We report the results of a numerical and theoretical study of buckling in elastic columns containing a line of holes. Buckling is a common failure mode of elastic columns under compression, found over scales ranging from metres in buildings and aircraft to tens of nanometers in DNA. This failure usually occurs through lateral buckling, described for slender columns by Euler’s theory. When the column is perforated with a regular line of holes, a new buckling mode arises, in which adjacent holes collapse in orthogonal directions. In this paper, we firstly elucidate how this alternate hole buckling mode coexists and interacts with classical Euler buckling modes, using finite-element numerical calculations with bifurcation tracking. We show how the preferred buckling mode is selected by the geometry, and discuss the roles of localized  and global  buckling. Secondly, we develop a novel predictive model for the buckling of columns perforated with large holes. This model is derived without arbitrary fitting parameters, and quantitatively predicts the critical strain for buckling. We extend the model to sheets perforated with a regular array of circular holes and use it to provide quantitative predictions of their buckling. As the column is compressed, it initially reduces in length, but preserves its vertical and horizontal reflection symmetries until it reaches a critical strain at which it buckles. We find from numerical calculations that the first unstable mode of in-plane buckling  is always one of two modes, which we term the alternating mode and the Euler mode (b), although other modes of buckling, including second- and higher-order Euler modes, bifurcate from the unbuckled compression branch at higher strains. In the alternating mode, the column remains straight under loading and the holes contained within the structure arrange in series of ellipses for which each major axes is orthogonal to its neighbour. The Euler mode is a classic sideways buckling, but, as we shall show, it can act in two qualitatively distinct ways. The Euler mode can act as a global mode, where the critical strain and other properties of the mode are dependent on the dimensions of the whole column. It can, alternatively, act as a localized buckling mode in which, although deformation occurs throughout the length of the column, the critical strain is independent of column length and depends only on the geometry of the holes.Here, we focus on in-plane  buckling of a holey column a as an eler mode b, althouet al. [Pihler-Puzović et al.  consideret al. [In this paper, we use the validated numerical model from Pihler-Puzović et al.  to inveset al. [The paper is organized as follows: in §et al.  in §2a. 2.(a)N≥2 and the geometry of a repeated ‘unit cell’, described by a width W, height h and hole diameter D (a). The geometry is, therefore, characterized by three non-dimensional parameters: N, D/W and h/W. As in [1 hyperelastic material within this geometry, using the C++ finite-element library oomph-lib [We parametrize holey columns of finite length by the number of holes ameter D a. The geW. As in , we inveomph-lib . In our As the deformations studied here are not large enough to cause contact or self-intersection of the column, we apply zero-stress boundary conditions to the column side walls and the boundaries of the holes. We consider two cases for the boundary conditions at the top and bottom of the column. For columns of finite length, ‘clamped’ boundary conditions are applied, i.e. the top and bottom of the column are constrained to allow no horizontal deformation, and a uniform vertical deformation is prescribed to emulate compression. We also model columns without these boundaries, by applying periodic boundary conditions that match the deformation and stress at the top and bottom edges of a column with two holes. In this case, the distance between the upper and lower boundaries of the periodic domain is varied to apply compression. These periodic columns are not influenced by the presence of upper and lower boundaries, and so they provide a straightforward way of studying localized buckling modes.ε=Δy/(Nh), where Nh is the total length of the uncompressed column and Δy is the amount by which the entire column is compressed vertically. For small strains, and before buckling occurs, the engineering strain varies linearly with engineering stress, defined as the ratio of the total applied compressive force F to column width W, Eeffε=F/W. The proportionality constant Eeff is the effective Young’s modulus. The critical buckling strain, εcr, is defined as the value of engineering strain at which buckling occurs; the corresponding stress is termed the critical stress. The buckling is a local bifurcation, and therefore occurs at a change in the sign of the real part of the most unstable eigenvalue. We use numerical continuation to solve for both the equilibrium configuration and the stability eigensystem [a). This choice of mesh facilitates accurate identification of the symmetry-breaking bifurcations. Uniform refinement of the mesh has been used to verify the convergence of the numerical results presented here.We quantify the compression by recording the engineering strain, ensystem , at succb, centre), and occurs through a pitchfork bifurcation. If the column has an even number of holes, buckling in the alternating mode breaks the vertical symmetry, through a pitchfork bifurcation . If the column has an odd number of holes (c) the alternating mode buckling does not break the vertical symmetry, and instead occurs via a transcritical bifurcation with two non-conjugate branches that meet in a limit point [N and the geometrical parameters h/W and D/W, and the bifurcations may swap their order of occurrence. We now study the behaviour of each mode in turn.Recall that an ideal undeformed holey column has both horizontal and vertical symmetries. The Euler buckling of a holey column is concurrent with the breaking of the horizontal symmetry b, centreurcation b, right.of holes c the altit point . We rest(b)ϵcr∼1/(Nh)2 (a–c). We call this a global buckling regime, because the critical buckling strain is dependent on the column length, and buckling occurs over the length of the whole column, and not at the lengthscale of the unit cells .The lateral buckling of long slender columns without holes is described by Euler’s theory, which predicts that the critical strain for buckling scales as the inverse square of the column length . The Eul∼1/(Nh)2 a–c. We cc, where the critical buckling strain for columns with holes has been normalized with respect to the critical strain predicted by Euler’s theory for a solid column of the same dimensions, and plotted against non-dimensional hole size D/W. Particularly, for large N, the numerical predictions collapse over a range of hole sizes, supporting the scaling ϵcr∼1/(Nh)2, and show a trend of increasing critical strain with increasing hole size. The cause of the increase of critical buckling strain with hole diameter is that enlarging a hole not only decreases the critical buckling stress, but also decreases the effective Young’s modulus of the column. This decrease in Young’s modulus can increase the critical buckling strain of a long column perforated with large holes by a factor of two, relative to the critical buckling strain of a solid column of the same length and width (figure 2c). For small holes (D/W≪1), the critical buckling strain approaches the prediction from Euler’s theory for a solid column, and, during the initial compression phase prior to bifurcation, the stress is concentrated near the holes.Counterintuitively, the critical buckling strain for long columns can be increased beyond the Euler prediction by the addition of holes to the column. This is shown in figure 2c that the collapse of critical buckling strains on a 1/(Nh)2 scaling no longer holds when the hole size D/W is large. Geometrical constraints mean that the diameter of the holes D must be smaller than both the column width W and the distance between hole centres h. As the hole diameter approaches this limit, two distinct behaviours are observed in the Euler mode, depending on whether the distance between hole centres is smaller or larger than the column width.It is evident from figure 2h<W), large holes result in very thin ligaments of elastic material between adjacent holes, in which the strain energy is concentrated. These thin ligaments allow the column to shear with minimal resistance . Consequently, as the hole diameter approaches the distance between hole centres, the critical buckling strain decreases rapidly (figure 2c). This reduction in critical buckling strain occurs for a wide range of hole sizes in short columns (D approaches h).In the first case, when the distance between hole centres is smaller than the column width (h>W), large holes instead result in very thin ligaments of elastic material separating the edges of the column from the holes, with relatively thicker regions of material between adjacent holes. In contrast with the behaviour when h<W, the critical buckling strain of such columns is nearly independent of the number of holes (b), and decreases with increasing hole size. The buckling of the whole column in this regime results from the individual buckling of the thin ligaments at the edges of the column . We refer to this as the ‘sliding’ regime of the Euler mode, as the thicker regions of the column separating the holes do not deform or rotate significantly, but instead slide left or right. An increase in the hole diameter D reduces the thickness of the ligaments at the edges of the column and causes a corresponding decrease in the critical buckling strain (figure 2b). The buckling of the ligaments at the edges of the column in this sliding regime is in contrast with the global regime of buckling (ϵcr∼1/(Nh)2) observed for long columns, in which the ligaments at the edges of the column are compressed or stretched by the bending of the column, but do not individually buckle.In the second case, when the distance between hole centres is larger than the column width , in which the ligaments buckle alternately left and right . A related consequence of this isolation of the buckling in adjacent holes is that the critical buckling strains for second- and higher-order Euler modes in the sliding regime are only slightly larger than that of the first Euler mode. This ‘clustering’ of many successive Euler modes around a single critical strain in the sliding regime explains why the two-hole periodic column is a good predictor of the critical strain of the first Euler mode , despite the fact that when extended periodically to N holes it is closest in appearance to the Euler mode of order (N−1) .As the critical buckling strain for the column in the sliding regime is independent of the number of holes in the column, it depends only on the localized geometry of these thin ligaments. In the sliding regime, the deformation of each ligament is isolated from the deformation in adjoining ligaments by the thicker region of material between holes. This means the ligaments at the edges of the column buckle to the left or to the right almost independently of one another. A consequence of this is that the critical buckling strain in this sliding regime is in quantitative agreement with the buckling strain in a two-hole periodic column with the same unit cell geometry a), rather than scaling as 1/N2. The critical buckling strain for long columns is in good agreement with that of a two-hole periodic column buckling in the alternating mode, indicated by dashed lines in figure 3a. As with the sliding regime of the Euler mode, this is a localized buckling mode, characterized by independence of the critical strain on N, and agreement between predictions from finite-length and periodic columns. The post-bucking states, illustrated in figure 3b, indicate that buckling of both the ligaments separating holes and the ligaments on the column edge occurs in this localized mode. The critical buckling strain for the alternating mode decreases with increasing hole size D/W, the opposite trend from that of long columns in the Euler buckling mode.The critical buckling strain for the alternating mode is qualitatively different from the Euler mode, in that it tends to be a constant for long columns a, ratherb, where the buckling of the finite-length column (column i) is close to periodic (column ii) everywhere except near the top and bottom boundaries.In the alternating mode, the critical strain in short columns is larger than that in long columns. This increase in strain is caused by boundary effects from the clamped boundary conditions; these boundary conditions prevent bending of the ligaments at the top and bottom of the column, and so prevent the alternating mode in finite columns from being exactly periodic. This behaviour can be seen in figure 3(d)N and the geometrical parameters h/W and D/W determine which of the two modes, Euler or alternating, occurs at the onset of the instability from the unbuckled compression branch.The number of holes N. At large N, the ϵcr∼1/N2 behaviour of the Euler mode and ϵcr∼const. behaviour of the alternating mode means that sufficiently long columns will always buckle first in the Euler mode. For short columns, the frustration of the alternating mode by the clamped boundary conditions (leading to increased ϵcr) has the same result; sufficiently short columns also buckle in the Euler mode. For the shortest column with an even number of holes, N=2, we have found no column geometry where the alternating mode bifurcation (b right) occurs at a lower strain than the Euler mode (b centre). However, at intermediate column lengths, the first buckling instability of the column can be in the alternating mode.The critical strain at which buckling occurs in the Euler mode and the critical strain at which buckling occurs in the alternating mode are compared in urcation b right oler mode b centre.N=6 holes) in D/W and hole spacing h/W. Each point on the figure corresponds to a numerical computation of solutions along the unbuckled compression branch, in which the