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Abstract Swine acute diarrhea syndrome coronavirus (SADS-CoV) is a novel porcine enteric coronavirus that causes acute watery diarrhea, vomiting, and dehydration in newborn piglets. The type III interferon (IFN-λ) response serves as the primary defense against viruses that replicate in intestinal epithelial cells. However, there is currently no information available on how SADS-CoV modulates the production of IFN-λ. In this study, we utilized IPI-FX cells (a cell line of porcine ileum epithelium) as an in vitro model to investigate the potential immune evasion strategies employed by SADS-CoV against the IFN-λ response. Our results showed that SADS-CoV infection suppressed the production of IFN-λ1 induced by poly(I:C). Through screening SADS-CoV-encoded proteins, nsp1, nsp5, nsp10, nsp12, nsp16, E, S1, and S2 were identified as antagonists of IFN-λ1 production. Specifically, SADS-CoV nsp1 impeded the activation of the IFN-λ1 promoter mediated by MAVS, TBK1, IKKε, and IRF1. Both SADS-CoV and nsp1 obstructed poly(I:C)-induced nuclear translocation of IRF1. Moreover, SADS-CoV nsp1 degraded IRF1 via the ubiquitin-mediated proteasome pathway without interacting with it. Overall, our study provides the first evidence that SADS-CoV inhibits the type III IFN response, shedding light on the molecular mechanisms employed by SADS-CoV to evade the host immune response.

ABSTRACT: The gamma coronavirus infectious bronchitis virus (IBV) is known to cause an acute and highly contagious infectious disease in poultry. Here, this study aimed to investigate the impact of virulent or avirulent IBV infection on the avian host by conducting proteomics with data-independent acquisition mass spectrometry (DIA-MS) in the kidneys of IBV-infected chickens. The results revealed 267, 489, and 510 differentially expressed proteins (DEPs) in the chicken kidneys at 3, 5, and 7 days postinfection (dpi), respectively, when infected with the GD17/04 strain, which is a highly nephrogenic strain and belongs to the 4/91 genotype. In contrast, the attenuated 4/91 vaccine resulted in the identification of 144, 175, and 258 DEPs at 3, 5, and 7 dpi, respectively. Functional enrichment analyses indicated distinct expression profiles between the 2 IBV strains. Upon GD17/04 infection, metabolic pathways respond initially in the early stage (3 dpi) and immune-related signaling pathways respond in the middle and late stages (5 and 7 dpi). The 4/91 vaccine elicited a completely opposite response compared to the GD17/04 infection. Among all DEPs, 62 immune-related DEPs were focused on and found to be mainly enriched in the type I interferon (IFN-I) signaling pathway and involved in humoral and cellular immunity. Notably, key molecules in the IFN-I signaling pathway including MDA5, LGP2, and TBK1 may serve as regulatory targets of IBV. Overall, this study highlights similarities and discrepancies in the patterns of protein expression at different stages of infection with virulent and avirulent IBV strains, with the IFN-I signaling pathway emerging as a critical response to IBV infection.

ABSTRACT: Mycoplasma gallisepticum (MG) is one of the important pathogens in poultry industry and has led to major economic losses. Understanding the epidemiology is crucial to improve the control and eradication program of MG. This study collected 1,250 chicken samples, including trachea and lung, from China in 2022 to investigate the epidemiology of MG. Among the collected samples, 938 samples were positive for MG infection, resulting in an average positive rate of 75.04%. Additionally, 570 samples were positive for both MG and Mycoplasma synoviae (MS) coinfection, with an average positive rate of 45.60%. A total of 183 MG infection positive samples in this study were selected for genotyping, and the multilocus sequence typing (MLST) method based on 7 housekeeping genes was used. As a result, 183 samples belonged to 11 sequence types (STs), with ST-78 being the most prevalent. After BURST analysis, all 183 sequences were divided into group 3. Besides, 119 reference sequences from database and 183 sequences of this study were selected to construct the phylogenetic tree using the neighbor-joining method. The results revealed that the sequences from China, total 196 sequences, were classified into 4 branches. The findings suggest that the MG strains in China exhibit diverse genotypes, which may be related to international trade and the use of live vaccines. Furthermore, we detected the drug susceptibility of 10 isolated strains randomly, which may be helpful to guide the clinical use of drugs to control MG infection.

