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Abstract Background M1 macrophages are closely associated with cardiac injury after myocardial infarction (MI). Increasing evidence shows that exosomes play a key role in pathophysiological regulation after MI, but the role of M1 macrophage-derived exosomes (M1-Exos) in myocardial regeneration remains unclear. In this study, we explored the impact of M1 macrophage-derived exosomes on cardiomyocytes regeneration in vitro and in vivo. Methods M0 macrophages were induced to differentiate into M1 macrophages with GM-CSF (50 ng/mL) and IFN-γ (20 ng/mL). Then M1-Exos were isolated and co-incubated with cardiomyocytes. Cardiomyocyte proliferation was detected by pH3 or ki67 staining. Quantitative real-time PCR (qPCR) was used to test the level of miR-155 in macrophages, macrophage-derived exosomes and exosome-treated cardiomyocytes. MI model was constructed and LV-miR-155 was injected around the infarct area, the proliferation of cardiomyocytes was counted by pH3 or ki67 staining. The downstream gene and pathway of miR-155 were predicted and verified by dual-luciferase reporter gene assay, qPCR and immunoblotting analysis. IL-6 (50 ng/mL) was added to cardiomyocytes transfected with miR-155 mimics, and the proliferation of cardiomyocytes was calculated by immunofluorescence. The protein expressions of IL-6R, p-JAK2 and p-STAT3 were detected by Western blot. Results The results showed that M1-Exos suppressed cardiomyocytes proliferation. Meanwhile, miR-155 was highly expressed in M1-Exos and transferred to cardiomyocytes. miR-155 inhibited the proliferation of cardiomyocytes and antagonized the pro-proliferation effect of interleukin 6 (IL-6). Furthermore, miR-155 targeted gene IL-6 receptor (IL-6R) and inhibited the Janus kinase 2(JAK)/Signal transducer and activator of transcription (STAT3) signaling pathway. Conclusion M1-Exos inhibited cardiomyocyte proliferation by delivering miR-155 and inhibiting the IL-6R/JAK/STAT3 signaling pathway. This study provided new insight and potential treatment strategy for the regulation of myocardial regeneration and cardiac repair by macrophages.

Abstract Background Cotton accounts for 80% of the global natural fibre production. Its leaf hairiness affects insect resistance, fibre yield, and economic value. However, this phenotype is still qualitatively assessed by visually attributing a Genotype Hairiness Score (GHS) to a leaf/plant, or by using the HairNet deep-learning model which also outputs a GHS. Here, we introduce HairNet2, a quantitative deep-learning model which detects leaf hairs (trichomes) from images and outputs a segmentation mask and a Leaf Trichome Score (LTS). Results Trichomes of 1250 images were annotated (AnnCoT) and a combination of six Feature Extractor modules and five Segmentation modules were tested alongside a range of loss functions and data augmentation techniques. HairNet2 was further validated on the dataset used to build HairNet (CotLeaf-1), a similar dataset collected in two subsequent seasons (CotLeaf-2), and a dataset collected on two genetically diverse populations (CotLeaf-X). The main findings of this study are that (1) leaf number, environment and image position did not significantly affect results, (2) although GHS and LTS mostly correlated for individual GHS classes, results at the genotype level revealed a strong LTS heterogeneity within a given GHS class, (3) LTS correlated strongly with expert scoring of individual images. Conclusions HairNet2 is the first quantitative and scalable deep-learning model able to measure leaf hairiness. Results obtained with HairNet2 concur with the qualitative values used by breeders at both extremes of the scale (GHS 1-2, and 5-5+), but interestingly suggest a reordering of genotypes with intermediate values (GHS 3-4+). Finely ranking mild phenotypes is a difficult task for humans. In addition to providing assistance with this task, HairNet2 opens the door to selecting plants with specific leaf hairiness characteristics which may be associated with other beneficial traits to deliver better varieties.

