Large-scale population structure and genetic architecture of agronomic traits of garlic.

Garlic, an asexually propagated crop, is the second important bulb crop after the onion and is used as a vegetable and medicinal plant. Abundant and diverse garlic resources have been formed over thousands of years of cultivation. However, genome variation, population structure and genetic architecture of garlic agronomic traits were still not well elucidated. Here, 1 100 258 single nucleotide polymorphisms (SNPs) were identified using genotyping-by-sequencing in 606 garlic accessions collected from 43 countries. Population structure, principal component and phylogenetic analysis showed that these accessions were divided into five subpopulations. Twenty agronomic traits, including above-ground growth traits, bulb-related and bolt-related traits in two consecutive years were implemented in a genome-wide association study. In total, 542 SNPs were associated with these agronomic traits, among which 188 SNPs were repeatedly associated with more than two traits. One SNP (chr6: 1896135972) was repeatedly associated with ten traits. These associated SNPs were located within or near 858 genes, 56 of which were transcription factors. Interestingly, one non-synonymous SNP (Chr4: 166524085) in ribosomal protein S5 was repeatedly associated with above-ground growth and bulb-related traits. Additionally, gene ontology enrichment analysis of candidate genes for genomic selection regions between complete-bolting and non-bolting accessions showed that these genes were significantly enriched in 'vegetative to reproductive phase transition of meristem', 'shoot system development', 'reproductive process', etc. These results provide valuable information for the reliable and efficient selection of candidate genes to achieve garlic genetic improvement and superior varieties.

Condensate cooperativity underlies transgenerational gene silencing.

Biomolecular condensates have been shown to interact in vivo, yet it is unclear whether these interactions are functionally meaningful. Here, we demonstrate that cooperativity between two distinct condensates-germ granules and P bodies-is required for transgenerational gene silencing in C. elegans. We find that P bodies form a coating around perinuclear germ granules and that P body components CGH-1/DDX6 and CAR-1/LSM14 are required for germ granules to organize into sub-compartments and concentrate small RNA silencing factors. Functionally, while the P body mutant cgh-1 is competent to initially trigger gene silencing, it is unable to propagate the silencing to subsequent generations. Mechanistically, we trace this loss of transgenerational silencing to defects in amplifying secondary small RNAs and the stability of WAGO-4 Argonaute, both known carriers of gene silencing memories. Together, these data reveal that cooperation between condensates results in an emergent capability of germ cells to establish heritable memory.

Microbiome Signature of Endophytes in Wheat Seed Response to Wheat Dwarf Bunt Caused by Tilletia controversa Kühn.

Wheat dwarf bunt leads to the replacement of seeds with fungal galls containing millions of teliospores of the pathogen Tilletia controversa Kühn. As one of the most devastating internationally quarantined wheat diseases, wheat dwarf bunt spreads to cause distant outbreaks by seeds containing teliospores. In this study, based on a combination of amplicon sequencing and isolation approaches, we analyzed the seed microbiome signatures of endophytes between resistant and susceptible cultivars after infection with T. controversa. Among 310 bacterial species obtained only by amplicon sequencing and 51 species obtained only by isolation, we found 14 overlapping species by both methods; we detected 128 fungal species only by amplicon sequencing, 56 only by isolation, and 5 species by both methods. The results indicated that resistant uninfected cultivars hosted endophytic communities that were much more stable and beneficial to plant health than those in susceptible infected cultivars. The susceptible group showed higher diversity than the resistant group, the infected group showed more diversity than the uninfected group, and the microbial communities in seeds were related to infection or resistance to the pathogen. Some antagonistic microbes significantly suppressed the germination rate of the pathogen's teliospores, providing clues for future studies aimed at developing strategies against wheat dwarf bunt. Collectively, this research advances the understanding of the microbial assembly of wheat seeds upon exposure to fungal pathogen (T. controversa) infection. IMPORTANCE This is the first study on the microbiome signature of endophytes in wheat seed response to wheat dwarf bunt caused by Tilletia controversa Kühn. Some antagonistic microbes suppressed the germination of teliospores of the pathogen significantly, which will provide clues for future studies against wheat dwarf bunt. Collectively, this research first advances the understanding of the microbial assembly of wheat seed upon exposure to the fungal pathogen (T. controversa) infection.

