Animal models of inflammatory bowel disease: category and evaluation indexes.

Inflammatory bowel disease (IBD) research often relies on animal models to study the etiology, pathophysiology, and management of IBD. Among these models, rats and mice are frequently employed due to their practicality and genetic manipulability. However, for studies aiming to closely mimic human pathology, non-human primates such as monkeys and dogs offer valuable physiological parallels. Guinea pigs, while less commonly used, present unique advantages for investigating the intricate interplay between neurological and immunological factors in IBD. Additionally, New Zealand rabbits excel in endoscopic biopsy techniques, providing insights into mucosal inflammation and healing processes. Pigs, with their physiological similarities to humans, serve as ideal models for exploring the complex relationships between nutrition, metabolism, and immunity in IBD. Beyond mammals, non-mammalian organisms including zebrafish, Drosophila melanogaster, and nematodes offer specialized insights into specific aspects of IBD pathology, highlighting the diverse array of model systems available for advancing our understanding of this multifaceted disease. In this review, we conduct a thorough analysis of various animal models employed in IBD research, detailing their applications and essential experimental parameters. These include clinical observation, Disease Activity Index score, pathological assessment, intestinal barrier integrity, fibrosis, inflammatory markers, intestinal microbiome, and other critical parameters that are crucial for evaluating modeling success and drug efficacy in experimental mammalian studies. Overall, this review will serve as a valuable resource for researchers in the field of IBD, offering insights into the diverse array of animal models available and their respective applications in studying IBD.

Simultaneous brain and neck time-of-flight MRA using spiral multiband with localized quadratic encoding.

PURPOSE: To develop a method that achieves simultaneous brain and neck time-of-flight (ToF) magnetic resonance angiography (MRA) within feasible scan timeframes. METHODS: Localized quadratic (LQ) encoding is efficient for both signal-to-noise ratio (SNR) and in-flow enhancement. We proposed a spiral multiband LQ method to enable simultaneous intracranial and carotid ToF-MRA within a single scan. To address the venous signal contamination that becomes a challenge with multiband (MB) ToF, tilt-optimized non-saturated excitation (TONE) and partial-Fourier slice selection (PFSS) were further introduced in the LQ framework to mitigate the venous signal and improve artery contrast. A sequential spiral MB and LQ reconstruction pipeline was employed to obtain the brain-and-neck image volumes. RESULTS: The proposed MB method was able to achieve simultaneous brain and neck ToF-MRA within a 2:50-min scan. The complementarily boosted SNR-efficiency by MB and LQ acquisitions allows for the increased spatial coverage without increase in scan time or noticeable compromise in SNR. The incorporation of both TONE and PFSS effectively alleviated the venous contamination with improved small vessel sensitivity. Selection of scan parameters such as the LQ factor and flip angle reflected the trade-off among SNR, blood contrast, and venous suppression. CONCLUSIONS: A novel MB spiral LQ approach was proposed to enable fast intracranial and carotid ToF-MRA with minimized venous corruption. The method has shown promise in MRA applications where large spatial coverage is necessary.

The anti-depression effect and potential mechanism of the petroleum ether fraction of CDB: Integrated network pharmacology and metabolomics.

