Human Cortical Traveling Waves: Dynamical Properties and Correlations with Responses

The spatiotemporal behavior of human EEG oscillations is investigated. Traveling waves in the alpha and theta ranges are found to be common in both prestimulus and poststimulus EEG activity. The dynamical properties of these waves, including their speeds, directions, and durations, are systematically characterized for the first time, and the results show that there are significant changes of prestimulus spontaneous waves in the presence of an external stimulus. Furthermore, the functional relevance of these waves is examined by studying how they are correlated with reaction times on a single trial basis; prestimulus alpha waves traveling in the frontal-to-occipital direction are found to be most correlated to reaction speeds. These findings suggest that propagating waves of brain oscillations might be involved in mediating long-range interactions between widely distributed parts of human cortex

Predictive value of cell-surface markers in infections in critically ill patients: protocol for an observational study (ImmuNe FailurE in Critical Therapy (INFECT) Study).

INTRODUCTION: Critically ill patients are at high risk of nosocomial infections, with between 20% and 40% of patients admitted to the intensive care unit (ICU) acquiring infections. These infections result in increased antibiotic use, and are associated with morbidity and mortality. Although critical illness is classically associated with hyperinflammation, the high rates of nosocomial infection argue for an importance of effect of impaired immunity. Our group recently demonstrated that a combination of 3 measures of immune cell function (namely neutrophil CD88, monocyte HLA-DR and % regulatory T cells) identified a patient population with a 2.4-5-fold greater risk for susceptibility to nosocomial infections. METHODS AND ANALYSIS: This is a prospective, observational study to determine whether previously identified markers of susceptibility to nosocomial infection can be validated in a multicentre population, as well as testing several novel markers which may improve the risk of nosocomial infection prediction. Blood samples from critically ill patients (those admitted to the ICU for at least 48 hours and requiring mechanical ventilation alone or support of 2 or more organ systems) are taken and undergo whole blood staining for a range of immune cell surface markers. These samples undergo analysis on a standardised flow cytometry platform. Patients are followed up to determine whether they develop nosocomial infection. Infections need to meet strict prespecified criteria based on international guidelines; where these criteria are not met, an adjudication panel of experienced intensivists is asked to rule on the presence of infection. Secondary outcomes will be death from severe infection (sepsis) and change in organ failure. ETHICS AND DISSEMINATION: Ethical approval including the involvement of adults lacking capacity has been obtained from respective English and Scottish Ethics Committees. Results will be disseminated through presentations at scientific meetings and publications in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT02186522; Pre-results.Innovate UK (formerly Technology Strategy Board) (Grant ID: 15457-108136), Becton Dickinson bioscience, NHS Lothian via the Edinburgh Health Services Research Unit, National Institute of Academic AnaesthesiaThis is the final version of the article. It first appeared from BMJ Publishing Group via http://dx.doi.org/10.1136/bmjopen-2016-01132

Cell-surface signatures of immune dysfunction risk-stratify critically ill patients: INFECT study.

PURPOSE: Cellular immune dysfunctions, which are common in intensive care patients, predict a number of significant complications. In order to effectively target treatments, clinically applicable measures need to be developed to detect dysfunction. The objective was to confirm the ability of cellular markers associated with immune dysfunction to stratify risk of secondary infection in critically ill patients. METHODS: Multi-centre, prospective observational cohort study of critically ill patients in four UK intensive care units. Serial blood samples were taken, and three cell surface markers associated with immune cell dysfunction [neutrophil CD88, monocyte human leucocyte antigen-DR (HLA-DR) and percentage of regulatory T cells (Tregs)] were assayed on-site using standardized flow cytometric measures. Patients were followed up for the development of secondary infections. RESULTS: A total of 148 patients were recruited, with data available from 138. Reduced neutrophil CD88, reduced monocyte HLA-DR and elevated proportions of Tregs were all associated with subsequent development of infection with odds ratios (95% CI) of 2.18 (1.00-4.74), 3.44 (1.58-7.47) and 2.41 (1.14-5.11), respectively. Burden of immune dysfunction predicted a progressive increase in risk of infection, from 14% for patients with no dysfunction to 59% for patients with dysfunction of all three markers. The tests failed to risk stratify patients shortly after ICU admission but were effective between days 3 and 9. CONCLUSIONS: This study confirms our previous findings that three cell surface markers can predict risk of subsequent secondary infection, demonstrates the feasibility of standardized multisite flow cytometry and presents a tool which can be used to target future immunomodulatory therapies. TRIAL REGISTRATION: The study was registered with clinicaltrials.gov (NCT02186522).The study was funded by Innovate UK (Sepsis 2: 101193), BD Biosciences and the National Institute for Academic Anaesthesia. Dr Conway Morris is supported by a Clinical Research Career Development Fellowship from the Wellcome Trust (WT 2055214/Z/16/Z). Dr Shankar-Hari is supported by the National Institute for Health Research Clinician Scientist Award (CS-2016-16- 011)

