Search Results (531)

The use of immune checkpoint inhibitors (ICIs) has increased exponentially in recent years, leading to a significant impact on cancer patient survival. However, their administration can trigger immune-mediated adverse effects, notably pulmonary toxicity, which is a potentially serious complication. ICI-induced pneumonitis has a variable incidence ranging from 5 to 19% and usually appears in the first few months of treatment. The diagnosis requires a high index of suspicion, especially in patients with risk factors (elderly male smokers with squamous cell lung cancer, previous respiratory or autoimmune disease, and receiving combination treatment with other ICIs or chemo-radiotherapy). Chest computed tomography (CT) is a key test, allowing the identification of different radiological patterns. This study can be completed with bronchoscopy with bronchoalveolar lavage (BAL) to rule out infection or tumour progression. In general terms, treatment is based on discontinuing the causative drug, with or without the initiation of systemic corticosteroids, escalating to immunosuppressants depending on the severity and/or refractoriness of the condition. This paper provides an updated narrative review of ICI pulmonary toxicity, addressing its pathophysiology, different types of lung damage, diagnostic and therapeutic algorithms, and the emerging role of biomarkers such as KL-6 or IL-6. This article emphasises the need for a multidisciplinary approach and further prospective studies to optimise the management and prognosis of this immune-mediated complication. Full article

Interleukin-24 (IL-24) is a cytokine known for its role in immune regulation and apoptosis, with potential implications in viral infections like COVID-19. This study aimed to investigate the association between IL-24 serum levels and the severity of COVID-19 disease. In this prospective bi-center cross-sectional study, we enrolled 41 COVID-19 patients from two hospitals in Germany. Serial blood samples were collected from a subset of patients, resulting in 88 total blood samples. Patients were categorized into critical, severe, moderate, and mild disease groups based on WHO criteria. IL-24 serum levels were measured during the acute or convalescent phase using an ELISA assay. Inflammatory markers, and kidney and liver function parameters were also evaluated. Statistical analysis included non-parametric tests and correlation analysis. Elevated IL-24 serum levels were observed in ambulant patients (mild disease), compared to hospitalized patients (critical, severe, moderate disease, p < 0.05). IL-24 levels were also significantly higher in patients without oxygenation disorder compared to those with oxygenation therapy (p < 0.05). A negative correlation was found between IL-24 levels and markers of inflammation and liver/kidney function. Elevated IL-24 serum levels were associated with milder COVID-19 courses, suggesting a protective role in modulating immune responses and promoting antiviral apoptosis. Conversely, reduced IL-24 in severe cases may reflect impaired immune regulation, highlighting its potential as a biomarker and therapeutic target. Full article

Introduction: People who exercise outdoors in urban environments may inhale increased amounts of polluted air due to temporary respiratory changes induced by physical activity. The objective of this scoping review was to map the physiological, morphological, and/or functional responses of the respiratory system to air pollution in healthy adults who exercise outdoors in urban environments. Methods: This review was conducted following the guidelines of the Preferred Reporting Items Extension for Scoping Reviews (PRISMA-ScR). A comprehensive search of Medline (PubMed), Redalyc, Scielo, and Web of Science was conducted to identify clinical trials, quasi-experimental studies, and cross-sectional studies published in the last 10 years in English. Studies with healthy adult participants engaged in outdoor physical activity in urban environments were included. Texts with participants with preexisting respiratory diseases, elite athletes, animal models, and computer simulations were excluded. Results: The most frequently reported air pollutants were PM_2.5, PM₁₀, and ozone (O₃); the most common forms of exercise were walking, running, and cycling. Exposure to air pollutants during physical activity was associated with reductions in forced vital capacity (FVC) and forced expiratory volume in 1 second (FEV₁), as well as increases in the fraction of exhaled nitric oxide (FeNO) and proinflammatory biomarkers. Conclusion: The findings indicated that there are modifications in lung function in those who exercise outdoors. However, the association between these respiratory responses and air pollution was not statistically significant in most cases. Some authors suggested that the health benefits of physical activity could mitigate the harmful effects of air pollution. Full article