Abstract Background Aberrant expression and activation of circular RNAs (circRNAs) are closely associated with various cancers. The role of circ_MAPK9 (hsa_circ_0001566) in cancer progression remains unknown. This study aims to investigate the function, mechanism and clinical significance of circ_MAPK9 in hepatocellular carcinoma (HCC). Methods Circ_MAPK9 expression on the microarray of tumor from clinical HCC patients was detected by in situ hybridization (ISH). Circ_MAPK9 knockdown was achieved with siRNAs in SMMC-7721 and SK-Hep1 HCC cell lines. The biological function of circ_MAPK9 was verified in vitro by CCK8 test, colony formation assay, transwell assay, PI-Annexin V staining, and in vivo by xenograft tumor in nude mice. Fluorescent in situ hybridization (FISH), subcellular fractionation assay, a dual-luciferase reporter assay and rescue experiments were employed for further mechanistic investigation. Results The expression of circ_MAPK9 was significantly up-regulated in HCC tissues and cells, which was found to be associated with poor prognosis. Patients with high expression of circ_MAPK9 had a shorter overall survival and disease-free survival in comparison to those with low circ_MAPK9 expression. Functional assays showed that circ_MAPK9 knockdown suppressed cellular proliferation, migration, invasion and tumor growth in vivo, and promoted apoptosis in HCC cells. Moreover, we found that circ_MAPK9 knockdown could inhibit aerobic glycolysis by decreasing the production of adenosine triphosphate (ATP) and lactic acid, which was mediated by lactate dehydrogenase (LDHA). Mechanistically, circ_MAPK9 functioned as ceRNA via sponging miR-642b-3p and alleviated the inhibitory effect of miR-642b-3p on its target signal transducer and activator of transcription 3 (STAT3) and LDHA, thereby leading to STAT3 activation and LDHA expression. Conclusions Circ_MAPK9, as an oncogene, promotes HCC growth and metastasis through miR-642b-3p/STAT3-LDHA axis. Circ_MAPK9 could serve as a potential biomarker for HCC poor prognosis and diagnosis.

Abstract Background The approach of directly testing yarn quality to define fibre quality breeding objectives and progress the selection is attractive but difficult when considering the need for time and labour. The question remains whether yarn prediction tools from textile research can serve as an alternative. In this study, using a dataset from three seasons of field testing recombinant inbred line population, Cottonspec, a software developed by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) for predicting ring spun yarn quality from fibre properties measured by High Volume Instrument (HVI), was used to select improved fibre quality and lint yield in the population. The population was derived from an advanced generation inter-crossing of four CSIRO conventional commercial varieties. The Cottonspec program was able to provide an integrated index of the fibre qualities affecting yarn properties. That was compared with selection based on HVI-measured fibre properties, and two composite fibre quality variables, namely, fibre quality index (FQI), and premium and discount (PD) points. The latter represents the net points of fibre length, strength, and micronaire based on the Premiums and Discounts Schedule used in the market while modified by the inclusion of elongation. Results The population had large variations for lint yield, fibre properties, predicted yarn properties, and composite fibre quality values. Lint yield with all fibre quality traits was not correlated. When the selection was conducted first to keep those with improved fibre quality, and followed for high yields, a large proportion in the resultant populations was the same between selections based on Cottonspec predicted yarn quality and HVI-measured fibre properties. They both exceeded the selection based on FQI and PD points. Conclusions The population contained elite segregants with improved yield and fibre properties, and Cottonspec predicted yarn quality is useful to effectively capture these elites. There is a need to further develop yarn quality prediction tools through collaborative efforts with textile mills, to draw better connectedness between fibre and yarn quality. This connection will support the entire cotton value chain research and evolution.

