MiRS-HF: A Novel Deep Learning Predictor for Cancer Classification and miRNA Expression Patterns.

Cancer classification and biomarker identification are crucial for guiding personalized treatment. To make effective use of miRNA associations and expression data, we have developed a deep learning model for cancer classification and biomarker identification. To make effective use of miRNA associations and expression data, we have developed a deep learning model for cancer classification and biomarker identification. We propose an approach for cancer classification called MiRNA Selection and Hybrid Fusion (MiRS-HF), which consists of early fusion and intermediate fusion. The early fusion involves applying a Layer Attention Graph Convolutional Network (LAGCN) to a miRNA-disease heterogeneous network, resulting in a miRNA-disease association degree score matrix. The intermediate fusion employs a Graph Convolutional Network (GCN) in the classification tasks, weighting the expression data based on the miRNA-disease association degree score. Furthermore, MiRS-HF can identify the important miRNA biomarkers and their expression patterns. The proposed method demonstrates superior performance in the classification tasks of six cancers compared to other methods. Simultaneously, we incorporated the feature weighting strategy into the comparison algorithm, leading to a significant improvement in the algorithm's results, highlighting the extreme importance of this strategy.

Fine-scale genomic analysis of the tree endophyte Annulohypoxylon sp. FPYF3050 producing monoterpene 1,8-cineole.

1,8-Cineole has a potential in control crop pests and biofuels. The endophytic fungus, Annulohypoxylon sp. FPYF3050 (Neolitsea pulchella), can produce over 90% 1,8-cineole of relative area in its natural volatiles, possessed nematicide properties. The annotated genome of this strain will provide insights into potential application in biofumigation and terpene-based advanced biofuel.

Discovering type I cis-AT polyketides through computational mass spectrometry and genome mining with Seq2PKS.

Type 1 polyketides are a major class of natural products used as antiviral, antibiotic, antifungal, antiparasitic, immunosuppressive, and antitumor drugs. Analysis of public microbial genomes leads to the discovery of over sixty thousand type 1 polyketide gene clusters. However, the molecular products of only about a hundred of these clusters are characterized, leaving most metabolites unknown. Characterizing polyketides relies on bioactivity-guided purification, which is expensive and time-consuming. To address this, we present Seq2PKS, a machine learning algorithm that predicts chemical structures derived from Type 1 polyketide synthases. Seq2PKS predicts numerous putative structures for each gene cluster to enhance accuracy. The correct structure is identified using a variable mass spectral database search. Benchmarks show that Seq2PKS outperforms existing methods. Applying Seq2PKS to Actinobacteria datasets, we discover biosynthetic gene clusters for monazomycin, oasomycin A, and 2-aminobenzamide-actiphenol.

Biobank-wide association scan identifies risk factors for late-onset Alzheimer's disease and endophenotypes.

Rich data from large biobanks, coupled with increasingly accessible association statistics from genome-wide association studies (GWAS), provide great opportunities to dissect the complex relationships among human traits and diseases. We introduce BADGERS, a powerful method to perform polygenic score-based biobank-wide association scans. Compared to traditional approaches, BADGERS uses GWAS summary statistics as input and does not require multiple traits to be measured in the same cohort. We applied BADGERS to two independent datasets for late-onset Alzheimer's disease (AD; n=61,212). Among 1738 traits in the UK biobank, we identified 48 significant associations for AD. Family history, high cholesterol, and numerous traits related to intelligence and education showed strong and independent associations with AD. Furthermore, we identified 41 significant associations for a variety of AD endophenotypes. While family history and high cholesterol were strongly associated with AD subgroups and pathologies, only intelligence and education-related traits predicted pre-clinical cognitive phenotypes. These results provide novel insights into the distinct biological processes underlying various risk factors for AD.

AdenPredictor: accurate prediction of the adenylation domain specificity of nonribosomal peptide biosynthetic gene clusters in microbial genomes.

