Outcome prediction in pneumonia induced ALI/ARDS by clinical features and peptide patterns of BALF determined by mass spectrometry

The aging lung: microenvironment, mechanisms, and diseases

With the development of global social economy and the deepening of the aging population, diseases related to aging have received increasing attention. The pathogenesis of many respiratory diseases remains unclear, and lung aging is an independent risk factor for respiratory diseases. The aging mechanism of the lung may be involved in the occurrence and development of respiratory diseases. Aging-induced immune, oxidative stress, inflammation, and telomere changes can directly induce and promote the occurrence and development of lung aging. Meanwhile, the occurrence of lung aging also further aggravates the immune stress and inflammatory response of respiratory diseases; the two mutually affect each other and promote the development of respiratory diseases. Explaining the mechanism and treatment direction of these respiratory diseases from the perspective of lung aging will be a new idea and research field. This review summarizes the changes in pulmonary microenvironment, metabolic mechanisms, and the progression of respiratory diseases associated with aging.

Alveolar epithelial cells of lung fibrosis patients are susceptible to severe virus-induced injury

Patients with pulmonary fibrosis (PF) often experience exacerbations of their disease, characterised by a rapid, severe deterioration in lung function that is associated with high mortality. Whilst the pathobiology of such exacerbations is poorly understood, virus infection is a trigger. The present study investigated virus-induced injury responses of alveolar and bronchial epithelial cells (AECs and BECs, respectively) from patients with PF and age-matched controls (Ctrls). Air-liquid interface (ALI) cultures of AECs, comprising type I and II pneumocytes or BECs were inoculated with influenza A virus (H1N1) at 0.1 multiplicity of infection (MOI). Levels of interleukin-6 (IL-6), IL-36γ and IL-1β were elevated in cultures of AECs from PF patients (PF-AECs, n = 8-11), being markedly higher than Ctrl-AECs (n = 5-6), 48 h post inoculation (pi) (P<0.05); despite no difference in H1N1 RNA copy numbers 24 h pi. Furthermore, the virus-induced inflammatory responses of PF-AECs were greater than BECs (from either PF patients or controls), even though viral loads in the BECs were overall 2- to 3-fold higher than AECs. Baseline levels of the senescence and DNA damage markers, nuclear p21, p16 and H2AXγ were also significantly higher in PF-AECs than Ctrl-AECs and further elevated post-infection. Senescence induction using etoposide augmented virus-induced injuries in AECs (but not viral load), whereas selected senotherapeutics (rapamycin and mitoTEMPO) were protective. The present study provides evidence that senescence increases the susceptibility of AECs from PF patients to severe virus-induced injury and suggests targeting senescence may provide an alternative option to prevent or treat the exacerbations that worsen the underlying disease.

Role of autophagy in lung diseases and ageing

The lungs face ongoing chemical, mechanical, biological, immunological and xenobiotic stresses over a lifetime. Advancing age progressively impairs lung function. Autophagy is a "housekeeping" survival strategy involved in numerous physiological and pathological processes in all eukaryotic cells. Autophagic activity decreases with age in several species, whereas its basic activity extends throughout the lifespan of most animals. Dysregulation of autophagy has been proven to be closely related to the pathogenesis of several ageing-related pulmonary diseases. This review summarises the role of autophagy in the pathogenesis of pulmonary diseases associated with or occurring in the context of ageing, including acute lung injury, chronic obstructive pulmonary disease, asthma and pulmonary fibrosis, and describes its potential as a therapeutic target.

Pulmonary Fibrosis as a Result of Acute Lung Inflammation: Molecular Mechanisms, Relevant In Vivo Models, Prognostic and Therapeutic Approaches

Pulmonary fibrosis is a chronic progressive lung disease that steadily leads to lung architecture disruption and respiratory failure. The development of pulmonary fibrosis is mostly the result of previous acute lung inflammation, caused by a wide variety of etiological factors, not resolved over time and causing the deposition of fibrotic tissue in the lungs. Despite a long history of study and good coverage of the problem in the scientific literature, the effective therapeutic approaches for pulmonary fibrosis treatment are currently lacking. Thus, the study of the molecular mechanisms underlying the transition from acute lung inflammation to pulmonary fibrosis, and the search for new molecular markers and promising therapeutic targets to prevent pulmonary fibrosis development, remain highly relevant tasks. This review focuses on the etiology, pathogenesis, morphological characteristics and outcomes of acute lung inflammation as a precursor of pulmonary fibrosis; the pathomorphological changes in the lungs during fibrosis development; the known molecular mechanisms and key players of the signaling pathways mediating acute lung inflammation and pulmonary fibrosis, as well as the characteristics of the most common in vivo models of these processes. Moreover, the prognostic markers of acute lung injury severity and pulmonary fibrosis development as well as approved and potential therapeutic approaches suppressing the transition from acute lung inflammation to fibrosis are discussed.

