Association of immune deficiency with prognosis and corticosteroid treatment benefits among patients with acute respiratory distress syndrome.

Background: The role of corticosteroids in acute respiratory distress syndrome (ARDS) remains contentious. This study aims to investigate the prognostic significance of immune deficiency in patients with ARDS and its response to varying doses of corticosteroids. Methods: This single-center, retrospective cohort study enrolled 657 ARDS patients from January 24, 2008, to September 12, 2022, at Zhongshan Hospital of Fudan University, Shanghai, China. The patients were categorized into a discovery dataset (n=357) and a validation dataset (n=300), based on admission date. Further validation of the results in the validation dataset was used to enhance the credibility of the study conclusions. The study examined the association between immune deficiency and the patients' clinical characteristics, treatment measures, and prognosis. The primary outcome was 28-day mortality post disease onset. Data analysis was conducted from June 15, 2023 to August 15, 2023. Results: The initial risk factor analysis in the discovery dataset was primarily based on the clinical characteristics, and the results suggested that immune deficiency likely impacted overall survival among patients receiving different doses of corticosteroid treatment. Multivariate analysis identified immune deficiency as an independent prognostic factor for overall survival in both the discovery and validation datasets. The final analysis revealed that patients with mild to moderate ARDS [discovery dataset: hazard ratio (HR) =1.719; 95% confidence interval (CI): 1.229-2.406; log-rank test P=0.001; validation dataset: HR =1.874; 95% CI: 1.238-2.837; log-rank test P=0.002] or severe ARDS (discovery dataset: HR =1.874; 95% CI: 1.007-3.488; log-rank test P=0.04; validation dataset: HR =1.698; 95% CI: 1.042-2.768; log-rank test P=0.03) with immune deficiency exhibited lower overall survival rates. Patients with mild to moderate ARDS and immune deficiency showed greater benefits from low-dose corticosteroid treatment (HR =0.409; 95% CI: 0.249-0.671; P<0.001 for interaction), whereas those with severe ARDS and immune deficiency benefitted from both low and high-dose treatments (low corticosteroid: HR =0.299; 95% CI: 0.136-0.654; high corticosteroid: HR =0.458; 95% CI: 0.214-0.981; P=0.005 for interaction). Conclusions: Immune deficiency is an independent risk factor in ARDS. Incorporating it into the disease severity grading system based on the Berlin criteria may enhance personalized treatment approaches for ARDS patients. These findings warrant further validation through prospective, large-scale, multicenter randomized controlled trials (RCTs).

m6A-mediated HDAC9 upregulation promotes particulate matter-induced airway inflammation via epigenetic control of DUSP9-MAPK axis and acts as an inhaled nanotherapeutic target.

Exposure to particulate matter (PM) can cause airway inflammation and worsen various airway diseases. However, the underlying molecular mechanism by which PM triggers airway inflammation has not been completely elucidated, and effective interventions are lacking. Our study revealed that PM exposure increased the expression of histone deacetylase 9 (HDAC9) in human bronchial epithelial cells and mouse airway epithelium through the METTL3/m6A methylation/IGF2BP3 pathway. Functional assays showed that HDAC9 upregulation promoted PM-induced airway inflammation and activation of MAPK signaling pathway in vitro and in vivo. Mechanistically, HDAC9 modulated the deacetylation of histone 4 acetylation at K12 (H4K12) in the promoter region of dual specificity phosphatase 9 (DUSP9) to repress the expression of DUSP9 and resulting in the activation of MAPK signaling pathway, thereby promoting PM-induced airway inflammation. Additionally, HDAC9 bound to MEF2A to weaken its anti-inflammatory effect on PM-induced airway inflammation. Then, we developed a novel inhaled lipid nanoparticle system for delivering HDAC9 siRNA to the airway, offering an effective treatment for PM-induced airway inflammation. Collectively, we elucidated the crucial regulatory mechanism of HDAC9 in PM-induced airway inflammation and introduced an inhaled therapeutic approach targeting HDAC9. These findings contribute to alleviating the burden of various airway diseases caused by PM exposure.

PAI-1 Deficiency Promotes NET-mediated Pyroptosis and Ferroptosis during Pseudomonas Aeruginosa-induced Acute Lung Injury by Regulating the PI3K/MAPK/AKT Axis.

