Early Diagnosis and Real-Time Monitoring of Regional Lung Function Changes to Prevent Chronic Obstructive Pulmonary Disease Progression to Severe Emphysema

Alleviatory Role of Panax Notoginseng Saponins in Modulating Inflammation and Pulmonary Vascular Remodeling in Chronic Obstructive Pulmonary Disease: mechanisms and Implications

COPD is an inflammatory lung disease that limits airflow and remodels the pulmonary vascular system. This study delves into the therapeutic potential and mechanistic underpinnings of Panax notoginseng Saponins (PNS) in alleviating inflammation and pulmonary vascular remodeling in a COPD rat model. Symmap and ETCM databases provided Panax notoginseng-related target genes, and the CTD and DisGeNET databases provided COPD-related genes. Intersection genes were subjected to protein-protein interaction analysis and pathway enrichment to identify downstream pathways. A COPD rat model was established, with groups receiving varying doses of PNS and a Roxithromycin control. The pathological changes in lung tissue and vasculature were examined using histological staining, while molecular alterations were explored through ELISA, RT-PCR, and Western blot. Network pharmacology research suggested PNS may affect the TLR4/NF-κB pathway linked to COPD development. The study revealed that, in contrast to the control group, the COPD model exhibited a significant increase in inflammatory markers and pathway components such as TLR4, NF-κB, HIF-1α, VEGF, ICAM-1, SELE mRNA, and serum TNF-α, IL-8, and IL-1β. Treatment with PNS notably decreased these markers and mitigated inflammation around the bronchi and vessels. Taken together, the study underscores the potential of PNS in reducing lung inflammation and vascular remodeling in COPD rats, primarily via modulation of the TLR4/NF-κB/HIF-1α/VEGF pathway. This research offers valuable insights for developing new therapeutic strategies for managing and preventing COPD.

Combining small airway parameters with conventional parameters obtained during spirometry to diagnose airflow obstruction: A cross-sectional study

BACKGROUND AND OBJECTIVE

The use of small airway parameters generated by spirometry, namely forced expiratory flow between 25% and 75% of forced vital capacity (FVC) (FEF25%-75%) and forced expiratory flow at 50% and 75% of FVC (FEF50% and FEF75%, respectively), is widely discussed. We evaluated the importance of these spirometric parameters in a large Chinese population.

METHODS

We conducted a cross-sectional observational study in which spirometry and bronchodilator responsiveness (BDR) data were collected in a healthcare centre from May 2021 to August 2022 and in a tertiary hospital from January 2017 to March 2022. Discordance was assessed between the classification of test results by the large airway parameters of forced expiratory volume in 1 second (FEV1) and FEV1/FVC ratio and by the small airway parameters of FEF25%-75%, FEF75% and FEF50%. The predictive power of Z-scores of spirometric parameters for airflow limitation and BDR was assessed using receiver operating characteristic curves.

RESULTS

Our study included 26,658 people. Among people with a normal FVC (n = 14,688), 3.7%, 4.5% and 3.6% of cases exhibited normal FEV1/FVC ratio but impaired FEF25%-75%, FEF75% and FEF50%, respectively, while 6.8%-7.0% of people exhibited normal FEV1 but impaired FEF25%-75%, FEF75% and FEF50%. Using the Z-scores of combining both large and small airway parameters in spirometry showed the best area under the curve for predicting airflow limitation (0.90; 95% CI 0.87-0.94) and predicting BDR (0.72; 95% CI 0.71-0.73).

CONCLUSION

It is important to consider both large and small airway parameters in spirometry to avoid missing a diagnosis of airflow obstruction.

Establishment and application of reference equations for FEF50 and FEF75 in the Chinese population

Background

Reference equations for forced expiratory flow at 50% and 75% of forced vital capacity (FVC) (FEF50 and FEF75) in the Chinese population are lacking. It is of great importance to establish equations covering most age groups and to study their applicability in clinical practice.

