Peptide Glycodendrimers as Potential Vaccines for Olive Pollen Allergy.

Olive pollen is one of the most important causes of respiratory allergy, with Ole e 1 being the most clinically relevant sensitizing allergen. Peptide-based vaccines represent promising therapeutic approaches, but the use of adjuvants is required to strengthen the weak immunogenicity of small peptides. We propose the use of dendrimeric scaffolds conjugated to the T cell immunodominant epitope of Ole e 1 (OE109-130) for the development of novel vaccines against olive pollen allergy. Four dendrimeric scaffolds containing an ester/ether with nine mannoses, an ester succinimidyl linker with nine N-acetyl-glucosamine units or nine ethylene glycol units conjugated to OE109-130 peptide were designed, and their cytotoxicity, internalization pattern, and immunomodulatory properties were analyzed in vitro. None of the dendrimers exhibited cytotoxicity in humanized rat basophil (RBL-2H3), human bronchial epithelial Calu-3, and human mast LAD2 cell lines. Confocal images indicated that mannosylated glycodendropeptides exhibited lower colocalization with a lysosomal marker. Moreover, mannosylated glycodendropeptides showed higher transport tendency through the epithelial barrier formed by Calu-3 cells cultured at the air-liquid interface. Finally, mannosylated glycodendropeptides promoted Treg and IL10+Treg proliferation and IL-10 secretion by peripheral blood mononuclear cells from allergic patients. Mannosylated dendrimers conjugated with OE109-130 peptide from Ole e 1 have been identified as suitable candidates for the development of novel vaccines of olive pollen allergy.

A Mobile Solution for Rhythmic Auditory Stimulation Gait Training.

Recent studies showed that Parkinson's disease (PD) patients improved their gait parameters while walking with rhythmic auditory stimulation (RAS). They achieved a longer stride length, a reduced stride time variability and a higher walking speed. Combining RAS with mobile gait analysis would allow continuous monitoring of RAS effects and gait in natural environments. This paper proposes a mobile solution for home-based assessment of RAS by combining RAS gait training and a mobile system for data acquisition. Existing datasets were used to investigate the cadence of PD patients and to propose suitable frequencies for RAS gait training. The cadence calculation was implemented using a peak detection algorithm, which uses the time difference between two mid-swing events as stride time values. We validated our system as a whole using a cohort of 13 PD patients who performed RAS gait training. The algorithms were also validated against the eGaIT system, a state-of-the-art system, and achieved a mean F1 score for detected strides of 97.57 % ± 0.86 % and a mean absolute error for the cadence of 0.16 spm ± 0.09 spm. This study lays the ground work for further clinical studies investigating the effectiveness of mobile RAS within a home environment.