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Objective: This study was to investigate the protective effect of Noni polysaccharides on ionizing radiation injury and its regulation of intestinal flora in mice. Methods: Fifty KM male mice were randomly divided into normal group, model group, noni polysaccharide low-dose group, noni polysaccharide medium-dose group and Noni polysaccharide high-dose group. The whole body of the mice was irradiated by the medical electron linear accelerator, thus establishing acute radiation-damaged mice model. Subsequently, survival quality of mice after irradiating was observed, and related biochemical indicators of serum and liver tissue of mice after irradiating for 72 h were detected. Furthermore, 16S rRNA sequencing of mouse feces was performed to analyze diversity of intestinal flora. Results: Noni polysaccharides could improve survival quality of radiation-damaged mice, and increase organ index, peripheral blood leukocyte (WBC) number, spleen nodule number, bone marrow DNA content. Moreover, noni polysaccharides could reduce the rate of bone marrow polychromatic erythrocyte micronucleus (MN-PCE), and increase the activities of antioxidant enzymes catalase (CAT), superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) in serum and liver, and reduce malondialdehyde (MDA) content. Compared with the MC group, the increase rate of peripheral white blood cell count and number of splenic noduleswas 46.85%, 38.23%, and the content of bone marrow DNA increased by 51.95%, the reduction rate of MN-PCE was 38.84% of Noni polysaccharide high-dose group. Meanwhile, the oxidative stress of mice after irradiating had improvement in different degree of Noni polysaccharide. Additionally, Noni polysaccharides could promote the growth of intestinal flora of radiation-damaged mice in a direction of beneficial to host health. Meanwhile, Noni polysaccharides could accelerate the growth of probiotics and inhibit the colonization of harmful bacteria, and recover the changes of intestinal flora caused by ionizing radiation. Conclusion: Noni polysaccharides exhibited obvious protective effect on ionizing radiation-damaged mice caused by X-ray, and showed certain restoring effect on intestinal flora disturbance caused by radiation.

Abstract The precise identification of surface imperfections in steel strips is crucial for ensuring steel product quality. To address the challenges posed by the substantial model size and computational complexity in current algorithms for detecting surface defects in steel strips, this paper introduces SS-YOLO (YOLOv7 for Steel Strip), an enhanced lightweight YOLOv7 model. This method replaces the CBS module in the backbone network with a lightweight MobileNetv3 network, reducing the model size and accelerating the inference time. The D-SimSPPF module, which integrates depth separable convolution and a parameter-free attention mechanism, was specifically designed to replace the original SPPCSPC module within the YOLOv7 network, expanding the receptive field and reducing the number of network parameters. The parameter-free attention mechanism SimAM is incorporated into both the neck network and the prediction output section, enhancing the ability of the model to extract essential features of strip surface defects and improving detection accuracy. The experimental results on the NEU-DET dataset show that SS-YOLO achieves a 97% mAP50 accuracy, which is a 4.5% improvement over that of YOLOv7. Additionally, there was a 79.3% reduction in FLOPs(G) and a 20.7% decrease in params. Thus, SS-YOLO demonstrates an effective balance between detection accuracy and speed while maintaining a lightweight profile.

Abstract Background Globally, breast cancer in women is the fifth leading cause of cancer death. There is an urgent need to explore the molecular mechanism of breast cancer proliferation and metastasis. Method TCGA database analysis was used to analyze genes expression in breast cancer and normal samples and the association between gene expression and prognosis. Immunohistochemical staining, qPCR and western blotting was sued to detected gene expression. The cell function tests were conducted to investigate the effects of TEX19 and CDK4 with abnormal expression on cell proliferation, migration, apoptosis, cell cycle, and colony formation. Bioinformatics analysis methods combined with CHX tracking experiment and Co-IP experiment were performed to screen and verify the downstream molecule and regulatory mechanism of TEX19. Besides, subcutaneous tumorigenesis model in nude mice was constructed. Results TEX19 was significantly upregulated in breast cancer, and the TEX19 level was related to tumor invasion and prognosis. TEX19 knockdown inhibited the proliferation and migration of breast cancer cells, increased cell apoptosis, and blocked the cell cycle in the G2 phase. Besides, TEX19 suppressed the growth of tumors in the body. Mechanically, TEX19 upregulated the level of CDK4 protein, which depended on the E3 ubiquitin ligase SKP2. Specifically, TEX19 knockdown and SKP2 protein overexpression destroyed the stability of CDK4 protein and enhanced the ubiquitination of CDK4 protein. Additionally, CDK4 knockdown inhibited the proliferation, migration, and colony formation of breast cancer cells, and alleviated the promotion of TEX19 overexpression on the proliferation and migration of breast cancer cell. Conclusion TEX19 and CDK4 were upregulated in breast cancer, and TEX19 increased the level of CDK4 protein by influencing SKP2-mediated ubiquitination of CDK4, thereby promoting the progression of breast cancer.

