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Whitlockite (WH, Ca 18 Mg 2 (HPO 4 ) 2 (PO 4 ) 12 ) is an important inorganic phase in human bones and has positive significance for participating in the bone reconstruction process. In this paper, we report different doping strategies to prepare WH and WH-Ln (Eu/Tb) nanocrystals, and have successfully synthesized WH-Ln (Eu/Tb) nanoparticles (NPs) with bright red or green fluorescence based on ions exchange doping by two-step hydrothermal reaction. WH-5%Ln (Eu/Tb) NPs with the best fluorescence properties were successfully applied to live cell imaging, and WH-5%Eu NPs were implanted into the bone defect site in rabbit femoral condyles to visually observe its degradation process. The related results would help us understand WH nanocrystals and further expand their potential applications in tissue engineering and related fields.

Cuprate superconductors have the highest critical temperatures ( T c ) at ambient pressure, yet a consensus on the superconducting mechanism remains to be established. Finding an empirical parameter that limits the highest reachable T c can provide crucial insight into this outstanding problem. Here, in the first two Ruddlesden-Popper members of the model Hg-family of cuprates, which are chemically nearly identical and have the highest T c among all cuprate families, we use inelastic photon scattering to reveal that the energy of magnetic fluctuations may play such a role. In particular, we observe the single-paramagnon spectra to be nearly identical between the two compounds, apart from an energy scale difference of ~30% which matches their difference in T c . The empirical correlation between paramagnon energy and maximal T c is further found to extend to other cuprate families with relatively high T c ’s, hinting at a fundamental connection between them. Finding a parameter that limits the critical temperature of cuprate superconductors can provide crucial insight on the superconducting mechanism. Here, the authors use inelastic photon scattering on two Ruddlesden-Popper members of the model Hg-family of cuprates to reveal that the energy of magnetic fluctuations may play such a role, and suggest that the Cooper pairing is mediated by paramagnons.

Acinetobacter baumannii ( A. baumannii ) is a pathogen that opportunistically infects patients in healthcare settings and poses a significant threat to human health due to its widespread resistance to antimicrobial agents. The temporal and regional distribution of A. baumannii in China is continually evolving, necessitating comprehensive surveillance to examine the prevalence, molecular characteristics, and clonal relationships of antimicrobial resistance determinants in burn wound A. baumannii isolates collected from six major Chinese provinces during 2016–2020. To address this need, we analyzed a total of 415 distinct A. baumannii isolates that were obtained from burn patients. Antimicrobial susceptibility testing was performed using the Kirby Bauer disk diffusion method, while genetic relatedness of the 415 isolates was assessed by utilizing multilocus sequence typing (MLST) and eBURST analysis. Additionally, the housekeeping genes and a comprehensive panel of drug resistance genes, including β-lactamases, membrane permeability factors, and efflux pump systems, were detected by multiplex PCR to elucidate their resistance mechanisms. Our analysis revealed that among the 415 isolates, 384 (92.5%) were classified as multidrug-resistant (MDR), with regional rates ranging from 88.2 to 96.0%. Additionally, 38 (9.2%) isolates were classified as extensively drug-resistant (XDR). All strains showed resistance to multiple antibiotics, except for lower resistance to Tigecycline (TGC) and Cefoperazone/sulbactam (CSL), suggesting their potential therapeutic utility. By MLST, all isolates represented 122 identified STs (sequence types). eBURST analysis identified the 415 isolates into 17 clonal complexes (CCs) in which CC1660 and CC1417 were considered large CCs with at least 100 isolates in each CC. Importantly, our investigation identified a notable epidemiological shift: CC1417 and CC1660 instead of CC92 have become the novel predominant strains in burn wound isolates of these Chinese provinces, and the predominant strain varied in separate regions. Consistently, our investigation identified ST1417, ST1660, and ST1145 instead of ST208 as predominant sequence types, indicating a notable shift in regional epidemiological patterns for burn wound A. baumannii isolates. In addition, the carrying rates of multiple antibiotic-resistant genes maintain a high level, indicating the evolution of strain genes and the severe drug resistance situation in burn wound isolates of these Chinese provinces. As a result, epidemiological surveillance and genetic evolution analysis of A. baumannii is of great significance to provide more strategies for the prevention of nosocomial infection and clinical treatment.

Automating shiitake mushroom picking is critical for modern agriculture, yet its biological traits hinder automation via target recognition, path planning, and precision challenges. Traditional manual picking is inefficient, labor-heavy, and unsuitable for large-scale production. In human- robot collaboration, computer vision - based human motion prediction enables efficient picking coordination, yet methods like LSTM and static graph networks struggle with robust spatiotemporal correlation capture and long-term stability in complex agricultural settings. To address this, we propose the Chaos-Optimized Adaptive Spatiotemporal Graph Convolutional Network (CSO-ASTGCN). First, it integrates three core modules: the Adaptive Spatial Feature Graph Convolution Module (ASF-GCN) for dynamic joint correlation modeling (e.g., wrist-finger coupling during grasping). Second, the Dynamic Temporal Feature Graph Convolution Module (DT-GCN) captures multi-scale temporal dependencies. Third, Chaos Search Optimization (CSO) globally optimizes hyper parameters to avoid local optima common in traditional optimization methods. Additionally, a flexible control system fuses CSO-ASTGCN motion prediction with GRCNN grasp pose estimation to optimize grasping paths and operational forces. Experiments show our model reduces the Mean Per - Joint Position Error (MPJPE) by 15.2% on the CMU dataset and 12.7% on the 3DPW dataset compared to methods like STSGCN and Transformers. The human - robot collaborative system boosts picking efficiency by 31% and cuts mushroom damage by 26% relative to manual operations. These results validate CSO - ASTGCN's superiority in spatiotemporal modeling for fine - grained agricultural motions and its practical value in intelligent edible fungi harvesting.

Background/Aims: As an “ESKAPE” pathogen, Acinetobacter baumannii is one of the leading causes of drug-resistant infections in humans. Phage therapy may be a useful strategy in treating infections caused by drug-resistant A. baumannii. Among 21 phage strains that were isolated and described earlier, we investigated the therapeutic efficacy of Abp1 because of its relatively wide host range. Methods: Phage stability assays were used to evaluate thermal and pH stability of Abp1. Abp1 was co-cultured with A. baumannii (AB1) over a range of multiplicities of infection to determine its bactericidal efficacy. HeLa or THP-1 cells were used in the cytotoxicity and protection assays. Finally, the therapeutic effects of Abp1 on local and systemic A. baumannii infection in mice were determined. Results: We found that Abp1 exhibits high thermal and pH stability and has a low frequency of lysogeny. Bacteriophage resistance also occurs at a very low frequency (3.51±0.46×10 -8 ), and Abp1 can lyse almost all host cells at a MOI as low as 0.1. Abp1 has no detectable cytotoxicity to HeLa or THP-1 cells as determined by LDH release assay. Abp1 can rescue HeLa cells from A. baumannii infection, even if introduced 2 hours post infection. In both local and systemic A. baumannii infection mouse models, Abp1 treatment exhibits good therapeutic effects. Conclusion: Abp1 is an excellent candidate for phage therapy against drug-resistant A. baumannii infections.

Manganese-based STING-activating tumor immunotherapy faces limitations due to T cell exhaustion. Mitochondrial dysfunction is a key factor contributing to T cell exhaustion. Modulating mitochondrial function during manganese-based immunotherapy offers a promising strategy to reverse T cell exhaustion. Spermidine (SPD) enhances mitochondrial function in T cells, making the co-delivery of Mn and SPD a potential therapeutic approach. However, intravenous co-delivery is hindered by the rapid formation of MnO(OH)₂ precipitates. In this study, liposomes were employed as nano-reactors to facilitate the reaction between pre-loaded Mn²⁺ and O₂ in the presence of SPD, forming MnO(OH)₂ precipitates within the liposomes. These liposomes function as nanofactories, further processing MnO(OH)₂ under the regulation of the tumor microenvironment (TME) and delivering Mn, SPD, and O₂. Beyond activating the STING pathway in dendritic cells, L@Mn@SPD alleviates TME hypoxia and effectively reverses CD8⁺ T cell exhaustion. In vivo, L@Mn@SPD achieved a 2.44-fold increase in tumor suppression compared to MnCl₂, along with a 47% rise in CD8⁺ T cell infiltration, a 62.1% reduction in PD-1 expression, and a 110% increase in IFN-γ secretion. This STING-activating nanofactory provides a promising strategy to enhance manganese-based tumor immunotherapy by addressing mitochondrial dysfunction in exhausted T cells.

