1H HR MAS NMR metabolomic and non-destructive 2D NMR relaxometry to assess internal quality in apples.

NMR can be considered a multi-scale multidimensional technology in the sense that it provides both spatial insight at macroscopic (MRI) or microscopic level (relaxometry), together with chemical characterization (HR-MAS). In this study 296 apples (from 4 cultivars) were MRI screened (20 slices per fruit) among which 7 fruits were used for metabolomic study by 1H HR MAS in order to assess various chemical shifts: malic acid, sucrose, glucose, fructose and ethanol. On the first season, tissue samples were taken from the sound and affected apples (near the core, centre and outer part of the mesocarp) belonging to sound and affected locations, while on the second season, tissue samples were focused on the comparison between sound and affected tissue. Beside, MRI and 2D non-destructive relaxometry (on whole fruits, and localized tissue) where performed on 72 and 12 apples respectively in order to compare features at macroscopic (tissue) and microscopic (subcellular) level. HR MAS shows higher content of ?-glucose, ?-glucose, malic acid and aromatic compounds in watercore affected tissues from both seasons, while sound tissue reflects higher sucrose. Microscopic (subcellular) degradation of tissue varies according to disorder development and is in good accordance with macroscopic characterization with MRI

Normal Proliferation and Tumorigenesis but Impaired Pancreatic Function in Mice Lacking the Cell Cycle Regulator Sei1

Sei1 is a positive regulator of proliferation that promotes the assembly of Cdk4-cyclin D complexes and enhances the transcriptional activity of E2f1. The potential oncogenic role of Sei1 is further suggested by its overexpression in various types of human cancers. To study the role of Sei1, we have generated a mouse line deficient for this gene. Sei1-null fibroblasts did not show abnormalities regarding proliferation or susceptibility to neoplastic transformation, nor did we observe defects on Cdk4 complexes or E2f activity. Sei1-null mice were viable, did not present overt pathologies, had a normal lifespan, and had a normal susceptibility to spontaneous and chemically-induced cancer. Pancreatic insulin-producing cells are known to be particularly sensitive to Cdk4-cyclin D and E2f activities, and we have observed that Sei1 is highly expressed in pancreatic islets compared to other tissues. Interestingly, Sei1-null mice present lower number of islets, decreased β-cell area, impaired insulin secretion, and glucose intolerance. These defects were associated to nuclear accumulation of the cell-cycle inhibitors p21Cip1 and p27Kip1 in islet cells. We conclude that Sei1 plays an important role in pancreatic β-cells, which supports a functional link between Sei1 and the core cell cycle regulators specifically in the context of the pancreas

Eukaryotic elongation factor 2 controls TNF-alpha translation in LPS-induced hepatitis

Bacterial LPS (endotoxin) has been implicated in the pathogenesis of acute liver disease through its induction of the proinflammatory cytokine TNF-alpha. TNF-alpha is a key determinant of the outcome in a well-established mouse model of acute liver failure during septic shock. One possible mechanism for regulating TNF-alpha expression is through the control of protein elongation during translation, which would allow rapid cell adaptation to physiological changes. However, the regulation of translational elongation is poorly understood. We found that expression of p38gamma/delta MAPK proteins is required for the elongation of nascent TNF-alpha protein in macrophages. The MKK3/6-p38gamma/delta pathway mediated an inhibitory phosphorylation of eukaryotic elongation factor 2 (eEF2) kinase, which in turn promoted eEF2 activation (dephosphorylation) and subsequent TNF-alpha elongation. These results identify a new signaling pathway that regulates TNF-alpha production in LPS-induced liver damage and suggest potential cell-specific therapeutic targets for liver diseases in which TNF-alpha production is involved