Astaxanthin ameliorates lipopolysaccharide-induced acute lung injury via inhibition of inflammatory reactions and modulation of the SOCS3/JAK2/STAT3 signaling pathways in mice

The results showed that astaxanthin had a protective effect on LPS-induced acute lung injury in mice, and its protective mechanism was through activating the SOCS3/JAK2/STAT3 signaling pathway.

Ageing mechanisms that contribute to tissue remodeling in lung disease

Age is a major risk factor for chronic respiratory diseases such as idiopathic pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD) and certain phenotypes of asthma. The recent COVID-19 pandemic also highlights the increased susceptibility of the elderly to acute respiratory distress syndrome (ARDS), a diffuse inflammatory lung injury with often long-term effects (ie parenchymal fibrosis). Collectively, these lung conditions are characterized by a pathogenic reparative process that, rather than restoring organ function, contributes to structural and functional tissue decline. In the ageing lung, the homeostatic control of wound healing following challenge or injury has an increased likelihood of being perturbed, increasing susceptibility to disease. This loss of fidelity is a consequence of a diverse range of underlying ageing mechanisms including senescence, mitochondrial dysfunction, proteostatic stress and diminished autophagy that occur within the lung, as well as in other tissues, organs and systems of the body. These ageing pathways are highly interconnected, involving localized and systemic increases in inflammatory mediators and damage associated molecular patterns (DAMPs); along with corresponding changes in immune cell function, metabolism and composition of the pulmonary and gut microbiomes. Here we comprehensively review the roles of ageing mechanisms in the tissue remodeling of lung disease.

Dexmedetomidine For The Treatment Of Acute Lung Injury: A Fact Or Fiction?

Dexmedetomidine has been widely used in the intensive care unit (ICU), with the primary aim to keep patients on an appropriate level of sedation. Both observational and randomized controlled trials have observed that the use of dexmedetomidine is associated with improved outcomes for mechanically ventilated patients [1]. In ICU patients receiving prolonged mechanical ventilation, dexmedetomidine was not inferior to other sedatives in maintaining sedation level, but was associated with shortened MV duration and improved ability to communicate pain [2]. MV is an important factor for delirium and dexmedetomidine was found to be associated with lower risk of delirium [3, 4]. Prophylactic low-dose dexmedetomidine is able to reduce the occurrence of delirium during the first 7 days after surgery for patients aged over 65 years who are admitted to the ICU after surgery [4]. Thus, the beneficial effect of might be explained by the reduction of delirium in the treated group. In fact, delirium can be considered as a type of acute organ dysfunction mediated via inflammatory response. There has been evidence that inflammatory biomarkers such as C-reactive protein was positively correlated with the occurrence of delirium [5].

Galloyl-Hexahydroxydiphenoyl (HHDP)-Glucose Isolated From Punica granatum L. Leaves Protects Against Lipopolysaccharide (LPS)-Induced Acute Lung Injury in BALB/c Mice

The hydroalcoholic extract and ethyl acetate fraction of Punica granatum leaves have been known to exhibit anti-inflammatory activities. In this study, we investigated the therapeutic effects of galloyl-hexahydroxydiphenoyl (HHDP)-glucose isolated from pomegranate leaves on lipopolysaccharide (LPS)-induced acute lung injury (ALI) in mice. Male BALB/c mice were treated with different doses of galloyl-HHDP-glucose (5, 50, and 100 mg/Kg) or dexamethasone at 5 mg/Kg (per os) 6 h after intra-tracheal instillation of LPS. Vehicle-treated mice were used as controls. Twenty-four hours after LPS challenge, bronchoalveolar lavage fluid (BALF), and lung samples were collected for analyses. They were evaluated by monitoring the expression of NF-κB, JNK, and cytokine genes and proteins, as well as cell migration and lung function. All doses of galloyl-HHDP-glucose inhibited LPS-induced JNK and NF-κB activation. Likewise, the galloyl-HHDP-glucose-treated animals presented reduced expression of the TNF-α, IL-6, and IL-1β genes in the lungs and reduced TNF-α, IL-6, IL-1β, and IL-8 protein levels when compared with the vehicle-treated LPS-challenged mice. In addition, the ALI mice treated with galloyl-HHDP-glucose also presented reduced lung inflammatory cell accumulation, especially that of neutrophils, in their BALF and lungs. In addition, galloyl-HHDP-glucose treatment markedly ameliorated the LPS-induced pulmonary mechanism complications and attenuated weight loss. Overall, we showed for the first time that galloyl-HHDP-glucose protects against ALI, and may be useful for treating ALI and other inflammatory disorders.

