KnoMol: A Knowledge-Enhanced Graph Transformer for Molecular Property Prediction.

Molecular property prediction (MPP) techniques are pivotal in reducing drug development costs by preemptively predicting bioactivity and ADMET properties. Despite the application of numerous deep learning approaches, enhancing the representational capacity of these models remains a significant challenge. This paper presents a novel knowledge-based Transformer framework, KnoMol, designed to improve the understanding of molecular structures. KnoMol integrates expert chemical knowledge into the Transformer, emulating the analytical methods of medicinal chemists. Additionally, the multiperspective attention mechanism provides a more precise way to represent ring systems. In the evaluation experiments, KnoMol achieved state-of-the-art performance on both MoleculeNet and small-scale data sets, surpassing existing models in terms of accuracy and generalization. Further research indicated that the incorporation of knowledge significantly reduces KnoMol's reliance on data volumes, offering a solution to the challenge of data scarcity. Moreover, KnoMol identified several new inhibitors of HER2 in a case study, demonstrating its value in real-world applications. Overall, this research not only provides a powerful tool for MPP but also serves as a successful precedent for embedding knowledge into Transformers, with positive implications for computer-aided drug discovery and the development of MPP algorithms.

Population pharmacokinetics of nirmatrelvir/ritonavir in critically ill Chinese COVID-19 patients and recommendations for medication use: a two-center retrospective study.

BACKGROUND: This study aimed to establish population pharmacokinetics (PPK) models of nirmatrelvir/ritonavir in critically ill Chinese patients with the coronavirus disease 2019 (COVID-19) infection, explore factors affecting the pharmacokinetics (PK) of nirmatrelvir/ritonavir. METHODS: A total of 285 serum samples and clinical data were collected from 152 patients. The PPK models of nirmatrelvir/ritonavir were analyzed using nonlinear mixed-effect modeling (NONMEM) approach. The optimal dosing regimen for patients with different renal function was determined using Monte Carlo simulations. RESULTS: The population typical values of apparent clearance (CL/F) and apparent volume of distribution (V/F) of nirmatrelvir were 2.26 L/h and 15.3 L, respectively. Notably, creatinine clearance (CrCL) significantly influenced the PK variation of nirmatrelvir. Monte Carlo simulations suggested that patients with mild-to-moderate renal impairment experienced a 22.0－59.9% increase in the area under the curve (AUC) when they were administered a standard dose of nirmatrelvir compared to those with normal renal function. The AUC in patients with severe renal impairment after administration of 150 mg q12h nirmatrelvir was similar to that in patients with normal renal function after administration of 300 mg q12h nirmatrelvir. CONCLUSIONS: PPK modeling and simulation provided a reference for the rational clinical application of nirmatrelvir/ritonavir in critically ill Chinese patients.

Building a Hospital Pharmacist Workforce by a Diversified and Position-Oriented Learning System.

Background: The role of hospital pharmacists has shifted from primarily ensuring drug supply to providing comprehensive pharmaceutical care. To accommodate this shift, new positions are needed. The traditional training model for hospital pharmacists is no longer sufficient for the evolving demands of pharmaceutical care and these new roles. This study aimed to describe the development of a position-oriented learning system explicitly tailored for hospital pharmacists and to assess its impact on workforce development and pharmacy service. Methods: The position-oriented learning system for hospital pharmacists, aimed at enhancing training and workforce development, was evaluated based on two critical criteria: the completion rate of learning modules and the subsequent improvement in pharmaceutical care at the hospital. The completion rate assessed the engagement and effectiveness of the training content. At the same time, the improvement in pharmaceutical care evaluated practical outcomes such as percentages of patients who received pharmaceutical care and percentages of inappropriate medication orders intercepted. Results: In 2021, 218 employees participated in the learning system. The pharmacy department has identified 22 pharmacists for various positions through this system. The quantity and quality of pharmaceutical care have improved significantly. Conclusion: The position-oriented diversified learning system achieves the perfect combination of department development direction and individual career planning of employees. The learning system can significantly improve the learning efficiency of pharmacists, enhance the quality of various pharmaceutical care, and promote the development of disciplines.

Discovery of New Phenyltetrazolium Derivatives as Ferroptosis Inhibitors for Treating Ischemic Stroke: An Example Development from Free Radical Scavengers.

