Premenstrual dysphoric disorder (PMDD) is a severe form of premenstrual syndrome (PMS), affecting 3%-8% of women of reproductive age. It is characterized by emotional, behavioral, and physical symptoms during the luteal phase, primarily driven by neuroendocrine sensitivity to hormonal fluctuations and dysregulation of central neurotransmitter systems. Genetic predisposition and environmental stressors contribute to its onset. Although conventional treatments such as selective serotonin reuptake inhibitors (SSRIs) and hormonal therapies offer symptom relief, they are often accompanied by adverse effects and limited long-term efficacy. Traditional Chinese medicine (TCM) posits that the core pathogenesis of PMDD lies in the dysfunction of liver's conveyance and dispersion, which may consistent with modern biological research evidence. TCM approaches, represented by Chinese herbal medicine and acupuncture, may alleviate symptoms of PMDD by targeting and modulating its core modern pathogenic mechanisms. With its few side effects and the unique advantage of individualized treatment based on syndrome differentiation, TCM holds the potential to become a mainstream therapeutic option for PMDD. This narrative review synthesizes evidence from clinical trials, animal and pharmacological studies to explore the efficacy and underlying mechanisms of TCM in the treatment of PMDD and compares these approaches with conventional therapies. Nonetheless, the integration of TCM into mainstream practice for PMDD is still hampered by challenges such as insufficient evidence-based medical data. Research in TCM focusing on biomarker identification, establishment of standardized treatment protocols, and refinement of efficacy evaluation systems is expected to drive its evolution into a mainstream treatment option for PMDD.

BackgroundPost-stroke depression (PSD) is the most common neuropsychiatric complication following stroke. Puerarin (PU), the principal bioactive compound extracted from the medicinal and edible plant Pueraria lobata, has shown beneficial therapeutic effects in both depression and stroke. However, the therapeutic effect of PU on PSD and its underlying mechanisms remain unclear. This study investigates the therapeutic efficacy of PU in ameliorating abnormal behaviors in PSD mice and elucidates the roles of intestinal microbiota disorder, intestinal barrier damage, activation of the NLRP3/CASPASE-1 inflammasome in the hippocampus, and dysregulated inflammatory cytokine production in the pathogenesis of PSD.MethodsTo investigate the ameliorative effect of PU on behavioral abnormalities and to clarify the role of intestinal microbiota regulation in the therapeutic effects of PU in PSD mice, various methodologies were employed, including a PSD model, behavioral tests, network pharmacology, hematoxylin-and-eosin staining, ultrastructural morphology, enzyme-linked immunosorbent assay, western blotting, 16S rRNA sequencing, metabolomic analyses, and fecal microbiota transplantation (FMT).ResultsOral administration of PU could effectively alleviate depressive-like behaviors in PSD mice, repair the damaged colonic mucosa, and increase the expression of occludin and ZO-1. Network pharmacology analysis indicated that the NLRP3/CASPASE-1 inflammasome pathway was a potential therapeutic target of PU, and PU inhibited activation of the hippocampal NLRP3/CASPASE-1 inflammasome. Additionally, PU suppressed pro-inflammatory cytokines in both the hippocampus and serum. PU restored the intestinal microbiota and regulated the microbial metabolism of PSD mice. More importantly, fecal microbiota transplantation from PSD mice reproduced depressive-like behaviors, while fecal microbiota transplantation from PU-treated mice (PU-FMT) prominently relieved depressive-like behaviors in PSD mice.ConclusionOur findings indicate that PU reduces depressive-like behaviors in PSD mice by modulating the intestinal microbiota and microbial metabolism and inhibiting the NLRP3/CASPASE-1 inflammasome.

