Incorporating network diffusion and peak location information for better single-cell ATAC-seq data analysis.

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) data provided new insights into the understanding of epigenetic heterogeneity and transcriptional regulation. With the increasing abundance of dataset resources, there is an urgent need to extract more useful information through high-quality data analysis methods specifically designed for scATAC-seq. However, analyzing scATAC-seq data poses challenges due to its near binarization, high sparsity and ultra-high dimensionality properties. Here, we proposed a novel network diffusion-based computational method to comprehensively analyze scATAC-seq data, named Single-Cell ATAC-seq Analysis via Network Refinement with Peaks Location Information (SCARP). SCARP formulates the Network Refinement diffusion method under the graph theory framework to aggregate information from different network orders, effectively compensating for missing signals in the scATAC-seq data. By incorporating distance information between adjacent peaks on the genome, SCARP also contributes to depicting the co-accessibility of peaks. These two innovations empower SCARP to obtain lower-dimensional representations for both cells and peaks more effectively. We have demonstrated through sufficient experiments that SCARP facilitated superior analyses of scATAC-seq data. Specifically, SCARP exhibited outstanding cell clustering performance, enabling better elucidation of cell heterogeneity and the discovery of new biologically significant cell subpopulations. Additionally, SCARP was also instrumental in portraying co-accessibility relationships of accessible regions and providing new insight into transcriptional regulation. Consequently, SCARP identified genes that were involved in key Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to diseases and predicted reliable cis-regulatory interactions. To sum up, our studies suggested that SCARP is a promising tool to comprehensively analyze the scATAC-seq data.

Reverse network diffusion to remove indirect noise for better inference of gene regulatory networks.

MOTIVATION: Gene regulatory networks (GRNs) are vital tools for delineating regulatory relationships between transcription factors and their target genes. The boom in computational biology and various biotechnologies has made inferring GRNs from multi-omics data a hot topic. However, when networks are constructed from gene expression data, they often suffer from false-positive problem due to the transitive effects of correlation. The presence of spurious noise edges obscures the real gene interactions, which makes downstream analyses, such as detecting gene function modules and predicting disease-related genes, difficult and inefficient. Therefore, there is an urgent and compelling need to develop network denoising methods to improve the accuracy of GRN inference. RESULTS: In this study, we proposed a novel network denoising method named REverse Network Diffusion On Random walks (RENDOR). RENDOR is designed to enhance the accuracy of GRNs afflicted by indirect effects. RENDOR takes noisy networks as input, models higher-order indirect interactions between genes by transitive closure, eliminates false-positive effects using the inverse network diffusion method, and produces refined networks as output. We conducted a comparative assessment of GRN inference accuracy before and after denoising on simulated networks and real GRNs. Our results emphasized that the network derived from RENDOR more accurately and effectively captures gene interactions. This study demonstrates the significance of removing network indirect noise and highlights the effectiveness of the proposed method in enhancing the signal-to-noise ratio of noisy networks. AVAILABILITY AND IMPLEMENTATION: The R package RENDOR is provided at https://github.com/Wu-Lab/RENDOR and other source code and data are available at https://github.com/Wu-Lab/RENDOR-reproduce.

The non-cell-autonomous function of ID1 promotes AML progression via ANGPTL7 from the microenvironment.

The bone marrow microenvironment (BMM) can regulate leukemia stem cells (LSCs) via secreted factors. Increasing evidence suggests that dissecting the mechanisms by which the BMM maintains LSCs may lead to the development of effective therapies for the eradication of leukemia. Inhibitor of DNA binding 1 (ID1), a key transcriptional regulator in LSCs, previously identified by us, controls cytokine production in the BMM, but the role of ID1 in acute myeloid leukemia (AML) BMM remains obscure. Here, we report that ID1 is highly expressed in the BMM of patients with AML, especially in BM mesenchymal stem cells, and that the high expression of ID1 in the AML BMM is induced by BMP6, secreted from AML cells. Knocking out ID1 in mesenchymal cells significantly suppresses the proliferation of cocultured AML cells. Loss of Id1 in the BMM results in impaired AML progression in AML mouse models. Mechanistically, we found that Id1 deficiency significantly reduces SP1 protein levels in mesenchymal cells cocultured with AML cells. Using ID1-interactome analysis, we found that ID1 interacts with RNF4, an E3 ubiquitin ligase, and causes a decrease in SP1 ubiquitination. Disrupting the ID1-RNF4 interaction via truncation in mesenchymal cells significantly reduces SP1 protein levels and delays AML cell proliferation. We identify that the target of Sp1, Angptl7, is the primary differentially expression protein factor in Id1-deficient BM supernatant fluid to regulate AML progression in mice. Our study highlights the critical role of ID1 in the AML BMM and aids the development of therapeutic strategies for AML.

