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The increasing abuse of facial manipulation methods, such as FaceSwap, Deepfakes etc., seriously threatens the authenticity of digital images/videos on the Internet. Therefore, it is of great importance to identify the facial videos to confirm the contents and avoid fake news or rumors. Many researchers have paid great attention to the detection of deepfakes and put forward a number of deep-learning-based detection models. The existing approaches mostly face the performance degradation in detecting low-quality(LQ) videos, i.e. heavily compressed or low-resolution videos through some SNS (Social Network Service), resulting in the limitation in real applications. To address this issue, in this paper, a novel Spatial Restore Detection Framework(SRDF) is proposed for improving the detection performance for LQ videos by restoring spatial features. We designed a feature extraction-enhancement block and a mapping block inspired by super-resolution methods, to restore and enhance texture features. An attention module was introduced to guide the texture features restoration and enhancement stage attending to different local areas and restoring the texture features. Besides, an improved isolated loss was put forward to prevent the expansion of a single area concerned. Moreover, we adopted a regional data augmentation strategy to prompt feature restore and enhancement in the region attended. Extensive experiments conducted on two deepfake datasets have validated the superiority of the proposed method compared to the state-of-the-art, especially in the scenarios of detecting low-quality deepfake videos. • Low-quality deepfake videos lost clues due to heavy compression or low resolution. • This paper put forward a novel Spatial Restore Detection Framework for LQ videos. • A feature extraction-enhancement block was designed to restore and enhance features. • An attention module was introduced to guide the texture features restoration. • The experiments conducted on two deepfake datasets have validated the superiority. [ABSTRACT FROM AUTHOR]

Given the substantial value and considerable training costs associated with deep neural network models, the field of deep neural network model watermarking has come to the forefront. While black-box model watermarking has made commendable strides, the current methodology for constructing poisoned images in the existing literature is simplistic and susceptible to forgery. Notably, there is a scarcity of black-box model watermarking techniques capable of discerning a unique user in a multi-user model distribution setting. For this reason, this paper proposes a novel black-box model watermarking method for unique identity identification, which is denoted as the ID watermarking of neural networks (IDwNet). Specifically, to enhance the distinguishability of deep neural network models in multi-user scenarios and mitigate the likelihood of poisoned image counterfeiting, this study develops a discrete cosine transform (DCT) and singular value decomposition (SVD)-based symmetrical embedding method to form the poisoned image. As this ID embedding method leads to indistinguishable deep features, the study constructs a poisoned adversary training strategy by simultaneously inputting clean images, poisoned images with the correct ID, and poisoned adversary images with incorrect IDs to train a deep neural network. Extensive simulation experiments show that the proposed scheme achieves excellent invisibility for the concealed ID, surpassing remarkably the state-of-the-art. In addition, the proposed scheme obtains a validation success rate exceeding 99% for the poisoned images at the cost of a marginal classification accuracy reduction of less than 0.5%. Moreover, even though there is only a 1-bit discrepancy between IDs, the proposed scheme still results in an accurate validation of user copyright. These results indicate that the proposed scheme is promising. [ABSTRACT FROM AUTHOR]

Bit rate is one of the important criterions for digital video quality. With some video tools, however, video bit rate can be easily increased without improving the video quality at all. In such a case, a claimed high bit rate video would actually have poor visual quality if it is up-converted from an original lower bit rate version. Therefore, exposing fake bit rate videos becomes an important issue for digital video forensics. To the best of our knowledge, although some methods have been proposed for exposing fake bit rate MPEG-2 videos, no relative work has been reported to further estimate their original bit rates. In this paper, we first analyze the statistical artifacts of these fake bit rate videos, including the requantization artifacts based on the first-digit law in the DCT frequency domain (12-D) and the changes of the structural similarity indexes between the query video and its sequential bit rate down-converted versions in the spatial domain (4-D), and then we propose a compact yet very effective 16-D feature vector for exposing fake bit rate videos and further estimating their original bit rates. The extensive experiments evaluated on hundreds of video sequences with four different resolutions and two typical compression schemes (i.e., MPEG-2 and H.264/AVC) have shown the effectiveness of the proposed method compared with the existing relative ones. [ABSTRACT FROM AUTHOR]

