Accounting for nutrition-related health impacts in food life cycle assessment: insights from an expert workshop

\ua9 The Author(s) 2024.Sub-optimal dietary patterns make major contributions to the Global Burden of Disease and are among the most pressing issues affecting human health. Consequently, they are key to consider when assessing the human health and other environmental impacts of foods and diets within life cycle assessments. The UN Environment Life Cycle Initiative convened a task force on nutrition-related human health impacts as part of the Global Life Cycle Impact Assessment Method (GLAM) project. The health impacts of dietary patterns can be expressed in disability-adjusted life years (DALYs), in line with reporting human health impacts of other impact categories within the life cycle impact assessment (LCIA) framework. The task force held a workshop with nutrition experts to receive guidance in its process to develop a consensus-based impact assessment framework for addressing nutrition-related health impacts in LCIA. The workshop aimed to (1) evaluate the general assessment framework, (2) discuss scientific questions for quantifying human health impacts from nutrition for food items and diets, and (3) provide initial guidance for further development. The proposed framework based on the Global Burden of Disease (GBD) risk ratios was regarded as a good starting point to assess the relative health risks of the general population, provided that the dietary context is considered and several limitations, such as incomplete disease coverage, are acknowledged. The experts advised against a potentially misleading use of adult-derived dietary risk factors for children. To improve global coverage of the GLAM framework, it is important to consider a wider range of dietary patterns. The experts also recommended using a metric complementary to DALYs, such as nutrient adequacy, also considering, e.g., vitamin A and iron, to complement the assessment

Measurement of the antineutrino neutral-current elastic differential cross section

arXiv:1309.7257v1 [hep-ex

Improved Search for νˉμ→νˉe\bar ν_μ\rightarrow \bar ν_e Oscillations in the MiniBooNE Experiment

Submitted to PRL. Further information provided in arXiv:1207.4809Submitted to PRL. Further information provided in arXiv:1207.4809The MiniBooNE experiment at Fermilab reports results from an analysis of $\bar \nu_e$ appearance data from $11.27 \times 10^{20}$ protons on target in antineutrino mode, an increase of approximately a factor of two over the previously reported results. An event excess of $78.4 \pm 28.5$ events ($2.8 \sigma$) is observed in the energy range $200<E_\nu^{QE}<1250$ MeV. If interpreted in a two-neutrino oscillation model, $\bar{\nu}_{\mu}\rightarrow\bar{\nu}_e$, the best oscillation fit to the excess has a probability of 66% while the background-only fit has a $\chi^2$-probability of 0.5% relative to the best fit. The data are consistent with antineutrino oscillations in the $0.01 < \Delta m^2 < 1.0$ eV$^2$ range and have some overlap with the evidence for antineutrino oscillations from the Liquid Scintillator Neutrino Detector (LSND). All of the major backgrounds are constrained by in-situ event measurements so non-oscillation explanations would need to invoke new anomalous background processes. The neutrino mode running also shows an excess at low energy of $162.0 \pm 47.8$ events ($3.4 \sigma$) but the energy distribution of the excess is marginally compatible with a simple two neutrino oscillation formalism. Expanded models with several sterile neutrinos can reduce the incompatibility by allowing for CP violating effects between neutrino and antineutrino oscillations

Using L/E Oscillation Probability Distributions

This paper explores the use of $L/E$ oscillation probability distributions to compare experimental measurements and to evaluate oscillation models. In this case, $L$ is the distance of neutrino travel and $E$ is a measure of the interacting neutrino's energy. While comparisons using allowed and excluded regions for oscillation model parameters are likely the only rigorous method for these comparisons, the $L/E$ distributions are shown to give qualitative information on the agreement of an experiment's data with a simple two-neutrino oscillation model. In more detail, this paper also outlines how the $L/E$ distributions can be best calculated and used for model comparisons. Specifically, the paper presents the $L/E$ data points for the final MiniBooNE data samples and, in the Appendix, explains and corrects the mistaken analysis published by the ICARUS collaboration

Copy number variation of microRNA genes in the human genome

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are important genetic elements that regulate the expression of thousands of human genes. Polymorphisms affecting miRNA biogenesis, dosage and target recognition may represent potentially functional variants. The functional consequences of single nucleotide polymorphisms (SNPs) within critical miRNA sequences and outside of miRNA genes were previously demonstrated using both experimental and computational methods. However, little is known about how copy number variations (CNVs) affect miRNA genes.</p> <p>Results</p> <p>In this study, we analyzed the co-localization of all miRNA <it>loci </it>with known CNV regions. Using bioinformatic tools we identified and validated 209 copy number variable miRNA genes (CNV-miRNAs) in CNV regions deposited in Database of Genomic Variations (DGV) and 11 CNV-miRNAs in two sets of CNVs defined as highly polymorphic. We propose potential mechanisms of CNV-mediated variation of functional copies of miRNAs (dosage) for different types of CNVs overlapping miRNA genes. We also showed that, consistent with their essential biological functions, miRNA <it>loci </it>are underrepresented in highly polymorphic and well-validated CNV regions.</p> <p>Conclusion</p> <p>We postulate that CNV-miRNAs are potential functional variants and should be considered high priority candidate variants in genotype-phenotype association studies.</p