critical strains at which the Euler and alternating bifurcations occur are recorded. Crosses show the region in parameter space where the Euler mode bifurcation occurs at a lower strain than the alternating mode bifurcation, and dots the region where the alternating mode occurs at a lower strain. The solid black line separating these two regions indicates the column geometries for which the two bifurcations occur at the same strain, and is obtained by plotting the zero contour of the difference between the critical strains for the Euler and alternating bifurcations. The alternating mode occurs at a lower strain than the Euler mode in regions of this geometric parameter space where the ligaments are relatively thin both at the side walls of the column and between the holes. In other regions, the Euler mode occurs at a lower strain.The first mode to become unstable is illustrated for such a column of intermediate length Our study, so far, has explored states arising at the primary bifurcation that occurs at the smallest strain on the unbuckled compression branch. We now study the secondary bifurcations that occur on the first branch to bifurcate from the unbuckled compression branch, either the alternating mode or the first Euler mode.et al. [figure 6a, a column with eight holes exhibits both the lateral buckling and the alternating mode, with both horizontal and vertical symmetries broken.In both cases, the primary bifurcation at the onset of the instability is supercritical. The continued compression of the column, therefore, initially results in stable solutions with a single broken symmetry that have bifurcated from the unbuckled compression branch. On these already bifurcated solution branches, we find that secondary bifurcations can exist, of the type first described by Bauer et al. . These sN=8 and D/W=0.7525, this point occurs at h/W=r0≈0.89426, and is marked by the vertical dashed line in figure 6b that separates the two regions of parameter space, in which either the Euler mode (h/W>r0) or the alternating mode (h/W<r0) occurs at the lowest strain on the trivial branch. By exploring the secondary bifurcations, we investigate the nature of the stability exchange between the two modes.We examine the behaviour of secondary bifurcations in the neighbourhood of a point in the geometric parameter space at which the Euler and alternating modes bifurcate from the unbuckled compression branch at the same critical strain. Choosing b. For h/W<r0, the alternating mode bifurcation (A) occurs at the lowest strain, and the solutions with broken top–bottom symmetry that originate from this bifurcation are subject to the secondary bifurcation (AE) where the solutions also buckle laterally, breaking the left–right symmetry (figure 6c). For h/W>r0, order of the bifurcations is reversed: here the Euler mode bifurcation (E) occurs at the lowest strain, and the laterally buckled solutions that originate from this bifurcation subsequently become unstable to an alternating mode (breaking the top–bottom symmetry) at the secondary bifurcation (EA). At h/W=r0, the Euler and alternating mode primary bifurcations occur at the same strain, and all the bifurcation points, both primary (A and E) and secondary (AE and EA), then coalesce to meet at the same critical strain, forming a multiple primary bifurcation point on the unbuckled compression branch. This feature has been identified and explained by previous studies on secondary bifurcations [In numerical calculations, we impose increasing applied strain until we reach the first bifurcation to occur on the unbuckled compression branch, at which point we perturb the numerical solution with the eigenvector associated with the bifurcation. This bifurcation is supercritical, so by increasing the applied strain further we find solutions on the bifurcated branch until the secondary bifurcation is located. The critical strains of both the primary and secondary bifurcations are shown in figure 6rcations ,17. The 3.a). These periodic columns with a period of two holes exhibit instability to both the alternating mode  and to the localized sliding regime of the Euler mode . Furthermore, as we have shown, the critical buckling strains of the periodic columns are in quantitative agreement with the appropriate localized buckling regime of non-periodic columns of finite length: localized Euler buckling in short columns with hole spacing larger than the width (figure 2b), and alternating mode buckling in long columns (figure 3a). The theory presented in this section is, thus, applicable both to periodic columns and to the localized buckling regimes of non-periodic columns, where the buckling properties are independent of the column length.Motivated by the existence of localized buckling modes and their importance in the overall behaviour of the column, we develop a theoretical model for the stress at the onset of bifurcation in a short section of column with two holes and with periodic boundary conditions imposed on the top and bottom edges a. These b. The thicker uncoloured parts of the structure remain comparatively rigid. By exploiting the large aspect ratio of the ligaments, and the comparative rigidity of other parts of the structure, we can obtain algebraic expressions for the critical buckling force for each mode. There are two types of ligament present in the system; those separating two holes, which we denote s, and those adjoining the side wall of the column, which we denote w (figure 7b). The minimum width of these ligaments isas≪D and aw≪D.When the holes in the column are similar in diameter to the column width or hole spacing, the deformation is localized, occurring through bending of the resulting thin regions of elastic material, or ligaments, highlighted in figure 7ws (a) is given as a function of the coordinate along its length x⋆ byR=D/2 is the radius of the hole. As expected from the geometry in figure 7a, ws takes a minimum value as when x⋆=0. Similarly the width ww of a ligament adjacent to the edge of the column, this time dependent on the coordinate y⋆, isws=O(as)), we find from (The width of the ligament separating two adjacent holes ws a is give(a)as,aw≪R, the strain energy is concentrated almost entirely in the thin ligaments, we assume that a column buckling in the alternating mode can be modelled as a system of rigid sections, formed from thick regions of elastic material, that are connected by the thin, flexible ligaments. Each ligament acts as a hinge with a torsion spring (a).Motivated by the results of finite-element computations, which indicate that when n spring a.FigureE is Young’s modulus of the material, x is the distance along the beam, ϕ is the perpendicular displacement of the beam,w(x) is the width of the beam, given for the two types of ligament by  along the length of the ligament. We consider a ligament with a general parabolic width profilea and x0 parametrize the beam geometry in either type of ligament ).x|. For small deflections of the beam, we may, therefore, define a bending angle for the entire beam, asκ isa=as and s ligaments . When this periodic unit is compressed by a force F and each of these ligaments is bent by an angle θ, the height of the periodic unit is reduced from 2h to θ=0, a bifurcation, occurs at a critical force,A single periodic unit of our model of the holey column consists of four igaments a. When tF measured by integrating the traction over the upper boundary. For these computations, an unstructured triangle mesh was used to discretize the domain, with elements concentrated in the thin ligaments. Our theoretical prediction (a).To validate this prediction, we compare it to the critical force at the bifurcation obtained from finite-element numerical calculations of a two-hole column with periodic boundary conditions applied to the top and bottom of the column. The compression of the system is controlled by altering the vertical offset between periodic units in the deformed configuration, and the force ediction  closely ediction a.Figure(b)w ligaments adjoining the edges of the column undergo deformation, whereas the s ligaments separating holes are undeformed (b). Here, we derive the critical force required for this Euler mode to be realized.Euler buckling of the two-hole periodic system occurs in the localized sliding regime. In this mode, only the deformed b. Here, w ligament supports half the compression force F, and so from =−ϕ(−X)). The critical force for bifurcation is thenaw/R is relatively large (b). As the thin s ligaments separating adjacent holes do not deform in this mode, the critical stress . Each w so from  we haveigaments , as in  occurs at a lower critical strain than buckling of the four w ligaments (in the Euler mode). This prediction is in agreement with numerical calculations of the critical buckling of periodic columns, particularly when aw,as≪1 .The onset of the buckling instability in cellular sheets has been studied numerically, under general in-plane loading in the case where a/h=1/2 , and und1/2 [a/h . Here, wa), in that we assume that the thin ligaments bend, while thicker regions of the structure rotate without significant deformation. This approach is supported by the concentration of the strain energy within the ligaments in numerical calculations. Furthermore, the approach predicts that Poisson’s ratio of the cellular sheet approaches −1 for large holes, which is consistent with numerical calculations [Our model for alternating-mode buckling in elastic cellular sheets perforated with large holes is similar to that in holey columns a, in thaulations .R=(h−a)/2, we find from  (shaded grey in figure 11a), and a region corresponding to thin ligaments that are parallel to the direction of compression, of length O((aR)1/2) and width O(a) (shaded red in 2 as the length of the region (in the direction of applied stress) over its width. The deformation in the two regions of the holey sheet, therefore, scales as h/h=O(1) for the thick (grey shaded) regions and as O((R/a)1/2)≫1 for the thin (red shaded) parts. These scalings suggest that, for small deformation when a/h≪1, the thick regions may be considered rigid and the deformation of the whole periodic unit predominantly results from compression of the thin ligaments that are parallel to the applied strain.Defining the hole radius as ind from  that theF/2. When compressed under a force F/2, the length change of a single column of the two-dimensional lattice isl, and so the relative strain isϵcr and F, which holds immediately prior to a bifurcation, allows us to convert the critical force for the bifurcation (b). For a/h=1/10  a Euler mode, in which the column buckles in a direction perpendicular to the applied compression; or (ii) an alternating mode, in which adjacent holes are deformed into ellipses with orthogonal major axes, but the column remains straight overall.The alternating mode is generally the first mode to become unstable under compression in columns of moderate length (≈4–16 holes) if the holes are relatively large, diameter greater than ≈75% of both the column width and hole spacing. For other column geometries, the Euler mode is the first mode to become unstable either via global buckling on the scale of the column  or localized buckling on the scale of a hole (favoured when the ligaments adjoining the column edge are thinner than those separating holes). We have also studied the exchange of stability between the two modes by exploring the secondary bifurcations in the system.Both Euler and alternating modes exhibit regimes of localized buckling, in which the buckling of the whole column occurs through buckling of thin ligaments around each hole, and at a critical strain that is nearly independent of the column length. This localized buckling of ligaments is captured by our asymptotic model, which provides an accurate quantitative description of the buckling when the holes are large. The model illustrates how the different types of buckling arise through deformation of the ligaments. The alternating mode involves bending of both those ligaments separating holes and those adjoining the column edges; this explains why the first buckling mode observed is the alternating mode only when both types of ligament are thin. By contrast, the Euler mode in its localized ‘sliding’ form involves buckling only of the ligaments adjoining the column edges, whereas in its global form the Euler mode involves the compression or extension, but not buckling, of these ligaments. The buckling behaviour of the column, and its dependence on the column geometry, can be understood and predicted from ligament deformations, as we demonstrate quantitatively for localized buckling in the alternating and Euler modes, equation . One reaAs shown in §et al. [We find that, counterintuitively, the critical strain of Euler buckling in a column can be significantly increased by the presence of holes in a column. One avenue for future investigation is a more detailed study and experimental validation of this potentially useful phenomenon. Although the compressed column bifurcates first from the unbuckled compression branch only through the Euler or the alternating modes, we have shown that other bifurcations can occur at only slightly greater strains, notably higher-order Euler modes of buckling in the sliding regime. This invites the possibility of custom tuning of buckling states, through the addition of small geometrical changes or other imperfections in the system, or through dynamical effects. Most studies of buckling in cellular structures, to date, have considered only quasi-static compression of samples, but the dynamical compression is still largely unexplored, and could be of more practical relevance in large structures. A step in this direction was taken by Box et al. , who stu


The authors would like to indicate that Dr. Orazio Palmieri and Dr. Teresa Maria Creanza contributed equally to the work published in the International Journal of Molecular Sciences . For thiThe changes do not affect the scientific results. The manuscript will be updated and the original will remain online on the article webpage.