Ferroptosis is a promising therapeutic target for injury-related diseases, yet diversity in ferroptosis inhibitors remains limited. In this study, initial structure optimization led us to focus on the bond dissociation enthalpy (BDE) of the N-H bond and the residency time of radical scavengers in a phospholipid bilayer, which may play an important role in ferroptosis inhibition potency. This led to the discovery of compound D1, exhibiting potent ferroptosis inhibition, high radical scavenging, and moderate membrane permeability. D1 demonstrated significant neuroprotection in an oxygen glucose deprivation/reoxygenation (OGD/R) model and reduced infarct volume in an in vivo stroke model upon intravenous treatment. Further screening based on this strategy identified NecroX-7 and Eriodictyol-7-O-glucoside as novel ferroptosis inhibitors with highly polar structural characteristics. This approach bridges the gap between free radical scavengers and ferroptosis inhibitors, providing a foundation for research and insights into novel ferroptosis inhibitor development.

Activation of glutamatergic neurons in the somatosensory cortex promotes remyelination in ischemic vascular dementia.

Chronic cerebral hypoperfusion can cause progressive demyelination as well as ischemic vascular dementia, however no effective treatments are available. Here, based on magnetic resonance imaging studies of patients with white matter damage, we found that this damage is associated with disorganized cortical structure. In a mouse model, optogenetic activation of glutamatergic neurons in the somatosensory cortex significantly promoted oligodendrocyte progenitor cell (OPC) proliferation, remyelination in the corpus callosum, and recovery of cognitive ability after cerebral hypoperfusion. The therapeutic effect of such stimulation was restricted to the upper layers of the cortex, but also spanned a wide time window after ischemia. Mechanistically, enhancement of glutamatergic neuron-OPC functional synaptic connections is required to achieve the protection effect of activating cortical glutamatergic neurons. Additionally, skin stroking, an easier method to translate into clinical practice, activated the somatosensory cortex, thereby promoting OPC proliferation, remyelination and cognitive recovery following cerebral hypoperfusion. In summary, we demonstrated that activating glutamatergic neurons in the somatosensory cortex promotes the proliferation of OPCs and remyelination to recover cognitive function after chronic cerebral hypoperfusion. It should be noted that this activation may provide new approaches for treating ischemic vascular dementia via the precise regulation of glutamatergic neuron-OPC circuits.

HDAC9 Deficiency Upregulates cGMP-dependent Kinase II to Mitigate Neuronal Apoptosis in Ischemic Stroke.

Histone deacetylase 9 (HDAC9) is implicated in ischemic stroke by genome-wide association studies. We conducted a series of experiments using a mouse model of ischemic stroke (middle cerebral artery occlusion followed by reperfusion) to examine the potential role of HDAC9. Briefly, HDAC9 was upregulated in the penumbra. Deletion of HDAC9 from neurons reduced infarction volume, inhibited neuronal apoptosis in the penumbra, and improved neurological outcomes. HDAC9 knockout from neurons in the penumbra upregulated cGMP-dependent kinase II (cGK II), blocking which abrogated the protective effects of HDAC9 deletion. Mechanistically, HDAC9 interacts with the transcription factor MEF2, thereby inhibiting MEF2's binding to the promoter region of the cGK II gene, which results in the suppression of cGK II expression. Inhibiting the interaction between HDAC9 and MEF2 by BML210 upregulated cGK II and attenuated ischemic injury in mice. These results encourage targeting the HDAC9-MEF2 interaction in developing novel therapy against ischemic stroke.

Discovery of orally bioavailable phenyltetrazolium derivatives for the acute treatment and the secondary prevention of ischemic stroke.

The potential for secondary stroke prevention, which can significantly reduce the risk of recurrent strokes by almost 90%, underscores its critical importance. N-butylphthalide (NBP) has emerged as a promising treatment for acute cerebral ischemia, yet its efficacy for secondary stroke prevention is hindered by inadequate pharmacokinetic properties. This study, driven by a comprehensive structural analysis, the iterative process of structure optimization culminated in the identification of compound B4, which demonstrated exceptional neuroprotective efficacy and remarkable oral exposure and oral bioavailability. Notably, in an in vivo transient middle cerebral artery occlusion (tMCAO) model, B4 substantially attenuated infarct volumes, surpassing the effectiveness of NBP. While oral treatment with B4 exhibited stronger prevention potency than NBP in photothrombotic (PT) model. In summary, compound B4, with its impressive oral bioavailability and potent neuroprotective effects, offers promise for both acute ischemic stroke treatment and secondary stroke prevention.

