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Background: Studies have shown that mitochondrial function and macrophages may play a role in the development of idiopathic pulmonary fibrosis (IPF). However, the understanding of the interactions and specific mechanisms between mitochondrial function and macrophages in pulmonary fibrosis is still very limited. Methods: To construct a prognostic model for IPF based on Macrophage- related genes (MaRGs) and Mitochondria-related genes (MitoRGs), differential analysis was performed to achieve differentially expressed genes (DEGs) between IPF and Control groups in the GSE28042 dataset. Then, MitoRGs, MaRGs and DEGs were overlapped to screen out the signature genes. The univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) algorithm were implemented to achieve key genes. Furthermore, the independent prognostic analysis was employed. The ingenuity pathway analysis (IPA) was employed to further understand the molecular mechanisms of key genes.Next, the immune infiltration analysis was implemented to identify differential immune cells between two risk subgroups. Results: There were 4791 DEGs between IPF and Control groups. Furthermore, 26 signature genes were achieved by the intersection processing. Three key genes including ALDH2, MCL1, and BCL2A1 were achieved, and the risk model based on the key genes was created. In addition, a nomogram for survival forecasting of IPF patients was created based on riskScore, Age, and Gender, and we found that key genes were associated with classical pathways including 'Apoptosis Signaling', 'PI3K/AKT Signaling', and so on. Next, two differential immune cells including Monocytes and CD8 T cells were identified between two risk subgroups. Moreover, we found that MIR29B2CHG and hsa-mir-1-3p could regulate the expression of ALDH2. Conclusion: We achieved 3 key genes including ALDH2, MCL1,, and BCL2A1 associated with IPF, providing a new theoretical basis for clinical treatment of IPF. [ABSTRACT FROM AUTHOR]

Background: Probiotics are a potentially effective therapy for inflammatory bowel disease (IBD); IBD is linked to impaired gut microbiota and intestinal immunity. However, the utilization of an antibiotic cocktail (Abx) prior to the probiotic intervention remains controversial. This study aims to identify the effect of Abx pretreatment from dextran sulfate sodium (DSS)-induced colitis and to evaluate whether Abx pretreatment has an enhanced effect on the protection of Clostridium butyricum Miyairi588 (CBM) from colitis. Results: The inflammation, dysbiosis, and dysfunction of gut microbiota as well as T cell response were both enhanced by Abx pretreatment. Additionally, CBM significantly alleviated the DSS-induced colitis and impaired gut epithelial barrier, and Abx pretreatment could enhance these protective effects. Furthermore, CBM increased the benefit bacteria abundance and short-chain fatty acids (SCFAs) level with Abx pretreatment. CBM intervention after Abx pretreatment regulated the imbalance of cytokines and transcription factors, which corresponded to lower infiltration of Th1 and Th17 cells, and increased Th2 cells. Conclusions: Abx pretreatment reinforced the function of CBM in ameliorating inflammation and barrier damage by increasing beneficial taxa, eliminating pathogens, and inducing a protective Th2 cell response. This study reveals a link between Abx pretreatment, microbiota, and immune response changes in colitis, which provides a reference for the further application of Abx pretreatment before microbiota-based intervention. [ABSTRACT FROM AUTHOR]

Chinese Materia Medica Resources (CMMRs) are crucial for developing the tradition and industry of traditional Chinese medicine. Given the increasing demand for CMMRs, an accurate and effective understanding of CMMRs is urgently needed. Chinese medicinal plants (CMPs) are the most important sources of CMMRs. Traditional methods of investigating medicinal plant resources have limitations, including severe subjectivity and poor timeliness, which make it difficult to meet the demand for real-time monitoring of large-scale medicinal plant resources. In recent years, remote sensing technology has become an important means of obtaining information on medicinal plants, and the application of this technology has made up for the shortcomings of traditional methods. This paper first discusses the development of investigation methods of CMMRs; points out the importance of remote sensing technology in the application of spatial distribution and information identification and extraction of Chinese medicinal plant resources (CMPRs); analyzes the characteristics of CMPs in different planting patterns, different habitats, and different regions from the perspective of remote sensing information extraction; and explores the selection of suitable data sources, providing a reference for medicinal plant identification and information extraction. Secondly, according to the existing classification and identification methods, previous studies are summarized from the perspectives of classification scales, classification features, and classification accuracy, and the advantages and disadvantages of the commonly used remote sensing classification methods in the investigation of CMPRs are summarized and compared. Finally, the development trend of remote sensing technology in the identification and information extraction of CMPs is examined, and the key technical problems to be solved in the identification and classification of CMPs and the extraction of area information are summarized so as to provide technical support and experience references for the application of remote sensing in the investigation of CMPRs. [ABSTRACT FROM AUTHOR]

