Deep Airway Research Articles

Developing human upper, lower, and deep lung airway models: Combining different scaffolds and developing complex co-cultures

Advanced in vitro models are crucial for studying human airway biology. Our objective was the development and optimization of 3D in vitro models representing diverse airway regions, including deep lung alveolar region. This initiative was aimed at assessing the influence of selective scaffold materials on distinct airway co-culture models. While PET membranes (30 µm thickness) were unsuitable for alveolar models due to their stiffness and relatively high Young’s modulus, a combination of collagenous scaffolds seeded with Calu-3 cells and fibroblasts, showed increased mucus production going from week 1 to week 4 of air lift culture. Meanwhile standard electrospun polymer membrane (50–60 µm thick), which possesses a considerably low modulus of elasticity, offered higher flexibility and supported co-cultures of primary alveolar epithelial (huAEC) and endothelial cells (hEC) in concert with lung biopsy-derived fibroblasts which enhanced maturation of the tissue model. As published, designing human alveolar in vitro models require thin scaffold to mimic the required ultra-thin ECM, in addition to assuring right balanced AT1/AT2 ratio for biomimetic representation. We concluded that co-cultivation of primary/stem cells or cell lines has a higher influence on the function of the airway tissue models than the applied scaffolds.

Systematic Review: Effectiveness of Early Chest Physiotherapy in Preventing Postoperative Pulmonary Complications in Patients Undergoing Thoracic or Abdominal Surgery

Background: Postoperative pulmonary complications (PPCs) are a common concern in patients undergoing thoracic or abdominal surgery, contributing to increased morbidity, extended hospital stays, and elevated healthcare costs. Early initiation of chest physiotherapy (CPT) has been proposed as a strategy to reduce the incidence of PPCs by enhancing respiratory function through various techniques, such as deep breathing exercises, incentive spirometry, and airway clearance. Materials and Methods: This systematic review was conducted following PRISMA guidelines. A comprehensive search was performed across multiple databases, including PubMed, Cochrane Library, Embase, and Scopus, to identify studies assessing the effectiveness of early CPT in reducing PPCs. Studies were screened and selected based on predetermined inclusion criteria focusing on adults undergoing thoracic or abdominal surgery who received CPT within the first 24–48 hours postoperatively. Data extraction and quality assessments were conducted using standardized tools to evaluate study bias and reliability. Results: The review included 12 studies, comprising randomized controlled trials and observational studies. Most studies demonstrated that early CPT significantly reduces the incidence of PPCs, such as atelectasis and pneumonia, and improves lung function. However, the degree of effectiveness varied based on the CPT techniques and timing. Some studies highlighted reductions in hospital stay and ICU admissions, underscoring CPT's potential for improving overall surgical outcomes. Conclusion: Chest physiotherapy after induction of surgery seems to be an efficient method for the prevention of postoperative pulmonary complications in patients who underwent thoracic and abdominal surgery. The results provide evidence for integrating CPT into the postoperative care pathways but the differences in CPT application imply that individualized strategies should be used depending on the patient characteristics and types of surgery. More work needs to be done to support such gains and fine-tune CPT procedure.

Intraoral gunshot injury associated with soot in the deep airways

In suicidal gunshots to the head, the oral cavity ranks among the preferred entrance sites. If the weapon’s muzzle end is located within the mouth, it is to be expected that the cartridge discharge residues are deposited on the buccal and palatal mucosa, the tongue and the pharynx, often in combination with tears of the lips due to the expanding combustion gases. Ensuing from the bullet entrance wound and any concomitant injuries, blood is released into the upper airways and subsequently aspirated into the lung periphery provided that respiration continues for at least a short time. Evidently, this impedes the detection of additional soot deposits in the trachea, bronchi and alveoli. Using the example of an intraoral gunshot with a revolver cal. 357 Magnum, the paper points out that in individual cases it may be possible to prove the presence of gunshot residues in the deep airways.

