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Rational design of single atom catalyst is critical for efficient sustainable energy conversion. However, the atomic-level control of active sites is essential for electrocatalytic materials in alkaline electrolyte. Moreover, well-defined surface structures lead to in-depth understanding of catalytic mechanisms. Herein, we report a single-atomic-site ruthenium stabilized on defective nickel-iron layered double hydroxide nanosheets (Ru 1 /D-NiFe LDH). Under precise regulation of local coordination environments of catalytically active sites and the existence of the defects, Ru 1 /D-NiFe LDH delivers an ultralow overpotential of 18 mV at 10 mA cm −2 for hydrogen evolution reaction, surpassing the commercial Pt/C catalyst. Density functional theory calculations reveal that Ru 1 /D-NiFe LDH optimizes the adsorption energies of intermediates for hydrogen evolution reaction and promotes the O–O coupling at a Ru–O active site for oxygen evolution reaction. The Ru 1 /D-NiFe LDH as an ideal model reveals superior water splitting performance with potential for the development of promising water-alkali electrocatalysts. Rational design of single atom catalyst is critical for efficient sustainable energy conversion. Single-atomic-site ruthenium stabilized on defective nickel-iron layered double hydroxide nanosheets achieve superior HER and OER performance in alkaline media.

Heavy metals pollution of aqueous solutions generates considerable concerns as they adversely impact the environment and health of humans. Among the remediation technologies, adsorption with metal sulfide nanomaterials has proven to be a promising strategy due to their cost-effective, environmentally friendly, surface modulational, and amenable properties. Their excellent adsorption characteristics are attributed to the inherently exposed sulfur atoms that interact with heavy metals through various processes. This work presents a comprehensive overview of the sequestration of heavy metals from water using metal sulfide nanomaterials. The common methods of synthesis, the structures, and the supports for metal sulfide nano-adsorbents are accentuated. The adsorption mechanisms and governing conditions and parameters are stressed. Practical heavy metal remediation application in aqueous media using metal sulfide nanomaterials is highlighted, and the existing research gaps are underscored.

Efficient electroreduction of CO 2 to multi-carbon products is a challenging reaction because of the high energy barriers for CO 2 activation and C–C coupling, which can be tuned by designing the metal centers and coordination environments of catalysts. Here, we design single atom copper encapsulated on N-doped porous carbon (Cu-SA/NPC) catalysts for reducing CO 2 to multi-carbon products. Acetone is identified as the major product with a Faradaic efficiency of 36.7% and a production rate of 336.1 μg h −1 . Density functional theory (DFT) calculations reveal that the coordination of Cu with four pyrrole-N atoms is the main active site and reduces the reaction free energies required for CO 2 activation and C–C coupling. The energetically favorable pathways for CH 3 COCH 3 production from CO 2 reduction are proposed and the origin of selective acetone formation on Cu-SA/NPC is clarified. This work provides insight into the rational design of efficient electrocatalysts for reducing CO 2 to multi-carbon products. Efficient electroreduction of CO 2 to multi-carbon products is challenging. Here, the single atom Cu encapsulated on N-doped porous carbon catalysts are designed for reducing CO 2 to acetone at low overpotentials and the active sites are identified as Cu coordination with four pyrrole-N atoms.

Studies have demonstrated that resveratrol (a natural polyphenol) and caloric restriction activate Sirtuin-1 (SIRT1) and induce autophagy. Furthermore, autophagy is induced by the SIRT1-FoxO signaling pathway and was recently shown to be a critical protective mechanism against non-alcoholic fatty liver disease (NAFLD) development. We aimed to compare the effects of resveratrol and caloric restriction on hepatic lipid metabolism and elucidate the mechanism by which resveratrol supplementation and caloric restriction alleviate hepatosteatosis by examining the molecular interplay between SIRT1 and autophagy. Eight-week-old male Wistar rats (40) were divided into four groups: the STD group, which was fed a standard chow diet; the HFD group, which was fed a high-fat diet; HFD-RES group, which was fed a high-fat diet plus resveratrol (200 mg/kg.bw); and the HFD-CR group, which was fed a high-fat diet in portions containing 70% of the mean intake of the HFD group rats. The groups were maintained for 18 weeks. Metabolic parameters, Oil Red O and hematoxylin-eosin staining of the liver, and the mRNA and protein expression of SIRT1, autophagy markers and endoplasmic reticulum(ER) stress-associated genes in the liver were assessed after the 18-week treatment. We found that resveratrol (200 mg/kg bw) and caloric restriction (30%) partially prevented hepatic steatosis and hepatocyte ballooning, increased the expression of SIRT1 and autophagy markers while decreasing ER stress markers in the liver and alleviated lipid metabolism disorder. Moreover, caloric restriction provided superior protection against HFD-induced hepatic fatty accumulation compared with resveratrol and the effects were associated with decreased total energy intake and body weight. We conclude that the SIRT1-autophagy pathway and decreased ER stress are universally required for the protective effects of moderate caloric restriction (30%) and resveratrol (a pharmacological SIRT1 activator) supplementation against HFD-induced hepatic steatosis.

