To investigate whether a simple observational tool may be a substitute to the time-consuming and costly 3-dimensional (3D) analysis, the study applied the Wisconsin Gait Scale (WGS), enabling assessment which is highly consistent with 3D gait parameters in patients after a stroke. The aim of this study was to determine whether, and to what extent, observational information obtained from WGS-based assessment can be applied to predict results of 3D gait analysis for selected symmetry indicators related to spatiotemporal and kinematic gait parameters. Fifty patients at a chronic stage of recovery post-stroke were enrolled in the study. The spatiotemporal and kinematic gait parameters were measured using a movement analysis system. The symmetry index (SI), was calculated for selected gait parameters. The patients’ gait was evaluated by means of the WGS. It was shown that stance % SI, as well as hip and knee flexion-extension range of motion SI can most effectively be substituted by WGS-based estimations (coefficient of determination exceeding 80%). It was shown that information acquired based on the WGS can be used to obtain results comparable to those achieved in 3D assessment for selected SIs of spatiotemporal and kinematic gait parameters. The study confirms that observation of gait using the WGS, which is an ordinal scale, is consistent with the selected aims of 3D assessment. Therefore, the scale can be used as a complementary tool in gait assessment.  Despite the fact that 3-dimensional gait analysis (3DGA) is the most accurate method enabling gait assessment and is recognized as a key outcome measure by gait researchers and healthcare professionals , for manThe Wisconsin Gait Scale (WGS), which is an observational tool enabling the assessment of gait quality in patients after a stroke, was developed by Rodriguez et al. . The WGSThe respective parts of the WGS focus on spatiotemporal  and kinematic parameters of gait . Video recordings are analyzed by an examiner and based on that, a score is assigned for the performance of the gait pattern . The speThe motivation for our research was provided by the studies published by Patterson et al. ,11 who eAs it reflects similarities in spatiotemporal and kinematic parameters of the right and left lower limb, symmetry is a significant measure of gait assessment, and can more effectively describe post-stroke gait mechanisms compared to conventional measures such as velocity. Furthermore, it may provide important information to be taken into account by clinicians during treatment decisions . In the The aim of this study was to determine whether, and to what extent, observational information about gait symmetry obtained from a WGS-based assessment can be used as a complementary tool that can be applied to predict results of 3D gait analysis for selected symmetry indicators related to spatiotemporal and kinematic gait parameters. This concurrent validity study was conducted among patients treated at the Rehabilitation Clinic of Provincial Hospital No. 2 in Rzeszow, Poland. All qualifying patients were fully informed about the procedure and signed informed consent to participate in the study. The research protocol was approved by the local Bioethics Commission of the Medical Faculty (5/2/2017), and the study was registered at the Australian New Zealand Clinical Trials Registry (ACTRN12617000436370). The study included 50 patients at a chronic period after a stroke  with a mean age 60.9 ± 11.2 years (range 30–75) and mean time from a stroke 42 months (range 8–120). Of the 50 patients, 15 had right hemisphere lesions, and 35 had left hemisphere lesions. The inclusion criteria were: Ischemic stroke; time from a stroke at least 6 months; independent walking  orthosis was permitted); and Brunnström recovery stage 3–4. Strokes were confirmed by computed tomography or magnetic resonance imaging. The exclusion criteria were: Unstable hemodynamic state; peripheral vascular disease; cognitive impairment ; lower limb contractures; difference in the length of the lower limbs exceeding 2 cm; osteoarthritis impairing gait; and other orthopedic, rheumatic and neurologic comorbidities impairing ambulation. The patients’ walking abilities were assessed at the Laboratory of Biomechanics of the Institute of Physiotherapy, University of Rzeszów. A 3-dimensional gait analysis was carried out using the SMART system , manufactured by BTS Bioengineering . The internal protocol of the system (Helen Hayes (Davis) Marker Placement) was applied in selecting locations for reference markers; these were placed on the sacrum, pelvis (anterior posterior iliac spine), femur , fibula , and foot  . The patThe video recording and 3D recording were carried out concurrently. Positioning of the two video cameras , working in synchronicity, was selected in such a way as to obtain images in the frontal and the sagittal plane. The walking path was 10 m long. One camera was set in line with the direction of the gait in the frontal plane, the other camera, recording sagittal plane view, was positioned halfway along the walking path, 2 m away from the path. The cameras were programmed to allow visualization of three walking trials examining the paretic and the non-paretic sides for a total of six ambulation trials. The subjects were asked to walk the specified distance at a self-selected (comfortable) speed, with the support of orthopedic aids if used on a regular basis.The recordings and WGS-based gait assessment were reviewed and interpreted by a physical therapist with over 10 years of experience in working with patients post-stroke, and with expertise using the WGS and interpreting the scores. A physical therapist reviewed the gait assessments via video. Based on the analysis of the video recordings, the evaluator assigns scores for the performance of the gait pattern. The WGS system allows one to assess 14 observable gait parameters. The five initial items relate to affected leg stance phase: (1) use of hand-held assistive device; (2) stance time on the affected side; (3) step length on the unaffected side; (4) weight shift to the paretic limb with/without assistive device; and (5) stance width. The next part of the scale relates to the affected leg toe-off phase and comprises two items: 6) guardedness (pause before advancing the paretic leg); and 7) affected leg hip extension . The third subscale covers the affected leg swing phase, and comprises six items: 8) external rotation during initial swing; 9) circumduction at mid-swing (path of the paretic foot); (10) hip hiking at mid-swing; (11) knee flexion from toe off to mid-swing; (12) toe clearance; and (13) pelvic rotation at terminal swing. The final subscale relates to the affected leg heel strike and comprises only one item: (14) initial foot contact of the affected leg. The total score, in the range of 13.35–42 points, is calculated for all the items. The points assigned to items 2–10 and 12–14 are added up. Responses to items 1 and 11 are weighted by 3/5 and 3/4, respectively and then the points are added to the total score. Higher scores correspond to poorer overall walking performance and more visible gait deviations [3.8]. Good intra- and inter-rater reliability of the WGS in patients post-stroke has been demonstrated by a number of studies [ guardedn affected external circumduxn is the value of the variable obtained from the non-paretic limb; and xi is the value of the corresponding variable obtained from the paretic limb [The analyses took into account six gait symmetry indexes calculated based on 3D assessment involving 50 patients. In the current study, the authors decided to apply symmetry indexes (SI), based on 3D gait parameters, to compare the results of equipment-based 3D assessment to those obtained using observational gait analysis performed using the subjective WGS. The measurement of gait symmetry applied the most commonly used method, the absolute index proposed by Robinson , which htic limb .The results of measurements obtained in 3D assessment for the non-paretic and paretic limb as well as the specific SIs were presented in the form of descriptive statistics and histograms. Analysis of the correlations between 3D symmetry indexes and the specific components, as well as the total score, of the WGS-based assessment is shown in the form of a correlation matrix presenting values of Spearman’s rank correlation coefficients. The strength of all the correlations were interpreted as: 0.3 ≤ ||R| < 0.5 low correlation; 0.5 ≤ |R| < 0.7 moderate correlation; 0.7 ≤ ||R| < 0.9 strong correlation; 0.9 ≤ ||R| < 1 very strong correlation .During the next stage, regression analysis was applied to investigate whether a simple observational tool may be a substitute to the time-consuming and costly 3D analysis. Symmetry indexes based on 3D assessment of the relevant parameters were adopted as dependent variables for the specific models, while scores in items 1–14 of the WGS were applied as independent variables. Subsequently, stepwise regression with forward selection was applied to find a model combining two desired characteristics: It would only contain statistically significant factors and would most successfully describe variability of the indexes. Determined based on such calculations, a regression model for each 3D symmetry index allows to estimate its value using selected WGS scores . p < 0.05. Statistical analyses were conducted with the use of Statistica 10.0 program .Statistical significance was assumed to be Symmetry indexes were determined for the six gait parameters taken into account in the study . NotablyThe analysis of the SI values identified for the specific parameters and the related graphic presentation suggest that a considerably greater relative differences between the two limbs are found in the parameters of Step Length (s), Hip FE ROM, and Knee FE ROM .It was shown that 3D symmetry indexes, related to Stance Time (s), Stance %, Hip FE ROM, and Knee FE ROM may be described with fairly high accuracy using item questions of the WGS (the identified correlations were strong 0.7 ≤ |R| < 0.9 or very strong 0.9 ≤ |R| < 1). The weakest correlation to WGS scores was found in the case of Step Length (m) SI (0.3 ≤ |R| < 0.5) . The subThe present study has a practical dimension as it confirms that the WGS is a valuable gait assessment tool and in the circumstances when the use of costly objective methods is not feasible, the WGS may effectively be applied as a diagnostic instrument to perform evaluation of post-stroke gait pattern asymmetry. Hsu et al.  demonstrIn order to answer the question formulated in the purpose of the study, and determine whether and to what extent observational information about gait symmetry obtained from WGS-based assessment can be used as a complementary tool and can be applied to predict results of 3D gait analysis for selected symmetry indicators related to spatiotemporal and kinematic gait parameters, the current analyses were designed to examine correlations of 3D symmetry indexes and the specific items of  the WGS. It was shown that 3D symmetry indexes, related to Stance Time (s), Stance %, Hip FE ROM, and Knee FE ROM may be described with fairly high accuracy using item questions of the WGS . This initial finding provided a rationale for the assumption that a combination of selected WGS items may enable even more accurate estimation of symmetry indexes for 3D parameters. Therefore, the next stage involved building regression models, where gait symmetry indexes for selected 3D parameters were used as dependent variables and specific components of WGS (items 1–14) were applied as independent variables. Given the fact that values of dependent variables do not have to be significantly related to all independent variables applied in a regression model, the analyses were designed to find an optimum model that would only contain statistically significant factors and would most effectively describe variability of the dependent characteristic. A formula determined as a result of this procedure allows to estimate a 3D symmetry index based on WGS scores. It was shown that Stance % SI, Hip FE ROM SI, and Knee FE ROM