Koenigfriis4625

Results In the present study, as the functional staging increased, the Ki-67 expression also increased. Ki-67 expression was highest in severe functional staging/severely decreased mouth opening (100.78) and is least in mild functional staging/mild decreased mouth opening (10.39). However, there was no significant correlation between epithelial thickness and functional staging/mouth opening (P > 0.05). Conclusion A decrease in functional staging (mouth opening) showed a greater expression of Ki-67, and there was no significant correlation between functional staging and epithelial thickness. Copyright © 2019 Journal of Microscopy and Ultrastructure.Background With the introduction of multiple uses of mobile phones, including social networking sites, people are being addicted to the device. Most people carry the device to places which are loaded with possible pathogenic microorganisms such as toilets and washrooms, enabling the device to act as a potent fomite. Aims and Objective This study aims to determine the presence of potential pathogenic and multidrug-resistant (MDR) bacteria on the surface of mobile phones used by different occupational groups. It also aims to identify a possible relationship between mobile phone usage in toilets and mobile phone usage while eating. Materials and Methods Two hundred and sixty-eight interviewees belonging to four different occupational groups; 204 students, 24 security staffs, 21 food vendors, and 19 cleaning staff participated in the study in a university, of which 67.54% (n = 181/268) admitted to carry their mobile phones into toilets and 60.07% (n = 161/268) of the total respondents stated that they used their mobile phones while being confined in toilets. Results MDR bacterial presence were observed for both case (90.54%, n = 67/74) and control (73.07%, n = 19/26) study of the 100 swabbed samples and the association between usage of the mobile phone while being confined in toilets and while eating by the same respondent were statistically significant (P = 0.00 ≤ 0.05). Conclusion The study signifies that mobile phones are carriers of pathogenic and MDR bacteria. Therefore, cleanliness and hygiene issues should be prioritized with an awareness to minimize or restrict the use of mobile phones in unfavorable and unhygienic environments such as toilets and washrooms. Copyright © 2019 Journal of Microscopy and Ultrastructure.Purpose Protease-activated receptors (PARs) are a family of G-protein-coupled receptors distributed in a number of tissues. PAR-2 is expressed on airway epithelium and smooth muscles and overexpressed under pathological conditions, such as asthma and chronic obstructive pulmonary disease. PX-105684 However, the role of PAR-2 in airways has not yet been defined. In this study, we investigated the role of PAR-2-activating peptide (SLIGRL) on histamine-induced bronchoconstriction and the mechanisms underlying the bronchoprotective effect both in vivo and in vitro. Materials and Methods The effect of SLIGRL was tested in vivo using histamine-induced bronchoconstriction in the guinea pig and in vitro using isolated tracheal spiral strips. Results In vivo pretreatment with SLIGRL significantly reduced the histamine-induced increased bronchoconstriction. Neither propranolol nor vagotomy abolished the inhibitory effect of SLIGRL. Furthermore, indomethacin or glibenclamide did not antagonize the inhibitory response to SLIGRL. In isolated tracheal spiral strips in vitro, SLIGRL did not affect the contractile response to acetylcholine or potassium chloride; however, histamine-induced contraction was inhibited in a dose-dependent manner. Conclusion Our data demonstrate the protective effect of SLIGRL in airways; however, this effect appears to be mediated independently of prostanoids, nitric oxide, circulating adrenaline, ATP-sensitive K + channels, and vagal stimulation. Copyright © 2019 Journal of Microscopy and Ultrastructure.Mesenchymal tumors of the thyroid are extremely rare. Only few isolated cases of primary thyroid granular cell tumor (GrCT) have been reported. The anatomic location of this lesion plays an important role in the differential diagnosis. It is well-known that GrCT commonly involves the head-and-neck region, lower extremity, nuchal region, chest wall, and internal viscera such as the gastrointestinal tract. However, primary GrCT of the thyroid are unexpected and might lead to misdiagnosis, especially with pathological diagnosis limitations such as frozen section and fine-needle aspiration. We believe that it is important to establish a good differential diagnosis because of its ability to simulate the appearance of invasive carcinoma, especially in cases lacking tissue block examination. In this paper, we try to focus on clinical, radiological potential characteristics, and the differential diagnosis of the tumor. Copyright © 2019 Journal of Microscopy and Ultrastructure.This study presents the design and feasibility testing of an interactive portable motion-analysis device for the assessment of upper-limb motor functions in clinical and home settings. The device engages subjects to perform tasks that imitate activities of daily living, e.g. drinking from a cup and moving other complex objects. Sitting at a magnetic table subjects hold a 3D printed cup with an adjustable magnet and move this cup on the table to targets that can be drawn on the table surface. A ball rolling inside the cup can enhance the task challenge by introducing additional dynamics. A single video camera with a portable computer tracks real-time kinematics of the cup and the rolling ball using a custom-developed, color-based computer-vision algorithm. Preliminary verification with marker-based 3D-motion capture demonstrated that the device produces accurate kinematic measurements. Based on the real-time 2D cup coordinates, audio-visual feedback about performance can be delivered to increase motivation. The feasibility of using this device in clinical diagnostics is demonstrated on 2 neurotypical children and also 3 children with upper-extremity impairments in the hospital, where conventional motion-analysis systems are difficult to use. The device meets key needs for clinical practice 1) a portable solution for quantitative motor assessment for upper-limb movement disorders at non-laboratory clinical settings, 2) a low-cost rehabilitation device that can increase the volume of in-home physical therapy, and 3) the device affords testing and training a variety of motor tasks inspired by daily challenges to enhance self-confidence to participate in day-to-day activities. 