Methods

Using the lambda-mu-sigma (LMS) method, reference equations for FEF50 and FEF75 were constructed based on pulmonary function data from healthy subjects collected from January 2007 to June 2010 at 24 centers throughout China. Differences between the established equations and extraneous equations were compared using standardized means (Z values) and percentage errors (PE). The proportion of small airway dysfunction (SAD) defined by the present equations was calculated. The Fisher precision probability test and the Mann-Whitney test were used to analyze the magnitude of changes in small and large airway indices after bronchodilator inhalation in patients with suspected asthma and chronic obstructive pulmonary disease (COPD).

Results

Reference equations for FEF50 and FEF75 were established based on data from 7,115 healthy individuals (aged 4 to 80 years, 50.9% female, height between 95 and 190 cm). The present equations (all Z values were -0.0 and PE ranged from 2.0% to 4.2%) showed advantages over the European Community for Steel and Coal (ECSC) equations in 1993 (with Z values ranging from -0.7 to -0.2 and PE ranged from -23.4% to -4.5%). A total of 4,356 patients with suspected asthma (51.1% female; a mean age of 45.4 years) and 6,558 patients with suspected COPD (10.1% female; a mean age of 65.0 years) were included. The present equations defined 95.7% and 99.9% of SAD in these patients. After bronchodilator inhalation, greater mean improvement rates in small airway indices were observed both in patients with suspected asthma [mean ± standard deviation (SD) =48%±47%] and in patients with suspected COPD (mean ± SD =20%±30%) (P<0.05).

Conclusions

The reference equations for FEF50 and FEF75 established in this study should be considered for use in China. Further studies are needed to validate their value in the diagnosis of some chronic respiratory diseases.

Desmosine as a biomarker for the emergent properties of pulmonary emphysema

Developing an effective treatment for pulmonary emphysema will require a better understanding of the molecular changes responsible for distention and rupture of alveolar walls. A potentially useful approach to studying this process involves the concept of emergence in which interactions at different levels of scale induce a phase transition comprising a spontaneous reorganization of chemical and physical systems. Recent studies in our laboratory provide evidence of this phenomenon in pulmonary emphysema by relating the emergence of airspace enlargement to the release of elastin-specific desmosine and isodesmosine (DID) crosslinks from damaged elastic fibers. When the mean alveolar diameter exceeded 400 μm, the level of peptide-free DID in human lungs was greatly increased, reflecting rapid acceleration of elastin breakdown, alveolar wall rupture, and a phase transition to an active disease state that is less responsive to treatment. Based on this finding, it is hypothesized that free DID in urine and other body fluids may serve as a biomarker for early detection of airspace enlargement, thereby facilitating timely therapeutic intervention and reducing the risk of respiratory failure.

Survey of Transfer Learning Approaches in the Machine Learning of Digital Health Sensing Data

Machine learning and digital health sensing data have led to numerous research achievements aimed at improving digital health technology. However, using machine learning in digital health poses challenges related to data availability, such as incomplete, unstructured, and fragmented data, as well as issues related to data privacy, security, and data format standardization. Furthermore, there is a risk of bias and discrimination in machine learning models. Thus, developing an accurate prediction model from scratch can be an expensive and complicated task that often requires extensive experiments and complex computations. Transfer learning methods have emerged as a feasible solution to address these issues by transferring knowledge from a previously trained task to develop high-performance prediction models for a new task. This survey paper provides a comprehensive study of the effectiveness of transfer learning for digital health applications to enhance the accuracy and efficiency of diagnoses and prognoses, as well as to improve healthcare services. The first part of this survey paper presents and discusses the most common digital health sensing technologies as valuable data resources for machine learning applications, including transfer learning. The second part discusses the meaning of transfer learning, clarifying the categories and types of knowledge transfer. It also explains transfer learning methods and strategies, and their role in addressing the challenges in developing accurate machine learning models, specifically on digital health sensing data. These methods include feature extraction, fine-tuning, domain adaptation, multitask learning, federated learning, and few-/single-/zero-shot learning. This survey paper highlights the key features of each transfer learning method and strategy, and discusses the limitations and challenges of using transfer learning for digital health applications. Overall, this paper is a comprehensive survey of transfer learning methods on digital health sensing data which aims to inspire researchers to gain knowledge of transfer learning approaches and their applications in digital health, enhance the current transfer learning approaches in digital health, develop new transfer learning strategies to overcome the current limitations, and apply them to a variety of digital health technologies.

