Do rye product structure, product perceptions and oral processing modulate satiety?

Food structure and cephalic phase factors are hypothesized to contribute to postprandial satiety in addition to established food properties such as energy content, energy density, and macronutrient and fibre composition of a preload. This study aimed to evaluate if the structure of rye products has an impact on subjective feelings of satiety, and whether cephalic phase factors including oral processing, satiety expectations and perceived pleasantness modulate the interaction. Four wholegrain rye based samples (extruded flakes and puffs, bread and smoothie) were studied in terms of texture characteristics, in vivo oral processing, and expected satiety (n=26) and satiety as well as perceived pleasantness (n=16) (ClinicalTrials.gov number: NCT02554162). The vast textural differences between products were reflected in mastication process, perceived pleasantness and satiety expectations. Extruded products required the most intensive mastication. Rye puffs and rye bread which were characterized by a solid and porous structure, and showed better satiety effect in the early postprandial phase compared to other products. Mastication effort interacted with satiety response. However, the products requiring the highest mastication effort were not the most satiating ones. It seems that there are some food structure related mechanisms that influence both mastication process and postprandial satiety, the mastication process itself not being the mediating factor. Higher palatability seems to weaken postprandial satiety response.Peer reviewe

Influence of tooth loss on mandibular morphology: A cone-beam computed tomography study

Background: Tooth loss adversely affects patients’ health and psychosocial wellbeing. In addition, it changes mandibular morphology. Objective: To evaluate the effect of tooth loss, age, and gender on mandibular morphology. Materials and Methods: Cone-beam computed tomographic (CBCT) scans of 101 patients were examined to measure the gonial angle (GA), ramus height (RH) and condylar height (CH). Patients’ age, gender, and dental status were recorded. Repeated measures analysis of variance (ANOVA) was used to assess the impact of gender, age, and tooth loss on the GA, RH and CH. The mean measurements of the GA, RH and CH were compared between dentate/edentulous patients after splitting by gender. Results: The GA was larger in edentulous patients compared to dentate ones, in females than in males, and in older than in younger. RH on the right side was significantly longer than on the left side (P< 0.0001), and also longer in males and younger patients. CH was shorter in younger than in older patients and in dentate than in edentulous patients. Conclusions: Tooth loss is associated with changes in mandibular morphology and its prevention would avoid these irreversible changes.</p

Deep Learning Enables Accurate Automatic Sleep Staging Based on Ambulatory Forehead EEG

We have previously developed an ambulatory electrode set (AES) for the measurement of electroencephalography (EEG), electrooculography (EOG), and electromyography (EMG). The AES has been proven to be suitable for manual sleep staging and self-application in in-home polysomnography (PSG). To further facilitate the diagnostics of various sleep disorders, this study aimed to utilize a deep learning-based automated sleep staging approach for EEG signals acquired with the AES. The present neural network architecture comprises a combination of convolutional and recurrent neural networks previously shown to achieve excellent sleep scoring accuracy with a single standard EEG channel (F4-M1). In this study, the model was re-trained and tested with 135 EEG signals recorded with AES. The recordings were conducted for subjects suspected of sleep apnea or sleep bruxism. The performance of the deep learning model was evaluated with 10-fold cross-validation using manual scoring of the AES signals as a reference. The accuracy of the neural network sleep staging was 79.7% (kappa = 0.729) for five sleep stages (W, N1, N2, N3, and R), 84.1% (kappa = 0.773) for four sleep stages (W, light sleep, deep sleep, R), and 89.1% (kappa = 0.801) for three sleep stages (W, NREM, R). The utilized neural network was able to accurately determine sleep stages based on EEG channels measured with the AES. The accuracy is comparable to the inter-scorer agreement of standard EEG scorings between international sleep centers. The automatic AES-based sleep staging could potentially improve the availability of PSG studies by facilitating the arrangement of self-administrated in-home PSGs.Peer reviewe

Genome-wide association study of primary tooth eruption identifies pleiotropic loci associated with height and craniofacial distances

Twin and family studies indicate that the timing of primary tooth eruption is highly heritable, with estimates typically exceeding 80%. To identify variants involved in primary tooth eruption we performed a population based genome-wide association study of ‘age at first tooth’ and ‘number of teeth’ using 5998 and 6609 individuals respectively from the Avon Longitudinal Study of Parents and Children (ALSPAC) and 5403 individuals from the 1966 Northern Finland Birth Cohort (NFBC1966). We tested 2,446,724 SNPs imputed in both studies. Analyses were controlled for the effect of gestational age, sex and age of measurement. Results from the two studies were combined using fixed effects inverse variance meta-analysis. We identified a total of fifteen independent loci, with ten loci reaching genome-wide significance (p<5x10−8) for ‘age at first tooth’ and eleven loci for ‘number of teeth’. Together these associations explain 6.06% of the variation in ‘age of first tooth’ and 4.76% of the variation in ‘number of teeth’. The identified loci included eight previously unidentified loci, some containing genes known to play a role in tooth and other developmental pathways, including a SNP in the protein-coding region of BMP4 (rs17563, P= 9.080x10−17). Three of these loci, containing the genes HMGA2, AJUBA and ADK, also showed evidence of association with craniofacial distances, particularly those indexing facial width. Our results suggest that the genome-wide association approach is a powerful strategy for detecting variants involved in tooth eruption, and potentially craniofacial growth and more generally organ development

Genome-Wide Association Study Reveals Multiple Loci Associated with Primary Tooth Development during Infancy

Peer reviewe