Tactile Sensibility of Single‐Tooth Implants and Natural Teeth Under Local Anesthesia of the Natural Antagonistic Teeth

Introduction and Aim: The term osseoperception describes the capability of developing a subtle tactile sensibility over dental implants. The present clinical study aims at clarifying the question of how far tactile sensibility is to be attributed to the periodontium of the natural opposing tooth of the implant. Material and Method: Thirty‐two subjects with single‐tooth implants with natural opposing teeth were included in this clinical, single‐blind, split‐mouth study. The natural antagonistic tooth of the implant and the corresponding natural contralateral tooth were anesthetized with a locally infiltrated articaine anesthetic. In a computer‐assisted and randomized way, copper foils of varying thickness (0–100 µm) were placed interocclusally between the single‐tooth implant and the natural opposing tooth, and between the contralateral pair of natural opposing teeth in order to investigate the active tactile sensibility according to the psychophysical method of constant stimuli and evaluate it statistically by the Weibull distribution. Results: The average tactile sensibility of the implants with anesthetized antagonists at the 50% value calculated by means of the Weibull distribution was 20 ± 11 µm with a support area (90%–10% value) of 77 ± 89 µm. For the pair of natural teeth, the tactile sensibility at the 50% value was 16 ± 9 µm with a support area of 48.4 ± 93 µm. This resulted in an average intraindividual difference of 3.5 ± 7 µm at the 50% value and 29 ± 93 µm in the support area. The statistical calculations demonstrated an equivalent tactile sensibility (50% value) of the single‐tooth implant and the contralateral natural control tooth with the natural antagonists being anesthetized in each case (double t‐test, equivalence limit ± 8 µm, P < 0.01, power >80%). Conclusion: Apparently, the active tactile sensibility of single‐tooth implants with natural opposing teeth is not only to be attributed to the periodontium of the opposing tooth but also to a perception over the implant itself. This could support the hypothesis according to which the implant may have a tactile sensibility of its own.     

Effects of fixed labial orthodontic appliances on speech sound production

Objective:To explore the impact of fixed labial orthodontic appliances on speech sound production.Materials and Methods:Speech evaluations were performed on 23 patients with fixed labial appliances. Evaluations were performed immediately prior to appliance insertion, immediately following insertion, and 1 and 2 months post insertion. Baseline dental/skeletal variables were correlated with the ability to accommodate the presence of the appliances.Results:Appliance effects were variable: 44% of the subjects were unaffected, 39% were temporarily affected but adapted within 2 months, and 17% of patients showed persistent sound errors at 2 months. Resolution of acquired sound errors was noted by 8 months post–appliance removal. Maladaptation to appliances was correlated to severity of malocclusion as determined by the Grainger’s Treatment Priority Index. Sibilant sounds, most notably /s/, were affected most often.Conclusions:(1) Insertion of fixed labial appliances has an effect on speech sound production. (2) Sibilant and stopped sounds are affected, with /s/ being affected most often. (3) Accommodation to fixed appliances depends on the severity of malocclusion.     

Cingulate activity and fronto-temporal connectivity in people with prodromal signs of psychosis

Schizophrenia is associated with fronto-temporal dysconnectivity, but it is not clear whether this is a risk factor for the disorder or is a consequence of the established illness. The aim of the present study was to use fMRI to investigate fronto-temporal connectivity in subjects with prodromal signs of schizophrenia using the Hayling Sentence Completion Task (HSCT). Thirty participants, 15 with an at risk mental state (ARMS) and 15 healthy controls were scanned whilst completing 80 sentence stems. The congruency and constraint of sentences varied across trials. Dynamic causal modelling (DCM) and Bayesian model selection (BMS) were used to compare alternative models of connectivity in a task related network. During the HSCT ARMS subjects did not differ from Healthy Controls in terms of fronto-temporal activation, i.e. there was neither a main effect of group nor a group-by-task interaction. However, there was both a significant main effect of group and a significant interaction in the anterior cingulate cortex (ACC), with greater ACC activity in the ARMS subjects. A systematic BMS procedure among 14 alternative DCMs including the ACC, middle frontal, and middle temporal gyri revealed intact task-dependent modulation of fronto-temporal effective connectivity in the ARMS group. However, ARMS subjects showed increased endogenous connection strength between the ACC and the middle temporal gyrus relative to healthy controls. Although task related fronto-temporal integration in the ARMS was intact, this may depend on increased engagement of the ACC which was not observed in healthy control subjects.     

