HMGB1 as an extracellular pro-inflammatory cytokine: Implications for drug-induced organic damage.

Drug-induced organic damage encompasses various intricate mechanisms, wherein HMGB1, a non-histone chromosome-binding protein, assumes a significant role as a pivotal hub gene. The regulatory functions of HMGB1 within the nucleus and extracellular milieu are interlinked. HMGB1 exerts a crucial regulatory influence on key biological processes including cell survival, inflammatory regulation, and immune response. HMGB1 can be released extracellularly from the cell during these processes, where it functions as a pro-inflammation cytokine. HMGB1 interacts with multiple cell membrane receptors, primarily Toll-like receptors (TLRs) and receptor for advanced glycation end products (RAGE), to stimulate immune cells and trigger inflammatory response. The excessive or uncontrolled HMGB1 release leads to heightened inflammatory responses and cellular demise, instigating inflammatory damage or exacerbating inflammation and cellular demise in different diseases. Therefore, a thorough review on the significance of HMGB1 in drug-induced organic damage is highly important for the advancement of pharmaceuticals, ensuring their effectiveness and safety in treating inflammation as well as immune-related diseases. In this review, we initially outline the characteristics and functions of HMGB1, emphasizing their relevance in disease pathology. Then, we comprehensively summarize the prospect of HMGB1 as a promising therapeutic target for treating drug-induced toxicity. Lastly, we discuss major challenges and propose potential avenues for advancing the development of HMGB1-based therapeutics.

Reporting of tumor lysis syndrome with targeted therapy for hepatic cancer in the FDA adverse events reporting system.

BACKGROUND: Hepatic cancer is a common cancer in clinical practice. Current drug therapies for this condition include targeted therapy, chemotherapy, and immunotherapy. Tumor lysis syndrome (TLS) is the most serious complication of oncology treatment. According to the literature, several cases reported TLS occurred with targeted therapies for hepatic cancer. METHODS: Reporting odds ratio and information component were used to measure the disproportionate signals for TLS associated with targeted therapies, using data from the FDA's Adverse Event Reporting System (FAERS). A stepwise sensitivity analysis was conducted to test the robustness of signals. Time-to-onset analysis was used to describe the latency of TLS events associated with targeted therapies. The Bradford Hill criteria were used to perform a global assessment of the evidence. RESULTS: Sorafenib, lenvatinib, cabozantinib, and bevacizumab showed higher disproportionate signals for TLS than chemotherapy. The median number of days to TLS occurrence after drug therapy was 5.5, 6.5, and 6.5 days for sorafenib, lenvatinib, and bevacizumab, respectively. CONCLUSIONS: There is a significant association between tumor lysis syndrome and targeted therapies for hepatic carcinoma, with particularly strong signals for sorafenib and lenvatinib. Clinicians should be aware of the potential for tumor lysis syndrome in targeted therapies for hepatic carcinoma.

Analyzing the correlation between quinolone-resistant Escherichia coli resistance rates and climate factors: A comprehensive analysis across 31 Chinese provinces.

BACKGROUND: The increasing problem of bacterial resistance, particularly with quinolone-resistant Escherichia coli (QnR eco) poses a serious global health issue. METHODS: We collected data on QnR eco resistance rates and detection frequencies from 2014 to 2021 via the China Antimicrobial Resistance Surveillance System, complemented by meteorological and socioeconomic data from the China Statistical Yearbook and the China Meteorological Data Service Centre (CMDC). Comprehensive nonparametric testing and multivariate regression models were used in the analysis. RESULT: Our analysis revealed significant regional differences in QnR eco resistance and detection rates across China. Along the Hu Huanyong Line, resistance rates varied markedly: 49.35 in the northwest, 54.40 on the line, and 52.30 in the southeast (P = 0.001). Detection rates also showed significant geographical variation, with notable differences between regions (P < 0.001). Climate types influenced these rates, with significant variability observed across different climates (P < 0.001). Our predictive model for resistance rates, integrating climate and healthcare factors, explained 64.1% of the variance (adjusted R-squared = 0.641). For detection rates, the model accounted for 19.2% of the variance, highlighting the impact of environmental and healthcare influences. CONCLUSION: The study found higher resistance rates in warmer, monsoon climates and areas with more public health facilities, but lower rates in cooler, mountainous, or continental climates with more rainfall. This highlights the strong impact of climate on antibiotic resistance. Meanwhile, the predictive model effectively forecasts these resistance rates using China's diverse climate data. This is crucial for public health strategies and helps policymakers and healthcare practitioners tailor their approaches to antibiotic resistance based on local environmental conditions. These insights emphasize the importance of considering regional climates in managing antibiotic resistance.