Long-term Tracking Research Articles

Hair Follicle Development and Cashmere Traits in Albas Goat Kids.

The objectives of this trial were to study the growth and development of hair follicles and cashmere traits in cashmere goats and to provide a theoretical basis for the regulation of secondary hair follicle development and the scientific breeding selection of cashmere goats. Twelve single-fetal female kids were selected as research objects. A long-term tracking plan was created to regularly determine their growth performance, cashmere performance, and hair follicle traits. The results showed no significant difference in live weight after the first and second combing. The cashmere yield and unit yield of the first combing were significantly higher than those of the second combing (p < 0.05). Sections of hair follicles showed that the primary hair follicles are almost fully developed by 1 month, and the secondary hair follicles are fully developed by 5-6 months after birth. The primary hair follicle density (PFD) and secondary hair follicle density (SFD) were highest at birth and decreased within 1 month; and SFD was stable at 5-6 months of age. The change of MSFD took a maximum time of 2 to 3 months. The S:P increase reached its peak at 6 months. BMP4 expression increased with time. FGF2, FGF21 and BMP7 were higher at 3 months old than at the other two-time points. In conclusion, this study determined the total development time of primary and secondary hair follicles from morphology and speculated that FGF2, FGF21, and BMP7 may play a regulatory role in developing secondary hair follicles. Therefore, the period from birth to 6 months of age was the best time to regulate secondary hair follicle development in cashmere goats kids. The traits of the hair follicle and cashmere at 6 months of age could be breeding selection indicators for cashmere goats.

De Novo Designed Self-Assembling Rhodamine Probe for Real-Time, Long-Term and Quantitative Live-Cell Nanoscopy.

Super-resolution imaging provides a powerful approach to image dynamic biomolecule events at nanoscale resolution. An ingenious method involving tuning intramolecular spirocyclization in rhodamine offers an appealing strategy to design cell-permeable fluorogenic probes for super-resolution imaging. Nevertheless, precise control of rhodamine spirocyclization presents a significant challenge. Through detailed study of the structure-activity relationship, we identified that multiple key factors control rhodamime spirocyclization. The findings provide opportunities to create fluorogenic probes with tailored properties. On the basis of our findings, we constructed self-assembling rhodamine probes for no-wash live-cell confocal and super-resolution imaging. The designed self-assembling probe Rho-2CF3 specifically labeled its target proteins and displayed high ring-opening ability, fast labeling kinetics (<1 min), and large turn-on fold (>80 folds), which is very difficult to be realized by the existing methods. Using the probe, we achieved high-contrast super-resolution imaging of nuclei and mitochondria with a spatial resolution of up to 42 nm. The probe also showed excellent photostability and proved ideal for real-time and long-term tracking of mitochondrial fission and fusion events with high spatiotemporal resolution. Furthermore, Rho-2CF3 could resolve the ultrastructure of mitochondrial cristae and quantify their morphological changes under drug treatment at nanoscale. Our strategy thus demonstrates its usefulness in designing self-assembling probes for super-resolution imaging.

Nanometer-resolution long-term tracking of single cargos reveals dynein motor mechanisms.

Cytoplasmic dynein is essential for intracellular transport. Despite extensive in vitro characterizations, how the dynein motors work collectively to transport vesicles and how they step in live cells remains elusive because of the much faster speed of dynein under physiological conditions. To dissect the molecular mechanism and dynamics of dynein, we developed novel optical probes which enabled long-term single particle tracking with high spatiotemporal resolutions. We found that the number of active dynein motors transporting the cargo switched stochastically from one to five pairs during the long-range transport. Our very bright optical probes allowed the observation of individual molecular steps. The dwell time between steps was found to be described by two equal and temperature-dependent rate constants. This finding suggests that two ATP molecules were hydrolyzed sequentially during each dynein step. Our observations shed new light on the chemomechanical cycle of dynein in living cells.

Long-term satellite tracking reveals patterns of long-distance dispersal in juvenile and adult Arctic foxes (Vulpes lagopus).