Emerging evidence suggests that circular RNAs (circRNAs) are involved in the regulation of tumourigenesis and progression of a variety of malignant tumours. In this study, we aimed to identify laryngeal squamous cell carcinoma (LSCC)-specific circRNAs and explore their biological functions and underlying molecular mechanisms. Employing microarray and qRT-PCR, hsa_circ_0000825 was found to be significantly increased in LSCC tissues versus para-cancerous tissues. High hsa_circ_0000825 expression was positively associated with advanced clinical stages, lymph node metastasis, and poor survival. Furthermore, the overexpression of hsa_circ_0000825 in TU177 and AMC-HN-8 cells promoted cell proliferation. Transwell assays showed enhanced migration and invasion of TU177 and AMC-HN-8 cells upon overexpression of hsa_circ_0000825. Conversely, the knockdown of hsa_circ_0000825 had the opposite effect. Xenograft tumours in BALB/c nude mice derived from hsa_circ_0000825-overexpressed TU177 cells showed greater volume and weight than those derived from control TU177 cells. Mechanistically, nuclear-cytoplasmic fractionation assay confirmed that hsa_circ_0000825 was mainly located in the cytoplasm of TU177 and AMC-HN-8 cells. The AGO2-RNA immunoprecipitation (RIP) assay revealed that hsa_circ_0000825 was significantly enriched in the AGO2-precipitated complex in both TU177 and AMC-HN-8 cells, suggesting that this circRNA may function via a competitive endogenous RNA (ceRNA) mechanism. Next, bioinformatics analysis, biotinylated-oligo pull-down assay and dual-luciferase reporter assay verified that miR-766 could be sponged by hsa_circ_0000825 and also target 3′UTR of HOXD10 mRNA. Moreover, miR-766 was shown to be involved in the pro-oncogenic effect of hsa_circ_0000825. This occurred via the mediation of hsa_circ_0000825-enhanced HOXD10 mRNA by the ceRNA mechanism in TU177 and AMC-HN-8 cells. Besides, RNA-binding protein (RBP) ELAVL1 interacted with hsa_circ_0000825 in TU177 and AMC-HN-8 cells, as revealed through bioinformatics analysis, biotinylated-oligo pull-down assays, and RIP assays. ELAVL1 knockdown decreased cell proliferation by 38 % and 34 % in hsa_circ_0000825-overexpressed TU177 and AMC-HN-8 cells (P

CO2 has rarely been examined as a fire indicator owing to the uncertainty in its background concentration. Nevertheless, for a specific building space with a detector, the background CO2 concentration signal can be determined and documented using artificial intelligence technology. Based on the aforementioned concept, this study explored the feasibility of using CO2 signal features as fire indicators for building fire detection. First, CO2 concentrations under fire and no-fire conditions were obtained to generate study databases. Second, the deep temporal clustering (DTC) model was used to classify CO2 signal features between fire and no-fire scenes, and the clustering accuracy and purity were selected to determine the clustering performance. Third, the k-means, agglomerative clustering, and spectral bi-clustering models were employed to validate the clustering advantages of the DTC model. The results proved the CO2 concentration to be more suitable as a combustion indicator for fire detection compared to the CO2 concentration rate, exhibiting higher clustering accuracy and purity values. Additionally, for time-series clustering, the DTC model outperformed traditional clustering models. The findings of this study represent a fundamental step toward the realization of space-exclusive multi-sensor fire-detection technology for assisting smart building construction in a cost-effective and accurate manner.

Aphidius gifuensis is the dominant parasitic natural enemy of aphids. Elucidating the molecular mechanism of host recognition of A. gifuensis would improve its biological control effect. Chemosensory proteins (CSPs) play a crucial role in insect olfactory systems and are mainly involved in host localization. In this study, a total of nine CSPs of A. gifuensis with complete open reading frames were identified based on antennal transcriptome data. Phylogenetic analysis revealed that AgifCSPs were mainly clustered into three subgroups (AgifCSP1/2/7/8, AgifCSP3/9, and AgifCSP4/5/6). AgifCSP2/5 showed high expression in the antennae of both sexes. Moreover, AgifCSP5 was found to be specifically expressed in the antennae. In addition, fluorescent binding assays revealed that AifCSP5 had greater affinities for 7 of 32 volatile odor molecules from various sources. Molecular docking and site-directed mutagenesis results revealed that the residue at which AgifCSP5 binds to these seven plant volatiles is Tyr75. Behavior tests further confirmed that trans-2-nonenal, one of the seven active volatiles in the ligand binding test, significantly attracted female adults at a relatively low concentration of 10 mg/mL. In conclusion, AgifCSP5 may be involved in locating aphid-infested crops from long distances by detecting and binding trans-2-nonenal. These findings provide a theoretical foundation for further understanding the olfactory recognition mechanisms and indirect aphid localization behavior of A. gifuensis from long distances by first identifying the host plant of aphids.

Sea surface wind, waves, and currents are the three basic parameters that describe the dynamic process of sea surface, and they are coupled with each other. To more accurately describe large-scale ocean motion and extract the ocean dynamic parameters, we adopt the spaceborne Doppler measurement to estimate the radial Doppler velocity generated by the sea surface motion. Due to the presence of wind and waves, the Doppler spectrum will be formed, shifted and broadened. Pulse-pair phase interference is used to obtain the Doppler spectrum from the sea surface echo. We simulate the Doppler spectrum with different look geometry and ocean states in a spaceborne condition. In this paper, the Doppler centroid variations are estimated after reducing the platform Doppler velocity under different observation conditions. With the increase in wind speed, the measured Doppler shift increases, and the simulated Doppler centroid accuracy is estimated. In addition, the measurement error along the trace direction is at the maximum, and the error in the cross-track is the smallest. At moderate wind-wave conditions, the Doppler velocity offset can be less than 0.1 m/s.

Abstract Face forgery represented by DeepFake technique has raised severe societal concerns. Due to the different scales of tampering traces and the different resolutions of face images, adopting common processing pipelines and standard form of convolutional neural networks (CNNs) will lead to problems such as omission, redundancy, and bias when extracting key discriminative features. To solve the above issues, unlike most existing methods that treat face forensics as a vanilla binary classification task, the authors instead reformulate it as a multi‐scale object detection problem and propose a novel framework called MSFRNet based on multi‐scale feature extraction. Concretely, to alleviate the issues of features omission and redundancy, the authors construct a two‐stream prediction network, where the shallow branch discovers small‐scale objects such as tiny noise by capturing low‐level features with higher resolution and more details, while the deep stream exploits larger receptive fields to detect large‐scale blocky artefacts. Moreover, a multi‐scale feature extraction module is designed to enrich feature representations in each stream. To solve the problem of features bias and ensure that unbiased feature representations are learned, more appropriate data augmentation approaches are proposed by introducing counterfactual causal reasoning. Extensive experiments demonstrate that our framework outperforms most ordinary binary classifiers and achieves positive performance.

