Case report: septic shock after endometrial polypectomy with tissue removal system.

As an emerging surgical technology, tissue removal systems have been widely used in the treatment of endometrial polyps due to its characteristics of less endometrial damage, shorter learning curve and clearer vision of the operative field. There are few cases in the literature reporting serious complications after endometrial polypectomy using tissue removal systems. As known, septic shock is a rare complication following hysteroscopic polypectomy. Now, we present the case of a 23-year-old woman who developed septic shock after polypectomy with tissue removal system. The patient had a history of recurrent vaginitis for more than half a year. Due to endometrial polyps, she was admitted to our hospital and scheduled to undergo hysteroscopic endometrial polypectomy. Three hours after the endometrial polypectomy using the tissue removal system, the patient had shock symptoms such as increased body temperature, decreased blood pressure and increased heart rate. Then, the patient was successfully treated and discharged after anti-infection and anti-shock treatments. The purpose of this case report is to remind clinicians to consider the possibility of serious infection and comprehensively evaluate the risk of infection before choosing hysteroscopic devices for endometrial polyps, especially for patients who choose the mechanical hysteroscopic tissue removal systems. Furthermore, the mechanical hysteroscopic tissue removal systems should be used with caution in patients with previous recurrent vaginitis.

RETICULON-LIKE PROTEIN B2 is a proviral factor co-opted for the biogenesis of viral replication organelles in plants.

Endomembrane remodeling to form a viral replication complex (VRC) is crucial for a virus to establish infection in a host. Although the composition and function of VRCs have been intensively studied, host factors involved in the assembly of VRCs for plant RNA viruses have not been fully explored. TurboID-based proximity labeling (PL) has emerged as a robust tool for probing molecular interactions in planta. However, few studies have employed the TurboID-based PL technique for investigating plant virus replication. Here, we used Beet black scorch virus (BBSV), an endoplasmic reticulum (ER)-replicating virus, as a model and systematically investigated the composition of BBSV VRCs in Nicotiana benthamiana by fusing the TurboID enzyme to viral replication protein p23. Among the 185 identified p23-proximal proteins, the reticulon family of proteins showed high reproducibility in the mass spectrometry data sets. We focused on RETICULON-LIKE PROTEIN B2 (RTNLB2) and demonstrated its proviral functions in BBSV replication. We showed that RTNLB2 binds to p23, induces ER membrane curvature, and constricts ER tubules to facilitate the assembly of BBSV VRCs. Our comprehensive proximal interactome analysis of BBSV VRCs provides a resource for understanding plant viral replication and offers additional insights into the formation of membrane scaffolds for viral RNA synthesis.

Hydroxychloroquine protects against autoimmune premature ovarian insufficiency by modulating the Treg/Th17 cell ratio in BALB/c mice.

AIMS: The role of hydroxychloroquine (HCQ) in premature ovarian insufficiency (POI) remains unclear. The purpose of this study was to evaluate the effect of HCQ on ovarian function in mice with POI and to clarify its potential mechanisms. METHODS: POI was induced in mice by injection with zona pellucida 3 peptide (pZP3), and HCQ was administered intragastrically. Stages of the estrous cycle were determined using vaginal cytology. The ovarian structure was observed under a microscope after hematoxylin-eosin staining. The levels of serum hormones and anti-ZP antibody (aZPAb) were measured using enzyme-linked immunosorbent assay (ELISA). The expression levels of CD4, CD45, and ZP2, ZP3 were determined using immunofluorescence and immunohistochemistry, respectively. The T regulatory (Treg)/ T helper 17 (Th17) cell ratio was analyzed using flow cytometry analysis. Western blotting was performed to assess the expression levels of proteins, transcription factors and cytokines. RESULTS: Administration of HCQ to mice with POI greatly restored their estrus cycle. In the treatment group compared to the POI group, estradiol (E2 ) levels were higher, and follicle stimulating hormone (FSH) levels were lower. In addition, following pZP3, HCQ treatment increased ZP2 and ZP3 expression. Additionally, by inhibiting the activation of the TLR7 signaling pathway, HCQ attenuated the infiltration of inflammatory cells and prevented the activated naive CD4+ T cells from developing into Th17 cells. CONCLUSION: Our findings showed that HCQ effectively restored ovarian function by altering the Treg/Th17 cell ratio in mice with POI, indicating that HCQ maybe a promising therapeutic method for patients with POI.

