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Objective Differential expression profiles of free microRNAs (miRNAs) in cerebrospinal fluid (CSF) from patients with intracerebral haemorrhage (ICH) and controls were analysed to identify miRNA markers associated with ICH-induced brain injury. Methods Five patients with acute ICH were enrolled alongside five control inpatients without CNS diseases. CSF specimens were collected during initial lumbar puncture after admission, total free RNAs were extracted from CSF, and miRNAs were detected by Agilent Human miRNA V21.0 chip experiments. Differential expression profiles were statistically analysed. Results Principal component analysis of miRNA microarray data confirmed that case and control groups were distinct, and biological repeats were homogeneous. After normalisation of chip data, differential miRNAs were screened using fold change and Student's t-tests; 77 miRNAs were up-regulated (fold change > 2), and 44 miRNAs were down-regulated (fold change Conclusion ICH patients display distinct miRNA expression profiles in CSF, suggesting that miRNAs may be auxiliary diagnostic biomarkers for ICH.

Ge-Di Zhang,1,* Xi-Xi Liu,2,* Jia-Lang Liang,3 Qi-Ming Hu4 1Department of Endocrinology, Yuncheng Hospital of Traditional Chinese Medicine, Yuncheng, 274700, People’s Republic of China; 2Department of Endocrinology, Yichun Hospital of Traditional Chinese Medicine, Yichun, 336000, People’s Republic of China; 3Department of Endocrinology, Guangdong Integrated Traditional Chinese and Western Medicine Hospital, Foshan, 528000, People’s Republic of China; 4Department of Endocrinology, Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, 330000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qi-Ming HuDepartment of Endocrinology, Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, No. 445 of Bayidadao Street, Donghu District, Nanchang, 330000, People’s Republic of ChinaTel +86 79107702803Email huqimingqw_as@163.comObjective: This study aimed to summarize the distribution pattern of traditional Chinese medicine (TCM) syndromes in patients with type 2 diabetes mellitus (T2DM).Methods: The frequency, characteristics and distribution of all TCM syndromes of 549 patients with T2DM were analyzed.Results: The average age of T2DM onset was higher in women than in men (ie, men experienced earlier onset). The distribution of TCM syndromes, in order of frequency, was as follows: damp-heat trapping spleen (including spleen deficiency and dampness, damp heat due to spleen deficiency, and qi weakness due to spleen deficiency) (58.29%), qi-yin deficiency (16.03%), deficiency of yin and excessive heat (12.93%), blood stasis in collaterals (9.41%), and yin-yang deficiency (3.21%). The physical intensity of patients’ occupational activity was mainly light (49.6%), followed by heavy (31.4%) and moderate (19.0%).Conclusion: Damp-heat trapping spleen is the most common TCM syndrome in patients with T2DM, with damp heat due to spleen deficiency the most significant subtype. This syndrome tends to occur in people over the age of 60 and those undertaking too much or too little physical activity in their occupational activities. The traditional “three more and one less” symptoms do not adequately describe the clinical symptoms of T2DM.Keywords: type 2 diabetes, TCM syndrome differentiation, damp heat due to spleen deficiency, epidemiology, clinical symptoms

Additional file 1: Figure S1. (A) Flow cytometry gating strategies and representative plots. (B) RT-qPCR was performed to detected TET3 mRNA level in ESCC tissues and para-cancerous tissues. (C) RT-qPCR was performed to detected TET3 mRNA level in ESCC cell lines and normal esophageal mucosa epithelium cell line. Figure S2. Kaplan-Meier product limit estimator was applied to draw overall survival (OS) curves of 299 enrolled ESCC patients, compared according to TET3 expression level, in stage I-II (A), stage III-IV (B), grade I (C) and grade II-III (D). Figure S3. The knockdown (si-control vs si-TET3) and overexpression (ov-control vs ov-TET3) of TET3 in cell lines were verified with RT-qPCR (A) and Western blot (B). Figure S4. Tumor xenograft was applied to assess the proliferation ability of ESCC cells influenced by TET3 expression. ov-Control group was implanted into the left posterior flank and ov-TET3 group was implanted into the right posterior flank of the same mouse. (ns: no significance, *p

Earned value management lacks research on the project completion trend forecasting method at the following two points: The project completion trend forecast is based on the state indicators at the project monitoring point, and the project execution efficiency before the monitoring time point is rarely considered; the project performance evaluation index How to reduce the non-efficiency noise caused by uncontrollable factors in the existing prediction methods when singularities occur. The above issues will affect the accuracy and stability of the earned value management forecasting system. This paper attempts to introduce the Kalman filtering method (KFFM) into the earned value management completion prediction calculation, and comprehensively considers the project execution efficiency in the logical order of “prediction-measure-correction”, and improves the prediction accuracy through dynamic correction of cost/progress indicators. And effectively reduce the impact of the earned value management forecasting system due to singularities

Additional file 1: Figure S1. Distribution plots showing the correlation between expression and Methylation. Each bar represents a sample, the names of the gene/transcript and CpGs are shown on the right, the methylation and expression values are shown on the left. The samples are reorders according to the expression value. A. Gene-level distribution plot. B. Transcript-level distribution plot.