ABSTRACT: Mycoplasma synoviae (M. synoviae) is an important pathogen in poultry industry and has led to major economic losses. Understanding the epidemiology is crucial to improve control and eradication program of M. synoviae. In this study, 487 samples suspected with M. synoviae infection were collected from August 2020 to June 2021 in China. Among 487 samples, 324 samples were MS positive, the positive rate was 66.53%, and 104 strains were isolated from 324 positive samples. The multilocus sequence typing (MLST) method based on seven housekeeping genes was used to conduct genotyping 104 M. synoviae strains isolated, and the 104 isolates belonged to 8 sequence types (STs) after MLST genotyping, and ST-34 had the highest proportion. After BURST analysis, all 104 isolates were divided into group 12 with other 56 strains isolated from China. Phylogenetic tree constructed by neighbor-joining method showed that nearly all of Chinese isolates (160 isolates) clustered together and separated from other reference isolates (217 isolates) in the PubMLST database. In conclusion, this study suggested that the M. synoviae strains in China were highly similar and independent of abroad strains.

Abstract Background The association between homocysteine (Hcy) and IgA nephropathy (IgAN) is not well understood. We aimed to investigate the relationship between Hcy and clinicopathologic features in IgAN patients. Methods A total of 337 IgAN patients and 150 sex- and age- matched healthy controls were enrolled in this single-center retrospective study. According to Hcy ≤ 10 μmol/L or > 10 μmol/L, patients were divided into low and high Hcy groups. Multivariate logistic regression was performed to explore the risk factors for elevated Hcy. Results Serum Hcy was higher in IgAN patients than in healthy controls [11.6 (9.1,15.3) vs. 8.8 (7.5,10.6) μmol/L, P

Summary: The commensal microbiota regulates the self-renewal and differentiation of hematopoietic stem and progenitor cells (HSPCs) in bone marrow. Whether and how the microbiota influences HSPC development during embryogenesis is unclear. Using gnotobiotic zebrafish, we show that the microbiota is necessary for HSPC development and differentiation. Individual bacterial strains differentially affect HSPC formation, independent of their effects on myeloid cells. Early-life dysbiosis in chd8−/− zebrafish impairs HSPC development. Wild-type microbiota promote HSPC development by controlling basal inflammatory cytokine expression in kidney niche, and chd8−/− commensals elicit elevated inflammatory cytokines that reduce HSPCs and enhance myeloid differentiation. We identify an Aeromonas veronii strain with immuno-modulatory activities that fails to induce HSPC development in wild-type fish but selectively inhibits kidney cytokine expression and rebalances HSPC development in chd8−/− zebrafish. Our studies highlight the important roles of a balanced microbiome during early HSPC development that ensure proper establishment of lineal precursor for adult hematopoietic system.

Abstract Background IgA nephropathy (IgAN) is the most common primary glomerulonephritis globally. Increasing evidence suggests the importance of host immunity in the development of IgAN, but its dynamics during the early stage of IgAN are still largely unclear. Results Here we successfully resolved the early transcriptomic changes in immune cells of IgAN by conducting single-cell RNA-sequencing (scRNA-seq) with peripheral blood mononuclear cells. The differentially expressed genes (DEGs) between control and IgAN were predominantly enriched in NK cell-mediated cytotoxicity and cell killing pathways. Interestingly, we discovered that the number and cytotoxicity of NK cells are significantly reduced in IgAN patients, where both the number and marker genes of NK cells were negatively associated with the clinical parameters, including the levels of urine protein creatinine ratio (UPCR), serum galactose-deficient IgA1 and IgA. A distinctive B cell subset, which had suppressed NFκB signaling was predominantly in IgAN and positively associated with disease progression. Moreover, the DEGs of B cells were enriched in different viral infection pathways. Classical monocytes also significantly changed in IgAN and a monocyte subset expressing interferon-induced genes was positively associated with the clinical severity of IgAN. Finally, we identified vast dynamics in intercellular communications in IgAN. Conclusions We dissected the immune landscape of IgAN at the single-cell resolution, which provides new insights in developing novel biomarkers and immunotherapy against glomerulonephritis.

BackgroundRenin-angiotensin system inhibitors (RASi) are the first choice and basic therapy for the treatment of IgA nephropathy (IgAN) with proteinuria. However, approximately 40% of patients have no response to RASi treatment. The aim of this study was to screen potential biomarkers for predicting the treatment response of RASi in patients with IgAN.MethodsWe included IgAN patients who were treatment-naive. They received supportive treatment, including a maximum tolerant dose of RASi for 3 months. According to the degree of decrease in proteinuria after 3 months of follow-up, these patients were divided into a sensitive group and a resistant group. The plasma of the two groups of patients was collected, and the exosomes were extracted for high-throughput sequencing. The screening of hub genes was performed using a weighted gene co-expression network (WGCNA) and filtering differentially expressed genes (DEGs). We randomly selected 20 patients in the sensitive group and 20 patients in the resistant group for hub gene validation by real-time quantitative polymerase chain reaction (qRT−PCR). A receiver operating characteristic (ROC) curve was used to evaluate hub genes that predicted the efficacy of the RASi response among the 40 validation patients.ResultsAfter screening 370 IgAN patients according to the inclusion and exclusion criteria and the RASi treatment response evaluation, there were 38 patients in the sensitive group and 32 patients in the resistant group. IRAK1, ABCD1 and PLXNB3 were identified as hub genes by analyzing the high-throughput sequencing of the plasma exosomes of the two groups through WGCNA and DEGs screening. The sequencing data were consistent with the validation data showing that these three hub genes were upregulated in the resistant group compared with the sensitive group. The ROC curve indicated that IRAK1 was a good biomarker to predict the therapeutic response of RASi in patients with IgAN.ConclusionsPlasma exosomal IRAK1 can be a potential biomarker for predicting the treatment response of RASi in patients with IgAN.

Background The mechanism of immunoglobulin A nephropathy (IgAN) is still unknown. A bioinformatics analysis is a powerful method to identify the biomarkers and possible therapeutic targets of a certain disease from related datasets. Methods The GSE93973 dataset, obtained from the Gene Expression Omnibus (GEO) database, was used to construct a weighted gene co-expression network (WGCNA) and filter differentially expressed genes (DEGs). The biological process (BP) enrichment among all the genes in the key modules was analyzed through a Gene Ontology (GO) enrichment analysis. We selected the overlap of hub genes in the WGCNA and Protein-Protein Interaction (PPI) network as the final hub genes in IgAN. We verified the final hub genes in two other datasets and in clinical kidney tissue specimens. A receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of hub genes for IgAN. Results The turquoise module, which contained 1,806 genes, was the module with the highest correlation coefficient with IgAN in the GSE93973 dataset. The GO enrichment analysis showed that these 1,806 genes were mainly enriched in inflammation and immune responses. There were five hub genes identified by WGCNA and 34 hub genes identified in a DEG analysis in the GSE93973 dataset. DUSP1 and FOSB were identified as the final hub genes in IgAN. The validation results of the final hub genes in two other databases and clinical kidney tissue specimens validated the result that, compared to the control group, FOSB and DUSP1 were expressed at lower levels in the glomerulus of IgAN patients. The ROC curve indicated that DUSP1 and FOSB were good diagnostic indicators for IgAN. Conclusions Our analysis identified two hub genes that might be potential targets for the intervention and treatment of IgAN.

