Yuping Li

Lung injury is one of the most common clinical respiratory diseases, caused by the exposure of lung tissue to various stimuli (including hypoxia, ischemia–reperfusion, and foreign substances). Among them, chronic lung injury is characterized by continuous inflammation in the lungs, which damages the endothelial and epithelial cell barriers within the lungs. Clinically, it presents as severe hypoxia and diffuse functional impairment, and on imaging, it shows diffuse alveolar damage, accompanied by varying degrees of inflammation and airway obstruction. Several studies have highlighted the role of gut microbiota in modulating immune responses and pathological features of respiratory diseases through the gut‐lung axis. However, the precise metabolic mechanism remains unknown. A lung injury model was generated by transplanting microbiota from acute lung injury (ALI) patients into healthy C57BL/6J mice. The changes in the gut microbiota and metabolic phenotypes of the feces samples from ALI patients and lung‐injured mice were analyzed using 16S rRNA sequencing technology and metabolomics based on ¹ H‐nuclear magnetic resonance ( ¹ H‐NMR), respectively. The effect of gut microbiota on lung injury was also explored after giving an oral vancomycin treatment to lung‐injury mice. The data presented here show that Firmicutes formed the vital species of microbiota that was different in lung‐injury mice. Moreover, butyrate (produced by Firmicutes ) was the most crucial metabolite in the feces samples of ALI patients and lung‐injury mice. ELISA and Hematoxylin–Eosin results showed aggravated functional disturbances in the intestinal barrier of ALI patients and lung inflammation in the lung‐injured mice. These phenomena were significantly alleviated after the oral administration of vancomycin. Besides, the utilization of butyrate in the colon of mice was increased considerably. Thus, vancomycin can affect the metabolism of butyrate in the colon by influencing the intestinal microbiota, and it can help in the treatment of lung injury.

Objective: Previous antibiotic therapy is acknowledged to potentially reduce the efficacy of single-agent immune checkpoint inhibitors. Nevertheless, the impact of antibiotics on the results for patients undergoing chemoimmunotherapy remains unclear. This research investigated the influence of antibiotic treatment on the effectiveness of chemoimmunotherapy in advanced non-small cell lung cancer (NSCLC). Methods: We recorded the characteristics of patients with advanced NSCLC and assessed potential associations between the use of antibiotics and the efficacy of chemoimmunotherapy. A mouse model using Lewis lung carcinoma (LLC) cell lines was developed to assess the effects of antibiotics on the gut microbiome and metabolites. Fecal samples were analyzed using 16S rRNA gene sequencing and ultra-high-performance liquid chromatography–mass spectrometry (UHPLC-MS) methods. Mouse fecal and serum samples and 16 human stool samples were used to validate the identified differentially metabolites. Deoxycholic acid (DCA) was further applied to a LLC mouse model. Results: This study included 387 NSCLC patients, among whom 86 patients had used antibiotics within the 30 days before the first cycle of chemoimmunotherapy (ATB group), and 301 patients had not used antibiotics (non-ATB group). Notable discrepancies were observed in overall survival and progression-free survival between the two groups, with overall survival recorded at 18.4 months versus 32.0 months, and progression-free survival at 7.6 months versus 13.0 months, in the ATB and non-ATB groups respectively. At the phylum level, the relative abundances of Proteobacteria, Cyanobacteria, and Deinococcus were increased in the ATB mice, while Firmicutes, Bacteroidetes, and Verrucomicrobia were decreased. We detected significant differences in DCA levels in the fecal and serum samples from mice as well as in the fecal sample from humans between the ATB and non-ATB groups. The respective proportions of CD4+ and CD8+ cells were greater in the non-ATB group than in the ATB group, whereas the proportion of Ki67-positive cells was greater in the ATB group. DCA was applied to LLC mice, and DCA along with chemoimmunotherapy effectively inhibited tumor growth in a LLC mouse model. The expression of programmed cell death ligand 1 increased in the DCA group. Conclusions: Antibiotic exposure is associated with decreased efficacy of chemoimmunotherapy in patients with NSCLC via dysregulation of the gut microbiome and DCA metabolism.

