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Through molecular engineering, single diarylethenes were covalently sandwiched between graphene electrodes to form stable molecular conduction junctions. Our experimental and theoretical studies of these junctions consistently show and interpret reversible conductance photoswitching at room temperature and stochastic switching between different conductive states at low temperature at a single-molecule level. We demonstrate a fully reversible, two-mode, single-molecule electrical switch with unprecedented levels of accuracy (on/off ratio of ~100), stability (over a year), and reproducibility (46 devices with more than 100 cycles for photoswitching and ~10⁵ to 10⁶ cycles for stochastic switching).

Background This study assessed the distribution characteristics of pathogens isolated from cases of orthopedic infections and focused on the antimicrobial susceptibility of the main pathogens. Methods This retrospective study involved patients with orthopedic infection in a tertiary medical center located in Shanghai, China, from 2008 to 2021.Pathogen information and the basic information of patients were identified from clinical microbiology laboratory data and the institutional medical record system. Results In total, the pathogen information of 2821 patients were enrolled in the study. S. aureus (37.71%) was the main causative pathogen responsible for orthopedic infection. Gender, pathogens distribution and polymicrobial infection rates were significantly different ( P  < 0.05) among patients with different orthopedic infection diseases.The trends in the distribution of pathogens in the total cohort, implant-related infection group (Group A), non-implant-related infection group (Group B), and the sub-group of cases with arthroplasty showed significant linear changes over time. And the polymicrobial infection rates of the total cohort (from 17.17% to 11.00%), Group B(from 24.35% to 14.47%), and the sub-group of cases with internal fixation (from 10.58% to 4.87%) decreased significantly. The antimicrobial susceptibility showed changing trends with time for some main pathogens, especially for S.aureus and Enterobacter spp. Conclusions Our research indicated that the pathogen distribution and antimicrobial susceptibility in orthopedic infections changed over time. And the distribution of pathogens varied significantly among different types of orthopedic infectious diseases. These findings may serve as a reference for prophylaxis and empirical treatment strategies of orthopedic infection.

Staphylococcus aureus can form aggregates within human synovial fluid, contributing to joint infections that are resistant to conventional therapies. However, the regulatory pathways underlying this process remain unclear. Here, we reveal that the S. aureus two-component system saeRS contributes to synovial aggregation by controlling the expression of fibrinectin-binding proteins A and B (FnbA/B), which bind to human fibrinogen and cause aggregation. We further demonstrate that the fatty acid kinase ( fak ) system is the primary regulator for SaeS activity under host conditions. Mechanistically, fak is epistatic to saeRS by scavenging exogenous fatty acids and altering the localization of SaeS into functional membrane microdomains (FMMs), which are essential for SaeS function. We also identify that undecanoic acid (UDA) is capable of inhibiting the fak pathway, demonstrating its efficacy and potential applicability in treating joint infections. Altogether, these findings highlight the fak-saeRS axis as a potential therapeutic target for joint infections and underscore UDA as a promising treatment for these infections. Staphylococcus aureus can aggregate within human synovial fluid and lead to joint infections. Here, the authors reveal that the fatty acid kinase system and its downstream saeRS regulator control S. aureus aggregation within synovial fluid.

Background This study aimed to delineate the cell heterogeneity in the bone-implant interface and investigate the fibroblast responses to implant-associated S. aureus infection. Methods Single-cell RNA sequencing of human periprosthetic tissues from patients with periprosthetic joint infection (PJI, n = 3) and patients with aseptic loosening (AL, n = 2) was performed. Cell type identities and gene expression profiles were analyzed to depict the single-cell landscape in the periprosthetic environment. In addition, 11 publicly available human scRNA-seq datasets were downloaded from GSE datasets and integrated with the in-house sequencing data to identify disease-specific fibroblast subtypes. Furthermore, fibroblast pseudotime trajectory analysis and Single-cell regulatory network inference and clustering (SCENIC) analysis were combined to identify transcription regulators responsible for fibroblast differentiation. Immunofluorescence was performed on the sequenced samples to validate the protein expression of the differentially expressed transcription regulators. Results Eight major cell types were identified in the human bone-implant interface by analyzing 36,466 cells. Meta-analysis of fibroblasts scRNA-seq data found fibroblasts in the bone-implant interface express a high level of CTHRC1 . We also found fibroblasts could differentiate into pro-inflammatory and matrix-producing phenotypes, each primarily presented in the PJI and AL groups, respectively. Furthermore, NPAS2 and TFEC which are activated in PJI samples were suggested to induce pro-inflammatory polarization in fibroblasts, whereas HMX1 , SOX5 , SOX9 , ZIC1 , ETS2 , and FOXO1 are matrix-producing regulators. Meanwhile, we conducted a CMap analysis and identified forskolin as a potential regulator for fibroblast differentiation toward matrix-producing phenotypes. Conclusions In this study, we discovered the existence of CTHRC1 + fibroblast in the bone-implant interface. Moreover, we revealed a bipolar mode of fibroblast differentiation and put forward the hypothesis that infection could modulate fibroblast toward a pro-inflammatory phenotype through NPAS2 and TFEC .