Highlights: [•] miRNAs are small noncoding RNAs that normally silence target gene expression. [•] Many miRNAs have enriched expression in the central nervous system. [•] miRNAs are required for proliferation and differentiation of neural stem cells. [•] Neuronal subtypes are specified by miRNAs by suppressing specific target genes. [•] Networks of miRNA-target are critical in cell fate determination of neurons and glia. [Copyright &y& Elsevier]

The analysis of video compression history is one of the important issues in video forensics. It can assist forensics analysts in many ways, e.g., to determine whether a video is original or potentially tampered with, or to evaluate the real quality of a re-encoded video, etc. In the existing literature, however, there are very few works targeting videos in HEVC format (the most recent standard), especially for the issue of the detection of transcoded videos. In this paper, we propose a novel method based on the statistics of Prediction Units (PUs) to detect transcoded HEVC videos from AVC format. According to the analysis of the footprints of HEVC videos, the frequencies of PUs (whether in symmetric patterns or not) are distinguishable between original HEVC videos and transcoded ones. The reason is that previous AVC encoding disturbs the PU partition scheme of HEVC. Based on this observation, a 5D and a 25D feature set are extracted from I frames and P frames, respectively, and are combined to form the proposed 30D feature set, which is finally fed to an SVM classifier. To validate the proposed method, extensive experiments are conducted on a dataset consisting of CIF ( 352 × 288 ) and HD 720p videos with a diversity of bitrates and different encoding parameters. Experimental results show that the proposed method is very effective at detecting transcoded HEVC videos and outperforms the most recent work. [ABSTRACT FROM AUTHOR]

Cerebral organoids recapitulate human brain development at a considerable level of detail, even in the absence of externally added signaling factors. The patterning events driving this self-organization are currently unknown. Here, we examine the developmental and differentiative capacity of cerebral organoids. Focusing on forebrain regions, we demonstrate the presence of a variety of discrete ventral and dorsal regions. Clearing and subsequent 3D reconstruction of entire organoids reveal that many of these regions are interconnected, suggesting that the entire range of dorso-ventral identities can be generated within continuous neuroepithelia. Consistent with this, we demonstrate the presence of forebrain organizing centers that express secreted growth factors, which may be involved in dorso-ventral patterning within organoids. Furthermore, we demonstrate the timed generation of neurons with mature morphologies, as well as the subsequent generation of astrocytes and oligodendrocytes. Our work provides the methodology and quality criteria for phenotypic analysis of brain organoids and shows that the spatial and temporal patterning events governing human brain development can be recapitulated in vitro. [ABSTRACT FROM AUTHOR]

Simple Summary: Reversion of the wild-type protein sequences of single transmembrane melanocortin accessory protein families (MRAP2) in mice and zebrafish created novel functional pharmacological modulators for regulating melanocortin 4 receptor (MC4R) signaling. All of the brand new reversed MRAP2 (rMRAP2) proteins could form proper dimeric topology on the plasma membrane and interact with and affect the ligand-stimulated pharmacological profiles of zebrafish and mouse MC4R signaling in vitro. As a member of the melanocortin receptor family, melanocortin 4 receptor (MC4R) plays a critical role in regulating energy homeostasis and feeding behavior, and has been proven as a promising therapeutic target for treating severe obesity syndrome. Numerous studies have demonstrated that central MC4R signaling is significantly affected by melanocortin receptor accessory protein 2 (MRAP2) in humans, mice and zebrafish. MRAP2 proteins exist as parallel or antiparallel dimers on the plasma membrane, but the structural insight of dual orientations with the pharmacological profiles has not yet been fully studied. Investigation and optimization of the conformational topology of MRAP2 are critical for the development of transmembrane allosteric modulators to treat MC4R-associated disorders. In this study, we synthesized a brand new single transmembrane protein by reversing wild-type mouse and zebrafish MRAP2 sequences and examined their dimerization, interaction and pharmacological activities on mouse and zebrafish MC4R signaling. We showed that the reversed zebrafish MRAPa exhibited an opposite function on modulating zMC4R signaling and the reversed mouse MRAP2 lost the capability for regulating MC4R trafficking but exhibited a novel function for cAMP cascades, despite proper expression and folding. Taken together, our results provided new biochemical insights on the oligomeric states and membrane orientations of MRAP2 proteins, as well as its pharmacological assistance for modulating MC4R signaling. [ABSTRACT FROM AUTHOR]