Circulating neutrophil extracellular trap (NET) formation is an adaptive process during acute lung injury (ALI). The important role of plasminogen activator inhibitor (PAI)-1 in NET formation during ALI remains unclear. This research intends to examine the impacts of the decrease in PAI-1 levels on NET formation and the underlying mechanism. We found a relative association between the increase in plasma NET levels and thromboinflammation-induced lung damage in patients with ARDS. PAI-1 knockout (KO) mice exhibited significant increases in Pseudomonas aeruginosa (PAO1 strain)-induced ALI, inflammation, inflammatory cell accumulation, and proinflammatory cytokine secretion, and wild-type mice exhibited the opposite changes. During PAO1-induced ALI, PAI-1 KO increased NET release and the levels of prothrombotic markers in mice. PAI-1 deficiency also promoted NET formation and NET-mediated pyroptosis and ferroptosis by activating the PI3K/MAPK/AKT pathway in a PAO1-induced ALI mouse model. In conclusion, PAI-1 KO exacerbated PAO1-induced pneumonia-associated injury and contributed to NET-mediated pyroptosis and ferroptosis through PI3K/MAPK/AKT pathway activation. Thus, targeting PAI-1 and NETs may be a promising therapeutic approach for ameliorating pneumonia and thromboinflammation-associated ALI.

Peroxiredoxin 6 Protects Pulmonary Epithelial Cells From Cigarette-related Ferroptosis in Chronic Obstructive Pulmonary Disease.

Peroxiredoxin 6 (PRDX6) has a protective effect on pulmonary epithelial cells against cigarette smoke (CS)-induced ferroptosis. This study investigates the role of PRDX6 in the development of chronic obstructive pulmonary disease (COPD) and its possibility as a target. We observed that PRDX6 was downregulated in lung tissues of COPD patients and in CS-stimulated cells. The degradation of PRDX6 could be through the lysosomal pathway. PRDX6 deficiency exacerbated pulmonary inflammation and mucus hypersecretion in vivo. Overexpression of PRDX6 in Beas-2B cells ameliorated CS-induced cell death and inflammation, suggesting its protective role against CS-induced damage. Furthermore, PRDX6 deficiency promoted ferroptosis by adding the content of iron and reactive oxygen species, while iron chelation with deferoxamine mitigated CS-induced ferroptosis, cell death, and inflammatory infiltration both in vitro and in vivo. The critical role of PRDX6 in regulating ferroptosis suggests that targeting PRDX6 or iron metabolism may represent a promising strategy for COPD treatment.

Metagenomic next-generation sequencing assistance in identifying Mycobacterium iranicum pulmonary infection: A case report.

Nontuberculous mycobacteria (NTM) are important opportunistic pathogens in humans, mostly affecting the lungs, and potentially causing progressive disease in individuals with underlying diseases. The prevalence of NTM infections is increasing worldwide. However, Mycobacterium iranicum (M. iranicum) infections are less common. Here we report a 65-year-old female who developed pneumonia caused by Mycobacterium iranicum, which was detected in bronchoalveolar lavage fluid (BALF) through metagenomic next-generation sequencing (mNGS). The patient was treated with moxifloxacin, doxycycline, and sulfamethoxazole/trimethoprim. Symptoms were relieved and lung abnormalities were shown to be partially absorbed on the follow-up chest computed tomography (CT) scans. As we know, this is the first case of Mycobacterium iranicum pulmonary infection identified by mNGS in BALF.

Weakly-Supervised Segmentation-Based Quantitative Characterization of Pulmonary Cavity Lesions in CT Scans.

