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Measurements of forward neutrons in pp collisions will allow us to investigate π-p cross-section via one-pion exchange process, which are important for air shower development. However, the precision of these measurements is limited by the energy resolution of the LHCf detectors. To improve it, a joint measurement with the ATLAS ZDC was planned. In 2021, a beam test was conducted to evaluate the performance of the joint measurement of the LHCf-Arm1 and ZDC detectors using proton beams of 350 GeV at SPS. Combining the LHCf data with the ZDC data, we confirmed that the energy resolution improved from about 40% to 21.4%.

Abstract Background Wheat yellow (stripe) rust caused by Puccinia striiformis f. sp. tritici (PST) is one of the most devastating diseases of wheat worldwide. To design effective breeding strategies that maximize the potential for durable disease resistance it is important to understand the molecular basis of PST pathogenicity. In particular, the characterisation of the structure, function and evolutionary dynamics of secreted effector proteins that are detected by host immune receptors can help guide and prioritize breeding efforts. However, to date, our knowledge of the effector repertoire of cereal rust pathogens is limited. Results We re-sequenced genomes of four PST isolates from the US and UK to identify effector candidates and relate them to their distinct virulence profiles. First, we assessed SNP frequencies between all isolates, with heterokaryotic SNPs being over tenfold more frequent (5.29 ± 2.23 SNPs/kb) than homokaryotic SNPs (0.41 ± 0.28 SNPs/kb). Next, we implemented a bioinformatics pipeline to integrate genomics, transcriptomics, and effector-focused annotations to identify and classify effector candidates in PST. RNAseq analysis highlighted transcripts encoding secreted proteins that were significantly enriched in haustoria compared to infected tissue. The expression of 22 candidate effector genes was characterised using qRT-PCR, revealing distinct temporal expression patterns during infection in wheat. Lastly, we identified proteins that displayed non-synonymous substitutions specifically between the two UK isolates PST-87/7 and PST-08/21, which differ in virulence to two wheat varieties. By focusing on polymorphic variants enriched in haustoria, we identified five polymorphic effector candidates between PST-87/7 and PST-08/21 among 2,999 secreted proteins. These allelic variants are now a priority for functional validation as virulence/avirulence effectors in the corresponding wheat varieties. Conclusions Integration of genomics, transcriptomics, and effector-directed annotation of PST isolates has enabled us to move beyond the single isolate-directed catalogues of effector proteins and develop a framework for mining effector proteins in closely related isolates and relate these back to their defined virulence profiles. This should ultimately lead to more comprehensive understanding of the PST pathogenesis system, an important first step towards developing more effective surveillance and management strategies for one of the most devastating pathogens of wheat.

Given there are no known studies which have examined multiple lower extremity muscles between different ankle positions during bridging activities, the objective was to assess how employing two different ankle positions (PF versus DF) while performing five common bridging exercises (three bipedal and two unipedal) used in rehabilitation and athletic performance affect core and select lower extremity muscle EMG recruitment. Twenty healthy subjects performed a 5 s isometric hold during five two- and one-leg bridge exercises: (1) on right leg with left knee to chest (1LB-LFlex); (2) on right leg with left knee extended (1LB-LExt); (3) standard two-leg bridge (2LB); (4) two-leg bridge with resistance band around knees (2LB-ABD); and (5) two-leg bridge with ball between knees (2LB-ADD). Surface electromyographic (EMG) data were collected using a Noraxon Telemyo Direct Transmission System from fourteen muscles: (1) three superficial quadriceps (VM, VL, and RF); (2) three hip abductors (TFL, GMED, and GMAX); (3) medial hamstrings (ST) and lateral hamstrings (BF); (4) hip adductors (ADD); (5) erector spinae (ES); (6) latissimus dorsi (LATS); (7) upper rectus abdominis (RA); and (8) external oblique (EO) and internal oblique (IO). EMG data were normalized by maximum voluntary isometric contractions (MVICs). A paired t-test (p < 0.01) was used to assess differences in normalized mean EMG activities between DF and PF for each exercise. EMG activities were significantly greater in DF than PF for the (a) VM, VL, and RF during 1LB-LFlex; (b) ADD during 1LB-LFlex, 1LB-LExt; (c) EO during 1LB-LFlex; and (d) IO during 1LB-LFex. In contrast, EMG activities were significantly greater in PF than DF for ST and BF during all five bridge exercises. Bridging with PF (feet flat) was most effective in recruiting the hamstrings, while bridging with DF (feet up) was most effective in recruiting the quadriceps, hip adductors, and internal and external obliques. [ABSTRACT FROM AUTHOR]