To elucidate whether Danggui Sini Decoction (DGSD) relieves sciatica by downregulating transient receptor potential (TRP) channels involved in peripheral sensitization. After conducting chronic constriction injury of sciatic nerve (CCI) operation, 32 SD rats, randomly assigned to the sham, CCI 7d, CCI 14d, and CCI 21d groups (n=8 per group), were used to observe the course of sciatica. mRNA sequencing of dorsal root ganglia (DRG) was conducted on rats in the sham and CCI 21d groups. Another 32 rats were divided into the sham, CCI, mecobalamin, and DGSD groups, 8 in each group. mRNA sequencing analysis and single-cell RNA-sequencing (scRNA-seq) data analysis were conducted. Behavioural tests were conducted to evaluate the therapeutic effects of DGSD. The levels of TRP vanilloid (TRPV)1–4, TRP ankyrin 1 (TRPA1), TRP melastatin 8 (TRPM8), Ras homolog family member A (RhoA), and phosphorylated p38 mitogen-activated protein kinase (p-p38MAPK) were measured via Western blot, and the serum levels of C-C motif chemokine ligand 2 and 5 (CCL2, CCL5), substance P (SP), and prostaglandin E2 (PGE2) were conducted via ELISA. scRNA-seq and mRNA sequencing analysis revealed that inflammatory mediator regulation of TRP channels played a role in the development of sciatica. CCI rats exhibited cold hyperalgesia from day 4 to 21, increased the DRG protein expression levels of TRP channels, including TRPV1–4, TRPA1, TRPM8, RhoA, p-p38MAPK, CCL2, CCL5, SP, and PGE2. Treatment with DGSD decreased the serum levels of CCL2, CCL5, SP, and PGE2, and reduced the levels of RhoA, p-p38MAPK, TRPV1–4, TRPA1, and TRPM8 in DRG (P<0.05). CCI increased the levels of TRP channels and inflammatory factors, inducing cold hyperalgesia, whereas DGSD relieved pain via inhibiting peripheral sensitization to relieve cold hyperalgesia by reducing the inflammatory factors and TRP.

Formononetin (FMNT), an isoflavone commonly found in medicinal and food-related plants, demonstrates promising therapeutic potential. In this study, FMNT treatment significantly improved depressive-like behaviors in rats, alleviated colonic tissue damage, and suppressed the release of peripheral lipopolysaccharide (LPS) and inflammatory factors. It also enhanced intestinal barrier function by increasing the expression of tight junction proteins (claudin-1, claudin-6, and occludin). Microbiota analysis revealed that FMNT mitigated LPS-induced dysbiosis, reducing Proteobacteria levels and restoring the Firmicutes/Bacteroidetes (F/B) ratio. At the genus level, FMNT increased the abundance of S24-7 and Lactobacillus while inhibiting Dorea. Moreover, FMNT modulated microbial metabolism by influencing pathways associated with lysine degradation, arginine biosynthesis, and steroid hormone biosynthesis, along with elevating short-chain fatty acids (SCFAs). Collectively, this study underscores FMNTu2019s vital role in ameliorating depressive-like symptoms triggered by neuroinflammation, primarily through the maintenance of intestinal homeostasis and the rebalancing of the gut microbiota.

In the context of the rapid development of artificial intelligence (AI) technology, the intelligentization of traditional Chinese medicine (TCM) diagnosis has become a key research direction for promoting the modernization and internationalization of TCM. TCM diagnosis is based on information from four diagnostic methods, featuring multiple modalities, high dimensions, strong overallness, and significant reliance on experience. It has long faced challenges, such as insufficient objectification, standardization, and repeatability. AI technology has made significant progress in TCM diagnosis, gradually achieving intelligent perception and fusion modeling of multiple sources of diagnostic information and demonstrating good potential in pattern identification, reasoning for pattern differentiation, and decision-making for auxiliary diagnosis. Language models provide a novel technical paradigm for the expression, reasoning, and interaction of elements of TCM diagnosis. This article systematically discusses the theoretical basis, key technologies, and application progress of AI in the intelligentization of TCM diagnosis, focusing on the current development status and challenges of multimodal diagnostic modeling, intelligent expression of patterns, and the development of large model-driven diagnostic systems, to provide references for the application and development of intelligent TCM diagnosis.