Microbial natural products represent a major source of bioactive compounds for drug discovery. Among these molecules, nonribosomal peptides (NRPs) represent a diverse class that include antibiotics, immunosuppressants, anticancer agents, toxins, siderophores, pigments, and cytostatics. The discovery of novel NRPs remains a laborious process because many NRPs consist of nonstandard amino acids that are assembled by nonribosomal peptide synthetases (NRPSs). Adenylation domains (A-domains) in NRPSs are responsible for selection and activation of monomers appearing in NRPs. During the past decade, several support vector machine-based algorithms have been developed for predicting the specificity of the monomers present in NRPs. These algorithms utilize physiochemical features of the amino acids present in the A-domains of NRPSs. In this article, we benchmarked the performance of various machine learning algorithms and features for predicting specificities of NRPSs and we showed that the extra trees model paired with one-hot encoding features outperforms the existing approaches. Moreover, we show that unsupervised clustering of 453 560 A-domains reveals many clusters that correspond to potentially novel amino acids. While it is challenging to predict the chemical structure of these amino acids, we developed novel techniques to predict their various properties, including polarity, hydrophobicity, charge, and presence of aromatic rings, carboxyl, and hydroxyl groups.

The use of physical restraints and PRN medications in adolescent psychiatric inpatient units.

PROBLEM: Although physical restraint practices and psychotropic/sedative pro re neta (PRN, as needed) medications have been commonly used for managing inpatient aggression, little is known about the characteristics of adolescents who receive them in psychiatric adolescent inpatient units. We aimed to determine the relationship between the use of physical restraints and psychotropic/sedative PRN medications, and to characterize individual attributes, substance use, clinical factors, and time of the first restraint episodes of the use of physical restraints and psychotropic/sedative PRN medications. METHODS: A retrospective case-control study approach was used with the data from electronic health records at a pediatric psychiatric hospital in the United States. Descriptive statistics, χ2 , multivariate logistic regression, and Cox proportional hazard model were used. FINDINGS: Participants of younger age and participants with a longer length of stay were significantly associated with the use of physical restraints and psychotropic/sedative PRN medications, although the substance-related risks were not significantly associated with the use of restraints. Physical restraints were more likely to have occurred soon after the admission and tapered off as the length of stay increased. CONCLUSIONS: This study provides important information in understanding the risk factors of the use of restraints and psychotropic/sedative PRN medications in psychiatric adolescent inpatient units.

Integrating pharmacokinetics and network analysis to investigate the mechanism of Moutan Cortex in blood-heat and blood stasis syndrome.

BACKGROUND: Raw Moutan Cortex (RMC) has been used in China and other Asian countries for thousands of years. Its medical application is the treatment of cooling blood and promoting blood circulation. However, its therapeutic mechanism is still undefined. METHODS: In this study, the pharmacokinetics strategy that integrated network analysis was employed to explore the mechanism of RMC in blood-heat and blood stasis syndrome (BHS) model rats. Firstly, Ultra-High performance Liquid Chromatography coupled with Diode Array Detector (UHPLC-DAD) method was developed to determine nine absorbed compounds in rat serum in BHS and normal rats after oral administration of RMC extract respectively. Then the pharmacology network was established based on the relationship between nine compounds absorbed into the blood and BHS targets. Finally, the predicted hub targets were validated experimentally in human umbilical vein endothelial cells (HUVECs). RESULTS: Pharmacokinetic study showed that the pharmacokinetic parameters of nine absorbed compounds had significant differences between BHS and normal groups (p < 0.05). Network analysis showed that 8 target genes, namely, F2, F10, F7, PLAU, MAPK14, MAPK10, AKT1, and NOS3 may be the primary targets regulated by RMC for the treatment of BHS. Among them, targets (F2, F10, F7 and MAPK14, MAPK10, AKT) and 4 active ingredients (paeonol, paeoniflorin, quercetin and oxypaeoniflorin) were selected for evaluating the reliability in vitro experiments, which revealed that the mechanism of RMC against BHS syndrome may inhibit inflammatory pathways and regulate coagulation cascades pathway for cooling and promoting blood circulation. CONCLUSION: The proposed pharmacokinetics study integrated network analysis strategy provides a combination method to explore the therapeutic mechanism of RMC on BHS.