Interaction-based transcriptome analysis via differential network inference.

Gene-based transcriptome analysis, such as differential expression analysis, can identify the key factors causing disease production, cell differentiation and other biological processes. However, this is not enough because basic life activities are mainly driven by the interactions between genes. Although there have been already many differential network inference methods for identifying the differential gene interactions, currently, most studies still only use the information of nodes in the network for downstream analyses. To investigate the insight into differential gene interactions, we should perform interaction-based transcriptome analysis (IBTA) instead of gene-based analysis after obtaining the differential networks. In this paper, we illustrated a workflow of IBTA by developing a Co-hub Differential Network inference (CDN) algorithm, and a novel interaction-based metric, pivot APC2. We confirmed the superior performance of CDN through simulation experiments compared with other popular differential network inference algorithms. Furthermore, three case studies are given using colorectal cancer, COVID-19 and triple-negative breast cancer datasets to demonstrate the ability of our interaction-based analytical process to uncover causative mechanisms.

Biologically informed machine learning modeling of immune cells to reveal physiological and pathological aging process.

The immune system undergoes progressive functional remodeling from neonatal stages to old age. Therefore, understanding how aging shapes immune cell function is vital for precise treatment of patients at different life stages. Here, we constructed the first transcriptomic atlas of immune cells encompassing human lifespan, ranging from newborns to supercentenarians, and comprehensively examined gene expression signatures involving cell signaling, metabolism, differentiation, and functions in all cell types to investigate immune aging changes. By comparing immune cell composition among different age groups, HLA highly expressing NK cells and CD83 positive B cells were identified with high percentages exclusively in the teenager (Tg) group, whereas unknown_T cells were exclusively enriched in the supercentenarian (Sc) group. Notably, we found that the biological age (BA) of pediatric COVID-19 patients with multisystem inflammatory syndrome accelerated aging according to their chronological age (CA). Besides, we proved that inflammatory shift- myeloid abundance and signature correlate with the progression of complications in Kawasaki disease (KD). The shift- myeloid signature was also found to be associated with KD treatment resistance, and effective therapies improve treatment outcomes by reducing this signaling. Finally, based on those age-related immune cell compositions, we developed a novel BA prediction model PHARE ( https://xiazlab.org/phare/ ), which can apply to both scRNA-seq and bulk RNA-seq data. Using this model, we found patients with coronary artery disease (CAD) also exhibit accelerated aging compared to healthy individuals. Overall, our study revealed changes in immune cell proportions and function associated with aging, both in health and disease, and provided a novel tool for successfully capturing features that accelerate or delay aging.

PathExpSurv: pathway expansion for explainable survival analysis and disease gene discovery.

BACKGROUND: In the field of biology and medicine, the interpretability and accuracy are both important when designing predictive models. The interpretability of many machine learning models such as neural networks is still a challenge. Recently, many researchers utilized prior information such as biological pathways to develop neural networks-based methods, so as to provide some insights and interpretability for the models. However, the prior biological knowledge may be incomplete and there still exists some unknown information to be explored. RESULTS: We proposed a novel method, named PathExpSurv, to gain an insight into the black-box model of neural network for cancer survival analysis. We demonstrated that PathExpSurv could not only incorporate the known prior information into the model, but also explore the unknown possible expansion to the existing pathways. We performed downstream analyses based on the expanded pathways and successfully identified some key genes associated with the diseases and original pathways. CONCLUSIONS: Our proposed PathExpSurv is a novel, effective and interpretable method for survival analysis. It has great utility and value in medical diagnosis and offers a promising framework for biological research.

Importance-Penalized Joint Graphical Lasso (IPJGL): differential network inference via GGMs.

