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Abstract 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.

Background and objective 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. Conclusion 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.

Abstract 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.

Asthma has become one of the most serious chronic respiratory diseases threatening people's lives worldwide. The pathogenesis of asthma is complex and driven by numerous cells and their interactions, which contribute to its genetic and phenotypic heterogeneity. The clinical characteristic is insufficient for the precision of patient classification and therapies; thus, a combination of the functional or pathophysiological mechanism and clinical phenotype proposes a new concept called “asthma endophenotype” representing various patient subtypes defined by distinct pathophysiological mechanisms. High-throughput omics approaches including genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiome enable us to investigate the pathogenetic heterogeneity of diverse endophenotypes and the underlying mechanisms from different angles. In this review, we provide a comprehensive overview of the roles of diverse cell types in the pathophysiology and heterogeneity of asthma and present a current perspective on their contribution into the bidirectional interaction between airway inflammation and airway remodeling. We next discussed how integrated analysis of multi-omics data via machine learning can systematically characterize the molecular and biological profiles of genetic heterogeneity of asthma phenotype. The current application of multi-omics approaches on patient stratification and therapies will be described. Integrating multi-omics and clinical data will provide more insights into the key pathogenic mechanism in asthma heterogeneity and reshape the strategies for asthma management and treatment.

ABSTRACT 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.IMPORTANCEPhage-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.

Abstract 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

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

Summary: 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.

Abstract Background Asthma is a heterogeneous disease characterized by airway inflammation and remodeling, whose pathogenetic complexity was associated with abnormal responses of various cell types in the lung. The specific interactions between immune and stromal cells, crucial for asthma pathogenesis, remain unclear. This study aims to determine the key cell types and their pathological mechanisms in asthma through single-cell RNA sequencing (scRNA-seq). Methods A 16-week mouse model of house dust mite (HDM) induced asthma (n = 3) and controls (n = 3) were profiled with scRNA-seq. The cellular composition and gene expression profiles were assessed by bioinformatic analyses, including cell enrichment analysis, trajectory analysis, and Gene Set Enrichment Analysis. Cell-cell communication analysis was employed to investigate the ligand-receptor interactions. Results The asthma model results in airway inflammation coupled with airway remodeling and hyperresponsiveness. Single-cell analysis revealed notable changes in cell compositions and heterogeneities associated with airway inflammation and remodeling. GdT17 cells were identified to be a primary cellular source of IL-17, related to inflammatory exacerbation, while a subpopulation of alveolar macrophages exhibited numerous significantly up-regulated genes involved in multiple pathways related to neutrophil activities in asthma. A distinct fibroblast subpopulation, marked by elevated expression levels of numerous contractile genes and their regulators, was observed in increased airway smooth muscle layer by immunofluorescence analysis. Asthmatic stromal-immune cell communication significantly strengthened, particularly involving GdT17 cells, and macrophages interacting with fibroblasts. CXCL12/CXCR4 signaling was remarkedly up-regulated in asthma, predominantly bridging the interaction between fibroblasts and immune cell populations. Fibroblasts and macrophages could jointly interact with various immune cell subpopulations via the CCL8/CCR2 signaling. In particular, fibroblast-macrophage cell circuits played a crucial role in the development of airway inflammation and remodeling through IL1B paracrine signaling. Conclusions Our study established a mouse model of asthma that recapitulated key pathological features of asthma. ScRNA-seq analysis revealed the cellular landscape, highlighting key pathological cell populations associated with asthma pathogenesis. Cell-cell communication analysis identified the crucial ligand-receptor interactions contributing to airway inflammation and remodeling. Our findings emphasized the significance of cell-cell communication in bridging the possible causality between airway inflammation and remodeling, providing valuable hints for therapeutic strategies for asthma.

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.

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.

BackgroundThis 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.MethodsThe 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

Abstract Background Acute exposures to high levels of air pollutants are thought to be associated with hospitalization of patients with lung infection, while relatively little is known about the association between air pollutants and HOSPITAL ADMISSIONS FOR pulmonary sepsis. Objectives To assess the correlation between low-level exposure to air pollutants and the hospitalizations for pulmonary sepsis in elderly patients. Methods A total of 249 elderly patients with pulmonary sepsis from January 2018 to December 2020 in Shenzhen people’s hospital were included. The data regarding hospitalizations for pulmonary sepsis, meteorological factors, and daily average levels of air pollutants on single-day lags (Lag0 to Lag7) in Shenzhen were collected. Low-level exposure was defined as the annual means of air pollutants below the levels of the Ambient Air Quality Standard (AAQS) in China (NO. GB3095-2012) and/or Global Air Quality Guidelines (AQG). A time-stratified case-crossover study design approach was used to evaluate the associations between exposure to air pollutants and incidence of the disease, univariate and multivariate logistic regression analysis to analyze the association between levels of air pollutants and hospitalizations for pulmonary sepsis in elderly patients. Results Exposure to PM1(P = 0.007, Lag 2 day; P = 0.038, Lag6 day), PM2.5(P = 0.046, Lag2 day), PM10(P = 0.048, Lag4 day), and O3(P = 0.044, Lag6 day) was positively correlated with elevated risk of hospitalizations for pulmonary sepsis. In addition, logistic regression analysis revealed that exposure to PM1 (OR = 1.833, 95%CI:1.032 ~ 3.256, Lag6 day) and O3 (OR = 2.091, 95%CI:1.019 ~ 4.289, Lag6 day) were the independent risk factors of pulmonary sepsis in elderly patients. Conclusion Our results demonstrate that short-term low-level exposure to PM1 and O3 could elevate the risk of hospitalizations for pulmonary sepsis in elderly patients in Shenzhen, providing evidence for developing early warning and screening systems for pulmonary sepsis.

Abstract Background The role of prophylactic antibiotics in preventing ventilator-associated pneumonia (VAP) in patients undergoing invasive mechanical ventilation (IMV) remains unclear. This network meta-analysis compared the efficacy and safety of antibiotic prophylaxis in preventing VAP in an IMV population in intensive-care units (ICUs). Methods We searched the PubMed, Web of Science, Embase, and Cochrane Library databases from inception to December 2021, to identify relevant studies assessing the impact of prophylactic antibiotics on the incidence of VAP, the mortality, and the duration of ICU stays and hospitalization to perform a meta-analysis. Results Thirteen studies (2144 patients) were included, 12 of which were selected for the primary analysis, which revealed that treatment with prophylactic antibiotics resulted in a lower VAP rate compared with control groups [risk ratio (RR) = 0.62]. Bayesian network meta-analysis indicated that aerosolized tobramycin and intravenous ampicillin–sulbactam presented the greatest likelihood being the most efficient regimen for reducing VAP. Conclusions Antibiotic prophylaxis may reduce the incidence of VAP, but not the mortality, for adult patients undergoing IMV in ICUs. Tobramycin via nebulization and ampicillin–sulbactam via intravenous administration presented the greatest likelihood of being the most efficient regimen for preventing VAP. However, well-designed randomized studies are warranted before definite recommendations can be made.

