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the Gateway to Research in Oklahoma

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Gateway to Research in Oklahoma


Oklahoma Shared Clinical and Translational Resources U54 GM104938

Researchers

imgResearchers

The GRO: Researcher Portal provides resources, information, and training to help individuals or communities involved in performing clinical and translational research in Oklahoma.

Providers

imgProviders

The GRO: Provider Portal assists medical providers to identify clinical research opportunities in Oklahoma, tools for patient education, and evidence-based resources to improve patient care.

Patients

imgPatients

The GRO: Patient Portal can help patients and families to learn more about clinical and translational research and to connect with opportunities to participate in research opportunities in your communities.

Oklahoma Research Highlights

Oral Trauma In Infants: An Indicator For Child Physical Abuse

2 months 2 weeks ago
No abstract
Darby Sparks

Enhancing diversity in endometriosis clinical trials: Application of the clinical diversity scoring framework

2 months 2 weeks ago
No abstract
Klaire Irwin

A Phase 2, multicenter, double-blind, randomized, placebo-controlled study of the safety and efficacy of forvisirvat (SP-624) in the treatment of adults with major depressive disorder

2 months 2 weeks ago
CONCLUSIONS: The novel epigenetic mechanism of action of forvisirvat, favorable safety profile, and consistent post-hoc efficacy results in women observed in this study support further development of forvisirvat. A phase 2b/3 trial of forvisirvat in major depressive disorder (NCT06254612), to confirm these results, is ongoing.
Joel Raskin

Lateral Decubitus Anterior Lumbar Interbody Fusion at the L4-5 Level is a Safe Alternative to Lateral Lumbar Interbody Fusion in 1-2 Level Lateral Decubitus Single Position Surgery

2 months 2 weeks ago
CONCLUSION: L-ALIF at L4-5 is a safe alternative to LLIF in L-SPS. Additionally, L4-5 L-ALIF enables more accurate restoration of L4-S1 lordosis and effectively improves L4-5 segmental lordosis.
Nam V Huynh

Multilayer GNN for predictive maintenance and clustering in power grids

2 months 2 weeks ago
Unplanned power outages create major economic costs. To better predict and manage these events, we present a multilayer graph neural network (GNN) framework that captures spatial, short-term co-occurrence, and statistically enriched co-failure patterns using 7 years of Oklahoma Gas & Electric data from 347 substations. These relations are encoded with weighted graph convolutions and fused by attention into a unified representation. For predictive maintenance, the model flags substations...
Muhammad Kazim

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