Gastroesophageal reflux leads to esophageal cancer in a surgical model with mice

<p>Abstract</p> <p>Background</p> <p>Esophago-gastroduodenal anastomosis with rats mimics the development of human Barrett's esophagus and esophageal adenocarcinoma by introducing mixed reflux of gastric and duodenal contents into the esophagus. However, use of this rat model for mechanistic and chemopreventive studies is limited due to lack of genetically modified rat strains. Therefore, a mouse model of esophageal adenocarcinoma is needed.</p> <p>Methods</p> <p>We performed reflux surgery on wild-type, <it>p53</it>^{<it>A</it>135<it>V </it>}transgenic, and <it>INK4a/Arf</it>^+/-mice of A/J strain. Some mice were also treated with omeprazole (1,400 ppm in diet), iron (50 mg/kg/m, <it>i.p</it>.), or gastrectomy plus iron. Mouse esophagi were harvested at 20, 40 or 80 weeks after surgery for histopathological analysis.</p> <p>Results</p> <p>At week 20, we observed metaplasia in wild-type mice (5%, 1/20) and <it>p53</it>^{<it>A</it>135<it>V </it>}mice (5.3%, 1/19). At week 40, metaplasia was found in wild-type mice (16.2%, 6/37), <it>p53</it>^{<it>A</it>135<it>V </it>}mice (4.8%, 2/42), and wild-type mice also receiving gastrectomy and iron (6.7%, 1/15). Esophageal squamous cell carcinoma developed in <it>INK4a/Arf</it>^+/-mice (7.1%, 1/14), and wild-type mice receiving gastrectomy and iron (21.4%, 3/14). Among 13 wild-type mice which were given iron from week 40 to 80, twelve (92.3%) developed squamous cell carcinoma at week 80. None of these mice developed esophageal adenocarcinoma.</p> <p>Conclusion</p> <p>Surgically induced gastroesophageal reflux produced esophageal squamous cell carcinoma, but not esophageal adenocarcinoma, in mice. Dominant negative <it>p53 </it>mutation, heterozygous loss of <it>INK4a/Arf</it>, antacid treatment, iron supplementation, or gastrectomy failed to promote esophageal adenocarcinoma in these mice. Further studies are needed in order to develop a mouse model of esophageal adenocarcinoma.</p

Coherent methods in the X-ray sciences

X-ray sources are developing rapidly and their coherent output is growing extremely rapidly. The increased coherent flux from modern X-ray sources is being matched with an associated rapid development in experimental methods. This article reviews the literature describing the ideas that utilise the increased brilliance from modern X-ray sources. It explores how ideas in coherent X-ray science are leading to developments in other areas, and vice versa. The article describes measurements of coherence properties and uses this discussion as a base from which to describe partially-coherent diffraction and X-ray phase contrast imaging, with its applications in materials science, engineering and medicine. Coherent diffraction imaging methods are reviewed along with associated experiments in materials science. Proposals for experiments to be performed with the new X-ray free-electron-lasers are briefly discussed. The literature on X-ray photon correlation spectroscopy is described and the features it has in common with other coherent X-ray methods are identified. Many of the ideas used in the coherent X-ray literature have their origins in the optical and electron communities and these connections are explored. A review of the areas in which ideas from coherent X-ray methods are contributing to methods for the neutron, electron and optical communities is presented.Comment: A review articel accepted by Advances in Physics. 158 pages, 29 figures, 3 table

Metabolic reconstruction of sulfur assimilation in the extremophile Acidithiobacillus ferrooxidans based on genome analysis

BACKGROUND: Acidithiobacillus ferrooxidans is a gamma-proteobacterium that lives at pH2 and obtains energy by the oxidation of sulfur and iron. It is used in the biomining industry for the recovery of metals and is one of the causative agents of acid mine drainage. Effective tools for the study of its genetics and physiology are not in widespread use and, despite considerable effort, an understanding of its unusual physiology remains at a rudimentary level. Nearly complete genome sequences of A. ferrooxidans are available from two public sources and we have exploited this information to reconstruct aspects of its sulfur metabolism. RESULTS: Two candidate mechanisms for sulfate uptake from the environment were detected but both belong to large paralogous families of membrane transporters and their identification remains tentative. Prospective genes, pathways and regulatory mechanisms were identified that are likely to be involved in the assimilation of sulfate into cysteine and in the formation of Fe-S centers. Genes and regulatory networks were also uncovered that may link sulfur assimilation with nitrogen fixation, hydrogen utilization and sulfur reduction. Potential pathways were identified for sulfation of extracellular metabolites that may possibly be involved in cellular attachment to pyrite, sulfur and other solid substrates. CONCLUSIONS: A bioinformatic analysis of the genome sequence of A. ferrooxidans has revealed candidate genes, metabolic process and control mechanisms potentially involved in aspects of sulfur metabolism. Metabolic modeling provides an important preliminary step in understanding the unusual physiology of this extremophile especially given the severe difficulties involved in its genetic manipulation and biochemical analysis

Exploring molecular variation in Schistosoma japonicum in China

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The attached file is the published version of the article