Long-distance dispersal plays a key role in species distribution and persistence. However, its movement metrics and ecological implications may differ whether it is undertaken by juveniles (natal dispersal) or adults (breeding dispersal). We investigated the influence of life stage on long-distance dispersal in the Arctic fox, an important tundra predator. We fitted 170 individuals with satellite collars during a 13-year study on Bylot Island (Nunavut, Canada), and analysed the tracks of 10 juveniles and 27 adults engaging in long-distance dispersal across the Canadian High Arctic. This behaviour was much more common than expected, especially in juveniles (62.5%, adults: 19.4%). Emigration of juveniles occurred mainly at the end of summer while departure of adults was not synchronized. Juveniles travelled for longer periods and over longer cumulative distances than adults, but spent similar proportions of their time travelling on sea ice versus land. Successful immigration occurred mostly in late spring and was similar for juveniles and adults (30% versus 37%). Our results reveal how life stage influences key aspects of long-distance dispersal in a highly mobile canid. This new knowledge is critical to understand the circumpolar genetic structure of the species, and how Arctic foxes can spread zoonoses across vast geographical areas.

Metal protoporphyrin-induced self-assembly nanoprobe enabling precise tracking and antioxidant protection of stem cells for ischemic stroke therapy.

Mesenchymal stem cell (MSC)-based therapy has provided a promising strategy for the treatment of ischemic stroke, which is still restricted by the lack of long-term cell tracking strategy as well as the poor survival rate of stem cells in ischemic region. Herein, a dual-functional nanoprobe, cobalt protoporphyrin-induced nano-self-assembly (CPSP), has been developed through a cobalt protoporphyrin IX (CoPP) aggregation-induced self-assembly strategy, which combines CoPP and superparamagnetic iron oxide (SPION) via a simple solvent evaporation-driven method. Without any additional carrier materials, the obtained CPSP is featured with good biocompatibility and high proportions of active ingredients. The SPIONs in CPSPs form a cluster-like structure, endowing this nano-self-assembly with excellent T2-weighted magnetic resonance (MR) imaging performance. Furthermore, the CoPP released from CPSPs could effectively protect MSCs by upregulating heme oxygenase 1 (HO-1) expression. The in vivo cell tracing capacity of CPSPs is confirmed by monitoring the migration of labeled MSCs with MR imaging in a middle cerebral artery occlusion mouse model. More importantly, the sustained release of CoPP from CPSPs improves the survival of transplanted MSCs and promotes neural repair and neurobehavioral recovery of ischemic mice. Overall, this work presents a novel dual-functional nanoagent with an ingenious design for advancing MSC-based therapy.

Active breeding seabirds prospect alternative breeding colonies

Compared to other animal movements, prospecting by adult individuals for a future breeding site is commonly overlooked. Prospecting influences the decision of where to breed and has consequences on fitness and lifetime reproductive success. By analysing movements of 31 satellite- and GPS-tracked gull and tern populations belonging to 14 species in Europe and North America, we examined the occurrence and factors explaining prospecting by actively breeding birds. Prospecting in active breeders occurred in 85.7% of studied species, across 61.3% of sampled populations. Prospecting was more common in populations with frequent inter-annual changes of breeding sites and among females. These results contradict theoretical models which predict that prospecting is expected to evolve in relatively predictable and stable environments. More long-term tracking studies are needed to identify factors affecting patterns of prospecting in different environments and understand the consequences of prospecting on fitness at the individual and population level.

A Method for Long-Term Target Anti-Interference Tracking Combining Deep Learning and CKF for LARS Tracking and Capturing

Autonomous underwater vehicles (AUV) recycling in an underwater environment is particularly challenging due to the continuous exploitation of marine resources. AUV recycling via visual technology is the primary method. However, the current visual technology is limited by harsh sea conditions and has problems, such as poor tracking and detection. To solve these problems, we propose a long-term target anti-interference tracking (LTAT) method, which integrates Siamese networks, You Only Look Once (YOLO) networks and online learning ideas. Meanwhile, we propose using the cubature Kalman filter (CKF) for optimization and prediction of the position. We constructed a launch and recovery system (LARS) tracking and capturing the AUV. The system consists of the following parts: First, images are acquired via binocular cameras. Next, the relative position between the AUV and the end of the LARS was estimated based on the pixel positions of the tracking AUV feature points and binocular camera data. Finally, using a discrete proportion integration differentiation (PID) method, the LARS is controlled to capture the moving AUV via a CKF-optimized position. To verify the feasibility of our proposed system, we used the robot operating system (ROS) platform and Gazebo software to simulate the system for experiments and visualization. The experiment demonstrates that in the tracking process when the AUV makes a sinusoidal motion with an amplitude of 0.2 m in the three-dimensional space and the relative distance between the AUV and LARS is no more than 1 m, the estimated position error of the AUV does not exceed 0.03 m. In the capturing process, the final capturing error is about 28 mm. Our results verify that our proposed system has high robustness and accuracy, providing the foundation for future AUV recycling research.

