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The exploitation of the stable and earth-abundant electrocatalyst with high catalytic activity remains a significant challenge for hydrogen evolution reaction. Being different from complex nanostructuring, this work focuses on a simple and feasible way to improve hydrogen evolution reaction performance via manipulation of intrinsic physical properties of the material. Herein, we present an interesting semiconductor-metal transition in ultrathin troilite FeS nanosheets triggered by near infrared radiation at near room temperature for the first time. The photogenerated metal-phase FeS nanosheets demonstrate intrinsically high catalytic activity and fast carrier transfer for hydrogen evolution reaction, leading to an overpotential of 142 mV at 10 mA cm −2 and a lower Tafel slope of 36.9 mV per decade. Our findings provide new inspirations for the steering of electron transfer and designing new-type catalysts. While earth-abundant materials are promising catalysts for renewable energy conversion, such materials tend to display poor activities. Here, authors show FeS troilite nanosheets to undergo a near-infrared light-triggered transition to a phase that displays improved H 2 evolution performances.

Non-small cell lung cancer (NSCLC) represents for approximately 85% of all lung cancers, which is the most common cancer worldwide. Tumor-associated macrophages (TAM) are crucial for tumor progression, which was widely believed to be mediated by long non-coding RNAs (LncRNAs). We aimed to explore the effect of one LncRNA, GNAS-AS1, in TAM-associated NSCLC progression. Relative mRNA levels were determined by qRT-PCR. Western blot and ELISA were used to detect protein levels. Proliferation in vitro was assessed by MTT and clone formation assays. Migration and invasion of cell lines were evaluated by transwell-based assays. Interaction between molecules was detected by luciferase report assay. GNAS-AS1 expression was dramatically enhanced in TAM, NSCLC cell lines, and clinical tumor tissues, and negatively correlated with overall survival of NSCLC patients. GNAS-AS1 promoted macrophage M2 polarization and NSCLC cell progression via directly inhibiting miR-4319, which could target N-terminal EF-hand calcium binding protein 3 (NECAB3) to inhibit its expression. GNAS-AS1/miR-4319/NECAB3 axis promotes tumor progression of NSCLC by altering macrophage polarization. This novel mechanism may provide potential strategy for NSCLC treatment.

Photocatalytic hydrogen evolution from water has triggered an intensive search for metal-free semiconducting photocatalysts. However, traditional semiconducting materials suffer from limited hydrogen evolution efficiency owing to low intrinsic electron transfer, rapid recombination of photogenerated carriers, and lack of artificial microstructure. Herein, we report a metal-free half-metallic carbon nitride for highly efficient photocatalytic hydrogen evolution. The introduced half-metallic features not only effectively facilitate carrier transfer but also provide more active sites for hydrogen evolution reaction. The nanosheets incorporated into a micro grid mode resonance structure via in situ pyrolysis of ionic liquid, which show further enhanced photoelectronic coupling and entire solar energy exploitation, boosts the hydrogen evolution rate reach up to 1009 μmol g −1  h −1 . Our findings propose a strategy for micro-structural regulations of half-metallic carbon nitride material, and meanwhile the fundamentals provide inspirations for the steering of electron transfer and solar energy absorption in electrocatalysis, photoelectrocatalysis, and photovoltaic cells. The “storage” of sunlight as a chemical fuel can provide renewable on-demand energy, although current earth-abundant materials usually show low activities. Here, authors construct a carbon nitride material whose half-metallicity and micro grid resonance structure boost light-driven H 2 evolution.

This study investigates the role of Al alloying in tailoring the oxidation resistance of AlTiCrZrNbTa refractory high-entropy alloy (RHEA) coatings on Zry-4 substrates under high-temperature steam environments. Coatings with varying Al contents (0–25 at.%) were deposited via magnetron sputtering and subjected to oxidation tests at 1000–1100 °C. The results demonstrate that Al content critically governs oxidation kinetics and coating integrity. The optimal performance was achieved at 10 at.% Al, above which a dense, continuous composite oxide layer (Al2O3, TiO2, Cr2O3) formed, effectively suppressing oxygen penetration and maintaining strong interfacial adhesion. Indentation tests confirmed enhanced mechanical integrity in Al-10 coatings, with minimal cracking post-oxidation. Excessive Al alloying (≥17 at.%) led to accelerated coating oxidation. This work establishes a critical Al threshold for balancing oxidation and interfacial bonding, providing a design strategy for developing accident-tolerant fuel cladding coatings.

Sarcopenia, which is defined by a decline in skeletal muscle mass and strength associated with aging, is common among older individuals and presents considerable health dangers. Alzheimer's disease (AD) is a prevalent degenerative brain condition linked to a decrease in cognitive function. The intersection of these conditions remains underexplored. The goal of this systematic review and meta-analysis was to establish the frequency of sarcopenia in individuals with AD and investigate the relationship between sarcopenia and AD. We performed an extensive review of literature databases, including PubMed, Embase, Web of Science, and the Cochrane Library, through April 2024. The inclusion criteria included studies that provided data on the frequency of sarcopenia in patients with AD or that examined the odds ratios (ORs) associated with these comorbidities. R Studio (4.3.1) was utilized for conducting the statistical analyses. A total of 27 studies, comprising 3902 AD patients were included. In patients with AD, the combined occurrence of sarcopenia was 33.9%, with a confidence interval (CI) of 95%, ranging from 27.6% to 40.2%. Sarcopenia was found in 31.2% (95% CI: 0.223-0.402) and 41.9% (95% CI: 0.321-0.516) of patients with mild and moderate AD, respectively. The OR for the association between AD and sarcopenia was 2.670 (95% CI: 1.566-4.555), suggesting a robust correlation. Sarcopenia is highly prevalent in AD patients, highlighting the need for integrated care approaches to address both cognitive and physical health issues. Further research is needed to elucidate the pathophysiological links between AD and sarcopenia.

