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

Fatigue, depression, and pain in multiple sclerosis: How neuroinflammation translates into dysfunctional reward processing and anhedonic symptoms

Fatigue, depression, and pain affect the majority of multiple sclerosis (MS) patients, which causes a substantial burden to patients and society. The pathophysiology of these symptoms is not entirely clear, and current treatments are only partially effective. Clinically, these symptoms share signs of anhedonia, such as reduced motivation and a lack of positive affect. In the brain, they are associated with overlapping structural and functional alterations in areas involved in reward processing. Moreover, neuroinflammation has been shown to directly impede monoaminergic neurotransmission that plays a key role in reward processing. Here, we review recent neuroimaging and neuroimmunological findings, which indicate that dysfunctional reward processing might represent a shared functional mechanism fostering the symptom cluster of fatigue, depression, and pain in MS. We propose a framework that integrates these findings with a focus on monoaminergic neurotransmission and discuss its therapeutic implications, limitations, and perspectives

Space-Time Distribution of G-Band and Ca II H-Line Intensity Oscillations in Hinode/SOT-FG Observations

We study the space-time distributions of intensity fluctuations in 2 - 3 hour sequences of multi-spectral, high-resolution, high-cadence broad-band filtergram images (BFI) made by the SOT-FG system aboard the Hinode spacecraft. In the frequency range 5.5 < f < 8.0 mHz both G-band and Ca II H-line oscillations are suppressed in the presence of magnetic fields, but the suppression disappears for f > 10 mHz. By looking at G-band frequencies above 10 mHz we find that the oscillatory power, both at these frequencies and at lower frequencies too, lies in a mesh pattern with cell scale 2 - 3 Mm, clearly larger than normal granulation, and with correlation times on the order of hours. The mesh pattern lies in the dark lanes between stable cells found in time-integrated G-band intensity images. It also underlies part of the bright pattern in time-integrated H-line emission. This discovery may reflect dynamical constraints on the sizes of rising granular convection cells together with the turbulence created in strong intercellular downflows.Comment: 24 pages, 15 figure

No Evidence for Disease History as a Risk Factor for Narcolepsy after A(H1N1)pdm09 Vaccination

OBJECTIVES: To investigate disease history before A(H1N1)pdm09 vaccination as a risk factor for narcolepsy.METHODS: Case-control study in Sweden. Cases included persons referred for a Multiple Sleep Latency Test between 2009 and 2010, identified through diagnostic sleep centres and confirmed through independent review of medical charts. Controls, selected from the total population register, were matched to cases on age, gender, MSLT-referral date and county of residence. Disease history (prescriptions and diagnoses) and vaccination history was collected through telephone interviews and population-based healthcare registers. Conditional logistic regression was used to investigate disease history before A(H1N1)pdm09 vaccination as a risk-factor for narcolepsy.RESULTS: In total, 72 narcolepsy cases and 251 controls were included (range 3-69 years mean19-years). Risk of narcolepsy was increased in individuals with a disease history of nervous system disorders (OR range = 3.6-8.8) and mental and behavioural disorders (OR = 3.8, 95% CI 1.6-8.8) before referral. In a second analysis of vaccinated individuals only, nearly all initial associations were no longer statistically significant and effect sizes were smaller (OR range = 1.3-2.6). A significant effect for antibiotics (OR = 0.4, 95% CI 0.2-0.8) and a marginally significant effect for nervous system disorders was observed. In a third case-only analysis, comparing cases referred before vaccination to those referred after; prescriptions for nervous system disorders (OR = 26.0 95% CI 4.0-170.2) and ADHD (OR = 35.3 95% CI 3.4-369.9) were statistically significant during the vaccination period, suggesting initial associations were due to confounding by indication.CONCLUSION: The findings of this study do not support disease history before A(H1N1)pdm09 vaccination as a risk factor for narcolepsy

Validation of the prognostic relevance of plasma C-reactive protein levels in soft-tissue sarcoma patients

Background: The concept of the involvement of systemic inflammation in cancer progression and metastases has gained attraction within the past decade. C-reactive protein (CRP), a non-specific blood-based marker of the systemic inflammatory response, has been associated with decreased survival in several cancer types. The aim of the present study was to validate the prognostic value of pre-operative plasma CRP levels on clinical outcome in a large cohort of soft-tissue sarcoma (STS) patients. Methods: Three hundred and four STS patients, operated between 1998 and 2010, were retrospectively evaluated. CRP levels and the impact on cancer-specific survival (CSS), disease-free survival (DFS) and overall survival (OS) were assessed using Kaplan–Meier curves and univariate as well as multivariate Cox proportional models. Additionally, we developed a nomogram by supplementing the plasma CRP level to the well-established Kattan nomogram and evaluated the improvement of predictive accuracy of this novel nomogram by applying calibration and Harrell’s concordance index (c-index). Results: An elevated plasma CRP level was significantly associated with established prognostic factors, including age, tumour grade, size and depth (P<0.05). In multivariate analysis, increased CRP levels were significantly associated with a poor outcome for CSS (HR=2.05; 95% CI=1.13–3.74; P=0.019) and DFS (HR=1.88; 95% CI=1.07–3.34; P=0.029). The estimated c-index was 0.74 using the original Kattan nomogram and 0.77 when the plasma CRP level was added. Conclusion: An elevated pre-operative CRP level represents an independent prognostic factor that predicts poor prognosis and improves the predictive ability of the Kattan nomogram in STS patients. Our data suggest to further prospectively validate its potential utility for individual risk stratification and clinical management of STS patients

LifeGene : a large prospective population-based study of global relevance

Studying gene-environment interactions requires that the amount and quality of the lifestyle data is comparable to what is available for the corresponding genomic data. Sweden has several crucial prerequisites for comprehensive longitudinal biomedical research, such as the personal identity number, the universally available national health care system, continuously updated population and health registries and a scientifically motivated population. LifeGene builds on these strengths to bridge the gap between basic research and clinical applications with particular attention to populations, through a unique design in a research-friendly setting. LifeGene is designed both as a prospective cohort study and an infrastructure with repeated contacts of study participants approximately every 5 years. Index persons aged 18-45 years old will be recruited and invited to include their household members (partner and any children). A comprehensive questionnaire addressing cutting-edge research questions will be administered through the web with short follow-ups annually. Biosamples and physical measurements will also be collected at baseline, and re-administered every 5 years thereafter. Event-based sampling will be a key feature of LifeGene. The household-based design will give the opportunity to involve young couples prior to and during pregnancy, allowing for the first study of children born into cohort with complete pre-and perinatal data from both the mother and father. Questions and sampling schemes will be tailored to the participants' age and life events. The target of LifeGene is to enroll 500,000 Swedes and follow them longitudinally for at least 20 years.Stockholm County CouncilVetenskapsrådetKarolinska InstitutetTorsten and Ragnar Söderbergs FoundationAFA FörsäkringarManuscrip

Intrinsic molecular signature of breast cancer in a population-based cohort of 412 patients

BACKGROUND: Molecular markers and the rich biological information they contain have great potential for cancer diagnosis, prognostication and therapy prediction. So far, however, they have not superseded routine histopathology and staging criteria, partly because the few studies performed on molecular subtyping have had little validation and limited clinical characterization. METHODS: We obtained gene expression and clinical data for 412 breast cancers obtained from population-based cohorts of patients from Stockholm and Uppsala, Sweden. Using the intrinsic set of approximately 500 genes derived in the Norway/Stanford breast cancer data, we validated the existence of five molecular subtypes – basal-like, ERBB2, luminal A/B and normal-like – and characterized these subtypes extensively with the use of conventional clinical variables. RESULTS: We found an overall 77.5% concordance between the centroid prediction of the Swedish cohort by using the Norway/Stanford signature and the k-means clustering performed internally within the Swedish cohort. The highest rate of discordant assignments occurred between the luminal A and luminal B subtypes and between the luminal B and ERBB2 subtypes. The subtypes varied significantly in terms of grade (p < 0.001), p53 mutation (p < 0.001) and genomic instability (p = 0.01), but surprisingly there was little difference in lymph-node metastasis (p = 0.31). Furthermore, current users of hormone-replacement therapy were strikingly over-represented in the normal-like subgroup (p < 0.001). Separate analyses of the patients who received endocrine therapy and those who did not receive any adjuvant therapy supported the previous hypothesis that the basal-like subtype responded to adjuvant treatment, whereas the ERBB2 and luminal B subtypes were poor responders. CONCLUSION: We found that the intrinsic molecular subtypes of breast cancer are broadly present in a diverse collection of patients from a population-based cohort in Sweden. The intrinsic gene set, originally selected to reveal stable tumor characteristics, was shown to have a strong correlation with progression-related properties such as grade, p53 mutation and genomic instability