Early PREdiction of sepsis using leukocyte surface biomarkers: the ExPRES-sepsis cohort study.

PURPOSE: Reliable biomarkers for predicting subsequent sepsis among patients with suspected acute infection are lacking. In patients presenting to emergency departments (EDs) with suspected acute infection, we aimed to evaluate the reliability and discriminant ability of 47 leukocyte biomarkers as predictors of sepsis (Sequential Organ Failure Assessment score ≥ 2 at 24 h and/or 72 h following ED presentation). METHODS: In a multi-centre cohort study in four EDs and intensive care units (ICUs), we standardised flow-cytometric leukocyte biomarker measurement and compared patients with suspected acute infection (cohort-1) with two comparator cohorts: ICU patients with established sepsis (cohort-2), and ED patients without infection or systemic inflammation but requiring hospitalization (cohort-3). RESULTS: Between January 2014 and February 2016, we recruited 272, 59 and 75 patients to cohorts 1, 2, and 3, respectively. Of 47 leukocyte biomarkers, 14 were non-reliable, and 17 did not discriminate between the three cohorts. Discriminant analyses for predicting sepsis within cohort-1 were undertaken for eight neutrophil (cluster of differentiation antigens (CD) CD15; CD24; CD35; CD64; CD312; CD11b; CD274; CD279), seven monocyte (CD35; CD64; CD312; CD11b; HLA-DR; CD274; CD279) and a CD8 T-lymphocyte biomarker (CD279). Individually, only higher neutrophil CD279 [OR 1.78 (95% CI 1.23-2.57); P = 0.002], higher monocyte CD279 [1.32 (1.03-1.70); P = 0.03], and lower monocyte HLA-DR [0.73 (0.55-0.97); P = 0.03] expression were associated with subsequent sepsis. With logistic regression the optimum biomarker combination was increased neutrophil CD24 and neutrophil CD279, and reduced monocyte HLA-DR expression, but no combination had clinically relevant predictive validity. CONCLUSIONS: From a large panel of leukocyte biomarkers, immunosuppression biomarkers were associated with subsequent sepsis in ED patients with suspected acute infection. CLINICAL TRIAL REGISTRATION: NCT02188992.The study was funded by Innovate UK (Sepsis 2: 101193). Dr Shankar-Hari is supported by the National Institute for Health Research Clinician Scientist Award (CS-2016-16-011). Dr Conway Morris is supported by a Clinical Research Career Development Fellowship from the Wellcome Trust (WT 2055214/Z/16/Z)