Identification of ophiostomatalean fungi associated with Tomicus pilifer infesting Pinus koraiensis in Northeastern China.

Ophiostomatalean fungi usually facilitate bark beetles to infest tree hosts and seriously endanger the health of coniferous forests. Tomicus pilifer Spessivtsev is a common endemic bark beetle in Asia and primarily threatens Pinus koraiensis. Tomicus species have similar morphology; however, they can be differentiated by their genetic characteristics through phylogenetic analyses. To date, the 28S rDNA sequence of T. pilifer and the diversity of ophiostomatalean fungi associated with T. pilifer have not been reported. In this study, we aimed to clarify the taxonomic status of T. pilifer and identify ophiostomatalean fungi associated with T. pilifer infesting P. koraiensis in northeastern China. In total, 315 ophiostomatalean fungal strains were isolated from 62 adults of T. pilifer and 220 tissue samples from T. pilifer galleries in Jilin Province. Thirty-five representative strains were further identified by comparing their morphological and physiological characteristics and conducting the phylogenetic analysis of ITS, ITS2-LSU, TUB2, and TEF1-α. We identified nine species of ophiostomatalean fungi belonging to four genera, which included six novel species (Ceratocystiopsis changbaiensis sp. nov., Leptographium linjiangense sp. nov., Leptographium qieshaoense sp. nov., Ophiostoma piliferi sp. nov., Ophiostoma tonghuaense sp. nov., and Ophiostoma yaluense sp. nov.), two previously described species (Graphilbum interstitiale and Ophiostoma fuscum), and one undefined specie (Ceratocystiopsis sp. 1). To the best of our knowledge, this is the first report of G. interstitiale and O. fuscum in China and the fungal diversity of ophiostomatalean in T. pilifer. The dominant species were O. piliferi and L. qieshaoense, representing 39.37% and 35.87% of the isolates, respectively. The results of this study provide valuable information on the symbiotic relationship between bark beetles and ophiostomatalean fungi.

PeTGA1 enhances disease resistance against Colletotrichum gloeosporioides through directly regulating PeSARD1 in poplar.

Basic leucine zipper (bZIP) proteins play important roles in responding to biotic and abiotic stresses in plants. However, the molecular mechanisms of plant resistance to pathogens remain largely unclear in poplar. The present study isolated a TGACG-binding (TGA) transcription factor, PeTGA1, from Populus euphratica. PeTGA1 belongs to subgroup D of the bZIP family and was localized to the nucleus. To study the role PeTGA1 plays in response to Colletotrichum gloeosporioides, transgenic triploid white poplars overexpressing PeTGA1 were generated. Results showed that poplars with overexpressed PeTGA1 showed a higher effective defense response to C. gloeosporioides than the wild-type plants. A yeast one-hybrid assay and an electrophoretic mobility shift assay revealed that PeTGA1 could directly bind to the PeSARD1 (P. euphratica SYSTEMIC ACQUIRED RESISTANCE DEFICIENT 1) promoter, an important regulator for salicylic acid biosynthesis. The transactivation assays indicated that PeTGA1 activated the expression of PeSARD1, and PR1 (PATHOGENESIS-RELATED 1), a SA marker gene involved in SA signaling. Subsequently, we observed that the PeTGA1 overexpression lines showed elevated SA levels, thereby resulting in the increased resistance to C. gloeosporioides. Taken together, our results indicated that PeTGA1 may exert a key role in plant immunity not only by targeting PeSARD1 thus participating in the SA biosynthesis pathway but also by involving in SA signaling via activating the expression of PR1.

TransDiscovery: Discovering Biotransformation from Human Microbiota by Integrating Metagenomic and Metabolomic Data.