Abstract Background To help elderly patients with severe or very severe chronic obstructive pulmonary disease (COPD) with pulmonary rehabilitation, we have developed Zheng's supine rehabilitation exercise (ZSRE). Currently, none of the terminal or critically ill patients with severe exercise limitation can complete the 6‐min walking distance (6MWD) and cardiopulmonary exercise testing (CPET). Methods In this study, we discuss the definition of the standardized 3‐min simulated pedal motion (3MSPM) test and its operational specifications. Also, we evaluate the minimal clinically important difference (MCID) value of the 3MSPM. Results The results showed that the mMRC score of COPD patients with acute exacerbation of dyspnea was progressively reduced from the second day of respiratory rehabilitation, and the difference between the first and seventh days was statistically significant (p

Abstract Background Leptospirosis is a zoonosis caused by spirochete “genus” leptospira. The clinical presentations of leptospirosis range from an influenza-like presentation of fever and myalgia, to severe forms. Leptospirosis can potentially lead to a misdiagnosis or delay in diagnosis when clinical similarities exist. Case presentation A 63-year-old man presented with fever, shock and thrombocytopenia followed by diffuse pulmonary hemorrhage. Peripheral blood Metagenomic Next-generation Sequencing (mNGS) reported Leptospira interrogans. The patient was treated with piperacillin-tazobactam (TZP) plus doxycycline and improved dramatically after 7 days. Conclusion We conclude that leptospirosis can potentially lead to a misdiagnosis or delay in diagnosis. Correctly evaluation of thrombocytopenia in acute febrile illnesses facilitates the differential diagnosis of leptospirosis. mNGS can accurately detect Leptospira DNA during the early stage of the infection.

BackgroundThe 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.MethodsAdult 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.ResultsFB 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.ConclusionFB demonstrated neuroprotective and anti-inflammatory effects by inhibiting the NLRP3 pathway through Sirt1 activation in CIRI.

BackgroundIdentification of new clinical markers contributes to a better understanding of the pathogenesis of asthma. Considering the crucial role of LIGHT in asthma, it may become a potential target for asthma. The aim of current study was to determine if circulating microRNAs (miRNAs) targeting LIGHT may be used as diagnostic biomarkers to distinguish asthma.MethodsBlood serum from a cohort of 60 subjects, including 20 cases with mild asthma, 20 cases with moderate-to-severe asthma, and 20 healthy controls were included. Serum was analyzed for circulating miRNAs profiles through miRNAs microarray. Real Time PCR was conducted to verify the results of miRNA microarray. Correlations between circulating miRNAs targeting LIGHT and clinical characteristics were investigated.ResultsA total of 365 miRNAs were differentially expressed in asthma patients. Among them, miR-107 and miR-140-5p were found to target LIGHT, and varied in asthmatics. Additionally, miR-107 and miR-140-5p expressions were positively correlated with the absolute value of peripheral eosinophils. Finally, miR-140-5p and miR-107 were demonstrated to have good diagnostic efficacy for asthma (AUC= 0.8667 and 0.9400) with good sensitivity (0.8000 and 0.8667,respectively) and specificity (0.8667 and 0.867). Thus, circulating miRNAs expressed differentially between healthy control and asthma patients.ConclusionPlasma miR-140-5p and miR-107 can be used as diagnostic biomarkers to distinguish patients with asthma from healthy control, and may take part in asthma pathogenesis by negatively regulating LIGHT. Further research was needed to evaluate their roles as potential biomarkers in the diagnosis of asthma.

Abstract Rationale Chronic obstructive pulmonary disease (COPD) is a complicated chronic inflammatory disease. It is important to investigate the characteristics of acute exacerbation of COPD to develop new therapeutic strategies. Objective This study aimed to determine the relationship between the human beta-defensin-2 (hBD-2) levels and aggravation of COPD. Methods We detected the sputum hBD-2 level of 254 patients from Guangzhou, China, for 2 years. The study participants were categorized into the COPD group (n = 203, GOLD 0–4) and the control group (n = 51, 40–79 years old). At baseline, 12th month, and 24th month, we detected the sputum hBD-2 level and levels of cytokines, such as CXCL10, CXCL11, and IFN. Results At baseline, there were no significant differences in the sputum and serum hBD-2 levels between the patients and the controls. However, the sputum hBD-2 levels of patients who had at least one symptom aggravation over the next 2 years were significantly lower than those of patients without any exacerbations (1130.9 ± 858.4 pg/mL vs. 2103.7 ± 1294.2 pg/mL, respectively; p = 0.001). Nevertheless, there were no statistically significant differences in the sputum hBD-2 levels between patients (no aggravation history) and controls (2084.9 ± 1317.6 pg/mL vs. 2152.5 ± 1251.6 pg/mL, respectively; p = 0.626). We used a logistic regression model to assess the relationship between aggravation and sputum hBD-2 levels. Interestingly, we found that low hBD-2 level (

The demand for respiratory disease and dynamic breathing studies has continuously driven researchers to update the pulmonary bronchial tree’s morphology model. This study aims to construct a bronchial tree morphology model efficiently and effectively with practical algorithms. We built a performance index system using failure branch rate, volume ratio, and coefficient of variation of terminal volumes to evaluate the model performance. We optimized the parameter settings and found the best options to build the morphology model, and we constructed a 14th-generation bronchial tree model with a decent performance index. The dimensions of our model closely matched published data from anatomic in vitro measurements. The proposed model is adjustable and computable and will be used in future dynamic breathing simulations and respiratory disease studies.

