Proliferation and differentiation of periodontal ligament cells following short term tooth movement in the rat using different regimes of loading

Previous studies have indicated that periodontal ligament cells demonstrate osteogenic potential and osteoblastic differentiation via the ERK pathway under mechanical stress in vitro and in vivo. This study aimed to further analyse this regulatory process experimentally in the rat. The right upper first molars of 25 anesthetised rats were loaded with forces in order to be moved mesially. Constant forces for 4 hours of 0.25 N and 0.5 N were applied in 5 animals each. Furthermore, constant forces for 2 hours of 0.1 N were applied in 10 animals and afterwards, the first and second molars were permanently separated with composite. In these animals, the antagonists were sliced and five rats were killed after 1 day and five ones after 2 days. At last, intermittent forces of 0.1 N and O.25 Hz were applied in 5 different animals for 4 hours. Untreated contralateral sides served as control. Parafin-embedded sections were analyzed quantitatively after immunohistochemistry for proliferating cell nuclear antigen (PCNA), runt-related transcription factor 2 (Runx2/Cbfa1) and phosphorylated extracellular signal-regulated kinase 1/2 (pERK1/2). In selected areas under tension the proportion of pERK1/2 positive cells was increased compared with those in control teeth in all types of loading, whereas these proportions in selected areas under pressure were increased only after the application of intermittent forces. In representative areas, both, under tension and pressure the proportion of Runx2 positive cells decreased after the application of constant forces. After the application of constant forces for 4 hours in representative areas, both under tension and pressure the proportion of PCNA positive cells was lower than that in control teeth. The involvement of pERK1/2, Runx2/cbfa-1 and PCNA in the reaction of periodontal ligament cells to different load regimes was verified. </p

Affect state recognition for adaptive human robot interaction in learning environments

Previous studies of robots used in learning environments suggest that the interaction between learner and robot is able to enhance the learning procedure towards a better engagement of the learner. Moreover, intelligent robots can also adapt their behavior during a learning process according to certain criteria resulting in increasing cognitive learning gains. Motivated by these results, we propose a novel Human Robot Interaction framework where the robot adjusts its behavior to the affect state of the learner. Our framework uses the theory of flow to label different affect states (i.e., engagement, boredom and frustration) and adapt the robot's actions. Based on the automatic recognition of these states, through visual cues, our method adapt the learning actions taking place at this moment and performed by the robot. This results in keeping the learner at most times engaged in the learning process. In order to recognizing the affect state of the user a two step approach is followed. Initially we recognize the facial expressions of the learner and therefore we map these to an affect state. Our algorithm perform well even in situations where the environment is noisy due to the presence of more than one person and/or situations where the face is partially occluded

CAUSES OF BULLYING, DIFFERENT REASONS FOR BULLYING AND CHARACTERISTICS - IDENTITY OF THE VICTIMS ACCORDING TO THE BULLIES (HIGH SCHOOL STUDENTS)

The research presents the results from the completion of a questionnaire exclusively by the participants of the study who have been perpetrators of acts of bullying. The results showed that the bullies to a small extent acknowledged that they became bullies because they felt powerful, because they like to dominate/oppress others, because they wanted recognition of their authority from their classmates, because they were afraid of becoming victims and because they had had previously been victims of bullying (in all cases the average value is equal to 2.0). Also, the results showed that the most important reason that pushed the bullies to bully was some particular characteristic of the victim (Mean=3.0, SD=1.0) and to a lesser extent identity -ethnicity, race, sexual orientation- (Mean=2.0, SD=1.0, Mean=2.0, SD=1.0, Mean=2.0, SD=1.0) respectively. According to the perpetrators, they bullied more often boys (Mean=3.0, SD=2.0), and students of their school (Mean=3.0, SD=2.0). Finally, it emerged that the most frequent form of bullying was derogatory comments (Mean=3.0, SD=2.0) followed by physical violence (Mean=2.0, SD=1.0).  Article visualizations

VICTIMIZATION OF STUDENTS WITH LEARNING DISABILITIES OR ADHD (ATTENTION DEFICIT HYPERACTIVITY DISORDER)

The primary research objective of this research has been to investigate the relationship between the victimization of high school students and the existence of learning difficulties and ADHD. 700 students participated (with and without ADHD) who attended Gymnasiums of Western Thessaloniki in which integration departments operated. Participants anonymously completed a questionnaire on bullying. The results we quote here refer to the second part of the questionnaire that is completed only by those students who were victimized. According to the research activity so far, it was expected and finally confirmed that the variable existence of learning difficulties / ADHD is a predictor of the participation of these students in bullying incidents and even with the role of the victim [each increase in the percentage by one point (i.e. by 1 [each increase in the percentage by one point (i.e. by 1%) of the factor of learning disabilities and of the dep with a diagnosis the average value of the variable of a person falling victim to bullying increases by 1.21 points (p&lt;0.001)].  Article visualizations

Numerical Modelling of Melt Behaviour in the Lower Vessel Head of a Nuclear Reactor

