Qualitative and Quantitative Determination of Decoquinate in Chicken Tissues by Gas Chromatography Tandem Mass Spectrometry.

A novel precolumn derivatization-GC-MS/MS method was developed for the determination of decoquinate residues in chicken tissues (muscle, liver, and kidney). The samples were extracted and purified by liquid-liquid extraction combined with solid-phase extraction and derivatized with acetic anhydride and pyridine. The recovery rates for decoquinate were 77.38~89.65%, and the intra-day and inter-day RSDs were 1.63~5.74% and 2.27~8.06%, respectively. The technique parameters meet the necessities for veterinary drug residue detection in China, the US, and the EU. Finally, the method was applied to analyze tissues of 60 chickens bought from a neighborhood supermarket, and solely one sample of chicken muscle contained 15.6 µg/kg decoquinate residue.

miRNA-10a-5p Targeting the BCL6 Gene Regulates Proliferation, Differentiation and Apoptosis of Chicken Myoblasts.

Proliferation, differentiation, and apoptosis are three essential stages in cell development, and miRNAs can achieve extensive regulation of cellular developmental processes by repressing the expression of target genes. According to our previous RNA-seq results, miRNA-10a-5p was differentially expressed at different periods in chicken myoblasts, revealing a possible association with muscle development. In this study, we concluded that miRNA-10a-5p inhibited chicken myoblasts' proliferation and differentiation and promoted chicken myoblasts' apoptosis by directly targeting BCL6, a critical transcription factor involved in muscle development and regeneration. Overexpression of BCL6 significantly facilitated myoblasts' proliferation and differentiation and suppressed myoblasts' apoptosis. On the contrary, knockdown of BCL6 significantly repressed myoblasts' proliferation and differentiation and induced myoblasts' apoptosis. The results above suggest that miRNA-10a-5p plays a potential role in skeletal muscle growth, development and autophagy by targeting the BCL6 gene. We first revealed the functions of miRNA-10a-5p and BCL6 in the proliferation, differentiation, and apoptosis of chicken myoblasts.

Study on the transcriptome for breast muscle of chickens and the function of key gene RAC2 on fibroblasts proliferation.

BACKGROUND: Growth performance is significant in broiler production. In the growth process of broilers, gene expression varies at different growth stages. However, limited research has been conducted on the molecular mechanisms of muscle growth and development in yellow-feathered male chickens. RESULTS: In the study, we used RNA-seq to study the transcriptome of the breast muscle of male Jinghai yellow chickens at 4 (M4F), 8 (M8F) and 12 weeks (M12F) of age. The results showed that 4608 differentially expressed genes (DEGs) were obtained by comparison in pairs of the three groups with Fold Change (FC) ≥ 2 and False Discovery Rate (FDR) ≤ 0.05, and 83, 3445 and 3903 DEGs were obtained separately from M4FvsM8F, M4FvsM12F and M8FvsM12F. Six genes were found as co-differentially expressed in the three age groups, namely SNCG, MYH1A, ARHGDIB, ENSGALG00000031598, ENSGALG00000035660 and ENSGALG00000030559. The GO analysis showed that 0, 304 and 408 biological process (BP) were significantly enriched in M4FvsM8F, M4FvsM12F and M8FvsM12F groups, respectively. KEGG pathway enrichment showed that 1, 2, 4 and 4 pathways were significantly enriched in M4FvsM8F, M4FvsM12F, M8FvsM12F and all DEGs, respectively. They were steroid biosynthesis, carbon metabolism, focal adhesion, cytokine-cytokine receptor interaction, biosynthesis of amino acids and salmonella infection. We constructed short hairpin RNA (shRNA) to interfere the differentially expressed gene RAC2 in DF-1 cells and detected mRNA and protein expression of the downstream genes PAK1 and MAPK8. Results of qPCR showed that RAC2, PAK1 and MAPK8 mRNA expression significantly decreased in the shRAC2-2 group compared with the negative control (NC) group. Western Blot (WB) results showed that the proteins of RAC2, PAK1 and MAPK8 also decreased in the shRAC2-2 group. Cell Counting Kit-8 (CCK-8) and 5-Ethynyl-2'-deoxyuridine (EdU) assay both showed that the proliferation of DF-1 cells was significantly inhibited after transfection of shRAC2-2. CONCLUSIONS: The results of RNA-seq revealed genes, BP terms and KEGG pathways related to growth and development of male Jinghai yellow chickens, and they would have important guiding significance to our production practice. Further research suggested that RAC2 might regulate cell proliferation by regulating PAKs/MAPK8 pathway and affect growth of chickens.

