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#microcirculation #space #spaceflight #medicine #microgravity #endothelialdysfunction #imedos #health #vasculardiagnostics #cardiovascular #vascular #biomarkers #cardiology #healthtech #innovation… | ... 𝗠𝗶𝗰𝗿𝗼𝗰𝗶𝗿𝗰𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝘀𝗽𝗮𝗰𝗲. 𝗠𝗲𝗮𝘀𝘂𝗿𝗲𝗱. 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗼𝗼𝗱. For many years, Imedos has been actively involved in spaceflight medicine research. This work is driven by the growing recognition that microcirculato...

𝗠𝗶𝗰𝗿𝗼𝗰𝗶𝗿𝗰𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 #𝘀𝗽𝗮𝗰𝗲

Imedos, with @HHU.de & DLR, is developing a #wearable, head-mounted fundus #camera for #retinal #vessel analysis in #microgravity. The goal: better understand spaceflight-related #vascular & neuro-ocular changes.🚀

Discover the full story: tinyurl.com/DVA-zerograv...

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Chloe Cable, Sidney P. Kuo and Eric A. Newman observed that junctional conductance of #retinal AII amacrine cell electrical synapses is decreased by #NMDA receptors 👁️ 🧠

📜 Read the study here: physoc.onlinelibrary.wiley.com/doi/10.1113/...

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#FYI #PaulBeckwith video lecture #phototrophy #photosynthesis #chlorophyll #retinal #ATP #plants #microorganisms #evolution #biology #biochemistry #science
Paul & Newton introduce a highly interesting paper on the biology of #energy production from #sunlight

www.youtube.com/watch?v=6qX0...

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Global morphological heterogeneity of retinal organoids across development. Top row: Image segmentation and analysis pipeline. A convolutional neural network (CNN) with the DeepLabV3 architecture was trained on 841 images and their manually annotated masks (left). The CNN was subsequently used to segment all images of the dataset that were finally subjected to a pipeline extracting a total of 165 morphological parameters (morphometrics, right), including, among others, shape descriptors and image moments.  Intra-experimental global morphological organoid heterogeneity. Time-series images from one representative experiment were analyzed using the image analysis pipeline and subjected to t-SNE dimensionality reduction on the first 20 principal components. Data points were colored by individual organoids (left graph) and time frames of organoid development within the imaging window (right graph). While organoids clustered closely at earlier time points (up to 24 h), they strongly diverged at later time points, suggesting increasing inter-individual changes of their morphological characteristics over time.

Global morphological heterogeneity of retinal organoids across development. Top row: Image segmentation and analysis pipeline. A convolutional neural network (CNN) with the DeepLabV3 architecture was trained on 841 images and their manually annotated masks (left). The CNN was subsequently used to segment all images of the dataset that were finally subjected to a pipeline extracting a total of 165 morphological parameters (morphometrics, right), including, among others, shape descriptors and image moments. Intra-experimental global morphological organoid heterogeneity. Time-series images from one representative experiment were analyzed using the image analysis pipeline and subjected to t-SNE dimensionality reduction on the first 20 principal components. Data points were colored by individual organoids (left graph) and time frames of organoid development within the imaging window (right graph). While organoids clustered closely at earlier time points (up to 24 h), they strongly diverged at later time points, suggesting increasing inter-individual changes of their morphological characteristics over time.

Organoids are key models for studying development & disease, but heterogeneity is a problem. @wittbrodtlab.bsky.social use #DeepLearning to predict differentiation paths & resulting tissues in #retinal organoids, with implications for other #organoid systems @plosborn.bsky.social 🧪 plos.io/45VTMt1

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Global morphological heterogeneity of retinal organoids across development. Top row: Image segmentation and analysis pipeline. A convolutional neural network (CNN) with the DeepLabV3 architecture was trained on 841 images and their manually annotated masks (left). The CNN was subsequently used to segment all images of the dataset that were finally subjected to a pipeline extracting a total of 165 morphological parameters (morphometrics, right), including, among others, shape descriptors and image moments.  Intra-experimental global morphological organoid heterogeneity. Time-series images from one representative experiment were analyzed using the image analysis pipeline and subjected to t-SNE dimensionality reduction on the first 20 principal components. Data points were colored by individual organoids (left graph) and time frames of organoid development within the imaging window (right graph). While organoids clustered closely at earlier time points (up to 24 h), they strongly diverged at later time points, suggesting increasing inter-individual changes of their morphological characteristics over time.

Global morphological heterogeneity of retinal organoids across development. Top row: Image segmentation and analysis pipeline. A convolutional neural network (CNN) with the DeepLabV3 architecture was trained on 841 images and their manually annotated masks (left). The CNN was subsequently used to segment all images of the dataset that were finally subjected to a pipeline extracting a total of 165 morphological parameters (morphometrics, right), including, among others, shape descriptors and image moments. Intra-experimental global morphological organoid heterogeneity. Time-series images from one representative experiment were analyzed using the image analysis pipeline and subjected to t-SNE dimensionality reduction on the first 20 principal components. Data points were colored by individual organoids (left graph) and time frames of organoid development within the imaging window (right graph). While organoids clustered closely at earlier time points (up to 24 h), they strongly diverged at later time points, suggesting increasing inter-individual changes of their morphological characteristics over time.