Assessment and management of radiation-induced trismus in patients with nasopharyngeal carcinoma: a best practice implementation project.

INTRODUCTION AND AIMS: Intensity-modulated radiotherapy (IMRT) is the most commonly used radiotherapy technology in oncology, which enables precise conformation of the radiation dose to the target volume and reduces the risk of radiation damage to the adjacent normal structures. Nevertheless, it is still inevitable for IMRT of head and neck cancer to cause radiation-related toxic and side effects, such as dry mouth, mucositis, oral dysarthria, taste disorder, osteonecrosis, and trismus. Trismus is one of the most common late side effects caused by radiotherapy of nasopharyngeal carcinoma (NPC), which seriously affects the quality of life for patients with NPC. However, the current clinical assessment and management of trismus after radiotherapy for NPC are still imperfect. This best practice implementation project aimed to implement an evidence-based practice in assessing and managing trismus for NPC patients who underwent radiotherapy, thereby improving the compliance of clinical practice with the best evidence and the quality of life of patients with NPC. METHODS: This evidence-based audit and feedback project was implemented using a three-phase approach at a third-class hospital in China, following JBI's Practical Application of Clinical Evidence System (PACES) and GRiP evidence application. The first phase included a baseline audit with six evidence-based audit criteria derived from the best available evidence. The second phase included analyzing the results of the baseline audit, identifying barriers to compliance with best practice principles, and developing and implementing strategies to address the barriers identified in the baseline audit. The third phase involved a follow-up audit to assess the results of the interventions implemented to improve practice. RESULTS: After evidence application, the compliance rate for audit criterion 1 increased from 0% at baseline audit to 70% at follow-up audit. The compliance rate for audit criterion 2 increased from 0% to 100%. The compliance rate for audit criterion 3 increased from 22 to 62%. The compliance rate for audit criterion 4 increased from 88 to 100%. The compliance rate for audit criterion 5 was 100% at baseline audit and follow-up audit. The compliance rate for audit criterion 6 increased from 0 to 55%. CONCLUSION: Implementation of the best evidence for the assessment and management of trismus of patients with NPC after radiotherapy is conducive to improving the compliance of clinical practice with the best evidence, standardizing clinical nursing practice, improving the quality of clinical nursing, and better preventing severe trismus in patients with NPC after radiotherapy.

Predicting Drug-Target Affinity Based on Recurrent Neural Networks and Graph Convolutional Neural Networks.

BACKGROUND: Drug development requires a lot of money and time, and the outcome of the challenge is unknown. So, there is an urgent need for researchers to find a new approach that can reduce costs. Therefore, the identification of drug-target interactions (DTIs) has been a critical step in the early stages of drug discovery. These computational methods aim to narrow the search space for novel DTIs and to elucidate the functional background of drugs. Most of the methods developed so far use binary classification to predict the presence or absence of interactions between the drug and the target. However, it is more informative but also more challenging to predict the strength of the binding between a drug and its target. If the strength is not strong enough, such a DTI may not be useful. Hence, the development of methods to predict drug-target affinity (DTA) is of significant importance Method: We have improved the GraphDTA model from a dual-channel model to a triple-channel model. We interpreted the target/protein sequences as time series and extracted their features using the LSTM network. For the drug, we considered both the molecular structure and the local chemical background, retaining the four variant networks used in GraphDTA to extract the topological features of the drug and capturing the local chemical background of the atoms in the drug by using BiGRU. Thus, we obtained the latent features of the target and two latent features of the drug. The connection of these three feature vectors is then inputted into a 2 layer FC network, and a valuable binding affinity is the output. RESULT: We used the Davis and Kiba datasets, using 80% of the data for training and 20% of the data for validation. Our model showed better performance when compared with the experimental results of GraphDTA Conclusion: In this paper, we altered the GraphDTA model to predict drug-target affinity. It represents the drug as a graph and extracts the two-dimensional drug information using a graph convolutional neural network. Simultaneously, the drug and protein targets are represented as a word vector, and the convolutional neural network is used to extract the time-series information of the drug and the target. We demonstrate that our improved method has better performance than the original method. In particular, our model has better performance in the evaluation of benchmark databases.