Monitoring flower development can provide useful information for production management, estimating yield and selecting specific genotypes of crops. The main goal of this study was to develop a methodology to detect and count cotton flowers, or blooms, using color images acquired by an unmanned aerial system. The aerial images were collected from two test fields in 4 days. A convolutional neural network (CNN) was designed and trained to detect cotton blooms in raw images, and their 3D locations were calculated using the dense point cloud constructed from the aerial images with the structure from motion method. The quality of the dense point cloud was analyzed and plots with poor quality were excluded from data analysis. A constrained clustering algorithm was developed to register the same bloom detected from different images based on the 3D location of the bloom. The accuracy and incompleteness of the dense point cloud were analyzed because they affected the accuracy of the 3D location of the blooms and thus the accuracy of the bloom registration result. The constrained clustering algorithm was validated using simulated data, showing good efficiency and accuracy. The bloom count from the proposed method was comparable with the number counted manually with an error of −4 to 3 blooms for the field with a single plant per plot. However, more plots were underestimated in the field with multiple plants per plot due to hidden blooms that were not captured by the aerial images. The proposed methodology provides a high-throughput method to continuously monitor the flowering progress of cotton. Improving cotton yield is one of the main objectives in cotton breeding projects and cotton growth and production management. Yield can be defined as the product of the number of bolls produced per unit area and the mass of lint per boll (a common measure of boll size). Cotton yield is associated with many physiological variables and environmental factors. However, an increase in cotton yield is generally associated with an increase in the number of bolls regardless of genotype or environment  is usually preferred over a ground vehicle or a robot because a UAV can provide superior data collection speed and larger spatial coverage. UAVs also do not interact with the plants, so constant data collection will not cause soil compaction and plant damage, which can happen when using a ground vehicle. Although many researchers have used UAVs for agriculture studies in recent years, only a few used UAVs to count flowers for crops. For example, aerial multispectral imaging has been used to calculate flower fraction in oilseed rape and monitor the peach flower  build and train a CNN to classify flowers, (2) construct dense point clouds from raw images and evaluate the quality, (3) develop an algorithm to register flowers, and analyze its accuracy and efficiency using simulated data, and (4) evaluate the performance of the data processing pipeline compared with manual counting. To avoid ambiguity, we used the term bloom to refer to a newly opened flower to distinguish it from its other growth stages.Two test fields were used, both of which were located in the Plant Science Farm in Watkinsville, GA   with a color camera  on August 12, August 19, August 26, and September 9, 2016  dense point cloud generation, 2) plot images extraction, (3) bloom detection, and (4) bloom registration  using the raw color images and the IMU/GPS measurements. The high accuracy and reference preselection settings were used for photo alignment, the high-quality setting for dense point cloud build, and default for other settings. After photo alignment, PhotoScan constructed a tie point cloud—often called a sparse point cloud in other software—from the feature points detected in the images. Before constructing the dense point cloud, the tie point cloud was used to calculate the accuracy of the dense point cloud.After building the dense point cloud, it was found that field 1 was not fully covered by the images collected on August 19 and those uncovered plots were excluded from further data analysis. Additionally, some plots had an incomplete point cloud for the canopy due to low side-overlap on August 19, August 26, and September 9, when the focal length was enlarged to reduce the ground pixel size. Point cloud coverage, which is the percentage of the plot constructed with valid point cloud, was used to evaluate the completeness of the point cloud. The plots with point cloud coverage less than 80% were excluded from further analysis. The method to calculate point cloud coverage is explained in section Quality of the dense point cloud.The main purpose of the plot images extraction step is to export plot images from the raw images such that one plot image contains only one plot or part of the plot. Since one plot can be imaged several times, one plot has multiple plot images from different raw images. This is helpful for detecting blooms inside the canopy because different raw images provide views of each plot from different angles, which greatly improves the chance of one bloom being imaged compared to the ortho-image, which only shows the top view of the canopy. To extract the plot images, plot boundaries were first manually drawn for each plot and stored as quadrangle shapes in PhotoScan. Then the four vertices of each shape were projected to each raw image to get the pixel location of the vertices in each image. One image was considered to cover part of the plot if two or three vertices were in the image (pixel location is within the boundary of the image), and the whole plot if four vertices were in the image. The pixel location of the four vertices was recorded and plot images were extracted from the raw image accordingly. The step was processed in PhotoScan using built-in Python functions. The image file name, plot number, and pixel locations of the four vertices were saved in a text file and imported into MATLAB  to extract plot images from raw images.The bloom detection process contains two steps. The first step is to screen out the locations that most likely contain cotton blooms based on the fact that cotton blooms usually have the highest pixel intensity because of their white color. The plot image was first transferred into CIELAB color space and then the screening was performed using the L channel. A threshold of 0.75 on the normalized L channel  was used to extract bright objects. The number of pixels for each object was counted and noisy small objects less than 15 pixels were removed. Objects separated by a distance of less than the diameter of a flower—which is about 20 pixels for our dataset—were combined into one object because some flowers were split into two objects by the leaves. Images with a size of 36 by 36 pixels around the center of the remaining objects were extracted from the plot image. Those images were treated as potential bloom images.The second step is to classify the potential bloom images into bloom and non-bloom class using the pre-trained CNN . After classification, the images classified as bloom class were kept and the pixel location of those images in the raw color images was recorded.Since the same bloom can be detected in several images, it is necessary to register the bloom before counting the blooms to prevent counting the same bloom more than once. Registration methods based on image features were not useful because very few features could be detected from the bloom images due to the resolution limit. Therefore, we first projected the pixel location of each detected bloom into the 3D location in the dense point cloud, and then clustered the blooms based on the locations because the same bloom should have the same 3D location in the dense point cloud. The projection was done in PhotoScan. Because each pixel in the image has a corresponding image ray, any point in the image ray will appear as the same pixel in the image, and the 3D location of that pixel in the point cloud is the intersection between the image ray and the point cloud. If there is no intersection between the image ray and the point cloud, PhotoScan will return the closest point to the image ray.Due to the accuracy of the point cloud and pixel location, the 3D location of the bloom may deviate from the true location, which increases the chance of incorrect bloom registration solely based on the location. However, since multiple blooms detected in the same image are different blooms and cannot be in the same cluster, the bloom registration based on the 3D position can be generalized as a constrained clustering problem as follows:Given the set of data points and the set of their corresponding classes, form the data points into clusters so that no data points in the same class will be in the same cluster and the distance between any two clusters are not smaller than a threshold.i, a set of clusters, i. Second, the distance between cluster i and every cluster in i was merged to the closest cluster in In the case of bloom registration, the data point is the bloom position and the class is the image number to indicate in which image the bloom was detected. Although existing constrained clustering algorithms can solve the problem, most of the algorithms are for general clustering problems and are not efficient for this specific problem. Therefore, inspired by hierarchical clustering, a deterministic clustering algorithm was designed specifically for the bloom registration problem. The algorithm initializes with each data point as one cluster. The algorithm involves cluster selection and merging. First, for each cluster i and μj are the center of the cluster i and j, Ei and Ej are the set of classes of the data points assigned to cluster i and j. Compared to the regular hierarchical clustering algorithms, the efficiency of our algorithm is improved because the distance calculation is only performed on a subset of the clusters.where μa =  and b =  was calculated using Equation (2). The final program used 0.5 for w.Euclidean distance was used to measure the cluster dissimilarity. However, because of the large error of the 3D position projection on the z-axis, the Euclidean distance was modified by adding a weight term on the z-axis to adjust the influence of z-axis on the distance. The weighted Euclidean distance between The CNN was used to classify potential bloom images. The network had seven layers, one input layer, two convolutional layers, two max pooling layers, and two fully connected layers Figure . Since tThe quality of the dense point cloud of the canopy greatly affects the accuracy of the 3D position of each bloom, and thus the clustering results, and ultimately the bloom numbers. The quality of the dense point cloud can be evaluated from two aspects—the accuracy and the completeness of the dense point cloud.The position accuracy of each point in the point cloud is difficult to calculate because the geometry of the canopy is unknown. Instead, the projection and reprojection error were calculated for the tie points to estimate the overall accuracy of the dense point cloud. The projection