The combination of Chaidangbo (CDB) is an antidepressant traditional Chinese medicine (TCM) prescription simplified by Xiaoyaosan (a classic antidepressant TCM prescription) through dismantling research, which has the effect of dispersing stagnated liver qi and nourishing blood in TCM theory. Although the antidepressant effect of CBD has been confirmed in animal studies, the material basis and possible molecular mechanism for antidepressant activity in CBD have not been clearly elucidated. Herein, we investigated the effects and potential mechanisms of CDB antidepressant fraction (petroleum ether fraction of CDB, PEFC) on chronic unpredictable mild stress (CUMS)-induced depression-like behavior in mice using network pharmacology and metabolomics. First, a UPLC-QE/MS was employed to identify the components of PEFC. To extract active ingredients, SwissADME screening was used to the real PEFC components that were found. Potential PEFC antidepressant targets were predicted based on a network pharmacology approach, and a pathway enrichment analysis was performed for the predicted targets. Afterward, a CUMS mouse depression model was established and LC-MS-based untargeted hippocampal metabolomics was performed to identify differential metabolites, and related metabolic pathways. Finally, the protein expressions in mouse hippocampi were determined by Western blot to validate the network pharmacology and metabolomics deduction. A total of 16 active compounds were screened in SwissADME that acted on 73 core targets of depression, including STAT3, MAPKs, and NR3C1; KEGG enrichment analysis showed that PEFC modulated signaling pathways such as PI3K-Akt signaling pathway, endocrine resistance, and MAPK to exert antidepressant effects. PEFC significantly reversed abnormalities of hippocampus metabolites in CUMS mice, mainly affecting the synthesis and metabolism of glycine, serine, and threonine, impacting catecholamine transfer and cholinergic synapses and regulating the activity of the mTOR signaling pathway. Furthermore, Western blot analysis confirmed that PEFC significantly influenced the main protein levels of the PI3K/Akt/mTOR signaling pathways in the hippocampus of mice subjected to CUMS. This study integrated metabolomics, network pharmacology and biological verification to explore the potential mechanism of PEFC in treating depression, which is related to the regulation of amino acid metabolism dysfunction and the activation of PI3K/Akt/mTOR signaling pathways in the hippocampus. The comprehensive strategy also provided a reasonable way for unveiling the pharmacodynamic mechanisms of multi-components, multi-targets, and multi-pathways in TCM with antidepressant effect.

In vivo absorption, in vitro simulated digestion and fecal fermentation properties of polysaccharides from Pinelliae Rhizoma Praeparatum Cum Alumine and their effects on human gut microbiota.

Polysaccharides from Pinelliae Rhizoma Praeparatum Cum Alumine (PPA) have various biological activities, but their properties after oral administration are not clear. In this study, the absorption, digestion and fermentation properties of PPA were studied using in vivo fluorescence tracking, in vitro simulated digestion and fecal fermentation experiments. The absorption experiment showed that fluorescence was only observed in the gastrointestinal system, indicating that PPA could not be absorbed. Simulated digestion results showed that there were no significant changes in the molecular weight, Fourier transform infrared spectroscopy (FT-IR) spectrum, monosaccharides and reducing sugar of PPA during the digestion process, showing that the overall structure of PPA was not damaged. However, the carbohydrate gel electrophoresis bands of PPA enzymatic hydrolysates after simulated digestion were significantly changed, indicating that simulated digestion might impact the configuration of PPA. In vitro fermentation showed that PPA could be degraded by microorganisms to produce short chain fatty acids, leading to a decrease in pH value. PPA can promote the proliferation of Bacteroideaceae, Megasphaera, Bacteroideaceae, and Bifidobacteriaceae, and inhibit the growth of Desulfobacteriota and Enterobacteriaceae. The results indicated that PPA could treat diseases by regulating gut microbiota, providing a scientific basis for the application and development of PPA.

Propagation dynamics of self-accelerating second-order Hermite complex-variable-function Gaussian wave packets in a harmonic potential.

This paper investigates the evolutionary dynamics of self-accelerating second-order Hermite complex-variable-function Gaussian (SSHCG) wave packets in a harmonic potential. The periodic variation of the wave packets is discussed via theoretical analysis and numerical simulation. The control variables method is applied to manipulate the distribution factor, cross-phase factor, potential depth, and chirp parameter, enabling the realization of unique propagation dynamics. In three-dimensional models, the SSHCG wave packets exhibit rotational states, featuring butterfly shape, three peaks shape, two polarity shape, elliptical shape, and ring-shaped double-vortex structures. Furthermore, the energy flow and the angular momentum of the wave packets are investigated. Additionally, the performance of the radiation force on a Rayleigh dielectric particle is studied. This investigation results in the emergence of distinct SSHCG wave packet propagation dynamics, and potential applications in optical communications and optical trapping are presented.

