1-es típusú cukorbetegség: ki dolgozik rajta

Intézményenként egy kártya. Válassz célpontot, és csak az azon dolgozó csoportok maradnak.

• Minden célpont
• GLP-1 21
• SGLT2 12
• NRF2 0
• CTLA-4 0
• STAT3 0
• AKT 0
• GIP 2
• PD-1 0
• SIRT1 0
• CD40 0
• PPAR 0
• TP53 0
• JAK 1
• JNK 0
• mTOR 0
• NLRP3 1
• TLR4 0
• AMPK 0
• DPP-4 0
• IL-6 0
• TNF 0
• IL-1 0
• IL-17 0
• MAPK 0
• PI3K 0
• VEGF 1
• CD47 0
• HMGB1 0
• PD-L1 0
• ACE2 0
• BDNF 0
• CD19 0
• CD20 1
• CD38 0
• ERK 0
• FOXP3 0
• G6PD 0
• IL-13 0
• IL-4 0
• PCSK9 0
• RANKL 0
• STING 0
• TIGIT 0
• AR 0
• B7-H3 0
• CD22 0
• CTNNB1 0
• CXCR4 0
• EGFR 0
• GPX4 0
• HDAC 0
• HER2 0
• HER3 0
• HSP90 0
• IGF1R 0
• LAG-3 0
• METTL3 0
• MYC 0
• NMDA 0
• PDGFR 0

Funded research projects that name this disease in their title, terms or summary and have not ended yet: who is funded, where, how much and until when. Organisations only; the funder's page has the details.

• European Commission (Horizon Europe) · HORIZON-ERC

  Modeling islet inflammation in early-stage type 1 diabetes: T1DstartEd (T1Dstarted)

  The Hebrew University of Jerusalem· Jerusalem, Izrael· EU contribution 2 796 250 EUR· until 2032. máj.

• European Commission (Horizon Europe) · HORIZON-EIC-ACC

  The Inreda bi-hormonal blood glucose control pump: A beacon for high-risk diabetes patients, providing fully automated in disease management (DIABEACON)

  Inreda Diabetic Bv· Goor, Hollandia· EU contribution 2 499 414 EUR· until 2028. jún.

• European Commission (Horizon Europe) · HORIZON-TMA-MSCA-PF-GF

  Type 1 Diabetes Simulator with Adjunctive therapies - GLP1 (T1SIA)

  Universitat Politecnica de Valencia· Valencia, Spanyolország· EU contribution 243 097 EUR· until 2028. jan.· 2 countries

• European Commission (Horizon Europe) · HORIZON-ERC

  From harassing to harnessing beta-cells in type 1 diabetes (Beta-STEALTH)

  Academisch Ziekenhuis Leiden· Leiden, Hollandia· EU contribution 2 500 000 EUR· until 2030. okt.

• European Commission (Horizon Europe) · HORIZON-TMA-MSCA-PF-EF

  Uncovering Protective Mechanisms in Pancreatic β-Cells to Enhance Their Survival in Type 1 Diabetes (Beta_cell_protection)

  Universite Libre de Bruxelles· Bruxelles, Belgium· EU contribution 200 400 EUR· until 2027. júl.

5 of 9 running projects, newest first. Listed amounts together: 48,3 M EUR.

Sources: NIH RePORTER (U.S. National Institutes of Health, public domain) and CORDIS (European Commission, CC BY 4.0). Changes: filtered by disease, organisations matched to ROR.

Vizsgálatok, amelyek regiszteradata szerint az egyéni résztvevői adatokat (IPD) megosztják.

Ebben a nézetben egy vizsgálat sem jelzi, hogy megosztaná a résztvevői adatokat.

Publikációk erről a betegségről egy MeSH-módszerkifejezés szerint, például szekvenálási vagy képalkotó módszerre.

• Single-Cell Analysis 10
• Organoids 4
• Mendelian Randomization Analysis 35
• CRISPR-Cas Systems 5
• Gene Expression Profiling 34
• Sequence Analysis, RNA 3
• Whole Genome Sequencing 1
• Exome Sequencing 3
• Proteomics 20
• Metabolomics 15
• Mass Spectrometry 4
• Flow Cytometry 12
• Immunohistochemistry 16
• Positron-Emission Tomography 3
• Magnetic Resonance Imaging 33
• Machine Learning 31
• Deep Learning 10
• Cohort Studies 158
• Genome-Wide Association Study 54

• Overcoming Cross-Sensitivity for the Accurate Identification of Acetone, Isopropanol, and Clinical Mixtures Using a MEMS Dual-Sensor Array and Multi-task Deep Learning.

  ACS Sens, 2026. okt.

• Accelerated Brain Aging in Type 1 Diabetes Across Painful and Painless Peripheral Neuropathy: MRI-Based Brain Age Estimates From Deep Learning.

  Diabetes, 2026. okt.

• GAT-BiGRU: explainable multi-task temporal graph learning for glucose forecasting, hypoglycemia risk, and counterfactual insulin adjustment.

  J Am Med Inform Assoc, 2026. szept.

• Data Augmentation via Digital Twins to Develop Personalized Deep Learning Glucose Prediction Algorithms for Type 1 Diabetes in Poor Data Context.

  IEEE Trans Biomed Eng, 2026. júl.

• Deep learning analysis of ECGs detects Cardiovascular-Kidney-Metabolic syndrome burden in people with diabetes: a report from the Silesia Diabetes-Heart Project.

  Cardiovasc Diabetol, 2026. jún.

• Diabetes Management Through Glucose Dynamics Analysis Network: A Novel Approach for Accurate Blood Glucose Level Forecasting.

  Diabetes Obes Metab, 2026. jún.

• Deep learning-powered quantification of endocrine cells and CD3+ T cells in the natural history of type 1 diabetes.

  Diabetologia, 2026. máj.

• Systematic Review on Deep Learning Algorithms for Blood Glucose Forecasting in Type 1 Diabetes.

  IEEE J Biomed Health Inform, 2026. máj.

• PathViT Model for Automated Disease Classification from Skeletal Muscle Histopathology.

  Am J Pathol, 2025. nov.

• Evaluating the Effect of Input Features on Deep Learning Models for Blood Glucose Forecasting.

  Annu Int Conf IEEE Eng Med Biol Soc, 2025. júl.

Megmutatjuk, a betegség mely célpontjait említi az absztrakt, és onnan a rajtuk dolgozókhoz jutsz.