Inhibitory Effect of Bovine Adipose-Derived Mesenchymal Stem Cells on Lipopolysaccharide Induced Inflammation of Endometrial Epithelial Cells in Dairy Cows.

Endometritis is a disease that affects reproductive health in dairy cows and causes serious economic damage to the dairy industry world-wide. Although in recent years, the application of mesenchymal stem cell (MSC) therapy for the treatment of inflammatory diseases has attracted much attention, there are few reports of the use of MSCs in dairy cows. In the present study, our objective was to explore the inhibitory effects of bovine adipose-derived mesenchymal stem cells (bAD-MSCs) on lipopolysaccharide (LPS) induced inflammation in bovine endometrial epithelial cells (bEECs) along with the potential underlying molecular mechanisms. We characterized isolated bAD-MSCs using cell surface marker staining and adipogenic/osteogenic differentiation, and analyzed them using immunofluorescence, flow cytometry (surface marker staining), and adipogenic and osteogenic differentiation. Furthermore, to understand the anti-inflammatory effects of bAD-MSCs on LPS induced bEEC inflammation, we used a bAD-MSC/bEEC co-culture system. The results showed that bAD-MSC treatments could significantly decrease LPS induced bEEC apoptosis and pro-inflammatory cytokine expression levels, such as interleukin-1ß (IL-1ß), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α). Furthermore, our results showed that bAD-MSC treatments could also significantly downregulate LPS induced p38, IkB-a, and JAK1 phosphorylation and Bax protein expression levels, which are closely related to inflammatory progress and cellular apoptosis in bEECs. Our findings demonstrate that bAD-MSCs play an inhibitory role in LPS induced bEEC inflammation and provide new insights for the clinical therapy of endometritis in dairy cows.

Accurate Prediction of Stroke for Hypertensive Patients Based on Medical Big Data and Machine Learning Algorithms: Retrospective Study.

BACKGROUND: Stroke risk assessment is an important means of primary prevention, but the applicability of existing stroke risk assessment scales in the Chinese population has always been controversial. A prospective study is a common method of medical research, but it is time-consuming and labor-intensive. Medical big data has been demonstrated to promote disease risk factor discovery and prognosis, attracting broad research interest. OBJECTIVE: We aimed to establish a high-precision stroke risk prediction model for hypertensive patients based on historical electronic medical record data and machine learning algorithms. METHODS: Based on the Shenzhen Health Information Big Data Platform, a total of 57,671 patients were screened from 250,788 registered patients with hypertension, of whom 9421 had stroke onset during the 3-year follow-up. In addition to baseline characteristics and historical symptoms, we constructed some trend characteristics from multitemporal medical records. Stratified sampling according to gender ratio and age stratification was implemented to balance the positive and negative cases, and the final 19,953 samples were randomly divided into a training set and test set according to a ratio of 7:3. We used 4 machine learning algorithms for modeling, and the risk prediction performance was compared with the traditional risk scales. We also analyzed the nonlinear effect of continuous characteristics on stroke onset. RESULTS: The tree-based integration algorithm extreme gradient boosting achieved the optimal performance with an area under the receiver operating characteristic curve of 0.9220, surpassing the other 3 traditional machine learning algorithms. Compared with 2 traditional risk scales, the Framingham stroke risk profiles and the Chinese Multiprovincial Cohort Study, our proposed model achieved better performance on the independent validation set, and the area under the receiver operating characteristic value increased by 0.17. Further nonlinear effect analysis revealed the importance of multitemporal trend characteristics in stroke risk prediction, which will benefit the standardized management of hypertensive patients. CONCLUSIONS: A high-precision 3-year stroke risk prediction model for hypertensive patients was established, and the model's performance was verified by comparing it with the traditional risk scales. Multitemporal trend characteristics played an important role in stroke onset, and thus the model could be deployed to electronic health record systems to assist in more pervasive, preemptive stroke risk screening, enabling higher efficiency of early disease prevention and intervention.