SI can most effectively be substituted by WGS based estimations (coefficient of determination exceeding 80%). In the case of Stance Time (s) SI and Stride Length (m) SI, the WGS values determined using appropriate equations did not reflect the distribution of 3D measurements as effectively. The least satisfying results were found in the case of Step Length (m) SI (coefficient of determination at a level of approximately 24%). We believe that the poor result related to Step Length may be linked with the fact that video recording and processing were carried out only at a basic level.Besides the traditional 3-dimensional motion capture, a number of advanced objective tools for gait analysis are available at present, e.g., GaitRite or Inertial Measurement Units. However, they are all costly and require technical expertise and specialist equipment. The current findings are not intended to undermine the importance of the objective gait assessment methods, which provide gold standard in this area; they only show that the WGS enables accurate assessment of gait, corresponding to the objective 3D gait measures. The findings suggest that in situations when costly equipment-based gait assessment systems are not accessible to medical facilities for various reasons, the regression models described here may be helpful for physicians and physiotherapists, enabling rough estimation of selected 3D symmetry indexes based on WGS scores. The study shows that this simple, easy, and time-effective scale can be used as a complementary tool in gait assessment and can be recommended as an alternative tool when 3DGA is unavailable. A limitation of the present study lies in the fact that traditional 3-dimensional motion capture was the only objective gait analysis method applied. Therefore, it is necessary to continue the research taking into account other advanced tools for clinical gait analysis.It was shown that information acquired based on the WGS can be used to obtain results comparable to those achieved in 3D assessment for selected SIs of spatiotemporal and kinematic gait parameters. 3D symmetry indexes related to the parameters of Stance %, Hip FE ROM, and Knee FE ROM can be fairly accurately described using item questions of WGS. In the case of Step Length (m) SI, the values of WGS determined using appropriate equations reflected the distribution of 3D measurements least effectively. The study confirms that observation of gait using the WGS, which is an ordinal scale, is consistent with the selected aims of 3D assessment, therefore, the scale can be used as a complementary tool in gait assessment.


We have developed an open-source software called bi-channel image registration and deep-learning segmentation (BIRDS) for the mapping and analysis of 3D microscopy data and applied this to the mouse brain. The BIRDS pipeline includes image preprocessing, bi-channel registration, automatic annotation, creation of a 3D digital frame, high-resolution visualization, and expandable quantitative analysis. This new bi-channel registration algorithm is adaptive to various types of whole-brain data from different microscopy platforms and shows dramatically improved registration accuracy. Additionally, as this platform combines registration with neural networks, its improved function relative to the other platforms lies in the fact that the registration procedure can readily provide training data for network construction, while the trained neural network can efficiently segment-incomplete/defective brain data that is otherwise difficult to register. Our software is thus optimized to enable either minute-timescale registration-based segmentation of cross-modality, whole-brain datasets or real-time inference-based image segmentation of various brain regions of interest. Jobs can be easily submitted and implemented via a Fiji plugin that can be adapted to most computing environments. Mapping all the cells and nerve connections in the mouse brain is a major goal of the neuroscience community, as this will provide new insights into how the brain works and what happens during disease. To achieve this, researchers must first capture three-dimensional images of the brain. These images are then processed using computational tools that can identify distinct anatomical features and cell types within the brain.Various microscopy techniques are used to capture three-dimensional images of the brain. This has led to an increasing number of computational programs that can extract data from these images. However, these tools have been specifically designed for certain microscopy techniques. For example, some work on whole-brain datasets while others are built to analyze specific brain regions. Developing a more flexible, standardized method for annotating microscopy images of the brain would therefore enable researchers to analyze data more efficiently and compare results across experiments.To this end, Wang, Zeng, Yang et al. have designed an open-source software program for extracting features from three-dimensional brain images which have been captured using different microscopes. Similar to other tools, the program uses an ‘image registration’ method that is able to recognize and annotate features in the brain. These tools, however, are limited to whole-brain datasets in which the complete anatomy of each feature must be present in order to be recognized by the software.To overcome this, Wang et al. combined the image registration method with a deep-learning algorithm which uses pixels in the image to identify features in isolated regions of the brain. Although these neural networks do not require whole-brain images, they do need large datasets to ‘learn’ from. Therefore, the image registration method also benefits the neural network by providing a dataset of annotated features that the algorithm can train on.Wang et al. showed that their software program, named BIRDS, could accurately recognize pixel-level brain features within imaging datasets of brain regions, as well as whole-brain images. The deep-learning algorithm could also adapt to analyze various types of imaging data from different microscopy platforms. This open-source software should make it easier for researchers to share, analyze and compare brain imaging datasets from different experiments. Allen Mouse Brain Connectivity Atlas , obtained by serial two-photon tomography , were first down-sampled into isotropic low-resolution data with a 20 μm voxel size identical to an averaged Allen template image  to each sub-stack, to finely compress (<0.5) or stretch (>0.5) the z depth of the sub-stacks, thereby better matching the depth of each sub-stack to the Allen template brain and rectifying the deformation along the AP axis  based on the abovementioned bi-channel registration was generated to support automatic annotation, analysis, and visualization of neurons in a whole mouse brain . The framework thus enabled large-scale mapping of neuronal connectivity and activity to reveal the architecture and function of brain circuits. Here, we demonstrated how the BIRDS pipeline visualizes and quantifies single-neuron projection patterns obtained by STPT imaging. A mouse brain containing six GFP-labeled layer-2/3 neurons in the right visual cortex was imaged with STPT at 1 × 1 × 10 μmsolution . After asolution . An intesolution , Video 1solution . The BIRsolution .3 resolution . Here, we demonstrate it with an example brain where neurons were retrogradely labeled by CAV-mCherry injected to the right striatum and imaged by STPT at 1×1×10 μmsolution . The whosolution . Comparesolution . Thanks In practice, acquired brain datasets are often incomplete, due to researcher’s particular interest in specific brain regions, or limited imaging conditions. The registration of such incomplete brain datasets to an Allen template is often difficult due to the lack of sufficient morphology information for comparison of both datasets. To overcome this limitation, we further introduced a deep neural network (DNN)-based method for efficient segmentation/annotation of incomplete brain sections with minimal human supervision. Herein, we optimized a Deeplab V3+ network, which was based on an encoding-decoding structure, for our deep-learning implementation . The inpIn summary, we demonstrate a bi-channel image registration method, in conjunction with a deep-learning framework, to readily provide accuracy-improved anatomical segmentation for whole mouse brain in reference to an Allen average template, and direct segmentation inference for incomplete brain datasets, which were otherwise not easily registered to standardized whole-brain space. The addition of a brain feature channel to the registration process greatly improved the accuracy of automatically registering individual whole-brain data with a standardized Allen average template. It should be noted that the registration was based on two-photon template images provided by Allen CCF, so it is currently limited to using on like-imaged brains, for example, brains imaged using wide-field, confocal, or light-sheet microscopes, etc. For processing various incomplete brain datasets, which were challenging for registration-based methods while remaining very common in neuroscience research, we applied our deep neural network to rapidly infer segmentations. The sufficiently accurate results shown using different types of incomplete data verify the advances of network segmentation. Though a full annotation using a neural network is currently too computationally demanding as compared to registration-based segmentation, it is undoubtedly a good complement to registration-based segmentation. Therefore, in our hybrid BIRDS pipeline, the DNN inference greatly reinforced the inefficient side of registration, while the registration also readily provided high-quality training data for our DNN. We believe such a synergistic effect in our method could provide a paradigm shift for enabling robust and efficient 3D image segmentation/annotation for biology research. With the unceasing development of deep learning, we envision that network-based segmentation will play an increasingly important role in new pipelines. A variety of applications, such as tracing of long-distance neuronal projections and parallel counting of cell populations in different brain regions, was also enabled as a result of our efficient brain mapping. The BIRDS pipeline is now fully open source and also has been packaged into a Fiji plugin to facilitate biological researchers. We sincerely expect that the BIRDS method can immediately allow new insights using current brain mapping techniques, and thus further push the resolution and scale limits in future explorations of brain space.3. The procedure of sample preparation and imaging acquisition were described in IMSR_JAX:000664) was anesthetized, and craniotomy was performed on top of the right visual cortex. Individuals neuronal axons were labeled with plasmid DNA (pCAG-eGFP [Addgene accession 11150]) by two-photon microscopy-guided single-cell electroporation, and the brain was fixed by cardioperfusion of 4% paraformaldehyde 8 days later. Striatum-projecting neurons were labeled by stereotactically injecting PRV-cre into the right striatum of tdTomato reporter mice , and the brain was fixed cardioperfusion 30 days later. The brains were embedded in 5% oxidized agarose and imaged with a commercial STPT  excited at 940 nm. Coronally, the brain was optically scanned every 10 μm at 1 μm/pixel without averaging and physically sectioned every 50 μm. The power of excitation laser was adjusted to compensate the depth of optical sections.Brains 1 and 2 were obtained with STPT, and each dataset encompassed ~180 Gigavoxels, for example, 11,980 × 7540 × 1075 in Dataset 1, with a voxel size of 1 × 1 × 10 μm3. Brain tissues of eight-week-old Thy-GFP-M mice (RRID:IMSR_JAX:007788) were first clarified with u-DISCO protocol , with an isotropic voxel size of 1 μmprotocol  before iprotocol , anotherSCR_002285) to correspond the coronal planes in the Allen Reference Atlas (ARA)  with those in the experimental 3D image stack . As shown in k sub-stacks (kth sub-stack sandwiched by