Introduction: Prostate cancer (PCa) is the second most common malignancy in men. Despite multidisciplinary treatments, patients with PCa continue to experience poor prognoses and high rates of tumor recurrence. Recent studies have shown that tumor-infiltrating immune cells (TIICs) are associated with PCa tumorigenesis.Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to derive multi-omics data for prostate adenocarcinoma (PRAD) samples. The CIBERSORT algorithm was used to calculate the landscape of TIICs. Weighted gene co-expression network analysis (WGCNA) was performed to determine the candidate module most significantly associated with TIICs. LASSO Cox regression was applied to screen a minimal set of genes and construct a TIIC-related prognostic gene signature for PCa. Then, 78 PCa samples with CIBERSORT output p-values of less than 0.05 were selected for analysis. WGCNA identified 13 modules, and the MEblue module with the most significant enrichment result was selected. A total of 1143 candidate genes were cross-examined between the MEblue module and active dendritic cell-related genes.Results: According to LASSO Cox regression analysis, a risk model was constructed with six genes (STX4, UBE2S, EMC6, EMD, NUCB1 and GCAT), which exhibited strong correlations with clinicopathological variables, tumor microenvironment context, antitumor therapies, and tumor mutation burden (TMB) in TCGA-PRAD. Further validation showed that the UBE2S had the highest expression level among the six genes in five different PCa cell lines.Discussion: In conclusion, our risk-score model contributes to better predicting PCa patient prognosis and understanding the underlying mechanisms of immune responses and antitumor therapies in PCa.

With the rapid development of remote sensing technology, the application of convolutional neural networks in remote sensing object detection has become very widespread, and some multimodal feature fusion networks have also been proposed in recent years. However, these methods generally do not consider the long-tailed problem that is widely present in remote sensing images, which limits the further improvement of model detection performance. To solve this problem, we propose a novel long-tailed object detection method for multimodal remote sensing images, which can effectively fuse the complementary information of visible light and infrared images and adapt to the imbalance between positive and negative samples of different categories. Firstly, the dynamic feature fusion module (DFF) based on image entropy can dynamically adjust the fusion coefficient according to the information content of different source images, retaining more key feature information for subsequent object detection. Secondly, the instance-balanced mosaic (IBM) data augmentation method balances instance sampling during data augmentation, providing more sample features for the model and alleviating the negative impact of data distribution imbalance. Finally, class-balanced BCE loss (CBB) can not only consider the learning difficulty of specific instances but also balances the learning difficulty between categories, thereby improving the model’s detection accuracy for tail instances. Experimental results on three public benchmark datasets show that our proposed method achieves state-of-the-art performance; in particular, the optimization of the long-tailed problem enables the model to meet various application scenarios of remote sensing image detection.

Long noncoding RNAs (lncRNAs) have an effect on the occurrence and progression of a considerable number of diseases, especially cancer. Existing research has suggested that MAGI2 antisense RNA 3 (MAGI2-AS3) takes on a critical significance in the development of hepatocellular carcinoma and lung cancer. However, the functions of MAGI2-AS3 in laryngeal squamous cell carcinoma (LSCC) remain unclear. In this study, MAGI2-AS3 expression level in LSCC tissue and cell lines was detected, and the effect of MAGI2-AS3 overexpressed on LSCC phenotypes and the possible influence mechanisms were examined. MAGI2-AS3 was downregulated in the tissues of LSCC patients versus non-tumor tissues, and it was correlated with advanced TNM (tumor, node, metastasis) stage and lymph node metastases, as indicated by the results of this study. MAGI2-AS3 inhibited the proliferation, migration, and invasion of LSCC cells in vitro and in vivo . Furthermore, the hypermethylation level of the MAGI2-AS3 promoter region was indicated by bisulfite genomic sequencing and methylation-specific polymerase chain reaction, such that MAGI2-AS3 expression was downregulated. Besides, MAGI2-AS3 promoter hypermethylation was regulated by DNA methyltransferase 1 (DNMT1), and MAGI2-AS3 expression was reversed by 5-Aza-2′-deoxycytidine (5-Aza). Moreover, the result of the RNA pull-down experiment suggested that 38 proteins were enriched in the MAGI2-AS3 group versus the control group in TU177 cells. To be specific, SPT6 (ie, a conserved protein) was enriched by fold change >10. SPT6 knockdown reduced the antitumor effect of MAGI2-AS3 in TU177 and AMC-HN-8 cells. Meanwhile, SPT6 overexpression inhibited the proliferation, metastasis, and invasion of TU177 and AMC-HN-8 cells. As revealed by the above findings, DNMT1-regulated MAGI2-AS3 promoter hypermethylation led to downregulated MAGI2-AS3 expression, such that the presence and progression of LSCC were inhibited in an SPT6 binding-dependent manner.

