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This paper presents a method for time-lapse 3D cell analysis. Specifically, we consider the problem of accurately localizing and quantitatively analyzing sub-cellular features, and for tracking individual cells from time-lapse 3D confocal cell image stacks. The heterogeneity of cells and the volume of multi-dimensional images presents a major challenge for fully automated analysis of morphogenesis and development of cells. This paper is motivated by the pavement cell growth process, and building a quantitative morphogenesis model. We propose a deep feature based segmentation method to accurately detect and label each cell region. An adjacency graph based method is used to extract sub-cellular features of the segmented cells. Finally, the robust graph based tracking algorithm using multiple cell features is proposed for associating cells at different time instances. We also demonstrate the generality of our tracking method on C. elegans fluorescent nuclei imagery. Extensive experiment results are provided and demonstrate the robustness of the proposed method. The code is available on GitHub and the method is available as a service through the BisQue portal.

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An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Policymakers around the world are turning to license-plate based driving restrictions in an effort to address urban air pollution. The format differs across cities, but most programs restrict driving once or twice a week during weekdays. This paper focuses on Mexico City, home to one of the oldest and best-known driving restriction policies. For almost two decades Mexico City's driving restrictions applied during weekdays only. This changed recently, however, when the program was expanded to include Saturdays. This paper uses hourly data from pollution monitoring stations to measure the effect of the Saturday expansion on air quality. Overall, there is little evidence that the program expansion improved air quality. Across eight major pollutants, the program expansion had virtually no discernible effect on pollution levels. These disappointing results stand in sharp contrast to estimates made before the expansion which predicted a 15%+ decrease in vehicle emissions on Saturdays. To understand why the program has been less effective than expected, the paper then turns to evidence from subway, bus, and light rail ridership, finding no evidence that the expansion was successful in getting drivers to switch to lower-emitting forms of transportation.

In this paper we have used second harmonic generation (SHG) and phasor approach to auto fluorescence lifetime imaging (FLIM) to obtain fingerprints of different collagens and then used these fingerprints to observe bone marrow fibrosis in the mouse femur. This is a label free approach towards fast automatable detection of fibrosis in tissue samples. FLIM has previously been used as a method of contrast in different tissues and in this paper phasor approach to FLIM is used to separate collagen I from collagen III, the markers of fibrosis, the largest groups of disorders that are often without any effective therapy. Often characterized by an increase in collagen content of the corresponding tissue, the samples are usually visualized by histochemical staining, which is pathologist dependent and cannot be automated.

Membrane nanotubes are dynamic structures that may connect cells over long distances. Nanotubes are typically thin cylindrical tubes, but they may occasionally have a beaded architecture along the tube. In this paper, we study the role of membrane mechanics in governing the architecture of these tubes and show that the formation of bead-like structures along the nanotubes can result from local heterogeneities in the membrane either due to protein aggregation or due to membrane composition. We present numerical results that predict how membrane properties, protein density, and local tension compete to create a phase space that governs the morphology of a nanotube. We also find that there exists a discontinuity in the energy that impedes two beads from fusing. These results suggest that the membrane-protein interaction, membrane composition, and membrane tension closely govern the tube radius, number of beads, and the bead morphology.

In this paper, we present peptide-pair encoding (PPE), a general-purpose probabilistic segmentation of protein sequences into commonly occurring variable-length sub-sequences. The idea of PPE segmentation is inspired by the byte-pair encoding (BPE) text compression algorithm, which has recently gained popularity in subword neural machine translation. We modify this algorithm by adding a sampling framework allowing for multiple ways of segmenting a sequence. PPE segmentation steps can be learned over a large set of protein sequences (Swiss-Prot) or even a domain-specific dataset and then applied to a set of unseen sequences. This representation can be widely used as the input to any downstream machine learning tasks in protein bioinformatics. In particular, here, we introduce this representation through protein motif discovery and protein sequence embedding. (i) DiMotif: we present DiMotif as an alignment-free discriminative motif discovery method and evaluate the method for finding protein motifs in three different settings: (1) comparison of DiMotif with two existing approaches on 20 distinct motif discovery problems which are experimentally verified, (2) classification-based approach for the motifs extracted for integrins, integrin-binding proteins, and biofilm formation, and (3) in sequence pattern searching for nuclear localization signal. The DiMotif, in general, obtained high recall scores, while having a comparable F1 score with other methods in the discovery of experimentally verified motifs. Having high recall suggests that the DiMotif can be used for short-list creation for further experimental investigations on motifs. In the classification-based evaluation, the extracted motifs could reliably detect the integrins, integrin-binding, and biofilm formation-related proteins on a reserved set of sequences with high F1 scores. (ii) ProtVecX: we extend k-mer based protein vector (ProtVec) embedding to variablelength protein embedding using PPE sub-sequences. We show that the new method of embedding can marginally outperform ProtVec in enzyme prediction as well as toxin prediction tasks. In addition, we conclude that the embeddings are beneficial in protein classification tasks when they are combined with raw amino acids k-mer features.