COMAP Early Science: VII. Prospects for CO Intensity Mapping at Reionization

We introduce COMAP-EoR, the next generation of the Carbon Monoxide Mapping Array Project aimed at extending CO intensity mapping to the Epoch of Reionization. COMAP-EoR supplements the existing 30 GHz COMAP Pathfinder with two additional 30 GHz instruments and a new 16 GHz receiver. This combination of frequencies will be able to simultaneously map CO(1--0) and CO(2--1) at reionization redshifts ($z\sim5-8$) in addition to providing a significant boost to the $z\sim3$ sensitivity of the Pathfinder. We examine a set of existing models of the EoR CO signal, and find power spectra spanning several orders of magnitude, highlighting our extreme ignorance about this period of cosmic history and the value of the COMAP-EoR measurement. We carry out the most detailed forecast to date of an intensity mapping cross-correlation, and find that five out of the six models we consider yield signal to noise ratios (S/N) $\gtrsim20$ for COMAP-EoR, with the brightest reaching a S/N above 400. We show that, for these models, COMAP-EoR can make a detailed measurement of the cosmic molecular gas history from $z\sim2-8$, as well as probe the population of faint, star-forming galaxies predicted by these models to be undetectable by traditional surveys. We show that, for the single model that does not predict numerous faint emitters, a COMAP-EoR-type measurement is required to rule out their existence. We briefly explore prospects for a third-generation Expanded Reionization Array (COMAP-ERA) capable of detecting the faintest models and characterizing the brightest signals in extreme detail.Comment: Paper 7 of 7 in series. 19 pages, 10 figures, to be submitted to Ap

COMAP Early Science: VI. A First Look at the COMAP Galactic Plane Survey

We present early results from the COMAP Galactic Plane Survey conducted between June 2019 and April 2021, spanning $20^\circ<\ell<40^\circ$ in Galactic longitude and |b|<1.\!\!^{\circ}5 in Galactic latitude with an angular resolution of $4.5^{\prime}$. The full survey will span $\ell \sim 20^{\circ}$- $220^{\circ}$ and will be the first large-scale radio continuum survey at $30$ GHz with sub-degree resolution. We present initial results from the first part of the survey, including diffuse emission and spectral energy distributions (SEDs) of HII regions and supernova remnants. Using low and high frequency surveys to constrain free-free and thermal dust emission contributions, we find evidence of excess flux density at $30\,$GHz in six regions that we interpret as anomalous microwave emission. Furthermore we model UCHII contributions using data from the $5\,$GHz CORNISH catalogue and reject this as the cause of the $30\,$GHz excess. Six known supernova remnants (SNR) are detected at $30\,$GHz, and we measure spectral indices consistent with the literature or show evidence of steepening. The flux density of the SNR W44 at $30\,$GHz is consistent with a power-law extrapolation from lower frequencies with no indication of spectral steepening in contrast with recent results from the Sardinia Radio Telescope. We also extract five hydrogen radio recombination lines to map the warm ionized gas, which can be used to estimate electron temperatures or to constrain continuum free-free emission. The full COMAP Galactic plane survey, to be released in 2023/2024, will be an invaluable resource for Galactic astrophysics.Comment: Paper 6 of 7 in series. 28 pages, 10 figures, submitted to Ap

COMAP Early Science: IV. Power Spectrum Methodology and Results

We present the power spectrum methodology used for the first-season COMAP analysis, and assess the quality of the current data set. The main results are derived through the Feed-feed Pseudo-Cross-Spectrum (FPXS) method, which is a robust estimator with respect to both noise modeling errors and experimental systematics. We use effective transfer functions to take into account the effects of instrumental beam smoothing and various filter operations applied during the low-level data processing. The power spectra estimated in this way have allowed us to identify a systematic error associated with one of our two scanning strategies, believed to be due to residual ground or atmospheric contamination. We omit these data from our analysis and no longer use this scanning technique for observations. We present the power spectra from our first season of observing and demonstrate that the uncertainties are integrating as expected for uncorrelated noise, with any residual systematics suppressed to a level below the noise. Using the FPXS method, and combining data on scales $k=0.051-0.62 \,\mathrm{Mpc}^{-1}$ we estimate $P_\mathrm{CO}(k) = -2.7 \pm 1.7 \times 10^4\mu\textrm{K}^2\mathrm{Mpc}^3$, the first direct 3D constraint on the clustering component of the CO(1-0) power spectrum in the literature.Comment: Paper 4 of 7 in series. 18 pages, 11 figures, as accepted in Ap