The human microbiome is a complex community of microorganisms, their enzymes, and the molecules they produce or modify. Recent studies show that imbalances in human microbial ecosystems can cause disease. Our microbiome affects our health through the products of biochemical reactions catalyzed by microbial enzymes (microbial biotransformations). Despite their significance, currently, there are no systematic strategies for identifying these chemical reactions, their substrates and molecular products, and their effects on health and disease. We present TransDiscovery, a computational algorithm that integrates molecular networks (connecting related molecules with similar mass spectra), association networks (connecting co-occurring molecules and microbes) and knowledge bases of microbial enzymes to discover microbial biotransformations, their substrates, and their products. After searching the metabolomics and metagenomics data from the American Gut Project and the Global Foodomic Project, TranDiscovery identified 17 potentially novel biotransformations from the human gut microbiome, along with the corresponding microbial species, substrates, and products.

Clinicopathological factors affecting the prognosis of massive hemorrhage after radiotherapy for patients having nasopharyngeal carcinoma.

AIMS: The aim of the study is to investigate the clinicopathological factors that determine prognosis of nasopharyngeal hemorrhage after radiotherapy in patients with nasopharyngeal carcinoma (NPC). PATIENTS AND METHODS: The clinicopathological data of 539 patients with NPC, who received radiotherapy, were analyzed retrospectively. Parameters included gender; age; T-stage; N-stage; pathological type; type of radiotherapy; synchronous chemotherapy; secondary-course radiotherapy; radiation-induced skull base osteonecrosis; diabetes, hypertension, or other systemic diseases; results of nasopharyngeal bacterial culture; and nasopharyngeal tumor recurrence. Univariate and multivariate analyses were performed using the Chi-square test and logistic regression. Afterward, the Kaplan-Meier's method was applied to analyze the survival of patients with nasopharyngeal hemorrhage. RESULTS: Among all patients examined, 64 (11.9%) had nasopharyngeal hemorrhage after radiotherapy. The univariate analysis showed that T-stage (P < 0.01), secondary-course radiotherapy (P < 0.01), radiation-induced skull base osteonecrosis (P < 0.01), nasopharyngeal bacterial culture results (P < 0.01), and nasopharyngeal tumor recurrence (P < 0.01) were associated with nasopharyngeal hemorrhage. Multivariate analysis showed that only radiation-induced skull base osteonecrosis was significantly associated with nasopharyngeal hemorrhage after radiotherapy (odds ratio = 41.83, P = 0.0001). Nevertheless, in patients with internal carotid artery hemorrhage, the survival rate was much lower than that in patients with external carotid artery bleeding. The main cause of death during follow-up was rebleeding. CONCLUSION: The rate of mortality in patients with nasopharyngeal hemorrhage after radiotherapy was high. The presence of radiation-induced skull base osteonecrosis was a decisive factor in these patients. However, after successful rescue, arterial embolization or stent implantation is proposed to prolong survival.

Development of a novel chemokine signaling-based multigene signature to predict prognosis and therapeutic response in colorectal cancer.

Colorectal cancer (CRC) is the most lethal gastrointestinal cancer in both males and females worldwide (Sung et al., 2021). Because of the high heterogeneity of tumors, robust prognostic biomarkers are urgently needed in CRC management (Koncina et al., 2020). Chemokine signaling is a well-known pivotal player in immunity, inflammation, and cancer metastasis (Lacalle et al., 2017; Poeta et al., 2019; Do et al., 2020), and multiple genes involved in chemokine signaling have been demonstrated as potential prognostic biomarkers for CRC (Cabrero-De Las Heras and Martínez-Balibrea, 2018; Ottaiano et al., 2020; Yu et al., 2020). Therefore, the aim of our study was to develop a chemokine signaling-based multigene signature (CSbMgSig) that could effectively predict overall survival (OS) and therapeutic response for patients with CRC.

Bacterial and fungal communities of traditional fermented Chinese soybean paste (Doujiang) and their properties.

