Reply to : Proofreading deficiency in mitochondrial DNA polymerase does not affect total dNTP pools in mouse embryos

Non peer reviewe

Translating land cover/land use classifications to habitat taxonomies for landscape monitoring: A Mediterranean assessment

Periodic monitoring of biodiversity changes at a landscape scale constitutes a key issue for conservation managers. Earth observation (EO) data offer a potential solution, through direct or indirect mapping of species or habitats. Most national and international programs rely on the use of land cover (LC) and/or land use (LU) classification systems. Yet, these are not as clearly relatable to biodiversity in comparison to habitat classifications, and provide less scope for monitoring. While a conversion from LC/LU classification to habitat classification can be of great utility, differences in definitions and criteria have so far limited the establishment of a unified approach for such translation between these two classification systems. Focusing on five Mediterranean NATURA 2000 sites, this paper considers the scope for three of the most commonly used global LC/LU taxonomies—CORINE Land Cover, the Food and Agricultural Organisation (FAO) land cover classification system (LCCS) and the International Geosphere-Biosphere Programme to be translated to habitat taxonomies. Through both quantitative and expert knowledge based qualitative analysis of selected taxonomies, FAO-LCCS turns out to be the best candidate to cope with the complexity of habitat description and provides a framework for EO and in situ data integration for habitat mapping, reducing uncertainties and class overlaps and bridging the gap between LC/LU and habitats domains for landscape monitoring—a major issue for conservation. This study also highlights the need to modify the FAO-LCCS hierarchical class description process to permit the addition of attributes based on class-specific expert knowledge to select multi-temporal (seasonal) EO data and improve classification. An application of LC/LU to habitat mapping is provided for a coastal Natura 2000 site with high classification accuracy as a result

Validated respiratory drug deposition predictions from 2D and 3D medical images with statistical shape models and convolutional neural networks

37 pages main text (including frontmatter). 9 figures. Additional supplementary material. [v1] Thu, 2 Mar 2023 07:47:07 UTC (14,131 KB). The file archived on this institutional repository is an arXiv preprint. It may not have been certified by peer review.For the one billion sufferers of respiratory disease, managing their disease with inhalers crucially influences their quality of life. Generic treatment plans could be improved with the aid of computational models that account for patient-specific features such as breathing pattern, lung pathology and morphology. Therefore, we aim to develop and validate an automated computational framework for patient-specific deposition modelling. To that end, an image processing approach is proposed that could produce 3D patient respiratory geometries from 2D chest X-rays and 3D CT images. We evaluated the airway and lung morphology produced by our image processing framework, and assessed deposition compared to in vivo data. The 2D-to-3D image processing reproduces airway diameter to 9% median error compared to ground truth segmentations, but is sensitive to outliers of up to 33% due to lung outline noise. Predicted regional deposition gave 5% median error compared to in vivo measurements. The proposed framework is capable of providing patient-specific deposition measurements for varying treatments, to determine which treatment would best satisfy the needs imposed by each patient (such as disease and lung/airway morphology). Integration of patient-specific modelling into clinical practice as an additional decision-making tool could optimise treatment plans and lower the burden of respiratory diseases.Simulations reported in this study were performed on Oracle cloud computing platform, funded by Open Clouds Research Environments (OCRE) ‘Cloud Funding for Research’. JW was funded by a 2019 PhD Scholarship from the Carnegie-Trust for the Universities of Scotland. The in vivo deposition data used in this study was obtained from a project sponsored by Air Liquide

Validated respiratory drug deposition predictions from 2D and 3D medical images with statistical shape models and convolutional neural networks

