Parhyale hawaiensis with multi-view light-sheet microscopy at high spatiotemporal resolution over several days of embryogenesis. The cell lineage of outgrowing thoracic limbs was reconstructed at single-cell resolution with new software called Massive Multi-view Tracker (MaMuT). In silico clonal analyses suggested that the early limb primordium becomes subdivided into anterior-posterior and dorsal-ventral compartments whose boundaries intersect at the distal tip of the growing limb. Limb-bud formation is associated with spatial modulation of cell proliferation, while limb elongation is also driven by preferential orientation of cell divisions along the proximal-distal growth axis. Cellular reconstructions were predictive of the expression patterns of limb development genes including the BMP morphogen Decapentaplegic.During development, coordinated cell behaviors orchestrate tissue and organ morphogenesis. Detailed descriptions of cell lineages and behaviors provide a powerful framework to elucidate the mechanisms of morphogenesis. To study the cellular basis of limb development, we imaged transgenic fluorescently-labeled embryos from the crustacean  During early life, animals develop from a single fertilized egg cell to hundreds, millions or even trillions of cells. These cells specialize to do different tasks; forming different tissues and organs like muscle, skin, lungs and liver. For more than a century, scientists have strived to understand the details of how animal cells become different and specialize, and have created many new techniques and technologies to help them achieve this goal.Parhyale hawaiensis, to study development, including limb growth. This species is useful because it is easy to grow, manipulate and observe its developing young in the laboratory. Understanding how its limbs develop offers important new insights into how limbs develop in other animals too. Wolff, Tinevez, Pietzsch et al. have now combined advanced microscopy with custom computer software, called Massive Multi-view Tracker (MaMuT) to investigate this.Limbs – such as arms, legs and wings – form from small lumps of cells called limb buds. Scientists use the shrimp-like crustacean, Parhyale, the MaMuT software tracks how cells behave, and how they are organized. This analysis revealed that for cells to produce a limb bud, they need to split at an early stage into separate groups. These groups are organized along two body axes, one that goes from head to tail, and one that runs from back to belly. The limb grows perpendicular to these main body axes, along a new ‘proximal-distal’ axis that goes from nearest to furthest from the body. Wolff et al. found that the cells that contribute to the extremities of the limb divide faster than the ones that stay closer to the body. Finally, the results show that when cells in a limb divide, they mostly divide along the proximal-distal axis, producing one cell that is further from the body than the other. These cell activities may help limbs to get longer as they grow.As limbs develop in Notably, the groups of cells seen by Wolff et al. were expressing genes that had previously been identified in developing limbs. This helps to validate the new results and to identify which active genes control the behaviors of the analyzed cells.These findings reveal new ways to study animal development. This approach could have many research uses and may help to link the mechanisms of cell biology to their effects. It could also contribute to new understanding of developmental and genetic conditions that affect human health. Morphogenesis, or the origin of biological form, is one of the oldest and most enduring problems in biology. Embryonic tissues change their size and shape during development through patterned cell activities controlled by intricate physico-chemical mechanisms . DevelopParhyale hawaiensis that satisfies a number of appealing biological and technical requirements for multi-level studies of appendage (limb) morphogenesis  into a single output z-stack, and visualization of the raw and fused images . These pParhyale LSFM datasets with MaMuT to understand the cellular basis of arthropod limb morphogenesis. As revealed by lineage tracing experiments in the leading arthropod model Drosophila melanogaster, the leg and wing primordia become progressively subdivided into distinct cell populations  along the anterior-posterior (AP) and dorsal-ventral (DV) axes  axes . Tissue DV) axes .Drosophila wing and other growing organs (Drosophila limbs (primarily the wing disc) using clonal analysis and lineage tracing across fixed specimens . A typical 4 to 5 day long recording was composed of more than 1 million images resulting in >7 TB datasets.Three-day old transgenic embryos with fluorescently labeled nuclei were mounted for LSFM in low melting agarose with scattered fluorescent beads. Several parameters were optimized to cover all stages of Parhyale development enabled imaging of each embryo from multiple highly overlapping views with minimal displacement of nuclei between views acquired in each time-point  at 25˚C. Over the next 4 days, limb buds bulged out ventrally, elongated along their PD axis and became progressively segmented until they acquired their definite morphology at around 8 days AEL  and detailed tutorials and training datasets can be found at http://imagej.net/MaMuT.To examine the cellular basis of morphogenesis, we developed a novel Fiji plugin to extract cell lineages from multi-view and multi-terabyte datasets. This tool was dubbed MaMuT for Massive Multi-view Tracker  and is aMaMuT is an interactive, user-friendly tool for visualization, annotation, tracking and lineage reconstruction of large multi-dimensional microscopy data . It is aParhyale thoracic limb. By convention, Parhyale parasegments are identified by ascending indices E1, E2, E3 etc., the AP rows of ectodermal cells in each parasegment by the letters a, b, c and d, and the DV columns of cells in each parasegment by numbers  gene that marks the posterior compartment  would stay separate and form a lasting straight interface between them. This analysis suggested that there is indeed a DV separation that took place at the 4-row-parasegment. The DV boundary ran between the E4b and c rows anteriorly, between the E5a and b rows posteriorly, and between cells E4c4-c5, E4d3-d4 and E5a4-a5 medially . ThroughParhyale limbs, we analyzed a second, independently imaged and reconstructed T2 limb (referred to as limb#2) from a different embryo (To investigate the stereotypy of the AP and DV separation across t embryo . Four idt embryo –H’. ThesThe first T2 limb (limb#1) was lineaged with the new MaMuT software from a multi-view acquisition of an embryo imaged at 26˚C , while tWe then examined the increase in cell number over time in the two limbs during the analyzed stages of limb outgrowth. The embryo with limb#2 imaged at higher temperature exhibited a faster growth rate compared to the embryo with limb#1 . Yet, itLimb bud formation entailed the remodeling of the flat epithelium into a 3D bulge . At the Two cell behaviors implicated in organ morphogenesis were readily quantifiable in our nuclear trackings: the pattern of cell proliferation and the orientation of cell divisions. These cell activities have been traditionally inferred from the distribution, size and shape of somatic clones induced in developing tissues . This apFirst, we calculated the cell cycle length (CCL), i.e. the branch length for every constituent cell in the lineage of limb#1 . This quTo explore the levels of variability in the pattern of cell divisions, we performed a hierarchical clustering of the founder cells within each of the two analyzed T2 limbs based on a lineage distance metric computed from the division patterns exhibited by the 34 cells . This analysis revealed very similar profiles in the two limbs, as well as their average, with their cells forming three clusters : the firParhyale limb outgrowth is driven by at least two patterned cell behaviors: the differential rates of cell proliferation and the orderly arrangement of mitotic spindles.Next, we looked for any biases in the orientation of mitotic divisions that could be associated with limb morphogenesis . All earTo understand the cellular basis of the establishment of positional values along the PD axis, we followed the fate of cells during T2 limb#1 segmentation. Segmentation involved the progressive subdivision of the elongating PD axis into an increasing number of elements . We tracThis analysis showed that the cells that gave rise to the proximal, medial and distal limb segments occupied distinct mediolateral positions in the germband grid at the 4-row-parasegment  and distParhyale decapentaplegic (Ph-dpp) gene that encodes a Bone Morphogenetic Protein 2/4 signaling molecule  columns and the border between high/moderate and low/no expressing cells was located in descendent cells from column 4 as also predicted by our in silico cellular analysis  gene  was detected in a subset of the Ph-dpp-expressing cells at 84–96 hr AEL  gene  that resleg disc . Express6 hr AEL , while 16 hr AEL . In both compare  providinParhyale H15 (Ph-H15) gene during early limb formation  a semi-automated option where individual nuclei can be selected by the user and tracked computationally over time, and (ii) the option to import into MaMuT fully automated annotations generated by the Tracking with Gaussian Mixture Models (TGMM) software , which iParhyale is already an attractive new model for developmental genetic and functional genomic studies , has demonstrated that the AP separation is conserved across arthropods and takes place during segmentation  and the periphery (slower dividing) of the limb primordium from early specification until limb bud formation. Such a growth-based morphogenesis model has been the dominant hypothesis for almost 50 years to explain the outgrowth of the vertebrate limb  – orientArtemia . Second,Overall, our approach demonstrates that the comprehensive fine-scale reconstruction of a developmental process can shed light into functionally interdependent patterning mechanisms operating across multiple scales.Drosophila leg disc, the Dpp and Wg ligands are induced at the AP boundary in the dorsal and ventral cells, respectively. Dpp and Wg create a concentration gradient with the highest overlap in their expression in the center of the disc and cooperate in the establishment of concentric domains of gene expression of a set of limb gap genes that pattern the PD axis  is located between descendent cells from columns 4 and 5. These are indeed the cells that contribute to the distal-most limb segments.The PD expression of the limb gap genes is conserved in arthropods, including Parhyale . Our anaDrosophila limbs is well understood, its role in promoting growth is still controversial  and Dmel_H2B_R_XhoI (5’-ACTTCTCGAGTTTAGAGCTGGTGTACTTGG-3’), and mRFPruby was amplified from plasmid pH2B-mRFPruby  survived the recording process and hatched into juveniles without any morphological abnormalities, and (ii) were imaged with the appropriate spatiotemporal resolution and signal-to-noise ratio for accurate and comprehensive cell tracking in developing appendages.Standard procedures for multi-view LSFM recordings of To prepare embryos for LSFM imaging, 2.5 day old transgenic embryos  were heParhyale embryogenesis from three angles/views  during 3 to 4.5 days AEL to avoid photo-damaging the dorsal thin extra-embryonic tissue, and continued imaging from five views  during 4.5 to 8 days AEL. A multi-view acquisition was made every 7.5 min at 26˚C. The H2B-mRFPruby fluorescence levels were replenished regularly every 12 hr by raising the temperature in the chamber from 26˚C to 37˚C and heat-shocking the embryo for 1 hr. Each view (z-stack) was composed of 250 16-bit frames with voxel size 0.254 µm x 0.254 µm