every two planes (ak to ak+1) was then calculated by: kth sub-stack to obtain the resliced version of the sub-stack. Finally, the six resliced sub-stacks together formed a complete image stack of whole brain (20 μm stepsize), which had a rectified shape more similar to the Allen average template image, as compared to the raw experimental data. According to the isotropic voxel size of 20 μm in the template, the lateral size of voxel in the resliced image stack was also adjusted from originally 1 μm to 20 μm with a uniform lateral down-sampling ratio of 20 applied to all the coronal planes. The computational cost of abovementioned data re-sampling operation was low, taking merely ~5 min for processing 180 GB raw STPT data on a Xeon workstation (E5-2630 V3 CPU).First, we developed an interactive GUI in the Fiji plugin  . Unlike SCR_007370), we could readily visualize the 3D digital map and perform various quantification in Imaris. After registration and interpolation applied to the experimental data, a 3D digital map was visualized in Imaris (9.0.0) invoked by our program. Then neuron tracing and cell counting tasks could be performed in Imaris at native resolution . During the neural tracing process, the brain regions where the selected neurons passed through could be three-dimensionally displayed under arbitrary view. Furthermore, the cell counting could be performed in parallel by simultaneously setting a number of kernel diameters and intensity thresholds for different segmented brain regions.We obtained a low-resolution annotation (20 μm isotropic resolution) for entire mouse brain after registration. In order to generate a 3D digital framework based on the high-resolution raw image, lgorithm  to generThe Euclidean distance between one pair of landmarks shown in different image datasets  indicateA is the ground truth of segmentation, while B is the result by brain-map. Dice score is the indicator for quantifying the accuracy of segmentation and can be calculated as:Here, with referring to BrainsMapi  methods,We chose 18 primary regions (levels 4 and 5): Isocortex, HPF, OLF, CTXsp, STR, PAL, CB, DORpm, DORsm, HY, MBsen, MBmot, Mbsta, P-sen, P-mot, P-sat, MY-sen, and MY-mot, in whole brain for the DNN training and performance validation. The ground-truth annotation masks for these regions were readily obtained from our bi-channel registration procedure of BIRDS. For high-generosity DNN segmentation of whole brain and incomplete brain, we specifically prepared two groups of data training and validation as following: (1) Nine whole mouse brains containing 5000 annotated sagittal slices (660 × 400 for each slice) were first used as the training dataset. Then, the sagittal sections of whole brains were cropped, to generate different types of incomplete brains, as shown in During network training, we defined the segmentation classes with the same number of regions, which is 19 in Our DNN is based on the modification of Deeplab V3+, which contains a classical encoder–decoder structure . The maiThe neurons in whole brain data were segmented semi-automatically using the Imaris software. With registering our brain to ABA, we obtained the anatomical annotation for all the segmented areas. The Autopath Mode of the Filament module was applied to trace long-distance neurons. We first assigned one point on a long-distance neuron to initiate the tracing. Then, Imaris automatically calculated the pathway in accordance with image data, reconstructed the 3D morphology, and linked it with the previous part. This procedure would repeat several times until the whole neuron, which could also be recognized by human’s eye, was segmented.The Spots module and Surface module of Imaris software were used to count retrogradely labeled striatum-projecting cells in SS and VIS areas. We first separated the brain regions into multiple channels in Surface module. Then automatic creation in Spots module was applied to count cells number for each channel. To achieve accurate counting, the essential parts were the appropriate estimate of cell bodies’ diameter and filtration of the chosen cells by tuning the quality parameters. The accuracy of this automatic counting procedure was compared with manual counting, which herein severed as ground truth. After obtaining the total number of cells in each brain region, according to the sub-region ranges divided by the Surface module, Imaris could also calculate the volume of each brain region. Then, with knowing the number of cell nuclei and the volume of each segmented brain region, the density of the cell nuclei inside each brain region could be calculated.We run BIRDS on a Windows 10 workstation equipped with dual Xeon E5-2630 V3 CPUs, 1 TB RAM, and two GeForce GTX 1080 Ti graphic cards. In https://github.com/bleach1by1/birds_reg (swh:1:rev:22cf3d792c3887708a65ddae43d6dde7ed8b7836). FIJI plugin and ancillary installation packages are provided at https://github.com/bleach1by1/BIRDS_plugin (swh:1:rev:41e90d4518321d6ca8e806ccadb2809bfa6bd475). BIRDS contains five core modules, image preprocessing, bi-channel registration, manual correction, link with Imaris software, and deep-learning segmentation, all of which can be executed on a GUI. We also provided a step-by-step tutorial and test data to facilitate the program implementation by other researchers.We have made our pipeline open access for the community. We have provided source code of the BIRDS for Windows 10 at  In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:A major advance in analyses of brain and neural circuit morphology is the capability to register labeled neuronal structures to a reference digital 3D brain structural atlas such as the Allen Institute for Brain Sciences mouse brain Common Coordinate Framework. In this technical advance, the authors have developed open source, automated methods for 3D morphological mapping in the mouse brain employing dual-channel microscopic neuroimage data and deep neural network learning. The authors demonstrate improved accuracy of image registration to the Allen Institute atlas and morphological reconstruction of mouse brain image sets, suggesting that the authors' approach is an important addition to the tool box for 3D brain morphological reconstruction and representation.Decision letter after peer review:eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Laura Colgin as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Charles R Gerfen (Reviewer #1); Jahandar Jahanipour (Reviewer #2).Thank you for submitting your article "Bi-channel Image Registration and Deep-learning Segmentation (BIRDS) for efficient, versatile 3D mapping of mouse brain" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.eLife papers without additional data, even if they feel that they would make the manuscript stronger. Thus the revisions requested below only address clarity and presentation.We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, we are asking editors to accept without delay manuscripts, like yours, that they judge can stand as Summary:Wang et al. present a technique for registering and analysis of whole mouse brain image sets to the Allen CCF. A major advance in the analysis of neuroanatomical circuits is the ability to register labeled neuronal structures in the whole mouse brain to a common mouse brain atlas. Numerous studies have used various techniques for such registration with varying success and accuracy. The authors' BIRDS process for registering whole mouse brain image sets to the Allen CCF uses a number of innovative approaches that provide some advances in the accuracy of registration, at least for the examples described. There are a number of major revisions listed below that need to be addressed.Essential revisions:1) Despite the steps being described in detail, parts of the image processing and registration process are difficult to understand, which requires careful revision of the text to clarify the steps in the procedure depicted in Figure 1:– The down-sampling is straightforward. However, the "dynamic down-sampling ratios applied to the.… " is not at all clear. What exactly is being done and what is the purpose? By "dynamic down-sampling ratio" is it meant that instead of the ratio of the original  that the ratio might be different at different rostro-caudal levels of the brain? And is this to account for differences in how the brains are processed. For instance, experimental brains might have different dimensions in the x and y planes than the Allen CCF or might be deformed in different ways. And that this process makes those corrections at the appropriate rostro-caudal levels.– The next step(s) are very difficult to follow: the "feature based iterative registration of the Allen reference image with pre-processed experimental images". This step involves the application of: 1) phase congruency algorithm to extract high contrast information from both experimental and template brain (CCF?) images and 2) enhanced axial mutual information extracted by grayscale reversal processing. And then somehow a "bi-channel" registration was performed. What is unclear is what channels are used for the "bi-channel" registration. Is a separate channel formed by the combination of the processes of 1) and 2)? Is the original image also combined with these channels? Are these processes applied to the Allen 2-photon images? And then exactly what is registered and how is that done?– It might be better if the process steps were described separately and succinctly from comments about how this is better than other methods. The description in the Materials and methods section is somewhat better, but still confusing. The figure legend for Figure 1—figure supplement 4 comes close to being understood.– The "bi-channel" process is the most confusing, and since it is part of the acronym should be better explained. In general, it seems straightforward, using not only the original image data but also that data that has been processed to enhance edges and other features. What is confusing is whether you are also using image data from channels that have labeled neurons and axons – which is stored in other channels?2) Authors propose an algorithm for registration of high-resolution large-scale microscopic images of whole mouse brain datasets. This type of computational processing requires adequate memory and processing power which might not be available in a standard laboratory environment. Authors should elaborate on the computational techniques to address the large dataset handling of the proposed algorithm in regards of memory and the speed. Furthermore, is the proposed algorithm expandable to larger datasets such as super-resolution images or high-resolution whole rat brain datasets specifically in the context of memory and speed?3) Authors discuss downsampling the dataset before registration. How does this downsampling affect the results specifically the smoothness of the borders between the regions?4) The tracing of each fluorescently labelled neuronal cell is not clear! The method for tracing is neither explained nor referenced in the Results section.5) Is the Deep Neural Network mainly to be used for incomplete brain datasets? Would be nice if it helped with providing better registration for registration of local structure differences, such as different layers in cortical structures or areas with multiple nuclei in addition to when there is damage to the tissue. Also, the 2-photon image data used for registration does not always provide sufficient morphologic features to identify certain brain structures, such as certain subnuclei in the brainstem and thalamus and to some extent different cortical layers. Basing the training data set on the structures detected using bi-channel procedures on 2-photon data may not best identify certain brain structures.6) The DNN structure needs further clarification in terms of input and output. The input size is not specified; is it 2D section or 3D? How many output classes are defined? Does each region get a specific node in the output? It is not clear how the network output is selected. In "Generation of ground-truth training data" section it is mentioned that 18 primary regions were chosen for training set. In inference, the four major sub-regions of hippocampus, CA1, CA2, CA3, and the DG are not in the original 18 regions defined in the training set. The structure of the training set both in the training and test mode should be clearly explained.7) It is recommended to report the median values of the comparison of different methods in a separate table rather than the legend of the figure for easier readability.8) Variables in Equations 1 and 2 are not fully defined.9) Equation 3 only explains the relationship of the final cost function to the Individual cost functions. The individual cost functions are not defined.10) The "Marching cubes" algorithm introduced in "Generation of 3D digital map for whole brain" section is not defined. Is it a proposed algorithm by authors or an algorithm used from somewhere else? If latter, the authors should cite the paper. Essential revisions:1) Despite the steps being described in detail, parts of the image processing and registration process are difficult to understand, which requires careful revision of the text to clarify the steps in the procedure depicted in Figure 1:– The down-sampling is straightforward. However, the "dynamic down-sampling ratios applied to the.