WheatCENet: A Database for Comparative Co-expression Networks Analysis of Allohexaploid Wheat and Its Progenitors.

Genetic and epigenetic changes after polyploidization events could result in variable gene expression and modified regulatory networks. Here, using large-scale transcriptome data, we constructed co-expression networks for diploid, tetraploid, and hexaploid wheat species, and built a platform for comparing co-expression networks of allohexaploid wheat and its progenitors, named WheatCENet. WheatCENet is a platform for searching and comparing specific functional co-expression networks, as well as identifying the related functions of the genes clustered therein. Functional annotations like pathways, gene families, protein-protein interactions, microRNAs (miRNAs), and several lines of epigenome data are integrated into this platform, and Gene Ontology (GO) annotation, gene set enrichment analysis (GSEA), motif identification, and other useful tools are also included. Using WheatCENet, we found that the network of WHEAT ABERRANT PANICLE ORGANIZATION 1 (WAPO1) has more co-expressed genes related to spike development in hexaploid wheat than its progenitors. We also found a novel motif of CCWWWWWWGG (CArG) specifically in the promoter region of WAPO-A1, suggesting that neofunctionalization of the WAPO-A1 gene affects spikelet development in hexaploid wheat. WheatCENet is useful for investigating co-expression networks and conducting other analyses, and thus facilitates comparative and functional genomic studies in wheat. WheatCENet is freely available at http://bioinformatics.cpolar.cn/WheatCENet and http://bioinformatics.cau.edu.cn/WheatCENet.

Metabonomic Characteristics of Myocardial Diastolic Dysfunction in Type 2 Diabetic Cardiomyopathy Patients.

Diabetic cardiomyopathy (DCM) is one of the most essential cardiovascular complications in diabetic patients associated with glucose and lipid metabolism disorder, fibrosis, oxidative stress, and inflammation in cardiomyocytes. Despite increasing research on the molecular pathogenesis of DCM, it is still unclear whether metabolic pathways and alterations are probably involved in the development of DCM. This study aims to characterize the metabolites of DCM and to identify the relationship between metabolites and their biological processes or biological states through untargeted metabolic profiling. UPLC-MS/MS was applied to profile plasma metabolites from 78 patients with diabetes (39 diabetes with DCM and 39 diabetes without DCM as controls). A total of 2,806 biochemical were detected. Compared to those of DM patients, 78 differential metabolites in the positive-ion mode were identified in DCM patients, including 33 up-regulated and 45 down-regulated metabolites; however, there were only six differential metabolites identified in the negative mode including four up-regulated and two down-regulated metabolites. Alterations of several serum metabolites, including lipids and lipid-like molecules, organic acids and derivatives, organic oxygen compounds, benzenoids, phenylpropanoids and polyketides, and organoheterocyclic compounds, were associated with the development of DCM. KEGG enrichment analysis showed that there were three signaling pathways (metabolic pathways, porphyrin, chlorophyll metabolism, and lysine degradation) that were changed in both negative- and positive-ion modes. Our results demonstrated that differential metabolites and lipids have specific effects on DCM. These results expanded our understanding of the metabolic characteristics of DCM and may provide a clue in the future investigation of reducing the incidence of DCM. Furthermore, the metabolites identified here may provide clues for clinical management and the development of effective drugs.

The Alteration of m6A Modification at the Transcriptome-Wide Level in Human Villi During Spontaneous Abortion in the First Trimester.