Abstract Background Next-generation sequencing technologies allow researchers to obtain millions of sequence reads in a single experiment. One important use of the technology is the sequencing of small non-coding regulatory RNAs and the identification of the genomic locales from which they originate. Currently, there is a paucity of methods for finding small RNA generative locales. Results We describe and implement an algorithm that can determine small RNA generative locales from high-throughput sequencing data. The algorithm creates a network, or graph, of the small RNAs by creating links between them depending on their proximity on the target genome. For each of the sub-networks in the resulting graph the clustering coefficient, a measure of the interconnectedness of the subnetwork, is used to identify the generative locales. We test the algorithm over a wide range of parameters using RFAM sequences as positive controls and demonstrate that the algorithm has good sensitivity and specificity in a range of Arabidopsis and mouse small RNA sequence sets and that the locales it generates are robust to differences in the choice of parameters. Conclusions NiBLS is a fast, reliable and sensitive method for determining small RNA locales in high-throughput sequence data that is generally applicable to all classes of small RNA.

Abstract Background We have created a software implementation of a published and verified method for assigning probabilities to potential phosphorylation sites on peptides using mass spectrometric data. Our tool, named PhosCalc, determines the number of possible phosphorylation sites and calculates the theoretical masses for the b and y fragment ions of a user-provided peptide sequence. A corresponding user-provided mass spectrum is examined to determine which putative b and y ions have support in the spectrum and a probability score is calculated for each combination of phosphorylation sites. Findings We test the implementation using spectra of phosphopeptides from bovine beta-casein and we compare the results from the implementation to those from manually curated and verified phosphopeptides from our own experiments. We find that the PhosCalc scores are capable of helping a user to identify phosphorylated sites and can remove a bottleneck in high throughput proteomics analyses. Conclusion PhosCalc is available as a web-based interface for examining up to 100 peptides and as a downloadable tool for examining larger numbers of peptides. PhosCalc can be used to speed up identification of phosphorylation sites and can be easily integrated into data handling pipelines making it a very useful tool for those involved in phosphoproteomic research.

Summary: The oomycete pathogen Hyaloperonospora arabidopsidis (Hpa) causes downy mildew disease on Arabidopsis. To colonize its host, Hpa translocates effector proteins that suppress plant immunity into infected host cells. Here, we investigate the relevance of the interaction between one of these effectors, HaRxL106, and Arabidopsis RADICAL‐INDUCED CELL DEATH1 (RCD1). We use pathogen infection assays as well as molecular and biochemical analyses to test the hypothesis that HaRxL106 manipulates RCD1 to attenuate transcriptional activation of defense genes. We report that HaRxL106 suppresses transcriptional activation of salicylic acid (SA)‐induced defense genes and alters plant growth responses to light. HaRxL106‐mediated suppression of immunity is abolished in RCD1 loss‐of‐function mutants. We report that RCD1‐type proteins are phosphorylated, and we identified Mut9‐like kinases (MLKs), which function as phosphoregulatory nodes at the level of photoreceptors, as RCD1‐interacting proteins. An mlk1,3,4 triple mutant exhibits stronger SA‐induced defense marker gene expression compared with wild‐type plants, suggesting that MLKs also affect transcriptional regulation of SA signaling. Based on the combined evidence, we hypothesize that nuclear RCD1/MLK complexes act as signaling nodes that integrate information from environmental cues and pathogen sensors, and that the Arabidopsis downy mildew pathogen targets RCD1 to prevent activation of plant immunity. [ABSTRACT FROM AUTHOR]