Cardiac index and heart rate as prognostic indicators for mortality in septic shock: A retrospective cohort study from the MIMIC-IV database.

Background: Septic shock is a life-threatening condition that can lead to organ dysfunction and death. In the ICU, monitoring of cardiac index (CI) and heart rate (HR) is commonly used to guide management and predict outcomes in septic shock patients. However, there is a lack of research on the association between CI and HR and the risk of mortality in this patient population. Therefore, the aim of this study was to investigate the relationship between different levels of CI and HR and mortality in septic shock patients. Methods: Data analysis was obtained from the MIMIC-IV version 2.0 database. Sepsis and septic shock were primarily defined by sepsis-3, the third international consensus on sepsis and septic shock. CI was computed using cardiac output (CO) and body surface area (BSA). To evaluate the incidence of CI with respect to each endpoint (7-, 14-, 21-, and 28-day mortality), a restricted cubic spline curve function (RCS) was used. The optimal cutoff value for predicted mortality was determined using the Youden index. Analyses of KM curves, cox regression, and logistic regression were conducted separately to determine the relationship between various CI and HR and 28-day mortality. Results: This study included 1498 patients with septic shock. A U-shaped relationship between CI levels and risk of mortality in septic shock was found by RCS analysis (p < 0.001). CI levels within the intermediate range of 1.85-2.8 L/min/m2 were associated with a mortality hazard ratio (HR) < 1. In contrast, low CI (HR = 1.87 95% CI: 1.01-3.49) and high CI (HR = 1.93 95% CI: 1.26-2.97) had a significantly increased risk of mortality. The AUC for heart rate prediction of mortality by Youden index analysis was 0.70 95%CI:0.64-0.76 with a cut-off value of 93.63 bpm. According to the characteristics of HR and CI, patients were divided into six subgroups HR↓+CI intermediate group (n = 772), HR↓+CI↓ group (n = 126), HR↓+CI↑ group (n = 294), HR↑+CI intermediate group (n = 132), HR↑+CI↓ group (n = 24), and HR↑+CI↑ group (n = 150). The KM curves, COX regression, and logistic regression analysis showed that the survival rates the of HR↓+CI intermediate group, HR↓+CI↓ group, and HR↓+CI↑ were higher than the other groups. The risk factors of HR↑+CI intermediate group, HR↑+CI↓, and HR↑+CI↑ with ICU 28-day mortality were HR = 2.91 (95% CI: 1.39-5.97), HR = 3.67 (95% CI: 1.39-11.63), and HR = 5.77 (95% CI: 2.98-11.28), respectively. Conclusion: Our retrospective study shows that monitoring cardiac index and heart rate in patients with septic shock may help predict the organismal response and hemodynamic consequences, as well as the prognosis. Thus, healthcare providers should carefully monitor changes in these parameters in septic shock patients transferred to the ICU for treatment.

Acute exacerbation prediction of COPD based on Auto-metric graph neural network with inspiratory and expiratory chest CT images.

Chronic obstructive pulmonary disease (COPD) is a widely prevalent disease with significant mortality and disability rates and has become the third leading cause of death globally. Patients with acute exacerbation of COPD (AECOPD) often substantially suffer deterioration and death. Therefore, COPD patients deserve special consideration regarding treatment in this fragile population for pre-clinical health management. Based on the above, this paper proposes an AECOPD prediction model based on the Auto-Metric Graph Neural Network (AMGNN) using inspiratory and expiratory chest low-dose CT images. This study was approved by the ethics committee in the First Affiliated Hospital of Guangzhou Medical University. Subsequently, 202 COPD patients with inspiratory and expiratory chest CT Images and their annual number of AECOPD were collected after the exclusion. First, the inspiratory and expiratory lung parenchyma images of the 202 COPD patients are extracted using a trained ResU-Net. Then, inspiratory and expiratory lung Radiomics and CNN features are extracted from the 202 inspiratory and expiratory lung parenchyma images by Pyradiomics and pre-trained Med3D (a heterogeneous 3D network), respectively. Last, Radiomics and CNN features are combined and then further selected by the Lasso algorithm and generalized linear model for determining node features and risk factors of AMGNN, and then the AECOPD prediction model is established. Compared to related models, the proposed model performs best, achieving an accuracy of 0.944, precision of 0.950, F1-score of 0.944, ad area under the curve of 0.965. Therefore, it is concluded that our model may become an effective tool for AECOPD prediction.

