Analyzing various models of Circadian Clock and Cell Cycle coupling

The daily rhythm can influence the proliferation rate of many cell types. In the mammalian system the transcription of the cell cycle regulatory protein Wee1 is controlled by the circadian clock. Zamborszky et al. (2007) present a computational model coupling the cell cycle and circadian rhythm, showing that this coupling can lead to multimodal cell cycle time distributions. Biological data points to additional couplings, including a link back from the cell cycle to the circadian clock. Proper modelling of this coupling requires a more detailed description of both parts of the model. Hence, we aim at further extending and analysing earlier models using a combination of modelling techniques and computer software, including CoSBI lab, BIOCHAM, and GINsim

BIOlogical Factors that Limit sustAined Remission in rhEumatoid arthritis (the BIO-FLARE study): protocol for a non-randomised longitudinal cohort study

Background Our knowledge of immune-mediated inflammatory disease (IMID) aetiology and pathogenesis has improved greatly over recent years, however, very little is known of the factors that trigger disease relapses (flares), converting diseases from inactive to active states. Focussing on rheumatoid arthritis (RA), the challenge that we will address is why IMIDs remit and relapse. Extrapolating from pathogenetic factors involved in disease initiation, new episodes of inflammation could be triggered by recurrent systemic immune dysregulation or locally by factors within the joint, either of which could be endorsed by overarching epigenetic factors or changes in systemic or localised metabolism. Methods The BIO-FLARE study is a non-randomised longitudinal cohort study that aims to enrol 150 patients with RA in remission on a stable dose of non-biologic disease-modifying anti-rheumatic drugs (DMARDs), who consent to discontinue treatment. Participants stop their DMARDs at time 0 and are offered an optional ultrasound-guided synovial biopsy. They are studied intensively, with blood sampling and clinical evaluation at weeks 0, 2, 5, 8, 12 and 24. It is anticipated that 50% of participants will have a disease flare, whilst 50% remain in drug-free remission for the study duration (24 weeks). Flaring participants undergo an ultrasound-guided synovial biopsy before reinstatement of previous treatment. Blood samples will be used to investigate immune cell subsets, their activation status and their cytokine profile, autoantibody profiles and epigenetic profiles. Synovial biopsies will be examined to profile cell lineages and subtypes present at flare. Blood, urine and synovium will be examined to determine metabolic profiles. Taking into account all generated data, multivariate statistical techniques will be employed to develop a model to predict impending flare in RA, highlighting therapeutic pathways and informative biomarkers. Despite initial recruitment to time and target, the SARS-CoV-2 pandemic has impacted significantly, and a decision was taken to close recruitment at 118 participants with complete data. Discussion This study aims to investigate the pathogenesis of flare in rheumatoid arthritis, which is a significant knowledge gap in our understanding, addressing a major unmet patient need

Neutrophil Responses to Sterile Implant Materials

In vivo implantation of sterile materials and devices results in a foreign body immune response leading to fibrosis of implanted material. Neutrophils, one of the first immune cells to be recruited to implantation sites, have been suggested to contribute to the establishment of the inflammatory microenvironment that initiates the fibrotic response. However, the precise numbers and roles of neutrophils in response to implanted devices remains unclear. Using a mouse model of peritoneal microcapsule implantation, we show 30–500 fold increased neutrophil presence in the peritoneal exudates in response to implants. We demonstrate that these neutrophils secrete increased amounts of a variety of inflammatory cytokines and chemokines. Further, we observe that they participate in the foreign body response through the formation of neutrophil extracellular traps (NETs) on implant surfaces. Our results provide new insight into neutrophil function during a foreign body response to peritoneal implants which has implications for the development of biologically compatible medical devices

Combinatorial hydrogel library enables identification of materials that mitigate the foreign body response in primates

The foreign body response is an immune-mediated reaction that can lead to the failure of implanted medical devices and discomfort for the recipient. There is a critical need for biomaterials that overcome this key challenge in the development of medical devices. Here we use a combinatorial approach for covalent chemical modification to generate a large library of variants of one of the most widely used hydrogel biomaterials, alginate. We evaluated the materials in vivo and identified three triazole-containing analogs that substantially reduce foreign body reactions in both rodents and, for at least 6 months, in non-human primates. The distribution of the triazole modification creates a unique hydrogel surface that inhibits recognition by macrophages and fibrous deposition. In addition to the utility of the compounds reported here, our approach may enable the discovery of other materials that mitigate the foreign body response.Leona M. and Harry B. Helmsley Charitable Trust (3-SRA-2014-285-M-R)United States. National Institutes of Health (EB000244)United States. National Institutes of Health (EB000351)United States. National Institutes of Health (DE013023)United States. National Institutes of Health (CA151884)United States. National Institutes of Health (P41EB015871-27)National Cancer Institute (U.S.) (P30-CA14051

A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns.

