Temporal–spectral signaling of sensory information and expectations in the cerebral processing of pain

The perception of pain is shaped by somatosensory information about threat. However, pain is also influenced by an individual's expectations. Such expectations can result in clinically relevant modulations and abnormalities of pain. In the brain, sensory information, expectations (predictions), and discrepancies thereof (prediction errors) are signaled by an extended network of brain areas which generate evoked potentials and oscillatory responses at different latencies and frequencies. However, a comprehensive picture of how evoked and oscillatory brain responses signal sensory information, predictions, and prediction errors in the processing of pain is lacking so far. Here, we therefore applied brief painful stimuli to 48 healthy human participants and independently modulated sensory information (stimulus intensity) and expectations of pain intensity while measuring brain activity using electroencephalography (EEG). Pain ratings confirmed that pain intensity was shaped by both sensory information and expectations. In contrast, Bayesian analyses revealed that stimulus-induced EEG responses at different latencies (the N1, N2, and P2 components) and frequencies (alpha, beta, and gamma oscillations) were shaped by sensory information but not by expectations. Expectations, however, shaped alpha and beta oscillations before the painful stimuli. These findings indicate that commonly analyzed EEG responses to painful stimuli are more involved in signaling sensory information than in signaling expectations or mismatches of sensory information and expectations. Moreover, they indicate that the effects of expectations on pain are served by brain mechanisms which differ from those conveying effects of sensory information on pain

Older Adult Homicide: Investigating Case, Victim and Perpetrator Characteristics in a National Sample from England and Wales

Older adult homicide (OAH) is the most severe, yet understudied, form of older adult abuse. This study examined the case, victim and perpetrator characteristics of OAH. A secondary analysis of national data from England and Wales (2008–2019) was conducted where cases of non-stranger OAH (victims aged sixty years and over) were compared to adult homicide (victims aged eighteen to fifty-nine years) at the case, victim (n ¼ 3,274) and perpetrator (n ¼ 2,763) levels. Logistic regression models used to identify characteristics that were OAH risk factors, showed only a slight increase in predictive power but high accuracy in classifying adult homicide cases. Nevertheless, some risk factors known to be predictors of older adult abuse were significant predictors of OAH (e.g. living with the perpetrator, the perpetrator’s mental state). Implications for research, policy and practice are discussed

Contamination of clinical specimens with MLV-encoding nucleic acids: implications for XMRV and other candidate human retroviruses

Efforts to assess the prevalence of xenotropic murine leukemia virus-related virus (XMRV) in patients with prostate cancer and chronic fatigue syndrome have relied heavily on PCR-based testing of clinical samples and have yielded widely divergent findings. This week in Retrovirology, reports from four independent research groups illustrate the extreme care needed to exclude DNA or RNA contamination in PCR analyses of XMRV. In addition, phylogenetic evidence suggesting that previously-published XMRV sequences originated from a commonly-used prostate carcinoma cell line (22Rv1) is presented. These findings raise important questions regarding the provenance of XMRV and its potential connection to human disease

Quantifying injury to common bottlenose dolphins from the Deepwater Horizon oil spill using an age-, sex- and class-structured population model

Field studies documented increased mortality, adverse health effects, and reproductive failure in common bottlenose dolphins Tursiops truncatus following the Deepwater Horizon (DWH) oil spill. In order to determine the appropriate type and amount of restoration needed to compensate for losses, the overall extent of injuries to dolphins had to be quantified. Simply counting dead individuals does not consider long-term impacts to populations, such as the loss of future reproductive potential from mortality of females, or the chronic health effects that continue to compromise survival long after acute effects subside. Therefore, we constructed a sex- and agestructured model of population growth and included additional class structure to represent dolphins exposed and unexposed to DWH oil. The model was applied for multiple stocks to predict injured population trajectories using estimates of post-spill survival and reproductive rates. Injured trajectories were compared to baseline trajectories that were expected had the DWH incident not occurred. Two principal measures of injury were computed: (1) lost cetacean years (LCY); the difference between baseline and injured population size, summed over the modeled time period, and (2) time to recovery; the number of years for the stock to recover to within 95% of baseline. For the dolphin stock in Barataria Bay, Louisiana, the estimated LCY was substantial: 30 347 LCY (95% CI: 11 511 to 89 746). Estimated time to recovery was 39 yr (95% CI: 24 to 80). Similar recovery timelines were predicted for stocks in the Mississippi River Delta, Mississippi Sound, Mobile Bay and the Northern Coastal Stock.Publisher PDFPeer reviewe

Assimilation of Global Total Chlorophyll OC‐CCI Data and Its Impact on Individual Phytoplankton Fields