x 1 µm. Each 1920x1920 pixel frame was acquired using two pivoting light-sheets to achieve a more homogeneous illumination and reduced image distortions caused by light scattering and absorption across the field of view. Each optical slice was acquired with a 561 nm laser and exposure time of 50 msec. With these conditions, Parhyale embryos, like the one bearing the T2 limb#1 analyzed in detail with MaMuT, were imaged routinely for a minimum of 4 days or even up to hatching. After hatching, the morphology of imaged specimen was compared between the left and the right side, as well as to its non-imaged siblings, to confirm that no obvious developmental or morphological abnormalities were detected.We started imaging The embryo bearing the T2 limb#2 was imaged on a Zeiss LSFM prototype  that offParhyale LSFM acquisitions typically resulted in 192 time-points/240K images/1.7 TB of raw data per day. Image processing was carried out on a MS Windows 7 Professional 64-bit workstation with 2 Intel Xeon E5-2687W processors, 256 GB RAM (16 X DIMMs 16384 MB 1600 MHz ECC DDR3), 4.8 TB hard disk space , 2 NVIDIA Quadro K4000 graphics cards (3 GB GDDR5). The workstation was connected through a 10 GB network interface to a MS Windows 2008 Server with 2 Intel Xeon E5-2680 processors, 196 GB RAM (24 X DIMM 8192 MB 1600 MHz ECC DDR3) and 144 TB hard disk space (36 X Seagate Constellation ES.3 4000 GB 7200 RPM 128 MB Cache SAS 6.0 Gb/s). All major LSFM image data processing steps were done with software modules available through the Multiview Reconstruction Fiji plugin (http://imagej.net/Multiview-Reconstruction) according to the following steps:Preprocessing: Image data acquired on Zeiss Lightsheet Z.1 were saved as an array of czi files labeled with ascending indices, where each file represented one view (z-stack). czi files were first renamed into the ‘spim_TL{t}_Angle{a}.czi’ filename, where t represented the time-point (e.g. 1 to 192 for a 1 day recording) and a the angle , and then resaved as tif files.Bead-based spatial multi-view registration: In each time-point, all views were aligned to eachother and to an arbitrary reference view fixed in 3D space  using the bead-based registration option . In eachFusion by multi-view deconvolution: Spatially registered views were down-sampled twice for time and memory efficient computations during the image fusion step. Input views were then fused into a single output 3D image with a more isotropic resolution using the Fiji plugin for multi-view deconvolution estimated from the point spread function of the fluorescent beads . The samBead-based temporal registration: To correct for small drifts of the embryo over the extended imaging periods (e.g. due to agarose instabilities), we stabilized the fused volume over time using the segmented beads (sigma = 1.8 and intensity threshold = 0.005) for temporal registration with the affine transformation model using an all-to-all matching within a sliding window of 5 time-points.Computation of spatiotemporally registered fused volumes: Using the temporal registration parameters, we generated a stabilized time-series of the fused deconvolved 3D images.Parhyale embryo was rendered over time from the spatiotemporally registered fused data using Fiji’s 3D Viewer.4D rendering: The Parhyale allows capturing cells from two or more neighboring views that can be interpreted independently for a more accurate analysis. Finally, MaMuT allows users to analyze sub-optimal datasets that cannot be fused properly or may create fusion artifacts. Of course, combining the raw views with a high-quality fused volume is the best available option, especially when handling complex datasets with high cell densities.MaMuT was developed as a tool for cell lineaging in multi-view LSFM image volumes by enabling to track objects synergistically from all available views. This functionality has a number of advantages. Raw views do not have to be fused into a single volume, which is computationally by far the most demanding step . The useWhile offering multi-view tracking, MaMuT delivers also other important functionalities. First, it is a turnkey software solution with a convenient interface for interactive exploration, annotation and curation of image data. Any image acquired by any microscopy modality that can be opened in Fiji can be also imported into MaMuT. Second, MaMuT offers a highly responsive and interactive navigation through multi-terabyte datasets. Individual z-stacks representing different views, channels and time-points of a multi-dimensional dataset can be displayed independently or in combinations in multiple synced Viewer windows. Third, objects of interest like cells and nuclei (spots) can be selected synergistically from all available Viewers and followed over time to reconstruct their trajectories (tracks) and lineage information. Fourth, the created spots and tracks can be visualized and edited interactively in the Viewers and the TrackScheme lineage browser, and animated in the 3D Viewer. For visual interpretation of the data, annotations can be colored based on the primary lineage information or derived numerical parameters. Fifth, lineages can be reconstructed in a manual, semi-automated or fully automated manner followed by manual curation if necessary. Sixth, all spot and track information can be exported from MaMuT to other interfaces for more specialized analyses. Seventh, decentralized annotation by multiple users has been made possible by also developing a web service for remote access to large image volumes stored online. Following on the tradition of the Fiji community for open-source distribution of biological image analysis software, MaMuT is provided freely and openly to the community, it is extensively documented and can be customized by other users.Parhyale multi-view LSFM raw views were registered spatiotemporally and the image data together with the registration parameters were converted into the custom HDF5/XML file formats utilized by the BigDataViewer and MaMuT Fiji plugins. The MaMuT reconstruction of the Parhyale T2 limb described in this article required about 10 weeks of dedicated manual cell tracking by an experienced annotator. The raw image data were displayed in Viewer windows and each z-stack was visualized in any desired color and brightness, scale (zoom), translation (position) and rotation (orientation). All Viewer windows were synced based on the calculated registration parameters and shared a common physical coordinate system; upon selecting an object of interest (spot) in one Viewer, the same spot was identified and displayed in all other windows, and its x, y, z position was mapped onto this common physical space. To guarantee the accuracy of our lineage reconstructions, the center of each tracked nucleus was verified in at least two neighboring views and by slicing the data orthogonally in separate Viewer windows. The nuclei contributing to the T2 limb of interest were identified in the first time-point and tracked manually every five time-points except during mitosis, in which case we also tracked one time-point before and one after segregation of the daughter chromosomes during anaphase/telophase. The reconstructed trajectories and lineages were also displayed in two additional synced windows, the TrackScheme and the 3D Viewer. The TrackScheme lineage browser and editor displayed the reconstructed cell lineage tree with tracked nuclei represented as nodes connected by edges over time and cell divisions depicted as split branches in the tree. The 3D Viewer window displayed interactive animations of the spots depicted as spheres and their tracks over time. The spots and the tracks in the Viewer, TrackScheme and 3D Viewer windows could be color-coded by lineage, position and other numerical features to assist visual analysis and interpretation of the data. In addition, all these windows were synced to simultaneously highlight active spots of interest at the selected time-point, greatly facilitating the cell lineaging process.In practical terms, for lineaging purposes, the L that starts with cell d. Cell d divides at time L as For comparative purposes, each reconstructed lineage tree was defined as a set of division times. For example, let’s consider a lineage tree Let’s now consider two lineage trees We then defined In this equation, To calculate The pairing We then define Parhyale T2 limb, we combined for each founder cell the information from the two limbs. The average lineage tree Once we computed all the pairwise distances between lineages of the cells under comparison, hierarchical clustering was performed using Ward’s method. For the hierarchical clustering in the average Parhyale decapentaplegic (Ph-dpp), Dorsocross (Ph-Doc), engrailed-2 (Ph-en2) and H15 (Ph-H15) genes were identified by BLAST analysis against the Parhyale transcriptome and genome  and two reviewers, one of whom, Alejandro Sánchez Alvarado (Reviewer #1), is a member of our Board of Reviewing Editors. The following individual involved in review of your submission has agreed to reveal their identity: Andreas Hejnol (Reviewer #2).Thank you for submitting your article "Reconstruction of cell lineages in arthropod limbs with multi-view light-sheet imaging and tracking" 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.Summary:Parhyale hawaiensis embryogenesis. MaMuT is designed to execute cell tracking in multidimensional datasets. In particular, the authors attempt to quantify multiview light-sheet data of the morphogenetic cellular behaviors operating during the direct development of arthropod limbs.This Tools and Resources paper by Wolff et al., describes the application of a new Fiji plug-in named MaMuT to the study of The reviewers agree that this effort is of great interest to the community of developmental biologists interested in real-time imaging quantification. More importantly, the fact that the software is open source will allow the community to put MaMuT through its paces and eventually help determine its range of utility and limitations.Essential revisions:Before the manuscript can be further considered, the authors must address the following concerns:not about arthropod limbs in general but about a single arthropod limb in a single embryo of a single species. As such, it is misleading and should be changed to reflect what the paper is really about: a method to do cell tracking.1) The title is not justified. As written this paper is 2) The text of the manuscript tends to be somewhat hyperbolic at places. We believe this is not necessary given the quality of the data presented. An additional shortcoming of doing this is that it prevents the readers to assess the utility of the method as little to no effort is put forward to describe its limitations. We suggest that the authors spend some time to write text in the manuscript discussing the limitations of the method being reported.3) Although proof-of-principle of the method presented is deftly described in this manuscript, an important question remains unanswered, which is, how much variability there may or may not be between individual specimens? No direct comparison between the two thoracic limbs is reported. Are these different? If so, how different? Given the purpose of cell tracking, it matters both biologically and methodologically speaking whether or not there are cell number differences, positional variability, and stereotypic versus stochastic behaviors. For instance, if the behavior recorded is stereotypic, the authors can provide names of the individual cells that can be probably recognized in both legs and thus provide the first identification of individual cells which then can be used for comparisons between legs. Also, why is there no comparison between the T2 data with a detailed analysis of a pleopod of choice? Pleopods show a different morphology and one could learn about the