PurposeThe hallmark of non-arteritic anterior ischemic optic neuropathy (NAION) is vascular compromise to the anterior optic nerve and thinning of the retinal nerve fiber layer (RNFL) and secondary degeneration of the retinal ganglion cell body or thinning of the ganglion cell complex (GCC). This study investigates optical coherence tomography (OCT) and OCT Angiography (OCTA) changes in chronic NAION and identifies imaging biomarkers that best predict disease.MethodsWe performed a retrospective case-control study of 24 chronic NAION eyes (18 patients) and 70 control eyes (45 patients) to compare both whole-eye and regional OCT, OCTA, static perimetry measurements. OCT measurements were quantified automatically using commercial software, and OCTA was analyzed using custom MATLAB script with large vessel removal to measure 154 total parameters per eye.ResultsWe confirmed that static perimetry mean deviation (MD) was significantly worse in chronic NAION (–13.53 ± 2.36) than control (–0.47 ± 0.72; P < 0.001) eyes, and NAION eyes had 31 μm thinner RNFL (control: 95.9 ± 25.8 μm; NAION: 64.5 ± 18.0, P < 0.001), and 21.8 μm thinner GCC compared with controls (control: 81.5 ± 4.4 μm; NAION: 59.7 ± 10.5, P < 0.001). Spearman correlation analysis of OCTA parameters reveal that vessel area density (VAD) and flux are highly correlated with visual field MD and OCT measurements. Hierarchical clustering two distinct groups (NAION and control), where standardized measurements of NAION eyes were generally lower than controls. Two-way mixed ANOVAs showed significant interaction between patient status (control and chronic NAION) and structure (optic disk and macula) for annulus VAD and flux values and mean RNFL and GCC thickness. Post-hoc tests showed this effect stems from lower peripapillary values in NAION compared to controls. Separate logistic regression models with LASSO regularization identified VAD and flux are one of the best OCTA parameters for predicting NAION.ConclusionIschemic insult to the optic disk is more severe likely from primary degeneration of the affected peripapillary region while macula is affected by secondary retrograde degeneration and loss of retinal ganglion cells. In addition to OCT measurements, peripapillary and macular vascular parameters such as VAD and flux are good predictors of optic nerve and retinal changes in NAION.

BackgroundA large and growing body of neuroimaging research has concentrated on patients with attention-deficit/hyperactivity disorder (ADHD), but with inconsistent conclusions. This article was intended to investigate the common and certain neural alterations in the structure and function of the brain in patients with ADHD and further explore the differences in brain alterations between adults and children with ADHD.MethodsWe conducted an extensive literature search of whole-brain voxel-based morphometry (VBM) and functional magnetic resonance imaging (fMRI) studies associated with ADHD. Two separate meta-analyses with the seed-based d mapping software package for functional neural activation and gray matter volume (GMV) were carried out, followed by a joint analysis and a subgroup analysis.ResultsThis analysis included 29 VBM studies and 36 fMRI studies. Structurally, VBM analysis showed that the largest GMV diminutions in patients with ADHD were in several frontal-parietal brain regions, the limbic system, and the corpus callosum. Functionally, fMRI analysis discovered significant hypoactivation in several frontal-temporal brain regions, the right postcentral gyrus, the left insula, and the corpus callosum.ConclusionThis study showed that abnormal alterations in the structure and function of the left superior frontal gyrus and the corpus callosum may be the key brain regions involved in the pathogenesis of ADHD in patients and may be employed as an imaging metric for patients with ADHD pending future research. In addition, this meta-analysis discovered neuroanatomical or functional abnormalities in other brain regions in patients with ADHD as well as findings that can be utilized to guide future research.

Abstract Generative adversarial network‐based deep generative model is widely applied in creating hyper‐realistic face‐swapping images and videos. However, its malicious use has posed a great threat to online contents, thus making detecting the authenticity of images and videos a tricky task. Most of the existing detection methods are only suitable for one type of forgery and only work for low‐quality tampered images, restricting their applications. This paper concerns the construction of a novel discriminator with better comprehensive capabilities. Through analysis of the visual characteristics of manipulated images from the perspective of image quality, it is revealed that the synthesized face does have different degrees of quality degradation compared to the source content. Therefore, several kinds of image quality‐related handicraft features are extracted, including texture, sharpness, frequency domain features, and deep features, to unveil the inconsistent information and modification traces in the fake faces. In this way, a 1065‐dimensional vector of each image is obtained through multi‐feature fusion, and it is then fed into RF to train a targeted binary classification detector. Extensive experiments have shown that the proposed scheme is superior to the previous methods in recognition accuracy on multiple manipulation databases including the Celeb‐DF database with better visual quality.

BackgroundMany neuroimaging studies have reported abnormalities in brain structure and function in internet gaming disorder (IGD). However, the findings were divergent. We aimed to provide evidence-based evidence of structural and functional changes in IGD by conducting a meta-analysis integrating these studies quantitatively.MethodA systematic search was conducted in PubMed, ScienceDirect, Web of Science, and Scopus from January 1, 2010 to October 31, 2021, to identify eligible voxel-based morphometry (VBM) and functional magnetic resonance imaging (fMRI) studies. Brain alternations between IGD subjects and healthy controls (HCs) were compared using the anisotropic seed-based d mapping (AES-SDM) meta-analytic method. Meta-regression analysis was used to investigate the relationship between gray matter volume (GMV) alterations and addiction-related clinical features.ResultsThe meta-analysis contained 15 VBM studies (422 IGD patients and 354 HCs) and 30 task-state fMRI studies (617 IGD patients and 550 HCs). Compared with HCs, IGD subjects showed: (1) reduced GMV in the bilateral anterior/median cingulate cortex, superior/inferior frontal gyrus and supplementary motor area; (2) hyperactivation in the bilateral inferior frontal gyrus, precentral gyrus, left precuneus, right inferior temporal gyrus and right fusiform; (3) hypoactivation in the bilateral lingual and the left middle frontal gyrus; and (4) both decreased GMV and increased activation in the left anterior cingulate. Furthermore, Meta-regression revealed that GMV reduction in left anterior cingulate were positively correlated with BIS-11 score [r = 0.725, p = 0.012(uncorrected)] and IAT score [r = 0.761, p = 0.017(uncorrected)].ConclusionThis meta-analysis showed structural and functional impairments in brain regions related to executive control, cognitive function and reward-based decision making in IGD. Furthermore, multi-domain assessments captured different aspects of neuronal changes in IGD, which may help develop effective interventions as potential therapeutic targets.

