Inflammatory biomarkers differentiate the stage of maturation in chronic subdural hematomas

The Evolution and Recurrence of Chronic Subdural Hematoma was Associated with Different Distribution of Macrophage M1/M2 Polarization

The pathogenesis of chronic subdural hematoma (CSDH) has traditionally been associated with inflammation, but the efficacy of anti-inflammatory drug therapy is limited. Recent literatures suggest that immune dysregulation rather than sole inflammation, plays a vital role in the development of CSDH. In this study, the dynamics of macrophage polarization were explored to elucidate changes in immune status during CSDH evolution. Nakaguchi computerized tomography (CT) classification method was employed to categorize CSDH into four types, including homogeneous, laminar, separated and trabecular subtypes. Samples from the hematoma cavity were collected. The percentages of M1 and M2 macrophages and the M1/M2 proportion were determined by flow cytometry. The M1-related inflammatory (IL-1β, IL-6, IL-12, and TNF-α) and M2-related anti-inflammatory factors (IL-4, IL-10, IL-13, and TGF-β) were measured by ELISA. The relationship among CT subtypes, macrophage polarization and recurrence were evaluated by univariate and multivariate logistic regression analyses. A nomogram was established to score significant factors, and the bootstrap method was used for internal validation to calculate the concordance index (C-index) and generating calibration plots. A total of 127 patients with CSDH were included, among which 28 cases (22.04%) experienced recurrence within three months post-surgery. Significant differences were found in the percentages of M1 and M2 macrophages, the M1/M2 ratio, and related cytokines among different subtypes in CT classifications (P < 0.001). As CSDH evolved according to different CT subtypes, M1 macrophages gradually decreased, while M2 macrophages significantly increased, accompanied by a downregulation of the M1/M2 ratio. The similar changes were found in M1-related inflammatory cytokines (IL-1β, IL-6, IL-12, and TNF-α) and M2-related anti-inflammatory cytokines. Additionally, compared to the non-recurrence group, the recurrence group had higher percentages of M1 and M1/M2 ratio, but lower percentages of M2 (P < 0.05). LASSO regression analysis identified the dichotomized Nakaguchi CT classification, degree of brain atrophy, postoperative drainage volume, and hematoma volume were independent risk factors of recurrence (P < 0.05). Based on this, the established nomogram prediction model showed an AUC of 0.898, indicating good predictive efficacy and accuracy. The study demonstrated that the immune status within the hematoma cavity shifts from an inflammatory to an anti-inflammatory state during CSDH progression. Furthermore, it was found that altered immune balance gives rise to CSDH evolution and recurrence following surgery instead of inflammation itself.

Methods and clinical biomarker discovery for targeted proteomics using Olink technology

PURPOSE

This paper is to offer insights for designing research utilizing Olink technology to identify biomarkers and potential therapeutic targets for disease treatment.

EXPERIMENTAL DESIGN

We discusses the application of Olink technology in oncology, cardiovascular, respiratory and immune-related diseases, and Outlines the advantages and limitations of Olink technology.

RESULTS

Olink technology simplifies the search for therapeutic targets, advances proteomics research, reveals the pathogenesis of diseases, and ultimately helps patients develop precision treatments.

CONCLUSIONS

Although proteomics technology has been rapidly developed in recent years, each method has its own disadvantages, so in the future research, more methods should be selected for combined application to verify each other.

Peptidomics insights: neutrophil extracellular traps (NETs) related to the chronic subdural hemorrhage

Chronic subdural hemorrhage (CSDH) refers to a hematoma with an envelope between the dura mater and the arachnoid membrane and is more common among the elderly. It was reported that the dura mater, which is highly vascularized with capillary beds, precapillary arterioles and postcapillary venules play an important role in the protection of the central nervous system (CNS). Numerous evidences suggests that peptides play an important role in neuroprotection of CNS. However, whether dura mater derived endogenous peptides participate in the pathogenesis of CSDH remains undetermined. In the current study, the peptidomic profiles were performed in human dura of CSDH (three patients) and the relative control group (three non-CSDH samples) by LC-MS (liquid chromatography-mass spectrometry). The results suggested that a total of 569 peptides were differentially expressed in the dura matter of CSDH compared with relative controls, including 217 up-regulated peptides and 352 down-regulated peptides. Gene Ontology (GO) analysis demonstrated that the precursor proteins of those differentially expressed peptides were involved in the various biological processes. Interestingly, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis suggested that NETs participated in the pathogenies of CSDH. Further investigate showed that H3Cit was significantly elevated in the dural and hematoma membranes of patients with CSDH compared to patients without CSDH. Taken together, our results showed the differentially expressed peptides in human dura mater of CSDH and demonstrated that NETs formation in the dural and hematoma membranes might be involved in the pathogenesis of CSDH. It is worth noting that pharmacological inhibition of NETs may have potential therapeutic implications for CSDH.

A Linear Regression Equation for Predicting the Residual Volume of Chronic Subdural Hematoma 1 Week After Surgery

Objective

The outcome of chronic subdural hematoma (CSDH) is influenced not only by the choice of treatment but also by various baseline characteristics. The main objective of this study is to identify the risk factors that can affect the prognosis of CSDH and develop a regression equation based on these risk factors.

Methods

A total of 212 patients with CSDH were included in the study. We collected clinical data including age, gender, and so on, and radiological data including preoperative hematoma volume (V1), effusion volume 1 day after surgery (V2), gas volume 1 day after surgery (V3), and so on. These were considered independent variables, while residual volume 1 week after surgery (V4) was the dependent variable. Univariate linear regression analysis was performed to identify factors that were significantly related. Subsequently, multivariate linear regression analysis was conducted to determine the relationship between each independent variable and the dependent variable. Multiple linear regression analysis was used to obtain a regression equation predicting V4.

Results

We have found that age (t = 3.109, P = 0.002), aspirin (t = 2.762, P = 0.006), hemostatic agents (haemocoagulase, t = 3.731, P < 0.001; vitamin K, t = 2.824, P = 0.005 < 0.05), V2 (t = 8.73, P < 0.001), and V3 (t = 5.968, P < 0.001) are significantly associated with V4. Furthermore, we have developed a regression equation that can predict this volume with CSDH. The fit of the model is robust with an R-squared value of 65.2% > 50%.

Conclusion

Age, aspirin, hemostatic agent, V2, and V3 are significantly associated with V4. We developed a regression equation to predict this volume with CSDH.