Cerebral small vessel disease (CSVD) is a leading cause of stroke and vascular cognitive impairment, but its metabolic determinants are not fully understood. Emerging evidence indicates that insulin resistance (IR) plays a crucial role in CSVD through vascular, inflammatory, and oxidative mechanisms. Higher IR levels may be associated with greater burdens of white matter hyperintensities, lacunes, cerebral microbleeds, and enlarged perivascular spaces. Mechanistic studies suggest that IR impairs endothelial nitric oxide signaling, disrupts the blood–brain barrier, promotes vascular remodeling, and alters astrocytic aquaporin-4 polarization, which together aggravate both ischemic and hemorrhagic microvascular injury. Clinically, IR represents a modifiable target, and interventions that reduce IR, including the use of pioglitazone, metformin, glucagon-like peptide-1 receptor agonists, physical activity, and dietary modification, may help slow CSVD progression. This mini review summarizes current epidemiological and mechanistic evidence linking IR to CSVD and highlights the potential of metabolic regulation as a strategy to prevent or mitigate small-vessel–related brain injury.

Accurate 3D terrain reconstruction from multi-view whisk-broom thermal infrared imagery with small intersection angles remains challenging because stereo geometry is weak and height sensitivity is limited. To address this challenge, we develop an affine-initialized rational polynomial coefficient (RPC) reconstruction framework for 3D positioning under weak geometric conditions. An affine model is first used to estimate initial 3D coordinates from image tie points, which are then used to initialize RPC-based refinement. The refinement adopts an iterative scheme with hierarchical updates, where longitude and latitude are optimized before altitude to mitigate error propagation when height observability is low. The method is evaluated using multi-view data acquired by the SDGSAT-1 Thermal Infrared Spectrometer (TIS) over plain, hilly, and mountainous terrains, with intersection angles ranging from 0.57° to 6.5°. The results show that approximately 80% of the reconstruction errors fall within 2 pixels and more than 90% fall within 3 pixels, corresponding to 60 m and 90 m at the image resolution used in this study. The root-mean-square error (RMSE) remains below 0.3 pixels in plains, 1.3 pixels in hilly areas, and 1.8 pixels in mountainous areas. Overall, the proposed framework facilitates stable 3D terrain reconstruction from whisk-broom thermal infrared imagery and reduces reliance on confidential rigorous sensor models.

We considered the problem of determining the singular elastic fields in a one-dimensional (1D) hexagonal quasicrystal strip containing two collinear cracks perpendicular to the strip boundaries under antiplane shear loading. The Fourier series method was used to reduce the boundary value problem to triple series equations, then to singular integral equations with Cauchy kernel. The analytical solutions are in a closed form for the stress field, and the stress intensity factors and the energy release rates of the phonon and phason fields near the crack tip are expressed using the first and third complete elliptic integrals. The effects of the geometrical parameters of the crack configuration on the dimensionless stress intensity factors are presented graphically. The studied crack model can be used to solve the problems of a periodic array of two collinear cracks of equal length in a 1D hexagonal quasicrystal strip and an eccentric crack in a 1D hexagonal quasicrystal strip. The propagation of cracks produced during their manufacturing process may result in the premature failure of quasicrystalline materials. Therefore, it is very important to study the crack problem of quasicrystalline materials with defects as mentioned above. It can provide a theoretical basis for the application of quasicrystalline materials containing the above defects.

The development and utilization of wind energy has alleviated the problems of energy shortage and environmental pollution; however, it caused many negative impacts due to suboptimal site selections. This study proposes an innovative method integrating Geographic Information System (GIS), fuzzy Analytic Hierarchy Process (FAHP), and fuzzy VIšekriterijumsko KOmpromisno Rangiranje (VIKOR) for site selection of wind farms in the Wafangdian region, China. The uncertainties caused by subjective judgments of the stakeholders were tackled by the FAHP method firstly, where weight values of six criteria were identified. Next, the fuzzy VIKOR method and GIS tool were used to generate the Qi value of each location for ranking their appropriate degrees for wind energy development. The results demonstrated that the middle and upper parts of the studied area are suitable for the exploitation of wind energy, while the central and eastern areas are unfavorable. The influences exerted by various weight combinations and climate change on a site suitability assessment were examined. The resulting comparison with existing wind farms reflected the practicability and reliability of the proposed method; the estimation of climate change impacts on site selection provided the suggestion and support of a long-term plan for wind power development, and even the energy structure adjustment scheme adapted to climate change.

Background A major current focus in the analysis of protein–protein interaction (PPI) data is how to identify essential proteins. As massive PPI data are available, this warrants the design of efficient computing methods for identifying essential proteins. Previous studies have achieved considerable performance. However, as a consequence of the features of high noise and structural complexity in PPIs, it is still a challenge to further upgrade the performance of the identification methods. Methods This paper proposes an identification method, named CTF, which identifies essential proteins based on edge features including h -quasi-cliques and uv -triangle graphs and the fusion of multiple-source information. We first design an edge-weight function, named EWCT, for computing the topological scores of proteins based on quasi-cliques and triangle graphs. Then, we generate an edge-weighted PPI network using EWCT and dynamic PPI data. Finally, we compute the essentiality of proteins by the fusion of topological scores and three scores of biological information. Results We evaluated the performance of the CTF method by comparison with 16 other methods, such as MON, PeC, TEGS, and LBCC, the experiment results on three datasets of Saccharomyces cerevisiae show that CTF outperforms the state-of-the-art methods. Moreover, our method indicates that the fusion of other biological information is beneficial to improve the accuracy of identification.