Immune cell early activation, apoptotic kinetic, and T-cell functional impairment in domestic pigs after ASFV CADC_HN09 strain infection.

African swine fever (ASF) caused by the African swine fever virus (ASFV) is a fatal and highly contagious disease of domestic pigs characterized by rapid disease progression and death within 2 weeks. How the immune cells respond to acute ASFV infection and contribute to the immunopathogenesis of ASFV has not been completely understood. In this study, we examined the activation, apoptosis, and functional changes of distinct immune cells in domestic pigs following acute infection with the ASFV CADC_HN09 strain using multicolor flow cytometry. We found that ASFV infection induced broad apoptosis of DCs, monocytes, neutrophils, and lymphocytes in the peripheral blood of pigs over time. The expression of MHC class II molecule (SLA-DR/DQ) on monocytes and conventional DCs as well as CD21 expression on B cells were downregulated after ASFV infection, implying a potential impairment of antigen presentation and humoral response. Further examination of CD69 and ex vivo expression of IFN-γ on immune cells showed that T cells were transiently activated and expressed IFN-γ as early as 5 days post-infection. However, the capability of T cells to produce cytokines was significantly impaired in the infected pigs when stimulated with mitogen. These results suggest that the adaptive cellular immunity to ASFV might be initiated but later overridden by ASFV-induced immunosuppression. Our study clarified the cell types that were affected by ASFV infection and contributed to lymphopenia, improving our understanding of the immunopathogenesis of ASFV.

YOLO-SK: A lightweight multiscale object detection algorithm.

YOLOv5 is an excellent object-detection model. However, it fails to fully use multiscale information when detecting objects with significant scale variations. It might use irrelevant contextual information, leading to incorrect predictions, particularly for low-performance devices. In this study, we selected lightweight YOLOv5s as the baseline model and proposed an improved model called YOLO-SK to overcome this limitation. YOLO-SK introduced several key improvements, the most important being the collaborative work of the weighted dense feature fusion network and SK attention prediction head. The proposed weighted dense feature fusion network could dynamically fuse features at different scales using autonomous learning parameters and cross-layer fusion capabilities. This enabled a balanced feature fusion ability in the output feature maps of different scales, thereby enhancing the richness of the effective information in the fused feature maps. The prediction head equipped with the SK attention mechanism broadened the scope of the model's receptive field and sharpened the focus on the target characteristics. This made it possible to glean more information about the target from the feature map output by employing a weighted dense feature fusion network. In addition, in order to improve the model's performance in terms of both accuracy and volume, we implemented the SIoU loss function and the Ghost Conv. The use of the model allowed for a more precise and in-depth comprehension of the event, which was made possible by all of these various methods of improvement. Extensive testing done on the PASCAL VOC 2007 and 2012 datasets showed that YOLO-SK was able to achieve considerable gains in prediction accuracy when compared with the baseline model (YOLOv5s), all while keeping the same level of model complexity. To be more specific, mAP@.5 increased by 2.6 %, and mAP@.5:.95 increased by 4.8 %. The advancements that were made and detailed in this paper could serve as a springboard for additional research that aims to improve the precision of multiscale object identification models for low-performance devices.

Co-administration of chicken IL-2 alleviates clinical signs and replication of the ILTV chicken embryo origin vaccine by pre-activating natural killer cells and cytotoxic T lymphocytes.

IMPORTANCE: Chickens immunized with the infectious laryngotracheitis chicken embryo origin (CEO) vaccine (Medivac, PT Medion Farma Jaya) experience adverse reactions, hindering its safety and effective use in poultry flocks. To improve the effect of the vaccine, we sought to find a strategy to alleviate the respiratory reactions associated with the vaccine. Here, we confirmed that co-administering the CEO vaccine with chIL-2 by oral delivery led to significant alleviation of the vaccine reactions in chickens after immunization. Furthermore, we found that the co-administration of chIL-2 with the CEO vaccine reduced the clinical signs of the CEO vaccine while enhancing natural killer cells and cytotoxic T lymphocyte response to decrease viral loads in their tissues, particularly in the trachea and conjunctiva. Importantly, we demonstrated that the chIL-2 treatment can ameliorate the replication of the CEO vaccine without compromising its effectiveness. This study provides new insights into further applications of chIL-2 and a promising strategy for alleviating the adverse reaction of vaccines.