The heterogeneity of neuroblastoma directly affects the prognosis of patients. Individualization of patient treatment to improve prognosis is a clinical challenge at this stage and the aim of this study is to characterize different patient populations. To achieve this, immune-related cell cycle genes, identified in the GSE45547 dataset using WGCNA, were used to classify cases from multiple datasets (GSE45547, GSE49710, GSE73517, GES120559, E-MTAB-8248, and TARGET) into subgroups by consensus clustering. ESTIMATES, CIBERSORT and ssGSEA were used to assess the immune status of the patients. And a 7-gene risk model was constructed based on differentially expressed genes between subtypes using randomForestSRC and LASSO. Enrichment analysis was used to demonstrate the biological characteristics between different groups. Key genes were screened using randomForest to construct neural network and validated. Finally, drug sensitivity was assessed in the GSCA and CellMiner databases. We classified the 1811 patients into two subtypes based on immune-related cell cycle genes. The two subtypes (Cluster1 and Cluster2) exhibited distinct clinical features, immune levels, chromosomal instability and prognosis. The same significant differences were demonstrated between the high-risk and low-risk groups. Through our analysis, we identified neuroblastoma subtypes with unique characteristics and established risk models which will improve our understanding of neuroblastoma heterogeneity. [ABSTRACT FROM AUTHOR]

Crop-distribution information constitutes the premise of precise management for crop cultivation. Euclidean distance and spectral angle mapper algorithms (ED and SAM) mostly use the spectral similarity and difference metric (SSDM) to determine the spectral variance associated with the spatial location for crop distribution acquisition. These methods are relatively insensitive to spectral shape or amplitude variation and must reconstruct a reference curve representing the entire class, possibly resulting in notable indeterminacy in the ultimate results. Few studies utilize these methods to compute the spectral variance associated with time and to define a new index for crop identification—namely, the spectral variance at key stages (SVKS)—even though this temporal spectral characteristic could be helpful for crop identification. To integrate the advantages of sensibility and avoid reconstructing the reference curve, an object self-reference combined algorithm comprising ED and SAM (CES) was proposed to compute SVKS. To objectively validate the crop-identification capability of SVKS-CES (SVKS computed via CES), SVKS-ED (SVKS computed via ED), SVKS-SAM (SVKS computed via SAM), and five spectral index (SI) types were selected for comparison in an example of maize identification. The results indicated that SVKS-CES ranges can characterize greater interclass spectral separability and attained better identification accuracy compared to other identification indexes. In particular, SVKS-CES2 provided the greatest interclass spectral separability and the best PA (92.73%), UA (100.00%), and OA (98.30%) in maize identification. Compared to the performance of the SI, SVKS attained greater interclass spectral separability, but more non-maize fields were incorrectly identified as maize fields via SVKS usage. Owning to the accuracy-improvement capability of SVKS-CES, the omission and commission errors were obviously reduced via the combined utilization of SVKS-CES and SI. The findings suggest that SVKS-CES application is expected to further spread in crop identification. [ABSTRACT FROM AUTHOR]

Background: Enterococcus raffinosus is one of the Enterococcus species that often cause nosocomial infections. To date, only one E. raffinosus genome has been completely assembled, and the genomic features have not been characterized. Here, we report the complete genome sequence of the strain CX012922, isolated from the feces of a Crohn's disease patient, and perform a comparative genome analysis to the relevant Enterococcus spp. strains in silico. Results: De novo assembly of the sequencing reads of the strain CX012922 generated a circular genome of 2.83 Mb and a circular megaplasmid of 0.98 Mb. Phylogenomic analysis revealed that the strain CX012922 belonged to the E. raffinosus species. By comparative genome analysis, we found that some strains previously identified as E. raffinosus or E. gilvus should be reclassified as novel species. Genome islands (GIs), virulence factors, and antibiotic genes were found in both the genome and the megaplasmid, although pathogenic genes were mainly encoded in the genome. A large proportion of the genes encoded in the megaplasmid were involved in substrate utilization, such as raffinose metabolism. Giant megaplasmids (~1 Mb) equipped with toxin-antitoxin (TA) systems generally formed symbiosis relationships with the genome of E. raffinosus strains. Conclusions: Enterococcus spp. have a higher species-level diversity than is currently appreciated. The pathogenicity of E. raffinosus is mainly determined by the genome-encoded virulence factors, while the megaplasmid broadens the gene function pool. The symbiosis between the genome and the megaplasmids endows E. raffinosus with large genomic sizes as well as versatile gene functions, especially for their colonization, adaptation, virulence, and pathogenesis in the human gut. [ABSTRACT FROM AUTHOR]