Discovery of a potent CDKs/FLT3 PROTAC with enhanced differentiation and proliferation inhibition for AML.

AML is an aggressive malignancy of immature myeloid progenitor cells. Discovering effective treatments for AML through cell differentiation and anti-proliferation remains a significant challenge. Building on previous studies on CDK2 PROTACs with differentiation-inducing properties, this research aims to enhance CDKs degradation through structural optimization to facilitate the differentiation and inhibit the proliferation of AML cells. Compound C3, featuring a 4-methylpiperidine ring linker, effectively degraded CDK2 with a DC50 value of 18.73 ± 10.78 nM, and stimulated 72.77 ± 3.51 % cell differentiation at 6.25 nM in HL-60 cells. Moreover, C3 exhibited potent anti-proliferative activity against various AML cell types. Degradation selectivity analysis indicated that C3 could be endowed with efficient degradation of CDK2/4/6/9 and FLT3, especially FLT3-ITD in MV4-11 cells. These findings propose that C3 combined targeting CDK2/4/6/9 and FLT3 with enhanced differentiation and proliferation inhibition, which holds promise as a potential treatment for AML.

Cell-specific IL-1R1 regulates the regional heterogeneity of microglial displacement of GABAergic synapses and motor learning ability.

Microglia regulate synaptic function in various ways, including the microglial displacement of the surrounding GABAergic synapses, which provides important neuroprotection from certain diseases. However, the physiological role and underlying mechanisms of microglial synaptic displacement remain unclear. In this study, we observed that microglia exhibited heterogeneity during the displacement of GABAergic synapses surrounding neuronal soma in different cortical regions under physiological conditions. Through three-dimensional reconstruction, in vitro co-culture, two-photon calcium imaging, and local field potentials recording, we found that IL-1ß negatively modulated microglial synaptic displacement to coordinate regional heterogeneity in the motor cortex, which impacted the homeostasis of the neural network and improved motor learning ability. We used the Cre-Loxp system and found that IL-1R1 on glutamatergic neurons, rather than that on microglia or GABAergic neurons, mediated the negative effect of IL-1ß on synaptic displacement. This study demonstrates that IL-1ß is critical for the regional heterogeneity of synaptic displacement by coordinating different actions of neurons and microglia via IL-1R1, which impacts both neural network homeostasis and motor learning ability. It provides a theoretical basis for elucidating the physiological role and mechanism of microglial displacement of GABAergic synapses.

MOINER: A Novel Multiomics Early Integration Framework for Biomedical Classification and Biomarker Discovery.

In the context of precision medicine, multiomics data integration provides a comprehensive understanding of underlying biological processes and is critical for disease diagnosis and biomarker discovery. One commonly used integration method is early integration through concatenation of multiple dimensionally reduced omics matrices due to its simplicity and ease of implementation. However, this approach is seriously limited by information loss and lack of latent feature interaction. Herein, a novel multiomics early integration framework (MOINER) based on information enhancement and image representation learning is thus presented to address the challenges. MOINER employs the self-attention mechanism to capture the intrinsic correlations of omics-features, which make it significantly outperform the existing state-of-the-art methods for multiomics data integration. Moreover, visualizing the attention embedding and identifying potential biomarkers offer interpretable insights into the prediction results. All source codes and model for MOINER are freely available https://github.com/idrblab/MOINER.

Application of Northern Goshawk Back-Propagation Artificial Neural Network in the Prediction of Monohydroxycarbazepine Concentration in Patients with Epilepsy.

INTRODUCTION: A northern goshawk back-propagation artificial neural network (NGO-BPANN) model was established to predict monohydroxycarbazepine (MHD) concentration in patients with epilepsy. METHODS: The data were collected from 108 Han Chinese patients with epilepsy on oxcarbazepine monotherapy. The results of 14 genotype variates were selected as the input layer in the first BPANN model, and the variables that had a more significant impact on the plasma concentration of MHD were retained. With demographic characteristics and clinical laboratory test results, the genotypes of SCN1A rs2298771 and SCN2A rs17183814 were used to construct the BPANN model. The BPANN model was comprehensively validated and used to predict the MHD plasma concentration of five patients with epilepsy in our hospital. RESULTS: The model demonstrated favorable fitness metrics, including a mean squared error of 0.00662, a gradient magnitude of 0.00753, an absence of validation tests amounting to zero, and a correlation coefficient of 0.980. Sex, BMI, and the genotype SCN1A rs2298771 were ranked highest by the absolute mean impact value (MIV), which is primarily associated with the concentration of MHD. The test group exhibited a range of - 20.84% to 31.03% bias between the predicted and measured values, with a correlation coefficient of 0.941 between the two. With BPANN, the MHD nadir concentration could be predicted precisely. CONCLUSION: The NGO-BPANN model exhibits exceptional predictive capability and can be a practical instrument for forecasting MHD concentration in patients with epilepsy. CLINICAL TRIAL REGISTRATION: www.chiCTR-OOC-17012141 .