Multi-Scale Frequency Bands Ensemble Learning for EEG-Based Emotion Recognition.

Emotion recognition has a wide range of potential applications in the real world. Among the emotion recognition data sources, electroencephalography (EEG) signals can record the neural activities across the human brain, providing us a reliable way to recognize the emotional states. Most of existing EEG-based emotion recognition studies directly concatenated features extracted from all EEG frequency bands for emotion classification. This way assumes that all frequency bands share the same importance by default; however, it cannot always obtain the optimal performance. In this paper, we present a novel multi-scale frequency bands ensemble learning (MSFBEL) method to perform emotion recognition from EEG signals. Concretely, we first re-organize all frequency bands into several local scales and one global scale. Then we train a base classifier on each scale. Finally we fuse the results of all scales by designing an adaptive weight learning method which automatically assigns larger weights to more important scales to further improve the performance. The proposed method is validated on two public data sets. For the "SEED IV" data set, MSFBEL achieves average accuracies of 82.75%, 87.87%, and 78.27% on the three sessions under the within-session experimental paradigm. For the "DEAP" data set, it obtains average accuracy of 74.22% for four-category classification under 5-fold cross validation. The experimental results demonstrate that the scale of frequency bands influences the emotion recognition rate, while the global scale that directly concatenating all frequency bands cannot always guarantee to obtain the best emotion recognition performance. Different scales provide complementary information to each other, and the proposed adaptive weight learning method can effectively fuse them to further enhance the performance.

Simultaneous Determination of Tetracyclines and Fluoroquinolones in Poultry Eggs by UPLC Integrated with Dual-Channel-Fluorescence Detection Method.

An innovative, rapid and stable method for simultaneous determination of three tetracycline (oxytetracycline, tetracycline and doxycycline) and two fluoroquinolone (ciprofloxacin and enrofloxacin) residues in poultry eggs by ultra-high performance liquid chromatography-fluorescence detection (UPLC-FLD) was established and optimized. The samples were homogenized and extracted with acetonitrile/ultrapure water (90:10, v/v) and then purified by solid-phase extraction (SPE). LC separation was achieved on an ACQUITY UPLC BEH C18 column (1.7 µm, 2.1 mm × 100 mm), and the mobile phase was composed of acetonitrile and a 0.1 mol/L malonic acid solution containing 50 mmol/L magnesium chloride (the pH was adjusted to 5.5 with ammonia). When the five target drugs were spiked at the limit of quantification, 0.5 times the maximum residue limit (MRL), 1.0 MRL and 2.0 MRL, the recoveries were above 83.5% and the precision ranged from 1.99% to 6.24%. These figures of merit complied with the parameter validation regulations of the EU and U.S. FDA. The limits of detection and quantifications of the targets were 0.1-13.4 µg/kg and 0.3-40.1 µg/kg, respectively. The proposed method was easily extended to quantitative analyses of target drug residues in 85 egg samples, thus demonstrating its reliability and applicability.

Determination of Eight Coccidiostats in Eggs by Liquid-Liquid Extraction-Solid-Phase Extraction and Liquid Chromatography-Tandem Mass Spectrometry.

A method for the simultaneous determination of robenidine, halofuginone, lasalocid, monensin, nigericin, salinomycin, narasin, and maduramicin residues in eggs by liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed. The sample preparation method used a combination of liquid-liquid extraction (LLE) and solid-phase extraction (SPE) technology to extract and purify these target compounds from eggs. The target compounds were separated by gradient elution using high-performance liquid chromatography (HPLC) and ultra-performance liquid chromatography (UPLC). Tandem mass spectrometry was used to quantitatively and qualitatively analyze the target compounds via electrospray ionization (ESI+) and multiple reaction monitoring mode. The HPLC-MS/MS and UPLC-MS/MS methods were validated according to the requirements defined by the European Union and the Food and Drug Administration. The limits of detection and limits of quantification of the eight coccidiostats in eggs were 0.23-0.52 µg/kg and 0.82-1.73 µg/kg for HPLC-MS/MS, and 0.16-0.42 µg/kg and 0.81-1.25 µg/kg for UPLC-MS/MS, respectively. The eggs were spiked with four concentrations of the eight coccidiostats, and the HPLC-MS/MS and UPLC-MS/MS average recoveries were all higher than 71.69% and 72.26%, respectively. Compared with the HPLC-MS/MS method, utilizing UPLC-MS/MS had the advantages of low reagent consumption, a short detection time, and high recovery and precision. Finally, the HPLC-MS/MS and UPLC-MS/MS methods were successfully applied to detect eight coccidiostats in 40 eggs.

