BACKGROUND: Manual analysis of (mini-)rhizotron (MR) images is tedious. Several methods have been proposed for semantic root segmentation based on homogeneous, single-source MR datasets. Recent advances in deep learning (DL) have enabled automated feature extraction, but comparisons of segmentation accuracy, false positives and transferability are virtually lacking. Here we compare six state-of-the-art methods and propose two improved DL models for semantic root segmentation using a large MR dataset with and without augmented data. We determine the performance of the methods on a homogeneous maize dataset, and a mixed dataset of > 8 species (mixtures), 6 soil types and 4 imaging systems. The generalisation potential of the derived DL models is determined on a distinct, unseen dataset. RESULTS: The best performance was achieved by the U-Net models; the more complex the encoder the better the accuracy and generalisation of the model. The heterogeneous mixed MR dataset was a particularly challenging for the non-U-Net techniques. Data augmentation enhanced model performance. We demonstrated the improved performance of deep meta-architectures and feature extractors, and a reduction in the number of false positives. CONCLUSIONS: Although correction factors are still required to match human labelled root lengths, neural network architectures greatly reduce the time required to compute the root length. The more complex architectures illustrate how future improvements in root segmentation within MR images can be achieved, particularly reaching higher segmentation accuracies and model generalisation when analysing real-world datasets with artefacts-limiting the need for model retraining.

• Keywords
• Automatic image segmentation, Data augmentation, Deep learning, False positives, Fine roots, Image processing, Minirhizotron, Neural networks, Root segmentation, U-Net,
• Publication type
• Journal Article MeSH

Image-based root phenotyping technologies, including the minirhizotron (MR), have expanded our understanding of the in situ root responses to changing environmental conditions. The conventional manual methods used to analyze MR images are time-consuming, limiting their implementation. This study presents an adaptation of our previously developed convolutional neural network-based models to estimate the total (cumulative) root length (TRL) per MR image without requiring segmentation. Training data were derived from manual annotations in Rootfly, commonly used software for MR image analysis. We compared TRL estimation with 2 models, a regression-based model and a detection-based model that detects the annotated points along the roots. Notably, the detection-based model can assist in examining human annotations by providing a visual inspection of roots in MR images. The models were trained and tested with 4,015 images acquired using 2 MR system types (manual and automated) and from 4 crop species (corn, pepper, melon, and tomato) grown under various abiotic stresses. These datasets are made publicly available as part of this publication. The coefficients of determination (R2), between the measurements made using Rootfly and the suggested TRL estimation models were 0.929 to 0.986 for the main datasets, demonstrating that this tool is accurate and robust. Additional analyses were conducted to examine the effects of (a) the data acquisition system and thus the image quality on the models' performance, (b) automated differentiation between images with and without roots, and (c) the use of the transfer learning technique. These approaches can support precision agriculture by providing real-time root growth information.

• Publication type
• Journal Article MeSH

The ability of plants to sense and orient their root growth towards gravity is studied in many laboratories. It is known that manual analysis of image data is subjected to human bias. Several semi-automated tools are available for analysing images from flatbed scanners, but there is no solution to automatically measure root bending angle over time for vertical-stage microscopy images. To address these problems, we developed ACORBA, which is an automated software that can measure root bending angle over time from vertical-stage microscope and flatbed scanner images. ACORBA also has a semi-automated mode for camera or stereomicroscope images. It represents a flexible approach based on both traditional image processing and deep machine learning segmentation to measure root angle progression over time. As the software is automated, it limits human interactions and is reproducible. ACORBA will support the plant biologist community by reducing labour and increasing reproducibility of image analysis of root gravitropism.

