Service Learning: Meeting Student and Community Needs

This article describes a program through which students with learning disabilities and culturally diverse backgrounds, and their peers in the general education program, demonstrated their abilities to be service providers to many people within their community

Online prevention of disordered eating in at-risk young-adult women: A two-country pragmatic randomized controlled trial

This article has been published in a revised form in Psychological Medicine. This version is free to view and download for private research and study only. Not for re-distribution, re-sale or use in derivative works. © Cambridge University Press 2017. This author accepted manuscript is made available following 6 month embargo from date of publication (Dec 2017) in accordance with the publisher’s copyright policyDisordered eating (DE) is a widespread, serious problem. Efficacious prevention programs that can be delivered at-scale are needed. A pragmatic randomized controlled trial of two online programs was conducted. Participants were young-adult women from Australia and New Zealand seeking to improve their body image. Media Smart-Targeted (MS-T) and Student Bodies (SB) were both 9-module interventions released weekly, whilst control participants received positive body image information. Primary [Eating Disorder Examination–Questionnaire (EDE-Q) Global], secondary (DE risk factors) and tertiary (DE) outcome measures were completed at baseline, post-program, 6- and 12-month follow-up. Baseline was completed by 608 women (M age = 20.71 years); 33 were excluded leaving 575 randomized to: MS-T (N = 191); SB (N = 190) or control (N = 194). Only 66% of those randomized to MS-T or SB accessed the intervention and were included in analyses with controls; 78% of this sample completed measures subsequent to baseline. Primary intent-to-treat (ITT) analyses revealed no differences between groups, while measure completer analyses found MS-T had significantly lower EDE-Q Global than controls at 12-month follow-up. Secondary ITT analyses found MS-T participants reported significantly higher quality of life–mental relative to both SB and controls (6-month follow-up), while MS-T and controls had lower clinical impairment relative to SB (post-program). Amongst measure completers, MS-T scored significantly lower than controls and SB on 5 variables. Of those with baseline DE, MS-T participants were significantly less likely than controls to have DE at 12-month follow-up. Given both programs were not therapist-moderated, MS-T has potential to achieve reductions in DE risk at low implementation costs

Relational Reasoning Network (RRN) for Anatomical Landmarking

Accurately identifying anatomical landmarks is a crucial step in deformation analysis and surgical planning for craniomaxillofacial (CMF) bones. Available methods require segmentation of the object of interest for precise landmarking. Unlike those, our purpose in this study is to perform anatomical landmarking using the inherent relation of CMF bones without explicitly segmenting them. We propose a new deep network architecture, called relational reasoning network (RRN), to accurately learn the local and the global relations of the landmarks. Specifically, we are interested in learning landmarks in CMF region: mandible, maxilla, and nasal bones. The proposed RRN works in an end-to-end manner, utilizing learned relations of the landmarks based on dense-block units and without the need for segmentation. For a given a few landmarks as input, the proposed system accurately and efficiently localizes the remaining landmarks on the aforementioned bones. For a comprehensive evaluation of RRN, we used cone-beam computed tomography (CBCT) scans of 250 patients. The proposed system identifies the landmark locations very accurately even when there are severe pathologies or deformations in the bones. The proposed RRN has also revealed unique relationships among the landmarks that help us infer several reasoning about informativeness of the landmark points. RRN is invariant to order of landmarks and it allowed us to discover the optimal configurations (number and location) for landmarks to be localized within the object of interest (mandible) or nearby objects (maxilla and nasal). To the best of our knowledge, this is the first of its kind algorithm finding anatomical relations of the objects using deep learning.Comment: 10 pages, 6 Figures, 3 Table

Exploring transparency: a new framework for responsible business management

The purpose of this paper is to critically review the relevant literature on transparency, provide a comprehensive definition of transparency, and present a new framework for facilitating the adoption of transparency as an ethical cornerstone and pragmatic strategy for organizational responsible business management.Ye

City-wide wastewater genomic surveillance through the successive emergence of SARS-CoV-2 Alpha and Delta variants

Genomic surveillance of SARS-CoV-2 has provided a critical evidence base for public health decisions throughout the pandemic. Sequencing data from clinical cases has helped to understand disease transmission and the spread of novel variants. Genomic wastewater surveillance can offer important, complementary information by providing frequency estimates of all variants circulating in a population without sampling biases. Here we show that genomic SARS-CoV-2 wastewater surveillance can detect fine-scale differences within urban centres, specifically within the city of Liverpool, UK, during the emergence of Alpha and Delta variants between November 2020 and June 2021. Furthermore, wastewater and clinical sequencing match well in the estimated timing of new variant rises and the first detection of a new variant in a given area may occur in either clinical or wastewater samples. The study's main limitation was sample quality when infection prevalence was low in spring 2021, resulting in a lower resolution of the rise of the Delta variant compared to the rise of the Alpha variant in the previous winter. The correspondence between wastewater and clinical variant frequencies demonstrates the reliability of wastewater surveillance. However, discrepancies in the first detection of the Alpha variant between the two approaches highlight that wastewater monitoring can also capture missing information, possibly resulting from asymptomatic cases or communities less engaged with testing programmes, as found by a simultaneous surge testing effort across the city

Wastewater monitoring for detection of public health markers during the COVID-19 pandemic: Near-source monitoring of schools in England over an academic year

Background Schools are high-risk settings for infectious disease transmission. Wastewater monitoring for infectious diseases has been used to identify and mitigate outbreaks in many near-source settings during the COVID-19 pandemic, including universities and hospitals but less is known about the technology when applied for school health protection. This study aimed to implement a wastewater surveillance system to detect SARS-CoV-2 and other public health markers from wastewater in schools in England. Methods A total of 855 wastewater samples were collected from 16 schools (10 primary, 5 secondary and 1 post-16 and further education) over 10 months of school term time. Wastewater was analysed for SARS-CoV-2 genomic copies of N1 and E genes by RT-qPCR. A subset of wastewater samples was sent for genomic sequencing, enabling determination of the presence of SARS-CoV-2 and emergence of variant(s) contributing to COVID-19 infections within schools. In total, >280 microbial pathogens and >1200 AMR genes were screened using RT-qPCR and metagenomics to consider the utility of these additional targets to further inform on health threats within the schools. Results We report on wastewater-based surveillance for COVID-19 within English primary, secondary and further education schools over a full academic year (October 2020 to July 2021). The highest positivity rate (80.4%) was observed in the week commencing 30th November 2020 during the emergence of the Alpha variant, indicating most schools contained people who were shedding the virus. There was high SARS-CoV-2 amplicon concentration (up to 9.2x106 GC/L) detected over the summer term (8th June - 6th July 2021) during Delta variant prevalence. The summer increase of SARS-CoV-2 in school wastewater was reflected in age-specific clinical COVID-19 cases. Alpha variant and Delta variant were identified in the wastewater by sequencing of samples collected from December to March and June to July, respectively. Lead/lag analysis between SARS-CoV-2 concentrations in school and WWTP data sets show a maximum correlation between the two-time series when school data are lagged by two weeks. Furthermore, wastewater sample enrichment coupled with metagenomic sequencing and rapid informatics enabled the detection of other clinically relevant viral and bacterial pathogens and AMR. Conclusions Passive wastewater monitoring surveillance in schools can identify cases of COVID-19. Samples can be sequenced to monitor for emerging and current variants of concern at the resolution of school catchments. Wastewater based monitoring for SARS-CoV-2 is a useful tool for SARS-CoV-2 passive surveillance and could be applied for case identification and containment, and mitigation in schools and other congregate settings with high risks of transmission. Wastewater monitoring enables public health authorities to develop targeted prevention and education programmes for hygiene measures within undertested communities across a broad range of use cases

Wastewater monitoring for detection of public health markers during the COVID-19 pandemic: Near-source monitoring of schools in England over an academic year

