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Subnanometric metal species (single atoms and clusters) have been demonstrated to be unique compared with their nanoparticulate counterparts. However, the poor stabilization of subnanometric metal species towards sintering at high temperature (>500 °C) under oxidative or reductive reaction conditions limits their catalytic application. Zeolites can serve as an ideal support to stabilize subnanometric metal catalysts, but it is challenging to localize subnanometric metal species on specific sites and modulate their reactivity. We have achieved a very high preference for localization of highly stable subnanometric Pt and PtSn clusters in the sinusoidal channels of purely siliceous MFI zeolite, as revealed by atomically resolved electron microscopy combining high-angle annular dark-field and integrated differential phase contrast imaging techniques. These catalysts show very high stability, selectivity and activity for the industrially important dehydrogenation of propane to form propylene. This stabilization strategy could be extended to other crystalline porous materials.

Zeolites containing Rh single sites stabilized by phosphorous were prepared through a one-pot synthesis method and are shown to have superior activity and selectivity for ethylene hydroformylation at low temperature (50 °C). Catalytic activity is ascribed to confined Rh 2 O 3 clusters in the zeolite which evolve under reaction conditions into single Rh 3+ sites. These Rh 3+ sites are effectively stabilized in a Rh-(O)-P structure by using tetraethylphosphonium hydroxide as a template, which generates in situ phosphate species after H 2 activation. In contrast to Rh 2 O 3 , confined Rh 0 clusters appear less active in propanal production and ultimately transform into Rh(I)(CO) 2 under similar reaction conditions. As a result, we show that it is possible to reduce the temperature of ethylene hydroformylation with a solid catalyst down to 50 °C, with good activity and high selectivity, by controlling the electronic and morphological properties of Rh species and the reaction conditions. Isolated Rh 3+ sites are stabilized inside the MFI zeolite channels with phosphorous which is added during zeolite synthesis in the form of a phosphonium zeolite template. This Rh 3+ shows high activity in the low-temperature ethylene hydroformylation.

Approaching the level of molecular recognition of enzymes with solid catalysts is a challenging goal, achieved in this work for the competing transalkylation and disproportionation of diethylbenzene catalyzed by acid zeolites. The key diaryl intermediates for the two competing reactions only differ in the number of ethyl substituents in the aromatic rings, and therefore finding a selective zeolite able to recognize this subtle difference requires an accurate balance of the stabilization of reaction intermediates and transition states inside the zeolite microporous voids. In this work we present a computational methodology that, by combining a fast high-throughput screeening of all zeolite structures able to stabilize the key intermediates with a more computationally demanding mechanistic study only on the most promising candidates, guides the selection of the zeolite structures to be synthesized. The methodology presented is validated experimentally and allows to go beyond the conventional criteria of zeolite shape-selectivity. Approaching the level of molecular recognition of enzymes with solid catalysts is a challenging goal. Here, the authors present a computational methodology that guides the selection of the most adequate zeolite frameworks for target reactions.

Water and nitrogen losses from farmland during the snowmelt process play a vital role in water and nitrogen management in cold regions. To explore the mechanisms and factors contributing to water and nitrogen loss from different sloping farmlands during the snowmelt period, field experiments were conducted under two slope treatments (8° and 15°), two soil water content (SWC) treatments, and two snow water equivalent (SWE) (5 mm and 10 mm) treatments in a seasonal freezing agricultural watershed of Northeast China. The results showed that during the snowmelt process, SWE was the most important factor affecting water and nitrogen production through the surface and total runoff of the sloping farmland, followed by the slope. The water and nitrogen yield in the high snow (HS) treatments ranged from 1.76 to 8.15 and 1.65 to 12.62 times higher than those in the low snow (LS) treatments. The generation of nitrogen was advanced compared with that of water induced by the preferential production of nitrogen. A higher slope promoted this preferential production function of nitrogen. Enhanced infiltration combined with the preferential yield of nitrogen resulted in a greatly decreased yield of water and nitrogen in the gentle slope and LS (GS_LS) treatments. These findings are valuable for accurately describing the water and nitrogen cycling in seasonally freezing sloping farmland.