• Keywords
• UNET, deep machine learning, image segmentation, python, root gravitropism,
• Publication type
• Journal Article MeSH

Accurate segmentation of biomedical time-series, such as intracardiac electrograms, is vital for understanding physiological states and supporting clinical interventions. Traditional rule-based and feature engineering approaches often struggle with complex clinical patterns and noise. Recent deep learning advancements offer solutions, showing various benefits and drawbacks in segmentation tasks. This study evaluates five segmentation algorithms, from traditional rule-based methods to advanced deep learning models, using a unique clinical dataset of intracardiac signals from 100 patients. We compared a rule-based method, a support vector machine (SVM), fully convolutional semantic neural network (UNet), region proposal network (Faster R-CNN), and recurrent neural network for electrocardiographic signals (DENS-ECG). Notably, Faster R-CNN has never been applied to 1D signals segmentation before. Each model underwent Bayesian optimization to minimize hyperparameter bias. Results indicated that deep learning models outperformed traditional methods, with UNet achieving the highest segmentation score of 88.9 % (root mean square errors for onset and offset of 8.43 ms and 7.49 ms), closely followed by DENS-ECG at 87.8 %. Faster R-CNN and SVM showed moderate performance, while the rule-based method had the lowest accuracy (77.7 %). UNet and DENS-ECG excelled in capturing detailed features and handling noise, highlighting their potential for clinical application. Despite greater computational demands, their superior performance and diagnostic potential support further exploration in biomedical time-series analysis.

• Keywords
• DENS-ECG, Electrophysiology Study, Faster R-CNN, Rule-based Delineation, Support Vector Machines, Time-series Segmentation, U-Net,
• MeSH
• Algorithms MeSH
• Bayes Theorem MeSH
• Deep Learning MeSH
• Electrocardiography * methods   MeSH
• Humans MeSH
• Neural Networks, Computer MeSH
• Signal Processing, Computer-Assisted * MeSH
• Support Vector Machine MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

Flax (Linum usitatissimum L.) is an important crop for the production of oil and fiber. In vitro manipulations of flax are used for genetic improvement and breeding while improvements in adventitious root formation are important for biotechnological programs focused on regeneration and vegetative propagation of genetically valuable plant material. Additionally, flax hypocotyl segments possess outstanding morphogenetic capacity, thus providing a useful model for the investigation of flax developmental processes. Here, we investigated the crosstalk between hydrogen peroxide and auxin with respect to reprogramming flax hypocotyl cells for root morphogenetic development. Exogenous auxin induced the robust formation of adventitious roots from flax hypocotyl segments while the addition of hydrogen peroxide further enhanced this process. The levels of endogenous auxin (indole-3-acetic acid; IAA) were positively correlated with increased root formation in response to exogenous auxin (1-Naphthaleneacetic acid; NAA). Histochemical staining of the hypocotyl segments revealed that hydrogen peroxide and peroxidase, but not superoxide, were positively correlated with root formation. Measurements of antioxidant enzyme activities showed that endogenous levels of hydrogen peroxide were controlled by peroxidases during root formation from hypocotyl segments. In conclusion, hydrogen peroxide positively affected flax adventitious root formation by regulating the endogenous auxin levels. Consequently, this agent can be applied to increase flax regeneration capacity for biotechnological purposes such as improved plant rooting.

• MeSH
• Antioxidants metabolism   MeSH
• Biotechnology MeSH
• Hypocotyl drug effects   growth & development   metabolism   MeSH
• Plant Roots drug effects   growth & development   metabolism   MeSH
• Indoleacetic Acids metabolism   MeSH
• Naphthaleneacetic Acids pharmacology   MeSH
• Flax drug effects   growth & development   metabolism   MeSH
• Hydrogen Peroxide metabolism   pharmacology   MeSH
• Cellular Reprogramming drug effects   MeSH
• Plant Growth Regulators metabolism   pharmacology   MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• 1-naphthaleneacetic acid MeSH Browser
• Antioxidants MeSH
• indoleacetic acid MeSH Browser
• Indoleacetic Acids MeSH
• Naphthaleneacetic Acids MeSH
• Hydrogen Peroxide MeSH
• Plant Growth Regulators MeSH

