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Our aim was to explore emotional reactions to intervening in an overdose event from the perspective of individuals who use opioids (peer responders). In addition, we were interested in the impact this experience may have on peer responders' feelings about helping in an overdose situation in the future.

For this qualitative sub-study of a randomized controlled trial (RCT), data from 61 interviews were analyzed thematically using an inductive approach.

Peer responders had diverse emotional reactions to the overdose event. These ranged from a sense of pride and other positive feelings associated with their ability to help to ambivalence about being involved in situations perceived as challenging and burdensome. There were few reports of the overdose event as an exclusively negative experience. Many peer responders perceived it as their duty to use naloxone again if required. However, some had ambivalent feelings toward this responsibility, which may be related to negative experiences with previous intervuations perceived as challenging and burdensome. There were few reports of the overdose event as an exclusively negative experience. Many peer responders perceived it as their duty to use naloxone again if required. However, some had ambivalent feelings toward this responsibility, which may be related to negative experiences with previous intervention efforts. Conclusions The capacity of people who use opioids to help reduce the harms associated with opioid overdose is experienced as empowering by some. Nonetheless, engaging peer responders in strategies to reduce opioid-related mortality should be coupled with appropriate resources to process their experiences and emotional responses.Substance use disorder (SUD) organizations are often siloed, with little integration across specialty addictions treatment, primary care and hospitals, harm reduction, policy, and advocacy. COVID-19 introduced a pressing need for collaboration and leadership, given a fast-changing, high-stakes environment; widespread anxiety; and lack of guidance. This research letter describes our approach to convening and supporting leaders across the US state of Oregon's SUD continuum during the pandemic. We rapidly developed and implemented a SUD COVID Response ECHO, adapting ECHO - a telementoring model - to convene leaders across 32 statewide agencies. Our experience allowed participants to lead their agencies to respond to real-time COVID-related needs, address existing barriers within SUD systems, and build relationships and community across statewide SUD leaders. This kind of collaboration - which helped bridge gaps among the diverse agencies, disciplines, and regions addressing SUDs in the state - was long overdue, and sows seeds for long-term advances in care for people with SUD.Hyaluronic acid is a high molecular weight polysaccharide that is widely distributed in animal tissues. Bacterial hyaluronidases degrade hyaluronic acid as secreted enzymes and have been shown to contribute to infection. Staphylococcus aureus UAMS-1 is a clinical isolate that codes for two hyaluronidases (hysA1 and hysA2). Previous research has shown the presence of a full-length HysA1 protein from the S. aureus UAMS-1 strain with no evidence of enzymatic activity. A single base change resulting in an E480G amino acid change was identified in the S. aureus UAMS-1 hysA1 gene when compared to the S. Polyethylenimine chemical structure aureus Sanger 252 hysA1 gene. A plasmid copy of the S. aureus Sanger 252 hysA1 gene transduced into a hysA2 deletion mutant strain of S. aureus UAMS-1 restored near wild type levels of enzymatic activity. Homology modeling and structural analysis suggested that Glu-480 in the HysA1 is critically responsible for maintaining the structural and functional ensemble of the catalytic and tunnel-forming residues, which are essential for enzyme activity. A high degree of relatedness among several Gram-positive bacterial hyaluronidases indicate the loss of enzymatic activity of HysA1 in the S. aureus UAMS-1 strain is most likely caused by the mutation identified in our study.

This work evaluated the on-treatment imaging workflow in the UK's first proton beam therapy (PBT) centre, with a view to reducing times and unnecessary imaging doses to patients.

Imaging dose and timing data from the first 20 patients (70% paediatrics, 30% TYA/adult) treated with PBT using the initial image-guided PBT (IGPBT) workflow of a 2-dimensional kilo-voltage (2DkV), followed by cone-beam computed-tomography (CBCT) and repeat 2DkV was included. Pearson correlations and Bland-Altman analysis were used to describe correlations between 2DkV and CBCT images to determine if any images were superfluous.

229 treatment sessions were evaluated. Patient repositioning following the initial 2DkV (i2DkV) was required on 19 (8.3%) fractions. This three-step process resulted in an additional mean imaging dose of 3.4 mGy per patient, and 5.1 minutes on the treatment bed for the patient, over a whole course of PBT, compared to a two-step workflow (removing the i2DkV image). Correspondence between the mean displacements from i2DkV and CBCT was high, with

= 0.94, 0.94 and 0.80 in the anteroposterior, superiorinferior and right-left directions, respectively. Bland-Altman analysis showed very little bias and narrow limits of agreement.

Removing the i2DkV, streamlining to a two-step workflow, would reduce treatment times and imaging dose, and has been implemented as standard verification protocol. For challenging cases (

paediatric patients under GA), further investigations are required before the three-step workflow can be modified.

This is the first report assessing a preliminary imaging protocol in PBT in the UK and determining a way to reduce dose and time, which ultimately benefits the patient.

