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Moiré superlattices formed by twisting trilayers of graphene are a useful model for studying correlated electron behaviour and offer several advantages over their formative bilayer analogues, including a more diverse collection of correlated phases and more robust superconductivity. Spontaneous structural relaxation alters the behaviour of moiré superlattices considerably and has been suggested to play an important role in the relative stability of superconductivity in trilayers. Here we use an interferometric four-dimensional scanning transmission electron microscopy approach to directly probe the local graphene layer alignment over a wide range of trilayer graphene structures. Our results inform a thorough understanding of how reconstruction modulates the local lattice symmetries crucial for establishing correlated phases in twisted graphene trilayers, evincing a relaxed structure that is markedly different from that proposed previously. The local layer alignment in a wide range of trilayer graphene structures has been extracted by interferometric four-dimensional scanning transmission electron microscopy, uncovering the complex picture of lattice reconstruction in twisted trilayers.

Energy efficiency and data reliability are important indicators to measure network performance in wireless sensor networks. In existing research schemes of routing protocols, the impact of node coverage on the network is often ignored, and the possibility that multiple sensor nodes may sense the same spatial point is not taken into account, which results in a waste of network resources, especially in large-scale networks. Apart from that, the blindness of geographic routing in data transmission has been troubling researchers, which means that the nodes are unable to determine the validity of data transmission. In order to solve the above problems, this paper innovatively combines the routing protocol with the coverage control technique and proposes the node collaborative scheduling algorithm, which fully considers the correlation characteristics between sensor nodes to reduce the number of active working nodes and the number of packets generated, to further reduce energy consumption and network delay and improve packet delivery rate. In order to solve the problem of unreliability of geographic routing, a highly reliable link detection and repair scheme is proposed to check the communication link status and repair the invalid link, which can greatly improve the packet delivery rate and throughput of the network, and has good robustness. A large number of experiments demonstrate the effectiveness and superiority of our proposed scheme and algorithm.

Additive manufacturing (AM) excels in engineering intricate shapes, pioneering functional components, and lightweight structures. Nevertheless, components fabricated through AM often manifest elevated residual stresses and a myriad of thermally induced micro-instabilities, including cracking, incomplete fusion, crazing, porosity, spheroidization, and inclusions. In response, this study proposed a sophisticated multi-sensing inspection system specifically tailored for the inspection of thermally induced micro-instabilities at the micro–nano scale. Simulation results substantiate that the modulation transfer function (MTF) values for each field of view in both visible and infrared optical channels surpass the benchmark of 0.3, ensuring imaging fidelity conducive to meticulous examination. Furthermore, the innovative system can discern and accurately capture data pertaining to thermally induced micro-instabilities across visible and infrared spectra, seamlessly integrating this information into a backend image processing system within operational parameters of a 380–450 mm distance and a 20–70 °C temperature range. Notably, the system’s design is harmoniously aligned with the requisites of processing and assembly, heralding a significant advancement in bolstering the inspection effect of thermally induced micro-instabilities for the AM component.

Background: Infectious diseases of the spine (IDS) cause structural destruction and abscess formation, requiring precise early diagnosis. While conventional culture methods show limited sensitivity and slow turnaround, metagenomic next-generation sequencing (mNGS) offers a promising alternative with its broader pathogen spectrum, rapid turnaround time, high detection rate, and sensitivity, showing significant advantages in the diagnosis of IDS. Objectives: This systematic review aims to synthesize the current evidence on the advantages and clinical utility of mNGS in diagnosing and managing IDS, focusing on pyogenic and granulomatous spinal infections. Design: The systematic review conducted in accordance with PRISMA guidelines. Data sources and methods: A comprehensive literature search was performed across nine electronic databases (including PubMed, Web of Science, and Embase) from 2010 to April 2025. Studies reporting on mNGS for pathogen detection in patients with suspected or confirmed spinal infections were included. The quality of included observational studies was assessed using the STROBE checklist. Data on detection spectrum, rate, sensitivity, turnaround time, and clinical impact were extracted and synthesized narratively due to high heterogeneity. Results: Twenty-nine studies (25 retrospective studies and 4 case reports) from China were included. mNGS demonstrated a significantly broader detection spectrum, identifying common pathogens (e.g., Staphylococcus aureus , Mycobacterium tuberculosis ) as well as rare and fastidious organisms that were missed by conventional methods. The pooled detection rate of mNGS (36.8%–95.5%) was consistently and significantly higher than that of culture (5.9%–59.2%). mNGS also showed superior sensitivity (39%–94.7%) compared to culture. The average turnaround time for mNGS (29–53 h) was substantially faster than for culture (2–10 days). mNGS-guided therapy was associated with improved clinical outcomes, including significant reductions in inflammatory markers. Conclusion: mNGS represents a powerful diagnostic tool for IDS, offering broader detection spectrum, higher detection rate, faster turnaround time, and greater sensitivity compared to conventional methods. This enables more targeted antimicrobial therapy and improves clinical management. Challenges including high costs and difficulty in distinguishing colonization from infection remain. Future efforts should focus on technical optimization, workflow automation, protocol standardization, and outcome validation in larger prospective studies. Trial registration: CRD420251170912.