Objectives: The effects of general anaesthetics on fetal brain development remain elusive. Radial glial progenitors (RGPs) generate the majority of neurons in developing brains. Here, we evaluated the acute alterations in RGPs after maternal sevoflurane exposure. Methods: Pregnant mice were exposed to 2.5% sevoflurane for 6 hours on gestational day 14.5. Interkinetic nuclear migration (INM) of RGPs in the ventricular zone (VZ) of the fetal brain was evaluated by thymidine analogues labelling. Cell fate of RGP progeny was determined by immunostaining using various neural markers. The Morris water maze (MWM) was used to assess the neurocognitive behaviours of the offspring. RNA sequencing (RNA‐Seq) was performed for the potential mechanism, and the potential mechanism validated by quantitative real‐time PCR (qPCR), Western blot and rescue experiments. Furthermore, INM was examined in human embryonic stem cell (hESC)‐derived 3D cerebral organoids. Results: Maternal sevoflurane exposure induced temporary abnormities in INM, and disturbed the cell cycle progression of RGPs in both rodents and cerebral organoids without cell fate alternation. RNA‐Seq analysis, qPCR and Western blot showed that the Notch signalling pathway was a potential downstream target. Reactivation of Notch by Jag1 and NICD overexpression rescued the defects in INM. Young adult offspring showed no obvious cognitive impairments in MWM. Conclusions: Maternal sevoflurane exposure during neurogenic period temporarily induced abnormal INM of RGPs by targeting the Notch signalling pathway without inducing long‐term effects on RGP progeny cell fate or offspring cognitive behaviours. More importantly, the defects of INM in hESC‐derived cerebral organoids provide a novel insight into the effects of general anaesthesia on human brain development. [ABSTRACT FROM AUTHOR]

Acute brain injuries evoke various response cascades directing the formation of the glial scar. Here, we report that acute lesions associated with hemorrhagic injuries trigger a re-programming of oligodendrocytes. Single-cell RNA sequencing highlighted a subpopulation of oligodendrocytes activating astroglial genes after acute brain injuries. By using PLP-DsRed1/GFAP-EGFP and PLP-EGFP mem /GFAP-mRFP1 transgenic mice, we visualized this population of oligodendrocytes that we termed AO cells based on their concomitant activity of a stro- and o ligodendroglial genes. By fate mapping using PLP- and GFAP-split Cre complementation and repeated chronic in vivo imaging with two-photon laser-scanning microscopy, we observed the conversion of oligodendrocytes into astrocytes via the AO cell stage. Such conversion was promoted by local injection of IL-6 and was diminished by IL-6 receptor-neutralizing antibody as well as by inhibiting microglial activation with minocycline. In summary, our findings highlight the plastic potential of oligodendrocytes in acute brain trauma due to microglia-derived IL-6. [Display omitted] • Upon acute brain injuries, oligodendrocytes can activate astroglial genes • Oligodendrocytes can become astrocytes via the transitional AO cell status • Microglia-derived IL-6 drives the transition of oligodendrocytes to AO cells Bai et al. identify a subset of cells in mice with concomitant activation of astro- and oligo-dendroglial genes (termed AO cells), derived from oligodendrocytes upon acute brain injury. AO cells differentiate into astrocytes, oligodendrocytes, and oligodendrocyte precursors, and microglial-derived interleukin-6 promotes the transition of mature oligodendrocytes to AO cells. [ABSTRACT FROM AUTHOR]

