An improved method for measuring muon energy using the truncated mean of dE/dx

The measurement of muon energy is critical for many analyses in large Cherenkov detectors, particularly those that involve separating extraterrestrial neutrinos from the atmospheric neutrino background. Muon energy has traditionally been determined by measuring the specific energy loss (dE/dx) along the muon's path and relating the dE/dx to the muon energy. Because high-energy muons (E_mu > 1 TeV) lose energy randomly, the spread in dE/dx values is quite large, leading to a typical energy resolution of 0.29 in log10(E_mu) for a muon observed over a 1 km path length in the IceCube detector. In this paper, we present an improved method that uses a truncated mean and other techniques to determine the muon energy. The muon track is divided into separate segments with individual dE/dx values. The elimination of segments with the highest dE/dx results in an overall dE/dx that is more closely correlated to the muon energy. This method results in an energy resolution of 0.22 in log10(E_mu), which gives a 26% improvement. This technique is applicable to any large water or ice detector and potentially to large scintillator or liquid argon detectors.Comment: 12 pages, 16 figure

All-particle cosmic ray energy spectrum measured with 26 IceTop stations

We report on a measurement of the cosmic ray energy spectrum with the IceTop air shower array, the surface component of the IceCube Neutrino Observatory at the South Pole. The data used in this analysis were taken between June and October, 2007, with 26 surface stations operational at that time, corresponding to about one third of the final array. The fiducial area used in this analysis was 0.122 km^2. The analysis investigated the energy spectrum from 1 to 100 PeV measured for three different zenith angle ranges between 0{\deg} and 46{\deg}. Because of the isotropy of cosmic rays in this energy range the spectra from all zenith angle intervals have to agree. The cosmic-ray energy spectrum was determined under different assumptions on the primary mass composition. Good agreement of spectra in the three zenith angle ranges was found for the assumption of pure proton and a simple two-component model. For zenith angles {\theta} < 30{\deg}, where the mass dependence is smallest, the knee in the cosmic ray energy spectrum was observed between 3.5 and 4.32 PeV, depending on composition assumption. Spectral indices above the knee range from -3.08 to -3.11 depending on primary mass composition assumption. Moreover, an indication of a flattening of the spectrum above 22 PeV were observed.Comment: 38 pages, 17 figure

Population Genomics Related to Adaptation in Elite Oat Germplasm

Six hundred thirty five oat ( L.) lines and 4561 single-nucleotide polymorphism (SNP) loci were used to evaluate population structure, linkage disequilibrium (LD), and genotype–phenotype association with heading date. The first five principal components (PCs) accounted for 25.3% of genetic variation. Neither the eigenvalues of the first 25 PCs nor the cross-validation errors from = 1 to 20 model-based analyses suggested a structured population. However, the PC and = 2 model-based analyses supported clustering of lines on spring oat vs. southern United States origin, accounting for 16% of genetic variation ( < 0.0001). Single-locus -statistic () in the highest 1% of the distribution suggested linkage groups that may be differentiated between the two population subgroups. Population structure and kinship-corrected LD of = 0.10 was observed at an average pairwise distance of 0.44 cM (0.71 and 2.64 cM within spring and southern oat, respectively). On most linkage groups LD decay was slower within southern lines than within the spring lines. A notable exception was found on linkage group Mrg28, where LD decay was substantially slower in the spring subpopulation. It is speculated that this may be caused by a heterogeneous translocation event on this chromosome. Association with heading date was most consistent across location-years on linkage groups Mrg02, Mrg12, Mrg13, and Mrg24

Refining and regaining skills in fixation/diversification stage performers: The Five-A Model

Technical change is one of many factors underpinning success in elite, fixation/diversification stage performers. Surprisingly, however, there is a dearth of research pertaining to this process or the most efficacious methods used to bring about such a change. In this paper we highlight the emergent processes, yet also the lack in mechanistic comprehension surrounding technical change, addressing issues within the motor control, sport psychology, coaching and choking literature. More importantly, we seek an understanding of how these changes can be made more secure to competitive pressure, and how this can be embedded within the process of technical change. Following this review, we propose The Five-A Model based on successful coaching techniques, psychosocial concomitants, the avoidance of choking and principles of effective behaviour change. Specific mechanisms for each stage are discussed, with a focus on the use of holistic rhythm-based cues as a possible way of internalising changes. Finally, we suggest the need for further research to examine these five stages, to aid a more comprehensive construction of the content and delivery of such a programme within the applied setting

