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Aiming at the shortcomings of the current face liveness detection attack methods in the low generation speed of adversarial examples and the implementation of white‐box attacks, a novel black‐box attack method for face liveness detection named as FLDATN is proposed based on adversarial transformation network (ATN). In FLDATN, a convolutional block attention module (CBAM) is used to improve the generalization ability of adversarial examples, and the misclassification loss function based on feature similarity is defined. Experiments and analysis on the Oulu‐NPU dataset show that the adversarial examples generated by the FLDATN have a good black‐box attack effect on the task of face liveness detection and can achieve better generalization performance than the traditional methods. In addition, since FLDATN does not need to perform multiple gradient calculations for each image, it can significantly improve the generation speed of the adversarial examples. [ABSTRACT FROM AUTHOR]

Face morphing attacks disrupt the essential correlation between a face image and its identity information, posing a significant challenge to face recognition systems. Despite advancements in face morphing attack detection methods, these techniques cannot reconstruct the face images of accomplices. Existing deep learning-based face de-morphing techniques have mainly focused on identity disentanglement, overlooking the morphing factors inherent in the morphed images. This paper introduces a novel face de-morphing method to restore the identity information of accomplices by predicting the corresponding de-morphing factor. To obtain reasonable de-morphing factors, a channel-wise attention mechanism is employed to perform feature interaction, and the correlation between the morphed image and the real-time captured reference image is integrated to promote the prediction of the de-morphing factor. Furthermore, the identity information of the accomplice is restored by mapping the morphed and reference images into the StyleGAN latent space and performing inverse linear interpolation using the predicted de-morphing factor. Experimental results demonstrate the superiority of this method in restoring accomplice facial images, achieving improved restoration accuracy and image quality compared to existing techniques. [ABSTRACT FROM AUTHOR]

Background: Beta 2‐microglobulin (β2‐MG) is a component of the class I major histocompatibility complex (MHCI) and has recently been reported to be involved in type 2 diabetes mellitus (T2DM) and cardiovascular disease. However, the association of β2‐MG with left ventricular hypertrophy (LVH) in T2DM patients remains unknown. This study aims to investigate the correlation between serum β2‐MG and LVH in T2DM patients. Methods: The retrospective analysis included 4602 eligible T2DM patients, divided into LVH and non‐LVH groups based on echocardiography results. Serum β2‐MG levels were measured, and participants were categorized into four groups (Q1–Q4) by their serum β2‐MG quartile. The relationship of serum β2‐MG level with LVH was evaluated using logistic regression, restricted cubic spline (RCS), subgroup analysis, and machine learning. Results: The prevalence of LVH in T2DM patients was 31.12%. Each standard deviation increase in serum β2‐MG level corresponded to a 1.17‐fold increase in the prevalence of LVH [OR = 1.17, (95% CI: 1.05–1.31); p = 0.006]. When considering β2‐MG as a categorical variable (quartile), Q3 [OR = 1.36, (95% CI: 1.09–1.69); p = 0.007] and Q4 [OR = 1.77, (95% CI: 1.36–2.31); p < 0.001] had a significantly higher prevalence of LVH than Q1. RCS analysis found a nonlinear association between β2‐MG and LVH prevalence (p for nonlinearity <0.05). Additionally, machine learning results confirmed the importance of β2‐MG for LVH in T2DM patients. Conclusion: Elevated serum β2‐MG levels were likely to be associated with an increased prevalence of LVH in T2DM patients, suggesting its potential role in LVH development. [ABSTRACT FROM AUTHOR]

The structures, mechanical properties and electronic structures of M metals (M=Ti, V, Cr, Mn and Fe) doped β-Si3N4 were investigated by First-principles calculations within CASTEP. The calculated lattice parameters of β-Si3N4 were consistent with previous date. The cohesive energy and formation enthalpy show that initial β-Si3N4 has the highest structural stability. The calculated elastic constant and the Voigt-Reuss-Hill approximation indicate that elastic moduli of β-Si3N4 are slightly reduced by M doping. Based on Poisson's and Pugh's ratio, β-Si3N4 is a ductile material and the toughness of β-Si3N4 increases with M doping, and Fe doping exhibited the best toughness. The results of density of states, charge distributions and overlapping populations indicate that β-Si3N4 has the strong covalent and ionic bond strength between N and Si. [ABSTRACT FROM AUTHOR]

