Design and Fabrication of Cell-laden Gelatin Methacrylated Hydrogel Scaffold for Improving Biotransportation

One of the main goals of Tissue Engineering (TE), which has been developed rapidly over the recent years, is to re-create organs or tissues in vitro or in vivo with mimicked the anatomy and functions of body systems. Nowadays, replacing damaged tissues or organs has been a main focus in this field for addressing a significant shortage of donor tissues. Vascularisation plays a crucial role in supplying cells and tissue with essential oxygen and nutrients and removing waste products from the engineered tissue constructs. Any issue in nutrient perfusion and mass transport could significantly restrict construct development to dimensions smaller than clinically useful size, thus limiting the ability for in vivo integration. The main objectives of this study are to develop a novel framework for computational design using topology optimisation and microfabrication of 3D scaffolds using gelatin-based hydrogels (GelMa), allowing artificial vascularisation in vitro for testing if the framework is valid through the investigation into cellular viability inside the construct. In this thesis, computational models were first generated to simulate oxygen transport through solving the diffusion equation. The diffusion models are then used to optimise scaffold topology. By means of microfabrication technologies, hydrogel-based constructs were fabricated to prototype the sophisticated scaffolds. Cellular viability study was also performed to validate computational simulations and design. The results showed a higher cellular survival rate in optimally patterned constructs than the control. In summary, the work presented here is not only technically simple and cost-effective, but also establishes an effective approach to the design and fabrication of a vascularised biodegradable and scaffold-free constructs. The proposed methodology will be of considerable implication for engineering bulk tissue constructs which require sufficient ongoing vascularization in the future

Using machine learning for automatic identification of evidence-based health information on the web

Automatic assessment of the quality of online health information is a need especially with the massive growth of online content. In this paper, we present an approach to assessing the quality of health webpages based on their content rather than on purely technical features, by applying machine learning techniques to the automatic identification of evidence-based health information. Several machine learning approaches were applied to learn classifiers using different combinations of features. Three datasets were used in this study for three different diseases, namely shingles, flu and migraine. The results obtained using the classifiers were promising in terms of precision and recall especially with diseases with few different pathogenic mechanisms

Social Media and Relationship Satisfaction

In this study, researchers looked at several factors between social media use and different relationships. One study showed that relationships can be torn apart if the members have different opinions on controversial topics (Kruse et al., 2008). The family systems theory suggests that family structure could shape social development and emotional functioning, caused by differences in family–level contexts (Wikle & Hoagland, 2020). Researchers looked to see if high utilization of social media within a relationship will result in lower satisfaction. To test the hypothesis, several Likert scales were put into a survey and distributed online to students from Susquehanna University enrolled in psychology courses. Questions within the scales related to information about student demographics, social media use, and self-efficacy. Students had the option to voluntarily take the survey as well as the option to withdraw at any time, but surveys that were withdrawn were not counted as part of the data. Our results did not support the hypothesis. The statistics from the t-test and the Pearson’s r correlation did not provide the statistical data that we hypothesized, t(143) = 0.21, p = 0.98, r(145) = 0.11, p = 0.201. One limitation was that we had a limited sample of psychology students at a small campus. Future research could include larger and broader sample sizes, along with more age-appropriate relationship scales. Even though the amount of time on social media did not cause less satisfaction, our implications included to use social media with caution as it could lead to potential harm, like self- consciousness or cyber-bullying

Hanbury Brown and Twiss interferometry at a free-electron laser

We present measurements of second- and higher-order intensity correlation functions (so-called Hanbury Brown and Twiss experiment) performed at the free-electron laser (FEL) FLASH in the non-linear regime of its operation. We demonstrate the high transverse coherence properties of the FEL beam with a degree of transverse coherence of about 80% and degeneracy parameter of the order 10^9 that makes it similar to laser sources. Intensity correlation measurements in spatial and frequency domain gave an estimate of the FEL average pulse duration of 50 fs. Our measurements of the higher-order correlation functions indicate that FEL radiation obeys Gaussian statistics, which is characteristic to chaotic sources.Comment: 19 pages, 6 figures, 1 table, 40 reference

Revealing three-dimensional structure of individual colloidal crystal grain by coherent x-ray diffractive imaging

We present results of a coherent x-ray diffractive imaging experiment performed on a single colloidal crystal grain. The full three-dimensional (3D) reciprocal space map measured by an azimuthal rotational scan contained several orders of Bragg reflections together with the coherent interference signal between them. Applying the iterative phase retrieval approach, the 3D structure of the crystal grain was reconstructed and positions of individual colloidal particles were resolved. As a result, an exact stacking sequence of hexagonal close-packed layers including planar and linear defects were identified.Comment: 8 pages, 5 figure

