Neuromedin U receptors in GtoPdb v.2023.1

Neuromedin U receptors (provisional nomenclature as recommended by NC-IUPHAR [30]) are activated by the endogenous 25 amino acid peptide neuromedin U (neuromedin U-25, NmU-25), a peptide originally isolated from pig spinal cord [92]. In humans, NmU-25 appears to be the sole product of a precursor gene (NMU, P48645) showing a broad tissue distribution, but which is expressed at highest levels in the upper gastrointestinal tract, CNS, bone marrow and fetal liver. Much shorter versions of NmU are found in some species, but not in human, and are derived at least in some instances from the proteolytic cleavage of the longer NmU. Despite species differences in NmU structure, the C-terminal region (particularly the C-terminal pentapeptide) is highly conserved and contains biological activity. Neuromedin S (neuromedin S-33) has also been identified as an endogenous agonist [97]. NmS-33 is, as its name suggests, a 33 amino-acid product of a precursor protein derived from a single gene and contains an amidated C-terminal heptapeptide identical to NmU. NmS-33 appears to activate NMU receptors with equivalent potency to NmU-25

Neuromedin U receptors (version 2019.4) in the IUPHAR/BPS Guide to Pharmacology Database

Neuromedin U receptors (provisional nomenclature as recommended by NC-IUPHAR [29]) are activated by the endogenous 25 amino acid peptide neuromedin U (neuromedin U-25, NmU-25), a peptide originally isolated from pig spinal cord [90]. In humans, NmU-25 appears to be the sole product of a precursor gene (NMU, P48645) showing a broad tissue distribution, but which is expressed at highest levels in the upper gastrointestinal tract, CNS, bone marrow and fetal liver. Much shorter versions of NmU are found in some species, but not in human, and are derived at least in some instances from the proteolytic cleavage of the longer NmU. Despite species differences in NmU structure, the C-terminal region (particularly the C-terminal pentapeptide) is highly conserved and contains biological activity. Neuromedin S (neuromedin S-33) has also been identified as an endogenous agonist [95]. NmS-33 is, as its name suggests, a 33 amino-acid product of a precursor protein derived from a single gene and contains an amidated C-terminal heptapeptide identical to NmU. NmS-33 appears to activate NMU receptors with equivalent potency to NmU-25

The greening of Arabia: multiple opportunities for human occupation of the Arabian peninsula during the Late Pleistocene inferred from an ensemble of climate model simulations

Climate models are potentially useful tools for addressing human dispersals and demographic change. The Arabian Peninsula is becoming increasingly significant in the story of human dispersals out of Africa during the Late Pleistocene. Although characterised largely by arid environments today, emerging climate records indicate that the peninsula was wetter many times in the past, suggesting that the region may have been inhabited considerably more than hitherto thought. Explaining the origins and spatial distribution of increased rainfall is challenging because palaeoenvironmental research in the region is in an early developmental stage. We address environmental oscillations by assembling and analysing an ensemble of five global climate models (CCSM3, COSMOS, HadCM3, KCM, and NorESM). We focus on precipitation, as the variable is key for the development of lakes, rivers and savannas. The climate models generated here were compared with published palaeoenvironmental data such as palaeolakes, speleothems and alluvial fan records as a means of validation. All five models showed, to varying degrees, that the Arabia Peninsula was significantly wetter than today during the Last Interglacial (130 ka and 126/125 ka timeslices), and that the main source of increased rainfall was from the North African summer monsoon rather than the Indian Ocean monsoon or from Mediterranean climate patterns. Where available, 104 ka (MIS 5c), 56 ka (early MIS 3) and 21 ka (LGM) timeslices showed rainfall was present but not as extensive as during the Last Interglacial. The results favour the hypothesis that humans potentially moved out of Africa and into Arabia on multiple occasions during pluvial phases of the Late Pleistocene

Altered regulation of Prox1-gene-expression in liver tumors

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Rapid Accumulation of Polymorphonuclear Neutrophils in the Corpus luteum during Prostaglandin F2α-Induced Luteolysis in the Cow