The APC/CFZY-1/Cdc20 Complex Coordinates With OMA-1 to Regulate the Oocyte-to-Embryo Transition in Caenorhabditis elegans.

During oocyte maturation and the oocyte-to-embryo transition, key developmental regulators such as RNA-binding proteins coordinate translation of particular messenger RNA (mRNAs) and related developmental processes by binding to their cognate maternal mRNAs. In the nematode Caenorhabditis elegans, these processes are regulated by a set of CCCH zinc finger proteins. Oocyte maturation defective-1 (OMA-1) and OMA-2 are two functionally redundant CCCH zinc finger proteins that turnover rapidly during the first embryonic cell division. These turnovers are required for proper transition from oogenesis to embryogenesis. A gain-of-function mutant of OMA-1, oma-1(zu405), stabilizes and delays degradation of OMA-1, resulting in delayed turnover and mis-segregation of other cell fate determinants, which eventually causes embryonic lethality. We performed a large-scale forward genetic screen to identify suppressors of the oma-1(zu405) mutant. We show here that multiple alleles affecting functions of various anaphase promoting complex/cyclosome (APC/C) subunits, including MAT-1, MAT-2, MAT-3, EMB-30, and FZY-1, suppress the gain-of-function mutant of OMA-1. Transcriptome analysis suggested that overall transcription in early embryos occurred after introducing mutations in APC/C genes into the oma-1(zu405) mutant. Mutations in APC/C genes prevent OMA-1 enrichment in P granules and correct delayed degradation of downstream cell fate determinants including pharynx and intestine in excess-1 (PIE-1), posterior segregation-1 (POS-1), muscle excess-3 (MEX-3), and maternal effect germ-cell defective-1 (MEG-1). We demonstrated that only the activator FZY-1, but not FZR-1, is incorporated in the APC/C complex to regulate the oocyte-to-embryo transition. Our findings suggested a genetic relationship linking the APC/C complex and OMA-1, and support a model in which the APC/C complex promotes P granule accumulation and modifies RNA binding of OMA-1 to regulate the oocyte-to-embryo transition process.

G-CSF and IL-6 may be involved in formation of endometriosis lesions by increasing the expression of angiogenic factors in neutrophils.

Evidence accumulated in recent years has revealed that neutrophils are involved in the initial establishment of endometriosis, which is well-known as a chronic inflammatory disease. So far, why and how neutrophils promote the formation of early endometriosis are still unclear. In this study, using a mouse model of endometriosis, we demonstrated that endometriosis mice (EMs mice) had a significantly increased number of neutrophils in peritoneal fluids and lesions, and increased levels of granulocyte colony-stimulating factor (G-CSF) and IL-6 in serum and peritoneal fluids compared to the control group. In the neutrophils and uterine fragments co-injection experiment, neutrophils regulated by G-CSF and IL-6 had a similar effect to neutrophils from EMs mice, increasing the number, area, weight and microvessel density (MVD) of endometriotic lesions. Blocking the effect of G-CSF and IL-6 in EMs mice resulted in a decrease in the number, area and weight of endometriotic lesions. Following the depletion of neutrophils in vivo using a anti-Ly6G antibody, the MVD in the lesions of mice treated with neutrophils from EMs mice and neutrophils from pG/pI6 mice were significantly reduced. Neutrophils from EMs mice and neutrophils from pG/pI6 mice altered the expression levels of Mmp9, Bv8 and Trail genes compared to the neutrophils from PBS-treated mice. IL-6 together with G-CSF induced a higher expression of phospho-STAT3 and STAT3 in neutrophils. These findings suggest that neutrophils modulated by G-CSF and IL-6 through the STAT3 pathway alter the expression levels of the angiogenesis-related genes Mmp9, Bv8 and Trail, and may promote the establishment of early endometriosis.

Cosmc transfection decreases malignant behavior of Tn+ cells and enhances sensitivity to apoptosis when induced by Apo2L/TRAIL via alteration of O-glycan structure.

