Correlation functions in SU(2)-invariant RVB spin liquids on nonbipartite lattices

We introduce a Monte Carlo scheme based on sampling of Pfaffians to investigate Anderson's resonating-valence-bond (RVB) spin liquid wave function on the kagome and the triangular lattice. This eliminates a sign problem that prevents utilization of the valence bond basis in Monte Carlo studies for non-bipartite lattices. Studying lattice sizes of up to 600 sites, we calculate singlet-singlet and spin-spin correlations, and demonstrate how the lattice symmetry is restored within each topological sector as the system size is increased. Our findings are consistent with the expectation that the nearest neighbor RVB states describe a topological spin liquid on these non-bipartite lattices.Comment: 4.5 pages and 1 page supplemental material, 5 figures, final versio

Specific protease activity indicates the degree of Pseudomonas aeruginosa infection in chronic infected wounds

Chronic non-healing wounds are a major health problem with resident bacteria strongly implicated in their impaired healing. A rapid-screen to provide detailed knowledge of wound bacterial populations would therefore be of value and help prevent unnecessary and indiscriminate use of antibiotics—a process associated with promoting antibiotic resistance. We analysed chronic wound fluid samples, which had been assessed for microbial content, using 20 different fluorescent labelled peptide substrates to determine whether protease activity correlated with the bacterial load. Eight of the peptide substrates showed significant release of fluorescence after reaction with some of the wound samples. Comparison of wound fluid protease activities with the microbiological data indicated that there was no correlation between bacterial counts and enzyme activity for most of the substrates tested. However, two of the peptide substrates produced a signal corresponding with the microbial data revealing a strong positive correlation with Pseudomonas aeruginosa numbers. This demonstrated that short fluorescent labelled peptides can be used to detect protease activity in chronic wound fluid samples. The finding that two peptides were specific indicators for the presence of P. aeruginosa may be the basis for a diagnostic test to determine wound colonisation by this organism

Synthetic Elastography using B-mode Ultrasound through a Deep Fully-Convolutional Neural Network

Shear-wave elastography (SWE) permits local estimation of tissue elasticity, an important imaging marker in biomedicine. This recently-developed, advanced technique assesses the speed of a laterally-travelling shear wave after an acoustic radiation force "push" to estimate local Young's moduli in an operator-independent fashion. In this work, we show how synthetic SWE (sSWE) images can be generated based on conventional B-mode imaging through deep learning. Using side-by-side-view B-mode/SWE images collected in 50 patients with prostate cancer, we show that sSWE images with a pixel-wise mean absolute error of 4.5+/-0.96 kPa with regard to the original SWE can be generated. Visualization of high-level feature levels through t-Distributed Stochastic Neighbor Embedding reveals substantial overlap between data from two different scanners. Qualitatively, we examined the use of the sSWE methodology for B-mode images obtained with a scanner without SWE functionality. We also examined the use of this type of network in elasticity imaging in the thyroid. Limitations of the technique reside in the fact that networks have to be retrained for different organs, and that the method requires standardization of the imaging settings and procedure. Future research will be aimed at development of sSWE as an elasticity-related tissue typing strategy that is solely based on B-mode ultrasound acquisition, and the examination of its clinical utility.Comment: (c) 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

Monitoring occurrence of SARS-CoV-2 in school populations: A wastewater-based approach

Clinical testing of children in schools is challenging, with economic implications limiting its frequent use as a monitoring tool of the risks assumed by children and staff during the COVID-19 pandemic. Here, a wastewater-based epidemiology approach has been used to monitor 16 schools (10 primary, 5 secondary and 1 post-16 and further education) in England. A total of 296 samples over 9 weeks have been analysed for N1 and E genes using qPCR methods. Of the samples returned, 47.3% were positive for one or both genes with a detection frequency in line with the respective local community. WBE offers a low cost, non-invasive approach for supplementing clinical testing and can provide longitudinal insights that are impractical with traditional clinical testing