Immune checkpoint inhibitors (ICIs) plus chemotherapy have become the first-line standard therapy for non-oncogene addicted advanced non-small cell lung cancer (NSCLC) patients. There is a lack of reliable biomarkers to predict treatment outcomes. This study aimed to identify relevant lipids that can predict treatment outcomes in NSCLC patients receiving first-line ICIs plus chemotherapy via lipidomics. We recruited non-oncogene addicted advanced NSCLC patients receiving first-line ICI plus chemotherapy to participate in this study. According to the progression free survival (PFS) criteria, these patients were categorized into a response (R) group (PFS ≥ 12 months) and a non-response (NR) group (PFS < 12 months). Plasma samples were collected from patients before the start of treatment for untargeted lipidomics and semi-targeted lipidomics analysis. A total of 49 patients were included in this study. We screened 13 differential lipids according to P < 0.05 and AUC > 0.7. Multivariate logistic regression further identified FA-18:2 (linoleic acid, LA), PE-P-34:2, and PI-40:4 as independent predictors. The triple-lipid biomarker panel demonstrated showed good predictive performance with an AUC of 0.878. We further investigated the role of LA, a pivotal lipid involved in immune regulation, in animal and cellular models and explored its potential in enhancing NSCLC immunotherapy. Our results showed that LA synergistically enhanced PD-1 inhibitor efficacy in the Lewis lung cancer mouse model, significantly suppressing tumor growth, and downregulating PD-L1 protein expression in both tumor cells and tumor tissues. We established the lipidomics-based predictive model for the efficacy of non-oncogene addicted advanced NSCLC patients treated with first-line chemotherapy plus ICI and elucidated a novel mechanism whereby LA potentiates immunotherapy by regulating the PD-L1 pathway. These findings provide dual theoretical foundations for personalized treatment strategies and the development of immunoadjuvants.

The reported incidence of aspergillosis among COVID-19 patients has varied significantly, which can be partly attributed to differences in diagnostic approaches and levels of physicians’ proficiency in diagnosing COVID-19-associated pulmonary aspergillosis (CAPA). Consequently, we conducted a retrospective study to investigate the potential reasons for these discrepancies and analyzed the risk factors for pulmonary aspergillosis in patients with COVID-19. Data were retrospectively collected from December 1, 2022, to September 30, 2023, from patients who were admitted to the First Affiliated Hospital of Wenzhou Medical University. The research platform was used to screen patients with discharge diagnoses of COVID-19 pneumonia. CAPA was defined according to the 2020 ECMM/ISHAM criteria and the Chinese expert consensus. Clinical data that were collected included data about underlying diseases, laboratory examinations and microbiological detection. Analyses were conducted with R software, with continuous variables analyzed with t-tests, categorical variables analyzed with chi-square tests, and logistic regression and ROC curves used to assess risk factors for CAPA. The incidence of CAPA was 13.4% in the general ward, 30.8% in the RICU, and 6.8% in other ICUs. The average time to CAPA diagnosis was 5.6 days in general wards, 3.7 days in the RICU, and 7.4 days in other ICUs. Diagnostic testing revealed the following sensitivities: 78% for BALF galactomannan (GM), 48% for serum GM, 52% for culture tests, and 71% for BALF mNGS. Risk factors for CAPA included chronic respiratory disease, chronic renal insufficiency, and diabetes. The primary Aspergillus species identified was A. fumigatus, followed by A. flavus. Differences in incidence may arise from varying levels of physician awareness, which can influence the rate at which BALF and serum GM samples are submitted for testing. The sensitivity of BALF GM is higher than that of serum GM. Furthermore, BALF mNGS has the potential to enhance the clinical detection sensitivity of CAPA. Risk factors for CAPA include chronic respiratory disease, chronic renal insufficiency, and diabetes, which may aid in identifying at-risk patients. The primary Aspergillus species identified was A. fumigatus, followed by A. flavus, providing a reference for clinical empirical treatment. Not applicable.