Morphing attacks (MAs) pose a substantial security threat to the Automatic Border Control (ABC) system. While a few morphing attack detection (MAD) methods have been proposed, the face morphing accomplice's facial restoration has not received sufficient attention. Due to the inability to foresee the morphing factor used for a particular morphed image, selecting the appropriate de‐morphing factor becomes a challenging problem in the restoration of the accomplice's facial image. If the morphing factor cannot be chosen reasonably, achieving the desired restoration effect is difficult. Therefore, this paper presents an adaptive de‐morphing factor framework (ADFF) architecture for restoring the accomplice's facial image. By exploiting the morphed images stored in the electronic passport system and the real‐time captured criminal's images, ADFF can effectively restore the accomplice's facial image. Experimental results and analysis show that ADFF can significantly reduce the security threats of MAs on ABC. [ABSTRACT FROM AUTHOR]

Oral mucositis (OM) is a severe side effect of anti‐cancer therapy, with limited available treatments. Mesenchymal stem cells (MSCs) and their secreted extracellular vesicles (EVs) have demonstrated effective protection against OM. However, the underlying mechanism remains elusive. In the current study, we purified EVs secreted by human umbilical cord MSCs (hUC‐MSC‐EVs) and investigated their role in lipopolysaccharide (LPS)‐induced human oral keratinocytes (HOKs). We observed that treatment with hUC‐MSC‐EVs significantly reduced the inflammatory response of HOKs to LPS induction. Through small RNA‐seq using miRNAs extracted from hUC‐MSC‐EVs, we identified hsa‐let‐7e‐5p as one of the most highly expressed miRNAs. Bioinformatic analysis data indicated that hsa‐let‐7e‐5p may inhibit the NF‐κB signalling pathway by targeting TAB2. Overexpression of the hsa‐let‐7e‐5p inhibitor significantly attenuated the anti‐inflammatory effect of hUC‐MSC‐EVs in LPS‐induced HOKs, which could be reversed by the knockdown of TAB2. In addition, we administered hUC‐MSC‐EVs in a hamster model for OM and observed that these EVs alleviated OM phenotypes. Taken together, our observations suggest that hsa‐let‐7e‐5p in hUC‐MSC‐EVs could protect the oral mucosa from OM by repressing TAB2 expression. [ABSTRACT FROM AUTHOR]

Nitric oxide (NO) is an important gas signaling molecule, and endoplasmic reticulum (ER) stress induced by NO may be related to the pathogenesis of many diseases. Therefore, the development of ER-targeted fluorescent probes for NO is of great significance to investigate the relationship between ER stress and NO concentration changes in related diseases. Herein, an ER-targeted fluorescent probe (ER-Np) for sensing NO was constructed. ER-Np was served as an excellent tool for detection NO with high selectivity, sensitivity and ER-targetable ability. Moreover, fluorescence imaging experiments indicated that ER-Np is capable of imaging NO in living cells. Impressively, visualization of endogenous NO production during dithiothreitol (DTT)-induced ER stress in living cells was successfully observed. In addition, we found that serum NO levels were upregulated in epilepsy children, which opens up a new avenue for further understanding the relationship between the diagnostic of epilepsy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The efficient transfer of H 2 plays a critical role in catalytic hydrogenation, particularly for the removal of recalcitrant contaminants from water. One of the most persistent contaminants, perfluorooctanoic acid (PFOA), was used to investigate how the method of H 2 transfer affected the catalytic hydrodefluorination ability of elemental palladium nanoparticles (Pd 0 NPs). Pd 0 NPs were synthesized through an in situ autocatalytic reduction of Pd 2+ driven by H 2 from the membrane. The Pd 0 nanoparticles were directly deposited onto the membrane fibers to form the catalyst film. Direct delivery of H 2 to Pd 0 NPs through the walls of nonporous gas transfer membranes enhanced the hydrodefluorination of PFOA, compared to delivering H 2 through the headspace. A higher H 2 lumen pressure (20 vs 5 psig) also significantly increased the defluorination rate, although 5 psig H 2 flux was sufficient for full reductive defluorination of PFOA. Calculations made using density functional theory (DFT) suggest that subsurface hydrogen delivered directly from the membrane increases and accelerates hydrodefluorination by creating a higher coverage of reactive hydrogen species on the Pd 0 NP catalyst compared to H 2 delivery through the headspace. This study documents the crucial role of the H 2 transfer method in the catalytic hydrogenation of PFOA and provides mechanistic insights into how membrane delivery accelerates hydrodefluorination.