changes cells undergo to create different morphologies. It seems the data has already been generated and is in the authors' hands. Given that the Discussion contains notable amounts of speculations on how changes in cell patterns can lead to changes in morphology and how gene expression relate to this, why not demonstrate it in this work? In sum, all of these factors impinge upon gene expression pattern interpretations and should be addressed/discussed by the authors.4) Looking through the data, we had difficulties determining how time-consuming this method may or may not be. This is important to know if, for example, more than one object were to be analyzed or for experiments in which multiple samples need to be measured and compared to each other. The authors could provide the reader with a timeline or with suggestions of how to increase the throughput of this method. Essential revisions:Before the manuscript can be further considered, the authors must address the following concerns:1) The title is not justified. As written this paper is not about arthropod limbs in general but about a single arthropod limb in a single embryo of a single species. As such, it is misleading and should be changed to reflect what the paper is really about: a method to do cell tracking.Parhyale embryos. Therefore, we appreciate the reviewers’ remark and have modified the title of our article as follows: “Multi-view light-sheet imaging and tracking with the MaMuT software reveals the cell lineage of a direct developing arthropod limb”Our article describes the development of MaMuT for cell tracking and lineage reconstruction in specimens imaged with multi-view light-sheet microscopy. As a first application and proof of principle for MaMuT’s functionalities, we have revealed the cellular architecture and dynamics underlying direct outgrowth of a single limb type in imaged 2) The text of the manuscript tends to be somewhat hyperbolic at places. We believe this is not necessary given the quality of the data presented. An additional shortcoming of doing this is that it prevents the readers to assess the utility of the method as little to no effort is put forward to describe its limitations. We suggest that the authors spend some time to write text in the manuscript discussing the limitations of the method being reported.Parhyale embryogenesis with multi-view LSFM and MaMuT” in the Discussion:We have addressed the reviewers’ concerns by modifying the text. In this context, we also discuss the limitations of our methodology with regard to the laborious and repetitive nature of manual cell tracking, as well as the partial incompatibility of MaMuT to handle the hundred thousands or millions of annotations that can be generated from automated segmentation and tracking approaches. The paragraph discussing these limitations has been expanded and transferred from Materials and methods to the section “Reconstruction of “The lineage reconstructions presented in this article were generated manually and required 2 to 3 months for each limb. […] As a trade-off until this constraint is addressed in the future, we also provide users the option to crop the imported TGMM annotations in space and/or in time to make them compatible with MaMuT.”3) Although proof-of-principle of the method presented is deftly described in this manuscript, an important question remains unanswered, which is, how much variability there may or may not be between individual specimens? No direct comparison between the two thoracic limbs is reported. Are these different? If so, how different? Given the purpose of cell tracking, it matters both biologically and methodologically speaking whether or not there are cell number differences, positional variability, and stereotypic versus stochastic behaviors. For instance, if the behavior recorded is stereotypic, the authors can provide names of the individual cells that can be probably recognized in both legs and thus provide the first identification of individual cells which then can be used for comparisons between legs. Also, why is there no comparison between the T2 data with a detailed analysis of a pleopod of choice? Pleopods show a different morphology and one could learn about the changes cells undergo to create different morphologies. It seems the data has already been generated and is in the authors' hands. Given that the Discussion contains notable amounts of speculations on how changes in cell patterns can lead to changes in morphology and how gene expression relate to this, why not demonstrate it in this work? In sum, all of these factors impinge upon gene expression pattern interpretations and should be addressed/discussed by the authors.We agree with the reviewers that our article would benefit from the comparison between the two reconstructed T2 limbs. Therefore, we performed such comparison facilitated crucially by Léo Guignard, who has been added to the author list. In particular, i) we compared the birth time of the 34 founder cells in each limb primordium, ii) we compared the increase in cell number as a proxy for the growth rate of each limb, iii) we devised a new metric to compare lineage trees based on the timing and number of divisions, iv) we used this metric to perform a hierarchical clustering of the 34 founder cells in each limb, and v) we used this metric to compare the cell lineages between homologous and non-homologous cells in the two limbs. These analyses are shown in the two new Figures 5 and 7. We have also split former Figure 4 into new Figures 4 and 6 and have renamed old Figures 5 to 7 to new Figures 8 to 10.In the future, we will advance these comparative approaches to a larger scale and address more adequately key questions regarding the stereotypy/variability of cellular behaviors in growing organs and the cellular basis of serial homology. In order to achieve that, we need to decrease the labor required for each lineage reconstruction from months to weeks, and to develop new computational tools for the systematic comparison and visualization of cell lineage information. Our labs are actively generating the necessary software and analysis algorithms and will share them with the scientific community in a timely manner via the same open access principles deployed for MaMuT.4) Looking through the data, we had difficulties determining how time-consuming this method may or may not be. This is important to know if, for example, more than one object were to be analyzed or for experiments in which multiple samples need to be measured and compared to each other. The authors could provide the reader with a timeline or with suggestions of how to increase the throughput of this method.Parhyale embryogenesis with multi-view LSFM and MaMuT”, second paragraph) described above in point 2 addresses how time-consuming manual lineaging has been in our case study and what steps have been taken to increase the throughput of lineaging efforts in the future. Besides this text in the Discussion, we have added the following statement in Materials and methods: “The MaMuT reconstruction of the Parhyale T2 limb described in this article required about 10 weeks of dedicated manual cell tracking by an experienced annotator.”The new text in the Discussion (subsection “Reconstruction of


Here, using in vivo recording in the Dp(16)1Yey model, we find alterations in the organization of spiking of hippocampal CA1 pyramidal neurons, including deficits in the generation of complex spikes. These changes lead to poorer spatial coding during exploration and less coordinated activity during sharp-wave ripples, events involved in memory consolidation. Further, the density of CA1 inhibitory neurons expressing neuropeptide Y, a population key for the generation of pyramidal cell bursts, were significantly increased in Dp(16)1Yey mice. Our data refine the ‘over-suppression’ theory of Down syndrome pathophysiology and suggest specific neuronal subtypes involved in hippocampal dysfunction in these model mice.Down syndrome, the leading genetic cause of intellectual disability, results from an extra-copy of chromosome 21. Mice engineered to model this aneuploidy exhibit Down syndrome-like memory deficits in spatial and contextual tasks. While abnormal neuronal function has been identified in these models, most studies have relied on  Down syndrome (DS), with an incidence of one in 700 to 1000 live births, is the most common genetic cause of intellectual disability . It resuA large portion of HSA21 possesses a syntenic region on mouse chromosome 16 (MMU16), conserving many of the genes in the same order and relative orientation. Mouse models of DS have thus been developed to circumvent the limited access to brain structures and the genetic variance in the DS population. These models, carrying various lengths of chromosomal duplications, recapitulate most of the DS-like characteristics . In partIn rodents the hippocampus is crucial for the encoding and consolidation of spatial memory . In the In vitro approaches have identified synaptic plasticity deficits in the hippocampus of DS mice 1Yey model carrying a large and stable tandem duplication on the MMU16 1Yey  and wild-type littermate control  mice were implanted with recording electrodes in the dorsal CA1 pyramidal cell layer and allowed to explore a linear track . We obseCA1 pyramidal cells from Dp16 animals had a significantly lower peak firing rate during exploration  but an aDuring movement the spiking of pyramidal cells is strongly modulated by the underlying theta oscillation . We nextThe hippocampal code of space is best reflected in the coordinated activity across the population of neurons . Thus, wTo assess absolute spatial coding, independent of the direction of movement, we compared the similarity of the population vectors for laps in opposite directions in the linear track (quadrants I and IV). Interestingly, whereas there was a clear diagonal band of structure obvious in the control data , this waFollowing exploration of the linear track mice were placed in a familiar rest box for 30 min and CA1 pyramidal cell activity was recorded to investigate activity during the post-run phase. During this quiescent period the peak and average firing rate of CA1 pyramidal cells were not significantly different between Dp16 and WT mice . HoweverFor a more detailed quantification we isolated bursts of spikes in both groups and examined their properties . The numThe decrease in bursting during rest in Dp16 mice  suggestsGiven the changes in pyramidal neuron bursting and SWR amplitude and duration we asked if this altered the firing of single cells during SWRs. The average number of spikes per cell per ripple was slightly, yet significantly, lower in Dp16 mice  and pyrain vivo physiology we observed we used immunohistochemistry to quantify the main populations of interneurons in the different layers of the CA1, employing the molecular markers parvalbumin (PV), somatostatin (SST) and neuropeptide Y (NPY) to differentiate among classes of interneurons.The complex spiking of pyramidal cells and their synchronized activity during population events are under tight control of local inhibitory circuits within CA1 . To addrstratum oriens (SO), stratum pyramidale (SP) and stratum lacunosum moleculare (SLM). The density of these NPY positive neurons was significantly increased in the SP and SLM layers from Dp16 samples (Populations of NPY positive interneurons  were obs samples . However samples . The den samples . In the  samples . The den samples . Our invin vivo CA1 function in the Dp(16)1Yey DS model. During exploration, CA1 pyramidal neurons in these mice showed a significant decrease in ability to burst and produce complex spikes, and while their phase locking to theta oscillations was conserved, spatial encoding and information content was significantly lower. A similar deficit in bursting was observed