Targeting Immunoproteasome in Polarized Macrophages Ameliorates Experimental Emphysema Via Activating NRF1/2-P62 Axis and Suppressing IRF4 Transcription.

Chronic obstructive pulmonary disease (COPD) stands as the prevailing chronic airway ailment, characterized by chronic bronchitis and emphysema. Current medications fall short in treatment of these diseases, underscoring the urgent need for effective therapy. Prior research indicated immunoproteasome inhibition alleviated various inflammatory diseases by modulating immune cell functions. However, its therapeutic potential in COPD remains largely unexplored. Here, an elevated expression of immunoproteasome subunits LMP2 and LMP7 in the macrophages isolated from mouse with LPS/Elastase-induced emphysema and polarized macrophages in vitro is observed. Subsequently, intranasal administration of the immunoproteasome-specific inhibitor ONX-0914 significantly mitigated COPD-associated airway inflammation and improved lung function in mice by suppressing macrophage polarization. Additionally, ONX-0914 capsulated in PLGA nanoparticles exhibited more pronounced therapeutic effect on COPD than naked ONX-0914 by targeting immunoproteasome in polarized macrophages. Mechanistically, ONX-0914 activated autophagy and endoplasmic reticulum (ER) stress are not attribute to the ONX-0914 mediated suppression of macrophage polarization. Intriguingly, ONX-0914 inhibited M1 polarization through the nuclear factor erythroid 2-related factor-1 (NRF1) and NRF2-P62 axis, while the suppression of M2 polarization is regulated by inhibiting the transcription of interferon regulatory factor 4 (IRF4). In summary, the findings suggest that targeting immunoproteasome in macrophages holds promise as a therapeutic strategy for COPD.

A prediction model for gestational diabetes mellitus based on steroid hormonal changes in early and mid-down syndrome screening: A multicenter longitudinal study.

BACKGROUND: Steroid hormones (SH) during pregnancy are associated with the development of gestational diabetes mellitus (GDM). Early and mid-Down syndrome screening is used to assess the risk of Down syndrome in the fetus. It is unclear whether changes in SH during this period can be used as an early predictor of GDM. METHODS: This study was a multicenter, longitudinal cohort study. GDM is diagnosed by an oral glucose tolerance test (OGTT) between 24 and 28 weeks of gestation. We measured SH levels at early and mid-Down syndrome screening, respectively. Based on the SH changes, logistic regression analysis was used to construct a prediction model for GDM. Finally, evaluated the model's predictive performance by creating a receiver operating characteristic curve (ROC) and performing external validation. RESULTS: This study enrolled 193 pregnant women (discovery cohort, n = 157; validation cohort, n = 36). SH changes occur dynamically after pregnancy. At early Down syndrome screening, only cortisol (F) (p < 0.05, 95 % CI 4780.95-46083.68) was elevated in GDM. At mid-Down syndrome screening, free testosterone (FT) (p < 0.01, 95 % CI 0.10-0.55) and estradiol (E2) (p < 0.05, 95 % CI 203.55-1784.78) were also significantly elevated. There were significant differences in the rates of change in E2 (Fold change (FC) = 1.3425, p = 0.0072), albumin (ALB) (FC=1.5759, p = 0.0117), and dihydrotestosterone (DHT) (FC=-2.1234, p = 0.0165) between GDM and no-GDM. Stepwise logistic regression analysis resulted in the best predictive model, including six variables (Δweight, ΔF, Δcortisone (E), ΔE2, Δprogesterone (P), ΔDHT). The area under the curve for this model was 0.791, and for the external validation cohort, it was 0.799. CONCLUSIONS: A GDM prediction model can be constructed using SH measures during early and mid-Down syndrome screening.

Phage-antibiotic synergy suppresses resistance emergence of Klebsiella pneumoniae by altering the evolutionary fitness.

