77 research outputs found
New Mechanics of Traumatic Brain Injury
The prediction and prevention of traumatic brain injury is a very important
aspect of preventive medical science. This paper proposes a new coupled
loading-rate hypothesis for the traumatic brain injury (TBI), which states that
the main cause of the TBI is an external Euclidean jolt, or SE(3)-jolt, an
impulsive loading that strikes the head in several coupled degrees-of-freedom
simultaneously. To show this, based on the previously defined covariant force
law, we formulate the coupled Newton-Euler dynamics of brain's micro-motions
within the cerebrospinal fluid and derive from it the coupled SE(3)-jolt
dynamics. The SE(3)-jolt is a cause of the TBI in two forms of brain's rapid
discontinuous deformations: translational dislocations and rotational
disclinations. Brain's dislocations and disclinations, caused by the
SE(3)-jolt, are described using the Cosserat multipolar viscoelastic continuum
brain model.
Keywords: Traumatic brain injuries, coupled loading-rate hypothesis,
Euclidean jolt, coupled Newton-Euler dynamics, brain's dislocations and
disclinationsComment: 18 pages, 1 figure, Late
The DNA Damage Response Pathway Contributes to the Stability of Chromosome III Derivatives Lacking Efficient Replicators
In eukaryotic chromosomes, DNA replication initiates at multiple origins. Large inter-origin gaps arise when several adjacent origins fail to fire. Little is known about how cells cope with this situation. We created a derivative of Saccharomyces cerevisiae chromosome III lacking all efficient origins, the 5ORIΔ-ΔR fragment, as a model for chromosomes with large inter-origin gaps. We used this construct in a modified synthetic genetic array screen to identify genes whose products facilitate replication of long inter-origin gaps. Genes identified are enriched in components of the DNA damage and replication stress signaling pathways. Mrc1p is activated by replication stress and mediates transduction of the replication stress signal to downstream proteins; however, the response-defective mrc1AQ allele did not affect 5ORIΔ-ΔR fragment maintenance, indicating that this pathway does not contribute to its stability. Deletions of genes encoding the DNA-damage-specific mediator, Rad9p, and several components shared between the two signaling pathways preferentially destabilized the 5ORIΔ-ΔR fragment, implicating the DNA damage response pathway in its maintenance. We found unexpected differences between contributions of components of the DNA damage response pathway to maintenance of ORIΔ chromosome derivatives and their contributions to DNA repair. Of the effector kinases encoded by RAD53 and CHK1, Chk1p appears to be more important in wild-type cells for reducing chromosomal instability caused by origin depletion, while Rad53p becomes important in the absence of Chk1p. In contrast, RAD53 plays a more important role than CHK1 in cell survival and replication fork stability following treatment with DNA damaging agents and hydroxyurea. Maintenance of ORIΔ chromosomes does not depend on homologous recombination. These observations suggest that a DNA-damage-independent mechanism enhances ORIΔ chromosome stability. Thus, components of the DNA damage response pathway contribute to genome stability, not simply by detecting and responding to DNA template damage, but also by facilitating replication of large inter-origin gaps
Metal-responsive gene regulation and metal transport in Helicobacter species
Helicobacter species are among the most successful colonizers of the mammalian gastrointestinal and hepatobiliary tract. Colonization is usually lifelong, indicating that Helicobacter species have evolved intricate mechanisms of dealing with stresses encountered during colonization of host tissues, like restriction of essential metal ions. The recent availability of genome sequences of the human gastric pathogen Helicobacter pylori, the murine enterohepatic pathogen Helicobacter hepaticus and the unannotated genome sequence of the ferret gastric pathogen Helicobacter mustelae has allowed for comparitive genome analyses. In this review we present such analyses for metal transporters, metal-storage and metal-responsive regulators in these three Helicobacter species, and discuss possible contributions of the differences in metal metabolism in adaptation to the gastric or enterohepatic niches occupied by Helicobacter species
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
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)
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
Tracking SARS-CoV-2 mutations and variants through the COG-UK-Mutation Explorer
COG-UK Mutation Explorer (COG-UK-ME, https://sars2.cvr.gla.ac.uk/cog-uk/—last accessed date 16 March 2022) is a web resource that displays knowledge and analyses on SARS-CoV-2 virus genome mutations and variants circulating in the UK, with a focus on the observed amino acid replacements that have an antigenic role in the context of the human humoral and cellular immune response. This analysis is based on more than 2 million genome sequences (as of March 2022) for UK SARS-CoV-2 data held in the CLIMB-COVID centralised data environment. COG-UK-ME curates these data and displays analyses that are cross-referenced to experimental data collated from the primary literature. The aim is to track mutations of immunological importance that are accumulating in current variants of concern and variants of interest that could alter the neutralising activity of monoclonal antibodies (mAbs), convalescent sera, and vaccines. Changes in epitopes recognised by T cells, including those where reduced T cell binding has been demonstrated, are reported. Mutations that have been shown to confer SARS-CoV-2 resistance to antiviral drugs are also included. Using visualisation tools, COG-UK-ME also allows users to identify the emergence of variants carrying mutations that could decrease the neutralising activity of both mAbs present in therapeutic cocktails, e.g. Ronapreve. COG-UK-ME tracks changes in the frequency of combinations of mutations and brings together the curated literature on the impact of those mutations on various functional aspects of the virus and therapeutics. Given the unpredictable nature of SARS-CoV-2 as exemplified by yet another variant of concern, Omicron, continued surveillance of SARS-CoV-2 remains imperative to monitor virus evolution linked to the efficacy of therapeutics
- …