Lung fluid biomarkers for acute respiratory distress syndrome: a systematic review and meta-analysis

Background

With the development of new techniques to easily obtain lower respiratory tract specimens, bronchoalveolar lavage fluid and other lung fluids are gaining importance in pulmonary disease diagnosis. We aimed to review and summarize lung fluid biomarkers associated with acute respiratory distress syndrome diagnosis and mortality.

Methods

After searching PubMed, Embase, Web of Science, and the Cochrane Library for articles published prior to January 11, 2018, we performed a meta-analysis on biomarkers for acute respiratory distress syndrome diagnosis in at-risk patients and those related to disease mortality. From the included studies, we then extracted the mean and standard deviation of the biomarker concentrations measured in the lung fluid, acute respiratory distress syndrome etiologies, sample size, demographic variables, diagnostic criteria, mortality, and protocol for obtaining the lung fluid. The effect size was measured by the ratio of means, which was then synthesized by the inverse-variance method using its natural logarithm form and transformed to obtain a pooled ratio and 95% confidence interval.

Results

In total, 1156 articles were identified, and 49 studies were included. Increases in total phospholipases A2 activity, total protein, albumin, plasminogen activator inhibitor-1, soluble receptor for advanced glycation end products, and platelet activating factor-acetyl choline were most strongly associated with acute respiratory distress syndrome diagnosis. As for biomarkers associated with acute respiratory distress syndrome mortality, interleukin-1β, interleukin-6, interleukin-8, Kerbs von Lungren-6, and plasminogen activator inhibitor-1 were significantly increased in the lung fluid of patients who died. Decreased levels of Club cell protein and matrix metalloproteinases-9 were associated with increased odds for acute respiratory distress syndrome diagnosis, whereas decreased levels of Club cell protein and interleukin-2 were associated with increased odds for acute respiratory distress syndrome mortality.

Conclusions

This meta-analysis provides a ranking system for lung fluid biomarkers, according to their association with diagnosis or mortality of acute respiratory distress syndrome. The performance of biomarkers among studies shown in this article may help to improve acute respiratory distress syndrome diagnosis and outcome prediction.

Electronic supplementary material

The online version of this article (10.1186/s13054-019-2336-6) contains supplementary material, which is available to authorized users.

Prediction model for patients with acute respiratory distress syndrome: use of a genetic algorithm to develop a neural network model

BACKGROUND

Acute respiratory distress syndrome (ARDS) is associated with significantly increased risk of death, and early risk stratification may help to choose the appropriate treatment. The study aimed to develop a neural network model by using a genetic algorithm (GA) for the prediction of mortality in patients with ARDS.

METHODS

This was a secondary analysis of two multicenter randomized controlled trials conducted in forty-four hospitals that are members of the National Heart, Lung, and Blood Institute, founded to create an acute respiratory distress syndrome Clinical Trials Network. Model training and validation were performed using the SAILS and OMEGA studies, respectively. A GA was employed to screen variables in order to predict 90-day mortality, and a neural network model was trained for the prediction. This machine learning model was compared to the logistic regression model and APACHE III score in the validation cohort.

RESULTS

A total number of 1,071 ARDS patients were included for analysis. The GA search identified seven important variables, which were age, AIDS, leukemia, metastatic tumor, hepatic failure, lowest albumin, and FiO₂. A representative neural network model was constructed using the forward selection procedure. The area under the curve (AUC) of the neural network model evaluated with the validation cohort was 0.821 (95% CI [0.753-0.888]), which was greater than the APACHE III score (0.665; 95% CI [0.590-0.739]; p = 0.002 by Delong's test) and logistic regression model, albeit not statistically significant (0.743; 95% CI [0.669-0.817], p = 0.130 by Delong's test).

CONCLUSIONS

The study developed a neural network model using a GA, which outperformed conventional scoring systems for the prediction of mortality in ARDS patients.

The top 2,000 cited articles in critical care medicine: a bibliometric analysis

BACKGROUND

The bibliometric analysis has been performed on several topics in critical care medicine (CCM) focusing on top 100 cited articles, but the analysis on CCM literature as a whole is missing. The present study aimed to perform a complete bibliometric analysis in the field of CCM.

