Tiam1-mediated maladaptive plasticity underlying morphine tolerance and hyperalgesia.

Opioid pain medications, such as morphine, remain the mainstay for treating severe and chronic pain. Prolonged morphine use, however, triggers analgesic tolerance and hyperalgesia (OIH), which can last for a long period after morphine withdrawal. How morphine induces these detrimental side effects remains unclear. Here, we show that morphine tolerance and OIH are mediated by Tiam1-coordinated synaptic structural and functional plasticity in the spinal nociceptive network. Tiam1 is a Rac1 GTPase guanine nucleotide exchange factor (GEF) that promotes excitatory synaptogenesis by modulating actin cytoskeletal dynamics. We found that prolonged morphine treatment activated Tiam1 in the spinal dorsal horn and Tiam1 ablation from spinal neurons eliminated morphine antinociceptive tolerance and OIH. At the same time, the pharmacological blockade of Tiam1-Rac1 signaling prevented the development and reserved the established tolerance and OIH. Prolonged morphine treatment increased dendritic spine density and synaptic NMDA receptor (NMDAR) activity in spinal dorsal horn neurons, both of which required Tiam1. Furthermore, co-administration of the Tiam1 signaling inhibitor NSC23766 was sufficient to abrogate morphine tolerance in chronic pain management. These findings identify Tiam1-mediated maladaptive plasticity in the spinal nociceptive network as an underlying cause for the development and maintenance of morphine tolerance and OIH and provide a promising therapeutic target to reduce tolerance and prolong morphine use in chronic pain management.

Novel insights into the role of ubiquitination in osteoarthritis.

Ubiquitination (Ub) and deubiquitination are crucial post-translational modifications (PTMs) that precisely regulate protein degradation. Under the catalysis of a cascade of E1-E2-E3 ubiquitin enzymes, ubiquitination extensively regulates protein degradation exerting direct impact on various cellular processes, while deubiquitination opposes the effect of ubiquitination and prevents proteins from degradation. Notably, such dynamic modifications have been widely investigated to be implicated in cell cycle, transcriptional regulation, apoptosis and so on. Therefore, dysregulation of ubiquitination and deubiquitination could lead to certain diseases through abnormal protein accumulation and clearance. Increasing researches have revealed that the dysregulation of catalytic regulators of ubiquitination and deubiquitination triggers imbalance of cartilage homeostasis that promotes osteoarthritis (OA) progression. Hence, it is now believed that targeting on Ub enzymes and deubiquitinating enzymes (DUBs) would provide potential therapeutic pathways. In the following sections, we will summarize the biological role of Ub enzymes and DUBs in the development and progression of OA by focusing on the updating researches, with the aim of deepening our understanding of the underlying molecular mechanism of OA pathogenesis concerning ubiquitination and deubiquitination, so as to explore novel potential therapeutic targets of OA treatment.

Mediation of PM2.5-induced cytotoxicity: the role of P2X7 receptor in NR8383 cells.

Ambient fine particulate matter (PM2.5) is a threat to public health. The P2 X 7purinergic receptor (P2X7R) is a modulator that responds to inflammation. Yet the role of P2X7R in the mediation of PM2.5-induced pulmonary cytotoxicity is rarely investigated. In this study, the expression of P2X7R and its effect on cell viability, oxidative damage, apoptosis, mitochondrial dysfunction and underlying mechanism following PM2.5 treatment in rat alveolar macrophages (NR8383) were analyzed. The outcome indicated that PM2.5 exposure significantly increased the expression of P2X7R, while P2X7R antagonist oATP markedly alleviate the production of reactive oxygen species (ROS), Nitrite Oxidation (NO), mitochondrial membrane potential, apoptosis rate, and release of inflammatory cytokines. In contrast, P2X7 agonist BzATP showed opposite effect in PM2.5-treated NR8383 cells. Therefore, these results demonstrated that P2X7R participated in PM2.5-induced pulmonary toxicity, while the blockade of P2X7R is a promising therapeutic approach of treating PM2.5-induced lung diseases.

A target-triggered fluorescence-SERS dual-signal nano-system for real-time imaging of intracellular telomerase activity.

