Hydrophobic Microenvironment Modulation of Ru Nanoparticles in Metal-Organic Frameworks for Enhanced Electrocatalytic N2 Reduction.

The modulation of the chemical microenvironment surrounding metal nanoparticles (NPs) is an effective means to enhance the selectivity and activity of catalytic reactions. Herein, a post-synthetic modification strategy is developed to modulate the hydrophobic microenvironment of Ru nanoparticles encapsulated in a metal-organic framework (MOF), MIP-206, namely Ru@MIP-Fx (where x represents perfluoroalkyl chain lengths of 3, 5, 7, 11, and 15), in order to systematically explore the effect of the hydrophobic microenvironment on the electrocatalytic activity. The increase of perfluoroalkyl chain length can gradually enhance the hydrophobicity of the catalyst, which effectively suppresses the competitive hydrogen evolution reaction (HER). Moreover, the electrocatalytic production rate of ammonia and the corresponding Faraday efficiency display a volcano-like pattern with increasing hydrophobicity, with Ru@MIP-F7 showing the highest activity. Theoretical calculations and experiments jointly show that modification of perfluoroalkyl chains of different lengths on MIP-206 modulates the electronic state of Ru nanoparticles and reduces the rate-determining step for the formation of the key intermediate of N2H2 *, leading to superior electrocatalytic performance.

Predictors, prevalence and prognostic role of pulmonary hypertension in patients with chronic kidney disease: a systematic review and meta-analysis.

BACKGROUND: To estimate the predictors, prevalence and prognostic role of pulmonary hypertension (PH) in patients with chronic kidney disease (CKD) using meta-analysis. METHODS: The PubMed, EmBase, and the Cochrane library were systematically searched for eligible studies from inception till May 2024. All of pooled analyses were performed using the random-effects model. RESULTS: Fifty observational studies involving 17,558 CKD patients were selected. The prevalence of PH in CKD patients was 38% (95% confidence interval [CI]: 33%-43%), and the prevalence according to CKD status were 31% (95% CI: 20%-42%) for CKD (I-V), 39% (95% CI: 25%-54%) for end stage kidney disease (ESKD) (predialysis), 42% (95% CI: 35%-50%) for ESKD (hemodialysis), and 26% (95% CI: 19%-34%) for renal transplant. We noted the risk factors for PH in CKD included Black individuals (relative risk [RR]: 1.39; 95% CI: 1.18-1.63; p < 0.001), chronic obstructive pulmonary disease (RR: 1.48; 95% CI: 1.21-1.82; p < 0.001), cardiovascular disease history (RR: 1.62; 95% CI: 1.05-2.51; p = 0.030), longer dialysis (RR: 1.70; 95% CI: 1.18-2.46; p = 0.005), diastolic dysfunction (RR: 1.88; 95% CI: 1.38-2.55; p < 0.001), systolic dysfunction (RR: 3.75; 95% CI: 2.88-4.87; p < 0.001), and grade 5 CKD (RR: 5.64; 95% CI: 3.18-9.98; p < 0.001). Moreover, PH in CKD patients is also associated with poor prognosis, including all-cause mortality, major cardiovascular events, and cardiac death. CONCLUSION: This study systematically identified risk factors for PH in CKD patients, and PH were associated with poor prognosis. Therefore, patients with high prevalence of PH should be identified for treatment.

Antielectric Potential Synthesis of Plasmonic Au-Ag Multidimensional Dimers Array for High-Resolution Encrypted Information.

Plasmonic superstructures hold great potential in encrypted information chips but are still unsatisfactory in terms of resolution and maneuverability because of the limited fabrication strategies. Here, we develop an antielectric potential method in which the interfacial energy from the modification of 5-amino-2-mercapto benzimidazole (AMBI) ligand is used to overcome the electric resistance between the Au nanospheres (NSs) and substrate, thereby realizing the in situ growth of a Au-Ag heterodimers array in large scale. The morphology, number, and size of Ag domains on Au units can be controlled well by modulating the reaction kinetics and thermodynamics. Experiments and theoretical simulations reveal that patterned 3D Au-2D Ag and 3D Au-3D Ag dimer arrays with line widths of 400 nm exhibit cerulean and cyan colors, respectively, and achieve fine color modulation and ultrahigh information resolution. This work not only develops a facile strategy for fabricating patterned plasmonic superstructures but also pushes the plasmon-based high-resolution encrypted information chip into more complex applications.