•We evaluated the impact of artifact correction and artifact rejection on EEG/ERP decoding performance.•We explored a wide range of experimental paradigms, including both easy and difficult decoding tasks, various subject populations, and differing electrode densities.•We found that the combination of artifact correction and rejection did not significantly enhance decoding performance in the vast majority of cases.•However, we strongly recommended using artifact correction prior to decoding analyses to reduce artifact-related confounds. Numerous studies have demonstrated that eyeblinks and other large artifacts can decrease the signal-to-noise ratio of EEG data, resulting in decreased statistical power for conventional univariate analyses. However, it is not clear whether eliminating these artifacts during preprocessing enhances the performance of multivariate pattern analysis (MVPA; decoding), especially given that artifact rejection reduces the number of trials available for training the decoder. This study aimed to evaluate the impact of artifact-minimization approaches on the decoding performance of support vector machines. Independent component analysis (ICA) was used to correct ocular artifacts, and artifact rejection was used to discard trials with large voltage deflections from other sources (e.g., muscle artifacts). We assessed decoding performance in relatively simple binary classification tasks using data from seven commonly-used event-related potential paradigms (N170, mismatch negativity, N2pc, P3b, N400, lateralized readiness potential, and error-related negativity), as well as more challenging multi-way decoding tasks, including stimulus location and stimulus orientation. The results indicated that the combination of artifact correction and rejection did not improve decoding performance in the vast majority of cases. However, artifact correction may still be essential to minimize artifact-related confounds that might artificially inflate decoding accuracy. Researchers who are using similar methods to decode EEG data from paradigms, populations, and recording setups that are similar to those examined here may benefit from our recommendations to optimize decoding performance and avoid incorrect conclusions.

Pyroelectric energy harvesting has received increasing attention due to its ability to convert low-grade waste heat into electricity. However, the low output energy density driven by low-grade temperature limits its practical applications. Here, we show a high-performance hybrid BNT-BZT- x GaN thermal energy harvesting system with environmentally friendly lead-free BNT-BZT pyroelectric matrix and high thermal conductivity GaN as dopant. The theoretical analysis of BNT-BZT and BNT-BZT- x GaN with x  = 0.1 wt% suggests that the introduction of GaN facilitates the resonance vibration between Ga and Ti, O atoms, which not only contributes to the enhancement of the lattice heat conduction, but also improves the vibration of TiO 6  octahedra, resulting in simultaneous improvement of thermal conductivity and pyroelectric coefficient. Therefore, a thermoelectric coupling enhanced energy harvesting density of 80 μJ cm −3 has been achieved in BNT-BZT- x GaN ceramics with x  = 0.1 wt% driven by a temperature variation of 2 o C, at the optical load resistance of 600 MΩ. Pyroelectric energy harvesting has received increasing attention due to its ability to convert low-grade waste heat into electricity. Here, authors report an enhanced thermoelectric coupling BNT-BZT-xGaN pyroelectric energy harvester by facilitating resonance vibration between Ga and Ti, O atoms.