MOTIVATION: Differential network inference is a fundamental and challenging problem to reveal gene interactions and regulation relationships under different conditions. Many algorithms have been developed for this problem; however, they do not consider the differences between the importance of genes, which may not fit the real-world situation. Different genes have different mutation probabilities, and the vital genes associated with basic life activities have less fault tolerance to mutation. Equally treating all genes may bias the results of differential network inference. Thus, it is necessary to consider the importance of genes in the models of differential network inference. RESULTS: Based on the Gaussian graphical model with adaptive gene importance regularization, we develop a novel Importance-Penalized Joint Graphical Lasso method (IPJGL) for differential network inference. The presented method is validated by the simulation experiments as well as the real datasets. Furthermore, to precisely evaluate the results of differential network inference, we propose a new metric named APC2 for the differential levels of gene pairs. We apply IPJGL to analyze the TCGA colorectal and breast cancer datasets and find some candidate cancer genes with significant survival analysis results, including SOST for colorectal cancer and RBBP8 for breast cancer. We also conduct further analysis based on the interactions in the Reactome database and confirm the utility of our method. AVAILABILITY AND IMPLEMENTATION: R source code of Importance-Penalized Joint Graphical Lasso is freely available at https://github.com/Wu-Lab/IPJGL. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

P38-DAPK1 axis regulated LC3-associated phagocytosis (LAP) of microglia in an in vitro subarachnoid hemorrhage model.

BACKGROUND: The phagocytosis and homeostasis of microglia play an important role in promoting blood clearance and improving prognosis after subarachnoid hemorrhage (SAH). LC3-assocaited phagocytosis (LAP) contributes to the microglial phagocytosis and homeostasis via autophagy-related components. With RNA-seq sequencing, we found potential signal pathways and genes which were important for the LAP of microglia. METHODS: We used an in vitro model of oxyhemoglobin exposure as SAH model in the study. RNA-seq sequencing was performed to seek critical signal pathways and genes in regulating LAP. Bioparticles were used to access the phagocytic ability of microglia. Western blot (WB), immunoprecipitation, quantitative polymerase chain reaction (qPCR) and immunofluorescence were performed to detect the expression change of LAP-related components and investigate the potential mechanisms. RESULTS: In vitro SAH model, there were increased inflammation and decreased phagocytosis in microglia. At the same time, we found that the LAP of microglia was inhibited in all stages. RNA-seq sequencing revealed the importance of P38 MAPK signal pathway and DAPK1 in regulating microglial LAP. P38 was found to regulate the expression of DAPK1, and P38-DAPK1 axis was identified to regulate the LAP and homeostasis of microglia after SAH. Finally, we found that P38-DAPK1 axis regulated expression of BECN1, which indicated the potential mechanism of P38-DAPK1 axis regulating microglial LAP. CONCLUSION: P38-DAPK1 axis regulated the LAP of microglia via BECN1, affecting the phagocytosis and homeostasis of microglia in vitro SAH model. Video Abstract.

Discovering cooperative biomarkers for heterogeneous complex disease diagnoses.

Biomarkers with high reproducibility and accurate prediction performance can contribute to comprehending the underlying pathogenesis of related complex diseases and further facilitate disease diagnosis and therapy. Techniques integrating gene expression profiles and biological networks for the identification of network-based disease biomarkers are receiving increasing interest. The biomarkers for heterogeneous diseases often exhibit strong cooperative effects, which implies that a set of genes may achieve more accurate outcome prediction than any single gene. In this study, we evaluated various biomarker identification methods that consider gene cooperative effects implicitly or explicitly, and proposed the gene cooperation network to explicitly model the cooperative effects of gene combinations. The gene cooperation network-enhanced method, named as MarkRank, achieves superior performance compared with traditional biomarker identification methods in both simulation studies and real data sets. The biomarkers identified by MarkRank not only have a better prediction accuracy but also have stronger topological relationships in the biological network and exhibit high specificity associated with the related diseases. Furthermore, the top genes identified by MarkRank involve crucial biological processes of related diseases and give a good prioritization for known disease genes. In conclusion, MarkRank suggests that explicit modeling of gene cooperative effects can greatly improve biomarker identification for complex diseases, especially for diseases with high heterogeneity.

Aucubin alleviates oxidative stress and inflammation via Nrf2-mediated signaling activity in experimental traumatic brain injury.