ResD-Net: A model for rapid prediction of antioxidant activity in gentian root using FT-IR spectroscopy.

Gentian, an herb resource known for its antioxidant properties, has garnered significant attention. However, existing methods are time-consuming and destructive for assessing the antioxidant activity in gentian root samples. In this study, we propose a method for swiftly predicting the antioxidant activity of gentian root using FT-IR spectroscopy combined with chemometrics. We employed machine learning and deep learning models to establish the relationship between FT-IR spectra and DPPH free radical scavenging activity. The results of model fitting reveal that the deep learning model outperforms the machine learning model. The model's performance was enhanced by incorporating the Double-Net and residual connection strategy. The enhanced model, named ResD-Net, excels in feature extraction and also avoids gradient vanishing. The ResD-Net model achieves an R2 of 0.933, an RMSE of 0.02, and an RPD of 3.856. These results support the accuracy and applicability of this method for rapidly predicting antioxidant activity in gentian root samples.

Regulating Oxygen Redox Chemistry through the Synergistic Effect of Transition-Metal Vacancy and Substitution Element for Layered Oxide Cathodes.

Reversible oxygen redox (OR) is considered as a paradigmatic avenue to boost the energy densities of layered oxide cathodes. However, its activation is largely coupled with the local coordination environment around oxygen, which is usually accompanied with irreversible oxygen release and unfavorable structure distortion. Herein, it is revealed that the synergistic effect of transition-metal (TM) vacancy and substitution element for modulating the OR activity and reversibility of layered Na0.67 MnO2 through multimodal operando synchrotron characterizations and electrochemical investigations. It is disclosed that TM vacancy can not only suppress the complicated phase transition but also stimulate the OR activity by creating nonbonding O 2p states via the Na─O─vacancy configurations. Notably, the substitution element plays a decisive role for regulating the reversibility of vacancy-boosted OR activity: the presence of strong Al─O bonds stabilizes the Mn-O motifs by sharing O with Al in the rigid Mn─O─Al frameworks, which mitigates TM migration and oxygen release induced by TM vacancy, leading to enhanced OR reversibility; while the introduction of weak Zn─O bonds exacerbates TM migration and irreversible oxygen release. This work clarifies the critical role of both TM vacancy and substitution element for regulating the OR chemistry, providing an effective avenue for designing high-performance cathodes employing anionic redox.

FHUSP-NET: A Multi-task model for fetal heart ultrasound standard plane recognition and key anatomical structures detection.

In prenatal ultrasound screening, rapid and accurate recognition of the fetal heart ultrasound standard planes(FHUSPs) can more objectively predict fetal heart growth. However, the small size and movement of the fetal heart make this process more difficult. Therefore, we design a deep learning-based FHUSP recognition network (FHUSP-NET), which can automatically recognize the five FHUSPs and detect tiny key anatomical structures at the same time. 3360 ultrasound images of five FHUSPs from 1300 mid-pregnancy pregnant women are included in this study. 10 fetal heart key anatomical structures are manually annotated by experts. We apply spatial pyramid pooling with a fully connected spatial pyramid convolution module to capture information about targets and scenes of different sizes as well as improve the perceptual ability and feature representation of the model. Additionally, we adopt the squeeze-and-excitation networks to improve the sensitivity of the model to the channel features. We also introduce a new loss function, the efficient IOU loss, which makes the model effective for optimizing similarity. The results demonstrate the superiority of FHUSP-NET in detecting fetal heart key anatomical structures and recognizing FHUSPs. In the detection task, the value of mAP@0.5, precision, and recall are 0.955, 0.958, and 0.931, respectively, while the accuracy reaches 0.964 in the recognition task. Furthermore, it takes only 13.6 ms to detect and recognize one FHUSP image. This method helps to improve ultrasonographers' quality control of the fetal heart ultrasound standard plane and aids in the identification of fetal heart structures in a less experienced group of physicians.