OBJECTIVE: Pulmonary cavity lesion is one of the commonly seen lesions in lung caused by a variety of malignant and non-malignant diseases. Diagnosis of a cavity lesion is commonly based on accurate recognition of the typical morphological characteristics. A deep learning-based model to automatically detect, segment, and quantify the region of cavity lesion on CT scans has potential in clinical diagnosis, monitoring, and treatment efficacy assessment. METHODS: A weakly-supervised deep learning-based method named CSA2-ResNet was proposed to quantitatively characterize cavity lesions in this paper. The lung parenchyma was firstly segmented using a pretrained 2D segmentation model, and then the output with or without cavity lesions was fed into the developed deep neural network containing hybrid attention modules. Next, the visualized lesion was generated from the activation region of the classification network using gradient-weighted class activation mapping, and image processing was applied for post-processing to obtain the expected segmentation results of cavity lesions. Finally, the automatic characteristic measurement of cavity lesions (e.g., area and thickness) was developed and verified. RESULTS: the proposed weakly-supervised segmentation method achieved an accuracy, precision, specificity, recall, and F1-score of 98.48%, 96.80%, 97.20%, 100%, and 98.36%, respectively. There is a significant improvement (P < 0.05) compared to other methods. Quantitative characterization of morphology also obtained good analysis effects. CONCLUSIONS: The proposed easily-trained and high-performance deep learning model provides a fast and effective way for the diagnosis and dynamic monitoring of pulmonary cavity lesions in clinic. Clinical and Translational Impact Statement: This model used artificial intelligence to achieve the detection and quantitative analysis of pulmonary cavity lesions in CT scans. The morphological features revealed in experiments can be utilized as potential indicators for diagnosis and dynamic monitoring of patients with cavity lesions.

Serum Metabolomics Reveals Metabolomic Profile and Potential Biomarkers in Asthma.

PURPOSE: Asthma is a highly heterogeneous disease. Metabolomics plays a pivotal role in the pathogenesis and development of asthma. The main aims of our study were to explore the underlying mechanism of asthma and to identify novel biomarkers through metabolomics approach. METHODS: Serum samples from 102 asthmatic patients and 18 healthy controls were collected and analyzed using liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) system. Multivariate analysis and weighted gene co-expression network analysis (WGCNA) were performed to explore asthma-associated metabolomics profile and metabolites. The Kyoto Encyclopedia of Genes and Genomes (KEGG) was used for pathway enrichment analysis. Subsequently, 2 selected serum hub metabolites, myristoleic acid and dodecanoylcarnitine, were replicated in a validation cohort using ultra-high performance LC-MS/MS system (UHPLC-MS/MS). RESULTS: Distinct metabolomics profile of asthma was revealed by multivariate analysis. Then, 116 overlapped asthma-associated metabolites between multivariate analysis and WGCNA, including 12 hub metabolites, were identified. Clinical features-associated hub metabolites were also identified by WGCNA. Among 116 asthma-associated metabolites, Sphingolipid metabolism and valine, leucine and isoleucine biosynthesis were revealed by KEGG analysis. Furthermore, serum myristoleic acid and dodecanoylcarnitine were significantly higher in asthmatic patients than in healthy controls in validation cohort. Additionally, serum myristoleic acid and dodecanoylcarnitine demonstrated high sensitivities and specificities in predicting asthma. CONCLUSIONS: Collectively, asthmatic patients showed a unique serum metabolome. Sphingolipid metabolism and valine, leucine and isoleucine biosynthesis were involved in the pathogenesis of asthma. Furthermore, our results suggest the promising values of serum myristoleic acid and dodecanoylcarnitine for asthma diagnosis in adults.

Neuroimmune recognition and regulation in the respiratory system.

Neuroimmune recognition and regulation in the respiratory system is a complex and highly coordinated process involving interactions between the nervous and immune systems to detect and respond to pathogens, pollutants and other potential hazards in the respiratory tract. This interaction helps maintain the health and integrity of the respiratory system. Therefore, understanding the complex interactions between the respiratory nervous system and immune system is critical to maintaining lung health and developing treatments for respiratory diseases. In this review, we summarise the projection distribution of different types of neurons (trigeminal nerve, glossopharyngeal nerve, vagus nerve, spinal dorsal root nerve, sympathetic nerve) in the respiratory tract. We also introduce several types of cells in the respiratory epithelium that closely interact with nerves (pulmonary neuroendocrine cells, brush cells, solitary chemosensory cells and tastebuds). These cells are primarily located at key positions in the respiratory tract, where nerves project to them, forming neuroepithelial recognition units, thus enhancing the ability of neural recognition. Furthermore, we summarise the roles played by these different neurons in sensing or responding to specific pathogens (influenza, severe acute respiratory syndrome coronavirus 2, respiratory syncytial virus, human metapneumovirus, herpes viruses, Sendai parainfluenza virus, Mycobacterium tuberculosis, Pseudomonas aeruginosa, Staphylococcus aureus, amoebae), allergens, atmospheric pollutants (smoking, exhaust pollution), and their potential roles in regulating interactions among different pathogens. We also summarise the prospects of bioelectronic medicine as a third therapeutic approach following drugs and surgery, as well as the potential mechanisms of meditation breathing as an adjunct therapy.