Telomerase (TE) is a promising diagnostic and prognostic biomarker for many cancers. Quantification of TE activity in living cells is of great significance in biomedical and clinical research. Conventional fluorescence-based sensors for quantification of intracellular TE may suffer from problems of fast photobleaching and auto-fluorescence of some endogenous molecules, and hence are liable to produce false negative or positive results. To address this issue, a fluorescence-SERS dual-signal nano-system for real-time imaging of intracellular TE was designed by functionalizing a bimetallic Au@Ag nanostructure with 4-p-mercaptobenzoic acid (internal standard SERS tag) and a DNA hybrid complex consisted of a telomerase primer strand and its partially complimentary strand modified with Rhodamine 6G. The bimetallic Au@Ag nanostructure serves as an excellent SERS-enhancing and fluorescence-quenching substrate. Intracellular TE will trigger the extension of the primer strand and cause the shedding of Rhodamine 6G-modified complimentary strand from the nano-system through intramolecular DNA strand displacement, resulting in the recovery of the fluorescence of Rhodamine 6G and decrease in its SERS signal. Both the fluorescence of R6G and the ratio between the SERS signals of 4-p-mercaptobenzoic acid and Rhodamine 6G can be used for in situ imaging of intracellular TE. Experimental results showed that the proposed nano-system was featured with low background, excellent cell internalization efficiency, good biocompatibility, high sensitivity, good selectivity, and robustness to false positive results. It can be used to distinguish cancer cells from normal ones, identify different types of cancer cells, as well as perform absolute quantification of intracellular TE, which endows it with great potential in clinical diagnosis, target therapy and prognosis of cancer patients.

Rapid detection and quantification of adulteration in saffron by excitation-emission matrix fluorescence combined with multi-way chemometrics.

BACKGROUND: Saffron has gained people's attention and love for its unique flavor and valuable edible value, but the problem of saffron adulteration in the market is serious. It is urgent for us to find a simple and rapid identification and quantitative estimation of adulteration in saffron. Therefore, excitation-emission matrix (EEM) fluorescence combined with multi-way chemometrics was proposed for the detection and quantification of adulteration in saffron. RESULTS: The fluorescence composition analysis of saffron and saffron adulterants (safflower, marigold and madder) were accomplished by alternating trilinear decomposition (ATLD) algorithm. ATLD and two-dimensional principal component analysis combined with k-nearest neighbor (ATLD-kNN and 2DPCA-kNN) and ATLD combined with data-driven soft independent modeling of class analogies (ATLD-DD-SIMCA) were applied to rapid detection of adulteration in saffron. 2DPCA-kNN and ATLD-DD-SIMCA methods were adopted for the classification of chemical EEM data, first with 100% correct classification rate. The content of adulteration of adulterated saffron was predicted by the N-way partial least squares regression (N-PLS) algorithm. In addition, new samples were correctly classified and the adulteration level in adulterated saffron was estimated semi-quantitatively, which verifies the reliability of these models. CONCLUSION: ATLD-DD-SIMCA and 2DPCA-kNN are recommended methods for the classification of pure saffron and adulterated saffron. The N-PLS algorithm shows potential in prediction of adulteration levels. These methods are expected to solve more complex problems in food authenticity. © 2023 Society of Chemical Industry.

Hemoglobin levels and clinical outcomes after extracorporeal circulation auxiliary to open heart surgery: a retrospective cohort study.

BACKGROUND: Extracorporeal circulation auxiliary to open heart surgery is a common procedure used to treat heart diseases. However, the optimal transfusion strategy for patients undergoing this surgery remains a subject of debate. This study aims to investigate the association between hemoglobin levels and clinical outcomes in patients undergoing extracorporeal circulation auxiliary to open heart surgery, with the ultimate goal of improving surgical success rates and enhancing patients' quality of life. METHODS: A retrospective analysis was conducted on data from the Medical Information Mart for Intensive Care IV 2.2 (MIMIC-IV 2.2) database, including 4144 patients. The patients were categorized into five groups based on their minimum hemoglobin levels during hospitalization. Baseline characteristics, clinical scores, laboratory results, and clinical outcome data were collected. Statistical analyses utilized descriptive statistics, ANOVA or Kruskal-Wallis tests, Kaplan-Meier method, and Log-rank test. RESULTS: The results revealed a significant correlation between hemoglobin levels and in-hospital mortality, as well as mortality rates at 30 days, 60 days, and 180 days (p < 0.001). Patients with lower hemoglobin levels exhibited higher mortality rates. However, once hemoglobin levels exceeded 7g/dL, no significant difference in mortality rates was observed (p = 0.557). Additionally, lower hemoglobin levels were associated with prolonged hospital stay, ICU admission time, and mechanical ventilation time (p < 0.001). Furthermore, hemoglobin levels were significantly correlated with complication risk, norepinephrine dosage, and red blood cell transfusion volume (p < 0.001). However, there was no significant difference among the groups in terms of major complications, specifically sepsis (p > 0.05). CONCLUSION: The study highlights the importance of managing hemoglobin levels in patients undergoing heart surgery with extracorporeal circulation. Hemoglobin levels can serve as valuable indicators for predicting clinical outcomes and guiding treatment decisions. Physicians should carefully consider hemoglobin levels to optimize transfusion strategies and improve postoperative patient outcomes. Further research and intervention studies are warranted to validate and implement these findings in clinical practice.

