Dendris (France)

Please confirm that an ethics committee approval has been applied for or granted: Yes: I’m uploading the Ethics Committee Approval as a PDF file with this abstract submissionBackground and AimsTherapeutic virtual reality (VR) can alleviate pain and anxiety (Colloca 2020, Terzulli 2022, Terzulli 2023). This study aimed to assess VR hypnosis (VRH) on pain and anxiety during heat stimulation in healthy volunteers.MethodsFrench ethic committee approved the study on 04/02/2020. After written consent obtention, heat nociceptive stimulations (45°C/25s, 46°C/20s and 47°C/10s) were applied to the wrist of 22 healthy volunteers with a contact probe (QST.Lab, Strasbourg, France). The control period (without VRH, CTRL) was compared with the VRH period (HypnoVR Biofeedback®, VRH). Data on demographics, anxiety (STAI-trait/80), suggestibility (Stanford/12), pain intensity (Visual analog scale VASi/10), unpleasantness (VASu/10), and state anxiety (STAI-State/80) before CTRL (State 1), between CTRL and VRH (State 2) and after VRH (State 3), were collected.ResultsSignificant reductions were observed in VASi (4.7 ± 2.3 vs. 3.8/10 ± 2.5, p=0.002), VASu (5.3 ± 1.9 vs. 3.7/10 ± 2.5; p < 0.001), and anxiety State 3 vs. State 2 (26.6/80 ± 9.9 vs. 31.7 ± 10.9; p < 0.001), whereas not between State 1 and 2 (p>.05). Responders to VRH (i.e., decreased pain intensity > 10%, non-responders as those with no change (-10 to +10%), and inverse responders as those with an increase > 10%. For intensity, proportions were 59%, 32%, and 9%, respectively. For unpleasantness, proportions were 77%, 14%, and 9%, respectively. EP165 Table 1 EP165 Figure 1ConclusionsHypnoVR Biofeedback® reduced pain intensity, unpleasantness, and anxiety during heat stimuli. However, 9% of volunteers responded negatively, it is comparable with our previous study2. Further studies on patients are needed to correctly characterize these patients.

Clinical microbiology is experiencing the emergence of the syndromic approach of diagnosis. This paradigm shift will require innovative technologies to detect rapidly, and in a single sample, multiple pathogens associated with an infectious disease. Here, we report on a multiplex technology based on DNA-microarray that allows detecting and discriminating 11 bacteria implicated in respiratory tract infection. The process requires a PCR amplification of bacterial 16S rDNA, a 30 min hybridization step on species-specific oligoprobes covalently linked on dendrimers coated glass slides (DendriChips®) and a reading of the slides by a dedicated laser scanner. A diagnostic result is delivered in about 4 h as a predictive value of presence/absence of pathogens using a decision algorithm based on machine-learning method, which was constructed from hybridization profiles of known bacterial and clinical isolated samples and which can be regularly enriched with hybridization profiles from clinical samples. We demonstrated that our technology converged in more than 95% of cases with the microbiological culture for bacteria detection and identification.