Phage-antibiotic synergy (PAS) represents a superior treatment strategy for pathogen infections with less probability of resistance development. Here, we aim to understand the molecular mechanism by which PAS suppresses resistance in terms of population evolution. A novel hypervirulent Klebsiella pneumoniae (KP) phage H5 was genetically and structurally characterized. The combination of H5 and ceftazidime (CAZ) showed a robust synergistic effect in suppressing resistance emergence. Single-cell Raman analysis showed that the phage-CAZ combination suppressed bacterial metabolic activities, contrasting with the upregulation observed with phage alone. The altered population evolutionary trajectory was found to be responsible for the contrasting metabolic activities under different selective pressures, resulting in pleiotropic effects. A pre-existing wcaJ point mutation (wcaJG949A) was exclusively selected by H5, conferring a fitness advantage and up-regulated activity of carbohydrate metabolism, but also causing a trade-off between phage resistance and collateral sensitivity to CAZ. The wcaJ point mutation was counter-selected by H5-CAZ, inducing various mutations in galU that imposed evolutionary disadvantages with higher fitness costs, and suppressed carbohydrate metabolic activity. H5 and H5-CAZ treatments resulted in opposite effects on the transcriptional activity of the phosphotransferase system and the ascorbate and aldarate metabolism pathway, suggesting potential targets for phage resistance suppression. Our study reveals a novel mechanism of resistance suppression by PAS, highlighting how the complexity of bacterial adaptation to selective pressures drives treatment outcomes. IMPORTANCE: Phage-antibiotic synergy (PAS) has been recently proposed as a superior strategy for the treatment of multidrug-resistant pathogens to effectively reduce bacterial load and slow down both phage and antibiotic resistance. However, the underlying mechanisms of resistance suppression by PAS have been poorly and rarely been studied. In this study, we tried to understand how PAS suppresses the emergence of resistance using a hypervirulent Klebsiella pneumoniae (KP) strain and a novel phage H5 in combination with ceftazidime (CAZ) as a model. Our study reveals a novel mechanism by which PAS drives altered evolutionary trajectory of bacterial populations, leading to suppressed emergence of resistance. The findings advance our understanding of how PAS suppresses the emergence of resistance, and are imperative for optimizing the efficacy of phage-antibiotic therapy to further improve clinical outcomes.

Comparison of chemical composition between imitation wild and transplanted Astragali Radix and their therapeutic effects on heart failure.

ETHNOPHARMACOLOGICAL RELEVANCE: Astragali Radix (AR) is a traditional Chinese herbal medicine, which has been widely used on treating chronic heart failure (CHF) in clinical practice. Two main types of AR in the market are the imitation wild AR (5YAR) and transplanted AR (2YAR). It remains unclear whether there are variations in the anti-heart failure effects of AR with different growth years. Further research is required to explore the material composition and mechanisms of AR in combating heart failure. AIM OF THE STUDY: The aim of the study was to compare the main chemical composition content and the protective effects of 2YAR and 5YAR on heart failure. MATERIALS AND METHODS: Ethanol extracts of 2YAR and 5YAR were prepared, and chemical composition analysis was conducted. C57BL/6 mice were subcutaneously injected with ISO to induce heart failure (HF) and were administrated with a corresponding dose of the extracts of 2YAR and 5YAR by gavage for 28 days. Cardiac function was evaluated using echocardiography. The serum levels of enzymes related to myocardial injury, oxidative stress, and inflammation were detected. The left ventricle was excised for hematoxylin-eosin, Masson, Sirius Red, wheat germ agglutinin, and TUNEL staining. Electron microscopy examination of mitochondrial structure in myocardial cells. Protein expression of monocarboxylate transporter 4 (MCT4), Peroxisome proliferator-activated receptor-γ coactivator 1α (PGC-1α), phosphorylated AMP-activated protein kinase (p-AMPK), phosphorylated serine/threonine protein kinase (p-AKT), and phosphorylated insulin receptor substrates 1 (p-IRS-1) were detected by immunohistochemistry and Western blot. RESULTS: The content of saponins and flavonoids in 5YAR was higher than that in the 2YAR. However, the content of polysaccharides in 5YAR is lower than in 2YAR. The treatment of 2YAR and 5YAR daily for 28 days prevented ISO-induced myocardial damage, including the decrease in serum cardiac enzymes and cardiomyocyte apoptotic index, and improvement in heart function and mitochondrial structure. Additionally, 2YAR and 5YAR reduced serum inflammatory factors and myocardial fibrosis levels. Treatment with 2YAR and 5YAR also decreased MCT4 expression and enhanced PGC-1α, p-AKT, p-AMPK, and p-IRS-1 expression in heart tissues. CONCLUSIONS: The 5YAR was better than 2YAR in anti-heart failure, which may be related to the increase in saponins and flavonoids content. AR exerts anti-heart failure effect by improving mitochondrial function and ameliorating cardiac insulin resistance through activation of the AMPK/PGC1α and IRS/AKT pathways.