ABSTRACT The limited efficacy and slow onset of current antidepressants underscore the urgent need for novel therapeutic strategies. Here, we established a novel zebrafish inflammation‐based screening model and identified 18β‐glycyrrhetinic acid (18β‐GA) as a potent anti‐inflammatory candidate. In a chronic social defeat stress (CSDS) mouse model, 18β‐GA demonstrated significant antidepressant effects, which were associated with attenuated neuroinflammation and a shift in microglial polarization toward an anti‐inflammatory phenotype. Mechanistically, 18β‐GA inhibited the mTOR/p70S6K signaling pathway, leading to the restoration of autophagy and subsequent suppression of NLRP3 inflammasome activation in microglia. Using a transwell co‐culture system, we further confirmed that 18β‐GA protects neurons from microglia‐mediated inflammatory injury. To overcome pharmacokinetic limitations, we developed a nanoliposomal formulation (Nano 18β‐GA) that achieved rapid brain accumulation within 0.5 h, as visualized by time‐dependent in vivo imaging. Remarkably, a single administration of Nano 18β‐GA produced significant antidepressant effects, maintained the original mechanism of action, and exhibited a favorable biosafety profile. Together, our work delineates a translational pipeline from natural product discovery to nano‐enabled therapy, offering a rapidly acting strategy with substantial translational potential for depressive disorder.

The main obstacle of influenza is that only a small proportion of cases progress to severe disease due to massive viral replication and excessive immune responses, while effective therapeutics for influenza-induced pneumonia are urgently needed. This study elucidates the protection of Fei-Yan-Qing-Hua decoction (FYQHD), a traditional Chinese medicine, against lethal influenza A virus (IAV) infection in murine models. NK cell depletion experiments showed that NK cells might play an important role during the protection of FYQHD against influenza. FYQHD enhances phosphorylation of the JAK/STAT pathway, leading to the upregulation of transcription factors as T-bet, etc., which promotes NK cell maturation and activation, and then markedly increases the expression of NKG2D, IFN-γ and perforin. Meanwhile, FYQHD upregulates the expression of chemokine receptors CCR2/3/6 on NK cells via JAK/STAT axis, thereby facilitating their chemotaxis towards the lungs. Importantly, the main bioactive compounds glabridin and naringenin show affinity to IL-2Rα, while ursolic acid binds to STAT5. Collectively, FYQHD suppresses viral replication by promoting the number and function of NK cells in lungs during the initial period of influenza. This provides a mechanistic foundation for the clinical application of FYQHD and highlights the translational potential of its active components, underscoring the value of traditional Chinese medicine in the treatment of influenza.

Depression is a widespread mental disorder with profound effects on both physical and psychological health. Aberrant signal transduction contributes to depression by impairing neuronal function, reducing synaptic plasticity, and disrupting neurotransmitter transmission. Aberrant signal transduction can impair neuronal function, reduce synaptic plasticity, and disrupt neurotransmitter transmission, thereby contributing to the development of depression. Xiao-Yao-San (XYS), a traditional Chinese medicine (TCM) formula, has been extensively employed in the treatment of depression, with a broad therapeutic profile. This review aims to critically assess current scientific evidence on the antidepressant effects of XYS, focusing on its modulation of key signaling pathways. The goal is to provide a more robust mechanistic foundation for XYS-based therapies and offer insights for developing novel antidepressants that target signaling pathways. We systematically searched PubMed, Web of Science, ScienceDirect, CNKI, and Wanfang databases from inception to May 1, 2025, using relevant terms to identify studies on XYS and its active components, particularly those elucidating its regulation of signaling pathways involved in depression. XYS and its active ingredients modulate several crucial signaling pathways implicated in depression, including the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt), NOD-like receptor family pyrin domain containing 3 (NLRP3), nuclear factor-kappa B (NF-κB), and mitogen-activated protein kinase (MAPK) pathways. The antidepressant effects of XYS are primarily mediated through anti-inflammatory actions, improved hippocampal architecture, suppression of neuronal and mitochondrial apoptosis, reduction of oxidative stress, and enhancement of synaptic plasticity. Despite current limitations, this review identifies future research directions focusing on unexplored and cross-linked signalling pathways, which may support the development of signalling-targeted antidepressant agents based on XYS.