Effectiveness of nirmatrelvir-ritonavir versus azvudine for adult inpatients with severe or critical COVID-19.

BACKGROUND: In China, both nirmatrelvir-ritonavir (Paxlovid) and azvudine have been granted approval to treat adult SARS-CoV-2-infected patients with moderate symptoms. Information about the clinical effect of the two available agents among inpatients with severe or critical COVID-19 is scarce. PURPOSE: To compare the clinical outcomes of Paxlovid and azvudine among adult inpatients with severe or critical COVID-19. METHOD: We conducted a retrospective cohort study in two large medical centres after the epidemic control measures were lifted in China. A new propensity score matched-inverse probability of treatment weighting cohort was constructed to evaluate the in-hospital all-cause mortality, hospital length of stay, Sequential Organ Failure Assessment (SOFA) score and safety. RESULTS: A total of 955 individuals were in the cohort. The antiviral therapy strategies were decided by the senior physician and the supplies of the pharmacy. A total of 451 patients were in the Paxlovid group, and 504 patients were in the azvudine group. Compared with Paxlovid, the effects of azvudine on in-hospital all-cause mortality were not significantly different, and the OR (95% CI) was 1.084 (0.822 to 1.430), and the average hospital length of stay of patients discharged alive was also similar in the azvudine group, and the difference (day) and (95% CI) was 0.530 (-0.334 to 1.393). After 7 days of therapy, the degree of decline in the SOFA score was greater in the Paxlovid group than in the azvudine group (p<0.001). The change in glomerular filtration rate was not significantly different (p=0.824). CONCLUSION: Paxlovid and azvudine had similar effectiveness on in-hospital all-cause mortality and hospital length of stay. Compared with the azvudine group, after 7 days of therapy, the degree of decline in SOFA score was significantly higher in the Paxlovid group. These findings need to be verified in larger prospective studies or randomised controlled trials.

MMDB: Multimodal dual-branch model for multi-functional bioactive peptide prediction.

Bioactive peptides can hinder oxidative processes and microbial spoilage in foodstuffs and play important roles in treating diverse diseases and disorders. While most of the methods focus on single-functional bioactive peptides and have obtained promising prediction performance, it is still a significant challenge to accurately detect complex and diverse functions simultaneously with the quick increase of multi-functional bioactive peptides. In contrast to previous research on multi-functional bioactive peptide prediction based solely on sequence, we propose a novel multimodal dual-branch (MMDB) lightweight deep learning model that designs two different branches to effectively capture the complementary information of peptide sequence and structural properties. Specifically, a multi-scale dilated convolution with Bi-LSTM branch is presented to effectively model the different scales sequence properties of peptides while a multi-layer convolution branch is proposed to capture structural information. To the best of our knowledge, this is the first effective extraction of peptide sequence features using multi-scale dilated convolution without parameter increase. Multimodal features from both branches are integrated via a fully connected layer for multi-label classification. Compared to state-of-the-art methods, our MMDB model exhibits competitive results across metrics, with a 9.1% Coverage increase and 5.3% and 3.5% improvements in Precision and Accuracy, respectively.

Dual-targeting tigecycline nanoparticles for treating intracranial infections caused by multidrug-resistant Acinetobacter baumannii.