Environmental conditions shape the nature of a minimal bacterial genome

Of the 473 genes in the genome of the bacterium with the smallest genome generated to date, 149 genes have unknown function, emphasising a universal problem; less than 1% of proteins have experimentally determined annotations. Here, we combine the results from state-of-the-art in silico methods for functional annotation and assign functions to 66 of the 149 proteins. Proteins that are still not annotated lack orthologues, lack protein domains, and/ or are membrane proteins. Twenty-four likely transporter proteins are identified indicating the importance of nutrient uptake into and waste disposal out of the minimal bacterial cell in a nutrient-rich environment after removal of metabolic enzymes. Hence, the environment shapes the nature of a minimal genome. Our findings also show that the combination of multiple different state-of-the-art in silico methods for annotating proteins is able to predict functions, even for difficult to characterise proteins and identify crucial gaps for further development

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC

Spatial growth rate of emerging SARS-CoV-2 lineages in England, September 2020-December 2021

This paper uses a robust method of spatial epidemiological analysis to assess the spatial growth rate of multiple lineages of SARS-CoV-2 in the local authority areas of England, September 2020–December 2021. Using the genomic surveillance records of the COVID-19 Genomics UK (COG-UK) Consortium, the analysis identifies a substantial (7.6-fold) difference in the average rate of spatial growth of 37 sample lineages, from the slowest (Delta AY.4.3) to the fastest (Omicron BA.1). Spatial growth of the Omicron (B.1.1.529 and BA) variant was found to be 2.81× faster than the Delta (B.1.617.2 and AY) variant and 3.76× faster than the Alpha (B.1.1.7 and Q) variant. In addition to AY.4.2 (a designated variant under investigation, VUI-21OCT-01), three Delta sublineages (AY.43, AY.98 and AY.120) were found to display a statistically faster rate of spatial growth than the parent lineage and would seem to merit further investigation. We suggest that the monitoring of spatial growth rates is a potentially valuable adjunct to outbreak response procedures for emerging SARS-CoV-2 variants in a defined population

Investigation of hospital discharge cases and SARS-CoV-2 introduction into Lothian care homes

Summary Background The first epidemic wave of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Scotland resulted in high case numbers and mortality in care homes. In Lothian, over one-third of care homes reported an outbreak, while there was limited testing of hospital patients discharged to care homes. Aim To investigate patients discharged from hospitals as a source of SARS-CoV-2 introduction into care homes during the first epidemic wave. Methods A clinical review was performed for all patients discharges from hospitals to care homes from 1st March 2020 to 31st May 2020. Episodes were ruled out based on coronavirus disease 2019 (COVID-19) test history, clinical assessment at discharge, whole-genome sequencing (WGS) data and an infectious period of 14 days. Clinical samples were processed for WGS, and consensus genomes generated were used for analysis using Cluster Investigation and Virus Epidemiological Tool software. Patient timelines were obtained using electronic hospital records. Findings In total, 787 patients discharged from hospitals to care homes were identified. Of these, 776 (99%) were ruled out for subsequent introduction of SARS-CoV-2 into care homes. However, for 10 episodes, the results were inconclusive as there was low genomic diversity in consensus genomes or no sequencing data were available. Only one discharge episode had a genomic, time and location link to positive cases during hospital admission, leading to 10 positive cases in their care home. Conclusion The majority of patients discharged from hospitals were ruled out for introduction of SARS-CoV-2 into care homes, highlighting the importance of screening all new admissions when faced with a novel emerging virus and no available vaccine

SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2

Background: Since the emergence of SARS-CoV-2, evolutionary pressure has driven large increases in the transmissibility of the virus. However, with increasing levels of immunity through vaccination and natural infection the evolutionary pressure will switch towards immune escape. Genomic surveillance in regions of high immunity is crucial in detecting emerging variants that can more successfully navigate the immune landscape. Methods: We present phylogenetic relationships and lineage dynamics within England (a country with high levels of immunity), as inferred from a random community sample of individuals who provided a self-administered throat and nose swab for rt-PCR testing as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. During round 14 (9 September–27 September 2021) and 15 (19 October–5 November 2021) lineages were determined for 1322 positive individuals, with 27.1% of those which reported their symptom status reporting no symptoms in the previous month. Results: We identified 44 unique lineages, all of which were Delta or Delta sub-lineages, and found a reduction in their mutation rate over the study period. The proportion of the Delta sub-lineage AY.4.2 was increasing, with a reproduction number 15% (95% CI 8–23%) greater than the most prevalent lineage, AY.4. Further, AY.4.2 was less associated with the most predictive COVID-19 symptoms (p = 0.029) and had a reduced mutation rate (p = 0.050). Both AY.4.2 and AY.4 were found to be geographically clustered in September but this was no longer the case by late October/early November, with only the lineage AY.6 exhibiting clustering towards the South of England. Conclusions: As SARS-CoV-2 moves towards endemicity and new variants emerge, genomic data obtained from random community samples can augment routine surveillance data without the potential biases introduced due to higher sampling rates of symptomatic individuals. © 2022, The Author(s)