The effects of vitamin C on respiratory, allergic and immunological diseases: an experimental and clinical-based review

Vitamin C is used in modern medicine supplements for treatment of various disorders associated with oxidative stress, inflammation and immune dysregulation. In this review article, experimental and clinical results regarding the effects of vitamin C on respiratory immunologic, and allergic diseases are reviewed. Various databases and appropriate keywords are used to search the effect of vitamin C on respiratory diseases until the end of May 2022. Books, theses and articles were included. These studies assessed the effects of vitamin C on respiratory disorders including asthma, chronic obstructive pulmonary disease (COPD), lung infection and lung cancer. Vitamin C showed relaxant effect on tracheal smooth muscle via various mechanisms. The preventive effects of vitamin C were mediated by antioxidant, immunomodulatory and anti-inflammatory mechanisms in the experimental animal models of different respiratory diseases. Some clinical studies also indicated the effect of vitamin C on lung cancer and lung infections. Therefore, vitamin C could be used a preventive and/or relieving therapy in respiratory diseases.

Role of cellular senescence in inflammatory lung diseases

Cellular senescence, a characteristic sign of aging, classically refers to permanent cell proliferation arrest and is a vital contributor to the pathogenesis of cancer and age-related illnesses. A lot of imperative scientific research has shown that senescent cell aggregation and the release of senescence-associated secretory phenotype (SASP) components can cause lung inflammatory diseases as well. In this study, the most recent scientific progress on cellular senescence and phenotypes was reviewed, including their impact on lung inflammation and the contributions of these findings to understanding the underlying mechanisms and clinical relevance of cell and developmental biology. Within a dozen pro-senescent stimuli, the irreparable DNA damage, oxidative stress, and telomere erosion are all crucial in the long-term accumulation of senescent cells, resulting in sustained inflammatory stress activation in the respiratory system. An emerging role for cellular senescence in inflammatory lung diseases was proposed in this review, followed by the identification of the main ambiguities, thus further understanding this event and the potential to control cellular senescence and pro-inflammatory response activation. In addition, novel therapeutic strategies for the modulation of cellular senescence that might help to attenuate inflammatory lung conditions and improve disease outcomes were also presented in this research.

Fibrosing Interstitial Lung Disease in Children: An HRCT-Based Analysis

OBJECTIVE

To determine high resolution CT (HRCT) patterns of pulmonary fibrosis (PF) in children; and their etiological correlates.

METHODS

This was a retrospective study involving 149 children with diffuse lung disease (DLD). Patterns of involvement were classified based on dominant lung finding as ground glass opacity (GGO) dominant, nodule dominant, cystic lung disease, or PF. Patterns of PF were classified based on distribution and morphology into airway centric fibrosis (ACF), subpleural fibrosis (SPF), progressive massive fibrosis (PMF) and fibrocavitary. A comparison was made between the two dominant groups for apicobasal distribution, associated findings (GGO, nodules, cysts), and pulmonary artery hypertension (PAH).

RESULTS

Nineteen patients showed PF on HRCT. ACF was commonest (52.6%), followed by SPF (42.1%). The common etiology was sarcoidosis (30%) in ACF, and connective tissue disorders (CTD) (50%) in SPF. Significant difference was found between ACF and SPF in apicobasal distribution (p = 0.04), presence of nodules (p = 0.03), and cysts (p = 0.02).

CONCLUSION

PF may present as an end stage of several childhood lung diseases. PF on imaging has discernible morphological patterns that correlate with underlying etiology.

