Constructing Asymmetric Fe-Nb Diatomic Sites to Enhance ORR Activity and Durability.

Iron-nitrogen-carbon (Fe-N-C) materials have been identified as a promising class of platinum (Pt)-free catalysts for the oxygen reduction reaction (ORR). However, the dissolution and oxidation of Fe atoms severely restrict their long-term stability and performance. Modulating the active microstructure of Fe-N-C is a feasible strategy to enhance the ORR activity and stability. Compared with common 3d transition metals (Co, Ni, etc.), the 4d transition metal atom Nb has fewer d electrons and more unoccupied orbitals, which could potentially forge a more robust interaction with the Fe site to optimize the binding energy of the oxygen-containing intermediates while maintaining stability. Herein, an asymmetric Fe-Nb diatomic site catalyst (FeNb/c-SNC) was synthesized, which exhibited superior ORR performance and stability compared with those of Fe single-atom catalysts (SACs). The strong interaction within the Fe-Nb diatomic sites optimized the desorption energy of key intermediates (*OH), so that the adsorption energy of Fe-*OH approaches the apex of the volcano plot, thus exhibiting optimal ORR activity. More importantly, introducing Nb atoms could effectively strengthen the Fe-N bonding and suppress Fe demetalation, causing an outstanding stability. The zinc-air battery (ZAB) and hydroxide exchange membrane fuel cell (HEMFC) equipped with our FeNb/c-SNC could deliver high peak power densities of 314 mW cm-2 and 1.18 W cm-2, respectively. Notably, the stable operation time for ZAB and HEMFC increased by 9.1 and 5.8 times compared to Fe SACs, respectively. This research offers further insights into developing stable Fe-based atomic-level catalytic materials for the energy conversion process.

Fe-S dually modulated adsorbate evolution and lattice oxygen compatible mechanism for water oxidation.

Simultaneously activating metal and lattice oxygen sites to construct a compatible multi-mechanism catalysis is expected for the oxygen evolution reaction (OER) by providing highly available active sites and mediate catalytic activity/stability, but significant challenges remain. Herein, Fe and S dually modulated NiFe oxyhydroxide (R-NiFeOOH@SO4) is conceived by complete reconstruction of NiMoO4·xH2O@Fe,S during OER, and achieves compatible adsorbate evolution mechanism and lattice oxygen oxidation mechanism with simultaneously optimized metal/oxygen sites, as substantiated by in situ spectroscopy/mass spectrometry and chemical probe. Further theoretical analyses reveal that Fe promotes the OER kinetics under adsorbate evolution mechanism, while S excites the lattice oxygen activity under lattice oxygen oxidation mechanism, featuring upshifted O 2p band centers, enlarged d-d Coulomb interaction, weakened metal-oxygen bond and optimized intermediate adsorption free energy. Benefiting from the compatible multi-mechanism, R-NiFeOOH@SO4 only requires overpotentials of 251 ± 5/291 ± 1 mV to drive current densities of 100/500 mA cm-2 in alkaline media, with robust stability for over 300 h. This work provides insights in understanding the OER mechanism to better design high-performance OER catalysts.

Targeting NTCP for liver disease treatment: A promising strategy.

The sodium taurocholate co-transporting polypeptide (NTCP), a bile acids transporter, has been identified as a new therapeutic target for the treatment of liver disease. This paper thoroughly investigates the function of NTCP for regulating bile acid regulation, its correlation with hepatitis B and D infections, and its association with various liver diseases. Additionally, in this review we examine recent breakthroughs in creating NTCP inhibitors and their prospective applications in liver disease treatment. While this review emphasizes the promising potential of targeting NTCP, it concurrently underscores the need for broader and more detailed research to fully understand the long-term implications and potential side effects associated with NTCP inhibition.

Trace alcohol ether electrolytes with dual-site hydrogen bonds and modulated solvation structures for ultralong-life zinc-ion batteries.