Background: In lung transplant recipients (LTRs), the primary causes of mortality are rejection and infection, which often present similar symptoms, making differentiation challenging. This study aimed to explore the diagnostic efficacy of plasma donor-derived cell-free DNA (dd-cfDNA) in conjunction with metagenomic next-generation sequencing (mNGS) for pathogen detection in differentiation between lung allograft rejection and infection in LTRs experiencing new-onset pulmonary complications. Methods: We conducted a retrospective study on 188 LTRs who underwent lung or heart-lung transplantation at our institution from 2015 to 2021. The LTRs were categorized into three groups: stable, rejection, and infection. We measured plasma dd-cfDNA levels and utilized both mNGS and culture methods to identify pathogens in the bronchoalveolar lavage fluid (BALF). Results: The rejection group exhibited the highest levels of plasma dd-cfDNA (median 1.34 %, interquartile range [IQR] 1.06–2.19 %) compared to the infection group (median 0.72 %, IQR 0.62–1.07 %) and the stable group (median 0.69 %, IQR 0.58–0.78 %) (both p 0.05) or bacterial infection subgroups (p > 0.05), when compared to the stable group. Elevated dd-cfDNA levels, in combination with negative mNGS results, strongly indicated lung allograft rejection, with a positive predictive value and negative predictive value of 88.7 % and 99.2 %, respectively. Conclusions: Plasma dd-cfDNA in combination with BALF pathogen detection by mNGS shows satisfactory accuracy in differentiating lung allograft rejection from infectious complications.

Background: Recently, Professor Chunxue Bai and colleagues have proposed a definition of the Metaverse in Medicine as the medical Internet of Things (MIoT) facilitated using AR and/or VR glasses. Methods: A multi-disciplinary panel of doctors and IT experts from Asia, the United States, and Europe analyzed published articles regarding expert consensus on the Medical Internet of Things, with reference to study results in the field of metaverse technology. Findings: It is feasible to implement the three basic functions of the MIoT, namely, comprehensive perception, reliable transmission, and intelligent processing, by applying a metaverse platform, which is composed of AR and VR glasses and the MIoT system, and integrated with the technologies of holographic construction, holographic emulation, virtuality-reality integration, and virtuality-reality interconnection. In other words, through interactions between virtual and real cloud experts and terminal doctors, we will be able to carry out medical education, science popularization, consultation, graded diagnosis and treatment, clinical research, and even comprehensive healthcare in the metaverse. The interaction between virtual and real cloud experts and terminal users (including terminal doctors, patients, and even their family members) could also facilitate different medical services, such as disease prevention, healthcare, physical examination, diagnosis and treatment of diseases, rehabilitation, management of chronic diseases, in-home care, first aid, outpatient attendance, consultation, etc. In addition, it is noteworthy that security is a prerequisite for the Metaverse in Medicine, and a reliable security system is the foundation to ensure the normal operation of such a platform. Conclusion: The application of a Cloud Plus Terminal platform could enable interaction between virtual and real cloud experts and terminal doctors, in order to realize medical education, science popularization, consultation, graded diagnosis and treatment, clinical research, and even comprehensive healthcare in the metaverse.

Abstract Background Cytomegalovirus (CMV) infection is a leading cause of morbidity and mortality after transplantation. This study aimed to investigate CMV seroprevalence, infection, and disease in Chinese thoracic organ transplant recipients. Methods The clinical data of the patients who underwent lung and/or heart transplantation between January 2015 and October 2020 were retrospectively collected from four transplantation centers in China. Results A total of 308 patients were analyzed. The CMV serostatus was donor positive (D+) recipient negative (R−) in 19 (6.17%) patients, D+/R+ in 233 (75.65%), D−/R+ in 36 (11.69%), and D−/R− in 20 (6.50%). CMV DNAemia was detected in 52.3% of the patients and tissue-invasive CMV disease was diagnosed in 16.2% of the patients. Only 31.8% of the patients adhered to the postdischarge valganciclovir therapy. The D+/R− serostatus (odds ratio [OR]: 18.32; 95% confidence interval [CI]:1.80-188.68), no valganciclovir prophylaxis (OR: 2.64; 95% CI: 1.05–6.64), and higher doses of rabbit anti-human thymocyte globulin (> 2 mg/kg) (OR: 4.25; 95% CI: 1.92–9.42) were risk factors of CMV disease. Conclusion CMV seroprevalence was high in Chinese thoracic organ transplant donors and recipients. The low adherence rate to the postdischarge CMV prophylaxis therapy in Chinese patients is still an unresolved issue.

Imine reductases can catalyze reductive amination reactions to produce chiral amines, however, transformation of bulky amines has been challenging. Here, by using an increasing-molecule-volume-screening method, the authors identify a group of imine reductases that can accept bulky amines and achieve an efficient gram-scale synthesis of an API sensipar analogue.

BackgroundAmbroxol is a widely used mucoactive drug in sputum clearance of respiratory diseases taken orally and by injection. However, there is a paucity of evidence for inhaled ambroxol in sputum clearance.MethodsThis study performed a multicenter, randomized, double-blind, placebo-controlled, phase 3 trial at 19 centers in China. Hospitalized adult patients with mucopurulent sputum and expectoration difficulty were recruited. Patients were randomized by 1:1 to receive inhalation of either ambroxol hydrochloride solution 3 mL (22.5 mg) + 0.9% sodium chloride 3 mL or 0.9% sodium chloride 6 mL twice daily for 5 days, with an interval of more than 6 h. The primary efficacy endpoint was the absolute change in the sputum property score after treatment compared to the baseline in the intention-to-treat population.ResultsBetween 10 April 2018 and 23 November 2020, 316 patients were recruited and assessed for eligibility, of whom 138 who received inhaled ambroxol and 134 who received a placebo were included. Patients who received inhaled ambroxol had a significantly greater decrease in the sputum property score compared with patients who received inhalation of placebo (difference: −0.29; 95% CI: −0.53 to −0.05; p = 0.0215). Compared with the placebo, inhaled ambroxol also significantly reduced more expectoration volume in 24 h (difference: −0.18; 95% CI: −0.34 to −0.03; p = 0.0166). There was no significant difference in the proportion of adverse events between the two groups, and no deaths were reported.DiscussionIn hospitalized adult patients with mucopurulent sputum and expectoration difficulty, inhaled ambroxol was safe and effective for sputum clearance compared with a placebo.Clinical trial registration[https://www.chictr.org.cn/showproj.html?proj=184677], Chinese Clinical Trial Registry [ChiCTR2200066348].

