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Results from BLASTX best hit and phylogenetic analyses showed that most of the genes had a close relationship with orthologs from other Lepidoptera species. A large number of OBPs and CSPs were tandemly arrayed in the genomic scaffolds and formed gene clusters. Reverse transcription-quantitative PCR results showed that GmelOBP19 and GmelOR47 are mainly expressed in male antennae. This work provides a transcriptome resource for olfactory genes in G. mellonella, and the findings pave the way for studying the function of these genes.Introduction Accounting for biological heterogeneity represents one of the greatest challenges in biomedical research. Dynamic computational and mathematical models can be used to enhance the study and understanding of biological systems, but traditional methods for calibration and validation commonly do not account for the heterogeneity of biological data, which may result in overfitting and brittleness of these models. Herein we propose a machine learning approach that utilizes genetic algorithms (GAs) to calibrate and refine an agent-based model (ABM) of acute systemic inflammation, with a focus on accounting for the heterogeneity seen in a clinical data set, thereby avoiding overfitting and increasing the robustness and potential generalizability of the underlying simulation model. Methods Agent-based modeling is a frequently used modeling method for multi-scale mechanistic modeling. However, the same properties that make ABMs well suited to representing biological systems also present significant challenorward to more effectively representing the heterogeneity of clinical populations and their data.Hibernators dramatically lower metabolism to save energy while fasting for months. Prolonged fasting challenges metabolic homeostasis, yet small-bodied hibernators emerge each spring ready to resume all aspects of active life, including immediate reproduction. The liver is the body's metabolic hub, processing and detoxifying macromolecules to provide essential fuels to brain, muscle and other organs throughout the body. Here we quantify changes in liver gene expression across several distinct physiological states of hibernation in 13-lined ground squirrels, using RNA-seq to measure the steady-state transcriptome and GRO-seq to measure transcription for the first time in a hibernator. Our data capture key timepoints in both the seasonal and torpor-arousal cycles of hibernation. Strong positive correlation between transcription and the transcriptome indicates that transcriptional control dominates the known seasonal reprogramming of metabolic gene expression in liver for hibernation. During the torpor-arousal cycle, however, discordance develops between transcription and the steady-state transcriptome by at least two mechanisms 1) although not transcribed during torpor, some transcripts are unusually stable across the torpor bout; and 2) unexpectedly, on some genes, our data suggest continuing, slow elongation with a failure to terminate transcription across the torpor bout. While the steady-state RNAs corresponding to these read through transcripts did not increase during torpor, they did increase shortly after rewarming despite their simultaneously low transcription. Both of these mechanisms would assure the immediate availability of functional transcripts upon rewarming. Integration of transcriptional, post-transcriptional and RNA stability control mechanisms, all demonstrated in these data, likely initiate a serial gene expression program across the short euthermic period that restores the tissue and prepares the animal for the next bout of torpor.Background In elite athletes, training individualization is widely recommended to optimize competitive performance. Previous studies have evidenced the impact of hormonal fluctuations on different performance parameters among female athletes. While consideration of menstrual cycle (MC) phases as a parameter in training individualization strategies is necessary, systematic evidence identifying such impacts in elite athletes should be evaluated. Objective Systematically review publications that have investigated the link between MC phases and performance in elite female athletes. The overarching aim is to identify whether a consensus across studies exists enabling evidence-based recommendations for training individualization depending on menstrual cycle phases. Methods This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Three major scientific publication databases were searched from inception until November 3, 2020. Studies included focused on the inf few performance-related outcomes, such as endurance or power resistance, ligament stiffness, decision making skills, psychology, or competitiveness. Conclusion Different sports performance-related parameters are affected during the menstrual cycle among elite athletes, but the parameters themselves and the magnitude and the direction of the effects are inconclusive. Additional longitudinal and prospective studies to systematically monitor on-field performance parameters are urgently required in order to enable recommendations and training individualization in female elite athletes.The longhorned tick, Haemaphysalis longicornis (Acari Ixodidae), is a hard tick and a vector for severe fever with thrombocytopenia syndrome (SFTS) virus. The number of patients infected with SFTS is rapidly increasing. Recently, the invertebrate pathogen Metarhizium anisopliae JEF-290 was reported to be useful to control the tick as an alternative to chemical acaricides, which are not easily applicable in human living areas where the tick is widely spread. In this study, we analyzed how the tick and the fungal pathogen interact at the transcriptional level. Field-collected tick nymphs were treated with JEF-290 conidia at 1 × 108 conidia/ml. In the early stage of infection with 2.5% mortality, the infected ticks were subjected to RNA sequencing, and non-infected ticks and fungal masses served as controls. Triapine manufacturer Fungus and tick genes were mostly up-regulated at the early stage of infection. In the gene set enrichment analysis of the infecting fungus, catabolic processes that included lipids, phospholipids, and detoxification processes, the response to oxidative stress, and toxic substances were significantly up-regulated.

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