Dataset Information

Molecular imaging-assisted optimization of hsp70 expression during laser-induced thermal preconditioning for wound repair enhancement.

ABSTRACT: Patients at risk for impaired healing may benefit from prophylactic measures aimed at improving wound repair. Several photonic devices claim to enhance repair by thermal and photochemical mechanisms. We hypothesized that laser-induced thermal preconditioning would enhance surgical wound healing that was correlated with hsp70 expression. Using a pulsed diode laser (lambda=1.85 microm, tau(p)=2 ms, 50 Hz, H=7.64 mJ cm(-2)), the skin of transgenic mice that contain an hsp70 promoter-driven luciferase was preconditioned 12 hours before surgical incisions were made. Laser protocols were optimized in vitro and in vivo using temperature, blood flow, and hsp70-mediated bioluminescence measurements as benchmarks. Biomechanical properties and histological parameters of wound healing were evaluated for up to 14 days. Bioluminescent imaging studies indicated that an optimized laser protocol increased hsp70 expression by 10-fold. Under these conditions, laser-preconditioned incisions were two times stronger than control wounds. Our data suggest that this molecular imaging approach provides a quantitative method for optimization of tissue preconditioning and that mild laser-induced heat shock may be a useful therapeutic intervention prior to surgery.

SUBMITTER: Wilmink GJ

PROVIDER: S-EPMC3846389 | biostudies-literature | 2009 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Molecular imaging-assisted optimization of hsp70 expression during laser-induced thermal preconditioning for wound repair enhancement.

Wilmink Gerald J GJ Opalenik Susan R SR Beckham Joshua T JT Abraham Alexander A AA Nanney Lillian B LB Mahadevan-Jansen Anita A Davidson Jeffrey M JM Jansen E Duco ED

The Journal of investigative dermatology 20080626 1

Patients at risk for impaired healing may benefit from prophylactic measures aimed at improving wound repair. Several photonic devices claim to enhance repair by thermal and photochemical mechanisms. We hypothesized that laser-induced thermal preconditioning would enhance surgical wound healing that was correlated with hsp70 expression. Using a pulsed diode laser (lambda=1.85 microm, tau(p)=2 ms, 50 Hz, H=7.64 mJ cm(-2)), the skin of transgenic mice that contain an hsp70 promoter-driven lucifera ...[more]

PMID: 18580963

Similar Datasets

Project description:Laser interstitial thermal therapy (LITT) is an alternative to open surgery for drug-resistant focal mesial temporal lobe epilepsy (MTLE). Studies suggest maximal ablation of the mesial hippocampal head and amygdalohippocampal complex (AHC) improves seizure freedom rates while better neuropsychological outcomes are associated with sparing of the parahippocampal gyrus (PHG). Optimal trajectories avoid sulci and CSF cavities and maximize distance from vasculature. Computer-assisted planning (CAP) improves these metrics, but the combination of entry and target zones has yet to be determined to maximize ablation of the AHC while sparing the PHG. We apply a machine learning approach to predict entry and target parameters and utilize these for CAP. Ten patients with hippocampal sclerosis were identified from a prospectively managed database. CAP LITT trajectories were generated using entry regions that include the inferior occipital, middle occipital, inferior temporal, and middle temporal gyri. Target points were varied by sequential AHC erosions and transformations of the centroid of the amygdala. A total of 7600 trajectories were generated, and ablation volumes of the AHC and PHG were calculated. Two machine learning approaches (random forest and linear regression) were investigated to predict composite ablation scores and determine entry and target point combinations that maximize ablation of the AHC while sparing the PHG. Random forest and linear regression predictions had a high correlation with the calculated values in the test set (ρ = 0.7) for both methods. Maximal composite ablation scores were associated with entry points around the junction of the inferior occipital, middle occipital, and middle temporal gyri. The optimal target point was the anteromesial amygdala. These parameters were then used with CAP to generate clinically feasible trajectories that optimize safety metrics. Machine learning techniques accurately predict composite ablation score. Prospective studies are required to determine if this improves seizure-free outcome while reducing neuropsychological morbidity following LITT for MTLE.

Dataset Information

Molecular imaging-assisted optimization of hsp70 expression during laser-induced thermal preconditioning for wound repair enhancement.

Publications

Molecular imaging-assisted optimization of hsp70 expression during laser-induced thermal preconditioning for wound repair enhancement.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets