Impact of high platelet turnover on the platelet transcriptome: Results from platelet RNA-sequencing in patients with sepsis

From reticulated platelets to immature platelet fraction: structure, function, and clinical applications

In comparison to mature platelets, reticulated platelets (RPs) are newly released from the bone marrow and exhibit a larger size, higher reactivity, and a greater quantity of RNA, and can be an agile indicator of platelet turnover. The transcriptome associated with platelet function is significantly upregulated in RPs, which is a possible explanation for RPs intrinsic hyper-reactivity. We presented a comprehensive overview of the detection techniques for RPs. Current methods to quantify RPs in clinical routine are flow cytometry and fully automated hematology analyzers (Sysmex-XE/XN, Abbott, ADVIA, Mindray), which make the detection of RPs simpler, faster and more affordable. The proportion of RPs increased in the circulation has potential diagnostic and prognostic values in multiple clinical settings (risk stratification in cardiovascular diseases, the effect on antiplatelet drugs, differential diagnosis of thrombocytopenia, monitor platelet recovery after bone marrow or stem cell transplantation, and other diseases). There have been several studies focusing on RPs in recent years, particularly in cardiovascular disease and thrombocytopenia. In this review we summarizes the current study with regard to RPs and discuss their likely contribution in clinical routine.

Inflammatory indices reflect distinct pathogenic cellular programs driving sepsis progression: The role of mmp9 protein macromolecules

Sepsis is a severe systemic inflammatory response syndrome in which matrix metalloproteinase 9 (MMP9) plays a key role in inflammatory response and cell migration. In this study, we analyzed different sepsis phenotypes to explore the role of MMP9 in promoting the progression of sepsis, especially how it affects the inflammatory index and related pathogenic cell programs. A standardized cecal ligation puncture (CLP) model was used to evaluate the inflammatory response in sepsis. The experiments followed animal ethical principles and extracted proteins and performed SDS-PAGE analysis for mass spectrometry identification. The samples were separated using filter-assisted sample preparation (FASP) and peptide digestion techniques, and the peptides were separated by ultra-high performance liquid chromatography (UHPLC). Subsequently, proteomic analysis, RNA extraction and differential expression analysis were performed on the data, and bioinformatics and machine learning methods were combined to evaluate the inflammatory index of both in vivo and in vitro samples. Through the integration of admission parameters, different sepsis endotypes and their clinical phenotypes were identified. Significantly, elevated MMP9 expression was found to be strongly associated with inflammatory indices such as NLR and PLR in patients with sepsis, suggesting that MMP9 may be involved in the proliferation of immune cells and the activation of their pro-inflammatory and hypoxic programs. Experimental CLP models validate the pathogenic cellular programs associated with NLR and PLR, demonstrating the critical role of MMP9 in the dynamic progression of sepsis.

Alterations in RNA Expression Profile Following S. aureus and S. epidermidis Inoculation into Platelet Concentrates

Microbial contamination of platelet concentrates (PC) remains a persistent challenge in transfusion medicine, necessitating robust preventive measures prior to product release. Differentially expressed gene (DEG) analysis of microbe inoculated PC offers a promising approach to identifying potential biomarkers for contamination detection. Within PC, each S. aureus (ATCC 29213) and S. epidermidis (ATCC 12228) was inoculated in a 103 CFU/mL concentration. Total RNA was extracted from the samples at predetermined time points (0-, 1-, 3-, and 6-hours post-inoculation), followed by high-throughput RNA sequencing. DEG, gene enrichment, and pathway analysis were conducted. Diagnostic potential was evaluated through the calculation of area under the curve (AUC) values and the assessment of additional performance metrics. DEG identified 5884 and 974 DEGs in S. aureus and S. epidermidis samples, respectively. Pathway analysis revealed distinct biological responses: S. aureus-inoculated samples showed prominent enrichment in ribosomal and spliceosome pathways, while S. epidermidis-inoculated samples demonstrated significant activation of mitogen-activated protein kinase (MAPK) signaling pathways and natural killer (NK) cell-mediated cytotoxicity pathways. ROC analysis of the commonly differentially expressed genes in both S. aureus and S. epidermidis-inoculated samples demonstrated significant diagnostic potential. The genes H19, CAVIN1, A2M, and EPAS1 exhibited statistically significant adjusted p-values and AUC values exceeding 0.8, with the exception of the H19 gene in S. epidermidis, suggesting their utility as potential biomarkers for staphylococcal contamination detection. Interaction between PC and microbial contaminants resulted in DEG and genes could be analyzed for microbial contamination of PC. However, to establish the robustness and broader applicability of these findings, further studies encompassing a more diverse range of microbial species are necessary.

