Pulmonary Manifestations of Inflammatory Bowel Disease and Treatment Strategies

Ghosh, Subha; Deshwal, Himanshu; Haraf, Rebecca; Raju, Shine; Saeedan, Mnahi Bin; Sarkar, Pralay; Gildea, Thomas; Farver, Carol F.; Mehta, Atul C.

doi:10.1016/j.chpulm.2023.100018

Cited by 4 publications

(1 citation statement)

References 76 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lastly, PPARG is found to regulate mucin and inflammatory factors in bronchial epithelial cells [137]. Given the pulmonary complications of IBD, PPARG could be a promising target to investigate for treating IBD and pulmonary symptoms [138]. The predictive power of cell type contexts to examine ITGA4 and PPARG, according to PINNACLE, for IBD therapeutic development are thus well-supported.…”

Section: Pinnacle Can Nominate Therapeutic Targets Across Cell Type C...mentioning

confidence: 99%

Contextual AI models for single-cell protein biology

Huang

Sumathipala

et al. 2023

Preprint

View full text Add to dashboard Cite

Understanding protein function and discovering molecular therapies require deciphering the cell types in which proteins act as well as the interactions between proteins. However, modeling protein interactions across diverse biological contexts, such as tissues and cell types, remains a significant challenge for existing algorithms. We introduce PINNACLE, a flexible geometric deep learning approach that is trained on contextualized protein interaction networks to generate context-aware protein representations. Leveraging a human multi-organ single-cell transcriptomic atlas, PINNACLE provides 394,760 protein representations split across 156 cell type contexts from 24 tissues and organs. PINNACLE's contextualized representations of proteins reflect cellular and tissue organization and PINNACLE's tissue representations enable zero-shot retrieval of the tissue hierarchy. Pretrained PINNACLE protein representations can be adapted for downstream tasks: to enhance 3D structure-based protein representations (PD-1/PD-L1 and B7-1/CTLA-4) at cellular resolution and to study the genomic effects of drugs across cellular contexts. PINNACLE outperforms state-of-the-art, yet context-free, models in nominating therapeutic targets for rheumatoid arthritis and inflammatory bowel diseases, and can pinpoint cell type contexts that are more predictive of therapeutic targets than context-free models (29 out of 156 cell types in rheumatoid arthritis; 13 out of 152 cell types in inflammatory bowel diseases). PINNACLE is a network-based contextual AI model that dynamically adjusts its outputs based on biological contexts in which it operates.

show abstract

Section: Pinnacle Can Nominate Therapeutic Targets Across Cell Type C...mentioning

confidence: 99%

Contextual AI models for single-cell protein biology

Huang

Sumathipala

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

Contextual AI models for single-cell protein biology

Li,

Huang,

Sumathipala

et al. 2024

Nat Methods

View full text Add to dashboard Cite

Understanding protein function and developing molecular therapies require deciphering the cell types in which proteins act as well as the interactions between proteins. However, modeling protein interactions across biological contexts remains challenging for existing algorithms. Here we introduce PINNACLE, a geometric deep learning approach that generates context-aware protein representations. Leveraging a multiorgan single-cell atlas, PINNACLE learns on contextualized protein interaction networks to produce 394,760 protein representations from 156 cell type contexts across 24 tissues. PINNACLE’s embedding space reflects cellular and tissue organization, enabling zero-shot retrieval of the tissue hierarchy. Pretrained protein representations can be adapted for downstream tasks: enhancing 3D structure-based representations for resolving immuno-oncological protein interactions, and investigating drugs’ effects across cell types. PINNACLE outperforms state-of-the-art models in nominating therapeutic targets for rheumatoid arthritis and inflammatory bowel diseases and pinpoints cell type contexts with higher predictive capability than context-free models. PINNACLE’s ability to adjust its outputs on the basis of the context in which it operates paves the way for large-scale context-specific predictions in biology.

show abstract

Pulmonary Manifestations of IBD: Case Report and Review of the Literature

Herling,

Perluk,

Freund

et al. 2024

JCM

View full text Add to dashboard Cite

This article explores the pulmonary complications associated with inflammatory bowel disease (IBD). It presents a detailed case study of a 22-year-old male with Crohn’s disease exhibiting pulmonary symptoms. The review delves into the spectrum of pulmonary involvement in IBD, covering clinical presentations, diagnostic challenges, underlying pathophysiology, and management strategies. It highlights the significance of these extraintestinal manifestations on patient outcomes and quality of life. The article underscores the need for heightened clinical awareness and a systematic approach to diagnosis and management, integrating the expertise of multiple specialists. The review identifies gaps in current research, suggesting avenues for future investigation to enhance the understanding and treatment of these complex manifestations.

show abstract

Pulmonary Manifestations of Inflammatory Bowel Disease and Treatment Strategies

Cited by 4 publications

References 76 publications

Contextual AI models for single-cell protein biology

Contextual AI models for single-cell protein biology

Contextual AI models for single-cell protein biology

Pulmonary Manifestations of IBD: Case Report and Review of the Literature

Contact Info

Product

Resources

About