Open Futures: an enquiry- and skills- based educational programme developed for primary education and its use in tertiary education

Open Futures is a transforming enquiry-based and skills-based system for education that is central to the curriculum, linking learning and life. It was developed to help children discover and develop practical skills, personal interests and values, which will contribute to their education and help to enhance their adult lives. Open Futures works in partnership with groups of schools in local clusters to develop a bespoke training programme, which extends the existing curriculum and nurtures independent learning through pupil-led approaches to personal learning. Schools benefit from the experience, knowledge and support of like-minded education professionals locally, nationally and internationally. Working with schools and their communities in the UK and India, Open Futures has been running with widespread success for 9 years. It now reaches more than 30,000 children in the UK. There is a body of independent evidence from primary and secondary education showing that both individual strands, as well as the complete Open Futures programme, significantly improve learner outcomes. We now wished to move Open Futures into the tertiary education sector. It was felt that an Open Futures approach to learning and teaching, particularly involving askit, would be beneficial to the community of learners at Central Bedfordshire Further Education College, rated Grade 2 by Ofsted in October 2013. Training has been in three areas so far: Construction, Public Services and Pathways (i.e. Learners with learning difficulties and disabilities). In all cases, there were significant positive impacts for learners and for teachers. As experience with Open Futures develops in the College, it should become clear how such a central enquiry-based and skills-based approach will help learners, and provide evidence for the use of Open Futures in tertiary education that could be used in other tertiary educational institutions

Rapid cell separation with minimal manipulation for autologous cell therapies

The ability to isolate specific, viable cell populations from mixed ensembles with minimal manipulation and within intra-operative time would provide significant advantages for autologous, cell-based therapies in regenerative medicine. Current cell-enrichment technologies are either slow, lack specificity and/or require labelling. Thus a rapid, label-free separation technology that does not affect cell functionality, viability or phenotype is highly desirable. Here, we demonstrate separation of viable from non-viable human stromal cells using remote dielectrophoresis, in which an electric field is coupled into a microfluidic channel using shear-horizontal surface acoustic waves, producing an array of virtual electrodes within the channel. This allows high-throughput dielectrophoretic cell separation in high conductivity, physiological-like fluids, overcoming the limitations of conventional dielectrophoresis. We demonstrate viable/non-viable separation efficacy of > 98% in pre-purified mesenchymal stromal cells, extracted from human dental pulp, with no adverse effects on cell viability, or on their subsequent osteogenic capabilities

Medications that relax the lower oesophageal sphincter and risk of oesophageal cancer : An analysis of two independent population-based databases

Acknowledgements We acknowledge collaboration with the Research Applications and Data Management Team lead by Ms Katie Wilde, University of Aberdeen in conducting our study. This research has been conducted using the UK Bio-bank Resource under application number 34374.Peer reviewedPostprin

Shared genetic risk between major orofacial cleft phenotypes in an African population

Nonsyndromic orofacial clefts (NSOFCs) represent a large proportion (70%–80%) of all OFCs. They can be broadly categorized into nonsyndromic cleft lip with or without cleft palate (NSCL/P) and nonsyndromic cleft palate only (NSCPO). Although NSCL/P and NSCPO are considered etiologically distinct, recent evidence suggests the presence of shared genetic risks. Thus, we investigated the genetic overlap between NSCL/P and NSCPO using African genome-wide association study (GWAS) data on NSOFCs. These data consist of 814 NSCL/P, 205 NSCPO cases, and 2159 unrelated controls. We generated common single-nucleotide variants (SNVs) association summary statistics separately for each phenotype (NSCL/P and NSCPO) under an additive genetic model. Subsequently, we employed the pleiotropic analysis under the composite null (PLACO) method to test for genetic overlap. Our analysis identified two loci with genome-wide significance (rs181737795 [p = 2.58E−08] and rs2221169 [p = 4.5E−08]) and one locus with marginal significance (rs187523265 [p = 5.22E−08]). Using mouse transcriptomics data and information from genetic phenotype databases, we identified MDN1, MAP3k7, KMT2A, ARCN1, and VADC2 as top candidate genes for the associated SNVs. These findings enhance our understanding of genetic variants associated with NSOFCs and identify potential candidate genes for further exploration.</p

Deciphering the complex interplay between pancreatic cancer, diabetes mellitus subtypes and obesity/BMI through causal inference and mediation analyses.