BACKGROUND: Aucubin (Au), an iridoid glycoside from natural plants, has antioxidative and anti-inflammatory bioactivities; however, its effects on a traumatic brain injury (TBI) model remain unknown. We explored the potential role of Au in an H2O2-induced oxidant damage in primary cortical neurons and weight-drop induced-TBI in a mouse model. METHODS: In vitro experiments, the various concentrations of Au (50 µg/ml, 100 µg/ml, or 200 µg/ml) were added in culture medium at 0 h and 6 h after neurons stimulated by H2O2 (100 µM). After exposed for 12 h, neurons were collected for western blot (WB), immunofluorescence, and M29,79-dichlorodihydrofluorescein diacetate (DCFH-DA) staining. In vivo experiments, Au (20 mg/kg or 40 mg/kg) was administrated intraperitoneally at 30 min, 12 h, 24 h, and 48 h after modeling. Brain water content, neurological deficits, and cognitive functions were measured at specific time, respectively. Cortical tissue around focal trauma was collected for WB, TdT-mediated dUTP Nick-End Labeling (TUNEL) staining, Nissl staining, quantitative real time polymerase chain reaction (q-PCR), immunofluorescence/immunohistochemistry, and enzyme linked immunosorbent assay (ELISA) at 72 h after TBI. RNA interference experiments were performed to determine the effects of nuclear factor erythroid-2 related factor 2 (Nrf2) on TBI mice with Au (40 mg/kg) treatment. Mice were intracerebroventricularly administrated with lentivirus at 72 h before TBI establishment. The cortex was obtained at 72 h after TBI and used for WB and q-PCR. RESULTS: Au enhanced the translocation of Nrf2 into the nucleus, activated antioxidant enzymes, suppressed excessive generation of reactive oxygen species (ROS), and reduced cell apoptosis both in vitro and vivo experiments. In the mice model of TBI, Au markedly attenuated brain edema, histological damages, and improved neurological and cognitive deficits. Au significantly suppressed high mobility group box 1 (HMGB1)-mediated aseptic inflammation. Nrf2 knockdown in TBI mice blunted the antioxidant and anti-inflammatory neuroprotective effects of the Au. CONCLUSIONS: Taken together, our data suggest that Au provides a neuroprotective effect in TBI mice model by inhibiting oxidative stress and inflammatory responses; the mechanisms involve triggering Nrf2-induced antioxidant system.

Peroxiredoxin 1/2 protects brain against H2O2-induced apoptosis after subarachnoid hemorrhage.

Recent studies suggest that peroxiredoxin1/2 (Prx1/2) may be involved in the pathophysiology of postischemic inflammatory responses in the brain. In this study, we assessed the distribution and function of Prx1/2 in mice after experimental subarachnoid hemorrhage (SAH). We investigated the distribution of Prx1/2 in the brains of mice both in vivo and in vitro using immunofluorescence staining. The expression of Prx1/2 after SAH was determined by Western blot. Adenanthin was used to inhibit Prx1/2 function, and Prx1/2 overexpression was achieved by injecting adeno-associated virus. Oxidative stress and neuronal apoptosis were assessed both in vivo and in vitro. The neurologic function, inflammatory response, and related cellular signals were analyzed. The results showed that Prx1 was mainly expressed in astrocytes, and Prx2 was abundant in neurons. The expression of Prx1/2 was elevated after SAH, and their expression levels peaked before proinflammatory cytokines. Inhibiting Prx1/2 promoted neuronal apoptosis by increasing the hydrogen peroxide (H2O2) levels via the apoptosis signal-regulating kinase 1/p38 pathway. By contrast, overexpression of Prx1/2 attenuated oxidative stress and neuronal apoptosis after SAH. Thus, early expression of Prx1/2 may protect the brain from oxidative damage after SAH and may provide a novel target for treating SAH.-Lu, Y., Zhang, X.-S., Zhou, X.-M., Gao, Y.-Y., Chen, C.-L., Liu, J.-P., Ye, Z.-N., Zhang, Z.-H., Wu, L.-Y., Li, W., Hang, C.-H. Peroxiredoxin 1/2 protects brain against H2O2-induced apoptosis after subarachnoid hemorrhage.

Inhibition of Elevated Hippocampal CD24 Reduces Neurogenesis in Mice With Traumatic Brain Injury.

