Acute lung injury (ALI) is a life-threatening condition characterized by dysregulated pulmonary inflammation and high mortality rates. Alveolar macrophages and neutrophils are central innate immune cells that orchestrate the inflammatory response in injured lungs. Accumulating evidence indicates that dynamic interactions between these two cell types play a pivotal role in ALI progression; however, the underlying regulatory mechanisms remain insufficiently understood. This review aims to comprehensively analyze themolecular and cellular processes governing the communication between alveolar macrophages and neutrophils in ALI and to discuss emerging therapeutic strategies targeting this cell-cell interaction, with the goal of providing insights into novel biomarkers and therapeutic targets for ALI. A comprehensive review of the relevant literature was conducted to summarize the molecular and cellular mechanisms underlyingalveolar macrophage-neutrophil crosstalk in ALI, including cytokine/chemokine signaling, pattern recognition receptor activation, inflammasome pathways, reactive oxygen species-mediated regulation, and neutrophil extracellular trap formation. In addition, therapeutic strategies targeting these interactions were collated and analyzed. Alveolar macrophage-neutrophil communication in ALI is mediatedby multiple pathways, including cytokine and chemokine signaling, pattern recognition receptor activation, inflammasome activation, reactive oxygen species regulation, and neutrophil extracellular trap (NET) formation. Bidirectional feedback loops exist between the two cell types,where they either amplify or limit each other’s activities depending on the pathological state, thereby regulating the balance between host defense and tissue damage. Emerging therapeutic strategies targeting this crosstalk, such as the modulation of macrophage inflammatory phenotypes, inhibition of neutrophil recruitment, and prevention of neutrophil extracellular trap formation, show promising translational potential for restoring immune homeostasis in ALI. Alveolar macrophage-neutrophil crosstalk constitutes a critical regulatory axisin ALI pathogenesis. Elucidating the mechanisms and feedback networks of this interaction is essential for identifying novel biomarkers and therapeutic targets, which will facilitate the development of more precise and effective immunomodulatory treatments for ALI.
This study comprehensively investigated the role of FAM3 family genes (FAM3A, FAM3B, FAM3C, and FAM3D) in Kidney Renal Clear Cell Carcinoma (KIRC) using an integrative multi-dimensional approach. Analyses included mRNA expression profiling, promoter methylation assessment, genetic alteration evaluation, prognostic modeling, immune and molecular subtype correlations, gene enrichment analysis, in vitro functional validation, and drug sensitivity evaluation based on TCGA datasets and experimental data. Expression analysis revealed significant upregulation of FAM3A and FAM3D and downregulation of FAM3B and FAM3C in KIRC tissues compared with normal kidney samples. ROC curve analysis demonstrated their diagnostic potential. Promoter methylation analysis indicated hypomethylation of FAM3A and FAM3D and hypermethylation of FAM3B and FAM3C, consistent with their expression profiles. Minimal genetic alterations were observed, suggesting that epigenetic regulation may primarily contribute to their dysregulation. Prognostic modeling associated FAM3 gene expression with overall survival, indicating their potential as predictive biomarkers. Immune infiltration and subtype analyses suggested that FAM3 genes are involved in the modulation of the tumor microenvironment. Functional validation demonstrated that knockdown of FAM3A and FAM3D suppressed cell proliferation and colony formation, while enhancing migratory and wound-healing abilities in KIRC cell lines. Drug sensitivity analysis identified correlations between FAM3 expression and responsiveness to anticancer compounds. These findings highlight the diagnostic, prognostic, and therapeutic significance of FAM3 family genes in KIRC, providing valuable insights for future clinical translation and potential targeted therapy development.
