Dynamic Modelling of Tooth Deformation Using Occlusal Kinematics and Finite Element Analysis

Background

Dental biomechanics based on finite element (FE) analysis is attracting enormous interest in dentistry, biology, anthropology and palaeontology. Nonetheless, several shortcomings in FE modeling exist, mainly due to unrealistic loading conditions. In this contribution we used kinematics information recorded in a virtual environment derived from occlusal contact detection between high resolution models of an upper and lower human first molar pair (M¹ and M₁, respectively) to run a non-linear dynamic FE crash colliding test.

Methodology

MicroCT image data of a modern human skull were segmented to reconstruct digital models of the antagonistic right M¹ and M₁ and the dental supporting structures. We used the Occlusal Fingerprint Analyser software to reconstruct the individual occlusal pathway trajectory during the power stroke of the chewing cycle, which was applied in a FE simulation to guide the M₁ 3D-path for the crash colliding test.

Results

FE analysis results showed that the stress pattern changes considerably during the power stroke, demonstrating that knowledge about chewing kinematics in conjunction with a morphologically detailed FE model is crucial for understanding tooth form and function under physiological conditions.

Conclusions/Significance

Results from such advanced dynamic approaches will be applicable to evaluate and avoid mechanical failure in prosthodontics/endodontic treatments, and to test material behavior for modern tooth restoration in dentistry. This approach will also allow us to improve our knowledge in chewing-related biomechanics for functional diagnosis and therapy, and it will help paleoanthropologists to illuminate dental adaptive processes and morphological modifications in human evolution.     

Cerebral Blood Volume ASPECTS Is the Best Predictor of Clinical Outcome in Acute Ischemic Stroke: A Retrospective,Combined Semi-Quantitative and Quantitative Assessment

Introduction

The capability of CT perfusion (CTP) Alberta Stroke Program Early CT Score (ASPECTS) to predict outcome and identify ischemia severity in acute ischemic stroke (AIS) patients is still questioned.

Methods

62 patients with AIS were imaged within 8 hours of symptom onset by non-contrast CT, CT angiography and CTP scans at admission and 24 hours. CTP ASPECTS was calculated on the affected hemisphere using cerebral blood flow (CBF), cerebral blood volume (CBV) and mean transit time (MTT) maps by subtracting 1 point for any abnormalities visually detected or measured within multiple cortical circular regions of interest according to previously established thresholds. MTT-CBV ASPECTS was considered as CTP ASPECTS mismatch. Hemorrhagic transformation (HT), recanalization status and reperfusion grade at 24 hours, final infarct volume at 7 days and modified Rankin scale (mRS) at 3 months after onset were recorded.

Results

Semi-quantitative and quantitative CTP ASPECTS were highly correlated (p<0.00001). CBF, CBV and MTT ASPECTS were higher in patients with no HT and mRS≤2 and inversely associated with final infarct volume and mRS (p values: from p<0.05 to p<0.00001). CTP ASPECTS mismatch was slightly associated with radiological and clinical outcomes (p values: from p<0.05 to p<0.02) only if evaluated quantitatively. A CBV ASPECTS of 9 was the optimal semi-quantitative value for predicting outcome.

Conclusions

Our findings suggest that visual inspection of CTP ASPECTS recognizes infarct and ischemic absolute values. Semi-quantitative CBV ASPECTS, but not CTP ASPECTS mismatch, represents a strong prognostic indicator, implying that core extent is the main determinant of outcome, irrespective of penumbra size.     

Eradicating tumor drug resistance at its YAP‐biomechanical roots

Treatment with BRAF kinase inhibitors leads to rapid resistance and tumor regression in BRAF V600E mutant melanoma patients. However, the underlying mechanism of the developed tumor resistance is not fully clear. In this issue of The EMBO Journal, Kim and colleagues show that melanoma cells acquire resistance to BRAF inhibitors by changing cell shape, modifying their cytoskeleton and, in turn, activating the YAP/TAZ mechanotransduction pathway (Kim et al, 2016 ).     

Ultra high risk status and transition to psychosis in 22q11.2 deletion syndrome

The 22q11.2 deletion syndrome (22q11DS) is characterized by high rates of psychotic symptoms and schizophrenia, making this condition a promising human model for studying risk factors for psychosis. We explored the predictive value of ultra high risk (UHR) criteria in a sample of patients with 22q11DS. We also examined the additional contribution of socio‐demographic, clinical and cognitive variables to predict transition to psychosis within a mean interval of 32.5 ± 17.6 months after initial assessment. Eighty‐nine participants with 22q11DS (age range: 8‐30 years; mean 16.1 ± 4.7) were assessed using the Structured Interview for Psychosis‐Risk Syndromes. Information on Axis I diagnoses, internalizing and externalizing symptoms, level of functioning and IQ was also collected. At baseline, 22 (24.7%) participants met UHR criteria. Compared to those without a UHR condition, they had a significantly lower functioning, more frequent anxiety disorders, and more severe psychopathology. Transition rate to psychosis was 27.3% in UHR and 4.5% in non‐UHR participants. Cox regression analyses revealed that UHR status significantly predicted conversion to psychosis. Baseline level of functioning was the only other additional predictor. This is the first study investigating the predictive value of UHR criteria in 22q11DS. It indicates that the clinical path leading to psychosis is broadly comparable to that observed in other clinical high‐risk samples. Nevertheless, the relatively high transition rate in non‐UHR individuals suggests that other risk markers should be explored in this population. The role of low functioning as a predictor of transition to psychosis should also be investigated more in depth.