COMAP Early Science: III. CO Data Processing

We describe the first season COMAP analysis pipeline that converts raw detector readouts to calibrated sky maps. This pipeline implements four main steps: gain calibration, filtering, data selection, and map-making. Absolute gain calibration relies on a combination of instrumental and astrophysical sources, while relative gain calibration exploits real-time total-power variations. High efficiency filtering is achieved through spectroscopic common-mode rejection within and across receivers, resulting in nearly uncorrelated white noise within single-frequency channels. Consequently, near-optimal but biased maps are produced by binning the filtered time stream into pixelized maps; the corresponding signal bias transfer function is estimated through simulations. Data selection is performed automatically through a series of goodness-of-fit statistics, including $\chi^2$ and multi-scale correlation tests. Applying this pipeline to the first-season COMAP data, we produce a dataset with very low levels of correlated noise. We find that one of our two scanning strategies (the Lissajous type) is sensitive to residual instrumental systematics. As a result, we no longer use this type of scan and exclude data taken this way from our Season 1 power spectrum estimates. We perform a careful analysis of our data processing and observing efficiencies and take account of planned improvements to estimate our future performance. Power spectrum results derived from the first-season COMAP maps are presented and discussed in companion papers.Comment: Paper 3 of 7 in series. 26 pages, 23 figures, submitted to Ap

COMAP Early Science: V. Constraints and Forecasts at z∼3z \sim 3

We present the current state of models for the $z\sim3$ carbon monoxide (CO) line-intensity signal targeted by the CO Mapping Array Project (COMAP) Pathfinder in the context of its early science results. Our fiducial model, relating dark matter halo properties to CO luminosities, informs parameter priors with empirical models of the galaxy-halo connection and previous CO(1-0) observations. The Pathfinder early science data spanning wavenumbers $k=0.051$-$0.62\,$Mpc$^{-1}$ represent the first direct 3D constraint on the clustering component of the CO(1-0) power spectrum. Our 95% upper limit on the redshift-space clustering amplitude $A_{\rm clust}\lesssim70\,\mu$K$^2$ greatly improves on the indirect upper limit of $420\,\mu$K$^2$ reported from the CO Power Spectrum Survey (COPSS) measurement at $k\sim1\,$Mpc$^{-1}$. The COMAP limit excludes a subset of models from previous literature, and constrains interpretation of the COPSS results, demonstrating the complementary nature of COMAP and interferometric CO surveys. Using line bias expectations from our priors, we also constrain the squared mean line intensity-bias product, $\langle{Tb}\rangle^2\lesssim50\,\mu$K$^2$, and the cosmic molecular gas density, $\rho_\text{H2}<2.5\times10^8\,M_\odot\,$Mpc$^{-3}$ (95% upper limits). Based on early instrument performance and our current CO signal estimates, we forecast that the five-year Pathfinder campaign will detect the CO power spectrum with overall signal-to-noise of 9-17. Between then and now, we also expect to detect the CO-galaxy cross-spectrum using overlapping galaxy survey data, enabling enhanced inferences of cosmic star-formation and galaxy-evolution history.Comment: Paper 5 of 7 in series. 17 pages + appendix and bibliography (30 pages total); 15 figures, 6 tables; accepted for publication in ApJ; v3 reflects the accepted version with minor changes and additions to tex

COMAP Early Science: II. Pathfinder Instrument

Line intensity mapping (LIM) is a new technique for tracing the global properties of galaxies over cosmic time. Detection of the very faint signals from redshifted carbon monoxide (CO), a tracer of star formation, pushes the limits of what is feasible with a total-power instrument. The CO Mapping Project (COMAP) Pathfinder is a first-generation instrument aiming to prove the concept and develop the technology for future experiments, as well as delivering early science products. With 19 receiver channels in a hexagonal focal plane arrangement on a 10.4 m antenna, and an instantaneous 26-34 GHz frequency range with 2 MHz resolution, it is ideally suited to measuring CO($J$=1-0) from $z\sim3$. In this paper we discuss strategies for designing and building the Pathfinder and the challenges that were encountered. The design of the instrument prioritized LIM requirements over those of ancillary science. After a couple of years of operation, the instrument is well understood, and the first year of data is already yielding useful science results. Experience with this Pathfinder will drive the design of the next generations of experiments.Comment: Paper 2 of 7 in series. 27 pages, 28 figures, submitted to Ap