BACKGROUND: Schools are high-risk settings for infectious disease transmission. Wastewater monitoring for infectious diseases has been used to identify and mitigate outbreaks in many near-source settings during the COVID-19 pandemic, including universities and hospitals but less is known about the technology when applied for school health protection. This study aimed to implement a wastewater surveillance system to detect SARS-CoV-2 and other public health markers from wastewater in schools in England. METHODS: A total of 855 wastewater samples were collected from 16 schools (10 primary, 5 secondary and 1 post-16 and further education) over 10 months of school term time. Wastewater was analysed for SARS-CoV-2 genomic copies of N1 and E genes by RT-qPCR. A subset of wastewater samples was sent for genomic sequencing, enabling determination of the presence of SARS-CoV-2 and emergence of variant(s) contributing to COVID-19 infections within schools. In total, >280 microbial pathogens and >1200 AMR genes were screened using RT-qPCR and metagenomics to consider the utility of these additional targets to further inform on health threats within the schools. RESULTS: We report on wastewater-based surveillance for COVID-19 within English primary, secondary and further education schools over a full academic year (October 2020 to July 2021). The highest positivity rate (80.4%) was observed in the week commencing 30th November 2020 during the emergence of the Alpha variant, indicating most schools contained people who were shedding the virus. There was high SARS-CoV-2 amplicon concentration (up to 9.2x106 GC/L) detected over the summer term (8th June - 6th July 2021) during Delta variant prevalence. The summer increase of SARS-CoV-2 in school wastewater was reflected in age-specific clinical COVID-19 cases. Alpha variant and Delta variant were identified in the wastewater by sequencing of samples collected from December to March and June to July, respectively. Lead/lag analysis between SARS-CoV-2 concentrations in school and WWTP data sets show a maximum correlation between the two-time series when school data are lagged by two weeks. Furthermore, wastewater sample enrichment coupled with metagenomic sequencing and rapid informatics enabled the detection of other clinically relevant viral and bacterial pathogens and AMR. CONCLUSIONS: Passive wastewater monitoring surveillance in schools can identify cases of COVID-19. Samples can be sequenced to monitor for emerging and current variants of concern at the resolution of school catchments. Wastewater based monitoring for SARS-CoV-2 is a useful tool for SARS-CoV-2 passive surveillance and could be applied for case identification and containment, and mitigation in schools and other congregate settings with high risks of transmission. Wastewater monitoring enables public health authorities to develop targeted prevention and education programmes for hygiene measures within undertested communities across a broad range of use cases

Common and divergent features in transcriptional control of the homologous small RNAs GlmY and GlmZ in Enterobacteriaceae

Small RNAs GlmY and GlmZ compose a cascade that feedback-regulates synthesis of enzyme GlmS in Enterobacteriaceae. Here, we analyzed the transcriptional regulation of glmY/glmZ from Yersinia pseudotuberculosis, Salmonella typhimurium and Escherichia coli, as representatives for other enterobacterial species, which exhibit similar promoter architectures. The GlmY and GlmZ sRNAs of Y. pseudotuberculosis are transcribed from σ54-promoters that require activation by the response regulator GlrR through binding to three conserved sites located upstream of the promoters. This also applies to glmY/glmZ of S. typhimurium and glmY of E. coli, but as a difference additional σ70-promoters overlap the σ54-promoters and initiate transcription at the same site. In contrast, E. coli glmZ is transcribed from a single σ70-promoter. Thus, transcription of glmY and glmZ is controlled by σ54 and the two-component system GlrR/GlrK (QseF/QseE) in Y. pseudotuberculosis and presumably in many other Enterobacteria. However, in a subset of species such as E. coli this relationship is partially lost in favor of σ70-dependent transcription. In addition, we show that activity of the σ54-promoter of E. coli glmY requires binding of the integration host factor to sites upstream of the promoter. Finally, evidence is provided that phosphorylation of GlrR increases its activity and thereby sRNA expression