Cosmc mutations may cause abnormal O-glycosylation and result in Tn antigen expression. In the current study, it was discovered that proliferation and migration of Tn+ cells (Jurkat T and LS174T-Tn+ cells) with mutant Cosmc decreased after transfected Cosmc, and their sensitivity to apoptosis induced by Apo2L/TRAIL increased. Core 1-, 2-, and 3-derived O-glycans were absent in Tn+ cells. After Cosmc transfection, normal extended core 1-derived O-glycans appeared and were accompanied by increased T-synthase activity. Core 2-derived O-glycans appeared in transfected LS174T-Tn+ cells, and their structural types and levels were lower than those in LS174T-Tn- cells. Core 3-derived O-glycans were present only in LS174T-Tn- cells. The activity of C3GnT in LS174T-Tn+ cells was lower than that in LS174T-Tn- cells, and it was absent in Jurkat T cells. Cosmc transfection did not alter C3GnT activity or core 3-derived O-glycans in Jurkat T and LS174T-Tn+ cells. The results demonstrated that the composition and structure of O-glycans were different among various Tn+ cells, which not only affected cell malignant behavior but also modulated sensitivity to apoptotic stimuli. Thus, Cosmc transfection may effectively decrease the malignant behavior of Tn+ tumor cells and enhance their sensitivity to apoptosis when induced by Apo2L/TRAIL through modification of O-glycans.

Development of an Agrobacterium tumefaciens-mediated transformation system for Tilletia controversa Kühn.

Dwarf bunt of wheat caused by Tilletia controversa Kühn has been identified an international quarantine disease, which replace the grain material into millions of teliospores. Agrobacterium tumefaciens-mediated transformation (ATMT) system is a powerful tool for fungi transformation with significant advantages of simple operation, high efficiency, and genetic stability of transformants. In this study, we constructed ATMT system for T. controversa. All the transformants were tested using Acetosyringone (AS) concentration at 150 µmol/l, hygromycin B at 25 µg/ml, 1 × 106 T. controversa hypha cells/ml, A. tumefaciens with OD600 of 0.5 co-cultivation at 16 °C for 48 h and culture was incubated at 16 °C for 20 days. Using the ATMT method, we cultivated 8 generations of transformants on complete medium (CM) containing hygromycin B antibiotic and validated by PCR, which indicate that T-DNA had been successfully inserted into each of T. controversa transformants. In addition, thermal asymmetric interlaced PCR (TAIL-PCR) evaluated the Ti element inserts were at random sites in the fungal genome. Thus, ATMT approach is an efficient tool for insertional mutagenesis of T. controversa.

Effects of Tilletia foetida on Microbial Communities in the Rhizosphere Soil of Wheat Seeds Coated with Different Concentrations of Jianzhuang.

Tilletia foetida (syn. T. laevis) leads to wheat common bunt, a worldwide disease that can lead to 80% yield loss and even total loss of production, together with degrading the quality of grains and flour by producing a rotten fish smell. To explore the potential microbial community that may contribute to the control of soil- and seed-borne pathogens, in this study, we analyzed the effects of the plant pathogenic fungus T. foetida on rhizosphere soil microorganisms in wheat seeds coated with different concentrations of a fungicide (Jianzhuang) used to control the disease. To analyze the bacterial and fungal abundance in T. foetida-infected and mock-infected plants, the microorganisms were sequenced using high-throughput HiSeq 2500 gene sequencing. The results showed that bacterial communities, including Verrucomicrobia, Patescibacteria, Armatimonadetes, Nitrospirae, Fibrobacteres, Chlamydiae, and Hydrogenedentes, and fungal communities, including Basidiomycota and Ciliophora, were more prevalent in the mock group than in the T. foetida-infected group, which may contribute to the control of wheat common bunt. Moreover, cluster and PCoA analysis revealed that replicates of the same samples were clustered together, and these results were also found in the distance index within-group analysis for bacterial and fungal communities in the T. foetida-infected and mock groups.

Transcriptome analysis of wheat spikes in response to Tilletia controversa Kühn which cause wheat dwarf bunt.