Summary: In this report, we provide evidence showing diminished expression of the mineral dust-induced gene (mdig), a previously identified oncogenic gene, in human triple negative breast cancer (TNBC). Using a mouse model of orthotopic xenograft of the TNBC MDA-MB-231 cells, we demonstrate that mdig promotes the growth of primary tumors but inhibits metastasis of these cells in vivo. Knockout of mdig resulted in an enhancement of H3K36me3 in the genome and upregulation of some X chromosome-linked genes for cell motility, invasion, and metastasis. Silencing MAGED2, one of the most upregulated and H3K36me3-enriched genes resulted from mdig depletion, can partially reverse the invasive migration of the mdig knockout cells. The anti-metastatic and inhibitory role of mdig on H3K36me3 was cross-validated in another cell line, A549 lung cancer cells. Together, our data suggest that mdig is antagonist against H3K36me3 that enforces expression of genes, such as MAGED2, for cell invasion and metastasis.

In recent years, with the rapid development of technology, artificial intelligence (AI) security issues represented by adversarial sample attack have aroused widespread concern in society. Adversarial samples are often generated by surrogate models and then transfer to attack the target model, and most AI models in real-world scenarios belong to black boxes; thus, transferability becomes a key factor to measure the quality of adversarial samples. The traditional method relies on the decision boundary of the classifier and takes the boundary crossing as the only judgment metric without considering the probability distribution of the sample itself, which results in an irregular way of adding perturbations to the adversarial sample, an unclear path of generation, and a lack of transferability and interpretability. In the probabilistic generative model, after learning the probability distribution of the samples, a random term can be added to the sampling to gradually transform the noise into a new independent and identically distributed sample. Inspired by this idea, we believe that by removing the random term, the adversarial sample generation process can be regarded as the static sampling of the probabilistic generative model, which guides the adversarial samples out of the original probability distribution and into the target probability distribution and helps to boost transferability and interpretability. Therefore, we proposed a score-matching-based attack (SMBA) method to perform adversarial sample attacks by manipulating the probability distribution of the samples, which showed good transferability in the face of different datasets and models and provided reasonable explanations from the perspective of mathematical theory and feature space. Compared with the current best methods based on the decision boundary of the classifier, our method increased the attack success rate by 51.36% and 30.54% to the maximum extent in non-targeted and targeted attack scenarios, respectively. In conclusion, our research established a bridge between probabilistic generative models and adversarial samples, provided a new entry angle for the study of adversarial samples, and brought new thinking to AI security.

To separate the noise and important signal features of the indoor carbon dioxide (CO2) concentration signal, we proposed a noise cancellation method, based on time-varying, filtering-based empirical mode decomposition (TVF-EMD) with Bayesian optimization (BO). The adaptive parameters of TVF-EMD, that is, bandwidth threshold ξ and B-spline order n, were determined by the BO algorithm, and the correlation coefficient for the kurtosis index (CCKur) constituted the objective function. Initially, the objective function CCKur was introduced to systematically identify anomalous signals while preserving signal feature extraction between the modes and the input signal. Subsequently, the proposed signal noise cancellation model based on TVF-EMD and the BO algorithm were employed, along with the Hurst exponent, to extract the sensitive mode. An examination of the optimization indices of the decomposed intrinsic mode functions (IMFs), namely CC, Kur, MI, EE, EEMI, and CCKur, revealed that the synthetic measurement index CCKur and objective function fitness were reasonable and effective. The proposed method exhibited better signal cancellation performance, compared to that of TVF-EMD with the default values, EMD, the moving average method, and the exponential smoothing method.

ASH1L is a member of the Trithorax-group protein and acts as a histone methyltransferase for gene transcription activation. It is known that ASH1L modulates H3K4me3 and H3K36me2/3 at its gene targets, but its specific mechanism of histone recognition is insufficiently understood. In this study, we found that the ASH1L plant homeodomain (PHD) finger interacts with mono-, di-, and trimethylated states of H3K4 peptides with comparable affinities, indicating that ASH1L PHD non-selectively binds to all three methylation states of H3K4. We solved nuclear magnetic resonance structures picturing the ASH1L PHD finger binding to the dimethylated H3K4 peptide and found that a narrow binding groove and residue composition in the methylated-lysine binding pocket restricts the necessary interaction with the dimethyl-ammonium moiety of K4. In addition, we found that the ASH1L protein is overexpressed in castrate-resistant prostate cancer (PCa) PC3 and DU145 cells in comparison to PCa LNCaP cells. The knockdown of ASH1L modulated gene expression and cellular pathways involved in apoptosis and cell cycle regulation and consequently induced cell cycle arrest, cell apoptosis, and reduced colony-forming abilities in PC3 and DU145 cells. The overexpression of the C-terminal core of ASH1L but not the PHD deletion mutant increased the overall H3K36me2 level but had no effect on the H3K4me2/3 level. Overall, our study identifies the ASH1L PHD finger as the first native reader that non-selectively recognizes the three methylation states of H3K4. Additionally, ASH1L is required for the deregulation of cell cycle and survival in PCas.

Due to the rising concentration of atmospheric CO2, climate change is predicted to intensify episodes of drought. However, our understanding of how combined environmental conditions, such as elevated CO2 and drought together, will influence crop-insect interactions is limited. In the present study, the direct effects of combined elevated CO2 and drought stress on wheat (Triticum aestivum) nutritional quality and insect resistance, and the indirect effects on the grain aphid (Sitobion miscanthi) performance were investigated. The results showed that, in wheat, elevated CO2 alleviated low water content caused by drought stress. Both elevated CO2 and drought promoted soluble sugar accumulation. However, opposite effects were found on amino acid content—it was decreased by elevated CO2 and increased by drought. Further, elevated CO2 down-regulated the jasmonic acid (JA) -dependent defense, but up-regulated the salicylic acid (SA)-dependent defense. Meanwhile, drought enhanced abscisic acid accumulation that promoted the JA-dependent defense. For aphids, their feeding always induced phytohormone resistance in wheat under either elevated CO2 or drought conditions. Similar aphid performance between the control and the combined two factors were observed. We concluded that the aphid damage suffered by wheat in the future under combined elevated CO2 and drier conditions tends to maintain the status quo. We further revealed the mechanism by which it happened from the aspects of wheat water content, nutrition, and resistance to aphids.

