High pressure evolution of Fe2_{2}O3_{3} electronic structure revealed by X-ray absorption

We report the first high pressure measurement of the Fe K-edge in hematite (Fe$_2$O$_3$) by X-ray absorption spectroscopy in partial fluorescence yield geometry. The pressure-induced evolution of the electronic structure as Fe$_2$O$_3$ transforms from a high-spin insulator to a low-spin metal is reflected in the x-ray absorption pre-edge. The crystal field splitting energy was found to increase monotonically with pressure up to 48 GPa, above which a series of phase transitions occur. Atomic multiplet, cluster diagonalization, and density-functional calculations were performed to simulate the pre-edge absorption spectra, showing good qualitative agreement with the measurements. The mechanism for the pressure-induced phase transitions of Fe$_2$O$_3$ is discussed and it is shown that ligand hybridization significantly reduces the critical high-spin/low-spin pressure.Comment: 5 pages, 4 figures and 1 tabl

Association of CD40 with rheumatoid arthritis confirmed in a large UK case-control study

OBJECTIVE: A recent meta-analysis of published genome-wide association studies (GWAS) in populations of European descent reported novel associations of markers mapping to the CD40, CCL21 and CDK6 genes with rheumatoid arthritis (RA) susceptibility while a large-scale, case-control association study in a Japanese population identified association with multiple single nucleotide polymorphisms (SNPs) in the CD244 gene. The aim of the current study was to validate these potential RA susceptibility markers in a UK population. METHODS: A total of 4 SNPs (rs4810485 in CD40, rs2812378 in CCL21, rs42041 in CDK6 and rs6682654 in CD244) were genotyped in a UK cohort comprising 3962 UK patients with RA and 3531 healthy controls using the Sequenom iPlex platform. Genotype counts in patients and controls were analysed with the chi(2) test using Stata. RESULTS: Association to the CD40 gene was robustly replicated (p=2 x 10(-4), OR 0.86, 95% CI 0.79 to 0.93) and modest evidence was found for association with the CCL21 locus (p=0.04, OR 1.08, 95% CI 1.01 to 1.16). However, there was no evidence for association of rs42041 (CDK6) and rs6682654 (CD244) with RA susceptibility in this UK population. Following a meta-analysis including the original data, association to CD40 was confirmed (p=7.8 x 10(-8), OR 0.87 (95% CI 0.83 to 0.92). CONCLUSION: In this large UK cohort, strong association of the CD40 gene with susceptibility to RA was found, and weaker evidence for association with RA in the CCL21 locus

PADI4 genotype is not associated with rheumatoid arthritis in a large UK Caucasian population

BACKGROUND: Polymorphisms of the peptidylarginine deiminase type 4 (PADI4) gene confer susceptibility to rheumatoid arthritis (RA) in East Asian people. However, studies in European populations have produced conflicting results. This study explored the association of the PADI4 genotype with RA in a large UK Caucasian population. METHODS: The PADI4_94 (rs2240340) single nucleotide polymorphism (SNP) was directly genotyped in a cohort of unrelated UK Caucasian patients with RA (n=3732) and population controls (n=3039). Imputed data from the Wellcome Trust Case Control Consortium (WTCCC) was used to investigate the association of PADI4_94 with RA in an independent group of RA cases (n=1859) and controls (n=10 599). A further 56 SNPs spanning the PADI4 gene were investigated for association with RA using data from the WTCCC study. RESULTS: The PADI4_94 genotype was not associated with RA in either the present cohort or the WTCCC cohort. Combined analysis of all the cases of RA (n=5591) and controls (n=13 638) gave an overall OR of 1.01 (95% CI 0.96 to 1.05, p=0.72). No association with anti-CCP antibodies and no interaction with either shared epitope or PTPN22 was detected. No evidence for association with RA was identified for any of the PADI4 SNPs investigated. Meta-analysis of previously published studies and our data confirmed no significant association between the PADI4_94 genotype and RA in people of European descent (OR 1.06, 95% CI 0.99 to 1.13, p=0.12). CONCLUSION: In the largest study performed to date, the PADI4 genotype was not a significant risk factor for RA in people of European ancestry, in contrast to Asian populations

Overlapping genetic susceptibility variants between three autoimmune disorders: rheumatoid arthritis, type 1 diabetes and coeliac disease