Impact of cigarette smoking on rheumatoid arthritis-associated lung diseases: a retrospective case control study on clinical and radiological features and prognosis

Our study aimed to investigate the clinical and radiological features and prognosis of male smoker patients with rheumatoid arthritis (RA). We consecutively enrolled male inpatients with RA who received chest HRCT during hospitalization in Peking University Third Hospital from Jan 1st, 2012 to August 1st, 2021. 154 male patients with RA were eligible for analysis, of whom 76.6% (n = 118) were current smokers or had a history of cigarette smoking. Compared to never-smokers, smoker patients had more respiratory symptoms, including cough (31.4% vs 5.6%, p = 0.002) and sputum production (26.3% vs 2.8%, p = 0.002), and a higher positive rate of rheumatoid factor (RF) (77.6% vs 58.8%, p = 0.030). A higher percentage of smoker patients showed emphysema (45.8% vs 16.7%, p = 0.002) and signs of lung fibrosis (51/54, 94.4% vs 7/13, 53.8%, p < 0.001) in those with interstitial lung disease (ILD, n = 67) on chest HRCT. The overall survival rate was different between smoker and never-smoker patients (p = 0.031), but instead of cigarette smoking, lung fibrosis on HRCT was the risk factor for survival of our patients. In conclusion, male patients with RA who were current smokers or had a history of cigarette smoking presented more respiratory symptoms and a higher positive rate of RF. They also showed more emphysema and signs of lung fibrosis on chest HRCT. Cigarette smoking impacted on the overall survival as a confounding factor in this cohort of male patients with RA.

Pulmonary endogenous progenitor stem cell subpopulation: Physiology, pathogenesis, and progress

Lungs are structurally and functionally complex organs consisting of diverse cell types from the proximal to distal axis. They have direct contact with the external environment and are constantly at risk of various injuries. Capable to proliferate and differentiate, pulmonary endogenous progenitor stem cells contribute to the maintenance of lung structure and function both under homeostasis and following injuries. Discovering candidate pulmonary endogenous progenitor stem cell types and underlying regenerative mechanisms provide insights into therapeutic strategy development for lung diseases. In this review, we reveal their compositions, roles in lung disease pathogenesis and injury repair, and the underlying mechanisms. We further underline the advanced progress in research approach and potential therapy for lung regeneration. We also demonstrate the feasibility and prospects of pulmonary endogenous stem cell transplantation for lung disease treatment.

COVID-19 and pneumonia diagnosis from chest X-ray images using convolutional neural networks

X-ray is a useful imaging modality widely utilized for diagnosing COVID-19 virus that infected a high number of people all around the world. The manual examination of these X-ray images may cause problems especially when there is lack of medical staff. Usage of deep learning models is known to be helpful for automated diagnosis of COVID-19 from the X-ray images. However, the widely used convolutional neural network architectures typically have many layers causing them to be computationally expensive. To address these problems, this study aims to design a lightweight differential diagnosis model based on convolutional neural networks. The proposed model is designed to classify the X-ray images belonging to one of the four classes that are Healthy, COVID-19, viral pneumonia, and bacterial pneumonia. To evaluate the model performance, accuracy, precision, recall, and F1-Score were calculated. The performance of the proposed model was compared with those obtained by applying transfer learning to the widely used convolutional neural network models. The results showed that the proposed model with low number of computational layers outperforms the pre-trained benchmark models, achieving an accuracy value of 89.89% while the best pre-trained model (Efficient-Net B2) achieved accuracy of 85.7%. In conclusion, the proposed lightweight model achieved the best overall result in classifying lung diseases allowing it to be used on devices with limited computational power. On the other hand, all the models showed a poor precision on viral pneumonia class and confusion in distinguishing it from bacterial pneumonia class, thus a decrease in the overall accuracy.

Lung-on-a-Chip Models of the Lung Parenchyma

Since the publication of the first lung-on-a-chip in 2010, research has made tremendous progress in mimicking the cellular environment of healthy and diseased alveoli. As the first lung-on-a-chip products have recently reached the market, innovative solutions to even better mimic the alveolar barrier are paving the way for the next generation lung-on-chips. The original polymeric membranes made of PDMS are being replaced by hydrogel membranes made of proteins from the lung extracellular matrix, whose chemical and physical properties exceed those of the original membranes. Other aspects of the alveolar environment are replicated, such as the size of the alveoli, their three-dimensional structure, and their arrangement. By tuning the properties of this environment, the phenotype of alveolar cells can be tuned, and the functions of the air-blood barrier can be reproduced, allowing complex biological processes to be mimicked. Lung-on-a-chip technologies also provide the possibility of obtaining biological information that was not possible with conventional in vitro systems. Pulmonary edema leaking through a damaged alveolar barrier and barrier stiffening due to excessive accumulation of extracellular matrix proteins can now be reproduced. Provided that the challenges of this young technology are overcome, there is no doubt that many application areas will benefit greatly.

