Decoding Subjective Intensity of Nociceptive Pain from Pre-stimulus and Post-stimulus Brain Activities

Pain is a highly subjective experience. Self-report is the gold standard for pain assessment in clinical practice, but it may not be available or reliable in some populations. Neuroimaging data, such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have the potential to be used to provide physiology-based and quantitative nociceptive pain assessment tools that complements self-report. However, existing neuroimaging-based nociceptive pain assessments only rely on the information in pain-evoked brain activities, but neglect the fact that the perceived intensity of pain is also encoded by ongoing brain activities prior to painful stimulation. Here, we proposed to use machine learning algorithms to decode pain intensity from both pre-stimulus ongoing and post-stimulus evoked brain activities. Neural features that were correlated with intensity of laser-evoked nociceptive pain were extracted from high-dimensional pre- and post-stimulus EEG and fMRI activities using partial least-squares regression (PLSR). Further, we used support vector machine (SVM) to predict the intensity of pain from pain-related time-frequency EEG patterns and BOLD-fMRI patterns. Results showed that combining predictive information in pre- and post-stimulus brain activities can achieve significantly better performance in classifying high-pain and low-pain and in predicting the rating of perceived pain than only using post-stimulus brain activities. Therefore, the proposed pain prediction method holds great potential in basic research and clinical applications.published_or_final_versio

Targeted knock-down of miR21 primary transcripts using snoMEN vectors induces apoptosis in human cancer cell lines

We have previously reported an antisense technology, 'snoMEN vectors', for targeted knock-down of protein coding mRNAs using human snoRNAs manipulated to contain short regions of sequence complementarity with the mRNA target. Here we characterise the use of snoMEN vectors to target the knock-down of micro RNA primary transcripts. We document the specific knock-down of miR21 in HeLa cells using plasmid vectors expressing miR21-targeted snoMEN RNAs and show this induces apoptosis. Knock-down is dependent on the presence of complementary sequences in the snoMEN vector and the induction of apoptosis can be suppressed by over-expression of miR21. Furthermore, we have also developed lentiviral vectors for delivery of snoMEN RNAs and show this increases the efficiency of vector transduction in many human cell lines that are difficult to transfect with plasmid vectors. Transduction of lentiviral vectors expressing snoMEN targeted to pri-miR21 induces apoptosis in human lung adenocarcinoma cells, which express high levels of miR21, but not in human primary cells. We show that snoMEN-mediated suppression of miRNA expression is prevented by siRNA knock-down of Ago2, but not by knock-down of Ago1 or Upf1. snoMEN RNAs colocalise with Ago2 in cell nuclei and nucleoli and can be co-immunoprecipitated from nuclear extracts by antibodies specific for Ago2

Resonances in J/ψ→ϕπ+π−J/\psi \to \phi \pi ^+\pi ^- and ϕK+K−\phi K^+K^-

A partial wave analysis is presented of $J/\psi \to \phi \pi ^+\pi ^-$ and $\phi K^+K^-$ from a sample of 58M $J/\psi$ events in the BES II detector. The $f_0(980)$ is observed clearly in both sets of data, and parameters of the Flatt\' e formula are determined accurately: $M = 965 \pm 8$ (stat) $\pm 6$ (syst) MeV/c$^2$, $g_1 = 165 \pm 10 \pm 15$ MeV/c$^2$, $g_2/g_1 = 4.21 \pm 0.25 \pm 0.21$. The $\phi \pi \pi$ data also exhibit a strong $\pi \pi$ peak centred at $M = 1335$ MeV/c$^2$. It may be fitted with $f_2(1270)$ and a dominant $0^+$ signal made from $f_0(1370)$ interfering with a smaller $f_0(1500)$ component. There is evidence that the $f_0(1370)$ signal is resonant, from interference with $f_2(1270)$. There is also a state in $\pi \pi$ with $M = 1790 ^{+40}_{-30}$ MeV/c$^2$ and $\Gamma = 270 ^{+60}_{-30}$ MeV/c$^2$; spin 0 is preferred over spin 2. This state, $f_0(1790)$, is distinct from $f_0(1710)$. The $\phi K\bar K$ data contain a strong peak due to $f_2'(1525)$. A shoulder on its upper side may be fitted by interference between $f_0(1500)$ and $f_0(1710)$.Comment: 17 pages, 6 figures, 1 table. Submitted to Phys. Lett.

