A novel rat model of cerebral small vessel disease based on vascular risk factors of hypertension, aging, and cerebral hypoperfusion.

Cerebral small vessel disease (CSVD) is a major cause of vascular cognitive impairment and functional loss in elderly patients. Progressive remodeling of cerebral microvessels due to arterial hypertension or other vascular risk factors, such as aging, can cause dementia or stroke. Typical imaging characteristics of CSVD include cerebral microbleeds (CMB), brain atrophy, small subcortical infarctions, white matter hyperintensities (WMH), and enlarged perivascular spaces (EPVS). Nevertheless, no animal models that reflect all the different aspects of CSVD have been identified. Here, we generated a new CSVD animal model using D-galactose (D-gal) combined with cerebral hypoperfusion in spontaneously hypertensive rats (SHR), which showed all the hallmark pathological features of CSVD and was based on vascular risk factors. SHR were hypodermically injected with D-gal (400 mg/kg/d) and underwent modified microcoil bilateral common carotid artery stenosis surgery. Subsequently, neurological assessments and behavioral tests were performed, followed by vascular ultrasonography, electron microscopy, flow cytometry, and histological analyses. Our rat model showed multiple cerebrovascular pathologies, such as CMB, brain atrophy, subcortical small infarction, WMH, and EPVS, as well as the underlying causes of CSVD pathology, including oxidative stress injury, decreased cerebral blood flow, structural and functional damage to endothelial cells, increased blood-brain barrier permeability, and inflammation. The use of this animal model will help identify new therapeutic targets and subsequently aid the development and testing of novel therapeutic interventions. Main process of the study: Firstly, we screened for optimal conditions for mimicking aging by injecting D-gal into rats for 4 and 8 weeks. Subsequently, we performed modified microcoil BCAS intervention for 4 and 8 weeks in rats to screen for optimal hypoperfusion conditions. Finally, based on these results, we combined D-gal for 8 weeks and modified microcoil BCAS for 4 weeks to explore the changes in SHR.

Ablated Sonic Hedgehog Signaling in the Dentate Gyrus of the Dorsal and Ventral Hippocampus Impairs Hippocampal-Dependent Memory Tasks and Emotion in a Rat Model of Depression.

Specific memory processes and emotional aberrations in depression can be attributed to the different dorsal-ventral regions of the hippocampus. However, the molecular mechanisms underlying the differential functions of the dorsal hippocampus (dHip) and ventral hippocampus (vHip) remain unclear. As Sonic Hedgehog (Shh) is involved in the dorsal-ventral patterning of the neural tube and its signaling is dysregulated by chronic unpredictable mild stress (CUMS), we investigated its role in influencing the differential functions of the dHip and vHip. Here, CUMS downregulated the expression of Shh signaling markers, including Shh and its downstream effectors GLI family zinc finger 12 (Gli1/2), Patched (Ptch), and smoothened (Smo), in both the dHip and vHip of rats, though more so in the vHip. Additionally, Shh knockdown in the dorsal or ventral dentate gyrus (DG) resulted in restrained neurogenic activity in newborn neurons, especially in immature neurons through decreased expression of Shh signaling markers. Furthermore, Shh knockdown in the DG of the dHip led to memory impairment by inhibiting experience-dependent activation of immature neurons, whereas its knockdown in the DG of the vHip led to an emotional handicap by delaying the maturation of immature neurons. Finally, Shh knockdown in either the dDG or vDG of hippocampus abolished the corresponding cognitive enhancement and emotional recovery of fluoxetine. In conclusion, Shh is essential to maintain the functional heterogeneity of dHip and vHip in depressed rat, which was mainly mediating by local changes of dependent activation and maturity of immature neurons, respectively.

Integrating serum metabolomics and network analysis to explore the antidepressant activity of crocin in rats with chronic unexpected mild stress-induced depression.

CONTEXT: Crocin exhibits anti-depressant properties. However, its underlying mechanisms and its relationship with metabolomics remain unclear. OBJECTIVE: This study elucidates the mechanism of action and potential targets of crocin in treating chronic unexpected mild stress (CUMS)-induced depression in rats. MATERIALS AND METHODS: Male Sprague-Dawley (SD) rats underwent 4 weeks of CUMS to establish the depression model. The normal control (distilled water), crocin (25 mg/kg), and fluoxetine (5.4 mg/kg) groups were orally administered for 4-weeks. Behavioural tests evaluated the effects of crocin, while liquid chromatography-mass spectrometry metabolomics identified differential metabolites and their associated metabolic pathways. Subsequently, network pharmacology was utilized to predict the targets of crocin. RESULTS: Crocin significantly increased body weight (from 319.16 ± 4.84 g to 325.67 ± 2.84 g), sucrose preference (from 0.46 ± 0.09 to 0.70 ± 0.09), vertical activity (from 2.83 ± 1.94 to 8 ± 2.36), horizontal activity (from 1 ± 0.63 to 4.5 ± 3.08) and decreased immobilization time (from 13.16 ± 2.69 to 3.97 ± 3.00). Metabolomics analysis identified 7 metabolites and 5 associated metabolic pathways. From the combined analysis of network pharmacology and metabolomics, three targets (PRMT1, CYP3A4, and GLB1) are the overlapping targets and the two most important metabolic pathways are tryptophan metabolism and glycerolipid metabolism. DISCUSSION AND CONCLUSIONS: This study provides insights into the antidepressant therapeutic effect of crocin and its underlying mechanisms. The findings contribute to a better understanding of the metabolic mechanism involved in the anti-depressant effect of crocin, establishing a strong foundation for future research in this area.