Bloodless lung transplantation: Comparison between 2 central venoarterial extracorporeal membrane oxygenation anticoagulation strategies and their impact on lung transplant outcomes

ObjectiveTo report differences between 2 anticoagulation protocols during venoarterial extracorporeal membrane oxygenation (VA-ECMO) intraoperative support and their effects on outcomes after lung transplantation. MethodsWe performed a retrospective analysis of patients undergoing double-lung transplantation with intraoperative VA-ECMO from January 1, 2016, to December 30, 2023. Two distinct anticoagulation protocols were in place during this period. One included targeted activated clotting time >180 seconds at all times with protamine reversal after decannulation. The second included 75 units per kilogram of heparin at the time of cannulation with no redosing plus a tranexamic acid infusion after ECMO initiation. ResultsA total of 116 patients (46 low heparin, 70 standard) were included in the analysis. Cannulation strategies and ECMO circuit were equivalent between the groups. The low-dose heparin protocol group had a shorter surgical time (7.28 hours vs 8.53 hours, P < .001) and required significantly less intraoperative packed red blood cells (median 0 vs 4.37 units, P < .001), fresh-frozen plasma (median 0 vs 2 units, P < .001), platelets (median 0 vs 1 units, P < .001), cryoprecipitate (median 0 vs 0 units, P < .001), and total blood products (median 0 vs 9 units, P < .001) compared with the standard group. There were no differences in rates of deep vein thrombosis (P = .13), airway dehiscence (P > .99), pneumonia (P = .38), or acute kidney injury requiring renal-replacement therapy (P = .59). There was no difference in rates of severe grade 3 primary graft dysfunction at 72 hours after transplant (P = .42). ConclusionsOur low-dose heparin VA-ECMO protocol for intraoperative support during lung transplantation led to a significant reduction of blood product use. Although this did not translate to a reduced rates of grade 3 primary graft dysfunction, the low-dose heparin protocol was associated with similar postoperative outcomes.

Accuracy of deep learning-based upper airway segmentation

IntroductionIn orthodontic treatments, accurately assessing the upper airway volume and morphology is essential for proper diagnosis and planning. Cone beam computed tomography (CBCT) is used for assessing upper airway volume through manual, semi-automatic, and automatic airway segmentation methods. This study evaluates upper airway segmentation accuracy by comparing the results of an automatic model and a semi-automatic method against the gold standard manual method. Materials and methodsAn automatic segmentation model was trained using the MONAI Label framework to segment the upper airway from CBCT images. An open-source program, ITK-SNAP, was used for semi-automatic segmentation. The accuracy of both methods was evaluated against manual segmentations. Evaluation metrics included Dice Similarity Coefficient (DSC), Precision, Recall, 95% Hausdorff Distance (HD), and volumetric differences. ResultsThe automatic segmentation group averaged a DSC score of 0.915±0.041, while the semi-automatic group scored 0.940±0.021, indicating clinically acceptable accuracy for both methods. Analysis of the 95% HD revealed that semi-automatic segmentation (0.997±0.585) was more accurate and closer to manual segmentation than automatic segmentation (1.447±0.674). Volumetric comparisons revealed no statistically significant differences between automatic and manual segmentation for total, oropharyngeal, and velopharyngeal airway volumes. Similarly, no significant differences were noted between the semi-automatic and manual methods across these regions. ConclusionIt has been observed that both automatic and semi-automatic methods, which utilise open-source software, align effectively with manual segmentation. Implementing these methods can aid in decision-making by allowing faster and easier upper airway segmentation with comparable accuracy in orthodontic practice.

An individualised 3D computational flow and particle model to predict the deposition of inhaled medicines — A case study using a nebuliser

Background and objective: Drug inhalation is generally accepted as the preferred administration method for treating respiratory diseases. To achieve effective inhaled drug delivery for an individual, it is necessary to use an interdisciplinary approach that can cope with inter-individual differences. The paper aims to present an individualised pulmonary drug deposition model based on Computational Fluid and Particle Dynamics simulations within a time frame acceptable for clinical use. Methods:We propose a model that can analyse the inhaled drug delivery efficiency based on the patient’s airway geometry as well as breathing pattern, which has the potential to also serve as a tool for a sub-regional diagnosis of respiratory diseases. The particle properties and size distribution are taken for the case of drug inhalation by using nebulisers, as they are independent of the patient’s breathing pattern. Finally, the inhaled drug doses that reach the deep airways of different lobe regions of the patient are studied. Results:The numerical accuracy of the proposed model is verified by comparison with experimental results. The difference in total drug deposition fractions between the simulation and experimental results is smaller than 4.44% and 1.43% for flow rates of 60 l/min and 15 l/min, respectively. A case study involving a COVID-19 patient is conducted to illustrate the potential clinical use of the model. The study analyses the drug deposition fractions in relation to the breathing pattern, aerosol size distribution, and different lobe regions. Conclusions:The entire process of the proposed model can be completed within 48 h, allowing an evaluation of the deposition of the inhaled drug in an individual patient’s lung within a time frame acceptable for clinical use. Achieving a 48-hour time window for a single evaluation of patient-specific drug delivery enables the physician to monitor the patient’s changing conditions and potentially adjust the drug administration accordingly. Furthermore, we show that the proposed methodology also offers a possibility to be extended to a detection approach for some respiratory diseases.

