
Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown
Published: June 7, 2024
Language: Английский
Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown
Published: June 7, 2024
Language: Английский
Cells, Journal Year: 2024, Volume and Issue: 13(15), P. 1262 - 1262
Published: July 26, 2024
Major depressive disorder (MDD) is a complex and devastating illness that affects people of all ages. Despite the large use antidepressants in current medical practice, neither their mechanisms action nor aetiology MDD are completely understood. Experimental evidence supports involvement Parvalbumin-positive GABAergic neurons (PV-neurons) pathogenesis MDD. DLX5 DLX6 (DLX5/6) encode two homeodomain transcription factors involved cortical differentiation function. In mouse, level expression these genes correlated with density PV-neurons anxiety-like behaviours. The same genomic region generates lncRNA DLX6-AS1, which, humans, participates regulatory module downregulated schizophrenia ASD. Here, we show levels Dlx5/6 adult mouse brain immobility time forced swim test, which used to measure depressive-like We administration antidepressant fluoxetine (Flx) normal mice induces, within 24 h, rapid stable reduction Dlx5, Dlx6 Dlx6-AS1 cerebral cortex through activation TrkB-CREB pathway. Dlx5 overexpression counteracts effects induced by Flx treatment. Our findings one short-term neurons, turn, has direct consequences on PV behavioural profiles. Variants DLX5/6 network could be implicated predisposition depression variability patients’ response
Language: Английский
Citations
1Briefings in Bioinformatics, Journal Year: 2023, Volume and Issue: 24(6)
Published: Sept. 22, 2023
Abstract Inference of gene regulatory network (GRN) from expression profiles has been a central problem in systems biology and bioinformatics the past decades. The tremendous emergency single-cell RNA sequencing (scRNA-seq) data brings new opportunities challenges for GRN inference: extensive dropouts complicated noise structure may also degrade performance contemporary models. Thus, there is an urgent need to develop more accurate methods inference while considering at same time. In this paper, we extend traditional structural equation modeling (SEM) framework by flexible strategy, namely use Gaussian mixtures approximate complex stochastic nature biological system, since mixture can be arguably served as universal approximation any continuous distributions. proposed non-Gaussian SEM called NG-SEM, which optimized iteratively performing Expectation-Maximization algorithm weighted least-squares method. Moreover, Akaike Information Criteria adopted select number components mixture. To probe accuracy stability our method, design comprehensive variate control experiments systematically investigate NG-SEM under various conditions, including simulations real sets. Results on synthetic demonstrate that strategy improve model results sets verify outperforms other five state-of-the-art methods.
Language: Английский
Citations
2Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown
Published: June 7, 2024
Language: Английский
Citations
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