Prevalence and clinical significance of potential drug-drug interactions among lung transplant patients.

Background: Drug-drug interactions (DDIs) are a major but preventable cause of adverse drug reactions. There is insufficient information regarding DDIs in lung transplant recipients. Objective: This study aimed to determine the prevalence of potential DDIs (pDDIs) in intensive care unit (ICU) lung transplant recipients, identify the real DDIs and the most frequently implicated medications in this vulnerable population, and determine the risk factors associated with pDDIs. Methods: This retrospective cross-sectional study included lung transplant recipients from January 2018 to December 2021. Pertinent information was retrieved from medical records. All prescribed medications were screened for pDDIs using the Lexicomp® drug interaction software. According to this interaction software, pDDIs were classified as C, D, or X (C = monitor therapy, D = consider therapy modification, X = avoid combination). The Drug Interaction Probability Scale was used to determine the causation of DDIs. All statistical analysis was performed in SPSS version 26.0. Results: 114 patients were qualified for pDDI analysis, and total pDDIs were 4051. The most common type of pDDIs was category C (3323; 82.0%), followed by D (653; 16.1%) and X (75; 1.9%). Voriconazole and posaconazole were the antifungal medicine with the most genuine DDIs. Mean tacrolimus concentration/dose (Tac C/D) before or after co-therapy was considerably lower than the Tac C/D during voriconazole or posaconazole co-therapy (p < 0.001, p = 0.027). Real DDIs caused adverse drug events (ADEs) in 20 patients. Multivariable logistic regression analyses found the number of drugs per patient (OR, 1.095; 95% CI, 1.048-1.145; p < 0.001) and the Acute Physiology and Chronic Health Evaluation II (APACHE Ⅱ) score (OR, 1.097; 95% CI, 1.021-1.179; p = 0.012) as independent risk factors predicting category X pDDIs. Conclusion: This study revealed a high incidence of both potential and real DDIs in ICU lung transplant recipients. Immunosuppressive drugs administered with azole had a high risk of causing clinically significant interactions. The number of co-administered drugs and APACHE Ⅱ score were associated with an increased risk of category × drug interactions. Close monitoring of clinical and laboratory parameters is essential for ensuring successful lung transplantation and preventing adverse drug events associated with DDIs.

SingPro: a knowledge base providing single-cell proteomic data.

Single-cell proteomics (SCP) has emerged as a powerful tool for detecting cellular heterogeneity, offering unprecedented insights into biological mechanisms that are masked in bulk cell populations. With the rapid advancements in AI-based time trajectory analysis and cell subpopulation identification, there exists a pressing need for a database that not only provides SCP raw data but also explicitly describes experimental details and protein expression profiles. However, no such database has been available yet. In this study, a database, entitled 'SingPro', specializing in single-cell proteomics was thus developed. It was unique in (a) systematically providing the SCP raw data for both mass spectrometry-based and flow cytometry-based studies and (b) explicitly describing experimental detail for SCP study and expression profile of any studied protein. Anticipating a robust interest from the research community, this database is poised to become an invaluable repository for OMICs-based biomedical studies. Access to SingPro is unrestricted and does not mandate a login at: http://idrblab.org/singpro/.

Discovery of a potent and selective PARP1 degrader promoting cell cycle arrest via intercepting CDC25C-CDK1 axis for treating triple-negative breast cancer.