How does the target of green innovation for cleaner production change in management process? Quality targeting and link targeting.

The global economy has accelerated the transition to a green, low-carbon economy. An enterprise's green innovation (GI) is directly related to its capacity for sustainable production as a micro-subject of economic development. This study examined the impact of managerial capacity on enterprise green innovation and changes of green innovation targeting. We used data collected manually from 423 Chinese A-share companies from 2010 to 2017. The effect of various external impact signals was then investigated. This study's findings are as follows: (1) Managerial ability stimulated green enterprise innovation. The marginal effect was 0.0696. While quality targeting has focused more on green invention innovation, managerial capacity significantly improved the marginal impact of green substantial innovation by 0.0375; (2) The clean production link targeting analysis confirmed that enterprises focused on end-of-pipe governance innovation (0.0466), along with new energy innovation (0.0495) rather than energy-saving innovation (-0.0227); (3) The multi-period DDD (Difference in Difference in Difference) model revealed that low-carbon city policy promoted green innovation with a diminishing trend; (4) The voluntary environmental regulation signals, ISO14001 certification, displayed a substitute effect for managerial capacity on enterprise green innovation. This paper provides recommendations, including that enterprises should improve the utilization of new and renewable energy while improving and optimizing production processes. The government should also improve innovation incentive policies and strengthen environmental information disclosure.

Characterization of chicken interleukin-9 receptor alpha chain.

Interleukin-9 receptor alpha chain (IL-9Rα) is the ligand-binding subunit of IL-9R that plays roles in IL-9-mediated allergy, inflammation, infection, and tumor immunity. While mammalian IL-9Rαs have been extensively investigated, avian IL-9Rα has not yet been identified and characterized. In this study, we cloned chicken IL-9Rα (chIL-9Rα) and performed a phylogenetic analysis, analyzed its tissue distribution, characterized the expression form of natural chIL-9Rα. Phylogenetic analysis showed that chIL-9Rα has less than 25% amino acid homology with mammalian IL-9Rαs. The chIL-9Rα mRNA was abundantly detected only in heart and mitogen-activated peripheral blood mononuclear cells. Furthermore, 4 monoclonal antibodies (mAbs) against chIL-9Rα were generated using prokaryotic recombinant chIL-9Rα (rchIL-9Rα). Using anti-chIL-9Rα mAbs, natural chIL-9Rα expressed on the splenocytes of chickens was observed by indirect immunofluorescence assay (IFA), and its molecular weight of 51 kDa was identified by Western blotting. Overall, our study reveals for the first time the presence of IL-9Rα in birds, and provides immunological tools for further investigating the roles of chIL-9 in diseases and immunity.

Quaternized carbon dots with enhanced antimicrobial ability towards Gram-negative bacteria for the treatment of acute peritonitis caused by E. coli.

Infections caused by Gram-negative bacteria still pose a clinical challenge. Although nanomaterials have been developed for antibacterial treatments, a systematic evaluation of the mechanisms and intervention models of antibacterial materials toward Gram-negative bacteria is still lacking. Herein, antibacterial quaternized carbon dots (QCDs) were synthesized via a one-step melting method using anhydrous citric acid and diallyl dimethyl ammonium chloride (DDA). The QCDs exhibited effective broad-spectrum antibacterial activity and enhanced inhibitory ability towards Gram-negative bacteria. The antibacterial mechanism of the QCDs with respect to Gram-negative bacteria was investigated through the characterization of bacterial morphology changes, the absorption modes of the QCDs on bacteria, and the potential generation of reactive oxygen species by the QCDs. The QCDs showed low toxicity in different cells, and did not cause hemolysis. The QCDs were administered via intraperitoneal injection to treat acute peritonitis in mice infected with E. coli. Routine blood examination, magnetic resonance imaging, and pathological analysis were undertaken and it was found that, similar to the positive control group treated with gentamicin sulfate, the QCDs exhibited a therapeutic effect that eliminated infection and inflammation. This study explores a controllable synthetic strategy for the synthesis of active carbon dots with antibacterial activity, a material that is a promising candidate for new treatments of Gram-negative bacterial infections.

Correlation between retinal structure and brain multimodal magnetic resonance imaging in patients with Alzheimer's disease.