Optimization of ASE and SPE conditions for the HPLC-FLD detection of piperazine in chicken tissues and pork.

Accelerated solvent extraction (ASE) and solid-phase extraction (SPE) conditions were optimized by a high-performance liquid chromatography-fluorescence detector (HPLC-FLD) method for the detection of piperazine in chicken tissues and pork. Piperazine residues were determined by precolumn derivatization with trimethylamine and dansyl chloride. Samples were extracted with 2% formic acid in acetonitrile using an ASE apparatus and purified using a Strata-X-C SPE column. The monosubstituted product of the reaction of piperazine with dansyl chloride was 1-dansyl piperazine (1-DNS-piperazine). Chromatographic separations were performed on an Athena C18 column (250 × 4.6 mm, id: 5 µm) with gradient elution using ultrapure water and acetonitrile (5:95, V/V) as the mobile phase. The calibration curves showed good linearity over a concentration range of LOQ-200.0 µg/kg with a coefficient of determination (R2 ) ≥ .9992. The recoveries and relative standard deviations (RSD values) ranged from 78.49% to 97.56% and 1.19% to 5.32%, respectively, across the limit of quantification (LOQ) and 0.5, 1, and 2.0 times the maximum residue limit (MRL; µg/kg). The limits of detection (LODs) and LOQs were 0.96 to 1.85 µg/kg and 3.20 to 5.50 µg/kg, respectively. The method was successfully applied for the validation of animal products in the laboratory.

Development of an Accelerated Solvent Extraction-Ultra-Performance Liquid Chromatography-Fluorescence Detection Method for Quantitative Analysis of Thiamphenicol, Florfenicol and Florfenicol Amine in Poultry Eggs.

A simple, rapid and novel method for the detection of residues of thiamphenicol (TAP), florfenicol (FF) and its metabolite, florfenicol amine (FFA), in poultry eggs by ultra-performance liquid chromatography-fluorescence detection (UPLC-FLD) was developed. The samples were extracted with acetonitrile-ammonia (98:2, v/v) using accelerated solvent extraction (ASE) and purified by manual degreasing with acetonitrile-saturated n-hexane. The target compounds were separated on an ACQUITY UPLC® BEH C18 (2.1 mm × 100 mm, 1.7 µm) chromatographic column using a mobile phase composed of 0.005 mol/L NaH2PO4, 0.003 mol/L sodium lauryl sulfate and 0.05% trimethylamine, adjusted to pH 5.3 ± 0.1 by phosphoric acid and acetonitrile (64:36, v/v). The limits of detection (LODs) and limits of quantification (LOQs) of the three target compounds in poultry eggs were 1.8-4.9 µg/kg and 4.3-11.7 µg/kg, respectively. The recoveries of the three target compounds in poultry eggs were above 80.1% when the spiked concentrations of three phenicols were the LOQ, 0.5 maximum residue limit (MRL), 1.0 MRL and 2.0 MRL. The intraday relative standard deviations (RSDs) were less than 5.5%, and the interday RSDs were less than 6.6%. Finally, this new detection method was successfully applied to the quantitative analysis of TAP, FF and FFA in 150 commercial poultry eggs.

A General DNA-like Hybrid Symbiosis Framework: An EEG Cognitive Recognition Method.