Catalysis with enzymes and zeolites have in common the presence of well-defined single active sites and pockets/cavities where the reaction transition states can be stabilized by longer-range interactions. We show here that for a complex reaction, such as the conversion of methanol-to-olefins (MTO), it is possible to synthesize reaction-adapted zeolites by using mimics of the key molecular species involved in the MTO mechanism. Effort has focused on the intermediates of the paring mechanism because the paring is less favoured energetically than the side-chain route. All the organic structure-directing agents based on intermediate mimics crystallize cage-based small-pore zeolitic materials, all of them capable of performing the MTO reaction. Among the zeolites obtained, RTH favours the whole reaction steps following the paring route and gives the highest propylene/ethylene ratio compared to traditional CHA-related zeolites (3.07 and 0.86, respectively). Methanol-to-olefins (MTO) conversion over zeolites is a promising route for the production of light olefins. Now, Corma and co-workers show that using mimics of reaction intermediates as structure-directing agents allows the synthesis of highly selective zeolite MTO-catalysts.

Modern GPU/CPU systems integrate hundreds of cores on a single die, and future scaling envisions even more cores being incorporated. However, this growth is constrained by the limited number of transistors per die. To address this challenge, chiplet technology has emerged as a promising approach due to its higher integration density, improved flexibility, and reduced cost. Nevertheless, existing chiplet interconnection technologies suffer from limitations in terms of bandwidth, latency, and energy efficiency. In contrast, optical interconnects offer significant advantages, including low latency, ultrahigh bandwidth, and good energy efficiency, making them an ideal choice for highperformance chiplet-based systems. However, previously proposed optical networks lack scalability and are not directly applicable to existing chiplet-based systems. Moreover, they ignore the communication characteristics specific to CPU/GPU systems.To address these issues comprehensively, we establish a power model and an optical device cost model for inter-chiplet optical interconnect. Additionally, we conduct a quantitative analysis of the traffic characteristics within chiplet-based CPU and GPU systems. Based on these findings, we introduce a photonic cache coherence network (PCCN) for chiplet-based manycore processors, which accelerates cache coherence transactions and alleviates cache coherence overhead. We propose a novel region-based optical network (RONet) with a tuning-free mechanism for chiplet-based GPU, which significantly enhances system performance and energy efficiency. Considering the limitation of RONet, we further optimize our design and propose a group-based optical network (GROOT), which is more scalable and resolves the NUMA issue in RONet.

Under complex illumination conditions, the spectral data distributions of a given material appear inconsistent in the hyperspectral images of the space target, making it difficult to achieve accurate material identification using only spectral features and local spatial features. Aiming at this problem, a material identification method based on an improved graph convolutional neural network is proposed. Superpixel segmentation is conducted on the hyperspectral images to build the multiscale joint topological graph of the space target global structure. Based on this, topological graphs containing the global spatial features and spectral features of each pixel are generated, and the pixel neighborhoods containing the local spatial features and spectral features are collected to form material identification datasets that include both of these. Then, the graph convolutional neural network (GCN) and the three-dimensional convolutional neural network (3-D CNN) are combined into one model using strategies of addition, element-wise multiplication, or concatenation, and the model is trained by the datasets to fuse and learn the three features. For the simulated data and the measured data, the overall accuracy of the proposed method can be kept at 85–90%, and their kappa coefficients remain around 0.8. This proves that the proposed method can improve the material identification performance under complex illumination conditions with high accuracy and strong robustness.

CHD patients often present region-specific symptom clusters, such as “upper-body heat-related” (e.g., bitter taste) or “lower-body cold-related” (e.g., cold extremities), occurring independently or concurrently. Phenotype classification relies on subjective assessment and lacks quantitative indicators. This study aimed to establish a urine color-based quantitative model for objective CHD phenotype classification. From April 2023 to January 2024, a multicenter cross-sectional study involved 200 CHD patients and 240 healthy controls. Morning urine chromaticity was quantified using CIE Lab parameters (L, a, b values). The study included correlation analysis, two-way ANOVA, and hierarchical multinomial logistic regression. CHD patients had higher rates of upper-heat (44.50% vs. 25.42%, P  = 0.033) and lower-cold (60.50% vs. 20.42%, P  = 0.005) clusters than controls. Upper-heat clusters negatively correlated with L ( r =-0.73) and positively with a ( r  = 0.79)/b ( r  = 0.74); lower-cold clusters showed opposite correlations (L: r  = 0.81; a: r =-0.77; b: r =-0.73). Two-way ANOVA confirmed independent effects (η²=0.08–0.13, P  < 0.01) with no interaction. Urine color parameters explained 86.3% of phenotypic variation, with model accuracy of 85.2%. This is the first study to validate urine color quantification via CIE Lab as an objective tool for CHD phenotypic classification, offering a novel auxiliary method for precise syndrome identification and targeted interventions.

