High-throughput multimodal optofluidic biophysical imaging cytometry.

Traditional biophysical cytometry has been limited by its low-dimensional phenotyping characteristics, often relying on only one or a few cellular biophysical phenotypes as readouts. This has perpetuated the perception that biophysical cytometry lacks the power to determine cellular heterogeneity. Here, we introduce a multimodal biophysical cytometry platform, termed quantitative phase morpho-rheological (QP-MORE) cytometry, which simultaneously captures a collection of high-resolution biophysical and mechanical phenotypes of single cells at ultrahigh throughput (>10 000 cells per s).

Training of physical neural networks.

Physical neural networks (PNNs) are a class of neural-like networks that make use of analogue physical systems to perform computations. Although at present confined to small-scale laboratory demonstrations, PNNs could one day transform how artificial intelligence (AI) calculations are performed. Could we train AI models many orders of magnitude larger than present ones? Could we perform model inference locally and privately on edge devices? Research over the past few years has shown that the answer to these questions is probably "yes, with enough research".

A label-free method for measuring the composition of multicomponent biomolecular condensates.

Many subcellular compartments are biomolecular condensates made of multiple components, often including several distinct proteins and nucleic acids. However, current tools to measure condensate composition are limited and cannot capture this complexity quantitatively because they either require fluorescent labels, which can perturb composition, or can distinguish only one or two components. Here we describe a label-free method based on quantitative phase imaging and analysis of tie-lines and refractive index to measure the composition of reconstituted condensates with multiple components.

Universal photonic processor for spatial mode decomposition.

Efficient and precise information storage and processing using light's various degrees of freedom - intensity, phase, and polarization - have vast applications in modern photonics. The corresponding utilization necessitates the accurate measurement and decomposition of arbitrary spatial modes into their orthogonal components. In this paper, we introduce a new modal decomposition technique based on a 16-pixel reconfigurable photonic integrated circuit programmed as a spatial mode decomposer.

Polarization Faticons: Chiral Localized Structures in Self-Defocusing Kerr Resonators.

We report on numerical predictions and experimental observations of a novel type of temporal localized dissipative structures that manifest themselves in the self-defocusing regime of driven nonlinear optical resonators with two polarization modes. These chiral dissipative solitons, which we term "polarization faticons," break both temporal and polarization symmetry and consist of two bright lobes of opposite polarization handedness, interlocked by a domain wall. Our study reveals that faticons are connected to a vectorial modulational instability, from which they can be excited through a collapsing dynamic.

Cryo-light microscopy with angstrom precision deciphers structural conformations of PIEZO1 in its native state.

Investigations based on cryo-electron microscopy (cryo-EM), atomic force microscopy, and super-resolution microscopy reveal a symmetric trimer with propeller-like blades for the mechanosensitive ion channel PIEZO. However, a conclusive understanding of its conformations in the cell membrane is lacking. Here, we implement a high-vacuum cryogenic shuttle to transfer shock-frozen cell membranes in and out of a cryostat designed for single-particle cryo-light microscopy (spCryo-LM).

Measuring Molecular Mass Densities at Subcellular Resolution Using Optical Diffraction Tomography.

Biological systems intricately regulate their density and volume throughout their life cycles and in response to physiological changes. Mass density, as a fundamental physical quantity, plays significant roles in biological processes such as differentiation, cell growth, protein synthesis, and condensate formation. Loss of density homeostasis on the other hand can have severe consequences including cellular senescence and disease states.

Conserved nucleocytoplasmic density homeostasis drives cellular organization across eukaryotes.

The confinement of macromolecules has profound implications for cellular biochemistry. It generates environments with specific physical properties affecting diffusion, macromolecular crowding, and reaction rates. Yet, it remains unknown how intracellular density distributions emerge and affect cellular physiology.

All-optical nonlinear activation function based on stimulated Brillouin scattering.

Optical neural networks have demonstrated their potential to overcome the computational bottleneck of modern digital electronics. However, their development towards high-performing computing alternatives is hindered by one of the optical neural networks' key components: the activation function. Most of the reported activation functions rely on opto-electronic conversion, sacrificing the unique advantages of photonics, such as resource-efficient coherent and frequency-multiplexed information encoding.

Controlling treatment toxicity in ovarian cancer to prime the patient for tumor extinction therapy.

High-grade serous ovarian cancer (HGSOC) remains a major clinical challenge. In particular among those patients with homologous recombination (HR)-proficient tumors (>50%), most eventually succumb to their disease due to high recurrence rates, acquired resistance, and cumulative toxicity. This report summarizes work from the 12 IMO Workshop in which we explored an alternative "extinction therapy" strategy for frontline treatment of HGSOC.

Violation of Bell inequality with unentangled photons.

Violation of local realism via Bell inequality-a profound and counterintuitive manifestation of quantum theory that conflicts with the prediction of local realism-is viewed to be intimately linked with quantum entanglement. Experimental demonstrations of such a phenomenon using quantum entangled states are among the landmark experiments of modern physics and paved the way for quantum technology. Here, we report the violation of the Bell inequality that cannot be described by quantum entanglement in the system but arises from quantum indistinguishability by path identity, shown by the multiphoton frustrated interference.

Hybridization of molecules via a common photonic mode.