In this paper, we present peptide-pair encoding (PPE), a general-purpose probabilistic segmentation of protein sequences into commonly occurring variable-length sub-sequences. The idea of PPE segmentation is inspired by the byte-pair encoding (BPE) text compression algorithm, which has recently gained popularity in subword neural machine translation. We modify this algorithm by adding a sampling framework allowing for multiple ways of segmenting a sequence. PPE segmentation steps can be learned over a large set of protein sequences (Swiss-Prot) or even a domain-specific dataset and then applied to a set of unseen sequences. This representation can be widely used as the input to any downstream machine learning tasks in protein bioinformatics. In particular, here, we introduce this representation through protein motif discovery and protein sequence embedding. (i) DiMotif: we present DiMotif as an alignment-free discriminative motif discovery method and evaluate the method for finding protein motifs in three different settings: (1) comparison of DiMotif with two existing approaches on 20 distinct motif discovery problems which are experimentally verified, (2) classification-based approach for the motifs extracted for integrins, integrin-binding proteins, and biofilm formation, and (3) in sequence pattern searching for nuclear localization signal. The DiMotif, in general, obtained high recall scores, while having a comparable F1 score with other methods in the discovery of experimentally verified motifs. Having high recall suggests that the DiMotif can be used for short-list creation for further experimental investigations on motifs. In the classification-based evaluation, the extracted motifs could reliably detect the integrins, integrin-binding, and biofilm formation-related proteins on a reserved set of sequences with high F1 scores. (ii) ProtVecX: we extend k-mer based protein vector (ProtVec) embedding to variablelength protein embedding using PPE sub-sequences. We show that the new method of embedding can marginally outperform ProtVec in enzyme prediction as well as toxin prediction tasks. In addition, we conclude that the embeddings are beneficial in protein classification tasks when they are combined with raw amino acids k-mer features.

Medicinal plants have been used to treat diseases from time immemorial. We aimed to examine the efficacy of the ethyl acetate fraction of Nymphaea nouchali flower extract (NNFE) against melanogenesis process, and the underlying mechanisms in vitro and in vivo. Paper spray ionisation mass spectroscopy and (+) mode electrospray ionisation revealed the presence of seven flavonoids, two spermidine alkaloids, 3,4,8,9,10-pentahydroxy-dibenzo[b,d]pyran-6-one, and shoyuflavone C in NNFE. NNFE (100 µg/mL) significantly inhibited the monophenolase and diphenolase activities of mushroom tyrosinase at 94.90 ± 0.003% and 93.034 ± 0.003%, respectively. NNFE significantly suppressed cellular tyrosinase activity and melanin synthesis in vitro in melan-a cells and in vivo in HRM2 hairless mice. Furthermore, NNFE inhibited tyrosinase (TYR), tyrosinase-related protein (TYRP)-1, TYRP-2, and microphthalmia-associated transcription factor (MITF) expression, thereby blocking melanin synthesis. In particular, NNFE suppressed cAMP production with subsequent downregulation of CREB phosphorylation. Additionally, it stimulated MAP kinase phosphorylation (p38, JNK, and ERK1/2) and the proteasomal debasement pathway, leading to degradation of tyrosinase and MITF and the suppression of melanin production. Moreover, selective inhibitors of ERK1/2, JNK, and p38 attenuated NNFE inhibitory effects on melanogenesis, and MG-132 (a proteasome inhibitor) prevented the NNFE-induced decline in tyrosinase protein levels. In conclusion, these findings indicate that NNFE is a potential therapy for hyperpigmentation.

