Biology subjects

Di, S.

Publications and source records attributed to Di, S..

3 recordsLinked to original sources

bioRxiv2025

Energy inefficiency underpinning brain state dysregulation in individuals with major depressive disorder

Disruptions in brain state dynamics are a hallmark of major depressive disorder (MDD), yet their underlying mechanisms remain unclear. This study, building on network control theory, revealed that decreased state stability and increased state-switching frequency in MDD are driven by elevated energy costs and reduced control stability, indicating energy inefficiency. Key brain regions, including the left dorsolateral prefrontal cortex, exhibited impaired energy regulation capacity, and these region-specific energy patterns were correlated with depressive symptom severity. Neurotransmitter and gene expression association analyses linked these energy deficits to intrinsic biological factors, notably the 5-HT2a receptor and excitatory-inhibitory balance. These findings shed light on the energetic mechanism underlying brain state dysregulation in MDD and its associated biological underpinnings, highlighting brain energy dynamics as a potential biomarker by which to explore therapeutic targets and advance precise interventions for restoring healthy brain dynamics in depression.

neuroscience↗

bioRxiv2025

Physical Activity and Depressive Mood Shared the Structural Connectivity between Motor and Reward Network: a population-based study from the UK Biobank

BackgroundExercise has been revealed to leave a positive effect on alleviating depressive symptoms by various existing studies. However, the neural basis behind this phenomenon remains unknown, as well as its underlying biological mechanism.AimsUsing a large neuroimaging cohort from UK Biobank, this study aimed to identify structural connectivity (SC) patterns simultaneously linked with physical activity and depression, as well as its biological interpretation.Method492 participants with major depression disorder (MDD) and 535 healthy controls (HC) were extracted from the UK Biobank dataset. Partial least squares regression was first utilized to explore a replicable SC pattern simultaneously associated with physical activity and depressive mood. The neuromaps toolbox was applied to interpret the biological ontologies of the identified SC pattern. Neuroimaging-transcriptome association and enrichment analyses were conducted to explore its underlying genetic basis, pathways and cell types. The reproducibility and generalizability were tested on another independent MDD dataset (N=3,496) and bipolar disorder (BD) dataset (N=81).ResultsA SC pattern linked with exercise was identified to be both significantly correlated with depressive mood and group discriminative between MDDs and HCs, which primarily located between the motor-related regions and reward-related regions. This pattern was associated with multiple neurotransmitter receptors, such as serotonin and GABA receptors, and enriched in pathways like synaptic signaling and astrocytes cell type. The SC pattern and genetic results were also replicated in another independent MDD dataset and present commonalities with BD.ConclusionsThis study not only initially identified a reproducible shared SC pattern between physical activity and depressive mood, but also elucidated the underlying biological mechanisms, which enhanced our understanding of how exercise helps alleviate depression and may inform the development of novel neuromodulation targets.

neuroscience↗

bioRxiv2024

Mapping Pesticide-Induced Metabolic Alterations in Human Gut Bacteria

Pesticides can modulate gut microbiota (GM) composition, but their specific effects on GM remain largely elusive. Our study demonstrated that pesticides inhibit or promote growth in various GM species, even at low concentrations, and can accumulate in GM to prolong their presence in the host. Meanwhile, the pesticide induced changes in GM composition are associated with significant alterations in gut bacterial metabolism that reflected by the changes of hundreds of metabolites. We generated a pesticide-GM-metabolites (PMM) network that not only reveals pesticide-sensitive gut bacteria species but also report specific metabolic changes in 306 pesticide-GM pairs (PGPs). Using an in vivo mice model, we further demonstrated a PGPs interactions and verified the inflammation-inducing effects of pesticides on the host through dysregulated lipid metabolism of microbes. Taken together, our findings generate a PMM interactions atlas, and shed light on the molecular level of how pesticides impact host health by modulating GM metabolism. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/623895v1_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@17ed5f5org.highwire.dtl.DTLVardef@10d3e0org.highwire.dtl.DTLVardef@c61b43org.highwire.dtl.DTLVardef@27d035_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