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

Oral Biofilm Architecture on Natural Teeth

Periodontitis and caries are infectious diseases of the oral cavity in which oral biofilms play a causative role. Moreover, oral biofilms are widely studied as model systems for bacterial adhesion, biofilm development, and biofilm resistance to antibiotics, due to their widespread presence and accessibility. Despite descriptions of initial plaque formation on the tooth surface, studies on mature plaque and plaque structure below the gum are limited to landmark studies from the 1970s, without appreciating the breadth of microbial diversity in the plaque. We used fluorescent in situ hybridization to localize in vivo the most abundant species from different phyla and species associated with periodontitis on seven embedded teeth obtained from four different subjects. The data showed convincingly the dominance of Actinomyces sp., Tannerella forsythia, Fusobacterium nucleatum, Spirochaetes, and Synergistetes in subgingival plaque. The latter proved to be new with a possibly important role in host-pathogen interaction due to its localization in close proximity to immune cells. The present study identified for the first time in vivo that Lactobacillus sp. are the central cells of bacterial aggregates in subgingival plaque, and that Streptococcus sp. and the yeast Candida albicans form corncob structures in supragingival plaque. Finally, periodontal pathogens colonize already formed biofilms and form microcolonies therein. These in vivo observations on oral biofilms provide a clear vision on biofilm architecture and the spatial distribution of predominant species

Contemporary snapshot of tumor regression grade (TRG) distribution in locally advanced rectal cancer: a cross sectional multicentric experience.

Pre-operative chemoradiotherapy (CRT) followed by surgical resection is still the standard treatment for locally advanced low rectal cancer. Nowadays new strategies are emerging to treat patients with a complete response to pre-operative treatment, rendering the optimal management still controversial and under debate. The primary aim of this study was to obtain a snapshot of tumor regression grade (TRG) distribution after standard CRT. Second, we aimed to identify a correlation between clinical tumor stage (cT) and TRG, and to define the accuracy of magnetic resonance imaging (MRI) in the restaging setting. Between January 2017 and June 2019, a cross sectional multicentric study was performed in 22 referral centers of colon-rectal surgery including all patients with cT3-4Nx/cTxN1-2 rectal cancer who underwent pre-operative CRT. Shapiro-Wilk test was used for continuous data. Categorical variables were compared with Chi-squared test or Fisher's exact test, where appropriate. Accuracy of restaging MRI in the identification of pathologic complete response (pCR) was determined evaluating the correspondence with the histopathological examination of surgical specimens.In the present study, 689 patients were enrolled. Complete tumor regression rate was 16.9%. The "watch and wait" strategy was applied in 4.3% of TRG4 patients. A clinical correlation between more advanced tumors and moderate to absent tumor regression was found (p = 0.03). Post-neoadjuvant MRI had low sensibility (55%) and high specificity (83%) with accuracy of 82.8% in identifying TRG4 and pCR.Our data provided a contemporary description of the effects of pre-operative CRT on a large pool of locally advanced low rectal cancer patients treated in different colon-rectal surgical centers

Standardisation of magnetic nanoparticles in liquid suspension

Suspensions of magnetic nanoparticles offer diverse opportunities for technology innovation, spanning a large number of industry sectors from imaging and actuation based applications in biomedicine and biotechnology, through large-scale environmental remediation uses such as water purification, to engineering-based applications such as position-controlled lubricants and soaps. Continuous advances in their manufacture have produced an ever-growing range of products, each with their own unique properties. At the same time, the characterisation of magnetic nanoparticles is often complex, and expert knowledge is needed to correctly interpret the measurement data. In many cases, the stringent requirements of the end-user technologies dictate that magnetic nanoparticle products should be clearly defined, well characterised, consistent and safe; or to put it another way—standardised. The aims of this document are to outline the concepts and terminology necessary for discussion of magnetic nanoparticles, to examine the current state-of-the-art in characterisation methods necessary for the most prominent applications of magnetic nanoparticle suspensions, to suggest a possible structure for the future development of standardisation within the field, and to identify areas and topics which deserve to be the focus of future work items. We discuss potential roadmaps for the future standardisation of this developing industry, and the likely challenges to be encountered along the way