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Bruch Membrane

Bruch's membrane is a thin, semipermeable layer located between the retinal pigment epithelium and the choroid in the eye.
It plays a critical role in the nutrient and waste exchange between these tissues.
Alterations to the structure and function of Bruch's membrane are implicated in various eye diseases, such as age-related macular degeneration.
Understainding the complex biology of Bruch's membrane is essential for developing effective treatments and preventive strategies for these conditions.
PubCompare.ai can help researchers optimize their Bruch's Membrane studies by providing access to the latest protocols and enabling data-driven comparisons to identify the best approaches for their research.

Most cited protocols related to «Bruch Membrane»

The choroid was imaged using the EDI mode of SD-OCT (Spectralis, Heidelberg Engineering, Heidelberg, Germany). The macular region was scanned using a 7 horizontal line scan (30° × 5°) centred on the fovea, with 100 frames averaged in each B-scan. Each scan was 8.9 mm in length and spaced 240 μm apart from each other. In our study, Bruch’s membrane and the choroid-scleral interface were delineated with the automatic segmentation algorithm developed by Tian et al.35 (link) which demonstrated excellent repeatability in our previously reported population-based study36 (link). The choroidal thickness was automatically measured as the distance between the Bruch’s membrane (lower boundary of retinal pigmented epithelium [RPE]) and the choroid-scleral interface. Although measurements of both eyes of each study participant were obtained, due to inter eye correlation only the right eye was used for further analysis.
Publication 2016
Bruch Membrane Choroid Macula Lutea Radionuclide Imaging Reading Frames Retinal Pigment Epithelium Sclera

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Publication 2013
Arteries Blood Vessel Bruch Membrane Capillaries Choriocapillaris Choroid Eye Haller Layer Healthy Volunteers LINE-1 Elements Nose Postmortem Changes POU2F1 protein, human Radionuclide Imaging Sattler's Layer Sclera Tissues Veins

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Publication 2012
Bruch Membrane Choroid Choroidal Neovascularization Epiretinal Membrane Intraretinal Fluid Macula Lutea POU2F1 protein, human Radionuclide Imaging Retina Retinal Detachment Retinal Pigment Epithelial Detachment Sub-Retinal Fluid

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Publication 2015
4-phenylenediamine Allium cepa ARID1A protein, human Autopsy Blood Vessel Bruch Membrane Buffers Choroid Donors Edema Epoxy Resins Eye Glutaral Immersion Lens, Crystalline Light Lipids Lipofuscin Macula Lutea Melanosomes Microscopy Multimodal Imaging Optic Disk Osmium paraform Pathologic Neovascularization Phosphates Photoreceptor Cells Pigmentation Polybed 812 Radionuclide Imaging Retina Tannins Tissue, Membrane Tissues Tolonium Chloride Woman
As previously described,7 (link),8 (link) the raw scan data were exported from the fdOCT machine and displayed by the segmentation program. Fig. 1A shows a sample 6-mm line scan of a control eye. The operator manually marked the boundary of a retinal layer by using the “mouse” and a “click” to place points along the boundary. The program, written in MATLAB (v7.4, Mathworks, Natick, MA), drew a curve through these points using a spline algorithm. Points could be added and/or changed until the operator was satisfied that the boundary was described by the smooth curve.
Four borders were marked (Fig. 1A): (1) the border between the vitreous and the RNFL (red); (2) the border between the RNFL and the RGC layer (orange); (3) the border between the IPL and the inner nuclear layer (INL) (green); and (4) the border between retinal pigment epithelium (RPE)/Bruch’s membrane (BM) and the choroid (violet). By using these borders, the thicknesses of four layers, which have been used in studies of glaucoma, were calculated. In particular, the RNFL thickness (red vertical line) was calculated as the difference between borders 1 (vitreous/RNFL border) and 2 (RNFL/RGC border). Similarly, the RGC layer plus IPL (RGC + IPL; orange line) was calculated as (2 – 3) and is shown as the orange vertical line. We measured the combined thickness, RGC + IPL, because on most scans, the border between RGC and IPL could not be visualized. The thickness of the total retina (white line) was calculated as (1 – 4). In addition, we included what has been called the ganglion cell complex (GCC) because it has been used in commercial machines and in other studies. The GCC thickness (green line) is the sum of the RNFL and RGC + IPL and is calculated as (1 – 3).
Publication 2011
Bruch Membrane Cells Choroid Ganglia Glaucoma Mice, Laboratory Radionuclide Imaging Retina Retinal Pigment Epithelium Viola

Most recents protocols related to «Bruch Membrane»

Example 8

In this model of age-related macular degeneration (AMD), CNV is induced by argon laser-induced rupture of Bruch's membrane in mice on Day 0 (3 burns per mouse). Groups of 10 mice are studied and treatment administered via weekly intravitreal injections (at day 0 and day 7) of human isotype control antibody, VGX-301-ΔN2, VGX-300, Eylea (VEGF-Trap), VGX-301-ΔN2+Eylea or VGX-300+Eylea. At day 14, animals are sacrificed and choroidal flat mounts prepared and stained with ICAM-2 to visualize the neovascularisation by fluorescence microscopy.