Interaction of rheumatoid factor and Entamoeba histolytica

The amoebae's cytotoxicity test and the amoebae's lysis test were used to show possible interactions between rheumatoid factor (RF) and Entamoeba histolytica. Amoebae's cytotoxic activity (ACA) was inhibited by affinity chromatography purified antiamoebae rabbit IgG (RIgG). Enhanced inhibition could be demonstrated with RIgG plus RF. But the same marked inhibition of ACA could be seen when replacing RF by heat inactivated normal human serum as a control. About 50% amoebae's lysis occurred when amoebae were brought together with native normal human serum (NNHS) as a source of complement. Amoebae's lysis increased to 60% when incubated with NHS plus human antiamoebae antibodies. No further augmentation could be obtained by the addition of RF. Using RIgG instead of human antibodies the lysis rate did not increase. Incubation of amoebae, NNHS, RIgG and RF even reduced amoebae's lysis. RF neither has an effect on ACA nor on complement mediated AL in vitro

Para-infectious brain injury in COVID-19 persists at follow-up despite attenuated cytokine and autoantibody responses

To understand neurological complications of COVID-19 better both acutely and for recovery, we measured markers of brain injury, inflammatory mediators, and autoantibodies in 203 hospitalised participants; 111 with acute sera (1–11 days post-admission) and 92 convalescent sera (56 with COVID-19-associated neurological diagnoses). Here we show that compared to 60 uninfected controls, tTau, GFAP, NfL, and UCH-L1 are increased with COVID-19 infection at acute timepoints and NfL and GFAP are significantly higher in participants with neurological complications. Inflammatory mediators (IL-6, IL-12p40, HGF, M-CSF, CCL2, and IL-1RA) are associated with both altered consciousness and markers of brain injury. Autoantibodies are more common in COVID-19 than controls and some (including against MYL7, UCH-L1, and GRIN3B) are more frequent with altered consciousness. Additionally, convalescent participants with neurological complications show elevated GFAP and NfL, unrelated to attenuated systemic inflammatory mediators and to autoantibody responses. Overall, neurological complications of COVID-19 are associated with evidence of neuroglial injury in both acute and late disease and these correlate with dysregulated innate and adaptive immune responses acutely

Delayed mucosal antiviral responses despite robust peripheral inflammation in fatal COVID-19

Background While inflammatory and immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in peripheral blood are extensively described, responses at the upper respiratory mucosal site of initial infection are relatively poorly defined. We sought to identify mucosal cytokine/chemokine signatures that distinguished coronavirus disease 2019 (COVID-19) severity categories, and relate these to disease progression and peripheral inflammation. Methods We measured 35 cytokines and chemokines in nasal samples from 274 patients hospitalized with COVID-19. Analysis considered the timing of sampling during disease, as either the early (0–5 days after symptom onset) or late (6–20 days after symptom onset) phase. Results Patients that survived severe COVID-19 showed interferon (IFN)-dominated mucosal immune responses (IFN-γ, CXCL10, and CXCL13) early in infection. These early mucosal responses were absent in patients who would progress to fatal disease despite equivalent SARS-CoV-2 viral load. Mucosal inflammation in later disease was dominated by interleukin 2 (IL-2), IL-10, IFN-γ, and IL-12p70, which scaled with severity but did not differentiate patients who would survive or succumb to disease. Cytokines and chemokines in the mucosa showed distinctions from responses evident in the peripheral blood, particularly during fatal disease. Conclusions Defective early mucosal antiviral responses anticipate fatal COVID-19 but are not associated with viral load. Early mucosal immune responses may define the trajectory of severe COVID-19

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism