Flowers Characteristics of Selected Species of Lime-Tree (Tilia spp.) in Terms of miRNA-Based Markers Activity, Mannose Expression and Biological Compounds Content

The significant healing effect of Tilia platyphyllos Scop. and Tilia cordata Mill. flowers are well known. However, the flowers of Tilia tomentosa Moench. are not suitable for harvest due to their toxic effects. To investigate the diverse background of this effect, we applied a functional miRNA-based marker, mannose expression analysis and determined the content of bioactive compounds. Out of nine tested markers, three (miR160, miR167 and miR408) provided reproducible miRNA-based loci and two of them (miR160 and miR398) enabled the acquisition of fingerprinting specific to flower and leaf samples of T. platyphyllos and T. tomentosa. The most pronounced profiling was specific for miR408 marker, the function of which is connected to plant defense and adaptation mechanisms. We confirmed the suitability of microRNA-based markers for polymorphism determination of flowers of selected species of lime-tree. The highest values of antioxidant activity, flavonoids, total polyphenols and phenolic acids content have been reached in silver linden flowers. When comparing the transcription activity of mannose in flowers, more than 30 times higher levels of mannose transcripts for the silver linden flowers was observed.

Redefining The Doctor-Patient Relationship in the Era of Artificial Intelligence – Modern Medicine’s Dilemma

"Nowadays, the traditional relationship between doctors and patients is changed by the artificial intelligence (AI) and its involvement in the medical act – ranging from diagnosis to therapeutic recommendations or personalized treatment. The balance in this triangular relationship is hard to find especially in a digitalized world, in which patients have access to unfiltered information that may lead to inaccurate self-diagnosis. When it comes to the diverse background of a disease, only a doctor will be able to draw the right conclusion. It is hard to imagine that AI will soon be able to recognize problems such as domestic violence or mental illness. Ultimately, this means that AI is only a means to an end and the responsibility of any taken decision lies with the doctor. Doctors are more than decision making machines and the emotional intelligence cannot be replaced, but the advantages of using AI in the medical field are widely recognized and ultimately the goal is to ensure the best care for the patient. The purpose of this paper is to point out ethical aspects that rise from the involvement of AI in the doctor-patient relationship and to describe the new roles of the doctor and the patient in the era of AI. "

The Delphi Process: Involving Parents of Children With Disabilities in Participatory Consensus Building

Educators recognize that parental participation is a critical factor in the success of children within a school setting. This is particularly true for parents who have children with disabilities or who are from a culturally or linguistically diverse background. However, reaching out to these families can be a difficult task even for the most empathetic and concerned educator. And while communicating directly with individual parents about their children’s academic and social welfare provides some degree of effective engagement and communication between them and the school, the parents often remain isolated from the concerns and thoughts of other parents who are in similar situations. The Delphi process described in this article creates a collaborative workspace that moves parents from being a “watcher” of school policy or school-based decisions to a “developer” of school policy or school-based decisions. The article outlines and illustrates the steps in the process and further elaborates through an ongoing commentary depicting the creation and implementation of a Delphi with the goal of better engagement with parents.

A Novel Digital Pill System for Medication Adherence Measurement and Reporting: A Usability Validation Study (Preprint)

BACKGROUND Medication nonadherence is a costly problem that is common in clinical use and and clinical trials alike with significant adverse consequences. Digital pill systems have proven to be effective and safe solutions to the challenges of nonadherence, with documented success in improving adherence and health outcomes. OBJECTIVE This human factors validation study evaluated a novel digital pill system, the ID-CapTM System from etectRx, for usability among patient users in a simulated real-world use environment. METHODS Seventeen patients of diverse background who regularly take oral prescription medications were recruited. After training and a period of training decay, participants were asked to complete 12 patient use scenarios during which errors or difficulties were logged. Participants also were interviewed about their experience with the ID-Cap System. RESULTS In this human factors validation study, patient users completed 97% of the use scenarios successfully, and 75% of these were completed without any failures or errors. Participants found the ID-Cap System easy to use and were able to accurately and proficiently record ingestion events using the device. CONCLUSIONS Participants demonstrated the ability to safely and effectively use the ID-Cap System for its intended use. Regardless of age, educational level, or background, patients were able to use it successfully. The ID-Cap System has great potential as a useful tool for encouraging medication adherence and can be easily implemented by patient users. CLINICALTRIAL Not applicable

Diagnosis and management of non-clonal erythrocytosis remains challenging: a single centre clinical experience

