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1.
Brain Behav Immun ; 119: 333-350, 2024 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-38561095

RESUMEN

Neonatal sepsis remains one of the leading causes of mortality in newborns. Several brainstem-regulated physiological processes undergo disruption during neonatal sepsis. Mechanistic knowledge gaps exist at the interplay between metabolism and immune activation to brainstem neural circuits and pertinent physiological functions in neonates. To delineate this association, we induced systemic inflammation either by TLR4 (LPS) or TLR1/2 (PAM3CSK4) ligand administration in postnatal day 5 mice (PD5). Our findings show that LPS and PAM3CSK4 evoke substantial changes in respiration and metabolism. Physiological trade-offs led to hypometabolic-hypothermic responses due to LPS, but not PAM3CSK4, whereas to both TLR ligands blunted respiratory chemoreflexes. Neuroinflammatory pathways modulation in brainstem showed more robust effects in LPS than PAM3CSK4. Brainstem neurons, microglia, and astrocyte gene expression analyses showed unique responses to TLR ligands. PAM3CSK4 did not significantly modulate gene expression changes in GLAST-1 positive brainstem astrocytes. PD5 pups receiving PAM3CSK4 failed to maintain a prolonged metabolic state repression, which correlated to enhanced gasping latency and impaired autoresuscitation during anoxic chemoreflex challenges. In contrast, LPS administered pups showed no significant changes in anoxic chemoreflex. Electrophysiological studies from brainstem slices prepared from pups exposed to either TLR4 or PAM3CSK4 showed compromised transmission between preBötzinger complex and Hypoglossal as an exclusive response to the TLR1/2 ligand. Spatial gene expression analysis demonstrated a region-specific modulation of PAM3CSK4 within the raphe nucleus relative to other anatomical sites evaluated. Our findings suggest that metabolic changes due to inflammation might be a crucial tolerance mechanism for neonatal sepsis preserving neural control of breathing.


Asunto(s)
Animales Recién Nacidos , Tronco Encefálico , Lipopolisacáridos , Sepsis Neonatal , Receptor Toll-Like 1 , Receptor Toll-Like 2 , Receptor Toll-Like 4 , Animales , Ratones , Receptor Toll-Like 4/metabolismo , Lipopolisacáridos/farmacología , Receptor Toll-Like 2/metabolismo , Sepsis Neonatal/metabolismo , Tronco Encefálico/metabolismo , Receptor Toll-Like 1/metabolismo , Lipopéptidos/farmacología , Respiración/efectos de los fármacos , Ratones Endogámicos C57BL , Neuronas/metabolismo , Astrocitos/metabolismo , Masculino , Ligandos , Microglía/metabolismo , Femenino , Inflamación/metabolismo
2.
Comput Struct Biotechnol J ; 20: 4600-4617, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-36090815

RESUMEN

Spatially resolved transcriptomics provides a new way to define spatial contexts and understand the pathogenesis of complex human diseases. Although some computational frameworks can characterize spatial context via various clustering methods, the detailed spatial architectures and functional zonation often cannot be revealed and localized due to the limited capacities of associating spatial information. We present RESEPT, a deep-learning framework for characterizing and visualizing tissue architecture from spatially resolved transcriptomics. Given inputs such as gene expression or RNA velocity, RESEPT learns a three-dimensional embedding with a spatial retained graph neural network from spatial transcriptomics. The embedding is then visualized by mapping into color channels in an RGB image and segmented with a supervised convolutional neural network model. Based on a benchmark of 10x Genomics Visium spatial transcriptomics datasets on the human and mouse cortex, RESEPT infers and visualizes the tissue architecture accurately. It is noteworthy that, for the in-house AD samples, RESEPT can localize cortex layers and cell types based on pre-defined region- or cell-type-enriched genes and furthermore provide critical insights into the identification of amyloid-beta plaques in Alzheimer's disease. Interestingly, in a glioblastoma sample analysis, RESEPT distinguishes tumor-enriched, non-tumor, and regions of neuropil with infiltrating tumor cells in support of clinical and prognostic cancer applications.

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