Background/Objectives: This study aimed to investigate the prevalence of liver damage and its associated non-invasive markers and echocardiographic risk factors in patients who underwent surgery for congenital heart disease. Methods: This retrospective observational study was conducted at a single tertiary-care university hospital in Niigata, Japan. Of 142 patients (ventricular septal defect [VSD] n = 47, tetralogy of Fallot [TOF] n = 67, Fontan n = 28), 52.8% were male [median age: 22.7 years; VSD (24.3 years), TOF (24.0 years), and Fontan (12.5 years)]. Pediatric patients with liver diseases unrelated to congestive liver disease, such as viral hepatitis and alcoholic liver disease, were excluded. We compared non-invasive liver fibrosis age-invariant biomarkers, such as the aspartate aminotransferase-to-platelet ratio index (APRI), and various serum markers and echocardiographic parameters to assess the prevalence and predictors of hepatic fibrosis. Results: The Fontan circulation group had the highest APRI, followed by the TOF group, while the VSD group had a low risk of APRI elevation. Postoperative TOF patients required monitoring for cirrhosis progression. Inferior vena cava mobility was associated with echocardiographic parameters and fibrosis severity, along with a loss of respiratory variability. The limitations of other cardiac assessments were highlighted by poor anatomical measurements. Gamma-glutamyl transpeptidase (γ-GTP) demonstrated strong discriminatory ability. The optimal cutoff value was 53.0 U/L, suggesting its use as a clinical marker. Conclusions: Assessing fibrosis is crucial in CHD patients, especially those with late post-TOF repair findings. Non-invasive markers (APRI, γ-GTP, and B-type natriuretic peptide), along with echocardiographic findings, may help detect fibrosis early, enabling timely intervention and improving long-term outcomes. Clinical trial registration: 2020-0199. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly recognized as a modulator of infection severity, yet its impact on the immune response in severe community-acquired pneumonia (sCAP) remains poorly understood. In this prospective cohort study of 108 adults with sCAP, we evaluated the prevalence and prognostic impact of MASLD and performed pathogen-stratified immune profiling of cytokines and semaphorins on hospital days 1 and 5. MASLD was present in 50% of patients and independently associated with early respiratory failure (OR 3.8) and vasopressor-dependent shock (OR 4.0), despite similar sCAP severity at baseline. MASLD patients exhibited distinct immune profiles, including elevated baseline serum levels of SEMA3A, SEMA7A, IL-2, IL-10, IL-17A, CXCL10, and TGF-β1, and reduced SEMA5A. By day 5, the MASLD group exhibited a greater decline in pro-inflammatory mediators compared to non-MASLD patients but failed to upregulate reparative mediators such as SEMA4D and TGF-β1, unlike the non-MASLD group. These kinetics may suggest a maladaptive immune response in MASLD, potentially consistent with early immune exhaustion. Immunokinetic patterns were pathogen-specific, including transient increase in IL-17A and IL-10 in Legionella and Mycoplasma infections, and CXCL10, IL-2, IL-17A, TGF-β1 and IL-10 in influenza. Serum IL-10, CXCL10, SEMA3F, SEMA4D and SEMA7A correlated with organ failure and sCAP complications. These findings underscore the clinical importance of the lung–liver axis and suggest that semaphorins could serve as valuable prognostic biomarkers for identifying high-risk patients. Full article

