Multi-template matching: a versatile tool for object-localization in microscopy images

Dysregulation of N-terminal acetylation causes cardiac arrhythmia and cardiomyopathy

N-terminal-acetyltransferases including NAA10 catalyze N-terminal acetylation (Nt-acetylation), an evolutionarily conserved co-translational modification. Little is known about the role of Nt-acetylation in cardiac homeostasis. To gain insights, we studied a novel NAA10 variant (p.R4S) segregating with QT-prolongation, cardiomyopathy and developmental delay in a large kindred. Here we show that the NAA10-R4S mutation reduced enzymatic activity, decreased expression levels of NAA10/NAA15 proteins, and destabilized the enzymatic complex NatA. In NAA10R4S/Y-iPSC-CMs, dysregulation of the late sodium and slow rectifying potassium currents caused severe repolarization abnormalities, consistent with clinical QT prolongation. Engineered heart tissues generated from NAA10R4S/Y-iPSC-CMs had significantly decreased contractile force and sarcomeric disorganization, consistent with the pedigree's cardiomyopathic phenotype. We identified small molecule and genetic therapies that normalized the phenotype of NAA10R4S/Y-iPSC-CMs. Our study defines novel roles of Nt-acetylation in cardiac regulation and delineates mechanisms underlying QT prolongation, arrhythmia, and cardiomyopathy caused by NAA10 dysfunction.

Efficient and reproducible generation of human iPSC-derived cardiomyocytes and cardiac organoids in stirred suspension systems

Human iPSC-derived cardiomyocytes (hiPSC-CMs) have proven invaluable for cardiac disease modeling and regeneration. Challenges with quality, inter-batch consistency, cryopreservation and scale remain, reducing experimental reproducibility and clinical translation. Here, we report a robust stirred suspension cardiac differentiation protocol, and we perform extensive morphological and functional characterization of the resulting bioreactor-differentiated iPSC-CMs (bCMs). Across multiple different iPSC lines, the protocol produces 1.2E6/mL bCMs with ~94% purity. bCMs have high viability after cryo-recovery (>90%) and predominantly ventricular identity. Compared to standard monolayer-differentiated CMs, bCMs are more reproducible across batches and have more mature functional properties. The protocol also works with magnetically stirred spinner flasks, which are more economical and scalable than bioreactors. Minor protocol modifications generate cardiac organoids fully in suspension culture. These reproducible, scalable, and resource-efficient approaches to generate iPSC-CMs and organoids will expand their applications, and our benchmark data will enable comparison to cells produced by other cardiac differentiation protocols.

Efficient and reproducible generation of human iPSC-derived cardiomyocytes using a stirred bioreactor

In the last decade human iPSC-derived cardiomyocytes (hiPSC-CMs) proved to be valuable for cardiac disease modeling and cardiac regeneration, yet challenges with scale, quality, inter-batch consistency, and cryopreservation remain, reducing experimental reproducibility and limiting clinical translation. Here, we report a robust cardiac differentiation protocol that uses Wnt modulation and a stirred suspension bioreactor to produce on average 124 million hiPSC-CMs with >90% purity using a variety of hiPSC lines (19 differentiations; 10 iPSC lines). After controlled freeze and thaw, bioreactor-derived CMs (bCMs) showed high viability (>90%), interbatch reproducibility in cellular morphology, function, drug response and ventricular identity, which was further supported by single cell transcriptomes. bCMs on microcontact printed substrates revealed a higher degree of sarcomere maturation and viability during long-term culture compared to monolayer-derived CMs (mCMs). Moreover, functional investigation of bCMs in 3D engineered heart tissues showed earlier and stronger force production during long-term culture, and robust pacing capture up to 4 Hz when compared to mCMs. bCMs derived from this differentiation protocol will expand the applications of hiPSC-CMs by providing a reproducible, scalable, and resource efficient method to generate cardiac cells with well-characterized structural and functional properties superior to standard mCMs.

Identification of side effects of COVID-19 drug candidates on embryogenesis using an integrated zebrafish screening platform

Drug repurposing is an important strategy in COVID-19 treatment, but many clinically approved compounds have not been extensively studied in the context of embryogenesis, thus limiting their administration during pregnancy. Here we used the zebrafish embryo model organism to test the effects of 162 marketed drugs on cardiovascular development. Among the compounds used in the clinic for COVD-19 treatment, we found that Remdesivir led to reduced body size and heart functionality at clinically relevant doses. Ritonavir and Baricitinib showed reduced heart functionality and Molnupiravir and Baricitinib showed effects on embryo activity. Sabizabulin was highly toxic at concentrations only 5 times higher than Cmax and led to a mean mortality of 20% at Cmax. Furthermore, we tested if zebrafish could be used as a model to study inflammatory response in response to spike protein treatment and found that Remdesivir, Ritonavir, Molnupiravir, Baricitinib as well as Sabizabulin counteracted the inflammatory response related gene expression upon SARS-CoV-2 spike protein treatment. Our results show that the zebrafish allows to study immune-modulating properties of COVID-19 compounds and highlights the need to rule out secondary defects of compound treatment on embryogenesis. All results are available on a user friendly web-interface https://share.streamlit.io/alernst/covasc_dataapp/main/CoVasc_DataApp.py that provides a comprehensive overview of all observed phenotypic effects and allows personalized search on specific compounds or group of compounds. Furthermore, the presented platform can be expanded for rapid detection of developmental side effects of new compounds for treatment of COVID-19 and further viral infectious diseases.