Soybean paste (Doujiang) is one of the traditional fermented foods from China, fermented by various microorganisms. However, the microflora of Doujiang keeps little known. In this study, the microbial communities of seven kinds of representative Doujiang samples were investigated by both culture-independent and culture-dependent methods. We found that core OTUs among seven Doujiang samples were mainly from Bacillus, Pseudomonas, Candida, and Aspergillus according to Illumina sequencing. Every type of Doujiang sample harbored a different composition of microbial community. Doujiang LSJ and LBJ had the highest bacterial and fungal richness and diversity, respectively. The structure of microbial community was remarkably correlated with Doujiang properties-pH, and the content of total protein, soluble protein, amino acid, and total sugar (p < .05). Bacillus spp. were most frequently isolated bacterial species. Fungi of Monascus, Candida, and Aspergillus were also isolated. Eleven microbial strains showed high protease activities to degrade corn proteins, which can form obvious transparent hydrolytic circles in corn gluten meal medium plates. Therefore, microbial communities were supposed to tightly connect to Doujiang type and properties. It is possible to apply potential protein-degrading microbial strains to corn byproducts for protein production in the future study.

A Ferroptosis-Related Gene Signature Identified as a Novel Prognostic Biomarker for Colon Cancer.

BACKGROUND: Colon cancer (CC) is a common gastrointestinal malignant tumor with high heterogeneity in clinical behavior and response to treatment, making individualized survival prediction challenging. Ferroptosis is a newly discovered iron-dependent cell death that plays a critical role in cancer biology. Therefore, identifying a prognostic biomarker with ferroptosis-related genes provides a new strategy to guide precise clinical decision-making in CC patients. METHODS: Alteration in the expression profile of ferroptosis-related genes was initially screened in GSE39582 dataset involving 585 CC patients. Univariate Cox regression analysis and LASSO-penalized Cox regression analysis were combined to further identify a novel ferroptosis-related gene signature for overall survival prediction. The prognostic performance of the signature was validated in the GSE17536 dataset by Kaplan-Meier survival curve and time-dependent ROC curve analyses. Functional annotation of the signature was explored by integrating GO and KEGG enrichment analysis, GSEA analysis and ssGSEA analysis. Furthermore, an outcome risk nomogram was constructed considering both the gene signature and the clinicopathological features. RESULTS: The prognostic signature biomarker composed of 9 ferroptosis-related genes accurately discriminated high-risk and low-risk patients with CC in both the training and validation datasets. The signature was tightly linked to clinicopathological features and possessed powerful predictive ability for distinct clinical subgroups. Furthermore, the risk score was confirmed to be an independent prognostic factor for CC patients by multivariate Cox regression analysis (p < 0.05). Functional annotation analyses showed that the prognostic signature was closely correlated with pivotal cancer hallmarks, particularly cell cycle, transcriptional regulation, and immune-related functions. Moreover, a nomogram with the signature was also built to quantify outcome risk for each patient. CONCLUSION: The novel ferroptosis-related gene signature biomarker can be utilized for predicting individualized prognosis, optimizing survival risk assessment and facilitating personalized management of CC patients.

Chinese chestnut yellow crinkle disease influence microbiota composition of chestnut trees.

CONTEXT: Candidatus-phytoplasma castaneae has been found as the causal agent of the Chinese chestnut yellow crinkle disease. However, the ecological impact of the disease on microbiota of chestnut trees is unknown. AIMS: The study aim was to clarify difference attributes in microbial community structure of asymptomatic and symptomatic chestnut leaves and twigs for chestnut tree health in orchard. METHODS: Sample collections were conducted with both symptomatic and asymptomatic chestnut trees. Total DNA was extracted. Fungal ITS rDNA and bacterial 16S rDNA were amplified. The PCR products were sequenced with Illumina HiSeq. Platform. RESULTS: A total number of 852 fungal and 1156 bacterial OTUs (operational taxonomic units) were detected. The asymptomatic samples had a higher fungal and bacterial diversity than symptomatic ones. Non-metric multidimensional scaling (NMDS) analysis showed microbial communities among symptomatic and asymptomatic leaves and twigs samples formed individual cluster. Overall, Ascomycota and Proteobacteria were the most abundant fungal and bacterial phyla, respectively. Significantly different taxa playing key roles for each microbiota structure were identified. In symptomatic trees, microbial groups of plant pathogens were more abundant. CONCLUSION: Our results demonstrated that the phytoplasma pathogen may exert significant influence on the microbial community structure. The study will provide further fundamental clues for the little studied phytoplasma pathogens effects on host microbiota, phytoplasma pathogen control strategies.

