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Recent research advances on fabric dyeing have focused on modeling the relationship between dye concentrations and the final color on fabrics. The emerging techniques in related studies have great potential to evolve the traditional dyeing industry to manufacture much more smartly. Given that dyeing is a complex process regulated by many factors, one of the challenging problems in the aforementioned techniques is to maintain the modeling accuracy at acceptable level. Other than developing high-performance algorithms and model architectures, it is also important to include effective data pre-processing techniques in modeling. In this paper, we show that conducting log-transform to the industrial dyeing data can greatly improve the performance of industrial dyeing recipe models. Such observations are confirmed on modeling tasks using different formats of color as input and different types of loss function in the model training. These findings may provide useful implications for related studies for the dyeing industry.

Many biological processes employ mechanisms involving the locations and interactions of multiple components. Given that most biological processes occur in three dimensions, the simultaneous measurement of three-dimensional locations and interactions is necessary. However, the simultaneous three-dimensional precise localization and measurement of interactions in real time remains challenging. Here, we report a new microscopy technique to localize two spectrally distinct particles in three dimensions with an accuracy (2.35σ) of tens of nanometers with an exposure time of 100 ms and to measure their real-time interactions using fluorescence resonance energy transfer (FRET) simultaneously. Using this microscope, we tracked two distinct vesicles containing t-SNAREs or v-SNARE in three dimensions and observed FRET simultaneously during single-vesicle fusion in real time, revealing the nanoscale motion and interactions of single vesicles in vesicle fusion. Thus, this study demonstrates that our microscope can provide detailed information about real-time three-dimensional nanoscale locations, motion, and interactions in biological processes.

Three-dimensional (3D) inter-site distance can be measured by single-molecule localization microscopy. Existing theories and analysis tools for 3D inter-site distance measurement only consider the simplest case where all measured distances are from an identical 3D Rician distribution. There are many problems where the 3D inter-site distance measurement result is made up of multiple components. For example, the measurement of intramolecular distances of deoxyribonucleic acid (DNA) with multiple possible conformations. In these cases, the overall distance distributions become finite mixtures of 3D Rician distributions (or 3D Rician mixtures). Here, we provide a numerical method using the 3D Rician mixture model (3D RMM) to resolve the finite 3D inter-site distance mixtures, which is based on the expectation-maximization (EM) algorithm. The proposed method has been tested on simulation data of finite 3D inter-site distance mixtures. The result using the Gaussian mixture model in the developed method is also discussed for comparison. Mini-abstract: In this paper, we provide a numerical method to resolve the finite 3D inter-site distance mixtures measured from 3D single-molecule localization microscopy. The paper contains 4 figures and 5 tables.

We report a new fabric dyeing recipe recommendation system which is based on mining industrial dyeing manufacturing data and a system design with modular architecture. Unlike traditional dyeing recipe recommendation systems, our method does not rely on labor-intensive calibration works between dye concentrations and the color. Also, the system is generally designed for different dyeing tasks. We describe the framework of our method and discuss strategies that are used for building the system. The system is built in the form of modular architecture which is made up of multiple gradient boosting regression tree models (GBRT). Each GBRT has been trained for predicting dye concentrations of a dye combination set (DCS) for a fabric type. Methods for model training and typical model performance are reported in the paper as well.

STIM1 (a Ca2+ sensor in the endoplasmic reticulum (ER) membrane) and Orai1 (a pore-forming subunit of the Ca2+-release-activated calcium channel in the plasma membrane) diffuse in the ER membrane and plasma membrane, respectively. Upon depletion of Ca2+ stores in the ER, STIM1 translocates to the ER-plasma membrane junction and binds Orai1 to trigger store-operated Ca2+ entry. However, the motion of STIM1 and Orai1 during this process and its roles to Ca2+ entry is poorly understood. Here, we report real-time tracking of single STIM1 and Orai1 particles in the ER membrane and plasma membrane in living cells before and after Ca2+ store depletion. We found that the motion of single STIM1 and Orai1 particles exhibits anomalous diffusion both before and after store depletion, and their mobility-measured by the radius of gyration of the trajectories, mean-square displacement, and generalized diffusion coefficient-decreases drastically after store depletion. We also found that the measured displacement distribution is non-Gaussian, and the non-Gaussian parameter drastically increases after store depletion. Detailed analyses and simulations revealed that single STIM1 and Orai1 particles are confined in the compartmentalized membrane both before and after store depletion, and the changes in the motion after store depletion are explained by increased confinement and polydispersity of STIM1-Orai1 complexes formed at the ER-plasma membrane junctions. Further simulations showed that this increase in the confinement and polydispersity after store depletion localizes a rapid increase of Ca2+ influx, which can facilitate the rapid activation of local Ca2+ signaling pathways and the efficient replenishing of Ca2+ store in the ER in store-operated Ca2+ entry.

