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Kadlec, K.

Publications and source records attributed to Kadlec, K..

2 recordsLinked to original sources

Central Glucagon-Like Peptide-1 Agonism Ameliorates Colonic Inflammation in a Murine Model of Inflammatory Bowel Disease

Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have revolutionized the treatment of obesity and type 2 diabetes (T2D). These drugs also have anti-inflammatory effects that have recently been extended to the treatment of inflammatory bowel disease (IBD). Whether the mechanism underlying this benefit involves a direct action on the intestine or instead is mediated via GLP-1Rs in the brain, however, is unknown. Based on evidence implicating the brain as the target for the anti-obesity and anti-inflammatory effects of GLP-1RAs, we sought to determine if central GLP-1R signaling is sufficient to explain its intestinal anti-inflammatory effects. To this end, we compared the efficacy of peripheral vs central administration of the GLP-1RA, semaglutide (SEMA), in diet-induced obese (DIO) mice with dextran sodium sulfate (DSS)-induced colitis. We report that compared to vehicle, both colitis severity and histopathological injury following DSS administration are reduced by peripheral administration of SEMA. We also report that this benefit is largely recapitulated by intracerebroventricular administration of SEMA at a low dose that, when administered peripherally, is below that needed to affect food intake and body weight. We conclude that in a mouse model of colitis, activation of GLP-1Rs in the brain is sufficient to explain the intestinal anti-inflammatory effect conferred by GLP-1R agonism.

neuroscience↗

Towards individualized deep brain stimulation: A stereoencephalography-based workflow for unbiased neurostimulation target identification

ObjectivesDeep brain stimulation (DBS) is increasingly being used to treat a variety of neuropsychiatric conditions, many of which exhibit idiosyncratic symptom presentations and neural correlates across individuals. Thus, we have utilized inpatient stereoelectroencephalography (sEEG) to identify personalized therapeutic stimulation sites for chronic implantation of DBS. Informed by our experience, we have developed a statistics-driven framework for stimulation testing to identify therapeutic targets. Materials and MethodsFourteen participants (major depressive disorder = 6, chronic pain = 6, obsessive-compulsive disorder = 2) underwent inpatient testing using sEEG and symptom monitoring to identify personalized stimulation targets for subsequent DBS implantation. We present a structured approach to this sEEG testing, integrating a Stimulation Testing Decision Tree with power analysis and effect size considerations to inform adequately powered results to detect therapeutic stimulation sites with statistical rigor. ResultsEffect sizes (Hedges g) of stimulation-induced symptom score changes ranged from -1.5 to +2.39. The standard deviation of sham trial responses was a strong predictor of stimulation response variability, as confirmed by a leave-one-out cross-validated linear regression (R2 = 0.67, permutation p<0.001). Thus, early sham trial data could be used to estimate the variability of stimulation responses for power analysis calculations. We show that approximately 10 sham trials were needed to robustly estimate sham variability. Power analysis (using a paired-t test) showed that for effect sizes [&ge;] 1.1, roughly 10 trials should be used per stimulation site for sufficiently powered results. ConclusionsThe presented workflow is adaptable to multiple indications and is specifically designed to overcome key challenges experienced during stimulation site testing. Through incorporating sham trials, effect size calculations, and tolerability testing, the described approach can be used to identify personalized and clinically efficacious stimulation sites.

neuroscience↗