Effective Local and Global Search for Fast Long-Term Tracking.

Compared with short-term tracking, long-term tracking remains a challenging task that usually requires the tracking algorithm to track targets within a local region and re-detect targets over the entire image. However, few works have been done and their performances have also been limited. In this paper, we present a novel robust and real-time long-term tracking framework based on the proposed local search module and re-detection module. The local search module consists of an effective bounding box regressor to generate a series of candidate proposals and a target verifier to infer the optimal candidate with its confidence score. For local search, we design a long short-term updated scheme to improve the target verifier. The verification capability of the tracker can be improved by using several templates updated at different times. Based on the verification scores, our tracker determines whether the tracked object is present or absent and then chooses the tracking strategies of local or global search, respectively, in the next frame. For global re-detection, we develop a novel re-detection module that can estimate the target position and target size for a given base tracker. We conduct a series of experiments to demonstrate that this module can be flexibly integrated into many other tracking algorithms for long-term tracking and that it can improve long-term tracking performance effectively. Numerous experiments and discussions are conducted on several popular tracking datasets, including VOT, OxUvA, TLP, and LaSOT. The experimental results demonstrate that the proposed tracker achieves satisfactory performance with a real-time speed. Code is available at https://github.com/difhnp/ELGLT.

A lysosome-targeted triazole near-infrared cyanine fluorescent probe for in vivo long-term cell tracking.

In vivo visualization of cell migration and engraftment in small animals provides crucial information for the development and clinical translation of cell-based therapies. Therefore, a good quality near-infrared (NIR) fluorescent probe with high optical properties and excellent cellular retention ability is desired for in vivo cell tracking. Herein, we designed and synthesized a lysosome-targeted triazole NIR cyanine fluorescent probe, named IR780-NT-NH2, for in vivo long-term cell tracking. For the design, the heptamethine cyanine dye IR780 was used as the NIR fluorescent skeleton to ensure that the absorption and emission wavelengths fall within the NIR window. The substituent N-triazole group endowed the probe with high photostability and brightness. It has a quantum yield of 17.3% and the brightness remained above 85% after continuous illumination for 30 min. Due to the primary amine docking group, IR780-NT-NH2 has excellent lysosomal targeting and retention abilities as it becomes protonated in an acidic environment. The strong signal strength of IR780-NT-NH2 was maintained in well-shaped cells after an additional 12 h incubation. Moreover, this NIR probe exhibited ideal cellular permeability and biosafety. Finally, we realized long-term cell tracking with IR780-NT-NH2 labeled PC-3 cells using a NIR imaging system. The present study provides evidence that IR780-NT-NH2 exhibits ideal optical properties, excellent cellular permeation and retention, and good biosafety, which are useful for in vivo long-term observation of cells, and thus it shows promising potential for visualization in cell-based therapy.

A Novel AD-PDA-BACF Algorithm for Real-Time Moving Target Shadow Tracking Using ViSAR Imagery

Detection and tracking using video synthetic aperture radar (ViSAR) have attracted a great deal of attention in recent years due to its ability to produce high-resolution videos for regions of interest. In this work, we have chosen the background-aware correlation filter (BACF) as a key algorithm due to its superior performance in real-time tracking scenarios. Dim and small shadows with weak visual features, time-varying shadows, and complex environments pose serious challenges to the target tracking problem using ViSAR videos. These factors lead to a multipeak problem in the BACF and many other correlation filter-based algorithms. As a result, incorrect target detection, template model contamination, and tracker drift or failure during long-term tracking can occur. In this work, we propose a novel appearance-distance information-assisted probabilistic data association (AD-PDA) algorithm to tackle the multipeak problem. Based on the correlation outputs of the BACF, the AD-PDA algorithm selects multiple peak locations as validated measurements. By exploiting the appearance-distance probability distribution functions, the AD-PDA algorithm calculates the mixed appearance-distance association weights and estimates target states accurately. Furthermore, we propose an efficient AD-PDA-BACF algorithm that can track targets accurately by combining the AD-PDA and BACF algorithms. This study conducts experiments using two public ViSAR video datasets released by the Sandia National Laboratory. Our results demonstrate that the proposed algorithm outperforms several state-of-the-art algorithms in tracking dim and small targets in terms of tracking accuracy, success rate, and tracking speed.

The Modified Cubature Kalman Filter for Relative Navigation of Space Target Tracking

At present, the trend of improving the mobility of fast acquisition, long-term tracking and high-precision control has been formed in China. The continuous observation ability of non-cooperative targets and good imaging performance in motion are important trends in the development of optical remote sensing technology. Aiming at the high-precision observation and real-time tracking requirements of high orbit space satellites, this paper studies the high-precision relative navigation of space non cooperative targets. In order to solve the problem that the estimation accuracy of Cubature Kalman filter (CKF) decreases when the system visibility is low, a modified Cubature Kalman filter (MCKF) based on the visibility is proposed. This algorithm defines a system visibility characterization method based on the error gain matrix of the filtering process, and proposes the visibility scaling parameter based on this method, The filter gain covariance matrix is adjusted online, so that the algorithm can adjust the weight of state prediction and system observation online according to the observability of the current time. Numerical simulation shows that compared with CKF, the estimation accuracy of MCKF is improved by about 4 times, and MCKF stabilizes faster and has higher accuracy.

Meso pyridinium BODIPY-based long wavelength infrared mitochondria-targeting fluorescent probe with high photostability.

Mito-tracker deep red (MTDR) as a commercially available mitochondria-targeting probe was easily bleached upon imaging. We designed and synthesized a family of meso-pyridinium BODIPY and introduced lipophilic methyl or benzyl as the head moiety to develop a mitochondria-targeting deep red probe. Moreover, we changed the substitution of the 3,5-phenyl moieties with the methoxy or methoxyethoxyethyl group to balance hydrophilicity. The designed BODIPY dyes possessed long absorption and good fluorescence emission. Among them, meso ortho-pyridinium BODIPYs with benzyl head and glycol substitution on phenyl moiety (3h) with favorable Stokes shift were found to have the best mitochondrial targeting performance. 3h was easily uptaken by cells and was less toxic and more photostable than MTDR. An immobilizable probe (3i) was further developed, and nice mitochondria targeting properties under the damaging condition of mitochondria membrane potential were maintained. BODIPY 3h or 3i may become alternative long-wavelength mitochondria targeting probes apart from MTDR and be suitable for long-term mitochondrial tracking studies.

Inorganic Nanoparticles-Based Systems in Biomedical Applications of Stem Cells: Opportunities and Challenges.

Stem cells (SC) are a kind of cells with self renewing ability and multipotent differentiation, which can differentiate into many types of cells such as osteoblast, chondrocyte, neurocyte to treat disease like osteoporosis, osteoarthritis and Alzheimer's disease. Despite the development of novel methods for inducing cell differentiation, the inefficiency and complexity of controlling differentiation of stem cells remain a serious challenge, which necessary to develop a new and alternative approach for effectively controlling the direction of stem cell differentiation in vitro and in vivo in stem cells therapy. Recent advancement in nanotechnology for developing a new class of inorganic nanoparticles that exhibit unique chemical and physical properties holds promise for the treatment of stem cells. Over the last decade, inorganic nanoparticle-based approaches against stem cells have been directed toward developing nanoparticles with drug delivery, or utilizing nanoparticles for controlled cell behaviors, and applying nanoparticles for inducing cell differentiation directly. In addition, a strategy to functionalize inorganic nanoparticles as a nanoprobe towards enhanced penetration through near-infrared light or nuclear magnetic resonance has been receiving considerable interest by means of long-term tracking stem cell in vivo. This review summarizes and highlights the recent development of these inorganic nanoparticle-based approaches as potential therapeutics for controlling differentiation of stem cells and so on for stem cell therapy, along with current opportunities and challenges that need to be overcome for their successful clinical translation.