X‐ray free electron lasers (XFELs) serve as advanced light sources and have become essential for investigating ultrafast dynamic phenomena in physics and materials with extraordinary resolution. Owing to the XFEL's ultrafast characteristics and short wavelengths, an arrival‐timing tool is crucial for pump–probe experiments. To address this, we have developed a timing diagnostic tool employing both spectral‐encoding and spatial‐imaging methods at the SBP beamline for the newly constructed Shanghai Soft X‐ray Free Electron Laser Facility (SXFEL). This timing tool was experimentally validated, proving that the spectral‐encoding technique could achieve single‐pulse measurement with an accuracy of under 40 fs [root mean square (RMS)], and exhibited a timing‐jitter measurement of 90.3 fs (RMS) at the CSI endstation of SXFEL. Furthermore, the spatial‐imaging approach used both polished‐ and rough‐surface GaAs crystals, which simplifies implementation in X‐ray pump–probe experiments, and allows for the characterization of X‐ray pulse arrival times at the endstation without rotating the sample stage. These findings confirm that the timing diagnostic tool provides dependable high‐precision temporal characterization of X‐ray pulses at SXFEL, facilitating high‐accuracy X‐ray pump–probe experiments. The development of a timing diagnostic tool at the CSI endstation of the Shanghai Soft X‐ray Free Electron Laser Facility achieves precise temporal characterization for advanced pump–probe experiments. The tool's unique design enables X‐ray pulse monitoring without sample‐stage rotation with both spectral‐encoding and spatial‐coupling methods, offering a reliable solution for X‐ray pump–probe experiments at the CSI endstation.

Emerging evidence revealed that gut microbial dysbiosis is implicated in the development of plasma cell dyscrasias and amyloid deposition diseases, but no data are available on the relationship between gut microbiota and immunoglobulin light chain (AL) amyloidosis. To characterize the gut microbiota in patients with AL amyloidosis, we collected fecal samples from patients with AL amyloidosis (n=27) and age-, gender-, and BMI-matched healthy controls (n=27), and conducted 16S rRNA MiSeq sequencing and amplicon sequence variants (ASV)-based analysis. There were significant differences in gut microbial communities between the two groups. At the phylum level, the abundance of and was significantly higher, while reduced remarkably in patients with AL amyloidosis. At the genus level, 17 genera, including , were enriched, while only 4 genera including , , , and decreased evidently in patients with AL amyloidosis. Notably, 5 optimal ASV-based microbial markers were identified as the diagnostic model of AL amyloidosis and the AUC value of the train set and the test set was 0.8549 (95% CI 0.7310-0.9789) and 0.8025 (95% CI 0.5771-1), respectively. With a median follow-up of 19.0 months, further subgroup analysis also demonstrated some key gut microbial markers were related to disease severity, treatment response, and even prognosis of patients with AL amyloidosis. For the first time, we demonstrated the alterations of gut microbiota in AL amyloidosis and successfully established and validated the microbial-based diagnostic model, which boosted more studies about microbe-based strategies for diagnosis and treatment in patients with AL amyloidosis in the future.

This paper presents a system state identification method based on back propagation (BP) neural network. First, the working modes of the hybrid power system are given. Besides, the method of normalizing training parameters is provided to facilitate the training of neural network. Then, a neural network method is applied to state identification of hybrid power system. Finally, the weights and thresholds of the structure are obtained by the normalized training parameters, and the test results indicate that the trained neural network structure satisfies the system identification requirements.

