Sustainability in the pharmacy and pharmaceutical science curriculum

BACKGROUND Sustainability is fast becoming a significant economic factor for the pharmaceutical industry and therefore important for future professionals in the sector. However, sustainability often plays only a marginal role in pharmaceutical science and pharmacy degrees. Sustainability in the pharmaceutical sector encompasses a wide range of environmental and socio-economic issues that require contributions from multiple science disciplines, complicating its introduction into curricula.   PLAN This curriculum initiative aims to identify suitable frameworks for embedding sustainability concepts and practices into the pharmaceutical science and pharmacy degrees at Monash University. We report here on preliminary insights from curriculum mapping, an analysis of literature frameworks and an evaluation of ‘pilot’ teaching activities addressing sustainability. Student perspectives will be investigated through assessment data and survey results (human ethics approval pending). ACTION AND EVALUATION Sustainability-focused teaching activities have recently been incorporated into the Monash University pharmaceutical science and pharmacy degrees. These activities draw on a range of frameworks and standards, including the UN sustainable development goals (United Nations, n.d.) and the ESG (environment, social, governance) framework. The AMEE consensus statement learning outcomes (Shaw et al., 2021) have been used for mapping sustainability content in the Monash Pharmacy degree. REFERENCES Shaw, E., Walpole, S., McLean, M., Alvarez-Nieto, C., Barna, S. et al. (2021) AMEE Consensus Statement: Planetary health and education for sustainable healthcare. Medical Teacher 43(3), 272-286, DOI: 10.1080/0142159X.2020.1860207 United Nations (n.d.), Sustainable development goals. Retrieved May 22, 2023 from https://sdgs.un.org/goal

ESTABLISHING TRAINING PARAMETERS FOR A DEEP NEURAL NETWORK TO ASSESS 2D, FRONTAL PLANE KINEMATICS

The purpose of this study was to establish the optimal training parameters to assess frontal plane, 2D kinematics using DeepLabCut. DeepLabCut is an open-source platform that allows the user to train neural networks for customized feature detection in 2D videos. Deep neural networks were trained using frontal plane videos from 41 participants who completed single- and double-leg drop landings. Networks were trained with an increasing number of training iterations (25-250k) and training frames (200-800). Our results indicate that a minimum of 175k training iterations and 400 training frames were adequate for stable network performance (training/test errors= 2.8/3.7 pixels)

Defect redistribution along grain boundaries in SrTiO3_3 by externally applied electric fields

During thermal annealing at 1425 °C nominal electric field strengths of 50 V/mm and 150 V/mm were applied along the grain boundary planes of a near 45° (100) twist grain boundary in SrTiO$_3$. Electron microscopy characterization revealed interface expansions near the positive electrode around 0.8 nm for either field strength. While the interface width decreased to roughly 0.4 nm after annealing at 50 V/mm, the higher field strength caused decomposition of the boundary structure close to the negative electrode. Electron energy-loss and X-ray photoelectron spectroscopies demonstrated an increased degree of oxygen sublattice distortion at the negative electrode side, and enhanced concentrations of Ti$^{3+}$ and Ti$^{2+}$ compared to bulk for both single crystals and bicrystals annealed with an external electric field, respectively. Oxygen migration due to the applied electric field causes the observed alteration of grain boundary structures. At sufficiently high field strength the agglomeration of anion vacancies may lead to the decomposition of the grain boundary

Death notification: a digital communication platform for simulated patient-based training with medical students

This article is made available for unrestricted research re-use and secondary analysis in any form or be any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Medical simulation experiences, focused on enhancing essential communication skills, provide high value to trainees. These communication-based simulations often require little equipment and instead use trained faculty facilitators who can impart clinical significance and expertise to trainees. Teaching communication skills and techniques remotely is theoretically possible but has been largely unexplored in medical education.1 The COVID-19 pandemic and the subsequent restrictions imposed by shelter-in-place orders and social distancing created a need to expand traditional training methods and experiment with remote simulation training for communication skills. In this brief report, we explore the experience, outcomes and barriers to implementing a simulated communication skill curriculum focused on death notification to a cohort of remote medical students

py4DSTEM: a software package for multimodal analysis of four-dimensional scanning transmission electron microscopy datasets