during post-exploratory rest and was associated at the network level with significant changes in ripple properties, suggesting a deficit in network recruitment and synchronization. These changes were accompanied by an increase in NPY expressing interneurons in the stratum pyramidale (SP) and at the stratum lacunosum moleculare – stratum radiatum (SLM-SR) interface.Here we provide the first detailed analysis of in vitro electrophysiology approaches have identified spatial learning and memory deficits associated with a clear long-term potentiation decrease at the Schaffer collateral-CA1 synapses (The Dp(16)1Yey model for DS reproduces learning and memory deficits that resemble those seen in people with DS. Behavioral screening and synapses . Pharmacsynapses . Here wesynapses . Althougsynapses . These csynapses .in vitro under tetanic stimulation in the Ts65Dn model  cells, defined by the location of their soma in the stratum oriens , bistratified cells  and Ivy cells (PV negative) in the stratum pyramidale and a newly identified class of SLM-SR interneurons 1Yey DS model. These changes affect hippocampal function both during exploration and post-exploratory rest periods, i.e. during memory encoding and consolidation phases. The concurrent observation of an increase in NPY expressing interneurons suggests that a subtype specific ‘over-suppression’ in the DS brain is likely contributing to these changes in physiology. These phenotypes could have a direct role in the spatial learning deficiency observed in these mice and suggest that a targeting of specific neuron subtypes may help recover some of their DS-like impairments.www.jax.org, Stock number 013530; RRID:MGI:5690055) and maintained by crossing carrier males with C57BL/6J females. Six Dp(16)1Yey and five WT littermate male mice aged 4 months were used in this study. All mice were group housed by 2 to 5 in ventilated racks with a 12 hr light/dark cycle and ad libitum access to food and water. They were single housed after stereotaxic surgical implantation of microdrives.All procedures were approved by the RIKEN Animal Care and Use Committee  and # H29-2-224(3)). The Dp(16)1Yey mouse line was obtained from Jackson Laboratory  and implanted with a custom microdrives  targeting the dorsal hippocampus . Microdrives consisted of eight independently adjustable nichrome tetrodes (14 μm) arranged in two rows of 4 and gold plated to reach an impedance of 200 to 250 kΩ. Stainless steel screws placed on the cerebellum were used as ground and two extra tetrodes placed in the corpus callosum were used as references. Tetrodes were then slowly lowered over the course of several days to reach CA1 stratum pyramidale, identified by the presence of sharp wave ripples and large amplitude spikes. During this adjustment period, mice were kept in a small circular sleep/rest box (15 cm diameter). Tetrodes were then finely adjusted daily to maximize cell yield before recording. Recordings consisted of 10 laps of exploration on a linear track  bracketed by 30 min pre- and post-exploratory rest/sleep sessions in the familiar circular rest box. Mice were trained for three consecutive days and data recorded on the third day were used for all analyses. Data were acquired using a 32-channel Digital Lynx4S system using Cheetah v5.6.0 acquisition software . Signals were sampled at 32556 Hz and spike waveforms filtered between 0.6–6 kHz. Position and head direction were concurrently tracked using a pair of red/green light emitting diodes affixed to the microdrive.AB_2236566) and revealed using biotinylated goat anti-rabbit IgG antibody  followed by ‘VECTASTAIN Elite ABC’  and NovaRed substrate kits . Images revealing the positions of the electrodes were acquired using a BZ-X710 light microscope (Keyence).At the end of the third recording session, mice were given a lethal dose of Avertin and tetrodes position was marked by electrolytic lesion . After transcardial perfusion with 0.9% NaCL/5 mM EGTA followed by 4% paraformaldehyde, brains were collected, post-fixed for 48 hr and embedded in 15% sucrose – 50% OCT. Frozen coronal sections (30 μm) were prepared and labeled by immunohistochemistry using an antibody targeting PCP4, a marker for CA2, to determine the borders of the CA1 area. Sections were incubated in RetrievagenA  and blocked using Avidin/Biotin blocking kit . Sections were then incubated with anti-PCP4 rabbit polyclonal IgG . Artifacts in the animal’s positional values caused by the obscuring of diodes were removed using a custom written algorithm and the positional data was smoothed with a Gaussian kernel of 0.05 standard deviation (SD) width. Single units were isolated manually, in SpikeSort3D software , by drawing cluster boundaries around the 3D projection of the spike features. The boundaries were tracked across same-day recording trials to ensure cluster stability. Clusters that had greater than 0.5% of their spikes violate a minimum 2 ms inter-spike interval (ISI), fire less than 50 spikes or display an isolation distance measure  <10 wereFiring rate maps were calculated by dividing the number of spikes falling into each 1 cm x 1 cm spatial bin by the total occupancy time of that bin and were subsequently smoothed with a 1 SD Gaussian kernel; unvisited bins and time periods when animal’s velocity was below 2 cm/sec were excluded. For a subset of analyses such as ‘directionality index’ and ‘population vectors’ a ‘firing rate curve’ i.e. a directionally-sensitive 1D representation of a ‘firing rate map’ was used. For the ‘firing rate curve’ calculation we first detect ‘laps’ – time periods when mouse was running along the track by using custom detection algorithm . The quaThe Complex Spike Index (CSI) is defined as CSI = 100 * (pos - neg), where ‘pos’ is the number of inter-spike intervals positively contributing to the CSI, that is, preceding spikes with larger amplitudes and following spikes with smaller amplitudes (complex bursts) occurring within 3 ms (refractory period) and 15 ms ; ‘neg’ is the number of inter-spike intervals that contribute negatively to CSI, i.e. violating either or both these rules. A burst was defined as least two spikes occurring within a 10 ms time bin and all burst detection and analyses were performed using Matlab code previously described .Population vector (PV) was defined as a set of firing rate values generated by all place cells from all mice within each group and corresponding to each particular spatial bin of the linear track. Left and right laps were treated separately. Note that for this analysis all place cells (including cells with place field at the ends of the track) were used. For auto- and cross-correlation of PVs a Spearman correlation coefficient was used.The raw LFP data were downsampled using custom software written in C to 1627.8 Hz (a factor of 20), followed by quality control measure and channel selection via visual inspection. A low-pass filter with a cut-off frequency equal to half the target sampling frequency was applied to the LFP prior to downsampling to prevent signal distortion.Power Spectral Density (PSD) during exploratory behavior was calculated by using Welch's averaged modified periodogram method (pwelch function in Matlab) with 2048 samples window size (1.26 s), 50% overlap and 4096 FFT points (2.52 s) resulting a time-varying spectrogram. A PSD curves corresponding to time bins when animal’s velocity was above 2 cm/sec were averaged yielding single PSD curve for each behavioral trial. In order to account for power fluctuations caused by difference in position/impedance of the electrodes and make PSD values comparable across mice we normalize each PSD curve by its own mean power within delta (1–3 Hz) band.Ripple events were detected using modifications to methods described previously . Wide baTo control for the impact of the significant decrease in normal ripple amplitude observed in the Dp16 mice on the quantification of ripple-related pyramidal cell spiking ripple we adjusted the threshold and repeated the ripple detection algorithm detection. At both a more permissive (2 SD) and a more restrictive (6 SD) threshold, the changes in spiking were observed see .The phase relationship between spikes and theta LFP was calculated as previously described . Brieflyin vivo electrophysiology recording experiments (AB_2716286), anti-SST-14  or anti-PV  and revealed using biotinylated goat anti-rabbit IgG antibody  followed by ‘VECTASTAIN Elite ABC’  and NovaRed substrate kits . Images were acquired using a BZ-X710 light microscope (Keyence) and processed using NIH ImageJ software for particle counting and area calculation. A total of six hippocampal images were counted for each animal in a blinded manner.Brains from adult mice (3.5 to 4 months old) were collected and fixed in 4% PFA. Equivalent frozen sections (30 µm thickness) from Dp(16)1Yey (N = 4) and their WT littermates (N = 4) were selected according to common landmarks at positions equivalent to the regions targeted in the eriments . Section In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.in vivo CA1 network activity in Dp(16)1Yey Down syndrome model mice" for consideration by eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by a Reviewing Editor and a Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting your work entitled "Alterations of eLife.Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in The reviewers seem to find that this study is interesting in that it reports altered network activities in a mouse model of Down syndrome, but the results are largely descriptive and do not provide sufficient insights into whether and how the decreased network activity in Dp(16)1Yey Down syndrome model mice affects hippocampal memory in these animals.Reviewer #1:in vivo neural circuit deficits in a Down syndrome model than previous literature and is valuable to the field of neurological diseases.This manuscript addresses the question of what circuit alterations in a mouse model of Down syndrome, the Dp(16)1Yey model, give rise to learning and memory deficits. The authors recorded from hippocampal CA1 place cells while animals ran on a linear track and while they rested. They found that place cells in the Dp mice have wider place fields with less prospective coding and local field potentials (LFPs) in the Dp mice show less ripple oscillations, both of which are linked to reduced bursty firing of CA1 cells. Together with the finding of more NPY-positive neurons in certain layers of CA1, the authors conclude that memory encoding and consolidation are impaired due to altered bursty firing caused by over inhibition. The manuscript is well written. Although I wish the story could be more exciting or specific, I believe this study provides a more comprehensive account of 1) The authors used lots of bar plots to present data. However, many of the measures, for example firing rate, spatial information, and spike number per SWR, are not necessarily normally distributed. Mean and standard error (s.e.) values may not correctly describe the data samples. I believe plotting the whole distribution, using either cumulative or histogram, is a better way of showing the data. Second, the Mann-Whitney U-test used in the manuscript does not compare mean values, but more appropriately for median values. It is inappropriate to place significance symbols (like ***) over two bars, which show mean values.2) Related to the concern above, the inter-spike interval (ISI) mean values in Reviewer #2:Raveau and colleagues perform extracellular recordings from the CA1 hippocampal region of behaving Down Syndrome (Dp16) model mice, alongside controls, and describe the observed differences. There is less spatial specificity, bidirectional coding, and individual and population bursting in Dp16 pyramidal cells. These animals also display more neuropeptide Y-positive cells in the CA1 pyramidal cell