PurposePituitary tumor is the common primary brain tumor in humans. For further studying the pathogenesis and new therapeutic targets of pituitary adenoma, cell lines and primary cells are necessary tools. Different from primary cells that have short survival time and hormone secretion maintenance time, cell lines would be endowed with immortal characteristics under the help of gene modification. This review is to explore whether these cell lines still have similar pathophysiological changes in pituitary adenoma cells and methods to prolong the lifespan of pituitary adenoma primary cells.ResultsIn the cell lines summarized in the review, HP75, PDFS, HPA and GX were derived from human pituitary adenomas. It was found that the cell lines commonly used in articles published between January 2014 and July 2019 were GH3, AtT20, MMQ, GH4C1, HP75 and TtT/GF. Besides, it was glad that many methods had been used to prolong the lifespan and maintain characteristics of pituitary adenoma primary cells.ConclusionThe paper reviews most of pituitary adenoma cell lines that have been successfully established since 1968 and the relevant situation of primary culture of pituitary adenoma cells. Obviously, it requires us to make more efforts to obtain human pituitary adenoma cell lines and prolong the lifespan of pituitary adenoma primary cells with maintaining their morphology and ability to secret hormones.

•We characterized temporal interference stimulation (TIS)-induced electric fields in the left hippocampus across age, sex, and cognitive status.•Modulation depth (MD) significantly varied with demographic and clinical factors, while its orientation relative to the hippocampal axis remained stable.•A regression model incorporating eight key anatomical features accurately predicted individual MD.•Mediation analysis revealed the anatomy-based model accounted for over 80% of the effects of sex, age, and cognitive status on MD.•This anatomy-based model enables rapid, individualized estimation of TIS-induced MD without full-scale simulations, supporting clinical translation. Temporal interference stimulation (TIS) enables noninvasive targeting of deep brain regions. However, individual variability in the induced electric field (EF), particularly in terms of modulation depth (MD) and directional alignment, remains poorly understood. We performed MRI-guided finite element modeling to simulate TIS-induced EF in the left hippocampus (LHippo), quantifying two metrics: MD and the angle between EF vectors and the hippocampal longitudinal axis. First, we evaluated these metrics across individuals stratified by age, sex, and cognitive status. To identify anatomical contributors to MD variability, we applied the least absolute shrinkage and selection operator (LASSO) regression for feature selection, followed by stepwise regression to construct a predictive model. We then conducted mediation analysis to determine whether the selected anatomical features accounted for the effects of age, sex, and cognitive status on MD. MD varied significantly with age, sex, and cognitive status, whereas the directional angle remained relatively stable under the fixed electrode configuration. The final predictive model, incorporating eight anatomical features (e.g., skull thickness, CSF-to-head ratio), demonstrated strong generalizability in two independent validation cohorts. Mediation analysis confirmed that the model-predicted MD significantly mediated the effects of age, sex, and cognitive status. These findings highlight the critical role of anatomical variability in shaping individual TIS outcomes and demonstrate that personalized MD could be efficiently estimated from clinically measurable features without subject-specific simulations. This anatomically informed framework supports scalable and interpretable strategies for precision-targeted brain stimulation. [Display omitted]

Unlike temporally symmetric inferences about simple sequences, inferences about our own lives are asymmetric: we are better able to infer the past than the future, since we remember our past but not our future. Here we explore whether there are asymmetries in inferences about the unobserved pasts and futures of other people’s lives. In two experiments (analyses of the replication experiment were pre-registered), our participants view segments of two character-driven television dramas and write out what they think happens just before or after each just-watched segment. Participants are better at inferring unseen past (versus future) events. This asymmetry is driven by participants’ reliance on characters’ conversational references in the narrative, which tend to favor the past. This tendency is also replicated in a large-scale analysis of conversational references in natural conversations. Our work reveals a temporal asymmetry in how observations of other people’s behaviors can inform inferences about the past and future. Memories of our past experiences enable us to reconstruct (in the present) our past better than our future. Here, the authors show that we are also able to better reconstruct the pasts (versus futures) in other people’s lives.

This paper presents a predictive model of subsurface damage depth h SSD and surface roughness in semi-consolidated abrasive grinding based on indentation fracture theory to rapidly and non-destructively detect subsurface damage of the workpiece. To verify the accuracy of the proposed model, cross-sectional microscopy was used to detect subsurface damage along the (100) and (010) crystal lographic planes in grinding of gallium oxide. In addition, the effects of grinding method, abrasive particle size, grinding pressure, and grinding disc speed on the damage along the (100) and (010) planes were analyzed. The results show a nonlinear relationship between the depth of the gallium oxide subsurface damage and surface roughness generated by semi-consolidated abrasive grinding. Under the same grinding conditions, the damage layer depth in semi-consolidated abrasive grinding is lower than in free abrasive grinding. When the same grinding method is used, the subsurface damage depth is greater along the (100) plane than along the (010) plane under the same grinding conditions. When the abrasive particle size is decreased from W14 to W3, the depth of the subsurface damage layer is reduced by 30% in semi-consolidated abrasive grinding. Reducing the grinding pressure can reduce the amount of subsurface damage, and the speed of the grinding disc also affects the subsurface damage of gallium oxide. The subsurface damage depth has little effect. After optimizing the grinding parameters, the surface roughness of gallium oxide along the (100) and (010) planes was 23 nm and 12 nm, respectively, and h SSD was 2.9 μm and 2.1 μm, respectively. The proposed model of the relationship between subsurface damage depth and surface roughness can be used to achieve rapid, accurate, and non-destructive detection of the depth of subsurface damage and provides technical guidance for subsequent grinding and polishing processes.