Abstract Cereal cyst nematodes (CCNs) lead to major losses in the cereal crop industry worldwide and have been reported in many provinces of China. However, this plant nematode’s distribution and genetic differences are not fully understood. In the present study, 821 soil and host root samples were collected from 16 provinces in 2019–2022 to investigate the distribution of the CCNs. Heterodera avenae was detected in 56.39% of the total samples, primarily in Hubei, Henan, Hebei, Shandong, Shanxi, Gansu, Beijing, Tianjin, Inner Mongolia, Ningxia, Xinjiang, Qinghai, Anhui, Shaanxi, and Jiangsu. H. filipjevi was present in 21 samples, with a detection rate of 2.60%, and it was found mainly in Henan, Anhui, Jiangsu, Shandong, Shanxi, and Qinghai. A phylogenetic analysis of the internal transcribed spacer (ITS) region of the rRNA gene indicated that significant evolutionary and genetic differences existed between the Chinese populations and populations from other countries. Our results indicate that ITS1 can be used as a phylogenetic analysis and genetic target for H. avenae populations. The haplotypes of the ITS1 sequences of H. avenae populations from 14 countries were analyzed, and we speculate that H. avenae originated in a Middle East hotspot, then spread westwards to Europe and the United States and eastwards to China and Australia. Genetic differences between Asian and European populations suggest that the Himalayas and Kunlun Mountains formed a barrier that resulted in the formation of a separate evolutionary group in China. The phylogenetic and haplotype analysis results from different hosts showed significant differences among populations isolated from different hosts, and those isolated from weeds were distinct from those from other hosts, indicating that the rich genetic diversity of H. avenae populations is related to the large number of available hosts. Above all, geographic barriers, time of origin, and host adaptation might explain the current known distribution patterns of Chinese H. avenae populations.

Abstract Soybean cyst nematode (SCN, Heterodera glycines) is widely considered as the model plant-parasitic nematode, which secretes effector proteins to manipulate host responses. In this study, we cloned a dorsal gland-expressed effector protein SCN-27D09 that belongs to the same family as Hg10A07 in SCN. We used the model plant pathogen rice blast fungus (Magnaporthe oryzae) to quickly predict and characterize the functions of SCN-27D09. By using M. oryzae secretion system in barley, we confirmed that the signal peptide of SCN-27D09 has secretory activity and can guide the protein into the host cells. Heterologous expression of SCN-27D09 in M. oryzae significantly enhanced the susceptibility of barley to M. oryzae. SCN-27D09 can inhibit Bax-triggered cell death when expressed in Nicotiana benthamiana. Overexpression of SCN-27D09 in soybean hairy root also increased the susceptibility of soybean plants to SCN. Moreover, yeast two-hybrid and firefly luciferase complementation imaging assays showed that SCN-27D09 interacts with a soybean plant kinase GmIPK-2. Functional characterization of GmIPK-2 revealed its positive role in soybean resistance, indicating that SCN-27D09 might compromise the function of GmIPK-2 to facilitate nematode infection. Our results not only uncover the biological role of SCN-27D09 in suppressing plant defense responses and therefore promoting nematode parasitism, but also reaffirm the potential application of the model plant pathogenic fungus M. oryzae in investigating the pathogenic roles of candidate effectors of phytonematodes.

Abstract Potato rot nematode Ditylenchus destructor is one of the most damaging pests in potato-producing regions and causes severe yield losses worldwide. However, D. destructor has been rarely reported in potato crops in China. We collected 542 samples from 17 Chinese provinces during 2016–2020 for the detection of D. destructor using species-specific primers and universal primers targeting ribosomal internal transcribed spacer (ITS) or 28S ribosomal RNA (rRNA) sequences. D. destructor was detected in 14.94% of total samples, primarily in Inner Mongolia Autonomous Region (43 sites), Jilin Province (12 sites), and Shaanxi Province (9 sites). The nematode was for the first time detected in Guizhou Province and Ningxia Hui Autonomous Region. Phylogenetic analysis of 33 ITS sequences along with the prediction of the secondary structure of the helix H9 of ITS1 sequences revealed that haplotypes A, B, and C accounted for 6.06%, 9.09%, and 69.70% of our detections, respectively, while 15.15% were comprised of haplotypes H–L, and extensive genetic diversity of ITS sequences was detected in samples from Gansu Province. Using RNAfold software, we analyzed the haplotypes of 124 Chinese D. destructor populations based on their ITS sequences, and the results showed that haplotypes A, B, C, E, F, and new haplotypes M–P accounted for 49.19%, 12.10%, 15.32%, 3.23%, 1.61%, and 18.55% of the total sequences, respectively. Infection tests on the potato cultivar ‘Helan 15’ showed significant difference in infection capacity among different D. destructor populations. The information obtained in this study on spatial patterns of D. destructor haplotypes in China provides valuable insights into the development of an integrated approach for the management of this plant-parasitic nematode.

