Biology subjects

van den Bosch, A.

Publications and source records attributed to van den Bosch, A..

5 recordsLinked to original sources

bioRxiv2024

Mitochondrial reverse electron transport in myeloid cells perpetuates neuroinflammation

Sustained smouldering, or low grade, activation of myeloid cells is a common hallmark of several chronic neurological diseases, including multiple sclerosis (MS)1. Distinct metabolic and mitochondrial features guide the activation and the diverse functional states of myeloid cells2. However, how these metabolic features act to perpetuate neuroinflammation is currently unknown. Using a multiomics approach, we identified a new molecular signature that perpetuates the activation of myeloid cells through mitochondrial complex II (CII) and I (CI) activity driving reverse electron transport (RET) and the production of reactive oxygen species (ROS). Blocking RET in pro-inflammatory myeloid cells protected the central nervous system (CNS) against neurotoxic damage and improved functional outcomes in animal disease models in vivo. Our data show that RET in myeloid cells is a potential new therapeutic target to foster neuroprotection in smouldering inflammatory CNS disorders3.

neuroscience↗

bioRxiv2023

Profiling of microglia nodules in multiple sclerosis reveals propensity for lesion formation

Clusters of ramified HLA-DR+ cells, known as microglia nodules, are associated with brain pathology. Here we investigated if microglia nodules in the normal-appearing white matter (NAWM) of multiple sclerosis (MS) are different from microglia nodules in white matter (WM) in stroke and whether they may relate to the start of demyelinating MS lesions. We studied the relation between microglia nodules and pathological severity in an MS autopsy cohort (n=167), and we compared frequency, size, and gene expression of microglia nodules in MS (n=7) and stroke (n=7). MS donors with microglia nodules (64%) had a higher lesion load and a higher proportion of active lesions compared to donors without microglia nodules (36%). We found altered expression of genes in microglia nodules in MS compared to stroke, including genes previously shown to be upregulated in MS lesions. Genes associated with lipid metabolism, presence and proliferation of T and B cells, production of and response to immunoglobulins and cytokines (specifically TNF and IFN), activation of the complement cascade, and metabolic stress were upregulated. Using immunohistochemistry, we confirmed that in MS, more than in stroke, microglia nodules are associated with membrane attack complexes, have phagocytosed oxidized phospholipids, and have a tubular mitochondrial network reflecting increased metabolic activity. Furthermore, in MS, some nodules encapsulated partially demyelinated axons. Taken together, we propose that activation of some microglia nodules in MS by pro-inflammatory cytokines and immunoglobulins in combination with phagocytosis of oxidized phospholipids may lead to a volatile phenotype prone to form MS lesions.

neuroscience↗

bioRxiv2020

Words in context: tracking context-processing during language comprehension using computational language models and MEG

The meaning of a word depends on its lexical semantics and on the context in which it is embedded. At the basis of this lays the distinction between lexical retrieval and integration, two basic operations supporting language comprehension. In this paper, we investigate how lexical retrieval and integration are implemented in the brain by comparing MEG activity to word representations generated by computational language models. We test both non-contextualized embeddings, representing words independently from their context, and contextualized embeddings, which instead integrate contextual information in their representations. Using representational similarity analysis over cortical regions and over time, we observed that brain activity in the left anterior temporal pole and inferior frontal regions shows higher similarity with contextualized word embeddings compared to non-contextualized embeddings, between 300 and 500 ms after word presentation. On the other hand, non-contextualized word embeddings show higher similarity with brain activity in the left lateral and anterior temporal lobe at earlier latencies - areas and latencies related to lexical retrieval. Our results highlight how lexical retrieval and context integration can be tracked in the brain using word embeddings obtained with computational models. These results also suggest that the distinction between lexical retrieval and integration might be framed in terms of context-independent and contextualized representations.

neuroscience↗

bioRxiv2019

Supramodal sentence processing in the human brain: fMRI evidence for the influence of syntactic complexity in more than 200 participants

This study investigated two questions. One is to which degree sentence processing beyond single words is independent of the input modality (speech vs. reading). The second question is which parts of the network recruited by both modalities is sensitive to syntactic complexity. These questions were investigated by having more than 200 participants read or listen to well-formed sentences or series of unconnected words. A largely left-hemisphere fronto-temporoparietal network was found to be supramodal in nature, i.e. independent of input modality. In addition, the left inferior frontal gyrus (LIFG) and the left posterior middle temporal gyrus (LpMTG) were most clearly associated with left-branching complexity. The left anterior middle temporal gyrus (LaMTG) showed the greatest sensitivity to sentences that differed in right-branching complexity. Moreover, activity in LIFG and LpMTG increased from sentence onset to end, in parallel with an increase of the left-branching complexity. While LIFG, bilateral anterior and posterior MTG and left inferior parietal lobe (LIPL) all contribute to the supramodal unification processes, the results suggest that these regions differ in their respective contributions to syntactic complexity related processing. The consequences of these findings for neurobiological models of language processing are discussed.

neuroscience↗

bioRxiv2018

Frequency-specific brain dynamics related to prediction during language comprehension

The brains remarkable capacity to process spoken language virtually in real time requires fast and efficient information processing machinery. In this study, we investigated how frequency-specific brain dynamics relate to models of probabilistic language prediction during auditory narrative comprehension. We recorded MEG activity while participants were listening to auditory stories in Dutch. Using trigram statistical language models, we estimated for every word in a story its conditional probability of occurrence. On the basis of word probabilities, we computed how unexpected the current word is given its context (word perplexity) and how (un)predictable the current linguistic context is (word entropy). We then evaluated whether source-reconstructed MEG oscillations at different frequency bands are modulated as a function of these language processing metrics. We show that theta-band source dynamics are increased in high relative to low entropy states, likely reflecting lexical computations. Beta-band dynamics are increased in situations of low word entropy and perplexity possibly reflecting maintenance of ongoing cognitive context. These findings lend support to the idea that the brain engages in the active generation and evaluation of predicted language based on the statistical properties of the input signal.

neuroscience↗