Characteristics of ''best'' and ''worst'' clinical teachers as perceived by university nursing faculty and students

This study identified and compared characteristics of 'best' and 'worst' clinical teachers as perceived by university nursing faculty and students. The Nursing Clinical Teacher Effectiveness Inventory (NCTEI) was distributed to 201 volunteer subjects. This survey instrument, developed by the authors, contains 48 clinical teacher characteristics grouped into five categories. Each participant was asked to rate, using the NCTEI, the 'best' and them the 'worst' clinical teacher from past observations. Results showed both groups perceived that being a good role model was the highest rated characteristic for 'best' teachers and the 'lowest' rated characteristic for 'worst' teachers. Faculty and students' perceptions were fairly similar as to highest rated characteristics of 'best' clinical teachers. Less agreement was noted about the characteristics of 'worst' clinical teachers. When categories of clinical teacher characteristics were compared, there were significant differences between the ratings of faculty and students for 'best' clinical teachers, but none for 'worst' clinical teachers.     

Not small adults: the emerging role of pediatric pain services

Purpose

This review article explores the need for specialized pain care for children and adolescents and provides some historical context for our current knowledge base and clinical practice.

Principal findings

Pediatric patients have specialized needs with respect to assessment and management of pain. Acute pain care is modified by developmental considerations in both these areas; chronic pain encompasses a wide range of complex developmental, social, and psychological factors requiring the skills of different health disciplines to provide the best care.

Conclusions

Awareness of children’s pain has increased dramatically over the past three decades, and Canadians have performed a leadership role in much of the research. Specific multidisciplinary teams are a more recent phenomenon, but they are shown to be more effective and probably more cost effective than traditional treatment models. Important gaps in availability of resources to manage these patients remain.     

Revealing the Pb Whisker Growth Mechanism from Al-Alloy Surface and Morphological Dependency on Material Stress and Growth Environment

Spontaneous metallic Pb whisker formation from Pb and Bi containing Al-alloy’s surfaces is a newly discovered phenomenon. The whiskers display unique formations, growth and morphology, which give the opportunity to be applied for specialized sensor and electronics applications. Within this work, the impact of environmental conditions (gas composition and moisture) is investigated and correlated with the modification of whisker evolution and growth dynamics. Furthermore, the residual stress state of the aluminum matrix using deep cryogenic treatment is modified and used to further increase whisker nucleation and growth by up to three- and seven-fold, respectively, supported by quantitative results. The results of this paper indicate the possibility to manipulate the whisker not only in terms of their kinetics but also their morphology (optimal conditions are 20% O₂ and 35% humidity). Such features allow the tailoring of the whisker structure and surface to volume ratio, which can be optimized for different applications. Finally, this research provides new insight into the growth dynamics of the whiskers through in situ and ex situ measurements, providing further evidence of the complex nucleation and growth mechanisms that dictate the spontaneous growth of Pb whiskers from Al-alloy 6026 surfaces with growth velocities up to 1.15 µm/s.     

Delta Variant with P681R Critical Mutation Revealed by Ultra-Large Atomic-Scale Ab Initio Simulation: Implications for the Fundamentals of Biomolecular Interactions

The SARS-CoV-2 Delta variant is emerging as a globally dominant strain. Its rapid spread and high infection rate are attributed to a mutation in the spike protein of SARS-CoV-2 allowing for the virus to invade human cells much faster and with an increased efficiency. In particular, an especially dangerous mutation P681R close to the furin cleavage site has been identified as responsible for increasing the infection rate. Together with the earlier reported mutation D614G in the same domain, it offers an excellent instance to investigate the nature of mutations and how they affect the interatomic interactions in the spike protein. Here, using ultra large-scale ab initio computational modeling, we study the P681R and D614G mutations in the SD2-FP domain, including the effect of double mutation, and compare the results with the wild type. We have recently developed a method of calculating the amino-acid–amino-acid bond pairs (AABP) to quantitatively characterize the details of the interatomic interactions, enabling us to explain the nature of mutation at the atomic resolution. Our most significant finding is that the mutations reduce the AABP value, implying a reduced bonding cohesion between interacting residues and increasing the flexibility of these amino acids to cause the damage. The possibility of using this unique mutation quantifiers in a machine learning protocol could lead to the prediction of emerging mutations.