Characterization of synaptic structural plasticity in mouse spinal dorsal horn neurons.

Here, we present a pipeline for the characterization of synaptic structural plasticity in mouse spinal dorsal horn (SDH) neurons. We describe steps for the intra-SDH microinjection of the EGFP virus to sparsely label L4 SDH neurons without laminectomy, wide dynamic range neuron imaging, dendritic spine morphometric analysis, and F-actin to G-actin ratio measurement. This protocol can be applied to investigate the synaptic structural plasticity mechanisms in the SDH as well as in the brain. For complete details on the use and execution of this protocol, please refer to Li et al. (2023).1.

Insights into the Notch signaling pathway in degenerative musculoskeletal disorders: Mechanisms and perspectives.

Degenerative musculoskeletal disorders are a group of age-related diseases of the locomotive system that severely affects the patient's ability to work and cause adverse sequalae such as fractures and even death. The incidence and prevalence of degenerative musculoskeletal disorders is rising owing to the aging of the world's population. The Notch signaling pathway, which is expressed in almost all organ systems, extensively regulates cell proliferation and differentiation as well as cellular fate. Notch signaling shows increased activity in degenerative musculoskeletal disorders and retards the progression of degeneration to some extent. The review focuses on four major degenerative musculoskeletal disorders (osteoarthritis, intervertebral disc degeneration, osteoporosis, and sarcopenia) and summarizes the pathophysiological functions of Notch signaling in these disorders, especially its role in stem/progenitor cells in each disorder. Finally, a conclusion will be presented to explore the research and application of the perspectives on Notch signaling in degenerative musculoskeletal disorders.

Progress of linking gut microbiota and musculoskeletal health: casualty, mechanisms, and translational values.

The musculoskeletal system is important for balancing metabolic activity and maintaining health. Recent studies have shown that distortions in homeostasis of the intestinal microbiota are correlated with or may even contribute to abnormalities in musculoskeletal system function. Research has also shown that the intestinal flora and its secondary metabolites can impact the musculoskeletal system by regulating various phenomena, such as inflammation and immune and metabolic activities. Most of the existing literature supports that reasonable nutritional intervention helps to improve and maintain the homeostasis of intestinal microbiota, and may have a positive impact on musculoskeletal health. The purpose of organizing, summarizing and discussing the existing literature is to explore whether the intervention methods, including nutritional supplement and moderate exercise, can affect the muscle and bone health by regulating the microecology of the intestinal flora. More in-depth efficacy verification experiments will be helpful for clinical applications.

Prognostic significance of the Gustave Roussy immune (GRIm) score in cancer patients: a meta-analysis.

BACKGROUND: The prognostic value of the Gustave Roussy immune (GRIm) score in cancer patients has been widely reported but remains inconsistent. The aim of this study is to systematically investigate the relationship between the GRIm score and survival outcomes in cancer patients. METHODS: Relevant literature was identified using electronic databases including Web of Science, PubMed, and Embase from the inception to March 2023. The primary endpoints were long-term oncological outcomes. Subgroup analysis and sensitivity analysis were conducted during the meta-analysis. RESULTS: Fifteen studies (20 cohorts) including 4997 cancer patients were enrolled. The combined results revealed that patients in the high GRIm group had a deteriorated overall survival (HR = 2.07 95%CI: 1.73-2.48; p < 0.0001; I2 = 62%) and progression-free survival (HR = 1.42; 95%CI: 1.22-1.66; p < 0.0001; I2 = 36%). The prognostic values of GRIm on overall survival and progression-free survival were observed across various tumour types and tumour stages. Sensitivity analysis supported the stability and reliability of the above results. CONCLUSION: Our evidence suggested that the GRIm score could be a valuable prognostic marker in cancer patients, which can be used by clinicians to stratify patients and formulate individualized treatment plans.

