A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the format itself – OME-Zarr – along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain — the file format that underlies so many personal, institutional, and global data management and analysis tasks.

Deformable surface models are often represented as triangular meshes in image segmentation applications. For a fast and easily regularized deformation onto the target object boundary, the vertices of the mesh are commonly moved along line segments (typically surface normals). However, in case of high mesh curvature, these lines may not intersect with the target boundary at all. Consequently, certain deformations cannot be achieved. We propose omnidirectional displacements for deformable surfaces (ODDS) to overcome this limitation. ODDS allow each vertex to move not only along a line segment but within the volumetric inside of a surrounding sphere, and achieve globally optimal deformations subject to local regularization constraints. However, allowing a ball-shaped instead of a linear range of motion per vertex significantly increases runtime and memory. To alleviate this drawback, we propose a hybrid approach, fastODDS, with improved runtime and reduced memory requirements. Furthermore, fastODDS can also cope with simultaneous segmentation of multiple objects. We show the theoretical benefits of ODDS with experiments on synthetic data, and evaluate ODDS and fastODDS quantitatively on clinical image data of the mandible and the hip bones. There, we assess both the global segmentation accuracy as well as local accuracy in high curvature regions, such as the tip-shaped mandibular coronoid processes and the ridge-shaped acetabular rims of the hip bones.

Advances in microscopy hold great promise for allowing quantitative and precise readouts of morphological and molecular phenomena at the single cell level in bacteria. However, the potential of this approach is ultimately limited by the availability of methods to perform unbiased cell segmentation, defined as the ability to faithfully identify cells independent of their morphology or optical characteristics. In this study, we present a new algorithm, Omnipose, which accurately segments samples that present significant challenges to current algorithms, including mixed bacterial cultures, antibiotic-treated cells, and cells of extended or branched morphology. We show that Omnipose achieves generality and performance beyond leading algorithms and its predecessor, Cellpose, by virtue of unique neural network outputs such as the gradient of the distance field. Finally, we demonstrate the utility of Omnipose in the characterization of extreme morphological phenotypes that arise during interbacterial antagonism and on the segmentation of non-bacterial objects. Our results distinguish Omnipose as a uniquely powerful tool for answering diverse questions in bacterial cell biology.

Advances in microscopy hold great promise for allowing quantitative and precise measurement of morphological and molecular phenomena at the single-cell level in bacteria; however, the potential of this approach is ultimately limited by the availability of methods to faithfully segment cells independent of their morphological or optical characteristics. Here, we present Omnipose, a deep neural network image-segmentation algorithm. Unique network outputs such as the gradient of the distance field allow Omnipose to accurately segment cells on which current algorithms, including its predecessor, Cellpose, produce errors. We show that Omnipose achieves unprecedented segmentation performance on mixed bacterial cultures, antibiotic-treated cells and cells of elongated or branched morphology. Furthermore, the benefits of Omnipose extend to non-bacterial subjects, varied imaging modalities and three-dimensional objects. Finally, we demonstrate the utility of Omnipose in the characterization of extreme morphological phenotypes that arise during interbacterial antagonism. Our results distinguish Omnipose as a powerful tool for characterizing diverse and arbitrarily shaped cell types from imaging data.

Sex determination in Drosophila melanogaster is under the control of the X chromosome:autosome ratio and at least four major regulatory genes: transformer (tra), transformer-2 (tra-2), doublesex (dsx) and intersex (ix). Attention is focused here on the roles of these four loci in sex determination. By examining the sexual phenotype of clones of homozygous mutant cells produced by mitotic recombination in flies heterozygous for a given recessive sex-determination mutant, we have shown that the tra, tra-2 and dsx loci determine sex in a cell-autonomous manner. The effect of removing the wild-type allele of each locus (by mitotic recombination) at a number of times during development has been used to determine when the wild-type alleles of the tra, tra-2 and dsx loci have been transcribed sufficiently to support normal sexual development. The wild-type alleles of all three loci are needed into the early pupal period for normal sex determination in the cells that produce the sexually dimorphic (in pigmentation) cuticle of the fifth and sixth dorsal abdominal segments. tra(+) and tra-2(+) cease being needed shortly before the termination of cell division in the abdomen, whereas dsx(+) is required at least until the end of division. By contrast, in the foreleg, the wild-type alleles of tra(+) and tra-2(+) have functioned sufficiently for normal sexual differentiation to occur by about 24 to 48 hours before pupariation, but dsx(+) is required in the foreleg at least until pupariation.--A comparison of the phenotypes produced in mutant/deficiency and homozygous mutant-bearing flies shows that dsx, tra-2 and tra mutants result in a loss of wild-type function and probably represent null alleles at these genes.-All possible homozygous doublemutant combinations of ix, tra-2 and dsx have been constructed and reveal a clear pattern of epistasis: dsx > tra, tra-2 > ix. We conclude that these genes function in a single pathway that determines sex. The data suggest that these mutants are major regulatory loci that control the batteries of genes necessary for the development of many, and perhaps all, secondary sexual characteristics.-The striking similarities between the properties of these loci and those of the homeotic loci that determine segmental and subsegmental specialization during development suggest that the basic mechanisms of regulation are the same in the two situations. The phenotypes and interactions of these sex-determination mutants provide the basis for the model of how the wild-type alleles of these loci act together to effect normal sex determination. Implications of these observations for the function of other homeotic loci are discussed.