BackgroundPrevious voxel-based morphometric (VBM) and functional magnetic resonance imaging (fMRI) studies have shown changes in brain structure and function in cocaine addiction (CD) patients compared to healthy controls (HC). However, the results of these studies are poorly reproducible, and it is unclear whether there are common and specific neuroimaging changes. This meta-analysis study aimed to identify structural, functional, and multimodal abnormalities in CD patients.MethodsThe PubMed database was searched for VBM and task-state fMRI studies performed in CD patients between January 1, 2010, and December 31, 2021, using the SEED-BASE d MAP software package to perform two independent meta-groups of functional neural activation and gray matter volume, respectively. Analysis, followed by multimodal analysis to uncover structural, functional, and multimodal abnormalities between CD and HC.ResultsThe meta-analysis included 14 CD fMRI studies (400 CD patients and 387 HCs) and 11 CD VBM studies (368 CD patients and 387 controls). Structurally, VBM analysis revealed significantly lower gray matter volumes in the right superior temporal gyrus, right insula, and right retrocentral gyrus than in the HC. On the other hand, the right inferior parietal gyrus increased in gray matter (GM) volume in CD patients. Functionally, fMRI analysis revealed activation in the right temporal pole, right insula, and right parahippocampal gyrus. In the right inferior parietal gyrus, the left inferior parietal gyrus, the left middle occipital gyrus, and the right middle frontal gyrus, the degree of activation was lower.ConclusionThis meta-analysis showed that CD patients had significant brain GM and neural changes compared with normal controls. Furthermore, multi-domain assessments capture different aspects of neuronal alterations in CD, which may help develop effective interventions for specific functions.

Blocking ataxia telangiectasia mutated (ATM), a crucial player in DNA repair responses, has been proposed as a promising strategy in anti-cancer therapy. Most previous studies have focused on DNA damage response-related pathways after administration of ATM inhibitors. However, ATM inhibition could potentially influence a wide range of changes in gene expression, which remain poorly defined. Here, we report that administration of the ATM inhibitor KU60019 led to impaired migration and enhanced apoptosis in the ovarian cancer cell line SKOV3, accompanied by abnormally elevated O-GlcNAc transferase and O-GlcNAcase expression levels. In addition, KU60019 treatment significantly suppressed expression of hsa-miR-542-5p in SKOV3 cells. Up-regulation of hsa-miR-542-5p expression inhibited increases in OGT and OGA level, and reversed the effects of ATM inhibition on apoptosis and migration in SKOV3 cells. Finally, we found aberrant expression of OGT and OGA to be associated with ovarian cancer patient survival. Taken together, our results suggest that ATM inhibition may promote SKOV3 cell apoptosis via suppressing hsa-miR-542-5p and elevating OGT and OGA expression, providing new insights into the application of ATM inhibitors in cancer immunotherapy.

The microwave scatterometer onboard the China-France Oceanography Satellite (CFOSAT Scatterometer, CSCAT) is the first rotating fan-beam scatterometer (RFSCAT) in operation. It is used to obtain the ocean surface wind field by measuring the backscattering coefficient over a large observation swath. To estimate the backscattering coefficient, the scatterometer needs to measure the scattered signal accurately. The process of removing noise from the echo signal (scattered signal plus noise) is called noise subtraction. Noise subtraction has a great influence on the measurement of the backscattering coefficient and subsequent wind field retrieval. Therefore, accurate noise subtraction is necessary and important. In this article, an improved noise subtraction method for CSCAT is proposed. According to the distribution characteristics of backscattering coefficients, noise correction factors are introduced to improve the noise subtraction of CSCAT. The ocean surface wind fields are obtained using the improved backscattering coefficient data, and the deviation of wind speed and direction are calculated by comparison with the European Centre for Medium Range Weather Forecasts wind fields. The results show that the improved noise subtraction method can lead to improvement of the quality of wind field effectively. In addition, based on the improved method of noise subtraction, a method of estimating the noise correction factor is proposed at a large incidence angle, furtherly improving the noise subtraction method. The results show that the proposed method is effective.

The software reliability is mainly obtained through modeling and estimating. The existing software reliability models are nonlinear, and the parameter estimation of these models is difficult. At the same time, there are many optimization methods for solving the nonlinear function problems, such as artificial bee colony algorithm (ABC) and Particle Swarm Optimization (PSO). ABC has the characteristics of fewer control parameters, strong exploration ability, and the high accuracy of the solution. The PSO algorithm has the characteristics of the relatively small amount of computation and fast search speed but it has premature convergence, especially in dealing with complex multi-peak search problems, and the problem of poor local search ability. This paper proposes the parameter estimation method of software reliability model based on hybrid PSO-ABC, constructs a new fitness function based on maximum likelihood estimation, removes the wrong solution during the algorithm execution process, and adds knowledge to improve the solution accuracy. This paper uses five classic sets of software failure data to estimate the GO model parameters and make predictions and performs a variety of comparisons of the algorithm results. The experimental results show that the new fitness function is better, the solution of parameter estimation using the hybrid PSO-ABC is more accurate, and the hybrid PSO-ABC has a great advantage in generality and especially in limited data.