The application of organic compost in farmland is a major agronomic measure to increase soil organic matter content, enhance soil nutrients, and regulate soil microbial activity and other soil micro components. The influence of organic compost dosage on soil DOM components was studied. In this study, greenhouse pot experiments were conducted with 7 cattle manure organic compost dosage ratios of 0%, 5%, 10%, 20%, 40%, 60%, and 80%. Three-dimensional fluorescence spectroscopy with fluorescence regional integrated volume integration (3DEEM-FRI) and ultraviolet spectroscopy (UV) were used to analyze the effect of organic compost dosage on soil DOM components and structural characteristics. The results indicated that with the increase in organic compost dosage, the soil TOM content showed a linear increase, and the soil DOM content showed an exponential increase. The proportion of humic acid-like components in soil DOM showed a linearly increasing trend, and the proportion of tryptophan protein and fulvic acid components showed a linearly decreasing trend. The proportion of tyrosine protein and microbial metabolites, as well as lignin and quinine in DOM components, showed Exponential (Exp3P2) changes which first presented an increasing and then a decreasing trend, and reached a turning point at 20 g center dot kg-1 of TOM. With the increase in the soil TOM content, such as fatty chains and esters, to polar functional groups such as hydroxyl, carboxyl, and carbonyl. a linearly increasing trend. The content of the hydrophobic organic component and the aromaticity of the soil DOM showed a linearly decreasing trend, and the proportion of biogenic sources showed an exponentially decreasing trend. The proportion of non-humified and humified substances in the soil DOM showed an initial increase and then a decreasing trend and reached the highest value at 35 g center dot kg-1 of TOM. The organic compost dosage affected the proportion and molecular structure of the soil DOM components by regulating the biological effects of microorganisms and enzyme activity, as well as the conversion process from soil TOM to DOM.
Ovarian cancer (OV) is one of the deadliest gynecological malignancies, and its high heterogeneity significantly impacts treatment efficacy. Against this background, the molecular mechanisms underlying the pathogenesis of this lethal disease have attracted extensive research attention. However, the pathogenic mechanisms of OV remain incompletely understood. Therefore, this study systematically investigates the pathogenesis of OV. This study collected 20 paired clinical samples comprising OV tissues and benign ovarian tissues to investigate RASSF2 expression. The biological effects of RASSF2 were investigated using both in vitro and in vivo models, including assessments of proliferation and migration. The impact of RASSF2 on PTEN protein stability was examined through co-immunoprecipitation and cycloheximide (CHX) chase assays. Additionally, chromatin immunoprecipitation (ChIP) was performed to investigate the SETDB1/RASSF2 interaction and H3K9me3 modifications on the chromatin of RASSF2. OV tissues exhibited significantly lower RASSF2 expression compared to normal tissues, and this reduction was associated with poorer patient survival. Overexpression of RASSF2 inhibited the proliferation and migration of OV cells. Additionally, RASSF2 inhibited OV growth in vivo. Mechanistically, RASSF2 stabilized PTEN expression to inhibit the activation of PI3K/AKT pathway. In addition, SETDB1 drove OV progression by increasing H3K9me3 enrichment at the RASSF2 promoter to negatively regulate RASSF2 expression. H3K9me3‑modified RASSF2 promotes ovarian cancer metastasis by regulating PTEN expression, which may offer a potential therapeutic target to counteract distant dissemination of OV.
Colorectal cancer liver metastasis (CRLM) remains a major determinant of long-term outcomes. Existing clinical models are typically static and single-modality, limiting early warning and individualized follow-up. We prospectively enrolled 300 treatment-na & iuml;ve colorectal cancer patients. We collected preoperative three-phase contrast-enhanced ultrasound (CEUS) dynamic sequences, longitudinal serum marker measurements (EZH2/CD10) from preoperation through 12 months, and 35 clinical-pathological variables. The proposed Dynamic Modality Alignment Network (DMA-Net) includes (i) an imaging encoder based on an enhanced 3D-ResNet18 to extract perfusion kinetics, (ii) a molecular encoder using BiLSTM with temporal attention to model serial biomarkers, and (iii) a clinical encoder (MLP) for structured variables. A dynamic alignment module and cross-modal attention fuse modalities, followed by a discrete-time survival head that outputs month-specific conditional hazards and cumulative risks. On the held-out test set, the tri-modal model achieved an area under the curve (AUC) of 0.918 at 12 months with favorable calibration (Brier score 0.123), outperforming a traditional Cox model built from clinical variables (AUC 0.782, Brier score 0.177). Time-dependent evaluation showed stable AUCs from 3 to 12 months (0.904-0.919). Ablation experiments indicated that imaging and molecular branches contributed most to discrimination, whereas clinical variables improved calibration. Multimodal dynamic modeling integrating CEUS perfusion, longitudinal biomarkers, and clinical variables improves early warning and risk stratification for CRLM, and provides a practical framework to support personalized surveillance.