Biomarkers as Common Data Elements for Symptom and Selfâ Management Science

PurposeBiomarkers as common data elements (CDEs) are important for the characterization of biobehavioral symptoms given that once a biologic moderator or mediator is identified, biologically based strategies can be investigated for treatment efforts. Just as a symptom inventory reflects a symptom experience, a biomarker is an indicator of the symptom, though not the symptom per se. The purposes of this position paper are to (a) identify a â minimum setâ of biomarkers for consideration as CDEs in symptom and selfâ management science, specifically biochemical biomarkers; (b) evaluate the benefits and limitations of such a limited array of biomarkers with implications for symptom science; (c) propose a strategy for the collection of the endorsed minimum set of biologic samples to be employed as CDEs for symptom science; and (d) conceptualize this minimum set of biomarkers consistent with National Institute of Nursing Research (NINR) symptoms of fatigue, depression, cognition, pain, and sleep disturbance.Design and MethodsFrom May 2016 through January 2017, a working group consisting of a subset of the Directors of the NINR Centers of Excellence funded by P20 or P30 mechanisms and NINR staff met bimonthly via telephone to develop this position paper suggesting the addition of biomarkers as CDEs. The full group of Directors reviewed drafts, provided critiques and suggestions, recommended the minimum set of biomarkers, and approved the completed document. Best practices for selecting, identifying, and using biological CDEs as well as challenges to the use of biological CDEs for symptom and selfâ management science are described. Current platforms for sample outcome sharing are presented. Finally, biological CDEs for symptom and selfâ management science are proposed along with implications for future research and use of CDEs in these areas.FindingsThe recommended minimum set of biomarker CDEs include proâ and antiâ inflammatory cytokines, a hypothalamicâ pituitaryâ adrenal axis marker, cortisol, the neuropeptide brainâ derived neurotrophic factor, and DNA polymorphisms.ConclusionsIt is anticipated that this minimum set of biomarker CDEs will be refined as knowledge regarding biologic mechanisms underlying symptom and selfâ management science further develop. The incorporation of biological CDEs may provide insights into mechanisms of symptoms, effectiveness of proposed interventions, and applicability of chosen theoretical frameworks. Similarly, as for the previously suggested NINR CDEs for behavioral symptoms and selfâ management of chronic conditions, biological CDEs offer the potential for collaborative efforts that will strengthen symptom and selfâ management science.Clinical RelevanceThe use of biomarker CDEs in biobehavioral symptoms research will facilitate the reproducibility and generalizability of research findings and benefit symptom and selfâ management science.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143764/1/jnu12378.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143764/2/jnu12378_am.pd

Transcription factor NRF2 as a therapeutic target for chronic diseases: a systems medicine approach

Systems medicine has a mechanism-based rather than a symptom- or organ-based approach to disease and identifies therapeutic targets in a nonhypothesis-driven manner. In this work, we apply this to transcription factor nuclear factor (erythroid-derived 2)-like 2 (NRF2) by cross-validating its position in a protein-protein interaction network (the NRF2 interactome) functionally linked to cytoprotection in low-grade stress, chronic inflammation, metabolic alterations, and reactive oxygen species formation. Multiscale network analysis of these molecular profiles suggests alterations of NRF2 expression and activity as a common mechanism in a subnetwork of diseases (the NRF2 diseasome). This network joins apparently heterogeneous phenotypes such as autoimmune, respiratory, digestive, cardiovascular, metabolic, and neurodegenerative diseases, along with cancer. Importantly, this approach matches and confirms in silico several applications for NRF2-modulating drugs validated in vivo at different phases of clinical development. Pharmacologically, their profile is as diverse as electrophilic dimethyl fumarate, synthetic triterpenoids like bardoxolone methyl and sulforaphane, protein-protein or DNA-protein interaction inhibitors, and even registered drugs such as metformin and statins, which activate NRF2 and may be repurposed for indications within the NRF2 cluster of disease phenotypes. Thus, NRF2 represents one of the first targets fully embraced by classic and systems medicine approaches to facilitate both drug development and drug repurposing by focusing on a set of disease phenotypes that appear to be mechanistically linked. The resulting NRF2 drugome may therefore rapidly advance several surprising clinical options for this subset of chronic diseases

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Local hydrological conditions influence tree diversity and composition across the Amazon basin

Tree diversity and composition in Amazonia are known to be strongly determined by the water supplied by precipitation. Nevertheless, within the same climatic regime, water availability is modulated by local topography and soil characteristics (hereafter referred to as local hydrological conditions), varying from saturated and poorly drained to well-drained and potentially dry areas. While these conditions may be expected to influence species distribution, the impacts of local hydrological conditions on tree diversity and composition remain poorly understood at the whole Amazon basin scale. Using a dataset of 443 1-ha non-flooded forest plots distributed across the basin, we investigate how local hydrological conditions influence 1) tree alpha diversity, 2) the community-weighted wood density mean (CWM-wd) – a proxy for hydraulic resistance and 3) tree species composition. We find that the effect of local hydrological conditions on tree diversity depends on climate, being more evident in wetter forests, where diversity increases towards locations with well-drained soils. CWM-wd increased towards better drained soils in Southern and Western Amazonia. Tree species composition changed along local soil hydrological gradients in Central-Eastern, Western and Southern Amazonia, and those changes were correlated with changes in the mean wood density of plots. Our results suggest that local hydrological gradients filter species, influencing the diversity and composition of Amazonian forests. Overall, this study shows that the effect of local hydrological conditions is pervasive, extending over wide Amazonian regions, and reinforces the importance of accounting for local topography and hydrology to better understand the likely response and resilience of forests to increased frequency of extreme climate events and rising temperatures