| 1. |
- Beal, Jacob, et al.
(författare)
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Robust estimation of bacterial cell count from optical density
- 2020
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Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Tidskriftsartikel (refereegranskat)abstract
- Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
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| 2. |
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| 3. |
- Yang, Jiabao, et al.
(författare)
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Overcome Low Intrinsic Conductivity of NiOx Through Triazinyl Modification for Highly Efficient and Stable Inverted Perovskite Solar Cells
- 2022
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Ingår i: Solar RRL. - : John Wiley & Sons. - 2367-198X. ; 6:9
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Tidskriftsartikel (refereegranskat)abstract
- Nickel oxide (NiOx) is a promising hole transport material in inverted organic-inorganic metal halide perovskite solar cells. However, its low intrinsic conductivity hinders its further improvement in device performance. Here, we employ a trimercapto-s-triazine trisodium salt (TTTS) as a chelating agent of Ni2+ in the NiOx layer to improve its conductivity. Due to the electron-deficient triazine ring, the TTTS complexes with Ni2+ in NiOx via a strong Ni2+-N coordination bond and increases the ratio of Ni3+:Ni2+. The increased Ni3+ concentration adjusts the band structure of NiOx, thus enhancing hole density and mobility, eventually improving the intrinsic conductivity of NiOx. As a result, the device with TTTS modification displays a champion power conversion efficiency (PCE) of 22.81%. The encapsulated device based on a modified-NiOx layer maintains 94% of its initial power output at the maximum power point and continuous one-sun illumination for 1000 h at 45 degrees C. In addition, the unencapsulated target devices also maintain 92% at 60 +/- 5% relative humidity and 25 degrees C in the air for 5000 h; and 91% at 85 degrees C in a nitrogen atmosphere for 1000 h. The research provides an effective strategy to enhance PCE and stability of inverted PSCs via modifying NiOx films with triazine molecule.
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| 4. |
- Shu, Xiang, et al.
(författare)
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Evaluation of associations between genetically predicted circulating protein biomarkers and breast cancer risk
- 2020
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Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 146:8, s. 2130-2138
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Tidskriftsartikel (refereegranskat)abstract
- A small number of circulating proteins have been reported to be associated with breast cancer risk, with inconsistent results. Herein, we attempted to identify novel protein biomarkers for breast cancer via the integration of genomics and proteomics data. In the Breast Cancer Association Consortium (BCAC), with 122,977 cases and 105,974 controls of European descendants, we evaluated the associations of the genetically predicted concentrations of >1,400 circulating proteins with breast cancer risk. We used data from a large-scale protein quantitative trait loci (pQTL) analysis as our study instrument. Summary statistics for these pQTL variants related to breast cancer risk were obtained from the BCAC and used to estimate odds ratios (OR) for each protein using the inverse-variance weighted method. We identified 56 proteins significantly associated with breast cancer risk by instrumental analysis (false discovery rate <0.05). Of these, the concentrations of 32 were influenced by variants close to a breast cancer susceptibility locus (ABO, 9q34.2). Many of these proteins, such as insulin receptor, insulin-like growth factor receptor 1 and other membrane receptors (OR: 0.82–1.18, p values: 6.96 × 10−4–3.28 × 10−8), are linked to insulin resistance and estrogen receptor signaling pathways. Proteins identified at other loci include those involved in biological processes such as alcohol and lipid metabolism, proteolysis, apoptosis, immune regulation and cell motility and proliferation. Consistent associations were observed for 22 proteins in the UK Biobank data (p < 0.05). The study identifies potential novel biomarkers for breast cancer, but further investigation is needed to replicate our findings.
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| 5. |
- Shu, Xiang, et al.
(författare)
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Large-scale Integrated Analysis of Genetics and Metabolomic Data Reveals Potential Links Between Lipids and Colorectal Cancer Risk
- 2022
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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 31:6, s. 1216-1226
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Tidskriftsartikel (refereegranskat)abstract
- Background: The etiology of colorectal cancer is not fully understood.Methods: Using genetic variants and metabolomics data including 217 metabolites from the Framingham Heart Study (n = 1,357), we built genetic prediction models for circulating metabolites. Models with prediction R2 > 0.01 (Nmetabolite = 58) were applied to predict levels of metabolites in two large consortia with a combined sample size of approximately 46,300 cases and 59,200 controls of European and approximately 21,700 cases and 47,400 controls of East Asian (EA) descent. Genetically predicted levels of metabolites were evaluated for their associations with colorectal cancer risk in logistic regressions within each racial group, after which the results were combined by meta-analysis.Results: Of the 58 metabolites tested, 24 metabolites were significantly associated with colorectal cancer risk [Benjamini-Hochberg FDR (BH-FDR) < 0.05] in the European population (ORs ranged from 0.91 to 1.06; P values ranged from 0.02 to 6.4 × 10-8). Twenty one of the 24 associations were replicated in the EA population (ORs ranged from 0.26 to 1.69, BH-FDR < 0.05). In addition, the genetically predicted levels of C16:0 cholesteryl ester was significantly associated with colorectal cancer risk in the EA population only (OREA: 1.94, 95% CI, 1.60−2.36, P = 2.6 × 10-11; OREUR: 1.01, 95% CI, 0.99−1.04, P = 0.3). Nineteen of the 25 metabolites were glycerophospholipids and triacylglycerols (TAG). Eighteen associations exhibited significant heterogeneity between the two racial groups (PEUR-EA-Het < 0.005), which were more strongly associated in the EA population. This integrative study suggested a potential role of lipids, especially certain glycerophospholipids and TAGs, in the etiology of colorectal cancer.Conclusions: This study identified potential novel risk biomarkers for colorectal cancer by integrating genetics and circulating metabolomics data.Impact: The identified metabolites could be developed into new tools for risk assessment of colorectal cancer in both European and EA populations.
