Skip to content
#protein folding Open access

Targeting GLP-1 signaling and barrier integrity with Leanskolin™, a standardized Coleus forskohlii extract: a Caco-2 cell-based study for metabolic health support

Sep 2026 · BMC Complementary Medicine and Therapies · 0 citations
Diabetes Treatment and Management Biochemical Analysis and Sensing Techniques

Abstract

Glucagon-like peptide-1 (GLP-1) is a key incretin hormone involved in glucose regulation and metabolic health. This study reports, for the first time, the GLP-1 enhancing potential of a standardized Coleus forskohlii extract (Leanskolin™, ≥ 10% forskolin) using differentiated Caco-2 cells. MTT assay was performed to assess the cytotoxicity of Leanskolin (25–500 µg/mL) in Caco-2 cells. Later, the cells were treated with non-cytotoxic concentrations (25, 50, and 100 µg/mL) for 24 h. Further, in vitro Dipeptidyl peptidase-4 (DPP-4) enzyme inhibition assay was performed. At 100 µg/mL, Leanskolin significantly upregulated Proglucagon (3.33-fold, p  < 0.001) and GLP-1R (3.32-fold, p  < 0.01) gene expression, indicating stimulation of endogenous GLP-1 signaling. The extract also markedly inhibited cellular DPP-4 activity and its gene expression ( p  < 0.05 vs. control). In vitro DPP-4 inhibition assay revealed an IC₅₀ of 262.5 µg/mL of Leanskolin, suggesting potential to prolong GLP-1 bioavailability. Furthermore, Leanskolin modulated bitter taste receptor genes ( TAS2R38 , TAS2R43 , TAS2R14 ) in a concentration-dependent manner ( p  < 0.05), implicating a role in nutrient sensing and enteroendocrine signaling. Leanskolin treatment (25–100 µg/mL, 24 h) did not alter TEER values but significantly reduced FITC-flux at 50 and 100 µg/mL ( p  < 0.01), indicating improved barrier integrity. Importantly, the extract enhanced the expression of tight junction (TJ) proteins ( p  < 0.05 vs. control). These findings highlight the multi-targeted potential of Leanskolin in promoting metabolic health via GLP-1 pathway activation, DPP-4 inhibition, and gut barrier support. This first report demonstrates integrated activity of this extract, offering promising insights into its therapeutic relevance for managing metabolic disorders.

Read PDF

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or sequence constraints.

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

Google DeepMind Blog Nov 25, 2025

AlphaFold: Five years of impact

Explore how AlphaFold has accelerated science and fueled a global wave of biological discovery.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.