The association between preserved ratio impaired spirometry and adverse outcomes of depression and anxiety: evidence from the UK Biobank.

BACKGROUND: Preserved ratio impaired spirometry (PRISm) is a new lung function impairment phenotype and has been recognized as a risk factor for various adverse outcomes. We aimed to examine the associations of this new lung function impairment phenotype with depression and anxiety in longitudinal studies. METHODS: We included 369 597 participants from the UK Biobank cohort, and divided them into population 1 without depression or anxiety and population 2 with depression or anxiety at baseline. Cox proportional hazard models were performed to evaluate the associations of lung function impairment phenotype with adverse outcomes of depression and anxiety, as well as their subtypes. RESULTS: At baseline, 38 879 (10.5%) participants were diagnosed with PRISm. In population 1, the adjusted hazard ratios (HRs) for PRISm (v. normal spirometry) were 1.12 (95% CI 1.07-1.18) for incident depression, and 1.11 (95% CI 1.06-1.15) for incident anxiety, respectively. In population 2, PRISm was a risk factor for mortality in participants with depression (HR: 1.46; 95% CI 1.31-1.62) and anxiety (HR: 1.70; 95% CI 1.44-2.02), compared with normal spirometry. The magnitudes of these associations were similar in the phenotypes of lung function impairment and the subtypes of mental disorders. Trajectory analysis showed that the transition from normal spirometry to PRISm was associated with a higher risk of mortality in participants with depression and anxiety. CONCLUSIONS: PRISm and airflow obstruction have similar risks of depression and anxiety. PRISm recognition may contribute to the prevention of depression and anxiety.

Respiratory physiological mechanism of two types of equal-intensity inspiratory muscle training in stable patients with chronic obstructive pulmonary disease.

PURPOSE: This study aimed to investigate the respiratory physiological changes resulting from short-term inspiratory resistance training (R-IMT) and inspiratory threshold training (T-IMT) in patients with chronic obstructive pulmonary disease (COPD) and to compare the mechanisms of the two training methods. PATIENTS AND METHODS: A total of 75 stable patients with COPD combined with inspiratory muscle weakness were randomly allocated to three groups: R-IMT (n = 26), T-IMT (n = 24), and control (n = 25). Before and after 8 weeks of inspiratory muscle training(IMT), cardiopulmonary exercise tests were conducted to assess respiratory patterns, respiratory central drive, exercise tolerance, and ventilation efficiency. RESULTS: After 8 weeks of IMT, Inspiratory muscle strength, represented by MIP (maximum inspiratory mouth pressure) and exercise capacity increased during exercise in both IMT groups (P < 0.05). In the R-IMT group, inspiratory time (Ti) prolonged (P < 0.05), tidal volume (Vt) increased (P < 0.05), ventilation efficiency (represented by ventilation-center coupling) increased (P < 0.05) during exercise. Conversely, the T-IMT group did not exhibit any of these changes after IMT (P > 0.05). CONCLUSION: In summary, the improvement in exercise tolerance was associated with an increase in inspiratory muscle reserve in both R-IMT and T-IMT. However, only R-IMT was associated with deeper and slower breathing, as well as improved ventilation efficiency.

[Antitumor Study of Neoantigen-reactive T Cells Co-expressing IL-7 and CCL19 
in Mouse Lung Cancer].

