Previously, it was suggested that haemadipsid leeches represent an important vector of trypanosomes amongst native animals in Australia. Consequently, Chtonobdella bilineata leeches were investigated for the presence of trypanosome species by polymerase chain reaction (PCR), DNA sequencing and in vitro isolation. Phylogenetic analysis ensued to further define the populations present. PCR targeting the 28S rDNA demonstrated that over 95% of C. bilineata contained trypanosomes; diversity profiling by deep amplicon sequencing of 18S rDNA indicated the presence of four different clusters related to the Trypanosoma (Megatrypanum) theileri. Novy–MacNeal–Nicolle slopes with liquid overlay were used to isolate trypanosomes into culture that proved similar in morphology to Trypanosoma cyclops in that they contained a large numbers of acidocalcisomes. Phylogeny of 18S rDNA/GAPDH/ND5 DNA sequences from primary cultures and subclones showed the trypanosomes were monophyletic, with T. cyclops as a sister group. Blood-meal analysis of leeches showed that leeches primarily contained blood from swamp wallaby (Wallabia bicolour), human (Homo sapiens) or horse (Equus sp.). The leech C. bilineata is a host for at least five lineages of Trypanosoma sp. and these are monophyletic with T. cyclops; we propose Trypanosoma cyclops australiensis as a subspecies of T. cyclops based on genetic similarity and biogeography considerations.

ABSTRACT IMPACT: A single seismocardiography (SCG) parameter has been shown to accurately classify aortic valve disease (AVD) status in healthy controls and AVD patients. This could support development of SCG as a quick, inexpensive screening tool to better tailor MRI examination to patients’ needs. OBJECTIVES/GOALS: MRI is used commonly for monitoring of aortic valve disease (AVD), but it has high costs. We hypothesize that energy in seismocardiograms (SCG)’‘ signals from chest surface vibrations’‘ is different between healthy controls and AVD patients, and we evaluate potential efficacy of using SCG to recommend MRI only for patients with flow abnormalities. METHODS/STUDY POPULATION: With IRB approval, 45 healthy control subjects (47 ±18years, 18 female) and 9 patients (63 ±16years, 2 female) with aortic valve disease history and known flow abnormalities were recruited. SCG signals were acquired supine, immediately prior to MRI of thoracic aortic blood flow at 1.5T with a time-resolved phase contrast (4D Flow) sequence.

The SCG was processed to calculate late-systole high-frequency (120-240Hz) RMS energy. MR velocity images were analyzed to measure peak velocity and trace pathlines of flow.

Screening efficacy of the SCG energy metric was assessed, with hypothesis testing for differences in energy level distributions between controls and patients, and receiver-operator characteristic (ROC) analysis was used to calculate rates of correct/incorrect classification of disease. RESULTS/ANTICIPATED RESULTS: Healthy subjects had coherent flow pathlines through the aortic arch and mid-ascending aorta peak velocities of 106 ±21cm/s (cohort mean ±standard deviation). All valve disease subjects had flow abnormalities, such as jetting flow near the valve or swirling through the arch, as visualized by pathlines. Patients’ peak mid-ascending aorta velocities were 167 ±69cm/s. The SCG energy for healthy controls was significantly different than that of valve patients (-5.6 ±0.3dBmm/s/s vs. -4.0 ±1.2dBmm/s/s respectively; p<0.001). Thresholding SCG energy to distinguish patients from controls correctly classifies subjects with a high true-positive rate and low false-positive rate. The ROC for this classification has area-under-curve 0.956. DISCUSSION/SIGNIFICANCE OF FINDINGS: A high potential screening efficacy was observed using a single, linear SCG metric to identify AVD patients with flow abnormalities. If used to complement MRI surveillance protocols for AVD, this method has potential to serve as a quick, inexpensive tool for better tailoring MRI exams to patient needs.

This article challenges the unidimensional view of abusive supervisors and examines how employees respond to abuse when the transgressing boss also has a positive impact on others. Drawing on deonance and fairness theory, we propose competing hypotheses about the influence of prosocial impact. Specifically, we use deonance theory to suggest that prosocial impact might buffer the effects of abusive supervision. Alternatively, we incorporate fairness theory to predict that prosocial impact strengthens injustice perceptions and thereby worsens consequences of abuse. Two field studies show support for fairness theory, demonstrating that employees perceive greater injustice, and show stronger retaliatory behaviors, when the abusive supervisor makes a positive difference in the workplace. A final field study replicates these results, while also testing the underlying cognitive process employees use to assess the interplay between “good” and “bad” supervisory characteristics. This article contributes insights to abusive supervision, prosocial impact, organizational justice, and behavioral ethics literatures.

Background: In low- and middle-income country (LMIC) healthcare facilities, gaps in infection prevention and control (IPC) practices increase risk of healthcare-associated infections (HAIs) and mortality among hospitalized neonates. Method: In this quasi-experimental study, we implemented the Comprehensive Unit-based Safety Program (CUSP) to improve adherence to evidence-based IPC practices in neonatal intensive care units (NICUs) in 4 tertiary-care facilities in Pune, India. CUSP is a validated strategy to empower staff to improve unit-level patient safety. Baseline safety culture was measured using the Hospital Survey on Patient Safety Culture (HSOPS). Baseline IPC assessments using the Infection Control Assessment Tool (ICAT) were completed to describe existing IPC practices to identify focus areas, the first of which was hand hygiene (HH). Sites received training in CUSP methodology and formed multidisciplinary CUSP teams, which met monthly and were supported by monthly coaching calls. Staff safety assessments (SSAs) guided selection of multimodal interventions. HH compliance was measured by direct observation using trained external observers. The primary outcome was HH compliance, evaluated monthly during the implementation and maintenance phases. Secondary outcomes included CUSP meeting frequency and HH compliance by healthcare worker (HCW) role. Result: In March 2018, 144 HCWs and administrators participated in CUSP training. Site meetings occurred monthly. During the implementation phase (June 2018–January 2019), HH monitoring commenced, sites formed their teams, completed the SSA, and selected interventions to improve HH based on the WHO’s IPC multimodal improvement strategy: (1) system change; (2) training and education; (3) monitoring and feedback; (4) reminders and communication; and (5) a culture of safety (Fig. 1). During the maintenance phase (February–September 2019), HH was monitored monthly and sites adapted interventions as needed. HH compliance improved from 58% to 70% at participant sites from implementation to maintenance phases (Fig. 2), with an odds ratio (OR) of 1.66 (95% CI, 1.50–1.84; P < .001). HH compliance improved across all HCW roles: (1) physician compliance improved from 55% to 67% (OR, 1.69; 95% CI, 1.42–2.01; P < .001); (2) nurse compliance from 61% to 73% (OR, 1.68; 95% CI, 1.46–1.93; P < .001); and (3) other HCW compliance from 52% to 62% (OR, 1.48; 95% CI, 1.10–1.99; P = .010). Conclusion: CUSP was successfully adapted by 4 diverse tertiary-care NICUs in Pune, India, and it resulted in increased HH compliance at all sites. This multimodal strategy is a promising framework for LMIC healthcare facilities to sustainably address IPC gaps and reduce HAI and mortality in neonates.

Funding: None

Disclosures: Aaron Milstone, Johns Hopkins University, BD (consulting)