Cross-Modal Retrieval With Noisy Correspondence via Consistency Refining and Mining.

The success of existing cross-modal retrieval (CMR) methods heavily rely on the assumption that the annotated cross-modal correspondence is faultless. In practice, however, the correspondence of some pairs would be inevitably contaminated during data collection or annotation, thus leading to the so-called Noisy Correspondence (NC) problem. To alleviate the influence of NC, we propose a novel method termed Consistency REfining And Mining (CREAM) by revealing and exploiting the difference between correspondence and consistency. Specifically, the correspondence and the consistency only be coincident for true positive and true negative pairs, while being distinct for false positive and false negative pairs. Based on the observation, CREAM employs a collaborative learning paradigm to detect and rectify the correspondence of positives, and a negative mining approach to explore and utilize the consistency. Thanks to the consistency refining and mining strategy of CREAM, the overfitting on the false positives could be prevented and the consistency rooted in the false negatives could be exploited, thus leading to a robust CMR method. Extensive experiments verify the effectiveness of our method on three image-text benchmarks including Flickr30K, MS-COCO, and Conceptual Captions. Furthermore, we adopt our method into the graph matching task and the results demonstrate the robustness of our method against fine-grained NC problem. The code is available on https://github.com/XLearning-SCU/2024-TIP-CREAM.

Nile Tilapia (Oreochromis niloticus) Patched1 Mutations Disrupt Cardiovascular Development and Vascular Integrity through Smoothened Signaling.

Hedgehog (Hh) signaling is crucial in cardiovascular development and maintenance. However, the biological role of Patched1 (Ptch1), an inhibitory receptor of the Hh signaling pathway, remains elusive. In this study, a Ptch1 ortholog was characterized in Nile tilapia (Oreochromis niloticus), and its function was investigated through CRISPR/Cas9 gene knockout. When one-cell embryos were injected with CRISPR/Cas9 targeting ptch1, the mutation efficiency exceeded 70%. During 0-3 days post fertilization (dpf), no significant differences were observed between the ptch1 mutant group and the control group; at 4 dpf (0 day after hatching), about 10% of the larvae showed an angiogenesis defect and absence of blood flow; from 5 dpf, most larvae exhibited an elongated heart, large pericardial cavity, and blood leakage and coagulation, ultimately dying during the 6-8 dpf period due to the lack of blood circulation. Consistently, multiple differentially expressed genes related to angiogenesis, blood coagulation, and heart development were enriched in the ptch1 mutants. Furthermore, Smoothened (Smo) antagonist (cyclopamine) treatment of the ptch1 mutants greatly rescued the cardiovascular disorders. Collectively, our study suggests that Ptch1 is required for cardiovascular development and vascular integrity via Smo signaling, and excessive Hh signaling is detrimental to cardiovascular development.

The extraction, purification, structural features, bioactivities, and applications of Schisandra chinensis polysaccharides: A review.

Schisandra chinensis, as a famous medicinal and food homologous plant, has a long history of medicinal and dietary therapy. It has the functions of nourishing the kidney, calming the heart, tranquilising the mind, tonifying Qi and producing fluid to relieve mental stress, based on the theory of traditional Chinese medicine. Accumulating evidence has shown that S. chinensis polysaccharides (SCPs) are one of the most important bioactive macromolecules and exhibit diverse biological activities in vitro and in vivo, including neuroprotective, hepatoprotective, immunomodulatory, antioxidant, hypoglycemic, cardioprotective, antitumour and anti-inflammatory activities, etc. This review aims to thoroughly review the recent advances in the extraction and purification methods, structural features, biological activities and structure-activity relationships, potential applications and quality assessment of SCPs, and further highlight the therapeutic potentials and health functions of SCPs in the fields of therapeutic agents and functional food development. Future insights and challenges of SCPs were also critically discussed. Overall, the present review provides a theoretical overview for the further development and utilization of S. chinensis polysaccharides in the health food and pharmaceutical fields.

