Critical current density: Measurements vs. reality

Different experimental techniques are employed to evaluate the critical current density (Jc), namely transport current measurements and two different magnetisation measurements forming quasi-equilibrium and dynamic critical states. Our technique-dependent results for superconducting YBa 2Cu3O7 (YBCO) film and MgB2 bulk samples show an extremely high sensitivity of Jc and associated interpretations, such as irreversibility fields and Kramer plots, which lose meaning without a universal approach. We propose such approach for YBCO films based on their unique pinning features. This approach allows us to accurately recalculate the magnetic-field-dependent Jc obtained by any technique into the Jc behaviour, which would have been measured by any other method without performing the corresponding experiments. We also discovered low-frequency-dependent phenomena, governing flux dynamics, but contradicting the considered ones in the literature. The understanding of these phenomena, relevant to applications with moving superconductors, can clarify their dramatic impact on the electric-field criterion through flux diffusivity and corresponding measurements. © Copyright EPLA, 2013

Bioinformatics in China: A Personal Perspective

Biochemical Research MethodsMathematical & Computational BiologySCI(E)PubMed3EDITORIAL MATERIAL4e1000020

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Robust estimation of bacterial cell count from optical density

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

Money matters : an empirical research into the impact of government funding on Singapore’s Voluntary Welfare Organizations

This study sought to evaluate the impact of government funding on VWOs, specifically in the expansion of their programs and in improving the quality of services rendered to beneficiaries. Utilizing a mixed methods research design, we analyzed both the financial data of VWOs and interviewed 13 managers from different organizations across the sector. Analysis of our data revealed that while government grants facilitate the ramping up of organization capacity and increase the outreach of VWOs, organizations are overdependent on these funds. Despite this, the findings suggest that a collaborative government-VWO relationship in Singapore encourages VWOs to seek out private donors to be more self-reliant while expanding their operations further. From a policymaking perspective, an underlying challenge to maintaining this complementary relationship is the need to balance both accountability and transparency requirements for VWOs without compromising their effectiveness in serving and representing their clients.Bachelor of Arts in Economics and Public Policy and Global Affair

An algebraic approach for supply network synthesis

This paper presents a novel algebraic technique of supply network synthesis and analysis. A case study of biomass processing for supply network synthesis using three techniques (i) mathematical modelling (ii) supermatrix scoring concept and (iii) algebraic analysis with graphical visualisation is demonstrated. The results and performances of three techniques are compared. Comparable modelling results are obtained for all three approaches. The introduction of quantitative cum graphical analysis of supply network allows the performance overview of each possible choice of supply network in one picture. Besides, the algebraic method allows the concurrent set-up of material allocation and ranking of possible supply network choices. This outweighs the mathematical modelling technique that allows for optimal supply network synthesis but giving no insight to the performance of next network choices; and the supermatrix scoring technique that ranks the general supply network choices in a whole picture yet incapable to capture the optimal selection which involves only part of the players, especially in supply network problem. © 2014 Elsevier Ltd. All rights reserved

Divergent Metabolomic Signatures of TGFβ2 and TNFα in the Induction of Retinal Epithelial-Mesenchymal Transition

Epithelial-mesenchymal transition (EMT) is a dedifferentiation program in which polarized, differentiated epithelial cells lose their cell-cell adhesions and transform into matrix-producing mesenchymal cells. EMT of retinal pigment epithelial (RPE) cells plays a crucial role in many retinal diseases, including age-related macular degeneration, proliferative vitreoretinopathy, and diabetic retinopathy. This dynamic process requires complex metabolic reprogramming to accommodate the demands of this dramatic cellular transformation. Both transforming growth factor-beta 2 (TGFβ2) and tumor necrosis factor-alpha (TNFα) have the capacity to induce EMT in RPE cells; however, little is known about their impact on the RPE metabolome. Untargeted metabolomics using high-resolution mass spectrometry was performed to reveal the metabolomic signatures of cellular and secreted metabolites of primary human fetal RPE cells treated with either TGFβ2 or TNFα for 5 days. A total of 638 metabolites were detected in both samples; 188 were annotated as primary metabolites. Metabolomics profiling showed distinct metabolomic signatures associated with TGFβ2 and TNFα treatment. Enrichment pathway network analysis revealed alterations in the pentose phosphate pathway, galactose metabolism, nucleotide and pyrimidine metabolism, purine metabolism, and arginine and proline metabolism in TNFα-treated cells compared to untreated control cells, whereas TGFβ2 treatment induced perturbations in fatty acid biosynthesis metabolism, the linoleic acid pathway, and the Notch signaling pathway. These results provide a broad metabolic understanding of the bioenergetic rewiring processes governing TGFβ2- and TNFα-dependent induction of EMT. Elucidating the contributions of TGFβ2 and TNFα and their mechanistic differences in promoting EMT of RPE will enable the identification of novel biomarkers for diagnosis, management, and tailored drug development for retinal fibrotic diseases

Divergent Metabolomic Signatures of TGFβ2 and TNFα in the Induction of Retinal Epithelial-Mesenchymal Transition.

Epithelial-mesenchymal transition (EMT) is a dedifferentiation program in which polarized, differentiated epithelial cells lose their cell-cell adhesions and transform into matrix-producing mesenchymal cells. EMT of retinal pigment epithelial (RPE) cells plays a crucial role in many retinal diseases, including age-related macular degeneration, proliferative vitreoretinopathy, and diabetic retinopathy. This dynamic process requires complex metabolic reprogramming to accommodate the demands of this dramatic cellular transformation. Both transforming growth factor-beta 2 (TGFβ2) and tumor necrosis factor-alpha (TNFα) have the capacity to induce EMT in RPE cells; however, little is known about their impact on the RPE metabolome. Untargeted metabolomics using high-resolution mass spectrometry was performed to reveal the metabolomic signatures of cellular and secreted metabolites of primary human fetal RPE cells treated with either TGFβ2 or TNFα for 5 days. A total of 638 metabolites were detected in both samples; 188 were annotated as primary metabolites. Metabolomics profiling showed distinct metabolomic signatures associated with TGFβ2 and TNFα treatment. Enrichment pathway network analysis revealed alterations in the pentose phosphate pathway, galactose metabolism, nucleotide and pyrimidine metabolism, purine metabolism, and arginine and proline metabolism in TNFα-treated cells compared to untreated control cells, whereas TGFβ2 treatment induced perturbations in fatty acid biosynthesis metabolism, the linoleic acid pathway, and the Notch signaling pathway. These results provide a broad metabolic understanding of the bioenergetic rewiring processes governing TGFβ2- and TNFα-dependent induction of EMT. Elucidating the contributions of TGFβ2 and TNFα and their mechanistic differences in promoting EMT of RPE will enable the identification of novel biomarkers for diagnosis, management, and tailored drug development for retinal fibrotic diseases