Computed tomography (CT) has been the most effective modality for characterizing and quantifying chronic obstructive pulmonary disease (COPD). Radiomics features extracted from the region of interest in chest CT images have been widely used for lung diseases, but they have not yet been extensively investigated for COPD. Therefore, it is necessary to understand COPD from the lung radiomics features and apply them for COPD diagnostic applications, such as COPD stage classification. Lung radiomics features are used for characterizing and classifying the COPD stage in this paper. First, 19 lung radiomics features are selected from 1316 lung radiomics features per subject by using Lasso. Second, the best performance classifier (multi-layer perceptron classifier, MLP classifier) is determined. Third, two lung radiomics combination features, Radiomics-FIRST and Radiomics-ALL, are constructed based on 19 selected lung radiomics features by using the proposed lung radiomics combination strategy for characterizing the COPD stage. Lastly, the 19 selected lung radiomics features with Radiomics-FIRST/Radiomics-ALL are used to classify the COPD stage based on the best performance classifier. The results show that the classification ability of lung radiomics features based on machine learning (ML) methods is better than that of the chest high-resolution CT (HRCT) images based on classic convolutional neural networks (CNNs). In addition, the classifier performance of the 19 lung radiomics features selected by Lasso is better than that of the 1316 lung radiomics features. The accuracy, precision, recall, F1-score and AUC of the MLP classifier with the 19 selected lung radiomics features and Radiomics-ALL were 0.83, 0.83, 0.83, 0.82 and 0.95, respectively. It is concluded that, for the chest HRCT images, compared to the classic CNN, the ML methods based on lung radiomics features are more suitable and interpretable for COPD classification. In addition, the proposed lung radiomics combination strategy for characterizing the COPD stage effectively improves the classifier performance by 12% overall (accuracy: 3%, precision: 3%, recall: 3%, F1-score: 2% and AUC: 1%).

The resting HR is an upward trend with the development of chronic obstructive pulmonary disease (COPD) severity. Chest computed tomography (CT) has been regarded as the most effective modality for characterizing and quantifying COPD. Therefore, CT images should provide more information to analyze the lung and heart relationship. The relationship between HR variability and PFT or/and COPD has been fully revealed, but the relationship between resting HR variability and COPD radiomics features remains unclear. 231 sets of chest high-resolution CT (HRCT) images from "COPD patients" (at risk of COPD and stage I to IV) are segmented by the trained lung region segmentation model (ResU-Net). Based on the chest HRCT images and lung segmentation images, 231 sets of the original lung parenchyma images are obtained. 1316 COPD radiomics features of each subject are calculated by the original lung parenchyma images and its derived lung parenchyma images. The 13 selected COPD radiomics features related to the resting HR are generated from the Lasso model. A COPD radiomics features combination strategy is proposed to satisfy the significant change of the lung radiomics feature among the different COPD stages. Results show no significance between COPD stage Ⅰ and COPD stage Ⅱ of the 13 selected COPD radiomics features, and the lung radiomics feature Y1-Y4 (P > 0.05). The lung radiomics feature F2 with the dominant selected COPD radiomics features based on the proposed COPD radiomics features combination significantly increases with the development of COPD stages (P < 0.05). It is concluded that the lung radiomics feature F2 with the dominant selected COPD radiomics features not only can characterize the resting HR but also can characterize the COPD stage evolution.

Background: Accumulating evidence indicated the crucial role for interleukin 6 (IL-6) signaling in the development of allergic asthma. Yet, the role of IL-6 signaling in toluene diisocyanate (TDI)-induced mixed granulocytic airway inflammation still remains unclear. Thus, the aims of this study were to dissect the role of IL-6 signaling and to evaluate the effect of tocilizumab on TDI-induced steroid-resistant asthma. Methods: TDI-induced asthma model was prepared and asthmatic mice were respectively given IL-6 monoclonal antibody, IL-6R monoclonal antibody (tocilizumab, 5 mg/kg, i.p. after each challenge) for therapeutic purposes or isotype IgG as control. Results: TDI exposure just elevated IL-6R expression in the infiltrated inflammatory cells around the airway, but increased glycoprotein 130 expression in the whole lung, especially in bronchial epithelium. Moreover, TDI inhalation increased airway hyperresponsiveness (AHR) to methacholine, coupled with mixed granulocytic inflammation, exaggerated epithelial denudation, airway smooth muscle thickening, goblet cell metaplasia, extensive submucosal collagen deposition, dysregulated Th2/Th17 responses, as well as innate immune responses and raised serum IgE. And almost all these responses except for raised serum IgE were markedly ameliorated by the administration of IL-6 neutralizing antibody or tocilizumab, but exhibited poor response to systemic steroid treatment. Also, TDI challenge induced nucleocytoplasm translocation of HMGB1 and promoted its release in the BALF, as well as elevated lung level of STAT3 phosphorylation, which were inhibited by anti-IL-6 and anti-IL-6R treatment. Conclusions: Our data suggested that IL-6 monoclonal antibody and tocilizumab might effectively abrogate TDI-induced airway inflammation and remodeling, which could be used as a clinical potential therapy for patients with severe asthma.

Abstract. Acinetobacter baumannii is a frequent cause of nosocomial infections. Here we report an intermittent outbreak caused by the emerging carbapenem-resistant A. baumannii (CRAB) clone ST457 and assess the effectiveness of patient screening for outbreak control. CRAB isolates were collected from 74 patients admitted to the respiratory intensive care unit of a tertiary hospital between May 2018 and March 2019. Fourteen CRAB isolates were assigned to ST457, and 13 belonged to an outbreak clone, as determined by phylogenomic analysis. Strict patient screening was started at the respiratory intensive care unit on May 2019, through which a ST457-positive patient transferred from the intensive care unit was detected. No positive patients were detected within 3 months onwards. The results of this study highlight the importance of rigorous infection prevention and control measures, combined with patient screening, in controlling the CRAB outbreak.

IntroductionBecause of persistent airflow limitation in chronic obstructive pulmonary disease (COPD), patients with COPD often have complications of dyspnea. However, as a leading symptom of COPD, dyspnea in COPD deserves special consideration regarding treatment in this fragile population for pre-clinical health management in COPD. Methods: Based on the above, this paper proposes a multi-modal data combination strategy by combining the local and global features for dyspnea identification in COPD based on the multi-layer perceptron (MLP) classifier.MethodsFirst, lung region images are automatically segmented from chest HRCT images for extracting the original 1,316 lung radiomics (OLR, 1,316) and 13,824 3D CNN features (O3C, 13,824). Second, the local features, including five selected pulmonary function test (PFT) parameters (SLF, 5), 28 selected lung radiomics (SLR, 28), and 22 selected 3D CNN features (S3C, 22), are respectively selected from the original 11 PFT parameters (OLF, 11), 1,316 OLR, and 13,824 O3C by the least absolute shrinkage and selection operator (Lasso) algorithm. Meantime, the global features, including two fused PFT parameters (FLF, 2), six fused lung radiomics (FLR, 6), and 34 fused 3D CNN features (F3C, 34), are respectively fused by 11 OLF, 1,316 OLR, and 13,824 O3C using the principal component analysis (PCA) algorithm. Finally, we combine all the local and global features (SLF + FLF + SLR + FLR + S3C + F3C, 5+ 2 + 28 + 6 + 22 + 34) for dyspnea identification in COPD based on the MLP classifier.ResultsOur proposed method comprehensively improves classification performance. The MLP classifier with all the local and global features achieves the best classification performance at 87.7% of accuracy, 87.7% of precision, 87.7% of recall, 87.7% of F1-scorel, and 89.3% of AUC, respectively.DiscussionCompared with single-modal data, the proposed strategy effectively improves the classification performance for dyspnea identification in COPD, providing an objective and effective tool for COPD management.