Abstract Background Leaf hairiness (pubescence) is an important plant phenotype which regulates leaf transpiration, affects sunlight penetration, and provides increased resistance or susceptibility against certain insects. Cotton accounts for 80% of global natural fibre production, and in this crop leaf hairiness also affects fibre yield and value. Currently, this key phenotype is measured visually which is slow, laborious and operator-biased. Here, we propose a simple, high-throughput and low-cost imaging method combined with a deep-learning model, HairNet, to classify leaf images with great accuracy. Results A dataset of $$\sim $$ ∼ 13,600 leaf images from 27 genotypes of Cotton was generated. Images were collected from leaves at two different positions in the canopy (leaf 3 & leaf 4), from genotypes grown in two consecutive years and in two growth environments (glasshouse & field). This dataset was used to build a 4-part deep learning model called HairNet. On the whole dataset, HairNet achieved accuracies of 89% per image and 95% per leaf. The impact of leaf selection, year and environment on HairNet accuracy was then investigated using subsets of the whole dataset. It was found that as long as examples of the year and environment tested were present in the training population, HairNet achieved very high accuracy per image (86–96%) and per leaf (90–99%). Leaf selection had no effect on HairNet accuracy, making it a robust model. Conclusions HairNet classifies images of cotton leaves according to their hairiness with very high accuracy. The simple imaging methodology presented in this study and the high accuracy on a single image per leaf achieved by HairNet demonstrates that it is implementable at scale. We propose that HairNet replaces the current visual scoring of this trait. The HairNet code and dataset can be used as a baseline to measure this trait in other species or to score other microscopic but important phenotypes.

Abstract Verticillium wilt is one of the most important diseases affecting cotton production in China. The fungus, Verticillium dahliae, has a wide host range and a high degree of genetic variability. No resistance resources have been found in the available planting resources, thus presenting difficulties and challenges for our study. The long-term production practice shows that selection of disease-resistant varieties is the most economical and effective measure to control Verticillium wilt of cotton to reduce the yield loss and quality decline of cotton. In this paper, we summarized the genetic mapping population, the analysis method of genetic localization, the discovery, mining and cloning of disease-resistant quantitative trait loci/markers, and the analysis of their genetic functions, so as to provide information for the molecular breeding approach of disease-resistant cotton.

Abstract Soybean cyst nematode (SCN), Heterodera glycines, is one of the most important pests in soybean production worldwide. In China, 11 different races of SCN, including a newly identified race ‘X12’ with super-virulence, have been surveyed and found to be distributed in 22 provinces. Among them, races 1, 3 and 4 are dominant in the two principal soybean-producing areas, Northeast China and Huanghuaihai Valley, causing over 120 million dollars of annual yield loss. Rapid and reliable PCR-based approaches have been developed for the molecular diagnosis of SCN. High-throughput methods for the identification of soybean resistance against SCN are also developed with specific single nucleotide polymorphism markers by using Kompetitive Allele Specific PCR technology. Over 10,000 soybean germplasm sources were evaluated for their SCN resistance, and 28 SCN-resistant soybean accessions were selected to construct an applied core collection, which has been used for soybean breeding in China. Recently, the genome sequences of SCN and soybean are publically available, and two major SCN-resistant genes (rhg1 and Rhg4) have been identified in soybean, which greatly facilitate the researches on SCN virulence and soybean resistance, and also soybean resistance breeding against SCN. However, the management of SCN still faces many bottlenecks, for instance, the single resistance genes in soybean cultivars can be easily overcome by new SCN races; the identified resistance genes are inadequate to meet the practical breeding needs; and our understanding of the mechanisms of SCN virulence and soybean resistance to SCN are limited. SCN is a destructive threat to soybean production throughout the world including China. In this review, the major progress on soybean SCN is summarized, mainly focusing on the recent research progress in SCN, soybean resistance to SCN and integrated management of SCN in China, and aiming at a better understanding of the current SCN research status and prospects for future work.