Multidrug-resistant (MDR) Acinetobacter baumannii (A. baumannii) is a formidable pathogen responsible for severe intracranial infections post-craniotomy, exhibiting a mortality rate as high as 71%. Tigecycline (TGC), a broad-spectrum antibiotic, emerged as a potential therapeutic agent for MDR A. baumannii infections. Nonetheless, its clinical application was hindered by a short in vivo half-life and limited permeability through the blood-brain barrier (BBB). In this study, we prepared a novel core-shell nanoparticle encapsulating water-soluble tigecycline using a blend of mPEG-PLGA and PLGA materials. This nanoparticle, modified with a dual-targeting peptide Aß11 and Tween 80 (Aß11/T80@CSs), was specifically designed to enhance the delivery of tigecycline to the brain for treating A. baumannii-induced intracranial infections. Our findings demonstrated that Aß11/T80@CSs nanocarriers successfully traversed the BBB and effectively delivered TGC into the cerebrospinal fluid (CSF), leading to a significant therapeutic response in a model of MDR A. baumannii intracranial infection. This study offers initial evidence and a platform for the application of brain-targeted nanocarrier delivery systems, showcasing their potential in administering water-soluble anti-infection drugs for intracranial infection treatments, and suggesting promising avenues for clinical translation.

Multifunctional fluorescence probe for simultaneous detection of viscosity, polarity, and ONOO- and its bioimaging in vitro and vivo.

Intracellular microenvironment (viscosity and polarity) and peroxynitrite ions (ONOO-) are involved in maintaining cell morphology, cell function, and signaling so that it is crucial to explore their level changes in vitro and vivo. In this work, we designed and synthesized a mitochondria-targeted fluorescence probe XBL for monitoring the dynamic changes of viscosity, polarity, and ONOO- based on TICT and ICT mechanism. The fluorescence spectra showed obvious changes for polarity at 500 nm as well as ONOO- and viscosity at 660 nm, respectively. The XBL can image simultaneously viscosity, polarity, and ONOO- in cells, and the results showed excess ONOO- leaded to the increase of viscosity in mitochondrial. The ferroptosis process was accompanied by increase of intracellular viscosity and ONOO- levels (or decrease of polarity), which allowed us to better understand the relevant physiological and pathological processes. The XBL can distinguish normal cells and cancerous cells by the fluorescence intensity changes in green and red channels, and image viscosity in inflamed mice. Thus, XBL can provided the chemical tool to understand the physiological and pathological mechanisms of disease by simultaneous detection of viscosity, polarity and ONOO-.

Single-photon ranging lidar based on multi-repetition-rate pulse train correlation and accumulation.

A single-photon lidar based on multi-repetition-rate pulse train correlation and accumulation is proposed, and a ranging experiment is conducted on a 32 m target. By accumulating the correlation ranging results of pulse trains with internal spacings of 80, 100, and 125 ns, the signal-to-noise ratio of the cross correlation function is improved by about three-fold, which enables our method to improve the ranging precisions by more than 20% compared with the single repetition-rate method, and the shorter the acquisition time, the more obvious the advantage will be. Experimental results show that at an acquisition time of 0.01 s, our method can still achieve a ranging precision of 2.59 cm, while the single repetition-rate method can no longer obtain effective ranging results at this time. This method will be of great significance for realizing high-speed, large-scale unambiguous single-photon lidar ranging.

STING Membrane Prevents Post-Surgery Tissue Adhesion and Tumor Recurrence of Colorectal Cancer.