Aqueous zinc-ion batteries (AZIBs) are highly regarded for their affordability, stability, safety, and eco-friendliness. Nevertheless, their practical application is hindered by severe side reactions and the formation of zinc (Zn) dendrites on the Zn metal anode surface. In this study, we employ tetrahydrofuran alcohol (THFA), an efficient and cost-effective alcohol ether electrolyte, to mitigate these issues and achieve ultralong-life AZIBs. Theoretical calculations and experimental findings demonstrate that THFA acts as both a hydrogen bonding donor and acceptor, effectively anchoring H2O molecules through dual-site hydrogen bonding. This mechanism restricts the activity of free water molecules. Moreover, the two oxygen (O) atoms in THFA serve as dual solvation sites, enhancing the desolvation kinetics of [Zn(H2O)6]2+ and improving the deposition dynamics of Zn2+ ions. As a result, even trace amounts of THFA significantly suppress adverse reactions and the formation of Zn dendrites, enabling highly reversible Zn metal anodes for ultralong-life AZIBs. Specifically, a Zn-based symmetric cell containing 2 % THFA achieves an ultralong cycle life of 8,800 h at 0.5 mA cm-2/0.5 mAh cm-2, while a Zn//VO2 full cell containing 2 % THFA maintains a remarkable 80.03 % capacity retention rate at 5 A g-1 over 2,000 cycles. This study presents a practical strategy to develop dendrite-free, cost-effective, and highly efficient aqueous energy storage systems by leveraging alcohol ether compounds with dual-site hydrogen bonding capabilities.

Phagemid-based capsid system for CRISPR-Cas13a antimicrobials targeting methicillin-resistant Staphylococcus aureus.

In response to the escalating antibiotic resistance in multidrug-resistant pathogens, we propose an innovative phagemid-based capsid system to generate CRISPR-Cas13a-loaded antibacterial capsids (AB-capsids) for targeted therapy against multidrug-resistant Staphylococcus aureus. Our optimized phagemid system maximizes AB-capsid yield and purity, showing a positive correlation with phagemid copy number. Notably, an 8.65-fold increase in copy number results in a 2.54-fold rise in AB-capsid generation. Phagemids carrying terL-terS-rinA-rinB (prophage-encoded packaging site genes) consistently exhibit high packaging efficiency, and the generation of AB-capsids using lysogenized hosts with terL-terS deletion resulted in comparatively lower level of wild-type phage contamination, with minimal compromise on AB-capsid yield. These generated AB-capsids selectively eliminate S. aureus strains carrying the target gene while sparing non-target strains. In conclusion, our phagemid-based capsid system stands as a promising avenue for developing sequence-specific bactericidal agents, offering a streamlined approach to combat antibiotic-resistant pathogens within the constraints of efficient production and targeted efficacy.

OLR-Net: Object Label Retrieval Network for principal diagnosis extraction.

BACKGROUND: Extracting principal diagnosis from patient discharge summaries is an essential task for the meaningful use of medical data. The extraction process, usually by medical staff, is laborious and time-consuming. Although automatic models have been proposed to retrieve principal diagnoses from medical records, many rare diagnoses and a small amount of training data per rare diagnosis provide significant statistical and computational challenges. OBJECTIVE: In this study, we aimed to extract principal diagnoses with limited available data. METHODS: We proposed the OLR-Net, Object Label Retrieval Network, to extract principal diagnoses for discharge summaries. Our approach included semantic extraction, label localization, label retrieval, and recommendation. The semantic information of discharge summaries was mapped into the diagnoses set. Then, one-dimensional convolutional neural networks slid into the bottom-up region for diagnosis localization to enrich rare diagnoses. Finally, OLR-Net detected the principal diagnosis in the localized region. The evaluation metrics focus on the hit ratio, mean reciprocal rank, and the area under the receiver operating characteristic curve (AUROC). RESULTS: 12,788 desensitized discharge summary records were collected from the oncology department at Hainan Hospital of Chinese People's Liberation Army General Hospital. We designed five distinct settings based on the number of training data per diagnosis: the full dataset, the top-50 dataset, the few-shot dataset, the one-shot dataset, and the zero-shot dataset. The performance of our model had the highest HR@5 of 0.8778 and macro-AUROC of 0.9851. In the limited available (few-shot and one-shot) dataset, the macro-AUROC were 0.9833 and 0.9485, respectively. CONCLUSIONS: OLR-Net has great potential for extracting principal diagnosis with limited available data through label localization and retrieval.

Exploring the molecular and immune landscape of cellular senescence in lung adenocarcinoma.

