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The precise structural integration of single-atom and high-entropy-alloy features for energy electrocatalysis is highly appealing for energy conversion, yet remains a grand challenge. Herein, we report a class of single-atom Mo-tailored PdPtNiCuZn high-entropy-alloy nanosheets with dilute Pt-Pt ensembles and intrinsic tensile strain (Mo 1 -PdPtNiCuZn) as efficient electrocatalysts for enhancing the methanol oxidation reaction catalysis. The as-made Mo 1 -PdPtNiCuZn delivers an extraordinary mass activity of 24.55 A mg Pt −1 and 11.62 A mg Pd+Pt −1 , along with impressive long-term durability. The planted oxophilic Mo single atoms as promoters modify the electronic structure of isolated Pt sites in the high-entropy-alloy host, suppressing the formation of CO adsorbates and steering the reaction towards the formate pathway. Meanwhile, Mo promoters and tensile strain synergistically optimize the adsorption behaviour of intermediates to achieve a more energetically favourable pathway and minimize the methanol oxidation reaction barrier. This work advances the design of atomically precise catalytic sites by creating a new paradigm of single atom-tailored high-entropy alloys, opening an encouraging pathway to the design of CO-tolerance electrocatalysts. Atomically precise modification of high-entropy alloys is highly appealing for electrocatalysis. Here, the authors design single-atom Mo-tailored high-entropy alloy nanosheets with dilute Pt-Pt ensembles and intrinsic tensile strain for promoting methanol electro-oxidation towards formate.

HighlightsA hybrid co-catalysts system comprising Au nanoparticles (NPs) and PtSAs with different functions was constructed on the polymeric carbon nitride (PCN) surface by double-solvent method.For the dual co-catalysts, the Au NPs absorb relatively long-wavelength light to produce plasmonic hot-electrons, and the adjacent Pt single atoms (PtSAs) can trap the plasmonic hot-electrons effectively for H2 evolution.The PtSAs–Au2.5/PCN exhibits excellent broad-spectrum photocatalytic H2 evolution activity with the H2 evolution rate of 8.8 mmol g−1 h−1 at 420 nm and 264 μmol g−1 h−1 at 550 nm, respectively.Rationally designing broad-spectrum photocatalysts to harvest whole visible-light region photons and enhance solar energy conversion is a “holy grail” for researchers, but is still a challenging issue. Herein, based on the common polymeric carbon nitride (PCN), a hybrid co-catalysts system comprising plasmonic Au nanoparticles (NPs) and atomically dispersed Pt single atoms (PtSAs) with different functions was constructed to address this challenge. For the dual co-catalysts decorated PCN (PtSAs–Au2.5/PCN), the PCN is photoexcited to generate electrons under UV and short-wavelength visible light, and the synergetic Au NPs and PtSAs not only accelerate charge separation and transfer though Schottky junctions and metal-support bond but also act as the co-catalysts for H2 evolution. Furthermore, the Au NPs absorb long-wavelength visible light owing to its localized surface plasmon resonance, and the adjacent PtSAs trap the plasmonic hot-electrons for H2 evolution via direct electron transfer effect. Consequently, the PtSAs–Au2.5/PCN exhibits excellent broad-spectrum photocatalytic H2 evolution activity with the H2 evolution rate of 8.8 mmol g−1 h−1 at 420 nm and 264 μmol g−1 h−1 at 550 nm, much higher than that of Au2.5/PCN and PtSAs–PCN, respectively. This work provides a new strategy to design broad-spectrum photocatalysts for energy conversion reaction.

This paper presents a sound source localization (SSL) model based on residual network and channel attention mechanism. The method takes the combination of log-Mel spectrogram and generalized cross-correlation phase transform (GCC-PHAT) as the input features, and extracts the time–frequency information by using the residual structure and channel attention mechanism, thus obtaining a better localizing performance. The residual blocks are introduced to extract deeper features, which can stack more layers for high-level features and avoid gradient vanishing or exploding at the same time. The attention mechanism is taken into account for the feature extraction stage in the proposed SSL model, which can focus on the most important information on the input features. We use the signals collected by microphone array to explore the performance of the model under different features, and find the most suitable input features of the proposed method. We compare our method with other models on public dataset. Experience results show a quite substantial improvement of sound source localizing performance.