Background: The retina imaging and brain magnetic resonance imaging (MRI) can both reflect early changes in Alzheimer's disease (AD) and may serve as potential biomarker for early diagnosis, but their correlation and the internal mechanism of retinal structural changes remain unclear. This study aimed to explore the possible correlation between retinal structure and visual pathway, brain structure, intrinsic activity changes in AD patients, as well as to build a classification model to identify AD patients. Methods: In the study, 49 AD patients and 48 healthy controls (HCs) were enrolled. Retinal images were obtained by optical coherence tomography (OCT). Multimodal MRI sequences of all subjects were collected. Spearman correlation analysis and multiple linear regression models were used to assess the correlation between OCT parameters and multimodal MRI findings. The diagnostic value of combination of retinal imaging and brain multimodal MRI was assessed by performing a receiver operating characteristic (ROC) curve. Results: Compared with HCs, retinal thickness and multimodal MRI findings of AD patients were significantly altered (p < 0.05). Significant correlations were presented between the fractional anisotropy (FA) value of optic tract and mean retinal thickness, macular volume, macular ganglion cell layer (GCL) thickness, inner plexiform layer (IPL) thickness in AD patients (p < 0.01). The fractional amplitude of low frequency fluctuations (fALFF) value of primary visual cortex (V1) was correlated with temporal quadrant peripapillary retinal nerve fiber layer (pRNFL) thickness (p < 0.05). The model combining thickness of GCL and temporal quadrant pRNFL, volume of hippocampus and lateral geniculate nucleus, and age showed the best performance to identify AD patients [area under the curve (AUC) = 0.936, sensitivity = 89.1%, specificity = 87.0%]. Conclusion: Our study demonstrated that retinal structure change was related to the loss of integrity of white matter fiber tracts in the visual pathway and the decreased LGN volume and functional metabolism of V1 in AD patients. Trans-synaptic axonal retrograde lesions may be the underlying mechanism. Combining retinal imaging and multimodal MRI may provide new insight into the mechanism of retinal structural changes in AD and may serve as new target for early auxiliary diagnosis of AD.

The associations of APP, PSEN1, and PSEN2 genes with Alzheimer's disease: A large case-control study in Chinese population.

AIM: The associations of non-pathogenic variants of APP, PSEN1, and PSEN2 with Alzheimer's disease (AD) remain unclear. This study is aimed at determining the role of these variants in AD. METHODS: Our study recruited 1154 AD patients and 2403 controls. APP, PSEN1, PSEN2, and APOE were sequenced using a targeted panel. Variants were classified into common or rare variants with the minor allele frequencies (MAF) cutoff of 0.01. Common variant (MAF≥0.01)-based association test was performed by PLINK 1.9, and gene-based (MAF <0.01) association analysis was conducted using Sequence Kernel Association Test-Optimal (SKAT-O test). Additionally, using PLINK 1.9, we performed AD endophenotypes association studies. RESULTS: A common variant, PSEN2 rs11405, was suggestively associated with AD risk (p = 1.08 × 10-2 ). The gene-based association analysis revealed that the APP gene exhibited a significant association with AD (p = 1.43 × 10-2 ). In the AD endophenotypes association studies, APP rs459543 was nominally correlated with CSF Aß42 level (p = 7.91 × 10-3 ). CONCLUSION: Our study indicated that non-pathogenic variants in PSEN2 and APP may be involved in AD pathogenesis in the Chinese population.

The role of digitalization on green economic growth: Does industrial structure optimization and green innovation matter?

The digital economy has demonstrated strong resilience and great potential, under the interwoven influence of the global pandemic and severe environmental concerns across the world. Therefore, there is a need to focus on the value of green economic growth in the digital economy. This paper constructs an evaluation index system and adopts the SEEA (System of Environmental and Economic Accounting) method to measure the digitalization level (Digi) and green economy growth level (GEG) of China. The internal mechanism and linear relationship between digitalization and green economy growth are examined based on the panel data from 2013 to 2019. Moreover, this study explores the spatial spillover effect. The major study findings are as follows: (1) Digitalization and green economy growth represent a steady growth trend, and the former as a whole significantly promotes the latter, with a marginal effect of 1.648. (2) The mechanism analysis indicates the intermediary effects' size of three crucial intermediaries: green technology innovation > advanced industrial structure > the rationalization of industrial structure. (3) Both the "local effect" (0.556; 0.574) and "neighboring effect" (1.382; 1.415) of digitalization on green economy growth are positive under the two weight matrices and display "simultaneous resonance" characteristics based on the spatial perspective. (4) There exists obvious regional spatial heterogeneity and resource endowment heterogeneity. Finally, this study put forward corresponding policy implications, such as construction of new digital infrastructures and guiding green-energy consumption.