A growing number of studies have demonstrated that N6 methyladenine (m6A) acts as an important role in the pathogenesis of reproductive diseases. Therefore, it is essential to profile the genome-wide m6A modifications such as in spontaneous abortion. In this study, due to the trace of human villi during early pregnancy, we performed high-throughput sequencing in villous tissues from spontaneous abortion (SA group) and controls with induced abortion (normal group) in the first trimester. Based on meRIP-seq data, 18,568 m6A peaks were identified. These m6A peaks were mainly located in the coding region near the stop codon and were mainly characterized by AUGGAC and UGGACG motif. Compared with normal group, the SA group had 2,159 significantly upregulated m6A peaks and 281 downregulated m6A peaks. Biological function analyses revealed that differential m6A-modified genes were mainly involved in the Hippo and Wnt signaling pathways. Based on the conjoint analysis of meRIP-seq and RNA-seq data, we identified thirty-five genes with differentially methylated m6A peaks and synchronously differential expression. And these genes were mainly involved in the Wnt signaling pathway, phosphatase activity regulation, protein phosphatase inhibitor activity, and transcription inhibitor activity. This study is the first to profile the transcriptome-wide m6A methylome in spontaneous abortion during early pregnancy, which provide novel insights into the pathogenesis and treatment of spontaneous abortion in the first trimester.

A Joint Model of Random Forest and Artificial Neural Network for the Diagnosis of Endometriosis.

Endometriosis (EM), an estrogen-dependent inflammatory disease with unknown etiology, affects thousands of childbearing-age couples, and its early diagnosis is still very difficult. With the rapid development of sequencing technology in recent years, the accumulation of many sequencing data makes it possible to screen important diagnostic biomarkers from some EM-related genes. In this study, we utilized public datasets in the Gene Expression Omnibus (GEO) and Array-Express database and identified seven important differentially expressed genes (DEGs) (COMT, NAA16, CCDC22, EIF3E, AHI1, DMXL2, and CISD3) through the random forest classifier. Among these DEGs, AHI1, DMXL2, and CISD3 have never been reported to be associated with the pathogenesis of EMs. Our study indicated that these three genes might participate in the pathogenesis of EMs through oxidative stress, epithelial-mesenchymal transition (EMT) with the activation of the Notch signaling pathway, and mitochondrial homeostasis, respectively. Then, we put these seven DEGs into an artificial neural network to construct a novel diagnostic model for EMs and verified its diagnostic efficacy in two public datasets. Furthermore, these seven DEGs were included in 15 hub genes identified from the constructed protein-protein interaction (PPI) network, which confirmed the reliability of the diagnostic model. We hope the diagnostic model can provide novel sights into the understanding of the pathogenesis of EMs and contribute to the clinical diagnosis and treatment of EMs.

HpeNet: Co-expression Network Database for de novo Transcriptome Assembly of Paeonia lactiflora Pall.

The herbaceous peony (Paeonia lactiflora Pall.) is a well-known ornamental flowering and pharmaceutical plant found in China. Its high medicinal value has long been recognized by traditional Chinese medicine (as Radix paeoniae Alba and Radix paeoniae Rubra), and it has become economically valued for its oilseed in recent years; like other Paeonia species, it has been identified as a novel resource for the α-linolenic acid used in seed oil production. However, its genome has not yet been sequenced, and little transcriptome data on Paeonia lactiflora are available. To obtain a comprehensive transcriptome for Paeonia lactiflora, RNAs from 10 tissues of the Paeonia lactiflora Pall. cv Shaoyou17C were used for de novo assembly, and 416,062 unigenes were obtained. Using a homology search, it was found that 236,222 (approximately 57%) unigenes had at least one BLAST hit in one or more public data resources. The construction of co-expression networks is a feasible means for improving unigene annotation. Using in-house transcriptome data, we obtained a co-expression network covering 95.13% of the unigenes. Then we integrated co-expression network analyses and lipid-related pathway genes to study lipid metabolism in Paeonia lactiflora cultivars. Finally, we constructed the online database HpeNet (http://bioinformatics.cau.edu.cn/HpeNet) to integrate transcriptome data, gene information, the co-expression network, and so forth. The database can also be searched for gene details, gene functions, orthologous matches, and other data. Our online database may help the research community identify functional genes and perform research on Paeonia lactiflora more conveniently. We hope that de novo transcriptome assembly, combined with co-expression networks, can provide a feasible means to predict the gene function of species that do not have a reference genome.