Functional trajectories during innate spinal cord repair

Adult zebrafish are capable of anatomical and functional recovery following severe spinal cord injury. Axon growth, glial bridging and adult neurogenesis are hallmarks of cellular regeneration during spinal cord repair. However, the correlation between these cellular regenerative processes and functional recovery remains to be elucidated. Whereas the majority of established functional regeneration metrics measure swim capacity, we hypothesize that gait quality is more directly related to neurological health. Here, we performed a longitudinal swim tracking study for 60 individual zebrafish spanning 8 weeks of spinal cord regeneration. Multiple swim parameters as well as axonal and glial bridging were integrated. We established rostral compensation as a new gait quality metric that highly correlates with functional recovery. Tensor component analysis of longitudinal data supports a correspondence between functional recovery trajectories and neurological outcomes. Moreover, our studies predicted and validated that a subset of functional regeneration parameters measured 1 to 2 weeks post-injury is sufficient to predict the regenerative outcomes of individual animals at 8 weeks post-injury. Our findings established new functional regeneration parameters and generated a comprehensive correlative database between various functional and cellular regeneration outputs.

LED Chip Defect Detection Method Based on a Hybrid Algorithm

LED is an extremely important energy-saving lighting products, which has greatly facilitated human life. Meanwhile, it also makes a positive contribution to global carbon neutrality and carbon peaking. Defect detection is a vital part of the production process to control the quality of LED chips. The traditional methods use a microscope for manual visual inspection, which is time-consuming and has inconsistent testing standards, low efficiency, and other deficiencies. To solve these problems, a hybrid algorithm based on geometric computation and a convolutional neural network is proposed for LED chip defect detection. The method takes advantage of the dimensionality reduction of geometric computation to perform coarse detection of defects on preprocessed chip lithography graphs in the form of grid segmentation, which realizes fast coarse screening of large-scale chip samples and reduces postcomputational costs. The convolutional neural network model is used for the secondary fine detection of “suspected defective” chips after geometric coarse screening, and the SPP (spatial pyramid pooling) network model is improved by directly introducing the original feature map into the SPP pooling layer for summation to enhance the global and local feature information of the output feature map. Furthermore, we construct an LED chip image acquisition platform using a high-frequency multimagnification zoom lens, collect training samples of defective chips, and increase the number of samples through image processing techniques. The research introduces the R-CNN, SDD, and YOLO methods to evaluate the superiority of our method in a number of experiments. The experimental results show that our algorithm proposed in this paper has an average precision (AP) of 96.7% for large-scale chip detection with a low defect rate. Compared with other methods, the testing mean average precision (mAP) is 10.39% higher than traditional YOLO v2. The testing mIoU is also 3.63% higher than traditional YOLO v5, the detection speed is also significantly improved, and it has good robustness.

Functional Trajectories during innate spinal cord repair

Adult zebrafish are capable of anatomical and functional recovery following severe spinal cord injury. Axon growth, glial bridging and adult neurogenesis are hallmarks of cellular regeneration during spinal cord repair. However, the correlation between these cellular regenerative processes and functional recovery remains to be elucidated. Whereas the majority of established functional regeneration metrics measure swim capacity, we hypothesize that gait quality is more directly related to neurological health. Here, we performed a longitudinal swim tracking study for sixty individual zebrafish spanning eight weeks of spinal cord regeneration. Multiple swim parameters as well as axonal and glial bridging were integrated. We established rostral compensation as a new gait quality metric that highly correlates with functional recovery. Tensor component analysis of longitudinal data supports a correspondence between functional recovery trajectories and neurological outcomes. Moreover, our studies predicted and validated that a subset of functional regeneration parameters measured 1 to 2 weeks post-injury is sufficient to predict the regenerative outcomes of individual animals at 8 weeks post-injury. Our findings established new functional regeneration parameters and generated a comprehensive correlative database between various functional and cellular regeneration outputs.