Introduction: The connection between aging and cancer is complex. Previous research has highlighted the association between the aging process of lung adenocarcinoma (LUAD) cells and the immune response, yet there remains a gap in confirming this through single-cell data validation. Here, we aim to develop a novel aging-related prognostic model for LUAD, and verify the alterations in the genome and immune microenvironment linked to cellular senescence. Methods: We integrated a comprehensive collection of senescence genes from the GenAge and CellAge databases and employed the least absolute shrinkage and selection operator (LASSO) Cox analysis to construct and validate a novel prognostic model for LUAD. This model was then utilized to examine the relationship between aging, tumor somatic mutations, and immune cell infiltration. Additionally, we explored the heterogeneity of senescence and intercellular communication within the LUAD tumor microenvironment (TME) through single-cell transcriptomic data analysis. Results: By exploring the expression profiles of 586 cellular senescence-related genes in 428 LUAD patients, we constructed an aging-related genes (ARGs) risk model included 10 ARGs and validated it as an independent prognostic predictor for LUAD patients. Notably, patients with low aging scores (LAS group) exhibited better survival, lower tumor mutation burden (TMB), lower somatic mutation frequency, lower tumor proliferation rate, and an immune activated phenotype compared to patients with high aging scores (HAS group). While the HAS group was enriched in tumor cells and showed a lower infiltration of CD8-CCR7, CD8- CXCL13, CD8-GNLY, FCGR3A NK cells, XCL1 NK cells, plasma cell (PC) and other immune subsets. Furthermore, the SPP1 and TENASCIN pathways, associated with tumor immune escape and tumor progression, were also enriched in the HAS group. Additionally, our study also indicated that senescence levels were heterogeneous in the LUAD tumor microenvironment (TME), especially with tumor cells in the LAS group showing higher age scores compared to those in the HAS group. Conclusions: Collectively, our findings underscore that ARRS through ARGs serves as a robust biomarker for the prognosis in LUAD.

A Comprehensive Review on Phage Therapy and Phage-Based Drug Development.

Phage therapy, the use of bacteriophages (phages) to treat bacterial infections, is regaining momentum as a promising weapon against the rising threat of multidrug-resistant (MDR) bacteria. This comprehensive review explores the historical context, the modern resurgence of phage therapy, and phage-facilitated advancements in medical and technological fields. It details the mechanisms of action and applications of phages in treating MDR bacterial infections, particularly those associated with biofilms and intracellular pathogens. The review further highlights innovative uses of phages in vaccine development, cancer therapy, and as gene delivery vectors. Despite its targeted and efficient approach, phage therapy faces challenges related to phage stability, immune response, and regulatory approval. By examining these areas in detail, this review underscores the immense potential and remaining hurdles in integrating phage-based therapies into modern medical practices.

Enrichment and characterization of thermophilic anaerobic ammonium oxidizing bacteria from hot spring.

Anaerobic ammonium oxidization (Anammox) process plays a crucial role in the global nitrogen cycle and sustainable biological nitrogen removal from wastewater. Although Anammox bacteria have been detected across mesophilic and thermophilic conditions, the direct cultivation of Anammox bacteria from thermal environments has remained elusive. This impedes limiting our understanding of their physiology and ecology in high-temperature habitats. Here, we successfully enriched Anammox bacteria from hot spring sediments at 45 °C, achieving an ammonium oxidation rate of 158.0 mg NH4+-N l-1d-1, with the genus 'Candidatus Brocadia' presenting 22.9 % of the total microbial community after about 500 days of operation. Metagenomic analysis recovered two high-quality genomes of novel Anammox bacteria, which we designed as 'Candidatus Brocadia thermophilus' and 'Candidatus Brocadia thermoanammoxidans'. Both of them encoded and actively expressed key metabolic genes involved in Anammox process and several genes associated with thermotolerance, demonstrating their remarkable ability to perform Anammox reaction in thermophilic environments. Notably, phylotypes related to 'Candidatus Brocadia thermoanammoxidans' have frequently been retrieved from geographically distinct natural habitats. These findings expand our understanding of thermophilic Anammox bacteria and underscore their potential in the nitrogen cycle of thermal natural and engineering ecosystems.