Infectious disease is a great enemy of humankind. The ravages of COVID-19 are leading to profound crises across the world. There is an urgent requirement for analyzing the current pandemic situation, predicting trends over time, and assessing the effectiveness of containment measures. Thus, numerous statistical models, primarily based on the susceptible–exposed–infected–recovered or removed (SEIR) model, have been established. However, these models are highly technical, which are difficult for the public and governing bodies to understand and use. To address this issue, we developed a simple operating software based on our improved K-SEIR model termed as the kernel SEIR simulator (K-SEIR-Sim). This software includes natural propagation parameters, containment measure parameters, and certain characteristic parameters that can deduce the effects of natural propagation and containment measures. Further, the applicability of the proposed software was demonstrated using the examples of the COVID-19 outbreak in the United States, Wuhan city of China, Diamond Princess, and France. Operating results verified the potency of the proposed software in evaluating the epidemic situation and human intervention during COVID-19. Importantly, no installation is required and the software can perform real-time, backward-looking, and forward-looking analysis by functioning in data-driven and model-driven ways. All of them have considerable practical values in their applications according to the actual needs of personal use. Conclusively, K-SEIR-Sim is the first simple customized operating software that is highly valuable for the global fight against COVID-19 and other infectious diseases.

Fibronectin glomerulopathy (FNG) is a rare inherited kidney disease characterized by extensive deposition of fibronectin in the glomeruli, especially in the mesangial and subendothelial regions. The disease progresses slowly and eventually leads to kidney failure in 15–20 years. Here, we report an interesting case. The patient presented with proteinuria and was diagnosed with immune complex–mediated glomerulonephritis, and lupus nephritis was suspected. This patient progressed to end-stage renal disease after 18 years and received an allogeneic kidney transplant. However, proteinuria recurred 27 months after kidney transplantation. The renal biopsy found extensive deposition in glomeruli, and the patient was diagnosed with FNG using mass spectrometry analysis and confirmed by immunohistochemistry in both the native and transplanted kidneys. Gene sequencing revealed that a missense mutation in the fibronectin 1 (FN1) gene caused reduced binding to heparin, endothelial cells, and podocytes and impaired stress fiber formation. The patient had stable renal function but persistent nephrotic proteinuria after 6 months of follow-up. Given the persistence of abnormal circulating fibronectin levels, FNG can relapse following renal transplantation. The circulating fibronectin deposits on grafts, and renal function progressively deteriorates after recurrence. Therefore, whether renal transplantation is an acceptable treatment for FNG is still debatable.

Since September 2020, the clinical symptoms of Muscovy duck spleen spots have appeared in Guangdong, Guangxi, Jiangxi, Hunan, Hubei, and other provinces, resulting in a large number of Muscovy duck deaths and great economic losses. The absence of the typical clinical symptoms caused by pathogenic microorganisms makes the cause of the spotted spleen a mystery. High-throughput sequencing results suggested that Riemerella anatipestifer (R. anatipestifer) may be the pathogen. Then, R. anatipestifer was regarded as the research target for isolation, identification, and pathogenicity assessment. After biochemical test, PCR amplification, and serotype determination, it was confirmed that the isolated strain CZG-1 was serotype 15 R. anatipestifer. Typical spotted spleen symptoms were observed after CZG-1 infection. Furthermore, drug sensitivity assays showed the similar drug-resistant spectrum of R. anatipestifer serotype 15 to other serotypes; for example, all test strains were resistant to polymyxin, gentamicin, and neomycin. The CZG-1 strain has high pathogenicity, and its lethal dose of 50% (LD50) is 35.122 CFU/ml. Virulence gene determination showed that the CZG-1 strain had at least five virulence genes, bioF, TSS9-1, TSS9-2, PncA, and 0373Right. Above all, this study identified and proved that the pathogen of spotted spleen in ducks was R. anatipestifer serotype 15, which caused death of ducks without the typical symptoms of bacterial infection. The results of this study enriched the knowledge of symptom after R. anatipestifer infection, provided a reference to the identification of the pathogen of spotted spleen, and provided theoretical basis for prevention and control of spotted spleen.