Xiaoyaosan (XYS) is a classical traditional prescription with well-documented antidepressant effects. However, the active components and molecular mechanisms to alleviate depression remain unclear. In this study, using chronic social defeat stress (CSDS) and lipopolysaccharide (LPS)-induced depression models, we found that XYS and its key ingredient isoliquiritigenin (ILG) not only significantly improved depressive-like behaviors in mice but also exerted dual regulatory effects at the cellular level, promoting hippocampal neural stem cell proliferation and differentiation, while inhibiting microglia-mediated neuroinflammation. Using Hi-C technology, we discovered that XYS and ILG reversed the abnormal chromatin 3D structure in hippocampal microglia of depression models. Integrated analyses of transcriptomics, molecular docking, and 3D genomics identified the transcription factor p65 as a target of XYS and ILG. Co-culture experiments with microglia and neural stem cells further confirmed that overexpression of p65 promotes inflammation and inhibits neuronal growth. In depressed mice, NF-κB p65 expression was elevated and further formed phase separated condensates, which was effectively suppressed by XYS and ILG. This study reveals how XYS and its active component ILG function mechanistically to exert therapeutic effects on depression, including restoring chromatin 3D structure, and normalizing pathological phase separation of NF-κB p65, and reversing depressive phenotypes. Collectively, these findings provide a solid experimental foundation for the development of natural antidepressants.

Introduction: Microglial activation is a key contributor to neuroinflammation in the pathogenesis of major depressive disorder (MDD). Isoliquiritigenin (ILG), a compound derived from medicinal plants such as Glycyrrhiza glabra, has been widely reported to inhibit microglial activation and reduce neuroinflammation; however, its antidepressant effects and underlying mechanisms remain unclear. Objectives: Here, we show that ILG exerts antidepressant effects that are dependent on its suppression of hippocampal microglia. Methods: This study first evaluated the antidepressant efficacy of ILG using multiple established depression models. We then employed pathological, molecular biological, and targeted inhibition approaches to establish the necessity of microglial involvement in ILG's antidepressant action. Furthermore, single-cell RNA sequencing was utilized to characterize the microglial landscape in depression and to identify the key microglial subset associated with ILG's therapeutic effect. Finally, we elucidated the regulatory mechanism of ILG on this specific microglial subset through molecular docking, microscale thermophoresis, and site-directed mutagenesis. Results: Specifically, single‑cell RNA sequencing revealed that ILG inhibits a subset of highly phagocytic microglia (HP‑MG), a population characterized by high expression of phagocytosis‑associated genes and markedly activated during depression. Mechanistically, ILG binds to the Thr446 phosphorylation site of PKR, blocking its activation and the downstream NF‑κB/ATF4 signaling cascade, thereby downregulating transcription of the HP‑MG marker gene Saa3 and ultimately suppressing HP‑MG. Conclusion: Taken together, these findings indicate that ILG possesses considerable antidepressant potential, which may be attributable to its inhibition of PKR‑mediated highly phagocytic microglia.

The complexity of traditional Chinese medicine (TCM), with its numerous components, targets, and varying efficacy, presents challenges for current evaluation methods. Most existing methods rely on single, qualitative indicators, which provide limited insight into the overall quality. These methods fail to fully capture the intrinsic quality, efficacy, and safety of Chinese medicine, highlighting the need for more advanced biological evaluation techniques. Target-based drug discovery has become the primary approach in pharmaceutical research and development, where drug targets play a crucial role in guiding the entire process. As our understanding deepens, integrating artificial intelligence (AI) with multi-omics technologies has opened new possibilities for enhancing treatment precision. AI's efficiency in identifying drug targets marks a significant leap forward in drug discovery, facilitating the modernization of the drug development process. Meanwhile, omics technologies offer distinct advantages, such as comprehensive controllability, strong correlations with clinical efficacy and safety, and a holistic view of the overall quality of Chinese medicine. These technologies provide an effective and rational approach for evaluating the quality of Chinese medicine and are instrumental in developing quality control systems for TCM. Consequently, combining AI with multi-omics methods is poised to become a key direction for future research into the discovery of targets for antidepressant Chinese medicine.