Magnetic resonance elastography of skeletal muscle deep tissue injury

The current state‐of‐the‐art diagnosis method for deep tissue injury in muscle, a subcategory of pressure ulcers, is palpation. It is recognized that deep tissue injury is frequently preceded by altered biomechanical properties. A quantitative understanding of the changes in biomechanical properties preceding and during deep tissue injury development is therefore highly desired. In this paper we quantified the spatial–temporal changes in mechanical properties upon damage development and recovery in a rat model of deep tissue injury. Deep tissue injury was induced in nine rats by two hours of sustained deformation of the tibialis anterior muscle. Magnetic resonance elastography (MRE), T₂‐weighted, and T₂‐mapping measurements were performed before, directly after indentation, and at several timepoints during a 14‐day follow‐up. The results revealed a local hotspot of elevated shear modulus (from 3.30 ± 0.14 kPa before to 4.22 ± 0.90 kPa after) near the center of deformation at Day 0, whereas the T₂ was elevated in a larger area. During recovery there was a clear difference in the time course of the shear modulus and T₂. Whereas T₂ showed a gradual normalization towards baseline, the shear modulus dropped below baseline from Day 3 up to Day 10 (from 3.29 ± 0.07 kPa before to 2.68 ± 0.23 kPa at Day 10, P < 0.001), followed by a normalization at Day 14. In conclusion, we found an initial increase in shear modulus directly after two hours of damage‐inducing deformation, which was followed by decreased shear modulus from Day 3 up to Day 10, and subsequent normalization. The lower shear modulus originates from the moderate to severe degeneration of the muscle. MRE stiffness values were affected in a smaller area as compared with T₂. Since T₂ elevation is related to edema, distributing along the muscle fibers proximally and distally from the injury, we suggest that MRE is more specific than T₂ for localization of the actual damaged area.     

Evaluation of manual and automatic segmentation of the mouse heart from CINE MR images

PURPOSE: To compare global functional parameters determined from a stack of cinematographic MR images of mouse heart by a manual segmentation and an automatic segmentation algorithm. MATERIALS AND METHODS: The manual and automatic segmentation results of 22 mouse hearts were compared. The automatic segmentation was based on propagation of a minimum cost algorithm in polar space starting from manually drawn contours in one heart phase. Intra- and interobserver variability as well as validity of the automatic segmentation was determined. To test the reproducibility of the algorithm the variability was calculated from the intra- and interobserver input. RESULTS: The mean time of segmentation for one dataset was around 10 minutes and approximately 2.5 hours for automatic and manual segmentation, respectively. There were no significant differences between the automatic and the manual segmentation except for the end systolic epicardial volume. The automatically derived volumes correlated well with the manually derived volumes (R(2) = 0.90); left ventricular mass with and without papillary muscle showed a correlation R(2) of 0.74 and 0.76, respectively. The manual intraobserver variability was superior to the interobserver variability and the variability of the automatic segmentation, while the manual interobserver variability was comparable to the variability of the automatic segmentation. The automatic segmentation algorithm reduced the bias of the intra- and interobserver variability. CONCLUSION: We conclude that automatic segmentation of the mouse heart provides a fast and valid alternative to manual segmentation of the mouse heart.     

Emotion labeling and socio-emotional outcomes 18 months after early childhood traumatic brain injury

A growing body of literature has documented evidence for emotion labeling (EL) deficits after traumatic brain injury (TBI); however, long-term effects of TBI on EL abilities, particularly among young children, are unclear. We investigated EL abilities and socio-emotional outcomes in 32 children with moderate-severe TBI, 23 with complicated-mild TBI, and 82 children with orthopedic injuries (OI), shortly after injury and at 18 months post-injury. All children were between 3:0 and 6:11 years of age at the time of injury. Repeated measures analyses indicated that all groups showed improved EL performance between acute and 18-month assessments, but that the moderate-severe TBI group improved at a slower rate than the OI group, so that the two groups showed significantly different performance at 18 months. Emotion labeling ability did not significantly contribute to the prediction of socio-emotional outcomes after controlling for pre-injury functioning. These results provide preliminary evidence of emerging EL deficits after early childhood TBI that are related to injury severity but that do not predict social and behavioral outcomes.