In the adult rodents' brain, CD24 expression is restricted to immature neurons located in the neurogenesis areas. Our previous studies have confirmed that CD24 expression could be markedly elevated in the cerebral cortex after traumatic brain injury (TBI) both in humans and in mice. Although there is a close relationship between CD24 and neurogenesis, it remains unknown about the specific role of CD24 in neurogenesis areas after TBI. Here, the expression of CD24 was detected in the ipsilateral hippocampus by the Western blotting and real-time quantitative polymerase chain reaction. RNA interference was applied to investigate the effects of CD24 on post-traumatic neurogenesis. Brain sections were labeled with CD24 and doublecortin (DCX) via immunofluorescence. The Morris water maze test was used to assess cognitive functions. The results indicated that both mRNA and protein levels of CD24 were markedly elevated in the hippocampus after TBI. Meanwhile, TBI could cause a decrease of DCX-positive cells in the dentate gyrus of the hippocampus. Downregulation of CD24 significantly inhibited the phosphorylation of Src homology region 2-containing protein tyrosine phosphatase 2 in the ipsilateral hippocampus. Meanwhile, inhibition of CD24 could reduce the number of DCX-positive cells in the dentate gyrus area and impair cognitive functions of the TBI mice. These data suggested that hippocampal expression of CD24 might positively regulate neurogenesis and improve cognitive functions after TBI.

DHEA Attenuates Microglial Activation via Induction of JMJD3 in Experimental Subarachnoid Haemorrhage.

BACKGROUND: Microglia are resident immune cells in the central nervous system and central to the innate immune system. Excessive activation of microglia after subarachnoid haemorrhage (SAH) contributes greatly to early brain injury, which is responsible for poor outcomes. Dehydroepiandrosterone (DHEA), a steroid hormone enriched in the brain, has recently been found to regulate microglial activation. The purpose of this study was to address the role of DHEA in SAH. METHODS: We used in vivo models of endovascular perforation and in vitro models of haemoglobin exposure to illustrate the effects of DHEA on microglia in SAH. RESULTS: In experimental SAH mice, exogenous DHEA administration increased DHEA levels in the brain and modulated microglial activation. Ameliorated neuronal damage and improved neurological outcomes were also observed in the SAH mice pretreated with DHEA, suggesting neuronal protective effects of DHEA. In cultured microglia, DHEA elevated the mRNA and protein levels of Jumonji d3 (JMJD3, histone 3 demethylase) after haemoglobin exposure, downregulated the H3K27me3 level, and inhibited the transcription of proinflammatory genes. The devastating proinflammatory microglia-mediated effects on primary neurons were also attenuated by DHEA; however, specific inhibition of JMJD3 abolished the protective effects of DHEA. We next verified that DHEA-induced JMJD3 expression, at least in part, through the tropomyosin-related kinase A (TrkA)/Akt signalling pathway. CONCLUSIONS: DHEA has a neuroprotective effect after SAH. Moreover, DHEA increases microglial JMJD3 expression to regulate proinflammatory/anti-inflammatory microglial activation after haemoglobin exposure, thereby suppressing inflammation.

Nectar supplementation changes pollinator behaviour and pollination mode in Pedicularis dichotoma: implications for evolutionary transitions.

Backgrounds and Aims: Gain or loss of floral nectar, an innovation in floral traits, has occurred in diverse lineages of flowering plants, but the causes of reverse transitions (gain of nectar) remain unclear. Phylogenetic studies show multiple gains and losses of floral nectar in the species-rich genus Pedicularis. Here we explore how experimental addition of nectar to a supposedly nectarless species, P. dichotoma, influences pollinator foraging behaviour. Methods: The liquid (nectar) at the base of the corolla tube in P. dichotoma was investigated during anthesis. Sugar components were measured by high-performance liquid chromatography. To understand evolutionary transitions of nectar, artificial nectar was added to corolla tubes and the reactions of bumble-bee pollinators to extra nectar were examined. Key Results: A quarter of unmanipulated P. dichotoma plants contained measurable nectar, with 0.01-0.49 µL per flower and sugar concentrations ranging from 4 to 39 %. The liquid surrounding the ovaries in the corolla tubes was sucrose-dominant nectar, as in two sympatric nectariferous Pedicularis species. Bumble-bees collected only pollen from control (unmanipulated) flowers of P. dichotoma, adopting a sternotribic pollination mode, but switched to foraging for nectar in manipulated (nectar-supplemented) flowers, adopting a nototribic pollination mode as in nectariferous species. This altered foraging behaviour did not place pollen on the ventral side of the bees, and sternotribic pollination also decreased. Conclusion: Our study is the first to quantify variation in nectar production in a supposedly 'nectarless' Pedicularis species. Flower manipulations by adding nectar suggested that gain (or loss) of nectar would quickly result in an adaptive behavioural shift in the pollinator, producing a new location for pollen deposition and stigma contact without a shift to other pollinators. Frequent gains of nectar in Pedicularis species would be beneficial by enhancing pollinator attraction in unpredictable pollination environments.