Glutamine sustains energy metabolism and alleviates liver injury in burn sepsis by promoting the assembly of mitochondrial HSP60-HSP10 complex via SIRT4 dependent protein deacetylation.

Burns and burn sepsis, characterized by persistent and profound hypercatabolism, cause energy metabolism dysfunction that worsens organ injury and systemic disorders. Glutamine (Gln) is a key nutrient that remarkably replenishes energy metabolism in burn and sepsis patients, but its exact roles beyond substrate supply is unclear. In this study, we demonstrated that Gln alleviated liver injury by sustaining energy supply and restoring redox balance. Meanwhile, Gln also rescued the dysfunctional mitochondrial electron transport chain (ETC) complexes, improved ATP production, reduced oxidative stress, and protected hepatocytes from burn sepsis injury. Mechanistically, we revealed that Gln could activate SIRT4 by upregulating its protein synthesis and increasing the level of Nicotinamide adenine dinucleotide (NAD+), a co-enzyme that sustains the activity of SIRT4. This, in turn, reduced the acetylation of shock protein (HSP) 60 to facilitate the assembly of the HSP60-HSP10 complex, which maintains the activity of ETC complex II and III and thus sustain ATP generation and reduce reactive oxygen species release. Overall, our study uncovers a previously unknown pharmacological mechanism involving the regulation of HSP60-HSP10 assembly by which Gln recovers mitochondrial complex activity, sustains cellular energy metabolism and exerts a hepato-protective role in burn sepsis.

Underwater image enhancement using multi-task fusion.

Underwater images are often scattered due to suspended particles in the water, resulting in light scattering and blocking and reduced visibility and contrast. Color shifts and distortions are also caused by the absorption of different wavelengths of light in the water. This series of problems will make the underwater image quality greatly impaired, resulting in some advanced visual work can not be carried out underwater. In order to solve these problems, this paper proposes an underwater image enhancement method based on multi-task fusion, called MTF. Specifically, we first use linear constraints on the input image to achieve color correction based on the gray world assumption. The corrected image is then used to achieve visibility enhancement using an improved type-II fuzzy set-based algorithm, while the image is contrast enhanced using standard normal distribution probability density function and softplus function. However, in order to obtain more qualitative results, we propose multi-task fusion, in which we solve for similarity, then we obtain fusion weights that guarantee the best features of the image as much as possible from the obtained similarity, and finally we fuse the image with the weights to obtain the output image, and we find that multi-task fusion has excellent image enhancement and restoration capabilities, and also produces visually pleasing results. Extensive qualitative and quantitative evaluations show that MTF method achieves optimal results compared to ten state-of-the-art underwater enhancement algorithms on 2 datasets. Moreover, the method can achieve better results in application tests such as target detection and edge detection.

Hesperitin-Copper(II) Complex Regulates the NLRP3 Pathway and Attenuates Hyperuricemia and Renal Inflammation.

BACKGROUND: Hyperuricaemia (HUA) is a disorder of purine metabolism in the body. We previously synthesized a hesperitin (Hsp)-Cu(II) complex and found that the complex possessed strong uric acid (UA)-reducing activity in vitro. In this study we further explored the complex's UA-lowering and nephroprotective effects in vivo. METHODS: A mouse with HUA was used to investigate the complex's hypouricemic and nephroprotective effects via biochemical analysis, RT-PCR, and Western blot. RESULTS: Hsp-Cu(II) complex markedly decreased the serum UA level and restored kidney tissue damage to normal in HUA mice. Meanwhile, the complex inhibited liver adenosine deaminase (ADA) and xanthine oxidase (XO) activities to reduce UA synthesis and modulated the protein expression of urate transporters to promote UA excretion. Hsp-Cu(II) treatment significantly suppressed oxidative stress and inflammatory in the kidney, reduced the contents of cytokines and inhibited the activation of the nucleotide-binding oligomerization domain (NOD)-like receptor thermal protein domain associated protein 3 (NLRP3) inflammatory pathway. CONCLUSIONS: Hsp-Cu(II) complex reduced serum UA and protected kidneys from renal inflammatory damage and oxidative stress by modulating the NLRP3 pathway. Hsp-Cu(II) complex may be a promising dietary supplement or nutraceutical for the therapy of hyperuricemia.