Iron Overload-Dependent Ferroptosis Aggravates LPS-Induced Acute Lung Injury by Impairing Mitochondrial Function.

Ferroptosis is a newly proposed form of programmed cell death that is iron-dependent and closely linked to oxidative stress. Its specific morphological changes include shrunken mitochondria, increased density of mitochondrial membrane, and rupture or disappearance of mitochondrial cristae. The main mechanism of ferroptosis involves excessive free iron reacting with membrane phospholipids, known as the Fenton reaction, resulting in lipid peroxidation. However, the role of iron in acute lung injury (ALI) remains largely unknown. In this study, LPS was instilled into the airway to induce ALI in mice. We observed a significant increase in iron concentration during ALI, accompanied by elevated levels of lipid peroxidation markers such as malonaldehyde (MDA) and 4-hydroxynonenal (4-HNE). Treatment with the iron chelator deferoxamine (DFO) or ferroptosis inhibitor ferrostatin-1 (Fer-1) reversed lipid peroxidation and significantly attenuates lung injury. Similarly, DFO or Fer-1 treatment improved the cell survival significantly in vitro. These results demonstrated that ferroptosis occurs during ALI and that targeting ferroptosis is an effective treatment strategy. Interestingly, we found that the increased iron was primarily concentrated in mitochondria and DFO treatment effectively restored normal mitochondria morphology. To further confirm the damaging effect of iron on mitochondria, we performed mitochondrial stress tests in vitro, which revealed that iron stimulation led to mitochondrial dysfunction, characterized by impaired basal respiratory capacity, ATP production capacity, and maximum respiratory capacity. MitoTEMPO, an antioxidant targeting mitochondria, exhibited superior efficacy in improving iron-induced mitochondrial dysfunction compared to the broad-spectrum antioxidant NAC. Treatment with MitoTEMPO more effectively alleviated ALI. In conclusion, ferroptosis contributes to the pathogenesis of ALI and aggravates ALI by impairing mitochondrial function.

Impact of Using Pre- and Post-Bronchodilator Spirometry Reference Values in a Chinese Population.

RATIONALE: Spirometry reference equations that are derived from a large, nationally representative, general population are warranted in China and the impact of using pre- and post-BD spirometry reference values has yet to be assessed in Chinese populations. OBJECTIVES: To present both the pre-BD and post-BD spirometry reference values for Chinese adults using the China Pulmonary Health (CPH) study. METHODS: A reference population of 17969 healthy, non-smoking participants in the CPH study was used to calculate the pre- and post-BD reference values for the forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC. Both pre- and post-BD reference values were applied to the entire CPH population (50991 individuals) to illustrate the divergence between the use of references in determining the disease prevalence and severity grading. MEASUREMENTS AND MAIN RESULTS: The prevalence of airflow limitation was 5.36% using pre-BD reference and 8.02% using the post-BD reference. Individuals who had post-BD FEV1/FVC below post-BD but higher than pre-BD reference values were found to have significantly higher rates of self-reported respiratory symptoms, and significantly lower values in spirometry indicators than those above post-BD reference values. An additional 3.51% of participants were identified as grade II-IV COPD using the post-BD FEV1 predicted values. CONCLUSION: This study generated and applied pre- and post-bronchodilator spirometry reference values in a nationally representative Chinese adult population. Post-BD reference values may serve as an additional criterion in identifying individuals at risk for obstructive pulmonary diseases, its diagnostic and prognostic values should be further investigated.

Diagnosis of malignant body fluids via cancer-universal methylation in cell-free DNA.