Prostaglandin F2α (PGF2α) induces luteolysis within a few days in cows, and immune cells increase in number in the regressing corpus luteum (CL), implying that luteolysis is an inflammatory-like immune response. We investigated the rapid change in polymorphonuclear neutrophil (PMN) numbers in response to PGF2α administration as the first cells recruited to inflammatory sites, together with mRNA of interleukin-8 (IL-8: neutrophil chemoattractant) and P-selectin (leukocyte adhesion molecule) in the bovine CL. CLs were collected by ovariectomy at various times after PGF2α injection. The number of PMNs was increased at 5 min after PGF2α administration, whereas IL-8 and P-selectin mRNA increased at 30 min and 2 h, respectively. PGF2α directly stimulated P-selectin protein expression at 5–30 min in luteal endothelial cells (LECs). Moreover, PGF2α enhanced PMN adhesion to LECs, and this enhancement by PGF2α was inhibited by anti-P-selectin antibody, suggesting that P-selectin expression by PGF2α is crucial in PMN migration. In conclusion, PGF2α rapidly induces the accumulation of PMNs into the bovine CL at 5 min and enhances PMN adhesion via P-selectin expression in LECs. It is suggested that luteolytic cascade by PGF2α may involve an acute inflammatory-like response due to rapidly infiltrated PMNs

Dual clumped isotope thermometry resolves kinetic biases in carbonate formation temperatures

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Bajnai, D., Guo, W., Spötl, C., Coplen, T. B., Methner, K., Löffler, N., Krsnik, E., Gischler, E., Hansen, M., Henkel, D., Price, G. D., Raddatz, J., Scholz, D., & Fiebig, J. Dual clumped isotope thermometry resolves kinetic biases in carbonate formation temperatures. Nature Communications, 11(1), (2020): 4005, doi:10.1038/s41467-020-17501-0.Surface temperature is a fundamental parameter of Earth’s climate. Its evolution through time is commonly reconstructed using the oxygen isotope and the clumped isotope compositions of carbonate archives. However, reaction kinetics involved in the precipitation of carbonates can introduce inaccuracies in the derived temperatures. Here, we show that dual clumped isotope analyses, i.e., simultaneous ∆47 and ∆48 measurements on the single carbonate phase, can identify the origin and quantify the extent of these kinetic biases. Our results verify theoretical predictions and evidence that the isotopic disequilibrium commonly observed in speleothems and scleractinian coral skeletons is inherited from the dissolved inorganic carbon pool of their parent solutions. Further, we show that dual clumped isotope thermometry can achieve reliable palaeotemperature reconstructions, devoid of kinetic bias. Analysis of a belemnite rostrum implies that it precipitated near isotopic equilibrium and confirms the warmer-than-present temperatures during the Early Cretaceous at southern high latitudes.This work became possible through DFG grant “INST 161/871-1” and the Investment in Science Fund at Woods Hole Oceanographic Institution. The authors would like to thank Sven Hofmann and Manuel Schumann for their assistance in the joint Goethe University – Senckenberg BiK-F Stable Isotope Facility at the Institute of Geosciences, Goethe University Frankfurt. K.M. acknowledges funding through “DFG ME 4955/1-1”, E.K. through “DFG MU 2845/6-1”, D.S. through “DFG SCHO 1274/8-1” and “DFG SCHO 1274/11-1”, and M.H. through “DFG HA 8694/1-1”. C.S. acknowledges funding from the University of Innsbruck. A review of the manuscript by David Evans on behalf of the USGS is acknowledged

Extracellular vesicles and their nucleic acids for biomarker discovery

Extracellular vesicles (EVs) are a heterogenous population of vesicles originate from cells. EVs are found in different biofluids and carry different macromolecules, including proteins, lipids, and nucleic acids, providing a snap shot of the parental cells at the time of release. EVs have the ability to transfer molecular cargoes to other cells and can initiate different physiological and pathological processes. Mounting lines of evidence demonstrated that EVs' cargo and machinery is affected in disease states, positioning EVs as potential sources for the discovery of novel biomarkers. In this review, we demonstrate a conceptual overview of the EV field with particular focus on their nucleic acid cargoes. Current knowledge of EV subtypes, nucleic acid cargo and pathophysiological roles are outlined, with emphasis placed on advantages against competing analytes. We review the utility of EVs and their nucleic acid cargoes as biomarkers and critically assess the newly available advances in the field of EV biomarkers and high throughput technologies. Challenges to achieving the diagnostic potential of EVs, including sample handling, EV isolation, methodological considerations, and bioassay reproducibility are discussed. Future implementation of ‘omics-based technologies and integration of systems biology approaches for the development of EV-based biomarkers and personalized medicine are also considered

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues