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| 2. |
- Golparian, degn, 1984-, et al.
(author)
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Antimicrobial-resistant Neisseria gonorrhoeae in Europe in 2020 compared with in 2013 and 2018 : a retrospective genomic surveillance study
- 2024
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In: The Lancet. Microbe. - : Elsevier. - 2666-5247. ; 5:5, s. e478-e488
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Journal article (peer-reviewed)abstract
- BACKGROUND: Regular quality-assured whole-genome sequencing linked to antimicrobial resistance (AMR) and patient metadata is imperative to elucidate the shifting gonorrhoea epidemiology, both nationally and internationally. We aimed to examine the gonococcal population in the European Economic Area (EEA) in 2020, elucidate emerging and disappearing gonococcal lineages associated with AMR and patient metadata, compare with 2013 and 2018 whole-genome sequencing data, and explain changes in gonococcal AMR and gonorrhoea epidemiology.METHODS: In this retrospective genomic surveillance study, we analysed consecutive gonococcal isolates that were collected in EEA countries through the European Gonococcal Antimicrobial Surveillance Programme (Euro-GASP) in 2020, and made comparisons with Euro-GASP data from 2013 and 2018. All isolates had linked AMR data (based on minimum inhibitory concentration determination) and patient metadata. We performed whole-genome sequencing and molecular typing and AMR determinants were derived from quality-checked whole-genome sequencing data. Links between genomic lineages, AMR, and patient metadata were examined.FINDINGS: 1932 gonococcal isolates collected in 2020 in 21 EEA countries were included. The majority (81·2%, 147 of 181 isolates) of azithromycin resistance (present in 9·4%, 181 of 1932) was explained by the continued expansion of the Neisseria gonorrhoeae sequence typing for antimicrobial resistance (NG-STAR) clonal complexes (CCs) 63, 168, and 213 (with mtrD/mtrR promoter mosaic 2) and the novel NG-STAR CC1031 (semi-mosaic mtrD variant 13), associated with men who have sex with men and anorectal or oropharyngeal infections. The declining cefixime resistance (0·5%, nine of 1932) and negligible ceftriaxone resistance (0·1%, one of 1932) was largely because of the progressive disappearance of NG-STAR CC90 (with mosaic penA allele), which was predominant in 2013. No known resistance determinants for novel antimicrobials (zoliflodacin, gepotidacin, and lefamulin) were found.INTERPRETATION: Azithromycin-resistant clones, mainly with mtrD mosaic or semi-mosaic variants, appear to be stabilising at a relatively high level in the EEA. This mostly low-level azithromycin resistance might threaten the recommended ceftriaxone-azithromycin therapy, but the negligible ceftriaxone resistance is encouraging. The decreased genomic population diversity and increased clonality could be explained in part by the COVID-19 pandemic resulting in lower importation of novel strains into Europe.
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- Rifes, Pedro, et al.
(author)
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Forced LMX1A expression induces dorsal neural fates and disrupts patterning of human embryonic stem cells into ventral midbrain dopaminergic neurons
- 2024
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In: Stem Cell Reports. - 2213-6711. ; 19:6, s. 830-838
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Journal article (peer-reviewed)abstract
- The differentiation of human pluripotent stem cells into ventral mesencephalic dopaminergic (DA) fate is relevant for the treatment of Parkinson's disease. Shortcuts to obtaining DA cells through direct reprogramming often include forced expression of the transcription factor LMX1A. Although reprogramming with LMX1A can generate tyrosine hydroxylase (TH)-positive cells, their regional identity remains elusive. Using an in vitro model of early human neural tube patterning, we report that forced LMX1A expression induced a ventral-to-dorsal fate shift along the entire neuroaxis with the emergence of roof plate fates despite the presence of ventralizing molecules. The LMX1A-expressing progenitors gave rise to grafts containing roof plate-derived choroid plexus cysts as well as ectopically induced TH-positive neurons of a forebrain identity. Early activation of LMX1A prior to floor plate specification was necessary for the dorsalizing effect. Our work suggests using caution in employing LMX1A for the induction of DA fate, as this factor may generate roof plate rather than midbrain fates.
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| 4. |
- Anwer, Danish M., et al.
(author)
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A comparison of machine learning approaches for the quantification of microglial cells in the brain of mice, rats and non-human primates
- 2023
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In: PLoS ONE. - 1932-6203. ; 18:5 MAY
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Journal article (peer-reviewed)abstract
- Microglial cells are brain-specific macrophages that swiftly react to disruptive events in the brain. Microglial activation leads to specific modifications, including proliferation, morphological changes, migration to the site of insult, and changes in gene expression profiles. A change in inflammatory status has been linked to many neurodegenerative diseases such as Parkinson's disease and Alzheimer's disease. For this reason, the investigation and quantification of microglial cells is essential for better understanding their role in disease progression as well as for evaluating the cytocompatibility of novel therapeutic approaches for such conditions. In the following study we implemented a machine learning-based approach for the fast and automatized quantification of microglial cells; this tool was compared with manual quantification (ground truth), and with alternative free-ware such as the threshold-based ImageJ and the machine learning-based Ilastik. We first trained the algorithms on brain tissue obtained from rats and non-human primate immunohistochemically labelled for microglia. Subsequently we validated the accuracy of the trained algorithms in a preclinical rodent model of Parkinson's disease and demonstrated the robustness of the algorithms on tissue obtained from mice, as well as from images provided by three collaborating laboratories. Our results indicate that machine learning algorithms can detect and quantify microglial cells in all the three mammalian species in a precise manner, equipotent to the one observed following manual counting. Using this tool, we were able to detect and quantify small changes between the hemispheres, suggesting the power and reliability of the algorithm. Such a tool will be very useful for investigation of microglial response in disease development, as well as in the investigation of compatible novel therapeutics targeting the brain. As all network weights and labelled training data are made available, together with our step-by-step user guide, we anticipate that many laboratories will implement machine learning-based quantification of microglial cells in their research.