Abstract With the emergence of highly pathogenic variant strains, porcine epidemic diarrhea virus (PEDV) has led to significant economic loss in the global swine industry. Many studies have described how coronaviruses enter cells, but information on PEDV invasion strategies remains insufficient. Given that the differences in gene sequences and pathogenicity between classical and mutant strains of PEDV may lead to diverse invasion mechanisms, this study focused on the cellular entry pathways and cellular transport of the PEDV GI and GII subtype strains in Vero cells and IPEC-J2 cells. We first characterized the kinetics of PEDV entry into cells and found that the highest invasion rate of PEDV was approximately 33% in the IPEC-J2 cells and approximately 100% in the Vero cells. To clarify the specific endocytic pathways, systematic research methods were used and showed that PEDV enters cells via the clathrin- and caveolae-mediated endocytosis pathways, in which dynamin II, clathrin heavy chain, Eps15, cholesterol, and caveolin-1 were indispensably involved. In addition, lipid raft extraction assay showed that PEDV can also enter cells through lipid raft-mediated endocytosis. To investigate the trafficking of internalized PEDV, we found that PEDV entry into cells relied on low pH and internalized virions reached lysosomes through the early endosome–late endosome–lysosome pathway. The results concretely revealed the entry mechanisms of PEDV and provided an insightful theoretical basis for the further understanding of PEDV pathogenesis and guidance for new targets of antiviral drugs.

ABSTRACT: Mycoplasma synoviae (MS), an important avian pathogen, can cause chronic respiratory disease, eggshell apex abnormalities, infectious synovitis, and arthritis in avian species, leading serious economic losses in the global poultry industry. To date, studies have shown significant different transcript profiles using various chicken cells after MS infection. However, in vitro cell models cannot fully represent the complex in vivo regulations after adventitious infection. The objective of this study was to explore the nature of the host-pathogen interaction during MS infection. The tracheal and spleen tissues of chickens were collected at d 0, 1, 3, and 5 postinoculation, and samples were analyzed for differential gene expression using Illumina RNA sequencing. A lot of significantly differentially expressed genes (DEGs) were observed in this analysis, and 861 DEGs were observed in trachea tissues and 753 DEGs were observed in spleen samples. Many of DEGs in trachea tissues participate in a variety of cellular activities, especially cellular metabolism. Immune-related DEGs were mainly enriched at d 3, and 5 postinfection in trachea tissues. While, DEGs in spleen tissues were significantly and mainly enriched into immune-related pathways. The results of this study show the direct interactions between MS and the chicken trachea and spleen for the first time. Early dysregulation of tissue-wide gene expression as observed here set the stage for persistent infection of MS.

Mycoplasma synoviae (MS) is a major avian pathogen that causes respiratory damage, infectious synovitis, and arthritis in chickens and causes serious economic losses to the global poultry industry. Despite its significance, knowledge on pathogenicity and pathogenic mechanism of MS is lacking, especially regarding its antigens. Bioinformatic analysis showed that the known MS proteins are only the tip of the iceberg among many MS membrane proteins. In this study, we identified and expressed a novel MS membrane protein P35. Sequence similarity showed that P35 was conservative and commonly existed among MS strains. Membrane protein extraction and immunofluorescence assay confirmed that P35 was distributed on the surface of MS. The production of specific antibodies after immunization with recombinant protein rP35 suggested its immunogenicity. The antigenicity of P35 was evaluated from two aspects by using polyantiserum against MS and rP35. Furthermore, in assays to identify the immune peptides of P35, all successfully expressed truncated segments could react with positive polyantiserum of MS, suggesting that P35 had more than one immune peptide. In conclusion, our study successfully identified P35 as a conservative antigen of MS, which may act as a potential candidate for the future development of a vaccine against MS.