It is contemplated that VGX-301-ΔN2, as a single-agent, will significantly inhibit choroidal neovascularisation in a mouse model of neovascular AMD, comparable to the effect demonstrated by Eylea®.

Patent 2024
aflibercept Age-Related Macular Degeneration Animals Argon Ion Lasers Bruch Membrane Burns Cardiac Arrest Choroid Choroidal Neovascularization eylea Homo sapiens Immunoglobulin Isotypes Immunoglobulins Intercellular Adhesion Molecules Microscopy, Fluorescence Mus Pathologic Neovascularization
After all OCT-A scans were manually checked for artefacts, shadows and correct segmentation, macula data was exported from the clinical database and then imported into the prototype SP-X1902 software (Heidelberg Engineering, Heidelberg, Germany). The Anatomic Positioning System function (APS, part of Glaucoma Module Premium Edition [GMPE], Heidelberg Engineering, Germany) allows each scan to be aligned to the patient´s individual Fovea to Bruch’s Membrane Opening (FoBMOC) axis for better intra- and interindividual scan comparability. Integration of APS information was also implemented into the Erlangen Angio-Tool (EA-Tool) version 2.0, coded in Matlab (The MathWorks, Inc., R2017b). In addition to the APS information, the macular en face OCT-A images of SVP, ICP and DCP were imported into the EA-Tool and analyzed separately for each scan. Overall and sectorial macula VD (12 sectors s1-s12 á 30°) were analyzed for SVP, ICP and DCP, respectively. The analyzed region of the scan size was 6.10 mm2.
Publication 2023
Bruch Membrane Epistropheus Face Glaucoma Macula Lutea Patients Radionuclide Imaging
All measurements were performed on each subject without prior pupil dilation at three consecutive sessions (9 AM, 3 PM and 9 PM) within one day. An interval of six hours had to be between each measurement. One eye of each subject was chosen randomly before the first acquisition. To avoid fluctuations in blood pressure and heart rate, the measurements were taken each time after a waiting period of ten minutes in a sitting position and the participants were prohibited to consume caffeine prior to each visit. Each session included a high-resolution three-layer en face OCT-A scan of macula region (including SVP, ICP and DCP) and a high-speed OCT scan with enhanced depth imaging mode (EDI) to determine subfoveal CT, both by Heidelberg Spectralis II OCT (Heidelberg Engineering, Heidelberg, Germany). In addition, AL was measured with IOL master 500 (Carl Zeiss Meditec AG, Jena, Germany). All OCT-A scans were recorded on a 2.9 x 2.9 mm2 window with a 15° x 15° angle and a lateral resolution of 5.7 μm/pixel. Subfoveal CT was measured manually with a vertical distance between the hyperreflective line of Bruch’s membrane and the choroid-scleral interface.
Publication 2023
Blood Pressure Bruch Membrane Caffeine Choroid Face Macula Lutea Mydriasis Radionuclide Imaging Rate, Heart Sclera
The choroidal image was taken with EDI mode SD-OCT. All scans were taken between 9.30 am and 11.30 am to avoid the diurnal variation of CT (21 (link)). In addition, patients’ blood pressure was checked before scanning as the highly vascularized choroid might be affected. The imaging protocol was comprised of 49 horizontal 9 mm raster B-scans centered at the fovea per volume scan of 30° Å~ 30°. Signal strength ≥7 was used for analysis. Subfoveal CT was measured manually at the fovea using the caliper tool in the software, as the vertical distance between the hyperreflective line of Bruch’s membrane and the hyper-reflective line of the choroido-scleral interface. To calculate CVI, macular SD-OCT scans were binarized using the publicly available software ImageJ 1.51s (National Institutes of Health, Bethesda, MD, United States of America [USA]), with a semi-automated technique (16 ). First, the EDI-OCT image was opened with ImageJ, and the polygon tool was used to assess the region of interest (ROI) across the entire length of the OCT scan. The upper boundary of the ROI was traced along the basal margin retina pigment epithelium and the lower boundary along the choroidoscleral border to define the TCA. The image was converted to eight bits, and auto local thresholding (Niblack method) was performed to this binarized image (16 ). Second, to allow a selection of dark pixels, as defined the LA, the image was again converted into red, green, and blue color. The LA was calculated as the sum of dark pixel areas. In the binarized image, bright pixels were defined as stromal area (SA), which was computed from the subtraction of LA from TCA of the ROI. CVI, an indicator of choroidal vascular status, was calculated as the ratio between LA and TCA (Fig. 1).
Publication 2023
Blood Pressure Blood Vessel Bruch Membrane Choroid Circadian Rhythms Macula Lutea Patients Radionuclide Imaging Retinal Pigment Epithelium Sclera
Segmentation of retinal layer boundaries on each OCT retinal B-scan and thickness maps of the desired retinal cell layers were performed and generated by Heidelberg software (Fig. 3C). Internal limiting membrane (ILM), external limiting membrane (ELM) and basement membrane (BM refers to the basement membrane of the choriocapillaries/Bruch’s membrane) were used for segmentation. The Heidelberg Spectralis segmentation software reliably detects these structures and provides accurate segmentation. Given that previous studies have shown significant thickness changes in the outer retinal layer, for the thickness maps, the retinal cell layers chosen for analysis were the outer retinal layer (between BM and ELM), inner retinal layer (between ELM and ILM), and overall retina (between BM and ILM).
For each analyzed retinal layer, the thicknesses across the 49 scans were averaged across nine regions of interest, including the foveal and the inner and outer perifoveal (superior, nasal, inferior, and temporal) regions (Fig. 1A, Supplementary Figs. 14A).
Averaged thicknesses across the foveal and inner and outer perifoveal regions were compared before and after dark adaptation for each subject. The absolute values of the before-and-after differences were compared between dark adapted/patched versus unpatched control eyes by paired t testing, two-tailed. Statistical significance was defined as p < 0.05.
For band intensity evaluation, all B-scans for the dark adapted/patched and unpatched control eyes, before and after the dark adaptation period, were masked and quantitatively and assessed for their EZ and IZ band intensities.
For assessing EZ band intensity changes, we used EZ:ELM ratio to eliminate potential intensity changes introduced to each scan because of factors such as media clarity, head tilt etc. Invitrogen GelQuant Express software was used to evaluate EZ band intensity changes over the central 2600 µm region on the central line scan. This region was split into 11 boxes, and due to irregular contour of bands in the fovea, the central-most box was excluded from analysis. The EZ and ELM band intensities were measured and the EZ:ELM ratios were calculated and averaged across the remaining 10 boxes. The EZ:ELM ratios, after vs before the dark adaptation period, were compared between light and dark adaptation conditions using paired t-testing, two-tailed.
In addition to EZ band intensity, we evaluated OCT images for any clinically significant changes. In a pilot observation we noticed some changes in the length of visibility of IZ band before and after dark adaptation. Thereafter, the IZ band lengths, before and after the dark adaptation period, were compared using paired t-testing, two-tailed.
Publication 2023
Bruch Membrane Cells Choriocapillaris Dark Adaptation Eye Figs Head Light Membrane, Basement Microtubule-Associated Proteins Nose Radionuclide Imaging Retina Temporal Lobe Tissue, Membrane Venous Catheter, Central