Determination of the Physiological Age in Two Tephritid Fruit Fly Species Using Artificial Intelligence

The Mexican fruit fly (Anastrepha ludens, Loew, Diptera: Tephritidae) and the Mediterranean fruit fly (Ceratitis capitata, Wiedemann, Diptera: Tephritidae) are among the world's most damaging pests affecting fruits and vegetables. The Sterile Insect Technique (SIT), which consists in the mass-production, irradiation, and release of insects in affected areas is currently used for their control. The appropriate time for irradiation, one to two days before adult emergence, is determined through the color of the eyes, which varies according to the physiological age of pupae. Age is checked visually, which is subjective and depends on the technician's skill. Here, image processing and Machine Learning techniques were implemented as a method to determine pupal development using eye color. First, Multi Template Matching (MTM) was used to correctly crop the eye section of pupae for 96.2% of images from A. ludens and 97.5% of images for C. capitata. Then, supervised Machine Learning algorithms were applied to the cropped images to classify the physiological age according to the color of the eyes. Algorithms based on Inception v1, correctly identified the physiological age of maturity at 2 d before emergence, with a 75.0% accuracy for A. ludens and 83.16% for C. capitata, respectively. Supervised Machine Learning algorithms based on Neural Networks could be used as support in determining the physiological age of pupae from images, thus reducing human error and uncertainty in decisions as when to irradiate. The development of a user interface and an automatization process could be further developed, based on the data obtained on this study.

Time-domain ultrasound as prior information for frequency-domain compressive ultrasound for intravascular cell detection: A 2-cell numerical model

This study proposes a new method for the detection of a weak scatterer among strong scatterers using prior-information ultrasound (US) imaging. A perfect application of this approach is in vivo cell detection in the bloodstream, where red blood cells (RBCs) serve as identifiable strong scatterers. In vivo cell detection can help diagnose cancer at its earliest stages, increasing the chances of survival for patients. This work combines time-domain US with frequency-domain compressive US imaging to detect a 20-μ MCF-7 circulating tumor cell (CTC) among a number of RBCs within a simulated venule inside the mouth. The 2D image reconstructed from the time-domain US is employed to simulate the reflected and scattered pressure field from the RBCs, which is then measured at the location of the receivers. The RBCs are tagged one time by a human operator and another time, automatically, by template-based computer vision. Next, the resulting signal from the RBCs is subtracted from the measured total signal in frequency domain to generate the scattered-field data, coming from the CTC alone. Feeding that signal and the background pressure field into a norm-one-based compressive sensing code enables detecting the CTC at various locations. As errors could arise in determining the location of the RBCs and their acoustic properties in the real world, small errors (up to 10% in the former and 5% in the latter) are purposefully introduced to the model, to which the proposed method is shown to be resilient. Localization errors are smaller than 12 μ when a human tags the RBCs and smaller than 25 μ when computer vision is applied. Despite its limitations, this study, for the first time, reports the results of combining two US modalities aimed at cell detection and introduces a unique and useful application for ultrahigh-frequency US imaging. It should be noted that this method can be used in detecting weak scatterers with ultrasound waves in other applications as well.

Spatial distribution of dust density wave properties in fluid complex plasmas

Complex plasmas consist of microparticles embedded in a low-temperature plasma and allow investigating various effects by tracing the motion of these microparticles. Dust density waves appear in complex plasmas as self-excited acoustic waves in the microparticle fluid at low neutral gas pressures. Here we show that various properties of these waves depend on the position of the microparticle cloud with respect to the plasma sheath and explain this finding in terms of the underlying ion-drift instability. These results may be helpful in better understanding the propagation of dust density waves in complex plasmas and beyond, for instance, in astrophysical dusty plasmas.

Stealth Effect of Short Polyoxazolines in Graft Copolymers: Minor Changes of Backbone End Group Determine Liver Cell-Type Specificity

Dye-loaded micelles of 10 nm diameter formed from amphiphilic graft copolymers composed of a hydrophobic poly(methyl methacrylate) backbone and hydrophilic poly(2-ethyl-2-oxazoline) side chains with a degree of polymerization of 15 were investigated concerning their cellular interaction and uptake in vitro as well as their interaction with local and circulating cells of the reticuloendothelial system in the liver by intravital microscopy. Despite the high molar mass of the individual macromolecules (M_n ≈ 20 kg mol^-1), backbone end group modification by attachment of a hydrophilic anionic fluorescent probe strongly affected the in vivo performance. To understand these effects, the end group was additionally modified by the attachment of four methacrylic acid repeating units. Although various micelles appeared similar in dynamic light scattering and cryo-transmission electron microscopy, changes in the micelles were evident from principal component analysis of the Raman spectra. Whereas an efficient stealth effect was found for micelles formed from polymers with anionically charged or thiol end groups, a hydrophobic end group altered the micelles' structure sufficiently to adapt cell-type specificity and stealth properties in the liver.