BACKGROUND: Neoantigen reactive T cell (NRT) has the ability to inhibit the growth of tumors expressing specific neoantigens. However, due to the difficult immune infiltration and the inhibition of tumor microenvironment, the therapeutic effect of NRT in solid tumors is limited. In this study, we designed NRT cells (7×19 NRT) that can express both interleukin-7 (IL-7) and chemokine C-C motif ligand 19 (CCL19) in mouse lung cancer cells, and evaluated the difference in anti-tumor effect between 7×19 NRT cells and conventional NRT cells. METHODS: We performed next-generation sequencing and neoantigen prediction for mouse Lewis lung carcinoma (LLC), prepared RNA vaccine, cultured NRT cells, constructed retroviral vectors encoding IL-7 and CCL19, transduced NRT cells and IL-7 and CCL19 were successfully expressed, and 7×19 NRT was successfully obtained. The anti-tumor effect was evaluated in vivo and in vitro in mice. RESULTS: The 7×19 NRT cells significantly enhanced the proliferation and invasion ability of T cells by secreting IL-7 and CCL19, achieved significant tumor inhibition in the mouse lung cancer and extended the survival period of mice. The T cell infiltration into tumor tissue and the necrosis of tumor tissue increased significantly after 7×19 NRT treatment. In addition, both 7×19 NRT treatment and conventional NRT treatment were safe. CONCLUSIONS: The anti-solid tumor ability of NRT cells is significantly enhanced by the arming of IL-7 and CCL19, which is a safe and effective genetic modification of NRT.

Artificial intelligence in COPD CT images: identification, staging, and quantitation.

Chronic obstructive pulmonary disease (COPD) stands as a significant global health challenge, with its intricate pathophysiological manifestations often demanding advanced diagnostic strategies. The recent applications of artificial intelligence (AI) within the realm of medical imaging, especially in computed tomography, present a promising avenue for transformative changes in COPD diagnosis and management. This review delves deep into the capabilities and advancements of AI, particularly focusing on machine learning and deep learning, and their applications in COPD identification, staging, and imaging phenotypes. Emphasis is laid on the AI-powered insights into emphysema, airway dynamics, and vascular structures. The challenges linked with data intricacies and the integration of AI in the clinical landscape are discussed. Lastly, the review casts a forward-looking perspective, highlighting emerging innovations in AI for COPD imaging and the potential of interdisciplinary collaborations, hinting at a future where AI doesn't just support but pioneers breakthroughs in COPD care. Through this review, we aim to provide a comprehensive understanding of the current state and future potential of AI in shaping the landscape of COPD diagnosis and management.

Predicting Acute Exacerbation Phenotype in Chronic Obstructive Pulmonary Disease Patients Using VGG-16 Deep Learning.

INTRODUCTION: Exacerbations of chronic obstructive pulmonary disease (COPD) have a significant impact on hospitalizations, morbidity, and mortality of patients. This study aimed to develop a model for predicting acute exacerbation in COPD patients (AECOPD) based on deep-learning (DL) features. METHODS: We performed a retrospective study on 219 patients with COPD who underwent inspiratory and expiratory HRCT scans. By recording the acute respiratory events of the previous year, these patients were further divided into non-AECOPD group and AECOPD group according to the presence of acute exacerbation events. Sixty-nine quantitative CT (QCT) parameters of emphysema and airway were calculated by NeuLungCARE software, and 2,000 DL features were extracted by VGG-16 method. The logistic regression method was employed to identify AECOPD patients, and 29 patients of external validation cohort were used to access the robustness of the results. RESULTS: The model 3-B achieved an area under the receiver operating characteristic curve (AUC) of 0.933 and 0.865 in the testing cohort and external validation cohort, respectively. Model 3-I obtained AUC of 0.895 in the testing cohort and AUC of 0.774 in the external validation cohort. Model 7-B combined clinical characteristics, QCT parameters, and DL features achieved the best performance with an AUC of 0.979 in the testing cohort and demonstrating robust predictability with an AUC of 0.932 in the external validation cohort. Likewise, model 7-I achieved an AUC of 0.938 and 0.872 in the testing cohort and external validation cohort, respectively. CONCLUSIONS: DL features extracted from HRCT scans can effectively predict acute exacerbation phenotype in COPD patients.

Largescale multicenter study of a serum metabolite biomarker panel for the diagnosis of breast cancer.

Breast cancer (BC) is currently the most prevalent malignancy worldwide, and finding effective non-invasive biomarkers for routine clinical detection of BC remains a significant challenge. Here, we performed non-targeted and targeted metabolomics analysis on the screening, training and validation cohorts of serum samples from 1,947 participants. A metabolite biomarker model including glutamate, erythronate, docosahexaenoate, propionylcarnitine, and patient's age was established for detecting BC. This model demonstrated better diagnostic performance than carbohydrate antigen 15-3 (CA15-3) and carcinoembryonic antigen (CEA) alone in discriminating BC from healthy controls both in the training and validation cohorts [area under the curve (AUC), 0.954; sensitivity, 87.1% and specificity, 93.5% for the training cohort and 0.834, 68.3%, and 85.2%, respectively, for the validation cohort 1]. This study has established a noninvasive approach for the detection of BC, which shows potential as a suitable supplement to the clinical screening methods currently employed for BC.

