Lung cancer is one of the most prevalent cancers globally, with non-small cell lung cancers constituting the majority. These cancers have a high incidence and mortality rate. In recent years, a growing body of research has demonstrated the intricate link between inflammation and cancer, highlighting that inflammation and cancer are inextricably linked and that inflammation plays a pivotal role in cancer development, progression, and prognosis of cancer. The Systemic Immunoinflammatory Index (SII), comprising neutrophil, lymphocyte, and platelet counts, is a more comprehensive indicator of the host’s systemic inflammation and immune status than a single inflammatory index. It is widely used in clinical practice due to its cost-effectiveness, simplicity, noninvasiveness, and ease of acquisition. This paper reviews the impact of SII on the development, progression, and prognosis of non-small cell lung cancer.

Lung cancer is one of the most common malignancies worldwide, with non-small cell lung cancer (NSCLC) being the most common type. As understanding of precise treatment options for NSCLC deepens, circulating tumor DNA (ctDNA) has emerged as a potential biomarker that has become a research hotspot and may represent a new approach for the individualized diagnosis and treatment of NSCLC. This article reviews the applications of ctDNA for the early screening of patients with NSCLC, guiding targeted therapy and immunotherapy, evaluating chemotherapy and postoperative efficacy, assessing prognosis and monitoring recurrence. With the in-depth study of the pathogenesis of NSCLC, plasma ctDNA may become an indispensable part of the precise treatment of NSCLC, which has great clinical application prospects.

Background. The impairment of microcirculation is associated with the unfavorable outcome for extracorporeal membrane oxygenation (ECMO) patients. Studies revealed that pulsatile modification improves hemodynamics and attenuates inflammation during ECMO support. However, whether flow pattern impacts microcirculation and endothelial integrity is rarely documented. The objective of this work was to explore how pulsatility affects microcirculation during ECMO. Methods. Canine animal models with cardiac arrest were supported by ECMO, with the i‐Cor system used to generate nonpulsatile or pulsatile flow. The sublingual microcirculation parameters were examined using the CytoCam microscope system. The expression of hsa_circ_0007367, a circular RNA, was measured during ECMO support. In vitro validation was performed in pulmonary vascular endothelial cells (PMVECs) exposed to pulsatile or nonpulsatile flow, and the expressions of hsa_circ_0007367, endothelial tight junction markers, endothelial adhesive molecules, endothelial nitric oxide synthases (eNOS), and NF‐κB signaling activity were analyzed. Results. The pulsatile modification of ECMO enhanced microcirculatory perfusion, attenuated pulmonary inflammation, and stabilized endothelial integrity in animal models; meanwhile, the expression of hsa_circ_0007367 was significantly upregulated both in animals and PMVECs exposed to pulsatile flow. In particular, upregulation of hsa_circ_0007367 stabilized the expressions of endothelial tight junction markers zonula occludens‐ (ZO‐) 1 and occludin, followed by modulating the endothelial nitric oxide synthases (eNOS) activity and inhibiting the NF‐κB signaling pathway. Conclusion. The modification of pulsatility contributes to microcirculatory perfusion and endothelial integrity during ECMO. The expression of hsa_circ_0007367 plays a pivotal role in this protective mechanism.

Introduction: Septic cardiomyopathy is a sepsis-mediated cardiovascular complication with severe microcirculatory malperfusion. Emerging evidence has highlighted the protective effects of pulsatile flow in case of microcirculatory disturbance, yet the underlying mechanisms are still elusive. The objective of this study was to investigate the mechanisms of N⁶-methyladenosine (m⁶A) modification in the alleviation of septic cardiomyopathy associated with extracorporeal membrane oxygenation (ECMO)-generated pulsatile flow. Methods: Rat model with septic cardiomyopathy was established and was supported under ECMO either with pulsatile or non-pulsatile flow. Peripheral perfusion index (PPI) and cardiac function parameters were measured using ultrasonography. Dot blot assay was applied to examine the m⁶A level, while qRT-PCR, Western blot, immunofluorescence, and immunohistochemistry were used to measure the expressions of related genes. RNA immunoprecipitation assay was performed to validate the interaction between molecules. Results: The ECMO-generated pulsatile flow significantly elevates microcirculatory PPI, improves myocardial function, protects the endothelium, and prolongs survival in rat models with septic cardiomyopathy. The pulsatile flow mediates the METTL14-mediated m⁶A modification to zonula occludens-1 (ZO-1) mRNA (messenger RNA), which stabilizes the ZO-1 mRNA depending on the presence of YTHDF2. The pulsatile flow suppresses the PI3K–Akt signaling pathway, of which the downstream molecule Foxo1, a negative transcription factor of METTL14, binds to the METTL14 promoter and inhibits the METTL14-induced m⁶A modification. Conclusion: The ECMO-generated pulsatile flow increases METTL14-induced m⁶A modification in ZO-1 and attenuates the progression of septic cardiomyopathy, suggesting that pulsatility might be a new therapeutic strategy in septic cardiomyopathy by alleviating microcirculatory disturbance.

Surface-Enhanced Raman Scattering technology has shown broad application potential in tumor diagnosis due to its excellent sensitivity and specificity. With the increasing demand for early tumor detection and precision medicine, SERS has been widely applied in the detection of tumor markers, particularly in liquid biopsy. This review systematically summarizes the recent advances of SERS in detecting key liquid biopsy biomarkers (exosomes, CTCs, ctDNA), critically analyzes its advantages in sensitivity and multiplexing, and discusses the main challenges for clinical translation, including signal interference in complex biological environments and the need for improved quantitative accuracy. Future perspectives integrating AI and multimodal strategies are also outlined to guide the development of precision oncology tools.