error was calculated as the distance between the projection of the feature points to the point cloud and their corresponding tie points. The reprojection error was calculated as the pixel distance between the projection of the tie points on the images and their original corresponding feature points. The projection error was analyzed on each single axis  and the summation of three axes.The completeness of the dense point cloud quantifies how completely the point cloud represents the real object or scene, and can be measured by the density of the point cloud. The completeness of the point cloud on the easting-northing plane was calculated since the camera only captures the top view. First, the point cloud was rasterized into a 2D elevation map using grid steps of 1.3 cm without interpolating the empty cells. The elevation map was divided into each plot. For each plot, the ground surface was calculated using the Maximum Likelihood Estimation SAmple Consensus (MLESAC)  blooms not having valid points (which cannot be counted using the imaging method) follow a binomial distribution B. The mean count error is n(1 − p) and the relative error is (1 − p). Therefore, the point cloud coverage should be close to 1 to make the counting error small.In the event of an incomplete dense point cloud for the canopy, some blooms may not be able to get 3D point positions and thus cannot be counted. If the blooms equally distribute over the canopy, the point cloud coverage can be considered as the probability of a bloom having a valid point in the dense point cloud. Assuming a canopy has Figure With more than 28,000 training images and mini batch size of 256, the CNN was trained about 114 iterations every epoch. Because of the large training sample size and relatively simple structure, the training process converged quickly and the training accuracy reached 0.94 in the first epoch. As shown in Figure The classification result for each dataset using the trained CNN varied due to the different lighting conditions and flowering stages Table . The claTo cluster the 1,250 data points, the bloom registration algorithm used 13.3 to 48.4 s, which is 0.0106 to 0.0387 s per data point Figure . Using aAt low noise level, the under-clustering takes the main effect because the bloom registration algorithm can split one cluster into smaller clusters at low noise level, generating a larger number of clusters compared to the real cluster number Figure . As the This section shows the bloom count results after removing the plots with point cloud coverage less than 0.8. The image count and manual count had the same trend for both fields Figure . The errThe overestimation was caused for two major reasons. One reason is the classification error of the CNN. For example, some leaves with specular highlights were classified as blooms Figure . The othWith enough datasets, it is possible to monitor the development of the flowers over time, which is one of the advantages of the proposed method. Figure This paper demonstrated a high-throughput methodology to count cotton blooms using aerial color images. Continuously monitoring the cotton blooms over time can provide information about the cotton growth status, such as the flowering time and peak flowering time, which can be used for production management and yield estimation. It is also helpful for breeding programs to identify short season or long season genotypes.Unlike sorghum or corn, whose flowers open at top of the stem, cotton flowers open from the bottom and progress up the plant. At the early cotton flowering stage, blooms at the bottom can be covered by the leaves and may not be able to be captured by the aerial images. Therefore, it is expected that image counting can underestimate the real bloom count. Instead of using the ortho-images which only take the top view of the canopy, we utilized all the raw images that take different views of a plot to get the bloom count in order to improve the underestimation to a certain extent. The inability to detect hidden blooms inside the canopy from aerial images is the major limitation of the proposed methodology. This issue could be addressed by using oblique aerial images or ground side-view images. The underestimation could be improved at the middle and later flowering stages since the flowers that open at the middle and top of the canopy are more likely to be imaged in the aerial images.Besides the inability to detect hidden flowers, the proposed bloom counting method can generate errors from two aspects: the bloom detection error and the bloom registration error. The bloom detection error was affected by the image quality, the threshold to select the potential bloom images, and the accuracy of the CNN. The image quality was affected by the illumination condition at the time of data collection. Ideally, the best image quality can be obtained when the illumination is uniform from all directions so there are no shadows or specular highlights. The ideal condition is hard to obtain in the field, but the approximate ideal condition can be obtained on a cloudy day. When the sunlight directly shines on the canopy without being scattered by clouds, shadows and specular highlights can be found in the aerial images, which cause non-uniformed intensity changes of the plot. Those changes will affect the selection of the potential bloom positions.The threshold to select the potential bloom positions was arbitrary and mainly based on the images. A high threshold can eliminate some blooms that have low intensity due to shadows. A low threshold can include more non-bloom objects (such as the specular highlights), which can increase the processing time and be misclassified by the CNN. The classification of the potential bloom images relied on the CNN but misclassifying a bloom image as a non-bloom image affected the result differently from misclassifying a non-bloom image. When a bloom was classified as a non-bloom in one image, it was possible to be correctly classified as a bloom in other images given a different perspective of the flower; therefore, this flower could be included in the final result. However, when a non-bloom image was classified as a bloom, this false bloom was counted and there was no approach to remove it in the current method. The training samples for the CNN were selected from images collected on only 4 different days, so the trained CNN may not be suitable for data collected in different growth stages, especially when the color of the cotton leaves changes over the season. Therefore, including more training samples from different dates over the growth season could improve the accuracy and robustness of the CNN. The different appearances of the cotton flower caused by genotype differences—for instance, the Pima cotton has yellow bloom in contrast with white bloom for some upland cotton varieties—should also be considered when constructing the training samples.The accuracy of the bloom registration was affected by the 3D position of the bloom and the registration algorithm. The 3D position of the bloom was affected by the pixel location and the dense point cloud. Therefore, the accuracy of the dense point cloud has an important impact on the accuracy of a bloom's 3D position, and thus affects the bloom registration results. A larger error of the 3D position can cause the bloom registration to under-cluster or over-cluster the blooms. Under-clustering can count the same bloom more than once and over-clustering may count several blooms as one bloom, making the bloom count unreliable. The completeness of the point cloud also affects the registration result. If the dense point cloud cannot cover the whole canopy, some blooms that are detected in the images may not have a valid projection on the dense point cloud. Those blooms will not be registered and underestimation of the bloom count will occur. Therefore, adequate image overlap is critical in data collection to capture the whole canopy. Increasing the image overlap can improve the completeness, but also requires more data collection and processing time. Oblique imagery can also improve the completeness of the point cloud by providing more views of a plot and potentially can image more occluded flowers.Although the proposed bloom counting methodology usually provides an underestimated bloom count compared to manual counting, it has the advantage in throughput over manual counting. It saves manual labor and makes continuously monitoring the flowering possible. Without such throughput, it is impossible to continuously monitor the flowering stage and determine the flowering time, peak flowering time, and seasonal bloom count. For farmers and breeders, it is helpful to estimate the fiber yield because some studies have shown the fiber yield is correlated with seasonal bloom count  and the data collection throughput is not enough for commercial farms or breeding programs with large fields. Although the throughput can be increased by increasing the flight altitude, the reduced ground resolution may not meet the requirement for the pipeline to correctly recognize cotton flowers. Alternative solution is to use high-resolution cameras to maintain the ground resolution when imaging at higher altitudes.To implement the proposed method, farmers and breeders can use commercial aerial photogrammetry systems or build custom systems to collect aerial images. The data processing pipeline can be used as long as the image quality (such as the ground resolution) meets the requirements. This study used small fields of 920 mThis study developed a high throughput methodology for cotton bloom detection using aerial images, which can be potentially used to monitor cotton flowering over the season for cotton production management and yield estimation. The method generally underestimated the bloom count due to the inability to count hidden flowers, but the bloom count for the single plant layout was less likely to be underestimated than the multiple plant layout. The accuracy and completeness of the dense point cloud has an impact on the bloom count result, so generating a good dense point cloud can improve the results significantly. The bloom registration algorithm developed in this study was efficient in terms of runtime and was more prone to under-clustering but less prone to over-clustering. The trained CNN correctly classified more than 97% of the training and test images, and more than 90% of the potential flowers extracted from individual datasets. Since the false classification from the CNN can result in false bloom count, designing a robust CNN that can handle images taken under different field illumination conditions and cotton growth stages will be included in future studies. In addition, oblique imagery will be explored to improve the quality of the dense point cloud.RX: performed the data analysis and wrote the main manuscript text; CL and AP: designed the experiments and wrote the manuscript; YJ: designed plot layout and contributed to the data collection; SS and JR: contributed to the data collection and field management; All of the authors