With the growing value and high training cost of deep neural network (DNN) models, there has been increasing research interest in deep neural network model watermarking. However, the existing literature lacks robust model watermarking methods with retrospective functionality, which hinders multi-user distribution and fine-grained copyright verification of deep neural network models. To achieve the model watermarking with retrospective functionality that is generally denoted the model fingerprinting, this study proposes a novel robust black-box fingerprinting scheme for deep classification neural networks, in which a fingerprint that is unique for each user is inserted in the given DNN. Specifically, a DWT-DCT-SVD-based embedding method is introduced to construct a high-quality poisoned image by spreading the fingerprint as a poisoned trigger to the entire image, which both leads to the traceability of the to-be-protected DNN and significantly enhances the stealthiness and anti-forgery of the embedded poisoned trigger. As the amplitude of the embedded fingerprint is rather small, it poses a challenge that makes the model hard to capture features of the embedded fingerprint during the training process. To tackle this challenge, this study then proposes a poisoned feature enhancement module, which groups classification categories of clean images without the fingerprint as one type while taking the poisoned images with the correct fingerprint and the poisoned adversarial images containing the other incorrect fingerprints as another two different types. This module, which can be removed during fingerprint verification, improves the reliability and fidelity of the model fingerprinting. Accordingly, an adversarial training strategy is designed, aiming at enhancing the effective training of classification neural network models that contain the fingerprint with small embedding strength. Combining these strategies then gives rise to the proposed scheme, which is denoted the UfNet for notational convenience. Extensive experimental simulation results demonstrate the excellent invisibility of the fingerprint in the poisoned image and the desirable verification of the fingerprint in case of even a one-bit difference. Additionally, it also exhibits robustness against the related attacks such as STRIP, Neural Cleanse, Fine-Pruning, and GradCAM, which outperforms the state-of-the-arts (SOTAs). Furthermore, the proposed UfNet is robust to collusion attacks and frame the innocent. These results show the feasibility and effectiveness of the introduced model fingerprinting framework and the proposed implementation methodology in this paper. • Introduce the concept and implementation of model fingerprinting. • Provide a digital-watermarking-based method for the poisoned image construction. • Develop a poisoned feature enhancement module and an adversarial training strategy. • Propose the UfNet for model fingerprinting, outperforming the state-of-the-arts. [ABSTRACT FROM AUTHOR]

Abstract: Chondroitin sulfate (CS) and dermatan sulfate (DS) proteoglycans are major components of the extracellular matrix implicated in neural development, plasticity and regeneration. While it is accepted that CS are major inhibitors of neural regeneration, the contributions of DS to regeneration have not been assessed. To enable a novel approach in studies on DS versus CS roles during development and regeneration, we generated a mouse deficient in the dermatan 4-O-sulfotransferase1 (Chst14 −/−), a key enzyme in the synthesis of iduronic acid-containing modules found in DS but not CS. In wild-type mice, Chst14 is expressed at high levels in the skin and in the nervous system, and is enriched in astrocytes and Schwann cells. Ablation of Chst14, and the assumed failure to produce DS, resulted in smaller body mass, reduced fertility, kinked tail and increased skin fragility compared with wild-type (Chst14 +/+) littermates, but brain weight and gross anatomy were unaffected. Neurons and Schwann cells from Chst14 −/− mice formed longer processes in vitro, and Chst14 −/− Schwann cells proliferated more than Chst14 +/+ Schwann cells. After femoral nerve transection/suture, functional recovery and axonal regrowth in Chst14 −/− mice were initially accelerated but the final outcome 3months after injury was not better than that in Chst14 +/+ littermates. These results suggest that while Chst14 and its enzymatic products might be of limited importance for neural development, they may contribute to the regeneration-restricting environment in the adult mammalian nervous system. [Copyright &y& Elsevier]

