Insects rely on their olfactory systems in antennae to recognize sex pheromones and plant volatiles in surrounding environments. Some carboxylesterases (CXEs) are odorant-degrading enzymes (ODEs), degrading odorant signals to protect the olfactory neurons against continuous excitation. However, there is no report about CXEs in Holotrichia parallela, one of the most major agricultural underground pests in China. In the present study, 20 candidate CXEs were identified based on transcriptome analysis of female and male antennae. Sequence alignments and phylogenetic analysis were performed to investigate the characterization of these candidate CXEs. The expression profiles of CXEs were compared by RT-qPCR analysis between olfactory and non-olfactory tissues of both genders. HparCXE4, 11, 16, 17, 18, 19, and 20 were antenna-biased expressed genes, suggesting their possible roles as ODEs. HparCXE6, 10, 11, 13, and 16 showed significantly higher expression profiles in male antennae, whereas HparCXE18 was expressed more in female antennae. This study highlighted candidate CXE genes linked to odorant degradation in antennae, and provided a useful resource for further work on the H. parallela olfactory mechanism and selection of target genes for integrative control of H. parallela.

Parkinsonism refers to Parkinsons disease (PD) and Atypical parkinsonian syndromes (APS). Speech disorder is a common and early symptom in Parkinsonism which makes speech analysis a very important research area for the purpose of early diagnosis. Most of research have however focused on discrimination between PD and healthy controls. Such research does not take into account the fact that PD and APS syndromes are very similar in early disease stages. The main problem that has to be addressed first is then differential diagnosis: discrimination between PD and APS and within APS. This paper is a continuation of an earlier pioneer work in differential diagnosis where we mostly address the machine learning problem due to the small amount of training data. We show that classical linear and generalized linear models can provide interpretable and robust classifiers in term of accuracy and generalization ability.

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Light is an important environmental factor influencing plant growth and development. However, artificial light supplement is difficult to spread for its high energy consumption. In recent years, rare-earth light conversion film (RPO) covering is being focused on to be a new technology to study the mechanism of light affecting plant growth and development. Compared with the polyolefin film (PO), the RPO film advanced the temperature and light environment inside the greenhouse. Ultimately, improved growth and higher yield were detected because of a higher photosynthesis, Rubisco activity and Rubisco small subunit transcription. Compared with that in the greenhouse with polyolefin film, the plant height, stem diameter and internode length of sweet pepper treated with RPO increased by 11.05, 16.96 and 25.27%, respectively. In addition, Gibberellic acid 3 (GA3), Indole-3-acetic acid (IAA), Zeatin Riboside contents were increased by 11.95, 2.84 and 16.19%, respectively, compared with that with PO film. The fruit quality was improved, and the contents of ascorbic acid (Vc), soluble protein and soluble sugar were significantly higher than those of PO film, respectively, increased by 14.29, 47.10 and 67.69%. On the basis of improved fruit quality, the yield of RPO treatment increased by 20.34% compared with PO film. This study introduces an effective and low-energy method to study the mechanism and advancing plant growth in fruit vegetables production.