BACKGROUNDDifferentiating malignant from nonmalignant body fluids remains a clinical challenge because of the unsatisfying performance of conventional cytology. We aimed to improve the sensitivity and ubiquity of cancer cell detection by assaying universal cancer-only methylation (UCOM) markers in supernatant cell-free DNA (cfDNA).METHODSAn observational prospective cohort including 1,321 nonmalignant and malignant body fluids of multiple cancers was used to develop and validate a cfDNA UCOM methylation diagnostic assay. All samples were divided into 2 portions for cytology and supernatant cfDNA methylation analysis.RESULTSThe significant hypermethylation of a potentially novel UCOM marker, TAGMe, together with the formerly reported PCDHGB7, was identified in the cfDNA of malignant body fluid samples. The combined model, cell-free cancer-universal methylation (CUE), was developed and validated in a prospective multicancer cohort with markedly elevated sensitivity and specificity, and was further verified in a set containing additional types of malignant body fluids and metastases. In addition, it remained hypersensitive in detecting cancer cells in cytologically negative malignant samples.CONCLUSIONcfDNA methylation markers are robust in detecting tumor cells and are applicable to diverse body fluids and tumor types, providing a feasible complement to current cytology-based diagnostic analyses.TRIAL REGISTRATIONThis study was registered at Chictr.org.cn (ChiCTR2200060532).FUNDINGNational Natural Science Foundation of China (32270645, 31872814, 32000505, 82170088), the National Key R&D Program of Ningxia Hui Autonomous region (2022BEG01003), Shanghai Municipal Key Clinical Specialty (shslczdzk02201), Science and Technology Commission of Shanghai Municipality (20DZ2261200, 20DZ2254400), and Major Special Projects of Basic Research of Shanghai Science and Technology Commission (18JC1411101).

Effects and long-term outcomes of endurance versus resistance training as an adjunct to standard medication in patients with stable COPD: a multicenter randomized trial.

BACKGROUND: Comparisons between endurance training (ET) and resistance training (RT) have produced equivocal findings in chronic obstructive pulmonary disease (COPD) patients. The purpose of our study is to investigate the effectiveness and long-term outcomes of adding ET and RT to conventional medical treatment in patients with COPD. A secondary objective is to investigate the clinical improvements resulting from exercise training in patients with different disease severities. METHODS: The study was a multicenter, prospective trial in people with stable COPD. The cohort was randomized to three groups: individualized medical treatment group (MT), MT + endurance training group (MT + ET) and MT + resistance training group (MT + RT). Exercise was performed 3 times weekly over a 12-week period. The endpoints of exercise capacity, health-related quality of life, COPD symptoms, lung function, and anxiety and depression questionnaires were re-evaluated at baseline, at the completion of the intervention and at 6 and 12-month follow-up. According to the COPD assessment tool offered by GOLD guidelines, patients were stratified into GOLD A and B groups and GOLD C and D groups for further subgroup analysis. RESULTS: The intention-to-treat (ITT) population included 366 patients, 328 of them completed the study protocol over 12 months (the PP-population). There were no significant differences in the primary outcome, quality of life, between patients who underwent medical treatment (MT) alone, MT + endurance training (MT + ET), or MT + resistance training (MT + RT) at the completion of the intervention, 6-, or 12-month follow-up. Additionally, no significant differences were observed between MT, MT + RT, or MT + ET groups concerning the primary outcome, exercise capacity (3MWD), after initial 3 months of intervention. However, a small statistically significant difference was noted in favor of MT + ET compared to MT + RT at 12 months (ITT: Δ3MWD in ET vs RT = 5.53 m, 95% confidence interval: 0.87 to 13.84 m, P = 0.03) (PP: Δ3MWD in ET vs RT = 7.67 m, 95% confidence interval: 0.93 to 16.27 m, P = 0.04). For patients in the GOLD C and D groups, improvement in quality of life following ET or RT was significantly superior to medical intervention alone. Furthermore, upon completion of the exercise regimen, RT exhibited a greater improvement in anxiety compared to ET in these patients (ITT: ΔHAD-A at 3-month: RT = -1.63 ± 0.31 vs ET = -0.61 ± 0.33, p < 0.01) (PP: ΔHAD-A at 3-month: RT = -1.80 ± 0.36 vs ET = -0.75 ± 0.37, p < 0.01). CONCLUSIONS: Our study presents evidence of the beneficial effects of ET and RT in combination with standard medical treatment, as well as the long-term effects over time after the intervention. While the statistically significant effect favoring ET over RT in terms of exercise capacity was observed, it should be interpreted cautiously. Patients in severe stages of COPD may derive greater benefits from either ET or RT and should be encouraged accordingly. These findings have implications for exercise prescription in patients with COPD. TRIAL REGISTRATION: ChiCTR-INR-16009892 (17, Nov, 2016).