Organoids are key models for studying development & disease, but heterogeneity is a problem. @wittbrodtlab.bsky.social use #DeepLearning to predict differentiation paths & resulting tissues in #retinal organoids, with implications for other #organoid systems @plosborn.bsky.social 🧪 plos.io/45VTMt1

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Global morphological heterogeneity of retinal organoids across development. Top row: Image segmentation and analysis pipeline. A convolutional neural network (CNN) with the DeepLabV3 architecture was trained on 841 images and their manually annotated masks (left). The CNN was subsequently used to segment all images of the dataset that were finally subjected to a pipeline extracting a total of 165 morphological parameters (morphometrics, right), including, among others, shape descriptors and image moments.  Intra-experimental global morphological organoid heterogeneity. Time-series images from one representative experiment were analyzed using the image analysis pipeline and subjected to t-SNE dimensionality reduction on the first 20 principal components. Data points were colored by individual organoids (left graph) and time frames of organoid development within the imaging window (right graph). While organoids clustered closely at earlier time points (up to 24 h), they strongly diverged at later time points, suggesting increasing inter-individual changes of their morphological characteristics over time.

Global morphological heterogeneity of retinal organoids across development. Top row: Image segmentation and analysis pipeline. A convolutional neural network (CNN) with the DeepLabV3 architecture was trained on 841 images and their manually annotated masks (left). The CNN was subsequently used to segment all images of the dataset that were finally subjected to a pipeline extracting a total of 165 morphological parameters (morphometrics, right), including, among others, shape descriptors and image moments. Intra-experimental global morphological organoid heterogeneity. Time-series images from one representative experiment were analyzed using the image analysis pipeline and subjected to t-SNE dimensionality reduction on the first 20 principal components. Data points were colored by individual organoids (left graph) and time frames of organoid development within the imaging window (right graph). While organoids clustered closely at earlier time points (up to 24 h), they strongly diverged at later time points, suggesting increasing inter-individual changes of their morphological characteristics over time.

Organoids are key models for studying development & disease, but heterogeneity is a problem. @wittbrodtlab.bsky.social use #DeepLearning to predict differentiation paths & resulting tissues in #retinal organoids, with implications for other #organoid systems @plosborn.bsky.social 🧪 plos.io/45VTMt1

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You Really Need To Step Up Your Game If You Want To Achieve Younger Looking Skin | Geek & Gorgeous 101 A-Game 5 0.05% Retinal Serum - Luke Sam Sowden I recently bought a Bottle of Geek & Gorgeous 101 A-Game 5 0.05% Retinal Serum, and I thought that I would tell you what I thought of it.

What I thought of the Geek & Gorgeous 0.05% Retinal Serum is up on the Blog today! https://shorturl.at/HMM7U #LukeSamSowden #GeekAndGorgeous #Retinal #RetinalSerum #AntiAgeing #Skincare #SkincareRoutine #VitaminA #YoungerLookingSkin #Wrinkles #FineLines #Retinol #Review

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Inamullah Inamullah from unisouthampton.bsky.social et al. explore the evolution of #retinal imaging techniques, the dire need for the integration of #AI-driven analysis, and the shift of retinal imaging from classical techniques to #oculomics 👁️ 🔎

🔗 📜 www.jprecisionmedicine.org/article/S305...

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Single-cell RNA-seq reveals cell type-specific molecular and genetic associations with primary open-angle glaucoma - Signal Transduction and Targeted Therapy Signal Transduction and Targeted Therapy - Single-cell RNA-seq reveals cell type-specific molecular and genetic associations with primary open-angle glaucoma

Researchers map #SystemicImmunity in #POAG via #SingleCellRNASeq of #PBMCs, revealing increased CD4+ T cells, impaired cytolytic potential, and a dual proinflammatory/neuroprotective landscape, linking immune dysregulation to #retinal health.

#OpenAccess #STTT: doi.org/10.1038/s413...

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Added #Retinal "Democracy Manifest" (October 12, 2025) to the database.

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Wie finden #Zugvögel ihr Ziel, auch bei Dunkelheit oder Nebel? Können sie über #Quanten​effekte in sog. #Retinal​-Molekülen im Auge das Erdmagnetfeld zur Orientierung nutzen?👀

Wir sind sehr gespannt auf die Erkenntnisse aus diesem Projekt @uni-hamburg.de, das wir in NEXT – #QuantumBiology fördern.🤞

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#Shopee เปิดตัวสินค้าใหม่ #ISDIN เป็นสินค้า #Trendy Exclusive ใช้โค้ดลดได้ 30% 🧡
👉 ISDIN ISDINCEUTICS #RETINAL EYES ✨ ใช้โค้ด Trendy ลดแล้วเหลือ 2,399 บาทค่ะ
❣️
s.shopee.co.th/AUlyrwreV7

#ShopeeTH #ShopeeTrendy #เรตินอล #รอบดวงตา

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In this study, Thomas E. Zapadka et al. observed that #optic nerve injury impairs intrinsic mechanisms underlying electrical activity in a resilient #retinal ganglion cell 👁️ 🔬

📜 Read the #Research: physoc.onlinelibrary.wiley.com/doi/10.1113/...