Amyotrophic lateral sclerosis (ALS) is still a heterogeneous neurodegenerative disorder that can be identified clinically and biologically, without a strong set of biomarkers that can adequately measure its fast rate of progression and molecular heterogeneity. In this review, we intend to consolidate the most relevant and timely advances in ALS biomarker discovery, in order to begin to bring molecular, imaging, genetic, and digital areas together for potential integration into a precision medicine approach to ALS. Our goal is to begin to display how several biomarkers in development (e.g., neurofilament light chain (NfL), phosphorylated neurofilament heavy chain (pNfH), TDP-43 aggregates, mitochondrial stress markers, inflammatory markers, etc.) are changing our understanding of ALS and ALS dynamics. We will attempt to provide a framework for thinking about biomarkers in a systematic way where our candidates are not signals alone but part of a tethered pathophysiological cascade. We are particularly interested in the fast progressor phenotype, a devastating and under-characterized subset of ALS due to a rapid axonal degeneration, early respiratory failure, and very short life span. We will try to highlight the salient molecular features of this ALS subtype, including SOD1 A5V toxicity, C9orf72 repeats, FUS variants, mitochondrial collapse, and impaired autophagy mechanisms, and relate these features to measurable blood and CSF (biomarkers) and imaging platforms. We will elaborate on several interesting tools, for example, single-cell transcriptomics, CSF exosomal cargo analysis, MRI techniques, and wearable sensor outputs that are developing into high-resolution windows of disease progression and onset. Instead of providing a static catalog, we plan on providing a conceptual roadmap to integrate biomarker panels that will allow for earlier diagnosis, real-time disease monitoring, and adaptive therapeutic trial design. We hope this synthesis will make a meaningful contribution to the shift from observational neurology to proactive biologically informed clinical care in ALS. Although there are still considerable obstacles to overcome, the intersection of a precise molecular or genetic association approach, digital phenotyping, and systems-level understandings may ultimately redefine how we monitor, care for, and treat this challenging neurodegenerative disease. Full article

Volatile organic compounds (VOCs) present in human exhaled breath have emerged as promising biomarkers for non-invasive disease diagnosis. However, traditional VOC detection technology that relies on large instruments is not widely used due to high costs and cumbersome testing processes. Machine learning-assisted gas sensor arrays offer a compelling alternative by enabling the accurate identification of complex VOC mixtures through collaborative multi-sensor detection and advanced algorithmic analysis. This work systematically reviews the advanced applications of machine learning-assisted gas sensor arrays in medical diagnosis. The types and principles of sensors commonly employed for disease diagnosis are summarized, such as electrochemical, optical, and semiconductor sensors. Machine learning methods that can be used to improve the recognition ability of sensor arrays are systematically listed, including support vector machines (SVM), random forests (RF), artificial neural networks (ANN), and principal component analysis (PCA). In addition, the research progress of sensor arrays combined with specific algorithms in the diagnosis of respiratory, metabolism and nutrition, hepatobiliary, gastrointestinal, and nervous system diseases is also discussed. Finally, we highlight current challenges associated with machine learning-assisted gas sensors and propose feasible directions for future improvement. Full article

Background/Objectives: The coronavirus disease 2019 (COVID-19) has more severe symptoms and increased mortality among men than women. To address the prognostic impact of vaccination, comorbidities, and inflammatory biomarkers on classified clinical outcomes in hospitalized COVID-19 patients, we compared common and sex differences. Methods: Besides laboratory and clinical parameters at hospital admission, we performed a common and sex-based comparative analysis for the clinical outcomes, RT-qPCR analyses, and measured severe acute respiratory syndrome coronavirus (SARS-CoV-2)-specific IgM and IgG antibody levels of 702 COVID-19 patients in a single centre from June 2020 to April 2022. Results: Pro-inflammatory biomarkers (C-reactive protein (CRP), interleukin-6 (IL-6), fibrinogen, lactate dehydrogenase (LDH), D-dimer, ferritin), and liver enzymes (AST, ALT, GGT) were significantly more increased in COVID-19 male patients and generally elevated with the severity of clinical outcome, regardless of the SARS-CoV-2 variant. Cycle threshold (Ct) values of RT-qPCR testing were in negative correlation with IL-6 in COVID-19 male patients, indicating that higher viral load largely increased IL-6 levels in parallel with the severity of clinical outcome and regardless of vaccination. IgG levels were higher in early post-COVID-19 male patients. Comorbidities were more frequent in COVID-19 female patients and generally more common in the severe clinical outcomes. Vaccination was negatively correlated with the severity of clinical outcome, liver enzymes, LDH, and inflammatory parameters in hospitalized COVID-19 patients, while the risk of pneumonia was reduced. Vaccination reduced the need for corticosteroid and anti-inflammatory therapies, but increased the need for antiviral drug treatment. Conclusions: In addition to confirming inflammatory biomarkers and the importance of anti-inflammatory therapy in vaccinated patients, this study showed that vaccination reduces, but does not prevent, mortality in patients with COVID-19. Full article