… " is not at all clear. What exactly is being done and what is the purpose? By "dynamic down-sampling ratio" is it meant that instead of the ratio of the original  that the ratio might be different at different rostro-caudal levels of the brain? And is this to account for differences in how the brains are processed. For instance, experimental brains might have different dimensions in the x and y planes than the Allen CCF or might be deformed in different ways. And that this process makes those corrections at the appropriate rostro-caudal levels.We apologize for the ambiguity brought to the reviewer. In addition to the individual difference, the sample preparation step often causes additional nonuniform deformation of samples. It means that the scaling factors of different parts of the brain are not the same, as compared to Allen CCF template. Such nonuniform deformation is found to be especially obvious along the AP axis and makes the following precise registration a lot more difficult. So at image preprocessing step, we divided the whole brain into a few z sub-stacks (6 in our demonstration) according to several selected landmark planes (7 in our demonstration) and applied appropriate re-sampling ratios, which are different, to them to finely re-adjust the depth of the sub-regions. Through compressing or stretching the depth of the sub-stacks by dynamic re-sampling ratio calculated by corresponding the positions of the landmark planes in Allen CCF3 template and sample data , we rectify the nonuniform deformation to restore a uniform rostro-caudal level of brain. This step was verified to be beneficial to the following image registration. Figure 1—figure supplement 2 of the revised manuscript shows the improvement of registration accuracy by using our dynamic downsampling preprocessing. We further illustrated this dynamic down-sampling operation in the revised Figure 1 and improved the descriptions in Results and Figure 1—figure supplement 1.– The next step(s) are very difficult to follow: the "feature based iterative registration of the Allen reference image with pre-processed experimental images". This step involves the application of: 1) phase congruency algorithm to extract high contrast information from both experimental and template brain (CCF?) images and 2) enhanced axial mutual information extracted by grayscale reversal processing. And then somehow a "bi-channel" registration was performed. What is unclear is what channels are used for the "bi-channel" registration. Is a separate channel formed by the combination of the processes of 1) and 2)? Is the original image also combined with these channels? Are these processes applied to the Allen 2-photon images? And then exactly what is registered and how is that done?– It might be better if the process steps were described separately and succinctly from comments about how this is better than other methods. The description in the Materials and methods section is somewhat better, but still confusing. The figure legend for Figure 1—figure supplement 4 comes close to being understood.– The "bi-channel" process is the most confusing, and since it is part of the acronym should be better explained. In general, it seems straightforward, using not only the original image data but also that data that has been processed to enhance edges and other features. What is confusing is whether you are also using image data from channels that have labeled neurons and axons – which is stored in other channels?st primary channel consisted of brain background images of both sample and Allen CCF brains is always included in the registration. The 2nd assistant channel consisted of the generated texture and geometry maps of both brains participates the registration procedure with appropriate weighting being applied. Therefore, both primary and assistant channels contain the graphic information from the background images of both sample and Allen CCF brains. Meanwhile, no neurons/axons labelled images are required at registration step. In the revised manuscript, we have further clarified the definitions and implementations of the bi-channel registration in Results and Materials and methods sections. Also, the registration procedure has been better illustrated in the revised Figure 1—figure supplement 4.Bi-channel is defined to be distinguished with conventional registration that merely uses the brain background images for registration. The 12) Authors propose an algorithm for registration of high-resolution large-scale microscopic images of whole mouse brain datasets. This type of computational processing requires adequate memory and processing power which might not be available in a standard laboratory environment. Authors should elaborate on the computational techniques to address the large dataset handling of the proposed algorithm in regards of memory and the speed. Furthermore, is the proposed algorithm expandable to larger datasets such as super-resolution images or high-resolution whole rat brain datasets specifically in the context of memory and speed?We appreciate the reviewer’s professional advices, which are indeed helpful to the improvement of our manuscript. We have discussed the computational cost and the possible expansion to larger dataset in the Materials and methods section. A new Supplementary file 1 is also provided to summarize the data size, memory cost and time consumption at different BIRDS stages for processing 180 GB STPT and 320 GB LSFM datasets.3) Authors discuss downsampling the dataset before registration. How does this downsampling affect the results specifically the smoothness of the borders between the regions?In consideration of the big saving of computational costs (speed and memory), down-sampling the raw image dataset before registration is a standard operation, which shows minor effect on the smoothness of the borders between regions. This step has been widely used in many established brain registration works such as: ClearMap , aMAP  and MIRACL  with downsampling the raw image data to 25-μm, 12.5-μm and 25-μm voxel size, respectively. In our method, we chose downsampling to 20-μm voxel size, which was within the normal range.4) The tracing of each fluorescently labelled neuronal cell is not clear! The method for tracing is neither explained nor referenced in the Results section.The tracing of fluorescently labelled neurons shown in Figure 3 was performed using the filament module of Imaris, which was based on the automatic neuron segmentation aided by human inspection / correction. We have added the descriptions on neuron tracing and counting in the Results and Materials and methods sections.5) Is the Deep Neural Network mainly to be used for incomplete brain datasets? Would be nice if it helped with providing better registration for registration of local structure differences, such as different layers in cortical structures or areas with multiple nuclei in addition to when there is damage to the tissue. Also, the 2-photon image data used for registration does not always provide sufficient morphologic features to identify certain brain structures, such as certain subnuclei in the brainstem and thalamus and to some extent different cortical layers. Basing the training data set on the structures detected using bi-channel procedures on 2-photon data may not best identify certain brain structures.We appreciate reviewer’s professional question. In our BIRDS pipeline, since the registration step has handled the whole brain datasets, DNN is designed to be used for incomplete brain datasets, which are otherwise difficult for registration. As long as finer labelling data being provided, the DNN itself certainly has the ability to segment finer brain structures, like CA1, CA2, CA3 and DG structures shown in Figure 5—figure supplement 4. Since only 2-photon and light-sheet datasets are available to us, it is a pity that we are currently unable to train the network with data containing sufficient morphologic features at certain brain structures, such as certain subnuclei in the brainstem and thalamus. However, it should be noted that BIRDS is a fully open-source approach, thus higher-quality data containing specific regions labelled from various laboratories could be processed using this approach. We also look forward to seeing increasingly stronger segmentation / capabilities shown by BIRDS in future.6) The DNN structure needs further clarification in terms of input and output. The input size is not specified; is it 2D section or 3D? How many output classes are defined? Does each region get a specific node in the output? It is not clear how the network output is selected. In "Generation of ground-truth training data" section it is mentioned that 18 primary regions were chosen for training set. In inference, the four major sub-regions of hippocampus, CA1, CA2, CA3, and the DG are not in the original 18 regions defined in the training set. The structure of the training set both in the training and test mode should be clearly explained.We apologize for the confusion to reviewer. The inputs for DNN are 2D image slices. We trained the network twice on dataset of 18 primary brain regions and dataset of 4 small sub-regions in hippocampus separately, to demonstrate network’s inference capability on both coarse segmentation of large incomplete brain  and fine segmentation of certain region of interest . During network training, we defined the segmentation classes the same with the number of regions, which is 19 in Figure 5 (background as one class) and 5 in Figure 5—figure supplement 4 (background as one class). Finally, each region was assigned a channel rather than a node for generating the segmented output. In the revised manuscript, we have included a Supplementary file 2 to provide the detailed information of training and test datasets. More DNN information can be found in the revised Materials and methods section and the source code we have provided.7) It is recommended to report the median values of the comparison of different methods in a separate table rather than the legend of the figure for easier readability.In response to reviewer’s suggestion, we have added a separate Supplementary file 3 to report the median values.8) Variables in Equations 1 and 2 are not fully defined.We have fully defined the variables in Equations 1 and 2 .9) Equation 3 only explains the relationship of the final cost function to the Individual cost functions. The individual cost functions are not defined.We have defined the individual cost functions as new Equation 4 in the Materials and methods section.10) The "Marching cubes" algorithm introduced in "Generation of 3D digital map for whole brain" section is not defined. Is it a proposed algorithm by authors or an algorithm used from somewhere else? If latter, the authors should cite the paper.We have cited the paper that reports Marching cubes algorithm in the revised manuscript .