The detection of gas leaks using acoustic signals is often compromised by environmental noise, which significantly impacts the accuracy of subsequent leak identification. Current noise reduction algorithms based on non-negative matrix factorization (NMF) typically utilize the Euclidean distance as their objective function, which can exacerbate noise anomalies. Moreover, these algorithms predominantly rely on simple techniques like Wiener filtering to estimate the amplitude spectrum of pure signals. This approach, however, falls short in accurately estimating the amplitude spectrum of non-stationary signals. Consequently, this paper proposes an improved non-negative matrix factorization (INMF) noise reduction algorithm that enhances the traditional NMF by refining both the objective function and the amplitude spectrum estimation process for reconstructed signals. The improved algorithm replaces the conventional Euclidean distance with the Kullback–Leibler (KL) divergence and incorporates noise and sparse constraint terms into the objective function to mitigate the adverse effects of signal amplification. Unlike traditional methods such as Wiener filtering, the proposed algorithm employs an adaptive Minimum Mean-Square Error-Log Spectral Amplitude (MMSE-LSA) method to estimate the amplitude spectrum of non-stationary signals adaptively across varying signal-to-noise ratios. Comparative experiments demonstrate that the INMF algorithm significantly outperforms existing methods in denoising leakage acoustic signals.

In practical work scenarios, it is common for multiple vessels to be present in close proximity within the same water area. In such cases, the acoustic signals emitted by these vessels often overlap, causing interference and reducing the accuracy of vessel identification. This paper proposes an improved GALR end-to-end underwater acoustic source separation algorithm, with ECA-DE (Efficient Channel Attention-Deep Encoder) and Bi-GRU (Bidirectional Gated Recurrent Unit), which consists of an encoder, separation blocks, and a decoder (EDBG-GALR). Addressing the issue of GALR encoder’s limited expressiveness due to its single-layer one-dimensional convolutional layer, we introduce a new deep encoder, ECA-DE, to enhance the encoder’s capability to process temporal signals and improve the efficiency of the separator’s input. Additionally, we integrate Bi-GRU into the GALR separation block’s local modeling module to enhance the local modeling ability of sequence features, thereby reducing the model’s computational and parameter requirements. Experimental results demonstrate that the proposed EDBG-GALR method can effectively separate mixed multi-target signals into multiple single-target signals, achieving a maximum scale-invariant signal-to-noise ratio (SI-SNR) improvement of 3.32 dB and a signal distortion ratio (SDR) improvement of 3.38 dB over baseline methods. These results highlight the practical applicability of EDBG-GALR in complex underwater environments.

Purpose Therapeutic options targeting programmed cell death protein 1 (PD-1) and programmed death ligand-1 (PD-L1) have been approved for use in human malignancies, showing clinical benefits. Nonetheless, a significant number of patients, particularly those with prostate cancer (PCa), show poor response to anti-PD-1/PD-L1 therapies, highlighting the necessity to explore supportive strategies that could enhance conventional PD-1/PD-L1-targeting immunotherapy. Methods PCa cell lines DU145 and RM1 were used to investigate the effects of pirenzepine (PZP) on the proliferation, colony formation, and migration of PCa cells in vitro. A subcutaneous tumor model bearing DU145 and RM1 was established to evaluate the anti-tumor effect in vivo. Lentivirus transfection and quantitative polymerase chain reaction (qPCR) assays were conducted to investigate the role of STING (endoplasmic reticulum-associated protein stimulator of interferon genes) in the antitumor mechanisms of PZP. The infiltration of CD8 + T cells in tumor tissues was examined using immunohistochemistry. The RM1 subcutaneous tumor model was employed to assess the combined effects of PZP and anti-programmed cell death 1 antibody (anti-PD1) immune checkpoint blockade therapy. Results The in vitro and in vivo experiment results indicated that PZP suppressed the proliferation, colony formation, and migration of PCa cells in a dose-dependent manner. Notably, PZP also promoted CD8 + T cell infiltration and enhanced the anti-PD1 therapeutic effect on PCa. Mechanistically, the results preliminarily indicated that PZP impeded PCa progression and stimulated tumor immune response by upregulating STING expression. Conclusions Our results revealed that PZP impaired the malignant biological behavior of PCa and enhanced antitumor immunity. These findings may provide a theoretical basis for combining PZP with anti-PD1 immune checkpoint blockade therapy on PCa.