Music emotion recognition (MER) studies have made great progress in detecting the emotions of music segments and analyzing the emotional dynamics of songs. The overall emotion and depth information of entire songs may be more suitable for real-life applications in certain scenarios. This study focuses on recognizing the overall emotion and depth of entire songs. First, we constructed a public dataset containing 3839 popular songs in China (PSIC3839) by conducting an online experiment to collect the arousal, valence, and depth annotation of each song. Second, we used handcrafted feature-based method to predict the overall emotion and depth values. Support vector regressions using Mel frequency cepstrum coefficients features as inputs achieve good model performance (arousal: R2 = 0.609; valence: R2 = 0.354; and depth: R2 = 0.465). Finally, the groupwise and personalized results were also investigated by training a unique regressor for each group or individual, which provides a reference for future research.

Intelligent manufacturing for the fabric dyeing industry requires high-performance dyeing recipe recommendation systems. Nowadays, recommending dyeing recipes by mining dyeing manufacturing data has become a new direction for the development of recipe recommendation systems. As one of the indispensable parts in the system development, data pre-processing needs more than routine steps such as the removal of missing data and outliers. Considering that dyes can have very different coloration properties on different fabrics, dyeing manufacturing records for a given dye combination to different fabric types should be properly categorized before they are used for training regression models for dyeing recipe prediction. In this paper, we propose a simple but effective method for this categorization work. Our method uses conventional K-means clustering analysis to find fabric types that have similar coloration properties for a given dye combination. We have applied the method on a dye combination formed by Colvaceton reactive dye-navy blue CF (CRD-navy blue), Colvaceton reactive dye-bright red 3BSN150% (CRD-red) and Colvaceton reactive dye-yellow 3RS150% (CRD-yellow) on 28 different types of fabrics. We show that these 28 types of fabrics can be well categorized into 8 groups based on the coloration properties. Our proposed method can be listed as one of the standard data pre-processing steps in the development of data-mining based recipe recommendation systems.

Myosin X (Myo10) has several unique design features including dimerization via an anti-parallel coiled coil and a long lever arm, which allow it to preferentially move on actin bundles. To understand the stepping behavior of single Myo10 on actin bundles, we labeled two heads of Myo10 dimers with different fluorophores. Unlike previously described for myosin V (Myo5) and VI (Myo6), which display alternating hand-over-hand stepping, Myo10 frequently took near simultaneous steps of both heads, and less frequently, 2–3 steps of one head before the other head stepped. We suggest that this behavior results from the unusual kinetic features of Myo10, in conjunction with the structural properties of the motor domain/lever arm, which will favor movement on actin bundles rather than on single filaments.

Due to the central limit theorem, experimental data usually follows the Gaussian distribution. However, the pore size of nonwoven fabrics, which is a type of quasi two-dimensional structure formed by curved filaments, has been found to deviate from Gaussian but shows Gamma shaped distributions with shape parameters larger than one. Namely, they show right skewness, have the only zero point at the origin, and show long tail that converges at the horizon. Most of existing literatures model the non-Gaussian distributed pore size based on integrate geometry theories, which neglect the curvature in filaments and are too mathematically complicated. In this paper, we provide a new theory based on the maximum-entropy principle for the non-Gaussian distributed pore size of nonwoven fabrics. We first derive the expression of the Shannon entropy and then set constraints based on the structural properties of nonwoven fabrics. By maximizing the Shannon entropy, we obtain a general expression for the pore-size distribution. The physical meanings of the constraints are discussed. Our theory has shed light on the underlying mechanisms of the non-Gaussian pore size distribution of nonwoven fabrics, and can be listed as a theoretic basis for related lab or industrial applications.