Measurement of the Branching Fraction of J/psi --> pi+ pi- pi0

Using 58 million J/psi and 14 million psi' decays obtained by the BESII experiment, the branching fraction of J/psi --> pi+ pi- pi0 is determined. The result is (2.10+/-0.12)X10^{-2}, which is significantly higher than previous measurements.Comment: 9 pages, 8 figures, RevTex

Search for K_S K_L in psi'' decays

K_S K_L from psi'' decays is searched for using the psi'' data collected by BESII at BEPC, the upper limit of the branching fraction is determined to be B(psi''--> K_S K_L) < 2.1\times 10^{-4} at 90% C. L. The measurement is compared with the prediction of the S- and D-wave mixing model of the charmonia, based on the measurements of the branching fractions of J/psi-->K_S K_L and psi'-->K_S K_L.Comment: 5 pages, 1 figur

First Measurements of eta_c Decaying into K^+K^-2(pi^+pi^-) and 3(pi^+pi^-)

The decays of eta_c to K^+K^-2(pi^+pi^-) and 3(pi^+pi^-) are observed for the first time using a sample of 5.8X10^7 J/\psi events collected by the BESII detector. The product branching fractions are determined to be B(J/\psi-->gamma eta_c)*B(eta_c-->K^+K^-pi^+pi^-pi^+pi^-)=(1.21+-0.32+- 0.23)X10^{-4}$,B(J/\psi-->gamma eta_c)*B(eta_c-->K^{*0}\bar{K}^{*0}pi^+pi^-)= (1.29+-0.43+-0.32)X10^{-4}$, and (J/\psi-->gamma eta_c)* B(eta_c-->pi^+pi^-pi^+pi^-pi^+pi^-)= (2.59+-0.32+-0.48)X10^{-4}. The upper limit for eta_c-->phi pi^+pi^-pi^+pi^- is also obtained as B(J/\psi-->gamma eta_c)*B(eta_c--> phi pi^+pi^-pi^+pi^-)< 6.03 X10^{-5} at the 90% confidence level.Comment: 11 pages, 4 figure

First observation of psi(2S)-->K_S K_L

The decay psi(2S)-->K_S K_L is observed for the first time using psi(2S) data collected with the Beijing Spectrometer (BESII) at the Beijing Electron Positron Collider (BEPC); the branching ratio is determined to be B(psi(2S)-->K_S K_L) = (5.24\pm 0.47 \pm 0.48)\times 10^{-5}. Compared with J/psi-->K_S K_L, the psi(2S) branching ratio is enhanced relative to the prediction of the perturbative QCD ``12%'' rule. The result, together with the branching ratios of psi(2S) decays to other pseudoscalar meson pairs (\pi^+\pi^- and K^+K^-), is used to investigate the relative phase between the three-gluon and the one-photon annihilation amplitudes of psi(2S) decays.Comment: 5 pages, 4 figures, 2 tables, submitted to Phys. Rev. Let

Study of psi(2S) decays to X J/psi

Using J/psi -> mu^+ mu^- decays from a sample of approximately 4 million psi(2S) events collected with the BESI detector, the branching fractions of psi(2S) -> eta J/psi, pi^0 pi^0 J/psi, and anything J/psi normalized to that of psi(2S) -> pi^+ pi^- J/psi are measured. The results are B(psi(2S) -> eta J/psi)/B(psi(2S) -> pi^+ pi^- J/psi) = 0.098 \pm 0.005 \pm 0.010, B(psi(2S) -> pi^0 pi^0 J/psi)/B(psi(2S) -> pi^+ pi^- J/psi) = 0.570 \pm 0.009 \pm 0.026, and B(psi(2S) -> anything J/psi)/B(psi(2S) -> pi^+ pi^- J/psi) = 1.867 \pm 0.026 \pm 0.055.Comment: 13 pages, 8 figure

Urinary MicroRNA Profiling in the Nephropathy of Type 1 Diabetes

Background: Patients with Type 1 Diabetes (T1D) are particularly vulnerable to development of Diabetic nephropathy (DN) leading to End Stage Renal Disease. Hence a better understanding of the factors affecting kidney disease progression in T1D is urgently needed. In recent years microRNAs have emerged as important post-transcriptional regulators of gene expression in many different health conditions. We hypothesized that urinary microRNA profile of patients will differ in the different stages of diabetic renal disease. Methods and Findings: We studied urine microRNA profiles with qPCR in 40 T1D with >20 year follow up 10 who never developed renal disease (N) matched against 10 patients who went on to develop overt nephropathy (DN), 10 patients with intermittent microalbuminuria (IMA) matched against 10 patients with persistent (PMA) microalbuminuria. A Bayesian procedure was used to normalize and convert raw signals to expression ratios. We applied formal statistical techniques to translate fold changes to profiles of microRNA targets which were then used to make inferences about biological pathways in the Gene Ontology and REACTOME structured vocabularies. A total of 27 microRNAs were found to be present at significantly different levels in different stages of untreated nephropathy. These microRNAs mapped to overlapping pathways pertaining to growth factor signaling and renal fibrosis known to be targeted in diabetic kidney disease. Conclusions: Urinary microRNA profiles differ across the different stages of diabetic nephropathy. Previous work using experimental, clinical chemistry or biopsy samples has demonstrated differential expression of many of these microRNAs in a variety of chronic renal conditions and diabetes. Combining expression ratios of microRNAs with formal inferences about their predicted mRNA targets and associated biological pathways may yield useful markers for early diagnosis and risk stratification of DN in T1D by inferring the alteration of renal molecular processes. © 2013 Argyropoulos et al