Carbapenem-resistant Klebsiella pneumoniae (CRKP) has spread globally and emerged as an urgent public health threat. Bacteriophages are considered an effective weapon against multidrug-resistant pathogens. In this study, we report a novel lytic phage, kpssk3, which is able to lyse CRKP and degrade exopolysaccharide (EPS). The morphological characteristics of kpssk3 observed by transmission electron microscopy, including a polyhedral head and a short tail, indicate that it belongs to the family Podoviridae. A one-step growth curve revealed that kpssk3 has a latent period of 10 min and a burst size of 200 plaque-forming units (pfu) per cell. kpssk3 was able to lyse 25 out of 27 (92.59%) clinically isolated CRKP strains, and it also exhibited high stability to changes in temperature and pH. kpssk3 has a linear dsDNA genome of 40,539 bp with 52.80% G+C content and 42 putative open reading frames (ORFs). No antibiotic resistance genes, virulence factors, or integrases were identified in the genome. Based on bioinformatic analysis, the tail fiber protein of phage kpssk3 was speculated to possess depolymerase activity towards EPS. By comparative genomics and phylogenetic analysis, it was determined that kpssk3 is a new T7-like virus and belongs to the subfamily Autographivirinae. The characterization and genomic analysis of kpssk3 will promote our understanding of phage biology and diversity and provide a potential strategy for controlling CRKP infection.

With the continuous emergence and development of 3D sensors in recent years, it has become increasingly convenient to collect point cloud data for 3D object detection tasks, such as the field of autonomous driving. But when using these existing methods, there are two problems that cannot be ignored: (1) The bird’s eye view (BEV) is a widely used method in 3D objective detection; however, the BEV usually compresses dimensions by combined height, dimension, and channels, which makes the process of feature extraction in feature fusion more difficult. (2) Light detection and ranging (LiDAR) has a much larger effective scanning depth, which causes the sector to become sparse in deep space and the uneven distribution of point cloud data. This results in few features in the distribution of neighboring points around the key points of interest. The following is the solution proposed in this paper: (1) This paper proposes multi-scale feature fusion composed of feature maps at different levels made of Deep Layer Aggregation (DLA) and a feature fusion module for the BEV. (2) A point completion network is used to improve the prediction results by completing the feature points inside the candidate boxes in the second stage, thereby strengthening their position features. Supervised contrastive learning is applied to enhance the segmentation results, improving the discrimination capability between the foreground and background. Experiments show these new additions can achieve improvements of 2.7%, 2.4%, and 2.5%, respectively, on KITTI easy, moderate, and hard tasks. Further ablation experiments show that each addition has promising improvement over the baseline.

Previous research has reported the transcriptomic phage-host interactions in Escherichia coli and Pseudomonas aeruginosa , leading to the detailed discovery of transcriptomic regulations and predictions of specific gene functions. However, a direct relationship between A. baumannii and its phage has not been previously reported, although A. baumannii is becoming a rigorous drug-resistant threat. We analyzed transcriptomic changes after φAbp1 infected its host, extensively drug-resistant (XDR) A. baumannii AB1, and found defense-like responses of the host, step-by-step control by the invader, elaborate interactions between host and phage, and elevated drug resistance gene expressions of AB1 after phage infection. These findings suggest the detailed interactions of A. baumannii and its phage, which may provide both encouraging suggestions for drug design and advice for the clinical use of vital phage particles. Acinetobacter baumannii is a growing threat, although lytic bacteriophages have been shown to effectively kill A. baumannii . However, the interaction between the host and the phage has not been fully studied. We demonstrate the global profile of transcriptional changes in extensively drug-resistant A. baumannii AB1 and the interaction with phage φAbp1 through RNA sequencing (RNA-seq) and bioinformatic analysis. Only 15.6% (600/3,838) of the genes of the infected host were determined to be differentially expressed genes (DEGs), indicating that only a small part of the bacterial resources was needed for φAbp1 propagation. Contrary to previous similar studies, more upregulated rather than downregulated DEGs were detected. Specifically, φAbp1 infection caused the most extensive impact on host gene expression at 10 min, which was related to the intracellular accumulation phase of virus multiplication. Based on the gene coexpression network, a middle gene ( gp34 , encoding phage-associated RNA polymerase) showed a negative interaction with numerous host ribosome protein genes. In addition, the gene expression of bacterial virulence/resistance factors was proven to change significantly. This work provides new insights into the interactions of φAbp1 and its host, which contributes to the further understanding of phage therapy, and provides another reference for antibacterial agents. IMPORTANCE Previous research has reported the transcriptomic phage-host interactions in Escherichia coli and Pseudomonas aeruginosa , leading to the detailed discovery of transcriptomic regulations and predictions of specific gene functions. However, a direct relationship between A. baumannii and its phage has not been previously reported, although A. baumannii is becoming a rigorous drug-resistant threat. We analyzed transcriptomic changes after φAbp1 infected its host, extensively drug-resistant (XDR) A. baumannii AB1, and found defense-like responses of the host, step-by-step control by the invader, elaborate interactions between host and phage, and elevated drug resistance gene expressions of AB1 after phage infection. These findings suggest the detailed interactions of A. baumannii and its phage, which may provide both encouraging suggestions for drug design and advice for the clinical use of vital phage particles.