Transcriptional Interactions of Single B-Subgenome Chromosome with C-Subgenome in B. oleracea-nigra Additional Lines.

Serial monosomic alien addition lines (MAALs) provide an ideal system to elucidate the transcriptomic interactions between the alien chromosomes and recipient genome under aneuploidy. Herein, five available Brassica oleracea-nigra MAALs (CCB1, CCB4, CCB5, CCB6, CCB8), their derived B. oleracea plants (non-MAALs), and two parents were analyzed for their gene expressions by using high-throughput technology. Compared to parental B. oleracea, all MAALs showed various numbers of DEGs, but CCB8 gave much higher DEGs; the number of downregulated DEGs was slightly higher than the number of upregulated ones, except for in relation to CCB8. All derived B. oleracea plants also gave certain numbers of DEGs, despite these being much lower than in the respective MAALs. Compared to B. nigra, in all five MAALs more DEGs were downregulated than upregulated. Trans-effects were likely more prevailing than cis-effects, and these DEGs were predominantly associated with material transport by dysregulating the cellular component. Meanwhile, the orthologous genes on alien chromosomes could only play a feeble compensatory role for those gene pairs in C-subgenome, and different levels of the expressed genes had a greater tendency towards downregulation. These results revealed transcriptional aneuploidy response patterns between two genomes and suggested that cis- and trans-mechanisms synergistically regulated alien gene transcriptions after distant hybridization.

Strategies for Optimizing the Zn Anode/Electrolyte Interfaces Toward Stable Zn-Based Batteries.

Aqueous rechargeable Zn-ion batteries (ARZIBs) have attracted extensive attention because of the advantages of high energy density, high safety, and low cost. However, the commercialization of ARZIBs is still challenging, mainly because of the low efficiency of Zn anodes. Several undesirable reactions (e.g., Zn dendrite and byproduct formation) always occur at the Zn anode/electrolyte interfaces, resulting in low Coulombic efficiency and rapid decay of ARZIBs. Motivated by the great interest in addressing these issues, various optimization strategies and related mechanisms have been proposed to stabilize the Zn anode-electrolyte interfaces and enlengthen the cycling lifespan of ARZIBs. Therefore, considering the rapid development of this field, updating the optimization strategies in a timely manner and understanding their protection mechanisms are highly necessary. This review provides a brief overview of the Zn anode/electrolyte interfaces from the fundamentals and challenges of Zn anode chemistry to related optimization strategies and perspectives. Specifically, these strategies are systematically summarized and classified, while several representative works are presented to illustrate the effect and corresponding mechanism in detail. Finally, future challenges and research directions for the Zn anode/electrolyte interfaces are comprehensively clarified, providing guidelines for accurate evaluation of the interfaces and further fostering the development of ARZIBs.

Steering the liquid-solid redox conversion of lithium-selenium batteries through ultrafine MoC catalyst.

Selenium cathodes have attracted much attention because of the high electronic conductivity and energy density. However, the shuttle effect of lithium polyselenides (LiPSes) leads to rapid capacity fading, hindering the practical application of lithium-selenium (Li-Se) batteries. Herein, an ultrafine MoC catalyst has been synthesized and utilized to accelerate the conversion from liquid LiPSes to solid Li2Se2/Li2Se, leading to suppressed shuttle effect and thus improved battery performance. Our present study provides valuable inspiration to the future exploration for the rational design of high-efficient catalysts for practical Li-Se batteries.

Supervertex Sampling Network: A Geodesic Differential SLIC Approach for 3D Mesh.

