A carvacrol-based product reduces Campylobacter jejuni load and alters microbiota composition in the caeca of chickens.

Aim: This study was conducted to test the ability of a carvacrol-based formulation (Phodé, France) to decrease the C. jejuni caecal load in inoculated broiler chickens and to study the impact of the C. jejuni inoculation alone or combined with the product, on the caecal microbiota.

Pharmacokinetic and antimicrobial activity of a new carvacrol-based product against a human pathogen, Campylobacter jejuni.

Aim: In vitro and in vivo studies were conducted to test a new carvacrol-based product designed to delay the carvacrol release so that it could reach the caeca of broiler chickens in order to control Campylobacter jejuni.

Methods And Results: Antimicrobial activity of carvacrol, a constituent of oregano and thyme essential oil, has been demonstrated against C. jejuni in vitro, and this compound was found beneficial for broiler growth.

Monoterpenoid-based preparations in beehives affect learning, memory, and gene expression in the bee brain.

Bees are exposed in their environment to contaminants that can weaken the colony and contribute to bee declines. Monoterpenoid-based preparations can be introduced into hives to control the parasitic mite Varroa destructor. The long-term effects of monoterpenoids are poorly investigated.

Regions of interest-based discriminant analysis of DaTSCAN SPECT and FDG-PET for the classification of dementia.

Purpose: Neuroimaging is increasingly used to support the clinical diagnosis of patients with cognitive impairment. Dopamine transporter (DAT) imaging, such as DaTSCAN SPECT, tests the integrity of the nigrostriatal pathway, whereas FDG-PET identifies typical patterns of cortical and subcortical hypometabolism. The aim of this study was to assess the relative contribution of DAT and regional glucose metabolism imaging to the differential diagnosis.

Anatomically guided voxel-based partial volume effect correction in brain PET: impact of MRI segmentation.

Partial volume effect is still considered one of the main limitations in brain PET imaging given the limited spatial resolution of current generation PET scanners. The accuracy of anatomically guided partial volume effect correction (PVC) algorithms in brain PET is largely dependent on the performance of MRI segmentation algorithms partitioning the brain into its main classes, namely gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). A comparative evaluation of four brain MRI segmentation algorithms bundled in the successive releases of Statistical Parametric Mapping (SPM) package (SPM99, SPM2, SPM5, SPM8) using clinical neurological examinations was performed.