Effects of body postures on respiratory muscle force and coughing in healthy people.

The respiratory muscle force determines the intensity of cough force. A greater cough force for cleaning the airways is essential for preventing and managing pneumonia. Body posture can affect the onset of aspiration pneumonia. However, the effects of body posture on the respiratory muscle and cough forces remain unclear. Thus, we aimed to explore the influence of the four body postures on respiratory muscle force, cough pressure, subjective ease of coughing, and pulmonary function in healthy individuals. Twenty healthy individuals were included in this study. Body postures were 0-degree supine, 30- and 60-degree semi-recumbent, and 90-degree sitting. The maximal inspiratory and expiratory pressures, maximal cough pressure, subjective ease of coughing, and pulmonary function, including peak expiratory flow, were evaluated. We set the measured values in the supine posture to 100% and showed the relative values. The 60-degree posture showed stronger inspiratory (125.1 ± 3.9%, mean ± standard error [SE]) and expiratory (116.4 ± 3.0%) muscle force, cough pressure, more subjective ease of coughing, and greater peak expiratory flow (113.4 ± 3.0%) than the supine posture. The sitting posture also showed greater inspiratory muscle force and peak expiratory flow than the supine posture. The correlation coefficient for the 60-degree posture showed that the maximal inspiratory pressure was moderately correlated with the maximal expiratory pressure (r = 0.512), cough pressure (r = 0.495), and peak expiratory flow (r = 0.558). The above findings suggest the advantage of keeping a 60-degree posture and avoiding the supine posture to generate a greater cough force in the prevention and management of pneumonia.

Anatomy and function of the lymphatic vessels in the parietal pleura and their plasticity under inflammation in mice.

Inflammatory pleuritis often causes pleural effusions, which are drained through lymphatic vessels (lymphatics) in the parietal pleura. The distribution of button- and zipper-like endothelial junctions can identify the subtypes of lymphatics, the initial, pre-collecting, and collecting lymphatics. Vascular endothelial growth factor receptor (VEGFR)-3 and its ligands VEGF-C/D are crucial lymphangiogenic factors. Currently, in the pleura covering the chest walls, the anatomy of the lymphatics and connecting networks of blood vessels are incompletely understood. Moreover, their pathological and functional plasticity under inflammation and the effects of VEGFR inhibition are unclear. This study aimed to learn the above-unanswered questions and immunostained mouse chest walls as whole-mount specimens. Confocal microscopic images and their 3-dimensional reconstruction analyzed the vasculatures. Repeated intra-pleural cavity lipopolysaccharide challenge induced pleuritis, which was also treated with VEGFR inhibition. Levels of vascular-related factors were evaluated by quantitative real-time polymerase chain reaction. We observed the initial lymphatics in the intercostals, collecting lymphatics under the ribs, and pre-collecting lymphatics connecting both. Arteries branched into capillaries and gathered into veins from the cranial to the caudal side. Lymphatics and blood vessels were in different layers with an adjacent distribution of the lymphatic layer to the pleural cavity. Inflammatory pleuritis elevated expression levels of VEGF-C/D and angiopoietin-2, induced lymphangiogenesis and blood vessel remodeling, and disorganized the lymphatic structures and subtypes. The disorganized lymphatics showed large sheet-like structures with many branches and holes inside. Such lymphatics were abundant in zipper-like endothelial junctions with some button-like junctions. The blood vessels were tortuous and had various diameters and complex networks. Stratified layers of lymphatics and blood vessels were disorganized, with impaired drainage function. VEGFR inhibition partially maintained their structures and drainage function. These findings demonstrate anatomy and pathological changes of the vasculatures in the parietal pleura and their potential as a novel therapeutic target.

Measuring and Predicting Tag Importance for Image Retrieval.

Textual data such as tags, sentence descriptions are combined with visual cues to reduce the semantic gap for image retrieval applications in today's Multimodal Image Retrieval (MIR) systems. However, all tags are treated as equally important in these systems, which may result in misalignment between visual and textual modalities during MIR training. This will further lead to degenerated retrieval performance at query time. To address this issue, we investigate the problem of tag importance prediction, where the goal is to automatically predict the tag importance and use it in image retrieval. To achieve this, we first propose a method to measure the relative importance of object and scene tags from image sentence descriptions. Using this as the ground truth, we present a tag importance prediction model to jointly exploit visual, semantic and context cues. The Structural Support Vector Machine (SSVM) formulation is adopted to ensure efficient training of the prediction model. Then, the Canonical Correlation Analysis (CCA) is employed to learn the relation between the image visual feature and tag importance to obtain robust retrieval performance. Experimental results on three real-world datasets show a significant performance improvement of the proposed MIR with Tag Importance Prediction (MIR/TIP) system over other MIR systems.