Current Respiratory Medicine Reviews (Volume 22 - Issue 2)

Asthma Pathogenesis: Clinical Expression, Molecular Mechanisms, and Risk Factors

2026-05-13

With variable airflow obstruction, bronchial hyperresponsiveness, and persistent inflammation, asthma is a chronic respiratory disorder characterized by its complex pathogenesis. This review further explores the complex pathogenesis of asthma by examining various clinical phenotypes, molecular mechanisms, and multifactorial risk factors. Asthma shows phenotypic heterogeneity clinically, often classified along immune profiles and biomarkers with eosinophilic and non-eosinophilic endotypes. At the molecular level, asthma is manifested as dysregulated immune responses, primarily Th2-mediated and, in some instances, Th17-mediated inflammation using cytokines IL-4, IL-5, IL-13, and IL-17. Furthermore, the airway remodelling layer, consisting of epithelial-mesenchymal transition, goblet cell hyperplasia, and subepithelial fibrosis, facilitates this progression. Genetic susceptibility, epigenetic changes, and alterations in gut microbiota contribute to immune dysregulation, while environmental triggers like allergens, pollutants, and infections worsen the disease. The genetic predisposition, environmental influences, and immune regulation are shown to be inextricably intertwined, emphasizing the need to use a phenotype- and endotype- based approach in the hope of providing better personalized care for asthma and saving the world from its burden.

Tobacco Dependence and Cessation in Rural India: Challenges, Strategies, and the Way Forward

2026-05-13

Tobacco use poses a serious health risk in rural India, where cessation support is limited. Although FDA-approved medications exist, access is hampered by low awareness and inadequate healthcare infrastructure. A comprehensive approach that includes raising awareness, expanding services, strengthening surveillance, and enforcing regulations is essential to curb nicotine depend-ence. Tailored interventions are needed to address usage patterns, particularly among vulnerable populations, and to reduce the public health burden.

Pulmonary Fibrosis: Causes, Development, Diagnosis, and Treatment with Emphasis on Murine and In vitro Models

2026-05-13

Excessive extracellular matrix accumulation characterizes pulmonary fibrosis (PF), a degenerative disease of the interstitial lung that worsens with time and leads to respiratory failure. The current review emphasizes the complicated etiology of PF, which includes environmental exposures, genetic predispositions, and concomitant conditions such as autoimmune diseases, followed by its pathophysiology, diagnosis, and treatment strategies. Murine models have significantly improved our understanding of the pathogenesis of PF. For example, studies of bleomycin-induced lung fibrosis in mice have improved our understanding of the inflammation-fibrosis nexus and revealed new treatment targets. Genetic animal models that lack certain cytokines or signaling pathways (e.g., TGF-γ, IL-13) have helped clarify the role of these mediators in fibrosis formation. In vitro studies with fibroblasts and lung epithelial cells have supplemented these findings by allowing for the analysis of cellular responses to fibrogenic stimuli as well as medication screening. The primary methods for diagnosing PF include histopathological exams, imaging examinations, and pulmonary function testing. New non-invasive biomarkers have the potential to improve early monitoring and identification. Antifibrotic drugs, as well as lung transplantation in severe cases, are the only therapy options available at this time. To improve outcomes for patients with pulmonary fibrosis, this review highlights the need for novel therapies that target key pathophysiological processes and are supported by preclinical models.

Artificial Intelligence: A Current and Updated Review of Repurposed Drugs for SARS-CoV-2

2026-05-13

Introduction: Expert systems are specific applications of artificial intelligence (AI) in pharmacy practice. This review explores various AI applications in optimizing pharmacotherapy using repurposed drugs for COVID-19 caused by SARS-CoV-2.

Methods: This is a focused literature review with keywords relevant to the terms used in PubMed, Scopus, and Web of Science. A total of 150 in-depth, relevant, and high-quality studies were reviewed in this study.

Results: Drug repositioning, reprofiling, or re-tasking could be used as an approach for recognizing new targets for accepted or tentative medications that were not initially approved or designated for COVID-19. The use of AI to optimize repurposed drugs for COVID-19 is a rapidly evolving and dynamic field, with new approaches and findings continually emerging. Future diagnosis and management could be expedited by AI assistance based on healthcare records and genetic data. In this direction, deep multi-layer recurrent neural networks, Random Forest (which combines the output of multiple decision trees to reach a single result), and the optimized distributed gradient boosting library (XGBoost) enable experienced medical workers to make predictions based on data.