Maximizing the Value of Real-World Data and Real-World Evidence to Accelerate Healthcare Transformation in China: Summary of External Advisory Committee Meetings.

Use of real-world data (RWD) is gaining wide attention. To bridge the gap between diverse healthcare stakeholders and to leverage the impact of Chinese real-world evidence (RWE) globally, a multi-stakeholder External Advisory Committee (EAC) and EAC meetings were initiated, aiming to elucidate the current and evolving RWD landscape in China, articulate the values of RWE in ensuring Chinese patients' equitable access to affordable medicines and solutions, and identify strategic opportunities and partnerships for expansion of RWE generation in China. Chinese and international experts who are clinicians and academic researchers were selected as EAC members based on their professional background and familiarity with RWD/RWE. Three EAC meetings were held quarterly in 2023. Various topics were presented and discussed for insights and suggestions. Nine experts from China, one from South Korea, and two from Europe were selected as EAC members and attended these meetings. Experts' presentations were summarized by theme, including the RWD landscape and RWE enablement in China, as well as global development of a patient-centric ecosystem. Experts' insights and suggestions on maximizing the RWD/RWE value to accelerate healthcare transformation in China were collected. We concluded that though data access, sharing, and quality are still challenging, RWD is developing to support evidence generation in the medicinal product lifecycle, inform clinical practice, and empower patient management in China. RWD/RWE creates value, accelerates healthcare transformation, and improves patient outcomes. Fostering a patient-centric ecosystem across healthcare stakeholders and maintaining global partnerships and collaboration are essential for unlocking the power of RWD/RWE.

Plasmonic Alloys Enhanced Metabolic Fingerprints for the Diagnosis of COPD and Exacerbations.

Accurate diagnosis of chronic obstructive pulmonary disease (COPD) and exacerbations by metabolic biomarkers enables individualized treatment. Advanced metabolic detection platforms rely on designed materials. Here, we design mesoporous PdPt alloys to characterize metabolic fingerprints for diagnosing COPD and exacerbations. As a result, the optimized PdPt alloys enable the acquisition of metabolic fingerprints within seconds, requiring only 0.5 µL of native plasma by laser desorption/ionization mass spectrometry owing to the enhanced electric field, photothermal conversion, and photocurrent response. Machine learning decodes metabolic profiles acquired from 431 individuals, achieving a precise diagnosis of COPD with an area under the curve (AUC) of 0.904 and an accurate distinction between stable COPD and acute exacerbations of COPD (AECOPD) with an AUC of 0.951. Notably, eight metabolic biomarkers identified accurately discriminate AECOPD from stable COPD while providing valuable information on disease progress. Our platform will offer an advanced nanoplatform for the management of COPD, complementing standard clinical techniques.

Contribution of small airway inflammation to the development of COPD.

BACKGROUND: Little attention has been paid to the pathophysiological changes in the natural history of chronic obstructive pulmonary disease (COPD). The destructions of the small airways were visualized on thoracic micro-computed tomography scan. We investigated whether small airway inflammation (SAI) was the risk for the development of COPD. METHODS: A total of 1062 patients were enrolled and analyzed in the study. The partitioned airway inflammation was determined by exhaled nitric oxide (NO) of FnNO, FeNO50, FeNO200, and calculated CaNOdual. Both FeNO200 and CaNOdual were compared to detect the promising predictor for peripheral airway/alveolar inflammation in COPD. The correlation between exhaled NO and white cell classification was evaluated to determine the inflammation type during the development of COPD. RESULTS: Exhaled NO levels (FnNO, FeNO50, FeNO200, and CaNOdual) were the highest in the COPD group compared with all other groups. Furthermore, compared with controls, exhaled NO levels (FeNO50, FeNO200, and CaNOdual) were also significantly higher in the emphysema, chronic bronchitis, and smoking groups. FeNO200 was found to be a promising predictor for peripheral airway/alveolar inflammation (area under the curve [AUC] of the receiver operating characteristic [ROC] curve, area under the curve [AUC] = 0.841) compared with CaNOdual (AUC ROC = 0.707) in COPD. FeNO200 was the main risk factor (adjusted odds ratio, 2.191; 95% CI, 1.797-2.671; p = 0.002) for the development of COPD. The blood eosinophil and basophil levels were correlated with FeNO50 and FeNO200. CONCLUSION: The complete airway inflammations were shown in COPD, whereas SAI was the main risk factor for the development of COPD, which might relate to eosinophil and basophil levels.