Surgery is the standard treatment regimen for resectable colorectal cancer (CRC). However, it is very hard to completely remove all cancer cells in clinical practice, leading to the high recurrence rates of the disease. Moreover, the post-surgery tissue adhesion greatly prevents the possibility of reoperation, significantly limiting the long-term surviving of CRC patients. To overcome CRC recurrence and avoid the post-surgery tissue adhesion, this work develops a novel stimulator of interferon genes "STING" membrane based on the coaxial electrospinning technology and hyaluronic acid modification. A reactive oxygen species responsive prodrug of gambogic acid (GB) and a potent STING agonist (CDN) are coloaded in the core-shell structure of the membrane, which endows the loaded drug with sustained and sequential release patterns. The localized delivery of GB and CDN can selectively induce efficient immunogenic cell death of cancer cells and then evoke the systemic anticancer immunity by activating the Cyclic GMP-AMP (cGAMP) synthase/STING pathway. As-designed "STING" membrane not only safely prevents tumor recurrence through the synergistic chemoimmunotherapy but also efficiently avoids the post-surgery tissue adhesion, facilitating the clinical intervention of CRC.

Metal-organic cages for gas adsorption and separation.

The unique high surface area and tunable cavity size endow metal-organic cages (MOCs) with superior performance and broad application in gas adsorption and separation. Over the past three decades, for instance, numerous MOCs have been widely explored in adsorbing diverse types of gas including energy gases, greenhouse gases, toxic gases, noble gases, etc. To gain a better understanding of the structure-performance relationships, great endeavors have been devoted to ligand design, metal node regulation, active metal site construction, cavity size adjustment, and function-oriented ligand modification, thus opening up routes toward rationally designed MOCs with enhanced capabilities. Focusing on the unveiled structure-performance relationships of MOCs towards target gas molecules, this review consists of two parts, gas adsorption and gas separation, which are discussed separately. Each part discusses the cage assembly process, gas adsorption strategies, host-guest chemistry, and adsorption properties. Finally, we briefly overviewed the challenges and future directions in the rational development of MOC-based sorbents for application in challenging gas adsorption and separation, including the development of high adsorption capacity MOCs oriented by adsorbability and the development of highly selective adsorption MOCs oriented by separation performance.

Systematic review on antibacterial photodynamic therapeutic effects of transition metals ruthenium and iridium complexes.

The prevalence of antibiotic-resistant pathogenic bacteria poses a significant threat to public health and ranks among the principal causes of morbidity and mortality worldwide. Antimicrobial photodynamic therapy is an emerging therapeutic technique that has excellent potential to embark upon antibiotic resistance problems. The efficacy of this therapy hinges on the careful selection of suitable photosensitizers (PSs). Transition metal complexes, such as Ruthenium (Ru) and Iridium (Ir), are highly suitable for use as PSs because of their surface plasmonic resonance, crystal structure, optical characteristics, and photonics. These metals belong to the platinum family and exhibit similar chemical behavior due to their partially filled d-shells. Ruthenium and Iridium-based complexes generate reactive oxygen species (ROS), which interact with proteins and DNA to induce cell death. As photodynamic therapeutic agents, these complexes have been widely studied for their efficacy against cancer cells, but their potential for antibacterial activity remains largely unexplored. Our study focuses on exploring the antibacterial photodynamic effect of Ruthenium and Iridium-based complexes against both Gram-positive and Gram-negative bacteria. We aim to provide a comprehensive overview of various types of research in this area, including the structures, synthesis methods, and antibacterial photodynamic applications of these complexes. Our findings will provide valuable insights into the design, development, and modification of PSs to enhance their photodynamic therapeutic effect on bacteria, along with a clear understanding of their mechanism of action.

Metatranscriptomics revealed the molecular characterization of circulating enterovirus strains causing aseptic meningitis in children in Wuxi, China.