The anatomical position of the subarachnoid space (SAS) in relation to dorsal root ganglia (DRG) and penetration of tracer from the SAS into DRG were investigated. We used intrathecal injection of methylene blue to visualize the anatomical position of the SAS in relation to DRG and immunostaining of dipeptidyl peptidase IV (DPP-IV) for detecting arachnoid limiting the SAS. Intrathecal administration of fluorescent-conjugated dextran (fluoro-emerald; FE) was used to demonstrate direct communication between the SAS and DRG. Intrathecal injection of methylene blue and DPP-IV immunostaining revealed that SAS delimited by the arachnoid was extended up to the capsule of DRG in a fold-like recess that may reach approximately half of the DRG length. The arachnoid was found in direct contact to the neuronal body-rich area in the angle between dorsal root and DRG as well as between spinal nerve roots at DRG. Particles of FE were found in the cells of DRG capsule, satellite glial cells, interstitial space, as well as in small and medium-sized neurons after intrathecal injection. Penetration of FE from the SAS into the DRG induced an immune reaction expressed by colocalization of FE and immunofluorescence indicating antigen-presenting cells (MHC-II+), activated (ED1+) and resident (ED2+) macrophages, and activation of satellite glial cells (GFAP+). Penetration of lumbar-injected FE into the cervical DRG was greater than that into the lumbar DRG after intrathecal injection of FE into the cisterna magna. Our results demonstrate direct communication between DRG and cerebrospinal fluid in the SAS that can create another pathway for possible propagation of inflammatory and signaling molecules from DRG primary affected by peripheral nerve injury into DRG of remote spinal segments.

• Keywords
• Cerebrospinal fluid, Dorsal root ganglia, Fluoro-emerald, Immunohistochemistry, Macrophages, Subarachnoid space,
• MeSH
• Dextrans chemistry   MeSH
• Rats MeSH
• Spinal Cord chemistry   cytology   MeSH
• Cerebrospinal Fluid chemistry   cytology   MeSH
• Rats, Wistar MeSH
• Ganglia, Spinal chemistry   cytology   MeSH
• Subarachnoid Space chemistry   cytology   MeSH
• Animals MeSH
• Check Tag
• Rats MeSH
• Male MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Dextrans MeSH

BACKGROUND: Extensive surgical resection of the thoracic aorta in patients with type A aortic dissection (TAAD) is thought to reduce the risk of late aortic wall degeneration and the need for repeat aortic operations. OBJECTIVES: We evaluated the early and late outcomes after aortic root replacement and supracoronary ascending aortic replacement in patients with TAAD involving the aortic root. DESIGN: Retrospective, multicenter cohort study. METHODS: The outcomes after aortic root replacement and supracoronary ascending aortic replacement in patients with TAAD involving the aortic root, that is dissection flap located at least in one of the Valsava segments, were herein evaluated. In-hospital mortality, neurological complications, dialysis as well as 10-year repeat proximal aortic operation, and mortality were the outcomes of this study. RESULTS: Supracoronary ascending aortic replacement was performed in 198 patients and aortic root replacement in 215 patients. During a mean follow-up of 4.0 ± 4.0 years, 19 patients underwent 22 repeat procedures on the aortic root and/or aortic valve. No operative death occurred after these reinterventions. The risk of proximal aortic reoperation was significantly lower in patients who underwent aortic root replacement (5.5% vs 12.9%, adjusted subdistributional hazard ratio (SHR) 0.085, 95% CI 0.022-0.329). Aortic root replacement was associated with higher rates of in-hospital (14.4% vs 12.1%, adjusted odds ratio 2.192, 95% CI 1.000-4.807) and 10-year mortality (44.5% vs 30.4%, adjusted hazard ratio 2.216, 95% CI 1.338-3.671). Postoperative neurological complications and dialysis rates were comparable in the study groups. CONCLUSION: Among patients with TAAD involving the aortic root, its replacement was associated with a significantly lower rate of repeat proximal aortic operation of any type compared to supracoronary aortic replacement. Still, aortic root replacement seems to be associated with an increased risk of mortality in these patients. UNLABELLED: ClinicalTrials.gov: NCT04831073 (https://clinicaltrials.gov/study/NCT04831073).

