Ipso-substitution — the hidden gate to xenobiotic degradation pathways

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Novel screening methods — biosensors

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Dynamics in the microbial cytome — single cell analytics in natural systems

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Anaerobic microbial dehalogenation of organohalides — state of the art and remediation strategies

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Molecular pharming — VLPs made in plants

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Towards metagenome-scale models for industrial applications — the case of Lactic Acid Bacteria

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Highlights► Genome-scale metabolic modelling is being increasingly applied in LAB research. ► Novel techniques that broaden applicability of models remain to be applied to LAB. ► Additional constraints allow better predictions of genome-scale metabolic models. ► Novel approaches to move from modelling monocultures to mixed cultures are being developed. ► The feasibility of metagenome-based modelling approaches is being appreciated.     

Somewhat in control — the role of transcription in regulating microbial metabolic fluxes

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Drinking water microbiology — from measurement to management

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Gaining mass: the structure of respiratory complex I — from bacterial towards mitochondrial versions

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RNA epigenetics — chemical messages for posttranscriptional gene regulation

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Making connections — strategies for single molecule fluorescence biophysics

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Nanostructured sensors for biomedical applications — a current perspective

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Protein homeostasis — more than resisting a hot bath

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Extremozymes — biocatalysts with unique properties from extremophilic microorganisms

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SYNE1-QK1 SNPs,G × G and G × E interactions on the risk of hyperlipidaemia

This study aimed to assess the relationship of 3 spectrin repeat containing nuclear envelope protein 1 (SYNE1) and 4 KH domain containing RNA binding (QK1) single nucleotide polymorphisms (SNPs), their haplotypes, gene-gene (G × G), gene-environment (G × E) interactions and hypercholesterolaemia (HCH) and hypertriglyceridaemia (HTG) in the Chinese Maonan minority. The genetic make-up of the SYNE1-QK1 SNPs in 1932 unrelated subjects (normal, 641; HCH, 649; and HTG, 642) was obtained by next-generation sequencing technologies. The genotypic frequencies of following SNPs were suggestively distinctive between the control and HCH groups (rs2623963, rs7745725, rs9459317, rs16897566), or between the control and HTG groups (rs2623963, rs1358317, rs7745725, rs1923608, rs16897566 SNPs; P < .05, respectively). Multiple-locus linkage disequilibrium analysis indicated that the identified SNPs were not inherited independently. Several haplotypes and gene-gene interaction haplotypes among the detected SNPs may be related with an increased morbidity of HCH (C-G-A, C-G-G and C-G-G-T-C-A-T) and HTG (C-G-G, G-T-G-C, C-G-G-G-T-G-C and C-G-G-T-C-A-T), whereas others may be related with an decreased risk of HCH (G-A-A, G-C-A-T, C-A-A-T-C-A-T and G-A-A-G-C-A-T) and HTG (G-A-A, G-C-A-T, C-A-A-T-C-A-T and G-A-A-G-C-A-T). The association evaluation based on haplotypes and gene-gene interactions could improve the power of detecting the risk of dyslipidaemia than anyone of SNP alone. There was significant three-locus model involving SNP-SNP, haplotype-haplotype/environment and G × G interactions (P < .05-0.001) that were detected by GMDR in HCH and HTG groups. Different interactions between genetic and environmental factors would produce different redundancy or synergy effects on the morbidity of HCH and/or HTG.     

Heavy enzymes — experimental and computational insights in enzyme dynamics

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Mechanisms of mechanosensing — mechanosensitive channels,function and re-engineering

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trans-Cyclooctene — a stable,voracious dienophile for bioorthogonal labeling

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