have read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Hct = 40%) even for small values of tortuosities and bends indicating that these parameters are dominant in determining blood clotting. Our calculated results overlapped with clinical data in 80% to 91%. Therefore, we conclude that tortuosities and bends have high impact on thrombus formation and should be under special attention during stent-graft recommendation and patients’ follow-ups.Complexity of the spatial configuration of an aortic implant with bifurcation in the distal part is related to changes in blood hemodynamic in the area of bifurcation which may disturb blood flow and lead to thrombus formation. This study was designed to characterize parameters which define spatial configuration of an aortic implant for which the risk of thrombus formation is the smallest. We used AngioCT data from 74 patients, aged 55 ±10 years, after endovascular procedure to prepare 3D geometries of stent-grafts. Computational Fluid Dynamics (CFD) simulations were used to reconstruct blood hemodynamic and simulate thrombus formation. Next, geometric parameters of stent-grafts included the ratio of volume of upper part to the bifurcations, the relation of inlet and outlet diameters of a stent-graft and deformations in the iliac part of the stent-graft were analyzed. We also analyzed tortuosities  and bends . The CFD results were confronted with AngioCT data to verify if computer generated thrombus appeared in particular patient. Additionally, geometric parameters of analyzed stent-grafts were used to propose a mathematical tool for prediction of thrombus appearance. The results showed that tortuosities and bends of a stent-graft had the highest impact on thrombus formation. Formation of thrombi was observed in 22% to 31% of cases (at blood hematocrit  One of the commonly applied methods for reconstruction of proper blood flow in vessel is implantation of endovascular prosthesis (stent-graft) in the area of wall dissection or abdominal aortic aneurysm (AAA) , 2.The implantation of stent-graft decreases the pressure acting directly on the vessel’s wall by accumulating energy carried by pulsation wave. This effect may reduce the probability of wall rapture in the area of aneurysm appearance. –6. AlthoMoreover, complexity of the construction of endovascular prosthesis for AAA area, connected with the bifurcation in the distal part (branching of iliac arteries), may lead to blood flow disturbances and further to thrombus development . TherefoA selection of an optimum shape of the endovascular prosthesis is undertaken during surgery planning. Therefore, optimization of the stent-graft's spatial configuration seems to be an important step. In the human body, the angles and diameters of bifurcating vessels are optimized in a natural way to improve blood flow hemodynamic. The angle at which blood vessels are bifurcating is approximately 45° and the ratio of diameters of branched blood vessels is around 0.8 .Many authors analyze the mechanical aspects of the endovascular prosthesis with the Computational Fluid Dynamic (CFD) technique –19. CurrTherefore, the aim of this study was to determine which part of the stent-graft has the highest impact on the thrombus formation and to propose a pre-operative method of optimization of the spatial configuration of endovascular prosthesis.In this study we used data collected form 74 patients aged 55 ±10 years after AngioCT  who underwent treatment with endovascular procedure in the Barlicki Hospital No. 2 in Lodz (Poland) from 2007 to 2016 . PatientPatients’ data were retrospectively collected after obtaining written informed consent to participate in the study. Medical data and images were anonymized by coding information before access and analysis. The study was approved by the Local Ethic Committee on Medical University of Lodz (RNN/126/07/KE).Using a specialized 3DDoctor software  for medical image processing, three-dimensional reconstructions of the analyzed stent-grafts were performed.Hct) ranging from 30% to 60%. The process of thrombus appearance/formation was calculated with the use of modified Quemada's model, as previously described in Polanczyk et al. [The 3d geometries were prepared so that in each case the inlet to the system was just below the mesenteric artery outlet and the outlets were located in the femoral arteries at the level below the stent-graft ending. Numerical calculations of blood flow in the analyzed geometries were carried out with the use of ANSYS FLUENT.12.1 software . The mathematical domain was described with the boundary conditions as follow: (1) the stent-graft wall was treated as a rigid structure, (2) at the inlet, an assumed condition of blood flow velocity was u = , (3) while at the outlets the condition p = const was taken. Blood was treated as a non-Newtonian described in details in our previous paper . For thek et al. . The bloHct at level 40%, and for this value a verification process was made. Higher value of Hct was applied as a prognostic tool to check how particular spatial configuration of a stent-graft behaves.Medical data base created for the purpose of this study consisted of patients with and without thrombus diagnosed in endovascular prosthesis. Number of patients with diagnosed thrombus was 51. This allowed verification of proposed methodology of optimization of spatial configuration of endovascular prosthesis. Analyzed patients had VB) to the volume of the iliac part of the endovascular prosthesis (VL).To optimize the spatial configuration of the endovascular prosthesis, the following geometric parameters were analyzed: the stent-graft volume, inlet and outlet diameters of the stent-graft and, deformations of the iliac part of stent-graft. Geometric parameters used in the calculations were selected basing on the criteria used by the surgeons before implantation of a stent-graft. These criteria included the diameter of aneurysm neck and the diameters of iliac arteries, i.e. places in which the upper and lower part of the stent-graft was mounted, bends in the iliac arteries, and the ratio of the length of the common part of the stent-graft compared to the length of branches was studied.(Le) between two parallel planes (inlet/outlet in the endoprosthesis branch) to the length of branch (L) calculated in its axis. A ratio of the left branch tortuosity (TL) to the right branch (TR) for which the fewest cases of endoprostheses for which the thrombus occurred was classified as optimal.A relation between deformations of branches in stent-graft and thrombus risk was analyzed for tortuosities and bends. Tortuosity of the stent-graft branches was determined as a relation of the distance bendout_L/bendout_R) and we searched for a range of bending at which thrombus occurrence was less frequent.The second analyzed parameter which determined the deformation of the stent-graft branches was bends. We measured bends assuming that the straight branch corresponded to the angle 180°, while a completely bent branch corresponded to the angle 0°. In each endoprosthesis branch we selected the biggest bend from all bends occurring in the branch and used it for further simulations. Finally, we determined the relation of bends in both stent-graft branches . Values were presented as mean±SEM. Correlations were evaluated with the Spearman rank correlation test or Pearson test. Data were considered as significantly different when p<0.05 unless otherwise noted.Hct = 40% , while at Hct = 50% thrombus occurred in 83% of stent-grafts. Comparison of CFD results and medical data indicated that thrombus was reconstructed each time in the patient with thrombus originally diagnosed for Hct = 40%. Increasing of Hct value increased the number of patients with thrombus inside endovascular prosthesis.Analysis of CFD results indicated that tthrombus was observed in 68% of stent-grafts when Hct the number of endoprostheses with thrombus was rising  was 2 to 5 times bigger than the volume of branches (VL)  . For thict = 50% . VerificDin) and outlet diameters (DL) and (DR)). Results showed that thrombus occurred more frequently in the geometries in which the diameters of both branches highly differed from each other. The risk of thrombus was lowest when diameters of both branches ranged from 0.8 to 1. Then, thrombus occurred in 16.7% of the stent-grafts at Hct = 40% and in 23% of the stent-grafts at Hct = 50%. Verification of received results indicated that for Hct = 40% and the same range of analyzed geometric parameter approximately 80% of CFD results were in line with clinical cases.Next analyzed parameter was branch asymmetry (inlet diameter (Dinlet) to the arithmetic mean of both outlet diameters (Dout_avg). Like in the case of the parameters analyzed previously, an increase in blood viscosity caused an increase of the number of stent-grafts with thrombus. The smallest risk of thrombus formation occurred when the analyzed parameter was in the range from 1.2 to 2. Then, thrombus was reported in 9,3% of the stent-grafts at Hct = 40% and in 17% of the endoprostheses at Hct = 50%. In conclusion, the risk of thrombus formation was the smallest when the diameter of the upper part of the endoprosthesis was 1.2 to 2 times of the diameters of its outlets. Verification of received results indicated that for Hct = 40% and the same range of analyzed geometric parameter approximately 80% of CFD results were in line with clinical cases.Our analysis of the relation of the upper to lower part of an endoprosthesis  showed tHct   .Hct = 40% thrombus was observed in 22% cases and at Hct = 50% in 31% of cases. Verification of received results indicated that for Hct = 40% and the same range of analyzed geometric parameter approximately 91% of CFD results were in line with clinical cases measured with AngioCT. Similarly as for tortuosity, we searched for an optimum range of bending with the lowest risk of thrombus formation. We indicated that the lowest risk of thrombus formation is for bends ranging from 140° to 180°  and another potential ones (e.g. native aorto-iliac anatomy configuration) that we did not addressed. However, our aim was to focus on factors associated with intervention procedure. Consequently, in further research on bigger groups of patients, risk factors that are well known and also this newly presented by our team can be included into analysis.Our study indicated that to minimize the risk of thrombus formation in the stent-graft, the volume of upper part of the endoprosthesis should be two to five times bigger than the volume of the iliac part. Inlet diameter of the stent-graft should be 1.2 to 2 times bigger than the diameters of branches of the endoprosthesis.Among the analyzed parameters, the most influential on thrombus formation are tortuosities and bends of the stent-graft. Even for small tortuosities and bends of the prosthesis thrombus was observed, in 22 to 31% cases. Hence, these seem to be the dominant parameters determining blood clotting which should be under special attention during stent-graft recommendation and patients’ follow-ups.