Store-operated Ca

STIM1 (a Ca(2+) sensor in the endoplasmic reticulum (ER) membrane) and Orai1 (a pore-forming subunit of the Ca(2+)-release-activated calcium channel in the plasma membrane) diffuse in the ER membrane and plasma membrane, respectively. Upon depletion of Ca(2+) stores in the ER, STIM1 translocates to the ER-plasma membrane junction and binds Orai1 to trigger store-operated Ca(2+) entry. However, the motion of STIM1 and Orai1 during this process and its roles to Ca(2+) entry is poorly understood. Here, we report real-time tracking of single STIM1 and Orai1 particles in the ER membrane and plasma membrane in living cells before and after Ca(2+) store depletion. We found that the motion of single STIM1 and Orai1 particles exhibits anomalous diffusion both before and after store depletion, and their mobility—measured by the radius of gyration of the trajectories, mean-square displacement, and generalized diffusion coefficient—decreases drastically after store depletion. We also found that the measured displacement distribution is non-Gaussian, and the non-Gaussian parameter drastically increases after store depletion. Detailed analyses and simulations revealed that single STIM1 and Orai1 particles are confined in the compartmentalized membrane both before and after store depletion, and the changes in the motion after store depletion are explained by increased confinement and polydispersity of STIM1-Orai1 complexes formed at the ER-plasma membrane junctions. Further simulations showed that this increase in the confinement and polydispersity after store depletion localizes a rapid increase of Ca(2+) influx, which can facilitate the rapid activation of local Ca(2+) signaling pathways and the efficient replenishing of Ca(2+) store in the ER in store-operated Ca(2+) entry.

The release of neurotransmitters via the fusion between synaptic vesicles and the presynaptic membrane is an essential step in synaptic transmission. Synaptic vesicles generally undergo two distinct modes of exocytosis called full-collapse fusion and kiss-and-run fusion. In kiss-and-run fusion, the fusion pore of the synaptic vesicle opens transiently without the vesicle collapsing fully into the plasma membrane; thus, each synaptic vesicle can be used multiple times to release neurotransmitters. Despite considerable research, the detailed mechanisms that underlie kiss-and-run fusion remain elusive, particularly the location of synaptic vesicles after kiss-and-run events. To address this question, we performed real-time three-dimensional tracking of single synaptic vesicles labeled with a single quantum dot in the presynaptic terminal of cultured hippocampal neurons and analyzed the three-dimensional trajectories of these vesicles undergoing kiss-and-run fusion. We found that the majority of these synaptic vesicles underwent another exocytosis event within 120 nm of their original fusion site and underwent a second exocytosis event within 10 s of the first fusion event. These results indicate that after kiss-and-run fusion, synaptic vesicles remain relatively close to their original fusion site and can release repeatedly at brief intervals, allowing neurons to maintain neurotransmitter release during bursting activity.

Store-operated Ca2+ entry (SOCE) is a major Ca2+ influx pathway that is controlled by the ER Ca2+ sensor STIM1. Abnormal activation of STIM1 directly influences Ca2+ influx, resulting in severe diseases such as Stormorken syndrome. The inactivation domain of STIM1 (IDstim) has been identified as being essential for Ca2+-dependent inactivation of STIM1 (CDI) after SOCE occurs. However, it is unknown whether IDstim is involved in keeping STIM1 inactive before CDI. Herein, we show that IDstim helps STIM1 keep inactive through intramolecular binding with the coiled-coil domain. Between IDstim and the coiled-coil domain, we found a short conserved linker whose extension or mutation leads to the constitutive activation of STIM1. We have demonstrated that IDstim needs the coiled-coil domain 1 (CC1) to inhibit the Ca2+ release-activated Ca2+ (CRAC) activation domain (CAD) activity and binds to a CC1-CAD fragment. Serial deletion of CC1 revealed that CC1α1 is a co-inhibitory domain of IDstim. CC1α1 deletion or leucine mutation, which abolishes the closed conformation, impaired the inhibitory effect and binding of IDstim. These results suggest that IDstim cooperates with CC1α1 to help STIM1 keep inactive under resting conditions.

