The Ising Susceptibility Scaling Function

We have dramatically extended the zero field susceptibility series at both high and low temperature of the Ising model on the triangular and honeycomb lattices, and used these data and newly available further terms for the square lattice to calculate a number of terms in the scaling function expansion around both the ferromagnetic and, for the square and honeycomb lattices, the antiferromagnetic critical point.Comment: PDFLaTeX, 50 pages, 5 figures, zip file with series coefficients and background data in Maple format provided with the source files. Vs2: Added dedication and made several minor additions and corrections. Vs3: Minor corrections. Vs4: No change to eprint. Added essential square-lattice series input data (used in the calculation) that were removed from University of Melbourne's websit

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Assessment of efficacy of treatment of carious primary molar teeth

The fate of 5,168 carious primary molar teeth from a cohort study of 2,654 children aged ~5 years at baseline undertaken by Cardiff University School of Dentistry in 1999-2003 was investigated

A Competing Risk Survival Analysis Model to Assess the Efficacy of Filling Carious Primary Teeth

In recent years a strategy of selective, symptom-based intervention of carious primary teeth has been developed amongst some British general dental practitioners. Practice-based studies appear to provide evidence that policies of restoration of symptomless carious primary teeth do not confer any significant benefits above those associated with non-restorative care. However, results from these studies contrast with those of many clinical trials and prospective studies of primary molar restorations. In the current investigation, cohort study data from 5,168 carious primary molar teeth from 2,654 British children aged 4–5 years at baseline, augmented with Dental Practice Board treatment data, was utilised to assess the effect of restorative treatment on the likelihood of carious teeth subsequently progressing to either exfoliation or extraction. The effect of demographic and tooth level covariates on the fate of these teeth was also assessed. Multivariate multilevel parametric survival models were applied to the analysis of the carious-exfoliation and carious-extraction transitions to which the teeth were subject, assuming an underlying data hierarchy with teeth nested within individuals. Time of occurrence of caries affected survival experience, with teeth in which caries occurred later in life being associated with higher survival rates to extraction. Amongst filled teeth, later fillings were also associated with higher survival rates to extraction. Demographic and tooth level variables had a limited effect on survival experience. Treatment was found to be significantly associated with survival with respect to extraction, with survival rates of over 80% at 14 years, double those of untreated teeth

Modelling Childhood Caries Using Parametric Competing Risks Survival Analysis Methods for Clustered Data

Caries in primary teeth is an ongoing issue in children’s dental health. Its quantification is affected by clustering of data within children and the concurrent risk of exfoliation of primary teeth. This analysis of caries data of 103,776 primary molar tooth surfaces from a cohort study of 2,654 British children aged 4–5 years at baseline applied multilevel competing risks survival analysis methodology to identify factors significantly associated with caries occurrence in primary tooth surfaces in the presence of the concurrent risk of exfoliation, and assessed the effect of exfoliation on caries development. Multivariate multilevel parametric survival models were applied at surface level to the analysis of the sound-carious and sound-exfoliation transitions to which primary tooth surfaces are subject. Socio-economic class, fluoridation status and surface type were found to be the strongest predictors of primary caries, with the highest rates of occurrence and lowest median survival times associated with occlusal surfaces of children from poor socio-economic class living in non-fluoridated areas. The concurrent risk of exfoliation was shown to reduce the distinction in survival experience between different types of surfaces, and between surfaces of teeth from children of different socio-economic class or fluoridation status. Clustering of data had little effect on inferences of parameter significance