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More about "Bruch Membrane"

Bruch's Membrane, also known as the Bruch Membrane or Bruch Membrane, is a critical component of the eye's structure, playing a vital role in the exchange of nutrients and waste between the retinal pigment epithelium (RPE) and the choroid.
This thin, semipermeable layer is essential for maintaining the health and function of the retina.
Alterations to the structure and function of Bruch's Membrane are linked to various eye diseases, such as age-related macular degeneration (AMD), a leading cause of vision loss in older adults.
Understanding the complex biology of Bruch's Membrane is crucial for developing effective treatments and preventive strategies for these conditions.
Researchers studying Bruch's Membrane can leverage advanced imaging technologies like Spectralis OCT, DRI OCT Triton, and Heidelberg Eye Explorer to visualize and analyze the structure and changes in this important tissue.
Techniques like MATLAB and Micron IV can also be used to model and quantify the behavior of Bruch's Membrane.
Additionally, the use of anesthetics like Rompun and Tropicamide can help facilitate the examination and manipulation of Bruch's Membrane in animal models and clinical settings.
By optimizing their research approaches and utilizing the latest tools and technologies, researchers can gain valuable insights into the role of Bruch's Membrane in eye health and disease.
PubCompare.ai, an AI-driven platform, can assist researchers in enhancing the reproducibility and accuracy of their Bruch's Membrane studies.
The platform provides access to the latest protocols from literature, pre-prints, and patents, and enables data-driven comparisons to identify the best approaches for their research.
By leveraging PubCompare.ai's powerful tools and data-driven insights, researchers can optimize their Bruch's Membrane studies and contribute to the development of more effective treatments and preventive strategies for related eye conditions.