Search Results (1,369)

Background: The detection of circulating tumor cells (CTCs) holds significant promise for the diagnosis and monitoring of lung cancer (LC). However, the clinical utility of CTCs is limited by the heterogeneity of their phenotypes and the shortcomings of existing detection methods, which often rely on epithelial markers like EpCAM. DNA aptamers offer a promising alternative due to their high affinity, stability, and ability to recognize diverse cancer-specific biomarkers. Methods: This study utilized DNA aptamers LC-17 and LC-18, previously selected against primary lung tumor tissue, to isolate and detect CTCs in the peripheral blood of 43 non-small cell lung cancer (NSCLC) patients. Mass spectrometry (LC-MS/MS) was employed to identify the target proteins of aptamer LC-17. CTCs from patients’ blood and healthy donors were isolated via filtration after erythrocyte and lymphocyte lysis and stained with FAM-labeled LC-17 and LC-18 aptamers for detection using fluorescence and light microscopy. Results: Mass spectrometry identified neutrophil defensin 1 (DEFA1) and peroxiredoxin-2 (PRDX2) as the primary protein targets of aptamer LC-17 in CTCs, both of which were absent in healthy donor samples. CTC enumeration revealed statistically significant correlations between elevated CTC counts (>3 cells/4 mL blood) and advanced primary tumor size (T4 vs. T1–T3, p = 0.012), extensive regional lymph node metastasis (N3 vs. N1–N2, p = 0.014), and shorter overall survival (median 24 vs. 32 months, p < 0.05). Conclusions: The developed aptamer-based liquid biopsy method effectively captures heterogeneous CTC populations independent of EpCAM expression. The strong correlation of CTC counts with disease progression and survival underscores their clinical relevance as a prognostic biomarker in NSCLC. This approach presents a viable, non-invasive tool for disease monitoring and stratification of NSCLC patients, with potential for integration into clinical practice. Full article

Northern Thailand experiences annual haze events with fine particulate matter (PM2.5) exceeding standards, posing risks to schoolchildren. This cross-sectional study (Chiang Mai, 2024) evaluated respiratory impacts among primary school children aged 8–12 years. Daily mean PM2.5 concentrations were obtained from a single fixed-site monitoring station (36T) located within 2 km of the spirometry site. Among 93 children with acceptable spirometry, 52% exhibited restrictive, 18% obstructive, and 30% had normal function. After adjustment for BMI, males had significantly lower odds of any pulmonary abnormality than females (AOR = 0.084; 95% CI 0.017–0.417; p = 0.002). The mean FEV₁/FVC ratio was normal (86.30 ± 13.07%), whereas mean FVC, FEV₁, and PEF were significantly below predicted values, indicating a predominantly restrictive pattern. This predominance likely reflects cumulative exposure to biomass-burning related PM2.5 during the haze season, infiltration of outdoor PM2.5 into indoor environments alongside indoor sources, and the vulnerability of developing lungs in children’s factors that reduce lung volumes while largely preserving the FEV₁/FVC ratio. The exposure assessment provides pragmatic, proximity-based estimates but is limited by reliance on one station and one season, which may not capture spatial or temporal variability. These findings highlight sex-based susceptibility and support stronger air quality protections for children. Full article

Radon exposure is the second leading cause of lung cancer worldwide, yet monitoring strategies remain limited, expensive, and unevenly applied. Recent advances in the Internet of Things (IoT) offer the potential to change radon surveillance through low-cost, real-time, distributed sensing networks. This review consolidates emerging research on IoT-based radon monitoring, drawing from both primary radon studies and analogous applications in environmental IoT. A search across six major databases and relevant grey literature yielded only five radon-specific IoT studies, underscoring how new this research field is rather than reflecting a shortcoming of the review. To enhance the analysis, we delve into sensor physics, embedded system design, wireless protocols, and calibration techniques, incorporating lessons from established IoT sectors like indoor air quality, industrial safety, and volcanic gas monitoring. This interdisciplinary approach reveals that many technical and logistical challenges, such as calibration drift, power autonomy, connectivity, and scalability, have been addressed in related fields and can be adapted for radon monitoring. By uniting pioneering efforts within the broader context of IoT-enabled environmental sensing, this review provides a reference point and a future roadmap. It outlines key research priorities, including large-scale validation, standardized calibration methods, AI-driven analytics integration, and equitable deployment strategies. Although radon-focused IoT research is still at an early stage, current progress suggests it could make continuous exposure assessment more reliable, affordable, and widely accessible with clear public health benefits. Full article

