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TFL1-, AP1- and LFY-like genes are known to be key regulators of inflorescence development. However, it remains to be tested whether the evolutionary modifications of inflorescence morphology result from shifts in their expression patterns. We compared the spatiotemporal expression patterns of CorTFL1, CorAP1 and CorLFY in six closely related Cornus species that display four types of closed inflorescence morphology using quantitative real-time polymerase chain reaction (qRT-PCR) and RNA in situ hybridization. Character mapping on the phylogeny was conducted to identify evolutionary changes and to assess the correlation between changes in gene expression and inflorescence morphology. Results demonstrated variation of gene expression patterns among species and a strong correlation between CorTFL1 expression and the branch index of the inflorescence type. Evolutionary changes in CorTFL1 and CorAP1 expression co-occurred on the phylogeny with the morphological changes underpinning inflorescence divergence. The study found a clear correlation between the expression patterns of CorTFL1 and CorAP1 and the inflorescence architecture in a natural system displaying closed inflorescences. The results suggest a role for the alteration in CorTFL1 and CorAP1 expression during the evolutionary modification of inflorescences in Cornus. We propose that a TFL1-like and AP1-like gene-based model may explain variation of closed inflorescences in Cornus and other lineages.

A sequencing batch biofilm reactor (SBBR) filled with polyurethane (PU) was operated in low dissolved oxygen (DO) (0.1–0.9 mg/L) at three different carbon to nitrogen ratios (C/N ratios) (C/N = 1.8:1, 5.0:1 and 10.5:1) with focus on reactor performance and microbial community composition of nitrifying and denitrifying bacteria. Meanwhile, the ammonium, nitrite, nitrate, pH and dissolved oxygen were analyzed to monitor the process of nitrification-denitrification. The reactor had a steady ammonium removal in spite of a large variation in the initial ammonium loading (the ammonium removal efficiency was 87.2% at C/N 1.8:1, 92.9% at C/N 5.0:1, 88.4% at C/N 10.5:1). However, the total nitrogen (TN) removal was strongly affected by the initial organic loading (the TN removal efficiency was 55.2% at C/N 1.8:1, 74.3% at C/N 5.0:1, 79.0% at C/N 10.5:1). It was indicated that higher organic load promoted denitrification. The real-time quantitative polymerase chain reaction (real-time qPCR) analysis shown that Beta-proteobacteria occupied over 35% numerically. As for the Nitrosomonas sp., Nitrosospira sp. and Nitrospira sp. gene copy numbers, their abundance was generally in the order of magnitude of 1010. The Nitrosospira sp. fluctuated significantly in the range of 3.1–9.8% at different C/N ratios, while the Nitrosomonas sp. just changed a little.

Purpose For an alkaline–saline region in Northwest China, we examined the responses of soil microbial communities to flue gas desulfurization gypsum by-products (FGDB), a new ameliorant for alkaline–saline soils. In 2009 and 2010, we collected soils from 0–20 cm and 20–40 cm depths along an experimental FGDB gradient (0, 0.74, 1.49, 2.25, and 3.00 kg FGDB m −2 ). Materials and methods As a measure of microbial community composition and biomass, we analyzed phospholipid fatty acids (PLFAs). We used real-time quantitative polymerase chain reaction (qPCR) to measure abundance of bacterial 16 S rRNA copy numbers. Additionally, physicochemical soil parameters were measured by common laboratory methods. Results and discussion Microbial community composition differed along the FGDB gradient; however, the microbial parameters did not follow a linear response. We found that, in 2009, total PLFA concentrations, and concentrations of total bacterial and Gram-negative bacterial PLFAs were slightly higher at intermediate FGDB concentrations. In 2010, total PLFA concentrations, and concentrations of total bacterial, Gram-positive bacterial, Gram-negative bacterial, and fungal PLFAs as well as the fungal:bacterial PLFA ratio were highest at 1.49 kg FGDB m −2 and 3.00 kg FGDB m −2 . PLFA concentrations often differed between 2009 and 2010; however, the patterns varied across the gradient and across microbial groups. For both years, PLFA concentrations were generally higher at 0–20 cm depth than at 20–40 cm depth. Similar results were obtained for the 16 S rRNA copy numbers of bacteria at 0–20 cm depth. FGDB addition resulted in an increase in soil Ca 2+ and NO 3 − –N and a decrease in pH and electrical conductivity (EC). Shifts in PLFA-based microbial community composition and biomass could partly be explained by pH, soil organic carbon, total nitrogen (TN), soil moisture, EC, inorganic nitrogen, C/N, and Ca 2+ . Indirect effects via shifts in abiotic soil properties, therefore, seem to be an important pathway through which FGDB affect soil microbial communities. Conclusions Our results demonstrate that addition of FGDB leads to significant changes in soil physicochemical and microbial parameters. As such, addition of FGDB can have large impacts on the functioning of soil ecosystems, such as carbon and nitrogen cycling processes.