• Keywords
• Bentall procedure, David procedure, aortic dissection, aortic root, reoperation, type A aortic dissection,
• MeSH
• Aortic Aneurysm, Thoracic * surgery   mortality   diagnostic imaging   MeSH
• Time Factors MeSH
• Blood Vessel Prosthesis Implantation * adverse effects   mortality   MeSH
• Aortic Dissection * surgery   mortality   MeSH
• Adult MeSH
• Risk Assessment MeSH
• Middle Aged MeSH
• Humans MeSH
• Hospital Mortality * MeSH
• Postoperative Complications * epidemiology   etiology   mortality   MeSH
• Reoperation MeSH
• Retrospective Studies MeSH
• Risk Factors MeSH
• Aged MeSH
• Treatment Outcome MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Multicenter Study MeSH
• Comparative Study MeSH

High-throughput root phenotyping in the soil became an indispensable quantitative tool for the assessment of effects of climatic factors and molecular perturbation on plant root morphology, development and function. To efficiently analyse a large amount of structurally complex soil-root images advanced methods for automated image segmentation are required. Due to often unavoidable overlap between the intensity of fore- and background regions simple thresholding methods are, generally, not suitable for the segmentation of root regions. Higher-level cognitive models such as convolutional neural networks (CNN) provide capabilities for segmenting roots from heterogeneous and noisy background structures, however, they require a representative set of manually segmented (ground truth) images. Here, we present a GUI-based tool for fully automated quantitative analysis of root images using a pre-trained CNN model, which relies on an extension of the U-Net architecture. The developed CNN framework was designed to efficiently segment root structures of different size, shape and optical contrast using low budget hardware systems. The CNN model was trained on a set of 6465 masks derived from 182 manually segmented near-infrared (NIR) maize root images. Our experimental results show that the proposed approach achieves a Dice coefficient of 0.87 and outperforms existing tools (e.g., SegRoot) with Dice coefficient of 0.67 by application not only to NIR but also to other imaging modalities and plant species such as barley and arabidopsis soil-root images from LED-rhizotron and UV imaging systems, respectively. In summary, the developed software framework enables users to efficiently analyse soil-root images in an automated manner (i.e. without manual interaction with data and/or parameter tuning) providing quantitative plant scientists with a powerful analytical tool.

• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

This study addresses two questions. Can mature, denervated and transplanted Pacinian corpuscles accept innervation from motor axons? If so, does the alien target influence the structural characteristics of the regenerated motor axon terminals? Pacinian corpuscles from the hind leg of young rats, together with a segment of the nerve branch through which they receive their sensory innervation, were autotransplanted to the surface of the spinal cord and the nerve stump anastomosed to the central stump of a transected lumbar ventral root. Between 4 and 5 months later the grafts were studied by electron microscopy. Ventral root axons regenerated through the endoneurial tubes of the grafted nerve to reach the corpuscles, most of which became reinnervated by one to three myelinated fibres. The fibres lost their myelin sheaths before entering the inner core, branched, and gave rise to multiple terminals in the inner core. The regenerated terminals were packed with spherical synaptic vesicles and closely resembled normal motor nerve terminals. Thus motor axons are able to reinnervate Pacinian corpuscles but the structural characteristics of the terminals are apparently not modified by the alien target tissue. This finding contrasts with previous studies, in which it was found that terminals of the central axons of large dorsal root ganglion cells, induced to reinnervate Pacinian corpuscles, displayed the structural characteristics of peripheral sensory endings rather than those of dorsal root terminals in the spinal cord.

• MeSH
• Axons physiology   ultrastructure   MeSH
• Rats, Inbred Strains MeSH
• Rats MeSH
• Spinal Cord surgery   MeSH
• Spinal Nerve Roots physiology   ultrastructure   MeSH
• Motor Neurons physiology   ultrastructure   MeSH
• Nerve Endings ultrastructure   MeSH
• Nerve Regeneration physiology   MeSH
• Pacinian Corpuscles transplantation   MeSH
• Animals MeSH
• Check Tag
• Rats MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