Background: Acute lung injury (ALI) is characterized by diffuse alveolar injury and acute non-cardiac pulmonary edema, with high morbidity and mortality. Lysophosphatidylcholine 14:0 (LPC14:0) has anti-inflammatory and anti-oxidative effects in sepsis and bacteremia. We hypothesized that LPC14:0 could be a potential treatment for ALI. Therefore, the effects of LPC14:0 on lung epithelial cells and the underlying mechanism on ALI were investigated. Methods: Lipopolysaccharide (LPS) was instilled intratracheally in vivo while the Murine Lung Epithelial-12 was stimulated by tert-butyl hydroperoxide (t-BHP) in vitro to induce the ALI model. In vivo, lung injury was evaluated by histopathological changes and pulmonary edema was assessed by wet/dry ratio. Evans blue infiltration in lung tissue, total protein content, total cell counts and inflammatory factors in bronchoalveolar lavage fluid were evaluated for alveolar permeability. In vitro, cell viability and cell death rate were assessed by cell counting kit-8 and Calcein-AM/PI stain respectively. The expression of ZO-1, Occludin, Nrf2, and HO-1 was evaluated by Western blot. Results: LPC14:0 attenuated the LPS-stimulated lung injury and oxidative stress in vivo, and alleviated the t-BHP-induced cell damage in vitro. Moreover, LPC14:0 significantly inhibited the degradation of the tight junction proteins and activated the Nrf2/HO-1 signaling pathway both in vivo and in vitro. Mechanistically, ML385, the Nrf2 inhibitor, inhibited the protective effects of LPC14:0 on barrier function in vitro. Conclusion: This study first demonstrated that LPC14:0 mitigated LPS-induced ALI and the destruction of tight junctions, at least in part through up-regulation of the Nrf2/HO-1 pathway.

Background: Identifying nutritional risk in COVID-19 patients poses a challenge due to the unique qualities of every nutritional screening instrument. The objective was to assess the efficacy of six nutritional scores, including the Nutritional Risk Screening 2002 (NRS-2002) score, the NUTRIC (nutrition risk in the critically ill) score, the modified NUTRIC score, the prognostic nutritional index (PNI), controlling nutritional status (CONUT) score, TCB index (TCBI), predicting prognosis of COVID-19 patients.Methods: Clinical data were collected from COVID-19 patients admitted to the First Affiliated Hospital of Wenzhou Medical University between December 2022 and February 2023. Participants in this research were divided into two groups: all patients and those specifically from the intensive care unit (ICU). Each group was further stratified into two groups: survivors and non-survivors.Result: 506 COVID-19 patients and 190 COVID-19 patients in intensive care unit (ICU) were evaluated. In all COVID-19 patients, we found that NRS-2002 (p < 0.001) and TCBI (p = 0.002) were statistically significant independent predictors in multivariate analyses, while APACHE II score (p = 0,048) and the mNUTRIC score (p = 0.025) were statistically significant independent predictors in multivariate analyses in ICU patients. The NRS-2002 demonstrated a higher AUC value (0.687) than other nutritional scores in all patients, with an optimum cut-off value of 3, translating into a corresponding sensitivity of 66.2% and specificity of 68.7%. With an optimum cut-off value of 4, the mNUTRIC score demonstrated a higher AUC value (0.884) in ICU patients, resulting in a sensitivity of 88.4% and a specificity of 76.9%. By using the discrimination and clinical application (DCA) curve, NRS-2002 demonstrated the greatest net benefit in all patients, while NUTRIC score and mNUTRIC score offered the more significant overall advantage than other nutritional scores in ICU patients. Kaplan–Meier analyses showed lower survival rates in patients in low nutritional risk.Conclusion: Malnutrition was common in COVID-19 patients. The mNUTRIC score and NRS-2002 were, respectively, more effctive scoring systems of prognosis in all COVID-19 patients and severe or critical COVID-19 patients of the intensive care unit (ICU).