In electroencephalogram (EEG) cognitive recognition research, the combined use of artificial neural networks (ANNs) and spiking neural networks (SNNs) plays an important role to realize different categories of recognition tasks. However, most of the existing studies focus on the unidirectional interaction between an ANN and a SNN, which may be overly dependent on the performance of ANNs or SNNs. Inspired by the symbiosis phenomenon in nature, in this study, we propose a general DNA-like Hybrid Symbiosis (DNA-HS) framework, which enables mutual learning between the ANN and the SNN generated by this ANN through parametric genetic algorithm and bidirectional interaction mechanism to enhance the optimization ability of the model parameters, resulting in a significant improvement of the performance of the DNA-HS framework in all aspects. By comparing with seven typical EEG cognitive recognition models, the performance of the seven hybrid network frameworks constructed using this method on different EEG-based cognitive recognition tasks are all improved to different degrees, verifying the effectiveness of the proposed method. This unified hybrid network framework similar to the DNA structure is expected to open up a new approach and form a new research paradigm for EEG-based cognitive recognition task.

Combining GC-MS/MS with a LLE-SPE sample pretreatment step to simultaneously analyse enrofloxacin and ofloxacin residues in chicken tissues and pork.

A widely applicable original gas chromatography-tandem mass spectrometry (GC-MS/MS) method was explored to qualitatively and quantitatively measure enrofloxacin and ofloxacin residues in chicken tissues and pork. The experimental samples were processed based on liquid-liquid extraction (LLE) and solid-phase extraction (SPE). Trimethylsilyl diazomethane (TMSD) was chosen to react derivatively with enrofloxacin and ofloxacin. In total, 78.25% âˆ¼ 90.56% enrofloxacin and 78.43% âˆ¼ 91.86% ofloxacin was recovered from the blank fortified samples. The limits of detection (LODs) were 0.7-1.0 µg/kg and 0.1-0.2 µg/kg, respectively. The limits of quantitation (LOQs) were 1.6-1.9 µg/kg and 0.3-0.4 µg/kg, respectively. It was verified that various experimental data met the requirements of the FAO & WHO (2014) for the detection of veterinary drug residues. Real samples obtained from local markets were analysed using the established method, and no residues of enrofloxacin or ofloxacin were detected in the samples.

Transcriptome analysis reveals that gga-miR-2954 inhibits the inflammatory response against Eimeria tenella infection.

Coccidiosis is an important parasitic protozoan disease in poultry farming, causing huge economic losses in the global poultry industry every year. MicroRNAs (miRNAs) are a class of RNA macromolecules that play important roles in the immune response to pathogens. However, the expression profiles and functions of miRNAs during Eimeria tenella (E. tenella) infection in chickens remain mostly uncharacterized. In this study, high-throughput sequencing of cecal tissues of control (JC), resistant (JR), and susceptible (JS) chickens led to the identification of 35 differentially expressed miRNAs among the three groups. Functional enrichment analysis showed that the differentially expressed miRNAs were mainly associated with the TGF-beta, NF-kB, and Jak-STAT signaling pathways. Notably, gga-miR-2954 was found to be significantly upregulated after coccidial infection. Functional analysis showed that gga-miR-2954 inhibited the production of the inflammatory cytokines IL-6, IL-1ß, TNF-α, and IL-8 in sporozoite-stimulated DF-1 cells. Mechanistically, we found that gga-miR-2954 targeted the RORC gene and that RORC promoted the inflammatory response in sporozoite-stimulated DF-1 cells. In conclusion, our study was the first to identify differentially expressed miRNAs in chicken cecal tissue during E. tenella infection and found that gga-miR-2954 regulates the host immune response to coccidial infection in chickens by targeting the RORC gene.

Automatic and direct identification of blink components from scalp EEG.

Eye blink is an important and inevitable artifact during scalp electroencephalogram (EEG) recording. The main problem in EEG signal processing is how to identify eye blink components automatically with independent component analysis (ICA). Taking into account the fact that the eye blink as an external source has a higher sum of correlation with frontal EEG channels than all other sources due to both its location and significant amplitude, in this paper, we proposed a method based on correlation index and the feature of power distribution to automatically detect eye blink components. Furthermore, we prove mathematically that the correlation between independent components and scalp EEG channels can be translating directly from the mixing matrix of ICA. This helps to simplify calculations and understand the implications of the correlation. The proposed method doesn't need to select a template or thresholds in advance, and it works without simultaneously recording an electrooculography (EOG) reference. The experimental results demonstrate that the proposed method can automatically recognize eye blink components with a high accuracy on entire datasets from 15 subjects.

A bidirectional interaction-based hybrid network architecture for EEG cognitive recognition.