This is the first report assessing a preliminary imaging protocol in PBT in the UK and determining a way to reduce dose and time, which ultimately benefits the patient.Machine learning provides a probabilistic framework for metabolic pathway inference from genomic sequence information at different levels of complexity and completion. However, several challenges, including pathway features engineering, multiple mapping of enzymatic reactions, and emergent or distributed metabolism within populations or communities of cells, can limit prediction performance. In this article, we present triUMPF (triple non-negative matrix factorization [NMF] with community detection for metabolic pathway inference), which combines three stages of NMF to capture myriad relationships between enzymes and pathways within a graph network. This is followed by community detection to extract a higher-order structure based on the clustering of vertices that share similar statistical properties. We evaluated triUMPF performance by using experimental datasets manifesting diverse multi-label properties, including Tier 1 genomes from the BioCyc collection of organismal Pathway/Genome Databases and low complexity microbial communities. Resulting performance metrics equaled or exceeded other prediction methods on organismal genomes with improved precision on multi-organismal datasets.

To evaluate the impact of fully automatic motion correction by data-driven respiratory gating (DDG) on positron emission tomography (PET) image quality, lesion detection and patient management.

A total of 149 patients undergoing PET/CT for cancer (re-)staging were retrospectively included. Patients underwent a PET/CT on a digital detector scanner and for every patient a PET data set where DDG was enabled (PET

) and as well as where DDG was not enabled (PET

) was reconstructed. All PET data sets were evaluated by two readers which rated the general image quality, motion effects and organ contours. Further, both readers reviewed all scans on a case-by-case basis and evaluated the impact of PET

on additional apparent lesion, change of report, and change of management.

In 85% (

= 126) of the patients, at least one bed position was acquired using DDG, resulting in mean scan time increase of 437 min per patient in the whole study cohort (

= 149). General image quality was not rated differently for PET

and PET

images (

= 1.000) while motion effects (

indicating general blurring) was rated significantly lower in PET

images and organ contours, including liver and spleen, were rated significantly sharper using PET

as compared to PET

(all

< 0.001). In 27% of patients, PET

resulted in a change of the report and in a total of 12 cases (8%), PET

resulted in a change of further clinical management.

Deviceless DDG provided reliable fully automatic motion correction in clinical routine and increased lesion detectability and changed management in a considerable number of patients.

DDG enables PET/CT with respiratory gating to be used routinely in clinical practice without external gating equipment needed.

DDG enables PET/CT with respiratory gating to be used routinely in clinical practice without external gating equipment needed.The use of 18F-FDG PET CT has become an essential part of the management of patients with lymphoma. The last decade has seen unrivalled progress in research efforts to personalise treatment approaches using PET as a predictive imaging biomarker. Critical to this success has been the standardisation of PET methods and reporting, including the 5-point Deauville scale, which has enabled the delivery of robust clinical trial data to develop response-adapted treatment approaches.(1, 2) The utility of PET as a predictive imaging biomarker in assessing treatment success or failure has been investigated extensively in malignant lymphomas. Considerable progress has been made over the last decade, in using PET to direct more personalised "risk-adapted" approaches, as well as an increased understanding of some of the limitations. Arguably the greatest success has been in Hodgkin Lymphoma (HL) where PET was initially demonstrated to be a powerful predictive biomarker (3) and is now routinely used in both early-stage and advanced HL to reduce or escalate the use of chemotherapy as well as guiding the delivery of more selective radiotherapy to patients.

Carbon ion radiation therapy (CIRT) is an emerging radiation technique with advantageous physical and radiobiologic properties compared to conventional radiotherapy (RT) providing better response in case of radioresistant and hypoxic tumors. Our aim is to critically review if functional imaging techniques could play a role in predicting outcome of CIRT-treated tumors, as already proven for conventional RT.

14 studies, concerning Magnetic resonance imaging (MRI) and Positron Emission Tomography (PET), were selected after a comprehensive search on multiple electronic databases from January 2000 to March 2020.

MRI studies (n = 5) focused on diffusion-weighted MRI and, even though quantitative parameters were the same in all studies (apparent diffusion coefficient, ADC), results were not univocal, probably due to different imaging acquisition protocols and tumoral histology. For PET studies (n = 9), different tracers were used such as [

F]FDG and other uncommon tracers ([

C]MET, [

F]FLT), with a relevant heterogeneity regarding parameters used for outcome assessment.

No conclusion can be drawn on the predictive value of functional imaging in CIRT-treated tumors. A standardization of image acquisition, multi-institutional large trials and external validations are needed in order to establish the prognostic value of functional imaging in CIRT and to guide clinical practice.

Emerging studies focused on functional imaging's role in predicting CIRT outcome. Due to the heterogeneity of images acquisition and studies, results are conflicting and prospective large studies with imaging standardized protocol are needed.

Emerging studies focused on functional imaging's role in predicting CIRT outcome. Due to the heterogeneity of images acquisition and studies, results are conflicting and prospective large studies with imaging standardized protocol are needed.

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