Search

Human plasma lipidome captures risk for cardio-metabolic diseases. To discover new lipid-associated variants and understand link between lipid species and cardiometabolic disorders, we performed univariate and multivariate genome-wide analyses of 179 lipid species in 7,174 Finnish individuals. We further fine-mapped the associated loci, prioritized genes, and examined their disease links in 377,277 FinnGen participants. We identified 495 genome-trait associations in 56 genetic loci including 9 novel loci, with a considerable boost provided by multivariate analysis. For 26 loci, fine-mapping identified variants with a high causal probability, including 14 coding variants indicating likely causal genes. Phenome-wide analysis across 953 disease endpoints in FinnGen revealed disease associations for 40 lipid loci. For 11 known coronary artery disease risk variants, we detected strong associations with lipid species. Our study demonstrates the power of multivariate genetic analysis in correlated lipidomics data and reveals genetic links between diseases and detailed lipid measures beyond standard lipids.

We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.

Background Despite well‐recognized differences in the atherosclerotic cardiovascular disease risk between men and women, sex differences in risk factors and sex‐specific mechanisms in the pathophysiology of atherosclerotic cardiovascular disease remain poorly understood. Lipid metabolism plays a central role in the development of atherosclerotic cardiovascular disease. Understanding sex differences in lipids and their genetic determinants could provide mechanistic insights into sex differences in atherosclerotic cardiovascular disease and aid in precise risk assessment. Herein, we examined sex differences in plasma lipidome and heterogeneity in genetic influences on lipidome in men and women through sex‐stratified genome‐wide association analyses. Methods and Results We used data consisting of 179 lipid species measured by shotgun lipidomics in 7266 individuals from the Finnish GeneRISK cohort and sought for replication using independent data from 2045 participants. Significant sex differences in the levels of 141 lipid species were observed ( P −4 ). Interestingly, 121 lipid species showed significant age‐sex interactions, with opposite age‐related changes in 39 lipid species. In general, most of the cholesteryl esters, ceramides, lysophospholipids, and glycerides were higher in 45‐ to 50‐year‐old men compared with women of same age, but the sex differences narrowed down or reversed with age. We did not observe any major differences in genetic effect in the sex‐stratified genome‐wide association analyses, which suggests that common genetic variants do not have a major role in sex differences in lipidome. Conclusions Our study provides a comprehensive view of sex differences in circulatory lipids pointing to potential sex differences in lipid metabolism and highlights the need for sex‐ and age‐specific prevention strategies.

Type 2 diabetes is a complex, multifactorial disease with varying presentation and underlying pathophysiology. Recent studies using data-driven cluster analysis have led to a stratification of type 2 diabetes into novel subgroups based on six clinical measurements. Whether these subgroups truly correspond to the underlying phenotypic differences is nevertheless unclear. Here, we apply an unsupervised, data-driven clustering method (Similarity Network Fusion) to characterize type 2 diabetes in two independent cohorts involving 1,134 subjects in total based on integrated plasma lipidomics and peptidomics data without pre-selection. Logistic regression was then used to explore clustering based on ≥ 180 circulating lipids and 1,195 protein biomarkers, alongside clinical signatures. Two subgroups were identified, one of which associated with elevated C-peptide levels, diabetic complications and more severe insulin resistance compared to the other. GWAS analysis against 403 type 2 diabetes risk variants revealed associations of several SNPs with clusters and altered molecular profiles. We thus demonstrate that heterogeneity in type 2 diabetes can be captured by circulating omics alone using an unsupervised bottom-up approach. Such multiomics signatures could reflect pathological mechanisms underlying type 2 diabetes and thus may help inform on precision medicine approaches to disease management.

Blood biomarkers of multiple sclerosis (MS) can provide a better understanding of pathophysiology and enable disease monitoring. Here, we performed quantitative shotgun lipidomics on the plasma of a unique cohort of 73 monozygotic twins discordant for MS. We analyzed 243 lipid species, evaluated lipid features such as fatty acyl chain length and number of acyl chain double bonds, and detected phospholipids that were significantly altered in the plasma of co‐twins with MS compared to their non‐affected siblings. Strikingly, changes were most prominent in ether phosphatidylethanolamines and ether phosphatidylcholines, suggesting a role for altered lipid signaling in the disease.