Learning-Assisted Fast Determination of Regularization Parameter in Constrained Image Reconstruction.

OBJECTIVE: To leverage machine learning (ML) for fast selection of optimal regularization parameter in constrained image reconstruction. METHODS: Constrained image reconstruction is often formulated as a regularization problem and selecting a good regularization parameter value is an essential step. We solved this problem using an ML-based approach by leveraging the finding that for a specific constrained reconstruction problem defined for a fixed class of image functions, the optimal regularization parameter value is weakly subject-dependent and the dependence can be captured using few experimental data. The proposed method has four key steps: a) solution of a given constrained reconstruction problem for a few (say, 3) pre-selected regularization parameter values, b) extraction of multiple approximated quality metrics from the initial reconstructions, c) predicting the true quality metrics values from the approximated values using pre-trained neural networks, and d) determination of the optimal regularization parameter by fusing the predicted quality metrics. RESULTS: The effectiveness of the proposed method was demonstrated in two constrained reconstruction problems. Compared with L-curve-based method, the proposed method determined the regularization parameters much faster and produced substantially improved reconstructions. Our method also outperformed state-of-the-art learning-based methods when trained with limited experimental data. CONCLUSION: This paper demonstrates the feasibility and improved reconstruction quality by using machine learning to determine the regularization parameter in constrained reconstruction. SIGNIFICANCE: The proposed method substantially reduces the computational burden of the traditional methods (e.g., L-curve) or relaxes the requirement of large training data by modern learning-based methods, thus enhancing the practical utility of constrained reconstruction.

2D Ni-Co bimetallic oxide nanosheets activate persulfate for targeted conversion of bisphenol A in wastewater into polymers.

The selective removal of targeted pollutants from complex wastewater is challenging. Herein, a novel persulfate (PS)-based advanced oxidation system equipped with a series of two-dimensional (2D) bimetallic oxide nanosheets (NSs) catalysts is developed to selectively degrade bisphenol A (BPA) within mixed pollutants via initiating nonradical-induced polymerization. Results indicate that the Ni0.60Co0.40Ox NSs demonstrate the highest catalytic efficiency among all Ni-Co NSs catalysts. Specifically, BPA degradation rate is 47.34, 27.26, and 9.72 times higher than that of 4-chlorophenol, phenol, and 2,4-dichlorophenol in the mixed solution, respectively. The lower oxidative potential of BPA in relation to the other pollutants renders it the primary target for oxidation within the PDS activation system. PDS molecules combine on the surface of Ni0.60Co0.40Ox NSs to form the surface-activated complex, triggering the generation of BPA monomer radicals through H-abstraction or electron transfer. These radicals subsequently polymerize on the surface of the catalyst through coupling reactions. Importantly, this polymerization process can occur under typical aquatic environmental conditions and demonstrates resistance to background matrices like Cl- and humic acid due to its inherent nonradical attributes. This study offers valuable insights into the targeted conversion of organic pollutants in wastewater into value-added polymers, contributing to carbon recycle and circular economy.

A nomogram based on quantitative EEG to predict the prognosis of nontraumatic coma patients in the neuro-intensive care unit.