In 22 human subjects we measured microsaccade count across 60 brief fixation trials both pre- and post- administration of 300mg of caffeine. There was a statistically significant reduction in average microsaccade count post-caffeine administration, with a moderate effect size (Cohen’s d of 0.42). Microsaccade count was stable within individuals across time points (Pearson’s r of 0.89). Sensitivity analysis suggests that the pre/post caffeine effect size is robust to choice of parameters used to identify microsaccades. Bootstrap resampling suggests that both the pre/post-caffeine difference and the across-time stability within individuals could be reliably assessed with far fewer trials. The results support the use of microsaccade count as both a trait measure of individual differences and a state measure of caffeine response. We discuss the results in the context of the theory that the superior colliculus is central to the generation of microsaccades and hence that microsaccade rate may be a useful assay for at least some drug-induced changes at the level of the colliculus: a potentially useful tool in the development of therapies for disorders that may involve collicular dysfunction such as ADHD. Microsaccades are miniature fixational eye movements approximately 6 to 25-milliseconds in duration, through 1-120 arcminutes (up to 2 full degrees of rotation), that occur at a rate of about 1-2 per second. Electrophysiological studies have demonstrated the role of the rostral pole of the superior colliculus in microsaccades in primate models , and GofEvidence suggests that collicular activity is modulated by a range of neurotransmitter systems, one of the least explored – at least in humans – is the adenosine system. Intraperitoneal administration of an adenosine deaminase inhibitor has been shown to enhance neural activity in the superficial grey layer of the superior colliculus following electrical activation of the optic tract in the anaesthetised rat in vivo , as has The present study follows on closely from the earlier pilot work by Collins and colleagues  by exploTwenty-seven participants  were recruited via intra-university advertising at the University of Sheffield. The final group of 22 participants (taking into account exclusions) had a mean age of 29.4 years ranging from 19-47 (SD = 8.57). Three participants were excluded from the final analysis as calibration problems prevented binocular tracking. Data for these participants were collected monocularly, but ultimately excluded from final analyses in order to standardise the data set. Two further participants were excluded due to strabismus that prevented successful calibration, leading to a total of five exclusions. All subjects were right-handed, free from diagnosed neurological disorder or injury, and free from stimulant class medications (including methylphenidate). Although none of the participants had a current diagnosis of ADHD, their relatively low levels of ADHD-like traits were confirmed by their low scores  on the Adult ADHD Self-Report Scale ASRS; .Participants were asked not to ingest caffeine in the two hours before the study, both upon registration and in an email reminder of their study appointment the day before. They were told specifically to avoid caffeinated drinks such as coffee and energy drinks, as well as caffeine tablets. All participants confirmed upon arrival, via the signing of the consent form, that they had not consumed any of the above examples of caffeinated beverages/tablets.Participants received £10 for taking part in the study. The subjects all gave their informed consent to take part in the experiment and the procedures were conducted in accordance with both the University of Sheffield’s ethics committee guidelines, and the Declaration of Helsinki. The eye tracking was performed using an Eyelink 1000 , which recorded data binocularly at 500Hz. The fixation task was created from scratch using the experiment builder  software packaged with the Eyelink hardware. The experiment was displayed to the participants on a 19" DMW LCD monitor with screen dimensions of 1024x768 and a 60hz refresh rate. The monitor was placed 65cm away from the participant headrest. The experiment took place inside an enclosed room with the curtains drawn and light turned on in order to achieve a constant illumination level. A 9-point grid was used for calibration. Validation was deemed successful if the disparities from calibration were less than 1 degree. If validation was unsuccessful, calibration was repeated. The process took approximately 2 minutes for each participant. Drift correction using a central fixation point was performed before every trial, to counter small inaccuracies in calibration produced by pupil dilation and participant movements. Calibration was performed twice for each participant; at the beginning of each block. The task was administered after calibration and validation were complete. Following the initial drift correction, a fixation cross appeared in the centre of the screen, which disappeared once the participant fixated upon it for 300ms. The removal of the fixation cross triggered the appearance of an orange target cross at one of 6 target positions with horizontal displacements of, respectively, -8.6, -4.3, 0, 0, +4.3, +8.6 degrees, and vertical displacements of 0, 0, +6.4,-6.4,0,0 degrees. Each target position was used 5 times in each block, with the order randomised to prevent predictive saccades. The participants were tasked with fixating upon the target cross for 5.5 s until it disappeared. Research has suggested that fixations of 10 s or longer can to cause pupil contractions, which are significant confounding factors with regards to pupil centration and thus eye tracking calibration . With thEach eye tracking session consisted of 2 blocks of 30 trials. The removal of the black fixation cross relied upon the participant fixating upon it successfully, which was of course reliant on both participant compliance and eye tracker accuracy. In the rare instances this was not achieved punctually, the eye tracker was recalibrated. The eye tracking sessions took an average of approximately 12 minutes each, with a range of 10-15 minutes. Once the first eye tracking session was complete, the participants were given tablets containing 300mg of caffeine to ingest with water. Caffeine was given in the form of one 200mg tablet (myvitamins.co.uk) and two 50mg tablets   in which the only listed active ingredient was caffeine. This dosage was chosen as 300mg of caffeine has been shown to significantly increase dopaminergic activity in the putamen and ventral striatum . Microsaccade identification was performed using the Microsaccade Toolbox 0.9 (24). Unless otherwise specified the parameters used for identifying microsaccades were a minimum duration of 6 samples (12 ms) and a velocity threshold scaling factor of 5. All raw data and scripts to reproduce the analysis are available at The mean count of microsaccades pre-caffeine administration was 1.40 (sd 0.52), compared to a post-administration mean of 1.18 (sd 0.43). This was a statistically significant reduction (t(21) = 4.367, p = 0.00027) with a standardised effect size of 0.42 .The pre-post correlation was 0.89 . The stability of microsaccade count as an individual difference measure is visualised in Figure 1.There was no significant correlation between the ASRS score of ADHD traits and either pre-administration microsaccade count or reduction in microsaccade count . We note that 15 of our 22 participants had ASRS scores in the narrow range 20-40.The prior analysis used standardised parameters for microsaccade identification (see method). We confirm that the apparent sensitivity of microsaccade count to caffeine administration is not due to the specific parameters picked to identify microsaccades by recalculating the pre and post caffeine microsaccade counts from the raw data with values of the minimum duration parameter between 2 and 11 samples (6 was our default) and velocity threshold scaling factor between 3 and 8 (5 was our default). The results are shown in Figure 2, confirming that the pre-post difference is not an artifact of choice of microsaccade identification parameters.Note that effect size is well above zero for all combinations of identification parameters, except for the most conservative.It is also possible to use the collected data to ask how stable the obtained results would be if less data had been collected from participants. Our standard analysis uses data from all 60 trials, but we are interested in how stable the results would have been if we had collected fewer trials. Using bootstrap resampling, we calculate 95% confidence ranges for the two summary statistics – pre-post correlation of microsaccade count within subjects, and effect size of pre-post microsaccade count difference. The results are shown in Figure 3 and Figure 4.Figure 5 shows average microsaccade count for each trial, both pre and post caffeine administration. Although later trials, both pre and post, are associated with a higher microsaccade count, the main effect of a lower count post-caffeine is also clearly visible.As predicted, caffeine administration reduced microsaccade count, on average. Additional analysis of the results suggests that microsaccade count has promise as an individual difference measure. There was a high consistency of microsaccade count across our testing sessions, as is desirable for a trait measure. The mean difference pre/post caffeine administration suggests that microsaccade count is sensitive to caffeine, as predicted by earlier work  and by aThe sensitivity analysis suggests that both the individual stability of microsaccade count and the sensitivity of caffeine (as reflected by the between session difference) could be reliably detected with approximately half the number of trials we used.Microsaccades can be measured with low participant effort and are suitable as a repeated measure (i.e. have negligible learning or fatigue effects). Our interest in microsaccades originated because we hoped they would provide a good index of collicular function. This is not directly tested by the present work, which is focused on the sensitivity and stability microsaccade count as a measure. Nonetheless, the present results support the potential of microsaccade count for further investigation as a possible biomarker of drug response, possibly at the collicular level. If microsaccade rate reflects collicular activity levels the measure may provide a means of initially screening potential pharmacotherapies for disorders with a collicular component. Attention Deficit Hyperactivity Disorder may be one such condition, and in that regard it is interesting that adults presenting with ADHD report regular and increased consumption of caffeine through a variety of beverages over time , and adoCircumstantial support for the idea that ADHD may involve collicular hyperactivity include that those higher in ADHD-like traits demonstrate heightened sensitivity to peripheral cues , have anLimitations of the present research which can be addressed in future work include assessing the stability of microsaccade count over longer time periods, and directly comparing caffeine administration with placebo. Factors such as fatigue, attention and arousal have a known influence on microsaccade rate , and so http://biblio.unibe.ch/portale/elibrary/BOP/jemr/ethics.html and that there is no conflict of interest regarding the publication of this paper. The author(s) declare(s) that the contents of the article are in agreement with the ethics described in We wish to thank all participants in the experiment, Maria Panagiotidi, Edwin Dalmaijer for discussion and advice on analysis, and Joel Martin at SR Research for eyetracking support.


