize the forged regions. We design a Character Texture Stream (CTS) based on optical character recognition to capture features of text areas that are essential components of a document image. Meanwhile, texture features of the whole document image are exploited by an Image Texture Stream (ITS). Combining the features extracted from the CTS and the ITS, the CTP-Net can reveal more subtle forgery traces from document images. Moreover, to overcome the challenge caused by the lack of fake document images, we design a data generation strategy that is utilized to construct a Fake Chinese Trademark dataset (FCTM). Experimental results on different datasets demonstrate that the proposed CTP-Net is able to localize multi-scale forged areas in document images, and outperform the state-of-the-art forgery localization methods, even though post-processing operations are applied.

The mushroomed Deepfake synthetic materials circulated on the internet have raised serious social impact to politicians, celebrities, and every human being on earth. In this survey, we provide a thorough review of the existing Deepfake detection studies from the reliability perspective. Reliability-oriented research challenges of the current Deepfake detection research domain are defined in three aspects, namely, transferability, interpretability, and robustness. While solutions have been frequently addressed regarding the three challenges, the general reliability of a detection model has been barely considered, leading to the lack of reliable evidence in real-life usages and even for prosecutions on Deepfake-related cases in court. We, therefore, introduce a model reliability study metric using statistical random sampling knowledge and the publicly available benchmark datasets to review the reliability of the existing detection models on arbitrary Deepfake candidate suspects. Case studies are further executed to justify the real-life Deepfake cases including different groups of victims with the help of the reliably qualified detection models as reviewed in this survey. Reviews and experiments upon the existing approaches provide informative discussions and future research directions of Deepfake detection., Comment: Survey paper submitted for peer review

Haiqing Fan *, Yue Yu *, Jinhui Du, Likun Liu, Yilin Luo, Hui Yu, Xin Liao Department of Medical Imaging, The Affiliated Hospital of Guizhou Medical University, Guiyang City, Guizhou Province, 550004, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xin Liao, Department of Medical Imaging, The Affiliated Hospital of Guizhou Medical University, No. 29 Guiyi Street, Yunyan District, Guiyang City, Guizhou Province, 550004, People’s Republic of China, Tel +86 13765065226, Email liaoxinlxlx@126.comObjective: To investigate the clinical, imaging, and pathological features of gliosarcoma.Methods: The clinical data of 14 patients with gliosarcoma confirmed by surgery and pathology at our hospital between 2010 and 2021 were analyzed retrospectively, and the relevant literature was reviewed.Results: In all 14 cases, the gliosarcoma was located in the supratentorial brain parenchyma and involved a single lesion. There were more male patients (64.3%) than female patients (35.7%), and 57.1% of all the patients were 40– 60 years of age. The prognosis of all 14 patients was poor, and the average survival time was approximately seven months. The computed tomography findings revealed mostly mixed density lesions, and some cases were complicated with bleeding. The magnetic resonance imaging revealed irregularly shaped mass lesions of different sizes, with uneven or circular enhancement. Cystic degeneration and necrosis could be seen in all the masses, some of which showed signs of bleeding and were surrounded by different degrees of edema and space-occupying effects. The pathological examination revealed that the tumors had bidirectional differentiation of the glial and sarcoma components, while the immunohistochemistry examination revealed glial fibrillary acidic protein-positive and reticular fiber-positive staining in the sarcoma.Conclusion: The clinical manifestations of gliosarcoma are nonspecific, but imaging

Liao X, Zhan W, Tian B, Luo Y, Gu F, Li R. OncoTargets Ther. 2020;13:7773–7783. The Editor and Publisher of OncoTargets and Therapy wish to retract the published article. Concerns were raised regarding the alleged duplication of images in Figure 5C with the same images in Figure 5C from Zhu et al, 2015 ‘bFGF-Regulating MAPKs Are Involved in High Glucose-Mediated ROS Production and Delay of Vascular Endothelial Cell Migration’ (https://doi.org/10.1371/journal.pone.0144495). Specifically, Figure 5C, HepG2, 0h, si-NC+NC inh appears to have been duplicated with the same image from Figure 5C, 0 h, HG+sp from Zhu et al, 2015. Figure 5C, HepG2, 0h, si-circZNF609+NC inh appears to have been duplicated with the same image from Figure 5C, 0 h, LG from Zhu et al, 2015. The authors did not respond to our queries and no explanation for the alleged image duplication was provided. The Editor requested to retract the article and the authors were notified of this. We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions. The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as “Retracted”.

