A new tracking algorithm for multiple colloidal particles close to contact

A charge-dependent long-ranged force drives tailored assembly of matter in solution

The interaction between charged objects in solution is generally expected to recapitulate two central principles of electromagnetics: (1) like-charged objects repel, and (2) they do so regardless of the sign of their electrical charge. Here we demonstrate experimentally that the solvent plays a hitherto unforeseen but crucial role in interparticle interactions, and importantly, that interactions in the fluid phase can break charge-reversal symmetry. We show that in aqueous solution, negatively charged particles can attract at long range while positively charged particles repel. In solvents that exhibit an inversion of the net molecular dipole at an interface, such as alcohols, we find that the converse can be true: positively charged particles may attract whereas negatives repel. The observations hold across a wide variety of surface chemistries: from inorganic silica and polymeric particles to polyelectrolyte- and polypeptide-coated surfaces in aqueous solution. A theory of interparticle interactions that invokes solvent structuring at an interface captures the observations. Our study establishes a nanoscopic interfacial mechanism by which solvent molecules may give rise to a strong and long-ranged force in solution, with immediate ramifications for a range of particulate and molecular processes across length scales such as self-assembly, gelation and crystallization, biomolecular condensation, coacervation, and phase segregation.

The spatial resolution limit of phagocytosis

Antibody-opsonized bacteria interact with Fc receptors in macrophages and trigger signaling cascades, which induce phagocytosis. The signaling pathways ultimately lead to actin polymerization that induces the protrusion of the membrane around the bacterium until it is completely engulfed. Although many proteins involved in the phagocytic cup formation have already been identified, it is still unclear how far the initial stimulus created by the bacterium-cell contact propagates in the cell. We hypothesize that this spreading distance is closely related to the spatial resolution limit of phagocytosis, the smallest distance in which two stimuli can be differentiated. Here, we probe this resolution limit by using holographic optical tweezers to attach pairs of immunoglobulin G-coated polystyrene microparticles (as models for opsonized bacteria) to murine macrophages in distances ranging from zero to several micrometers. By using 2-μm-sized particles, we found that the particles can be internalized jointly into one phagosome if they are attached to the cell very close together, but that they are taken up separately if they are attached far from each other. To explain this, we developed a model of the signaling process, which predicts the probabilities for separate uptake for different particle sizes and distances using cellular parameters including the average receptor distance. We tested the model by measuring the separate uptake probabilities for particles with a diameter of 1 to 3 μm and for cells with reduced numbers of Fcγ receptors and found very good agreement. Our model shows that the phagocytic uptake behavior can be explained by assuming an effective phagocytic signaling range of about 500 nm. Interestingly, this value corresponds to the lower size limit of phagocytosis. Our work provides quantitative access to spatial parameters of cellular signaling during phagocytosis and thereby contributes to a more quantitative understanding of cellular information processing.

Precision single-particle localization using radial variance transform

We introduce an image transform designed to highlight features with high degree of radial symmetry for identification and subpixel localization of particles in microscopy images. The transform is based on analyzing pixel value variations in radial and angular directions. We compare the subpixel localization performance of this algorithm to other common methods based on radial or mirror symmetry (such as fast radial symmetry transform, orientation alignment transform, XCorr, and quadrant interpolation), using both synthetic and experimentally obtained data. We find that in all cases it achieves the same or lower localization error, frequently reaching the theoretical limit.

Active particle feedback control with a single-shot detection convolutional neural network

The real-time detection of objects in optical microscopy allows their direct manipulation, which has recently become a new tool for the control, e.g., of active particles. For larger heterogeneous ensembles of particles, detection techniques are required that can localize and classify different objects with strongly inhomogeneous optical contrast at video rate, which is often difficult to achieve with conventional algorithmic approaches. We present a convolutional neural network single-shot detector which is suitable for real-time applications in optical microscopy. The network is capable of localizing and classifying multiple microscopic objects at up to 100 frames per second in images as large as [Formula: see text] pixels, even at very low signal-to-noise ratios. The detection scheme can be easily adapted and extended, e.g., to new particle classes and additional parameters as demonstrated for particle orientation. The developed framework is shown to control self-thermophoretic active particles in a heterogeneous ensemble selectively. Our approach will pave the way for new studies of collective behavior in active matter based on artificial interaction rules.