Qing Fei Hua Xian Decoction ameliorates bleomycin-induced pulmonary fibrosis by suppressing oxidative stress through balancing ACE-AngII-AT1R/ACE2-Ang-(1-7)-Mas axis

Objectives

We aimed to investigate the preventative effect of Qing Fei Hua Xian Decoction (QFHXD) against pulmonary fibrosis (PF) and its potential mechanisms.

Materials and Methods

Bleomycin (BLM)-induced rats were respectively treated with 413.3, 826.6, and 1239.9 mg/kg of QFHXD and prednisone for 28 days. The lung tissues of rats were collected on day 28 for histological and western blotting analysis.

Results

QFHXD significantly reduced alveolus inflammation, collagen accumulation, and fibrosis deposition in BLM-induced PF rats (P<0.05). Collagen I and III, vimentin, and α-smooth muscle actin(α-SMA) expression levels were likewise decreased in PF rats treated with QFHXD (P<0.05). Additionally, QFHXD increased the expression of nuclear factor erythroid 2-related factor 2 (Nrf2) while decreasing NADPH oxidase 4 (NOX4) expression (P<0.05). Furthermore, QFHXD suppressed the PF progression by down-regulating Angiotensin-Converting Enzyme (ACE) -Angiotensin II (AngII) -Angiotensin II Type 1 Receptor (AT1R) axis (P<0.01) and up-regulating Angiotensin-Converting Enzyme 2 (ACE2) -Angiotensin-(1-7) (Ang-(1-7)) -Mas axis (P<0.05).

Conclusion

QFHXD suppressed inflammatory infiltration and PF brought on by BLM in lung tissues through reducing oxidative stress by maintaining the equilibrium of ACE-AngII-AT1R and ACE2-Ang-(1-7) -Mas axes. This study may provide a novel clinical therapy option for PF.

Death, Disability, and Premature Life Years Lost Due to Cigarettes, Bidis, and Smokeless Tobacco in India: A Comparative Assessment

BACKGROUND

Due to the staggering number of tobacco users in India, it is important to determine the exact mortality and morbidity rates due to tobacco use. This study aimed to estimate deaths, disability-adjusted life years (DALYs), and years of life lost (YLLs) attributable to cigarettes, bidis, and smokeless tobacco (SLT) in India.

METHODS

Data pooling and meta-analysis were done using case-control studies available on the three types of tobacco products. Health burden was estimated by applying the population attributable fraction (PAF) value to the total disease burden.

FINDINGS

A total of 33 studies were included. PAF was calculated for oral and lung cancer as well as ischemic heart disease (IHD) due to cigarettes, oral and lung cancer, IHD, and chronic obstructive pulmonary disease due to bidi, and oral and stomach cancer and IHD due to SLT. Cigarettes resulted in 8.4 million DALYs, 8.26 million YLLs, and 341 deaths; bidis led to 11.7 million DALYs, 10.7 million YLLs, and 478 thousand deaths, and SLTs accounted for 4.38 million DALYs, 4.3 million YLLs, and 171 thousand deaths annually.

CONCLUSION

Evidence of measurable health burden and methodology for calculation for individual states was provided in the study. The generated evidence could be utilized for policy recommendations and revision of the existing taxation norms.

Machine learning-based techniques to improve lung transplantation outcomes and complications: a systematic review

BACKGROUND

Machine learning has been used to develop predictive models to support clinicians in making better and more reliable decisions. The high volume of collected data in the lung transplant process makes it possible to extract hidden patterns by applying machine learning methods. Our study aims to investigate the application of machine learning methods in lung transplantation.

METHOD

A systematic search was conducted in five electronic databases from January 2000 to June 2022. Then, the title, abstracts, and full text of extracted articles were screened based on the PRISMA checklist. Then, eligible articles were selected according to inclusion criteria. The information regarding developed models was extracted from reviewed articles using a data extraction sheet.