Xingfang Yu,1,* Xin Liao,2,* Hongwei Chen1 1Department of Orthopedics, The Affiliated Yiwu Hospital of Wenzhou Medical University, Yiwu, Zhejiang, 322000, People’s Republic of China; 2Department of Orthopedics, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Hongwei ChenDepartment of Orthopedics, The Affiliated Yiwu Hospital of Wenzhou Medical University, Yiwu, Zhejiang, 322000, People’s Republic of ChinaTel +86-13506896988Email sssaaa18@163.comBackground: Bone infections remain one of the most common and serious complications of orthopedic surgery, posing a tremendous economic burden to society and patients. This is because bacteria colonize and multiply on the surface of the implant. The (MMT/PLL)8 multilayer films have been shown to effectively release antibiotics depending on the changes in the microenvironment. Here, vancomycin was loaded into the (MMT/PLL)8 multilayer films, which were prepared to be used as a local delivery system for the treatment of bone infections.Methods: We used the layer-by-layer self-assembly method to prepare VA-loaded coatings (MMT/PLL-VA)8 consisting of montmorillonite (MMT), poly-L-lysine (PLL), and VA. The thickness and surface morphology of coatings were characterized using spectroscopic ellipsometry and scanning electron microscopy (SEM). In order to evaluate the drug release behavior from coatings in different media, we measured the size of the zone of inhibition. Additionally, in vitro antibacterial activity was assessed using the shake-flask culture method and SEM images, while that of in vivo was evaluated by establishing an animal model of bone infection.Results: Our findings revealed that small-molecule antibiotics were successfully loaded into the (MMT/PLL-VA)8 multilayer film structure during the hierarchical self-assembly

Aiyuan Zhou, 1,* Qing Song, 2,* Yating Peng, 2 Dingding Deng, 3 Xin Liao, 4 Peng Huang, 5 Wenlong Liu, 6 Zhi Xiang, 7 Qimi Liu, 8 Mingyan Jiang,  9 Xiaoying Huang, 10 Xudong Xiang, 11 Hong Peng,  2 Ping Chen  2 1Department of Respiratory and Critical Medicine, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China; 2Department of Respiratory and Critical Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China; 3Department of Respiratory Medicine, The First Attached Hospital of Shaoyang University, Shaoyang, Hunan, 422001, China; 4Department of Respiratory Medicine, Affiliated Shaoyang Central Hospital of University of South China, Shaoyang, Hunan, 422001, China; 5Department of Respiratory Medicine, Zhuzhou Central Hospital, Zhuzhou, Hunan, 412000, China; 6Department of Respiratory Medicine, Yueyang Second People’s Hospital, Designated Hospital of Junshan District, Yueyang, Hunan, 414005, China; 7Department of Respiratory Medicine, The First People’s Hospital of Huaihua Affiliated to University of South China, Huaihua, Hunan, 418000, China; 8Department of Respiratory Medicine, The Second People’s Hospital of Guilin, Guilin, Guangxi, 541001, China; 9Department of Respiratory and Critical Medicine, Xiangtan Central Hospital, Xiangtan, Hunan, 411100, China; 10Department of Respiratory and Critical Medicine, Loudi Central Hospital, Loudi, Hunan, 411100, China; 11Department of Emergency Medicine, Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China*These authors contributed equally to this workCorrespondence: Ping Chen; Hong PengDepartment of Respiratory and Critical Care Medicine, Second Xiangya Hospital, Central South University, 139 Renmin Middle Road, Changsha, Hunan, 410011, People’s Republic of ChinaEmail pingchen0731@csu.edu.cn; penghong66@csu.edu.cnBackground: Oxygen therapy (OT) is the most widely used