layer. The analysis is mostly appropriate though I had some addressable concerns in a couple of areas. The writing was fine except for some minor redundancies and problematic reference citations. With minor revision, this work will be helpful for researchers working to understanding circuit and cognitive deficiencies in Down Syndrome, though I don't believe the level of insights provided are of high general impact.I have some concern regarding the various analyses.1) For the ISI distribution analysis, I am concerned that a few outlier neurons may be contributing disproportionately to the distributions. To account for this possibility, please show the distributions of average ISIs for the neurons underlying 2) In the ripple event/firing rate analysis, I am concerned that the lower amplitude of events in Dp16 mice may make detection of their onsets and offsets less reliable, thus confounding the other measures . I noted[Editors’ note: what now follows is the decision letter after the authors submitted for further consideration.]in vivo CA1 network activity in Dp(16)1Yey Down syndrome model mice" for consideration by eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by a Reviewing Editor and a Senior Editor. The reviewers have opted to remain anonymous.Thank you for resubmitting your article "Alterations of The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.The reviewers find that the approach is novel and the data are interesting and solid. However, the manuscript still contains a point not addressed, and, more importantly, the reviewers are seriously concerned about the possibility that some of key conclusions may not be associated with the pathology of Down syndrome. Therefore, we request that you fully address these points by performing additional analyses and carefully discuss all the arguments in the main text in a balanced manner.Reviewer #1:in vivo neurophysiological deficits in the hippocampus of a mouse model of Down syndrome. The main finding is that reduced bursty firing of hippocampal place cells leads to less precise place fields during running, suggesting a deficit in memory encoding, and less participation of cells in sharp-wave ripples during resting, suggesting a deficit in memory consolidation. The authors further performed immunohistochemistry to suggest that the reduction in bursty firing is related to changes in the number of NPY-positive interneurons, which results in over-inhibition in the mouse model. The revision has improved the writing and data presentation. The authors have also addressed the potential impacts of their finding on the understanding and treatment of Down syndrome. The quality of the manuscript has been improved. Also, I believe the issue of general impact has been strengthened to a degree that I believe the paper should be published.This revised manuscript describes Reviewer #2:My assessment remains that the different observations made in this manuscript of differences between Dp16 and wild-type mice , while of interest for a better understanding of mouse models of Down Syndrome, do not aggregate to important mechanistic insights that will be of high general impact. That these changes stem from increased NPY expression in the pyramidal and LM layers is still speculative at this stage.concurrent with ripples, to avoid the issue they mentioned of contamination from non-ripple periods. I also think the outcomes of this analysis should be presented in the main text, not just for reviewers.One other point regarding the ripple/MUA burst analysis, I think the authors missed my suggestion to perform the analysis on MUA bursts that are  [Editors’ note: the author responses to the first round of peer review follow.]Reviewer #1:This manuscript addresses the question of what circuit alterations in a mouse model of Down syndrome, the Dp(16)1Yey model, give rise to learning and memory deficits. The authors recorded from hippocampal CA1 place cells while animals ran on a linear track and while they rested. They found that place cells in the Dp mice have wider place fields with less prospective coding and local field potentials (LFPs) in the Dp mice show less ripple oscillations, both of which are linked to reduced bursty firing of CA1 cells. Together with the finding of more NPY-positive neurons in certain layers of CA1, the authors conclude that memory encoding and consolidation are impaired due to altered bursty firing caused by over inhibition. The manuscript is well written. Although I wish the story could be more exciting or specific, I believe this study provides a more comprehensive account of in vivo neural circuit deficits in a Down syndrome model than previous literature and is valuable to the field of neurological diseases.in vivo.We thank the reviewer for the helpful and supportive comments. While we agree that the characterization of the physiological changes in a disease model mouse can result in a largely descriptive study, we would like to emphasize to both you and the readers why we feel this work is important. One reason it has been difficult to generate simple and targetable hypotheses concerning the underlying mechanisms of cognitive deficits in DS patients is the lack of data on circuit level functional changes. To make this clear, and more explicitly position our data in light of current literature and hypotheses, we have added a paragraph to the Discussion on this issue. Specifically, we feel our study supports and extends the “GABAergic hypothesis” of DS cognitive dysfunction and can serve as the basis for the design of novel biomarkers to address and test this theory 1) The authors used lots of bar plots to present data. However, many of the measures, for example firing rate, spatial information, and spike number per SWR, are not necessarily normally distributed. Mean and standard error (s.e.) values may not correctly describe the data samples. I believe plotting the whole distribution, using either cumulative or histogram, is a better way of showing the data. Second, the Mann-Whitney U-test used in the manuscript does not compare mean values, but more appropriately for median values. It is inappropriate to place significance symbols (like ***) over two bars, which show mean values.We thank the reviewer for this excellent suggestion and completely agree. We have now revised all the figures that represented large sets of data for which we used the Mann-Whitney U-test to assess the statistical significance.In a similar way, we modified the Finally, the 2) Related to the concern above, the inter-spike interval (ISI) mean values in We apologize for the confusion caused by our mislabeling The Reviewer #2:Raveau and colleagues perform extracellular recordings from the CA1 hippocampal region of behaving Down Syndrome (Dp16) model mice, alongside controls, and describe the observed differences. There is less spatial specificity, bidirectional coding, and individual and population bursting in Dp16 pyramidal cells. These animals also display more neuropeptide Y-positive cells in the CA1 pyramidal cell layer. The analysis is mostly appropriate though I had some addressable concerns in a couple of areas. The writing was fine except for some minor redundancies and problematic reference citations. With minor revision, this work will be helpful for researchers working to understanding circuit and cognitive deficiencies in Down Syndrome, though I don't believe the level of insights provided are of high general impact.We are grateful for the reviewers input and support. As we stated in our reply to reviewer #2 above, we agree that it can be challenging to identify a precise mechanism underlying phenotypes observed in disease model mice. However, given the high degree of genetic change and the plethora of developmental and adult phenotypes that accompany DS, it has been difficult to generate simple and targetable hypotheses concerning the underlying mechanisms of cognitive deficits in these patients. We feel that our data can be very useful in extending and refining current thinking, particularly the idea that cognitive phenotypes associated with DS stem from a shift in the I/E balance in the hippocampus. We have modified our Discussion to more directly reflect this and are more explicit in stating how we believe our findings can help more the field forward.I have some concern regarding the various analyses.1) For the ISI distribution analysis, I am concerned that a few outlier neurons may be contributing disproportionately to the distributions. To account for this possibility, please show the distributions of average ISIs for the neurons underlying 2: WT: 154.4, Dp16: 124.5). Further, there was no significant difference between genotypes, with the group exhibiting similar medians  and quartile values .We are happy to address this concern for the reviewer. First, as detailed in response to point #2 of reviewer 1 above, we apologize for the confusion caused by our poor description of An important point of note is that for a single neuron the distribution of ISIs is large and non-normal, ranging from the short ISIs generated during bursts or high-frequency spiking to seconds long ISIs frequently observed in pyramidal cells during rest. Thus, we feel that the data presented in the original Finally, to demonstrate to the reviewer that this increase in the mode is independent of the mean ISI, we divided pyramidal cells of each group into bins based on their average ISI and calculated the mean ISI mode across these subpopulations. As see in We have now updated the text in the subsection “Decreased bursting during memory consolidation in Dp(16)1Yey mice” to better explain this analysis and updated the legend of 2) In the ripple event/firing rate analysis, I am concerned that the lower amplitude of events in Dp16 mice may make detection of their onsets and offsets less reliable, thus confounding the other measures . I notedAs the reviewer notes, the average normalized amplitude of ripple events in Dp16 mutant mice is lower than in WT. Nonetheless, we would like to explain why we think that the properties of our ripple detection algorithm allow our spiking analysis to remain robust.First we would like to clarify our standard approach. The onset and offset times of ripple events were detected on each LFP channel individually, based on how many standard deviations instantaneous LFP power in the ripple frequency band (80-250 Hz) deflect from that channel’s mean LFP power value measured in the same band, using a threshold of 3 s.d., which is standard in the field. The candidate ripple events detected based on the normalized LFP power are then checked for co-occurrence with the underlying MUA bursts. The MUA bursts are detected by converting spike trains generated by multiple putative pyramidal cells into single instantaneous firing rate curve, which is also normalized in the same way as the instantaneous LFP power, yielding start and stop timestamps of the MUA bursts. Only these candidate ripple events detected from the LFP signal which co-occurred with supra-threshold MUA bursts were used then for the further analysis.Given the normalization and combined LFP/MUA approach we are confident we are reliably detecting true ripple events and not omitting events in the DS mice. Note that we observed no change in the number of events detected with this approach. However we are happy to address the reviewer’s concern as requested. We have now repeated the analysis using three variations of the ripple detection algorithm. First, as asked, we detected candidate “ripple” event using only the significant increase in MUA activity, independent of the LFP recordings, and use the threshold crossing times of the MUA activity to define event onset and offset. While this approach detects significantly more events in both groups of mice, likely due to the inclusion of non-ripple related firing rate changes, the