MiR-23a-3p alleviates cigarette smoke extract-induced pulmonary vascular endothelial cell apoptosis by targeting DNAJB1 in emphysema

BACKGROUND

Cigarette smoke (CS) is an important risk factor for chronic obstructive pulmonary disease, including emphysema. MicroRNAs (miRNAs) are important regulators of emphysema progression. However, miR-23a-3p role in emphysema is unclear.

METHODS

CS exposure was used to construct emphysema mice models, and cigarette smoke extract (CSE)-induced pulmonary vascular endothelial cells (PMVECs) were used to mimic emphysema cell models. Mouse lung tissue was stained by immunohistochemical staining, hematoxylin and eosin staining, and TUNEL staining. MiR-23a-3p and DnaJ homolog subfamily B member 1 (DNAJB1) levels were tested using quantitative real-time PCR. DNAJB1 and apoptosis-related markers' protein levels were examined via western blot analysis. Cell viability and apoptosis were analyzed by MTT assay and flow cytometry. The interaction between miR-23a-3p and DNAJB1 was evaluated by dual-luciferase reporter assay and RIP assay.

RESULTS

MiR-23a-3p was downregulated, and DNAJB1 was upregulated in CS-induced emphysema mice models and CSE-induced PMVECs. MiR-23a-3p overexpression promoted viability and repressed apoptosis in CSE-induced PMVECs. MiR-23a-3p targeted DNAJB1 and negatively regulated DNAJB1 expression. Moreover, DNAJB1 knockdown repressed CSE-induced PMVECs apoptosis, and miR-23a-3p inhibitor reversed this effect. Additionally, miR-23a-3p alleviated lung tissue injury and improved emphysema in mice by reducing DNAJB1 expression.

CONCLUSION

MiR-23a-3p alleviated emphysema progression, which could inhibit CSE-induced PMVECs apoptosis by targeting DNAJB1.

Oscillometry in Lung Function Assessment: A Comprehensive Review of Current Insights and Challenges

Oscillometry, a non-invasive technique for assessing lung function, has gained significant recognition and importance in modern pulmonary medicine. This comprehensive review thoroughly explores its principles, applications, advantages, limitations, recent innovations, and future directions. Oscillometry's primary strength lies in its ability to offer a holistic assessment of lung mechanics. Unlike traditional spirometry, oscillometry captures the natural airflow during quiet breathing, making it suitable for patients of all ages and those with severe respiratory conditions. It provides a comprehensive evaluation of airway resistance, reactance, and compliance, offering insights into lung function that were previously challenging to obtain. In clinical practice, oscillometry finds extensive application in diagnosing and managing respiratory diseases. It plays a pivotal role in asthma, chronic obstructive pulmonary disease (COPD), and interstitial lung diseases. By detecting subtle changes in lung function before symptoms manifest, oscillometry facilitates early interventions, improving disease management and patient outcomes. Oscillometry's non-invasive and patient-friendly nature is precious in pediatric care, where traditional spirometry may be challenging for young patients. It aids in diagnosing and monitoring pediatric respiratory disorders, ensuring that children receive the care they need from an early age. Despite its many advantages, oscillometry faces challenges, such as the need for standardized protocols and the complexity of data interpretation. However, ongoing efforts to establish global standards and provide education and training for healthcare professionals aim to address these issues. Looking ahead, oscillometry holds great promise in the field of personalized medicine. With its ability to tailor treatment plans based on individualized lung function data, healthcare providers can optimize therapy selection and dosing, ultimately improving patient care and quality of life. In conclusion, oscillometry is poised to play an increasingly pivotal role in modern pulmonary medicine. As standardization efforts continue and technology evolves, it is an indispensable tool in the clinician's arsenal for diagnosing, managing, and personalizing respiratory care, ultimately leading to improved patient outcomes and better respiratory health.