PARP1 is a multifaceted component of DNA repair and chromatin remodeling, making it an effective therapeutic target for cancer therapy. The recently reported proteolytic targeting chimera (PROTAC) could effectively degrade PARP1 through the ubiquitin-proteasome pathway, expanding the therapeutic application of PARP1 blocking. In this study, a series of nitrogen heterocyclic PROTACs were designed and synthesized through ternary complex simulation analysis based on our previous work. Our efforts have resulted in a potent PARP1 degrader D6 (DC50 = 25.23 nM) with high selectivity due to nitrogen heterocyclic linker generating multiple interactions with the PARP1-CRBN PPI surface, specifically. Moreover, D6 exhibited strong cytotoxicity to triple negative breast cancer cell line MDA-MB-231 (IC50 = 1.04 µM). And the proteomic results showed that the antitumor mechanism of D6 was found that intensifies DNA damage by intercepting the CDC25C-CDK1 axis to halt cell cycle transition in triple-negative breast cancer cells. Furthermore, in vivo study, D6 showed a promising PK property with moderate oral absorption activity. And D6 could effectively inhibit tumor growth (TGI rate = 71.4 % at 40 mg/kg) without other signs of toxicity in MDA-MB-321 tumor-bearing mice. In summary, we have identified an original scaffold and potent PARP1 PROTAC that provided a novel intervention strategy for the treatment of triple-negative breast cancer.

Initial therapeutic target attainment of perampanel in pediatric patients with epilepsy.

Perampanel is a promising option for the treatment of pediatric epilepsy, but its plasma concentration varies among patients. This retrospective study aimed to investigate the initial target attainment of perampanel plasma concentration in pediatric patients with epilepsy in China. Inpatients admitted from January 2020 to December 2021 in a tertiary hospital were retrospectively included according to pre-set criteria. Demographic characteristics of patients and dosing strategies and therapeutic drug monitoring results were collected. A total of 137 pediatric patients (84 females and 53 males, aged from 0.6 to 16.4 years) were include for analysis. The perampanel concentrations varied greatly from 60 to 1,560 mg/L among patients, but 89.8% had suitable perampanel concentrations (100-1,000 ng/mL). The concomitant use of enzyme-inductive antiepileptic drugs (AEDs) was the only identified risk factor associated with target nonattainment (OR = 5.92, 95% confidence interval 1.68-20.9). Initial perampanel target attainment in pediatric patients is satisfactory. Routine therapeutic drug monitoring to achieved the suggested concentration range for these patients may be unnecessary, except for those receiving combined enzyme inductive AEDs.

An interpretable ensemble learning model facilitates early risk stratification of ischemic stroke in intensive care unit: Development and external validation of ICU-ISPM.

Ischemic stroke (IS) is a common and severe condition that requires intensive care unit (ICU) admission, with high mortality and variable prognosis. Accurate and reliable predictive tools that enable early risk stratification can facilitate interventions to improve patient outcomes; however, such tools are currently lacking. In this study, we developed and validated novel ensemble learning models based on soft voting and stacking methods to predict in-hospital mortality from IS in the ICU using two public databases: MIMIC-IV and eICU-CRD. Additionally, we identified the key predictors of mortality and developed a user-friendly online prediction tool for clinical use. The soft voting ensemble model, named ICU-ISPM, achieved an AUROC of 0.861 (95% CI: 0.829-0.892) and 0.844 (95% CI: 0.819-0.869) in the internal and external test cohorts, respectively. It significantly outperformed the APACHE scoring system and was more robust than individual models. ICU-ISPM obtained the highest performance compared to other models in similar studies. Using the SHAP method, the model was interpretable, revealing that GCS score, age, and intubation were the most important predictors of mortality. This model also provided a risk stratification system that can effectively distinguish between low-, medium-, and high-risk patients. Therefore, the ICU-ISPM is an accurate, reliable, interpretable, and clinically applicable tool, which is expected to assist clinicians in stratifying IS patients by the risk of mortality and rationally allocating medical resources. Based on ICU-ISPM, an online risk prediction tool was further developed, which was freely available at: http://ispm.idrblab.cn/.

Upregulation of HDAC9 in hippocampal neurons mediates depression-like behaviours by inhibiting ANXA2 degradation.

Major depressive disorder (MDD) is a pervasive and devastating mental disease. Broad spectrum histone deacetylase (HDAC) inhibitors are considered to have potential for the treatment of depressive phenotype in mice. However, due to its non-specific inhibition, it has extensive side effects and can not be used in clinical treatment of MDD. Therefore, finding specific HDAC subtypes that play a major role in the etiology of MDD is the key to develop corresponding specific inhibitors as antidepressants in the future. Copy number variation in HDAC9 gene is thought to be associated with the etiology of some psychiatric disorders. Herein, we found that HDAC9 was highly expressed in the hippocampus of chronic restraint stress (CRS) mouse model of depression. Upregulation of HDAC9 expression in hippocampal neurons of mice induced depression-like phenotypes, including anhedonia, helplessness, decreased dendritic spine density, and neuronal hypoexcitability. Moreover, knockdown or knockout of HDAC9 in hippocampal neurons alleviated depression-like phenotypes caused by chronic restraint stress (CRS) in WT mice. Importantly, using immunoprecipitation-mass spectrometry (IP-MS), we further found that Annexin A2 (ANXA2) was coupled to and deacetylated by HDAC9. This coupling resulted in the inhibition of ubiquitinated ANXA2 degradation and then mediates depression-like behavior. Overall, we discovered a previously unrecognized role for HDAC9 in hippocampal neurons in the pathogenesis of depression, indicating that inhibition of HDAC9 might be a promising clinical strategy for the treatment of depressive disorders.