Identification of novel targets for breast cancer by exploring gene switches on a genome scale

<p>Abstract</p> <p>Background</p> <p>An important feature that emerges from analyzing gene regulatory networks is the "switch-like behavior" or "bistability", a dynamic feature of a particular gene to preferentially toggle between two steady-states. The state of gene switches plays pivotal roles in cell fate decision, but identifying switches has been difficult. Therefore a challenge confronting the field is to be able to systematically identify gene switches.</p> <p>Results</p> <p>We propose a top-down mining approach to exploring gene switches on a genome-scale level. Theoretical analysis, proof-of-concept examples, and experimental studies demonstrate the ability of our mining approach to identify bistable genes by sampling across a variety of different conditions. Applying the approach to human breast cancer data identified genes that show bimodality within the cancer samples, such as estrogen receptor (ER) and ERBB2, as well as genes that show bimodality between cancer and non-cancer samples, where tumor-associated calcium signal transducer 2 (TACSTD2) is uncovered. We further suggest a likely transcription factor that regulates TACSTD2.</p> <p>Conclusions</p> <p>Our mining approach demonstrates that one can capitalize on genome-wide expression profiling to capture dynamic properties of a complex network. To the best of our knowledge, this is the first attempt in applying mining approaches to explore gene switches on a genome-scale, and the identification of TACSTD2 demonstrates that single cell-level bistability can be predicted from microarray data. Experimental confirmation of the computational results suggest TACSTD2 could be a potential biomarker and attractive candidate for drug therapy against both ER+ and ER- subtypes of breast cancer, including the triple negative subtype.</p

Identification of ORC1/CDC6-Interacting Factors in Trypanosoma brucei Reveals Critical Features of Origin Recognition Complex Architecture

DNA Replication initiates by formation of a pre-replication complex on sequences termed origins. In eukaryotes, the pre-replication complex is composed of the Origin Recognition Complex (ORC), Cdc6 and the MCM replicative helicase in conjunction with Cdt1. Eukaryotic ORC is considered to be composed of six subunits, named Orc1–6, and monomeric Cdc6 is closely related in sequence to Orc1. However, ORC has been little explored in protists, and only a single ORC protein, related to both Orc1 and Cdc6, has been shown to act in DNA replication in Trypanosoma brucei. Here we identify three highly diverged putative T. brucei ORC components that interact with ORC1/CDC6 and contribute to cell division. Two of these factors are so diverged that we cannot determine if they are eukaryotic ORC subunit orthologues, or are parasite-specific replication factors. The other we show to be a highly diverged Orc4 orthologue, demonstrating that this is one of the most widely conserved ORC subunits in protists and revealing it to be a key element of eukaryotic ORC architecture. Additionally, we have examined interactions amongst the T. brucei MCM subunits and show that this has the conventional eukaryotic heterohexameric structure, suggesting that divergence in the T. brucei replication machinery is limited to the earliest steps in origin licensing

Both Positive and Negative Selection Pressures Contribute to the Polymorphism Pattern of the Duplicated Human CYP21A2 Gene.

The human steroid 21-hydroxylase gene (CYP21A2) participates in cortisol and aldosterone biosynthesis, and resides together with its paralogous (duplicated) pseudogene in a multiallelic copy number variation (CNV), called RCCX CNV. Concerted evolution caused by non-allelic gene conversion has been described in great ape CYP21 genes, and the same conversion activity is responsible for a serious genetic disorder of CYP21A2, congenital adrenal hyperplasia (CAH). In the current study, 33 CYP21A2 haplotype variants encoding 6 protein variants were determined from a European population. CYP21A2 was shown to be one of the most diverse human genes (HHe=0.949), but the diversity of intron 2 was greater still. Contrary to previous findings, the evolution of intron 2 did not follow concerted evolution, although the remaining part of the gene did. Fixed sites (different fixed alleles of sites in human CYP21 paralogues) significantly accumulated in intron 2, indicating that the excess of fixed sites was connected to the lack of effective non-allelic conversion and concerted evolution. Furthermore, positive selection was presumably focused on intron 2, and possibly associated with the previous genetic features. However, the positive selection detected by several neutrality tests was discerned along the whole gene. In addition, the clear signature of negative selection was observed in the coding sequence. The maintenance of the CYP21 enzyme function is critical, and could lead to negative selection, whereas the presumed gene regulation altering steroid hormone levels via intron 2 might help fast adaptation, which broadly characterizes the genes of human CNVs responding to the environment

Synthetic biology: Understanding biological design from synthetic circuits

An important aim of synthetic biology is to uncover the design principles of natural biological systems through the rational design of gene and protein circuits. Here, we highlight how the process of engineering biological systems — from synthetic promoters to the control of cell–cell interactions — has contributed to our understanding of how endogenous systems are put together and function. Synthetic biological devices allow us to grasp intuitively the ranges of behaviour generated by simple biological circuits, such as linear cascades and interlocking feedback loops, as well as to exert control over natural processes, such as gene expression and population dynamics