Alzheimer's Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1-3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature.

The ability to control a magnetic phase with an electric field is of great current interest for a variety of low power electronics in which the magnetic state is used either for information storage or logic operations. Over the past several years, there has been a considerable amount of research on pathways to control the direction of magnetization with an electric field. More recently, an alternative pathway involving the change of the magnetic state (ferromagnet to antiferromagnet) has been proposed. In this paper, we demonstrate electric field control of the Anomalous Hall Transport in a metamagnetic FeRh thin film, accompanying an antiferromagnet (AFM) to ferromagnet (FM) phase transition. This approach provides us with a pathway to "hide" or "reveal" a given ferromagnetic region at zero magnetic field. By converting the AFM phase into the FM phase, the stray field, and hence sensitivity to external fields, is decreased or eliminated. Using detailed structural analyses of FeRh films of varying crystalline quality and chemical order, we relate the direct nanoscale origins of this memory effect to site disorder as well as variations of the net magnetic anisotropy of FM nuclei. Our work opens pathways toward a new generation of antiferromagnetic - ferromagnetic interactions for spintronics.

In this paper, we report a new type of electrospinning collector that allows simultaneous collection and alignment of multiple poly(vinylidene fluoride-trifluoroethylene) piezoelectric fiber bundles with a controlled separation. The key enabling feature is the serrated teeth along the edges across an inclined gap as a part of the conductive collector. As a result, the electrical field across the gap is shaped to direct the electrospun fibers to merge into multiple bundles. The sharp points on the serrated teeth provide favorable charge dissipation points and thus fibers are preferentially formed bridging two closest sharp points across the gap. To investigate the effectiveness of serrated teeth on the formation of multiple fiber bundles, three-dimensional finite element simulations are conducted. The corresponding collectors are implemented to experimentally study the resulting electrospun fibers. Both simulation and experimental results suggest that multiple fiber bundles can be formed under the condition of a low teeth pitch to gap distance ratio. Furthermore, a sharper tooth angle results in a higher preferential formation of fiber bundles. Finally, the total electrospinning time should be less than 60 seconds to maintain favorable electric field profile. We also demonstrate that these piezoelectric fiber bundles can serve as ultra-flexible textile sensors.

Porous silica is an attractive biomaterial in many applications, including drug-delivery systems, bone-graft fillers and medical devices. The issue with porous silica biomaterials is the rate at which they resorb and the significant role played by interfacial chemistry on the host response in vivo. This paper explores the potential of diatom-biosilica as a model tool to assist in the task of mapping and quantifying the role of surface topography and chemical cues on cell fate. Diatoms are unicellular microalgae whose cell walls are composed of, amorphous nanopatterned biosilica that cannot be replicated synthetically. Their unique nanotopography has the potential to improve understanding of interface reactions between materials and cells. This study used Cyclotella meneghiniana as a test subject to assess cytotoxicity and pro-inflammatory reactions to diatom-biosilica. The results suggest that diatom-biosilica is non-cytotoxic to J774.2 macrophage cells, and supports cell proliferation and growth. The addition of amine and thiol linkers have shown a significant effect on cytotoxicity, growth and cytokine response, thus warranting further investigation into the interfacial effects of small chemical modifications to substrate surfaces. The overall findings suggest diatom-biosilica offers a unique platform for in-depth investigation of the role played by nanotopography and chemistry in biomedical applications.

Brain imaging genetics intends to uncover associations between genetic markers and neuroimaging quantitative traits. Sparse canonical correlation analysis (SCCA) can discover bi-multivariate associations and select relevant features, and is becoming popular in imaging genetic studies. The L1-norm function is not only convex, but also singular at the origin, which is a necessary condition for sparsity. Thus most SCCA methods impose [Formula: see text]-norm onto the individual feature or the structure level of features to pursuit corresponding sparsity. However, the [Formula: see text]-norm penalty over-penalizes large coefficients and may incurs estimation bias. A number of non-convex penalties are proposed to reduce the estimation bias in regression tasks. But using them in SCCA remains largely unexplored. In this paper, we design a unified non-convex SCCA model, based on seven non-convex functions, for unbiased estimation and stable feature selection simultaneously. We also propose an efficient optimization algorithm. The proposed method obtains both higher correlation coefficients and better canonical loading patterns. Specifically, these SCCA methods with non-convex penalties discover a strong association between the APOE e4 rs429358 SNP and the hippocampus region of the brain. They both are Alzheimer's disease related biomarkers, indicating the potential and power of the non-convex methods in brain imaging genetics.