decrease in single unit spiking and the shortening of the ripple duration are still significantly altered in the Dp16 mice. With this method the change in ripple participation, albeit lower in the Dp16 mice, was no longer significant as p=0.08. This could be explained by the 2x increase in event number being contaminated with non-ripple periods. A table of results is included below for the reviewer:To further test the robustness of our observation and increase our confidence we were restricting our analysis to true ripple periods, we repeated the ripple detection procedure in all mice using a lower (2 s.d.) and a higher (6 s.d.) threshold for the LFP ripple power measure, again combined with MUA cooccurrence. Although this dramatically changes the number of events detected, once more we found that ripple related spiking of pyramidal cells in the Dp16 mice was significantly altered. We have included these additional analyses as a new supplemental figure  and now [Editors’ note: the author responses to the re-review follow.]Reviewer #2:My assessment remains that the different observations made in this manuscript of differences between Dp16 and wild-type mice , while of interest for a better understanding of mouse models of Down Syndrome, do not aggregate to important mechanistic insights that will be of high general impact. That these changes stem from increased NPY expression in the pyramidal and LM layers is still speculative at this stage.eLife, 2013; PP2B cKO (schizophrenia): Suh et al., Neuron, 2013; Fmr1-Null (fragile X): Talbot et al., Neuron 2018.As stated in our previous point-by-point response, we fully recognize the challenges in the identification of precise mechanisms underlying the phenotypes observed in disease model mice. This is an issue not just for DS, but extends to other models of disease and cognitive dysfunction as well. Nonetheless, there is clear support and interest in the field for these types of studies, as borne out by the continued publication and citation of work addressing the physiological changes in circuit function in disease model organisms. For several recent examples similar in approach to our current work please see: 22q11.2 model (schizophrenia): Zaremba et al., Nat. Neuro. 2017; MeCP2 -/- (Rett syndrome): Lu et al., Neuron 2016; rTg4510 (AD): Cheng and Ji, Further, we agree that our results do not allow us to establish a cause-consequence relationship between our electrophysiological and cell count observations. For exactly that reason, in the previous and current versions of the manuscript we do not state that the increase in NPY interneuron populations is directly responsible for the abnormal properties of CA1 pyramidal cells. We frame our conclusions on this matter as a hypothesis and acknowledge further study is required to fully test it. In order to emphasize this point, we added the following sentence to the Discussion:“Further studies will be required to investigate potential cause-consequence relationships between changes in interneuron populations and the deficits we observed in pyramidal cell properties.”in vivo physiological characterization of a well-established mouse model of DS, along with the anatomical data, lend strong support to the existing hypothesis that cognitive deficits in DS are related to increased inhibition. Most importantly, these novel data can serve to provide a benchmark for circuit function in the brain of DS model mice and prove useful in the design and testing of future therapeutic interventions.Finally, regarding the issues of mechanism and impact the reviewer raises, perhaps not surprisingly, we respectfully disagree. We remain confident that our high-quality One other point regarding the ripple/MUA burst analysis, I think the authors missed my suggestion to perform the analysis on MUA bursts that are concurrent with ripples, to avoid the issue they mentioned of contamination from non-ripple periods. I also think the outcomes of this analysis should be presented in the main text, not just for reviewers.We apologies if we misunderstood this suggestion in the previous set of revisions. We believe this refers to your previous major comment #3:“3) In the ripple event/firing rate analysis, I am concerned that the lower amplitude of events in Dp16 mice may make detection of their onsets and offsets less reliable, thus confounding the other measures . I noted?”As requested, we reanalyzed all the parameters regarding ripple events and pyramidal cell activity using the multiunit activity to detect onsets and offsets of ripple events. The results are highly similar to those obtained when we used the LFP to detect event onset and offset . RipplesAccordingly, the following sentence was added to the Results section:“To further confirm that these changes were not attributable simple to the smaller amplitude of ripples in the Dp16 group we also detected the onset and offset of the events using only multiunit spiking activity and again observed a significant decrease in ripple amplitude, duration, number of spikes and participation in ripple events .”


Supplemental Digital Content is available in the text. Intravenous thrombolysis with alteplase is one of the few approved treatments for acute ischemic stroke; nevertheless, little is known about its long-term effects on survival and recovery because clinical trials follow-up times are limited.Patients registered between January 2005 and December 2015, to the population-based South London Stroke Register of first-ever strokes. Propensity score was used to match thrombolyzed and control cases to a 1:2 ratio by demographical and clinical covariates. The primary outcome was survival up to 10 years using Kaplan–Meier estimates, Cox proportional hazards, and restricted mean survival time. Secondary outcomes included stroke recurrence and functional status (Barthel Index and Frenchay Activities Index scores) at 5 years.From 2052 ischemic strokes, 246 treated patients were matched to 492 controls. Median follow-up time 5.45 years . Survival was higher in the treatment group  compared with control group . The number needed to treat to prevent 1 death at 5 years was 12 and 20 at 10 years. After Cox regression analysis, thrombolysis reduced risk of mortality by 37%  at 10 years; however, after introducing a multiplicative interaction term into the model, mortality risk reduction was 42%  at 10 years for those arriving within 3 hours to the hospital. On average, in a 10-year period, treated patients lived 1 year longer than controls. At 5 years, thrombolysis was associated with independence  and increased odds of a higher Frenchay Activities Index . There was no difference in stroke recurrence.Thrombolysis with intravenous alteplase is associated with improved long-term survival and functional status after ischemic stroke. This has led to some concerns of whether the early risks associated with thrombolysis  translate into better prognosis over time.4 Furthermore, most of the studies that have examined differences in outcomes between groups have had a limited follow-up time (5–17). Currently, information available about effects on survival after intravenous thrombolysis come from 2 randomized clinical trials and 3 observational studies.9 The National Institute of Neurological Disorders and Stroke Recombinant Tissue Plasminogen Activator Stroke Study assessed mortality at 12 months, without finding any significant difference between the 2 study arms.5 More recently, a study using participants from the IST-3  found a small reduction in 3-year mortality in the treatment arm which was nonsignificant for all study subjects but only for those who survived the first week.6 However, the IST-3 trial randomized patients who did not meet current eligibility criteria for intravenous thrombolysis with alteplase in standard practice . Three observational studies have examined long-term outcomes of intravenous alteplase; however, 28 are limited by the lack of a comparison group. The third study,9 and the only other propensity score-matched study on intravenous alteplase found a 34% decrease in mortality for treated stroke patients in Denmark. However, this study had a limited median follow-up of 1.4 years and did not examine differences in activities of daily living between groups.Evidence from randomized controlled trials and meta-analysis shows improved functional outcomes for acute ischemic stroke patients receiving intravenous tissue thrombolysis with the recombinant tissue-type plasminogen activator alteplase.10 improves long-term survival up to 10 years after an acute ischemic stroke. Propensity score methods are tools for the analysis of observational studies that allow reducing the effect of the confounding that can occur because differences in the distribution of baseline characteristics and allow to replicate the measures of effect commonly reported in randomized clinical trials.11 As secondary outcomes, we examine whether the benefits in functional status, as assessed by the Barthel Index (BI) and Frenchay Activities Index (FAI), persist at 5 years after a stroke, as well as if stroke recurrence is affected by intravenous alteplase.In this study, we use a propensity score-matched cohort study design to determine whether thrombolysis with intravenous alteplase, as given in standard daily clinical practice in the United Kingdom,The data that support the findings of this study are available from the corresponding author on reasonable request.12) in patients of all ages for an inner area of South London that includes 22 electoral wards in the Boroughs of Lambeth and Southwark.13 The total source population of the SLSR area is 357 308 inhabitants, as estimated in the 2011 census and comprises a distinctly multiethnic population with a significant proportion of black Caribbean and African residents.14The South London Stroke Register (SLSR) is an ongoing, prospective, population-based, stroke register. The SLSR started in January 1995 and documents all first-ever confirmed strokes 17 and the Oxfordshire Community Stroke Project subtype.18 The Oxfordshire Community Stroke Project subtype, which was used to calculate the propensity score, consists of 4 defined subgroups total anterior circulation infarcts, partial anterior circulation infarcts, lacunar infarcts, and posterior circulation infarcts.Specially trained study nurses and field workers collected all data prospectively. Patients were examined within 48 hours of referral to SLSR when possible.13Age at stroke was calculated as the difference between the date of birth and date of symptoms onset; ethnicity was self-reported by the patient and then collated into 1 of the 3 main categories according to the UK 2001 census .Vascular risk factors before stroke  were collected, including smoking, hypertension, diabetes mellitus, atrial fibrillation, ischemic heart disease , peripheral vascular disease, and history of transient ischemic attack. Information on thrombolysis was collected from medical charts from 2005 onwards. The window for thrombolysis with intravenous alteplase was up to 3 hours after symptoms’ onset at the start of the study period and then extended up to 4.5 hours from 2009 onwards.19 was used to assess functional status previous to stroke as well as at each follow-up visit. A cutoff of BI≥90 was used to reflect functional independence.20 The National Institutes of Health Stroke Scale (NIHSS) score was used to assess stroke severity21 during the acute phase. The degree of neurological deficit was classified according to the total NIHSS score as follows minor , moderate (5–15), moderate-severe (16–20), and severe (≥21). The FAI is a frequently used measurement of Extended Activities of Daily Living in stroke and was assessed by trained fieldworker during follow-up visits.22 Follow-up visits were performed at 3 months, 1 year, and annually thereafter. Survival was