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One concern to the patients is the off-line detection of pneumonia infection status after using the ventilator in the intensive care unit. Hence, machine learning methods for ventilator-associated pneumonia (VAP) rapid diagnose are proposed. A popular device, Cyranose 320 e-nose, is usually used in research on lung disease, which is a highly integrated system and sensor comprising 32 array using polymer and carbon black materials. In this study, a total of 24 subjects were involved, including 12 subjects who are infected with pneumonia, and the rest are non-infected. Three layers of back propagation artificial neural network and support vector machine (SVM) methods were applied to patients’ data to predict whether they are infected with VAP with Pseudomonas aeruginosa infection. Furthermore, in order to improve the accuracy and the generalization of the prediction models, the ensemble neural networks (ENN) method was applied. In this study, ENN and SVM prediction models were trained and tested. In order to evaluate the models’ performance, a fivefold cross-validation method was applied. The results showed that both ENN and SVM models have high recognition rates of VAP with Pseudomonas aeruginosa infection, with 0.9479 ± 0.0135 and 0.8686 ± 0.0422 accuracies, 0.9714 ± 0.0131, 0.9250 ± 0.0423 sensitivities, and 0.9288 ± 0.0306, 0.8639 ± 0.0276 positive predictive values, respectively. The ENN model showed better performance compared to SVM in the recognition of VAP with Pseudomonas aeruginosa infection. The areas under the receiver operating characteristic curve of the two models were 0.9842 ± 0.0058 and 0.9410 ± 0.0301, respectively, showing that both models are very stable and accurate classifiers. This study aims to assist the physician in providing a scientific and effective reference for performing early detection in Pseudomonas aeruginosa infection or other diseases.

3D morphology of poly(3-hydroxybutyrate) (PHB), crystallized in the presence of diluents of poly(1,3-trimethylene adipate) and poly(ethylene oxide), is probed using a novel approach coupled with selective etching. For interpreting the mechanisms of crystal periodic aggregation, various microscopic techniques and synchrotron microbeam X-ray analysis are used to observe the top surface in connection with the 3D crystal assemblies. Periodic grating architectures, with the cross-bar pitch exactly matching with the optical band spacing, are proved in banded PHB. The crystals under the ridge branch out to spawn finer crystals orienting/bending horizontally underneath the valley band, repeating till species drainage or impingement. The grating structure in the banded PHB resembles many nature's iridescence crystals and is further proved by photonic reflection results as a critical breakthrough novel finding.

The human pathogen Pseudomonas aeruginosa can rapidly induce fatal sepsis, even in previously healthy infants or children treated with appropriate antibiotics. To reduce antibiotic overuse, exploring novel complementary therapies, such as probiotics that reportedly protect patients against P. aeruginosa infection, would be particularly beneficial. However, the major mechanism underlying the clinical effects is not completely understood. We thus aimed to investigate how probiotics affect IL-8 and human beta-defensin 2 (hBD-2) in P. aeruginosa–infected intestinal epithelial cells (IECs). We infected SW480 IECs with wild type PAO1 P. aeruginosa following probiotic treatment with Lactobacillus rhamnosus GG or Bifidobacterium longum spp. infantis S12, and analysed the mRNA expression and secreted protein of IL-8 and hBD-2, Akt signalling and NOD1 receptor protein expression. We observed that probiotics enhanced hBD-2 expression but suppressed IL-8 responses when administered before infection. They also enhanced P. aeruginosa–induced membranous NOD1 protein expression and Akt activation. The siRNA-mediated Akt or NOD1 knockdown counteracted P. aeruginosa–induced IL-8 or hBD-2 expression, indicating regulatory effects of these probiotics. In conclusion, these data suggest that probiotics exert reciprocal regulation of inflammation and antimicrobial peptides in P. aeruginosa–infected IECs and provide supporting evidence for applying probiotics to reduce antibiotic overuse.

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