Glucose transporter type 1 deficiency syndrome (Glut1-DS) is a rare neurometabolic disorder caused by mutations of the SLC2A1 gene. Paroxysmal exercise-induced dyskinesia is regarded as a representative symptom of Glut1-DS. Paroxysmal non-kinesigenic dyskinesia is usually caused by aberrations of the MR1 and KCNMA1 genes, but it also appears in Glut1-DS. We herein document a patient with Glut1-DS who suffered first from paroxysmal exercise-induced dyskinesia and subsequently paroxysmal non-kinesigenic dyskinesia and experienced a recent worsening of symptoms accompanied with a low fever. The lumbar puncture result showed a decreased glucose concentration and increased white blood cell (WBC) count in cerebrospinal fluid (CSF). The exacerbated symptoms were initially suspected to be caused by intracranial infection due to a mild fever of

Quercetin is a natural product that has been shown to induce tumor apoptosis and necrosis through multiple mechanisms. Tumor-induced myeloid-derived suppressor cell (MDSC) expansion negatively regulates the immune response by inhibiting T cell function through signal transducer and activator of transcription 3 (STAT3) activation, thereby facilitating tumor escape from host immune surveillance. Thus MDSC is an attractive target for cancer immunotherapy to enhance cytotoxic T cell responses. However, the effects of quercetin on MDSC are poorly understood. Here, we demonstrate that quercetin treatment enhanced mouse- and human- derived granulocytic-myeloid-derived suppressor cells (G-MDSC) survival and promoted the secretion of T cell-suppressive factors in vitro. Bioinformatics analysis further showed that quercetin was highly correlated with the estrogen receptor signaling pathway, which was confirmed by quantitative reverse transcription-polymerase chain reaction and flow cytometric analysis. These findings highlight the potential advantages and feasibility of quercetin in reinforcing the suppressive property of G-MDSC. Thus impact of G-MDSC should be taken into consideration when quercetin is applied to tumor therapy.

Hashimoto’s encephalopathy (HE) is a rare neuropsychiatric syndrome characterized by elevated levels of anti-thyroid antibodies. Diverse manifestations make timely diagnosis of HE difficult. Herein, we report a case of HE, in which the clinical symptoms and laboratory test results mimicked viral encephalitis. A 59-year-old male patient, who presented with a fever, headache, slow and unclear speech, sentence confusion, elevated levels of anti-thyroid antibodies in the serum, an increased white blood cell count, and positivity for anti-thyroid antibodies in the CSF, was finally diagnosed with HE and responded well to a small dose of methylprednisolone. This report helps bring the attention of clinicians to the fact that HE should be considered when cases of unexplained encephalopathy are encountered.

Compared with slope surface measurement, subsurface monitoring has the potential to detect abnormal changes at an earlier stage. Due to the large-scale deformation of landslides and the complex geological environment, the existing subsurface devices generally have limited measuring range or high economic cost. Thus, it is urgent to develop an advanced method to improve the sustainable monitoring of large subsurface deformation. In this study, a novel flexible device is designed for slope subsurface monitoring, which combines an active waveguide of acoustic emission and the distinctive structure of a large-deformation bolt. An experimental system is built and a loading process of three-stage deformation is carried out to test the performance of the flexible device. The kinematic, mechanical and acoustic emission parameters are synchronously obtained in the whole landslide model test. The results indicate that different evolution stages of a landslide can be distinguished by sliding acceleration. The axial tension within the anchor cable changes consistently with sliding thrust. In addition, using acoustic emission to quantify slope deformation has achieved strong correlation. An extra experiment with constant velocity is conducted to explore the precision of deformation quantification by acoustic emission. A schematic diagram is presented for how this novel device would be used for landslide monitoring in the field, with the potential practicability of stabilizing the slope.

Antineutrophil cytoplasmic antibody- (ANCA-) associated vasculitis (AAV) is characterized by small-vessel inflammation in association with autoantibodies. Balance between T follicular helper (Tfh) cells and T follicular regulatory (Tfr) cells is critical for humoral immune responses. Accumulating evidence supports that Tfh and Tfr are involved in autoimmune diseases; however, their roles in AAV are unclear. In this study, we tested the changes of circulatory Tfh and Tfr in patients with AAV. Twenty patients with AAV and twenty healthy controls were enrolled. Sixteen AAV patients had kidney involvement. We found that the AAV patients had increased circulating Tfh cells (CD4+CXCR5+CD25−CD127interm-hi), decreased Tfr cells (CD4+CXCR5+CD25+CD127lo-interm), and elevated Tfh/Tfr ratios compared with healthy controls (P

Acoustic emission (AE) monitoring has become an optional technology to quantify slope deformation. However, there are still challenges in developing generic AE interpretation strategies. Dynamics and kinematics models are two physical methods for analysing slope stability, which appear to improve the interpretability of AE monitoring data. The aim of this study is to explore the change patterns and interrelations of dynamics, kinematics, and AE measurements using a model test and physical analysis, to further understand the development process of a progressive landslide. A model test is designed based on the kinematics model of landslide three-stage deformation. An equation between factor of safety (FoS) and thrust is proposed based on the mechanical model of a landslide test. There is a clear correspondence between the displacement and inverse velocity during the deformation-controlled process. Relationships are uncovered between the thrust and FoS as well as the thrust and acceleration. As a characteristic parameter of AE, ring down count (RDC) is able to quantify the deformation process of the soil slope. Moreover, acceleration and RDC can reflect the sudden change of the slope state and, hence, can be effective indicators for the early warning in a progressive landslide.

Different regions in China have different energy consumption characteristics and changing trends. This paper focuses on analyzing trends in energy consumption changes along the timeline for 30 regions in China. Using the Hybrid Input-Output Model, this paper decomposes energy consumption in 30 regions in 2007, 2012 and 2016 into energy embedded of final consumption expenditure, gross capital formation, inflow and outflow. We use these four dimensions as coordinates to draw a regional radar map. According to the changing characteristics of the radar map, 30 regions are divided into three groups. By analyzing the reasons for the changes in three regions, we draw the following conclusions. For regions where energy consumption is mainly inflow, the economically developed regions have to form a low energy consumption environment while achieving economic growth. The economically underdeveloped regions need to carry out energy conservation and emission reduction as well as ensuring the level of economic development. For some outflow regions with moderately economic development, it is necessary to balance the economic development and energy consumption control according to regional characteristics. For resource-rich regions which are in the process of transformation from agriculture to industrialization, they have to maintain the rapid development speed and strengthen their infrastructure with less energy consumption of buildings.