Mammalian cell membranes have different phospholipid composition and cholesterol content, displaying a profile of fluidity that depends on their intracellular location. Among the dyes used in membrane studies, LAURDAN has the advantage to be sensitive to the lipid composition as well as to membrane fluidity. The LAURDAN spectrum is sensitive to the lipid composition and dipolar relaxation arising from water penetration, but disentangling lipid composition from membrane fluidity can be obtained if time resolved spectra could be measured at each cell location. Here we describe a method in which spectral and lifetime information obtained in different measurements at the same plane in a cell are used in the phasor plot providing a solution to analyze multiple lifetime or spectral data through a common visualization approach. We exploit a property of phasor plots based on the reciprocal role of the phasor plot and the image. In the phasor analysis each pixel of the image is associated with a phasor and each phasor maps to pixels and features in the image. In this paper the lifetime and spectral fluorescence data are used simultaneously to determine the contribution of polarity and dipolar relaxations of LAURDAN in each pixel of an image.

The human chaperonin TRiC consists of eight non-identical subunits, and its protein-folding activity is critical for cellular health. Misfolded proteins are associated with many human diseases, such as amyloid diseases, cancer, and neuropathies, making TRiC a potential therapeutic target. A detailed structural understanding of its ATP-dependent folding mechanism and substrate recognition is therefore of great importance. Of particular health-related interest is the mutation Histidine 147 to Arginine (H147R) in human TRiC subunit 5 (CCT5), which has been associated with hereditary sensory neuropathy. In this paper, we describe the crystal structures of CCT5 and the CCT5-H147R mutant, which provide important structural information for this vital protein-folding machine in humans. This first X-ray crystallographic study of a single human CCT subunit in the context of a hexadecameric complex can be expanded in the future to the other 7 subunits that form the TRiC complex.

Quantitative analysis of fluorescence signals from cells reacted with fluorescently labeled probes is a widely-used method for assessing cell biology. This method has become especially powerful for screening novel nanostructured materials for their influence on cell behavior. However, the effect of nanostructured surface on fluorescence intensity has largely been ignored, which likely leads to erroneous conclusions about cell behavior. This paper investigates this possibility by using fibroblasts cultured on nanoporous gold (np-Au) as a model nanostructured material system. We found that fibroblasts stained for f-actin using phalloidin conjugated with common fluorophores display different levels of fluorescence on np-Au, planar gold, and glass, suggesting different levels of f-actin composition. However, direct quantification via western blots indicates that the actin expression is the same across all conditions. We further investigated whether the fluorescence intensity depended on np-Au feature size, complementing the findings with reflection dark field measurements from different np-Au surfaces. Overall, our experimental measurements in agreement with our electrodynamic simulations suggest that nanostructured surfaces alter the fluorescence intensity of fluorophores by modulating both the excitation and light emission processes. We conclude that comparison of fluorescence on materials with different nanostructures should be done with a quantification method decoupled from the nanostructure's influence.

The human chaperonin TRiC consists of eight non-identical subunits, and its protein-folding activity is critical for cellular health. Misfolded proteins are associated with many human diseases, such as amyloid diseases, cancer, and neuropathies, making TRiC a potential therapeutic target. A detailed structural understanding of its ATP-dependent folding mechanism and substrate recognition is therefore of great importance. Of particular health-related interest is the mutation Histidine 147 to Arginine (H147R) in human TRiC subunit 5 (CCT5), which has been associated with hereditary sensory neuropathy. In this paper, we describe the crystal structures of CCT5 and the CCT5-H147R mutant, which provide important structural information for this vital protein-folding machine in humans. This first X-ray crystallographic study of a single human CCT subunit in the context of a hexadecameric complex can be expanded in the future to the other 7 subunits that form the TRiC complex.