Enzyme specificity in lipid metabolic pathways often remains unresolved at the lipid species level, which is needed to link lipidomic molecular phenotypes with their protein counterparts to construct functional pathway maps. We created lipidomic profiles of 23 gene knockouts in a proof-of-concept study based on a CRISPR/Cas9 knockout screen in mammalian cells. This results in a lipidomic resource across 24 lipid classes. We highlight lipid species phenotypes of multiple knockout cell lines compared to a control, created by targeting the human safe-harbor locus AAVS1 using up to 1228 lipid species and subspecies, charting lipid metabolism at the molecular level. Lipid species changes are found in all knockout cell lines, however, some are most apparent on the lipid class level (e.g., SGMS1 and CEPT1), while others are most apparent on the fatty acid level (e.g., DECR2 and ACOT7). We find lipidomic phenotypes to be reproducible across different clones of the same knockout and we observed similar phenotypes when two enzymes that catalyze subsequent steps of the long-chain fatty acid elongation cycle were targeted.

Direct lifetime measurements via gamma -gamma coincidences using a fast timing detector array consisting of LaBr3(Ce) scintillators has been applied to determine the lifetime of low-lying states in the semimagic (N = 50) nucleus Ru-94. The experiment was carried out as the first in a series of "FAIR-0" experiments with the DESPEC experimental setup at the Facility for Antiproton and Ion Research (FAIR). Excited states in Ru-94 were populated primarily via the beta-delayed proton emission of Pd-95 nuclei, produced in the projectile fragmentation of an 850 MeV/nucleon Xe-124 beam impinging on a 4 g/cm(2) Be-9 target. While the deduced E2 strength for the 2(+) -> 0(+) transition in the yrast cascade follows the expected behavior for conserved seniority symmetry, the intermediate 4(+) -> 2(+) transition exhibits a drastic enhancement of transition strength in comparison with pure-seniority model predictions as well as standard shell model predictions in the f pg proton hole space with respect to doubly magic Sn-100. The anomalous behavior is ascribed to a subtle interference between the wave function of the lowest seniority v = 2, I-pi = 4(+) state and that of a close-lying v = 4 state that exhibits partial dynamic symmetry. In addition, the observed strongly prohibitive 6(+) -> 4(+) transition can be attributed to the same mechanism but with a destructive interference. It is noted that such effects may provide stringent tests of the nucleon-nucleon interactions employed in state-of-the-art theoretical model calculations.

OBJECTIVE Type 2 diabetes mellitus (T2DM) is associated with dyslipidemia, but the detailed alterations in lipid species preceding the disease are largely unknown. We aimed to identify plasma lipids associated with development of T2DM and investigate their associations with lifestyle. RESEARCH DESIGN AND METHODS At baseline, 178 lipids were measured by mass spectrometry in 3,668 participants without diabetes from the Malmö Diet and Cancer Study. The population was randomly split into discovery (n = 1,868, including 257 incident cases) and replication (n = 1,800, including 249 incident cases) sets. We used orthogonal projections to latent structures discriminant analyses, extracted a predictive component for T2DM incidence (lipid-PCDM), and assessed its association with T2DM incidence using Cox regression and lifestyle factors using general linear models. RESULTS A T2DM-predictive lipid-PCDM derived from the discovery set was independently associated with T2DM incidence in the replication set, with hazard ratio (HR) among subjects in the fifth versus first quintile of lipid-PCDM of 3.7 (95% CI 2.2–6.5). In comparison, the HR of T2DM among obese versus normal weight subjects was 1.8 (95% CI 1.2–2.6). Clinical lipids did not improve T2DM risk prediction, but adding the lipid-PCDM to all conventional T2DM risk factors increased the area under the receiver operating characteristics curve by 3%. The lipid-PCDM was also associated with a dietary risk score for T2DM incidence and lower level of physical activity. CONCLUSIONS A lifestyle-related lipidomic profile strongly predicts T2DM development beyond current risk factors. Further studies are warranted to test if lifestyle interventions modifying this lipidomic profile can prevent T2DM.