RESULTS

Searches yielded 414 citations. Of them, 136 studies were excluded after the title and abstract screening. Finally, 16 articles were determined as eligible studies that met our inclusion criteria. The objectives of eligible articles are classified into eight main categories. The applied machine learning methods include the Support vector machine (SVM) (n = 5, 31.25%) technique, logistic regression (n = 4, 25%), Random Forests (RF) (n = 4, 25%), Bayesian network (BN) (n = 3, 18.75%), linear regression (LR) (n = 3, 18.75%), Decision Tree (DT) (n = 3, 18.75%), neural networks (n = 3, 18.75%), Markov Model (n = 1, 6.25%), KNN (n = 1, 6.25%), K-means (n = 1, 6.25%), Gradient Boosting trees (XGBoost) (n = 1, 6.25%), and Convolutional Neural Network (CNN) (n = 1, 6.25%). Most studies (n = 11) employed more than one machine learning technique or combination of different techniques to make their models. The data obtained from pulmonary function tests were the most used as input variables in predictive model development. Most studies (n = 10) used only post-transplant patient information to develop their models. Also, UNOS was recognized as the most desirable data source in the reviewed articles. In most cases, clinicians succeeded to predict acute diseases incidence after lung transplantation (n = 4) or estimate survival rate (n = 4) by developing machine learning models.

CONCLUSION

The outcomes of these developed prediction models could aid clinicians to make better and more reliable decisions by extracting new knowledge from the huge volume of lung transplantation data.

LWSNet - a novel deep-learning architecture to segregate Covid-19 and pneumonia from x-ray imagery

Automatic detection of lung diseases using AI-based tools became very much necessary to handle the huge number of cases occurring across the globe and support the doctors. This paper proposed a novel deep learning architecture named LWSNet (Light Weight Stacking Network) to separate Covid-19, cold pneumonia, and normal chest x-ray images. This framework is based on single, double, triple, and quadruple stack mechanisms to address the above-mentioned tri-class problem. In this framework, a truncated version of standard deep learning models and a lightweight CNN model was considered to conviniently deploy in resource-constraint devices. An evaluation was conducted on three publicly available datasets alongwith their combination. We received 97.28%, 96.50%, 97.41%, and 98.54% highest classification accuracies using quadruple stack. On further investigation, we found, using LWSNet, the average accuracy got improved from individual model to quadruple model by 2.31%, 2.55%, 2.88%, and 2.26% on four respective datasets.

LWSNet - a novel deep-learning architecture to segregate Covid-19 and pneumonia from x-ray imagery

Automatic detection of lung diseases using AI-based tools became very much necessary to handle the huge number of cases occurring across the globe and support the doctors. This paper proposed a novel deep learning architecture named LWSNet (Light Weight Stacking Network) to separate Covid-19, cold pneumonia, and normal chest x-ray images. This framework is based on single, double, triple, and quadruple stack mechanisms to address the above-mentioned tri-class problem. In this framework, a truncated version of standard deep learning models and a lightweight CNN model was considered to conviniently deploy in resource-constraint devices. An evaluation was conducted on three publicly available datasets alongwith their combination. We received 97.28%, 96.50%, 97.41%, and 98.54% highest classification accuracies using quadruple stack. On further investigation, we found, using LWSNet, the average accuracy got improved from individual model to quadruple model by 2.31%, 2.55%, 2.88%, and 2.26% on four respective datasets.

Enabling effective breathing sound analysis for automated diagnosis of lung diseases

With the emergence of the COVID-19 pandemic, early diagnosis of lung diseases has attracted growing attention. Generally, monitoring the breathing sound is the traditional means for assessing the status of a patient's respiratory health through auscultation; for that a stethoscope is one of the clinical tools used by physicians for diagnosis of lung disease and anomalies. On the other hand, recent technological advances have made telehealth systems a practical and effective option for health status assessment and remote patient monitoring. The interest in telehealth solutions have further grown with the COVID-19 pandemic. These telehealth systems aim to provide increased safety and help to cope with the massive growth in healthcare demand. Particularly, employing acoustic sensors to collect breathing sound would enable real-time assessment and instantaneous detection of anomalies. However, existing work focuses on autonomous determination of respiratory rate which is not suitable for anomaly detection due to inability to deal with noisy data recording. This paper presents a novel approach for effective breathing sound analysis. We promote a new segmentation mechanism of the captured acoustic signals to identify breathing cycles in recorded sound signals. A scoring scheme is applied to qualify the segment based on the targeted respiratory illness by the overall breathing sound analysis. We demonstrate the effectiveness of our approach via experiments using published COPD datasets.