METHODS

An electronic search of the Scopus database was performed on Feb 13, 2018. The search strategy involved core terms related to CCM. The top 2,000 most cited articles in the field of CCM were included in the analysis. Descriptive statistics on these top-cited articles, country distributions, and journals are reported. Individual author's productivity was assessed with the Lotka's law. Co-occurrence of keywords was visualized with the Fruchterman-Reingold layout. The Walktrap algorithm was employed for clustering analysis.

RESULTS

A total of 2,000 documents were included in the analysis with median citations of 386 times [interquartile range (IQR): 308-562 times]. The most cited article was the original paper that described the Acute Physiology and Chronic Health Evaluation (APACHE) II score. The included articles were published in 411 journals. The median number of documents published in one journal was 1, and the mean number was 4.9, indicating a skewed distribution. The maximum number of publications was 217 in CCM. Author's productivity profile was significantly different from the Lotka's law (P=0.001), with n and C values of 2.8 and 0.52, respectively. Fruchterman-Reingold network plot showed that studies involving human subject were the most common literature type. Sepsis was a major research topic that co-occurred with keywords such as disease severity, nonhuman, risk assessment and practice guideline.

CONCLUSIONS

The study performed bibliometric analyses of 2,000 top-cited articles in CCM. The most cited article was the one which developed the APACHE II score. Author's productivity was significantly different from the Lotka's law.

Identification of three classes of acute respiratory distress syndrome using latent class analysis

Acute respiratory distress syndrome (ARDS) is a highly heterogeneous syndrome that can exhibit significant differences in the underlying causes, leading to different responses to treatment. It is required to identify subtypes of ARDS to guideline clinical treatment and trial design. The study aimed to identify subtypes of ARDS using latent class analysis (LCA). The study was a secondary analysis of the EDEN study, which was a randomized, controlled, multicenter trial conducted from January 2, 2008 to April 12, 2011. The primary study endpoint was death through 90-day follow up. LCA was performed incorporating variables on day 0 before randomization. The number of classes was chosen by a bootstrapped likelihood ratio test, Bayesian information criterion and the number of patients in each class. A total of 943 patients were enrolled in the study, including 219 (23.2%) non-survivors and 724 (76.8%) survivors. The LCA identified three classes of ARDS. Class 1 (hemodynamically unstable type) had significantly higher mortality rate (p = 0.003) than class 2 (intermediate type) and 3 (stable type) through 90 days follow up. There was significant interaction between cumulative fluid balance and the class (p = 0.02). While more fluid balance was beneficial for class 1, it was harmful for class 2 and 3. In conclusion, the study identified three classes of ARDS, which showed different clinical presentations, responses to fluid therapy and prognosis. The classification system used simple clinical variables and could help to design ARDS trials in the future.

The Processes and Mechanisms of Cardiac and Pulmonary Fibrosis

Fibrosis is the formation of fibrous connective tissue in response to injury. It is characterized by the accumulation of extracellular matrix components, particularly collagen, at the site of injury. Fibrosis is an adaptive response that is a vital component of wound healing and tissue repair. However, its continued activation is highly detrimental and a common final pathway of numerous disease states including cardiovascular and respiratory disease. Worldwide, fibrotic diseases cause over 800,000 deaths per year, accounting for ~45% of total deaths. With an aging population, the incidence of fibrotic disease and subsequently the number of fibrosis-related deaths will rise further. Although, fibrosis is a well-recognized cause of morbidity and mortality in a range of disease states, there are currently no viable therapies to reverse the effects of chronic fibrosis. Numerous predisposing factors contribute to the development of fibrosis. Biological aging in particular, interferes with repair of damaged tissue, accelerating the transition to pathological remodeling, rather than a process of resolution and regeneration. When fibrosis progresses in an uncontrolled manner, it results in the irreversible stiffening of the affected tissue, which can lead to organ malfunction and death. Further investigation into the mechanisms of fibrosis is necessary to elucidate novel, much needed, therapeutic targets. Fibrosis of the heart and lung make up a significant proportion of fibrosis-related deaths. It has long been established that the heart and lung are functionally and geographically linked when it comes to health and disease, and thus exploring the processes and mechanisms that contribute to fibrosis of each organ, the focus of this review, may help to highlight potential avenues of therapeutic investigation.