Wheat dwarf bunt is caused by Tilletia controversa Kühn, which is one of the most destructive diseases of wheat worldwide. To explore the interaction of T. controversa and wheat, we analysed the transcriptome profile of spikes of the susceptible wheat cultivar Dongxuan 3, which was subjected to a T. controversa infection and a mock infection. The results obtained from a differential expression analysis of T. controversa-infected plants compared with mock-infected ones showed that 10,867 out of 21,354 genes were upregulated, while 10,487 genes were downregulated, and these genes were enriched in 205 different pathways. Our findings demonstrated that the genes associated with defence against diseases, such as PR-related genes, WRKY transcription factors and mitogen-activated protein kinase genes, were more highly expressed in response to T. controversa infection. Additionally, a number of genes related to physiological attributes were expressed during infection. Three pathways were differentiated based on the characteristics of gene ontology classification. KEGG enrichment analysis showed that twenty genes were expressed differentially during the infection of wheat with T. controversa. Notable changes were observed in the transcriptomes of wheat plants after infection. The results of this study may help to elucidate the mechanism governing the interactions between this pathogen and wheat plants and may facilitate the development of new methods to increase the resistance level of wheat against T. controversa, including the overexpression of defence-related genes.

Accurate Prediction of Coronary Heart Disease for Patients With Hypertension From Electronic Health Records With Big Data and Machine-Learning Methods: Model Development and Performance Evaluation.

BACKGROUND: Predictions of cardiovascular disease risks based on health records have long attracted broad research interests. Despite extensive efforts, the prediction accuracy has remained unsatisfactory. This raises the question as to whether the data insufficiency, statistical and machine-learning methods, or intrinsic noise have hindered the performance of previous approaches, and how these issues can be alleviated. OBJECTIVE: Based on a large population of patients with hypertension in Shenzhen, China, we aimed to establish a high-precision coronary heart disease (CHD) prediction model through big data and machine-learning. METHODS: Data from a large cohort of 42,676 patients with hypertension, including 20,156 patients with CHD onset, were investigated from electronic health records (EHRs) 1-3 years prior to CHD onset (for CHD-positive cases) or during a disease-free follow-up period of more than 3 years (for CHD-negative cases). The population was divided evenly into independent training and test datasets. Various machine-learning methods were adopted on the training set to achieve high-accuracy prediction models and the results were compared with traditional statistical methods and well-known risk scales. Comparison analyses were performed to investigate the effects of training sample size, factor sets, and modeling approaches on the prediction performance. RESULTS: An ensemble method, XGBoost, achieved high accuracy in predicting 3-year CHD onset for the independent test dataset with an area under the receiver operating characteristic curve (AUC) value of 0.943. Comparison analysis showed that nonlinear models (K-nearest neighbor AUC 0.908, random forest AUC 0.938) outperform linear models (logistic regression AUC 0.865) on the same datasets, and machine-learning methods significantly surpassed traditional risk scales or fixed models (eg, Framingham cardiovascular disease risk models). Further analyses revealed that using time-dependent features obtained from multiple records, including both statistical variables and changing-trend variables, helped to improve the performance compared to using only static features. Subpopulation analysis showed that the impact of feature design had a more significant effect on model accuracy than the population size. Marginal effect analysis showed that both traditional and EHR factors exhibited highly nonlinear characteristics with respect to the risk scores. CONCLUSIONS: We demonstrated that accurate risk prediction of CHD from EHRs is possible given a sufficiently large population of training data. Sophisticated machine-learning methods played an important role in tackling the heterogeneity and nonlinear nature of disease prediction. Moreover, accumulated EHR data over multiple time points provided additional features that were valuable for risk prediction. Our study highlights the importance of accumulating big data from EHRs for accurate disease predictions.

Discovery and characterization of a novel insect-specific reovirus isolated from Psammotettix alienus.