Medial vascular calcification (MVC) is a highly prevalent disease associated with a high risk of severe, potentially lethal, complications. While animal studies may not systematically be circumvented, in vitro systems have been proven useful to study disease physiopathology. In the context of MVC, the absence of a clinically relevant standardized in vitro method prevents the appropriate comparison and overall interpretation of results originating from different experiments. The aim of our study is to establish in vitro models mimicking in vivo vascular calcification and to select the best methods to unravel the mechanisms involved in MVC. Human aortic smooth muscle cells and rat aortic rings were cultured in different conditions. The influence of fetal calf serum (FCS), alkaline phosphatase, phosphate and calcium concentrations in the medium were evaluated. We identified culture conditions, including the herein reported Aorta Calcifying Medium (ACM), which allowed a reproducible and specific medial calcification of aortic explants. Studying cells and aortic explants cultured, the involvement of bone morphogenetic protein 2 (BMP2) pathway, fibrosis and apoptosis processes in in vitro MVC were demonstrated. Expression of osteoblastic markers was also observed suggesting the occurrence of transdifferentiation of smooth muscle cells to osteoblasts in our models. The use of these models will help researchers in the field of vascular calcification to achieve reproducible results and allow result comparison in a more consistent way. Medial vascular calcification (MVC), also known as Mönckeberg’s sclerosis, occurs with aging in the general population and may also concern young adults with very prevalent diseases such as diabetes and chroIn keeping with these aims, vascular calcification is explored by in vitro techniques mainly involving two models, vascular smooth muscle cells (VSMC) and aortic rings from different species, commonly human, bovine, mouse and rat. Both cells and aortic rings are cultured with a variety of different calcifying media–12. MostThe methods and systems used to asses MVC involve a variety of pathogenetic mechanisms, some of which, particularly in the proposed “in vitro” systems could reflect only passive deposition and may be unrelated to those observed in human disease conditions. The aim of our study was to establish the most appropriate in vitro models mimicking as much as possible the vascular calcification observed in vivo and to select the best methods to unravel the mechanisms involved in MVC. In particular, we have tested different concentrations of serum, phosphate and calcium and assessed the influence of factors known to enhance calcification such as alkaline phosphatase.2) and then killed by decapitation. Aortas were removed, gently cleaned up, and 2–3 mm rings were cut for culture.The present animal experiments complied with the European and French laws (permit numbers D34-172-25 and 34179) and conform to the Guide for the Care and Use of Laboratory Animals published by the NIH . This study was approved by the local ethics committee “Comité d’éthique pour l’expérimentation animale Languedoc Roussillon N°36”. Six week-old Wistar rats (Charles River Laboratories) were housed in climate controlled conditions with a 12h light/dark cycle in a temperature-controlled room (22±1°C). Rats were fed normal rat chow  and tap water ad libitum. After one week of acclimatation, rats were anesthetized with isoflurane . Different concentrations of fetal calf serum , calcium (Sigma-Aldrich), phosphate (Sigma-Aldrich) and alkaline phosphatase (Promega) were used to induce calcification.Human aortic smooth muscle cells (HASMCs) were grown in smooth muscle cell medium (Science Cell). After the cells were grown to confluence, the smooth muscle cell medium was replaced with serum-free Dulbecco’s modified Eagle’s medium (Sigma-Aldrich) for 24h. Then cells were cultured 2, 3, 7 or 14 days and the basal medium is the Dulbecco’s modified Eagle’s medium containing 4.5 g.LThe thoracic aortas were harvested from the descending part of the aortic cross to the diaphragm. The adjacent connective tissue was gently removed and the aorta was submitted to three successive PBS washings. Aorta was cut in rings of around 2mm thickness and aortic rings were cultured in 24 well plates with culture media and conditions as described above for cell culture.Aortic rings were dehydrated at 110 °C. Cells or dried aortic rings were decalcified with 1mL and 100μL of 0.6 M of HCl, respectively for 24 h. Calcium content was measured in the supernatants using the O-cresolphthalein complexone method according to the instructions provided by the supplier (Biovision). HASMCs were solubilized in 1mL of 0.1M NaOH/0.1% SDS for the protein content determination by the bicinchoninic acid (BCA) protein assay kit (Pierce). Results were normalised to dry weight for aortic rings or protein content for cells.Segments of aorta were fixed in formalin and embedded in paraffin. Five micrometer-thick sections were cut and mounted on glass slides. Some slides were deparaffinized and stained with silver nitrate (Sigma-Aldrich) and counterstained with nuclear Fast Red (Sigma-Aldrich) for evaluation of calcium precipitation by von Kossa staining. Other slides were deparaffinized too and stained with Sirius red (Sigma-Aldrich) for evaluation of collagen localization. Positive signal for collagen was seen in intense red. The sections were mounted in Entelan (Merck) mounting medium and examined under a light microscope (Nikon Eclipse TE300). For each sample, quantification was performed with Image J software on pictures taken from 3 aorta sections at 40-fold magnification or 10 fields of HASMCs at 200-fold magnification. The staining area was measured on aortic medial layer and HASMC fields.™ AQ (Vector Laboratories) and examined under a light microscope (Nikon Eclipse TE300). Quantification was carried out as for histological staining.Immunohistochemical analyses of aorta were performed using paraffin sections. The primary antibodies, anti-osteopontin , anti-osteocalcin  and anti phospho-Smad1  were incubated overnight at 4°C. Revelation was performed with Universal vectastain ABC kit and ImmPACT AEC (Vector Laboratories) following the instructions of suppliers. Then, the sections were mounted in an aqueous mounting medium, VectaMount ™ Colorimetric TUNEL System, Promega, USA). Briefly, sections were deparaffinized, fixed in 10% buffered formalin (Sigma-Aldrich) and immersed in 20 μg.mL-1 proteinase K. Sections were washed in PBS, re-fixed in 10% buffered formalin. After equilibrating, sections were incubated at 37°C with biotinylated nucleotide and the recombinant terminal deoxynucleotidyl transferase (rTdT) enzyme. After washing, sections were blocked in 0.3% H2O2 (Sigma-Aldrich). One section was processed in parallel without rTdT enzyme as negative control. Another section was treated with DNase 1 to cause DNA fragmentation and processed in parallel as positive control. Then, the sections were mounted in Entelan mounting media and examined under a light microscope (Nikon Eclipse TE300). Quantification was carried out as for histological staining.Apoptotic nuclei in aortic wall were identified by TUNEL staining according to the manufacturer’s instructions . Reverse transcription was performed using 1 μg total RNA, anchored oligo-dT and Verso Reverse transcriptase (Thermo Scientific) according to the supplier protocol. For real-time PCR, gene expression levels were measured using SYBR Green I dye chemistry on LightCycler 480 system (Roche Applied Sciences). PCR primers were designed using the LightCycler Probe Design software 2.0 and table of primers is in supplementary data (S1_Table). Expression levels were determined with the LightCycler analysis software (version 3.5) relative to standard curves. Data were represented as the mean level of gene expression relative to the expression of the reference gene GAPDH.All data are expressed as mean ± SEM and analyzed by Analysis of variance (ANOVA) or mixed models. Data transformation was used to approach homoscedasticity. Random effects were included to control for the clustering of cultured aortas obtained from the same animal. Differences between groups were detected with post-hoc Tukey-Kramer’s test. P-values less than 0.05 were considered statistically significant.2PO4/Na2HPO4 as phosphate donor and 0 or 15% FCS. We used wells containing the same medium without cells as internal controls. The highest calcium deposition was observed in HASMCs cultured with high phosphate (3.8 mM) and 0% FCS , one with neutral pH (NaH2PO4 / Na2HPO4) and one with basic pH (Na2HPO4). Acidic, neutral and basic pH showed successively increasing calcium deposits on cells in terms of calcified surface areas as observed by von Kossa staining , which had the weakest calcium staining in the absence of cells and a strong calcium staining of the cells -1 of alkTaken together, these results suggest that FCS is required by alkaline phosphatase to exert its enhancing activity on calcium deposition and that this enhancing activity may be independent of the presence of cells .2PO4 / Na2HPO4). The expression of BMP2 and BMPR1A assessed by qPCR was increased after 48 hours of culture in calcifying medium compared to control medium  characterized by high phosphate (3.8 mM) and calcium (2.4 mM) concentration, 15% FCS and neutral phosphate donor  or high phosphate (3.8 mM). Aortic rings, cultured in the presence of FCS displayed a positive von Kossa staining distributed alongside the medial layer of the arterial explant demonstrating mediacalcosis . No calc2PO4), neutral (NaH2PO4 / Na2HPO4) and basic (Na2HPO4), P = 0.6). In contrast, von Kossa staining suggested differences in the positively stained surface (P = 0.08). Aortic rings cultured with NaH2PO4 / Na2HPO4 as phosphate donor displayed the highest surface area with labelled calcium in the medial layer  in the subsequent experiments.Culture of aortic rings with ACM resulted in medial layer calcification associated with fibrosis (positively labelled