NSCLC patients with a changing T grade after operation may represent a special subset of tumor staging

BACKGROUND

There is consensus that postoperative adjuvant therapy is not recommended in patients with stage 1a non-small cell lung cancer (NSCLC). Meanwhile, it is still controversial whether postoperative adjuvant chemotherapy is recommended for NSCLC patients with T2aN0M0 (stage 1b). In some patients with stage 1b NSCLC without pleural invasion, tumor diameter was measured between 3 and 4 cm by preoperative imaging and less than 3 cm by postoperative pathology specimens. TNM staging in such patients is both radiologic stage 1b and pathologic stage 1a. Thoracic surgeons are often confused about whether such patients with NSCLC will require subsequent treatment and how the survival prognosis for this group of patients will be.

METHODS

All data of radiographic TNM stage 1b patients who underwent radical R0 resection at the department of thoracic surgery, the First Affiliated Hospital of Soochow University between January 2013 and July 2017 were retrieved, and 208 patients were finally included in the study. Clinical data, including imaging data, pathology data, were obtained by reviewing the patients' electronic medical records. Disease-free survival (DFS) and overall survival (OS) were obtained by telephone interview. Statistical analysis was performed using SPSS (SPSS 26.0 for windows, SPSS).

RESULTS

A total of 208 patients were included in this study, 61 patients with T-stage migration (observation group) and 147 patients without T-stage migration (control group). There were significant statistical differences between the two groups in terms of preoperative FEV1/FVC and tumor diameter (specimens, CT and 3-dimensional measurements). Logistic regression results showed that lower FEV1/FVC and smaller CT measurements would make the patient's T stage more likely to migrate. Bland-Altman plots showed that tumor length measured by imaging was significantly higher than that measured by pathological specimens. Taking DFS as the outcome, the survival curve of the observation group was significantly better than that of the control group. Similarly, there was a significant difference in OS between the two groups.

CONCLUSIONS

For NSCLC patients whose preoperative imaging evaluation was stage 1b (tumor diameter more than 3 cm, no main bronchus, pleura, no atelectasis), the presence of lung tissue with smaller tumor diameter and/or higher air content may indicate that the postoperative pathological staging may be changed to stage 1a (tumor diameter less than 3 cm). These patients had better survival prognosis than those who did not undergo TNM stage change and were diagnosed with stage 1b non-small cell lung cancer before and after surgery.

Quantifying ventilation by X-ray velocimetry in healthy adults

RATIONALE

X-ray velocimetry (XV) has been utilized in preclinical models to assess lung motion and regional ventilation, though no studies have compared XV-derived physiologic parameters to measures derived through conventional means.

OBJECTIVES

To assess agreement between XV-analysis of fluoroscopic lung images and pitot tube flowmeter measures of ventilation.

METHODS

XV- and pitot tube-derived ventilatory parameters were compared during tidal breathing and with bilevel-assisted breathing. Levels of agreement were assessed using the Bland-Altman analysis. Mixed models were used to characterize the association between XV- and pitot tube-derived values and optimize XV-derived values for higher ventilatory volumes.

MEASUREMENTS AND MAIN RESULTS

Twenty-four healthy volunteers were assessed during tidal breathing and 11 were reassessed with increased minute ventilation with bilevel-assisted breathing. No clinically significant differences were observed between the two methods for respiratory rate (average Δ: 0.58; 95% limits of agreement: -1.55, 2.71) or duty cycle (average Δ: 0.02; 95% limits of agreement: 0.01, 0.03). Tidal volumes and flow rates measured using XV were lower than those measured using the pitot tube flowmeter, particularly at the higher volume ranges with bilevel-assisted breathing. Under these conditions, a mixed-model based adjustment was applied to the XV-derived values of tidal volume and flow rate to obtain closer agreement with the pitot tube-derived values.

CONCLUSION

Radiographically obtained measures of ventilation with XV demonstrate a high degree of correlation with parameters of ventilation. If the accuracy of XV were also confirmed for assessing the regional distribution of ventilation, it would provide information that goes beyond the scope of conventional pulmonary function tests or static radiographic assessments.