Data Availability: The data and code underlying the results presented in the study are available from https://doi.org/10.5281/zenodo.10512507 which provides a static link to our git repository (https://github.com/jvwilliams23/respiratory2Dto3Dpaper).Supporting information is available online at: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0297437#sec017 .For the one billion sufferers of respiratory disease, managing their disease with inhalers crucially influences their quality of life. Generic treatment plans could be improved with the aid of computational models that account for patient-specific features such as breathing pattern, lung pathology and morphology. Therefore, we aim to develop and validate an automated computational framework for patient-specific deposition modelling. To that end, an image processing approach is proposed that could produce 3D patient respiratory geometries from 2D chest X-rays and 3D CT images. We evaluated the airway and lung morphology produced by our image processing framework, and assessed deposition compared to in vivo data. The 2D-to-3D image processing reproduces airway diameter to 9% median error compared to ground truth segmentations, but is sensitive to outliers of up to 33% due to lung outline noise. Predicted regional deposition gave 5% median error compared to in vivo measurements. The proposed framework is capable of providing patient-specific deposition measurements for varying treatments, to determine which treatment would best satisfy the needs imposed by each patient (such as disease and lung/airway morphology). Integration of patient-specific modelling into clinical practice as an additional decision-making tool could optimise treatment plans and lower the burden of respiratory diseases.Funding: Simulations reported in this study were performed on Oracle cloud computing platform, funded by Open Clouds Research Environments (OCRE) ‘Cloud Funding for Research’. JW was funded by a 2019 PhD Scholarship from the Carnegie-Trust for the Universities of Scotland. The in vivo deposition data used in this study was obtained from a project sponsored by Air Liquide

mtDNA Mutagenesis Disrupts Pluripotent Stem Cell Function by Altering Redox Signaling

mtDNA mutagenesis in somatic stem cells leads to their dysfunction and to progeria in mouse. The mechanism was proposed to involve modification of reactive oxygen species (ROS)/redox signaling. We studied the effect of mtDNA mutagenesis on reprogramming and stemness of pluripotent stem cells (PSCs) and show that PSCs select against specific mtDNA mutations, mimicking germline and promoting mtDNA integrity despite their glycolytic metabolism. Furthermore, mtDNA mutagenesis is associated with an increase in mitochondrial H2O2, reduced PSC reprogramming efficiency, and self-renewal. Mitochondria-targeted ubiquinone, MitoQ, and N-acetyl-L-cysteine efficiently rescued these defects, indicating that both reprogramming efficiency and stemness are modified by mitochondrial ROS. The redox sensitivity, however, rendered PSCs and especially neural stem cells sensitive to MitoQ toxicity. Our results imply that stem cell compartment warrants special attention when the safety of new antioxidants is assessed and point to an essential role for mitochondrial redox signaling in maintaining normal stem cell function.Peer reviewe

Direct Repeat 6 from Human Herpesvirus-6B Encodes a Nuclear Protein that Forms a Complex with the Viral DNA Processivity Factor p41

The SalI-L fragment from human herpesvirus 6A (HHV-6A) encodes a protein DR7 that has been reported to produce fibrosarcomas when injected into nude mice, to transform NIH3T3 cells, and to interact with and inhibit the function of p53. The homologous gene in HHV-6B is dr6. Since p53 is deregulated in both HHV-6A and -6B, we characterized the expression of dr6 mRNA and the localization of the translated protein during HHV-6B infection of HCT116 cells. Expression of mRNA from dr6 was inhibited by cycloheximide and partly by phosphonoacetic acid, a known characteristic of herpesvirus early/late genes. DR6 could be detected as a nuclear protein at 24 hpi and accumulated to high levels at 48 and 72 hpi. DR6 located in dots resembling viral replication compartments. Furthermore, a novel interaction between DR6 and the viral DNA processivity factor, p41, could be detected by confocal microscopy and by co-immunoprecipitation analysis. In contrast, DR6 and p53 were found at distinct subcellular locations. Together, our data imply a novel function of DR6 during HHV-6B replication

MtDNA mutagenesis impairs elimination of mitochondria during erythroid maturation leading to enhanced erythrocyte destruction

Haematopoietic progenitor cells show special sensitivity to mitochondrial DNA (mtDNA) mutagenesis, which suggests that increased mtDNA mutagenesis could underlie anemias. Here we show that elevated mtDNA mutagenesis in mice with a proof-reading deficient mtDNA polymerase (PolG) leads to incomplete mitochondrial clearance, with asynchronized iron loading in erythroid precursors, and increased total and free cellular iron content. The resulting Fenton chemistry leads to oxidative damage and premature destruction of erythrocytes by splenic macrophages. Our data indicate that mitochondria actively contribute to their own elimination in reticulocytes and modulate iron loading. Asynchrony of this sequence of events causes severe mitochondrial anaemia by depleting the organism of red blood cells and the bone marrow of iron. Our findings account for the anaemia development in a progeroid mouse model and may have direct relevance to the anemias associated with human mitochondrial disease and ageing.Peer reviewe