CT strain metrics allow for earlier diagnosis of bronchiolitis obliterans syndrome after hematopoietic cell transplant.

Bronchiolitis obliterans syndrome (BOS) after hematopoietic cell transplantation (HCT) is associated with substantial morbidity and mortality. Quantitative computed tomography (qCT) can help diagnose advanced BOS meeting National Institutes of Health (NIH) criteria (NIH-BOS) but has not been used to diagnose early, often asymptomatic BOS (early BOS), limiting the potential for early intervention and improved outcomes. Using pulmonary function tests (PFTs) to define NIH-BOS, early BOS, and mixed BOS (NIH-BOS with restrictive lung disease) in patients from 2 large cancer centers, we applied qCT to identify early BOS and distinguish between types of BOS.

Comparative expression profiles of carboxylesterase orthologous in two closely related tea geometrid species, Prout and Warren.

Insect carboxylesterases (CXEs) can be expressed in multiple tissues and play crucial roles in detoxifying xenobiotic insecticides and degrading olfactory cues. Therefore, they have been considered as an important target for development of eco-friendly insect pest management strategies. Despite extensive investigation in most insect species, limited information on CXEs in sibling moth species is currently available.

(+)-Catechin, epicatechin and epigallocatechin gallate are important inducible defensive compounds against Ectropis grisescens in tea plants.

The tea plant, Camellia sinensis (L.) O. Kuntze, is an economically important, perennial woody plant rich in catechins.

Expression patterns and ligand binding characterization of Plus-C odorant-binding protein 14 from Adelphocoris lineolatus (Goeze).

Odorant-binding proteins (OBPs) can bind and transport hydrophobic odorants across the sensillum lymph to the olfactory receptors (ORs) and play crucial roles in insect chemosensory systems. Although the ligand spectra of classical OBPs have been extensively characterized, little is known about OBPs in the Plus-C subgroup. Here, we focus on AlinOBP14, a Plus-C OBP from the hemipteran mirid bug pest Adelphocoris lineolatus (Goeze).

Identification and Expression Patterns of Putative Diversified Carboxylesterases in the Tea Geometrid Prout.

Carboxylesterases (CXEs) belong to a family of metabolic enzymes. Some CXEs act as odorant-degrading enzymes (ODEs), which are reportedly highly expressed in insect olfactory organs and participate in the rapid deactivation of ester pheromone components and plant volatiles. The tea geometrid Prout produces sex pheromones consisting of non-ester functional compounds but relies heavily on acetic ester plant volatiles to search for host plants and locate oviposition sites.

Detecting deep divergence in seventeen populations of tea geometrid (Ectropis obliqua Prout) in China by COI mtDNA and cross-breeding.

The tea geometrid (Ectropis obliqua Prout, Lepidoptera: Geometridae) is a dominant chewing insect endemic in most tea-growing areas in China. Recently some E. obliqua populations have been found to be resistant to the nucleopolyhedrovirus (EoNPV), a host-specific virus that has so far been found only in E.

Optimization design of a Lamb wave device for density sensing of nonviscous liquid.

A Lamb wave device composed of a piezoelectric plate loaded with a nonviscous liquid layer is presented. The relation between the Lamb wave phase velocity and the liquid density can be used for liquid density sensing. In this paper, utilizing the partial wave theory, the concept of effective permittivity is introduced to analyze the Lamb wave's excitation and the phase velocity calculation under a certain liquid density.

Evaluating sensor reliability in classification problems based on evidence theory.

This paper presents a new framework for sensor reliability evaluation in classification problems based on evidence theory (or the Dempster-Shafer theory of belief functions). The evaluation is treated as a two-stage training process. First, the authors assess the static reliability from a training set by comparing the sensor classification readings with the actual values of data, which are both represented by belief functions.