Markov basis and Groebner basis of Segre-Veronese configuration for testing independence in group-wise selections

We consider testing independence in group-wise selections with some restrictions on combinations of choices. We present models for frequency data of selections for which it is easy to perform conditional tests by Markov chain Monte Carlo (MCMC) methods. When the restrictions on the combinations can be described in terms of a Segre-Veronese configuration, an explicit form of a Gr\"obner basis consisting of moves of degree two is readily available for performing a Markov chain. We illustrate our setting with the National Center Test for university entrance examinations in Japan. We also apply our method to testing independence hypotheses involving genotypes at more than one locus or haplotypes of alleles on the same chromosome.Comment: 25 pages, 5 figure

Magnetic Field Stimulated Transitions of Excited States in Fast Muonic Helium Ions

It is shown that one can stimulate, by using the present-day laboratory magnetic fields, transitions between the $lm$ sub-levels of fast $\mu He^+$ ions formating in muon catalyzed fusion. Strong fields also cause the self-ionization from highly excited states of such muonic ions. Both effects are the consequence of the interaction of the bound muon with the oscillating field of the Stark term coupling the center-of-mass and muon motions of the $\mu He^+$ ion due to the non-separability of the collective and internal variables in this system. The performed calculations show a possibility to drive the population of the $lm$ sub-levels by applying a field of a few $Tesla$, which affects the reactivation rate and is especially important to the $K\alpha$ $x$-ray production in muon catalyzed fusion. It is also shown that the $2s-2p$ splitting in $\mu He^+$ due to the vacuum polarization slightly decreases the stimulated transition rates.Comment: 5 figure

Unmet need in rheumatology: reports from the Advances in Targeted Therapies meeting, 2023

The Advances in Targeted Therapies meets annually, convening experts in the field of rheumatology to both provide scientific updates and identify existing scientific gaps within the field. To review the major unmet scientific needs in rheumatology. The 23rd annual Advances in Targeted Therapies meeting convened with more than 100 international basic scientists and clinical researchers in rheumatology, immunology, infectious diseases, epidemiology, molecular biology and other specialties relating to all aspects of immune-mediated inflammatory diseases. We held breakout sessions in five rheumatological disease-specific groups including: rheumatoid arthritis (RA), psoriatic arthritis (PsA), axial spondyloarthritis (axSpa), systemic lupus erythematosus (SLE), systemic sclerosis (SSc) and vasculitis, and osteoarthritis (OA). In each group, experts were asked to identify and prioritise current unmet needs in clinical and translational research. An overarching theme across all disease states is the continued need for clinical trial design innovation with regard to therapeutics, endpoint and disease endotypes. Within RA, unmet needs comprise molecular classification of disease pathogenesis and activity, pre-/early RA strategies, more refined pain profiling and innovative trials designs to deliver on precision medicine. Continued scientific questions within PsA include evaluating the genetic, immunophenotypic, clinical signatures that predict development of PsA in patients with psoriasis, and the evaluation of combination therapies for difficult-to-treat disease. For axSpA, there continues to be the need to understand the role of interleukin-23 (IL-23) in pathogenesis and the genetic relationship of the IL-23-receptor polymorphism with other related systemic inflammatory diseases (eg, inflammatory bowel disease). A major unmet need in the OA field remains the need to develop the ability to reliably phenotype and stratify patients for inclusion in clinical trials. SLE experts identified a number of unmet needs within clinical trial design including the need for allowing endpoints that reflect pharmacodynamic/functional outcomes (eg, inhibition of type I interferon pathway activation; changes in urine biomarkers). Lastly, within SSc and vasculitis, there is a lack of biomarkers that predict response or disease progression, and that allow patients to be stratified for therapies. There remains a strong need to innovate clinical trial design, to identify systemic and tissue-level biomarkers that predict progression or response to therapy, endotype disease, and to continue developing therapies and therapeutic strategies for those with treatment-refractory disease. This document, based on expert consensus, should provide a roadmap for prioritising scientific endeavour in the field of rheumatology.Pathophysiology and treatment of rheumatic disease

Reproducibility in the absence of selective reporting : An illustration from large-scale brain asymmetry research

Altres ajuts: Max Planck Society (Germany).The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes

Demonstrating High-Temperature Superconductivity in the Chemistry Lab through the Meissner Effect

A method to sensitively measure the Meissner effect with a top-loading balance