No abstract

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We present the design, analysis, and validation of a tunable-volume handheld pipette that enables precise drawing and dispensing of ml and μl liquid volumes. The design builds upon the standard mechanism of a handheld micropipette by incorporating an elastic diaphragm that de-amplifies the volume displacement of the internal piston via compression of an entrapped air volume. The degree of de-amplification is determined by the stiffness of the elastic diaphragm and the amount of entrapped air. An analytical model of the diaphragm mechanism is derived, which guides how to achieve linear de-amplification over an extended range where leading-order nonlinear contributions are significant. In particular, nonlinearities inherent in the mechanical behavior of the diaphragm and entrapped air volume may exactly cancel one another by careful design of the pipette’s parameter constants. This linearity is a key attribute for enabling the pipette’s tunable volumetric range, as this allows diaphragms with different stiffnesses to be selectively used with a conventional linear-stepping piston mechanism. Design considerations regarding the range, accuracy, and precision of the proposed pipette are detailed based on the model. Additionally, we have constructed a handheld prototype that uses a planar latex sheet as the diaphragm. Our pipetting experiments validate the derived model and exhibit linearity between the piston stroke and drawn liquid volume. We propose that this design enables a single handheld mechanical pipette to achieve drawing and dispensing of liquids over a 1μl-10ml range (i.e., the range of the entire micropipette suite), with volumetric resolution and precision comparable to commercially available counterparts.

This study was designed in response to the pandemic. This was to increase the accessibility of Simulation Training whilst under lockdown restrictions and limited departmental capacity due to social distancing.The aim of the study was to assess final-year medical students’ perspectives on a new method of delivering a simulation course remotely.The technique utilized in the intervention group was a guided experience via ‘Avatars’ – Faculty members who were physically present in the simulation room. Course participants joined via a live video stream and directed the ‘Avatar’ in real time. The scenarios were driven by a script that directed focus to the learning objectives. The debrief followed a ‘pause and perfect’ approach to enhance participation. During these pauses, the students, with guidance from a facilitator, reflected on developments so far and then gave their ‘Avatar’ instructions for the next stage of the scenario. The study took the form of a pragmatic cross-over trial, splitting the cohort into two groups. Group 1 received a face-to-face medicine simulation course and a remote surgery simulation course. Of this group, approximately half had the remote course first and the face-to-face second, the other half in the reverse order. Group 2 had a similar format, however with a face-to-face surgery simulation course and a remote medicine simulation course. The intention was to minimize the influence of pre-course perceptions based on what has already been experienced (i.e. a group might have a different perspective on a face-to-face course if they have had a remote course first and vice versa). Feedback was collected and compared for each.A total of 44 final-year medical students took part in the trial. 40 feedback responses were collected for the face-to-face sessions and 37 for the remote. Overall, the face-to-face simulation sessions were received more positively with 100% of participants scoring face-to-face sessions overall as ‘Excellent’ or ‘Very Good’ compared with 70.2% for the remote simulation. Participants were asked to score out of 10 how much these sessions would change their future practice; the mean score for the face-to-face was 9.29 compared with 8.5 for the remote. Remote simulation produced lower student satisfaction scores compared with face-to-face teaching. Further research is needed to determine the differential impact on knowledge and skills transfer. If there is limited impact, remote simulation could be a viable and valuable alternative to face-to-face simulation, not only during a pandemic but also in diverse environments.