IntroductionPositive airway pressure (PAP) therapy is currently the first-line respiratory support technique for acute respiratory failure (ARF) due to acute cardiogenic pulmonary edema (ACPE), but the accompanied adverse events and patient's intolerance with treatment in some cases limited its use in clinical practice. Some recent trials indicated that high-flow nasal cannula oxygen (HFNO) is a promising alternative to PAP therapy. In order to choose the optimum treatment for patients with ACPE, this network meta-analysis will firstly compares the efficacy of HFNO, PAP, and conventional oxygen therapy (COT).Methods and analysisThe Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols 2015 statement and its extension for network meta-analysis will be followed in the conduct of this investigation. We will examine these databases: PubMed, EMBASE, Cochrane Central Register of Controlled Trials and Web of Science. The ClinicalTrials.gov and World Health Organization International Clinical Trials Registry Platform Search Portal will be used to search ongoing trials. Only randomized controlled trials meeting the eligibility criteria will be included. Through the Cochrane Collaboration's tool, the included studies' risk of bias will be assessed. The pairwise meta-analysis will be performed with RevMan 5.4.1 software. A Bayesian network meta-analysis will use random-effects models to derive odds ratios for the treatment effects of all interventions compared to each other using R software (version 3.6.1), and the rjags and gemtc packages. The Q statistic and I2 index will be used for investigating the heterogeneity, and subgroup analysis or sensitivity analysis will be used to explore the source of heterogeneity. In addition, the Grading of Recommendations Assessment, Development and Evaluation system will be used to inspect the quality of evidence.

Background: Effective strategies are dramatically needed to prevent and improve the recovery from myocardial ischemia and reperfusion (I/R) injury. Direct interactions between the mitochondria and endoplasmic reticulum (ER) during heart diseases have been recently investigated. This study was designed to explore the cardioprotective effects of gypenoside XVII (GP-17) against I/R injury. The roles of ER stress, mitochondrial injury, and their crosstalk within I/R injury and in GP-17–induced cardioprotection are also explored. Methods: Cardiac contractility function was recorded in Langendorff-perfused rat hearts. The effects of GP-17 on mitochondrial function including mitochondrial permeability transition pore opening, reactive oxygen species production, and respiratory function were determined using fluorescence detection kits on mitochondria isolated from the rat hearts. H9c2 cardiomyocytes were used to explore the effects of GP-17 on hypoxia/reoxygenation. Results: We found that GP-17 inhibits myocardial apoptosis, reduces cardiac dysfunction, and improves contractile recovery in rat hearts. Our results also demonstrate that apoptosis induced by I/R is predominantly mediated by ER stress and associated with mitochondrial injury. Moreover, the cardioprotective effects of GP-17 are controlled by the PI3K/AKT and P38 signaling pathways. Conclusion: GP-17 inhibits I/R-induced mitochondrial injury by delaying the onset of ER stress through the PI3K/AKT and P38 signaling pathways.

BackgroundJAK (Janus kinases) inhibitors have been proposed as a promising treatment option for the coronavirus disease-2019 (COVID-19). However, the benefits of JAK inhibitors and the optimum thereof for COVID-19 have not been adequately defined.MethodsDatabases were searched from their inception dates to 17 June 2022. Eligible studies included randomized controlled trials and observational studies. Extracted data were analyzed by pairwise and network meta-analysis. The primary outcome was the coefficient of mortality.ResultsTwenty-eight studies of 8,206 patients were included and assessed qualitatively (modified Jadad and Newcastle–Ottawa Scale scores). A pairwise meta-analysis revealed that JAK inhibitors effectively reduced the mortality (OR = 0.54; 95% CI: 0.46–0.63; P < 0.00001; I2 = 32%) without increasing the risk of adverse events (OR = 1.02; 95% CI: 0.88–1.18; P = 0.79; I2 = 12%). In a network meta-analysis, clinical efficacy benefits were seen among different types of JAK inhibitors (baricitinib, ruxolitinib, and tofacitinib) without the observation of a declined incidence of adverse events. The assessment of rank probabilities indicated that ruxolitinib presented the greatest likelihood of benefits regarding mortality and adverse events.ConclusionJAK inhibitors appear to be a promising treatment for COVID-19 concerning reducing mortality, and they do not increase the risk of adverse events vs. standard of care. A network meta-analysis suggests that mortality benefits are associated with specific JAK inhibitors, and among these, ruxolitinib presents the greatest likelihood of having benefits for mortality and adverse events.Systematic review registration[www.crd.york.ac.uk/prospero], identifier [CRD42022343338].

Atherosclerosis is the pathological basis of various vascular diseases, including those with high mortality, such as myocardial infarction and stroke. However, its pathogenesis is complex and has not been fully elucidated yet. Over the past few years, single-cell RNA sequencing (scRNA-seq) has been developed and widely used in many biological fields to reveal biological mechanisms at the cellular level and solve the problems of cellular heterogeneity that cannot be solved using bulk RNA sequencing. In this review, we briefly summarize the existing scRNA-seq technologies and focus on their application in atherosclerosis research to provide insights into the occurrence, development and treatment of atherosclerosis.

Cellular energy metabolism plays a crucial role in the regulation of macrophage polarization and in the execution of immune functions. A recent study showed that Slc6a8-mediated creatine uptake from exogenous supplementation modulates macrophage polarization, yet little is known about the role of the de novo creatine de novobiosynthesis pathway in macrophage polarization. Here, we observed that glycine amidinotransferase (GATM), the rate-limiting enzyme for creatine synthesis, was upregulated in alternative (M2) polarized macrophages, and was dependent on the transcriptional factor STAT6, whereas GATM expression was suppressed in the classical polarized (M1) macrophage. Next, we revealed that exogenous creatine supplementation enhanced IL-4-induced M2 polarization, confirming recent work. Furthermore, we revealed that genetic ablation of GATM did not affect expression of M1 marker genes (Nos2, IL1b, IL12b) or the production of nitric oxide in both peritoneal macrophages (PMs) and bone marrow-derived macrophages (BMDMs). By contrast, expression levels of M2 markers (Arg1, Mrc1, Ccl17 and Retnla) were lower following GATM deletion. Moreover, we found that deletion of GATM in resident alveolar macrophages (AMs) significantly blocked M2 polarization but with no obvious effect on the number of cells in knockout mice. Lastly, an upregulation of GATM was found in lung tissue and bronchoalveolar lavage fluid macrophages from HDM-induced asthmatic mice. Our study uncovers a previously uncharacterized role for the de novo creatine biosynthesis enzyme GATM in M2 macrophage polarization, which may be involved in the pathogenesis of related inflammatory diseases such as an T helper 2 (Th2)-associated allergic asthma.