Enteroviruses are major etiological agents of aseptic meningitis globally, however information on circulating enterovirus types associated with this disease in Wuxi, China is limited. In this study, cerebrospinal fluid samples were collected from 20 pediatric aseptic meningitis cases in a Wuxi hospital in 2020 and subjected to metagenomic analysis to detect pathogens. Enterovirus B was detected in 9 cases, including 7 echovirus 18 (E18) and 2 echovirus 11 (E11) strains. The E18 strains exhibited 87.5-98.2% nucleotide identity and phylogenetically clustered with other China E18 strains, while the E11 strains showed 97.59% identity and clustered within the D5 subgroup along with other China E11 strains. One E18 strain was identified as a novel recombinants with a distinct recombination breakpoint within 3D gene. These findings expand knowledge on enteroviruses associated with pediatric aseptic meningitis in Wuxi, and highlight the circulation of genetically diverse E18 and E11 strains, including novel E18 recombinants. Characterization of enterovirus diversity by metagenomic analysis is important for molecular diagnosis and epidemiological tracking of aseptic meningitis cases. Continued surveillance of circulating enterovirus strains in Wuxi that may cause future outbreaks is warranted.

Gastrointestinal manifestations of critical ill heatstroke patients and their associations with outcomes: A multicentre, retrospective, observational study.

BACKGROUND: Extreme heat exposure is a growing health problem, and the effects of heat on the gastrointestinal (GI) tract is unknown. This study aimed to assess the incidence of GI symptoms associated with heatstroke and its impact on outcomes. AIM: To assess the incidence of GI symptoms associated with heatstroke and its impact on outcomes. METHODS: Patients admitted to the intensive care unit (ICU) due to heatstroke were included from 83 centres. Patient history, laboratory results, and clinically relevant outcomes were recorded at ICU admission and daily until up to day 15, ICU discharge, or death. GI symptoms, including nausea/vomiting, diarrhoea, flatulence, and bloody stools, were recorded. The characteristics of patients with heatstroke concomitant with GI symptoms were described. Multivariable regression analyses were performed to determine significant predictors of GI symptoms. RESULTS: A total of 713 patients were included in the final analysis, of whom 132 (18.5%) patients had at least one GI symptom during their ICU stay, while 26 (3.6%) suffered from more than one symptom. Patients with GI symptoms had a significantly higher ICU stay compared with those without. The mortality of patients who had two or more GI symptoms simultaneously was significantly higher than that in those with one GI symptom. Multivariable logistic regression analysis revealed that older patients with a lower GCS score on admission were more likely to experience GI symptoms. CONCLUSION: The GI manifestations of heatstroke are common and appear to impact clinically relevant hospitalization outcomes.

Analysis of intestinal flora and cognitive function in maintenance hemodialysis patients using combined 16S ribosome DNA and shotgun metagenome sequencing.

BACKGROUND: Cognitive impairment is widely prevalent in maintenance hemodialysis (MHD) patients, and seriously affects their quality of life. The intestinal flora likely regulates cognitive function, but studies on cognitive impairment and intestinal flora in MHD patients are lacking. METHODS: MHD patients (36) and healthy volunteers (18) were evaluated using the Montreal Cognitive Function Scale, basic clinical data, and 16S ribosome DNA (rDNA) sequencing. Twenty MHD patients and ten healthy volunteers were randomly selected for shotgun metagenomic analysis to explore potential metabolic pathways of intestinal flora. Both16S rDNA sequencing and shotgun metagenomic sequencing were conducted on fecal samples. RESULTS: Roseburia were significantly reduced in the MHD group based on both 16S rDNA and shotgun metagenomic sequencing analyses. Faecalibacterium, Megamonas, Bifidobacterium, Parabacteroides, Collinsella, Tyzzerella, and Phascolarctobacterium were positively correlated with cognitive function or cognitive domains. Enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways included oxidative phosphorylation, photosynthesis, retrograde endocannabinoid signaling, flagellar assembly, and riboflavin metabolism. CONCLUSION: Among the microbiota, Roseburia may be important in MHD patients. We demonstrated a correlation between bacterial genera and cognitive function, and propose possible mechanisms.

SERS imaging investigation of the removal efficiency of pesticide on vegetable leaves by using different surfactants.

