Acute kidney injury (AKI) is the primary cause of morbidity and mortality after major abdominal surgery. However, little is known about the effect of anesthetics on the development of AKI after pediatric liver transplantation (LT). This study aimed to compare the effects of propofol and sevoflurane anesthetics on postoperative AKI after LT surgery. A total of 120 pediatric patients scheduled for pediatric LT were randomly assigned to receive either continuous infusion of propofol or inhalation of sevoflurane. Serum creatinine (Scr), inflammatory medium and oxidative stress factors and renal biomarkers were measured before surgery (T1), 5 min after anhepatic phase (T2), 10 min after ischemia reperfusion (T3), 2 h after ischemia reperfusion (T4), 24 h after surgery (T5), and 3 d after surgery (T6) to evaluate the effects of anesthetics on the development of postoperative AKI. The incidence of AKI was lower in patients receiving sevoflurane than those receiving propofol. The mean arterial pressure was changed slightly in sevoflurane group. The inflammatory factors of interleukin-18, tumor necrosis factor-α, and the levels of neutrophil gelatinase-associated lipocalin (NGAL) were lower in sevoflurane group, while no oxidative stress factors [hydrogen peroxide (H2O2), malondialdehyde and superoxide dismutase)] and interleukin-10 showed differences between the groups. Anesthesia with sevoflurane may be associated with a modest decrease in the incidence of AKI when compared with propofol. Further clarification with relevance to such association is warranted.

Co‐detection of multiplex cancer subtypes and bacteria subtypes in situ is crucial for understanding tumor microbiome interactions in tumor microenvironment. Current standard techniques such as immunohistochemical staining and immunofluorescence staining are limited for their multiplicity. Simultaneously visualizing detailed cell subtypes and bacteria distribution across the same pathological section remains a major technical challenge. Herein, we developed a rapid semi‐quantitative method for in situ imaging of bacteria and multiplex cell phenotypes on the same solid tumor tissue sections. We designed a panel of antibody probes labeled with mass tags, namely prokaryotic and eukaryotic cell hybrid probes for in situ imaging (PEHPSI). For application demonstration, PEHPSI stained two bacteria subtypes (lipopolysaccharides (LPS) for Gram‐negative bacteria and lipoteichoic acid (LTA) for Gram‐positive bacteria) simultaneously with four types of immune cells (leukocytes, CD8 + T‐cells, B‐cells and macrophages) and four breast cancer subtypes (classified by a panel of 12 human proteins) on the same tissue section. We unveiled that breast cancer cells are commonly enriched with Gram‐negative bacteria and almost absent of Gram‐positive bacteria, regardless of the cancer subtypes (triple‐negative breast cancer [TNBC], HER2+, Luminal A and Luminal B). Further analysis revealed that on the single‐cell level, Gram‐negative bacteria have a significant correlation with CD8 + T‐cells only in HER2+ breast cancer, while PKCD, ER, PR and Ki67 are correlated with Gram‐negative bacteria in the other three subtypes of breast cancers. On the cell population level, in TNBC, CD19 expression intensity is up‐regulated by approximately 25% in bacteria‐enriched cells, while for HER2+, Luminal A and Luminal B breast cancers, the intensity of biomarkers associated with the malignancy, metastasis and proliferation of cancer cells (PKCD, ISG15 and IFI6) is down‐regulated by 29%–38%. The flexible and expandable PEHPSI system permits intuitive multiplex co‐visualization of bacteria and mammalian cells, which facilitates future research on tumor microbiome and tumor pathogenesis.

Background: Tyrosine kinase inhibitors (TKIs) have demonstrated significant effectiveness in treating advanced non-small cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR) mutations. Despite initial success, resistance to EGFR-TKIs inevitably occurs. One observed phenomenon in resistant lung cancers is the histological transformation from NSCLC to neuroendocrine carcinoma (NEC). The objective of this study is to explore and delineate the genetic and immune features linked to the transition from lung adenocarcinoma (LUAD) to NEC. Methods: Bulk RNA-sequencing and Mendelian randomization (MR) analysis were utilized to identify candidate genes associated with the progression from LUAD to NEC. Expression quantitative trait locus data from publicly available databases were leveraged to pinpoint key genes in relevant tissues. Furthermore, the immune microenvironment was explored using weighted gene co-expression network (WGCNA) and cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) databases. Single-cell RNA sequencing data from 16,765 cells across six tissue biopsy samples of LUAD and NEC were scrutinized to investigate cell interaction networks during histological transformation. The molecular pathways involved in dynamic cellular processes were elucidated through the analysis of cellular communication and pseudotime trajectory. Results: Through the use of RNA-sequencing and MR analysis, it was determined that mucin-1 (MUC1) displayed a negative correlation with the progression of LUAD to NEC, as evidenced by its downregulation in clinical specimens. Additionally, MUC1 expression was found to be significantly correlated with the infiltration of diverse immune cell populations, notably CD8⁺ T cells. These results suggest a notable enrichment of neuron-related signaling pathways in the context of transformed NEC. Examination of immune cell infiltration in NEC indicated a reduction in the proportion of CD8⁺ central memory T cells, which has implications for the immune microenvironment and may point to potential therapeutic targets. Further investigation into cell-cell interactions among subpopulations identified the MIF-CD74 axis as the principal signaling pathway facilitating intercellular communication between immune cells and epithelial cells. Conclusions: In conclusion, our study provides insights into the molecular landscape governing the LUAD-to-NEC transition, highlighting MUC1 as a potential biomarker. The immune microenvironment is believed to exert a substantial influence on histological transformation, particularly with regards to T cells.