The Staphylococcus aureus (S. aureus) SaeRS two-component system (TCS) regulates over 20 virulence factors. While its impact on chronic infection has been thoroughly discussed, its role in the early stage of infection remains elusive. Since macrophages serve as the primary immune defenders at the onset of infection, this study investigates the influence of SaeRS on macrophage functions and elucidates the underlying mechanisms. Macrophage expression of inflammatory and chemotactic factors, phagocytosis, and bactericidal activity against S. aureus were assessed, along with the evaluation of cellular oxidative stress. SaeRS was found to impair macrophage function. Mechanistically, SaeRS inhibited NF-κB pathway activation via toll-like receptor 2 (TLR2). Its immune-modulating effect could partially be explained by the strengthened biofilm formation. More importantly, we found SaeRS compromised macrophage immune functions at early infection stages even prior to biofilm formation. These early immune evasion effects were dependent on bacterial clumping as cytokine secretion, phagocytosis, and bactericidal activity were repaired when clumping was inhibited. We speculate that the bacterial clumping-mediated antigen mask is responsible for SaeRS-mediated immune evasion at the early infection stage. In vivo, ΔsaeRS infection was cleared earlier, accompanied by early pro-inflammatory cytokines production, and increased tissue oxidative stress. Subsequently, macrophages transitioned to an anti-inflammatory state, thereby promoting tissue repair. In summary, our findings underscore the critical role of the SaeRS TCS in S. aureus pathogenicity, particularly during early infection, which is likely initiated by SaeRS-mediated bacterial clumping.

Considering the essential expansion of agricultural production, current research primarily focuses on static factors, such as the distribution of fine-grained arable land, omitting an in-depth analysis of its developmental dynamics and key drivers. Addressing this knowledge gap is crucial for enhancing the scalability of agricultural production. This research utilizes landscape ecology techniques, correlation analysis, random forest algorithms, and structural equation modeling to explore spatial pattern trends of arable land in the Beijing–Tianjin–Hebei region. Its objective is to clarify how the expansion of agricultural production scale affects food production through changes in arable land patterns and to determine the impact of socio-economic factors on these configurations. The results show that: (1) the landscape pattern of arable land is transitioning to a more fragmented arrangement with complex contours, (2) grain yield per unit area correlates positively with the landscape pattern index in Beijing, negatively in Hebei, and exhibits no significant correlation in Tianjin, and (3) land ownership plays a crucial role in land fragmentation, alterations in land morphology, and influences other socio-economic variables. Analyzing the spatial pattern of arable land in conjunction with socio-economic factors is essential for developing holistic land management approaches, improving resource efficiency, minimizing external inputs, and mitigating food security challenges.

The clinical efficacy of reverse shoulder arthroplasty (RSA), hemiarthroplasty (HA), and non-surgical management in the treatment of proximal humeral fractures (PHFs) is inconclusive. This systematic review and meta-analysis compared the clinical outcomes of arthroplasty and non-surgical management of PHFs. The databases of PubMed, Embase, Web of Science, and Cochrane Library were searched on 5 May 2023 for studies comparing arthroplasty and non-surgical treatment of PHFs. Both randomized controlled trials (RCTs) and non-randomized controlled trials (nRCTs), were included. Standard methodological quality assessments were conducted for both types of studies. The primary outcome was the Constant-Murley Score (CMS) after surgical or non-surgical treatment. Secondary study outcomes included the visual analog scale (VAS), range of motion, and complications. All functional scores and complications were subjected to subgroup and sensitivity analyses. A total of four RCTs and six nRCTs were included in this study, which provided 508 patients in total for meta-analysis: 238 treated with arthroplasty and 270 treated non-surgically, of which 83 were treated with HA and 155 with RSA. All relevant information was collected, including functional scores, VAS, range of motion, and complications. The study found no significant difference in functional outcomes (mean difference, 2.82; 95% confidence interval, -0.49 to 6.14; = 0.10; = 77%) and complications (mean difference, 1.08; 95% confidence interval, 0.51-2.25; = 0.85; = 47%) between arthroplasty and non-surgical treatment. Both RCTs and nRCTs showed the same results. However, VAS scores were significantly lower in surgical treatment compared to non-surgical treatment. Subgroup and sensitivity analyses showed that RSA could achieve better functional scores than non-surgical treatment (mean difference, 6.00; 95% confidence interval, 1.97-10.03; = 0.004; = 0%), while the results for HA were not significant ( > 0.05). There were no significant differences in complications between arthroplasty and non-surgical treatment for PHFs. RSA could achieve better functional results than non-surgical treatment, while HA could only achieve better forward flexion.