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| 6. |
- Wei, Wendong, et al.
(författare)
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Embodied greenhouse gas emissions from building China's large-scale power transmission infrastructure
- 2021
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Ingår i: Nature Sustainability. - : NATURE RESEARCH. - 2398-9629. ; 4:8, s. 739-747
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Tidskriftsartikel (refereegranskat)abstract
- China has built the world's largest power transmission infrastructure by consuming massive volumes of greenhouse gas-(GHG-) intensive products such as steel. A quantitative analysis of the carbon implications of expanding the transmission infrastructure would shed light on the trade-offs among three connected dimensions of sustainable development, namely, climate change mitigation, energy access and infrastructure development. By collecting a high-resolution inventory, we developed an assessment framework of, and analysed, the GHG emissions caused by China's power transmission infrastructure construction during 1990-2017. We show that cumulative embodied GHG emissions have dramatically increased by more than 7.3 times those in 1990, reaching 0.89 GtCO(2)-equivalent in 2017. Over the same period, the gaps between the well-developed eastern and less-developed western regions in China have gradually narrowed. Voltage class, transmission-line length and terrain were important factors that influenced embodied GHG emissions. We discuss measures for the mitigation of GHG emissions from power transmission development that can inform global low-carbon infrastructure transitions.
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| 7. |
- Wu, Lang, et al.
(författare)
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An integrative multi-omics analysis to identify candidate DNA methylation biomarkers related to prostate cancer risk.
- 2020
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- It remains elusive whether some of the associations identified in genome-wide association studies of prostate cancer (PrCa) may be due to regulatory effects of genetic variants on CpG sites, which may further influence expression of PrCa target genes. To search for CpG sites associated with PrCa risk, here we establish genetic models to predict methylation (N = 1,595) and conduct association analyses with PrCa risk (79,194 cases and 61,112 controls). We identify 759 CpG sites showing an association, including 15 located at novel loci. Among those 759 CpG sites, methylation of 42 is associated with expression of 28 adjacent genes. Among 22 genes, 18 show an association with PrCa risk. Overall, 25 CpG sites show consistent association directions for the methylation-gene expression-PrCa pathway. We identify DNA methylation biomarkers associated with PrCa, and our findings suggest that specific CpG sites may influence PrCa via regulating expression of candidate PrCa target genes.
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| 8. |
- Yang, Yaohua, et al.
(författare)
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Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk
- 2019
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Ingår i: Cancer Research. - : AMER ASSOC CANCER RESEARCH. - 0008-5472 .- 1538-7445. ; 79:3, s. 505-517
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Tidskriftsartikel (refereegranskat)abstract
- DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P < 7.94 x 10(-7). Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely MAPT, HOXB3, ABHD8, ARHGAP27, and SKAP1. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. Significance: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.
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| 9. |
- Yang, Yaohua, et al.
(författare)
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Genetically Predicted Levels of DNA Methylation Biomarkers and Breast Cancer Risk : Data From 228 951 Women of European Descent
- 2020
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 1460-2105 .- 0027-8874. ; 112:3, s. 295-304
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: DNA methylation plays a critical role in breast cancer development. Previous studies have identified DNA methylation marks in white blood cells as promising biomarkers for breast cancer. However, these studies were limited by low statistical power and potential biases. Using a new methodology, we investigated DNA methylation marks for their associations with breast cancer risk. METHODS: Statistical models were built to predict levels of DNA methylation marks using genetic data and DNA methylation data from HumanMethylation450 BeadChip from the Framingham Heart Study (n = 1595). The prediction models were validated using data from the Women's Health Initiative (n = 883). We applied these models to genomewide association study (GWAS) data of 122 977 breast cancer patients and 105 974 controls to evaluate if the genetically predicted DNA methylation levels at CpG sites (CpGs) are associated with breast cancer risk. All statistical tests were two-sided. RESULTS: Of the 62 938 CpG sites CpGs investigated, statistically significant associations with breast cancer risk were observed for 450 CpGs at a Bonferroni-corrected threshold of P less than 7.94 × 10-7, including 45 CpGs residing in 18 genomic regions, that have not previously been associated with breast cancer risk. Of the remaining 405 CpGs located within 500 kilobase flaking regions of 70 GWAS-identified breast cancer risk variants, the associations for 11 CpGs were independent of GWAS-identified variants. Integrative analyses of genetic, DNA methylation, and gene expression data found that 38 CpGs may affect breast cancer risk through regulating expression of 21 genes. CONCLUSION: Our new methodology can identify novel DNA methylation biomarkers for breast cancer risk and can be applied to other diseases.
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