The coupled ocean circulation‐ecosystem model MITgcm‐REcoM2 is used to simulate biogeochemical variables in a global configuration. The ecosystem model REcoM2 simulates two phytoplankton groups, diatoms and small phytoplankton, using a quota formulation with variable carbon, nitrogen, and chlorophyll contents of the cells. To improve the simulation of the phytoplankton variables, chlorophyll‐a data from the European Space Agency Ocean‐Color Climate Change Initiative (OC‐CCI) for 2008 and 2009 are assimilated with an ensemble Kalman filter. Utilizing the multivariate cross covariances estimated by the model ensemble, the assimilation constrains all model variables describing the two phytoplankton groups. Evaluating the assimilation results against the satellite data product SynSenPFT shows an improvement of total chlorophyll and more importantly of individual phytoplankton groups. The assimilation improves both phytoplankton groups in the tropical and midlatitude regions, whereas the assimilation has a mixed response in the high‐latitude regions. Diatoms are most improved in the major ocean basins, whereas small phytoplankton show small deteriorations in the Southern Ocean. The improvement of diatoms is larger when the multivariate assimilation is computed using the ensemble‐estimated cross covariances between total chlorophyll and the phytoplankton groups than when the groups are updated so that their ratio to total chlorophyll is preserved. The comparison with in situ observations shows that the correlation of the simulated chlorophyll of both phytoplankton groups with these data is increased whereas the bias and error are decreased. Overall, the multivariate assimilation of total chlorophyll modifies the two phytoplankton groups separately, even though the sum of their individual chlorophyll concentrations represents the total chlorophyll

Assigning stranded bottlenose dolphins to source stocks using stable isotope ratios following the Deepwater Horizon oil spill

The potential for stranded dolphins to serve as a tool for monitoring free-ranging populations would be enhanced if their stocks of origin were known. We used stable isotopes of carbon, nitrogen, and sulfur from skin to assign stranded bottlenose dolphins Tursiops truncatus to different habitats, as a proxy for stocks (demographically independent populations), following the Deepwater Horizon oil spill. Model results from biopsy samples collected from dolphins from known habitats (n = 205) resulted in an 80.5% probability of correct assignment. These results were applied to data from stranded dolphins (n = 217), resulting in predicted assignment probabilities of 0.473, 0.172, and 0.355 to Estuarine, Barrier Island (BI), and Coastal stocks, respectively. Differences were found west and east of the Mississippi River, with more Coastal dolphins stranding in western Louisiana and more Estuarine dolphins stranding in Mississippi. Within the Estuarine East Stock, 2 groups were identified, one predominantly associated with Mississippi and Alabama estuaries and another with western Florida. δ15N values were higher in stranded samples for both Estuarine and BI stocks, potentially indicating nutritional stress. High probabilities of correct assignment of the biopsy samples indicate predictable variation in stable isotopes and fidelity to habitat. The power of δ34S to discriminate habitats relative to salinity was essential. Stable isotopes may provide guidance regarding where additional testing is warranted to confirm demographic independence and aid in determining the source habitat of stranded dolphins, thus increasing the value of biological data collected from stranded individuals.Publisher PDFPeer reviewe

Geostatistical modeling and spatial distribution analysis of porosity and permeability in the Shurijeh-B reservoir of Khangiran gas field in Iran

The main objectives of this study are analysis of spatial behavior of the porosity and permeability, presenting direction of anisotropy for each variable and describing variation of these parameters in Shurijeh B gas reservoir in Khangiran gas field. Porosity well log data of 32 wells are available for performing this geostatistical analysis. A univariate statistical analysis is done on both porosity and permeability to provide a framework for geostatistical analysis and modeling. For spatial analysis of these parameters, the experimental semivariogram of each variable in different direction as well as their variogram map plotted to find out the direction of anisotropy and their geostatistical parameters such as range, sill, and nugget effect for later geostatistical work and finally for geostatistical modeling, two approaches kriging and Sequential Gaussian Simulation are used to get porosity and permeability maps through the entire reservoir. All of statistical and geostatistical analysis has been done using GSLIB and PETREL software. Maximum and minimum direction of continuity are found to be N75W and N15E, respectively. Geostatistical parameters of calculated semivariogram in this direction like range of 7000 m and nugget of 0.2 are used for modeling. Both kriging and SGS method used for modeling but kriging tends to smooth out estimates but on the other hand SGS method tends to show up details. Cross-validation also used to validate the generated modeling

A Fokker-Planck formalism for diffusion with finite increments and absorbing boundaries

Gaussian white noise is frequently used to model fluctuations in physical systems. In Fokker-Planck theory, this leads to a vanishing probability density near the absorbing boundary of threshold models. Here we derive the boundary condition for the stationary density of a first-order stochastic differential equation for additive finite-grained Poisson noise and show that the response properties of threshold units are qualitatively altered. Applied to the integrate-and-fire neuron model, the response turns out to be instantaneous rather than exhibiting low-pass characteristics, highly non-linear, and asymmetric for excitation and inhibition. The novel mechanism is exhibited on the network level and is a generic property of pulse-coupled systems of threshold units.Comment: Consists of two parts: main article (3 figures) plus supplementary text (3 extra figures