Research on AGC control performance optimization and application of 135MW coal-fired unit

This paper studies the corresponding performance optimization of unit coordinated control system. Combined with the actual operation of the unit, targeted optimization strategies are formulated and implemented for the main parameters such as active power, main steam pressure, feed water flow, main steam temperature and furnace pressure. After long-term tracking of operation and repeated adjustment of relevant control parameters, a more reasonable optimization effect is finally obtained, and the regulation performance of the unit coordinated control system meets the AGC input conditions.

Persistent olfactory learning deficits during and post-COVID-19 infection.

Quantifying olfactory impairments can facilitate early detection of Coronavirus disease 2019 (COVID-19). Despite being a debated topic, many reports provide evidence for the neurotropism of SARS-CoV-2. However, a sensitive, specific, and accurate non-invasive method for quantifying persistent neurological impairments is missing to date. To quantify olfactory detectabilities and neurocognitive impairments in symptomatic COVID-19 patients during and post-infection periods, we used a custom-built olfactory-action meter (OAM) providing accurate behavioral readouts. Ten monomolecular odors were used for quantifying olfactory detectabilities and two pairs of odors were employed for olfactory matching tests. We followed cohorts of healthy subjects, symptomatic patients, and recovered subjects for probing olfactory learning deficits, before the Coronavirus Omicron variant was reported in India. Our method identifies severe and persistent olfactory dysfunctions in symptomatic patients during COVID-19 infection. Symptomatic patients and recovered subjects showed significant olfactory learning deficits during and post-infection periods, 4-18 months, in comparison to healthy subjects. On comparing olfactory fitness, we found differential odor detectabilities and olfactory function scores in symptomatic patients and asymptomatic carriers. Our results indicate probable long-term neurocognitive deficits in COVID-19 patients imploring the necessity of long-term tracking during post-infection period. Differential olfactory fitness observed in symptomatic patients and asymptomatic carriers demand probing mechanisms of potentially distinct infection routes.

Design and synthesis of photostable triphenylamine based neutral AIE nano luminogens: specific and long-term tracking of mitochondria in cells.

With the increasing dependence on fluorescence bioimaging, luminogens with aggregation-induced emission (AIE) properties have gained significant attention due to their excellent photostabilization, minimal photobleaching, high reliability, and superior biocompatibility. Since mitochondria are crucial subcellular organelles in eukaryotic cells with important biological functions, organelle-specific AIE emitters with distinct functions have been highly sought after, but with limited success using simple synthetic methods. Here, we describe a strategy for synthesizing two triphenylamine (TPA) based acrylonitriles, tethered to different donor groups, TPA and phenothiazine (PTZ), respectively, with superior AIE properties using Suzuki coupling. We conducted a systematic and detailed experimental analysis of the structural characteristics of both AIE luminogens, which exhibited excellent photostability, a large Stokes shift, and bright solid-state emission. A cell viability study carried out with F1 and F2 dyes revealed that both luminogens exhibited excellent biocompatibility. Based on fluorescence experiments, F2 displayed excellent AIE characteristics, permeability, biocompatibility, and photostability compared to rhodamine 123, allowing it to selectively stain and track mitochondria in cancer cells over an extended period of time. The Pearson correlation coefficient of F2 and rhodamine 123 was estimated to have an r-value of 0.99. Our findings are expected to provide insight into the synthesis of an extensive archive of AIE-based acrylonitriles with fascinating properties for mitochondrial staining.

In Vivo Analysis of Heterogeneous Extracellular Vesicles Using a Red-Shifted Bioluminescence Resonance Energy Transfer Reporter Protein.

Current methods for characterizing the biodistribution of extracellular vesicles (EVs) are not sensitive enough to track EVs in vivo, despite significant advances over the past decade. Commonly used lipophilic fluorescent dyes are convenient, but lack specificity and yield inaccurate spatiotemporal images in the long-term tracking of EVs. In contrast, protein-based fluorescent or bioluminescent EV reporters have more accurately revealed their distribution in cells and mouse models. Here, we describe a red-shifted bioluminescence resonance energy transfer (BRET) EV reporter, PalmReNL, to analyze the trafficking of small EVs (<200nm; sEVs) and medium/large EVs (>200nm; m/lEVs) in mice. Its advantages are that (i) background signals in bioluminescence imaging (BLI) are negligible and (ii) the photons PalmReNL emits have spectral wavelengths longer than 600nm and can more efficiently penetrate tissues than reporters emitting shorter wavelength light.