Assessing the impact of a respiratory care bundle on health status and quality of life of chronic obstructive pulmonary disease patients in Jordan: A quasi-experimental study.

This study aimed to evaluate the effectiveness of a respiratory care bundle, including deep breathing exercises, incentive spirometry, and airway clearance techniques, on the quality of life (QoL) of chronic obstructive pulmonary disease (COPD) patients in Jordan. A quasi-experimental study design and convenience sampling method was used to recruit 120 COPD patients, with 54 in the intervention group and 66 in the control group. The intervention group received additional respiratory care bundle training, while the control group received only discharge instructions and an education program. The St. George's Respiratory Questionnaire (SGRQ-C) was used to assess participants' QoL before and after the intervention. Independent t-tests, paired t-tests, and analysis of covariance (ANCOVA) analysis were used to analyze the data. The study found no significant differences between patients' characteristics, health status, and SGRQ-C scores between the two groups at baseline. After the intervention, there were statistically significant differences in all SGRQ-C subscales, which were lower in the intervention group compared to the control group. The paired t-test showed significant reductions in all SGRQ-C symptoms components (t = 7.62, P < .001), activity component (t = 7.58, P < .001), impact component (t = 7.56, P < .001), and total scores post-intervention (t = 7.52, P < .001) for the intervention group. The ANCOVA analysis showed significant differences in scores of SGRQ-C components and total scores (f = 11.3, P < .001) post-intervention between the two groups. The study's findings suggest that providing additional respiratory care bundle training for COPD patients can significantly improve their QoL, as measured by the SGRQ-C scores. The respiratory care bundle intervention was effective in reducing COPD symptoms and improving the QoL of COPD patients. Healthcare providers should consider implementing respiratory care bundles as part of COPD management to improve patients' outcomes.

CFPD-PK simulation of inhaled Delta-9-tetrahydrocannabinol aerosol dynamics: Transport, deposition, and translocation in a mouth-to-G10 subject-specific human airway

Medical cannabis is increasingly used as an alternative therapy for various conditions, including chronic pain, multiple sclerosis, epilepsy, and cancer-related symptoms. However, it is crucial to ensure that patients receive the intended dose of tetrahydrocannabinol (THC) from inhaled cannabis for optimal therapeutic effect without overdose risk. This requires a comprehensive understanding of the factors that influence the pharmacokinetics (PKs) of THC in the respiratory system. However, accurate estimation of lung dosimetry and blood concentration of inhaled THC remains challenging partially because the influence of diversified patient-specific puff patterns on inhaled THC transport, deposition, and translocation is still not well quantified. To address the knowledge gap mentioned above, this study employed a hybrid computational fluid-particle dynamics (CFPD) and PK model to evaluate factors that influence delivered doses of THC to the human respiratory system and the resultant THC-plasma concentration-time profile. Specifically, this study compared multiple puff waveforms for inhalation-holding-exhalation (IHE) with total puff volumes from 55 to 82 ml for 2 or 3 s, hold durations from 0 to 5 s, and three puff waveforms (i.e., square, sinusoidal, and realistic). THC deposition in the airways was recorded during all phases for each case using either 452,849 particles per second for the 1.128-μm monodisperse cases or 399,866 particles per second for the polydisperse cases, with the mass median aerodynamic diameter (MMAD) of 1.128 μm. Pulmonary air-THC particle flow transport dynamics, THC particle deposition data, and THC vapor absorption were predicted using CFPD for four airway regions, then scaled by region-specific bioavailability factors. The deposited THC mass in airway regions represents the initial mass entering a 3-compartment PK model, to predict the THC-plasma concentration-time profiles. The CFPD-PK results revealed significant variability in THC transport, deposition, and plasma concentration based on IHE factors. Specifically, larger puff volumes and longer holding times enhanced THC deposition in deeper airways and increased THC-plasma concentrations. Realistic transient puff waveforms predicted higher particle deposition and THC-plasma concentrations than simplified square waveforms. Polydisperse particle distributions show more realistic deposition patterns than monodisperse particle simulations. This study provides insights into the complexity of THC inhalation therapy, emphasizing the importance of considering individualized puff patterns and realistic particle size distributions in accurately predicting therapeutic outcomes, which is highly related to THC deposition in the lung and THC plasma concentration. These findings and the CFPD-PK modeling framework offer guidance for clinicians in prescribing personalized THC dosages, support regulatory science in evaluating inhalation devices, and contribute to ongoing research aimed at optimizing THC delivery for maximum therapeutic effectiveness while minimizing potential overdose risks.