Prevalence and influencing factors of probiotic usage among colorectal cancer patients in China: A national database study.

Probiotics have become increasingly popular among cancer patients. However, there is limited data from a real-world setting. This study aims to conduct a retrospective analysis to understand the trend of probiotic prescriptions in Chinese colorectal cancer patients. The Mann-Kendall and Cochran-Armitage trend test was applied to estimate the trend significance. Gephi software identified the combination of probiotic strains. The binary logistic regression investigated influence factors, and Spearman's rank correlation coefficient calculated correlations between probiotics and antitumor drug usage. The probiotic prescription percentage increased from 3.3% in 2015 to 4.2% in 2021 (Z = 12.77, p < 0.001). Although 48.3% of probiotic prescriptions had no indication-related diagnosis, diarrhea (OR 10.91, 95% CI 10.57-11.26) and dyspepsia (3.97, 3.82-4.12) included prescriptions most likely to contain probiotics. Prescriptions from the tertiary hospital (1.43,1.36-1.50), clinics (1.30, 1.28-1.33), and senior patients (1.018 per year, 1.017-1.019) were more likely to contain probiotics. Most probiotic prescriptions (95.0%) contained one probiotic product but multiple strains (69.3%). Enterococcus faecalis (49.7%), Lactobacillus acidophilus (39.4%), and Clostridium butyricum (27.9%) were the most prescribed strains. The probiotics co-prescribed with antitumor agents increased rapidly from 6.6% to 13.8% in seven years (Z = 15.31, p < 0.001). Oral fluorouracil agents (2.35, 2.14-2.59), regorafenib (1.70,1.27-2.26), and irinotecan (1.27,1.15-1.41) had a higher probability to co-prescribed with probiotics. There was no correlation between probiotic strain selection and specific antitumor drug use. The increasing prescription of probiotics in colorectal cancer patients in China may be related to treating the gastrointestinal toxicity of anti-cancer drugs. With unapproved indications and a lack of strain selectivity, evidence-based guidelines are urgently needed to improve probiotic use in this population.

Salvianolic acid B ameliorates neuroinflammation and neuronal injury via blocking NLRP3 inflammasome and promoting SIRT1 in experimental subarachnoid hemorrhage.

The nucleotide-binding oligomerization domain (NOD)-like receptor family pyrin domain containing 3 (NLRP3) inflammasome-mediated immuno-inflammatory response plays a critical role in exacerbating early brain injury (EBI) after subarachnoid hemorrhage (SAH). Salvianolic acid B (SalB) has previously been shown to suppress neuroinflammatory responses in many disorders. Meanwhile, a previous study has demonstrated that SalB mitigated oxidative damage and neuronal degeneration in a prechiasmatic injection model of SAH. However, the therapeutic potential of SalB on immuno-inflammatory responses after SAH remains unclear. In the present study, we explored the therapeutic effects of SalB on neuroinflammatory responses in an endovascular perforation SAH model. We observed that SalB ameliorated SAH-induced functional deficits. Additionally, SalB significantly mitigated microglial activation, pro-inflammatory cytokines release, and neuronal injury. Mechanistically, SalB inhibited NLRP3 inflammasome activation and increased sirtuin 1 (SIRT1) expression after SAH. Administration of EX527, an inhibitor of SIRT1, abrogated the anti-inflammatory effects of SalB against SAH and further induced NLRP3 inflammasome activation. In contrast, MCC950, a potent and selective NLRP3 inflammasome inhibitor, reversed the detrimental effects of SIRT1 inhibition by EX527 on EBI. These results indicated that SalB effectively repressed neuroinflammatory responses and neuronal damage after SAH. The action of SalB appeared to be mediated by blocking NLRP3 inflammasome and promoting SIRT1 signaling.