ascertained by follow-up, which included contacting next of kin if the participant was unreachable, and by checking with the office of National Statistics. Because the registration of deaths in the United Kingdom is complete, all patients with no death record at the day of censoring were assumed to be alive.The BIThe study included patients recruited into the SLSR from 2005 to 2015, inclusive. Survival time was censored at the December 31, 2015. All patients receiving intravenous thrombolysis with complete data for matching variables (see below) were included in the analysis. None of the participants in this study were treated with intra-arterial thrombolysis or mechanical clot retrieval.The study was approved by the ethics committees of Guy’s and St Thomas’ Hospital Trust, King’s College Hospital, Queen’s Square, and Westminster Hospital. Informed consent from patients or assent from next of kin was obtained for all participants for their inclusion into the South London Stroke Register.23 and year of stroke. Figure I in the online-only Data Supplement shows the substantial overlap in propensity score distributions between both groups; this suggests a large area of common support for the eligible participants. We matched treated participants with controls in a 1:2 ratio using a greedy nearest neighbor method.24 Figure Propensity scores were calculated for each patient based on a multivariable logistic regression model. This model included demographic variables , prestroke number of vascular risk factors, functional status previous to stroke (BI), stroke severity (NIHSS), stroke Oxfordshire Community Stroke Project subtype,6 that the proportionality of the hazards assumption would be violated, we further assessed survival time after stroke by comparing the restricted mean survival time (RMST) between groups. We then adjusted the RMST for the same covariates used in the Cox model with an analysis of covariance.25 A similar method was used to examine the difference in stroke recurrence between groups. Independence at 5-year BI (≥90) and FAI scores at 5-year follow-up were compared between groups and adjusted for age, sex, ethnicity, prestroke BI, acute phase NIHSS, and stroke subtype by performing multiple regression analysis. We conducted a sensitivity analysis with multiple imputation to examine how robust our results were to missing data. All analyses were performed using R26 version 3.2.2 (2015) on R-Studio27 version 1.0.136.Descriptive data are expressed in percentages, mean±SD or median and interquartile range (IQR) as appropriate. The primary outcome of this study was survival up to 10 years after the date of first-ever acute ischemic stroke; we report Kaplan–Meier survival estimates and the difference between survival curves tested using the log-rank test stratified to matched sets. We obtained the adjusted hazard ratio (HR) from a Cox regression model of proportional hazards with robust variance estimator. The Cox model was developed by iteratively adding clinical relevant variables to a model including only treatment arm  regressed by the propensity score, and used a log-likelihood test to evaluate whether the addition of the new predictor improved the fit of the previous model. To examine whether onset-to-arrival time modified the effect of alteplase, we then tested if a multiplicative interaction term between treatment with alteplase and arrival within 3 hours further improved the fit our model. Because we expected, based on the reviewed literature,28 indicated that the sample was adequately matched, with a standardized difference of the means of propensity scores between groups of 0.14  and a ratio of variances of propensity scores of 1.27 . A comparison of the baseline characteristics further supports the good balance of our matched sample (Table online-only Data Supplement).A total of 2052 patients with their first-ever ischemic stroke were recruited between the January 1, 2005 and the December 31, 2015; 285 (13.9%) of these patients received intravenous thrombolysis with alteplase. From the total recruited, 334 (16.3%) had missing data for at least 1 of the variables used to calculate the propensity score and thus had to be excluded. Of the 1718 remaining subjects, we paired 246 treated patients with 492 controls , and a total of 344 (46.6%) patients died during the study period.The Kaplan–Meier estimate shows a higher survival for patients treated with intravenous alteplase than for those in the control group at 5 and 10 years . After including a multiplicative interaction term between thrombolysis with intravenous alteplase and arrival to the hospital within 3 hours, mortality reduction for those treated earlier was 32%  at 5 years and 42%  at 10 years (Table online-only Data Supplement).The unadjusted HR shows a 19%  and 28%  decrease in mortality risk for the treated group at 5 and 10 years, respectively. After adjusting for age, prestroke BI, prestroke use of anticoagulants, NIHSS during the acute phase, and poststroke treatment with antiplatelets, thrombolysis with intravenous alteplase was associated with a 28%  decrease in mortality at 5 years and 37%  at 10 years (Table II in the P<0.0001) for the whole duration of the follow-up. To account for this, we calculated the RMST for each group. Patients receiving intravenous alteplase had an RMST of 6.06 years, whereas the control group RMST was 5.18 years. The estimated difference in RMST between groups was 0.88 years  over a 10-year follow-up period. After adjustment for the same covariates used in the Cox proportional hazards model, the estimated difference between RMST was 1.04 years .Visual and formal testing revealed hazards to be nonproportional  at discharge  and at 5 years . Intravenous alteplase was also associated with increased odds of higher FAI score  at 5 years. There was no difference in stroke recurrence between groups.9 and the subanalysis of the IST-3 trial6 by demonstrating that the benefits of thrombolysis in survival are appreciable even after a period as long as 10 years poststroke and the improved functional outcomes are still perceivable at 5 years. Furthermore, our findings also suggest that the observed benefit in survival is seemingly driven by older patients and those with NIHSS≥16  a significantly longer median follow-up time (5.45 versus 1.4 years), and consequently a higher proportion of deaths (46.6% compared with 14.7%). Furthermore, our study included a higher proportion of moderate  and severe strokes , a comparable proportion of moderate-severe strokes  and significantly fewer minor strokes  according to the scale used by each study .The median stroke severity was also slightly higher in our cohort . Our population also had a higher prevalence of hypertension , and diabetes mellitus . Additionally, our population was comprised of first-ever strokes only. Despite these differences our adjusted HR for the whole duration of the study, without time to arrival interaction term, are similar  suggesting the benefits from intravenous alteplase are generalizable across populations.Compared with the Danish nationwide register study,30 and reduces the risk of readmissions because of pneumonia,31 although the impact on other factors is still unclear. Nevertheless, previous studies have shown that good functional outcomes in the short term  are associated with improved long-term survival, in part because of fewer complications and more independence.33 In our cohort, patients in the treatment group had overall better scores in BI and FAI even at 5-years poststroke after adjustment, further suggesting the association between functional status and survival. Furthermore, better BI scores have been strongly associated with quality of life34 which means that the improved survival seen with alteplase is also accompanied by improved quality of life.The precise mechanism or mechanisms by which thrombolysis improves survival are unknown, although there is an evidence thrombolysis decreases infarct size25 Furthermore, the difference in RMST can be straightforwardly interpreted in clinical settings by both the treating physician, the patients and their next of kin. The main limitation of this study lies in its design as an observational rather than experimental study. However, we have used propensity score matching to reduce potential bias and strengthen our reported effect estimates.35 Additionally, we matched every treated patient with a similar control and included the calculated propensity score into the multivariable analysis (double propensity score adjustment), thus reducing as much as possible confounding because of incomplete matching and residual confounding. Another limitation is the effect of missing data in the propensity score matching as well as the analysis. This limitation is common to all studies, particularly those with long follow-up times. Nevertheless, a sensitivity analysis demonstrated that our results were robust to the influence of missing data. Additional limitations include that the SLSR does not collect information about the time of thrombolysis and that the modified Rankin Scale score is not available for follow-ups before 2014. However, although it is not possible for us to calculate the onset-to-treatment time, we have used onset-to-arrival times as a proxy instead; this value is not only correlated with the time from onset to treatment, but also is available for nontreated patients, and thus, it could be fitted into the Cox model. Although we do not have enough data on the modified Rankin Scale score at 5 years, we have used the BI with a threshold of ≥90 to define independence; using this cutoff point has been shown to be comparable to a modified Rankin Scale score of ≤220.The main strengths of this study include a long follow-up time , a per protocol, prospectively collected data set with a wide range of variables that allowed a good balance in baseline variables between groups, an ethnically diverse study population of a well-defined area with a near-complete recording of deaths, achieved by linking with the Office of National Statistics and follow-up by the register fieldworkers. Additionally, we provide the adjusted difference in RMST, a summary statistic which has been shown to better estimate time-to-event than the HR when the proportionality of the hazards assumption is not met.Despite the amount of evidence provided by clinical trials demonstrating that thrombolysis with alteplase improves functional outcomes in ischemic strokes at 1 year, the adoption of thrombolysis has been slow by many centers. Although the reasons for this are multifactorial, including concerns with regards to costs and required experience, one of the main arguments has been the uncertainty on whether the risks associated with thrombolysis indeed result in better outcomes in the long-term. In this study, we have shown that not only patients treated with intravenous alteplase have better BI and FAI scores at 5 years but that they also experience a lower mortality risk, with relatively low numbers needed to treat to prevent a death at 10 years. Furthermore, this study was done using data from a real-world setting from a diverse population, and thus our results are generalizable. These findings should provide much-needed evidence to reassure treating clinicians and patients about the long-term benefits of intravenous thrombolysis therapy with alteplase following currently accepted guidelines.We thank patients, their families, and the fieldworkers who have collected data for the South London Stroke Register since 1995.We would like to acknowledge the support and funding from the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care South London at King’s College Hospital NHS Foundation Trust and the Royal College of Physicians, as well as the support from the NIHR Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London.None.