Cerebrovascular and airway structures are tubular structures used for transporting blood and gases, respectively, providing essential support for the normal activities of the human body. Accurately segmenting these tubular structures is the basis of morphology research and pathological detection. Nevertheless, accurately segmenting these structures from images presents great challenges due to their complex morphological and topological characteristics. To address this challenge, this paper proposes a framework UARAI based on the U-Net multi-scale reverse attention network and sparse convolution network. The framework utilizes a multi-scale structure to effectively extract the global and deep detail features of vessels and airways. Further, it enhances the extraction ability of fine-edged features by a joint reverse attention module. In addition, the sparse convolution structure is introduced to improve the features’ expression ability without increasing the model’s complexity. Finally, the proposed training sample cropping strategy reduces the influence of block boundaries on the accuracy of tubular structure segmentation. The experimental findings demonstrate that the UARAI-based metrics, namely Dice and IoU, achieve impressive scores of 90.31% and 82.33% for cerebrovascular segmentation and 93.34% and 87.51% for airway segmentation, respectively. Compared to commonly employed segmentation techniques, the proposed method exhibits remarkable accuracy and robustness in delineating tubular structures such as cerebrovascular and airway structures. These results hold significant promise in facilitating medical image analysis and clinical diagnosis, offering invaluable support to healthcare professionals.

Abstract Hypoxia promotes inflammation in the tumor microenvironment. Although hypoxia-inducible factor 1α (HIF1α) is a master modulator of the response to hypoxia, the exact mechanisms through which HIF1α regulates the induction of inflammation remain largely unclear. Using The Cancer Genome Atlas Lung Squamous Cell Carcinoma (TCGA-LUSC) database, we divided patients with LUSC into two groups based on low or high HIF1α expression. After analyzing the differentially expressed genes in these two groups, we found that HIF1α was positively correlated with interleukin 1A (IL1A) and IL6 expression. Our in vitro study showed that hypoxic stress did not induce IL1A or IL6 expression in tumor cells or macrophages but dramatically enhanced their expression when co-cultured with tumor cells. We then investigated the effect of tumor-derived exosomes on macrophages. Our data suggested that the changes in miR101 in the tumor-derived exosomes played an important role in IL1A and IL6 expression in macrophages, although the hypoxic stress did not change the total amount of exosome secretion. The expression of miR101 in exosomes was suppressed by hypoxic stress, since depletion of HIF1α in tumor cells recovered the miR101 expression in both tumor cells and exosomes. In vitro, miRNA101 overexpression or uptake enriched exosomes by macrophages suppressed their reprogramming into a pro-inflammatory state by targeting CDK8. Injection of miR101 into xenografted tumors resulted in the suppression of tumor growth and macrophage tumor infiltration in vivo. Collectively, this study suggests that the HIF1α-dependent suppression of exosome miR101 from hypoxic tumor cells activates macrophages to induce inflammation in the tumor microenvironment.

Abstract Background Differences between adult patients with severe early-onset and late-onset asthma have not been well studied. Objectives To determine the phenotypic distinction regarding age at onset in patients with severe asthma. Methods The present study enrolled thirty-two patients with severe early-onset (onset age 12 years) asthma. Severe asthma was defined according to Global Initiative for Asthma criteria. The clinical, spirometric, and laboratory parameters were collected for group comparisons. Results Among the 64 patients included (mean age, 46.22 ± 13.90 years; 53.1% male), the mean percent of predicted forced expiratory volume in 1 s (FEV1) was 68.43 ± 20.55%. Patients with severe early-onset asthma had a younger age, longer duration of asthma, higher rate of family history, and better small-airway function (MEF25% and MMEF75/25%) compared with severe late-onset asthma. Furthermore, levels of serum IL-17 and sputum neutrophil percentage were significantly higher for patients with severe early-onset asthma (P = 0.016, 0.033, respectively). Multiple logistic regression analysis revealed that increased serum IL-17 (odds ratio = 1.065, P = 0.016) was independently associated with severe early-onset asthma. The combination of serum IL-17 and sputum neutrophil percentage yielded a sensitivity of 80.0% and a specificity of 86.7% for identifying patients with severe early-onset asthma. Conclusions Patients with severe early-onset asthma exhibit elevated levels of serum IL-17 and sputum neutrophil percentage, suggesting a potential role in the pathogenesis of severe early-onset phenotype.

Background: The coronavirus disease of 2019 (COVID-19) is a severe public health issue that has infected millions of people. The effective prevention and control of COVID-19 has resulted in a considerable increase in the number of cured cases. However, little research has been done on a complete metabonomic examination of metabolic alterations in COVID-19 patients following treatment. The current project pursues rigorously to characterize the variation of serum metabolites between healthy controls and COVID-19 patients with nucleic acid turning negative via untargeted metabolomics.Methods: The metabolic difference between 20 COVID-19 patients (CT ≥ 35) and 20 healthy controls were investigated utilizing untargeted metabolomics analysis employing High-resolution UHPLC-MS/MS. COVID-19 patients’ fundamental clinical indicators, as well as health controls, were also collected.Results: Out of the 714 metabolites identified, 203 still significantly differed between COVID-19 patients and healthy controls, including multiple amino acids, fatty acids, and glycerophospholipids. The clinical indexes including monocytes, lymphocytes, albumin concentration, total bilirubin and direct bilirubin have also differed between our two groups of participators.Conclusion: Our results clearly showed that in COVID-19 patients with nucleic acid turning negative, their metabolism was still dysregulated in amino acid metabolism and lipid metabolism, which could be the mechanism of long-COVID and calls for specific post-treatment care to help COVID-19 patients recover.

