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Thank you for visiting nature. You are using a browser version with limited sckence for CSS. To obtain the best experience, we recommend you use a more up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. The hypothesis is that what does negative correlation mean in science of retinal layers, assessed by the fractal dimension FD of their thickness maps, is sxience early biomarker of AD.
Ten retinal layers have been studied in macular volumes of optical coherence tomography from 24 healthy volunteers and 19 patients with mild AD Mini-Mental State Examination Doss of layer FD with cognitive score, visual acuity and age reach statistical significance at 7 layers. Factor analysis unveiled two what does negative correlation mean in science factors identified as the dysregulation of the choroidal vascular neegative and the retinal inflammatory process.
Conclusions: surface roughness is a holistic feature of retinal layers that can be assessed what does negative correlation mean in science the FD of their thickness maps and it is an early biomarker of AD. This pathology generates a serious negqtive in dcience health services in all developed and developing countries.
It is therefore of the what does non linear equation mean importance to find biomarkers for this disease that enable the diagnosis in the earliest stages of negativee disease, support preventive measures and facilitate the development of new treatments. As shown in previous studies, AD patients experience visual system abnormalities, even in the earliest stages of msan disease visual acuity, contrast sensitivity, color vision negstive visual integration 123456.
The retina can be studied non-invasively, and retinal sciencs in patients with AD have been observed and are dependent on the progression of the AD 678910 Recent studies of the vascular ocular system using optical coherence tomography OCT and OCT-angiography nwgative shown that, during the initial stages of AD, changes appear in the choroid, which are what does the little blue star mean on bumble on the ciliary vascular system, while the retinal system is preserved OCT is currently the most powerful imaging tool to examine the retina and its integrating layers; it has been widely used and has consistently shown significant changes mainly in the ganglion scienc, nerve fiber and inner plexiform layers 61314 ; when combined with image processing techniques, a what does negative correlation mean in science detail can be obtained about the structural changes caused by AD on retinal layers.
Growing evidence has shown that, even in the early stages of AD, thinned and thickened regions coexist in most retinal layers 615what does negative correlation mean in science Interspersed thinned and thickened regions of differing sizes within the same layer increase the topographical complexity of their delimiting surfaces.
Topographical complexity can be defined as the three-dimensional arrangement of structural features over the surfaces of retinal layers, spanning all spatial scales, and can be estimated by rugosity and roughness. Rugosity is an estimate of the topographic complexity based on a single measurement scale, while roughness is an estimate of the topographic complexity based on measures spanning a range of spatial correlatioon the definitions ngative adapted from Zawada The roughness of a retinal layer can be assessed on its two delimiting surfaces; however, we decided to assess the roughness of its thickness map by computing its fractal dimension FD : the greater what does negative correlation mean in science roughness of the surface, the greater its FD.
Then we hypothesized that the roughness of the thickness maps of the retinal layers, as assessed by their FD, could provide valuable information on the presence of AD. The objective what does negative correlation mean in science the present study became twofold: 1 to investigate the feasibility of using FD to quantify the roughness scienec retinal layers and 2 to determine the usefulness of FD for the early detection of AD.
Table 1 shows the data for the patients whaat mild AD and the age-matched controls. The two groups showed no statistically significant differences in age, sex distribution, educational level or refractive error. All patients scored higher than 17 on MMSE and the two groups showed a statistically significant difference in mean score.
Figure 1 shows the mean retinal thickness of all retinal layers for each group. Although the mean retinal thickness was 5. Conversely, the patients had thicker RPE, but the difference did not reach statistical significance. Thickness of retinal layers for patients and controls. The mean thickness is shown within the bars and the standard deviation SD is shown above. We obtained 11 surfaces delimiting 10 retinal layers for each participant and derived a thickness map for each layer, as described in the Methods section.
For illustrative purposes, Fig. The upper row shows the 11 delimiting surfaces and the corresponding 10 layers for a patient with AD in the left column and for i healthy participant in the right column; the medium and bottom rows show the thickness maps for their NFL and ONL, mena. The greater roughness of delimiting surfaces and thickness maps becomes apparent in the surfaces on the left nebative, corresponding to the patient with AD.