Annexin A2 contributes to lung injury and fibrosis by augmenting factor Xa fibrogenic activity

In lung injury and disease, including idiopathic pulmonary fibrosis (IPF), extravascular factor X is converted into factor Xa (FXa), a coagulant protease with fibrogenic actions. Extracellular annexin A2 binds to FXa, augmenting activation of the protease-activated receptor-1 (PAR-1). In this study, the contribution of annexin A2 in lung injury and fibrosis was investigated. Annexin A2 immunoreactivity was observed in regions of fibrosis, including those associated with fibroblasts in lung tissue of IPF patients. Furthermore, annexin A2 was detected in the conditioned media and an EGTA membrane wash of human lung fibroblast (LF) cultures. Incubation with human plasma (5% vol/vol) or purified FXa (15–50 nM) evoked fibrogenic responses in LF cultures, with FXa increasing interleukin-6 (IL-6) production and cell number by 270 and 46%, respectively ( P < 0.05, n = 5–8). The fibrogenic actions of plasma or FXa were attenuated by the selective FXa inhibitor apixaban (10 μM, or antibodies raised against annexin A2 or PAR-1 (2 μg/ml). FXa-stimulated LFs from IPF patients ( n = 6) produced twice as much IL-6 as controls ( n = 10) ( P < 0.05), corresponding with increased levels of extracellular annexin A2. Annexin A2 gene deletion in mice reduced bleomycin-induced increases in bronchoalveolar lavage fluid (BALF) IL-6 levels and cell number (* P < 0.05; n = 4–12). Lung fibrogenic gene expression and dry weight were reduced by annexin A2 gene deletion, but lung levels of collagen were not. Our data suggest that annexin A2 contributes to lung injury and fibrotic disease by mediating the fibrogenic actions of FXa. Extracellular annexin A2 is a potential target for the treatment of IPF.

Mesenchymal stromal cells for treatment of the acute respiratory distress syndrome: The beginning of the story

In spite of decades of research, the acute respiratory distress syndrome (ARDS) continues to have an unacceptably high mortality and morbidity. Mesenchymal stromal cells (MSCs) present a promising candidate for the treatment of this condition and have demonstrated benefit in preclinical models. MSCs, which are a topic of growing interest in many inflammatory disorders, have already progressed to early phase clinical trials in ARDS. While a number of their mechanisms of effect have been elucidated, a better understanding of the complex actions of these cells may pave the way for MSC modifications, which might enable more effective translation into clinical practice.

Text mining and medicine: usefulness in respiratory diseases

It is increasingly common to have medical information in electronic format. This includes scientific articles as well as clinical management reviews, and even records from health institutions with patient data. However, traditional instruments, both individual and institutional, are of little use for selecting the most appropriate information in each case, either in the clinical or research field. So-called text or data «mining» enables this huge amount of information to be managed, extracting it from various sources using processing systems (filtration and curation), integrating it and permitting the generation of new knowledge. This review aims to provide an overview of text and data mining, and of the potential usefulness of this bioinformatic technique in the exercise of care in respiratory medicine and in research in the same field.

Availability of MudPIT data for classification of biological samples

Background

Mass spectrometry is an important analytical tool for clinical proteomics. Primarily employed for biomarker discovery, it is increasingly used for developing methods which may help to provide unambiguous diagnosis of biological samples. In this context, we investigated the classification of phenotypes by applying support vector machine (SVM) on experimental data obtained by MudPIT approach. In particular, we compared the performance capabilities of SVM by using two independent collection of complex samples and different data-types, such as mass spectra (m/z), peptides and proteins.

Results

Globally, protein and peptide data allowed a better discriminant informative content than experimental mass spectra (overall accuracy higher than 87% in both collection 1 and 2). These results indicate that sequencing of peptides and proteins reduces the experimental noise affecting the raw mass spectra, and allows the extraction of more informative features available for the effective classification of samples. In addition, proteins and peptides features selected by SVM matched for 80% with the differentially expressed proteins identified by the MAProMa software.

Conclusions

These findings confirm the availability of the most label-free quantitative methods based on processing of spectral count and SEQUEST-based SCORE values. On the other hand, it stresses the usefulness of MudPIT data for a correct grouping of sample phenotypes, by applying both supervised and unsupervised learning algorithms. This capacity permit the evaluation of actual samples and it is a good starting point to translate proteomic methodology to clinical application.

Bioinformatics insights into acute lung injury/acute respiratory distress syndrome

Bioinformatics is the application of omics science, information technology, mathematics and statistics in the field of biomarker detection. Clinical bioinformatics can be applied for identification and validation of new biomarkers to improve current methods of monitoring disease activity and identify new therapeutic targets. Acute lung injurt (ALI)/Acute respiratory distress syndrome (ARDS) affects a large number of patients with a poor prognosis. The present review mainly focused on the progress in understanding disease heterogeneity through the use of evolving biological, genomic, and genetic approaches and the role of clinical bioinformatics in the pathogenesis and treatment of ALI/ARDS. The remarkable advances in clinical bioinformatics can be a new way for understanding disease pathogenesis, diagnosis and treatment.