Chronic non-specific low back pain lacks a defined pathoanatomical cause, leading to diverse treatment methods including physiotherapy and complementary alternative medicine techniques such as Tuina. This study aimed to evaluate the effectiveness of Tuina for managing chronic non-specific low back pain by comparing it to physiotherapy and a combination of physiotherapy and Tuina. In this randomized, parallel-controlled, single-blind trial, 204 participants aged 21 to 75 with chronic non-specific low back pain were randomly assigned to physiotherapy, Tuina, or combined therapy. Pain intensity and quality of life were measured with the visual analog scale, 36-Item Short Form Survey and the Oswestry Disability Index, alongside trunk range of motion. Outcomes were assessed at baseline, two months, and five months. Data were analyzed using analysis of variance for within- and between-group comparisons, and post-hoc tests were applied to between-group comparisons. After two months, all groups had significant improvement in pain scores. Tuina was only significantly better than the combination treatment for reducing pain (p = 0.021; mean difference = − 1.04 [95

Objective Identification of quality marker (Q-Marker) is central to the modernization and quality control of traditional Chinese medicine (TCM). Existing methods, though diverse, lack a unified and scalable strategy to address the chemical and pharmacological complexity of TCM prescriptions. This study established a machine learning-driven framework to integrate multi-source data and systematically prioritize Q-Marker, using Xiaoyao Heji (XYHJ), a modern antidepressant formulation derived from Xiaoyao San, as a case study. Methods Firstly, a dataset of 302 compounds was constructed by summarizing 14 reported Q-Marker discovery strategies and annotated with five core dimensions—compatibility, specificity, measurability, traceability, and effectiveness. Subsequently, five ranking models (RankNet, Random Forest, XGBoost, Linear Regression and K-Nearest Neighbors) were trained with 8-fold GroupKFold cross-validation and evaluated by normalized discounted cumulative gain (NDCG), mean average precision (MAP), and Recall. Thirdly, the optimal model was applied to XYHJ, followed by systematic characterization of chemical profiles, quantitative analysis, drug metabolism and pharmacokinetics (DMPK), quality transitivity, and bioactivity. Finally, Q-Markers were further validated through radar chart modeling, Monte Carlo simulations, and chemometric analyses. Results Through a comparison of the machine learning models, XGBoost outperformed other models, exhibiting high and stable performance with NDCG, MAP, and Recall values ranging from 0.84 to 0.95. For the first time, the XYHJ prescription was comprehensively evaluated across its chemical profile, DMPK properties, quantitative content, manufacturing traceability, and biological efficacy. Using the optimal XGBoost ranking model, 15 components were screened and ranked, successfully identifying paeoniflorin, albiflorin, and glycyrrhizic acid as critical Q-Marker. The reliability of the ranking approach was further validated by integrating a previously published radar chart model with Monte Carlo simulations with over 10 000 sampling iterations. Furthermore, fingerprint similarity and chemometric analysis demonstrated the effectiveness of these Q-Markers in distinguishing XYHJ produced through different manufacturing processes. Conclusion This study developed a machine learning-driven ranking framework that unifies multiple Q-Marker discovery strategies. Using XYHJ as a case study, this approach not only enhances its quality control system but also provides a valuable reference for the standardization and modernization of other TCM prescriptions.