INTRODUCTION: Genome wide association studies, replicated by numerous well powered validation studies, have revealed a large number of loci likely to play a role in susceptibility to many multifactorial diseases. It is now well established that some of these loci are shared between diseases with similar aetiology. For example, a number of autoimmune diseases have been associated with variants in the PTPN22, TNFAIP3 and CTLA4 genes. Here we have attempted to define overlapping genetic variants between rheumatoid arthritis (RA), type 1 diabetes (T1D) and coeliac disease (CeD). METHODS: We selected eight SNPs previously identified as being associated with CeD and six T1D-associated SNPs for validation in a sample of 3,962 RA patients and 3,531 controls. Genotyping was performed using the Sequenom MassArray platform and comparison of genotype and allele frequencies between cases and controls was undertaken. A trend test P-value < 0.004 was regarded as significant. RESULTS: We found statistically significant evidence for association of the TAGAP locus with RA (P = 5.0 × 10-4). A marker at one other locus, C1QTNF6, previously associated with T1D, showed nominal association with RA in the current study but did not remain statistically significant at the corrected threshold. CONCLUSIONS: In exploring the overlap between T1D, CeD and RA, there is strong evidence that variation within the TAGAP gene is associated with all three autoimmune diseases. Interestingly a number of loci appear to be specific to one of the three diseases currently studied suggesting that they may play a role in determining the particular autoimmune phenotype at presentation

Study of the common genetic background for rheumatoid arthritis and systemic lupus erythematosus

BACKGROUND: Evidence is beginning to emerge that there may be susceptibility loci for rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) that are common to both diseases. OBJECTIVE: To investigate single nucleotide polymorphisms that have been reported to be associated with SLE in a UK cohort of patients with RA and controls. METHODS: 3962 patients with RA and 9275 controls were included in the study. Eleven SNPs mapping to confirmed SLE loci were investigated. These mapped to the TNFSF4, BANK1, TNIP1, PTTG1, UHRF1BP1, ATG5, JAZF1, BLK, KIAA1542, ITGAM and UBE2L3 loci. Genotype frequencies were compared between patients with RA and controls using the trend test. RESULTS: The SNPs mapping to the BLK and UBE2L3 loci showed significant evidence for association with RA. Two other SNPs, mapping to ATG5 and KIAA1542, showed nominal evidence for association with RA (p=0.02 and p=0.02, respectively) but these were not significant after applying a Bonferroni correction. Additionally, a significant global enrichment in carriage of SLE alleles in patients with RA compared with controls (p=9.1×10(-7)) was found. Meta-analysis of this and previous studies confirmed the association of the BLK and UBE2L3 gene with RA at genome-wide significance levels (p<5×10(-8)). Together, the authors estimate that the SLE and RA overlapping loci, excluding HLA-DRB1 alleles, identified so far explain ∼5.8% of the genetic susceptibility to RA as a whole. CONCLUSION: The findings confirm the association of the BLK and UBE2L3 loci with RA, thus adding to the list of loci showing overlap between RA and SLE

Eumycetoma causative agents:A systematic review to inform the World Health Organization priority list of fungal pathogens

The World Health Organization, in response to the growing burden of fungal disease, established a process to develop a fungal priority pathogens list. This systematic review aimed to evaluate the epidemiology and impact of eumycetoma. PubMed and Web of Science were searched to identify studies published between 1 January 2011 and 19 February 2021. Studies reporting on mortality, inpatient care, complications and sequelae, antifungal susceptibility, risk factors, preventability, annual incidence, global distribution, and emergence during the study time frames were selected. Overall, 14 studies were eligible for inclusion. Morbidity was frequent with moderate to severe impairment of quality of life in 60.3%, amputation in up to 38.5%, and recurrent or long-term disease in 31.8%-73.5% of patients. Potential risk factors included male gender (56.6%-79.6%), younger age (11-30 years; 64%), and farming occupation (62.1%-69.7%). Mycetoma was predominantly reported in Sudan, particularly in central Sudan (37%-76.6% of cases). An annual incidence of 0.1/100 000 persons and 0.32/100  000 persons/decade was reported in the Philippines and Uganda, respectively. In Uganda, a decline in incidence from 3.37 to 0.32/100  000 persons between two consecutive 10-year periods (2000-2009 and 2010-2019) was detected. A community-based, multi-pronged prevention programme was associated with a reduction in amputation rates from 62.8% to 11.9%. With the pre-specified criteria, no studies of antifungal drug susceptibility, mortality, and hospital lengths of stay were identified. Future research should include larger cohort studies, greater drug susceptibility testing, and global surveillance to develop evidence-based treatment guidelines and to determine more accurately the incidence and trends over time.</p

Reproducibility of the mfERG between instruments

Purpose First, to examine both the reproducibility of the multifocal electroretinogram (mfERG) recorded on different versions of the same instrument, and the repeatability of the mfERG recorded on a single instrument using two different amplifiers. Second, to demonstrate a means by which multicenter and longitudinal studies that use more than one recording instrument can compare and combine data effectively. Methods Three different amplifiers and two mfERG setups, one using VERIS™ 4.3 software (mfERG1) and another using VERIS™ Pro 5.2 software (mfERG2), were evaluated. A total of 73 subjects with normal vision were tested in three groups. Group 1 (n = 42) was recorded using two amplifiers in parallel on mfERG1. Group 2 (n = 52) was recorded on mfERG2 using a single amplifier. Group 3 was a subgroup of 21 subjects from groups 1 and 2 that were tested sequentially on both instruments. A fourth group of 26 subjects with diabetes were also recorded using the two parallel amplifiers on mfERG1. P1 implicit times and N1-P1 amplitudes of the 103 local first order mfERGs were measured, and the differences between the instruments and amplifiers were evaluated as raw scores and Z-scores based on normative data. Measurements of individual responses and measurements averaged over the 103 responses were analyzed. Results Simultaneous recordings made on mfERG1 with the two different amplifiers showed differences in implicit times but similar amplitudes. There was a mean implicit time difference of 2.5 ms between the amplifiers but conversion to Z-scores improved their agreement. Recordings made on different days with the two instruments produced similar but more variable results, with amplitudes differing between them more than implicit times. For local response implicit times, the 95% confidence interval of the difference between instruments was approximately ±1 Z-score (±0.9 ms) in either direction. For local response amplitude, it was approximately ±1.6 Z-scores (±0.3 μV). Conclusions Different amplifiers can yield quite different mfERG P1 implicit times, even with identical band-pass settings. However, the reproducibility of mfERG Z-scores across recording instrumentation is relatively high. Comparison of data across systems and laboratories, necessary for multicenter or longitudinal investigations, is facilitated if raw data are converted into Z-scores based on normative data

Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations

Abstract Background Directed acyclic graphs (DAGs) are an increasingly popular approach for identifying confounding variables that require conditioning when estimating causal effects. This review examined the use of DAGs in applied health research to inform recommendations for improving their transparency and utility in future research. Methods Original health research articles published during 1999–2017 mentioning ‘directed acyclic graphs’ (or similar) or citing DAGitty were identified from Scopus, Web of Science, Medline and Embase. Data were extracted on the reporting of: estimands, DAGs and adjustment sets, alongside the characteristics of each article’s largest DAG. Results A total of 234 articles were identified that reported using DAGs. A fifth (n = 48, 21%) reported their target estimand(s) and half (n = 115, 48%) reported the adjustment set(s) implied by their DAG(s). Two-thirds of the articles (n = 144, 62%) made at least one DAG available. DAGs varied in size but averaged 12 nodes [interquartile range (IQR): 9–16, range: 3–28] and 29 arcs (IQR: 19–42, range: 3–99). The median saturation (i.e. percentage of total possible arcs) was 46% (IQR: 31–67, range: 12–100). 37% (n = 53) of the DAGs included unobserved variables, 17% (n = 25) included ‘super-nodes’ (i.e. nodes containing more than one variable) and 34% (n = 49) were visually arranged so that the constituent arcs flowed in the same direction (e.g. top-to-bottom). Conclusion There is substantial variation in the use and reporting of DAGs in applied health research. Although this partly reflects their flexibility, it also highlights some potential areas for improvement. This review hence offers several recommendations to improve the reporting and use of DAGs in future research

Investigating the viability of genetic screening/testing for RA susceptibility using combinations of five confirmed risk loci

Objective. Five loci—the shared epitope (SE) of HLA-DRB1, the PTPN22 gene, a locus on 6q23, the STAT4 gene and a locus mapping to the TRAF1/C5 genetic region—have now been unequivocally confirmed as conferring susceptibility to RA. The largest single effect is conferred by SE. We hypothesized that combinations of susceptibility alleles may increase risk over and above that of any individual locus alone