Senescence is a dynamic, multifaceted process implicated in tissue aging, organ dysfunction, and intricately associated with numerous chronic diseases. As senescent cells accumulate, they drive inflammation, fibrosis, and metabolic disruption through the senescence-associated secretory phenotype (SASP). Despite its clinical relevance, senescence remains challenging to detect non-invasively due to its heterogeneous nature and the lack of universal biomarkers. Recent advances in the development of specific imaging probes for positron emission tomography (PET) enable in vivo visualization of senescence-associated pathways across key organs, such as the lung, heart, kidney, and metabolic processes. For instance, [¹⁸F]FPyGal, a β-galactosidase-targeted tracer, has demonstrated selective accumulation in senescent cells in both preclinical and early clinical studies, while FAP-targeted radioligands are emerging as tools for imaging fibrotic remodeling in the lung, liver, kidney, and myocardium. This review examines a new generation of PET radioligands targeting hallmark features of senescence, with the potential to track and measure the process, the ability to be translated into clinical interventions for early diagnosis, and longitudinal monitoring of senescence-driven pathologies. By integrating organ-specific imaging biomarkers with molecular insights, PET probes are poised to transform our ability to manage and treat age-related diseases through personalized approaches. Full article

Immune checkpoint inhibitors (ICIs) improve lung cancer prognosis but are associated with immune-related adverse events, most commonly thyroid dysfunction. While prior studies and guidelines have focused on thyroid dysfunction during ICI therapy, data on hypothyroidism and its monitoring after ICI therapy remain limited. We aimed to investigate hypothyroidism incidence and implementation of thyroid function monitoring after ICI therapy completion in patients with lung cancer. We conducted a retrospective observational study using the DeSC claims database of approximately 12 million individuals in Japan. Patients with lung cancer who received ICI therapy between April 2014 and August 2023 were included; those with a history of thyroid hormone replacement or insufficient follow-up were excluded. Among 6883 eligible patients, 277 (4.0%) developed hypothyroidism requiring hormone replacement post-ICI therapy completion (median onset, 67.0 d). Risk factors included ICI plus bevacizumab therapy and a history of myasthenia gravis, while steroid use for ≥28 d during ICI therapy lowered the risk. Post-ICI therapy completion thyroid monitoring was performed in 73.7% of patients, with test date distribution showing a median of 126.0 d and mode of 21.0 d. Hypothyroidism was frequently found to develop within 2 months post-ICI therapy completion, highlighting the need for continued thyroid monitoring and prospective studies to establish optimal surveillance strategies. Full article

Microphysiological systems (MPSs) have emerged as alternatives to animal testing in drug development, following the FDA Modernization Act 2.0. Double-layer channel-type MPS chips with porous membranes are widely used for modeling various organs, including the intestines, blood–brain barrier, renal tubules, and lungs. However, these chips faced challenges owing to optical interference caused by light scattering from the porous membrane, which hinders cell observation. Trans-epithelial electrical resistance (TEER) measurement offers a non-invasive method for assessing barrier integrity in these chips. However, existing electrode-integrated MPS chips for TEER measurement have non-uniform current densities, leading to compromised measurement accuracy. Additionally, chips made from polydimethylsiloxane have been associated with drug absorption issues. This study developed an electrode-integrated MPS chip for TEER measurement with a uniform current distribution and minimal drug absorption. Through a finite element method simulation, electrode patterns were optimized and incorporated into a polyethylene terephthalate (PET)-based chip. The device was fabricated by laminating PET films, porous membranes, and patterned gold electrodes. The chip’s performance was evaluated using a perfused Caco-2 intestinal model. TEER levels increased and peaked on day 5 when cells formed a monolayer, and then they decreased with the development of villi-like structures. Concurrently, capacitance increased, indicating microvilli formation. Exposure to staurosporine resulted in a dose-dependent reduction in TEER, which was validated by immunostaining, indicating a disruption of the tight junction. This study presents a TEER measurement MPS platform with a uniform current density and reduced drug absorption, thereby enhancing TEER measurement reliability. This system effectively monitors barrier integrity and drug responses, demonstrating its potential for non-animal drug-testing applications. Full article