Pesticide residues on vegetables could be removed by commercial detergents to guarantee food safety, but the removal efficiencies of different formulations of detergents need to be further investigated. In this work, surface enhanced Raman scattering (SERS) imaging method due to its good space resolution as well as high sensitivity is used to track the thiram residue, and evaluate the pesticide removing efficiencies by mixtures of several surfactants at different ratios. Sodium linear alkylbenzene sulphonate-alkyl glycoside (LAS-APG) with the ratio at 5:5 and the concentration at 0.2 % show the best removing effect. In addition, HPLC method is employed to validate the results of SERS imaging. Furthermore, LAS-APG mixture could be efficiently washed out from the leaves through simple household cleaning, meaning no secondary contamination. It is perspective that SERS imaging is an effective technique to explore the effect of fruit and vegetable detergents in removing pesticide residues.

COPD stage detection: leveraging the auto-metric graph neural network with inspiratory and expiratory chest CT images.

Chronic obstructive pulmonary disease (COPD) is a common lung disease that can lead to restricted airflow and respiratory problems, causing a significant health, economic, and social burden. Detecting the COPD stage can provide a timely warning for prompt intervention in COPD patients. However, existing methods based on inspiratory (IN) and expiratory (EX) chest CT images are not sufficiently accurate and efficient in COPD stage detection. The lung region images are autonomously segmented from IN and EX chest CT images to extract the [Formula: see text] lung radiomics and [Formula: see text] 3D CNN features. Furthermore, a strategy for concatenating and selecting features was employed in COPD stage detection based on radiomics and 3D CNN features. Finally, we combine all the radiomics, 3D CNN features, and factor risks (age, gender, and smoking history) to detect the COPD stage based on the Auto-Metric Graph Neural Network (AMGNN). The AMGNN with radiomics and 3D CNN features achieves the best performance at 89.7[Formula: see text] of accuracy, 90.9[Formula: see text] of precision, 89.5[Formula: see text] of F1-score, and 95.8[Formula: see text] of AUC compared to six classic machine learning (ML) classifiers. Our proposed approach demonstrates high accuracy in detecting the stage of COPD using both IN and EX chest CT images. This method can potentially establish an efficient diagnostic tool for patients with COPD. Additionally, we have identified radiomics and 3D CNN as more appropriate biomarkers than Parametric Response Mapping (PRM). Moreover, our findings indicate that expiration yields better results than inspiration in detecting the stage of COPD.

ZmARF1 positively regulates low phosphorus stress tolerance via modulating lateral root development in maize.

Phosphorus (P) deficiency is one of the most critical factors for plant growth and productivity, including its inhibition of lateral root initiation. Auxin response factors (ARFs) play crucial roles in root development via auxin signaling mediated by genetic pathways. In this study, we found that the transcription factor ZmARF1 was associated with low inorganic phosphate (Pi) stress-related traits in maize. This superior root morphology and greater phosphate stress tolerance could be ascribed to the overexpression of ZmARF1. The knock out mutant zmarf1 had shorter primary roots, fewer root tip number, and lower root volume and surface area. Transcriptomic data indicate that ZmLBD1, a direct downstream target gene, is involved in lateral root development, which enhances phosphate starvation tolerance. A transcriptional activation assay revealed that ZmARF1 specifically binds to the GC-box motif in the promoter of ZmLBD1 and activates its expression. Moreover, ZmARF1 positively regulates the expression of ZmPHR1, ZmPHT1;2, and ZmPHO2, which are key transporters of Pi in maize. We propose that ZmARF1 promotes the transcription of ZmLBD1 to modulate lateral root development and Pi-starvation induced (PSI) genes to regulate phosphate mobilization and homeostasis under phosphorus starvation. In addition, ZmERF2 specifically binds to the ABRE motif of the promoter of ZmARF1 and represses its expression. Collectively, the findings of this study revealed that ZmARF1 is a pivotal factor that modulates root development and confers low-Pi stress tolerance through the transcriptional regulation of the biological function of ZmLBD1 and the expression of key Pi transport proteins.