The tantalizing prospect of harnessing the unique properties of graphene crumpled nanostructures continues to fuel tremendous interest in energy storage and harvesting applications. However, the paper ball-like, hard texture, and closed-sphere morphology of current 3D graphitic nanostructure production not only constricts the conductive pathways but also limits the accessible surface area. Here, we report new insights into electrohydrodynamically-generated droplets as colloidal nanoreactors in that the stimuli-responsive nature of reduced graphene oxide can lead to the formation of crumpled nanostructures with a combination of open structures and doubly curved, saddle-shaped edges. In particular, the crumpled nanostructures dynamically adapt to non-spherical, polyhedral shapes under continuous deposition, ultimately assembling into foam-like microstructures with a highly accessible surface area and spatially interconnected transport pathways. The implementation of such crumpled nanostructures as three-dimensional rear contacts for solar conversion applications realize benefits of a high aspect ratio, electrically addressable and energetically favorable interfaces, and substantial enhancement of both short-circuit currents and fill-factors compared to those made of planar graphene counterparts. Further, the 3D crumpled nanostructures may shed lights onto the development of effective electrocatalytic electrodes due to their open structure that simultaneously allows for efficient water flow and hydrogen escape.

Five periods of increased electrical conductivity have been found in the karst conduits supplying one of the largest first magnitude springs in Florida with water. Numerous well-developed conduit networks are distributed in the Woodville Karst Plain (WKP), Florida and connected to the Gulf of Mexico. A composite analysis of precipitation and electrical conductivity data provides strong evidence that the increases in conductivity are directly tied to seawater intrusion moving inland and traveling 11 miles against the prevailing regional hydraulic gradient from from Spring Creek Spring Complex (SCSC), a group of submarine springs at the Gulf Coast. A geochemical analysis of samples from the spring vent rules out anthropogenic contamination and upwelling regional recharge from the deep aquifer as sources of the rising conductivity. The interpretation is supported by the conceptual model established by prior researchers working to characterize the study area. This paper documents the first and longest case of seawater intrusion in the WKP, and also indicates significant possibility of seawater contamination through subsurface conduit networks in a coastal karst aquifer.

Flying animals accomplish high-speed navigation through fields of obstacles using a suite of sensory modalities that blend spatial memory with input from vision, tactile sensing, and, in the case of most bats and some other animals, echolocation. Although a good deal of previous research has been focused on the role of individual modes of sensing in animal locomotion, our understanding of sensory integration and the interplay among modalities is still meager. To understand how bats integrate sensory input from echolocation, vision, and spatial memory, we conducted an experiment in which bats flying in their natural habitat were challenged over the course of several evening emergences with a novel obstacle placed in their flight path. Our analysis of reconstructed flight data suggests that vision, echolocation, and spatial memory together with the possible exercise of an ability in using predictive navigation are mutually reinforcing aspects of a composite perceptual system that guides flight. Together with the recent development in robotics, our paper points to the possible interpretation that while each stream of sensory information plays an important role in bat navigation, it is the emergent effects of combining modalities that enable bats to fly through complex spaces.

Crystalline polymers have attracted significant interest in recent years due to their enhanced mechanical and thermal properties. As one type of organic-inorganic hybrid polymer crystals, polysilsesquioxane can be synthesized by large-scale and inexpensive so-gel processes with two precursors. In this paper, both octylene-bridged and hexylene-bridged PSQ crystals are characterized with infrared spectroscopy and X-ray crystallography to reveal their super high crystallinity. To study the thermal transport in these unique polymer crystals, we use a suspended micro thermal device to examine their thermal properties from 20 K to 320 K, and demonstrate their tunable thermal conductivity by varying the length of alkyl chains. We also conduct non-equilibrium molecular dynamics simulations to study the phonon behaviors across the hydrogen bond interface. The simulation results demonstrate good agreement with the experimental results regarding both the value and trend of the PSQ thermal conductivity. Furthermore, from the simulation, we find that the anharmonic phonon scattering and interfacial anharmnic coupling effects across the hydrogen bond interface may explain the experimentally observed thermal properties.