Erythrocytosis has a diverse background. While polycythaemia vera has well defined criteria, the diagnostic approach and management of other types of erythrocytosis are more challenging. The aim of study was to retrospectively analyse the aetiology and management of non-clonal erythrocytosis patients referred to a haematology outpatient clinic in an 8-year period using a 3-step algorithm. The first step was inclusion of patients with Hb > 185 g/L and/or Hct > 0.52 in men and Hb > 165 g/L and/or Hct > 0.48 in women on two visits ≥ two months apart, thus confirming true erythrocytosis. Secondly, polycythaemia vera was excluded and secondary causes of erythrocytosis (SE) identified. Thirdly, idiopathic erythrocytosis patients (IE) were referred to next-generation sequencing for possible genetic background evaluation. Of the 116 patients, 75 (65%) are men and 41 (35%) women, with non-clonal erythrocytosis 34/116 (29%) had SE, 15/116 (13%) IE and 67/116 (58%) stayed incompletely characterized (ICE). Patients with SE were significantly older and had significantly higher Hb and Hct compared to patients with IE. Most frequently, SE was attributed to obstructive sleep apnoea and smoking. Phlebotomies were performed in 56, 53 and 40% of patients in the SE, IE, and ICE group, respectively. Approx. 70% of patients in each group received aspirin. Thrombotic events were registered in 12, 20 and 15% of SE, IE and ICE patients, respectively. Congenital erythrocytosis type 4 (ECYT4) was diagnosed in one patient. The study demonstrates real-life management of non-clonal erythrocytosis which could be optimized using a 3-step diagnostic algorithm.

Supervening impossibility of the provision of sports training and coaching due to the 'coronavirus'

The paper analyses the situation of the contracts to provide services that persons or sport organisations agree with their students in the context of expanded health crisis worldwide caused by the coronavirus. Given the diverse background of the readers, reference to specific national or local regulations will be avoided. Instead, general principles of the service contract contained in some studies that have dealt with the transnational harmonisation of private law are considered.

The changing map of international student mobility

This article presents fifteen essays following a prompt on the changing map of international student mobility through three disruptions, namely Brexit, America First and COVID-19. These essays written by postgraduate students at Beijing Normal University were collected during the Spring semester of 2020 and edited by Stephanie Hollings and Zhang Man under the supervision of Professor Michael Peters. The fifteen texts, written in the midst of the COVID-19 pandemic, highlight the many factors and faces of the changing map of international student mobility from fifteen different perspectives. The world map is a key aspect of these essays as it is not only important as a geographical concept but as a discourse of knowledge, power, identity and ideas that will be reflected in each student’s interpretation of international student mobility. Each student draws on their own diverse background and lived experiences, some as Chinese students and some as international students in China, to give light to these disruptions through the eyes of ‘globally mobile’ students, making an important contribution to global discussions on international student mobility. These students, reflecting on being in the midst of a pandemic spreading across the world map, imagine the future post-COVID-19 and how that will interplay with the other two major student mobility disruptions of recent years (Brexit and America First) to impact international student mobility, international education, the ever-changing map of international student mobility and the discourse that comes from that changing map.

Improved YOLOv3 Network for Insulator Detection in Aerial Images with Diverse Background Interference

Automatic inspection of insulators from high-voltage transmission lines is of paramount importance to the safety and reliable operation of the power grid. Due to different size insulators and the complex background of aerial images, it is a difficult task to recognize insulators in aerial views. Most of the traditional image processing methods and machine learning methods cannot achieve sufficient performance for insulator detection when diverse background interference is present. In this study, a deep learning method—based on You Only Look Once (YOLO)—will be proposed, capable of detecting insulators from aerial images with complex backgrounds. Firstly, aerial images with common aerial scenes were collected by Unmanned Aerial Vehicle (UAV), and a novel insulator dataset was constructed. Secondly, to enhance feature reuse and propagation, on the basis of YOLOv3 and Dense-Blocks, the YOLOv3-dense network was utilized for insulator detection. To improve detection accuracy for different sized insulators, a structure of multiscale feature fusion was adapted to the YOLOv3-dense network. To obtain abundant semantic information of upper and lower layers, multilevel feature mapping modules were employed across the YOLOv3-dense network. Finally, the YOLOv3-dense network and compared networks were trained and tested on the testing set. The average precision of YOLOv3-dense, YOLOv3, and YOLOv2 were 94.47%, 90.31%, and 83.43%, respectively. Experimental results and analysis validate the claim that the proposed YOLOv3-dense network achieves good performance in the detection of different size insulators amid diverse background interference.