Regeneration Ecology of Chrysopogon aucheri and Cymbopogon jwarancusa in Grasslands of Upland Balochistan , Pakistan

Field experiments were conducted to investigate the seed attributes, movements and fates of dispersal units, and seedling establishment of Chrysopogon aucheri and Cymbopogon jwarancusa in a representative grassland ecosystem in upland Balochistan, Pakistan. Cymbopogon jwarancusa had more filled and viable caryopses than Chrysopogon aucheri. Seeds (spikelets) of both species had similar morphological features. Chrysopogon aucheri had one dispersal unit, a triplet spikelet. Cymbopogon jwarancusa had four types of dispersal units: a paired spikelet, a partial raceme, an entire raceme, and a partial inflorescence comprised of two racemes. Paired spikelets and partial racemes of Cymbopogon jwarancusa had greater mean dispersal distances (94 and 101 cm) from the edge of the basal crown of marked plants to the ground surface than triplet spikelets of Chrysopogon aucheri (79 cm). Spikelets of Cymbopogon jwarancusa and Chrysopogon aucheri moved mean distances of 26 and 32 cm, respectively, on the ground surface before becoming trapped in a microhabitat. The mean angle of dispersal for both species was toward the northeast, according to the prevailing wind direction. An ant (Tica verona) was the only detected seed (spikelet) predator for Chrysopogon aucheri. Both species had a weakly persistent soil seed bank, with higher amounts of seeds found under plant canopies compared to open interspaces. The recruitment of Chrysopogon aucheri and Cymbopogon jwarancusa seedlings from the natural seed bank was monitored in seven different microhabitats under natural and above-normal precipitation regimes . Above-normal precipitation increased seedling recruitment for both species in all microhabitats. Cymbopogon jwarancusa had higher seedling densities than Chrysopogon auchfiri. Seedling survival and tiller development for both species were greatest in the gravel microhabitat in the natural precipitation treatment. Monsoon rains in late July enhanced emergence of both species from recently dispersed seeds but emerged seedlings did not survive to the end of the growing season. The field studies indicate that Cymbopogon jwarancusa has a greater regeneration potential than Chrysopogon aucheri in this grassland ecosystem in upland Balochistan. It may be difficult to increase the composition of Chrysopogon aucheri, the more desirable species in these grasslands, when using management techniques that rely on natural regeneration

Endobronchial Ultrasound-guided Transbronchial Needle Biopsy for Diagnosis of Mediastinal Lymphadenopathy in Patients with Extrathoracic Malignancy

Mediastinal lymphadenopathy associated with extrathoracic malignancy or a metastasis of unknown origin (MUO) requires pathological verification. Surgical exploration or endoscopic ultrasound-guided fine needle aspiration is limited to application. We investigated the effectiveness of endobronchial ultrasound-guided transbronchial needle biopsy (EBUS-TBNA) for evaluating mediastinal lymphadenopathy in patients with an extrathoracic malignancy. We retrospectively analyzed data from 59 patients who underwent EBUS-TBNA with a core biopsy because of a suspected mediastinal metastasis between September 2008 and August 2010. All patients had previously been diagnosed with an extrathoracic malignancy (n = 39, 66.1%) or a suspected MUO without a thoracic lesion (n = 20, 33.9%). A total of 88 lymph nodes was analyzed. EBUS-TBNA findings indicated malignancies in 34 patients (57.6%). The EBUS-TBNA sensitivity and specificity for the detection of mediastinal malignancy in patients with a previous extrathoracic malignancy were 96.3% and 100%, respectively. For MUO patients without a thoracic lesion, the sensitivity and specificity were 61.5% and 100%, respectively. The overall sensitivity and specificity were 81.0% and 100%, respectively (P = 0.053). EBUS-TBNA is a safe and effective modality for evaluating mediastinal lymphadenopathy in patients with a previous extrathoracic malignancy or a MUO without a thoracic lesion. The application of this diagnostic tool is likely to have significant clinical implications

The Role of Transbronchial Lung Biopsy in Diagnosing Pulmonary Mucormycosis in a Critical Care Unit

Background Pulmonary mucormycosis (PM) is an emerging infectious disease and a life-threatening infection with high mortality. The clinical outcomes of PM have not improved significantly over the last decade because early diagnosis of PM is difficult and antifungal agents show limited activity. We evaluated the clinical manifestations of PM in a Korean tertiary hospital and identified the role of transbronchial lung biopsy (TBLB) in diagnosing PM in patients admitted to an intensive care unit. Methods The medical records of adult patients (aged 16 years and older) who met the criteria for proven or probable PM in a Korean tertiary hospital were retrospectively reviewed from January 2003 to December 2013. The clinical features, computed tomographic findings, diagnostic methods, treatment, and outcomes in patients with PM were evaluated. Results Of the nine patients, four were male. The median age was 64 years (range, 12 to 73 years). PM was proven and probable in seven and two cases, respectively. Computed tomography findings of PM were unilateral involvement in eight cases (89%), consolidation in eight (89%), ground glass opacity in four (44%), and reverse halo sign in one (11%). Six of nine cases (67%) were diagnosed as PM from TBLB via portable bronchoscopy. There were no complications after TBLB. Mortality rate was 56% (five of nine cases). Conclusions TBLB can be an easy and useful technique for diagnosing PM in the intensive care unit

