Lipid metabolism involves multiple biological processes. As one of the most important lipid metabolic pathways, fatty acid oxidation (FAO) and its key rate-limiting enzyme, the carnitine palmitoyltransferase (CPT) system, regulate host immune responses and thus are of great clinical significance. The effect of the CPT system on different tissues or organs is complex: the deficiency or over-activation of CPT disrupts the immune homeostasis by causing energy metabolism disorder and inflammatory oxidative damage and therefore contributes to the development of various acute and chronic inflammatory disorders and cancer. Accordingly, agonists or antagonists targeting the CPT system may become novel approaches for the treatment of diseases. In this review, we first briefly describe the structure, distribution, and physiological action of the CPT system. We then summarize the pathophysiological role of the CPT system in chronic obstructive pulmonary disease, bronchial asthma, acute lung injury, chronic granulomatous disease, nonalcoholic fatty liver disease, hepatic ischemia–reperfusion injury, kidney fibrosis, acute kidney injury, cardiovascular disorders, and cancer. We are also concerned with the current knowledge in either preclinical or clinical studies of various CPT activators/inhibitors for the management of diseases. These compounds range from traditional Chinese medicines to novel nanodevices. Although great efforts have been made in studying the different kinds of CPT agonists/antagonists, only a few pharmaceuticals have been applied for clinical uses. Nevertheless, research on CPT activation or inhibition highlights the pharmacological modulation of CPT-dependent FAO, especially on different CPT isoforms, as a promising anti-inflammatory/antitumor therapeutic strategy for numerous disorders.

Purpose Mutation-specific T-cell response to epithelial cancers and T-cell-based immunotherapy has been successfully used to treat several human solid cancers. We aimed to investigate the anti-tumour effect of neo-antigen-reactive T(NRT) cells induced by RNA mutanome vaccine, which may serve as a feasible and effective therapeutic approach for lung cancer. Methods We predicted candidate neo-antigens according to the mutant gene analysis by sequencing the mouse Lewis cells and C57BL/6 mouse tail tissue. RNA vaccine was prepared with the neo-antigens as the template. We assessed antitumor efficacy, cytokine secretion and pathological changes after adoptive transfer of NRT cells in vitro and vivo experiments. Results We identified 10 non-synonymous somatic mutations and successfully generated NRT cells. The percentage of T-cell activation proportion was increased from 0.072% in conventional T cells to 9.96% in NRT cells. Interferon-γ secretion augmented from 17.8 to 24.2% as well. As an in vivo model, adoptive NRT cell infusion could promote active T-cell infiltration into the tumour tissue and could delay tumour progression. Conclusion NRT cells induced by RNA mutanome vaccine exert a significant anti-tumour effect in mouse lung cancer, and adoptive NRT cell therapy might be considered a feasible, effective therapeutic approach for lung cancer.

BackgroundChronic obstructive pulmonary disease (COPD) remains underdiagnosed globally. The coronavirus disease 2019 pandemic has also severely restricted spirometry, the primary tool used for COPD diagnosis and severity evaluation, due to concerns of virus transmission. Computed tomography (CT)-based deep learning (DL) approaches have been suggested as a cost-effective alternative for COPD identi cation within smokers. The present study aims to develop weakly supervised DL models that utilize CT image data for the automated detection and staging of spirometry-de ned COPD among natural population. MethodsA large, highly heterogenous dataset was established comprising 1393 participants recruited from outpatient, inpatient and physical examination center settings of 4 large public hospitals in China. CT scans, spirometry data, demographic data, and clinical information of each participant were collected for the purpose of model development and evaluation. An attention-based multi-instance learning (MIL) model for COPD detection was trained using CT scans from 837 participants and evaluated using a test set comprised of data from 278 non-overlapping participants. External validation of the COPD detection was performed with 620 low-dose CT (LDCT) scans acquired from the National Lung Screening Trial (NLST) cohort. A multi-channel 3D residual network was further developed to categorize GOLD stages among con rmed COPD patients and evaluated using 5-fold cross validation. Spirometry tests were used to diagnose COPD, with stages de ned according to the GOLD criteria. ResultsThe attention-based MIL model used for COPD detection achieved an area under the receiver operating characteristic curve (AUC) of 0.934 on the test set and 0.866 on the LDCT subset acquired from NLST.The model exhibited high generalizability across distinct scanning devices and slice thicknesses, with an AUC above 0.90. The multi-channel 3D residual network was able to correctly grade 76.4% of COPD patients in the test set (423/553) using the GOLD scale, with a Cohen's weighted Kappa of 0.619 for the assessment of GOLD categorization . ConclusionThe proposed chest CT-DL approach can automatically identify spirometry-de ned COPD and categorize patients according to the GOLD scale, with clinically acceptable performance. As such, this approach may be a powerful novel tool for COPD diagnosis and staging at the population level. BackgroundChronic obstructive pulmonary disease (COPD) is a worldwide public health challenge, due to its high prevalence and long-term effects on related disabilities and mortality (1, 2). The accurate diagnosis of

Acute respiratory distress syndrome (ARDS) is a common respiratory critical syndrome with no effective therapeutic intervention. Neutrophils function in the overwhelming inflammatory process of acute lung injury (ALI) caused by ARDS; however, the phenotypic heterogeneity of pulmonary neutrophils in ALI/ARDS remains largely unknown. Here, using single-cell RNA sequencing, we identify two transcriptionally and functionally heterogeneous neutrophil populations (Fth1hi Neu and Prok2hi Neu) with distinct locations in LPS-induced ALI mouse lungs. Exposure to LPS promotes the Fth1hi Neu subtype, with more inflammatory factors, stronger antioxidant, and decreased apoptosis under the regulation of interleukin-10. Furthermore, prolonged retention of Fth1hi Neu within lung tissue aggravates inflammatory injury throughout the development of ALI/ARDS. Notably, ARDS patients have high ratios of Fth1 to Prok2 expression in pulmonary neutrophils, suggesting that the Fth1hi Neu population may promote the pathological development and provide a marker of poor outcome.

Acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) is a common respiratory critical syndrome that currently has no effective therapeutic interventions. Pulmonary macrophages play a principal role in the initiation and progression of the overwhelming inflammation in ALI/ARDS. Here, a type of fluorous‐tagged bioactive peptide nanoparticle termed CFF13F is developed, which can be efficiently internalized by macrophages and suppress the excessive expression of cytokines and the overproduction of reactive oxygen species (ROS) triggered by lipopolysaccharide (LPS). The cytoprotective effect of CFF13F may be attributed to the lysosomal‐stabilization property and regulation of the antioxidative system. Moreover, intratracheal pretreatment with CFF13F can effectively reduce local and systematic inflammation, and ameliorate pulmonary damage in an LPS‐induced ALI murine model. The therapeutic efficacy of CFF13F is affected by the administration routes, and the local intratracheal injection is found to be the optimal choice for ALI treatment, with preferred biodistribution profiles. The present study provides solid evidence of the potent immunomodulatory bioactivity of the fluorous‐tagged peptide nanoparticles CFF13F in vitro and in vivo, and sheds light on the development of novel efficient nanodrugs for ALI/ARDS.