Table S2. The antibodies used in this study. (DOC 38 kb)

Figure S2. The correlations assessed by Spearman's correlation between protein (Western blot) level of TEX9 and the number of metastatic lym nodes. (DOCX 42 kb)

Figure S1. Normalization of the microarray datasets from GEO. A. Before normalization. The batch effect among five datasets can be observed. B. After removal of batch effect and normalization. Figure S2. Model construction and selection. X-axis represents the number of risk models, y-axis represents the C-index, each green point represents the C-index of a particular risk model. We used red lines to connect these points. The C-indices of the model we captured were highlighted. Figure S3. 16 genes were selected by LASSO regression analysis. A. The dashed vertical line represents the optimal value of log Îť with the minimum partial likelihood deviance. B. LASSO coefficient of the 16 genes. Figure S4. Stratification analysis. TCGA stage III LUAD patients were stratified into high- and low- subgroups based the predictive signature, and high-risk group patients had poorer OS compared to low-risk group patients. Hazard Ratio: 2.89; 95% CI: 1.47 â 5.69; p-value < 0.001. Figure S5. Kaplan-Meier survival curves of recurrence-free survival (RFS) between high-risk and low-risk patients. A. TCGA LUAD patients. B. GEO LUAD patients. In both patient datasets, the RFS time of patients in the high-risk group was significantly shorter than that in the low-risk group. Figure S6. Independent validation on GSE72094 dataset. Kaplan-Meier survival analysis showing the predictive signature can separate GSE72094 LUAD patients into high- and low-risk groups with different OS (p-value < 0.0001). (DOCX 3130 kb)

The p38 mitogen-activated protein kinase (MAPK) plays a key role in lipopolysaccharide (LPS)-induced signal transduction pathways that lead to inflammatory cytokine synthesis in macrophages; however, whether the inhibition of p38 MAPK regulates LPS-induced inflammatory cytokine expression in different types of macrophages remains the subject of debate. Herein, we assessed whether the inhibition of p38 MAPK by SB203580 regulates LPS-induced expression of the inflammatory cytokines tumor necrosis factor α (TNF-α) and interleukin 6 (IL-6) in RAW264.7 and resident peritoneal macrophages. Lipopolysaccharide stimulation of RAW264.7 macrophages or mouse resident peritoneal macrophages significantly increased TNF-α and IL-6 production. The addition of SB203580 to cultures dramatically blocked LPS-induced TNF-α production in RAW264.7 and mouse resident peritoneal macrophages, and dramatically blocked LPS-induced IL-6 production in RAW264.7 macrophages, but not in mouse resident peritoneal macrophages. Additionally, high concentrations of SB203580 resulted in increased IL-6 production. However, LPS-stimulation significantly up-regulated the mRNA transcript levels of TNF-α and IL-6 in RAW264.7 and mouse resident peritoneal macrophages, whereas pretreatment with SB203580 dramatically down-regulated LPS-induced mRNA transcript levels of TNF-α and IL-6 in these cells. Our data show that SB203580 differentially modulates LPS-induced production of the inflammatory cytokine IL-6 in two different sources of macrophages, and that this course of regulation occurs at the IL-6 mRNA post-transcriptional stage.

By use of a tensor method, the transform formulae for the beam coherence-polarization matrix of the partially polarized Gaussian Schell-model (GSM) beams through aligned and misaligned optical systems are derived. As an example, the propagation properties of the partially polarized GSM beam passing through a misaligned thin lens are illustrated numerically and discussed in detail. The derived formulae provide a convenient way to study the propagation properties of the partially polarized GSM beams through aligned and misaligned optical systems.

Inflammatory responses are important to host immune reactions, but uncontrolled inflammatory mediators may aid in the pathogenesis of other inflammatory diseases. Geniposide, an iridoid glycoside found in the herb gardenia, is believed to have broad-spectrum anti-inflammatory effects in murine models but its mechanism of action is unclear. We investigated the action of this compound in murine macrophages stimulated by lipopolysaccharide (LPS), as the stimulation of macrophages by LPS is known to induce inflammatory reactions. We determined the effect of geniposide on LPS-induced production of the inflammatory mediators, nitric oxide (NO) and prostaglandin E2 (PGE2), the mRNA and protein expression of the NO and PGE2 synthases, inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), respectively, and the mRNA and protein expression of the inflammatory cytokine, tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6). Furthermore, nuclear factor (NF)-κB, mitogen-activated protein kinase (MAPK) and activator protein (AP)-1 activity were assayed. To understand the action of geniposide on the NF-κB and MAPK pathways, we studied the effect of NF-κB and MAPK inhibitors on the LPS-induced production of NO, PGE2 and TNF-α. Our findings clearly showed that geniposide mainly exerts its anti-inflammatory effects by inhibiting the LPS-induced NF-κB, MAPK and AP-1 signaling pathways in macrophages, which subsequently reduces overexpression of the inducible enzymes iNOS and COX-2 and suppresses the expression and release of the inflammatory factors, TNF-α, IL-6, NO and PGE2. Thus, geniposide shows promise as a therapeutic agent in inflammatory diseases.

Publication in the conference proceedings of EUSIPCO, Lausanne, Switzerland, 2008

Excitable cells, such as neurons, produce action potentials (APs) that in extracel- lular recordings are often referred to as spikes. In these recordings, APs indeed appear as sharp spikes deviated from the noisy baseline. The contributions of each cell must be isolated from the background noise and from those of the other cells. The process of estimating one or more AP waveforms and their discharge instances (firing patterns) from multiunit recordings is known as spike sorting. Resolving overlapped APs is a major difficulty in automatic spike sorting methods. Therefore, this chapter is in large part dedicated to discussing this issue; we focus on state-of-the-art techniques addressing the problem of spike sorting, including the resolution of overlapped APs. In the section "Signal model", we propose the mathematical modeling of multiunit recordings and the complexity in the resolution of overlapped APs. Then, in section "State of the art," we sum- marize state-of-the-art spike sorting algorithms and discuss the advantages and limitations of each and the applicability of these methods for different types of experimental demands. The final section provides the conclusions.