In this retrospective study, we investigated whether the kinetic change of serum carcinoembryonic antigen (CEA) levels can be an early indicator for the progression in metastatic non-small cell lung cancer (NSCLC) patients during maintenance therapy with bevacizumab plus pemetrexed. Ten patients diagnosed with metastatic lung adenocarcinoma who received a first-line therapy including bevacizumab-based chemotherapy and a following maintenance therapy including bevacizumab plus pemetrexed from June 2015 to October 2016 were recruited in this study. During the maintenance treatment, patients’ CEA levels all elevated at or after the first cycle of maintenance treatment with a median CEA elevation-free survival time as 17.7 days, which was far more shorter than the median progression-free survival time evaluated by CT imaging specially for maintenance treatment (102.2 days). Before the disease progressed, the values of CEA increased steadily for several cycles with the response evaluation still as stable disease, indicating that the changes of CEA level would be earlier and more sensitive for detection of progression. The CEA kinetic was calculated with a mean of 9.6451 and a median of 8.0135, which sensitively reflected the increasing rate of CEA levels at an early stage. Our study showed that the kinetic change of CEA could be an early predictor for the progression in metastatic NSCLC patients during maintenance therapy. Accounting for >80% of primary lung cancers, non-small-cell lung cancer (NSCLC) is a leading cause of cancer-related mortality all around the world . PatientCarcinoembryonic antigen, first identified in 1965 by Phil Gold and Samuel O. Freedman, is related to tumor burden and therapy response . Given tTen patients who have received first-line treatment composed of anti-angiogenic therapy with bevacizumab plus standard chemotherapy with pemetrexed and cisplatin, and more than two cycles of sequential maintenance treatment including bevacizumab plus pemetrexed were observed . With an increment varied from 0.89 to 23.77 ng/mL, patients’ CEA levels all elevated at or after the first cycle of maintenance treatment with a median CEA elevation-free survival time as 17.7 days, which was far more shorter than the median progression-free survival time evaluated by CT imaging specially for maintenance treatment (102.2 days). Before the disease progression, CEA levels of all the patients kept sustainable growth without any progressive changes in radiological evaluation according to RECIST 1.1 criteria, indicating that the changes of CEA level would be more sensitive and earlier for detection of progression. There was a 44-year-old patient whose serum CEA has increased steadily from 8.97 to 41.38 ng/mL, with all three response evaluation as SD during the 8 cycles of maintenance treatment. However, it was the fourth CT imaging operated before the ninth cycle of treatment showed that she got metastasis of spinal dura mater, which meant a failure in maintenance treatment and demand for shift of therapeutic regimen. The CEA kinetic was calculated as 3.729, which indicated a quick increasing rate of serum CEA levels , which indicated that a preoperative serum CEA level of ≥2.5 ng/ml was an independent prognostic factor for NSCLC patients . While, CEA has been proved to be effective in predicting the prognosis of disease. In our study, we investigated whether the kinetic change of CEA levels can be an early indicator for the progression in metastatic NSCLC patients during maintenance therapy with bevacizumab plus pemetrexed. The results of this study have showed that serum CEA levels of all the patients increased continuously before the CT imaging response evaluation as PD according to RECIST 1.1 criteria, indicating that the changes of CEA level would be more sensitive and earlier for detection of disease progression. In addition, our study was specifically evaluated the CEA kinetic by calculating of a regression line based on a minimum of three values of CEA level, which sensitively reflected the increasing rate of CEA. The baseline CEA and the CEA at disease progression of the ten patients were obviously different with great variations from 3.75 to 46.31 ng/mL and 7.15 to 134.30 ng/mL. The kinetic of CEA ranged from 1.104 to 30.005. Researches have proved that there was no significant difference between ROC curves calculated with the CEA kinetic involved in six and four CEA values for patients with disease progression or response, which meant that the CEA kinetic calculated by a few of CEA values can be useful . In anotThe mechanism for CEA values to be used as predictors for bevacizumab-based maintenance therapy may be complicated. First of all, CEA serum levels are associated with the tumor load, which would elevate when the tumor progression occurs. Furthermore, there was study observed a novel functional role of CEA in promoting endothelial cell activation and subsequent tumor angiogenesis, indicating that increasing CEA can antagonize the anti-angiogenesis effect of bevacizumab and be a cause for the failure of the bevacizumab-based maintenance therapy . In addiIn conclusion, with the main advantages of CEA values, namely, low cost, convenient detection, and accessibility of using a standard personal computer to calculate the sensitive CEA kinetic, the serum CEA levels should be observed during the bevacizumab-based maintenance treatment in patients with metastatic NSCLC to predict early disease progression and subsequently to optimize and individualize the treatment by modifying the therapeutic regimen. Further studies included larger numbers of patients are expected to validate such a finding and a cut-off value of CEA kinetic should be defined for disease progression. In addition, there is now extensive research on imaging response markers that may be better indicators than traditional RECIST criteria , 21. In 2 every 21 days) and cisplatin (75 mg/m2). After four or six cycles of treatment, all the patients got partial response or stable disease according to the revised Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 criteria and received the subsequent maintenance treatment including bevacizumab (7.5 mg/kg every 21 days) plus pemetrexed (500 mg/m2 every 21 days). This cohort was analyzed to assess the predictive value of CEA for metastatic NSCLC patients during bevacizumab-based maintenance treatment. Table Ten patients with metastatic lung adenocarcinoma treated at our hospital with a first-line therapy including bevacizumab-based chemotherapy and a following maintenance therapy including bevacizumab plus pemetrexed from June 2015 to October 2016 were recruited in this study, all of whom met the eligibility criteria: ≥18 years old; histologically confirmed lung adenocarcinoma; unresectable metastasis; an Eastern Cooperative Oncology Group performance status <2; and adequate renal and hepatic function. The patients from our hospital received first-line therapy composed of anti-angiogenic therapy with bevacizumab (7.5 mg/kg every 21 days) plus standard chemotherapy with pemetrexed  and results were given as ng/mL. The kinetic of CEA level was calculated based on at least three values of serum CEA, using the slope of a regressive curve with SPSS software.Assessment of response was determined every two cycles according to the revised Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 criteria: a complete response (CR) was defined as the disappearance of all clinical target lesions for at least 4 weeks without no lesion appearing, a partial response (PR) was defined as a 30% or greater decrease in the sum of the longest diameters of target lesions taking the sum at baseline as the reference, progressive disease (PD) was defined as an increase of at least 20% in the sum of the greatest dimensions of treated lesions or the appearance of one or more new lesions, and stable disease (SD) was defined as neither sufficient shrinkage to qualify as a PR nor a sufficient increase to qualify as PD .