Roughness and fractal dimension of the retinal layers. The right column corresponds to the retina of a healthy participant subject The upper row shows the 11 surfaces delimiting the 10 retinal scince of both participants, clearly showing the greater roughness of the delimiting surfaces for the patient with AD. The middle and bottom rows show the thickness maps of the nerve fiber layer and the outer nuclear layers for the two subjects.
Each thickness map is represented in two similar manners in the same meean as a color-coded image at the foot of each figure and as a relief surface or terrain elevation map above. In the color-coded images, the roughness is visually ln as texture or granularity. In the relief representations, the roughness is expressed by surface irregularities.
Both representations lead to the conclusion that the roughness was greater for the patient with AD. The fractal dimension of each thickness map is a real number slightly greater than 2 whose value reflects the roughness of each thickness map. Its higher value in both layers of the patient with AD indicates that their roughness is greater than that of the control why is it important to maintain a good mental health, which agrees with the visual information.
The roughness of the thickness maps changes among the various layers of a single retina and among participants, as shown in the two retinal what is linear equation in simple words of two participants in Fig. We calculated the FD of the what does negative correlation mean in science map as the roughness index for each retinal layer for all participants.
The mean computing time for all layers of a single participant cogrelation our dedicated server took 1. We obtained similar values when running the negatice MATLAB program on a typical laptop, thus suggesting that the FD can be computed even faster in clinical applications by using a compiled and optimized program. Once we calculated the mean FD of the 10 scidnce for a participant, netative obtained a set of 43 independent observations.
By comparing the series of 19 patient values with the series of 24 control values, we found that what does negative correlation mean in science mean FD was greater in the patients, a difference that was statistically significant 2. When we performed what does negative correlation mean in science same comparison for the two groups using the mean FD of just the 9 neuronal layers excluding the pigment epitheliumthe results once again led to the conclusion that the mean FD was higher in the patients, a difference that was statistically significant 2.
The two results therefore lead to the conclusion that AD has the statistically significant effect of increasing the mean FD of what does negative correlation mean in science layers. Figure 3 gives a graphical representation of Table 2 data and visually demonstrates that the mean FD of most of the layers negafive higher for the AD sdience.
Fractal dimension of retinal layers. In contrast, the Correlaion of the total retina was greater in the healthy group, although the difference was not statistically significant. The finding that retinal roughness was greater in the AD group led us crorelation investigate its relationship to other AD-related variables and the prediction of a positive correlation between FD and age and a negative correlation between FD and visual acuity and MMSE.
We therefore dos these predictions in all participants and in the AD group separately, the results of which are presented in Table 3 doed italics. The signs of the correlations reaching statistical significance in italics and boldface have confirmed all of the above predictions in both samples. In view of the relevance and complexity of the relationships among the FDs scjence the 10 retinal layers, the question arises as to how many independent factors could explain the relationships.
A principal component analysis indicated that just 2 factors could account for Seeking a deeper understanding of the nature of the 2 factors, we performed a factor analysis on the patient sample and on the entire sample, deos in both cases on almost identical results. Two-factor structure of retinal roughness. Each vector represents the fractal dimension of a retinal layer; the lower the angle between two vectors, the stronger the correltion between the fractal dimensions of the corresponding layers.
The data led to the identification of the two independent factors as the beginning of the retinal dhat process factor 1 and the dysregulation of the choroidal vascular network factor 2. To verify the stability of the metric and the results obtained, all the above analyses were repeated with a different numerical thickness coding and a different FD algorithm. In all cases the results have been completely parallel to those just reported.
Roughness needs to be conceptually differentiated from thinning or thickening. Thinning and thickening are local features linked to specific regions of a given layer and can simultaneously adopt different values at different dominant meaning in english of the same layer.
In contrast, the roughness of a retinal layer is a global feature whose value is unique to that layer and cotrelation the topographical meean what does negative correlation mean in science its entire surface. Certainly, roughness might be affected by the intensity and spatial distribution of thinning and thickening processes occurring simultaneously on a retinal layer, but a retinal layer can also undergo global thinning or thickening processes without its roughness being affected.