The analysis of 3D meshes with deep learning has become prevalent in computer graphics. As an essential structure, hierarchical representation is critical for mesh pooling in multiscale analysis. Existing clustering-based mesh hierarchy construction methods involve nonlinear discretization optimization operations, making them nondifferential and challenging to embed in other trainable networks for learning. Inspired by deep superpixel learning methods in image processing, we extend them from 2D images to 3D meshes by proposing a novel differentiable chart-based segmentation method named geodesic differential supervertex (GDSV). The key to the GDSV method is to ensure that the geodesic position updates are differentiable while satisfying the constraint that the renewed supervertices lie on the manifold surface. To this end, in addition to using the differential SLIC clustering algorithm to update the nonpositional features of the supervertices, a reparameterization trick, the Gumbel-Softmax trick, is employed to renew the geodesic positions of the supervertices. Therefore, the geodesic position update problem is converted into a linear matrix multiplication issue. The GDSV method can be an independent module for chart-based segmentation tasks. Meanwhile, it can be combined with the front-end feature learning network and the back-end task-specific network as a plug-in-plug-out module for training; and be applied to tasks such as shape classification, part segmentation, and 3D scene understanding. Experimental results show the excellent performance of our proposed algorithm on a range of datasets.

Local Construction of Mn-Based Layered Cathodes through Covalency Modulation for Sodium-Ion Batteries.

P2-type Mn-based layered oxides are among the most prevalent cathodes for sodium-ion batteries (SIBs) owing to their low cost, resource abundance, and high theoretical specific capacity. However, they usually suffer from Jahn-Teller (J-T) distortion from high-spin Mn3+ and poor cycling stability, resulting in rapid degradation of their structural and electrochemical properties. Herein, a stable P2-type Mn-based layered oxide is realized through a local construction strategy by introducing high-valence Ru4+ to overcome these issues. It has been revealed that the Ru substitution in the as-constructed Na0.6Mg0.3Mn0.6Ru0.1O2 (NMMRO) renders the following favorable effects. First, the detrimental P2-OP4 phase transition is effectively inhibited owing to the robust Ru-O covalency bond. Second, the Mg/Mn ordering is disturbed and the out-of-plane displacement of Mg2+ and in-plane migration of Mn4+ are suppressed, leading to improved structural stability. Third, the redox ability of Mn is increased by weakening the covalence between Mn and O through the local Ru-O-Mn configurations, which contributes to the attenuated J-T distortion. Last, the strong Ru-O covalency bond also leads to enhanced electron delocalization between Ru and O, which decreases the oxidation of oxygen anion and thereby reduces the driving force of metal migration. Because of these advantages, the structural integrity and electrochemical properties of NMMRO are largely improved compared with the Ru-free counterpart. This work provides deeper insights into the effect of local modulation for cationic/anionic redox-active cathodes for high-performance SIBs.

TUSPM-NET: A multi-task model for thyroid ultrasound standard plane recognition and detection of key anatomical structures of the thyroid.

The thyroid gland is a vital gland located in the anterior part of the neck. Ultrasound imaging of the thyroid gland is a non-invasive and widely used technique for diagnosing nodular growth, inflammation, and enlargement of the thyroid gland. In ultrasonography, the acquisition of ultrasound standard planes is crucial for disease diagnosis. However, the acquisition of standard planes in ultrasound examinations can be subjective, laborious and heavily reliant on the sonographer's clinical experience. To overcome these challenges, we design a multi-task model TUSP Multi-task Network (TUSPM-NET) that can recognize Thyroid Ultrasound Standard Plane (TUSP) and detect key anatomical structures in TUSPs in real-time. To improve TUSPM-NET's accuracy and learn prior knowledge in medical images, we proposed the plane target classes loss function and the plane targets position filter. Additionally, we collected 9778 TUSP images of 8 standard planes to train and validate the model. Experiments have shown that TUSPM-NET can accurately detect anatomical structures in TUSPs and recognize TUSP images. Compared to current models with better performance, TUSPM-NET's object detection map@0.5:0.95 improves by 9.3%; the precision and recall of plane recognition improve by 3.49% and 4.39%, respectively. Furthermore, TUSPM-NET recognizes and detects a TUSP image in just 19.9 ms, which means that the method is well suited to the needs of real-time clinical scanning.

Electrochemical Restoration of Battery Materials Guided by Synchrotron Radiation Technology for Sustainable Lithium-Ion Batteries.