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Frontiers | Research Advances on Artificial Intelligence Assisted Diagnosis and Risk Assessment in Cardiovascular Disease using retinal Imaging Objective: Cardiovascular disease (CVD) is the leading cause of death worldwide, and early prediction and prevention are essential to reduce its incidence. I...

🫀 Frontiers | Research Advances on #ArtificialIntelligence Assisted #Diagnosis and Risk Assessment in #Cardiovascular #Disease using #retinal Imaging

www.frontiersin.org/journals/car...

#MedSky #AImedicine #AI #HealthAI #AIinHealthcare #MedTech

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Chip implant restores some vision lost to retinal disease - UW Medicine | Newsroom

Eye surgeon Lisa Olmos de Koo @uwmedicine.bsky.social discusses how an implanted wireless microchip helped to restore some vision for people with an incurable #retinal disease.

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Life-changing eye implant helps blind patients read again The results are astounding and a major advance, say surgeons involved in international research using the pioneering technology.

This is what innovation and research is all about, improving patient lives #bionic #retinal #implant #AMD: www.bbc.co.uk/news/article...
🧪💊

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Kinō Shitai (SCH) and a praying mantis...beta Ceapă!?

Kinō Shitai (SCH) and a praying mantis...beta Ceapă!?

Vasily papercraft concept art from some time ago (literally my first ever fanart of him)
He looks a bit like a toy soldier

Vasily papercraft concept art from some time ago (literally my first ever fanart of him) He looks a bit like a toy soldier

Revisited an old sketch. Dai Jinsei, Retinal, The Wolfram System, TWS

Revisited an old sketch. Dai Jinsei, Retinal, The Wolfram System, TWS

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I made drawings for days 7-9 of goretober but Day 6 is still a WIP teehee.. SOHO and Shinji Hibiki are going through it
Might end up spamming again
#nmnsocks #TheWolframSystem #Retinal #DaiJinsei #yaoihand

Here are some things in the meantime

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Subclinical Coronary Atherosclerosis and Retinal Optical Coherence Tomography Angiography This cross-sectional cohort study demonstrates the association of reduced retinal vascular density and subclinical coronary atherosclerosis in asymptomatic individuals.

Densidad vascular parafoveal retiniana reducida se asocia con la aterosclerosis coronaria subclínica en una población con riesgo vascular elevado y ayuda a identificar individuos que podrían beneficiarse de una evaluación coronaria #coronary #atherosclerosis #retinal jamanetwork.com/journals/jam...

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This study links the cyclic guanosine monophosphate-adenosine monophosphate synthase & stimulator of #Interferon genes pathway to #Retinal #Inflammation, offering new treatment strategies for #Uveitis. @fudan-university.bsky.social #medsky
#OpenAccess:
www.sciencedirect.com/science/arti...

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Added #Retinal "Heavy Bells" (August 15, 2025) to the database.

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In case you missed it! The latest issue of Ophthalmology Management looked at optogenetics, rapid developments in geographic atrophy, remote surveillance of retinal disease, and much more! ow.ly/FzJK50Wk0WL
#retina #retinal #ophthalmology

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Boehringer Ingelheim and Palatin Technologies to develop potential first-in-class melanocortin receptor targeted treatment for patients with retinal diseases Boehringer and Palatin Technologies team up to develop potential first-in-class melanocortin receptor targeted treatment for patients with retinal...

Boehringer Ingelheim and Palatin Technologies to develop potential first-in-class #melanocortin receptor targeted treatment for patients with #retinal diseases

Total deal up to €280 million

www.globenewswire.com/news-release...

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#Medsky🧪 #IDSky #ophthalmology #Retinal involvement & anomalies have been reported due to #COVID. COVID can lead to #retinopathy, which can impair vision. Generalised #hypoxia resulting from #pulmonaryfibrosis in #COVID patients may also cause visual disturbances.

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Prof Peter van Wijngaarden, Head of The Florey, gave a great seminar at FHMRI last week on #retinal imaging for detecting #Alzheimers and other neuropathologies - fascinating, beautiful work @flindersuniversity.bsky.social 🤩 👏 👁️ #PhDsiblings #labfam #astrophysics

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Flip through the pages of this month’s digital edition of Ophthalmology Management: digital.ophthalmologymanagement.com/publication/...

#retina #retinal #retinaldisease #homemonitoring #RemotePatientMonitoring #optogenetics #geographicatrophy #privateequity #ophthalmology #youngophthalmologists

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