Advanced microscopy methods allow obtaining information on (dynamic) conformational changes in biomolecules via measuring a single molecular distance in the structure. It is, however, extremely challenging to capture the full depth of a three-dimensional biochemical state, binding-related structural changes or conformational cross-talk in multi-protein complexes using one-dimensional assays. In this paper we address this fundamental problem by extending the standard molecular ruler based on Förster resonance energy transfer (FRET) into a two-dimensional assay via its combination with protein-induced fluorescence enhancement (PIFE). We show that donor brightness (via PIFE) and energy transfer efficiency (via FRET) can simultaneously report on e.g., the conformational state of double stranded DNA (dsDNA) following its interaction with unlabelled proteins (BamHI, EcoRV, and T7 DNA polymerase gp5/trx). The PIFE-FRET assay uses established labelling protocols and single molecule fluorescence detection schemes (alternating-laser excitation, ALEX). Besides quantitative studies of PIFE and FRET ruler characteristics, we outline possible applications of ALEX-based PIFE-FRET for single-molecule studies with diffusing and immobilized molecules. Finally, we study transcription initiation and scrunching of E. coli RNA-polymerase with PIFE-FRET and provide direct evidence for the physical presence and vicinity of the polymerase that causes structural changes and scrunching of the transcriptional DNA bubble.

Roll-to-roll (R2R) printing has been pursued as a commercially viable high-throughput technology to manufacture flexible, disposable, and inexpensive printed electronic devices. However, in recent years, pessimism has prevailed because of the barriers faced when attempting to fabricate and integrate thin film transistors (TFTs) using an R2R printing method. In this paper, we report 20 × 20 active matrices (AMs) based on single-walled carbon nanotubes (SWCNTs) with a resolution of 9.3 points per inch (ppi) resolution, obtained using a fully R2R gravure printing process. By using SWCNTs as the semiconducting layer and poly(ethylene terephthalate) (PET) as the substrate, we have obtained a device yield above 98%, and extracted the key scalability factors required for a feasible R2R gravure manufacturing process. Multi-touch sensor arrays were achieved by laminating a pressure sensitive rubber onto the SWCNT-TFT AM. This R2R gravure printing system overcomes the barriers associated with the registration accuracy of printing each layer and the variation of the threshold voltage (Vth). By overcoming these barriers, the R2R gravure printing method can be viable as an advanced manufacturing technology, thus enabling the high-throughput production of flexible, disposable, and human-interactive cutting-edge electronic devices based on SWCNT-TFT AMs.

Germanium is an extremely important material used for numerous functional applications in many fields of nanotechnology. In this paper, we study the crystallization of amorphous Ge using atomistic simulations of critical nano-metric nuclei at high temperatures. We find that crystallization occurs by the recurrent transfer of atoms via a diffusive process from the amorphous phase into suitably-oriented crystalline layers. We accompany our simulations with a comprehensive thermodynamic and kinetic analysis of the growth process, which explains the energy balance and the interfacial growth velocities governing grain growth. For the 〈111〉 crystallographic orientation, we find a degenerate atomic rearrangement process, with two zero-energy modes corresponding to a perfect crystalline structure and the formation of a Σ3 twin boundary. Continued growth in this direction results in the development a twin network, in contrast with all other growth orientations, where the crystal grows defect-free. This particular mechanism of crystallization from amorphous phases is also observed during solid-phase epitaxial growth of 〈111〉 semiconductor crystals, where growth is restrained to one dimension. We calculate the equivalent X-ray diffraction pattern of the obtained nanotwin networks, providing grounds for experimental validation.

To develop a full understanding of interactions in nanomagnet arrays is a persistent challenge, critically impacting their technological acceptance. This paper reports the experimental, numerical and analytical investigation of interactions in arrays of Co nanoellipses using the first-order reversal curve (FORC) technique. A mean-field analysis has revealed the physical mechanisms giving rise to all of the observed features: a shift of the non-interacting FORC-ridge at the low-HC end off the local coercivity HC axis; a stretch of the FORC-ridge at the high-HC end without shifting it off the HC axis; and a formation of a tilted edge connected to the ridge at the low-HC end. Changing from flat to Gaussian coercivity distribution produces a negative feature, bends the ridge, and broadens the edge. Finally, nearest neighbor interactions segment the FORC-ridge. These results demonstrate that the FORC approach provides a comprehensive framework to qualitatively and quantitatively decode interactions in nanomagnet arrays.