Abstract Background Soybean cyst nematode, Heterodera glycines, is one of the most devastating pathogens of soybean and causes severe annual yield losses worldwide. Different soybean varieties exhibit different responses to H. glycines infection at various levels, such as the genomic, transcriptional, proteomic and metabolomic levels. However, there have not yet been any reports of the differential responses of incompatible and compatible soybean varieties infected with H. glycines based on combined metabolomic and transcriptomic analyses. Results In this study, the incompatible soybean variety PI437654 and three compatible soybean varieties, Williams 82, Zhonghuang 13 and Hefeng 47, were used to clarify the differences in metabolites and transcriptomics before and after the infection with HG1.2.3.5.7. A local metabolite-calibrated database was used to identify potentially differential metabolites, and the differences in metabolites and metabolic pathways were compared between the incompatible and compatible soybean varieties after inoculation with HG1.2.3.5.7. In total, 37 differential metabolites and 20 KEGG metabolic pathways were identified, which were divided into three categories: metabolites/pathways overlapped in the incompatible and compatible soybeans, and metabolites/pathways specific to either the incompatible or compatible soybean varieties. Twelve differential metabolites were found to be involved in predicted KEGG metabolite pathways. Moreover, 14 specific differential metabolites (such as significantly up-regulated nicotine and down-regulated D-aspartic acid) and their associated KEGG pathways (such as the tropane, piperidine and pyridine alkaloid biosynthesis, alanine, aspartate and glutamate metabolism, sphingolipid metabolism and arginine biosynthesis) were significantly altered and abundantly enriched in the incompatible soybean variety PI437654, and likely played pivotal roles in defending against HG1.2.3.5.7 infection. Three key metabolites (N-acetyltranexamic acid, nicotine and D,L-tryptophan) found to be significantly up-regulated in the incompatible soybean variety PI437654 infected by HG1.2.3.5.7 were classified into two types and used for combined analyses with the transcriptomic expression profiling. Associated genes were predicted, along with the likely corresponding biological processes, cellular components, molecular functions and pathways. Conclusions Our results not only identified potential novel metabolites and associated genes involved in the incompatible response of PI437654 to soybean cyst nematode HG1.2.3.5.7, but also provided new insights into the interactions between soybeans and soybean cyst nematodes.

Abstract Background Non-alcoholic steatohepatitis (NASH) is a key stage in leading development of non-alcoholic simple fatty liver (NAFL) into cirrhosis and even liver cancer. This study aimed at exploring the lncRNAs expression profile in NASH and the biological function of a novel LncRNA-gm9795. Methods Microarray analysis was performed to compare the expression profiles of lncRNAs in the liver of NASH, NAFLD and normal mice (5 mice for each group). Methionine-choline-deficient Medium (MCD) with Lipopolysaccharide (LPS) or palmitic acid (PA)were used to built NASH cell models. The role and mechanism of LncRNA-gm9795 in NASH were explored by knocking down or over-expressing its expression. Results A total of 381 lncRNAs were found to be not only highly expressed in NAFLD, but also is going to go even higher in NASH. A novel LncRNA-gm9795 was significantly highly expressed in liver tissues of NASH animal models and NASH cell models. By staining with Nile red, we found that gm9795 did not affect the fat accumulation of NASH. However, gm9795 in NASH cell models significantly promoted the expression of TNF $$\alpha {}$$ α , IL-6, IL-1 $$\beta {}$$ β , the important inflammatory mediators in NASH. At the same time, we found that gm9795 upregulated the key molecules in endoplasmic reticulum stress (ERS), while NF- $$\kappa {}$$ κ B/JNK pathways were also activated. When ERS activator Thapsigargin (TG) was introduced in cells with Ggm9757 si-RNA, NF- $$\kappa {}$$ κ B and JNK pathways were activated. Conversely, ERS inhibitor Tauroursodeoxycholic acid (TUDCA) inhibited NF-kB and JNK pathways in cells with gm9795 overexpression plasmid. Conclusion LncRNA-gm9795 promotes inflammatory response in NASH through NF-kB and JNK pathways by ERS, which might provide theoretical basis for revealing the pathogenesis of NASH and discovering new therapeutic targets

