Predictive Value of Degranulating Factors of Neutrophils in Massive Cerebral Infarction

Neutrophil migration participates in the side effect of recombinant human tissue plasminogen activator

AIMS

Ischemic stroke remains a challenge in medical research because of the limited treatment options. Recombinant human tissue plasminogen activator (rtPA) is the primary treatment for recanalization. However, nearly 50% of the patients experience complications that result in ineffective reperfusion. The precise factors contributing to ineffective reperfusion remain unclear; however, recent studies have suggested that immune cells, notably neutrophils, may influence the outcome of rtPA thrombolysis via mechanisms such as the formation of neutrophil extracellular traps. This study aimed to explore the nonthrombolytic effects of rtPA on neutrophils and highlight their contribution to ineffective reperfusion.

METHODS

We evaluated the effects of rtPA treatment on middle cerebral artery occlusion in rats. We also assessed neutrophil infiltration and activation after rtPA treatment in vitro and in vivo in a small cohort of patients with massive cerebral ischemia (MCI).

RESULTS

rtPA increased neutrophil infiltration into the brain microvessels and worsened blood-brain barrier damage during ischemia. It also increased the neutrophil counts of the patients with MCI.

CONCLUSION

Neutrophils play a crucial role in promoting ischemic injury and blood-brain barrier disruption, making them potential therapeutic targets.

Value of novel thrombotic markers for predicting occurrence of the malignant cerebral artery infarction: a prospective clinical study

Objective

This study investigated the diagnostic performance of thrombin-antithrombin complex (TAT), plasmin-α2 plasmin inhibitor complex (PIC), tissue plasminogen activator-plasminogen activator inhibitor complex (t-PAIC), and thrombomodulin (TM) in predicting the progression of massive cerebral infarction to the malignant cerebral artery infarction.

Method

A total of 71 patients with massive cerebral infarction confirmed by imaging examination were divided into malignant cerebral artery infarction group (MCAI) and non-malignant cerebral artery infarction group (NMCAI) based on whether they progressed to MCAI after admission. TAT, PIC, t-PAIC, and TM were measured immediately after admission. The predictive performance was analyzed by the receiver characteristic operating curve (ROC).

Result

The median plasma concentrations of TM, PIC, TAT, and t-PAIC in the MCAI patients at admission were 10.65 IU/mL, 1.17 μg/mL, 12.25 ng/mL, and 13.85 ng/mL, respectively, which were higher than those in the NMCAI patients (9.00 IU/mL, 1.07 μg/mL, 4.60 ng/mL, and 8.70 ng/mL), and the difference was statistically significant (p = 0.045, p = 0.035, p = 0.004, and p = 0.003). Elevated plasma t-PAIC concentration was shown to be an independent risk factor for progression of massive cerebral infarction to MCAI (OR = 1.131) by multivariate logistic regression analysis. ROC curve analysis showed that t-PAIC was the best predictor of MCAI (AUC = 74.7%), with a sensitivity of 75.0% and specificity of 75.9% when t-PAIC concentration was ≥12.4 ng/mL; TAT had the highest specificity in predicting MCAI, with a specificity of 90.7% when the TAT concentration was ≥13.5 ng/mL.

Conclusion

The detection of PIC, TAT, t-PAIC, and TM is a comprehensive assessment of vascular endothelial damage and activation of the coagulation and fibrinolytic systems and has predictive value for poor prognosis in patients with MCAI. The widespread use of these tests will likely greatly improve the early diagnosis rate of MCAI.

Bioinformatic identification of hub genes Myd88 and Ccl3 and TWS-119 as a potential agent for the treatment of massive cerebral infarction

Background

Massive cerebral infarction (MCI) causes severe neurological deficits, coma and can even result in death. Here, we identified hub genes and pathways after MCI by analyzing microarray data from a murine model of ischemic stroke and identified potential therapeutic agents for the treatment of MCI.

Methods

Microarray expression profiling was performed using the GSE28731 and GSE32529 datasets from the Gene Expression Omnibus (GEO) database. Data from a sham group (n = 6 mice) and a middle cerebral artery occlusion (MCAO) group (n = 7 mice) were extracted to identify common differentially expressed genes (DEGs). After identifying gene interactions, we generated a protein-protein interaction (PPI) network with Cytoscape software. Then, the MCODE plug-in in Cytoscape was used to determine key sub-modules according to MCODE scores. Enrichment analyses were then conducted on DEGs in the key sub-modules to evaluate their biological functions. Furthermore, hub genes were identified by generating the intersections of several algorithms in the cytohubba plug-in; these genes were then verified in other datasets. Finally, we used Connectivity MAP (CMap) to identify potential agents for MCI therapy.

Results

A total of 215 common DEGs were identified and a PPI network was generated with 154 nodes and 947 edges. The most significant key sub-module had 24 nodes and 221 edges. Gene ontology (GO) analysis showed that the DEGs in this sub-module showed enrichment in inflammatory response, extracellular space and cytokine activity in terms of biological process, cellular component and molecular function, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that TNF signaling was the most enriched pathway. Myd88 and Ccl3 were identified as hub genes and TWS-119 was identified as the most potential therapeutic agent by CMap.

Conclusions

Bioinformatic analysis identified two hub genes (Myd88 and Ccl3) for ischemic injury. Further analysis identified TWS-119 as the best potential candidate for MCI therapy and that this target may be associated with TLR/MyD88 signaling.