Purpose Prostate cancer (PCa) is a prevalent and lethal malignancy affecting males, with a considerable proportion of patients experiencing poor survival outcomes. The regulatory role of LIMD1-AS1 in the initiation and progression of PCa is emerging as a significant factor, however, the precise mechanisms governing its influence are yet to be fully elucidated. Methods qRT-PCR was employed to assess the expression of LIMD1-AS1 and miR-29c-3p. The Cell Counting Kit-8 (CCK-8) was used to assess cell proliferation in PCa cells. Apoptosis rates were determined using flow cytometry. Cell migration and invasion were evaluated using the transwell assay. The targeted relationship of LIMD1-AS1 and miR-29c-3p was confirmed through dual-luciferase reporter gene analysis. Results Increased expression of LIMD1-AS1 and decreased expression of miR-29c-3p were observed in both tumor tissues and serum from PCa patients. LIMD1-AS1 exhibited diagnostic and prognostic significance in PCa patients. Functionally, LIMD1-AS1 modulated the expression of miR-29c-3p to potentiate the proliferative, migratory, and invasive capabilities of PCa cells while concurrently inhibiting apoptosis. Conclusion LncRNA LIMD1-AS1 promotes the advancement of PCa by regulating miR-29c-3p, indicating that LIMD1-AS1/miR-29c-3p axis could serve as potential therapeutic targets for the therapeutic intervention of PCa.

Chemotherapy-induced reproductive toxicity remains a formidable off-target consequence of anticancer regimens, creating a critical barrier to the preservation of ovarian endocrine and gametogenic function in female patients. This review dissects the molecular and cellular cascades that underpin chemotherapy-driven ovarian insult—including DNA double-strand breaks, mitochondrial depolarization, accelerated primordial follicle activation, and oxidative stress—and critically evaluates emerging cytoprotective modalities. By synthesizing current mechanistic insights with pre-clinical and early-phase clinical data, we outline innovative strategies poised to mitigate ovarian damage without compromising oncological efficacy. Graphical Abstract

The morphology and size of Pt-based bimetallic alloys are known to determine their electrocatalytic performance in reactions relevant to fuel cells. Here, we report a general approach for preparing Pt-M (M = Fe, Co and Ni) bimetallic nano-branched structure (NBs) by a simple high temperature solution-phase synthesis. As-prepared Pt-M NBs show a polycrystalline structure and are rich in steps and kinks on the surface, which promote them favorable bifunctional catalytic properties in acidic electrolytes, specifically in terms of the oxygen reduction reaction (ORR) and methanol oxidation reaction (MOR). Specially, Pt-Co NBs/C catalyst shows 6.1 and 5.3 times higher in specific activity (SA) and mass activity (MA) for ORR than state-of-the-art commercial Pt/C catalysts, respectively. Moreover, it exhibits a loss of 4.0% in SA and 14.4% in MA after 10,000 cycles of accelerated durability tests (ADTs) compared with the initial activities. In addition, we also confirmed the superior MOR activity of Pt-Co NBs/C catalyst in acidic electrolytes. For Pt-M NBs with other alloying metals, the ORR and MOR activities are both higher than commercial catalysts and are in the sequence of Pt-Co/C > Pt-Fe/C > Pt-Ni/C > commercial Pt/C (or PtRu/C). The improved activities and durability can benefit from the morphological and compositional effects. This synthesis approach may be applied to develop bifunctional catalysts with enhanced ORR and MOR properties for future fuel cells designs.

A largely unexplored approach for optimizing surface strains on terrace-type catalysts is the break of atomic symmetry to release surface stress. The key challenge lies in how to implement this approach into practical nanocatalysts, in particular the promising high-entropy alloys (HEAs). Herein, we design and synthesize a series of HEA nanorings (NRs) with abundant terrace-type defects for oxygen reduction reaction (ORR) electrocatalysis. The asymmetry-triggered release of surface stress enables the modulation of compressive strain for optimizing the electronic structure. On the optimally-tuned PtPdFeCoNi HEA NRs, we achieve mass and specific activities of 0.99 A mg -1 platinum group metal (PGM) and 1.32 mA cm -2 PGM at 0.95 V versus reversible hydrogen electrode (vs. RHE), demonstrating a competitive performance. Experimental and theoretical investigations unveil that the stress-released compressive strain lowers the d -band center of Pt sites in HEA NRs, resulting in favorable desorption of oxygenated intermediates and thus accelerated ORR kinetics. Breaking the symmetry of high-entropy alloy surfaces for delicate strain tuning is highly appealing for electrocatalysis. Herein, high-entropy alloy nanorings with stress-release-driven compressive strain at stepped defects are reported for efficient oxygen reduction reaction.