A novel double-stranded RNA (dsRNA) virus designated Psammotettix alienus reovirus (PARV) was found in the leafhopper Psammotettix alienus in China. Spherical particles approximately 70 nm in diameter arranged in a crystalline array were observed in the salivary gland tissues of infected leafhoppers by transmission electron microscopy. Some viral particles were also encased in tubules, similar to those of previously described reoviruses. Whole-genome sequencing revealed that the dsRNA genome of PARV consists of 29 569 nucleotides (nt) divided into 10 segments ranging from 4403 to 1476 nt, with low G+C content (29.5-36.5 %). All segments contained conserved terminal sequences (5'AAC…GUCA3') and specific panhandle structures formed by inverted terminal repeats in the noncoding regions. Phylogenetic analysis based on the deduced RNA-dependent RNA polymerase (RdRp) revealed that PARV was in the fijivirus clade, but in a monophyletic lineage with an unassigned insect reovirus (Hubei insect virus 2, HBIV-2), although PARV and HBIV-2 are distinct enough to represent a new group within the genus Fijivirus. Biological assays showed that PARV infects P. alienus but not wheat plants, implying that it is a new insect-specific reovirus in the leafhopper. Given these features, PARV should be considered as a new species in the genus Fijivirus, family Reoviridae.

Interleukin-37b inhibits the growth of murine endometriosis-like lesions by regulating proliferation, invasion, angiogenesis and inflammation.

Endometriosis is a gynecological disease with abnormal expression of interleukin (IL)-37 which can suppress inflammation and the immune system. Here we investigated the role of the IL-37b splice variant in endometriosis in vivo and in vitro. In a murine model of endometriosis, in vivo administration of IL-37b significantly inhibited the development of lesions judged by the number (P = 0.0213), size (P = 0.0130) and weight (P = 0.0152) of lesions. IL-37b had no effect on the early stage of lesion formation, however administration in the growth stage of lesions decreased the number (P = 0.0158), size (P = 0.0158) and weight (P = 0.0258) of lesions compared with PBS control, an effect that was not reversed by macrophage depletion. Expressions of inflammatory factors, matrix metalloproteinases and vascular endothelial growth factor-A mRNA/protein were significantly inhibited in ectopic lesions following IL-37b administration, and in uterine segments treated in vitro. In vitro treatment of uterine segments with IL-37b inhibited phosphorylation of Akt and Erk1/2 in uterine segments. Isolated mouse endometrial stromal treated with IL-37b and transfected with pIL-37b plasmid got suppressed cell proliferation, invasion, angiogenesis and the expression of inflammatory factors. In addition, transfection with pIL-37b significantly decreased the phosphorylation of Akt and Erk1/2. IL-37b also inhibited proliferation and the expression of inflammatory and angiogenesis factors in epithelial cell line RL95-2. These findings suggest that IL-37b may inhibit the growth of lesions by regulating proliferation, invasion, angiogenesis and inflammation through Akt and Erk1/2 signaling pathway.

SE-OnionNet: A Convolution Neural Network for Protein-Ligand Binding Affinity Prediction.

Deep learning methods, which can predict the binding affinity of a drug-target protein interaction, reduce the time and cost of drug discovery. In this study, we propose a novel deep convolutional neural network called SE-OnionNet, with two squeeze-and-excitation (SE) modules, to computationally predict the binding affinity of a protein-ligand complex. The OnionNet is used to extract a feature map from the three-dimensional structure of a protein-drug molecular complex. The SE module is added to the second and third convolutional layers to improve the non-linear expression of the network to improve model performance. Three different optimizers, stochastic gradient descent (SGD), Adam, and Adagrad, were also used to improve the performance of the model. A majority of protein-molecule complexes were used for training, and the comparative assessment of scoring functions (CASF-2016) was used as the benchmark. Experimental results show that our model performs better than OnionNet, Pafnucy, and AutoDock Vina. Finally, we chose the macrophage migration inhibitor factor (PDB ID: 6cbg) to test the stability and robustness of the model. We found that the prediction results were not affected by the docking position, and thus, our model is of acceptable robustness.

Transmission Characteristics of Wheat Yellow Striate Virus by its Leafhopper Vector Psammotettix alienus.