Emerging role of an immunomodulatory protein secretoglobin 3A2 in human diseases

Secretoglobin (SCGB) 3A2 was first identified in 2001 as a protein exhibiting similarities in amino acid sequence and gene structure to SCGB1A1, a multi-functional cytokine-like molecule highly expressed in airway epithelial Club cells that was the first identified and extensively studied member of the SCGB gene superfamily. SCGB3A2 is a small secretory protein of ~10 kDa that forms a dimer and a tetramer. SCGB3A2 is predominantly expressed in airway epithelial Club cells, and has anti-inflammatory, growth factor, anti-fibrotic, and anti-cancer activities that influence various lung diseases. This review summarizes the current understanding of SCGB3A2 biological functions and its role in human diseases with emphasis on its mechanisms of actions and signaling pathway.

The rationale of applying inspiratory/expiratory muscle training within the same respiratory cycle in children with bronchial asthma: A placebo-controlled randomized clinical investigation

Objective: Even though positive implications of inspiratory muscle training (In-MT) have been established in children and adolescents with bronchial asthma (C/AwBA), the role of combined inspiratory and expiratory muscle training (Ex-MT) within the same respiratory cycle (In/Ex-SC) is still unknown. This study was, therefore, set out to explore the effect of In/Ex-SC on respiratory muscle strength, pulmonary functions, and control of asthma symptoms in C/AwBA.Methods: This was a placebo-controlled randomized clinical investigation that included 51 C/AwBA (12-18 years). Participants were assigned randomly into three groups: Placebo, In-MT only, or combined In/Ex-SC training (n = 17, each group). The training was conducted for ∼35 min, thrice/week over 12 weeks. The maximal inspiratory (IP_max) and expiratory (EP_max) pressure (indicating the strength of the inspiratory and expiratory muscles, respectively), pulmonary functions [forced expiratory volume in one second (FEV₁), forced vital capacity (FVC), and FEV₁/FVC index], and asthma control test (ACT) were assessed before and after the intervention.Results: The In/Ex-SC yielded larger increases in IP_max and EP_max than either the Placebo training (P=.031 and P=.009 respectively) or the In-MT (P=.029 and P=.032 respectively). Further, In/Ex-SC produced favorable improvement in FEV₁, FVC, and FEV₁/FVC compared to the Placebo training (P=.001, P=.004, and P=.0005 respectively) or In-MT (P=.038, P=.037, and P=.025 respectively) training. Furthermore, In/Ex-SC led to better control of asthma symptoms than the Placebo (P<.001) or In-MT (P=.002) training.Conclusion: This study provides evidence that combined In/Ex-SC can considerably improve respiratory muscle strength, enhance pulmonary function, and promote control over asthma symptoms in C/AwBA.

Smoking related environmental microbes affecting the pulmonary microbiome in Chinese population

BACKGROUND

Smoking is a serious public health problem that affects human health conditions. Although there is evidence that microorganisms are associated with smoking-related lung diseases, the relationship between the rich lung microbiome of upper respiratory tract groups and smoking has not been studied.

OBJECTIVE

In this study, we investigated the effects of smoking on environmental microbes and lung microbiome in the Chinese population and provided clues for the role of smoking in the development of respiratory disease.

METHODS

Bronchoalveolar lavage fluid samples were collected from 55 individuals with a history of smoking. Microbial gene sequencing was carried out through NGS technology. We analyzed and compared the diversity, community structure, and species abundance of bronchoalveolar lavage microbiome between smokers and nonsmokers, to speculate the effects of smoking on the lung microbiome.

RESULTS

Smoking hardly affected the α diversity of microbial groups of bronchoalveolar lavage, but it had a huge influence on the microbiome composition. The relative abundance of Rothia, Actinomycetes, Haemophilus, Porphyrins, Neisseria, Acinetobacter, and Streptococcus genera had a remarkable increase in the smoking group. On the other hand, the relative abundance of Plusella and Veronella decreased significantly.

CONCLUSION

Smoking may change the environmental microbes and then alter the structure of the lung microbiome, which may lead to smoking-related diseases.

Chronic obstructive pulmonary disease and asthma: mesenchymal stem cells and their extracellular vesicles as potential therapeutic tools

Chronic lung diseases, such as chronic obstructive pulmonary disease (COPD) and asthma, are one of the most frequent causes of morbidity and mortality in the global. COPD is characterized by progressive loss of lung function through inflammation, apoptosis, and oxidative stress caused by chronic exposure to harmful environmental pollutants. Airway inflammation and epithelial remodeling are also two main characteristics of asthma. In spite of extensive efforts from researchers, there is still a great need for novel therapeutic approaches for treatment of these conditions. Accumulating evidence suggests the potential role of mesenchymal stem cells (MSCs) in treatment of many lung injuries due to their beneficial features including immunomodulation and tissue regeneration. Besides, the therapeutic advantages of MSCs are chiefly related to their paracrine functions such as releasing extracellular vesicles (EVs). EVs comprising exosomes and microvesicles are heterogeneous bilayer membrane structures loaded with various lipids, nucleic acids and proteins. Due to their lower immunogenicity, tumorigenicity, and easier management, EVs have appeared as favorable alternatives to stem cell therapies. Therefore, in this review, we provided an overview on the current understanding of the importance of MSCs and MSC-derived EVs from different sources reported in preclinical and clinical COPD and asthmatic models.

Extracellular vesicles in respiratory disease

Extracellular vesicles (EVs) are membranous nanoparticles secreted by nearly all cell types and play a critical role in cell-to-cell crosstalk. EVs can be categorized based on their size, surface markers, or the cell type from which they originate. EVs carry "cargo," including but not limited to, RNA, DNA, proteins, and small signaling molecules. To date, many methods have been developed to isolate EVs from biological fluids, such as blood plasma, urine, bronchoalveolar lavage fluid, and urine. Once isolated, EVs can be characterized by dynamic light scattering, nanotracking analysis, nanoscale flow cytometry, and transmission electron microscopy. Given the ability of EVs to transport cargo between cells, research has recently focused on understanding their role in various human diseases. As understanding of their significance to disease processes grows, insight into the mechanisms behind the physiological role of their cargo in target cells can facilitate the development of a new type of biomarker and therapeutic target for diseases in future. In addition, their ability to deliver their cargo selectively to target cells within the human body means that they could serve as therapeutic agents or methods of drug delivery. In this review, we will first introduce EVs and the cargo they carry, outline current methods for EV isolation and characterization, and discuss their potential use as biomarkers and therapeutic agents in the near future.

Fibrotic Cystic Lung Disease Post Hematopoietic Stem Cell Transplant: Who is the Culprit?

Pulmonary complications post hematopoietic stem cell transplant (HSCT) are associated with poor outcomes and require extensive management depending on the etiology. They usually present in the form of bronchiolitis obliterans syndrome, interstitial pneumonitis, or drug toxicity that can lead to fibrosis. Scant data exists regarding diffuse cystic lung disease following HSCT, and the existing literature only mentions mild cystic changes. We present the case of a 25-year-old man with stage IVB Hodgkin's lymphoma post allogeneic HSCT, who developed progressive traction bronchiectasis, with the appearance of extensive pulmonary cysts that followed significant fibrotic changes and discuss the possible etiologies behind it.

Therapeutic role of mesenchymal stem cell-derived exosomes in respiratory disease

Exosomes are extracellular vesicles found in various tissues, blood circulation, and tissue fluids, secreted into the extracellular environment by fusing a multivesicular body with a plasma membrane. Various cell types release these vesicles to contribute to many cellular functions, including intercellular communication, cell proliferation, differentiation, angiogenesis, response to stress, and immune system signaling. These natural nanoparticles have therapeutic effects in various diseases and exhibit a behavior similar to the cell from which they originated. In the meantime, exosomes derived from mesenchymal stem cells have attracted the attention of many researchers and physicians due to their unique ability to modulate the immune system, repair tissue and reduce inflammation. Numerous clinical and preclinical studies have examined the effect of MSC-derived exosomes in various diseases, and their results have been published in prestigious journals. This review article discusses the biogenesis and sources of exosomes, MSC-derived exosomes, the use of these exosomes in regenerative medicine, and treatments based on exosomes derived from stem cells in respiratory diseases.

Low body mass index as a barrier to lung transplant in cystic fibrosis

RATIONALE

Low body mass index (BMI) may influence lung transplant decisions for patients with advanced cystic fibrosis (CF) lung disease.

OBJECTIVE

Determine whether patients with advanced CF lung disease and BMI ≤17 kg/m2 are less likely to be listed for lung transplant or have a higher risk of death without listing compared to those with higher BMI.

METHODS

Using merged United Network for Organ Sharing and CF Foundation Patient Registries, we identified adults with onset of advanced lung disease (FEV1 ≤ 40% predicted) between May-2005 and December-2016. We analyzed survival using competing risks regression with cause-specific risks of listing for lung transplant and death without listing. BMI ≤ 17 kg/m2 was our predictor.

MEASUREMENTS AND MAIN RESULTS

Among 5,121 CF patients with advanced lung disease, 23% were listed for lung transplant (n = 1,201), 23% died without listing (n = 1,190), and 44% were alive without listing (n = 2,730) as of December-2016. Patients with BMI ≤ 17 kg/m2 were less likely to be listed for transplant (HR 0.69; 95% CI 0.57, 0.83) and more likely to die without listing (HR 1.63; 95% CI 1.41, 1.88). We identified important regional variations in the likelihood of referral and listing, based on BMI.

CONCLUSIONS

Patients with advanced CF lung disease and BMI ≤ 17 kg/m2 are less likely to be listed for lung transplant and have a higher risk of dying without listing, compared to those with higher BMI. Regional differences suggest access to transplant for malnourished CF patients may be limited by location.

Natural products in the treatment of pulmonary emphysema: Therapeutic effects and mechanisms of action

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a class of lung diseases including chronic bronchitis, asthma, and emphysema. Long-time smoking is considered the main reason for developing emphysema. Emphysema can be defined as damage to the walls of the air sacs (alveoli) of the lung. It has been demonstrated that natural compounds with antioxidant and anti-inflammatory effects can effectively improve or protect the lung against this disease. This paper is dedicated to systematically review the effective natural compounds in the treatment of pulmonary emphysema.

PURPOSE

This is the first systematic and comprehensive review on the role of plant-derived secondary metabolites in managing and/or treating pulmonary emphysema STUDY DESIGN AND METHODS: A systematic and comprehensive review was done based on Scopus, PubMed, and Cochrane Library databases were searched using the "emphysema", "plant", "herb", and "phytochemical" keywords. Non-English, review, and repetitive articles were excluded from the study. Search results were included in the Prisma diagram.

RESULTS

From a total of 1285 results, finally, 22 articles were included in the present study. The results show that some herbs such as Scutellaria baicalensis Georgi and Monascus adlay and some phytochemicals such as gallic acid and quercetin and blackboard tree indole alkaloids affect more factors in improving the lung emphysema. Also, some natural compounds such as marijuana smoke and humic acid also play an aggravating role in this disease. It also seems that some of the medicinal plants such as PM014 herbal formula, pomegranate juice and açaí berry sometimes have side effects that are inconsistent with their therapeutic effects.

CONCLUSION

We concluded that natural compounds can effectively improve pulmonary emphysema due to their antioxidant, anti-inflammatory, and anti-apoptotic properties. However, additional studies are suggested to prove efficacy and side effects.