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full 2D image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields and other sample-dependent properties. However, extracting this information requires complex analysis pipelines, from data wrangling to calibration to analysis to visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail, and present results from several experimental datasets. We have also implemented a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open source HDF5 standard. We hope this tool will benefit the research community, helps to move the developing standards for data and computational methods in electron microscopy, and invite the community to contribute to this ongoing, fully open-source project

The cellular and synaptic architecture of the mechanosensory dorsal horn

The deep dorsal horn is a poorly characterized spinal cord region implicated in processing low-threshold mechanoreceptor (LTMR) information. We report an array of mouse genetic tools for defining neuronal components and functions of the dorsal horn LTMR-recipient zone (LTMR-RZ), a role for LTMR-RZ processing in tactile perception, and the basic logic of LTMR-RZ organization. We found an unexpectedly high degree of neuronal diversity in the LTMR-RZ: seven excitatory and four inhibitory subtypes of interneurons exhibiting unique morphological, physiological, and synaptic properties. Remarkably, LTMRs form synapses on between four and 11 LTMR-RZ interneuron subtypes, while each LTMR-RZ interneuron subtype samples inputs from at least one to three LTMR classes, as well as spinal cord interneurons and corticospinal neurons. Thus, the LTMR-RZ is a somatosensory processing region endowed with a neuronal complexity that rivals the retina and functions to pattern the activity of ascending touch pathways that underlie tactile perception

A National US Survey of Pediatric Emergency Department Coronavirus Pandemic Preparedness

This article is made available for unrestricted research re-use and secondary analysis in any form or be any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Objective: We aim to describe the current coronavirus disease 2019 (COVID-19) preparedness efforts among a diverse set of pediatric emergency departments (PEDs) within the United States. Methods: We conducted a prospective multicenter survey of PED medical director(s) from selected children's hospitals recruited through a long established national research network. The questionnaire was developed by physicians with expertise in pediatric emergency medicine, disaster readiness, human factors, and survey development. Thirty-five children's hospitals were identified for recruitment through an established national research network. Results: We report on survey responses from 25 (71%) of 35 PEDs, of which 64% were located within academic children's hospitals. All PEDs witnessed decreases in non-COVID-19 patients, 60% had COVID-19-dedicated units, and 32% changed their unit pediatric patient age to include adult patients. All PEDs implemented changes to their staffing model, with the most common change impacting their physician staffing (80%) and triaging model (76%). All PEDs conducted training for appropriate donning and doffing of personal protective equipment (PPE), and 62% reported shortages in PPE. The majority implemented changes in the airway management protocols (84%) and cardiac arrest management in COVID patients (76%). The most common training modalities were video/teleconference (84%) and simulation-based training (72%). The most common learning objectives were team dynamics (60%), and PPE and individual procedural skills (56%). Conclusions: This national survey provides insight into PED preparedness efforts, training innovations, and practice changes implemented during the start of COVID-19 pandemic. Pediatric emergency departments implemented broad strategies including modifications to staffing, workflow, and clinical practice while using video/teleconference and simulation as preferred training modalities. Further research is needed to advance the level of preparedness and support deep learning about which preparedness actions were effective for future pandemics

Exome capture of Antarctic krill (Euphausia superba) for cost effective genotyping and population genetics with historical collections

Antarctic krill (Euphausia superba Dana) is a keystone species in the Southern Ocean ecosystem, with ecological and commercial significance. However, its vulnerability to climate change requires an urgent investigation of its adaptive potential to future environmental conditions. Historical museum collections of krill from the early 20th century represent an ideal opportunity to investigate how krill have changed over time due to predation, fishing and climate change. However, there is currently no cost-effective method for implementing population scale collection genomics for krill given its genome size (48 Gbp). Here, we assessed the utility of two inexpensive methods for population genetics using historical krill samples, specifically low-coverage shotgun sequencing (i.e. ‘genome-skimming’) and exome capture. Two full-length transcriptomes were generated and used to identify 166 putative gene targets for exome capture bait design. A total of 20 historical krill samples were sequenced using shotgun and exome capture. Mitochondrial and nuclear ribosomal sequences were assembled from both low-coverage shotgun and off-target of exome capture data demonstrating that endogenous DNA sequences could be assembled from historical collections. Although, mitochondrial and ribosomal sequences are variable across individuals from different populations, phylogenetic analysis does not identify any population structure. We find exome capture provides approximately 4500-fold enrichment of sequencing targeted genes, suggesting this approach can generate the sequencing depth required to call identify a significant number of variants. Unlocking historical collections for genomic analyses using exome capture, will provide valuable insights into past and present biodiversity, resilience and adaptability of krill populations to climate change