Treatment of infantile hemangioma with topical β-blockers in pediatric practice: a review of the literature

The purpose of this review is to acquaint the audience with the benefits of infantile hemangioma (IH) treatment with local β-blockers, which are safe for the child, allow for the complete cure of hemangiomas without surgery, complications, scars, and cosmetic defects, and have practically no systemic side effects. We aimed to analyze the effectiveness and limitations of the use of local β-blockers, to show the possibility and expediency of IH management in pediatric practice, and to demonstrate that the goal of therapy is not the treatment of complications, but the prevention of their occurrence and complete resolution of the hemangioma without surgical intervention. The use of topical β-blockers, such as timolol gel or solution, provides a non-surgical, non-invasive treatment option for IH, minimizing the systemic exposure and possible side effects associated with oral β-blockers. Local treatment is best started before the age of 2 months - at an early stage, when IHs are small in size, potentially preventing the need for more invasive treatment methods. Topical use is associated with a lower risk of systemic side effects, such as hypotension or bradycardia, that can occur with oral β-blockers. Topical treatment can be applied at home, which can be more convenient for parents and caregivers, and also increases the opportunity for treatment and follow-up by pediatricians. In case of natural disasters or military operations, treatment can be done remotely using teledermatology. The effectiveness of local β-blockers mostly depends on the age at which treatment was started: the earlier it was started, the higher the effectiveness. Treatment of complicated IH with deep soft tissue, mucosal, or airway involvement usually requires a combination of systemic propranolol and topical β-blockers or other interventions such as laser therapy. The choice of treatment should be selected individually according to the degree of risk of IH, its size, localization, child's age, weight, and other parameters in each clinical case. β-adrenoblockers are the most modern, effective, non-surgical, and safe method of treating IH, they can be used both for systemic and local application. IH can be successfully treated by pediatricians and dermatologists. No conflict of interests was declared by the authors.

Etiologic characteristics revealed by mNGS-mediated ultra-early and early microbiological identification in airway secretions from lung transplant recipients.

Post-operative etiological studies are critical for infection prevention in lung transplant recipients within the first year. In this study, mNGS combined with microbial culture was applied to reveal the etiological characteristics within one week (ultra-early) and one month (early) in lung transplant recipients, and the epidemiology of infection occurred within one month. In 38 lung transplant recipients, deep airway secretions were collected through bronchofiberscope within two hours after the operation and were subjected to microbial identification by mNGS and microbial culture. The etiologic characteristics of lung transplant recipients were explored. Within one month, the infection status of recipients was monitored. The microbial species detected by mNGS were compared with the etiological agents causing infection within one month. The detection rate of mNGS in the 38 airway secretions specimens was significantly higher than that of the microbial culture (P<0.0001). MNGS identified 143 kinds of pathogenic microorganisms; bacterial pathogens account for more than half (72.73%), with gram-positive and -negative bacteria occupying large proportions. Fungi such as Candida are also frequently detected. 5 (50%) microbial species identified by microbial culture had multiple drug resistance (MDR). Within one month, 26 (68.42%) recipients got infected (with a median time of 9 days), among which 10 (38.46%) cases were infected within one week. In the infected recipients, causative agents were detected in advance by mNGS in 9 (34.62%) cases, and most of them (6, 66.67%) were infected within one week (ultra-early). In the infection that occurred after one week, the consistency between mNGS results and the etiological agents was decreased. Based on the mNGS-reported pathogens in airway secretions samples collected within two hours, the initial empirical anti-infection regimes covering the bacteria and fungi are reasonable. The existence of bacteria with MDR forecasts the high risk of infection within 48 hours after transplant, reminding us of the necessity to adjust the antimicrobial strategy. The predictive role of mNGS performed within two hours in etiological agents is time-limited, suggesting continuous pathogenic identification is needed after lung transplant.