Atoms and molecules usually hybridize and form bonds when they come in very close proximity of each other. In this work, we show that molecules can hybridize even through far-field electromagnetic interactions mediated by the shared mode of an optical microcavity. We discuss a collective enhancement of the vacuum Rabi splitting and study super- and subradiant states that arise from the cavity-mediated coupling both in the resonant and dispersive regimes.

Ångström-resolution imaging of cell-surface glycans.

Glycobiology is rooted in the study of monosaccharides, ångström-sized molecules that are the building blocks of glycosylation. Glycosylated biomolecules form the glycocalyx, a dense coat encasing every human cell with central relevance-among others-in immunology, oncology and virology. To understand glycosylation function, visualizing its molecular structure is fundamental.

Bioengineered Bacterial Vesicles and Biomimetic Hybrids Eliminate Biofilms and Balance the Gut Microbiome.

Antibiotic-resistant pathogens are a global health challenge, necessitating innovative solutions beyond conventional antibiotics. This study introduces biomimetic nanocarriers - hybrids of bacteriomimetic liposomes and biocompatible Myxobacteria outer-membrane vesicles (OMVs) - as tunable platforms for targeted antibiotic delivery. Comparative analyses of their physicochemical properties and interactions with immune cells, intestinal epithelium, and biofilm-forming pathogens reveal distinct advantages.

Quantum equilibrium propagation for efficient training of quantum systems based on Onsager reciprocity.

The widespread adoption of machine learning and artificial intelligence in all branches of science and technology creates a need for energy-efficient, alternative hardware. While such neuromorphic systems have been demonstrated in a wide range of platforms, it remains an open challenge to find efficient and general physics-based training approaches. Equilibrium propagation (EP), the most widely studied approach, has been introduced for classical energy-based models relaxing to an equilibrium.

Influence of polarisation states on the axial point spread function in subtractive second harmonic generation microscopy with a vortex beam.

Doughnut-shaped vortex beams are widely used to enhance lateral resolution in super-resolution fluorescence microscopy and subtractive second harmonic generation microscopy. The influence of polarisation states on the axial point spread function is investigated theoretically and experimentally in subtractive second harmonic generation microscopy using a first-order Laguerre-Gaussian vortex beam. The influence of left-handed circular, right-handed circular and linear polarised states are analysed for second harmonic generation imaging and compared with results of fluorescence imaging.

Small U-Net for Fast and Reliable Segmentation in Imaging Flow Cytometry.

Imaging flow cytometry requires rapid and accurate segmentation methods to ensure high-quality cellular morphology analysis and cell counting. In deformability cytometry (DC), a specific type of imaging flow cytometry, accurately detecting cell contours is critical for evaluating mechanical properties that serve as disease markers. Traditional thresholding methods, commonly used for their speed in high-throughput applications, often struggle with low-contrast images, leading to inaccuracies in detecting the object contour.

From Biophysics to Biomedical Physics.

The intersection of physics and medicine has long been a fertile ground for innovation, with advances in one field driving breakthroughs in the other. In recent years, the emergence of modern biophysical techniques has provided a toolbox for understanding complex physiological processes across scales. These tools have the potential to revolutionize medical practice, from diagnosis to therapy.

Cell state-specific cytoplasmic density controls spindle architecture and scaling.

Mitotic spindles are dynamically intertwined with the cytoplasm they assemble in. How the physicochemical properties of the cytoplasm affect spindle architecture and size remains largely unknown. Using quantitative biochemistry in combination with adaptive feedback microscopy, we investigated mitotic cell and spindle morphology during neural differentiation of embryonic stem cells.

Cellular morphodynamics as quantifiers for functional states of resident tissue macrophages in vivo.

Resident tissue macrophages (RTMs) are essential for tissue homeostasis. Their diverse functions, from monitoring interstitial fluids to clearing cellular debris, are accompanied by characteristic morphological changes that reflect their functional status. While current knowledge of macrophage behavior comes primarily from in vitro studies, their dynamic behavior in vivo is fundamentally different, necessitating a more physiologically relevant approach to their understanding.

Investigation of Thin Silicone Films on Opaque Solid Surfaces Using Coherent Raman Scattering Imaging.

The measurement of thin films with a thickness in the nanometer range is challenging because it requires extensive sample preparation, vacuum condition, long measurement times or using test inks that additionally contaminate the surface. The detection of those films is crucial for production processes that rely on a boundary layer to create a proper interface like adhesive bonding, coating, or lithography in various industries like automotive, solar, energy storage and semiconductor manufacturing. Consequently, there is a need for quick, reliable measurement techniques with high sensitivity to ensure the technical cleanliness of the opaque surface.

Fine particulate matter (PM) induces microRNA-192-5p causing glomerular damage.

An association between air pollution and the incidence of membranous glomerulonephritis (MGN) has been shown in epidemiological studies. However, the causality of this relationship and data on potential pathomechanisms are still missing. Anti-phospholipase A2 receptor (PLA2R1) antibodies, upregulation of microRNA-192-5p, and decreased expression of its podocyte target nephronectin (NPNT) in patients with MGN have been shown, but the trigger for these regulations remained unknown.

Boosting the Host-Guest Binding by Programming the Curvature in Geodesic Nanoribbons.

The curvature of an aromatic system is an essential parameter that can be used to program the self-assembly and host-guest complementarity in geodesic polyarenes. However, the challenging synthesis of curved aromatics impedes exploration of the related effects on the binding properties. The design and synthesis of a polyarene with programmed curvature fitting to C by a stepwise introduction of five-membered rings are presented to solve this challenge.