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Drought is a main factor affecting the growth and yield of Chinese chestnut trees in Yan-shan Mountains. To investigate the responses of chestnut seedlings to drought stress, the growth and physiological indices, including photosynthetic characteristics, biomass, proline, malondialdehyde, carbon and nitrogen contents were measured in roots, stems, and leaves after the Chinese chestnut 'Yanshanzaofeng' seedlings in the pots were treated by simulating drought for 22 days. The results showed that, compared with the normal irrigation, water contents in the roots, stems and leaves were decreased by 18.3%, 29.0% and 62.8%, respectively, accompanied by the considerable increases in the contents of proline (355.0%-1586.7%) and malondialdehyde except in the stems (41.1%-81.3%). The non-photochemical quenching coefficiency and net photosynthetic rate in the leaves were significantly decreased by 49.4% and 77.4%, respectively. The contents of non-structural carbohydrates were increased by 21.4% in stems and 69.5% in leaves, but that in roots did not change. The contents of nitrate were increased by 28.9% in stems and 26.8% in leaves, but that in roots did not change. Ammonium nitrogen was increased by 16.2%, 12.9% and 217.6% in roots, stems, and leaves, but being statistically significant in the leaves. These results indicated that drought stress led to serious damage to 'Yanshanzaofeng' chestnut seedlings, which inhibited photosynthetic performance, but they could improve their adaptation to drought stress by enhancing carbon and nitrogen metabolism. Our results provide a reference for the breeding and cultivation of drought resistance of the local Chinese chestnut resources.

Nine absorbed components pharmacokinetic of raw and processed Moutan Cortex in normal and blood-heat and hemorrhage syndrome model rats.

Raw Moutan Cortex (RMC) and Processed Moutan Cortex (PMC) have a long history of use in China and other Asian countries. In this study, a rapid and accurate ultra-high-pressure liquid chromatography coupled with diode array detector (UHPLC-DAD) method was developed and validated for the simultaneous determination of nine absorbed compounds of RMC/PMC. After extraction by protein precipitation with methanol from plasma, the analytes were separated on an Acquity UPLC® BEH Shield RP18 column (2.1 × 100 mm, 1.7 µm, Waters, USA). Acetonitrile (A) and 0.1% (v/v) formic acid in water (B) were selected as the mobile phase to perform gradient elution. The linearity of nine analytes was >0.9915. The intra- and inter-assay precision (RSD) values were within 11.18%, and accuracy ranged from 91.32 to 101.29%. Suitable stability, matrix effect and extraction recoveries were also obtained. The validated method was applied to compare the pharmacokinetics of RMC and PMC in Blood-Heat and Hemorrhage Syndrome Model and normal rats. The results revealed that processing and the pathological state could influence the pharmacokinetic characteristics of compounds in RMC/PMC. The study willbe useful for further studies on pharmacokinetics and clinical application of raw and processed Moutan Cortex.

Effects of GABA and Vigabatrin on the Germination of Chinese Chestnut Recalcitrant Seeds and Its Implications for Seed Dormancy and Storage.