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| 5. |
- Canals, Isaac, et al.
(author)
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Astrocyte dysfunction and neuronal network hyperactivity in a CRISPR engineered pluripotent stem cell model of frontotemporal dementia
- 2023
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In: Brain Communications. - 2632-1297. ; 5:3, s. 1-16
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Journal article (peer-reviewed)abstract
- Frontotemporal dementia (FTD) is the second most prevalent type of early-onset dementia and up to 40% of cases are familial forms. One of the genes mutated in patients is CHMP2B, which encodes a protein found in a complex important for maturation of late endosomes, an essential process for recycling membrane proteins through the endolysosomal system. Here, we have generated a CHMP2B-mutated human embryonic stem cell line using genome editing with the purpose to create a human in vitro FTD disease model. To date, most studies have focused on neuronal alterations; however, we present a new co-culture system in which neurons and astrocytes are independently generated from human embryonic stem cells and combined in co-cultures. With this approach, we have identified alterations in the endolysosomal system of FTD astrocytes, a higher capacity of astrocytes to uptake and respond to glutamate, and a neuronal network hyperactivity as well as excessive synchronization. Overall, our data indicates that astrocyte alterations precede neuronal impairments and could potentially trigger neuronal network changes, indicating the important and specific role of astrocytes in disease development.
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| 7. |
- Gubinelli, F., et al.
(author)
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Characterisation of functional deficits induced by AAV overexpression of alpha-synuclein in rats
- 2023
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In: Current Research in Neurobiology. - : Elsevier BV. - 2665-945X. ; 4
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Journal article (peer-reviewed)abstract
- Background: In the last decades different preclinical animal models of Parkinson's disease (PD) have been generated, aiming to mimic the progressive neuronal loss of midbrain dopaminergic (DA) cells as well as motor and non-motor impairment. Among all the available models, AAV-based models of human alpha-synuclein (h-aSYN) overexpression are promising tools for investigation of disease progression and therapeutic interventions. Objectives: The goal with this work was to characterise the impairment in motor and non-motor domains following nigrostriatal overexpression of h-aSYN and correlate the behavioural deficits with histological assessment of associated pathology. Methods: Intranigral injection of an AAV9 expressing h-aSYN was compared with untreated animals, 6-OHDA and AAV9 expressing either no transgene or GFP. The animals were assessed on a series of simple and complex behavioural tasks probing motor and non-motor domains. Post-mortem neuropathology was analysed using immunohistochemical methods. Results: Overexpression of h-aSYN led to progressive degeneration of DA neurons of the SN and axonal terminals in the striatum (STR). We observed extensive nigral and striatal pathology, resembling that of human PD brain, as well as the development of stable progressive deficit in simple motor tasks and in non-motor domains such as deficits in motivation and lateralised neglect. Conclusions: In the present work we characterized a rat model of PD that closely resembles human PD pathology at the histological and behavioural level. The correlation of cell loss with behavioural performance enables the selection of rats which can be used in neuroprotective or neurorestorative therapies.
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| 8. |
- Amici, Julia, et al.
(author)
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A Roadmap for Transforming Research to Invent the Batteries of the Future Designed within the European Large Scale Research Initiative BATTERY 2030
- 2022
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In: Advanced Energy Materials. - : John Wiley & Sons. - 1614-6832 .- 1614-6840. ; 12:17
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Research review (peer-reviewed)abstract
- This roadmap presents the transformational research ideas proposed by "BATTERY 2030+," the European large-scale research initiative for future battery chemistries. A "chemistry-neutral" roadmap to advance battery research, particularly at low technology readiness levels, is outlined, with a time horizon of more than ten years. The roadmap is centered around six themes: 1) accelerated materials discovery platform, 2) battery interface genome, with the integration of smart functionalities such as 3) sensing and 4) self-healing processes. Beyond chemistry related aspects also include crosscutting research regarding 5) manufacturability and 6) recyclability. This roadmap should be seen as an enabling complement to the global battery roadmaps which focus on expected ultrahigh battery performance, especially for the future of transport. Batteries are used in many applications and are considered to be one technology necessary to reach the climate goals. Currently the market is dominated by lithium-ion batteries, which perform well, but despite new generations coming in the near future, they will soon approach their performance limits. Without major breakthroughs, battery performance and production requirements will not be sufficient to enable the building of a climate-neutral society. Through this "chemistry neutral" approach a generic toolbox transforming the way batteries are developed, designed and manufactured, will be created.
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| 9. |
- Bethlehem, RAI, et al.
(author)
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Brain charts for the human lifespan
- 2022
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In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 604:7906, s. 525-
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Journal article (peer-reviewed)abstract
- Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data (http://www.brainchart.io/). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.
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