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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.
Electron blocks are typically composed of a low melting point alloy (LMPA), which is poured into an insert frame containing a manually placed Styrofoam aperture negative used to define the desired field shape. Current implementations of the block fabrication process involve numerous steps which are subjective and prone to user error. Occasionally, bowing of the sides of the insert frame is observed, resulting in premature frame decommissioning. Recent works have investigated the feasibility of utilising 3D printing technology to replace the conventional electron block fabrication workflow; however, these approaches involved long print times, were not compatible with commonly used cadmium-free LMPAs, and did not address the problem of insert frame bowing. In this work, we sought to develop a new 3D printing technique that would remedy these issues.
Materials and Methods:
Electron cutout negatives and alignment jigs were printed using Acrylonitrile Butadiene Styrene, which does not warp at the high temperatures associated with molten cadmium-free alloys. The accuracy of the field shape produced by electron blocks fabricated using the 3D printed negatives was assessed using Gafchromic film and beam profiler measurements. As a proof-of-concept, electron blocks with off-axis apertures, as well as complex multi-aperture blocks to be used for passive electron beam intensity modulation, were also created.
Film and profiler measurements of field size were in excellent agreement with the values calculated using the Eclipse treatment planning system, showing less than a 1% difference in line profile full-width at half-maximum. The multi-aperture electron blocks produced fields with intensity modulation ≤3.2% of the theoretically predicted value. Use of the 3D printed alignment jig – which has contours designed to match those of the insert frame – was found to reduce the amount of frame bowing by factors of 1.8 and 2.1 in the lateral and superior–inferior directions, respectively.
The 3D printed ABS negatives generated with our technique maintain their spatial accuracy even at the higher temperatures associated with cadmium-free LMPA. The negatives typically take between 1 and 2 hours to print and have a material cost of approximately $2 per patient.
To conduct a pilot study implementing combined genomic and epidemiologic surveillance for hospital-acquired multidrug-resistant organisms (MDROs) to predict transmission between patients and to estimate the local burden of MDRO transmission.
Pilot prospective multicenter surveillance study.
The study was conducted in 8 university hospitals (2,800 beds total) in Melbourne, Australia (population 4.8 million), including 4 acute-care, 1 specialist cancer care, and 3 subacute-care hospitals.
All clinical and screening isolates from hospital inpatients (April 24 to June 18, 2017) were collected for 6 MDROs: vanA VRE, MRSA, ESBL Escherichia coli (ESBL-Ec) and Klebsiella pneumoniae (ESBL-Kp), and carbapenem-resistant Pseudomonas aeruginosa (CRPa) and Acinetobacter baumannii (CRAb). Isolates were analyzed and reported as routine by hospital laboratories, underwent whole-genome sequencing at the central laboratory, and were analyzed using open-source bioinformatic tools. MDRO burden and transmission were assessed using combined genomic and epidemiologic data.
In total, 408 isolates were collected from 358 patients; 47.5% were screening isolates. ESBL-Ec was most common (52.5%), then MRSA (21.6%), vanA VRE (15.7%), and ESBL-Kp (7.6%). Most MDROs (88.3%) were isolated from patients with recent healthcare exposure.
Combining genomics and epidemiology identified that at least 27.1% of MDROs were likely acquired in a hospital; most of these transmission events would not have been detected without genomics. The highest proportion of transmission occurred with vanA VRE (88.4% of patients).
Genomic and epidemiologic data from multiple institutions can feasibly be combined prospectively, providing substantial insights into the burden and distribution of MDROs, including in-hospital transmission. This analysis enables infection control teams to target interventions more effectively.
Alzheimer’s disease (AD) studies are increasingly targeting earlier (pre)clinical populations, in which the expected degree of observable cognitive decline over a certain time interval is reduced as compared to the dementia stage. Consequently, endpoints to capture early cognitive changes require refinement. We aimed to determine the sensitivity to decline of widely applied neuropsychological tests at different clinical stages of AD as outlined in the National Institute on Aging – Alzheimer’s Association (NIA-AA) research framework.
Amyloid-positive individuals (as determined by positron emission tomography or cerebrospinal fluid) with longitudinal neuropsychological assessments available were included from four well-defined study cohorts and subsequently classified among the NIA-AA stages. For each stage, we investigated the sensitivity to decline of 17 individual neuropsychological tests using linear mixed models.
1103 participants (age = 70.54 ± 8.7, 47% female) were included: n = 120 Stage 1, n = 206 Stage 2, n = 467 Stage 3 and n = 309 Stage 4. Neuropsychological tests were differentially sensitive to decline across stages. For example, Category Fluency captured significant 1-year decline as early as Stage 1 (β = −.58, p < .001). Word List Delayed Recall (β = −.22, p < .05) and Trail Making Test (β = 6.2, p < .05) became sensitive to 1-year decline in Stage 2, whereas the Mini-Mental State Examination did not capture 1-year decline until Stage 3 (β = −1.13, p < .001) and 4 (β = −2.23, p < .001).
We demonstrated that commonly used neuropsychological tests differ in their ability to capture decline depending on clinical stage within the AD continuum (preclinical to dementia). This implies that stage-specific cognitive endpoints are needed to accurately assess disease progression and increase the chance of successful treatment evaluation in AD.
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.