Abnormalities of autophagy can result in neurodegenerative disorders such as Alzheimer’s disease (AD). Nevertheless, the regulatory mechanisms of autophagy in AD are not well understood. Here, we describe our findings that microRNA (miR)-299-5p functions as an autophagy inhibitor by suppressing Atg5 and antagonizing caspase-dependent apoptosis. We observed decreased levels of miR-299-5p both in primary neurons under conditions of starvation and in hippocampi of APPswe/PS1dE9 mice. Additionally, low levels of miR-299-5p were observed in cerebrospinal fluid of AD patients. MiR-299-5p treatment resulted in attenuation of Atg5 and autophagy in primary neurons from APPswe/PS1dE9 mice, N2a cells and SH-SY5Y cells, whereas antagomiR-299-5p enhanced autophagy. Atg5 was verified as a direct target of miR-299-5p by dual luciferase reporter assays. Furthermore, transfection of miR-299-5p into primary hippocampal neurons caused the attenuation of caspase-mediated apoptosis, which was reversed upon starvation-induced autophagy. Inhibition of autophagy by shRNA knockdown of LC3β reduced apoptotic neuron death induced by antagomiR-299-5p. Injection of agomiR-299-5p into the cerebral ventricles of AD mice inhibited both autophagy and apoptosis and also improved the cognitive performance of mice. Overall, our results suggest that miR-299-5p modulates neuron survival programs by regulating autophagy. Thus, miR-299-5p serves as a potential neuroprotective factor in AD.

Objective We aimed to establish a method to determine whether amyloid‐β (Aβ) protein and miR‐384 in peripheral blood neural cell adhesion molecule (NCAM)/ATP‐binding cassette transporter A1 (ABCA1) dual‐labeled exosomes may serve as diagnostic markers for the diagnosis of Alzheimer's disease (AD). Methods This was a multicenter study using a two‐stage design. The subjects included 45 subjective cognitive decline (SCD) patients, 50 amnesic mild cognitive impairment (aMCI) patients, 40 AD patients, and 30 controls in the discovery stage. The results were validated in the verification stage in 47 SCD patients, 45 aMCI patients, 45 AD patients, and 30 controls. NCAM single‐labeled and NCAM/ABCA1 double‐labeled exosomes in the peripheral blood were captured and detected by immunoassay. Results The Aβ42, Aβ42/40, Tau, P‐T181‐tau, and miR‐384 levels in NCAM single‐labeled and NCAM/ABCA1 double‐labeled exosomes of the aMCI and AD groups were significantly higher than those of the SCD, control, and vascular dementia (VaD) groups (all p < 0.05). The Aβ42 and miR‐384 levels in NCAM/ABCA1 dual‐labeled exosomes of the aMCI and AD groups were higher than those of the control and VaD groups (all p < 0.05). The exosomal Aβ42, Aβ42/40, Tau, P‐T181‐tau, and miR‐384 levels in peripheral blood were correlated with those in cerebrospinal fluid (all p < 0.05). Conclusion This study, for the first time, established a method that sorts specific surface marker exosomes using a two‐step immune capture technology. The plasma NCAM/ABCA1 dual‐labeled exosomal Aβ42/40 and miR‐384 had potential advantages in the diagnosis of SCD. In this study, we applied a newly developed technology to capture peripheral blood exosomes with both NCAM and ABCA1 protein tags. We found that Aβ42 and miR‐384 in these exosomes have great potential value for the diagnosis of SCD and aMCI.