Anti-DPT (aa 45-94) polyclonal antibody

Understanding the spatial distribution of dead pine trees (DPTs) in mountainous areas is vital for diseased wood cleanup and the prediction ofpine wilt disease. The study induced a deep learning (DL) model of convolutional neural networks (CNNs) for the DPT detection using unmanned aerial vehicle images. Two thousand manually labelled DPT and Non-DPT samples were collected to train (80%) and optimize (20%) the CNNs of AlexNet and GoogLeNet, and 768 samples from other three areas were used to predict the categories in Jinjiang, Fujian, southeastern China. The same dataset was used to compare the classification accuracy between CNNs and the traditional template matching (TM) method. In addition, the potential factors influencing the overall accuracy of the DL model for DPT detection were evaluated. Training results of AlexNet and GoogLeNet showed an accuracy of over 93.30% and 97.38% respectively for the top-1 test after the final training iteration. For the DPT classification in the prediction areas of pure forests, the TM method showed the 56-65% of overall accuracy while CNNs showed 65-80%. CNNs-based DPT detection was more accurate than the traditional TM method. Terrains and red broadleaf trees influence the CNNs-based DPT detection from aerial visible-images in mixed artificial forest and peaks areas.

BACKGROUND: Hypersensitivity reactions (HRs) to macrolides are rare. OBJECTIVE: The aim of this study was to evaluate the diagnostic value of in vivo tests in the diagnosis of HRs to macrolides and also to assess cross-reactivity between 4 different macrolides (clarithromycin, dirithromycin, spiramycin, and azithromycin) belonging to 3 different groups. METHODS: Twenty-five patients with a history of immediate or delayed-type HRs to at least 1 macrolide and 20 healthy control subjects underwent skin testing for both the culprit and alternative macrolides. Then, all subjects underwent single-blind drug provocation tests (SBDPTs) with these drugs. RESULTS: Twenty-one patients (84%) described an early reaction, whereas the remaining 4 (16%) had delayed-type reactions. Skin prick test results with culprit macrolides were positive in only 2 patients who had experienced anaphylaxis. These 2 and another 4 patients with anaphylaxis history and 6 patients with negative skin test results who did not give consent were not challenged. A total of 13 patients with negative skin test results were challenged with the culprit drugs and all of them experienced HRs during the SBDPTs. Skin test results with alternative drugs were positive in only 2 patients with negative SBDPT results. Conversely, 5 patients with negative skin test results reacted to SBDPTs with alternative macrolides. In healthy control subjects, the skin test results were positive in 3 patients (1 positivity with clarithromycin, 2 positivity with spiramycin) whereas all DPT results were negative. CONCLUSIONS: Our results suggested that DPT is the only reliable method to predict macrolide hypersensitivity as well as to detect cross-reactivity between macrolides. (C) 2017 American Academy of Allergy, Asthma & Immunology