In order to improve the ride comfort of the cab of construction machinery and reduce the harm of vibration to the driver, the lumped parameter model of passive hydraulic damping rubber mount (PHDRM) considering the nonlinearity of multi-inertial tracks is first established. Then the overall FE (finite element) fluid-solid coupling model of the vibration isolator is proposed by using ABAQUS combined simulation mode in this paper. Meanwhile, Combined with bidirectional strong coupling algorithm, the parameters of the rubber main spring and inertial track are identified respectively. Also, the dynamic characteristic experiments of the PHDRM samples are carried out. The experiment results show that the analytical solution and FE modeling method of the HDRM system are reliable and accurate under larger amplitude excitation. On the basis of this, the effects of the rubber main spring and inertial track of PHDRM on low frequency dynamic characteristics under larger amplitude excitation are respectively analyzed and discussed. It provides practical reference value for nonlinear modeling method research and dynaimc performance analysis of PHDRM with complex structure further.

The secular behavior of an orbit under the gravitational perturbation due to a two-dimensional uniform disk is studied in this paper, through analytical and numerical approaches. We develop the secular approximation of this problem and obtain the averaged Hamiltonian for this system first. We find that, when the ratio of the semimajor axes of the inner orbit and the disk radius takes very small values ($\ll1$), and if the inclination between the inner orbit and the disk is greater than the critical value of $30^\circ$, the inner orbit will undergo the (classical) Lidov-Kozai resonance in which variations of eccentricity and inclination are usually very large and the system has two equilibrium points at $\omega=\pi/2,3\pi/2$ ($\omega$ is the argument of perihelion). The critical value will slightly drop to about $27^\circ$ as the ratio increases to 0.4. However, the secular resonances will not occur for the outer orbit and the variations of the eccentricity and inclination are small. When the ratio of the orbit and the disk radius is nearly $1$, there are many more complicated Lidov-Kozai resonance types which lead to the orbital behaviors that are different from the classical Lidov-Kozai case. In these resonances, the system has more equilibrium points which could appear at $\omega=0,\pi/2,\pi,3\pi/2$, and even other values of $\omega$. The variations of eccentricity and inclination become relatively moderate, moreover, in some cases the orbit can be maintained at a highly inclined state. In addition, a analysis shows that a Kuzmin disk can also lead to the (classical) Lidov-Kozai resonance and the critical inclination is also $30^\circ$.

This paper has been retracted. Liao X, Zhan W, Tian B, Luo Y, Gu F, Li R. OncoTargets Ther. 2020;13:7773–7783. The Editor and Publisher of OncoTargets and Therapy wish to retract the published article. Concerns were raised regarding the alleged duplication of images in Figure 5C with the same images in Figure 5C from Zhu et al, 2015 ‘bFGF-Regulating MAPKs Are Involved in High Glucose-Mediated ROS Production and Delay of Vascular Endothelial Cell Migration’ (https://doi.org/10.1371/journal.pone.0144495). Specifically, Figure 5C, HepG2, 0h, si-NC+NC inh appears to have been duplicated with the same image from Figure 5C, 0 h, HG+sp from Zhu et al, 2015. Figure 5C, HepG2, 0h, si-circZNF609+NC inh appears to have been duplicated with the same image from Figure 5C, 0 h, LG from Zhu et al, 2015. The authors did not respond to our queries and no explanation for the alleged image duplication was provided. The Editor requested to retract the article and the authors were notified of this. We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions. The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as “Retracted”.

The development of high-efficiency oxygen electrode with well structural and chemical stability is critical to boost the rapid development of lithium-oxygen (Li-O2) batteries. Which are reckoned as a potent contender for next-generation energy storage devices due to their ultra-high theoretical energy density. Here, a flower-like three-dimensional self-standing ZnCo2S4-based electrode without an addition of binders are fabricated and employing as positive electrode for Li-O2 batteries. The bifunctional catalytic activity of flower-like ZnCo2S4 is conducive to improving the hysteresis kinetics of oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Representative ultrathin petal edge exposes adequate active sites and provides a sufficient contact interface between Li2O2 and positive electrode, which are essential for reducing the charge overpotential during OER. Compared with the control electrodes, the flower-like ZnCo2S4@Ni-based Li-O2 battery shows decreased overpotential (0.78 V) and improved cycle stability (over 500 cycles).