Sirius red) and apoptosis (positive for TUNEL assays), To mimic vascular calcification, commonly observed in humans during the normal physiological life span (aging) and in pathological conditions such as chronic kidney disease, different models have been proposed. In vitro systems are preferred when the full animal is not strictly needed. The multiplicity of systems may render difficult comparison and extrapolation of the results of the different reports. The main aim of our study was to evaluate the different factors influencing the yielding and reproducibility of the in vitro calcification systems in order to propose a method which might be used by several groups, allowing proper comparison of the data contributed by a wider community of researchers. Two widely used in vitro models of vascular calcification systems are presented and analysed: in vitro vascular smooth muscle cells and ex vivo aortic ring explants cultured in calcifying conditions. Our data demonstrate the influence of many factors on the calcium content and distribution in cells and tissues to be taken into account when performing calcification experiments, and even more importantly when interpreting the results of such experiments. We described the influence of the type of phosphate donor, the presence of FCS in the culture medium, the phosphate and calcium concentrations and the presence of alkaline phosphatase. In addition to individual effects, complex interactions between factors were present, which could vary between cell and aortic ring models. Use of internal controls, reproducibility and cautious interpretation of the results are main aspects to consider when using an in vitro system in the study of vascular calcification. Still, when adequately assessed, in vitro systems allow the characterization of phenomena participating in the calcification process, such as the involvement of the BMP2 pathway, the expression of osteoblastic genes and proteins, and changes in fibrosis and in apoptosis processes. The expression of BMP2 is upregulated in human arteries with medial calcification and BMP2In vitro techniques can be useful to study the implication of one protein or pathway, however they may also provide results that are unrelated or unimportant for vascular calcification as suggested by Hortells et al. Our app4), elevated in CKD patients, has been considered to be central in vascular calcification until recently.Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: YesReviewer #2: YesReviewer #3: YesReviewer #4: Yes**********2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: YesReviewer #2: YesReviewer #3: YesReviewer #4: Yes**********3. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: YesReviewer #2: YesReviewer #3: YesReviewer #4: Yes**********4. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: YesReviewer #3: YesReviewer #4: Yes**********5. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: COMMENTS FOR AUTHORSPlosONEMANUSCRIPT # PONE-D-19-33486 REVIEWER # 1Nathalie GayrardOptimization of cell and ex vivo culture 1 conditions to study vascular calcificationThe authors of this manuscript establish in vitro models mimicking in vivo vascular calcification and to select an optimal method to unravel the mechanisms involved in medial vascular calcification. The authors identified culture conditions, which allowed a reproducible and specific medial calcification of aortic explants as well as calcification of human aortic smooth muscle cells. The authors concluded these approaches will help to achieve reproducible results and allow result comparison in a consistent way.The data presented in this manuscript are interesting for terms of analyses of vascular calcification processes. However, the reviewer has some major remarks:Major points:1. The introduction section has to be revised. The authors should focus on the main topic of the manuscript and should avoid an very general description of the methods available for the investigation of vascular calcification processes .2. The authors should prepare a table demonstrating the condition analyze within the study.3. NG, KM, FD and AA are obviously employees of a company (RD-Nephrologie). A statement has to be added whether these authors have to declare a conflict of interest based on the employment.4. Figure 3.B: A bar graph demonstrating the quantification of Phosphosmad1 should be added.5. Not significant data has to be removed from the revised version of the manuscript 6. The authors should discuss the overall aim of the study in the discussion section in more detail.7. Some typos should be removed in the revised version of the manuscript, e.g. page 9, line 169 (3.8mM instead of 3.8 mM).Reviewer #2: This experiment allows overcoming of an ethical issue for using animal models in experiments of vascular calcification research as one of the most important outcome for experiencing major cardiovascular events in humans as a topic for research, although the authors well pointed out the extrapolation of the data should be taken carefully into account.Reviewer #3: The aim of this study is to analyze in vitro and ex vivo models of vascular calcification and to select factors that may affect the process of calcification.Th study is well performed and I cannot identify methodological defectsHowever there are points that should be clarified-Fig1 shows that calcium deposits in HASMCs cultured with high phosphate(3.8 mM) are decreased by supplementing with 15% FCS. It is important to determine if ionized calcium and the concentration of phosphate are modified by 15% FCS. It is know that FCS contains large proteins “calciproteins” that may substract Ca and P from the solution. At least the authors should evaluate if for a given pH, FCS modifies the Ca x P product.-The total calcium content in the wells was significantly increased in thewells with cells cultured with the basic P donor only (P < 0.001) vs acidic and neutralconditions. It is likely that the high pH is increasing calcium deposit the opposed is expected to occur in acid pH. Again ionized Ca and pH should be measured minute after the addition of the different forms of phosphate.-It seems that FCS is required by alkaline phosphatase to increase activity on calcium deposition and that this enhancing activity may be independent of the presence of cells . It will be important to analyze if FCS contains pyrophosphate; hydrolysis of pyrophosphate by alkaline phosphatase may affect calcification-The authors state the the optimal culture conditions to obtain medial calcification of aortic rings were 15% FCS supplemented medium without alkaline phosphatase. Thus data should be contrasted with results by KI 2008 73(9):1024 .Reviewer #4: The authors address a key problem in calcification research, which is the lack of reproducibility of in vitro calcification set ups. I have only minor comments.1. What was the cell culture media pH for different phosphate donors used to induce calcification?2. Please indicate the number of times that experiments were repeated and provide DS for graphs without DS3. Specifically, for the optimal ACM, please indicate whether every time the experiment was repeated, calcification was obtained or whether there are still some uncontrolled factors that may prevent calcification in certain experiments4. Please in the discussion, add the concentrations of calcium and phosphate used in mg/dl, which are commonly used units in many countries, so as readers can easily contextualize to the clinical situation. Since calcium binds albumin and albumin levels in 15% FCS are lower than in 100% human serum, please discuss what would be the free calcium and total calcium equivalent of the concentrations used in experiments.**********what does this mean?). If published, this will include your full peer review and any attached files.6. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  14 Feb 2020Dear Editor,Please find enclosed the response to reviewers. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. We checked the style requirementshttp://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.2. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see The complete data are available in supplemental data, S2_Table Datahttps://journals.plos.org/plosone/s/figures#loc-blot-and-gel-reporting-requirements and https://journals.plos.org/plosone/s/figures#loc-preparing-figures-from-image-files. When you submit your revised manuscript, please ensure that your figures adhere fully to these guidelines and provide the original underlying images for all blot or gel data reported in your submission. See the following link for instructions on providing the original image data: https://journals.plos.org/plosone/s/figures#loc-original-images-for-blots-and-gels.3. PLOS ONE now requires that authors provide the original uncropped and unadjusted images underlying all blot or gel results reported in a submission’s figures or Supporting Information files. This policy and the journal’s other requirements for blot/gel reporting and figure preparation are described in detail at plosone@plos.org if you have any questions.In your cover letter, please note whether your blot/gel image data are in Supporting Information or posted at a public data repository, provide the repository URL if relevant, and provide specific details as to which raw blot/gel images, if any, are not available. Email us at Blot/gel image data are in Supporting Information, S5_raw_images WB phosphosmad1 day 3 original images Figure 3B.pdf and S6_raw_images WB phosphosmad1 day 7 original images Figure 3B.pdfhttp://journals.plos.org/plosone/s/supporting-information.4. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: OkReviewer #1: COMMENTS FOR AUTHORSPlosONEMANUSCRIPT # PONE-D-19-33486 REVIEWER # 1Nathalie GayrardOptimization of cell and ex vivo culture 1 conditions to study vascular calcificationThe authors of this manuscript establish in vitro models mimicking in vivo vascular calcification and to select an optimal method to unravel the mechanisms involved in medial vascular calcification. The authors identified culture conditions, which allowed a reproducible and specific medial calcification of aortic explants as well as calcification of human aortic smooth muscle cells. The authors concluded these approaches will help to achieve reproducible results and allow result comparison in a consistent way.The data presented in this manuscript are interesting for terms of analyses of vascular calcification processes. However, the reviewer has some major remarks:Major points:1. The introduction section has to be revised. The authors should focus on the main topic of the manuscript and should avoid an very general description of the methods available for the investigation of vascular calcification processes .The introduction has been revised following the suggestion of the reviewer and two references have been added.2. The authors should prepare a table demonstrating the condition analyze within the study.A supplementary table including all the culture conditions as required by the reviewer has been added to the manuscript .3. NG, KM, FD and AA are obviously employees of a company (RD-Nephrologie). A statement has to be added whether these authors have to declare a conflict of interest based on the employment.NG, KM FD and AA are employees of RD – Néphrologie and have declared to have no conflict of interest.4. Figure 3.B: A bar graph demonstrating the quantification of Phosphosmad1 should be added.The bar graph requested by the reviewer with the quantification of phosphosmad1 has been added to the figure 3B and the complete data have been included in the supplemental data file, S2_Table Data5. Not significant data has to be removed from the revised version of the manuscript The paragraph alluded to by the reviewer has been removed as requested 6. The authors should discuss the overall aim of the study in the discussion section in more detail.The overall aim of the manuscript has been now better presented in the discussion section of the new version of the manuscript.7. Some typos should be removed in the revised version of the manuscript, e.g. page 9, line 169 (3.8mM instead of 3.8 mM). The typos have been correctedReviewer #2: This experiment allows overcoming of an ethical issue for using animal models in experiments of vascular calcification research as one of the most important outcome for experiencing major cardiovascular events in humans as a topic for research, although the authors well pointed out the extrapolation of the data should be taken carefully into account.Reviewer #3: The aim of this study is to analyze in vitro and ex vivo models of vascular calcification and to select factors that may affect the process of calcification.Th study is well performed and I cannot identify methodological defectsHowever there are points that should be clarified-Fig1 shows that calcium deposits in HASMCs cultured with high phosphate(3.8 mM) are decreased by supplementing with 15% FCS. It is important to determine if ionized calcium and the concentration of phosphate are modified by 15% FCS. It is know that FCS contains large proteins “calciproteins” that may substract Ca and P from the solution. At least the authors should evaluate if for a given pH, FCS modifies the Ca x P product.The remark of the reviewer is very pertinent. We checked, as suggested by the reviewer, the pH and the content of calcium and phosphate in both, serum free and serum supplemented media. The pH was 7.6 in both media showing that the DMEM medium used is highly buffered. Concerning the calcium content it was 1.9mM and 2.2mMy while the phosphate was 3mM and 3,25mM without and with 15% FCS respectively. The Ca x P product was 5.7 and 7.2 in 0% and 15% FCS medium respectively. Unfortunately, we were not able to measure the ionised calcium, as we do not have specific electrodes to do so. Therefore, the putative substraction of calcium and phosphate from the culture medium by the serum components added in 15% FCS conditions was not observed in our experiments. By the contrary, the slight increase in Ca x Phos product might be the result of the addition of the calcium and phosphate contained in the FCS.-The total calcium content in the wells was significantly increased in thewells with cells cultured with the basic P donor only (P < 0.001) vs acidic and neutralconditions. It is likely that the high pH is increasing calcium deposit the opposed is expected to occur in acid pH. Again ionized Ca and pH should be measured minute after the addition of the different forms of phosphate.The pH of culture medium was 7,6 for all the medium and was not modified by P donors. Unbound calcium was also measured and no difference was observed between the media with different P donors. The results are given in the S4_Medium calcium concentration of the open data.-It seems that FCS is required by alkaline phosphatase to increase activity on calcium deposition and that this enhancing activity may be independent of the presence of cells . It will be important to analyze if FCS contains pyrophosphate; hydrolysis of pyrophosphate by alkaline phosphatase may affect calcification.The interaction between pyrophosphate and alkaline phosphatase is an interesting and probably very complex point. We included alkaline phosphatase effects on the tested media, both for cell culture systems and aortic explants on that basis. However, the surprising effects observed in both systems, with the decrease in the calcification of the aortic explants in the presence of alkaline phosphatase, led us to remove it from the proposed medium, as already stated in the discussion section (page 19). As underlined by reviewer #1 the main aim of the present paper was to find a calcifying system optimised to be proposed to a wider group of researchers interested in calcification processes. The interaction between pyrophosphate and alkaline phosphatase may be proposed as a separate topic to be explored in a completely different project. -The authors state the optimal culture conditions to obtain medial calcification of aortic rings were 15% FCS supplemented medium without alkaline phosphatase. Thus data should be contrasted with results by KI 2008 73(9):1024.The article of Lomashvili, has been commented (reference #28) and the results contrasted with our findings in the new version of the manuscript. Reviewer #4: The authors address a key problem in calcification research, which is the lack of reproducibility of in vitro calcification set ups. I have only minor comments.1. What was the cell culture media pH for different phosphate donors used to induce calcification?The pH was 7.6 for all the culture media except for the culture media without FCS the pH was 7.9.2. Please indicate the number of times that experiments were repeated and provide DS for graphs without DSThe complete data of all the experiments performed are now available in the supplemental data (S2 of the present version). In it it can be found the number of repeats for all the experiments. 3. Specifically, for the optimal ACM, please indicate whether every time the experiment was repeated, calcification was obtained or whether there are still some uncontrolled factors that may prevent calcification in certain experiments.Calcification was obtained every time when using optimal ACM. However, the amount of calcium and calcium deposits may vary when changing the batch of FCS. 4. Please in the discussion, add the concentrations of calcium and phosphate used in mg/dl, which are commonly used units in many countries, so as readers can easily contextualize to the clinical situation. Since calcium binds albumin and albumin levels in 15% FCS are lower than in 100% human serum, please discuss what would be the free calcium and total calcium equivalent of the concentrations used in experiments.We added the equivalent concentration in the discussion in mg/dL in brackets. We understand the willingness of the reviewer in trying to make an easy parallelism between the proposed experimental systems and the clinical situation. However, we have to keep in mind that the in vitro and ex vivo settings are far from the in vivo and clinical situations and trying to make any equivalence is a hazardous approach that may be misleading and we would like to avoid if possible.AttachmentResponse to Reviewers.docxSubmitted filename: Click here for additional data file. 25 Feb 2020 ex vivo  culture conditions to study vascular calcificationOptimisation of cell and PONE-D-19-33486R1Dear Dr. gayrard,We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.Within one week, you will receive an e-mail containing information on the amendments required prior to publication. 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Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact With kind regards,Harald MischakAcademic EditorPLOS ONEAdditional Editor Comments :Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.Reviewer #3: All comments have been addressedReviewer #4: All comments have been addressed**********2. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #3: YesReviewer #4: Yes**********3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #3: YesReviewer #4: Yes**********4. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #3: YesReviewer #4: Yes**********5. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #3: YesReviewer #4: Yes**********6. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #3: All comments have been addressed. I do not think that additional experiments are required. The data definitely support the conclusionReviewer #4: (No Response)**********what does this mean?). If published, this will include your full peer review and any attached files.7. PLOS authors have the option to publish the peer review history of their article (If you choose “no”, your identity will remain anonymous but your review may still be made public.Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.Reviewer #3: NoReviewer #4: No 27 Feb 2020PONE-D-19-33486R1  ex vivo  culture conditions to study vascular calcification Optimisation of cell and Dear Dr. gayrard:I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! 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