Clinical characteristics and genotype-phenotype correlation analysis of familial Alzheimer's disease patients with pathogenic/likely pathogenic amyloid protein precursor mutations.

Alzheimer's disease (AD) is a progressive neurodegenerative disease associated with aging, environmental, and genetic factors. Amyloid protein precursor (APP) is a known pathogenic gene for familial Alzheimer's disease (FAD), and now more than 70 APP mutations have been reported, but the genotype-phenotype correlation remains unclear. In this study, we collected clinical data from patients carrying APP mutations defined as pathogenic/likely pathogenic according to the American college of medical genetics and genomics (ACMG) guidelines. Then, we reanalyzed the clinical characteristics and identified genotype-phenotype correlations in APP mutations. Our results indicated that the clinical phenotypes of APP mutations are generally consistent with typical AD despite the fact that they show more non-demented symptoms and neurological symptoms. We also performed genotype-phenotype analysis according to the difference in APP processing caused by the mutations, and we found that there were indeed differences in onset age, behavioral and psychological disorders of dementia (BPSD) and myoclonus.

Macular Microvascular Density as a Diagnostic Biomarker for Alzheimer's Disease.

BACKGROUND: Some previous studies showed abnormal pathological and vascular changes in the retina of patients with Alzheimer's disease (AD). However, whether retinal microvascular density is a diagnostic indicator for AD remains unclear. OBJECTIVE: This study evaluated the macular vessel density (m-VD) in the superficial capillary plexus and fovea avascular zone (FAZ) area in AD, explored their correlations with clinical parameters, and finally confirmed an optimal machine learning model for AD diagnosis. METHODS: 77 patients with AD and 145 healthy controls (HCs) were enrolled. The m-VD and the FAZ area were measured using optical coherence tomography angiography (OCTA) in all participants. Additionally, AD underwent neuropsychological assessment, brain magnetic resonance imaging scan, cerebrospinal fluid (CSF) biomarker detection, and APOE ɛ4 genotyping. Finally, the performance of machine learning algorithms based on the OCTA measurements was evaluated by Python programming language. RESULTS: The m-VD was noticeably decreased in AD compared with HCs. Moreover, m-VD in the fovea, superior inner, inferior inner, nasal inner subfields, and the whole inner ring declined significantly in mild AD, while it was more serious in moderate/severe AD. However, no significant difference in the FAZ was noted between AD and HCs. Furthermore, we found that m-VD exhibited a significant correlation with cognitive function, medial temporal atrophy and Fazekas scores, and APOE ɛ4 genotypes. No significant correlations were observed between m-VD and CSF biomarkers. Furthermore, results revealed the Adaptive boosting algorithm exhibited the best diagnostic performance for AD. CONCLUSION: Macular vascular density could serve as a diagnostic biomarker for AD.

Machine learning based on Optical Coherence Tomography images as a diagnostic tool for Alzheimer's disease.

AIMS: We mainly evaluate retinal alterations in Alzheimer's disease (AD) patients, investigate the associations between retinal changes with AD biomarkers, and explore an optimal machine learning (ML) model for AD diagnosis based on retinal thickness. METHODS: A total of 159 AD patients and 299 healthy controls were enrolled. The retinal parameters of each participant were measured using optical coherence tomography (OCT). Additionally, cognitive impairment severity, brain atrophy, and cerebrospinal fluid (CSF) biomarkers were measured in AD patients. RESULTS: AD patients demonstrated a significant decrease in the average, superior, and inferior quadrant peripapillary retinal nerve fiber layer, macular retinal nerve fiber layer, ganglion cell layer (GCL), inner plexiform layer (IPL) thicknesses, as well as total macular volume (TMV) (all p < 0.05). Moreover, TMV was positively associated with Mini-Mental State Examination and Montreal Cognitive Assessment scores, IPL thickness was correlated negatively with the medial temporal lobe atrophy score, and the GCL thickness was positively correlated with CSF Aß42 /Aß40 and negatively associated with p-tau level. Based on the significantly decreased OCT variables between both groups, the XGBoost algorithm exhibited the best diagnostic performance for AD, whose four references, including accuracy, area under the curve, f1 score, and recall, ranged from 0.69 to 0.74. Moreover, the macular retinal thickness exhibited an absolute superiority for AD diagnosis compared with other enrolled variables in all ML models. CONCLUSION: We identified the retinal alterations in AD patients and found that macular thickness and volume were associated with AD severity and biomarkers. Furthermore, we confirmed that OCT combined with ML could serve as a potential diagnostic tool for AD.

