Mutations in the histone methyltransferase gene KMT2B cause complex early-onset dystonia.

Histone lysine methylation, mediated by mixed-lineage leukemia (MLL) proteins, is now known to be critical in the regulation of gene expression, genomic stability, cell cycle and nuclear architecture. Despite MLL proteins being postulated as essential for normal development, little is known about the specific functions of the different MLL lysine methyltransferases. Here we report heterozygous variants in the gene KMT2B (also known as MLL4) in 27 unrelated individuals with a complex progressive childhood-onset dystonia, often associated with a typical facial appearance and characteristic brain magnetic resonance imaging findings. Over time, the majority of affected individuals developed prominent cervical, cranial and laryngeal dystonia. Marked clinical benefit, including the restoration of independent ambulation in some cases, was observed following deep brain stimulation (DBS). These findings highlight a clinically recognizable and potentially treatable form of genetic dystonia, demonstrating the crucial role of KMT2B in the physiological control of voluntary movement.Funding for the project was provided by the Wellcome Trust for UK10K (WT091310) and DDD Study. The DDD study presents independent research commissioned by the Health Innovation Challenge Fund [grant number HICF-1009-003] - see www.ddduk.org/access.html for full acknowledgement. This work was supported in part by the Intramural Research Program of the National Human Genome Research Institute and the Common Fund, NIH Office of the Director. This work was supported in part by the German Ministry of Research and Education (grant nos. 01GS08160 and 01GS08167; German Mental Retardation Network) as part of the National Genome Research Network to A.R. and D.W. and by the Deutsche Forschungsgemeinschaft (AB393/2-2) to A.R. Brain expression data was provided by the UK Human Brain Expression Consortium (UKBEC), which comprises John A. Hardy, Mina Ryten, Michael Weale, Daniah Trabzuni, Adaikalavan Ramasamy, Colin Smith and Robert Walker, affiliated with UCL Institute of Neurology (J.H., M.R., D.T.), King’s College London (M.R., M.W., A.R.) and the University of Edinburgh (C.S., R.W.)

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Predicting assemblages and species richness of endemic fish in the upper Yangtze River

The present work describes the ability of two modeling methods, Classification and Regression Tree (CART) and Random Forest (RF), to predict endemic fish assemblages and species richness in the upper Yangtze River, and then to identify the determinant environmental factors contributing to the models. The models included 24 predictor variables and 2 response variables (fish assemblage and species richness) for a total of 46 site units. The predictive quality of the modeling approaches was judged with a leave-one-out validation procedure. There was an average success of 60.9% and 71.7% to assign each site unit to the correct assemblage of fish, and 73% and 84% to explain the variance in species richness, by using CART and RF models, respectively. RF proved to be better than CART in terms of accuracy and efficiency in ecological applications. In any case, the mixed models including both land cover and river characteristic variables were more powerful than either individual one in explaining the endemic fish distribution pattern in the upper Yangtze River. For instance, altitude, slope, length, discharge, runoff, farmland and alpine and sub-alpine meadow played important roles in driving the observed endemic fish assemblage structure, while farmland, slope grassland, discharge, runoff, altitude and drainage area in explaining the observed patterns of endemic species richness. Therefore, the various effects of human activity on natural aquatic ecosystems, in particular, the flow modification of the river and the land use changes may have a considerable effect on the endemic fish distribution patterns on a regional scale. (C) 2010 Elsevier B.V. All rights reserved

Negative bias temperature instability on plasma-nitrided silicon dioxide film

Japanese Journal of Applied Physics, Part 2: Letters413 BL314-L316JAPL

STRUCTURE OF ENDEMIC FISH ASSEMBLAGES IN THE UPPER YANGTZE RIVER BASIN

This study focused on characterizing the endemic fish assemblages in the upper Yangtze River Basin and identifying the relative influences of catchment land-cover variables on observed fish patterns in order to suggest a conservation strategy. A model based on a self-organizing map was applied to determine endemic fish assemblages along the river network, based on presence/absence data for 124 endemic species. Five fish assemblages (Ia, Ib, IIa, IIb1, IIb2) were described. These assemblages varied significantly in terms of individual species patterns as well as species richness. Indicator species were identified for each class of community (0, 3, 9, 27, 0 species for cluster Ia, Ib, IIa, IIb1, IIb2, respectively). Structure of the endemic fish assemblages in the upper Yangtze River was highly correlated with local topographic and geomorphic characteristics. Simultaneously, the catchment land cover features also reflected out this endemic fish distribution structure. Among 18 land-cover types, alpine and sub-alpine meadow, together with farmland, were revealed to be the most important factors both in discriminating the endemic fish assemblages and in correlating species distributions by using discriminant analysis and co-inertia analysis. Finally, in order to preserve the rare and endemic fish in the upper Yangtze River, reserve networks, rather than a single national nature reserve, should be established. Copyright (C) 2009 John Wiley& Sons, Ltd

Anthropometric measures and HbA1c to detect dysglycemia in young Asian women planning conception: The S-PRESTO cohort

10.1038/s41598-020-66147-xScientific Reports10

Author Correction: Anthropometric measures and HbA1c to detect dysglycemia in young Asian women planning conception: The S-PRESTO cohort (Scientific Reports, (2020), 10, 1, (9228), 10.1038/s41598-020-66147-x)

10.1038/s41598-020-69653-0Scientific Reports10

A three gene immunohistochemical panel serves as an adjunct to clinical staging of patients with head and neck cancer

10.18632/oncotarget.18568Oncotarget84579556-7956