Gender Differences in Antitussive Prescriptions for Chronic Cough in Korea

Background: We investigated the differences in the characteristics and prognoses between the sexes of patients with chronic cough who were prescribed antitussive agents, using a Korean population-based database. Methods: Claims data from South Korea’s Health Insurance Review and Assessment (HIRA) service were analyzed. This retrospective observational cohort study considered chronic cough patients aged 18 years and older who were consistently prescribed antitussive agents for more than 2 months between 1 January 2017 and 30 June 2019. Results: Among the 207,989 patients treated for chronic cough, the prevalence of unexplained cough was higher in women (men: 6.2% vs. women: 9.7%) and the prevalence of persistent cough was higher in men (men: 16.8% vs. women: 14.3%). The gap in the proportion of COPD, lung cancer, ILD, GERD, and TB between women and men were largest around the age range of 60–70 years. With the exception of those in their 60s and 70s, women were more likely to have chronic cough and persistent cough than men. Women were more likely to discontinue medication after treatment completion than men. Only 53.9% of patients discontinued cough medication for more than 6 months after treatment completion. Within 12 and 18 months, respectively, 8.9% and 11.9% of them revisited the hospital for chronic cough. Via Cox regression analysis, an age in the 60s or 70s and explained cough were independently associated with a higher risk of revisit for treatment. Conclusions: Among patients treated for chronic cough, there were distinct differences in cough characteristics and prescription status between men and women. Our data highlight the need for a new personalized treatment approach to chronic cough, taking into account the gender, age, and underlying diseases of patients. Further research is needed to determine whether appropriate underlying disease control and gender-specific treatment are effective for managing chronic cough

Robust Airway Generation Labeling With Airway Segmentation for Reliable Airway Assessment

This study aims to accurately classify the airways in the human respiratory system, which are characterized by diverse pattern forming a complex tree-like structure. Although recent advances in deep learning show promise for automatic airway segmentation, further research is needed to make it practical for determining a patient’s airway status for tailored treatment. To enhance diagnostics and treatments, it’s crucial to delve into the study of airway generation. This exploration helps in understanding specific structures and pinpointing issues like airway narrowing and lung compliance. Current methods, such as template-matching and machine learning based methods that interpret this as classification problem, have limitations in capturing the complexity of higher-generation airways. To overcome these challenges, our study proposes a novel approach. The Prim algorithm initially establishes a minimum spanning tree from the centerline to create an accurate tree structure that reflects airway connections. A new secondary branch is formed when a main branch with an outdegree of 1 is detected, ensuring precise airway generation labeling. To mitigate false branch generation, the study proposes an approach that increases the cost of trunk lines connected to a centerline with an outdegree of 1. Additionally, a method for pruning trees based on subtree length is proposed to effectively handle segmentation results in deep learning. This method prevents the generation of false branches by removing vertices with shorter subtree airway lengths than their siblings. The approach successfully addresses the common issue of false branch generation, providing reliable labeling of airway generation in higher-generation sections. In conclusion, the technique we propose offers substantial benefits for patient health monitoring, disease prediction, and prevention. It achieves this by providing precise and dependable identification of airway generations within the intricate anatomy of the respiratory system

Motility Analysis of Diaphragm in Patients With Chronic Pulmonary Lung Disease Based on Computed Tomography Technique

The diaphragm plays a crucial role in respiration, and diaphragm dysfunction is common in COPD, contributing to worsening symptoms and higher mortality rates. Many methods have been implemented to evaluate the function of the diaphragm, but each comes with its unique set of limitations. To overcome this challenge, a novel approach was introduced to assess diaphragm function in patients with chronic obstructive pulmonary disease (COPD) using thoracic computed tomography scans. This novel approach involves generating a simulation of the diaphragm from lung DICOM slice images and calculating the dynamic change in respiratory motion by quantifying the difference in the simulated diaphragm mesh area during inhalation and exhalation. The experimental design incorporates various image processing algorithms, computational geometry algorithms, and a surface fitting algorithm optimized to minimize the potential sources of error. When the proposed technique was applied to detect diaphragmatic dysfunction in patients with COPD, the results of the Pearson correlation analysis showed a strong relationship between the variables ratio of exhalation to inhalation surface and average z-value difference inhalation and exhalation surfaces, with a coefficient of 0.731. The results suggest that the proposed technique is highly accurate and beneficial in scenarios where diaphragm function is essential, such as respiratory disorders, neuromuscular diseases like Amyotrophic Lateral Sclerosis or muscular dystrophy, spinal cord injuries, and conditions such as sleep apnea. By providing specific numerical data on sensitivity and specificity, this approach offers a quantitative evaluation of its effectiveness in detecting diaphragmatic dysfunction in patients with COPD. In conclusion, the proposed approach is currently semi-automated, however, future study may investigate fully automated approaches using this technique

