The Scottish economy [March 1999]

This section presents long and short term forecasts for the quarterly growth rates of Scottish manufacturing (Division D of the 1992 SIC) output

The Scottish economy [January 2000]

This section presents short-term forecasts for the quarterly growth rates of Scottish manufacturing (Division D of the 1992 SIC) output and annual growth rates are also included

Infiltration issues in printed mesoporous carbon perovskite solar cells: a troubleshooting guide

Printed mesoscopic carbon perovskite solar cells (CPSCs) represent a potential frontrunner to perovskite commercialisation due to their inherent stability and easily scaled fabrication methods. Devices consist of three screen printed mesoporous layers of TiO2, ZrO2 and carbon, which are subsequently infiltrated with perovskite. It is well established that complete infiltration, or filling, of the base TiO2 layer is key to achieving peak performance and reproducibility in both lab-scale devices and modules. A thorough understanding of the factors influencing infiltration is therefore essential for both lab-scale research and scale-up. TiO2 infiltration is easily examined by optical microscopy through the glass substrate. This work identifies common characteristic infiltration defects at multiple scales, caused by specific issues in the manufacturing process such as mesh marking, printing issues, contaminant damage and environmental fluctuations. Likely causes and potential solutions are presented for each type of defect, to produce a troubleshooting reference resource for tackling this problem at multiple scales. This should help enhance lab-scale reproducibility providing a simple method for quality control in future large-scale ventures

Integrating genome-wide polygenic risk scores and non-genetic risk to predict colorectal cancer diagnosis using UK Biobank data: population based cohort study

Objective: To evaluate the benefit of combining polygenic risk scores with the QCancer-10 (colorectal cancer) prediction model for non-genetic risk to identify people at highest risk of colorectal cancer. Design: Population based cohort study. Setting: Data from the UK Biobank study, collected between March 2006 and July 2010. Participants: 434 587 individuals with complete data for genetics and QCancer-10 predictions were included in the QCancer-10 plus polygenic risk score modelling and validation cohorts. Main outcome measures: Prediction of colorectal cancer diagnosis by genetic, non-genetic, and combined risk models. Using data from UK Biobank, six different polygenic risk scores for colorectal cancer were developed using LDpred2 polygenic risk score software, clumping, and thresholding approaches, and a model based on genome-wide significant polymorphisms. The top performing genome-wide polygenic risk score and the score containing genome-wide significant polymorphisms were combined with QCancer-10 and performance was compared with QCancer-10 alone. Case-control (logistic regression) and time-to-event (Cox proportional hazards) analyses were used to evaluate risk model performance in men and women. Results: Polygenic risk scores derived using the LDpred2 program performed best, with an odds ratio per standard deviation of 1.584 (95% confidence interval 1.536 to 1.633), and top age and sex adjusted C statistic of 0.733 (95% confidence interval 0.710 to 0.753) in logistic regression models in the validation cohort. Integrated QCancer-10 plus polygenic risk score models out-performed QCancer-10 alone. In men, the integrated LDpred2 model produced a C statistic of 0.730 (0.720 to 0.741) and explained variation of 28.2% (26.3 to 30.1), compared with 0.693 (0.682 to 0.704) and 21.0% (18.9 to 23.1) for QCancer-10 alone. In women, the C statistic for the integrated LDpred2 model was 0.687 (0.673 to 0.702) and explained variation was 21.0% (18.7 to 23.7), compared with 0.645 (0.631 to 0.659) and 12.4% (10.3 to 14.6) for QCancer-10 alone. In the top 20% of individuals at highest absolute risk, the sensitivity and specificity of the integrated LDpred2 models for predicting colorectal cancer diagnosis was 47.8% and 80.3% respectively in men, and 42.7% and 80.1% respectively in women, with increases in absolute risk in the top 5% of risk in men of 3.47-fold and in women of 2.77-fold compared with the median. Illustrative decision curve analysis indicated a small incremental improvement in net benefit with QCancer-10 plus polygenic risk score models compared with QCancer-10 alone. Conclusions: Integrating polygenic risk scores with QCancer-10 modestly improves risk prediction over use of QCancer-10 alone. Given that QCancer-10 data can be obtained relatively easily from health records, use of polygenic risk score in risk stratified population screening for colorectal cancer currently has no clear justification. The added benefit, cost effectiveness, and acceptability of polygenic risk scores should be carefully evaluated in a real life screening setting before implementation in the general population