Corynoline protects chronic pancreatitis via binding to PSMA2 and alleviating pancreatic fibrosis.

BACKGROUND: Pancreatic fibrosis is the main pathological feature of chronic pancreatitis. There is a lack of medications that effectively alleviate or reverse pancreatic fibrosis and thus cure chronic pancreatitis. METHODS: We screened drugs that could alleviate pancreatic fibrosis from 80 traditional Chinese medicine monomers and verified their efficacy and mechanisms. RESULTS: We preliminarily identified corynoline as an antifibrotic candidate by drug screening among 80 compounds. In vitro, corynoline dose-dependently reduces collagen I synthesis in pancreatic stellate cells induced by TGF-ß1 and inhibits its activation. Furthermore, we found that corynoline could alleviate the morphological disruption, such as acinar cell atrophy, collagen deposition etc., as well as reduced pancreatic weight in mice with chronic pancreatitis. We further validated the antifibrotic effect of corynoline in mRNA and protein levels. We also found that corynoline could inhibit NF-κB signaling pathway in vitro and in vivo. Next, we identified PSMA2 as the binding protein of corynoline by Lip-SMap and validated it using DARTS. Moreover, the siRNA of PSMA2 disrupts the anti-fibrotic effect of corynoline. CONCLUSION: In conclusion, corynoline is a promising agent for the treatment of pancreatic fibrosis and chronic pancreatitis.

Retinal Degeneration Response to Graphene Quantum Dots: Disruption of the Blood-Retina Barrier Modulated by Surface Modification-Dependent DNA Methylation.

Graphene quantum dots (GQDs) are used in diverse fields from chemistry-related materials to biomedicines, thus causing their substantial release into the environment. Appropriate visual function is crucial for facilitating the decision-making process within the nervous system. Given the direct interaction of eyes with the environment and even nanoparticles, herein, GQDs, sulfonic acid-doped GQDs (S-GQDs), and amino-functionalized GQDs (A-GQDs) were employed to understand the potential optic neurotoxicity disruption mechanism by GQDs. The negatively charged GQDs and S-GQDs disturbed the response to light stimulation and impaired the structure of the retinal nuclear layer of zebrafish larvae, causing vision disorder and retinal degeneration. Albeit with sublethal concentrations, a considerably reduced expression of the retinal vascular sprouting factor sirt1 through increased DNA methylation damaged the blood-retina barrier. Importantly, the regulatory effect on vision function was influenced by negatively charged GQDs and S-GQDs but not positively charged A-GQDs. Moreover, cluster analysis and computational simulation studies indicated that binding affinities between GQDs and the DNMT1-ligand binding might be the dominant determinant of the vision function response. The previously unknown pathway of blood-retinal barrier interference offers opportunities to investigate the biological consequences of GQD-based nanomaterials, guiding innovation in the industry toward environmental sustainability.

Plasma Olink Proteomics Reveals Novel Biomarkers for Prediction and Diagnosis in Dilated Cardiomyopathy with Heart Failure.

In this study, we utilized the Olink Cardiovascular III panel to compare the expression levels of 92 cardiovascular-related proteins between patients with dilated cardiomyopathy combined with heart failure (DCM-HF) (n = 20) and healthy normal people (Normal) (n = 18). The top five most significant proteins, including SPP1, IGFBP7, F11R, CHI3L1, and Plaur, were selected by Olink proteomics. These proteins were further validated using ELISA in plasma samples collected from an additional cohort. ELISA validation confirmed significant increases in SPP1, IGFBP7, F11R, CHI3L1, and Plaur in DCM-HF patients compared to healthy controls. GO and KEGG analysis indicated that NT-pro BNP, SPP1, IGFBP7, F11R, CHI3L1, Plaur, BLM hydrolase, CSTB, Gal-4, CCL15, CDH5, SR-PSOX, and CCL2 were associated with DCM-HF. Correlation analysis revealed that these 13 differentially expressed proteins have strong correlations with clinical indicators such as LVEF and NT-pro BNP, etc. Additionally, in the GEO-DCM data sets, the combined diagnostic value of these five core proteins AUC values of 0.959, 0.773, and 0.803, respectively indicating the predictive value of the five core proteins for DCM-HF. Our findings suggest that these proteins may be useful biomarkers for the diagnosis and prediction of DCM-HF, and further research is prompted to explore their potential as therapeutic targets.