OBJECTIVE: We aimed to establish a quantitative electroencephalography-based prognostic prediction model specifically tailored for nontraumatic coma patients to guide clinical work. METHODS: This retrospective study included 126 patients with nontraumatic coma admitted to the First Affiliated Hospital of Chongqing Medical University from December 2020 to December 2022. Six in-hospital deaths were excluded. The Glasgow Outcome Scale assessed the prognosis at 3 months after discharge. The least absolute shrinkage and selection operator regression analysis and stepwise regression method were applied to select the most relevant predictors. We developed a predictive model using binary logistic regression and then presented it as a nomogram. We assessed the predictive effectiveness and clinical utility of the model. RESULTS: After excluding six deaths that occurred within the hospital, a total of 120 patients were included in this study. Three predictor variables were identified, including APACHE II score [39.129 (1.4244-1074.9000)], sleep cycle [OR: 0.006 (0.0002-0.1808)], and RAV [0.068 (0.0049-0.9500)]. The prognostic prediction model showed exceptional discriminative ability, with an AUC of 0.939 (95 % CI: 0.899-0.979). CONCLUSION: A lack of sleep cycles, smaller relative alpha variants, and higher APACHE II scores were associated with a poor prognosis of nontraumatic coma patients in the neurointensive care unit at 3 months after discharge. CLINICAL IMPLICATION: This study presents a novel methodology for the prognostic assessment of nontraumatic coma patients and is anticipated to play a significant role in clinical practice.

High-Dimensional MR Reconstruction Integrating Subspace and Adaptive Generative Models.

OBJECTIVE: To develop a new method that integrates subspace and generative image models for high-dimensional MR image reconstruction. METHODS: We proposed a formulation that synergizes a low-dimensional subspace model of high-dimensional images, an adaptive generative image prior serving as spatial constraints on the sequence of "contrast-weighted" images or spatial coefficients of the subspace model, and a conventional sparsity regularization. A special pretraining plus subject-specific network adaptation strategy was proposed to construct an accurate generative-network-based representation for images with varying contrasts. An iterative algorithm was introduced to jointly update the subspace coefficients and the multi-resolution latent space of the generative image model that leveraged an recently proposed intermediate layer optimization technique for network inversion. RESULTS: We evaluated the utility of the proposed method for two high-dimensional imaging applications: accelerated MR parameter mapping and high-resolution MR spectroscopic imaging. Improved performance over state-of-the-art subspace-based methods was demonstrated in both cases. CONCLUSION: The proposed method provided a new way to address high-dimensional MR image reconstruction problems by incorporating an adaptive generative model as a data-driven spatial prior for constraining subspace reconstruction. SIGNIFICANCE: Our work demonstrated the potential of integrating data-driven and adaptive generative priors with canonical low-dimensional modeling for high-dimensional imaging problems.

The great potential of polysaccharides from natural resources in the treatment of asthma: A review.

Despite significant progress in diagnosis and treatment, asthma remains a serious public health challenge. The conventional therapeutic drugs for asthma often have side effects and unsatisfactory clinical efficacy. Therefore, it is very urgent to develop new drugs to overcome the shortcomings of conventional drugs. Natural polysaccharides provide enormous resources for the development of drugs or health products, and they are receiving a lot of attention from scientists around the world due to their safety, effective anti-inflammatory and immune regulatory properties. Increasing evidence shows that polysaccharides have favorable biological activities in the respiratory disease, including asthma. This review provides an overview of primary literature on the recent advances of polysaccharides from natural resources in the treatment of asthma. The mechanisms and practicability of polysaccharides, including polysaccharides from plants, fungus, bacteria, alga, animals and others are reviewed. Finally, the further research of polysaccharides in the treatment of asthma are discussed. This review can provide a basis for further study of polysaccharides in the treatment of asthma and provides guidance for the development and clinical application of novel asthma treatment drugs.

Dietary Zinc Ameliorates TNBS-Induced Colitis in Mice Associated with Regulation of Th1/Th2/Th17 Balance and NF-κB/NLRP3 Signaling Pathway.