A Deep Attention-based U-Net for Airways Segmentation in Computed Tomography Images.

Airway segmentation is a way to quantify the diagnosis of pulmonary diseases, including chronic obstructive problems and bronchiectasis. Manual analysis by radiologists is a challenging task due to the complex airway structure. Additionally, tree-like patterns, varied shapes, sizes, and intensity make the manual airway segmentation task more complex. Deeper airways are even more difficult to segment as their intensity starts matching the lung parenchyma as the diameter of the airway cross-section gets reduced. Many earlier works have proposed different deep learning networks for airway segmentation but were unable to achieve the desired performance; hence the task of airway segmentation still possesses challenges in this field. This work proposes a convolutional neural network based on deep U-Net architecture and employs an attention block technique for airway segmentation. The attention mechanism aids in the extraction of the complicated and multi-sized airways found in the lung region, hence increasing the efficiency of the U-Net architecture. The model has been validated using VESSEL12 and EXACT09 datasets, individually and combined, with and without trachea images. The best DSC scores on EXACT09 and VESSEL12 datasets are 95.21% and 95.80%, respectively. The performance on both datasets combined gave a DSC score of 94.1%, showing that the overall performance of the proposed methodology is quite satisfactory. The generalizability of the model is also confirmed using k-fold cross-validation. The comparison of the proposed model to existing research on airway segmentation found competitive results. The use of an attention unit in the proposed model highlights the relevant information and reduces the irrelevant features, which helps to improve the performance and saves time.

Effects of PM2.5 Exposure on the ACE/ACE2 Pathway: Possible Implication in COVID-19 Pandemic.

Particulate matter (PM) is a harmful component of urban air pollution and PM2.5, in particular, can settle in the deep airways. The RAS system plays a crucial role in the pathogenesis of pollution-induced inflammatory diseases: the ACE/AngII/AT1 axis activates a pro-inflammatory pathway counteracted by the ACE2/Ang(1-7)/MAS axis, which in turn triggers an anti-inflammatory and protective pathway. However, ACE2 acts also as a receptor through which SARS-CoV-2 penetrates host cells to replicate. COX-2, HO-1, and iNOS are other crucial proteins involved in ultrafine particles (UFP)-induced inflammation and oxidative stress, but closely related to the course of the COVID-19 disease. BALB/c male mice were subjected to PM2.5 sub-acute exposure to study its effects on ACE2 and ACE, COX-2, HO-1 and iNOS proteins levels, in the main organs concerned with the pathogenesis of COVID-19. The results obtained show that sub-acute exposure to PM2.5 induces organ-specific modifications which might predispose to greater susceptibility to severe symptomatology in the case of SARS-CoV-2 infection. The novelty of this work consists in using a molecular study, carried out in the lung but also in the main organs involved in the disease, to analyze the close relationship between exposure to pollution and the pathogenesis of COVID-19.

Exploring pulmonary distribution of intratracheally instilled liquid foams in excised porcine lungs

The applicability of inhalation therapy to some severe pulmonary conditions is often compromised by limited delivery rates (i.e. total dose) and low deposition efficiencies in the respiratory tract, most notably in the deep pulmonary acinar airways. To circumvent such limitations, alternative therapeutic techniques have relied for instance on intratracheal liquid instillations for the delivery of high-dose therapies. Yet, a longstanding mechanistic challenge with such latter methods lies in delivering solutions homogeneously across the whole lungs, despite an inherent tendency of non-uniform spreading driven mainly by gravitational effects. Here, we hypothesize that the pulmonary distribution of instilled liquid solutions can be meaningfully improved by foaming the solution prior to its instillation, owing to the increased volume and the reduced gravitational bias of foams. As a proof-of-concept, we show in excised adult porcine lungs that liquid foams can lead to significant improvement in homogenous pulmonary distributions compared with traditional liquid instillations. Our ex-vivo results suggest that liquid foams can potentially offer an attractive novel pulmonary delivery modality with applications for high-dose regimens of respiratory therapeutics.

Advanced formulations and nanotechnology-based approaches for pulmonary delivery of sildenafil: A scoping review.