BackgroundCheckpoint inhibitor–related pneumonitis (CIP) is a lethal immune-related adverse event. However, the development process of CIP, which may provide insight into more effective management, has not been extensively examined.MethodsWe conducted a multicenter retrospective analysis of 56 patients who developed CIP. Clinical characteristics, radiological features, histologic features, and laboratory tests were analyzed. After a comprehensive analysis, we proposed acute, subacute, and chronic phases of CIP and summarized each phase’s characteristics.ResultsThere were 51 patients in the acute phase, 22 in the subacute phase, and 11 in the chronic phase. The median interval time from the beginning of CIP to the different phases was calculated (acute phase: ≤4.9 weeks; subacute phase: 4.9~13.1 weeks; and chronic phase: ≥13.1 weeks). The symptoms relieved from the acute phase to the chronic phase, and the CIP grade and Performance Status score decreased (P

Abstract Noninvasive ventilation (NIV) is beneficial in acute respiratory failure (ARF) caused by chest trauma; however, NIV-related complications affect the efficacy. We evaluated whether NIV with helmet decreases the incidence of complications and improves its effects in a single center. Patients with ARF after chest trauma were randomized to receive NIV with helmet or face mask. The primary outcome was the rate of NIV-related complications. Secondary outcomes were PaO2/FiO2, patient’s tolerance, intubation rate, length of intensive care unit (ICU) stay, and ICU mortality. The trial was terminated early after an interim analysis with 59 patients. The incidence of complications was lower in the helmet group [10% (3/29) vs 43% (13/30), P = 0.004], and PaO2/FiO2s were higher at 1 h and at the end of NIV (253.14 ± 64.74 mmHg vs 216.06 ± 43.86 mmHg, 277.07 ± 84.89 mmHg vs 225.81 ± 63.64 mmHg, P = 0.013 and 0.012) compared with them in face mask group. More patients reported excellent tolerance of the helmet vs face mask after 4 h of NIV [83% (24/29) vs 47% (14/30), P = 0.004] and at the end of NIV [69% (20/29) vs 30% (9/30), P = 0.03]. Differences in intubation rate, ICU stay, and mortality were non-significant (P = 0.612, 0.100, 1.000, respectively). NIV with helmet decreased NIV-related complications, increased PaO2/FiO2, and improved tolerance compared with NIV with face mask in patients with chest trauma. Trial registration: Registered in the Chinese Clinical Trial Registry (ChiCTR1900025915), a WHO International Clinical Trials Registry Platform ( http://www.chictr.org.cn/searchprojen.aspx ).

BackgroundChronic obstructive pulmonary disease (COPD), a preventable lung disease, has the highest prevalence in the elderly and deserves special consideration regarding earlier warnings in this fragile population. The impact of age on COPD is well known, but the COPD risk of the aging process in the lungs remains unclear. Therefore, it is necessary to understand the COPD risk of the aging process in the lungs, providing an early COPD risk decision for adults.MethodsCOPD risk is evaluated for adults to make an early COPD risk decision from the perspective of lung radiomics features. First, the subjects are divided into four groups according to the COPD stages. Their ages are divided into eight equal age intervals in each group. Second, four survival Cox models are established based on the lung radiomics features to evaluate the risk probability from COPD stage 0 to suffering COPD and COPD stages. Finally, four risk ranks are defined by equally dividing the COPD risk probability from 0 to 1. Subsequently, the COPD risk at different stages is evaluated with varying age intervals to provide an early COPD risk decision.ResultsThe evaluation metrics area under the curve (AUC)/C index of four survival Cox models are 0.87/0.94, 0.84/0.83, 0.94/0.89, and 0.97/0.86, respectively, showing the effectiveness of the models. The risk rank levels up every 5 years for the subjects who had suffered COPD after 60. For the subjects with COPD stage 0, the risk rank of suffering COPD stage I levels up every 5 years after the age of 65 years, and the risk rank of suffering COPD stages II and III & IV levels up every 5 years after the age of 70 years.ConclusionOnce the age is above 60 years, the patients with COPD need to take action to prevent the progress and deterioration of COPD. Once the age is above 65 years, the patients with COPD stage 0 need to take precautions against COPD.

ABSTRACT Antimicrobial resistance is a global concern in chronic respiratory diseases, including chronic obstructive pulmonary disease (COPD). The collection of antibiotic resistance genes or resistome in human airways may underlie the resistance. COPD is heterogeneous, and understanding the airway resistome in relation to patient phenotype and endotype may inform precision antibiotic therapy. Here, we characterized the airway resistome for 94 COPD participants at stable disease. Among all demographic and clinical factors, patient inflammatory endotype was associated with the airway resistome. There were distinct resistome profiles between patients with neutrophilic or eosinophilic inflammation, two primary inflammatory endotypes in COPD. For neutrophil-predominant COPD, the resistome was dominated by multidrug resistance genes. For eosinophil-predominant COPD, the resistome was diverse, with an increased portion of patients showing a macrolide-high resistome. The differential antimicrobial resistance pattern was validated by sputum culture and in vitro antimicrobial susceptibility testing. Ralstonia and Pseudomonas were the top contributors to the neutrophil-associated resistome, whereas Campylobacter and Aggregatibacter contributed most to the eosinophil-associated resistome. Multiomic analyses revealed specific host pathways and inflammatory mediators associated with the resistome. The arachidonic acid metabolic pathway and matrix metallopeptidase 8 (MMP-8) exhibited the strongest associations with the neutrophil-associated resistome, whereas the eosinophil chemotaxis pathway and interleukin-13 (IL-13) showed the greatest associations with the eosinophil-associated resistome. These results highlight a previously unrecognized link between inflammation and the airway resistome and suggest the need for considering patient inflammatory subtype in decision-making about antibiotic use in COPD and broader chronic respiratory diseases. IMPORTANCE Antibiotics are commonly prescribed for both acute and long-term prophylactic treatment in chronic airway disorders, such as chronic obstructive pulmonary disease (COPD), and the rapid growth of antibiotic resistance is alarming globally. The airway harbors a diverse collection of microorganisms known as microbiota, which serve as a reservoir for antibiotic resistance genes or the resistome. A comprehensive understanding of the airway resistome in relation to patient clinical and biological factors may help inform decisions to select appropriate antibiotics for clinical therapies. By deep multiomic profiling and in vitro phenotypic testing, we showed that inflammatory endotype, the underlying pattern of airway inflammation, was most strongly associated with the airway resistome in COPD patients. There were distinct resistome profiles between neutrophil-predominant and eosinophil-predominant COPD that were associated with different bacterial species, host pathways, and inflammatory markers, highlighting the need of considering patient inflammatory status in COPD antibiotic management.