Under certain conditions, regenerative voltage spikes can be initiated locally in the dendrites of CA1 pyramidal neurons. These are interesting events that could potentially provide neurons with additional computational abilities. Using whole-cell dendritic recordings from the distal apical trunk and proximal tuft regions and realistic computer modeling, we have determined that highly synchronized and moderately clustered inputs are required for dendritic spike initiation: approximately 50 synaptic inputs spread over 100 mum of the apical trunk/tuft need to be activated within 3 msec. Dendritic spikes are characterized by a more depolarized voltage threshold than at the soma [-48 +/- 1 mV (n = 30) vs -56 +/- 1 mV (n = 7), respectively] and are mainly generated and shaped by dendritic Na+ and K+ currents. The relative contribution of AMPA and NMDA currents is also important in determining the actual spatiotemporal requirements for dendritic spike initiation. Once initiated, dendritic spikes can easily reach the soma, but their propagation is only moderately strong, so that it can be modulated by physiologically relevant factors such as changes in the V(m) and the ionic composition of the extracellular solution. With effective spike propagation, an extremely short-latency neuronal output is produced for greatly reduced input levels. Therefore, dendritic spikes function as efficient detectors of specific input patterns, ensuring that the neuronal response to high levels of input synchrony is a precisely timed action potential output.

Onconase (ONC) is a member of the ribonuclease A superfamily that is toxic to cancer cells in vitro and in vivo. ONC is now in Phase IIIb clinical trials for the treatment of malignant mesothelioma. Internalization of ONC to the cytosol of cancer cells is essential for its cytotoxic activity, despite the apparent absence of a cell-surface receptor protein. Endocytosis and cytotoxicity do, however, appear to correlate with the net positive charge of ribonucleases. To dissect the contribution made by the endogenous arginine and lysine residues of ONC to its cytotoxicity, 22 variants were created in which cationic residues were replaced with alanine. Variants with the same net charge (+2 to +5) as well as equivalent catalytic activity and conformational stability were found to exhibit large (> 10-fold) differences in toxicity for the cells of a human leukemia line. In addition, a more cationic ONC variant could be either much more or much less cytotoxic than a less cationic variant, again depending on the distribution of its cationic residues. The endocytosis of variants with widely divergent cytotoxic activity was quantified by flow cytometry using a small-molecule fluorogenic label, and was found to vary by twofold or less. This small difference in endocytosis did not account for the large difference in cytotoxicity, implicating the distribution of cationic residues as being critical for lipid-bilayer translocation subsequent to endocytosis. This finding has fundamental implications for understanding the interaction of ribonucleases and other proteins with mammalian cells.

Memory guides the choices an animal makes across widely varying conditions in dynamic environments. Consequently, the most adaptive choice depends on the options available. How can a single memory support optimal behavior across different sets of choice options? We address this using olfactory learning in Drosophila. Even when we restrict an odor-punishment association to a single set of synapses using optogenetics, we find that flies still show choice behavior that depends on the options it encounters. Here we show that how the odor choices are presented to the animal influences memory recall itself. Presenting two similar odors in sequence enabled flies to not only discriminate them behaviorally but also at the level of neural activity. However, when the same odors were encountered as solitary stimuli, no such differences were detectable. These results show that memory recall is not simply a comparison to a static learned template, but can be adaptively modulated by stimulus dynamics.

Insect neural systems are a promising source of inspiration for new navigation algorithms, especially on low size, weight, and power platforms. There have been unprecedented recent neuroscience breakthroughs with Drosophila in behavioral and neural imaging experiments as well as the mapping of detailed connectivity of neural structures. General mechanisms for learning orientation in the central complex (CX) of Drosophila have been investigated previously; however, it is unclear how these underlying mechanisms extend to cases where there is translation through an environment (beyond only rotation), which is critical for navigation in robotic systems. Here, we develop a CX neural connectivity-constrained model that performs sensor fusion, as well as unsupervised learning of visual features for path integration; we demonstrate the viability of this circuit for use in robotic systems in simulated and physical environments. Furthermore, we propose a theoretical understanding of how distributed online unsupervised network weight modification can be leveraged for learning in a trajectory through an environment by minimizing orientation estimation error. Overall, our results may enable a new class of CX-derived low power robotic navigation algorithms and lead to testable predictions to inform future neuroscience experiments.

A group leader decided that his lab would share the fluorescent dyes they create, for free and without authorship requirements. Nearly 12,000 aliquots later, he reveals what has happened since.