Wheat yellow striate virus (WYSV), which is found in wheat fields of Northwest China and transmitted by leafhopper vector Psammotettix alienus, is a tentative new species in the genus Nucleorhabdovirus. Although the insect vector and host range of WYSV have been characterized, many aspects of the acquisition and transmission processes by its insect vector have not been elucidated. Here, the transmission parameters of WYSV by P. alienus were determined using wheat cv. Yangmai 12 as the indicator plant under a controlled temperature (23 ± 1°C) and photoperiod (16 h of light). The results showed that the minimum periods for acquisition were 5 min and 10 min for inoculation access. The latent period for successful transmission was most commonly 16 to 20 days (minimum, 10 days; maximum, 22 days). The quantitative reverse-transcriptase PCR results indicated that the WYSV titer increased with time after acquisition, suggesting that WYSV can replicate in P. alienus. Notably, female P. alienus transovarially transmitted the virus to next generations at relatively high efficiency. Electron microscopy of the WYSV-infected leafhopper revealed bacilliform particles aggregated in the cytoplasm of the salivary gland and midgut tissues. Our present studies suggested that acquisition and transmission of WYSV by P. alienus is consistent with a propagative, circulative, and persistent mode of transmission. Details regarding transmission competencies and distribution of WYSV in P. alienus will provide a basis for designing preventive measures.

Detection of Neutralizing Antibodies in HIV-1 Patients on Antiretroviral Treatment for Over Ten Years.

BACKGROUND: Recently, many broadly applicable and potent neutralizing antibodies have been screened from HIV-1-infected patients. However, all these effective neutralizing antibodies were isolated from patients naive to anti-retroviral treatment (ART). METHODS: To better understand the induction of neutralizing antibodies in patients on ART, we screened 3 patients with an over ten-year infection history on ART from 350 patients in China for a cross-reactive neutralizing antibody response based on the use of different antigens and recombinant viruses. We studied the evolution of neutralizing activity in two patients during a one-year period with previously described recombinant viruses NL4-3 and SF162 using ELISA and neutralization assays. RESULTS: Antibodies purified from sera were able to react with recombinant virus antigens R2-gp120 and SF162-gp140 and neutralize SF162 recombinant virus but not NL4-3 recombinant virus. In addition, we observed a significant increase in the neutralizing response of immunoglobulin G (IgG) isolated from the serum sample in Patient 1 and compared it with the serum from Patient 1 six months ago. CONCLUSIONS: We thus confirm the possibility of production of neutralizing antibodies in patients infected for over ten years on ART, and it is possible over time of the improvement of HIV-1 potent neutralizing activity associated with viremia and immune reconstruction.

Resistance and clonal selection among Allium sativum L. germplasm resources to Delia antiqua M. and its correlation with allicin content.

BACKGROUND: Garlic is the second largest allium crop after onion and is grown all over the world. The onion maggot (Delia antiqua M.) is a pest that seriously affects the yield and quality of garlic. Cultural controls and insecticides have several potential problems, including pesticide residue and development of resistance. Screening resistant varieties is an ideal alternative method. RESULTS: The resistance of 213 accessions of garlic clones against onion maggot was identified. The results showed that the pest index was between 5.56% and 91.11%, with classification into six groups by cluster analysis: HR (highly resistant), R (resistant), MR (moderately resistant), MS (moderately susceptible), S (susceptible) and HS (highly susceptible). Among these accessions, 9 and 30 were HR and R to onion maggot, respectively. Comparing the resistances of seven pairs of accessions between the original accessions and their progenies showed that single bulb clonal selection could be an effective way to improve allicin content, onion maggot resistance and most morphological traits. The relationship between allicin content and resistance was investigated, and a significant positive relationship was found. Accessions with a high content of allicin have great potential as resistant accessions. CONCLUSION: This study showed significant differences among garlic germplasm in their response to Delia antiqua M. Some accessions were highly resistant and tolerant. Utilization of these accessions will help minimize environmental pollution, preserve agro-ecosystems and biodiversity, and make management processes more economical. Furthermore, these accessions could be used in breeding programs to develop new maggot-resistant onion cultivars. © 2019 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.