Changhua Bao, Vincent Eggers, Manuel Meierhofer
et al.
Abstract Dispersionless electronic bands lead to an extremely high density of states and suppressed kinetic energy, thereby increasing electronic correlations and instabilities that can shape emergent ordered states, such as excitonic, ferromagnetic, and superconducting phases. A flat band that extends over the entire momentum space and is well isolated from other dispersive bands is, therefore, particularly interesting. Here, the band structure of the van der Waals crystal NbOCl2 is revealed by utilizing photoelectron momentum microscopy. We directly map out an electronic band that is flat throughout the entire Brillouin zone and features a width of only ~ 100 meV. This band is well isolated from both the conduction and remote valence bands. Moreover, the quasiparticle band gap shows a high tunability upon the deposition of cesium atoms on the surface. By combining the single-particle band structure with the optical transmission spectrum, the optical gap is identified. The fully isolated flat band in a van der Waals crystal provides a qualitatively new testbed for exploring flat-band physics.
Materials of engineering and construction. Mechanics of materials
Vision models pretrained on large-scale RGB natural image datasets are widely reused for electron microscopy image segmentation. In electron microscopy, volumetric data are acquired as serial sections and processed as stacks of adjacent grayscale slices, where neighboring slices provide symmetric contextual information for identifying features on the central slice. The common strategy maps such stacks to pseudo-RGB inputs to enable transfer learning from pretrained models. However, this mapping imposes channel-specific semantics inherited from natural images, even though electron microscopy slices are homogeneous in the modality and symmetric in their predictive roles. As a result, pretrained models may encode inductive biases that are misaligned with the inherent symmetry of volumetric electron microscopy data. In this work, it is demonstrated that RGB-pretrained models systematically assign unequal importance to individual input slices when applied to stacked electron microscopy data, despite the absence of any intrinsic channel ordering. Using saliency-based attribution analysis across multiple architectures, a consistent channel-level asymmetry was observed that persists after fine-tuning and affects model interpretability, even when segmentation performance is unchanged. To address this issue, a targeted modification of pretraining weights based on uniform channel initialization was proposed, which restores symmetric feature attribution while preserving the benefits of pretraining. Experiments on the SNEMI, Lucchi and GF-PA66 datasets confirm a substantial reduction in attribution bias without compromising or even improving segmentation accuracy.
Postbiotics are increasingly incorporated into functional foods and supplements due to their potential health benefits, particularly immune modulation. However, the mechanisms by which these products influence antiviral immunity remain incompletely understood. Type I interferons, especially interferon-α (IFN-α), are central mediators of early antiviral defense, acting primarily through the activation of plasmacytoid dendritic cells (pDCs). Five commercially available postbiotic products containing heat-killed bacterial strains were evaluated for their ability to stimulate pDCs and induce IFN-α production. Bacterial uptake by pDCs was analyzed using confocal microscopy with Z-stack imaging, and IFN-α levels were quantified by ELISA. Among the tested strains, only <i>Lactococcus lactis</i> strain Plasma (LC-Plasma) demonstrated significant internalization by pDCs and induced measurable IFN-α production (73.8 ± 2.5 pg/mL) at the recommended daily dose. This effect was not observed with other strains, even at higher bacterial loads (up to 1 × 10<sup>11</sup> cells). Z-stack imaging confirmed that LC-Plasma was actively phagocytosed by pDCs, whereas other strains, such as <i>L. paracasei</i> MCC1849, adhered to the cell surface without internalization. The pDC concentration used in the assay approximated physiological levels in human blood. Notably, the IFN-α level induced by LC-Plasma exceeded that reported in the serum of hospitalized COVID-19 patients. <i>L. lactis</i> strain Plasma uniquely activates pDCs and induces IFN-α production under physiologically relevant conditions, distinguishing it from other postbiotic strains. These findings suggest that LC-Plasma may serve as a functional postbiotic with the potential to enhance antiviral immunity and mitigate disease severity.
AbstractDiagnostic electron microscopy (EM) is indispensable in all cases of infectious diseases which deserve or profit from the detection of the entire pathogen (i.e. the infectious unit). The focus of its application has shifted during the last decades from routine diagnostics to diagnostics of special cases, emergencies and the investigation of disease pathogenesis. While the focus of application has changed, the methods remain more or less the same. However, since the number of cases for diagnostic EM has declined as the number of laboratories that are able to perform such investigations, the preservation of the present knowledge is important. The aim of this article is to provide a review of the methods and strategies which are useful for diagnostic EM related to infectious diseases in our days. It also addresses weaknesses as well as useful variants or extensions of established methods. The main techniques, negative staining and thin section EM, are described in detail with links to suitable protocols and more recent improvements, such as thin section EM of small volume suspensions. Sample collection, transport and conservation/inactivation are discussed. Strategies of sample examination and requirements for a proper recognition of structures are outlined. Finally, some examples for the actual application of diagnostic EM related to infectious diseases are presented. The outlook section will discuss recent trends in microscopy, such as automated object recognition by machine learning, regarding their potential in supporting diagnostic EM.
Jonathan T. Weber, Niklas Müller, Alexander Schröder
et al.
The phase-resolved imaging of confined light fields by homodyne detection is a cornerstone of metrology in nano-optics and photonics, but its application in electron microscopy has been limited so far. Here, we report the mapping of optical modes in a waveguide structure by illumination with femtosecond light pulses in a continuous-beam transmission electron microscope. Multi-photon photoemission results in a remanent charging pattern which we image by Lorentz microscopy. The resulting image contrast is linked to the intensity distribution of the standing light wave and quantitatively described within an analytical model. The robustness of the approach is showcased in a wider parameter range and more complex sample geometries including micro- and nanostructures. We discuss further applications of light-interference-based charging for electron microscopy with in-situ optical excitation, laying the foundation for advanced measurement schemes for the phase-resolved imaging of propagating light fields.
Cathodoluminescence (CL) microscopy has emerged as a powerful tool for investigating the optical properties of materials at the nanoscale, offering unique insights into the behavior of photonic and plasmonic materials under electron excitation. We introduce an atlas of bulk CL spectra and intensity for a broad range of materials used in photonics and plasmonics. Through a combination of experimental CL microscopy and Monte Carlo simulations, we characterize spectra and intensity of coherent and incoherent CL, electron penetration depth and energy deposition, offering a foundational reference for interpreting CL signals and understanding material behavior under electron excitation. Our atlas captures CL signals across a wide range of materials, offering valuable insight into intrinsic emission properties for informed material selection and device design in photonics and plasmonics.
Kevin Murzyn, Maarten L. S. van der Geest, Leo Guery
et al.
Nonlinear optical microscopy provides elegant means for label-free imaging of biological samples and condensed matter systems. The widespread areas of application could even be increased if resolution was improved, which is currently limited by the famous Abbe diffraction limit. Super-resolution techniques can break the diffraction limit but rely on fluorescent labeling. This makes them incompatible with (sub-)femtosecond temporal resolution and applications that demand the absence of labeling. Here, we introduce harmonic deactivation microscopy (HADES) for breaking the diffraction limit in non-fluorescent samples. By controlling the harmonic generation process on the quantum level with a second donut-shaped pulse, we confine the third harmonic generation to three times below the original focus size and use this pulse for scanning microscopy. We demonstrate that resolution improvement by deactivation is more efficient for higher harmonic orders, and only limited by the maximum applicable deactivation-pulse fluence. This provides a route towards sub-100~nm resolution in a regular nonlinear microscope. The new capability of label-free super-resolution can find immediate applications in condensed matter physics, semiconductor metrology, and biomedical imaging.