Clinical features and associated factors of impaired ventilatory efficiency: findings from the ECOPD study in China.

BACKGROUND: Impaired ventilatory efficiency during exercise is a predictor of mortality in chronic obstructive pulmonary disease. However, little is known about the clinical features and associated factors of impaired ventilatory efficiency in China. METHODS: We conducted a cross-sectional community-based study in China and collected demographic and clinical information, cardiopulmonary exercise testing, spirometry, and CT data. Impaired ventilatory efficiency was defined by a nadir ventilatory equivalent for CO2 production above the upper limit of normal. Multivariable linear and logistic regression models were used to explore the clinical features and associated factors of impaired ventilatory efficiency. RESULTS: The final analyses included 941 subjects, 702 (74.6%) of whom had normal ventilatory efficiency and 239 (25.4%) had impaired ventilatory efficiency. Participants with impaired ventilatory efficiency had more chronic respiratory symptoms, poorer lung function and exercise capacity, and more severe emphysema (natural logarithm transformation of the low-attenuation area of the lung with attenuation values below -950 Hounsfield units, logLAA-950: 0.19±0.65 vs -0.28±0.63, p<0.001) and air trapping (logLAA-856: 1.03±0.65 vs 0.68±0.70, p<0.001) than those with normal ventilatory efficiency. Older age (60-69 years, OR 3.10 (95% CI 1.33 to 7.21), p=0.009 and 70-80 years, OR 6.48 (95% CI 2.56 to 16.43), p<0.001 vs 40-49 years) and smoking (former, OR 3.19 (95% CI 1.29 to 7.86), p=0.012; current, OR 4.27 (95% CI 1.78 to 10.24), p=0.001 vs never) were identified as high risk factors of impaired ventilatory efficiency. CONCLUSIONS: Impaired ventilatory efficiency was associated with poorer respiratory characteristics. Longitudinal studies are warranted to explore the progression of individuals with impaired ventilatory efficiency.

Forsythoside B alleviates cerebral ischemia-reperfusion injury via inhibiting NLRP3 inflammasome mediated by SIRT1 activation.

BACKGROUND: The inflammatory response is a key factor in the pathogenesis of cerebral ischemia/reperfusion injury (CIRI), and anti-inflammatory interventions may offer a promising therapeutic strategy. Forsythoside B (FB) is a phenylethanoid glycoside isolated from Forsythiae fructus, which has been reported to have anti-inflammatory effects. However, the mechanism of the neuroprotective effect of FB on CIRI remains unclear. METHODS: Adult male Sprague-Dawley rats were subjected to transient middle cerebral artery occlusion/reperfusion (MCAO/R). FB was administered intraperitoneally for 3 days prior to MCAO/R. Cerebral infarct volume and neurological deficit score were used as indices to evaluate MCAO/R injury. The serum levels of inflammatory factors and antioxidant enzymes were measured. The activation of silent information regulator 2 homolog 1 (Sirt1) and the inhibition of the nucleotide-binding oligomerization domain-like receptor with a pyrin domain 3 (NLRP3) pathway were assessed through western blot and immunohistochemistry analysis. Furthermore, the rats were treated with Sirt1 shRNA 3 days before MCAO/R by stereotactical injection into the ipsilateral hemispheric region to assess the impact of Sirt1 knockdown on the protection of FB during MCAO/R. RESULTS: FB reduced cerebral infarct volume and neurological deficit score in MCAO/R rats. FB reduced pathological changes and cell apoptosis in the hippocampal CA1 region and cortex on the ischemic side of rats. FB inhibited the serum levels of inflammatory factors and increased the activities of antioxidant enzymes. Further study showed that FB inhibited the activation of the NLRP3 pathway and induced Sirt1 activation. CONCLUSION: FB demonstrated neuroprotective and anti-inflammatory effects by inhibiting the NLRP3 pathway through Sirt1 activation in CIRI.