Can the digital economy development curb carbon emissions? Evidence from China.

"Carbon neutrality, carbon peaking" is China's national commitment to the whole world about its plans to manage global climate change. China faces many severe challenges in fulfilling its commitments to reduce emissions. China's digital economy is currently booming, and whether it can provide opportunities for reducing regional carbon emissions is worth exploring. This study constructed a comprehensive system to evaluate the development of its digital economy based on China's regional data and empirically tested the direct, indirect, and spatial effects of the comprehensive development of digital economy on regional carbon emissions. In addition, it examined the special stage characteristics using a Hansen threshold model. This study found the following: first, the digital economy significantly suppresses carbon emissions in general, notably with a spatial spillover effect to neighboring provinces. Secondly, an analysis of the mechanism shows that the comprehensive development of a digital economy can restrain regional carbon emissions through industrial progress and the optimization of energy consumption. Third, there are double thresholds, special driving trends and an "inverted N-type" relationship with development. Fourth, a spatial heterogeneity analysis revealed that significant "local" and "neighboring" impacts on the reduction of carbon emissions only exist in the central and eastern areas. This study has a reference value for releasing the dividend of digital economy development and reducing carbon emissions.

A dominant internal gene cassette of high pathogenicity avian influenza H7N9 virus raised since 2018.

The zoonotic H7N9 avian influenza virus emerged with the H9N2-origin internal gene cassette. Previous studies have reported that genetic reassortments with H9N2 were common in the first five human H7N9 epidemic waves. However, our latest work found that the circulating high pathogenicity H7N9 virus has established a dominant internal gene cassette and has decreased the frequency of reassortment with H9N2 since 2018. This dominant cassette of H7N9 was distinct from the cocirculating H9N2, although they shared a common ancestor. As a result, we suppose that this dominant cassette may benefit the viral population fitness and promote its continuous circulation in chickens.

Effects of different concentrations of intraluminal sodium chloride solution on intracavitary ECG used for arm infusion port implantation.

At present, there are few clinical studies on the application of high-concentration sodium chloride solutions in intracavitary ECG-guided catheter tip localization during the arm infusion port implantation. This study observed the effects of sodium chloride solutions with different concentrations on intracavitary ECG-guided arm infusion port implantation in the patients with cancer. The 657 patients receiving arm infusion port implantation in our hospital between January 2020 and August 2021 were randomly divided into 0.9% sodium chloride solution conduction group (group A), 5.45% sodium chloride solution conduction group (group B) and 10% sodium chloride solution conduction group (group C). The derived rate of stable intracavitary ECG, the occurrence rate of characteristic P wave, the time used for catheter tip localization and the optimal position rate of catheter tip were compared between the three groups. The derived rate of stable intracavitary ECG was significantly higher in the group B (97.78%) and group C (98.63%) than in the group A (93.90%) (all P < 0.05). The occurrence rate of characteristic P wave was also significantly higher in the group B (96.89%) and group C (97.72%) than in the group A (88.73%) (all P < 0.001). The time used for catheter tip localization was significantly shorter in the group B [(49.73 ± 8.15) s] and group C [(48.27 ± 8.61) s] than in the group A [(69.37 ± 19.99) s] (all P < 0.001). There was no significant difference in the optimal position rate of catheter tip among the three groups (P > 0.05). The 5.45% and 10% sodium chloride solutions are significantly superior comparing with 0.9% sodium chloride solution in the derived rate of stable intracavitary ECG, occurrence rate of characteristic P wave and time used for catheter tip localization, but there were no significant differences between 5.45 and 10% sodium chloride solutions. Moreover, the 5.45% sodium chloride solution is closer to physiological state comparing with 10% sodium chloride solution, so the 5.45% sodium chloride solution may be recommended for the intracavitary ECG-guided arm infusion port implantation.

