The aim of this study was to evaluate the levels of vitamin D (25OHD) and other bone biomarkers in patients with third molar impaction (TMI). Thirty males and 30 females with unilateral or bilateral impacted mandibular third molar, and 15 males and 15 females as a control group (CG) were recruited. Rx-OPT was used to evaluate dental position and Pederson index to measure the difficulty of the intervention. Bone biomarkers were measured through blood venous sample in TMI group and CG. Mann-Whitney test, Pearson’s correlation coefficient, linear regression model were used to compare the different parameters in the two groups. 25OHD showed lower values in TMI group than in CG (p < 0.05) with values significantly lower in bilateral impaction (p < 0.05). Pearson’s coefficient for 25OHD presented a negative correlation with the Pederson index (ρ = −0.75). Bone alkaline phosphatase (BALP) showed significantly lower dosage in TMI group than CG (p = 0.02), Pearson’s coefficient for BALP presented a negative correlation with the Pederson index. Serum calcium, serum phosphorus, ionized calcium levels in TMI and CG groups were similar and Mann-Whitney test did not significantly differ between TMI and CG. TMI could be a sign of vitamin D deficiency and of low BALP levels that should be investigated.

Purpose: to investigate the effects of intensive chemotherapy and glucocorticoid (GC) treatment on bone remodeling markers in children with acute lymphoblastic leukemia (ALL). Methods: A cross-sectional study was carried out in 39 ALL children (aged 7.64 ± 4.47) and 49 controls (aged 8.7 ± 4.7 years). Osteoprotegerin (OPG), receptor activator of NF-κB ligand (RANKL), osteocalcin (OC), C-terminal telopeptide of type I collagen (CTX), bone alkaline phosphatase (bALP), tartrate-resistant acid phosphatase 5b (TRACP5b), procollagen type I N-terminal propeptide (P1NP), Dickkopf-1 (DKK-1), and sclerostin were assessed. Statistical analysis was conducted using the principal component analysis (PCA) to study patterns of associations in bone markers. Results: ALL patients showed significantly higher OPG, RANKL, OC, CTX, and TRACP5b than the controls (p ≤ 0.02). Considering ALL group, we found a strong positive correlation among OC, TRACP5b, P1NP, CTX, and PTH (r = 0.43–0.69; p < 0.001); between CTX and P1NP (r = 0.5; p = 0.001); and between P1NP and TRAcP (r = 0.63; p < 0.001). The PCA revealed OC, CTX, and P1NP as the main markers explaining the variability of the ALL cohort. Conclusions: Children with ALL showed a signature of bone resorption. The assessment of bone biomarkers could help identify ALL individuals who are most at risk of developing bone damage and who need preventive interventions.

The aim of this study was to evaluate changes in the concentration of N-terminal type I collagen extension pro-peptide (PINP), tartrate-resistant acid phosphatase (TRAcP), and parathyroid hormone-related protein (PTHrP) in saliva during orthodontic treatment in order to evaluate whether changes in bone turnover marker (BTM) concentration can help highlight the effects of orthodontic mechanical loading in the absence of clinical evidence of tooth movement in terms of tooth movement. Saliva samples from 25 apparently healthy young subjects (10 females and 15 males) were collected using Salivette^® (Sarstedt) with cotton swabs and the concentrations of PTHrP, TRAcP 5b, and PINP were analyzed at time 0 (T1), 25 days (T2), and at 45 days (T3). Differences in the median value of biomarker levels between baseline T1 and follow-up of the different groups (T2 and T3) were assessed using the non-parametric Mann–Whitney U test. Trough concentrations of P1NP, PTHrP, and TRAcP were 0.80 µg/L, 0.21 ng/mL, and 0.90 U/L above the method LOD. The non-parametric Mann–Whitney U test confirmed a statistically significant difference in T1 versus concentrations of T2 and T3. All subjects evaluated had a statistically significant difference between T1 vs. T3. when compared with the specific critical difference (RCV) for the analyte The results obtained demonstrate that the evaluation of BTM changes in saliva can help the evaluation of orthodontic procedures and the monitoring of biomechanical therapy.