A whole transcriptome profiling analysis for antidepressant mechanism of Xiaoyaosan mediated synapse loss via BDNF/trkB/PI3K signal axis in CUMS rats.

BACKGROUND: Depression is a neuropsychiatric disease resulting from deteriorations of molecular networks and synaptic injury induced by stress. Traditional Chinese formula Xiaoyaosan (XYS) exert antidepressant effect, which was demonstrated by a great many of clinical and basic investigation. However, the exact mechanism of XYS has not yet been fully elucidated. METHODS: In this study, chronic unpredictable mild stress (CUMS) rats were used as a model of depression. Behavioral test and HE staining were used to detect the anti-depressant effects of XYS. Furthermore, whole transcriptome sequencing was employed to establish the microRNA (miRNA), long non-coding RNA (lncRNA), circular RNA (circRNA), and mRNA profiles. The biological functions and potential mechanisms of XYS for depression were gathered from the GO and KEGG pathway. Then, constructed the competing endogenous RNA (ceRNA) networks to illustrate the regulatory relationship between non-coding RNA (ncRNA) and mRNA. Additionally, longest dendrite length, total length of dendrites, number of intersections, and density of dendritic spines were detected by Golgi staining. MAP2, PSD-95, SYN were detected by immunofluorescence respectively. BDNF, TrkB, p-TrkB, PI3K, Akt, p-Akt were measured by Western Blotting. RESULTS: The results showed that XYS could increase the locomotor activity and sugar preference, decreased swimming immobility time as well as attenuate hippocampal pathological damage. A total of 753 differentially expressed lncRNAs (DElncRNAs), 28 circRNAs (DEcircRNAs), 101 miRNAs (DEmiRNAs), and 477 mRNAs (DEmRNAs) were identified after the treatment of XYS in whole transcriptome sequencing analysis. Enrichment results revealed that XYS could regulate multiple aspects of depression through different synapse or synaptic associated signal, such as neurotrophin signaling and PI3K/Akt signaling pathways. Then, vivo experiments indicated that XYS could promote length, density, intersections of synapses and also increase the expression of MAP2 in hippocampal CA1, CA3 regions. Meanwhile, XYS could increase the expression of PSD-95, SYN in the CA1, CA3 regions of hippocampal by regulating the BDNF/trkB/PI3K signal axis. CONCLUSION: The possible mechanism on synapse of XYS in depression was successfully predicted. BDNF/trkB/PI3K signal axis were the potential mechanism of XYS on synapse loss for its antidepressant. Collectively, our results provided novel information about the molecular basis of XYS in treating depression.

A cascaded QSAR model for efficient prediction of overall power conversion efficiency of all-organic dye-sensitized solar cells.

A cascaded model is proposed to establish the quantitative structure-activity relationship (QSAR) between the overall power conversion efficiency (PCE) and quantum chemical molecular descriptors of all-organic dye sensitizers. The cascaded model is a two-level network in which the outputs of the first level (JSC, VOC, and FF) are the inputs of the second level, and the ultimate end-point is the overall PCE of dye-sensitized solar cells (DSSCs). The model combines quantum chemical methods and machine learning methods, further including quantum chemical calculations, data division, feature selection, regression, and validation steps. To improve the efficiency of the model and reduce the redundancy and noise of the molecular descriptors, six feature selection methods (multiple linear regression, genetic algorithms, mean impact value, forward selection, backward elimination, and +n-m algorithm) are used with the support vector machine. The best established cascaded model predicts the PCE values of DSSCs with a MAE of 0.57 (%), which is about 10% of the mean value PCE (5.62%). The validation parameters according to the OECD principles are R(2) (0.75), Q(2) (0.77), and Qcv2 (0.76), which demonstrate the great goodness-of-fit, predictivity, and robustness of the model. Additionally, the applicability domain of the cascaded QSAR model is defined for further application. This study demonstrates that the established cascaded model is able to effectively predict the PCE for organic dye sensitizers with very low cost and relatively high accuracy, providing a useful tool for the design of dye sensitizers with high PCE.