In this work, a novel 2D CuCo2S4 (CCS)nanosheets with spinel type structure is fabricated and used as the cathode catalyst for rechargeable Li-O2 battery. The characteristic 2D nanosheets structure with exposure of special (113), (004), and (044)crystal faces provide sufficient active sites for ORR and OER, which promote the rate capability immensely as well as improve discharge capacity and cycle life of the battery. Specifically, Li-O2 batteries with CCS electrodes show excellent cycle stability of more than 176 cycles at limiting capacity 500 mA h g−1 and superior rate performance (2254 mA h g−1 at 2000 mA g−1). For comparison, nanostructures of CuS and Co3S4 have been synthesized employing the similar process used for CCS. When compared to conventional carbon material (Super P)and these two binary metal sulfides, CCS NSs provided the highest catalytic activities at the same mass loading. Which can be attributed to the introduction of copper in the Co3S4 lattice offers the oxygen evolution and kinetics by enhancing Cu2+ sites and also by providing a high-active high-spin stat of octahedral Co3+ for ORR and OER catalysis.

Wei Zhan*,1, Xin Liao*,2, Lianghe Li3, Zhongsheng Chen3, Tian Tian4, Lei Yu5, Zupeng Chen6 1Department of Colorectal Surgery, The Affiliated Hospital of Guizhou Medical University, Guiyang 550004, People’s Republic of China; 2Department of Imaging, The Affiliated Hospital of Guizhou Medical University, Guiyang 550004, People’s Republic of China; 3Department of Surgery, Clinical Medical College, Guizhou Medical University, Guiyang 550004, People’s Republic of China; 4Department of Pathophysiology, Basic Medical College, Guizhou Medical University, Guiyang 550004, People’s Republic of China; 5Department of Pathology, Guiyang Maternal and Child Health Hospital, Guiyang 550004, People’s Republic of China; 6Department of Neurosurgery, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou 310006, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zupeng ChenDepartment of Neurosurgery, The First Affiliated Hospital of Zhejiang Chinese Medical University, No. 54, Youdian Road, Hangzhou 310006, People’s Republic of ChinaTel +86 05 718 707 2175Email czpvip1@163.comIntroduction: Reactive oxygen species (ROS) are major contributors to cancer and involved in numerous tumor proliferation signaling pathways. Mitochondria are the major ROS-producing organelles, and ROS are produced from the synthesis of adenosine triphosphate and cell metabolism.Methods: A novel mitochondria-targeted peptide, namely KRSH, was synthesized and characterized. KRSH consists of four amino acids; lysine and arginine contain positively charged groups that help KRSH target the mitochondria, while tyrosine and cysteine neutralize excessive endogenous ROS, thereby inhibiting tumorigenesis.Results: The results indicated that KRSH is specifically inhibiting the growth of HeLa and MCF-7 cancer cell lines. However, MCF10A cells can resist the effects of KRSH even in a relative high

Xin-Yu Liao,1,* Yang Lei,2,* Song-Feng Chen,2 Jing Cheng,3 Dan Zhao,4 Zhi-Feng Zhang,2 Xin Han,5 Ya Zhang,2 Hua-Bao Liao,2 Yang Zhuang,2 Juan Chen,6 Hai-Bing Zhou,5 Qi Wan,7 Ying-Ying Zou,11Department of Pathology and Pathophysiology, Faculty of Basic Medical Sciences, Kunming Medical University, Kunming 650500, People’s Republic of China; 2Department of Physiology, School of Basic Medical Sciences, Wuhan University School of Medicine, Wuhan 430071, People’s Republic of China; 3Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan 430060, People’s Republic of China; 4Department of Physiology, School of Basic Medical Sciences, Hubei University of Medicine, Shiyan, Hubei 442000, People’s Republic of China; 5School of Pharmacy, Wuhan University, Wuhan 430071, People’s Republic of China; 6Department of Neurology, The Central Hospital of Wuhan, Tongji Medical College of Huazhong University of Science & Technology, Wuhan 430013, People’s Republic of China; 7Institute of Neuroregeneration & Neurorehabilitation, Collaborative Innovation Center for Brain Science, Department of Neurosurgery of the Affiliated Hospital, Qingdao University, Qingdao 266071, People’s Republic of China*These authors contributed equally to this work Background: The authors have recently designed a new compound bisperoxovandium (pyridin-2-squaramide) [bpV(pis)] and verified that bpV(pis) confers neuroprotection through suppressing PTEN and activating ERK1/2, respectively. Intracerebral hemorrhage (ICH) is the second most common cause of stroke and has severe clinical outcome. In this study, we investigate the effect of bpV(pis) in ICH model both in vivo and in vitro.Materials and methods: The novel drug bpV(pis) was synthesized in the Faculty of Pharmacy, Wuhan University School of Medicine. An ICH model was generated on both SD rats and cells. bpV(pis) was injected into intracerebroventricular or c