No statistically significant distribution of ARI scores was found among the levels of feldspathic, p value = 0.569. However, statistically significant distribution of ARI scores was found among the levels of zirconia, p value = 0.026. The study concluded that silanization following sandblasting resulted in tensile bond strengths comparable to other bonding protocols for feldspathic and zirconia surface.This study evaluates tensile bond strength (TBS) of metal orthodontic attachments to sandblasted feldspathic porcelain and zirconia with various bonding protocols. Thirty-six (36) feldspathic and 36 zirconia disc samples were prepared, glazed, embedded in acrylic blocks and sandblasted, and divided into three groups according to one or more of the following treatments: hydrofluoric acid 4% (HF), Porcelain Conditioner silane primer, Reliance Assure® primer, Reliance Assure plus® primer, and Z Prime™ plus zirconia primer. A round traction hook was bonded to each sample. Static tensile bond strength tests were performed in a universal testing machine and adhesive remnant index (ARI) scoring was done using a digital camera. One-way ANOVA and Pearson chi-square tests were used to analyze TBS (MPa) and ARI scores. No statistically significant mean differences were found in TBS among the different bonding protocols for feldspathic and zirconia,  Advancements in cosmetic dentistry and orthodontic treatment needs in the United States have led to increasing number of adult patients seeking orthodontic care . OrthodoOrthodontic bonding primarily involves three steps: etching, primer application, and bonding . To miniBonding orthodontic attachments to zirconia surfaces differs in bonding protocol from that of the feldspathic crown surfaces. In contrast to feldspathic porcelain, zirconia does not contain a glass phase and etching zirconia surface with hydrofluoric acid does not enhance bond strength , 18. A sThis study aims to investigate different bonding procedures for metal orthodontic attachments to feldspathic porcelain and zirconia surfaces.A total of 36 zirconia specimens, 97% zirconium dioxide stabilized with a 3% Yttria-Lava Frame , was obtained. The blocks were sectioned with diamond blade  to obtain 2.5 mm thick and 8.5 mm in diameter disc specimens. The samples were polished using 600-grit silicon carbide paper and subsequently water-cooled. The blocks were then ultrasonically cleansed and glazed in a Dekema oven  at 1500°C for one minute.A total of 36 glazed feldspathic porcelain specimens measuring 2 mm thick and 8.5 mm in diameter were prepared. Feldspathic porcelain powder  was stacked onto degassed metal disks and fired in a Dekema oven  at a temperature of 895°C. The sintered specimens were ultrasonically cleaned and glazed.μm aluminium oxide particles at 30 psi for 4 seconds in a Basic Meter Sandblaster . The ideal protocol for air abrasion is sandblasting with aluminium oxide particles for 4 sec at 2.5-bar pressure (36.5 psi) [All the samples were embedded in acrylic , placed in mounting blocks, and sandblasted with 50 6.5 psi) .Each material was divided into three groups Tables  and 2 acReliance Assure (RA) primer: the bonding protocol following the manufacturer instructions is to sandblast the porcelain surface with aluminium oxide particles for 4 sec, followed by surface treatment with 4% hydrofluoric acid for 60 sec, rinsing with water and light air drying, applying a single coat of silane, and light air drying for 3–5 sec. Lastly a single coat of the RA primer is applied before using the adhesive for bonding.Reliance Assure plus (RA plus) primer: manufacturers suggest sandblasting with aluminium oxide particles for 4 sec, followed by application of a single coat of the RA plus primer and light air drying for 3–5 sec before bonding to porcelain and zirconia surfaces. Per the manufacturer, this bonding protocol has reduced number of clinical steps involved in surface preparation for bonding to porcelain and zirconia surfaces.Z Prime plus (Bisco) primer: the bonding protocol following the manufacturer instructions includes sandblasting with aluminium oxide particles for 4 sec, followed by a single coat application of Z Prime plus primer and light air drying for 3–5 sec before bonding to zirconia.Porcelain Conditioner silane primer: it was suggested by the manufacturer to be used as one of the preliminary bonding protocol steps to condition feldspathic porcelain. In this study it is a control to the other bonding protocols.Four different kinds of bonding adhesives  were use2. For consistency, all the attachments were bonded to the samples by the same clinician. Each sample was light cured for 20 seconds from the center of the sample to its rim with Ortholux light at 900–1,100 mW/cm2 . Light intensity was measured using a curing light intensity meter, Model #8000  for standardization.Following the surface intervention, a round traction hook with a laminated mesh bonding pad, Product # 224–011 from TP Orthodontics , was bonded using Pad Lock™ light cure composite . The bonding surface of the traction hook measured 9.95 mmFeldspathic porcelain and zirconia samples were stabilized in the acrylic blocks and ensured for parallelism using stainless steel ruler. Using a 12 V cordless drill , holes measuring 5/32 inches were drilled into the acrylic units. All the samples were labeled with material group (feldspathic or zirconia) and bonding agent group . Samples were randomized into three batches constituting four samples from each bonding protocol. Each batch was prepared according to the respective bonding protocol and tested for tensile bond strength measurement immediately. This helped minimize bias with environmental conditions and clinician efficiency.A round 0.012-inch stainless steel wire was used to loop around the traction hook. A perpendicular tensile force was ensured by attaching this wire to the upper unit of the Instron testing machine Model 1125 . The acrylic units were secured via a rod to the lower unit of the Instron machine. The Instron machine was directed to provide tensile stress to the bracket unit until bond failure occurred at a cross head speed of 1.0 mm/minute.R = F/A, where “R” is the strength (MPa), “F” is the load required for rupture of the specimen (N), and “A” is the interface area of the specimen (mm square). A digital caliper was used to measure the interface surface area of the specimen. The surface area of the bondable surface of the traction hook measured to be 9.95 mm2.Machine calibration was performed each time a batch was tested and the load balance was set at zero to ensure uniformity. The size load cell for the testing was set to be at 500 kg. Once the sample to be tested was engaged with the stainless wire looping around the traction hook and attached to the upper unit the test was run. The data collection was done using TestWorks® software . The bond strength measured was calculated using the formula  Score 0: no adhesive left on the porcelain or zirconia surface. Score 1: less than half of the adhesive left on the porcelain or zirconia surface. Score 2: more than half of the adhesive left on the porcelain or zirconia surface. Score 3: almost all adhesive left on the porcelain or zirconia surface, with distinct impression on the attachment mesh.The digital camera Model GT800 used in this study has a magnification up to 700x . An optical magnification of 230x was deemed sufficient for this study's purpose. To minimize bias all images were randomly selected and scored for ARI indices by three calibrated examiners. In case the individual scores differed amongst the examiners the majority score was chosen to be the final score.To determine the adhesive remnant index , a digital camera Model GT800  was used to examine the debonded surface and the bracket mesh. The scores are as follows:The Shapiro-Wilk test was used to check the distribution of raw data and descriptive statistics were calculated. To determine the differences in mean tensile bond strengths amongst the different bonding agents for feldspathic and zirconia samples, a one-way ANOVA was used. ARI scores were reported for each group. A cross-tabulation followed by Pearson chi-square test was done for ARI scores among the bonding agents for feldspathic and zirconia. Statistical significance was set at 0.05. Data analysis was performed using IBM SPSS Statistics for Windows .F = 1.029, p value = 0.369, and zirconia, F = 0.058, p value = 0.944.All study data showed normal distribution. Descriptive statistics were presented for feldspathic samples in The literature on minimum bond strengths is not consistent. Some authors reported the minimum shear bond strength for orthodontic bonding purpose to be 13 to 21.3 MPa , while sFeldspathic porcelain (silica based) undergoes surface roughness after sandblasting and/or exposure to hydrofluoric acid, exposing silica oxides for chemically bonding with silane coupling agent and resin. The silanol (Si-OH) group of the primer and the OH group of the ceramic combine to liberate a water molecule and in the process form a stable siloxane (Si-O-Si) bond , 29. It While debonding brackets from enamel, it is important to prevent enamel damage but at the same time have minimal adhesive left on the tooth surface. Likewise, for ceramics, the aim is a debond site that has minimal cohesive damage to porcelain or zirconia but at the same time has minimal residual composite left to remove.χ2 = 2.934, df = 4, N = 36, p value = 0.569. For zirconia group the Pearson chi-square results indicate that Reliance Assure plus, Z Prime, and Porcelain Conditioner are significantly different on whether they were scored as 1, 2, or 3, χ2 = 11.059, df = 4, N = 36, p value = 0.026.The ARI scores for various bonding agents on feldspathic group and in zirconia group are shown in Tables This type of failure mode signifies that the physiochemical bond that was formed between the various bonding agents and the sandblasted feldspathic and zirconia samples in this study was higher than the micromechanical retention between the adhesive and the traction hook base. It can be interpreted that the traction hook base was not retentive enough for the adhesive and before the bond strength limit could be reached for any of the samples the traction hook debonded. This may also be purely intentional on the part of the manufacturer because bond strength that is significantly high may pose a risk to harming tooth enamel; thus, by design, the bracket is supposed to debond at the bracket-adhesive interface. Therefore, with the current study design it cannot be determined if there was no difference in tensile bond strength of orthodontic attachments to sandblasted feldspathic and zirconia samples with the included bonding protocols.The limitation of this study is no inclusion of a material group that was not sandblasted. It is recommended that future studies include a control group where a nonsandblasted surface is tested for application of various bonding protocols.From the results obtained in this study it can be concluded that bonding metal orthodontic attachments to sandblasted surfaces of feldspathic porcelain and zirconia with Porcelain Conditioner, Reliance Assure (RA), Reliance Assure plus (RA plus), and Z Prime plus resulted in tensile bond strengths that were higher than the micromechanical retention between the adhesive and the orthodontic attachment hook base.