Lithium-ion batteries (LIBs) have been ubiquitous in modern society, especially in the fields of electronic devices, electric vehicles and grid storage, while raising concerns about a tremendous number of spent batteries in the next five to ten years. As environmental awareness and resource security is gaining increasingly extensive attention, how to effectively deal with spent LIBs has become a challenging issue academically and industrially. Accordingly, the development of battery recycling has surfaced as a highly researched topic in the battery community. Recently, the structural and electrochemical restoration of recycled electrode materials have been proposed as a non-destructive method to save more energy and chemical agents compared with mature metallurgical methods. Such a refurbishment process of electrode materials is also regarded as a reverse process of their degradation in the working condition. Notably, synchrotron radiation technology, which is previously applied to diagnose battery degrade, has started to play major roles in gaining more insight into the structural restoration of electrode materials. Here, the contribution of synchrotron radiation technology to reveal the underlying degradation and regeneration mechanisms of LIBs cathodes is highlighted, providing a theoretical basis and guidance for the direct recycling and reuse of degraded cathodes.

Rapid controllable synthesis of branched Au superparticles: formation mechanism of toggling the growth mode and their applications in optical broadband absorption.

We develop a tunable, ultrafast (5 seconds), and mass-producible seed-mediated synthesis method to prepare branched Au superparticles consisting of multiple small Au island-like nanoparticles by a wet chemical route. We reveal and confirm the toggling formation mechanism of Au superparticles between the Frank-van der Merwe (FM) growth mode and the Volmer-Weber (VW) growth mode. The key factor of this special structure is the frequent toggling between the FM (layer by layer) growth mode and the VW (island) growth mode induced by 3-aminophenol, which is continuously absorbed on the surface of newborn Au nanoparticles, leading to a relatively high surface energy during the overall synthesis process, thus achieving an island on island growth. Such Au superparticles demonstrate broadband absorption from visible to near-infrared regions due to their multiple plasmonic coupling and hence they have important applications in sensors, photothermal conversion and therapy, etc. We also exhibit the excellent properties of Au superparticles with different morphologies, such as NIR-II photothermal conversion and therapy and SERS detection. The photothermal conversion efficiency under 1064 nm laser irradiation was calculated to be as high as 62.6% and they exhibit robust photothermal therapy efficiency. This work provides insight into the growth mechanism of plasmonic superparticles and develops a broadband absorption material for highly efficient optical applications.

Unraveling Large and Polyploidy Genome of the Crucifer Orychophragmus violaceus in China, a Potential Oil Crop.

The genus Orychophragmus in the Brassicaceae family includes the types with 2n = 20, 22, 24, and 48. The species O. violaceus (L.) O. E. Schulz has 2n = 24 and is widely cultivated as an ornamental plant in China. This review summarizes the research progress of its genome structure and evolution in the context of cytogenetics and genome sequencing. This species has a large genome size of ~1 Gb and longer chromosomes than those of Brassica species, which is attributable to the burst of TE insertions. Even more, one tetraploidization event from about 600-800 million years ago is elucidated to occur during its genome evolution, which is consistent with the polyploidy nature of its genome revealed by the meiotic pairing patterns. Its chromosomes are still characterized by a larger size and deeper staining than those from Brassica species in their intergeneric hybrids, which is likely related to their inherent differences between genome structures and cytology. Its genome is dissected by the development of additional alien lines, and some traits are located on individual chromosomes. Due to the abundant dihydroxy fatty acids in its seed oil with superior lubricant properties and wide environmental adaptations, this plant promises to be utilized as one new oil crop in the future.

Ultra-Attention: Automatic Recognition of Liver Ultrasound Standard Sections Based on Visual Attention Perception Structures.

Acquisition of a standard section is a prerequisite for ultrasound diagnosis. For a long time, there has been a lack of clear definitions of standard liver views because of physician experience. The accurate automated scanning of standard liver sections, however, remains one of ultrasonography medicine's most important issues. In this article, we enrich and expand the classification criteria of liver ultrasound standard sections from clinical practice and propose an Ultra-Attention structured perception strategy to automate the recognition of these sections. Inspired by the attention mechanism in natural language processing, the standard liver ultrasound views will participate in the global attention algorithm as modular local images in computer vision of ultrasound images, which will significantly amplify small features that would otherwise go unnoticed. In addition to using the dropout mechanism, we also use a Part-Transfer Learning training approach to fine-tune the model's rate of convergence to increase its robustness. The proposed Ultra-Attention model outperforms various traditional convolutional neural network-based techniques, achieving the best known performance in the field with a classification accuracy of 93.2%. As part of the feature extraction procedure, we also illustrate and compare the convolutional structure and the Ultra-Attention approach. This analysis provides a reasonable view for future research on local modular feature capture in ultrasound images. By developing a standard scan guideline for liver ultrasound-based illness diagnosis, this work will advance the research on automated disease diagnosis that is directed by standard sections of liver ultrasound.