Meng-Zhi Han,1,2 Tzuen-Ren Hsiue,3 Sheng-Han Tsai,1 Tang-Hsiu Huang,2,3 Xin-Min Liao,2,3 Chiung-Zuei Chen3 1Division of General Medicine, Department of Internal Medicine, National Cheng Kung University, College of Medicine and Hospital, Tainan, Taiwan; 2Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan; 3Division of Pulmonary Medicine, Department of Internal Medicine, National Cheng Kung University, College of Medicine and Hospital, Tainan, Taiwan Background and objective: A multidimensional assessment of COPD was recommended by the Global Initiative for Chronic Obstructive Lung Disease (GOLD) in 2013 and revised in 2017. We examined the ability of the GOLD 2017 and the new 16 subgroup (1A–4D) classifications to predict clinical outcomes, including exacerbation and mortality, and compared them with the GOLD 2013 classifications. Methods: Patients with COPD were recruited from January 2006 to December 2017. The predictive abilities of grades 1–4 and groups A–D were examined through a logistic regression analysis with receiver operating curve estimations and area under the curve (AUC). Results: A total of 553 subjects with COPD were analyzed. The mortality rate was 48.6% during a median follow-up period of 5.2 years. Both the GOLD 2017 and the 2013 group A–D classifications had good predictive ability for total and severe exacerbations, for which the AUCs were 0.79 vs 0.77 and 0.79 vs 0.78, respectively. The AUCs for the GOLD 2017 groups A–D, grades 1–4, and the GOLD 2013 group A–D classifications were 0.70, 0.66, and 0.70 for all-cause mortality and 0.73, 0.71, and 0.74 for respiratory cause mortality, respectively. Combining the spirometric staging with the grouping for the GOLD 2017 subgroups (1A–4D), the all-cause mortality rate for group B and D patients was significantly increased from subgroups 1B–4B (27.7%, 50.6%, 53.3%, a

Background The X-linked inhibitor of apoptosis protein (XIAP) is a well-known potent apoptosis suppressor and also participates in cancer cell biological behaviors, therefore attracting great attentions as a potential antineoplastic therapeutic target for past years. Anti-IAP therapy is reported to be closely related to epidermal growth factor receptor (EGFR) expression level. However, whether and how XIAP modulates EGFR expression remains largely unknown. Methods Human XIAP was knockdown with short-hairpin RNA in two different bladder cancer cell lines, T24T and UMUC3. Two XIAP mutants, XIAP ∆BIR (deletion of N-terminal three BIR domains) and XIAP ∆RING (deletion of C-terminal RING domain and keeping the function of BIR domains), were generated to determine which domain is involved in regulating EGFR. Results We found here that lacking of XIAP expression resulted in a remarkable suppression of EGFR expression, consequently leading to the deficiency of anchorage-independent cell growth. Further study demonstrated that BIR domain of XIAP was crucial for regulating the EGFR translation by suppressing the transcription and expression of miR-200a. Mechanistic studies indicated that BIR domain activated the protein phosphatase 2 (PP2A) activity by decreasing the phosphorylation of PP2A at Tyr307 in its catalytic subunit, PP2A-C. Such activated PP2A prevented the deviant phosphorylation and activation of MAPK kinases/MAPKs, their downstream effector c-Jun, and in turn inhibiting transcription of c-Jun-regulated the miR-200a. Conclusions Our study uncovered a novel function of BIR domain of XIAP in regulating the EGFR translation, providing significant insight into the understanding of the XIAP overexpression in the cancer development and progression, further offering a new theoretical support for using XIAP BIR domain and EGFR as targets for cancer therapy.