Regulation of human PAX6 expression by miR-7

The paired box gene 6 (PAX6) is a powerful mediator of eye and brain organogenesis whose spatiotemporal expression is exquisitely controlled by multiple mechanisms, including post-transcriptional regulation by microRNAs (miRNAs). In the present study, we use bioinformatic predictions to identify three candidate microRNA-7 (miR-7) target sites in the human PAX6 3′ untranslated region (3′-UTR) and demonstrate that two of them are functionally active in a human cell line. Furthermore, transient transfection of cells with synthetic miR-7 inhibits PAX6 protein expression but does not alter levels of PAX6 mRNA, suggesting that miR-7 induces translational repression of PAX6. Finally, a comparison of PAX6 3′-UTRs across species reveals that one of the functional miR-7 target sites is conserved, whereas the second functional target site is found only in primates. Thus, the interaction between PAX6 and miR-7 appears to be highly conserved; however, the precise number of sites through which this interaction occurs may have expanded throughout evolution

Integrating genome-wide polygenic risk scores and non-genetic risk to predict colorectal cancer diagnosis: a cohort study in UK Biobank

OBJECTIVE: To evaluate the benefit of combining polygenic risk scores with the QCancer-10 (colorectal cancer) prediction model for non-genetic risk to identify people at highest risk of colorectal cancer. DESIGN: Population based cohort study. SETTING: Data from the UK Biobank study, collected between March 2006 and July 2010. PARTICIPANTS: 434 587 individuals with complete data for genetics and QCancer-10 predictions were included in the QCancer-10 plus polygenic risk score modelling and validation cohorts. MAIN OUTCOME MEASURES: Prediction of colorectal cancer diagnosis by genetic, non-genetic, and combined risk models. Using data from UK Biobank, six different polygenic risk scores for colorectal cancer were developed using LDpred2 polygenic risk score software, clumping, and thresholding approaches, and a model based on genome-wide significant polymorphisms. The top performing genome-wide polygenic risk score and the score containing genome-wide significant polymorphisms were combined with QCancer-10 and performance was compared with QCancer-10 alone. Case-control (logistic regression) and time-to-event (Cox proportional hazards) analyses were used to evaluate risk model performance in men and women. RESULTS: Polygenic risk scores derived using the LDpred2 program performed best, with an odds ratio per standard deviation of 1.584 (95% confidence interval 1.536 to 1.633), and top age and sex adjusted C statistic of 0.733 (95% confidence interval 0.710 to 0.753) in logistic regression models in the validation cohort. Integrated QCancer-10 plus polygenic risk score models out-performed QCancer-10 alone. In men, the integrated LDpred2 model produced a C statistic of 0.730 (0.720 to 0.741) and explained variation of 28.2% (26.3 to 30.1), compared with 0.693 (0.682 to 0.704) and 21.0% (18.9 to 23.1) for QCancer-10 alone. In women, the C statistic for the integrated LDpred2 model was 0.687 (0.673 to 0.702) and explained variation was 21.0% (18.7 to 23.7), compared with 0.645 (0.631 to 0.659) and 12.4% (10.3 to 14.6) for QCancer-10 alone. In the top 20% of individuals at highest absolute risk, the sensitivity and specificity of the integrated LDpred2 models for predicting colorectal cancer diagnosis was 47.8% and 80.3% respectively in men, and 42.7% and 80.1% respectively in women, with increases in absolute risk in the top 5% of risk in men of 3.47-fold and in women of 2.77-fold compared with the median. Illustrative decision curve analysis indicated a small incremental improvement in net benefit with QCancer-10 plus polygenic risk score models compared with QCancer-10 alone. CONCLUSIONS: Integrating polygenic risk scores with QCancer-10 modestly improves risk prediction over use of QCancer-10 alone. Given that QCancer-10 data can be obtained relatively easily from health records, use of polygenic risk score in risk stratified population screening for colorectal cancer currently has no clear justification. The added benefit, cost effectiveness, and acceptability of polygenic risk scores should be carefully evaluated in a real life screening setting before implementation in the general population

The Scottish economy [June 1997]

This section presents short and long term forecasts for the quarterly growth rates of Scottish manufacturing (Division D of the 1992 SIC) output

The Scottish economy [December 1995]

This section presents short and long term forecasts for the quarterly growth rates of Scottish manufacturing (Division D of the 1992 SIC) output

The Scottish economy [September 1995]

This section presents short and long term forecasts for the quarterly growth rates of Scottish manufacturing (Division D of the 1992 SIC) output

The Scottish economy [December 1995]

This section presents short and long term forecasts for the quarterly growth rates of Scottish manufacturing (Division D of the 1992 SIC) output