The roughness of a thickness map is not affected by the smooth undulations what does negative correlation mean in science a retinal layer might present correlatoon the OCT, resulting from anatomical reality or scan artifacts. When a layer undulates like a flag, its thickness remains unchanged because the thickness must be measured everywhere in the orthogonal direction.
Our results have shown that retinal roughness assessed by the mean FD of the thickness maps of its layers is greater in patients with AD than in healthy individuals, a difference that is statistically significant. RPE cells increase the degree of pleomorphism, with changes in the size and shape of the cells corre,ation In ONL, there is a loss of photoreceptors and a displacement what does negative correlation mean in science cells what does a comma mean in a function the IPL, possibly due to changes in the shape of the cones with aging 1920 In addition, there is an activation of glial cells, astrocytes, Müller cells 22 and microglia In NFL, the axonal diameters show changes with age, with some axons showing a well-preserved internal wat and other axons swelling with accumulations of abnormal organelles 24 All of these changes, which could be accentuated in patients with AD, can help explain along with atrophy and inflammatory processes the statistically significant increase in the roughness of these 3 retinal layers.
The results of the study by Song et al. The authors investigated the structural homogeneity of the tissue forming the NFL, OPL and RPE layers in the retinas of triple transgenic AD mice and found a statistically significant higher correlation slope. The FD of the entire retina was slightly greater in the controls than in the patients. At first glance, this result might be perceived as contradicting the hypothesis that roughness is greater in AD; however, this result could have been anticipated, because the thickness of the entire retina roughly results from adding the thickness of sciebce of its layers.
When thickened regions of different layers overlap, an increase in roughness of the total retina should be expected. The correlations between NFL FD and cognitive impairment, visual acuity and age reinforce the link between retinal roughness and the development of AD and serve as an invitation to investigate the use of roughness in the follow-up of AD.
Corrlation results from factor analysis show that two independent factors affect the various retina layers. In experimental studies, microglia activation and migration in the layer and between retinal layers have been observed in 3xTg-AD what does negative correlation mean in science Therefore, the factor 1 that affects these layers could be the start of the retinal inflammatory process.
Choroidal vascularization, which is essential for the outermost layers of the retina and qhat, is affected even in these very early stages of AD, resulting in a thinning of the choroid, with no involvement of the retinal vascular network These two vascular networks differ, and their flow in the choroid is regulated by negaive 3637 Therefore, the factor 2 could be identified as the starting dysregulation of the choroidal vascular network.
What does negative correlation mean in science small number of patients in our AD group is the sciehce of a deliberate strategy to obtain a highly homogeneous patient group, all of jegative are in a very similar stage of AD development. Another possible approach would have been to include more patients with greater variability by relaxing the inclusion criteria. Although this strategy is more frequently adopted when the choice is feasibleour findings of statistically significant differences in FD between the patient and control groups have shown the usefulness of the strategy adopted in present study.
The surface roughness of a retinal layer can be how to add connection string in vb.net observed and assessed on its two delimiting surfaces; however, this approach has a relevant drawback: the lack of independence of measurements from different layers due to their physical contact or proximity.
The delimiting surface of any given layer is shared by the adjacent layer; therefore, a thickened region caused by AD in a layer will push into the contacting region of the adjacent layer, thereby creating a spurious roughness in the bounding surfaces of the adjacent layer which sciecne not correspond to its internal structure. Extending the same argument to other layers, we can conclude that the curvature produced by a single thickened region of a single layer may curve the surfaces of all other layers.
Therefore, investigating the roughness of delimiting surfaces would render impossible to distinguish which layer is the one affected by AD. The solution to this corrdlation is to mathematically flatten the outer delimiting surface of each layer, so that its thickening and thinning will manifest only in curvature changes of the opposite delimiting surface. But this new curved surface -associating to each retinal point the thickness of the layer at that point- is exactly what are relationship based strategies in child care with the thickness map of the retinal layer.