2168-2372 © 2019 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http//www.ieee.org/publications_standards/publications/rights/index.html for more information.We aimed at reducing alarm fatigue in neonatal intensive care units by developing a model using machine learning for the early prediction of critical cardiorespiratory alarms. During this study in over 34,000 patient monitoring hours in 55 infants 278,000 advisory (yellow) and 70,000 critical (red) alarms occurred. Vital signs including the heart rate, breathing rate, and oxygen saturation were obtained at a sampling frequency of 1 Hz while heart rate variability was calculated by processing the ECG - both were used for feature development and for predicting alarms. Yellow alarms that were followed by at least one red alarm within a short post-alarm window constituted the case-cohort while the remaining yellow alarms constituted the control cohort. For analysis, the case and control cohorts, stratified by proportion, were split into training (80%) and test sets (20%). Classifiers based on decision trees were used to predict, at the moment the yellow alarm occurred, whether a red alarm(s) would shortly follow. The best performing classifier used data from the 2-min window before the occurrence of the yellow alarm and could predict 26% of the red alarms in advance (18.4s, median), at the expense of 7% additional red alarms. These results indicate that based on predictive monitoring of critical alarms, nurses can be provided a longer window of opportunity for preemptive clinical action. Further, such as algorithm can be safely implemented as alarms that are not algorithmically predicted can still be generated upon the usual breach of the threshold, as in current clinical practice. 2168-2372 © 2019 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http//www.ieee.org/publications_standards/publications/rights/index.html for more information.OBJECTIVE Non-invasive respiration detection methods are of great value to healthcare applications and disease diagnosis with their advantages of minimizing the patient's physical burden and lessen the requirement of active cooperation of the subject. This method avoids extra preparations, reduces environmental constraints, and strengthens the possibility of real-time respiratory detection. Furthermore, identifying abnormal breathing patterns in real-time is necessary for the diagnosis and monitoring of possible respiratory disorders. METHOD A non-invasive method for detecting multiple breathing patterns using C-band sensing technique is presented, which is used for identifying different breathing patterns in addition to extract respiratory rate. We first evaluate the feasibility of this non-contact method in measuring different breathing patterns. Then, we detect several abnormal breathing patterns associated with certain respiratory disorders at real time using C-band sensing technique in indoor environment. RESULTS Mean square error (MSE) and correlation coefficient (CC) are used to evaluate the correlation between C-band sensing technique and contact respiratory sensor. The results show that all the MSE are less than 0.6 and all CC are more than 0.8, yielding a significant correlation between the two used for detecting each breathing pattern. Clinical Impact C-band sensing technique is not only used to determine respiratory rates but also to identify breathing patterns, regarding as a preferred noncontact alternative approach to the traditional contact sensing methods. C-band sensing technique also provides a basis for the non-invasive detection of certain respiratory disorders. 2168-2372 © 2019 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http//www.ieee.org/publications_standards/publications/rights/index.html for more information.OBJECTIVE Parkinson's disease (PD) is a serious neurodegenerative disorder. It is reported that most of PD patients have voice impairments. But these voice impairments are not perceptible to common listeners. Therefore, different machine learning methods have been developed for automated PD detection. However, these methods either lack generalization and clinically significant classification performance or face the problem of subject overlap. METHODS To overcome the problems discussed above, we attempt to develop a hybrid intelligent system that can automatically perform acoustic analysis of voice signals in order to detect PD. The proposed intelligent system uses linear discriminant analysis (LDA) for dimensionality reduction and genetic algorithm (GA) for hyperparameters optimization of neural network (NN) which is used as a predictive model. Moreover, to avoid subject overlap, we use leave one subject out (LOSO) validation. RESULTS The proposed method namely LDA-NN-GA is evaluated in numerical experiments on multiple types of sustained phonations data in terms of accuracy, sensitivity, specificity, and Matthew correlation coefficient.