Triazole fungicides disrupt embryonic stem cell differentiation: Potential modulatory role of the retinoic acid signaling pathway.

The developmental toxicity and human health risks of triazole fungicides (TFs) have attracted worldwide attention due to the ability to enter the human body in a variety of ways. Nevertheless, the specific mechanism by which TFs exert remains incompletely understood. Given that retinoic acid (RA) signaling pathway are closely related to development, this study aimed to screen and identify developmentally disabled chemicals in commonly used TFs and to reveal the potential effects of TFs on developmental retardation through the RA signaling pathway in mouse embryonic stem cells (mESCs). Specifically, six typical TFs (myclobutanil, tebuconazole, hexaconazole, propiconazole, difenoconazole, and flusilazole) were exposed through the construction of an embryoid bodies (EBs)-based in vitro global differentiation models. Our results clarified that various TFs disturbed lineage commitment during early embryonic development. Crucially, the activation of RA signaling pathway, which alters the expression of key genes and interferes the transport and metabolism of retinol, may be responsible for this effect. Furthermore, molecular docking, molecular dynamics simulations, and experiments using a retinoic acid receptor α inhibitor provide evidence supporting the potential modulatory role of the retinoic acid signaling pathway in developmental injury. The current study offers new insights into the TFs involved in the RA signaling pathway that interfere with the differentiation process of mESCs, which is crucial for understanding the impact of TFs on pregnancy and early development.

Modeling of the Particle Abrasion Process and a Discrete Element Method Study of Its Shape Effect.

This study introduces a novel method for particle abrasion derived from fundamental natural phenomena and mechanical principles, allowing precise control over the degree of abrasion and more accurately mimicking natural processes. The method's validity is confirmed using a specific shape index. Through conventional triaxial tests, the mechanical behavior of granular aggregates with varying degrees of abrasion was analyzed. The findings indicate that increased particle abrasion leads to a decrease in the average coordination number and sliding amount, while the rotation amount increases. This suggests an inverse relationship between the degree of abrasion and the structural stability and interlocking of the particle aggregate. The fabric anisotropy of the system is mainly attributed to the anisotropy of the contact normal force, which decreases as particle abrasion increases. The partial stress ratio of the particle system is influenced by fabric anisotropy and remains independent of particle shape. Additionally, the internal friction angle may be overestimated in conventional triaxial tests.

Uni-to-Multi Modal Knowledge Distillation for Bidirectional LiDAR-Camera Semantic Segmentation.

Combining LiDAR points and images for robust semantic segmentation has shown great potential. However, the heterogeneity between the two modalities (e.g. the density, the field of view) poses challenges in establishing a bijective mapping between each point and pixel. This modality alignment problem introduces new challenges in network design and data processing for cross-modal methods. Specifically, 1) points that are projected outside the image planes; 2) the complexity of maintaining geometric consistency limits the deployment of many data augmentation techniques. To address these challenges, we propose a cross-modal knowledge imputation and transition approach. First, we introduce a bidirectional feature fusion strategy that imputes missing image features and performs cross-modal fusion simultaneously. This allows us to generate reliable predictions even when images are missing. Second, we propose a Uni-to-Multi modal Knowledge Distillation (U2MKD) framework, leveraging the transfer of informative features from a single-modality teacher to a cross-modality student. This overcomes the issues of augmentation misalignment and enables us to train the student effectively. Extensive experiments on the nuScenes, Waymo, and SemanticKITTI datasets demonstrate the effectiveness of our approach. Notably, our method achieves an 8.3 mIoU gain over the LiDAR-only baseline on the nuScenes validation set and achieves state-of-the-art performance on the three datasets.

A deep learning-based cascade algorithm for pancreatic tumor segmentation.

