A prototype of an Electronic Pegboard Test to measure Hand-Time Dexterity with impaired hand functionality

This paper proposes an electronic prototype of the Grooved Pegboard Test (GPT), which is normally used to test the presence of hand dexterity. The prototype imitates the geometrical dimensions of an on-the-market GPT device, but it is electronic, not manual like the one available now for users. The suggested electronic GPT device makes automated time calculation between placing the first and the last peg in their designated locations, instead of manually observing a stopwatch normally used during the GPT. The electronic GPT prototype consists of a fabricated wooden box, electronics (switches and microcontroller), and liquid crystal display (LCD). A set of 40 normal volunteers, 20 females and 20 males, tested the designed prototype. A set of six volunteers with chronic medical conditions also participated in evaluating the proposed model. The results on normal volunteers showed that the proposed electronic GPT device yielded time calculations that match the population mean value of similar calculations by the GPT device. The one-sample t-test showed no significant difference in calculations between the new electronic GPT and the manual GPT device. The p-value was much higher than 0.05, indicating the possible use of the suggested electronic GPT device

The ubiquitin-like molecule interferon-stimulated gene 15 (ISG15) is a potential prognostic marker in human breast cancer

INTRODUCTION: ISG15 is an ubiquitin-like molecule that is strongly upregulated by type I interferons as a primary response to diverse microbial and cellular stress stimuli. However, alterations in the ISG15 signalling pathway have also been found in several human tumour entities. To the best of our knowledge, in the current study we present for the first time a systematic characterisation of ISG15 expression in human breast cancer and normal breast tissue both at the mRNA and protein level. METHOD: Using semiquantitative real-time PCR, cDNA dot-blot hybridisation and immunohistochemistry, we systematically analysed ISG15 expression in invasive breast carcinomas (n = 910) and normal breast tissues (n = 135). ISG15 protein expression was analysed in two independent cohorts on tissue microarrays; in an initial evaluation set of 179 breast carcinomas and 51 normal breast tissues; and in a second large validation set of 646 breast carcinomas and 10 normal breast tissues. In addition, a collection of benign and malignant mammary cell lines (n = 9) were investigated for ISG15 expression. RESULTS: ISG15 was overexpressed in breast carcinoma cells compared with normal breast tissue, both at the RNA and protein level. Recurrence-free (p = 0.030), event-free (p = 0.001) and overall (p = 0.001) survival analyses showed a significant correlation between ISG15 overexpression and unfavourable prognosis. CONCLUSION: Therefore, ISG15 may represent a novel breast tumour marker with prognostic significance and may be helpful in selecting patients for and predicting response to the treatment of human breast cancer

J.N.: ‘Identification of aortic stenosis disease using discrete wavelet packet analyses

Abstract Heart auscultation which is the interpretation of sounds produced by the heart is a fundamental tool in the diagnosis of heart disease

Identification of Aortic Stenosis Disease using Discrete Wavelet Packet Analysis

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The Application of the Morlet transform Wavelet in the Detection of Paradoxical Splitting of the Second Heart Sound

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Self-powered WiFi-connected monitoring stations for environmental pollution app-based control in urban and industrial areas

This paper presents the design of a sensing device for monitoring and storing the atmospheric and noise pollution data, using technology with zero impact on the environment. The system consists of an eco-friendly sensor pitch equipped with a multi-sources harvesting system used to scavenge energy from renewable sources (wind and solar light), making it suitable to be accumulated into a storage device. The harvested energy is used to feed a sensing section, which samples the environmental parameters (i.e. PM2.5, PM10, NH3, CO2, NO2, CO) at regular intervals. The hardware and firmware development of the sensor node is discussed; this last is based on the Arduino Pro Micro microcontroller board, which acquires, processes and stores the data from sensors and manages their transmissions towards the cloud platform. Finally, the test results of the developed sensor pitch are presented, demonstrating the correct operation of all system sections