Reliable automatic sleep stage classification based on hybrid intelligence.

Sleep staging is a vital aspect of sleep assessment, serving as a critical tool for evaluating the quality of sleep and identifying sleep disorders. Manual sleep staging is a laborious process, while automatic sleep staging is seldom utilized in clinical practice due to issues related to the inadequate accuracy and interpretability of classification results in automatic sleep staging models. In this work, a hybrid intelligent model is presented for automatic sleep staging, which integrates data intelligence and knowledge intelligence, to attain a balance between accuracy, interpretability, and generalizability in the sleep stage classification. Specifically, it is built on any combination of typical electroencephalography (EEG) and electrooculography (EOG) channels, including a temporal fully convolutional network based on the U-Net architecture and a multi-task feature mapping structure. The experimental results show that, compared to current interpretable automatic sleep staging models, our model achieves a Macro-F1 score of 0.804 on the ISRUC dataset and 0.780 on the Sleep-EDFx dataset. Moreover, we use knowledge intelligence to address issues of excessive jumps and unreasonable sleep stage transitions in the coarse sleep graphs obtained by the model. We also explore the different ways knowledge intelligence affects coarse sleep graphs by combining different sleep graph correction methods. Our research can offer convenient support for sleep physicians, indicating its significant potential in improving the efficiency of clinical sleep staging.

Internet of things-based management versus standard management of home noninvasive ventilation in COPD patients with hypercapnic chronic respiratory failure: a multicentre randomized controlled non-inferiority trial.

Background: Effective monitoring and management are crucial during long-term home noninvasive positive pressure ventilation (NPPV) in patients with hypercapnic chronic obstructive pulmonary disease (COPD). This study investigated the benefit of Internet of Things (IOT)-based management of home NPPV. Methods: This multicenter, prospective, parallel-group, randomized controlled non-inferiority trial enrolled patients requiring long-term home NPPV for hypercapnic COPD. Patients were randomly assigned (1:1), via a computer-generated randomization sequence, to standard home management or IOT management based on telemonitoring of clinical and ventilator parameters over 12 months. The intervention was unblinded, but outcome assessment was blinded to management assignment. The primary outcome was the between-group comparison of the change in health-related quality of life, based on severe respiratory insufficiency questionnaire scores with a non-inferiority margin of -5. This study is registered with Chinese Clinical Trials Registry (No. ChiCTR1800019536). Findings: Overall, 148 patients (age: 72.7 ± 6.8 years; male: 85.8%; forced expiratory volume in 1 s: 0.7 ± 0.3 L; PaCO2: 66.4 ± 12.0 mmHg), recruited from 11 Chinese hospitals between January 24, 2019, and June 28, 2021, were randomly allocated to the intervention group (n = 73) or the control group (n = 75). At 12 months, the mean severe respiratory insufficiency questionnaire score was 56.5 in the intervention group and 50.0 in the control group (adjusted between-group difference: 6.26 [95% CI, 3.71-8.80]; P < 0.001), satisfying the hypothesis of non-inferiority. The 12-month risk of readmission was 34.3% in intervention group compared with 56.0% in the control group, adjusted hazard ratio of 0.56 (95% CI, 0.34-0.92; P = 0.023). No severe adverse events were reported. Interpretation: Among stable patients with hypercapnic COPD, using IOT-based management for home NPPV improved health-related quality of life and prolonged the time to readmission. Funding: Air Liquide Healthcare (Beijing) Co., Ltd.

Critical roles of PAI-1 in lipopolysaccharide-induced acute lung injury.

