Comprehensive machine learning models for predicting therapeutic targets in type 2 diabetes utilizing molecular and biochemical features in rats DOI Creative Commons
Marwa Matboli,

Hiba S. Al-Amodi,

Abdelrahman Khaled

et al.

Frontiers in Endocrinology, Journal Year: 2024, Volume and Issue: 15

Published: May 24, 2024

Introduction With the increasing prevalence of type 2 diabetes mellitus (T2DM), there is an urgent need to discover effective therapeutic targets for this complex condition. Coding and non-coding RNAs, with traditional biochemical parameters, have shown promise as viable therapy. Machine learning (ML) techniques emerged powerful tools predicting drug responses. Method In study, we developed ML-based model identify most influential features response in treatment using three medicinal plant-based drugs (Rosavin, Caffeic acid, Isorhamnetin), a probiotics (Z-biotic), at different doses. A hundred rats were randomly assigned ten groups, including normal group, streptozotocin-induced diabetic eight treated groups. Serum samples collected analysis, while liver tissues (L) adipose (A) underwent histopathological examination molecular biomarker extraction quantitative PCR. Utilizing five machine algorithms, integrated 32 12 select predictive each combined model. Results discussion Our results indicated that high doses selected effectively mitigated inflammation, reduced insulin resistance, improved lipid profiles renal function biomarkers. The identified 13 features, 10 20 accuracy 80% AUC (0.894, 0.93, 0.896), respectively. This study presents ML accurately identifies implicated pathways associated T2DM pathogenesis.

Language: Английский

Z‐Nucleic Acid Sensing and Activation of ZBP1 in Cellular Physiology and Disease Pathogenesis DOI Open Access

Sanchita Mishra,

Ayushi Amin Dey,

Sannula Kesavardhana

et al.

Immunological Reviews, Journal Year: 2025, Volume and Issue: 329(1)

Published: Jan. 1, 2025

ABSTRACT Z‐nucleic acid binding protein 1 (ZBP1) is an innate immune sensor recognizing nucleic acids in Z‐conformation. Upon sensing, ZBP1 triggers activation, inflammation, and programmed cell death during viral infections, mice development, inflammation‐associated diseases. The Zα domains of sense promote RIP‐homotypic interaction motif (RHIM)‐dependent signaling complex assembly to mount inflammation. studies on spurred understanding the role Z‐form RNA DNA cellular physiological functions. In particular, short genomic segments, endogenous retroviral elements, 3′UTR regions are likely sources Z‐RNAs that orchestrate Recent seminal identify intriguing association with adenosine deaminase acting RNA‐1 (ADAR1), cyclic GMP‐AMP synthase (cGAS) regulating aberrant chronic cancer. Thus, attractive target aid development specific therapeutic regimes for disease biology. Here, we discuss Z‐RNA activation death, Also, how coordinates intracellular perturbations homeostasis, formation regulate diseases

Language: Английский

Citations

2
Pyroptosis in sepsis-associated acute kidney injury: mechanisms and therapeutic perspectives DOI Creative Commons
Wenyu Wu,

Wanning Lan,

Xin Jiao

et al.

Critical Care, Journal Year: 2025, Volume and Issue: 29(1)

Published: April 23, 2025

Language: Английский

Citations

0
Suppression of ZBP1-mediated NLRP3 inflammasome by the tegument protein VP22 facilitates pseudorabies virus infection DOI Creative Commons
Zicheng Ma, Depeng Liu,

Wandi Cao

et al.

mBio, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 30, 2024

ABSTRACT The interaction between Z-DNA binding protein 1 (ZBP1) and the NLR family pyrin domain-containing 3 (NLRP3) inflammasome has been uncovered in several viral infections. However, role of this molecular pathway during infection with alpha-herpesvirus pseudorabies virus (PRV) remains largely elusive. Here, we report that PRV infection, ZBP1-mediated NLRP3 activation is inhibited by tegument VP22, thereby facilitating infection. Through a combination RNA sequencing genetic studies, demonstrate VP22 functions as virus-encoded virulence factor evading inhibitory effects ZBP1 on Importantly, replication pathogenicity recombinant lacking are significantly increased ZBP1-deficient cells mice. Mechanistically, interacts ZBP1, impeding recruitment receptor-interacting kinase Caspase-8, inhibiting activation. Furthermore, show N-terminal 1–50 amino acid domain dominantly destabilizes function. Taken together, these findings identify functional link inflammatory response, providing novel insights into pathogenesis other herpesviruses. IMPORTANCE pivotal innate immune sensor regulates cell death its unknown. serves restrictive triggering inflammasome, process counteracted PRV-encoded VP22. interferes 3/Caspase-8, particularly through acids. deficiency enhances viruses or These reveal how escapes responses potentially informing rational design therapeutic interventions.

Language: Английский

Citations

1
Comprehensive machine learning models for predicting therapeutic targets in type 2 diabetes utilizing molecular and biochemical features in rats DOI Creative Commons
Marwa Matboli,

Hiba S. Al-Amodi,

Abdelrahman Khaled

et al.

Frontiers in Endocrinology, Journal Year: 2024, Volume and Issue: 15

Published: May 24, 2024

Introduction With the increasing prevalence of type 2 diabetes mellitus (T2DM), there is an urgent need to discover effective therapeutic targets for this complex condition. Coding and non-coding RNAs, with traditional biochemical parameters, have shown promise as viable therapy. Machine learning (ML) techniques emerged powerful tools predicting drug responses. Method In study, we developed ML-based model identify most influential features response in treatment using three medicinal plant-based drugs (Rosavin, Caffeic acid, Isorhamnetin), a probiotics (Z-biotic), at different doses. A hundred rats were randomly assigned ten groups, including normal group, streptozotocin-induced diabetic eight treated groups. Serum samples collected analysis, while liver tissues (L) adipose (A) underwent histopathological examination molecular biomarker extraction quantitative PCR. Utilizing five machine algorithms, integrated 32 12 select predictive each combined model. Results discussion Our results indicated that high doses selected effectively mitigated inflammation, reduced insulin resistance, improved lipid profiles renal function biomarkers. The identified 13 features, 10 20 accuracy 80% AUC (0.894, 0.93, 0.896), respectively. This study presents ML accurately identifies implicated pathways associated T2DM pathogenesis.

Language: Английский

Citations

1