VR.Krishnakumar

148 posts

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VR.Krishnakumar

VR.Krishnakumar

@KKNephBytes

MD, DNB,DM, DrNB Nephrology,Glomcon-KPCP 2024,Fellowship in Glomerular Disease -Glomcon 2025 ,Fellow Renal Transplant & immunology, IJN Visual Abstract Creator,

Katılım Mart 2018
339 Takip Edilen702 Takipçiler
Dr Priti MD,FASN🇮🇳 (प्रिति)
🌸Winning Best Research Abstract at World Congress of Nephrology — a moment I’ll truly cherish ✨🏆 Deeply grateful to International Society of Nephrology and my amazing team for being part of this journey 🙌💙
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Arvind Canchi (Conjeevaram)🇮🇳
Paired Kidney Donation Guidelines okayed by the Karnataka Government. This is great news.
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Sayed S Rahman
Sayed S Rahman@SayedSRahman1·
Membranous Nephropathy 🔬Anti-PLA2R = used for Diagnosis , Prognosis, Monitoring 📊 Risk stratify: Based on Proteinuria + eGFR + AntiPLA2R 🟢 Low risk→ Supportive 🟡 Mod→ Observe ± RTX 🔴 High→ Rituximab / Cyclophosphamide+Steroid 👍for Antigens: VA @KKNephBytes 💯 #KDIGO
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VR.Krishnakumar
VR.Krishnakumar@KKNephBytes·
*When Positivity Misleads: Recognizing False Signals in SAB Testing* *********************** ⚡SAB positivity can represent artefact rather than true immunologic risk ⚡High MFI alone is unreliable without pattern and clinical context ⚡A broad, tapering (“long-tail”) pattern suggests non-specific reactivity ⚡Lack of sensitization history should prompt cautious interpretation ⚡FlowPRA and FCXM discordance helps identify non-clinical antibodies ⚡Absence of a shared epitope supports non-specific binding ⚡Misinterpretation can lead to false DSA assignment and inflated cPRA ⚡Result in unnecessary exclusion of compatible donors ⚡Always interpret SAB results in integration with clinical and laboratory correlation ⚡Pattern recognition is more reliable than numerical thresholds #KKNephBytes #Immunology @arvindcanchi @DrAkshayaJ @drshyambansal @hardik4u24 @isn_india @priti899 @suhalikapath @AnjanaGopal9 @raja_1980 @dr_sourabha @iamnephrologist
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VR.Krishnakumar
VR.Krishnakumar@KKNephBytes·
Hi! We are currently analyzing HLA-DQ antibodies, and our observations suggest a predominant role of the beta chain in driving immunogenicity. However, the alpha chain significantly modulates this response, and in some cases, we are seeing isolated alpha-chain–targeted epitopes contributing to DSA formation. These findings highlight the complexity of DQ heterodimer immunogenicity—both chains cannot be interpreted in isolation. Further population-based and eplet-level analyses are needed to better understand these patterns and their clinical relevance.
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Raffaele Di Giacomo, PhD
Fascinating insight into HLA-DQ antibodies! It's crucial to understand how they can impact graft outcomes and lead to sensitization. Have you come across any effective strategies to mitigate this risk? #TransplantImmunology #Medicine. For more in-depth information, Sci-Quest is a fantastic resource to explore these kinds of topics—check it out at sciqst.com.
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VR.Krishnakumar
VR.Krishnakumar@KKNephBytes·
*HLA-DQ Antibodies: The Silent Cracker That Starts the Blast* *************************** ⚡HLA-DQ antibodies are the most common de novo DSA ⚡HLA-DQ DSA have the worst graft outcomes (ABMR, TG, graft loss) ⚡DQ mismatch carries the highest risk of sensitization (↑cPRA) ⚡ HLA-DQ has dual polymorphism (α + β chains) ⚡Can form multiple heterodimers (cis + trans pairing) ⚡ More heterodimers → more epitopes → higher immunogenicity ⚡ HLA-DQ shows low expression but high pathogenicity ⚡ Expression is delayed but sustained → chronic rejection ⚡ DQ antibodies activate Akt / S6 / IL-6 pathways ⚡ Current matching underestimates DQ risk ⚡ Eplet/pairing-based analysis > antigen matching #KKNephBytes #Immunology @arvindcanchi @DrAkshayaJ @drshyambansal @hardik4u24 @isn_india @priti899 @suhalikapath @JJayameena
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