PURPOSE: Plasminogen activator inhibitor-1 (PAI-1) is the main inhibitor of fibrinolytic systems. The effect of PAI-1 on inflammatory response is still inconsistent. Our study was conducted to investigate its effects on inflammation to clarify the role of PAI-1 in acute lung injury (ALI) induced by lipopolysaccharide (LPS). MATERIAL AND METHODS: ALI models were established in wild-type (WT) and PAI-1 knockout (KO) mice by LPS intervention for 48 â€‹h. Lung histopathology, wet-dry ratio, total cell count and TNF-α concentration in bronchoalveolar lavage fluid (BALF), and inflammation related proteins were detected. Flow cytometry was used to sort neutrophils, macrophages, regulatory T cells (Treg) and T helper cell 17 (Th17). RNA sequencing was performed to find differentially expressed genes. Masson staining and immunohistochemistry were used to analyze pulmonary fiber deposition and proliferation. RESULTS: Compared with ALI (WT) group, the wet-dry ratio, the total number of BALF cells, the concentration of TNF-α in BALF, and the expression of pp65 in the lung tissue was increased in ALI (PAI-1 KO) group, with increased proportion of neutrophils, decreased proportion of macrophages and decreased proportion of Treg/Th17 in the lung tissue. Collagen fiber deposition and PCNA expression were lighter in ALI (PAI-1 KO) group than ALI (WT) group. PPI analysis showed that PAI-1 was closely related to TNF, IL-6, IL-1ß, Smad2/3 and mainly concentrated in the complement and coagulation system, TNF-α and IL-17 signaling pathways. CONCLUSIONS: PAI-1 KO could aggravate ALI induced by LPS at 48 â€‹h. PAI-1 may be an important target to improve the prognosis of ALI.

Proteome analysis develops novel plasma proteins classifier in predicting the mortality of COVID-19.

COVID-19 has been a global concern for 3 years, however, consecutive plasma protein changes in the disease course are currently unclear. Setting the mortality within 28 days of admission as the main clinical outcome, plasma samples were collected from patients in discovery and independent validation groups at different time points during the disease course. The whole patients were divided into death and survival groups according to their clinical outcomes. Proteomics and pathway/network analyses were used to find the differentially expressed proteins and pathways. Then, we used machine learning to develop a protein classifier which can predict the clinical outcomes of the patients with COVID-19 and help identify the high-risk patients. Finally, a classifier including C-reactive protein, extracellular matrix protein 1, insulin-like growth factor-binding protein complex acid labile subunit, E3 ubiquitin-protein ligase HECW1 and phosphatidylcholine-sterol acyltransferase was determined. The prediction value of the model was verified with an independent patient cohort. This novel model can realize early prediction of 28-day mortality of patients with COVID-19, with the area under curve 0.88 in discovery group and 0.80 in validation group, superior to 4C mortality and E-CURB65 scores. In total, this work revealed a potential protein classifier which can assist in predicting the outcomes of COVID-19 patients and providing new diagnostic directions.

A phase 4 multicentre, 2×2 factorial randomised, double-blind, placebo-controlled trial to investigate the efficacy and safety of tobramycin inhalation solution for Pseudomonas aeruginosa eradication in bronchiectasis: ERASE.

Chronic Pseudomonas aeruginosa (PA) infection significantly contributes to morbidity and mortality in bronchiectasis patients. Initiating antibiotics early may lead to the eradication of PA. Here we outline the design of a trial (ERASE; NCT06093191) assessing the efficacy and safety of inhaled tobramycin, alone or with oral ciprofloxacin, in bronchiectasis patients with a new isolation of PA. This multicentre, 2×2 factorial randomised, double-blind, placebo-controlled, parallel-group trial includes a 2-week screening period, a 12-week treatment phase (with a combination of ciprofloxacin or a placebo at initial 2 weeks) and a 24-week follow-up. 364 adults with bronchiectasis and a new PA isolation will be randomly assigned to one of four groups: placebo (inhaled saline and ciprofloxacin placebo twice daily), ciprofloxacin alone (750 mg ciprofloxacin and inhaled saline twice daily), inhaled tobramycin alone (inhaled 300 mg tobramycin and ciprofloxacin placebo twice daily) or a combination of both drugs (inhaled 300 mg tobramycin and 750 mg ciprofloxacin twice daily). The primary objective of this study is to assess the proportion of patients successfully eradicating PA in each group by the end of the study. Efficacy will be evaluated based on the eradication rate of PA at other time points (12, 24 and 36 weeks), the occurrence of exacerbations and hospitalisations, time to first pulmonary exacerbations, patient-reported outcomes, symptom measures, pulmonary function tests and the cost of hospitalisations. To date no randomised trial has evaluated the benefit of different PA eradication strategies in bronchiectasis patients. The ERASE trial will therefore generate crucial data to inform future clinical guidelines.