Comprehensive transcriptomics and metabolomics analyses reveal that hyperhomocysteinemia is a high risk factor for coronary artery disease in a chinese obese population aged 40-65: a prospective cross-sectional study.

BACKGROUND: Clinical observations suggest a complex relationship between obesity and coronary artery disease (CAD). This study aimed to characterize the intermediate metabolism phenotypes among obese patients with CAD and without CAD. METHODS: Sixty-two participants who consecutively underwent coronary angiography were enrolled in the discovery cohort. Transcriptional and untargeted metabolomics analyses were carried out to screen for key molecular changes between obese patients with CAD (CAD obese), without CAD (Non-CAD obese), and Non-CAD leans. A targeted GC-MS metabolomics approach was used to further identify differentially expressed metabolites in the validation cohorts. Regression and receiver operator curve analysis were performed to validate the risk model. RESULTS: We found common aberrantly expressed pathways both at the transcriptional and metabolomics levels. These pathways included cysteine and methionine metabolism and arginine and proline metabolism. Untargeted metabolomics revealed that S-adenosylhomocysteine (SAH), 3-hydroxybenzoic acid, 2-hydroxyhippuric acid, nicotinuric acid, and 2-arachidonoyl glycerol were significantly elevated in the CAD obese group compared to the other two groups. In the validation study, targeted cysteine and methionine metabolomics analyses showed that homocysteine (Hcy), SAH, and choline were significantly increased in the CAD obese group compared with the Non-CAD obese group, while betaine, 5-methylpropanedioic acid, S-adenosylmethionine, 4-PA, and vitamin B2 (VB2) showed no significant differences. Multivariate analyses showed that Hcy was an independent predictor of obesity with CAD (hazard ratio 1.7; 95%CI 1.2-2.6). The area under the curve based on the Hcy metabolomic (HCY-Mtb) index was 0.819, and up to 0.877 for the HCY-Mtb.index plus clinical variables. CONCLUSION: This is the first study to propose that obesity with hyperhomocysteinemia is a useful intermediate metabolism phenotype that could be used to identify obese patients at high risk for developing CAD.

Anti-interference and non-destructive identification of textile fabrics using front-face excitation-emission matrix fluorescence spectroscopy combined with multi-way chemometrics.

The identification of trace textile fabrics discovered at crime scenes plays a crucial role in the case of forensic investigations. Additionally, in practical situations, fabrics may be contaminated, making identification more challenging. To address the aforementioned issue and promote the application of fabrics identification in forensic analysis, front-face excitation-emission matrix (FF-EEM) fluorescence spectra coupled with multi-way chemometric methods were proposed for the interference-free and non-destructive identification of textile fabrics. Common commercial dyes in the same color range under different materials (cotton, acrylic, and polyester) that cannot be visually distinguished were investigated, and several binary classification models for the identification of dye were established using partial least squares discriminant analysis (PLS-DA). The identification of dyed fabrics in the presence of fluorescent interference was also taken into consideration. In each kind of pattern recognition model mentioned above, the classification accuracy (ACC) of the prediction set was 100%. The alternating trilinear decomposition (ATLD) algorithm was executed to separate mathematically and remove the interference, and the classification model based on the reconstructed spectra attained an accuracy of 100%. These findings indicate that FF-EEM technology combined with multi-way chemometric methods has broad prospects for forensic trace textile fabric identification, especially in the presence of interference.

Tiam1 coordinates synaptic structural and functional plasticity underpinning the pathophysiology of neuropathic pain.

Neuropathic pain is a common, debilitating chronic pain condition caused by damage or a disease affecting the somatosensory nervous system. Understanding the pathophysiological mechanisms underlying neuropathic pain is critical for developing new therapeutic strategies to treat chronic pain effectively. Tiam1 is a Rac1 guanine nucleotide exchange factor (GEF) that promotes dendritic and synaptic growth during hippocampal development by inducing actin cytoskeletal remodeling. Here, using multiple neuropathic pain animal models, we show that Tiam1 coordinates synaptic structural and functional plasticity in the spinal dorsal horn via actin cytoskeleton reorganization and synaptic NMDAR stabilization and that these actions are essential for the initiation, transition, and maintenance of neuropathic pain. Furthermore, an antisense oligonucleotides (ASO) targeting spinal Tiam1 persistently alleviate neuropathic pain sensitivity. Our findings suggest that Tiam1-coordinated synaptic functional and structural plasticity underlies the pathophysiology of neuropathic pain and that intervention of Tiam1-mediated maladaptive synaptic plasticity has long-lasting consequences in neuropathic pain management.