Peroxiredoxin 2 activates microglia by interacting with Toll-like receptor 4 after subarachnoid hemorrhage.

BACKGROUND: Peroxiredoxin (Prx) protein family have been reported as important damage-associated molecular patterns (DAMPs) in ischemic stroke. Since peroxiredoxin 2 (Prx2) is the third most abundant protein in erythrocytes and the second most protein in the cerebrospinal fluid in traumatic brain injury and subarachnoid hemorrhage (SAH) patients, we assessed the role of extracellular Prx2 in the context of SAH. METHODS: We introduced a co-culture system of primary neurons and microglia. Prx2 was added to culture medium with oxyhemoglobin (OxyHb) to mimic SAH in vitro. Neuronal cell viability was assessed by lactate dehydrogenase (LDH) assay, and neuronal apoptosis was determined by TUNEL staining. Inflammatory factors in culture medium were measured by ELISA, and their mRNA levels in microglia were determined by qPCR. Toll-like receptor 4 knockout (TLR4-KO) mice were used to provide TLR4-KO microglia; ST-2825 was used to inhibit MyD88, and pyrrolidine dithiocarbamate (PDTC) was used to inhibit NF-κB. Related cellular signals were analyzed by Western blot. Furthermore, we detected the level of Prx2 in aneurysmal SAH patients' cerebrospinal fluids (CSF) and compared its relationship with Hunt-Hess grades. RESULTS: Prx2 interacted with TLR4 on microglia after SAH and then activated microglia through TLR4/MyD88/NF-κB signaling pathway. Pro-inflammatory factors were expressed and released, eventually caused neuronal apoptosis. The levels of Prx2 in SAH patients positively correlated with Hunt-Hess grades. CONCLUSIONS: Extracellular Prx2 in CSF after SAH is a DAMP which resulted in microglial activation via TLR4/MyD88/NF-κB pathway and then neuronal apoptosis. Prx2 in patients' CSF may be a potential indicator of brain injury and prognosis.

Heterostyly promotes compatible pollination in buckwheats: Comparisons of intraflower, intraplant, and interplant pollen flow in distylous and homostylous Fagopyrum.

PREMISE OF THE STUDY: Heterostyly, the reciprocal positioning of stigmas and anthers in different floral morphs, has long been thought to promote intermorph pollination. However, extensive intramorph pollination occurs commonly in heterostylous species, leading to recurrent questions about the functional and evolutionary significance of heterostyly. METHODS: To identify the sources of stigmatic pollen (autogamous [intraflower], geitonogamous [intraplant], vs. interplant), we emasculated either one flower or entire plants in experimental populations of the two closely related buckwheat species, distylous Fagopyrum esculentum and homostylous F. tataricum. Differences in pollen size allowed unambiguous identification of pollen on stigmas. RESULTS: Only 2.4% of F. tataricum pollen and 1.5% of F. esculentum pollen arrived successfully on compatible stigmas of other plants. In the former (homostylous) species, 71.3% of the pollen load on stigmas was autogamous, 10.8% was geitonogamous, and 17.9% was interplant. In the latter (distylous) species, 37.45% of the pollen on stigmas was autogamous, 13.8% was geitonogamous, 17.0% was intramorph, and 31.75% was intermorph. The amount of incompatible pollen arriving on stigmas was greatly decreased by both one-flower and whole-plant emasculations, and thus, the proportion of compatible pollen deposited increased with one-flower emasculation and increased even more with whole-plant emasculation. CONCLUSIONS: Our quantification of pollen-donor sources in these two species indicated that heterostyly in Fagopyrum esculentum provided a nearly 2-fold fitness advantage (in terms of compatible pollination) over expected (random) pollen transfers between morphs. Because of reduced herkogamy, the homostylous F. tataricum was highly autogamous.

The rise of soluble platelet-derived growth factor receptor ß in CSF early after subarachnoid hemorrhage correlates with cerebral vasospasm.

