ABSTRACT
INTRODUCTION: PANS is a controversial clinical entity, consisting of a complex constellation of psychiatric symptoms, adventitious changes, and expression of various serological alterations, likely sustained by an autoimmune/inflammatory disease. Detection of novel biomarkers of PANS is highly desirable for both diagnostic and therapeutic management of affected patients. Analysis of metabolites has proven useful in detecting biomarkers for other neuroimmune-psychiatric diseases. Here, we utilize the metabolomics approach to determine whether it is possible to define a specific metabolic pattern in patients affected by PANS compared to healthy subjects. DESIGN: This observational case-control study tested consecutive patients referred for PANS between June 2019 to May 2020. A PANS diagnosis was confirmed according to the PANS working criteria (National Institute of Mental Health [NIMH], 2010). Healthy age and sex-matched subjects were recruited as controls. METHODS: Thirty-four outpatients referred for PANS (mean age 9.5 years; SD 2.9, 71% male) and 25 neurotypical subjects matched for age and gender, were subjected to metabolite analysis. Serum samples were obtained from each participant and were analyzed using Nuclear Magnetic Resonance (NMR) spectroscopy. Subsequently, multivariate and univariate statistical analyses and Receiver Operator Curves (ROC) were performed. RESULTS: Separation of the samples, in line with the presence of PANS diagnosis, was observed by applying a supervised model (R2X = 0.44, R2Y = 0.54, Q2 = 0.44, p-value < 0.0001). The significantly altered variables were 2-Hydroxybutyrate, glycine, glutamine, histidine, tryptophan. Pathway analysis indicated that phenylalanine, tyrosine, and tryptophan metabolism, as well as glutamine and glutamate metabolism, exhibited the largest deviations from neurotypical controls. CONCLUSION: We found a unique plasma metabolic profile in PANS patients, significantly differing from that of healthy children, that suggests the involvement of specific patterns of neurotransmission (tryptophan, glycine, histamine/histidine) as well as a more general state of neuroinflammation and oxidative stress (glutamine, 2-Hydroxybutyrate, and tryptophan-kynurenine pathway) in the disorder. This metabolomics study offers new insights into biological mechanisms underpinning the disorder and supports research of other potential biomarkers implicated in PANS.
ABSTRACT
A minimally invasive implant treatment approach for future full arch implant prosthetic rehabilitations of trophic jaws represents a challenge. An optimal implant planning is strongly related with an accurate merge of the prosthetic information and the radiographic data. To comply with that, most computer aided implantology (CAI) systems require additional steps, as radiographic stents or fiducial markers to overlap digital jaw scans to cone beam computed tomography (CBCT) data. Using dynamic CAI, residual teeth (up to three) make it possible for the merge to avoid new radiographic scans. An additional challenge is the treatment involving immediate implants compared with delayed implants placed into healed bone. As for other static CAI systems, the operator's experience and the quality of the CBCT data make the planning affordable and secure the entire implants placement procedure. The literature reports accuracies in terms of comparison between placed implants and planned implants, following a double CBCT approach, based on radiographic volume overlapping. Thirteen consecutive future totally edentulous patients (77 implants), divided into two groups (group A: 3-4 teeth traced; group B: 5-6 teeth traced) requiring a full arch implant prosthetic rehabilitation were included in the reported case series. A dynamic CAI was used to plan and to place all implants following all the recommended digital steps. The software used provided a tool (Trace and Place) that made the merge between X-ray views of the residual teeth and their own positions possible. This method definitely registered that teeth positions comply with the required accuracy live check. After implants placement, a post-operative CBCT was taken in order to evaluate the deviations of the achieved implants at coronal, apical, and depth level as well as angular deviations. Statistically significant radiological mean difference between the two groups was found in the coronal position of implants (0.26 mm, p < 0.001), in the apical position of implants (0.29 mm, p < 0.001), in the depth of implants (0.16 mm, p = 0.022), and in the angular deviation (0.7, p = 0.004). The use of the TaP technology for the treatment of the patients with at least three stable teeth that need to be removed for a totally implant prosthetic treatment is a promising technique. The performed accuracy analysis demonstrated that this digital protocol can be used without a loss of accuracy of the achieved implants compared to planned ones.