CYLD variants identified in Alzheimer's disease and frontotemporal dementia patients.

OBJECTIVES: CYLD was a novel causative gene for frontotemporal dementia (FTD) and amyotrophic lateral sclerosis. Given the clinical and pathological overlap of FTD and Alzheimer's disease (AD), it is necessary to screen CYLD in AD patients and FTD patients in the Chinese population. METHODS: In our study, using a targeted sequencing panel, we sequenced the CYLD gene in a large cohort of 2485 participants in the Chinese population, including 1008 AD patients, 105 FTD patients, and 1372 controls. RESULTS: In the present study, the average onset age of AD and FTD patients was 66.84 ± 30.42 years old and 60 ± 10.00 years old, respectively. Our study reported three novel CYLD variants: p.Phe288Leu (patient No. 1, AD), p.Tyr485Phe (patients No. 6-9, all AD) and p.Thr951Ala (patient No. 10, AD), plus a previously reported variant: p.Arg397Ser (patient No. 2-5, AD and No. 11, FTD). These variants were absent in our in-house controls and predicted to be deleterious according to the MutationTaster. The variant carriers were composed of 10 AD patients and one FTD patient, and the average onset age was 61.2 ± 10.9 years. The frequency of CYLD variants in AD was similar to that in FTD, which was 0.99% (10/1008) and 0.95% (1/105), respectively. INTERPRETATION: Our finding extended the genotype and phenotype of the CYLD gene and demonstrated that CYLD rare damaging variants may be implicated in AD and FTD pathogenesis.

Dairy Cows Experimentally Infected With Bovine Leukemia Virus Showed an Increased Milk Production in Lactation Numbers 3-4: A 4-Year Longitudinal Study.

Bovine leukemia virus (BLV) is widespread in global cattle populations, but the effects of its infection on milk quantity and quality have not been clearly elucidated in animal models. In this study, 30 healthy first-lactation cows were selected from ≈2,988 cows in a BLV-free farm with the same criteria of parity, age, lactation number, as well as milk yield, SCS, and composition (fat, protein, and lactose). Subsequently, these cows were randomly assigned to the intervention (n = 15) or control (n = 15) group, and reared in different cowsheds. Cows in the intervention group were inoculated with 1 × phosphate-buffered solution (PBS) resuspended in peripheral blood mononuclear cells (PBMC) from a BLV-positive cow, while the controls were inoculated with the inactivated PBMC from the same individual. From June 2016 to July 2021, milk weight (kg) was automatically recorded by milk sensors, and milk SCS and composition were originated from monthly performed dairy herd improvement (DHI) testing. Fluorescence resonance energy transfer (FRET)-qPCR and ELISA showed that cows in the intervention group were successfully infected with BLV, while cows in the control group were free of BLV for the entire period. At 45 days post-inoculation (DPI), the numbers of whole blood cells (WBCs) (P = 0.010), lymphocytes (LYMs) (P = 0.002), and monocytes (MNCs) (P = 0.001) and the expression levels of IFN-γ (P = 0.013), IL-10 (P = 0.031), and IL-12p70 (P = 0.008) increased significantly in the BLV infected cows compared to the non-infected. In lactation numbers 2-4, the intervention group had significantly higher overall milk yield (P < 0.001), fat (P = 0.031), and protein (P = 0.050) than the control group, while milk SCS (P = 0.038) and lactose (P = 0.036) decreased significantly. Further analysis indicated that BLV infection was associated with increased milk yield at each lactation stage in lactation numbers 3-4 (P = 0.021 or P < 0.001), but not with SCS and milk composition. Together, this 4-year longitudinal study revealed that artificial inoculation of BLV increased the milk yield in cows in this BLV challenge model.

First Characterization of Chicken Interleukin-9.