Atom Absorption Energy Directed Symmetry-Breaking Synthesis of Au-Ag Hierarchical Nanostructures and Their Efficient Photothermal Conversion.

Asymmetric plasmonic hierarchical nanostructures (HNs) are of great significance in optics, catalysis, and sensors, but the complex growth kinetics and lack of fine structure design limit their practical applications. Herein, a new atom absorption energy strategy is developed to achieve a series of Au-Ag HNs with the continuously tuned contact area in Janus and Ag island number/size on Au seeds. Different from the traditional passive growth mode, this strategy endows seed with a hand to capture the hetero atoms in a proactive manner, which is beyond the size, shape, and assembles of Au seed. Density functional theory reveals ththe adsorption of PDDA on Au surface leads to lower formation energy of Au-Ag bonds (-3.96 eV) than FSDNA modified Au surface (-2.44 eV). The competitive adsorption of two ligands on Au seed is the decisive factor for the formation of diverse Au-Ag HNs. In particular, the Au-Ag2 HNs exhibit outstanding photothermal conversion capability in the near-infrared window, and in vivo experiments verify them as superior photothermal therapy agents. This work highlights the importance of the atom absorption energy strategy in unlocking the diversity of HNs and may push the synthesis and application of superstructures to a higher level.

Rapid Identification of Wild Gentiana Genus in Different Geographical Locations Based on FT-IR and an Improved Neural Network Structure Double-Net.

Gentiana Genus, a herb mainly distributed in Asia and Europe, has been used to treat the damp heat disease of the liver for over 2000 years in China. Previous studies have shown significant differences in the compositional contents of wild Gentiana Genus samples from different geographical origins. Therefore, the traceable geographic locations of the wild Gentiana Genus samples are essential to ensure practical medicinal value. Over the last few years, the developments in chemometrics have facilitated the analysis of the composition of medicinal herbs via spectroscopy. Notably, FT-IR spectroscopy is widely used because of its benefit of allowing rapid, nondestructive measurements. In this paper, we collected wild Gentiana Genus samples from seven different provinces (222 samples in total). Twenty-one different FT-IR spectral pre-processing methods that were used in our experiments. Meanwhile, we also designed a neural network, Double-Net, to predict the geographical locations of wild Gentiana Genus plants via FT-IR spectroscopy. The experiments showed that the accuracy of the neural network structure Double-Net we designed can reach 100%, and the F1_score can reach 1.0.

Strengthened d-p Orbital Hybridization through Asymmetric Coordination Engineering of Single-Atom Catalysts for Durable Lithium-Sulfur Batteries.

Although single-atom catalysts (SACs) have been largely explored in lithium-sulfur (Li-S) batteries, the commonly reported nonpolar transition metal-N4 coordinations only demonstrate inferior adsorption and catalytic activity toward shuttled lithium polysulfides (LiPSs). Herein, single Fe atoms with asymmetric coordination configurations of Fe-N3C2-C were precisely designed and synthesized as efficient immobilizer and catalyst for LiPSs. The experimental and theoretical results elucidate that the asymmetrically coordinated Fe-N3C2-C moieties not only enhance the LiPSs anchoring capability by the formation of extra π-bonds originating from S p orbital and Fe dx2-y2/dxy orbital hybridization but also boost the redox kinetics of LiPSs with reduced Li2S precipitation/decomposition barrier, leading to suppressed shuttle effect. Consequently, the Li-S batteries assembled with Fe-N3C2-C exhibit high areal capacity and cycling stability even under high sulfur loading and lean electrolyte conditions. This work highlights the important role of coordination symmetry of SACs for promoting the practical application of Li-S batteries.