The potential therapeutic roles of Rho GTPases in substance dependence.

Rho GTPases family are considered to be molecular switches that regulate various cellular processes, including cytoskeleton remodeling, cell polarity, synaptic development and maintenance. Accumulating evidence shows that Rho GTPases are involved in neuronal development and brain diseases, including substance dependence. However, the functions of Rho GTPases in substance dependence are divergent and cerebral nuclei-dependent. Thereby, comprehensive integration of their roles and correlated mechanisms are urgently needed. In this review, the molecular functions and regulatory mechanisms of Rho GTPases and their regulators such as GTPase-activating proteins (GAPs) and guanine nucleotide exchange factors (GEFs) in substance dependence have been reviewed, and this is of great significance for understanding their spatiotemporal roles in addictions induced by different addictive substances and in different stages of substance dependence.

Front-face excitation-emission matrix fluorescence spectroscopy combined with interpretable deep learning for the rapid identification of the storage year of Ningxia wolfberry.

Ningxia wolfberry stored for many years may be disguised as fresh wolfberry by unscrupulous traders and sold for huge profits. In this work, the front-face excitation-emission matrix (FF-EEM) fluorescence spectroscopy coupled with interpretable deep learning was proposed to identify the storage year of Ningxia wolfberry in a lossless, fast and accurate way. Alternating trilinear decomposition (ATLD) algorithm was used to decompose the three-way data array obtained by Ningxia wolfberry samples, extracting the chemically meaningful information. Meanwhile, a convolutional neural network (CNN) model for the identification of the storage year of Ningxia wolfberry, called EEMnet, was proposed. The model successfully classified wolfberry samples from different storage years by extracting the subtle feature differences of the spectra, and the correct classification rate of the training set, test set and prediction set was more than 98%. In addition, a series of interpretability analyses were implemented to break the "black box" of the deep learning model. These results indicated that the method based on FF-EEM fluorescence spectroscopy combined with EEMnet could quickly and accurately identify the year of Ningxia wolfberry in a green way, providing a new idea for the identification of the storage years of Chinese medicinal materials.

Fighting age-related orthopedic diseases: focusing on ferroptosis.

Ferroptosis, a unique type of cell death, is characterized by iron-dependent accumulation and lipid peroxidation. It is closely related to multiple biological processes, including iron metabolism, polyunsaturated fatty acid metabolism, and the biosynthesis of compounds with antioxidant activities, including glutathione. In the past 10 years, increasing evidence has indicated a potentially strong relationship between ferroptosis and the onset and progression of age-related orthopedic diseases, such as osteoporosis and osteoarthritis. Therefore, in-depth knowledge of the regulatory mechanisms of ferroptosis in age-related orthopedic diseases may help improve disease treatment and prevention. This review provides an overview of recent research on ferroptosis and its influences on bone and cartilage homeostasis. It begins with a brief overview of systemic iron metabolism and ferroptosis, particularly the potential mechanisms of ferroptosis. It presents a discussion on the role of ferroptosis in age-related orthopedic diseases, including promotion of bone loss and cartilage degradation and the inhibition of osteogenesis. Finally, it focuses on the future of targeting ferroptosis to treat age-related orthopedic diseases with the intention of inspiring further clinical research and the development of therapeutic strategies.

Chemometrics-assisted excitation-emission matrix fluorescence spectroscopy for rapid identification of commercial reconstituted and sweetened grape juices.

As a common fruit juice, grape juice is delicious and nutritious, making it very popular among consumers. However, some illegal manufacturers used shoddy products to lower costs and obtain high profits, which seriously threatens the health and interests of consumers. Hence, this paper proposed excitation-emission matrix (EEM) fluorescence spectroscopy combined with chemometric methods for the rapid identification and classification of commercial grape juices. Spectral characterization of different samples was achieved using the alternating trilinear decomposition (ATLD) algorithm, and chemically meaningful information was obtained and analyzed. Although both reconstituted and sweetened grape juices contain methyl anthranilate (MA) and 2'-aminoacetophenone (o-AAP), the content of MA in sweetened grape juice far exceeds that in reconstituted grape juice, and the MA in sweetened grape juice mainly comes from artificially added grape essence. Then two chemometric methods of hierarchical cluster analysis (HCA) and partial least squares discriminant analysis (PLS-DA) were used for the classification of reconstituted and sweetened grape juices. The results showed that the supervised classification model had a higher correct classification rate (CCR) than the unsupervised classification model, with PLS-DA obtaining 100% CCRs in both training and prediction sets. Therefore, the proposed strategy can be used as a powerful analytical method for the identification and classification of reconstituted and sweetened grape juices and provides a reliable scientific means for ensuring the authenticity and safety of the juice market.