Learning and depicting lobe-based radiomics feature for COPD Severity staging in low-dose CT images.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a prevalent and debilitating respiratory condition that imposes a significant healthcare burden worldwide. Accurate staging of COPD severity is crucial for patient management and treatment planning. METHODS: The retrospective study included 530 hospital patients. A lobe-based radiomics method was proposed to classify COPD severity using computed tomography (CT) images. First, we segmented the lung lobes with a convolutional neural network model. Secondly, the radiomic features of each lung lobe are extracted from CT images, the features of the five lung lobes are merged, and the selection of features is accomplished through the utilization of a variance threshold, t-Test, least absolute shrinkage and selection operator (LASSO). Finally, the COPD severity was classified by a support vector machine (SVM) classifier. RESULTS: 104 features were selected for staging COPD according to the Global initiative for chronic Obstructive Lung Disease (GOLD). The SVM classifier showed remarkable performance with an accuracy of 0.63. Moreover, an additional set of 132 features were selected to distinguish between milder (GOLD I + GOLD II) and more severe instances (GOLD III + GOLD IV) of COPD. The accuracy for SVM stood at 0.87. CONCLUSIONS: The proposed method proved that the novel lobe-based radiomics method can significantly contribute to the refinement of COPD severity staging. By combining radiomic features from each lung lobe, it can obtain a more comprehensive and rich set of features and better capture the CT radiomic features of the lung than simply observing the lung as a whole.

Human genetic associations of the airway microbiome in chronic obstructive pulmonary disease.

Little is known about the relationships between human genetics and the airway microbiome. Deeply sequenced airway metagenomics, by simultaneously characterizing the microbiome and host genetics, provide a unique opportunity to assess the microbiome-host genetic associations. Here we performed a co-profiling of microbiome and host genetics with the identification of over 5 million single nucleotide polymorphisms (SNPs) through deep metagenomic sequencing in sputum of 99 chronic obstructive pulmonary disease (COPD) and 36 healthy individuals. Host genetic variation was the most significant factor associated with the microbiome except for geography and disease status, with its top 5 principal components accounting for 12.11% of the microbiome variability. Within COPD individuals, 113 SNPs mapped to candidate genes reported as genetically associated with COPD exhibited associations with 29 microbial species and 48 functional modules (P < 1 × 10-5), where Streptococcus salivarius exhibits the strongest association to SNP rs6917641 in TBC1D32 (P = 9.54 × 10-8). Integration of concurrent host transcriptomic data identified correlations between the expression of host genes and their genetically-linked microbiome features, including NUDT1, MAD1L1 and Veillonella parvula, TTLL9 and Stenotrophomonas maltophilia, and LTA4H and Haemophilus influenzae. Mendelian randomization analyses revealed a potential causal link between PARK7 expression and microbial type III secretion system, and a genetically-mediated association between COPD and increased relative abundance of airway Streptococcus intermedius. These results suggest a previously underappreciated role of host genetics in shaping the airway microbiome and provide fresh hypotheses for genetic-based host-microbiome interactions in COPD.

Acute exacerbation prediction of COPD based on Auto-metric graph neural network with inspiratory and expiratory chest CT images.

Chronic obstructive pulmonary disease (COPD) is a widely prevalent disease with significant mortality and disability rates and has become the third leading cause of death globally. Patients with acute exacerbation of COPD (AECOPD) often substantially suffer deterioration and death. Therefore, COPD patients deserve special consideration regarding treatment in this fragile population for pre-clinical health management. Based on the above, this paper proposes an AECOPD prediction model based on the Auto-Metric Graph Neural Network (AMGNN) using inspiratory and expiratory chest low-dose CT images. This study was approved by the ethics committee in the First Affiliated Hospital of Guangzhou Medical University. Subsequently, 202 COPD patients with inspiratory and expiratory chest CT Images and their annual number of AECOPD were collected after the exclusion. First, the inspiratory and expiratory lung parenchyma images of the 202 COPD patients are extracted using a trained ResU-Net. Then, inspiratory and expiratory lung Radiomics and CNN features are extracted from the 202 inspiratory and expiratory lung parenchyma images by Pyradiomics and pre-trained Med3D (a heterogeneous 3D network), respectively. Last, Radiomics and CNN features are combined and then further selected by the Lasso algorithm and generalized linear model for determining node features and risk factors of AMGNN, and then the AECOPD prediction model is established. Compared to related models, the proposed model performs best, achieving an accuracy of 0.944, precision of 0.950, F1-score of 0.944, ad area under the curve of 0.965. Therefore, it is concluded that our model may become an effective tool for AECOPD prediction.

