Identification and expression profile analysis of NUCLEAR FACTOR-Y families in Physcomitrella patens

NUCLEAR FACTOR Y transcription factors belong to a multimember family and consist of NF-YA/B/C subunits. Members of the NF-Y family have been reported to regulate physiological processes in plant. In this study, we identified and annotated two NF-YA, nine NF-B and twelve NF-YC proteins in the genome of Physcomitrella patens. Analyses of conserved domains demonstrated that PpNF-YA/B/C shared the same conserved domains with their orthologous proteins in Arabidopsis, O. sativa and mouse. Expression profiles indicated that PpNF-Ys were widely expressed in different tissues and developmental stages of P. patens throughout protonema and gametophores. The majority of PpNF-Y genes were responsive to abiotic stress via either ABA-independent or -dependent pathways. Some of ABA-regulated PpNF-Y expression were mediated by ABI3. To our knowledge, this study was the first to evaluate NF-Y families in Physcomitrella patens, and provides a foundation to dissect the function of PpNF-Ys

Optimum neural tuning curves for information efficiency with rate coding and finite-time window

An important question for neural encoding is what kind of neural systems can convey more information with less energy within a finite time coding window. This paper first proposes a finite-time neural encoding system, where the neurons in the system respond to a stimulus by a sequence of spikes that is assumed to be Poisson process and the external stimuli obey normal distribution. A method for calculating the mutual information of the finite-time neural encoding system is proposed and the definition of information efficiency is introduced. The values of the mutual information and the information efficiency obtained by using Logistic function are compared with those obtained by using other functions and it is found that Logistic function is the best one. It is further found that the parameter representing the steepness of the Logistic function has close relationship with full entropy, and that the parameter representing the translation of the function associates with the energy consumption and noise entropy tightly. The optimum parameter combinations for Logistic function to maximize the information efficiency are calculated when the stimuli and the properties of the encoding system are varied respectively. Some explanations for the results are given. The model and the method we proposed could be useful to study neural encoding system, and the optimum neural tuning curves obtained in this paper might exhibit some characteristics of a real neural system

Comparing gene expression profiles between Bt and non-Bt rice in response to brown planthopper infestation

Bt proteins are the most widely used insecticidal proteins in transgenic crops for improving insect resistance. We previously observed longer nymphal developmental duration and lower fecundity in brown planthopper (BPH) fed on Bt rice line KMD2, although Bt insecticidal protein Cry1Ab could rarely concentrate in this non-target rice pest. In the present study, we performed microarray analysis in an effort to detect Bt-independent variation, which might render Bt rice more defensive and/or less nutritious to BPH. We detected 3,834 and 3,273 differentially expressed probe-sets in response to BPH infestation in non-Bt parent Xiushui 11 and Bt rice KMD2, respectively, only 439 of which showed significant differences in expression between rice lines. Our analysis revealed a shift from growth to defense responses in response to BPH infestation, which was also detected in many other studies of plants suffering biotic and abiotic stresses. Chlorophyll biosynthesis and basic metabolism pathways were inhibited in response to infestation. IAA and GA levels decreased as a result of the repression of biosynthesis-related genes or the induction of inactivation-related genes. In accordance with these observations, a number of IAA-, GA-, BR-signaling genes were downregulated in response to BPH. Thus, the growth of rice plants under BPH attack was reduced and defense related hormone signaling like JA, SA and ET were activated. In addition, growth-related hormone signaling pathways, such as GA, BR and auxin signaling pathways, as well as ABA, were also found to be involved in BPH-induced defense. On the other side, 51 probe-sets (represented 50 genes) that most likely contribute to the impact of Bt rice on BPH were identified, including three early nodulin genes, four lipid metabolic genes, 14 stress response genes, three TF genes and genes with other functions. Two transcription factor genes, bHLH and MYB, together with lipid transfer protein genes LTPL65 and early nodulin gene ENOD93, are the most likely candidates for improving herbivore resistance in plants

Automated diagnoses of attention deficit hyperactive disorder using magnetic resonance imaging

Successful automated diagnoses of attention deficit hyperactive disorder (ADHD) using imaging and functional biomarkers would have fundamental consequences on the public health impact of the disease. In this work, we show results on the predictability of ADHD using imaging biomarkers and discuss the scientific and diagnostic impacts of the research. We created a prediction model using the landmark ADHD 200 data set focusing on resting state functional connectivity (rs-fc) and structural brain imaging. We predicted ADHD status and subtype, obtained by behavioral examination, using imaging data, intelligence quotients and other covariates. The novel contributions of this manuscript include a thorough exploration of prediction and image feature extraction methodology on this form of data, including the use of singular value decompositions, CUR decompositions, random forest, gradient boosting, bagging, voxel-based morphometry and support vector machines as well as important insights into the value, and potentially lack thereof, of imaging biomarkers of disease. The key results include the CUR-based decomposition of the rs-fc-fMRI along with gradient boosting and the prediction algorithm based on a motor network parcellation and random forest algorithm. We conjecture that the CUR decomposition is largely diagnosing common population directions of head motion. Of note, a byproduct of this research is a potential automated method for detecting subtle in-scanner motion. The final prediction algorithm, a weighted combination of several algorithms, had an external test set specificity of 94% with sensitivity of 21%. The most promising imaging biomarker was a correlation graph from a motor network parcellation. In summary, we have undertaken a large-scale statistical exploratory prediction exercise on the unique ADHD 200 data set. The exercise produced several potential leads for future scientific exploration of the neurological basis of ADHD

Screening for biomarkers of liver injury induced by Polygonum multiflorum: a targeted metabolomic study

Heshouwu (HSW), the dry roots of Polygonum multiflorum, a classical traditional Chinese medicine is used as a tonic for a wide range of conditions，particularly those associated with aging. However, it tends to be taken overdose or long term in these years, which has resulted in liver damage reported in many countries. In this study, the indicative roles of nine bile acids (BAs) were evaluated to offer potential biomarkers for HSW induced liver injury. Nine BAs including cholic acid (CA) and chenodeoxycholic acid (CDCA), taurocholic acid (TCA), glycocholic acid (GCA), glycochenodeoxycholic acid (GCDCA), deoxycholic acid (DCA), glycodeoxycholic acid (GDCA), ursodeoxycholic acid (UDCA) and hyodeoxycholic acid (HDCA) in rat bile and serum were detected by a developed LC-MS method after 42 days treatment. Partial least square-discriminate analysis (PLS-DA) was applied to evaluate the indicative roles of the nine BAs, and metabolism of the nine BAs was summarized. Significant change was observed for the concentrations of nine BAs in treatment groups compared with normal control; In the PLS-DA plots of nine BAs in bile, normal control and raw HSW groups were separately clustered and could be clearly distinguished, GDCA was selected as the distinguished components for raw HSW overdose treatment group. In the PLS-DA plots of nine BAs in serum, the normal control and raw HSW overdose treatment group were separately clustered and could be clearly distinguished, and HDCA was selected as the distinguished components for raw HSW overdose treatment group. The results indicated the perturbation of nine BAs was associated with HSW induced liver injury; GDCA in bile, as well as HDCA in serum could be selected as potential biomarkers for HSW induced liver injury; it also laid the foundation for the further search on the mechanisms of liver injury induced by HSW