In this paper, the dynamic response characteristics of a common double shear lap joint structure with viscoelastic layer are investigated. Firstly, an analytical model is established in shear vibration based on phenomenological model. The fourth order Runge-Kutta method is employed to calculate the harmonic response, where the effect of Coulomb friction and excitation levels on system are presented. Secondly, a new nonlinear finite element model for the bolted joint structure with viscoelastic layer is developed. The simulation results show good agreement with the corresponding experimental results. Finally, the proposed harmonic excitation experiments with laser vibrometer in tangential direction are carried out to investigate the nonlinear behaviors of system, as well as the influence of bolt preload and viscoelastic material on dynamic characteristics of the bolted joint beam. The results show that the viscoelastic layer help reduce vibration at certain extent, especially in the high frequency region of vibration, and some peak frequencies of system can be changed through the viscoelastic layer.

Xiao-dong Zhuang,1,* Li-zhen Liao,2,* Xiao-bian Dong,1 Xun Hu,1 Yue Guo,1 Zhi-min Du,1 Xin-xue Liao,1 Li-chun Wang1 1Department of Cardiology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, People’s Republic of China; 2Department of Health, Guangdong Pharmaceutical University, Guangzhou Higher Education Mega Center, Guangzhou, People’s Republic of China *These authors contributed equally to this work Abstract: This study describes the synthesis of a novel series of curcumin-inspired compounds via a facile synthetic route. The structures of these derivatives were ascertained using various spectroscopic and analytic techniques. The pharmacological effects of the target analogs were assessed by assaying their inhibition of angiotensin-converting enzyme (ACE). All of the synthesized derivatives exhibited considerable inhibition of ACE, with half-maximal inhibitory concentrations ranging from 1.23 to 120.32 µM. In a docking analysis with testicular ACE (tACE), the most promising inhibitor (4j) was efficiently accommodated in the deep cleft of the protein cavity, making close interatomic contacts with Glu162, His353, and Ala356, comparable with lisinopril. Compounds 4i, 4j, 4k, and 4l were further selected for determination of their vasodilator activity (cardiac output and stroke volume) on isolated rat hearts using the Langendorff technique. The bioavailability of compound 4j was determined in experimental mice. Keywords: curcumin, synthesis, ACE inhibition, antihypertensive, vasodilation, bioavail­ability

New strategies for the treatment of advanced melanoma are urgently required. The RAS/RAF/MAPK pathway and c-Src are deregulated in the majority of malignant melanomas, suggesting that they may interact functionally and are involved in the development and progression of the malignancy. Preclinical studies have demonstrated variable inhibition of melanoma cell growth by dasatinib in vitro. Src may act through different downstream signaling pathways. In the present study, we demonstrate that dasatinib induces changes in cell morphology, characterized by an arborized and contracted appearance, and accompanied by a reduction in cell proliferation in primary melanoma cells. This morphological change is demonstrated to be associated with the inhibition of nuclear translocation of activated ERK1/2. Together, these results indicate that Src may promote cell proliferation through the activation of the ERK signaling pathway in melanoma oncogenesis.

We investigate the nature of the recently observed narrow resonance $Z_{c}(3900)$, which is assumed to be a $D^{*}\bar{D}$ molecular state with quantum numbers $I^{G}J^{P}=1^{+}1^{+}$. Using QCD sum rules, we consider contributions up to dimension eight in the operator product expansion and work at the leading order in $\alpha_{s}$. The mass we arrived at is $(3.88 \pm 0.17) \mbox{GeV}$, which coincides with the mass of $Z_{c}(3900)$., Comment: 8 pages, 5 figures. accepted by JPG. arXiv admin note: substantial text overlap with arXiv:1107.1343