Targeting BRD4 with PROTAC degrader ameliorates LPS-induced acute lung injury by inhibiting M1 alveolar macrophage polarization.

OBJECTIVES: Acute lung injury (ALI) is a highly inflammatory condition with the involvement of M1 alveolar macrophages (AMs) polarization, eventually leading to the development of non-cardiogenic edema in alveolar and interstitial regions, accompanied by persistent hypoxemia. Given the significant mortality rate associated with ALI, it is imperative to investigate the underlying mechanisms of this condition so as to identify potential therapeutic targets. The therapeutic effects of the inhibition of bromodomain containing protein 4 (BRD4), an epigenetic reader, has been proven with high efficacy in ameliorating various inflammatory diseases through mediating immune cell activation. However, little is known about the therapeutic potential of BRD4 degradation in acute lung injury. METHODS: This study aimed to assess the protective efficacy of ARV-825, a novel BRD4-targeted proteolysis targeting chimera (PROTAC), against ALI through histopathological examination in lung tissues and biochemical analysis in bronchoalveolar lavage fluid (BALF). Additionally, the underlying mechanism by which BRD4 regulated M1 AMs was elucidated by using CUT & Tag assay. RESULTS: In this study, we found the upregulation of BRD4 in a lipopolysaccharide (LPS)-induced ALI model. Furthermore, we observed that intraperitoneal administration of ARV-825, significantly alleviated LPS-induced pulmonary pathological changes and inflammatory responses. These effects were accompanied by the suppression of M1 AMs. In addition, our findings revealed that the administration of ARV-825 effectively suppressed M1 AMs by inhibiting the expression of IRF7, a crucial transcriptional factor involved in M1 macrophages. CONCLUSION: Our study suggested that targeting BRD4 using ARV-825 is a potential therapeutic approach for ALI.

Wogonoside Ameliorates Airway Inflammation and Mucus Hypersecretion via NF-κB/STAT6 Signaling in Ovalbumin-Induced Murine Acute Asthma.

Asthma is recognized as a chronic respiratory illness characterized by airway inflammation and airway hyperresponsiveness. Wogonoside, a flavonoid glycoside, is reported to significantly alleviate the inflammation response and oxidative stress. Herein, this study aimed to investigate the therapeutic effect and underlying mechanism of wogonoside on airway inflammation and mucus hypersecretion in a murine asthma model and in human bronchial epithelial cells (16HBE). BALB/c mice were sensitized and challenged with ovalbumin (OVA). Pulmonary function and the number of cells in the bronchoalveolar lavage fluid (BALF) were examined. Pathological changes in lung tissue in each group were evaluated via hematoxylin and eosin and periodic acid-Schiff staining, and changes in levels of cytokines in BALF and of immunoglobulin E in serum were determined via an enzyme-linked immunosorbent assay. The expression of relevant genes in lung tissue was analyzed via real-time PCR. Western blotting and immunofluorescence were employed to detect the expression of relevant proteins in lung tissue and 16HBE cells. Treatment with 10 and 20 mg/kg wogonoside significantly attenuated the OVA-induced increase of inflammatory cell infiltration, mucus secretion, and goblet cell percentage and improved pulmonary function. Wogonoside treatment reduced the level of T-helper 2 cytokines including interleukin (IL)-4, IL-5, and IL-13 in BALF and of IgE in serum and decreased the mRNA levels of cytokines (IL-4, IL-5, IL-6, IL-13, and IL-1ß and tumor necrosis factor-α), chemokines (CCL-2, CCL-11, and CCL-24), and mucoproteins (MUC5AC, MUC5B, and GOB5) in lung tissues. The expression of MUC5AC and the phosphorylation of STAT6 and NF-κB p65 in lung tissues and 16HBE cells were significantly downregulated after wogonoside treatment. Thus, wogonoside treatment may effectively decrease airway inflammation, airway remodeling, and mucus hypersecretion via blocking NF-κB/STAT6 activation.