Clostridium thermocellum could potentially be used as a microbial biocatalyst to produce renewable fuels directly from lignocellulosic biomass due to its ability to rapidly solubilize plant cell walls. While the organism readily ferments sugars derived from cellulose, pentose sugars from xylan are not metabolized. Here, we show that non-fermentable pentoses inhibit growth and end-product formation during fermentation of cellulose-derived sugars. Metabolomic experiments confirmed that xylose is transported intracellularly and reduced to the dead-end metabolite xylitol. Comparative RNA-seq analysis of xylose-inhibited cultures revealed several up-regulated genes potentially involved in pentose transport and metabolism, which were targeted for disruption. Deletion of the ATP-dependent transporter, CbpD partially alleviated xylose inhibition. A putative xylitol dehydrogenase, encoded by Clo1313_0076, was also deleted resulting in decreased total xylitol production and yield by 41% and 46%, respectively. Finally, xylose-induced inhibition corresponds with the up-regulation and biogenesis of a cyclical AgrD-type, pentapeptide. Medium supplementation with the mature cyclical pentapeptide also inhibits bacterial growth. Together, these findings provide new foundational insights needed for engineering improved pentose utilizing strains of C. thermocellum and reveal the first functional Agr-type cyclic peptide to be produced by a thermophilic member of the Firmicutes. Clostridium thermocellum, have marked this bacterium as a potential biocatalyst for lignocellulosic biofuel production through consolidated bioprocessing (CBP)1C. thermocellum colonizes plant cell walls where it utilizes a diverse suite of lignocellulose deconstructing enzymes to generate fermentable sugars3The cellulolytic capabilities of the thermophilic anaerobe, Miscanthus, switchgrass and Populus, contain xylan-based hemicelluloses568C. thermocellum is highly capable of deconstructing and solubilizing hemicellulose polymers as a means of improving accessibility to cellulose1011914Potential bioenergy crops, such as C. thermocellum mediated hemicellulose deconstruction would typically be consumed by other saccharolytic, pentose-fermenting thermophiles such as Thermoanaerobacter and Thermoanaerobacterium sppC. thermocellum is able to hydrolyze hemicellulose polymers, but unable to catabolize pentoses, little effort has been given to understanding how the microorganism interacts with these residual saccharides. Despite the lack of catabolic activity, it is possible that: i) interactions occur; and ii) the nature of the interactions may be detrimental to the microbe. For example, despite its inability to ferment xylose, glucose uptake in Saccharomyces cerevisiae can be competitively inhibited by the pentose sugar17C. thermocellum pure culture fermentation on minimally pretreated biomass, the purpose of this study was to assess the impact of xylose and xylo-oligomers on the metabolism of the bacterium.In nature, the products of C. thermocellum M1570The model substrates xylose and Beechwood xylan were added at increasing concentrations to C. thermocellum-mediated xylan hydrolysis has been reported to yield xylobiose as the principal hydrolysis product followed by xylotriose and xylotetraose10111-X4 were tested for their effect on growth rate  relative to the uninhibited control. Given the similarity in inhibition, the monomer xylose was chosen as a model substrate for continued investigation.wth rate . All comC. thermocellum was next challenged with various other D- and L-isomer pentose sugars  provide insight into the basis for inhibition in strain M1570; and ii) help identify the genes/enzymes responsible for the observed transformations of xylose. From mid-exponential phase cultures, 23 genes were significantly  down-regulated by a factor of two-fold or more, while 37 genes were significantly up-regulated two-fold or more in the xylose inhibited cultures relative to the uninhibited control . Genes aC. thermocellum datasets have identified that these transketolase genes are expressed at low levels during uninhibited growth, while another annotated transketolase (Clo1313_0295-0296) is much more abundantly expressed21Eight genes at one locus (Clo1313_0073-0080), predicted to form three distinct operons, were in the top ten most highly up-regulated (3-6 fold) genes in the xylose inhibited cultures . Two of C. thermocellum genes within the Transporter Classification DatabaseC. thermocellum ATCC 27405, which has previously been characterized and its homology to pentose-binding proteins noted+ symporter with homology to arabinose binding proteins. Deletion mutants hpt ΔClo1313_1055) showed comparable levels of inhibition when comparing their growth rates under 0 g/L and 15 g/L xylose conditions  but statistically significant relief of inhibition relative to the parental strain indicating that, at least in part, xylose uptake involves an ATP-dependent transporter.While the ratio of xylose to cellobiose did not seem to affect the observed inhibition , we rati mutants  of each nditions  indicatiEscherichia coli. Despite successful overexpression of the protein, in vitro activity when tested with either xylose or xylulose was not observed when assayed aerobically or anaerobically at 55 °C using NADH or NADPH as co-factors (not shown).Consistent with the formation of xylulose and xylitol in our metabolomics data was the significant up-regulation of an annotated xylitol dehydrogenase (XDH - Clo1313_0076) within the highly up-regulated 8-gene cluster . 6X-His-hpt parental strain and JE0148, the latter produced significantly less formate and more lactate than the parental strain.Alternatively, a deletion mutant of Clo1313_0076, designated strain JE0148, was constructed . DeletioC. thermocellum growth, however  suggests that xylose uptake also occurs, at least in part, by ATP-dependent mechanisms. Due to the inability to catabolize the sugar and generate ATP from its breakdown, xylose uptake could impose an energetic penalty on the cell equal to −1 mol of ATP per mol of xylose transported. Consistent with this hypothesis is the observation that strain M1570, whose acetate production capabilities have been reduced by deletion of its phosphotransacetylase gene (Δpta)21We identified that various oligomers of xylose, most notably the principal hydrolysis product xylobiose1011C. thermocellum fermentations and has been associated with catabolic overflow metabolism36C. thermocellum can convert D-xylose to xylitol presumably at the expense of reduced nicotinamide cofactors. This reduction is important to consider in developing the bacterium into a robust biofuel producing microbe. Fuel molecules are electron-rich and any electron diversion away from the fuel is undesirable. Ethanol yields have been greatly improved in C. thermocellum through efforts to disrupt fermentation pathways that compete for electrons3839xdh did not significantly affect ethanol production . The high expression level observed at the mid-point of inhibited culture growth is consistent with the high growth-phase expression levels previously reported during switchgrass and Populus fermentationsagrD would, by default, seemingly be linked to an unknown effector molecule or be possibly induced as part of a xylose-induced stress response.Up-regulation of C. thermocellum.The synthetic AIP clearly had a limiting effect on growth in the absence of pentose sugars , yet itsC. thermocellum, or through co-culturing with pentose-fermenting thermophiles16C. thermocellum fermentation or simultaneously alongside hydrolysis and fermentation to avoid pentose accumulation. In any case, investigations into the effect of biomass derived compounds on C. thermocellum hydrolysis and metabolism are warranted.The focus of this research was to study the effect of xylo-oligomers on the fermentation of soluble substrates. The accumulation of non-metabolizable saccharides may also influence continued biomass hydrolysis as has been reported with commercial enzyme cocktails14A further complication is that xylose does not just inhibit growth, but also consumes valuable reducing equivalents. Construction of strain JE0148 significantly reduced electron loss to xylose, but led to an increase in lactate, rather than ethanol, formation. Combining this gene deletion with strains recently engineered to have reduced lactate, acetate, formate and hydrogen production capabilities193839Clostridium acetobutylicum2728C. thermocellum encodes multiple putative signalling peptides within its genome (others include Clo1313_0024 and Clo1313_0946). Elucidation of potential cellular cross-talk mechanisms in C. thermocellum, as well as how other axenic culture-induced limitations affect the bacterium’s physiology, will be important in the continued development of the microorganism.Finally, with the exception of C. thermocellum ATCC 27405, C. thermocellum DSM 1313, and C. thermocellum M1570600) of 0.45–0.55.Lab stocks of 2 : 10% CO2 : 85% N2. OD600 measurements were taken every 15 minutes for 24 hours using a Biotek Eon spectrophotometer . Growth rates were calculated using the Growth Rates Made Easy software packageFor growth rate studies, 200 μl cultures were grown in 96-well pre-sterilized polystyrene plates in an anaerobic chamber with an inlet gas comprised of 5% H2 production calculations (headspace and liquid fractions) were done as previously describedSugar consumption and fermentation end-products were measured as previously reportedC. thermocellum were grown in MTC medium containing 15 g/L xylose or with no added xylose. Upon reaching the mid-point of growth as determined via OD600, the culture was pelleted by centrifugation at 8,000 x g for 5 minutes at 4 °C. Cell pellets was then frozen in liquid nitrogen and stored at −80 °C until RNA could be extracted. RNA isolation and library preparation were done essentially as describedQuadruplicate, 40 mL cultures of 2 transformed differential gene expression of ±1.Raw reads were mapped to the genome [GenBank:CP002416] using CLC Genomics Workbench version 8.0  and the default settings for prokaryote genomes. Counts of uniquely mapped reads were analyzed for differential gene expression by DESeq213C-xylose (D-[U-13C] xylose) was purchased from Omicron Biochemicals Inc. . For metabolomic analyses, strain M1570 was grown as 12 mL cultures in MTC medium containing 15 g/L xylose, 15 g/L D-[U-13C] xylose or in the absence of added xylose. At the mid-point of growth for each respective condition, entire cultures were sacrificed. As xylose uptake was a primary interest of the experiment, cell pellets were washed with ice cold phosphate buffered saline (PBS) to minimize the amount of contaminating xylose or D-[U-13C] xylose associated with the cell pellet. In brief, cultures taken from the incubator were pelleted at 8,000 x g for five minutes, washed twice with equal volumes of PBS and then snap frozen in liquid nitrogen. Cell pellets were stored at −80 °C until metabolomic analyses could be performed.Universally labelled 12C- and 13C-xylose samples compared to the untreated control. GC-MS analyses of our 12C- and 13C-xylose stock solutions confirmed that they did not contain either xylulose or xylitol (not shown).Intracellular metabolites were extracted from cell pellets (42–81 mg fresh