Platelet-derived growth factor ß (PDGFß) has been proposed to contribute to the development of cerebral vasospasm (CVS) after subarachnoid hemorrhage (SAH), and soluble PDGFRß (sPDGFRß) is considered to be an inhibitor of PDGF signaling. We aimed at determining the sPDGFRß concentrations in the cerebrospinal fluid (CSF) of patients with aneurysmal SAH (aSAH) and analyzing the relationship between sPDGFRß level and CVS. CSF was sampled from 32 patients who suffered aSAH and five normal controls. Enzyme-linked immunosorbent assay was performed to determine the sPDGFRß concentrations in the CSF. Functional outcome was assessed using modified Rankin scale (mRS) at 6 months after aSAH. CVS was identified using transcranial Doppler or angio-CT or DSA. The cutoff of sPDGFRß for CVS was defined on the ROC curve. The concentrations of sPDGFRß following aSAH were both higher than those of normal controls on days 1-3 and 4-6, and peaked on days 7-9 post-SAH. The cutoff value of sPDGFRß level on days 1-3 for CVS was defined as 975.38 pg/ml according to the ROC curve (AUC = 0.680, p = 0.082). In addition, CSF sPDGFRß concentrations correlated with CVS (r = 0.416, p = 0.018), and multivariate analysis indicated that sPDGFRß level higher than 975.38 pg/ml on days 1-3 was an independent predictor of CVS (p = 0.001, OR = 19.22, 95% CI: 3.27-113.03), but not for unfavorable outcome after aSAH in the current study. CSF sPDGFRß level increases after aSAH and is higher in patients who developed CVS, and sPDGFRß level higher than 975.38 pg/ml on days 1-3 is a potential predictor for CVS after SAH.

Structure alignment-based classification of RNA-binding pockets reveals regional RNA recognition motifs on protein surfaces.

BACKGROUND: Many critical biological processes are strongly related to protein-RNA interactions. Revealing the protein structure motifs for RNA-binding will provide valuable information for deciphering protein-RNA recognition mechanisms and benefit complementary structural design in bioengineering. RNA-binding events often take place at pockets on protein surfaces. The structural classification of local binding pockets determines the major patterns of RNA recognition. RESULTS: In this work, we provide a novel framework for systematically identifying the structure motifs of protein-RNA binding sites in the form of pockets on regional protein surfaces via a structure alignment-based method. We first construct a similarity network of RNA-binding pockets based on a non-sequential-order structure alignment method for local structure alignment. By using network community decomposition, the RNA-binding pockets on protein surfaces are clustered into groups with structural similarity. With a multiple structure alignment strategy, the consensus RNA-binding pockets in each group are identified. The crucial recognition patterns, as well as the protein-RNA binding motifs, are then identified and analyzed. CONCLUSIONS: Large-scale RNA-binding pockets on protein surfaces are grouped by measuring their structural similarities. This similarity network-based framework provides a convenient method for modeling the structural relationships of functional pockets. The local structural patterns identified serve as structure motifs for the recognition with RNA on protein surfaces.

TP53 mutations predict decitabine-induced complete responses in patients with myelodysplastic syndromes.

To identify the molecular signatures that predict responses to decitabine (DAC), we examined baseline gene mutations (28 target genes) in 109 myelodysplastic syndrome (MDS) patients at diagnosis. We determined that TP53 mutations predicted complete response (CR), as 10 of 15 patients (66·7%) who possessed TP53 mutations achieved a CR. Univariate and multivariate analyses showed that TP53 mutations are the only molecular signatures predictive of a CR to DAC in MDS. Among the ten patients with TP53 mutations who achieved a CR, nine presented with complex karyotypes due to abnormalities involving chromosome 5 and/or chromosome 7, and eight possessed monosomies. Although TP53 mutations were associated with a higher frequency of CRs, they were not associated with improved survival. Poor outcomes were attributed to early relapses and transformation to acute myeloid leukaemia after CR. Post-DAC therapy patient gene mutation profiles showed that most CR patients exhibited fewer gene mutations after achieving a CR. It seems that suppression of these gene mutations was facilitated by DAC, resulting in a CR. In summary, TP53 mutations might predict decitabine-induced complete responses in patients with MDS. DAC-induced responses may result from partial suppression of malignant clones containing mutated TP53 genes.