Association between cooking fuel exposure and respiratory health: Longitudinal evidence from the China Health and Retirement Longitudinal Study (CHARLS).

The epidemiological evidences for the association between cooking fuel exposure and respiratory health were inconsistent, and repeated-measures prospective evaluation of cooking fuel exposure was still lacking. We assessed the longitudinal association of chronic lung disease (CLD) and lung function with cooking fuel types among Chinese adults aged ≥ 40 years. In this prospective, nationwide representative cohort of the China Health and Retirement Longitudinal Study from 2011 to 2018, 9004 participants from 28 provinces in China were included. CLD was identified based on self-reported physician diagnosis in 2018. Lung function was assessed by peak expiratory flow (PEF) in 2011, 2013 and 2015. Multivariable logistic and linear mixed-effects repeated-measures models were conducted to measure the associations of CLD and PEF with cooking fuel types. Three-level mixed-effects model was performed as sensitivity analysis. Among the participants, 3508 and 3548 participants used persistent solid and clean cooking fuels throughout the survey, and 1948 participants who used solid cooking fuels at baseline switched to clean cooking fuels. Use of persistent clean cooking fuels (adjusted odds ratio [aOR] = 0.73, 95 % confidence interval [CI]: 0.61, 0.88) and switch of solid fuels to clean fuels (aOR = 0.81, 95 % CI: 0.67, 0.98) were associated with lower risk of CLD. The use of clean cooking fuels throughout the survey and switch of solid fuels to clean fuels in 2013 were also significantly associated with higher PEF level. Similar results were observed in stratified analyses and different statistical models. The evidence from CHARLS cohort suggested that reducing solid cooking fuel exposure was associated with lower risk of CLD and better lung function. Given the recent evidence, improving household air quality will reduce the burden of chronic lung diseases.

Prognostic analysis of high-flow nasal cannula therapy and non-invasive ventilation in mild to moderate hypoxemia patients and construction of a machine learning model for 48-h intubation prediction-a retrospective analysis of the MIMIC database.

Background: This study aims to investigate the clinical outcome between high-flow nasal cannula (HFNC) and non-invasive ventilation (NIV) therapy in mild to moderate hypoxemic patients on the first ICU day and to develop a predictive model of 48-h intubation. Methods: The study included adult patients from the MIMIC III and IV databases who first initiated HFNC or NIV therapy due to mild to moderate hypoxemia (100 < PaO2/FiO2 ≤ 300). The 48-h and 30-day intubation rates were compared using cross-sectional and survival analysis. Nine machine learning and six ensemble algorithms were deployed to construct the 48-h intubation predictive models, of which the optimal model was determined by its prediction accuracy. The top 10 risk and protective factors were identified using the Shapley interpretation algorithm. Result: A total of 123,042 patients were screened, of which, 673 were from the MIMIC IV database for ventilation therapy comparison (HFNC n = 363, NIV n = 310) and 48-h intubation predictive model construction (training dataset n = 471, internal validation set n = 202) and 408 were from the MIMIC III database for external validation. The NIV group had a lower intubation rate (23.1% vs. 16.1%, p = 0.001), ICU 28-day mortality (18.5% vs. 11.6%, p = 0.014), and in-hospital mortality (19.6% vs. 11.9%, p = 0.007) compared to the HFNC group. Survival analysis showed that the total and 48-h intubation rates were not significantly different. The ensemble AdaBoost decision tree model (internal and external validation set AUROC 0.878, 0.726) had the best predictive accuracy performance. The model Shapley algorithm showed Sequential Organ Failure Assessment (SOFA), acute physiology scores (APSIII), the minimum and maximum lactate value as risk factors for early failure and age, the maximum PaCO2 and PH value, Glasgow Coma Scale (GCS), the minimum PaO2/FiO2 ratio, and PaO2 value as protective factors. Conclusion: NIV was associated with lower intubation rate and ICU 28-day and in-hospital mortality. Further survival analysis reinforced that the effect of NIV on the intubation rate might partly be attributed to the other impact factors. The ensemble AdaBoost decision tree model may assist clinicians in making clinical decisions, and early organ function support to improve patients' SOFA, APSIII, GCS, PaCO2, PaO2, PH, PaO2/FiO2 ratio, and lactate values can reduce the early failure rate and improve patient prognosis.