Discussion: Methods based on AI could increase pharmacotherapy efficiency in different diseases. In the preliminary study, several repurposed drugs, such as ritonavir, lopinavir, ivermectin, remdesivir, and others, have emerged as effective treatment strategies.

Conclusion: Limitations in AI artifact development, precise instruction provisions, challenges in confirming interpretability, and concerns over time are obstacles to reliable AI-based outcomes for repurposed drugs in SARS-CoV-2 patients. Targeting multiple sites may be more effective because the mutability of RNA viruses can lead to drug resistance.

Systematic Review of Radiomics Applications in Small Cell Lung Cancer: Insights from Bibliometric Analysis and Research Frontiers

2026-05-13

Background: Radiomics has shown significant promise in Small Cell Lung Cancer (SCLC) research, yet trends and hotspots remain unclear. This bibliometric analysis identifies future research directions.

Method: Publications on radiomics in SCLC (2000-2025) were retrieved from Web of Science Core Collection. Bibliometrix, CiteSpace, and VOSviewer analyzed countries, institutions, authors, journals, keywords, and references.

Results: Analysis of 725 articles revealed marked growth over the past decade. China and the USA were the leading contributors. Institutionally, the University of Texas System was the top contributor, while Shanghai Jiao Tong University led in collaborations. Dekker Andre was the most published author. Frontiers in Oncology published the most articles; Magnetic Resonance Imaging was the most cited. Hotspots identified through keyword and co-citation analysis include radiomics, machine learning, feature selection, survival prediction, and tumor microenvironment.

Discussion: SCLC has the characteristics of strong invasiveness and poor prognosis. Radiomics uses artificial intelligence for preoperative diagnosis, efficacy assessment, prognosis prediction, and genotyping. Currently facing challenges such as sample scarcity, data heterogeneity, insufficient model generalization, and a lack of clinical translation standards. In the future, we need to focus on multimodal image fusion, deep feature mining for machine learning, gene regulatory network analysis, multi-center verification, and unified clinical standards. This study is limited to WoSCC English data, software analysis bias, and timeliness, and needs to be optimized later.

Conclusion: Radiomics enables early SCLC detection through integrative image-feature analysis. AI-assisted imaging diagnosis, personalized treatment, and prognostic prediction hold significant potential to enhance progression prediction accuracy and advance novel therapies.

A Meta-analysis of the Therapeutic Effects of Capsaicin in Patients with Chronic Cough

2026-05-13

Objective: This study aimed to assess the efficacy of inhaled topical capsaicin versus placebo in reducing cough frequency and cough sensitivity scores in patients with chronic cough. To address this objective, a systematic review and meta-analysis of randomized controlled trials (RCTs) were performed.

Methods: Web of Science, Embase, PubMed, Cochrane Library, CNKI, Weipu, and Wanfang were searched for RCTs evaluating capsaicin for the treatment of chronic cough. Studies were screened, their quality assessed, and data extracted; those that failed to meet the inclusion criteria were excluded. A systematic review and meta-analysis were then performed on the eligible studies.

Results: This meta-analysis was prospectively registered in PROSPERO. A total of five high-quality RCTs were included. Compared to the control group, there was a statistically significant reduction in cough frequency (Z=18.52, p < 0.00001, 95% CI: 2.09-2.59). Additionally, the difference in cough sensitivity scores was also statistically significant (Z=18.88, p < 0.00001, 95% CI: 1.33-1.65).

Discussion: While the results of this meta-analysis suggest that capsaicin may have a beneficial effect on chronic cough, the findings are limited by the small number of trials and the relatively small sample sizes included in the analysis.

Conclusion: Capsaicin represents a novel therapeutic strategy for chronic cough, suggesting it a non-traditional antitussive treatment. Further well-designed, large-scale randomized controlled trials are needed to confirm its efficacy, elucidate its long-term mechanisms, and support the development of standardized clinical guidelines.