Nowadays, it remains a major challenge to efficiently compress encrypted images. In this paper, we propose a novel encryption-then-compression (ETC) scheme to enhance the performance of lossy compression on encrypted gray images through heuristic optimization of bitplane allocation. Specifically, in compressing an encrypted image, we take a bitplane as a basic compression unit and formulate the lossy compression task as an optimization problem that maximizes the peak signal-to-noise ratio (PSNR) subject to a given compression ratio. We then develop a heuristic strategy of bitplane allocation to approximately solve this optimization problem, which leverages the asymmetric characteristics of different bitplanes. In particular, an encrypted image is divided into four sub-images. Among them, one sub-image is reserved, while the most significant bitplanes (MSBs) of the other sub-images are selected successively, and so are the second, third, etc., MSBs until a given compression ratio is met. As there exist clear statistical correlations within a bitplane and between adjacent bitplanes, where bitplane denotes those belonging to the first three MSBs, we further use the low-density parity-check (LDPC) code to compress these bitplanes according to the ETC framework. In reconstructing the original image, we first deploy the joint LDPC decoding, decryption, and Markov random field (MRF) exploitation to recover the chosen bitplanes belonging to the first three MSBs in a lossless way, and then apply content-adaptive interpolation to further obtain missing bitplanes and thus discarded pixels, which is symmetric to the encrypted image compression process. Experimental simulation results show that the proposed scheme achieves desirable visual quality of reconstructed images and remarkably outperforms the state-of-the-art ETC methods, which indicates the feasibility and effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Polysialic acid (PSA) is a large and highly negatively charged glycan that plays crucial roles in nervous system development and function in the adult. It has been suggested to facilitate cell migration, neurite outgrowth, and synaptic plasticity because its hydration volume could enhance flexibility of cell interactions. Evidence for receptors of PSA has so far been elusive. We now identified histone H1 as binding partner of PSA via a single-chain variable fragment antibody using an anti-idiotypic approach. Histone H1 directly binds to PSA as shown by ELISA. Surface biotinylation of cultured cerebellar neurons indicated an extracellular localization of histone H1. Immuno-staining of live cerebellar neurons and Schwann cells confirmed that an extracellular pool of histone H1 colocalizes with PSA at the cell surface. Histone H1 was also detected in detergent-insoluble synaptosomal membrane subfractions and postsynaptic densities. When applied in vitro, histone H1 stimulated neuritogenesis, process formation and proliferation of Schwann cells, and migration of neural precursor cells via a PSA-dependent mechanism, further indicating that histone H1 is active extracellularly. These in vitro observations suggested an important functional role for the interaction between histone H1 and PSA not only for nervous system development but also for regeneration in the adult. Indeed, histone H1 improved functional recovery, axon regrowth, and precision of reinnervation of the motor branch in adult mice with femoral nerve injury. Our findings encourage investigations on the therapeutic potential of histone H1 in humans. [ABSTRACT FROM AUTHOR]

α2,8 Polysialic acid (PSA) is a carbohydrate attached to the glycoprotein backbone of the neural cell adhesion molecule (NCAM) and implicated in nervous system development and repair. Here, we investigated whether PSA can improve functional recovery after peripheral nerve lesion in adult mice. We applied a functional PSA mimicking peptide or a control peptide in a polyethylene cuff used to surgically reconnect the severed stumps of the femoral nerve before it bifurcates into the motor and sensory branches. Using video-based motion analysis to monitor motor recovery over a 3 month postoperative period, we observed a better functional outcome in the PSA mimetic-treated than in control mice receiving a control peptide or phosphate buffered saline. Retrograde tracing of regenerated motoneurons and morphometric analyses showed that motoneuron survival, motoneuron soma size and axonal diameters were not affected by treatment with the PSA mimetic. However, remyelination of regenerated axons distal to the injury site was considerably improved by the PSA mimetic indicating that effects on Schwann cells in the denervated nerve may underlie the functional effects seen in motor recovery. In line with this notion was the observation that the PSA mimetic enhanced the elongation of Schwann cell processes and Schwann cell proliferation in vitro, when compared with the control peptide. Moreover, Schwann cell proliferation in vivo was enhanced in both motor and sensory branches of the femoral nerve by application of the PSA mimetic. These effects were likely mediated by NCAM through its interaction with the fibroblast growth factor receptor (FGFR), since they were not observed when the PSA mimetic was applied to NCAM-deficient Schwann cells, and since application of two different FGFR inhibitors reduced process elongation from Schwann cells in vitro. Our results indicate the potential of PSA mimetics as therapeutic agents promoting motor recovery and myelination after peripheral nerve injury. [ABSTRACT FROM PUBLISHER]