Background Colorectal cancer, a prevalent malignancy worldwide, poses a significant challenge due to the lack of effective prognostic tools. In this study, we aimed to develop a functional gene signature to stratify colorectal cancer patients into different groups with distinct characteristics, which will greatly facilitate disease prediction. Results Patients were stratified into high- and low-risk groups using a prediction model built based on the functional gene signature. This innovative approach not only predicts clinicopathological features but also reveals tumor immune microenvironment types and responses to immunotherapy. The study reveals that patients in the high-risk group exhibit poorer pathological features, including invasion depth, lymph node metastasis, and distant metastasis, as well as unfavorable survival outcomes in terms of overall survival and disease-free survival. The underlying mechanisms for these observations are attributed to upregulated tumor-related signaling pathways, increased infiltration of pro-tumor immune cells, decreased infiltration of anti-tumor immune cells, and a lower tumor mutation burden. Consequently, patients in the high-risk group exhibit a diminished response to immunotherapy. Furthermore, the high-risk group demonstrates enrichment in extracellular matrix-related functions and significant infiltration of cancer-associated fibroblasts (CAFs). Single-cell transcriptional data analysis identifies CAFs as the primary cellular type expressing hub genes, namely ACTA2 , TPM2 , MYL9 , and T AGLN . This finding is further validated through multiple approaches, including multiplex immunohistochemistry (mIHC), polymerase chain reaction (PCR), and western blot analysis. Notably, TPM2 emerges as a potential biomarker for identifying CAFs in colorectal cancer, distinguishing them from both colorectal cancer cell lines and normal colon epithelial cell lines. Co-culture of CAFs and colorectal cancer cells revealed that CAFs could enhance the tumorigenic biofunctions of cancer cells indirectly, which could be partially inhibited by knocking down CAF original TPM2 expression. Conclusions This study introduces a functional gene signature that effectively and reliably predicts clinicopathological features and the tumor immune microenvironment in colorectal cancer. Moreover, the identification of TPM2 as a potential biomarker for CAFs holds promising implications for future research and clinical applications in the field of colorectal cancer.

s Circulating tumor cell (CTC) clusters, key in metastasis, rely on intercellular junctions for stability. However, the specific mechanisms governing intercellular connections within CTC clusters and the strategy targeting intercellular junctions to break CTC clusters remain elusive. Anticoagulants, commonly used to manage tumor-associated thrombosis, may potentially serve as CTC cluster dissociators, but their effects and mechanisms in inhibiting tumor metastasis are unclear. Hirudin, an anticoagulant peptide was used as a tool drug and found to inhibit breast tumor lung retention and colonization through its disruption of CTC clusters rather than directly inhibiting cell migration. Further research confirmed that within CTC clusters, desmosome junctions play a dominant role in maintaining CTC cluster formation with high expression of related proteins, while adhesion junctions express rarely. Desmoglein 2 (DSG2) mediates conversion between desmosome and adhesion junctions in CTC clusters. When DSG2 is highly expressed, the intercellular junctions within the CTC clusters are mainly composed of desmosomes. Reversely, low expression of DSG2 results in adhesion junctions. In addition, hypoxia-inducible factor-1 alpha (HIF-1α) positively controls DSG2-mediated desmosome junctions. Inhibiting HIF-1α promotes the conversion from desmosome to adhesion junctions, destabilizing CTC clusters. Hirudin inhibits hematogenous metastasis of breast cancer through suppression of HIF-1α-controlled DSG2-mediated desmosome junctions, ultimately leading to the disintegration of CTC clusters. Our findings highlight the therapeutic potential of targeting HIF-1α-controlled DSG2-mediated desmosome junction conversion and position hirudin as a promising CTC clusters dissociator optimized for the clinical prevention of breast cancer metastasis. Hirudin disrupts tumor cell clusters to prevent metastasis Breast cancer is a leading cause of death among women, often due to the spread of cancer cells to other parts of the body. This study explores how hirudin, which prevents blood clots, might help stop this spread. The researchers focused on circulating tumor cell (CTC) clusters, which can lead to new tumors. The study involved experiments with breast cancer cells and mice to see how hirudin affects CTC clusters. The researchers found that hirudin can break up these clusters by interfering with proteins that help the cells stick together. This is important because breaking up the clusters could reduce the chance of cancer spreading. The results show that hirudin not only reduced the size and number of CTC clusters but also made it harder for them to form new tumors in the lungs. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.