Abstract Background Acute lung injury (ALI) is a serious disease with highly morbidity and mortality that causes serious health problems worldwide. Atypical mitogen activated protein kinases (MAPKs) play critical roles in the development of tissues and have been proposed as promising therapeutic targets for various diseases. However, the potential role of atypical MAPKs in ALI remains elusive. In this study, we investigated the role of atypical MAPKs family member MAPK4 in ALI using LPS-induced murine ALI model. Results We found that MAPK4 deficiency mice exhibited prolonged survival time after LPS challenge, accompanied by alleviated pathology in lung tissues, decreased levels of pro-inflammatory cytokines and altered composition of immune cells in BALF. Furthermore, the transduction of related signaling pathways, including MK5, AKT, JNK, and p38 MAPK pathways, was reduced obviously in LPS-treated MAPK4−/− mice. Notably, the expression of MAPK4 was up-regulated in lung tissues of ALI model, which was not related with MAPK4 promoter methylation, but negatively orchestrated by transcriptional factors NFKB1 and NR3C1. Further studies have shown that the expression of MAPK4 was also increased in LPS-treated macrophages. Meanwhile, MAPK4 deficiency reduced the expression of related pro-inflammatory cytokines in macrophage in response to LPS treatment. Finally, MAPK4 knockdown using shRNA pre-treatment could ameliorate the pathology of lung tissues and prolong the survival time of mice after LPS challenge. Conclusions Collectively, these findings reveal an important biological function of atypical MAPK in mediating the pathology of ALI, indicating that MAPK4 might be a novel potential therapeutic target for ALI treatment.

Abstract Background There has been little published data on estimates of HBV and/or HCV coinfection in HIV-positive patients in China or an understanding of how this coinfection varies with different factors. Therefore, this study aimed to determine, through a systematic review and meta-analysis, the prevalence of HBV and/or HCV in HIV-positive patients in China and explore variations in prevalence. Methods The Medicine, Web of Science, Chinese Web of Knowledge, and Wanfang databases were searched using a search strategy combining key words and related disease-specific subject terms to identify relevant cohort or cross-sectional studies published up to April 2019. Included articles were assessed for quality. Pooled prevalence and 95% confidence intervals (CIs) were calculated according to study region and other specific characteristics. Results Our searches identified 7843 records, but only 66 studies were included in our meta-analysis. The pooled HBsAg prevalence in HIV-positive patients was 13.7% (95% CI 12.3–15.3%), with variations found in terms of age and geographic region. The meta-HCV prevalence was 24.7% (95% CI 19.3–30.5%), which varied over the study period and age. The pooled HBV-HCV coinfection prevalence was 3.5% (95% CI 2.4–4.8%), with variations found in terms of age and geographic region. Conclusion Given the high burden of HBV and HCV coinfections in HIV-positive patients, the incorporation of comprehensive screening, treatment, prevention, and vaccination programs into general HIV management in China is imperative.

Abstract MicroRNAs (miRNAs), which are endogenous about 20–23 nucleotides non-coding RNAs, have been acted as post-transcriptional regulators of gene expression. Current studies demonstrated that miRNAs are promising candidates for tumor gene therapy because of their important biological functions in tumor cell proliferation, metastasis, apoptosis, and drug resistance. As an important delivery system, nanostructured lipid carriers (NLCs) have great potential in tumor gene therapy, particularly for miRNA delivery, due to low toxicity, low immunogenicity, long metabolic cycles, and easy modification. This article reviews recent research progress on NLCs for miRNA delivery in tumor gene therapy and prospective applications.

Abstract Background Algal biofilm technology is recently supposed to be a promising method to produce algal biomass as the feedstock for the production of biofuels. However, the carrier materials currently used to form algal biofilm are either difficult to be obtained at a low price or undurable. Commercialization of the biofilm technology for algal biomass production extremely requires new and inexpensive materials as biofilm carriers with high biomass production performances. Results Four types of lignocellulosic materials were investigated to evaluate their performance of acting as carriers for algal cells attachment and the relevant effects on the algal biomass production in this study. The cultivation of algal biofilm was processed in a self-designed flat plate photo-bioreactor. The biofilm production and chemical composition of the harvested biomass were determined. The surface physics properties of the materials were examined through a confocal laser-scanning microscopy. Algal biomass production varied significantly with the variation of the carriers (P