BACKGROUND AND OBJECTIVE: Extracting cognitive representation and computational representation information simultaneously from electroencephalography (EEG) data and constructing corresponding information interaction models can effectively improve the recognition capability of brain cognitive status. However, due to the huge gap in the interaction between the two types of information, existing studies have yet to consider the advantages of the interaction of both. METHODS: This paper introduces a novel architecture named the bidirectional interaction-based hybrid network (BIHN) for EEG cognitive recognition. BIHN consists of two networks: a cognitive-based network named CogN (e.g., graph convolution network, GCN; capsule network, CapsNet) and a computing-based network named ComN (e.g., EEGNet). CogN is responsible for extracting cognitive representation features from EEG data, while ComN is responsible for extracting computational representation features. Additionally, a bidirectional distillation-based coadaptation (BDC) algorithm is proposed to facilitate information interaction between CogN and ComN to realize the coadaptation of the two networks through bidirectional closed-loop feedback. RESULTS: Cross-subject cognitive recognition experiments were performed on the Fatigue-Awake EEG dataset (FAAD, 2-class classification) and SEED dataset (3-class classification), and hybrid network pairs of GCN + EEGNet and CapsNet + EEGNet were verified. The proposed method achieved average accuracies of 78.76% (GCN + EEGNet) and 77.58% (CapsNet + EEGNet) on FAAD and 55.38% (GCN + EEGNet) and 55.10% (CapsNet + EEGNet) on SEED, outperforming the hybrid networks without the bidirectional interaction strategy. CONCLUSIONS: Experimental results show that BIHN can achieve superior performance on two EEG datasets and enhance the ability of both CogN and ComN in EEG processing as well as cognitive recognition. We also validated its effectiveness with different hybrid network pairs. The proposed method could greatly promote the development of brain-computer collaborative intelligence.

Untargeted and targeted metabolomics identify metabolite biomarkers for Salmonella enteritidis in chicken meat.

Salmonella Enteritidis easily contaminate chicken during slaughtering, processing, transportation, and sales, which seriously endangers human health. This study aimed to identify metabolite biomarkers for Salmonella Enteritidis contamination in chicken meat. UPLC-Q-Orbitrap MS untargeted metabolomics analysis identified 441 and 240 confidently metabolites in positive and negative ion mode, respectively. Thirty metabolites were defined as potential biomarkers for Salmonella enteritidis contamination in chicken meat. UPLC-QQQ-MS based targeted metabolomics was used to quantitatively analyze candidate metabolite biomarkers in Salmonella enteritidis contaminated and fresh chicken samples. A total of 10 candidate metabolite biomarkers were confirmed in the validation set, among which acetylcholine, l-Methionine, l-Proline, l-Valine, and l-Norleucine were identified as biomarkers for Salmonella Enteritidis contamination in chicken. The combined receiver operating characteristic curve analysis of the five biomarkers achieved an AUC of 0.956, indicating their high sensitivity and specificity in predicting Salmonella Enteritidis in raw chicken. In conclusion, the present study identified five metabolite biomarkers for Salmonella enteritidis in raw chicken. These results provide a potential theoretical basis for developing Salmonella Enteritidis detection methods in raw chicken.

Comprehensive analysis of gut microbiome and host transcriptome in chickens after Eimeria tenella infection.

Background: Coccidiosis is an intestinal parasitic disease caused by Eimeria protozoa, which endangers the health and growth of animals, and causes huge economic losses to the poultry industry worldwide every year. Studies have shown that poultry gut microbiota plays an important role in preventing the colonization of pathogens and maintaining the health of the host. Coccidia infection also affects host gene expression. However, the underlying potential relationship between gut microbiome and host transcriptome during E. tenella infection in chickens remain unclear. Methods: In this study, metagenomic and transcriptome sequencing were applied to identify microbiota and genes in cecal contents and cecal tissues of infected (JS) and control (JC) chickens on day 4.5 postinfection (pi), respectively. Results: First, microbial sequencing results of cecal contents showed that the abundance of Lactobacillus, Roseburia sp. and Faecalibacterium sp decreased significantly after E. tenella infection (P < 0.05), while the abundance of Alistipes and Prevotella pectinovora increased significantly (P < 0.05). Second, transcriptome sequencing results showed that a total of 434 differentially expressed mRNAs were identified, including 196 up-regulated and 238 down-regulated genes. These differentially expressed genes related to inflammation and immunity, such as GAMA, FABP1, F2RL1 and RSAD2, may play an important role in the process of host resistance to coccidia infection. Functional studies showed that the enriched pathways of differentially expressed genes included the TGF-beta signaling pathway and the ErbB signaling pathways. Finally, the integrated analysis of gut microbiome and host transcriptome suggested that Prevotella pectinovora associated with FABP1, Butyricicoccus porcorum and Colidextribacter sp. associated with RSAD2 were involved in the immune response upon E. tenella infection. Conclusion: In conclusion, this study provides valuable information on the microbiota and key immune genes after chicken E. tenella infection, with the aim of providing reference for the impact of coccidia infection on cecal microbiome and host.