OBJECTIVES: To characterise the association between type 2 diabetes mellitus (T2DM) subtypes (new-onset T2DM (NODM) or long-standing T2DM (LSDM)) and pancreatic cancer (PC) risk, to explore the direction of causation through Mendelian randomisation (MR) analysis and to assess the mediation role of body mass index (BMI). DESIGN: Information about T2DM and related factors was collected from 2018 PC cases and 1540 controls from the PanGenEU (European Study into Digestive Illnesses and Genetics) study. A subset of PC cases and controls had glycated haemoglobin, C-peptide and genotype data. Multivariate logistic regression models were applied to derive ORs and 95% CIs. T2DM and PC-related single nucleotide polymorphism (SNP) were used as instrumental variables (IVs) in bidirectional MR analysis to test for two-way causal associations between PC, NODM and LSDM. Indirect and direct effects of the BMI-T2DM-PC association were further explored using mediation analysis. RESULTS: T2DM was associated with an increased PC risk when compared with non-T2DM (OR=2.50; 95% CI: 2.05 to 3.05), the risk being greater for NODM (OR=6.39; 95% CI: 4.18 to 9.78) and insulin users (OR=3.69; 95% CI: 2.80 to 4.86). The causal association between T2DM (57-SNP IV) and PC was not statistically significant (ORLSDM=1.08, 95% CI: 0.86 to 1.29, ORNODM=1.06, 95% CI: 0.95 to 1.17). In contrast, there was a causal association between PC (40-SNP IV) and NODM (OR=2.85; 95% CI: 2.04 to 3.98), although genetic pleiotropy was present (MR-Egger: p value=0.03). Potential mediating effects of BMI (125-SNPs as IV), particularly in terms of weight loss, were evidenced on the NODM-PC association (indirect effect for BMI in previous years=0.55). CONCLUSION: Findings of this study do not support a causal effect of LSDM on PC, but suggest that PC causes NODM. The interplay between obesity, PC and T2DM is complex

A systems approach identifies time-dependent associations of multimorbidities with pancreatic cancer risk

Background Pancreatic ductal adenocarcinoma (PDAC) is usually diagnosed in late adulthood; therefore, many patients suffer or have suffered from other diseases. Identifying disease patterns associated with PDAC risk may enable a better characterization of high-risk patients. Methods Multimorbidity patterns (MPs) were assessed from 17 self-reported conditions using hierarchical clustering, principal component, and factor analyses in 1705 PDAC cases and 1084 controls from a European population. Their association with PDAC was evaluated using adjusted logistic regression models. Time since diagnosis of morbidities to PDAC diagnosis/recruitment was stratified into recent (<3 years) and long term (≥3 years). The MPs and PDAC genetic networks were explored with DisGeNET bioinformatics-tool which focuses on gene-diseases associations available in curated databases. Results Three MPs were observed: gastric (heartburn, acid regurgitation, Helicobacter pylori infection, and ulcer), metabolic syndrome (obesity, type-2 diabetes, hypercholesterolemia, and hypertension), and atopic (nasal allergies, skin allergies, and asthma). Strong associations with PDAC were observed for ≥2 recently diagnosed gastric conditions [odds ratio (OR), 6.13; 95% confidence interval CI 3.01–12.5)] and for ≥3 recently diagnosed metabolic syndrome conditions (OR, 1.61; 95% CI 1.11–2.35). Atopic conditions were negatively associated with PDAC (high adherence score OR for tertile III, 0.45; 95% CI, 0.36–0.55). Combining type-2 diabetes with gastric MP resulted in higher PDAC risk for recent (OR, 7.89; 95% CI 3.9–16.1) and long-term diagnosed conditions (OR, 1.86; 95% CI 1.29–2.67). A common genetic basis between MPs and PDAC was observed in the bioinformatics analysis. Conclusions Specific multimorbidities aggregate and associate with PDAC in a time-dependent manner. A better characterization of a high-risk population for PDAC may help in the early diagnosis of this cancer. The common genetic basis between MP and PDAC points to a mechanistic link between these conditions