A critical factor contributing to the burden of childhood asthma is the lack of effective self-management in homecare settings. Artificial intelligence (AI) and lung sound monitoring could help address this gap. Yet, existing AI-driven auscultation tools focus on wheeze detection and often rely on subjective human labels. To improve the early detection of asthma worsening in children in homecare setting, we trained and evaluated a Deep Learning model based on spirometry-labelled lung sounds recordings to detect asthma exacerbation. A single-center prospective observational study was conducted between November 2020 and September 2022 at a tertiary pediatric pulmonology department. Electronic stethoscopes were used to record lung sounds before and after bronchodilator administration in outpatients. In the same session, children also underwent spirometry, which served as the reference standard for labelling the lung sound data. Model performance was assessed on an internal validation set using receiver operating characteristic (ROC) curves. A total of 16.8 h of lung sound recordings from 151 asthmatic pediatric outpatients were collected. The model showed promising discrimination performance, achieving an AUROC of 0.763 in the training set, but performance in the validation set was limited (AUROC = 0.398). This negative result demonstrates that acoustic features alone may not provide sufficient diagnostic information for the early detection of asthma attacks, especially in mostly asymptomatic outpatients typical of homecare settings. It also underlines the challenges introduced by differences in how digital stethoscopes process sounds and highlights the need to define the severity threshold at which acoustic monitoring becomes informative, and clinically relevant for home management. Full article

Noninvasive liquid biopsy for monitoring circulating tumor cells offers valuable insights for predicting therapeutic responses. We developed TelomeScan^® (OBP-401), based on the detection of telomerase activity as a universal cancer cell marker and an indicator of the presence of viable circulating tumor cells (CTCs) for patients with advanced non-small cell lung cancer (NSCLC). This system evaluated CTC subtypes characterized by programmed death ligand 1 (PD-L1), an immune checkpoint molecule, and vimentin, an epithelial–mesenchymal transition (EMT) marker, using a multi-fluorescent color microscope reader. The prognostic value and therapeutic responses were predicted by dynamically monitoring CTC counts in 79 patients with advanced NSCLC. The sensitivity and specificity values of TelomeScan^® for PD-L1⁽⁺⁾ cells (≥1 cell) were 75% and 100%, respectively, indicating high diagnostic accuracy. PD-L1⁽⁺⁾ and EMT⁽⁺⁾ in CTCs were detected in 75% and 12% of patients, respectively. Detection of PD-L1⁽⁺⁾CTCs and PD-L1⁽⁺⁾EMT⁽⁺⁾ CTCs before treatment was associated with poor prognosis (p < 0.05). Monitoring of reducing and increasing PD-L1⁽⁺⁾ CTC counts in two sequential samples (baseline, cycle 2 treatment) correlated significantly with partial response (p = 0.032) and progressive disease (p = 0.023), respectively. Monitoring PD-L1⁽⁺⁾CTCs by TelomeScan^® will aid in anticipating responses or resistance to frontline treatments, optimizing precision medicine choices in patients with NSCLC. Full article

Background: Elevated serum IgE has been reported in severe COVID-19, suggesting that mast cell activation, allergic-like responses, and possible viral immune evasion occur. Objective: This study aimed to assess serum IgE, IgG, eosinophils, basophils, IL-10, and IL-33 in COVID-19 patients, and evaluate the infiltration of mast cells, basophils, and plasma cells in fatal cases. Methods: This retrospective study included 21 patients with severe COVID-19 or related respiratory conditions hospitalized in Plovdiv, Bulgaria (February 2020–May 2022). Serum immunoglobulins were quantified via immunoassays; IL-10 and IL-33 were also measured. Lung tissues from 30 autopsies were examined histologically and immunohistochemically using CD117 (mast cells) and CD138 (plasma cells). Results: Elevated IgE (>100 IU/mL) occurred in 10/21 patients, with two patients exhibiting levels exceeding 1000 IU/mL. High IgE correlated with reduced eosinophils and basophils, except in post-COVID lobar pneumonia. IL-10 was significantly increased, while IL-33 was reduced in acute and long COVID. Lung histology showed the accumulation of mast cells and plasma cells (5–20/field) during the diffuse alveolar damage and acute respiratory distress syndrome (ARDS) phases, but not in later fibrotic stages. Basophils are located near capillary basement membranes and the endothelium. Conclusions: SARS-CoV-2 may induce IgE-driven allergic-like mechanisms that contribute to severity. Monitoring IgE and mast cell activity may provide prognostic and therapeutic value, while elevated IgG4 could mitigate the effects of IgE. Full article