Recalcitrant chestnut seeds are rich in γ-aminobutyric acid (GABA), which negatively regulates adventitious root development by altering carbon/nitrogen metabolism. However, little is known regarding the role of this metabolite in chestnut seeds. In this study, we investigated the effects of GABA changes on the germination of chestnut seeds treated with exogenous GABA and vigabatrin (VGB, which inhibits GABA degradation). Both treatments significantly inhibited seed germination and primary root growth and resulted in the considerable accumulation of H2O2, but the endogenous GABA content decreased before germination at 48 h. Soluble sugar levels increased before germination, but subsequently decreased, whereas starch contents were relatively unchanged. Changes to organic acids were observed at 120 h after sowing, including a decrease and increase in citrate and malate levels, respectively. Similarly, soluble protein contents increased at 120 h, but the abundance of most free amino acids decreased at 48 h. Moreover, the total amino acid levels increased only in response to VGB at 0 h. Accordingly, GABA and VGB altered the balance of carbon and nitrogen metabolism, thereby inhibiting chestnut seed germination. These results suggested that changes to GABA levels in chestnut seeds might prevent seed germination. The study data may also help clarify the dormancy and storage of chestnut seeds, as well as other recalcitrant seeds.

Distinctive Gene Expression Profiles and Effectors Consistent With Host Specificity in Two Formae Speciales of Marssonina brunnea.

The knowledge on the host specificity of a pathogen underlying an interaction is becoming an urgent necessity for global warming. In this study, the gene expression profiles and the roles of effectors in host specificity were integrally characterized with two formae speciales, multigermtubi and monogermtubi, of a hemibiotrophic pathogen Marssonina brunnea when they were infecting respective susceptible poplar hosts. With a functional genome comparison referring to a de novo transcriptome of M. brunnea and Pathogen-Host Interaction database functional annotations, the multigermtubi strain showed abundant and significant differentially expressed unigenes (DEGs) (more than 40%) in colonizing the initial invasion stage and in the necrotrophic stage. The monogermtubi strain induced less than 10% of DEGs in the initial invasion stage but which abruptly increased to more than 80% DEGs in the necrotrophic stage. Both strains induced the least DEGs in the biotrophic stage compared to the initial invasion and necrotrophic stages. The orthologs of the effector genes Ecp6, PemG1, XEG1, ACE1, and Mg3LysM were exclusively induced by one of the two formae speciales depending on the infection stages. Some unigenes homologous to carbohydrate lytic enzyme genes, especially pectate lyases, were notably induced with multigermtubi forma specialis infection but not expressed in the monogermtubi forma specialis at an earlier infection stage. The extraordinary differences in the functional genome level between the two formae speciales of M. brunnea could be fundamental to exploring their host specificity determinant and evolution. This study also firstly provided the fungal transcriptome of the monogermtubi forma specialis for M. brunnea.

Epstein-Barr Virus Infection and Increased Sporadic Breast Carcinoma Risk: A Meta-Analysis.

OBJECTIVE: An association of Epstein-Barr virus (EBV) infection with breast carcinoma (BC) risk has so far been disputed in the literature. Therefore, we performed a meta-analysis to clarify this relationship. MATERIALS AND METHODS: An electronic database search for eligible case-control studies was performed using PubMed, Embase, Web of Science, the Cochrane Library, CNKI, and Wanfang Data until May 17, 2018. The pooled OR and 95% CI were used to estimate the relationship between EBV infection and BC risk using a fixed or random-effects model depending on heterogeneity. Subgroup analysis and meta-regression were used to explore the heterogeneity. Publication bias was assessed using Egger's and Harbord's tests. RESULTS: A total of 16 studies with 1,279 patients and 814 controls were reviewed based on our inclusion and exclusion criteria. Compared with the control group, EBV infection had a significant association with BC risk (OR 4.75, 95% CI 2.53-8.92, p < 0.01) with significant heterogeneity observed (I2 = 65.3%). The subgroup analysis revealed that region and tissue type might explain potential sources of heterogeneity. The sensitivity analyses yielded stable results. No significant publication bias was observed. CONCLUSION: The current results suggest that EBV infection is significantly associated with increased risk of BC.