An increasing number of studies have shown that Faecalibacterium prausnitzii (F. prausnitzii) is a promising anti-inflammatory bacterium that colonizes in the gut and that gut microbiota dysbiosis plays an important role in the pathogenesis of inflammatory bowel disease (IBD). In this study, we report the gut microbiota profile of 2,4,6-trinitrobenzenesulfonic acid (TNBS)-induced colitis mice treated with F. prausnitzii and its supernatant on the basis of high-throughput sequencing. We interestingly found that both F. prausnitzii and its metabolites exerted protective effects against colitis in mice, which ameliorated gut dysbiosis, with an increase in bacterial diversity and the abundance of short-chain fatty acid (SCFA)-producing bacteria and a decrease in serum TNF-α and the abundance of Proteinbacteria, Acidobacteria, and Bacteroidetes. These findings will provide further evidence of the anti-inflammatory effect of F. prausnitzii, which presents therapeutic potential for IBD treatment. [ABSTRACT FROM AUTHOR]

Acquired immune deficiency syndrome, caused by the human immunodeficiency virus (HIV), has been associated with intestinal dysbiosis, which includes an increase in the number of mucosa-associated pathobionts. In the present study, the intestinal mucosal microbiota patterns of HIV-infected patients were compared with those of healthy individuals in a population from Guangzhou, China. The gut microbiota of intestinal mucosal samples from 12 patients with HIV (transmission routes included sex and intravenous drug abuse) was compared with that of 12 healthy age- and sex-matched controls. Gut microbial communities were profiled via sequencing of the bacterial 16S ribosomal RNA genes. Dysbiosis in HIV-infected individuals was characterized by decreased α-diversity, decreased levels of Firmicutes and increased levels of Proteobacteria. Furthermore, low mean counts of Lachnoclostridium, Roseburia, Thauera, Dorea and Roseburia inulinivorans, and high mean counts of Halomonas and Shewanella bacteria, were indicated to be HIV-associated mucosal bacterial alterations. The relative abundance of Fusobacterium and Lachnoclostridium was significantly decreased, while that of Halomonas and Shewanella was significantly increased in patients with sexually transmitted HIV-infection compared with healthy controls. Alterations of the gut microbiota during HIV infection were also indicated to be associated with the route of HIV transmission. Certain bacteria may be potential biomarkers for HIV infection in patients from Guangzhou, China. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to investigate the underlying mechanisms of diabetic retinopathy (DR) development. Methods: Real-Time qPCR was used to detect Casein kinase 2 interacting protein-1 (CKIP-1) and Nuclear factor E2-related factor 2 (Nrf2) mRNA levels. Western Blot was employed to detect protein levels. Malondialdehyde (MDA) assay kit, superoxide dismutase (SOD) kit and glutathione peroxidase (GSH-Px) kit were used to evaluate oxidative stress in high-glucose treated human retinal endothelial cells (HRECs). Calcein-AM/propidium iodide (PI) double stain kit was employed to detect cell apoptosis. Enzyme-linked ImmunoSorbent Assay (ELISA) was used to detect inflammation associated cytokines secretion. Co-immunoprecipitation (CO-IP) was performed to investigate the interactions between CKIP-1 and Nrf2. Luciferase reporter gene system was used to detect the transcriptional activity of Nrf2. Results: CKIP-1 was significantly downregulated in either DR tissues or high-glucose treated HRECs comparing to the Control groups. Besides, high-glucose (25 mM) inhibited HRECs viability and induced oxidative stress, inflammation associated cytokines (TNF-α, IL-6 and IL-1β) secretion and cell apoptosis, which were all reversed by synergistically overexpressing CKIP-1 and aggravated by knocking down CKIP-1. Of note, we found that overexpressed CKIP-1 activated Nrf2/ARE signaling pathway and increased its downstream targets including HO-1, NQO-1, γGCS and SOD in high-glucose treated HRECs. Further results also showed that CKIP-1 regulated cell viability, oxidative stress, inflammation and apoptosis in high-glucose treated HRECs by activating Nrf2/ARE signaling pathway. Conclusion: We concluded that overexpressed CKIP-1 alleviated DR progression by activating Nrf2/ARE signaling pathway. [ABSTRACT FROM AUTHOR]