The European eel, Anguilla anguilla, is classified as critically endangered by the IUCN. To protect what remains of the European eel population, accurate monitoring methods for this species are important. Environmental DNA (eDNA) techniques are gaining popularity for ecological monitoring of aquatic organisms because they are sensitive and noninvasive. This study directly compared catch data from a standardized fyke‐net fishing survey with a single species A. anguilla eDNA survey in five freshwater lakes in Ireland. The eDNA was recovered by the filtration of water samples and amplified by quantitative real‐time polymerase chain reaction (qPCR). European eel eDNA was reliably determined in 83% (70/84) of surface water samples collected from lakes classified as having high, medium, and low eel populations. In addition, there was a positive association between the eDNA concentrations recovered and the eel population classification with lower eDNA concentrations in lakes classified as low eel population lakes. Similar amounts of A. anguilla eDNA were detected in water samples collected from open water and shore‐side, suggesting shore sampling is an adequate method for eel detection. Together, the results demonstrate that eDNA sampling is more sensitive for detecting eel presence in low eel population environments than standard survey methods and may be a useful noninvasive tool for monitoring A. anguilla species distribution. This study directly compared catch data from a fyke‐net fishing survey with an Anguilla anguilla eDNA survey in five freshwater lakes in Ireland. Eel eDNA was reliably determined in 83% (70/84) of surface water samples collected. The results demonstrate that eDNA sampling is more sensitive for detecting eel presence in low eel population environments than standard survey methods.

A high frequency of MAGE‐CT (cancer testis) antigens are expressed in Multiple Myeloma (MM) patients; however, in other plasma cell dyscrasias, their potential function remains unclear. We measured the expression of MAGE‐CT genes (MAGE‐C1/CT7, MAGE‐A3, MAGE‐C2/CT10) in 105 newly diagnosed amyloid light‐chain (AL) amyloidosis patients between June 2013 and January 2018 at Peking University People's Hospital using real‐time quantitative polymerase chain reaction. In the newly diagnosed AL patients, the positive expression rates of patients with MAGE‐C1/CT7, MAGE‐C2/CT10 and MAGE‐A3 were 83.8% (88/105), 56.71% (38/67) and 22.0% (13/59) respectively. There was no significant correlation between organ propensity and MAGE‐CT gene expression. Changes in the MAGE‐C1/CT7 levels were consistent with a therapeutic effect. The expression levels of MAGE‐C1/CT7, MAGE‐C2/CT10 and MAGE‐A3 provide potentially effective clinical indicators for auxiliary diagnoses and monitoring treatment efficacy in AL amyloidosis patients.