Background: Occupational bronchopulmonary diseases (OBPDs)—including pneumoconiosis, silicosis, and occupational COPD—remain a pressing public health issue, especially in regions with intensive mining, metallurgy, and construction industries. Caused by chronic inhalation of fibrogenic dusts, these conditions are often diagnosed at late stages, resulting in irreversible lung damage and diminished work capacity. Methods: A scoping review was performed using the Arksey and O’Malley framework, with methodological refinements from the Joanna Briggs Institute. Following PRISMA-ScR guidelines, we searched PubMed, Scopus, and gray literature for publications from 2014 to 2024. After screening 1761 records and full-text review, nine studies were included in the final synthesis, comprising two systematic reviews, two narrative literature reviews, and five observational studies. Results: Key risk factors identified included prolonged exposure to silica and coal dust, tobacco use, and genetic susceptibility. Diagnostic delays were attributed to the underuse of high-resolution CT and exhaled nitric oxide analysis. Several studies highlighted the diagnostic value of oxidative stress and inflammatory markers (e.g., IL-6, TNF-α). Nutritional rehabilitation and polyphenol-enriched herbal therapies were associated with improved respiratory function and quality of life. However, these strategies remain underutilized, particularly in low-resource settings. Conclusions: A coordinated, biomarker-driven approach integrating early diagnosis, dust exposure control, and tailored rehabilitation is urgently needed. Multidisciplinary models may reduce the clinical and socioeconomic burden of OBPDs. Full article

Asthma is a multifactorial respiratory disease that naturally occurs in horses, humans, and cats, presenting common clinical signs and species-specific mechanisms. This review addresses the impact of asthma on the cardiovascular and neurological systems, with a primary focus on horses. It highlights the need for new biomarkers beyond the respiratory system due to diagnostic difficulties in animals. A comprehensive literature search was conducted using PubMed and Google Scholar, focusing on cardiovascular and neurological manifestations of asthma in humans, horses, cats, and experimental animal models. Studies were qualitatively compared, noting species-specific differences and mechanisms. Humans with asthma show an increased risk of cardiovascular disease and elevated cardiac biomarkers during exacerbations, while horses develop pulmonary hypertension and vascular remodeling. Cats exhibit significant pulmonary vascular changes. Heart rate variability analysis reveals altered autonomic function in humans and horses. Increased peripheral airway innervation and cough reflex sensitivity are noted across species. The renin–angiotensin–aldosterone system (RAAS) plays a crucial role in asthma pathophysiology in murine models. Asthma impacts the cardiovascular and nervous systems differently across species, emphasizing the importance of comparative medicine. Future research should integrate cardiovascular, autonomic, and inflammatory pathways to develop effective therapeutic approaches in human and veterinary medicine, leveraging insights from naturally occurring asthma models. Full article

Motor Neuron Diseases (MNDs) such as Amyotrophic Lateral Sclerosis (ALS), Primary Lateral Sclerosis (PLS), Hereditary Spastic Paraplegia (HSP), Spinal Muscular Atrophy with Respiratory Distress Type 1 (SMARD1), Multisystem Proteinopathy (MSP), Spinal and Bulbar Muscular Atrophy (SBMA), and ALS associated to Frontotemporal Dementia (ALS-FTD), have traditionally been studied as distinct entities, each one with unique genetic and clinical characteristics. However, emerging research reveals that these seemingly disparate conditions converge on shared molecular mechanisms that drive progressive neuroaxonal degeneration. This narrative review addresses a critical gap in the field by synthesizing the most recent findings into a comprehensive, cross-disease mechanisms framework. By integrating insights into RNA dysregulation, protein misfolding, mitochondrial dysfunction, DNA damage, kinase signaling, axonal transport failure, and immune activation, we highlight how these converging pathways create a common pathogenic landscape across MNDs. Importantly, this perspective not only reframes MNDs as interconnected neurodegenerative models but also identifies shared therapeutic targets and emerging strategies, including antisense oligonucleotides, autophagy modulators, kinase inhibitors, and immunotherapies that transcend individual disease boundaries. The diagnostic and prognostic potential of Neurofilament Light Chain (NfL) biomarkers is also emphasized. By shifting focus from gene-specific to mechanism-based approaches, this paper offers a much-needed roadmap for advancing both research and clinical management in MNDs, paving the way for cross-disease therapeutic innovations. Full article