Recent advances in fluorescence microscopy have provided researchers with powerful new tools to visualize cellular processes occurring in real time, giving researchers an unprecedented opportunity to address many biological questions that were previously inaccessible. With respect to neurobiology, these real-time imaging techniques have deepened our understanding of molecular and cellular processes, including the movement and dynamics of single proteins and organelles in living cells. In this review, we summarize recent advances in the field of real-time imaging of single synaptic vesicles in live neurons.

Huntington’s disease (HD) is an inherited neurodegenerative disorder caused by the abnormal expansion of CAG repeats in the huntingtin (HTT) gene, which leads to progressive loss of neurons starting in the striatum and cortex. One possible mechanism for this selective loss of neurons in the early stage of HD is altered neurotransmission at synapses. Despite the recent finding that presynaptic terminals play an important role in HD, neurotransmitter release at synapses in HD remains poorly understood. Here, we measured synaptic vesicle release in real time at single presynaptic terminals during electrical field stimulation. We found the increase in synaptic vesicle release at presynaptic terminals in primary cortical neurons in a knock-in mouse model of HD (zQ175). We also found the increase in Ca2+ influx at presynaptic terminals in HD neurons during the electrical stimulation. Consistent with increased Ca2+-dependent neurotransmission in HD neurons, the increase in vesicle release and Ca2+ influx was rescued with Ca2+ chelators or by blocking N-type voltage-gated Ca2+ channels, suggesting N-type voltage-gated Ca2+ channels play an important role in HD. Taken together, our results suggest that the increased synaptic vesicles release due to increased Ca2+ influx at presynaptic terminals in cortical neurons contributes to the selective neurodegeneration of these neurons in early HD and provide a possible therapeutic target.

Huntington’s disease (HD) is a dominantly inherited neurodegenerative disease caused by an increase in CAG repeats in the Huntingtin gene (HTT). The striatum is one of the most vulnerable brain regions in HD, and altered delivery of BDNF to the striatum is believed to underlie this high vulnerability. However, the delivery of BDNF to the striatum in HD remains poorly understood. Here, we used real-time imaging to visualize release of BDNF from cortical neurons cultured alone or co-cultured with striatal neurons. BDNF release was significantly decreased in the cortical neurons of zQ175 mice (a knock-in model of HD), and total internal reflection fluorescence microscopy revealed several release patterns of single BDNF-containing vesicles, with distinct kinetics and prevalence, in co-cultured cortical HD neurons. Notably, a smaller proportion of single BDNF-containing vesicles underwent full release in HD neurons than in wild-type neurons. This decreased release of BDNF in cortical neurons might lead to decreased BDNF levels in the striatum because the striatum receives BDNF mainly from the cortex. In addition, we observed a decrease in the total travel length and speed of BDNF-containing vesicles in HD neurons, indicating altered transport of these vesicles in HD. Our findings suggest a potential mechanism for the vulnerability of striatal neurons in HD and offer new insights into the pathogenic mechanisms underlying the degeneration of neurons in HD.

Mitochondria are essential for cellular survival and function. In neurons, mitochondria are transported to various subcellular regions as needed. Thus, defects in the axonal transport of mitochondria are related to the pathogenesis of neurodegenerative diseases, and the movement of mitochondria has been the subject of intense research. However, the inability to accurately track mitochondria with subpixel accuracy has hindered this research. Here, we report an automated method for tracking mitochondria based on the center of fluorescence. This tracking method, which is accurate to approximately one-tenth of a pixel, uses the centroid of an individual mitochondrion and provides information regarding the distance traveled between consecutive imaging frames, instantaneous speed, net distance traveled, and average speed. Importantly, this new tracking method enables researchers to observe both directed motion and undirected movement (i.e., in which the mitochondrion moves randomly within a small region, following a sub-diffusive motion). This method significantly improves our ability to analyze the movement of mitochondria and sheds light on the dynamic features of mitochondrial movement.