Environmental DNA (eDNA) is revolutionizing species monitoring in nature. At the heart of any eDNA approach is the reliance upon sufficient DNA sequence information to satisfy the demands of eDNA assay specificity and sensitivity. The most common source of this information has been restricted to short barcoding regions of the mitochondrial genome (mitogenome) and marker genes. The use of these limited regions for assay design has often resulted in substantial trade‐offs in assay performance. With increased accessibility of full mitogenome assemblies, the potential for designing more robust eDNA assays is considerably enhanced. However, this also poses a new challenge to effectively identify suitable regions for assay design using considerably larger sequences. We present unikseq, a utility that uses words of length k (k‐mers) to identify unique regions in a reference sequence relative to tolerated (ingroup) and not‐tolerated (outgroup or non‐target) sequence sets, quickly and with low memory that can yield highly specific assays. We illustrate its application within an assay development workflow through use‐case examples for the design and validation of four quantitative real‐time polymerase chain reaction (qPCR)‐based assays selective for American bullfrog (Rana [Lithobates] catesbeiana), Burbot (Lota lota), Lake trout (Salvelinus namaycush), and Quillback rockfish (Sebastes maliger). The chosen target species vary in range, habitat, and degree of relatedness to their sympatric species that, consequently, impact eDNA assay design difficulty. We demonstrate the effectiveness of unikseq through assay validation and characterization using DNA from voucher specimens, synthetic DNA, and, where possible, field samples, to verify the specificity and sensitivity of the newly designed assays. By facilitating whole mitogenome sequence comparison, the creation of high‐performing eDNA assays is substantially enhanced. Having several adjustable parameters for specifying user requirements within unikseq, this approach can facilitate the identification of suitable regions for a broad range of applications requiring nucleotide sequence comparisons. Unikseq is a scalable freely available tool for effectively identifying suitable regions for eDNA assay design using large DNA sequences such as whole mitogenomes. It parses sets of full mitogenome sequences in an unbiased fashion to highlight regions of the target taxon mitogenome that are unique in comparison to non‐target taxa for creating highly specific assays. Having several adjustable parameters for specifying user requirements within unikseq, this approach can also be applied for the identification of metabarcoding primer sets and other eDNA applications.

Long non-coding RNAs (lncRNAs) play a key role in craniocerebral disease, although their expression profiles in human traumatic brain injury are still unclear. In this regard, in this study, we examined brain injury tissue from three patients of the 101st Hospital of the People's Liberation Army, China (specifically, a 36-year-old male, a 52-year-old female, and a 49-year-old female), who were diagnosed with traumatic brain injury and underwent brain contusion removal surgery. Tissue surrounding the brain contusion in the three patients was used as control tissue to observe expression characteristics of lncRNAs and mRNAs in human traumatic brain injury tissue. Volcano plot filtering identified 99 lncRNAs and 63 mRNAs differentially expressed in frontotemporal tissue of the two groups (P < 0.05, fold change > 1.2). Microarray analysis showed that 43 lncRNAs were up-regulated and 56 lncRNAs were down-regulated. Meanwhile, 59 mRNAs were up-regulated and 4 mRNAs were down-regulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed 27 signaling pathways associated with target genes and, in particular, legionellosis and influenza A signaling pathways. Subsequently, a lncRNA-gene network was generated, which showed an absolute correlation coefficient value > 0.99 for 12 lncRNA-mRNA pairs. Finally, quantitative real-time polymerase chain reaction confirmed different expression of the five most up-regulated mRNAs within the two groups, which was consistent with the microarray results. In summary, our results show that expression profiles of mRNAs and lncRNAs are significantly different between human traumatic brain injury tissue and surrounding tissue, providing novel insight regarding lncRNAs' involvement in human traumatic brain injury. All participants provided informed consent. This research was registered in the Chinese Clinical Trial Registry (registration number: ChiCTR-TCC-13004002) and the protocol version number is 1.0.