Common and distinct neural features of social and non-social reward processing in autism and social anxiety disorder

Autism spectrum disorders (ASDs) and social anxiety disorder (SAD) are both characterized by social dysfunction, but no study to date has compared neural responses to social rewards in ASDs and SAD. Neural responses during social and non-social reward anticipation and outcomes were examined in individuals with ASD (n = 16), SAD (n = 15) and a control group (n = 19) via functional magnetic resonance imaging. Analyses modeling all three groups revealed increased nucleus accumbens (NAc) activation in SAD relative to ASD during monetary reward anticipation, whereas both the SAD and ASD group demonstrated decreased bilateral NAc activation relative to the control group during social reward anticipation. During reward outcomes, the SAD group did not differ significantly from the other two groups in ventromedial prefrontal cortex activation to either reward type. Analyses comparing only the ASD and SAD groups revealed greater bilateral amygdala activation to social rewards in SAD relative to ASD during both anticipation and outcome phases, and the magnitude of left amygdala hyperactivation in the SAD group during social reward anticipation was significantly correlated with the severity of trait anxiety symptoms. Results suggest reward network dysfunction to both monetary and social rewards in SAD and ASD during reward anticipation and outcomes, but that NAc hypoactivation during monetary reward anticipation differentiates ASD from SAD

National preparedness survey of pediatric intensive care units with simulation centers during the coronavirus pandemic

Background: The coronavirus disease pandemic caught many pediatric hospitals unprepared and has forced pediatric healthcare systems to scramble as they examine and plan for the optimal allocation of medical resources for the highest priority patients. There is limited data describing pediatric intensive care unit (PICU) preparedness and their health worker protections. Aim: To describe the current coronavirus disease 2019 (COVID-19) preparedness efforts among a set of PICUs within a simulation-based network nationwide. Methods: A cross-sectional multi-center national survey of PICU medical director(s) from children's hospitals across the United States. The questionnaire was developed and reviewed by physicians with expertise in pediatric critical care, disaster readiness, human factors, and survey development. Thirty-five children's hospitals were identified for recruitment through a long-established national research network. The questions focused on six themes: (1) PICU and medical director demographics; (2) Pediatric patient flow during the pandemic; (3) Changes to the staffing models related to the pandemic; (4) Use of personal protective equipment (PPE); (5) Changes in clinical practice and innovations; and (6) Current modalities of training including simulation. Results: We report on survey responses from 22 of 35 PICUs (63%). The majority of PICUs were located within children's hospitals (87%). All PICUs cared for pediatric patients with COVID-19 at the time of the survey. The majority of PICUs (83.4%) witnessed decreases in non-COVID-19 patients, 43% had COVID-19 dedicated units, and 74.6% pivoted to accept adult COVID-19 patients. All PICUs implemented changes to their staffing models with the most common changes being changes in COVID-19 patient room assignment in 50% of surveyed PICUs and introducing remote patient monitoring in 36% of the PICU units. Ninety-five percent of PICUs conducted training for donning and doffing of enhanced PPE. Even 6 months into the pandemic, one-third of PICUs across the United States reported shortages in PPE. The most common training formats for PPE were hands-on training (73%) and video-based content (82%). The most common concerns related to COVID-19 practice were changes in clinical protocols and guidelines (50%). The majority of PICUs implemented significant changes in their airway management (82%) and cardiac arrest management protocols in COVID-19 patients (68%). Simulation-based training was the most commonly utilized training modality (82%), whereas team training (73%) and team dynamics (77%) were the most common training objectives. Conclusions: A substantial proportion of surveyed PICUs reported on large changes in their preparedness and training efforts before and during the pandemic. PICUs implemented broad strategies including modifications to staffing, PPE usage, workflow, and clinical practice, while using simulation as the preferred training modality. Further research is needed to advance the level of preparedness, support staff assuredness, and support deep learning about which preparedness actions were effective and what lessons are needed to improve PICU care and staff protection for the next COVID-19 patient waves