As a vital pivot for the human circulatory system, the brain-gut axis is now being considered as an important channel for many of the small immune molecules’ transductions, including interleukins, interferons, neurotransmitters, peptides, and the chemokines penetrating the mesentery and blood brain barrier (BBB) during the development of an ischemic stroke (IS). Hypoxia-ischemia contributes to pituitary and neurofunctional disorders by interfering with the molecular signal release and communication then providing feedback to the gut. Suffering from such a disease on a long-term basis may cause the peripheral system’s homeostasis to become imbalanced, and it can also lead to multiple intestinal complications such as gut microbiota dysbiosis (GMD), inflammatory bowel disease (IBD), necrotizing enterocolitis (NEC), and even the tumorigenesis of colorectal carcinoma (CRC). Correspondingly, these complications will deteriorate the cerebral infarctions and, in patients suffering with IS, it can even ruin the brain’s immune system. This review summarized recent studies on abnormal immunological signal exchange mediated polarization subtype changes, in both macrophages and microglial cells as well as T-lymphocytes. How gut complications modulate the immune signal transduction from the brain are also elucidated and analyzed. The conclusions drawn in this review could provide guidance and novel strategies to benefit remedies for both IS and relative gut lesions from immune-prophylaxis and immunotherapy aspects.

Background: For anaphylaxis, a life-threatening allergic reaction, the incidence rate was presented to have increased from the beginning of the 21st century. Underdiagnosis and undertreatment of anaphylaxis are public health concerns.Objective: This guideline aimed to provide high-quality and evidence-based recommendations for the emergency management of anaphylaxis.Method: The panel of health professionals from fifteen medical areas selected twenty-five clinical questions and formulated the recommendations with the supervision of four methodologists. We collected evidence by conducting systematic literature retrieval and using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach.Results: This guideline made twenty-five recommendations that covered the diagnosis, preparation, emergency treatment, and post-emergency management of anaphylaxis. We recommended the use of a set of adapted diagnostic criteria from the American National Institute of Allergy and Infectious Diseases and the Food Allergy and Anaphylaxis Network (NIAID/FAAN), and developed a severity grading system that classified anaphylaxis into four grades. We recommended epinephrine as the first-line treatment, with specific doses and routes of administration for different severity of anaphylaxis or different conditions. Proper dosage is critical in the administration of epinephrine, and the monitor is important in the IV administration. Though there was only very low or low-quality evidence supported the use of glucocorticoids and H1 antagonists, we still weakly recommended them as second-line medications. We could not make a well-directed recommendation regarding premedication for preventing anaphylaxis since it is difficult to weigh the concerns and potential effects.Conclusion: For the emergency management of anaphylaxis we conclude that:• NIAID/FAAN diagnostic criteria and the four-tier grading system should be used for the diagnosis• Prompt and proper administration of epinephrine is critical.

Abstract Coronavirus disease (COVID-19) is an emerging viral infection that is rapidly spreading across the globe. SARS-CoV-2 belongs to the same coronavirus class that caused respiratory illnesses such as severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). During the SARS and MERS outbreaks, many frontline healthcare workers were infected when performing high-risk aerosol-generating medical procedures as well as when providing basic patient care. Similarly, COVID-19 disease has been reported to infect healthcare workers at a rate of ~ 3% of cases treated in the USA. In this review, we conducted an extensive literature search to develop practical strategies that can be implemented when providing respiratory treatments to COVID-19 patients, with the aim to help prevent nosocomial transmission to the frontline workers.

Background: Diabetic cardiomyopathy (DCM) is a serious complication of diabetes that can lead to significant mortality. Cyclocarya paliurus is a tree, the leaves of which are often utilized to prevent and treat diabetes mellitus. Whether C. paliurus leaves can prevent or treat DCM, however, it remains to be formally assessed. The present study was therefore designed to assess the ability of C. paliurus to protect against DCM in db/db mice. Methods: Male wild-type (WT) and db/db mice were administered C. paliurus ethanol leaf extracts (ECL) or appropriate vehicle controls daily via gavage, and levels of blood glucose in treated animals were assessed on a weekly basis. After a 10-week treatment, the levels of cardiac troponin I (cTn-I), lactate dehydrogenase (LDH), creatine kinase MB (CK-MB), aspartate transaminase (AST), total triglycerides (TG), and total cholesterol (TC) in serum were measured. Activities of malondialdehyde (MDA), superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT) and the levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and IL-6 in heart tissues were detected. Hematoxylin-eosin (HE) and Masson staining were conducted. The protein expression that related with oxidative stress and inflammatory reaction was evaluated by Western blotting. Results: Compared with WT mice, the TG, TC, and blood glucose levels in db/db mice increased significantly, which were reduced by ECL treatment. Compared with WT mice, the levels of LDH, CK-MB, AST, and cTn-I in serum and MDA in heart tissues of db/db mice increased significantly. Activities of SOD, GSH-Px, and CAT in heart tissues of db/db mice decreased significantly. The levels of inflammatory cytokines (TNF-α, IL-1β, and IL-6) in heart tissues of db/db mice increased remarkably. However, ECL treatment improved the above pathological changes significantly. ECL alleviated pathological injury and fibrosis in heart tissues of mice. Western blotting showed that ECL increased Bcl-2 level and decreased Bax, cle-caspase-3, and cle-caspase-9 expression. Furthermore, ECL inhibited NF-κB nuclear translocation and increased PI3K and p-Akt expressions. Conclusion: Our results indicate that ECL treatment can markedly reduce pathological cardiac damage in db/db mice through antiapoptotic, antifibrotic, and anti-inflammatory mechanisms. Specifically, this extract was able to suppress NF-κB activation via the PI3K/Akt signaling pathway. Given its diverse activities and lack of significant side effects, ECL may thus have therapeutic value for the treatment of DCM.

The aim is to diagnose COVID-19 earlier and to improve its treatment by applying medical technology, the “COVID-19 Intelligent Diagnosis and Treatment Assistant Program (nCapp)” based on the Internet of Things. Terminal eight functions can be implemented in real-time online communication with the “cloud” through the page selection key. According to existing data, questionnaires, and check results, the diagnosis is automatically generated as confirmed, suspected, or suspicious of 2019 novel coronavirus (2019-nCoV) infection. It classifies patients into mild, moderate, severe or critical pneumonia. nCapp can also establish an online COVID-19 real-time update database, and it updates the model of diagnosis in real time based on the latest real-world case data to improve diagnostic accuracy. Additionally, nCapp can guide treatment. Front-line physicians, experts, and managers are linked to perform consultation and prevention. nCapp also contributes to the long-term follow-up of patients with COVID-19. The ultimate goal is to enable different levels of COVID-19 diagnosis and treatment among different doctors from different hospitals to upgrade to the national and international through the intelligent assistance of the nCapp system. In this way, we can block disease transmission, avoid physician infection, and epidemic prevention and control as soon as possible.