Oral sildenafil (SDF) is used to treat pulmonary arterial hypertension (PAH), and its bioavailability is approximately 40%. Several formulations of nano and microparticles (for pulmonary delivery) are being developed because it is possible to improve characteristics such as release time, bioavailability, dose, frequency, and even directly target the drug to the lungs. This review summarizes the latest SDF drug delivery systems for PAH and explains challenges related to the development, the preclinical, and the clinical studies. A scoping review was conducted by searching electronic databases including PubMed, Scopus, and Web of Science to identify studies published between 2001 and 2021. From 300 articles found, 31 met the inclusion criteria. This review identified colloidal formulations such as polymeric, lipid, and metal-organic framework nanoparticles. Strategies were determined to reach the deep airways such as polymeric microparticles, large porous microparticles, nanocomposites, and nano in microparticles. Finally, aspects related to toxicological, pharmacokinetics, and gaps in information for potential use in humans were discussed. SDF formulations are significant candidates for the treatment of PAH by inhalation. In summation, future preclinical studies are still required in large animals, as there is no particular formulation yet submitted to clinical studies.

Artificial Intelligence Techniques to Predict the Airway Disorders Illness: A Systematic Review.

Airway disease is a major healthcare issue that causes at least 3 million fatalities every year. It is also considered one of the foremost causes of death all around the globe by 2030. Numerous studies have been undertaken to demonstrate the latest advances in artificial intelligence algorithms to assist in identifying and classifying these diseases. This comprehensive review aims to summarise the state-of-the-art machine and deep learning-based systems for detecting airway disorders, envisage the trends of the recent work in this domain, and analyze the difficulties and potential future paths. This systematic literature review includes the study of one hundred fifty-five articles on airway diseases such as cystic fibrosis, emphysema, lung cancer, Mesothelioma, covid-19, pneumoconiosis, asthma, pulmonary edema, tuberculosis, pulmonary embolism as well as highlights the automated learning techniques to predict them. The study concludes with a discussion and challenges about expanding the efficiency and machine and deep learning-assisted airway disease detection applications.

Analysis of volatile organic compounds from deep airway in the lung through intubation sampling.

Exhaled volatile organic compounds (VOCs) have been widely applied for the study of disease biomarkers. Oral exhalation and nasal exhalation are two of the most common sampling methods. However, VOCs released from food residues and bacteria in the mouth or upper respiratory tract were also sampled and usually mistaken as that produced from body metabolism. In this study, exhalation from deep airway was first directly collected through intubation sampling and analyzed. The exhalation samples of 35 subjects were collected through a catheter, which was inserted into the trachea or bronchus through the mouth and upper respiratory tract. Then, the VOCs in these samples were detected by proton transfer reaction mass spectrometry (PTR-MS). In addition, fast gas chromatography proton transfer reaction mass spectrometry (FGC-PTR-MS) was used to further determine the VOCs with the same mass-to-charge ratios. The results showed that there was methanol, acetonitrile, ethanol, methyl mercaptan, acetone, isoprene, and phenol in the deep airway. Compared with that in oral exhalation, ethanol, methyl mercaptan, and phenol had lower concentrations. In detail, the median concentrations of ethanol, methyl mercaptan, and phenol were 7.3, 0.6, and 23.9 ppbv, while those in the oral exhalation were 80.0, 5.1, and 71.3 ppbv, respectively, which meant the three VOCs mainly originated from the food residues and bacteria in the mouth or upper respiratory tract, rather than body metabolism. The research results in our study can provide references for expiratory VOC research based on oral and nasal exhalation samplings, which are more feasible in clinical practice.

Strategies to fight COVID-19: Beyond the difference between SARS-CoV-2 and Influenza virus

Background: Since the outbreak of COVID-19 emerged in Wuhan, China, in December 2019, the epidemic has spread worldwide and posed a great threat to society. Despite great achievements in COVID-19 research, few studies have focused on the similarities and differences between SARS-CoV-2 and influenza viruses. Results: Through a review of the literature on SARS-CoV-2 and influenza viruses, we found that influenza occurs every year, and influenza pandemics occur irregularly. The uncomplicated human influenza viruses primarily affect the larger airways and rarely the alveoli. However, SARS-CoV-2 mainly involves the deep airways and lungs and can cause DAD, leading to severe hypoxemia. In general, SARS-CoV-2 is no less infectious than the influenza virus. However, its destructive power to the lungs is no less than the avian influenza virus. There is currently no clinical vaccine and specific inhibitor against SARS-CoV-2. Conclusions: SASR-CoV-2 damages lung function more severely than the influenza virus, with higher morbidity, mortality, and severe disease rates. Controlling the source of infection, cutting off the route of transmission, and protecting susceptible populations are critical to the fight against SARS-CoV-2.