A Novel Method of Situ Measurement Algorithm for Oudemansiella raphanipies Caps Based on YOLO v4 and Distance Filtering

Oudemansiella raphanipies has gradually gained more and more popularity in the market for its delicious taste, while enhancing human immunity and regulating human body functions as well. To achieve the high-throughput and automatic monitoring of the phenotypes of Oudemansiella raphanipies, a novel method, based on YOLO v4 and Distance Filter (DF), was proposed for high-precision diameter estimation of Oudemansiella raphanipies caps. To begin with, a dataset of Oudemansiella raphanipies was established by the laboratory cultivation and collection of factory samples. The improved YOLO v4 target detection model with added CBAM modules to each convolution block in the backbone was trained to locate the caps and, thus, obtain an approximate bounding box. Secondly, the approximate contour of the cap was gained through the H component, canny edge detection operators, and distance filtering to conduct the noise elimination. Finally, the center of the fitted circle and its accurate contour of the cap could be obtained by the constrained least square method, and the diameter of the fitted circle was estimated by the calibration data. The results of practical tests showed that this method achieved an accuracy of 95.36% in recognizing Oudemansiella raphanipies caps in the growing bed, and the fitting effect of caps was superior to Circle Hough Transform (CHT), the least square method (LS), and Ransac, with no manual adjustment on parameters. Compared with the manual measurement, the mean absolute error (MAE) of this method was 0.77 mm, the coefficient of determination (R2) was 0.95, and the root mean square error (RMSE) was 0.96 mm. Therefore, the model had high-cost performance and could meet the needs of continuous and long-term tracking of the cap shape of Oudemansiella raphanipies, providing the basis for future high-throughput breeding and machine picking.

Long-term tracking with transformer and template update

Aiming at the tracking failure due to the disappearance of the target in the long-term target tracking process, this paper proposes a long-term target tracking network based on the visual transformer and template update. First of all, we construct a feature extraction network based on the transformer and adopt a knowledge distillation strategy to improve the effectiveness of the network for global feature extraction. Secondly, in the modeling transformer, the target features are fully fused with the search area features by using encoder, and the position information in the target query is learned by the decoder. Then, target predictions are performed on the information from the encoder–decoder to obtain tracking results. Meanwhile, we design a score head model to judge the validity of the dynamic template of the current frame before tracking in the next frame. We select the appropriate dynamic template for the tracking of the next frame according to the score result. In this paper, we performed extensive experiments on LaSOT, VOT2021-LT, TrackingNet, TLP, and UAV123 datasets, and the experimental results prove the effectiveness of our method. In particular, it exceeds STARK by 0.8 % (F score) on VOT2021-LT, 1.0 % (S score) on LaSOT, and TrackingNet exceed STARK by 1.1 % (NP score), which also demonstrates the superiority of the method in this paper.

Mechano-fluorescence actuation in single synaptic vesicles with a DNA framework nanomachine.

Biomimetic machines that can convert mechanical actuation to adaptive coloration in a manner analogous to cephalopods have found widespread applications at various length scales. At the nanoscale, a transmutable nanomachine with adaptive colors that can sense and mediate cellular or intracellular interactions is highly desirable. Here, we report the design of a DNA framework nanomachine (DFN) that can autonomously change shape in response to pH variations in single synaptic vesicles, which, in turn, displays adaptive fluorescent colors with a mechano-fluorescence actuation mechanism. To construct a DFN, we used a tetrahedral DNA nanostructure as the framework to incorporate an embedded pH-responsive, i-motif sequence tagged with a Förster resonance energy transfer pair and an affinity cholesterol moiety targeting vesicular membranes. We found that endocytosed DFNs are individually trapped in single endocytic vesicles in living synaptic cells due to the size-exclusion effect. The adaptive fluorescence coloration of DFNs enabled single-vesicle quantification of resting pH values in a processive manner, allowing long-term tracking of the exocytosis and fusion dynamics in intracellular processes and cell-cell communications.