Association between the Respiratory Microbiome and Plasma Microbial Extracellular Vesicles in Intubated Patients

Extracellular vesicles (EVs) regulate various cellular and immunological functions in human diseases. There is growing interest in the clinical role of microbial EVs in pneumonia. However, there is a lack of research on the correlation between lung microbiome with microbial EVs and the microbiome of other body sites in pneumonia. We investigated the co-occurrence of lung microbiome and plasma microbe-derived EVs (mEVs) in 111 samples obtained from 60 mechanically ventilated patients (41 pneumonia and 19 non-pneumonia cases). The microbial correlation between the two samples was compared between the pneumonia and non-pneumonia cases. Bacterial composition of the plasma mEVs was distinct from that of the lung microbiome. There was a significantly higher correlation between lung microbiome and plasma mEVs in non-pneumonia individuals compared to pneumonia patients. In particular, Acinetobacter and Lactobacillus genera had high correlation coefficients in non-pneumonia patients. This indicates a beneficial effect of mEVs in modulating host lung immune response through EV component transfer

Metagenomic Analysis of Plasma Microbial Extracellular Vesicles in Patients Receiving Mechanical Ventilation: A Pilot Study

Background: Previous studies reported a significant association between pneumonia outcome and the respiratory microbiome. There is increasing interest in the roles of bacterial extracellular vesicles (EVs) in various diseases. We studied the composition and function of microbiota-derived EVs in the plasma of patients receiving mechanical ventilation to evaluate whether they can be used as a diagnostic marker and to predict clinical outcomes. Methods: Plasma samples (n = 111) from 59 mechanically ventilated patients (41 in the pneumonia group; 24 in the nursing home and hospital-associated infection [NHAI] group) were prospectively collected on days one and seven. After isolating the bacterial EVs from plasma samples, nucleic acid was extracted for 16S rRNA gene pyrosequencing. The samples were evaluated to determine the α and β diversity, bacterial composition, and predicted functions. Results: Principal coordinates analysis revealed significantly different clustering of microbial EVs between the pneumonia and non-pneumonia groups. The proportions of Lactobacillus, Cutibacterium, and Sphingomonas were significantly different between the pneumonia and non-pneumonia groups. In addition, the abundances of Lactobacillus and Bifidobacterium were significantly higher in the non-NHAI than the NHAI group. In the analysis of β diversity, the structure of microbial EVs differed significantly different between 28-day survivors and non-survivors (Bray-Curtis distance, p = 0.014). Functional profiling revealed significant differences between the pneumonia and non-pneumonia groups. The longitudinal change in predicted functions of microbial EV genes showed a significant difference between 28-day survivors and non-survivors. Conclusions: Bacterial microbiota–derived EVs in the plasma have potential as diagnostic and prognostic markers for patients receiving mechanical ventilation. Further large prospective studies are needed to determine the clinical utility of plasma microbiota-EVs in intubated patients

Metagenomic Analysis of Plasma Microbial Extracellular Vesicles in Patients Receiving Mechanical Ventilation: A Pilot Study

Background: Previous studies reported a significant association between pneumonia outcome and the respiratory microbiome. There is increasing interest in the roles of bacterial extracellular vesicles (EVs) in various diseases. We studied the composition and function of microbiota-derived EVs in the plasma of patients receiving mechanical ventilation to evaluate whether they can be used as a diagnostic marker and to predict clinical outcomes. Methods: Plasma samples (n = 111) from 59 mechanically ventilated patients (41 in the pneumonia group; 24 in the nursing home and hospital-associated infection [NHAI] group) were prospectively collected on days one and seven. After isolating the bacterial EVs from plasma samples, nucleic acid was extracted for 16S rRNA gene pyrosequencing. The samples were evaluated to determine the α and β diversity, bacterial composition, and predicted functions. Results: Principal coordinates analysis revealed significantly different clustering of microbial EVs between the pneumonia and non-pneumonia groups. The proportions of Lactobacillus, Cutibacterium, and Sphingomonas were significantly different between the pneumonia and non-pneumonia groups. In addition, the abundances of Lactobacillus and Bifidobacterium were significantly higher in the non-NHAI than the NHAI group. In the analysis of β diversity, the structure of microbial EVs differed significantly different between 28-day survivors and non-survivors (Bray-Curtis distance, p = 0.014). Functional profiling revealed significant differences between the pneumonia and non-pneumonia groups. The longitudinal change in predicted functions of microbial EV genes showed a significant difference between 28-day survivors and non-survivors. Conclusions: Bacterial microbiota–derived EVs in the plasma have potential as diagnostic and prognostic markers for patients receiving mechanical ventilation. Further large prospective studies are needed to determine the clinical utility of plasma microbiota-EVs in intubated patients