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Abstract Background Sepsis remains a leading cause of mortality in intensive care units, and rapid and accurate pathogen detection is crucial for effective treatment. This study evaluated the clinical application of multi-site metagenomic next-generation sequencing (mNGS) for the diagnosis of sepsis, comparing its performance against conventional methods. Methods A retrospective analysis was conducted on 69 patients with sepsis consecutively admitted to the Department of Intensive Care Medicine, Meizhou People’s Hospital. Samples of peripheral blood and infection sites were collected for mNGS and conventional method tests to compare the positive rate of mNGS and traditional pathogen detection methods and the distribution of pathogens. The methods used in this study included a comprehensive analysis of pathogen consistency between peripheral blood and infection site samples. Additionally, the correlation between the pathogens detected and clinical outcomes was investigated. Results Of the patients with sepsis, 57.97% experienced dyspnea, and 65.2% had underlying diseases, with hypertension being the most common. mNGS demonstrated a significantly higher pathogen detection rate (88%) compared to the conventional method tests (26%). The pathogen consistency rate was 60% between plasma and bronchoalveolar lavage fluid samples, and that of plasma and local body fluid samples was 63%. The most frequently detected pathogens were gram-negative bacteria, and Klebsiella pneumonia. There were no significant differences in the clinical features between the pathogens. Conclusion mNGS is significantly superior to conventional methods in pathogen detection. There was a notable high pathogen consistency detection between blood and local body fluid samples, supporting the clinical relevance of mNGS. This study highlights the superiority of mNGS in detecting a broad spectrum of pathogens quickly and accurately. Trial registration Not applicable.

Abstract The homeodomain-leucine zipper (HD-Zip) gene family plays a pivotal role in plant development and stress responses. Nevertheless, a comprehensive characterization of the HD-Zip gene family in kiwifruit has been lacking. In this study, we have systematically identified 70 HD-Zip genes in the Actinidia chinensis (Ac) genome and 55 in the Actinidia eriantha (Ae) genome. These genes have been categorized into four subfamilies (HD-Zip I, II, III, and IV) through rigorous phylogenetic analysis. Analysis of synteny patterns and selection pressures has provided insights into how whole-genome duplication (WGD) or segmental may have contributed to the divergence in gene numbers between these two kiwifruit species, with duplicated gene pairs undergoing purifying selection. Furthermore, our study has unveiled tissue-specific expression patterns among kiwifruit HD-Zip genes, with some genes identified as key regulators of kiwifruit responses to bacterial canker disease and postharvest processes. These findings not only offer valuable insights into the evolutionary and functional characteristics of kiwifruit HD-Zips but also shed light on their potential roles in plant growth and development.