Pediatric asthma is a multifactorial and heterogeneous disease determined by the dynamic interplay of genetic susceptibility, environmental exposures, and immune dysregulation. Recent advances have highlighted the pivotal role of epigenetic mechanisms, in particular, DNA methylation, histone modifications, and non-coding RNAs, in the regulation of inflammatory pathways contributing to asthma phenotypes and endotypes. This review examines the role of respiratory viruses such as respiratory syncytial virus (RSV), rhinovirus (RV), and other bacterial and fungal infections that are mediators of infection-induced epithelial inflammation that drive epithelial homeostatic imbalance and induce persistent epigenetic alterations. These alterations lead to immune dysregulation, remodeling of the airways, and resistance to corticosteroids. A focused analysis of T2-high and T2-low asthma endotypes highlights unique epigenetic landscapes directing cytokines and cellular recruitment and thereby supports phenotype-specific aspects of disease pathogenesis. Additionally, this review also considers the role of miRNAs in the control of post-transcriptional networks that are pivotal in asthma exacerbation and the severity of the disease. We discuss novel and emerging epigenetic therapies, such as DNA methyltransferase inhibitors, histone deacetylase inhibitors, miRNA-based treatments, and immunomodulatory probiotics, that are in preclinical or early clinical development and may support precision medicine in asthma. Collectively, the current findings highlight the translational relevance of including pathogen-related biomarkers and epigenomic data for stratifying pediatric asthma patients and for the personalization of therapeutic regimens. Epigenetic dysregulation has emerged as a novel and potentially transformative approach for mitigating chronic inflammation and long-term morbidity in children with asthma. Full article

Introduction: Cystic fibrosis (CF) is a genetic condition affecting several organs and systems, including the pancreas, colon, respiratory system, and reproductive system. The detection of a growing number of CFTR variants and genotypes has contributed to an increase in the CF population which, in turn, has had an impact on the overall statistics regarding the prognosis and outcome of the condition. Given the increase in life expectancy, it is critical to better predict outcomes and prognosticate in CF. Thus, each person’s choice to aggressively treat specific disease components can be more appropriate and tailored, further increasing survival. The objective of our narrative review is to summarize the most recent information concerning the value and significance of clinical parameters in predicting outcomes, such as gender, diabetes, liver and pancreatic status, lung function, radiography, bacteriology, and blood and sputum biomarkers of inflammation and disease, and how variations in these parameters affect prognosis from the prenatal stage to maturity. Materials and methods: A methodological search of the available data was performed with regard to prognostic factors in the evolution of CF in children and young adults. We evaluated articles from the PubMed academic search engine using the following search terms: prognostic factors AND children AND cystic fibrosis OR mucoviscidosis. Results: We found that it is crucial to customize CF patients’ care based on their unique clinical and biological parameters, genetics, and related comorbidities. Conclusions: The predictive significance of more dynamic clinical condition markers provides more realistic future objectives to center treatment and targets for each patient. Over the past ten years, improvements in care, diagnostics, and treatment have impacted the prognosis for CF. Although genotyping offers a way to categorize CF to direct research and treatment, it is crucial to understand that a variety of other factors, such as epigenetics, genetic modifiers, environmental factors, and socioeconomic status, can affect CF outcomes. The long-term management of this complicated multisystem condition has been made easier for patients, their families, and physicians by earlier and more accurate identification techniques, evidence-based research, and centralized expert multidisciplinary care. Full article