Interleukin-9 (IL-9) is a pleiotropic cytokine that acts on a variety of cells and tissues, and plays roles in inflammation and infection as well as tumor immunity. While mammalian IL-9s have been widely investigated, avian IL-9 has not yet been identified and characterized. In this study, we cloned chicken IL-9 (chIL-9) and performed a phylogenetic analysis, examined its tissue distribution, characterized the biological functions of recombinant chIL-9 (rchIL-9) and the expression form of natural chIL-9. Phylogenetic analysis showed that chIL-9 has less than 30% amino acid identity with mammalian IL-9s. The chIL-9 mRNA can be abundantly detected only in the testis and thymus, and are significantly up-regulated in peripheral blood mononuclear cells (PBMCs) upon mitogen stimulation. The rchIL-9 was produced by prokaryotic and eukaryotic expression systems and showed biological activity in activating monocytes/macrophages to produce inflammatory cytokines and promoting the proliferation of CD3+ T cells. In addition, four monoclonal antibodies (mAbs) and rabbit polyclonal antibody (pAb) against rchIL-9 were generated. Using anti-chIL-9 mAbs and pAb, natural chIL-9 expressed by the activated PBMCs of chickens with a molecular weight of 25kD was identified by Western-blotting. Collectively, our study reveals for the first time the presence of functional IL-9 in birds and lays the ground for further investigating the roles of chIL-9 in diseases and immunity.

Genome-Wide Reassortment Analysis of Influenza A H7N9 Viruses Circulating in China during 2013-2019.

Reassortment with the H9N2 virus gave rise to the zoonotic H7N9 avian influenza virus (AIV), which caused more than five outbreak waves in humans, with high mortality. The frequent exchange of genomic segments between H7N9 and H9N2 has been well-documented. However, the reassortment patterns have not been described and are not yet fully understood. Here, we used phylogenetic analyses to investigate the patterns of intersubtype and intrasubtype/intralineage reassortment across the eight viral segments. The H7N9 virus and its progeny frequently exchanged internal genes with the H9N2 virus but rarely with the other AIV subtypes. Before beginning the intrasubtype/intralineage reassortment analyses, five Yangtze River Delta (YRD A-E) and two Pearl River Delta (PRD A-B) clusters were divided according to the HA gene phylogeny. The seven reset segment genes were also nomenclatured consistently. As revealed by the tanglegram results, high intralineage reassortment rates were determined in waves 2-3 and 5. Additionally, the clusters of PB2 c05 and M c02 were the most dominant in wave 5, which could have contributed to the onset of the largest H7N9 outbreak in 2016-2017. Meanwhile, a portion of the YRD-C cluster (HP H7N9) inherited their PB2, PA, and M segments from the co-circulating YRD-E (LP H7N9) cluster during wave 5. Untanglegram results revealed that the reassortment rate between HA and NA was lower than HA with any of the other six segments. A multidimensional scaling plot revealed a robust genetic linkage between the PB2 and PA genes, indicating that they may share a co-evolutionary history. Furthermore, we observed relatively more robust positive selection pressure on HA, NA, M2, and NS1 proteins. Our findings demonstrate that frequent reassortment, particular reassorted patterns, and adaptive mutations shaped the H7N9 viral genetic diversity and evolution. Increased surveillance is required immediately to better understand the current state of the HP H7N9 AIV.

Development of a Monoclonal Antibody to Pig CD69 Reveals Early Activation of T Cells in Pig after PRRSV and ASFV Infection.

The CD69 molecule, as an early activation marker of lymphocytes, is often used to assess the activation of cellular immunity. However, for pigs, an anti-pig CD69 antibody is not yet available for this purpose after infection or vaccination. In this study, a monoclonal antibody (mAb) against pig CD69 was produced by peptide immunization and hybridoma technique. One mAb (5F12) showed good reactivity with pig CD69 that was expressed in transfected-HEK-293T cells and on mitogen-activated porcine peripheral blood mononuclear cells (PBMCs) by indirect immunofluorescence assay and flow cytometry. This mAb did not cross-react with activated lymphocytes from mouse, bovine, and chicken. Epitope mapping showed that the epitope recognized by this mAb was located at amino acid residues 147-161 of pig CD69. By conjugating with fluorochrome, this mAb was used to detect the early activation of lymphocytes in PRRSV- and ASFV-infected pigs by flow cytometry. The results showed that PRRSV infection induced the dominant activation of CD4 T cells in mediastinal lymph nodes and CD8 T cells in the spleen at 14 days post-infection, in terms of CD69 expression. In an experiment on ASFV infection, we found that ASFV infection resulted in the early activation of NK cells, B cells, and distinct T cell subsets with variable magnitude in PBMCs, spleen, and submandibular lymph nodes. Our study revealed an early event of lymphocyte and T cell activation after PRRSV and ASFV infections and provides an important immunological tool for the in-depth analysis of cellular immune response in pigs after infection or vaccination.