Background The anterior cingulate cortex (ACC) regulates emotion, and its dysfunction is associated with depression. 18β-glycyrrhetinic acid (18β-GA) exerts robust antidepressant effects; however, its roles in neural circuit remodeling of the ACC and underlying molecular mechanisms remain unclear. This study investigated its phenotypic changes within the ACC in chronic social defeat stress (CSDS) mice using multimodal MRI, histopathology and molecular assays. Methods Male C57BL/6J mice with CSDS depression model received 18β-GA treatment. We detected ACC neuroimaging alterations via multimodal MRI, and assessed BDNF, myelin-related molecules and myelin morphology. Hippocampal changes were also analyzed to explore the ACC-hippocampus emotional circuit. Results CSDS induced severe structural and functional deficits in the ACC, including gray matter atrophy, decreased FA, increased ReHo and disrupted functional connectivity between the ACC and limbic regions. 18β-GA-related effects coincided with ameliorated ACC imaging deficits, improved network homeostasis, attenuated stress-induced myelin injury, preserved myelin integrity, and elevated BDNF together with myelin-related molecular markers, pointing to parallel myelin-remodeling-associated phenotypic shifts. Consistent molecular and myelin changes were found in the hippocampus, indicating remodeling of the ACC-hippocampus emotional circuit. Conclusion 18β-GA is accompanied by restored BDNF abundance, alleviated myelin lesions and normalized ACC neural circuits, which coincides with the alleviation of depressive-like phenotypes. Multimodal MRI parameters of the ACC, especially FA combined with myelin histopathological features, serve as promising biomarkers for evaluating the efficacy of 18β-GA. This study provides correlational evidence for BDNF-associated myelin remodeling alterations under chronic stress in depression-like mouse models and preclinical pharmacological evidence for the antidepressant use of 18β-GA.

Ulcerative colitis (UC) represents a chronic relapsing inflammatory bowel disease characterized by substantial unmet clinical needs and limited curative modalities. Accumulating evidence implicates gut microbiota dysbiosis as a pivotal pathogenic driver, positioning microbiota-targeted interventions as promising therapeutic strategies. This review systematically delineates the mechanisms by which herbal compounds from Traditional Chinese Medicine ameliorate UC through the restoration of microbial and metabolic homeostasis-including the modulation of beneficial commensals and their bioactive metabolites-thereby reinforcing intestinal barrier integrity and dampening mucosal inflammation. Although translational bottlenecks persist, integrative multi-omics frameworks coupled with advanced pharmaceutical engineering offer viable pathways to bridge preclinical findings and clinical application. Taken together, deciphering the bidirectional crosstalk between herbal compounds and the gut microbiome paves the way for mechanism-based, personalized botanical therapeutics in UC management.

The clinical management of depression presents significant challenges. While acupuncture has shown efficacy in alleviating depressive symptoms, the underlying mechanisms through which it exerts its antidepressant effects remain incompletely understood. Recent research has underscored the crucial role of glial cells in the pathophysiology of depression. This discovery opens a novel and promising avenue for investigating the mechanisms underlying acupuncture's antidepressant actions. Based on clinical evidence supporting the use of acupuncture in treating depression, this article reviews recent studies on how acupuncture influences the glial cell network. This is the first review of studies examining the effects of acupuncture on glial cells in depression. The review encompasses several key aspects, including microglial polarization and associated inflammatory signaling pathways, the role of astrocytes in maintaining metabolic homeostasis, the processes of oligodendrocyte differentiation and myelin repair, as well as the intricate interactions among these three types of glial cells. However, this paper also has certain limitations, such as the majority of mechanistic evidence deriving from animal models, and due to the heterogeneity of acupuncture protocols and the lack of human causal data.

