The Role of Age, Neutrophil Infiltration and Antibiotics Timing in the Severity of Streptococcus pneumoniae Pneumonia. Insights from a Multi-Level Mathematical Model Approach

Integration of transcriptomics data into agent-based models of solid tumor metastasis

Recent progress in our understanding of cancer mostly relies on the systematic profiling of patient samples with high-throughput techniques like transcriptomics. With this approach, one can find gene signatures and networks underlying cancer aggressiveness and therapy resistance. However, omics data alone cannot generate insights into the spatiotemporal aspects of tumor progression. Here, multi-level computational modeling is a promising approach that would benefit from protocols to integrate the data generated by the high-throughput profiling of patient samples. We present a computational workflow to integrate transcriptomics data from tumor patients into hybrid, multi-scale cancer models. In the method, we conduct transcriptomics analysis to select key differentially regulated pathways in therapy responders and non-responders and link them to agent-based model parameters. We then determine global and local sensitivity through systematic model simulations that assess the relevance of parameter variations in triggering therapy resistance. We illustrate the methodology with a de novo generated agent-based model accounting for the interplay between tumor and immune cells in a melanoma micrometastasis. The application of the workflow identifies three distinct scenarios of therapy resistance.

Efficacy and safety of Tanreqing injection combined with antibiotics against Streptococcus pneumoniae pneumonia: A systematic review and meta-analysis

WHAT IS KNOWN AND OBJECTIVE

Tanreqing injection (TRQ) is a traditional Chinese medicine injection. The goal of this study was to assess the clinical efficacy and safety of TRQ injection in combination with azithromycin or ceftriaxone, as well as azithromycin or ceftriaxone alone, in treating Streptococcus pneumoniae pneumonia (SPP).

METHODS

The randomized controlled trial (RCT) of TRQ injection combined with antibiotics versus antibiotics alone in the treatment of SPP was retrieved from Chinese and English databases (the control group was treated with antibiotics alone, while the experimental group received TRQ injection combined with antibiotics). The retrieval period was from the database's inception through February 2022. The data was extracted using the Cochrane Collaboration Network Quality Evaluation Standards, the methodological quality of the included literature was assessed, and the outcome indicators were calculated using RevMan5.4.1 software.

RESULTS AND DISCUSSION

A total of 25 RCTs were collected, including 2057 patients. TRQ injection combined with antibiotics significantly improved clinical efficacy and reduced defervescence time, lung rale disappearance time, cough disappearance time, disappearance time of chest pain, and average hospitalization time when compared to control group, according to meta-analysis results (p < 0.05).

WHAT IS NEW AND CONCLUSION

In the treatment of SPP, TRQ injection combination with antibiotics can significantly improve the total effect rate when compared to standard western medicine. Due to the low quality of the randomized controlled trials included in this investigation, more high-quality, multi-center, large-sample, prospective, randomized, double-blind clinical studies are needed to confirm the aforementioned conclusions.

An experimental in silico study on COVID‐19: Response of neutrophil‐related genes to antibiotics

Background and Aims

All components of the immune system are involved in alleviating severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection. Further research is required to provide detailed insights into COVID‐19‐related immune compartments and pathways. In addition, a significant percentage of hospitalized COVID‐19 patients suspect bacterial infections and antimicrobial resistance occurs following antibiotics treatment. The aim of this study was to evaluate the possible effects of antibiotics on the response of neutrophil‐related genes in SARS‐CoV‐2 patients by an experimental in silico study.

Methods

The two data sets GSE1739 and GSE21802 including 10 SARS positive patients and 35 influenza A (H1N1) patients were analyzed, respectively. Differentially expressed genes (DEGs) between these two data sets were determined by GEO2R analysis and the Venn diagram online tool. After determining the hub genes involved in immune responses, the expression of these genes in 30 COVID‐19 patients and 30 healthy individuals was analyzed by real‐time polymerase chain reaction (PCR). All patients received antibiotics, including levofloxacin, colistin, meropenem, and ceftazidime.

Results

GEO2R analysis detected 240 and 120 DEGs in GSE21802 and GSE1739, respectively. Twenty DEGs were considered as enriched hub genes involved in immune processes such as neutrophil degranulation, neutrophil activation, and antimicrobial humoral response. The central nodes were attributed to the genes of neutrophil elastase (ELANE), arginase 1 (ARG‐1), lipocalin 2 (LCN2), and defensin 4 (DEFA4). Compared to the healthy subjects, the expression of LCN2 and DEFA4 were significantly reduced in COVID‐19 patients. However, no significant differences were observed in the ELANE and AGR‐1 levels between COVID‐19 subjects and the control group.

Conclusions

Activation and degranulation of neutrophils were observed mainly in SARS, and H1N1 infection processes and antibiotics administration could affect neutrophil activity during viral infection. It can be suggested that antibiotics can decrease inflammation by restoring the expression of neutrophil‐related genes in COVID‐19 patients.