Predicative factors and development of a nomogram for postoperative delayed neurocognitive recovery in elderly patients with gastric cancer

BACKGROUND

Delayed neurocognitive recovery (DNR) is a common complication after radical gastrectomy and closely associated with poor outcomes. This study aimed to investigate predictors and develop a nomogram prediction model for DNR.

METHODS

Elderly gastric cancer (GC) patients (≥ 65 years) undergoing elective laparoscopic radical gastrectomy between 2018 and 2022 were prospectively included in this study. DNR was diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V, 2013). Independent risk factors for DNR were screened by the multivariate logistic regression analysis. Based on these factors, the nomogram model was established and validated by R.

RESULTS

A total of 312 elderly GC patients were enrolled in the training set, with an incidence of DNR within postoperative 1 month of 23.4% (73/312). Multivariate logistic regression analysis indicated that age (OR: 1.207, 95%CI: 1.113-1.309, P < 0.001), nutritional risk screening 2002 (NRS2002) score (OR: 1.716, 95%CI: 1.211-2.433, P = 0.002), neutrophil-to-lymphocyte ratio (NLR) (OR: 1.976, 95%CI: 1.099-3.552, P = 0.023), albumin-to-fibrinogen ratio (AFR) (OR: 0.774, 95%CI: 0.620-0.966, P = 0.024), and prognostic nutritional index (PNI) (OR: 0.768, 95%CI: 0.706-0.835, P < 0.001) were five independent factors for DNR in elderly GC patients. The constructed nomogram model based on these five factors has a good predictive value for DNR with an area under the curve (AUC) of 0.863.

CONCLUSIONS

In conclusions, the established nomogram model based on age, NRS-2002, NLR, AFR, and PNI has a well predictive value for postoperative DNR in elderly GC patients.

Association between myeloperoxidase and the risks of ischemic stroke, heart failure, and atrial fibrillation: A Mendelian randomization study

BACKGROUND AND AIMS

The causality between myeloperoxidase (MPO) and cardiovascular disease still remains unclear. We performed a two-sample Mendelian randomization (MR) study to estimate the potential causal effect of MPO on the risks of ischemic stroke, ischemic stroke subtypes, heart failure (HF), and atrial fibrillation (AF).

METHODS AND RESULTS

Seventeen independent single-nucleotide polymorphisms associated with MPO levels were identified as instrumental variables from a European-descent genome-wide association study. Summary-level data on ischemic stroke originated from the Multiancestry Genome-wide Association Study of Stroke Consortium with 440 328 European individuals. We used the inverse-variance weighted method to assess the potential causality of plasma MPO with ischemic stroke and its subtypes in the main analysis. Genetically determined higher plasma MPO concentration was significantly associated with increased risks of ischemic stroke (odds ratio [OR] per standard deviation [SD] increase, 1.05; 95% confidence interval [CI], 1.02-1.09; P = 0.002) and cardioembolic stroke (CES) (OR per SD increase, 1.10; 95% CI, 1.03-1.18; P = 0.005), but was not associated with risks of large artery stroke or small vessel stroke. In the secondary analysis, MPO was associated with a high risk of HF (OR per SD increase, 1.05; 95% CI, 1.02-1.07; P = 0.001) and AF (OR per SD increase, 1.04; 95% CI, 1.01-1.07; P = 0.004). MR-Egger regression showed no directional pleiotropy for all associations, and the sensitivity analyses further confirmed these findings.

CONCLUSION

High plasma MPO levels were potentially associated with increased risks of ischemic stroke, CES, HF, and AF, suggesting that MPO plays an important role in the development of cardiovascular disease.

High neutrophil percentage and neutrophil-lymphocyte ratio in acute phase of ischemic stroke predict cognitive impairment: A single-center retrospective study in China

Background and aims

Recently, various hemocyte and blood cell ratios have garnered researchers' attention, as a low-cost, widely prevalent, and easy-to-measure index for diagnosing and predicting disease. Therefore, we sought to investigate the effect and predictive value of the peripheral blood neutrophil percentage and neutrophil-lymphocyte ratio (NLR) in the acute phase of ischemic stroke (AIS) in post-stroke cognitive impairment (PSCI).

Methods

We selected 454 patients with mild AIS and acquired general clinical data. The patients were divided into PSCI and post-stroke no cognitive impairment (PSNCI) groups according to their Montreal Cognitive Assessment (MOCA) scores. We assessed whether there were differences in clinical data, peripheral blood neutrophil percentage, and NLR values between the different groups. We also analyzed the independent influences on the occurrence of PSCI using a binary logistic regression. Receiver operating characteristic (ROC) curves were used to analyze the predictive value of the above inflammatory indicators and models containing different inflammatory indicators for PSCI.

Results

In total, 454 patients were included, of whom 253 (55.7%) patients were in the PSCI group, with a mean age of 62.15 ± 7.34 years and median neutrophil percentage and NLR of 0.64 (0.32–0.95) and 2.39 (0.71–54.46), respectively. Both neutrophil percentage (adjusted OR = 1.025; 95% confidence interval: 1.005–1.406) and NLR as a categorical variable (Q5, adjusted OR = 2.167; 95% CI: 1.127–4.166) were independent risk factors for PSCI, and the Q5 group (NLR ≥ 4.05) had significantly worse overall cognition and executive function.

Conclusions

Neutrophil percentage and NLR in the acute phase of AIS were independently associated with PSCI, and a high NLR was strongly associated with executive function. In addition, neutrophil percentage and NLR have diagnostic values for PSCI.