Intelligent analysis of excitation-emission matrix fluorescence fingerprint to identify and quantify adulteration in camellia oil based on machine learning.

Camellia oil (CAO) is a premium edible vegetable oil with medical value and biological activity, but it is susceptible to adulteration. Therefore, the demand for intelligent analysis to decipher the category and proportion of adulterated oil in CAO was the main driver of this work. Excitation-emission matrix fluorescence (EEMF) spectra of 933 vegetable oil samples were characterized by a chemometric method to obtain chemically meaningful information. Authenticity identification models were constructed using four machine learning methods to realize the discrimination of oil species adulterated in CAO mixtures. Meanwhile, quantitative models were established aiming at the fraud of CAO proportion in blended oil. Results showed that the specially constructed CNN obtained the optimal performance when evaluating unseen real-world samples, with a classification accuracy of 95.8% and 92.2%, and mean-absolute quantitative errors between 2.6 and 6.7%. Therefore, EEMF fingerprints coupled with machine learning are expected to provide intelligent and accurate analysis for authenticity detection of CAO.

Telomerase-initiated three-dimensional DNAzyme motor for monitoring of telomerase activity in living cells.

Telomerase (TE) is recognized as a potential biomarker for early diagnosis, monitoring and treatment of cancer. At present, most of the methods for TE detection are only applicable to in vitro assays, and unsuitable for in vivo applications. Though a few intracellular probes have been reported to have good specificity for TE, they do not involve signal amplification, which hinders their applicability in scenarios requiring high sensitivity. It is rather challenging to develop highly sensitive biosensors for intracellular TE detection due to the difficulty in design TE probes with both high specificity and compatibility with signal amplification in living cells. Herein, a highly sensitive and selective three-dimensional DNAzyme motor for monitoring of TE activity in living cells was developed by innovatively integrating TE-mediated chain replacement reaction with a three-dimensional DNA walker. Specifically, the DNAzyme motor was constructed by assembling both DNAzyme substrates and swing arms made up of a hairpin-structured DNAzyme and a telomeric primer onto gold nanoparticles. TE in cells can activate the DNAzyme motor to carry out continuous chain replacement and substrate cutting reactions, and hence realize signal amplification in living cells. The DNAzyme motor was successfully utilized to monitor the dynamic changes of TE activity in four types of cells. Due to the advantages of simple synthesis, good biocompatibility and high sensitivity and specificity for TE, the proposed DNAzyme motor is expected to have great application potential in the early diagnosis of cancer.

TIAM1-mediated synaptic plasticity underlies comorbid depression-like and ketamine antidepressant-like actions in chronic pain.

Chronic pain often leads to depression, increasing patient suffering and worsening prognosis. While hyperactivity of the anterior cingulate cortex (ACC) appears to be critically involved, the molecular mechanisms underlying comorbid depressive symptoms in chronic pain remain elusive. T cell lymphoma invasion and metastasis 1 (Tiam1) is a Rac1 guanine nucleotide exchange factor (GEF) that promotes dendrite, spine, and synapse development during brain development. Here, we show that Tiam1 orchestrates synaptic structural and functional plasticity in ACC neurons via actin cytoskeleton reorganization and synaptic N-methyl-d-aspartate receptor (NMDAR) stabilization. This Tiam1-coordinated synaptic plasticity underpins ACC hyperactivity and drives chronic pain-induced depressive-like behaviors. Notably, administration of low-dose ketamine, an NMDAR antagonist emerging as a promising treatment for chronic pain and depression, induces sustained antidepressant-like effects in mouse models of chronic pain by blocking Tiam1-mediated maladaptive synaptic plasticity in ACC neurons. Our results reveal Tiam1 as a critical factor in the pathophysiology of chronic pain-induced depressive-like behaviors and the sustained antidepressant-like effects of ketamine.