In cancer, the primary tumour's organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, we train a deep learning classifier to predict cancer type based on patterns of somatic passenger mutations detected in whole genome sequencing (WGS) of 2606 tumours representing 24 common cancer types produced by the PCAWG Consortium. Our classifier achieves an accuracy of 91% on held-out tumor samples and 88% and 83% respectively on independent primary and metastatic samples, roughly double the accuracy of trained pathologists when presented with a metastatic tumour without knowledge of the primary. Surprisingly, adding information on driver mutations reduced accuracy. Our results have clinical applicability, underscore how patterns of somatic passenger mutations encode the state of the cell of origin, and can inform future strategies to detect the source of circulating tumour DNA

Signatures of mutational processes in human cancer.

All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, 'kataegis', is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy

Trace elements at the intersection of marine biological and geochemical evolution

Life requires a wide variety of bioessential trace elements to act as structural components and reactive centers in metalloenzymes. These requirements differ between organisms and have evolved over geological time, likely guided in some part by environmental conditions. Until recently, most of what was understood regarding trace element concentrations in the Precambrian oceans was inferred by extrapolation, geochemical modeling, and/or genomic studies. However, in the past decade, the increasing availability of trace element and isotopic data for sedimentary rocks of all ages has yielded new, and potentially more direct, insights into secular changes in seawater composition – and ultimately the evolution of the marine biosphere. Compiled records of many bioessential trace elements (including Ni, Mo, P, Zn, Co, Cr, Se, and I) provide new insight into how trace element abundance in Earth's ancient oceans may have been linked to biological evolution. Several of these trace elements display redox-sensitive behavior, while others are redox-sensitive but not bioessential (e.g., Cr, U). Their temporal trends in sedimentary archives provide useful constraints on changes in atmosphere-ocean redox conditions that are linked to biological evolution, for example, the activity of oxygen-producing, photosynthetic cyanobacteria. In this review, we summarize available Precambrian trace element proxy data, and discuss how temporal trends in the seawater concentrations of specific trace elements may be linked to the evolution of both simple and complex life. We also examine several biologically relevant and/or redox-sensitive trace elements that have yet to be fully examined in the sedimentary rock record (e.g., Cu, Cd, W) and suggest several directions for future studies

The wide-field, multiplexed, spectroscopic facility WEAVE : survey design, overview, and simulated implementation

Funding for the WEAVE facility has been provided by UKRI STFC, the University of Oxford, NOVA, NWO, Instituto de Astrofísica de Canarias (IAC), the Isaac Newton Group partners (STFC, NWO, and Spain, led by the IAC), INAF, CNRS-INSU, the Observatoire de Paris, Région Île-de-France, CONCYT through INAOE, Konkoly Observatory (CSFK), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Lund University, the Leibniz Institute for Astrophysics Potsdam (AIP), the Swedish Research Council, the European Commission, and the University of Pennsylvania.WEAVE, the new wide-field, massively multiplexed spectroscopic survey facility for the William Herschel Telescope, will see first light in late 2022. WEAVE comprises a new 2-degree field-of-view prime-focus corrector system, a nearly 1000-multiplex fibre positioner, 20 individually deployable 'mini' integral field units (IFUs), and a single large IFU. These fibre systems feed a dual-beam spectrograph covering the wavelength range 366-959 nm at R ∼ 5000, or two shorter ranges at R ∼ 20,000. After summarising the design and implementation of WEAVE and its data systems, we present the organisation, science drivers and design of a five- to seven-year programme of eight individual surveys to: (i) study our Galaxy's origins by completing Gaia's phase-space information, providing metallicities to its limiting magnitude for ∼ 3 million stars and detailed abundances for ∼ 1.5 million brighter field and open-cluster stars; (ii) survey ∼ 0.4 million Galactic-plane OBA stars, young stellar objects and nearby gas to understand the evolution of young stars and their environments; (iii) perform an extensive spectral survey of white dwarfs; (iv) survey  ∼ 400 neutral-hydrogen-selected galaxies with the IFUs; (v) study properties and kinematics of stellar populations and ionised gas in z 1 million spectra of LOFAR-selected radio sources; (viii) trace structures using intergalactic/circumgalactic gas at z > 2. Finally, we describe the WEAVE Operational Rehearsals using the WEAVE Simulator.PostprintPeer reviewe