Coexpression Analysis Reveals Dynamic Modules Regulating the Growth and Development of Cirri in the Rattans (Calamus simplicifolius and Daemonorops jenkinsiana).

Rattan is regarded as one of the major non-timber forest products, second only to wood and bamboo, worldwide. Although the published genomes of Calamus simplicifolius and Daemonorops jenkinsiana have facilitated genome-wide gene functional analyses, coexpression networks (CENs) provide more comprehensive and complete annotations of gene function at the transcriptome level. Thus, we analyzed the CENs of the two rattans, C. simplicifolius and D. jenkinsiana, by integrating the genome sequences and analyzing in-house transcriptome data from different development stages of their cirri using a well-developed strategy. A total of 3,504 and 3,027 functional modules were identified in C. simplicifolius and D. jenkinsiana, respectively, based on a combination of CENs, gene family classification, and function enrichment tools. These modules covered the major developmental processes, including photosynthesis, lignin biosynthesis, flavonoid biosynthesis, and phenylpropanoid biosynthesis. Reference annotations were refined using CENs and functional modules. Moreover, we obtained novel insights into the regulation of cirrus growth and development in rattans. Furthermore, Rattan-NET (http://rattan.bamboogdb.org/), an online database with analysis tools for gene set enrichment analysis, module enrichment, network comparison analysis, and cis-element analysis, was constructed for the easy analysis of gene function and regulation modules involved in the growth and development of cirri in rattans.

AppleMDO: A Multi-Dimensional Omics Database for Apple Co-Expression Networks and Chromatin States.

As an economically important crop, apple is one of the most cultivated fruit trees in temperate regions worldwide. Recently, a large number of high-quality transcriptomic and epigenomic datasets for apple were made available to the public, which could be helpful in inferring gene regulatory relationships and thus predicting gene function at the genome level. Through integration of the available apple genomic, transcriptomic, and epigenomic datasets, we constructed co-expression networks, identified functional modules, and predicted chromatin states. A total of 112 RNA-seq datasets were integrated to construct a global network and a conditional network (tissue-preferential network). Furthermore, a total of 1,076 functional modules with closely related gene sets were identified to assess the modularity of biological networks and further subjected to functional enrichment analysis. The results showed that the function of many modules was related to development, secondary metabolism, hormone response, and transcriptional regulation. Transcriptional regulation is closely related to epigenetic marks on chromatin. A total of 20 epigenomic datasets, which included ChIP-seq, DNase-seq, and DNA methylation analysis datasets, were integrated and used to classify chromatin states. Based on the ChromHMM algorithm, the genome was divided into 620,122 fragments, which were classified into 24 states according to the combination of epigenetic marks and enriched-feature regions. Finally, through the collaborative analysis of different omics datasets, the online database AppleMDO (http://bioinformatics.cau.edu.cn/AppleMDO/) was established for cross-referencing and the exploration of possible novel functions of apple genes. In addition, gene annotation information and functional support toolkits were also provided. Our database might be convenient for researchers to develop insights into the function of genes related to important agronomic traits and might serve as a reference for other fruit trees.

croFGD: Catharanthus roseus Functional Genomics Database.

Catharanthus roseus is a medicinal plant, which can produce monoterpene indole alkaloid (MIA) metabolites with biological activity and is rich in vinblastine and vincristine. With release of the scaffolded genome sequence of C. roseus, it is necessary to annotate gene functions on the whole-genome level. Recently, 53 RNA-seq datasets are available in public with different tissues (flower, root, leaf, seedling, and shoot) and different treatments (MeJA, PnWB infection and yeast elicitor). We used in-house data process pipeline with the combination of PCC and MR algorithms to construct a co-expression network exploring multi-dimensional gene expression (global, tissue preferential, and treat response) through multi-layered approaches. In the meanwhile, we added miRNA-target pairs, predicted PPI pairs into the network and provided several tools such as gene set enrichment analysis, functional module enrichment analysis, and motif analysis for functional prediction of the co-expression genes. Finally, we have constructed an online croFGD database (http://bioinformatics.cau.edu.cn/croFGD/). We hope croFGD can help the communities to study the C. roseus functional genomics and make novel discoveries about key genes involved in some important biological processes.