Military personnel deployed to Iraq and Afghanistan were exposed to emissions from open-air burn pits, where plastics, metals, and medical waste were incinerated. These exposures have been linked to deployment-related respiratory diseases (DRRD) and may also impact neurological health via the lung–brain axis. To investigate molecular mechanisms, adult male rats were exposed to filtered air, naphthalene (a representative volatile organic compound), or a combination of naphthalene and carbon black (surrogate for particulate matter; CBN) via whole-body inhalation (six hours/day, three consecutive days). Lung, brain, and plasma samples were collected 24 h after the final exposure. Pro-inflammatory biomarkers were assessed using multiplex electrochemiluminescence and western blot. Differentially expressed genes (DEGs) were identified by RNA sequencing, and elastic net modeling was used to define exposure-predictive gene signatures. CBN exposure altered inflammatory biomarkers across tissues, with activation of nuclear factor kappa B (NF-κB) signaling. In the lung, gene set enrichment revealed activated pathways related to proliferation and inflammation, while epithelial–mesenchymal transition (EMT) and oxidative phosphorylation were suppressed. In the brain, EMT, inflammation, and senescence pathways were activated, while ribosomal function and oxidative metabolism were downregulated. Elastic net modeling identified a lung gene signature predictive of CBN exposure, including Kcnq3, Tgfbr1, and Tm4sf19. These findings demonstrate that inhalation of a surrogate burn pit mixture induces inflammatory and metabolic gene expression changes in both lung and brain tissues, supporting the utility of this animal model for understanding systemic effects of airborne military toxicants and for identifying potential biomarkers relevant to DRRD and Veteran health. Full article

Respiratory diseases represent a persistent global health challenge, underscoring the need for intelligent, accurate, and personalized diagnostic and therapeutic systems. Existing methods frequently suffer from limitations in diagnostic precision, lack of individualized treatment, and constrained adaptability to complex clinical scenarios. To address these challenges, our study introduces a modular AI-powered framework that integrates an audio-based disease classification model with simulated molecular biomarker profiles to evaluate the feasibility of future multimodal diagnostic extensions, alongside a synthetic-data-driven prescription recommendation engine. The disease classification model analyzes respiratory sound recordings and accurately distinguishes among eight clinical classes: bronchiectasis, pneumonia, upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), asthma, chronic obstructive pulmonary disease (COPD), bronchiolitis, and healthy respiratory state. The proposed model achieved a classification accuracy of 99.99% on a holdout test set, including 94.2% accuracy on pediatric samples. In parallel, the prescription module provides individualized treatment recommendations comprising drug, dosage, and frequency trained on a carefully constructed synthetic dataset designed to emulate real-world prescribing logic.The model achieved over 99% accuracy in medication prediction tasks, outperforming baseline models such as those discussed in research. Minimal misclassification in the confusion matrix and strong clinician agreement on 200 prescriptions (Cohen’s $\kappa$ = 0.91 [0.87–0.94] for drug selection, 0.78 [0.74–0.81] for dosage, 0.96 [0.93–0.98] for frequency) further affirm the system’s reliability. Adjusted clinician disagreement rates were 2.7% (drug), 6.4% (dosage), and 1.5% (frequency). SHAP analysis identified age and smoking as key predictors, enhancing model explainability. Dosage accuracy was 91.3%, and most disagreements occurred in renal-impaired and pediatric cases. However, our study is presented strictly as a proof-of-concept. The use of synthetic data and the absence of access to real patient records constitute key limitations. A trialed clinical deployment was conducted under a controlled environment with a positive rate of satisfaction from experts and users, but the proposed system must undergo extensive validation with de-identified electronic medical records (EMRs) and regulatory scrutiny before it can be considered for practical application. Nonetheless, the findings offer a promising foundation for the future development of clinically viable AI-assisted respiratory care tools. Full article