Acknowledgements The authors would like to thank the EPSRC MEMPHIS multi-phase programme grant, the EPSRC Computational modelling for advanced nuclear power plants project and the EU FP7 projects THINS and GoFastR for helping to fund this work.Peer reviewedPublisher PD

Numerical Modelling of Debris Bed Water Quenching

Acknowledgements The authors would like to thank the EPSRC MEMPHIS multi-phase programme grant, the EPSRC Computational modelling for advanced nuclear power plants project, the EU FP7 projects THINS and GoFastR and ExxonMobil for helping to fund this work.Peer reviewedPublisher PD

Circulating microRNAs and Clinicopathological Findings of Papillary Thyroid Cancer: A Systematic Review

BACKGROUND/AIM: Papillary thyroid cancer (PTC) is the most common endocrine malignancy with a rising incidence. There is a need for a non-invasive preoperative test to enable better patient counselling. The aim of this systematic review was to investigate the potential role of circulating microRNAs (miRNAs) in the diagnosis and prognosis of PTC. MATERIALS AND METHODS: A systematic literature search was performed using MEDLINE, Cochrane, and Scopus databases (last search date was December 1, 2021). Studies investigating the expression of miRNAs in the serum or plasma of patients with PTC were deemed eligible for inclusion. RESULTS: Among the 1,533 screened studies, 39 studies met the inclusion criteria. In total, 108 miRNAs candidates were identified in the serum, plasma, or exosomes of patients suffering from PTC. Furthermore, association of circulating miRNAs with thyroid cancer-specific clinicopathological features, such as tumor size (13 miRNAs), location (3 miRNAs), extrathyroidal extension (9 miRNAs), pre- vs. postoperative period (31 miRNAs), lymph node metastasis (17 miRNAs), TNM stage (9 miRNAs), BRAF V600E mutation (6 miRNAs), serum thyroglobulin levels (2 miRNAs), 131I avid metastases (13 miRNAs), and tumor recurrence (2 miRNAs) was also depicted in this study. CONCLUSION: MiRNAs provide a potentially promising role in the diagnosis and prognosis of PTC. There is a correlation between miRNA expression profiles and specific clinicopathological features of PTC. However, to enable their use in clinical practice, further clinical studies are required to validate the predictive value and utility of miRNAs as biomarkers

Evaluation of a differential medium for the preliminary identification of members of the Lactobacillus plantarum and Lactobacillus casei groups

A medium originally developed for differential enumeration of probiotic species in fermented milk (mMRS-BPB, Lee and Lee 2008) was evaluated for its ability to correctly discriminate members of the Lactobacillus plantarum (L. plantarum) and L. casei groups from other species. The medium was tested on 461 strains of lactic acid bacteria (LAB) belonging to eight genera and thirty-five species. Colony morphology was relatively consistent for L. plantarum, L. paraplantarum, L. pentosus, L. paracasei, L. casei, and L. rhamnosus, but, when used alone, was not always sufficient to discriminate these species from other species potentially present in cheese. A procedure based on tree classification was developed to obtain preliminary identification on the basis of colony morphology, cell morphology, and CO2 production from glucose. By combining results of the tree classification procedure and heuristic rules, correct preliminary identification at the species or group level could be obtained in 74.4 % of cases overall, and the percentage of correct identifications was as high as 88-100 % for members of the L. plantarum and L. casei groups. When species belonging to groups that can be easily discriminated by rapid molecular methods were combined, the decision tree allowed to correct identification at the group level for the 95 % of the strains. Logistic regression was used to evaluate the effect of strain, operator, light source, and incubation temperature. Although all factors significantly affected one or more of the characters used for identification, the classification procedure proved to be quite robust. It may be difficult to use mMRS-BPB in the differential enumeration of LAB in cheese, except when species composition is relatively simple; however, it can be used as a simple tool to guide molecular identification in studies focused on the isolation of new strains from cheese

Multispectral image analysis approach to detect adulteration of beef and pork in raw meats

The aim of this study was to investigate the potential of multispectral imaging supported by multivariate data analysis for the detection of minced beef fraudulently substituted with pork and vice versa. Multispectral images in 18 different wavelengths of 220 meat samples in total from four independent experiments (55 samples per experiment) were acquired for this work. The appropriate amount of beef and pork-minced meat was mixed in order to achieve nine different proportions of adulteration and two categories of pure pork and beef. After an image processing step, data from the first three experiments were used for partial least squares-discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) so as to discriminate among all adulteration classes, as well as among adulterated, pure beef and pure pork samples. Results showed very good discrimination between pure and adulterated samples, for PLS-DA and LDA, yielding 98.48% overall correct classification. Additionally, 98.48% and 96.97% of the samples were classified within a ± 10% category of adulteration for LDA and PLS-DA respectively. Lastly, the models were further validated using the data of the fourth experiment for independent testing, where all pure and adulterated samples were classified correctly in the case of PLS-DA, while LDA was proved to be less accurate