The Indirect Effects of Servant Leadership Behavior on Organizational Citizenship Behavior and Job Performance: Organizational Justice as a Mediator

The relationship between leader and followers plays a vital role, particularly in educational institutions where a keen understanding of human character and high level of social interaction ought to be facilitated. For this reason, in stark contrast to contemporary leaders who see people only as units of production or expendable resources in a profit and loss statement, servant leadership focuses on meeting the needs of followers, making them reach their maximum potential and so perform optimally in order to achieve organizational goals and objectives. This study examines the effects of servant leadership behaviors of private college principals on teachers’ organizational citizenship behavior and job performance. Using 300 respondents from the private education institutes in Turkey, servant leadership behavior is examined for its indirect effects on organizational citizenship behavior and job performance by its impact on organizational justice. Organizational justice acts as a mediator between the variables in question. All the results are in support of the studied mediation effects. Implications of the findings and suggestions for future research are discussed

Adaptability and learning Intraprofessional collaboration of residents during the COVID-19 pandemic

CONTEXT: The COVID-19 pandemic created a worldwide public health emergency, in which hospitals created new COVID departments and doctors from different disciplines had to work together. In the Netherlands, a large proportion of doctors in these departments were residents. With knowledge of the disease developing only gradually, the influx of COVID-19 patients called for adaptability, innovative work behavior, and intraprofessional collaboration (intraPC) between residents and between residents and medical specialists. RESEARCH GOAL: This study investigates how the delivery of COVID-19 care in hospital settings altered the way residents develop their sense of adaptability and intraPC during their training. METHODS: Sixteen semi-structured interviews were conducted with residents and medical specialists from various disciplines who worked at a COVID department or Intensive Care Unit (ICU) during the COVID pandemic in the Netherlands, focusing on adaptability and intraPC learning. Transcripts were analyzed using (thematic) template analysis. RESULTS: Four themes that influenced learning during COVID care were identified: collective uncertainty, social cohesion and a sense of safety, the need for adaptive performance and intraPC learning. During the first wave, collective uncertainty about the unknown disease and the continuation of the crisis urged residents to adapt in order to take care of patients with a disease that was as yet unknown. The combination of collective uncertainty, social cohesion and a sense of safety, and the presence of different disciplines in one department promoted residents’ intraPC learning. However, intraPC learning was not always the matter of course due to the scope of the crisis and the huge numbers of new patients. CONCLUSION: Collective uncertainty affected the residents’ adaptability. The combination of collective uncertainty, social cohesion, and the presence of different disciplines in one department promoted the residents’ intraPC learning. An important facilitating factor for both adaptability and intraPC learning is a high level of social cohesion and safety. The physical and psychological proximity of supervisors is an important factor contributing to a safe learning environment. This study provides implications for practice for learning during postgraduate training in non-crisis settings. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12909-022-03868-9

Risk factors for ulnar nerve compression at the elbow: a case control study

Background. Ulnar nerve compression at the elbow is frequently encountered as the second most common compression neuropathy in the arm. As dexterity may be severely affected, the disease entity can seriously interfere with daily life and work. However, epidemiological research considering the risk factors is rarely performed

Amniotic fluid-derived stem cells for cardiovascular tissue engineering applications

Recent research has demonstrated that a population of stem cells can be isolated from amniotic fluid removed by amniocentesis that are broadly multipotent and non-tumorogenic. These amniotic fluid-derived stem cells (AFSC) could potentially provide an autologous cell source for treatment of congenital defects identified during gestation, particularly cardiovascular defects. In this review, the various methods of isolating, sorting and culturing AFSC are compared, along with techniques for inducing differentiation into cardiac myocytes and endothelial cells. Though research has not demonstrated complete and high yield cardiac differentiation, AFSC have been shown to effectively differentiate into endothelial cells and can effectively support cardiac tissue. Additionally, several tissue engineering and regenerative therapeutic approaches for the use of these cells in heart patches, injection after myocardial infarction, heart valves, vascularized scaffolds and blood vessels are summarized. These applications show great promise in the treatment of congenital cardiovascular defects, and further studies of isolation, culture, and differentiation of AFSC will help to develop their use for tissue engineering, regenerative medicine, and cardiovascular therapies