UNLABELLED: Development of progressive muscle spasticity resulting from spinal traumatic injury can be mediated by loss of local segmental inhibition and/or by an increased sensory afferent drive with resulting exacerbated α-motoneuron activity. To identify potential contributions of neuroactive substances in the development of such spasticity state, we employed a well-defined spinal injury-evoked spasticity rat model. Signaling molecules were analyzed in the spinal parenchyma below the level of spinal injury and in the corresponding dorsal root ganglion cells using Kinex™ antibody microarrays. The results uncovered the involvement of angiogenesis and neurodegeneration pathways together with direct cross-talk mediated by several hub proteins with SH-2 domains. At 2 and 5weeks after transection, up-regulation of several proteins including CaMKIV, RONα and PKCδ as well as MAPK3/ERK1 phosphorylation was observed in the spinal ventral horns. Our results indicate that these signaling molecules and their neuronal effector systems cannot only play an important role in the initiation but also in the maintenance of spasticity states after spinal trauma. The exclusivity of specific protein changes observed in lumbar spinal parenchyma but not in dorsal root ganglia indicates that new treatment strategies should primarily target specific spinal segments to prevent or attenuate spasticity states. BIOLOGICAL SIGNIFICANCE: Development of progressive muscle spasticity and rigidity represents a serious complication associated with spinal ischemic or traumatic injury. Signaling proteins, including their phosphorylation status, were analyzed in the spinal parenchyma below the level of spinal injury and in the corresponding dorsal root ganglion cells in a rat model of spinal injury using Kinex™ antibody microarrays. The results uncovered direct protein interaction mediated cross-talk between angiogenesis and neurodegeneration pathways, which may significantly contribute to the healing process in the damaged region. Importantly, we identified several target proteins exclusively observed in the spinal lumbar ventral horns, where such proteins may not only play an important role in the initiation but also in the maintenance of spasticity states after spinal trauma. Hence, potential new treatment strategies such as gene silencing or drug treatment should primarily target spinal parenchymal sites at and around the injury epicenter and most likely employ intrathecal or targeted spinal segment-specific vector or drug delivery. We believe that this work will stimulate future translational research, ultimately leading to the improvement of quality of life of patients with spinal traumatic injury.

• Keywords
• AMPA, CASP, CK, CREB, CaMK, DRG, Dorsal root ganglia, EMG, ERK, FAK, FGFR, GABA, Hyper-reflexia, I2D, IGFR, JNK, LTP, Lck, MAPK, MAPK/ERK kinase kinase 4, MEKK4, MSP, N-methyl d-aspartate, NMDA, PK, Proteomic profiling, RONα, SCI, Spasticity, Spinal cord trauma, Spinal gray matter, TEK/TIE2, VEGFR, angiopoietin-1 receptor-tyrosine kinase, c-Jun N-terminal kinase, cAMP response element binding protein, calcium/calmodulin-dependent protein-serine kinase, casein protein-serine kinase, dorsal root ganglion, eIF4G, eNOS, electromyography, endothelial nitric oxide synthase, eukaryotic translation initiation factor 4 gamma, extracellular signal-regulated kinase, fibroblast growth factor receptor, focal adhesion protein-tyrosine kinase, gamma-aminobutyric acid, iNOS, inducible nitric oxide synthase, insulin-like growth factor receptor, interologous interaction database, long-term potentiation, lymphocyte-specific protein-tyrosine kinase, macrophage-stimulating protein, macrophage-stimulating protein receptor alpha chain, mitogen-activated protein kinase, pro-caspase, protein kinase, spinal cord injury, vascular endothelial growth factor receptor, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid,
• MeSH
• Phosphorylation MeSH
• Rats MeSH
• Protein Interaction Mapping MeSH
• Spinal Cord pathology   MeSH
• Microarray Analysis MeSH
• Neurodegenerative Diseases metabolism   MeSH
• Neovascularization, Pathologic MeSH
• Spinal Injuries metabolism   MeSH
• Rats, Sprague-Dawley MeSH
• Antibodies MeSH
• Gene Expression Regulation * MeSH
• Signal Transduction * MeSH
• Ganglia, Spinal metabolism   MeSH
• Animals MeSH
• Check Tag
• Rats MeSH
• Male MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH
• Names of Substances
• Antibodies MeSH