ABSTRACT: Chicken astrovirus (CAstV) is associated with kidney disease and visceral gout, runting and stunting syndrome, and white chick hatchery disease, causing economic losses to the poultry industry worldwide. In this study, 55.6% of 36 clinical samples from Guangdong province in China were positive for CAstV, but negative for other common enteric viruses, including avian nephritis virus, infectious bronchitis virus, fowl adenovirus Group I, Newcastle disease virus, chicken parvovirus, reovirus, and rotavirus by PCRs and RT-PCRs. A CAstV strain, named GD202013, was isolated from Guangdong province in south China, and was identified by CAstV RT-PCR. A whole genome sequence analysis demonstrated that GD202013 shares 76.0 to 88.1% identity with 24 reference strains in GenBank. Phylogenetic analysis, based on whole genome and capsid protein, showed that GD202013 is more closely related to 2 US strains (GA2011/US/2011 and 4175/US/2011) belonging to subgroup Bii. Recombination analysis indicated that GD202013 is a recombinant strain formed by 3 strains: a major parent strain CkP5/US/2016, and 2 minor parent strains (GA2011/US/2011 and G059/PL/2014). In addition, the chicken embryo infection experiment demonstrated that GD202013 causes hatchability reduction, growth depression, and death of embryos. Macroscopic and microscopic lesions in the liver, kidney and small intestine were observed in the dead-in-shell embryos. This is the first report of the novel CAstV infection in China.

Porcine epidemic diarrhea virus (PEDV) is the etiological agent of porcine epidemic diarrhea (PED) characterized by vomit, watery diarrhea, dehydration and high mortality. Outbreaks of highly pathogenic variant strains of PEDV have resulted in extreme economic losses to the swine industry all over the world. The study of host–virus interaction can help to better understand the viral pathogenicity. Many studies have shown that poly(A)-binding proteins are involved in the replication process of various viruses. Here, we found that the infection of PEDV downregulated the expression of poly(A)-binding protein cytoplasmic 1 (PABPC1) at the later infection stage in Vero cells. The overexpression of PABPC1 inhibited the proliferation of PEDV at transcription and translation level, and siRNA-mediated depletion of PABPC1 promoted the replication of PEDV. Furthermore, mass spectrometry analysis and immunoprecipitation assay confirmed that PABPC1 interacted with the nucleocapsid (N) protein of PEDV. Confocal microscopy revealed the co-localizations of PABPC1 with N protein in the cytoplasm. Taken together, these results demonstrate the antiviral effect of PABPC1 against PEDV replication by interacting with N protein, which increases understanding of the interaction between PEDV and host.

Abstract Clear cell renal cell carcinoma (ccRCC) has been previously classified into putative discrete prognostic subtypes by gene expression profiling. To investigate the robustness of these proposed subtype classifications, we evaluated 12 public datasets, together with a new dataset of 265 ccRCC gene expression profiles. Consensus clustering showed unstable subtype and principal component analysis (PCA) showed a continuous spectrum both within and between datasets. Considering the lack of discrete delineation and continuous spectrum observed, we developed a continuous quantitative prognosis score (Continuous Linear Enhanced Assessment of RCC, or CLEAR score). Prognostic performance was evaluated in independent cohorts from The Cancer Genome Atlas (TCGA) (n = 414) and EMBL-EBI (n = 53), CLEAR score demonstrated both superior prognostic estimates and inverse correlation with anti-angiogenic tyrosine-kinase inhibition in comparison to previously proposed discrete subtyping classifications. Inverse correlation with high-dose interleukin-2 outcomes was also observed for the CLEAR score. Multiple somatic mutations (VHL, PBRM1, SETD2, KDM5C, TP53, BAP1, PTEN, MTOR) were associated with the CLEAR score. Application of the CLEAR score to independent expression profiling of intratumoral ccRCC regions demonstrated that average intertumoral heterogeneity exceeded intratumoral expression heterogeneity. Wider investigation of cancer biology using continuous approaches may yield insights into tumor heterogeneity; single cell analysis may provide a key foundation for this approach.