Background: Lung cancer remains the leading cause of cancer-related mortality globally, largely due to delayed diagnosis in its early stages. While conventional diagnostic tools like low-dose CT and tissue biopsy are routinely used, they suffer from limitations including invasiveness, radiation exposure, cost, and limited sensitivity for early-stage detection. Liquid biopsy, a minimally invasive alternative that captures circulating tumor-derived biomarkers such as ctDNA, cfRNA, and exosomes from body fluids, offers promising diagnostic potential—yet its sensitivity in early disease remains suboptimal. Recent advances in Artificial Intelligence (AI) and radiomics are poised to bridge this gap. Objective: This review aims to explore how AI, in combination with radiomics, enhances the diagnostic capabilities of liquid biopsy for early detection of lung cancer and facilitates personalized monitoring strategies. Content Overview: We begin by outlining the molecular heterogeneity of lung cancer, emphasizing the need for earlier, more accurate detection strategies. The discussion then transitions into liquid biopsy and its key analytes, followed by an in-depth overview of AI techniques—including machine learning (e.g., SVMs, Random Forest) and deep learning models (e.g., CNNs, RNNs, GANs)—that enable robust pattern recognition across multi-omics datasets. The role of radiomics, which quantitatively extracts spatial and morphological features from imaging modalities such as CT and PET, is explored in conjunction with AI to provide an integrative, multimodal approach. This convergence supports the broader vision of precision medicine by integrating omics data, imaging, and electronic health records. Discussion: The synergy between AI, liquid biopsy, and radiomics signifies a shift from traditional diagnostics toward dynamic, patient-specific decision-making. Radiomics contributes spatial information, while AI improves pattern detection and predictive modeling. Despite these advancements, challenges remain—including data standardization, limited annotated datasets, the interpretability of deep learning models, and ethical considerations. A push toward rigorous validation and multimodal AI frameworks is necessary to facilitate clinical adoption. Conclusion: The integration of AI with liquid biopsy and radiomics holds transformative potential for early lung cancer detection. This non-invasive, scalable, and individualized diagnostic paradigm could significantly reduce lung cancer mortality through timely and targeted interventions. As technology and regulatory pathways mature, collaborative research is crucial to standardize methodologies and translate this innovation into routine clinical practice. Full article

The persistent evolution of SARS-CoV-2 has led to the emergence of antigenically distinct Omicron subvariants exhibiting increased transmissibility, immune evasion, and altered pathogenicity. Among these, recent subvariants such as JN.1, KP.3.1.1, and LB.1 possess unique antigenic and virological features, underscoring the need for continued surveillance and therapeutic evaluation. As vaccines and commercial monoclonal antibodies show reduced effectiveness against these variants, the role of direct-acting antivirals, such as Nirmatrelvir, targeting conserved viral elements like the main protease inhibitor, becomes increasingly crucial. In this study, we investigated the replication kinetics, host immune responses, and therapeutic susceptibility of three recently circulating Omicron subvariants in the K18-hACE2 transgenic mouse model, using the SARS-CoV-2 parent WA1/2020 strain as a reference. Omicron subvariants exhibited a marked temporal shift in viral infection kinetics characterized by an early lung viral titer peak (~7–8 Log PFU) at 2 days post-infection (dpi), followed by a decline (1–3 Log PFU) by 4 dpi. Pulmonary cytokine and chemokine responses (GM-CSF, TNF-α, IL-1β, IL-6) showed an earlier increase in subvariant-infected mice compared to a gradual response in WA1/2020 infection. Notably, Nirmatrelvir treatment led to significant reductions in lung viral titers in subvariant-infected mice compared to WA1/2020, surpassing its efficacy against the parent strain. These findings highlight that infection with Omicron subvariants yields a broad dynamic range in viral burden with minimum variability, while retaining a prominent therapeutic response to Nirmatrelvir. This study provides insights into the emerging subvariants’ pathogenesis and therapeutic responsiveness, reinforcing the importance of continued variant monitoring and the development of effective countermeasures. Full article