Megakaryocytes possess a STING pathway that is transferred to platelets to potentiate activation

Platelets display unexpected roles in immune and coagulation responses. Emerging evidence suggests that STING is implicated in hypercoagulation. STING is an adaptor protein downstream of the DNA sensor cyclic GMP-AMP synthase (cGAS) that is activated by cytosolic microbial and self-DNA during infections, and in the context of loss of cellular integrity, to instigate the production of type-I IFN and pro-inflammatory cytokines. To date, whether the cGAS-STING pathway is present in platelets and contributes to platelet functions is not defined. Using a combination of pharmacological and genetic approaches, we demonstrate here that megakaryocytes and platelets possess a functional cGAS-STING pathway. Our results suggest that in megakaryocytes, STING stimulation activates a type-I IFN response, and during thrombopoiesis, cGAS and STING are transferred to proplatelets. Finally, we show that both murine and human platelets contain cGAS and STING proteins, and the cGAS-STING pathway contributes to potentiation of platelet activation and aggregation. Taken together, these observations establish for the first time a novel role of the cGAS-STING DNA sensing axis in the megakaryocyte and platelet lineage.

Alterations in the megakaryocyte transcriptome impacts platelet function in sepsis and COVID-19 infection

Platelets and their parent cell, the megakaryocyte (MK), are increasingly recognized for their roles during infection and inflammation. The MK residing in the bone marrow or arising from precursors trafficked to other organs for development go on to form platelets through thrombopoiesis. Infection, by direct and indirect mechanisms, can alter the transcriptional profile of MKs. The altered environment, whether mediated by inflammatory cytokines or other signaling mechanisms results in an altered platelet transcriptome. Platelets released into the circulation, in turn, interact with each other, circulating leukocytes and endothelial cells and contribute to the clearance of pathogens or the potentiation of pathophysiology through such mechanisms as immunothrombosis. In this article we hope to identify key contributions that explore the impact of an altered transcriptomic landscape during severe, systemic response to infection broadly defined as sepsis, and viral infections, including SARS-CoV2. We include current publications that outline the role of MKs from bone-marrow and extra-medullary sites as well as the circulating platelet. The underlying diseases result in thrombotic complications that exacerbate organ dysfunction and mortality. Understanding the impact of platelets on the pathophysiology of disease may drive therapeutic advances to improve the morbidity and mortality of these deadly afflictions.

An Analysis of Predictive Factors for Severe Neonatal Infection and the Construction of a Prediction Model

Objective

To investigate the primary predictive factors for the occurrence of severe neonatal infection, construct a prediction model and assess its effectiveness.

Methods

A total of 160 neonates hospitalised in the Department of Neonatology at Suixi County Hospital from January 2019 to June 2022 were retrospectively analysed. Clinical data was analyzed to determine the primary predictive factors for the occurrence of severe neonatal infection. Predictive efficacy was evaluated using a receiver operating characteristic curve, and a nomogram model was constructed according to the predictors. A bootstrap technique was used to verify the accuracy of the model.

Results

The neonates were divided, based on the degree of infection, into a mild infection group (n = 80) and a severe infection group (n = 80) according to a 1:1 ratio. Multivariate logistic regression analysis showed that compared with the recovery stage, white blood cell count (WBC) and platelet count (PLT) in the two groups were significantly decreased in the early stage of infection, and the ratio of mean platelet volume to PLT, as well as C-reactive protein (CRP) and procalcitonin levels, was elevated (P < 0.05). The area under the curves (AUCs) of decreased WBC, decreased PLT and elevated CRP levels, and the combination of these three indicators, were 0.881, 0.798, 0.523 and 0.914, respectively. According to the filtered indicators, two models (a dichotomous variable equation model and a nomogram model) of continuous numerical variables were constructed, and their AUCs were 0.958 and 0.914, respectively. The calibration curve of the nomogram model was validated with a consistency index of 0.908 (95% confidence interval [0.862, 0.954]).

Conclusion

Decreased WBC and PLT levels and an elevated CRP level were the primary independent predictors of severe neonatal infection.