Author Correction: The architecture of the human default mode network explored through cytoarchitecture, wiring and signal flow
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Advancements in ultrafast photonics: confluence of nonlinear optics and intelligent strategies
Automatic mode-locking techniques, the integration of intelligent technologies with nonlinear optics offers the promise of on-demand intelligent control, potentially overcoming the inherent limitations of traditional ultrafast pulse generation that have predominantly suffered from the instability and suboptimality of open-loop manual tuning. The advancements in intelligent algorithm-driven automatic mode-locking techniques primarily are explored in this review, which also revisits the fundamental principles of nonlinear optical absorption, and examines the evolution and categorization of conventional mode-locking techniques. The convergence of ultrafast pulse nonlinear interactions with intelligent technologies has intricately expanded the scope of ultrafast photonics, unveiling considerable potential for innovation and catalyzing new waves of research breakthroughs in ultrafast photonics and nonlinear optics characters.
Segment Anything for Microscopy
Accurate segmentation of objects in microscopy images remains a bottleneck for many researchers despite the number of tools developed for this purpose. Here, we present Segment Anything for Microscopy (μSAM), a tool for segmentation and tracking in multidimensional microscopy data. It is based on Segment Anything, a vision foundation model for image segmentation. We extend it by fine-tuning generalist models for light and electron microscopy that clearly improve segmentation quality for a wide range of imaging conditions. We also implement interactive and automatic segmentation in a napari plugin that can speed up diverse segmentation tasks and provides a unified solution for microscopy annotation across different microscopy modalities. Our work constitutes the application of vision foundation models in microscopy, laying the groundwork for solving image analysis tasks in this domain with a small set of powerful deep learning models.
Cardiac conduction system regeneration prevents arrhythmias after myocardial infarction
Arrhythmias are a hallmark of myocardial infarction (MI) and increase patient mortality. How insult to the cardiac conduction system causes arrhythmias following MI is poorly understood. Here, we demonstrate conduction system restoration during neonatal mouse heart regeneration versus pathological remodeling at non-regenerative stages. Tissue-cleared whole-organ imaging identified disorganized bundling of conduction fibers after MI and global His–Purkinje disruption. Single-cell RNA sequencing (scRNA-seq) revealed specific molecular changes to regenerate the conduction network versus aberrant electrical alterations during fibrotic repair. This manifested functionally as a transition from normal rhythm to pathological conduction delay beyond the regenerative window. Modeling in the infarcted human heart implicated the non-regenerative phenotype as causative for heart block, as observed in patients. These findings elucidate the mechanisms underpinning conduction system regeneration and reveal how MI-induced damage elicits clinical arrhythmogenesis.
Stromal architecture and fibroblast subpopulations with opposing effects on outcomes in hepatocellular carcinoma
Dissecting the spatial heterogeneity of cancer-associated fibroblasts (CAFs) is vital for understanding tumor biology and therapeutic design. By combining pathological image analysis with spatial proteomics, we revealed two stromal archetypes in hepatocellular carcinoma (HCC) with different biological functions and extracellular matrix compositions. Using paired single-cell RNA and epigenomic sequencing with Stereo-seq, we revealed two fibroblast subsets CAF-FAP and CAF-C7, whose spatial enrichment strongly correlated with the two stromal archetypes and opposing patient prognosis. We discovered two functional units, one is the intratumor inflammatory hub featured by CAF-FAP plus CD8_PDCD1 proximity and the other is the marginal wound-healing hub with CAF-C7 plus Macrophage_SPP1 co-localization. Inhibiting CAF-FAP combined with anti-PD-1 in orthotopic HCC models led to improved tumor regression than either monotherapy. Collectively, our findings suggest stroma-targeted strategies for HCC based on defined stromal archetypes, raising the concept that CAFs change their transcriptional program and intercellular crosstalk according to the spatial context.
Collective quantum enhancement in critical quantum sensing
Critical systems represent a valuable resource in quantum sensing and metrology. Critical quantum sensing (CQS) protocols can be realized using finite-component phase transitions, where criticality arises from the rescaling of system parameters rather than the thermodynamic limit. Here, we show that a collective quantum advantage can be achieved in a multipartite CQS protocol using a chain of parametrically coupled critical resonators in the weak-nonlinearity limit. We derive analytical solutions for the low-energy spectrum of this unconventional quantum many-body system, which is composed of locally critical elements. We then assess the scaling of the quantum Fisher information with respect to fundamental resources. We demonstrate that the coupled chain outperforms an equivalent ensemble of independent critical sensors, achieving quadratic scaling in the number of resonators. Finally, we show that even with finite Kerr nonlinearity or Markovian dissipation, the critical chain retains its advantage, making it relevant for implementing quantum sensors with current microwave superconducting technologies.
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