Identification of metabolite biomarkers in Salmonella enteritidis-contaminated chickens using UHPLC-QTRAP-MS-based targeted metabolomics.

This study aimed to characterize the metabolic profile of Salmonella enteritidis (S. enteritidis) in chicken matrix and to identify metabolic biomarkers of S. enteritidis in chicken. The UHPLC-QTRAP-MS high-throughput targeted metabolomics approach was employed to analyze the metabolic profiles of contaminated and control group chickens. A total of 348 metabolites were quantified, and the application of deep learning least absolute shrinkage and selection operator (LASSO) modelling analysis obtained eight potential metabolite biomarkers for S. enteritidis. Metabolic abundance change analysis revealed significantly enriched abundances of anthranilic acid, l-pyroglutamic acid, 5-hydroxylysine, n,n-dimethylarginine, 4-hydroxybenzoic acid, and menatetrenone in contaminated chicken samples. The receiver operating characteristic (ROC) curve analysis demonstrated the strong ability of these six metabolites as biomarkers to distinguish S. enteritidis contaminated and fresh chicken samples. The findings presented in this study offer a theoretical foundation for developing an innovative approach to identify and detect foodborne contamination caused by S. enteritidis.

Polymorphisms of the myostatin gene and its relationship with reproduction traits in the Bian chicken.

Myostatin, or growth and differentiation factor 8, is a member of the transforming growth factor-ß superfamily; it functions as a negative regulator of skeletal muscle development and growth in mammals. In this study, single nucleotide polymorphisms in the 5' regulatory region and exon 1 of the myostatin gene were detected by PCR-SSCP in the Bian, Jinghai, Youxi, and Arbor Acre chickens, and the associations of the polymorphisms with reproduction traits were analyzed. Seven SNPs (A326G, C334G, C1346T, G1375A, A1473G, G1491A, and G2283A) were found in the myostatin gene. Association analysis showed that the G2283A were significantly associated with reproduction traits. Bian chickens of the GG genotype had a greater age at first egg than those of the GA and AA genotypes (P<0.01). Correspondingly, Bian chickens of the GA and AA genotypes had larger egg number at 300 days than those of the GG genotype (P<0.05 and P<0.01, respectively). Bian chickens of the AA genotype had significantly higher body weight at 300 days than those of the GG genotype (P<0.05). These results suggested that the myostatin gene may have certain effects on reproduction traits other than merely as a negative regulator of skeletal muscle development and growth in mammals previously reported.

Energy-efficient scheduling for hybrid tasks in control devices for the Internet of Things.

In control devices for the Internet of Things (IoT), energy is one of the critical restriction factors. Dynamic voltage scaling (DVS) has been proved to be an effective method for reducing the energy consumption of processors. This paper proposes an energy-efficient scheduling algorithm for IoT control devices with hard real-time control tasks (HRCTs) and soft real-time tasks (SRTs). The main contribution of this paper includes two parts. First, it builds the Hybrid tasks with multi-subtasks of different function Weight (HoW) task model for IoT control devices. HoW describes the structure of HRCTs and SRTs, and their properties, e.g., deadlines, execution time, preemption properties, and energy-saving goals, etc. Second, it presents the Hybrid Tasks' Dynamic Voltage Scaling (HTDVS) algorithm. HTDVS first sets the slowdown factors of subtasks while meeting the different real-time requirements of HRCTs and SRTs, and then dynamically reclaims, reserves, and reuses the slack time of the subtasks to meet their ideal energy-saving goals. Experimental results show HTDVS can reduce energy consumption about 10%-80% while meeting the real-time requirements of HRCTs, HRCTs help to reduce the deadline miss ratio (DMR) of systems, and HTDVS has comparable performance with the greedy algorithm and is more favorable to keep the subtasks' ideal speeds.