Multicentric carpotarsal osteolysis (MCTO) is a rare skeletal dysplasia with osteolysis at the carpal and tarsal bones. Heterozygous missense mutations in the transcription factor MAFB are found in patients with MCTO. MAFB is reported to negatively regulate osteoclastogenesis in vitro. However, the in vivo function of MAFB and its relation to MCTO remains unknown. In this study, we generated zebrafish MAFB homolog mafbb mutant utilizing CRISPR/Cas9 technology. Mafbb deficient zebrafish demonstrated enhanced osteoclast cell differentiation and abnormal cartilage and bone development resembling MCTO patients. It is known that osteoclasts are hematopoietic cells derived from macrophages. Loss of mafbb caused selective expansion of definitive macrophages and myeloid cells, supporting that mafbb restricts myeloid differentiation in vivo. We also demonstrate that MAFB MCTO mutations failed to rescue the defective osteoclastogenesis in mafbb−/− embryos, but did not affect osteoclast cells in wild type embryos. The mechanism of MCTO mutations is likely haploinsufficiency. Zebrafish mafbb mutant provides a useful model to study the function of MAFB in osteoclastogenesis and the related MCTO disease.

The weighted sum and genetic algorithm-based hybrid method (WSGA-based HM), which has been applied to multiobjective orbit optimizations, is negatively influenced by human factors through the artificial choice of the weight coefficients in weighted sum method and the slow convergence of GA. To address these two problems, a cluster and principal component analysis-based optimization method (CPC-based OM) is proposed, in which many candidate orbits are gradually randomly generated until the optimal orbit is obtained using a data mining method, that is, cluster analysis based on principal components. Then, the second cluster analysis of the orbital elements is introduced into CPC-based OM to improve the convergence, developing a novel double cluster and principal component analysis-based optimization method (DCPC-based OM). In DCPC-based OM, the cluster analysis based on principal components has the advantage of reducing the human influences, and the cluster analysis based on six orbital elements can reduce the search space to effectively accelerate convergence. The test results from a multiobjective numerical benchmark function and the orbit design results of an Earth observation satellite show that DCPC-based OM converges more efficiently than WSGA-based HM. And DCPC-based OM, to some degree, reduces the influence of human factors presented in WSGA-based HM.

First, for a process U(t,τ)∣t≥τ, we introduce a new concept, called the weak D-pullback exponential attractor, which is a family of sets M(t)∣t≤T, for any T∈R, satisfying the following: (i) M(t) is compact, (ii) M(t) is positively invariant, that is, U(t,τ)M(τ)⊂M(t), and (iii) there exist k,l>0 such that dist(U(t,τ)B(τ),M(t))≤ke-(t-τ); that is, M(t) pullback exponential attracts B(τ). Then we give a method to obtain the existence of weak D-pullback exponential attractors for a process. As an application, we obtain the existence of weak D-pullback exponential attractor for reaction diffusion equation in H01 with exponential growth of the external force.

Target selective drugs, such as dopamine receptor (DR) subtype selective ligands, are developed for enhanced therapeutics and reduced side effects. In silico methods have been explored for searching DR selective ligands, but encountered difficulties associated with high subtype similarity and ligand structural diversity. Machine learning methods have shown promising potential in searching target selective compounds. Their target selective capability can be further enhanced. In this work, we introduced a new two-step support vector machines target-binding and selectivity screening method for searching DR subtype-selective ligands, which was tested together with three previously-used machine learning methods for searching D1, D2, D3 and D4 selective ligands. It correctly identified 50.6%-88.0% of the 21-408 subtype selective and 71.7%-81.0% of the 39-147 multi-subtype ligands. Its subtype selective ligand identification rates are significantly better than, and its multi-subtype ligand identification rates are comparable to the best rates of the previously used methods. Our method produced low false-hit rates in screening 13.56 M PubChem, 168,016 MDDR and 657,736 ChEMBLdb compounds. Molecular features important for subtype selectivity were extracted by using the recursive feature elimination feature selection method. These features are consistent with literature-reported features. Our method showed similar performance in searching estrogen receptor subtype selective ligands. Our study demonstrated the usefulness of the two-step target binding and selectivity screening method in searching subtype selective ligands from large compound libraries.