BACKGROUND:Fear memory (FM) is a neurophysiological process regulated by diverse neural cell populations and closely linked to general memory function. However, the precise cellular and molecular mechanisms underlying FM remain insufficiently understood. METHODS:In this study, spatial transcriptomic data from four sagittal mouse brain sections obtained from 10xGenomics were systematically analyzed. Cell2location deconvolution was applied to characterize cellular composition and identify key cell populations associated with FM. CellChat and Monocle analyses were used to investigate intercellular communication and cellular activation trajectories during FM progression. Signaling pathways identified utilizing CellChat, together with pathways enriched from hypervariable genes identified by MFUZZ and DESeq2, were analyzed to clarify the molecular basis of FM. To further explore the mechanisms through which FM influences general memory function, key ligands, receptors, transcription factors (TFs), and downstream targets were identified using scMLnet. RESULTS:Spatial transcriptomic analysis revealed extensive interactions among M2 macrophages, astrocytes, oligodendrocytes, and cholinergic neurons during FM, while M1 macrophages and dopaminergic neurons exhibited supportive roles in cellular co-occurrence networks. These interactions mediated autocrine and paracrine transmission through JAM, EPHB, NCAM, NRXN, and AMPK signaling pathways. Among the identified genes, Opalin, Thbs4, and Cyp2j12 emerged as potential biomarkers associated with dominant cellular interactions and were upregulated in FM-related regions. FM-associated molecular alterations may impair memory function through EPH/Ephrin-mediated ligand-receptor interactions that activate TFs, including CREB, E1A-binding proteins, and estrogen receptors, subsequently regulating Ras-related proteins and epidermal growth factor receptors. These findings suggest that estrogen signaling may represent a potential strategy for FM modulation. DISCUSSION:Astrocytes, cholinergic neurons, M1/M2 macrophages, and oligodendrocytes appear to play central roles in FM regulation. Notably, M1 macrophages may promote the transcriptional transition toward M2 macrophages, thereby contributing to neuroinflammatory resolution. EPHB and NRXN signaling pathways demonstrated prominent regulatory associations with FM, whereas the functional significance of pathways such as JAM requires further investigation. In addition, competitive interactions between FM and general memory processes were closely linked to EPH/Ephrin signaling. Estrogen-mediated regulation may therefore provide a therapeutic avenue for suppressing maladaptive FM, although the underlying mechanisms remain incompletely defined. CONCLUSIONS:This study provides a spatially resolved characterization of cellular composition, intercellular communication, and molecular regulation associated with FM. The findings generate new hypotheses regarding the relationship between emotional regulation and memory function, particularly the possibility that FM formation and consolidation compromise general memory processes. Collectively, these results offer new insights into the cellular and molecular neurobiology of FM.

BACKGROUND:Post-stroke depression (PSD) represents the most prevalent complication of stroke and has been reported to be associated with an imbalance in the gut microbiota. Clinically, Xiaoyaosan (XYS) alleviates depressive symptoms in patients with PSD. However, the existing literature does not provide sufficient evidence to ascertain whether XYS can alleviate these symptoms by modulating gut microbiota. PURPOSE:This study aims to investigate the potential mechanism of XYS to improve depression-like behavior in mice with PSD by regulating intestinal flora and microbial metabolism. STUDY DESIGN:The authors assessed the effect of XYS on the behaviour of PSD mice and evaluated the effects of XYS on structure and metabolism of gut microbiota, the protein expression levels of P2X7 and NLRP3, and associated inflammatory factors in PSD mice. In addition, by performing faecal microbiota transplantation (FMT) on PSD mice with faecal bacteria treated with XYS, the authors further clarified the relationship between intestinal flora disorder, the onset of PSD, and the intervention effect of XYS. METHODS:To investigate the ameliorative effect of XYS on behavioural abnormalities and clarify the important role of intestinal flora regulation in the improvement of PSD by XYS in diseased mice, the authors employed various methodologies, including the PSD model, behavioural tests, haematoxylin and eosin staining, ultrastructural morphology, enzyme-linked immunosorbent assay, western blotting, 16S rRNA sequencing, metabolomic analyses, and FMT. RESULTS:Oral administration of XYS effectively alleviated depression-like behaviours in PSD mice and repaired the damaged colonic mucosa. XYS inhibited inflammatory factors in serum and hippocampus and regulated the protein expression levels of P2X7 and NLRP3 in the colon and hippocampus of PSD mice. Moreover, XYS restored the gut microbiota and modulated intestinal metabolites in PSD mice. It effectively reduced the abundances of microbes including Ligullacoccus, Streptococcus, and Staphylococcus, while significantly increased the abundances of microbes including Faecalibaculum, Allobaculum, and Monolobus. Furthermore, XYS effectively regulated intestinal metabolites such as methylparaben, valproic acid (Depakene), and disulfiram. More importantly, faecal transplants from the PSD models reproduced depression-like behaviours in normal mice, while XYS-FMT effectively alleviated depression-like behaviours in PSD mice. CONCLUSION:Our findings indicate that XYS improves depression-like behaviours in mice with PSD by modulating the gut microbiota and microbial metabolism, and regulating the P2X7R/NLRP3 inflammasome.