Determining acute ischemic stroke onset time using machine learning and radiomics features of infarct lesions and whole brain.

Accurate determination of the onset time in acute ischemic stroke (AIS) patients helps to formulate more beneficial treatment plans and plays a vital role in the recovery of patients. Considering that the whole brain may contain some critical information, we combined the Radiomics features of infarct lesions and whole brain to improve the prediction accuracy. First, the radiomics features of infarct lesions and whole brain were separately calculated using apparent diffusion coefficient (ADC), diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) sequences of AIS patients with clear onset time. Then, the least absolute shrinkage and selection operator (Lasso) was used to select features. Four experimental groups were generated according to combination strategies: Features in infarct lesions (IL), features in whole brain (WB), direct combination of them (IW) and Lasso selection again after direct combination (IWS), which were used to evaluate the predictive performance. The results of ten-fold cross-validation showed that IWS achieved the best AUC of 0.904, which improved by 13.5% compared with IL (0.769), by 18.7% compared with WB (0.717) and 4.2% compared with IW (0.862). In conclusion, combining infarct lesions and whole brain features from multiple sequences can further improve the accuracy of AIS onset time.

Targeting the macrophage immunocheckpoint: a novel insight into solid tumor immunotherapy.

Tumor immunotherapy, which targets immune checkpoints, presents a promising strategy for the treatment of various cancer types. However, current clinical data indicate challenges in its application to solid tumors. Recent studies have revealed a significant correlation between the degree of immune response in immunotherapy and the tumor microenvironment, particularly with regard to tumor-infiltrating immune cells. Among these immune cells, macrophages, a critical component, are playing an increasingly vital role in tumor immunotherapy. This review focuses on elucidating the role of macrophages within solid tumors and provides an overview of the progress in immunotherapy approaches centered around modulating macrophage responses through various immune factors. Video Abstract.

Modified Sijunzi Granules Exhibit Hemostatic Effect by Activating Akt and Erk Signal Pathways via Regulating 5-HT and Its Receptors Levels.

OBJECTIVE: To investigate the hemostatic effect of modified Sijunzi Granules (MSG) in primary immune thrombocytopenia (ITP) zebrafish model and explore the potential mechanism. METHODS: AB strain wild type zebrafish were treated with simvastatin (6 µmol/L) for 24 h to establish the hemorrhage model (model control group). The zebrafish were treated with MSG at different doses (55.6, 167, and 500 µg/mL), respectively. The hemostatic effect was assessed by examining the intestinal bleeding and hemostatic rate. 5-Hydroxytryptamine (5-HT) content was determined using enzyme-linked immunosorbent assay (ELISA) assay. The expressions of 5-HT2aR, 5-HT2bR, and SERT genes were detected by quantitative real-time polymerase chain reaction(PCR). The protein expressions of protein kinase B (Akt), p-Akt, extracellular regulated protein kinases (Erk), and p-Erk were examined using Western blot analysis. RESULTS: The intestinal bleeding rate was 37%, 40%, and 80% in the 55.6, 167, and 500 µg/mL dose of MSG, respectively, in which 55.6 and 167 µg/mL MSG dose groups were associated with significantly decreased intestinal bleeding rate when compared with the model control group (70%, P<0.05). Significantly higher hemostatic rates were also observed in the 55.6 (54%) and 167 (52%) µg/mL MSG dose groups (P<0.05). MSG increased the 5-HT content and mRNA expression levels of 5-HT2aR, 5-HT2bR, and SERT (P<0.05). In addition, caspase3/7 activity was inhibited (P<0.05). Significant increase in p-Akt and p-Erk was also detected after treatment with MSG (P<0.05). CONCLUSIONS: MSG could reduce the incidence and severity of intestinal bleeding in zebrafish by activating MAPK/Erk and PI3K/Akt signal pathways through regulating the levels of 5-HT and its receptors, which may provide evidence for the treatment of ITP.