Do we really target the receptors? Deposition and co-deposition of ICS-LABA fixed combination drugs

Fixed dose combinations of aerosolized bronchodilators and steroids are routinely used in current asthma and COPD management. As spatial distribution of their receptors within the human airways is different, it is a challenging task to deliver the right drug component to the right receptor. The aim of this work was to apply numerical methods to analyse the airway deposition distribution of two inhalation corticosteroid (ICS) – long-acting beta-agonist (LABA) combination drugs in comparison with the distribution of the corresponding receptors. Our results revealed that different combination drugs exhibit different co-deposition patterns depending on the aerodynamic properties of their components. While ICS and LABA components of Symbicort® Turbuhaler® had similar deposition efficiencies in the same airway generation throughout the whole respiratory tract, the steroid component of Relvar® Ellipta® had up to 25% higher deposition than its bronchodilator component in the large bronchi and up to 40% lower deposition in the deeper airways. Present results highlight the need for extensive research to elucidate whether each drug component should deposit according to its receptor distribution or similar deposition distribution patterns of the components should be attained to benefit from the synergistic effects documented in the open literature. Once this aspect clarified, the next step will be to tailor the aerodynamic properties of each component of combination drugs to yield the desired deposition distribution in the lungs.

Exhaled breath condensate (EBC) for SARS-CoV-2 diagnosis still an open debate

The real-time PCR (RT-PCR) on nasopharyngeal swabs (NPS) is the gold standard for the diagnosis of SARS-CoV-2. The exhaled breath condensate (EBC) is used to perform collection of biological fluid condensed in a refrigerated device from deep airways’ exhaled air. We aimed to verify the presence of SARS-CoV-2 virus in the EBC from patients with confirmed SARS-CoV-2 infection by RT-PCR, and to determine if the EBC may represent a valid alternative to the NPS. Seventeen consecutive patients admitted to the Emergency Department of the Policlinico were enrolled in the present study with RT-PCR, clinical and radiological evidence of SARS-CoV-2. Within 24 h from the NPS collection the EBC collection was performed on SARS-CoV-2 positive patients. Informed written consent was gathered and the Ethic Committee approved the study. The mean age of patients was 60 years (24–92) and 64.7% (11/17) were male. Patient n.9 and n.17 died. All NPS resulted positive for SARS-CoV-2 at RT-PCR. RT-PCR on EBC resulted negative for all but one patients (patient n.12). In this study we did not find any correlation between positive NPS and the EBC in all but one patients enrolled. Based on these data which greatly differ from previous reports on the topic, this study opens several questions related to small differences in the complex process of EBC collection and how EBC could be really standardized for the diagnosis of SARS-CoV-2 infection. Further studies will be warranted to deepen this topic.

Revisiting Airflow and Aerosol Transport Phenomena in the Deep Lungs with Microfluidics.

The dynamics of respiratory airflows and the associated transport mechanisms of inhaled aerosols characteristic of the deep regions of the lungs are of broad interest in assessing both respiratory health risks and inhalation therapy outcomes. In the present review, we present a comprehensive discussion of our current understanding of airflow and aerosol transport phenomena that take place within the unique and complex anatomical environment of the deep lungs, characterized by submillimeter 3D alveolated airspaces and nominally slow resident airflows, known as low-Reynolds-number flows. We exemplify the advances brought forward by experimental efforts, in conjunction with numerical simulations, to revisit past mechanistic theories of respiratory airflow and particle transport in the distal acinar regions. Most significantly, we highlight how microfluidic-based platforms spanning the past decade have accelerated opportunities to deliver anatomically inspired in vitro solutions that capture with sufficient realism and accuracy the leading mechanisms governing both respiratory airflow and aerosol transport at true scale. Despite ongoing challenges and limitations with microfabrication techniques, the efforts witnessed in recent years have provided previously unattainable in vitro quantifications on the local transport properties in the deep pulmonary acinar airways. These may ultimately provide new opportunities to explore improved strategies of inhaled drug delivery to the deep acinar regions by investigating further the mechanistic interactions between airborne particulate carriers and respiratory airflows at the pulmonary microscales.