Background: The COVID-19 pandemic prompted investigation into the interaction between SARS-CoV-2 infection and immune checkpoint inhibitor (ICI) therapy in lung cancer patients. Understanding this interplay is crucial for optimizing cancer immunotherapy. Methods: A retrospective analysis was conducted on lung cancer patients, characterizing changes in peripheral immune cells and plasma cytokines (including IL-10 and IL-12p70) before, during, and after SARS-CoV-2 infection. Progression-free survival (PFS) was compared between ICI-treated patients with and without COVID-19. Cytokine dynamics were further analyzed in a non-infected cohort. Results: SARS-CoV-2 infection induced a prolonged systemic cytokine storm, with elevated IL-10 and IL-12p70 levels and reduced monocyte proportions lasting up to 10 weeks post-recovery. Despite this immune perturbation, COVID-19 did not impair long-term PFS; instead, a transient improvement in disease control was observed in infected patients. In non-infected patients, sustained or increased IL-10 and IL-12p70 levels during ICI therapy were associated with longer PFS (p < 0.05). Conclusions: SARS-CoV-2 infection transiently alters the immune landscape in lung cancer patients without compromising ICI efficacy. The sustained elevation of IL-10 and IL-12p70 may contribute to short-term clinical benefits. Monitoring cytokine dynamics could serve as a prognostic tool for predicting ICI response. Full article

Respiratory infections and chronic lung disease are major contributors to morbidity in children. Aztreonam lysine for inhalation (AZLI) delivers high local antibiotic concentrations while limiting systemic exposure; however, its safety in younger patients remains uncertain. This systematic review and meta-analysis searched MEDLINE, CENTRAL, and Google Scholar for randomized and observational studies reporting adverse events in children and adolescents (≤18 years) receiving AZLI, with no date limit. Fourteen studies were included. Most studies were moderate-to-high quality. Comparative analysis showed no clinically relevant increase in common adverse events relative to placebo or other inhaled antibiotics. The pooled relative risk for severe respiratory disorders (grade 3/4) was 1.65 (95% CI 1.07–2.57), suggesting a higher incidence of serious respiratory events, while a protective effect against decline in pulmonary function was observed (RR 0.70, 95% CI 0.54–0.90). Adverse events were generally mild; serious adverse events and hospitalizations were infrequent and comparable between groups. Cumulative prevalence estimates indicated that respiratory irritation occurred in 10–25% of patients, whereas systemic effects were uncommon. Overall, AZLI appears to have an acceptable tolerability and safety profile in children and adolescents, though careful monitoring is warranted, especially for severe respiratory events. Full article

This study evaluates occupational exposure to respirable particulate matter (PM2.5) and crystalline silica (c-silica) among workers in five ceramic industries in Indonesia. Personal sampling revealed that 55.3% of workers were exposed to c-silica levels exceeding the Threshold Limit Value (TLV) of 50 µg/m³, with concentrations ranging from 1.5 to 1395.3 µg/m³. PM2.5 levels reached as high as 4152.4 µg/m³ in certain production zones. Health surveys identified frequent respiratory symptoms such as shortness of breath (27.1%) and chronic cough (14.6%), with 6.4% of workers showing lung abnormalities on chest X-rays. Risk assessments based on chronic daily intake (CDI), hazard quotient (HQ), and risk quotient (RQ) revealed that 63.8% of workers faced unsafe exposure, particularly those with longer job tenures, older age, and poor compliance with personal protective equipment (PPE). To mitigate risks, the study recommends engineering controls such as more local exhaust ventilation, improved PPE usage, and administrative measures including job rotation and regular health monitoring. These findings highlight the urgent need for improved occupational health strategies in silica-intensive industries and call for further research on long-term health impacts and effective intervention programs. Full article

Background/Objectives: A new multivalent vaccine (DIVENCE^® PENTA), containing Bovine viral diarrhoea virus (BVDV) types 1 and 2 recombinant proteins, live gE/tk double gene deleted Bovine Herpesvirus type 1 (BoHV-1 or IBR), live attenuated Bovine respiratory syncytial virus (BRSV) and inactivated parainfluenza-3 virus (PI-3) has been designed to protect cattle against the main viral pathogens associated with Bovine respiratory disease (BRD). The aim of this study was to demonstrate the efficacy of DIVENCE^® PENTA against experimental infections with BVDV-1, BVDV-2, IBR, BRSV and PI-3 in young calves. Methods: Ten-week-old calves were given two intramuscular doses three weeks apart. The efficacy was evaluated by means of an experimental challenge three weeks after vaccination. Serology, clinical signs, rectal temperature, white blood cell count, viral shedding and lung lesions were monitored after the challenge. Results/Conclusions: The results demonstrated a significant sparing of BRD in calves vaccinated with DIVENCE^® PENTA, as evidenced by fewer clinical signs, lower rectal temperatures, reduced viral shedding and less severe pulmonary lesions compared to control animals. A significant reduction in hyperthermia, leukopenia and viraemia post-challenge was also observed, highlighting the efficacy of the multivalent vaccine against BVDV types 1 and 2, IBR, BRSV and PI-3 in young calves. Full article