Inflammatory bowel diseases (IBDs), including Crohn's disease and ulcerative colitis, are chronic relapsing inflammatory gastrointestinal tract diseases of uncertain origin, which are frequently associated with zinc deficiency. Animal models have a considerable value in elucidating the process of IBD. In this study, 50 male C57BL/6 J mice were randomly assigned to five groups: control group (Con), 2,4,6-trinitrobenzenesulfonic acid (TNBS) group, and three zinc supplementation groups, namely 160 ppm group, 400 ppm group, and 1000 ppm group. The results showed that supplementation of dietary zinc with zinc oxide could effectively relieve the severity of ulcerative colitis induced by TNBS in mice. We demonstrate that the protective mechanism involves the immunomodulation of dietary zinc by increasing CD3+, CD3+CD8+, and Th2 cells, suppressing Th1 and Th17 cells, and decreasing the production of serum IL-1ß and IL-18. The dietary zinc oxide seems to be able to suppress the NF-κB/NLRP3 signaling pathway by downregulating the mRNA and protein expression of NIK, IKK, NF-κB, and NLRP3. The results suggest that dietary supplementation of zinc oxide may protect against colitis, and proper daily zinc supplementation may reduce the risk of IBD.

Semantic Invariant Multi-View Clustering With Fully Incomplete Information.

Robust multi-view learning with incomplete information has received significant attention due to issues such as incomplete correspondences and incomplete instances that commonly affect real-world multi-view applications. Existing approaches heavily rely on paired samples to realign or impute defective ones, but such preconditions cannot always be satisfied in practice due to the complexity of data collection and transmission. To address this problem, we present a novel framework called SeMantic Invariance LEarning (SMILE) for multi-view clustering with incomplete information that does not require any paired samples. To be specific, we discover the existence of invariant semantic distribution across different views, which enables SMILE to alleviate the cross-view discrepancy to learn consensus semantics without requiring any paired samples. The resulting consensus semantics remains unaffected by cross-view distribution shifts, making them useful for realigning/imputing defective instances and forming clusters. We demonstrate the effectiveness of SMILE through extensive comparison experiments with 13 state-of-the-art baselines on five benchmarks. Our approach improves the clustering accuracy of NoisyMNIST from 19.3%/23.2% to 82.7%/69.0% when the correspondences/instances are fully incomplete. We will release the code after acceptance.

Rosmarinic acid alleviate CORT-induced depressive-like behavior by promoting neurogenesis and regulating BDNF/TrkB/PI3K signaling axis.

Rosmarinic acid (RA), a natural phenolic acid compound with a variety of bioactive properties. However, the antidepressant activity and mechanism of RA remain unclear. The aim of this study is to investigate the effects and potential mechanisms of RA on chronic CORT injection induced depression-like behavior in mice. Male C57BL/6 J mice were intraperitoneally injected with CORT (10 mg/kg) and were orally given RA daily (10 or 20 mg/kg) for 21 consecutive days. In vitro, the HT22 cells were exposed to CORT (200 µM) with RA (12.5, 25 or 50 µM) and LY294002 (a PI3K inhibitor) or ANA-12 (a TrkB inhibitor) treatment. The depression-like behavior and various neurobiological changes in the mice and cell injury and levels of target proteins in vitro were subsequently assessed. Here, RA treatment decreased the expression of p-GR/GR, HSP90, FKBP51, SGK-1 in mice hippocampi. Besides, RA increased the average optical density of Nissl bodies and number of dendritic spines in CA3 region, and enhanced Brdu and DCX expression and synaptic transduction in DG region, as well as up-regulated both the BDNF/TrkB/CREB and PI3K/Akt/mTOR signaling. Moreover, RA reduced structural damage and apoptosis in HT22 cells, increased the differentiation and maturation of them. More importantly, LY294002, but not ANA-12, reversed the effect of RA on GR nuclear translocation. Taken together, RA exerted antidepressant activities by modulating the hippocampal glucocorticoid signaling and hippocampal neurogenesis, which related to the BDNF/TrkB/PI3K signaling axis regulating GR nuclear translocation, provide evidence for the application of RA as a candidate for depression.