Since cancer stem cells (CSCs) were first identified in leukemia in 1994, they have been considered promising therapeutic targets for cancer therapy. These cells have self-renewal capacity and differentiation potential and contribute to multiple tumor malignancies, such as recurrence, metastasis, heterogeneity, multidrug resistance, and radiation resistance. The biological activities of CSCs are regulated by several pluripotent transcription factors, such as OCT4, Sox2, Nanog, KLF4, and MYC. In addition, many intracellular signaling pathways, such as Wnt, NF-κB (nuclear factor-κB), Notch, Hedgehog, JAK-STAT (Janus kinase/signal transducers and activators of transcription), PI3K/AKT/mTOR (phosphoinositide 3-kinase/AKT/mammalian target of rapamycin), TGF (transforming growth factor)/SMAD, and PPAR (peroxisome proliferator-activated receptor), as well as extracellular factors, such as vascular niches, hypoxia, tumor-associated macrophages, cancer-associated fibroblasts, cancer-associated mesenchymal stem cells, extracellular matrix, and exosomes, have been shown to be very important regulators of CSCs. Molecules, vaccines, antibodies, and CAR-T (chimeric antigen receptor T cell) cells have been developed to specifically target CSCs, and some of these factors are already undergoing clinical trials. This review summarizes the characterization and identification of CSCs, depicts major factors and pathways that regulate CSC development, and discusses potential targeted therapy for CSCs.

A lightweight infrared image denoising method based on adversarial transfer learning is proposed. The method adopts a generative adversarial network (GAN) framework and optimizes the model through a phased transfer learning strategy. In the initial stage, the generator is pre-trained using a large-scale grayscale visible light image dataset. Subsequently, the generator is fine-tuned on an infrared image dataset using feature transfer techniques. This phased transfer strategy helps address the problem of insufficient sample quantity and variety in infrared images. Through the adversarial process of the GAN, the generator is continuously optimized to enhance its feature extraction capabilities in environments with limited data. Moreover, the generator structure incorporates structural reparameterization technology, edge convolution modules, and progressive multi-scale attention block (PMAB), significantly improving the model’s ability to recognize edge and texture features. During the inference stage, structural reparameterization further optimizes the network architecture, significantly reducing model parameters and complexity and thereby improving denoising efficiency. The experimental results of public and real-world datasets demonstrate that this method effectively removes additive white Gaussian noise from infrared images, showing outstanding denoising performance.

The underwater imaging process is often hindered by high noise levels, blurring, and color distortion due to light scattering, absorption, and suspended particles in the water. To address the challenges of image enhancement in complex underwater environments, this paper proposes an underwater image color correction and detail enhancement model based on an improved Cycle-consistent Generative Adversarial Network (CycleGAN), named LPIPS-MAFA CycleGAN (LM-CycleGAN). The model integrates a Multi-scale Adaptive Fusion Attention (MAFA) mechanism into the generator architecture to enhance its ability to perceive image details. At the same time, the Learned Perceptual Image Patch Similarity (LPIPS) is introduced into the loss function to make the training process more focused on the structural information of the image. Experiments conducted on the public datasets UIEB and EUVP demonstrate that LM-CycleGAN achieves significant improvements in Structural Similarity Index (SSIM), Peak Signal-to-Noise Ratio (PSNR), Average Gradient (AG), Underwater Color Image Quality Evaluation (UCIQE), and Underwater Image Quality Measure (UIQM). Moreover, the model excels in color correction and fidelity, successfully avoiding issues such as red checkerboard artifacts and blurred edge details commonly observed in reconstructed images generated by traditional CycleGAN approaches.

Glioma is a common primary tumor of the central nervous system (CNS), with glioblastoma multiforme (GBM) being the most malignant, aggressive, and drug resistant. Most drugs are designed to induce cancer cell death, either directly or indirectly, but malignant tumor cells can always evade death and continue to proliferate, resulting in a poor prognosis for patients. This reflects our limited understanding of the complex regulatory network that cancer cells utilize to avoid death. In addition to classical apoptosis, pyroptosis, ferroptosis, and autophagy are recognized as key cell death modalities that play significant roles in tumor progression. Various inducers or inhibitors have been discovered to target the related molecules in these pathways, and some of them have already been translated into clinical treatment. In this review, we summarized recent advances in the molecular mechanisms of inducing or inhibiting pyroptosis, ferroptosis, or autophagy in GBM, which are important for treatment or drug tolerance. We also discussed their links with apoptosis to better understand the mutual regulatory network among different cell death processes. 4Vv5afGRyKdvQDZYoNbTk5 Video Abstract