Levels of bone turnover markers (BTM) can be measured using saliva. The aim of the present study was to determine the Biological Variability of BTM in young subjects, on serial biological salivary samples. Saliva samples of 20 apparently healthy young subjects (9 females and 11 males) have been analyzed. Samples collected using salivette with cotton swabs were obtained three times every 15 days. PTHrP; TRAcP-5b and P1NP have been assayed. The ANOVA test was used to calculate intra and interindividual variance (CVI and CVG). The individuality index (II) and reference change value (RCV) were evaluated for the clinically significant variation between two results in the same individual. CVI was highest for PTHrP and lowest for P1NP while CVG was highest for TRAcP-5b. RCV was maximum for PTHrP and minimum for P1NP. The critical difference (RCV) is of particular interest in evaluating variations in the concentrations of BMT on the salivary matrix during oral pathologies and/or dental treatments The salivary dosage of BMT during dental treatments could be fundamental to establishing establish the timing of the treatment and, in the case of orthodontic treatments, to evaluate the effectiveness of the applied forces.

Background: The aim of this study was to evaluate the changes in platelet indices (PLT) provided by the ADVIA 2120 hematology analyzer (Siemens Hematology System) in the early stages of onset of infections and acute coronary syndromes (ACSs). Methods: Samples were selected from 40 patients admitted to the intensive care unit with suspected uncomplicated sepsis at presentation, from 40 patients with a biochemical diagnosis of ACS at presentation and from 40 apparently healthy subjects. These samples were tested for PLT and PLT indices [mean platelet volume (MPV); mean platelet mass (MPM); mean platelet component (MPC); immature platelets (RtcPlts)] obtained by automation with the ADVIA 2120 and specific biomarkers for sepsis [white blood cells (WBCs); neutrophil granulocytes (NGs); presepsin (PSP); procalcitonin (Pct); C-reactive protein (CRP)] and for SCA (hs cTnI). Results: Platelet indices (RtcPlts, MPV, MPM) were significantly altered (p > 0.005) in patients with suspected sepsis and patients with ACS compared to control subjects; however, no statistically significant difference was observed between the two groups of patients with disease. Cutoff values (ROC curves) were obtained for platelet indices that best discriminated healthy subjects from subjects with severe infection or ACS. Conclusions: Our data show that, in subjects with suspected sepsis and ACS at disease onset, a state of early platelet activation exists that is not disease-specific. Immature platelets (RtcPlts) and the platelet indices MPM and MPV, provided by the ADVIA 2120 hematology analyzer, showed high sensitivity in subjects with suspected sepsis or ACS at disease onset.

Aim of the study: We evaluated and compared blood gas analysis (EGA) non-conformities (NC) considered operator-dependent performed in Point-Of-Care (POC) analyzer as quality indicators (IQ) of the pre-analytical phase. To this end, four different NC registered in the resuscitation departments of the Hospital Polyclinic Bari from the beginning of the pandemic (March 2020) until February 2022 were evaluated. The results obtained were compared with those recorded in the pre-COVID period (March 2018–February 2020) to check if there were differences in number and type. Material and methods: GEM 4000 series blood gas analyzers (Instrumentation Laboratory, Bedford, MA, United States) are installed with integrated Intelligent Quality Management (iQM^®), which automatically identify and log pre-analytical errors. All blood gas analyzers are connected to the company intranet and interfaced with the GEM Web Plus (Werfen Instrumentation Laboratory, Bedford, MA, United States) data management information system, which allows the core laboratory to remotely supervise all decentralized POC stations. The operator-dependent process NC were expressed in terms of absolute and relative proportions (percentiles and percentage changes). For performance evaluation, the Mann–Whitney U test, Chi-squared test and Six-Sigma Metric calculation for performance classification were performed. Results: In the COVID period, 31,364 blood gas tests were performed vs. 16,632 tests in the pre-COVID period. The NC related to the suitability of the EGA sample and manageable by the operators were totals of 652 (3.9%) and 749 (2.4%), respectively, in the pre-COVID and COVID periods. The pre-analytical phase IQs used did not show statistically significant differences in the two periods evaluated. The Sigma evaluation did not show an increase in error rates. Conclusions: Considering the increase in the number of EGAs performed in the two periods, the training procedures performed by the core laboratory staff were effective; the clinical users of the POC complied with the indications and procedures shared with the core laboratory without increasing the operator-dependent NCs. Furthermore, the core laboratory developed monitoring activities capable of guaranteeing the maintenance of the pre-analytical quality.