Background Osteoarthritis (OA) is a common joint disease, and existing drugs cannot cure OA, so there is an urgent need to identify new targets. Mitophagy plays an important role in OA; however, the role of mitophagy in the OA immune system is not yet clear. Methods In this study, differential analysis and enrichment analysis were used to identify mitophagy‐related genes (MRGs) with differential expression in OA and the functional pathways involved in OA. Subsequently, two machine learning methods, RF and LASSO, were used to screen MRGs with diagnostic value and construct nomograms. At the same time, the relationship between mitophagy and OA immune response was explored by immunoinfiltration analysis. Results Forty‐three differentially MRGs were identified in OA, of which six MRGs (GABARAPL2, PARL, GABARAPL1, JUN, RRAS, and SNX7) were associated with the diagnosis of OA. The ROC analysis results show that these 6 MRGs have high predictive accuracy in the diagnosis of OA. In immune infiltration analysis, we found that the abundance of significantly different immune cells in OA was mostly upregulated. In addition, the expression of diagnostic‐related MRGs is correlated with changes in the abundance of immune cells in OA. Conclusion This study demonstrates that six MRGs can be used as diagnostic biomarkers. The expression of diagnostic‐related MRGs is correlated with changes in the abundance of immune cells in OA. At the same time, mitophagy may affect the immune microenvironment of OA by regulating immune cells, ultimately leading to the progression of OA. Differential analysis of OA‐related datasets identified 43 mitophagy‐related genes (MRGs) differentially expressed in OA. Subsequently, six MRGS (GABARAPL2, PARL, GABARAPL1, JUN, RRAS and SNX7) associated with OA diagnosis were identified using RF and LASSO regression analysis. ROC analysis showed that the six MRGS had high predictive accuracy for the diagnosis of OA. Given the high predictive accuracy of the six diagnosis‐related MRGS, the nomogram model we constructed performed similarly to the ideal model in clinical practice. In the immune infiltration analysis, we found that the significantly different immune cell abundances were mostly upregulated in OA. In addition, there is a correlation between the expression of diagnosis‐related MRGs and the changes in the abundance of immune cells in OA, suggesting that mitophagia may affect the immune microenvironment of OA by regulating immune cells, ultimately leading to the progression of OA. In addition, the results of qPCR experiments showed significant differences in the expression of six MRGs between OA and normal tissues, consistent with the results of bioinformatics analysis. The results of this study may provide new insights into the role of mitophagy in OA and provide new targets for the diagnosis and treatment of OA.

This study aimed to research the roles of miR-139, miR-221, miR-200c, miR-145, miR-223, miR-424, and miR-377 in endoplasmic reticulum stress (ERS), oxidative stress (OS), fibrosis, and apoptosis processes in chronic pancreatitis (CP) rat model. Fourteen rats were randomized into 2 groups (Group 1, sham group (n=7) and Group 2, CP group (n=7)). TGF-beta and malondialdehyde concentrations were measured in rat blood samples. qRT-PCR was used to investigate the expression levels of 7 miRNAs in the pancreas tissues. The correlations of mRNA undergoing significant changes with inflammation (TNF-α, IL-6), ERS ( ), apoptosis ( ), OS ( ), and fibrosis ( ) were investigated The biochemical results and histopathological scores in Group 1 were statistically significantly high compared with Group 2 ( <0.5). Expression levels of seven miRNAs (miR-200c, miR-145, miR-223, miR-424) were significantly higher, while miR-139 was significantly lower in CP. In our study, we found that miR-200c, miR-145, and miR-139 may contribute to CP progression and cellular processes based on the correlation between ERS, OS, apoptosis, and inflammation with miRNA expression levels. miR-200c, miR-145, miR-139, miR-223, and miR-424 play roles in the CP model. They may be used as candidate biomarkers for the CP process.

Prostate cancer (PCa) exhibits epidemiological and molecular heterogeneity. Despite extensive studies of its phenotypic and genetic properties in Western populations, its molecular basis is not clear in Chinese patients. To determine critical molecular characteristics and explore correlations between genomic markers and clinical parameters in Chinese populations, we applied an integrative genetic/transcriptomic assay that combines targeted next-generation sequencing and quantitative real-time PCR (qRT-PCR) on samples from 46 Chinese patients with PCa. Lysine (K)-specific methyltransferase 2D (KMT2D), zinc finger homeobox 3 (ZFHX3), A-kinase anchoring protein 9 (AKAP9), and GLI family zinc finger 1 (GLI1) were frequently mutated in our cohort. Moreover, a clinicopathological analysis showed that RB transcriptional corepressor 1 (RB1) deletion was common in patients with a high risk of disease progression. Remarkably, four genomic events, MYC proto-oncogene (MYC) amplification, RB1 deletion, APC regulator of WNT signaling pathway (APC) mutation or deletion, and cyclin-dependent kinase 12 (CDK12) mutation, were correlated with poor disease-free survival. In addition, a close link between KMT2D expression and the androgen receptor (AR) signaling pathway was observed both in our cohort and in The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) data. In summary, our results demonstrate the feasibility and benefits of integrative molecular characterization of PCa samples in disease pathology research and personalized medicine.