weight) by sonication for 3 min at 20% amplitude, 10 s on and 10 s off, with the pellets kept on ice. Extracts were then centrifuged for 20 min at 4,500 rpm and stored at −20 °C until analysis. Extracts were analyzed as trimethylsilyl derivatives by gas chromatography-mass spectrometry (GC-MS), using electron impact ionization (70 eV), as described elsewhereC. thermocellum cultures grown with or without 15 g/L xylose were either concentrated or processed via solid-phase extraction (SPE) to enrich for the AIP. Regardless of the enrichment method, supernatant was first precleared via centrifugation  and filtered through a 5 kDa MWCO spin column  to remove larger proteins and polypeptides. Two mL of precleared supernatant were concentrated to 150 μL by SpeedVac centrifugation and adjusted to 10% acetonitrile and 0.5% formic acid prior to sample loading. To enrich for the AIP via SPE, 5 mL of precleared supernatant was passed through an equilibrated C18 Sep-Pak Lite SPE cartridge , washed twice with 10 mL solvent A  and eluted with 3 mL of 100% acetonitrile into three 1 mL aliquots. Enriched aliquots were then concentrated via SpeedVac centrifugation, combined , and acidified to 0.1% formic acid prior to sample loading.Supernatant samples collected from 2O, 95% acetonitrile, 0.1% formic acid). Targetted monitoring of the predicted cyclical AIP (642.3292 m/z) was performed using an Orbitrap Pro mass spectrometer . Briefly, a m/z range of 642.33 ± 1.1 was continuously isolated and fragmented by successive CID (35% energy) and HCD (30% energy) events over the course of the separation. Fragment ions resulting from either CID or HCD were passed to the Orbitrap mass analyzer for high-resolution measurements with parts-per-million (ppm) accuracy. Extracted-ion chromatograms  for specific fragment ions mapping to the predicted AIP, as gleaned from a preliminary CID and HCD measurements of the synthetic AIP, were monitored using Xcalibur Qual Browser v.2.2. XIC peaks at the same retention time indicate the presence of the AIP in culture supernatants.Sample loads representing 5% (SPE) to 20% (concentrate) of unadulterated supernatant were loaded onto a 150-micron ID back column with 5 cm C18 resin . After washing the loaded back column with solvent A for 10 min, it was placed in-line with an in-house-pulled nanospray emitter packed with 15 cm C18 resin and analyzed by LC-MS/MS over a 30 min organic gradient to 100% solvent B , while the L5 linear peptide was supplied by LifeTein LLC . The lyophilized peptides were reconstituted in filter sterilized DMSO, diluted to the desired concentrations and then added to MTC medium with or without 15 g/L xylose. The final concentration of DMSO for all concentrations was 0.8% (v/v). Growth assays were conducted as 200 μl cultures using 96-well plates and growth rates were determined as described above.C. thermocellumhpt ΔcbpD) and JE0149 (Δhpt ΔClo1313_1055), the effect of gene deletion was assessed through growth rate analyses under 0 g/L or 15 g/L xylose conditions as described above. For the xdh gene deletion, comparative 72-hour fermentations were performed between the Δhpt parental strain and strain JE0148 (Δhpt ΔClo1313_0076) in medium supplemented with 15 g/L cellobiose, 15 g/L xylose and an additional 5 g/L MOPS buffer . Xylitol and end-product analyses were performed via HPLC as described above.Standard methods for vector construction via Gibson’assemblyAccession codes: Raw RNA-Seq data have been deposited in NCBI Sequence Read Archive under accession SRP070709 and gene expression data under NCBI GEO accession GSE78219.How to cite this article: Verbeke, T. J. et al. Pentose sugars inhibit metabolism and increase expression of an AgrD-type cyclic pentapeptide in Clostridium thermocellum. Sci. Rep.7, 43355; doi: 10.1038/srep43355 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


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SVG) compared with the left internal mammary artery (LIMA) graft, which is affected by the hemodynamic environment. A comprehensive analysis of postoperative structure‐function changes is important to study the atherogenesis in the SVG. A comparison of morphometric and hemodynamic parameters was carried out between LIMA grafts and SVGs and between different time points postoperatively. Various parameters were obtained from the image reconstruction and flow simulation in patients, who underwent CT exams for ~1 year, 5 and 10 years after revascularization. Morphometric data showed a decrease in lumen size in the entire SVG and anastomosis of different patients in a sequence of ~1 year, 5 and 10 years postoperatively despite negligible changes of LIMA size. Computational results indicated the fourfold increased surface area ratio (SAR) of low time‐averaged wall shear stress (TAWSS) in the SVG and anastomosis at postoperative 10 years than that at postoperative ~1 year. The SAR of high TAWSS gradient (TAWSSG) at the distal anastomosis between SVG and coronary arteries was significantly higher (14 ± 9% vs. 6 ± 8%) than that in the LIMA group at postoperative ~1 year. There were strong correlations between morphometric and hemodynamic parameters in the SVG and distal anastomosis at various time points postoperatively, which showed deterioration relevant to persistent diffuse diseases at postoperative ~10 years.There is higher long‐term failure of the saphenous vein graft ( Coronary artery bypass graft (CABG) can effectively relieve symptoms of ischemic heart diseases  in SVGs and anastomoses of different patients in a sequence of postoperative ~1 year, 5 and 10 years despite relatively small difference in LIMA grafts. The correlation between the highest SAR‐TAWSS and the smallest lumen size of SVGs and anastomoses in patients at postoperative ~10 years indicated the high incidence of mild atherosclerotic lesions as compared with those at postoperative ~1 year and 5 years. To test the hypotheses, the geometry of the graft and coronary arteries was reconstructed from CTA images of 132 patients. We computed multiple hemodynamic parameters, that is, TAWSS, OSI, TAWSSG and transWSS (transverse WSS)  for the Affiliated Hospital of Xuzhou Medical University, which confirms the declaration of Helsinki. All patients gave the signed informed consent for all methods of the study performed in accordance with the relevant guidelines and regulations of the IRB for the Affiliated Hospital of Xuzhou Medical University.Similar to previous studies  at the College of Engineering, Peking University as well as a Radiologist (Yingjin Xu) at the Affiliated Hospital of Hebei University and a Cardiologist (Yuan Lu) at the Affiliated Hospital of Xuzhou Medical University. The reproducibility of those measurements showed 87 Cohen .Based on these morphometric data, geometrical models were meshed using the ANSYS ICEM software  and then smoothed using the Geomagic Studio software . Similar to a previous study  and density (ρ) of the solution were set as 4.5 × 10−3 Pa∙s and 1060 kg/m3, respectively, to mimic blood flows with a hematocrit of about 45% in these arteries. Hemodynamic parameters including the WSS, OSI, WSSG, and transWSS (see details in the 2) and high OSI (OSI ≥ 0.15), TAWSSG (TAWSSG ≥ 500 dynes/cm3), and transWSS (transWSS ≥ 6 dynes/cm2), respectively, in the graft or distal anastomosis.The Navier‐Stokes and continuity equations  values of morphometric and hemodynamic parameters were computed by averaging over all subjects in a population. The best fit diameter, DTable fit along the normalized graft centerline in LIMA and SVG groups, respectively, while Figure fit along the normalized anastomotic centerline. The centerlines are normalized by the accumulative length from A1 to A10 in Figure inlet, Dmean, Lchord, Larc, and Danas refer to the inlet diameter of a graft, the averaged diameter in the entire graft except for the anastomotic region, the accumulative length along the entire graft, the straight length from the inlet to the distal anastomosis of the graft, and the averaged diameter in the anastomosis, respectively. Morphometric parameters, Dinlet, Dmean, and Danas, decrease with time in the SVG group, but remain relatively unchanged in the LIMA group. The ratios of Lchord to Larc in the LIMA group are similar to those in the SVG group.Figure P‐value < 0.05) than those in the LIMA; at postoperative ~10 years, SAR‐TAWSS in the SVG and anastomosis are 1.5‐3.5 times higher  and SAR‐OSI in the SVG is 2.2 times higher , compared with the LIMA group.Figure P‐value < 0.05); (2) There is relatively small difference of diameters in the LIMA group over time while patients in SVG and LIMA groups have similar diameters for ~10 years after revascularization; (3) SAR‐TAWSS and SAR‐OSI increase in the graft and anastomosis of different patients for a sequence of postoperative ~1 year, 5 and 10 years, which shows significant difference of SAR‐TAWSS in the SVG and anastomosis between different time points, but no statistical difference of SAR‐OSI; and (4) SAR‐TAWSSG in the anastomosis at postoperative ~1 year and SAR‐TAWSS in the graft and anastomosis at postoperative ~10 years are significantly higher in the SVG group than those in the LIMA group. The findings are discussed in relation to the potential improvement of graft patency.We carried out the morphometric and hemodynamic analysis in the graft (LIMA vs. SVG) and coronary arteries with the end‐to‐side anastomosis as well as severe coronary stenoses, reconstructed from CTA images of 132 patients. Three major findings are reported as: (1) Patients at postoperative ~1 year have the maximal diameters in the SVG and anastomosis while patients at postoperative ~10 years have the minimal values  in patients for ~10 years after revascularization Fig. A vs. B. The anastomosis between the graft and coronary artery is the most frequent site for the graft failure  implies an enhanced graft attrition rate over 10 years after revascularization  are also needed to find the relation between hemodynamic changes and chronic endothelial cell injury and dysfunction in the graft and distal anastomosis (Motwani and Topol The retrospective study showed morphometric and hemodynamic changes in LIMAs or SVGs of different patients for ~1 year, 5 and 10 years after surgical revascularization. There were strong correlations between high SAR‐TAWSS and small lumen size in the SVG and distal anastomosis at different time points despite the negligible changes in the LIMA graft. The high SAR‐TAWSSG in the anastomosis between SVG and coronary arteries could also contribute to the vascular remodeling within the initial years after grafting. The findings can improve our understanding of hemodynamic mechanisms for graft failure.The authors declare no conflicts of financial/personal interest.


The Brazilian Journal of Cardiovascular Surgery (BJCVS) is grateful for the reviewers,listed below, which collaborated in this edition. Without their work would be impossibleto keep the high scientific standard of our journal.Carlos PiccinatoEduardo Augusto Victor RochaEduardo Keller SaadiFrancisco CostaGibran Roder FeguriGiovani Jose Dal Poggetto MolinariGuilherme AgreliHélcio GiffhornJoão Carlos Ferreira LealJosé Glauco Lobo FilhoNelson HossneOtoni GomesPablo Maria Alberto PomerantzeffPaulo BrofmanRicardo Ribeiro DiasStevan Krieger Martins