Tumor Lung Visualization and Localization through Virtual Reality and Thermal Feedback Interface

The World Health Organization estimates that there were around 10 million deaths due to cancer in 2020, and lung cancer was the most common type of cancer, with over 2.2 million new cases and 1.8 million deaths. While there have been advances in the diagnosis and prediction of lung cancer, there is still a need for new, intelligent methods or diagnostic tools to help medical professionals detect the disease. Since it is currently unable to detect at an early stage, speedy detection and identification are crucial because they can increase a patient's chances of survival. This article focuses on developing a new tool for diagnosing lung tumors and providing thermal touch feedback using virtual reality visualization and thermal technology. This tool is intended to help identify and locate tumors and measure the size and temperature of the tumor surface. The tool uses data from CT scans to create a virtual reality visualization of the lung tissue and includes a thermal display incorporated into a haptic device. The tool is also tested by touching virtual tumors in a virtual reality application. On the other hand, thermal feedback could be used as a sensory substitute or adjunct for visual or tactile feedback. The experimental results are evaluated with the performance comparison of different algorithms and demonstrate that the proposed thermal model is effective. The results also show that the tool can estimate the characteristics of tumors accurately and that it has the potential to be used in a virtual reality application to "touch" virtual tumors. In other words, the results support the use of the tool for diagnosing lung tumors and providing thermal touch feedback using virtual reality visualization, force, and thermal technology.

Exhaled Aldehydes as Biomarkers for Lung Diseases: A Narrative Review

Breath analysis provides great potential as a fast and non-invasive diagnostic tool for several diseases. Straight-chain aliphatic aldehydes were repeatedly detected in the breath of patients suffering from lung diseases using a variety of methods, such as mass spectrometry, ion mobility spectrometry, or electro-chemical sensors. Several studies found increased concentrations of exhaled aldehydes in patients suffering from lung cancer, inflammatory and infectious lung diseases, and mechanical lung injury. This article reviews the origin of exhaled straight-chain aliphatic aldehydes, available detection methods, and studies that found increased aldehyde exhalation in lung diseases.

Identification of Dysregulated Mechanisms and Candidate Gene Markers in Chronic Obstructive Pulmonary Disease

Purpose

This study aimed to identify candidate gene markers that may facilitate chronic obstructive pulmonary disease (COPD) diagnosis and treatment.

Methods

The GSE47460 and GSE151052 datasets were analyzed to identify differentially expressed mRNAs (DEmRs) between COPD patients and controls. DEmRs that were differentially expressed in the same direction in both datasets were analyzed for functional enrichment and for coexpression. Genes from the largest three modules were tested for their ability to diagnose COPD based on the area under the receiver operating characteristic curve (AUC). Genes with AUC > 0.7 in both datasets were used to perform regression based on the "least absolute shrinkage and selection operator" in order to identify feature genes. We also identified differentially expressed miRNAs (DEmiRs) between COPD patients and controls using the GSE38974 dataset, then constructed a regulatory network. We also examined associations between feature genes and immune cell infiltration in COPD, and we identified methylation markers of COPD using the GSE63704 dataset.

Results

A total of 1350 genes differentially regulated in the same direction in the GSE47460 and GSE151052 datasets were found. The genes were significantly enriched in immune-related biological functions. Of 186 modules identified using MEGENA, the largest were C1_ 6, C1_ 3, and C1_ 2. Of the 22 candidate genes screened based on AUC, 11 feature genes emerged from analysis of a subset of GSE47460 data, which we validated using another subset of GSE47460 data as well as the independent GSE151052 dataset. Feature genes correlated significantly with infiltration by immune cells. The feature genes GPC4 and RS1 were predicted to be regulated by miR-374a-3p. We identified 117 candidate methylation markers of COPD, including PRRG4.

Conclusion

The feature genes we identified may be potential diagnostic markers and therapeutic targets in COPD. These findings provide new leads for exploring disease mechanisms and targeted treatments.