Long noncoding RNA profiling reveals that LncRNA BTN3A2 inhibits the host inflammatory response to Eimeria tenella infection in chickens.

Coccidiosis is a widespread parasitic disease that causes serious economic losses to the poultry industry every year. Long noncoding RNAs (lncRNAs) play important roles in transcriptional regulation and are involved in a variety of diseases and immune responses. However, the lncRNAs associated with Eimeria tenella (E. tenella) resistance have not been identified in chickens. In addition, the expression profiles and functions of lncRNAs during E. tenella infection remain unclear. In the present study, high-throughput sequencing was applied to identify lncRNAs in chicken cecal tissues from control (JC), resistant (JR), and susceptible (JS) groups on day 4.5 post-infection (pi), and functional tests were performed. A total of 564 lncRNAs were differentially expressed, including 263 lncRNAs between the JS and JC groups, 192 between the JR and JS groups, and 109 between the JR and JC groups. Functional analyses indicated that these differentially expressed lncRNAs were involved in pathways related to E. tenella infection, including the NF-kappa B signaling, B cell receptor signaling and natural killer cell-mediated cytotoxicity pathways. Moreover, through cis regulation network analysis of the differentially expressed lncRNAs, we found that a novel lncRNA termed lncRNA BTN3A2 was significantly increased in both cecum tissue and DF-1 cells after coccidia infection or sporozoite stimulation. Functional test data showed that the overexpression of lncRNA BTN3A2 reduced the production of inflammatory cytokines, including IL-6, IL-1ß, TNF-α and IL-8, while lncRNA BTN3A2 knockdown promoted the production of these inflammatory cytokines. Taken together, this study identify the differentially expressed lncRNAs during E. tenella infection in chickens for the first time and provide the direct evidence that lncRNA BTN3A2 regulates the host immune response to coccidia infection.

Identification of miRNA-mRNA Networks Associated with Pigeon Skeletal Muscle Development and Growth.

The growth and development of skeletal muscle determine the productivity of pigeon meat production, and miRNA plays an important role in the growth and development of this type of muscle. However, there are few reports regarding miRNA regulating the growth and development of skeletal muscle in pigeons. To explore the function of miRNA in regulating the growth and development of pigeon skeletal muscle, we used RNA sequencing technology to study the transcriptome of pigeons at two embryonic stages (E8 and E13) and two growth stages (D1 and D10). A total of 32,527 mRNAs were identified in pigeon skeletal muscles, including 14,378 novel mRNAs and 18,149 known mRNAs. A total of 2362 miRNAs were identified, including 1758 known miRNAs and 624 novel miRNAs. In total, 839 differentially expressed miRNAs (DEmiRNAs) and 11,311 differentially expressed mRNAs (DEGs) were identified. STEM clustering analysis assigned DEmiRNAs to 20 profiles, of which 7 were significantly enriched (p-value < 0.05). These seven significantly enriched profiles can be classified into two categories. The first category represents DEmiRNAs continuously downregulated from the developmental stage to the growth stage of pigeon skeletal muscle, and the second category represents DEmiRNAs with low expression at the development and early growth stage, and significant upregulation at the high growth stage. We then constructed an miRNA−mRNA network based on target relationships between DEmiRNAs and DEGs belonging to the seven significantly enriched profiles. Based on the connectivity degree, 20 hub miRNAs responsible for pigeon skeletal muscle development and growth were identified, including cli-miR-20b-5p, miR-130-y, cli-miR-106-5p, cli-miR-181b-5p, miR-1-z, cli-miR-1a-3p, miR-23-y, cli-miR-30d-5p, miR-1-y, etc. The hub miRNAs involved in the miRNA−mRNA regulatory networks and their expression patterns during the development and growth of pigeon skeletal muscle were visualized. GO and KEGG enrichment analysis found potential biological processes and pathways related to muscle growth and development. Our findings expand the knowledge of miRNA expression in pigeons and provide a database for further investigation of the miRNA−mRNA regulatory mechanism underlying pigeon skeletal muscle development and growth.