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Background The poultry red mite (PRM), Dermanyssus gallinae , is one of the most economically deleterious ectoparasites affecting egg-laying hens worldwide. It may be possible to control D. gallinae populations by manipulating lighting regimes within poultry units. However, no studies have clearly shown the effects of darkness on the population growth rate of D. gallinae . Methods The effect of darkness on the population growth rate of D. gallinae was investigated, together with the first description of the molecular identity of the mite from China. Mite variables under two lighting regimens (1:23 h L:D and 12:12 h L:D) were compared, including number of mites and eggs, survival and feeding rates, engorgement, oviposition, hatchability and the life-cycle of D. gallinae. Results The results showed that the number of mites (13,763 ± 956) and eggs (5424 ± 317) in the rearing system with prolonged darkness of 1:23 h L:D at 4th week were 2.4- and 3.6-fold higher than those under a conventional lighting regimen of 12:12 h L:D, respectively. The feeding rates of mites under prolonged darkness ranged from 36.7 ± 1.1% to 52.0 ± 7.0%, which were significantly higher than those under conventional lighting regimen (ranging from 22.6 ± 1.9% to 37.3 ± 1.6%). The mean weight of engorged females (0.26 ± 0.01 mg) and the mean number of eggs per female (on average 5.87 ± 0.36) under prolonged darkness were significantly higher than those under conventional lighting regimen (0.22 ± 0.01 mg and 3.62 ± 0.31, respectively). However, the survival rate ranging from 98.07 ± 0.10% to 98.93 ± 0.19%, hatchability of 97.93 ± 0.01% and the life-cycle of D. gallinae (9 days) was not affected by the lighting period. Conclusions Our findings demonstrated that prolonged darkness significantly promoted the proliferation levels of D. gallinae , resulting in increased number of mites and eggs in the rearing system. The promoted population growth of D. gallinae was found to be related to the increased feeding rate, engorgement level and oviposition level of mites under prolonged darkness. The egg hatchability, the survival rates and the duration of life-cycle of D. gallinae were not affected by the light regimes.

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Motivation There is growing evidence showing that the dysregulations of miRNAs cause diseases through various kinds of the underlying mechanism. Thus, predicting the multiple-category associations between microRNAs (miRNAs) and diseases plays an important role in investigating the roles of miRNAs in diseases. Moreover, in contrast with traditional biological experiments which are time-consuming and expensive, computational approaches for the prediction of multicategory miRNA–disease associations are time-saving and cost-effective that are highly desired for us. Results We present a novel data-driven end-to-end learning-based method of neural multiple-category miRNA–disease association prediction (NMCMDA) for predicting multiple-category miRNA–disease associations. The NMCMDA has two main components: (i) encoder operates directly on the miRNA–disease heterogeneous network and leverages Graph Neural Network to learn miRNA and disease latent representations, respectively. (ii) Decoder yields miRNA–disease association scores with the learned latent representations as input. Various kinds of encoders and decoders are proposed for NMCMDA. Finally, the NMCMDA with the encoder of Relational Graph Convolutional Network and the neural multirelational decoder (NMR-RGCN) achieves the best prediction performance. We compared the NMCMDA with other baselines on three experimental datasets. The experimental results show that the NMR-RGCN is significantly superior to the state-of-the-art method TDRC in terms of Top-1 precision, Top-1 Recall, and Top-1 F1. Additionally, case studies are provided for two high-risk human diseases (namely, breast cancer and lung cancer) and we also provide the prediction and validation of top-10 miRNA–disease-category associations based on all known data of HMDD v3.2, which further validate the effectiveness and feasibility of the proposed method.

The poultry red mite (PRM), Dermanyssus gallinae, is one of the most detrimental ectoparasite on poultry farms worldwide. The blood fed on birds provides the mites with nutrition and energy for their activities, development and reproduction. In the evaluation of the efficacy of novel drugs or vaccines against PRMs, their effects on blood digestion are generally used as a key parameter. The blood digestion of haematophagous arthropods (including D. gallinae) is usually assessed by weighing; however, this method shows some limitations. The main objective of the present study was to develop a scoring method that can quickly and visually evaluate the blood digestion status of PRMs. A 0–4 point scoring criterion was established to describe the blood digestion status of D. gallinae based on the changes in appearance in the intestinal tract of PRMs during the blood digestion process. There was a good consistency between the results obtained by the blood digestion scoring and the weighing, indicating the reliability of this new method. The results obtained from volunteers were consistent with the results from researchers with low coefficient of variation, indicating that the scoring method has good practicability. The applicability of the scoring method was confirmed in an efficacy study, where it was found that doramectin could significantly inhibit the blood digestion of PRMs, lowering the blood digestion score.

Many jurisdictions have implemented data protective legislations. However, these rules of law accentuate personal data protection and it seems that the safeguard of other valuable data is neglected. Premised on the assumption that other data should be under the equal supervision like personal data, this essay deploys a holistic legal approach to briefly construct a data protective regime that incorporates other traditionally protected data including IP-protected data and confidential data in the specific data legislation for policymakers to regulate data comprehensively and effectively However, is this new regime practically feasible? The feasibility analysis demonstrates that the data within the protection of intellectual property (IP) law and confidential law are constrained to a small amount and the extant legislations have already been adequate to safeguard these data. The sufficiency analysis shows that the new regime is inadequate to safeguard various data and many data are out of its regulation. This essay firstly presents a simple holistic data protective regime that illustrates from the scope, process and enforcement regime aspects. The feasibility analysis is followed from necessity and sufficiency perspectives.

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