Pancreatic tumors are small in size, diverse in shape, and have low contrast and high texture similarity with surrounding tissue. As a result, the segmentation model is easily confused by complex and changeable background information, leading to inaccurate positioning of small targets and false positives and false negatives. Therefore, we design a cascaded pancreatic tumor segmentation algorithm. In the first stage, we use a general multi-scale U-Net to segment the pancreas, and we exploit a multi-scale segmentation network based on non-local localization and focusing modules to segment pancreatic tumors in the second stage. The non-local localization module learns channel and spatial position information, searches for the approximate area where the pancreatic tumor is located from a global perspective, and obtains the initial segmentation results. The focusing module conducts context exploration based on foreground features (or background features), detects and removes false positive (or false negative) interference, and obtains more accurate segmentation results based on the initial segmentation. In addition, we design a new loss function to alleviate the insensitivity to small targets. Experimental results show that the proposed algorithm can more accurately locate pancreatic tumors of different sizes, and the Dice coefficient outperforms the existing state-of-the-art segmentation model. The code will be available at https://github.com/HeyJGJu/Pancreatic-Tumor-SEG.

GLIM-defined malnutrition in patients with acute abdomen associated with poor prognosis and increased economic burden: A cross-sectional study.

BACKGROUND: The Global Leadership Initiative on Malnutrition (GLIM) criteria have rapidly developed into a principal methodological framework for nutrition diagnosis. However, the applicability of the GLIM criteria in patients with acute abdomen has not been validated. METHODS: This is a cross-sectional study conducted on patients diagnosed with acute abdomen and admitted to a tertiary hospital in southwest China. Nutrition risk screening was conducted using the Nutrition Risk Screening 2002, and patients identified with nutrition risk were assessed for malnutrition based on the GLIM criteria. RESULTS: We enrolled a total of 440 patients with acute abdomen. The top three diagnoses of acute abdomen were intestinal obstruction (47.2%), acute appendicitis (23.1%), and digestive system perforation (8.8%). The prevalence of nutrition risk was 46.5%, with a malnutrition rate of 32.5% based on the GLIM. Patients with malnutrition according to the GLIM showed significantly higher rates of intensive care unit (ICU) admission (13.28% vs 7.07%; P = 0.003), increased hospitalization costs (median: 3315USD [interquartile range (IQR): 978-7852] vs 1641 [IQR: 816-3523] USD; P < 0.001), and longer length of hospital stay (LOS) (median: 8 [IQR: 5-13] vs 6 [IQR: 4-8] days; P < 0.001) compared with patients without malnutrition. Multivariate analysis indicated that GLIM-defined malnutrition was an independent predictor of hospitalization costs, and severe malnutrition was an independent predictor of ICU admission. CONCLUSION: GLIM criteria are applicable for diagnosing malnutrition in patients with acute abdomen. The prevalence of malnutrition was high in patients with acute abdomen. Malnutrition was associated with increased ICU admission and LOS, along with higher economic burden.

Supramolecular control over the variability of color and fluorescence in low-molecular-weight glass.

Colorful and fluorescent transparent materials have been extensively used in industrial and scientific activities, with inorganic and polymeric glasses being the most typical representatives. Recently, artificial glass originating from low-molecular-weight monomers has attracted considerable attention. Compared with the deep understanding of the building blocks and driving forces of supramolecular glass, related studies on its optical properties are insufficient in terms of systematicness and pertinence. In this study, a supramolecular strategy was applied to introduce versatile colors and fluorescence emissions into a low-molecular-weight glass. Pillar[5]arene and cucurbit[8]uril were selected to recognize the functional components and yield the desired optical performances. Macrocycle-based host-guest chemistry endows artificial glass with controllable and programmable colors and fluorescence emissions.

Phase Transformations and Mechanical Properties in In-Bi-Sn Alloys as a Result of Low-Temperature Storage.

The In-Bi-Sn low-temperature solder alloys are regarded as potential candidates for cryogenic and space exploration applications. This study investigates the variations in the mechanical properties and microstructures of two different compositions: In15wt%Bi35wt%Sn and In30wt%Bi20wt%Sn, after exposure to a low-temperature environment (-20 °C) for 10 months. An increase in the ultimate tensile strength was observed across all the tested samples and a decrease in elongation to failure was observed in In30wt%Bi20wt%Sn. Changes in the microstructure were identified through scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD). The impact of this low-temperature environment is described, considering the varying proportions and compositions of the three phases (BiIn2(Sn), γ-InSn4(Bi), and ß-In3Sn(Bi)) present within the alloys and their contribution to the mechanical properties.