Familial hemiplegic migraine (FHM) is a rare, monogenic, autosomal dominant subtype of migraine, in which three genes, CACNA1A, ATP1A2, and SCN1A, are currently known to be involved. The familial hemiplegic migraine type 3 (FHM3) is seldom caused by mutations in SCN1A. Here, we report a rare case of an SCN1A mutation leading to FHM3 in a Chinese family. This case report describes a 62-year-old female patient that was admitted to our clinic. She presented with recurrent attacks of hemiplegic migraine. Her symptoms were first suspicious of a transient ischemic attack (TIA), but they were eventually diagnosed as FHM with a c.4495T>C mutation being found in the SCN1A gene. This case highlights that when a patient presents at the clinic with TIA symptoms associated with migraine, the diagnosis of an FHM should be considered and a genetic test is indicated. The identification of SCN1A gene mutations may help us to further understand the FHM pathophysiology.

This paper studies an M/G/1 repairable queueing system with multiple vacations and N-policy, in which the service station is subject to occasional random breakdowns. When the service station breaks down, it is repaired by a repair facility. Moreover, the repair facility may fail during the repair period of the service station. The failed repair facility resumes repair after completion of its replacement. Under these assumptions, applying a simple method, the probability that the service station is broken, the rate of occurrence of breakdowns of the service station, the probability that the repair facility is being replaced and the rate of occurrence of failures of the repair facility along with other performance measures are obtained. Following the construction of the long-run expected cost function per unit time, the direct search method is implemented for determining the optimum threshold N* that minimises the cost function.

Increased expression of mineral dust-induced gene (mdig, also named as mina53, MINA, or NO52) has been observed in a number of human cancers. The mechanism of how mdig contribute to the pathogenesis of cancer remains to be fully elucidated. In this report, we demonstrated that overexpression of mdig decreased the nuclear staining signal by 4',6-diamidino-2-phenylindole (DAPI), along with a considerable enhancement in cell proliferation. Silencing mdig by shRNA resulted in a statistically significant decrease of cell proliferation. Intriguingly, mdig overexpression reduced the capacity of the cells in migration and invasion in vitro, whereas silencing mdig by shRNA/siRNA enhanced migration and invasion. Clinically, we found that increased expression of mdig in cancer tissues correlates with poorer overall survival of the lung cancer patients, esp., for those without lymph node metastasis. Taken together, our results suggest that mdig plays opposite roles on cell growth and motility, which possibly indicates the paradoxical effect of mdig at the different stages of carcinogenesis.

This paper deals with a discrete-time bulk-service Geo/Geo/1 queueing system with infinite buffer space and multiple working vacations. Considering an early arrival system, as soon as the server empties the system in a regular busy period, he leaves the system and takes a working vacation for a random duration at time n. The service times both in a working vacation and in a busy period and the vacation times are assumed to be geometrically distributed. By using embedded Markov chain approach and difference operator method, queue length of the whole system at random slots and the waiting time for an arriving customer are obtained. The queue length distributions of the outside observer’s observation epoch are investigated. Numerical experiment is performed to validate the analytical results.

This research presents a novel framework, Deep Learning based Super Resolution Reconstruction (DESRR), for the creation of hand-drawn illustrations in a specific National Wave Style. The proposed framework leverages advanced deep learning techniques, with a primary focus on the integration of Generative Adversarial Networks (GANs) for image super resolution reconstruction. The objective is to enhance the resolution and fidelity of hand-drawn illustrations while preserving the distinctive characteristics of the chosen national wave style. The DESRR framework involves a two-step process: firstly, the utilization of GAN algorithms for generating illustrations that encapsulate the unique artistic nuances of the targeted national wave style; and secondly, the application of image super resolution techniques to refine and elevate the quality of the generated illustrations. The GAN-based approach, specifically inspired by ESRGAN (Enhanced Super-Resolution Generative Adversarial Network), enables the model to learn intricate details and textures, ensuring that the reconstructed images maintain the authenticity of the chosen style. To implement DESRR, a curated dataset of hand-drawn images in the specified national wave style is employed for training. The model is fine-tuned to strike a balance between increased resolution and the faithful representation of the targeted artistic style. The framework's effectiveness is evaluated through a comprehensive analysis, considering both quantitative measures of image quality and qualitative assessments of style preservation. The proposed DESRR framework not only contributes to the field of artistic illustration design but also showcases the potential of combining deep learning and image super resolution techniques for creative applications. [ABSTRACT FROM AUTHOR]

N6-Methyladenosine (m6A) is the most abundant posttranscriptional modification, and its contribution to cancer evolution has recently been appreciated. Renal cancer is the most common adult genitourinary cancer, approximately 85% of which is accounted for by the clear cell renal cell carcinoma (ccRCC) subtype characterized by VHL loss. However, it is unclear whether VHL loss in ccRCC affects m6A patterns. In this study, we demonstrate that VHL binds and promotes METTL3/METTL14 complex formation while VHL depletion suppresses m6A modification, which is distinctive from its canonical E3 ligase role. m6A RNA immunoprecipitation sequencing (RIP-Seq) coupled with RNA-Seq allows us to identify a selection of genes whose expression may be regulated by VHL-m6A signaling. Specifically, PIK3R3 is identified to be a critical gene whose mRNA stability is regulated by VHL in a m6A-dependent but HIF-independent manner. Functionally, PIK3R3 depletion promotes renal cancer cell growth and orthotopic tumor growth while its overexpression leads to decreased tumorigenesis. Mechanistically, the VHL-m6A-regulated PIK3R3 suppresses tumor growth by restraining PI3K/AKT activity. Taken together, we propose a mechanism by which VHL regulates m6A through modulation of METTL3/METTL14 complex formation, thereby promoting PIK3R3 mRNA stability and protein levels that are critical for regulating ccRCC tumorigenesis. [ABSTRACT FROM AUTHOR]