Clinical risk factors explain only a fraction of the variability of estimated glomerular filtration rate (eGFR) decline in people with type 2 diabetes. Cross-omics technologies by virtue of a wide spectrum screening of plasma samples have the potential to identify biomarkers for the refinement of prognosis in addition to clinical variables. Here we utilized proteomics, metabolomics and lipidomics panel assay measurements in baseline plasma samples from the multinational PROVALID study (PROspective cohort study in patients with type 2 diabetes mellitus for VALIDation of biomarkers) of patients with incident or early chronic kidney disease (median follow-up 35 months, median baseline eGFR 84 mL/min/1.73 m(2), urine albumin-to-creatinine ratio 8.1 mg/g). In an accelerated case-control study, 258 individuals with a stable eGFR course (median eGFR change 0.1 mL/min/year) were compared to 223 individuals with a rapid eGFR decline (median eGFR decline -6.75 mL/min/year) using Bayesian multivariable logistic regression models to assess the discrimination of eGFR trajectories. The analysis included 402 candidate predictors and showed two protein markers (KIM-1, NTproBNP) to be relevant predictors of the eGFR trajectory with baseline eGFR being an important clinical covariate. The inclusion of metabolomic and lipidomic platforms did not improve discrimination substantially. Predictions using all available variables were statistically indistinguishable from predictions using only KIM-1 and baseline eGFR (area under the receiver operating characteristic curve 0.63). Thus, the discrimination of eGFR trajectories in patients with incident or early diabetic kidney disease and maintained baseline eGFR was modest and the protein marker KIM-1 was the most important predictor.

Lipidomics has become an indispensable method for the quantitative assessment of lipid metabolism in basic, clinical, and pharmaceutical research. It allows for the generation of information-dense datasets in a large variety of experimental setups and model organisms. Previous studies, mostly conducted in mice (Mus musculus), have shown a remarkable specificity of the lipid compositions of different cell types, tissues, and organs. However, a systematic analysis of the overall variation of the mouse lipidome is lacking. To fill this gap, in the present study, the effect of diet, sex, and genotype on the lipidomes of mouse tissues, organs, and bodily fluids has been investigated. Baseline quantitative lipidomes consisting of 796 individual lipid molecules belonging to 24 lipid classes are provided for 10 different sample types. Furthermore, the susceptibility of lipidomes to the tested parameters is assessed, providing insights into the organ-specific lipidomic plasticity and flexibility. This dataset provides a valuable resource for basic and pharmaceutical researchers working with murine models and complements existing proteomic and transcriptomic datasets. It will inform experimental design and facilitate interpretation of lipidomic datasets.

Low-lying states of Cd-98 have been populated by the two-nucleon removal reaction (In-100, Cd-98+gamma) and studied using in-beam gamma-ray spectroscopy at the Radioactive Isotope Beam Factory at RIKEN. Two new gamma transitions were identified and assigned as decays from a previously unknown state. This state is suggested to be based on a pi 1g(/9/2)(-1)2p(1/2)(-2) configuration with J(pi) = 5(-). The present observation extends the systematics of the excitation energies of the first 5(-) state in N = 50 isotones toward Sn-100. The determined energy of the 5(- )state in Cd-98 continues a smooth trend along the N = 50 isotones. The systematics are compared with shell-model calculations in different model spaces. Good agreement is achieved when considering a model space consisting of the pi(1f(5/2), 2p(3/2), 2p(1/2), 1g(9/2)) orbitals. The calculations with a smaller model space omitting the orbitals below the Z = 38 subshell could not reproduce the experimental energy difference between the ground and first 5(-) states in N = 50 isotones, because proton excitations across Z = 38 subshell yield a large amount of correlation energy that lowers the ground states. (Less)

Most research on human pancreatic islets is conducted on samples obtained from normoglycaemic or diseased brain-dead donors and thus cannot accurately describe the molecular changes of pancreatic islet beta cells as they progress towards a state of deficient insulin secretion in type 2 diabetes (T2D). Here, we conduct a comprehensive multi-omics analysis of pancreatic islets obtained from metabolically profiled pancreatectomized living human donors stratified along the glycemic continuum, from normoglycemia to T2D. We find that islet pools isolated from surgical samples by laser-capture microdissection display remarkably more heterogeneous transcriptomic and proteomic profiles in patients with diabetes than in non-diabetic controls. The differential regulation of islet gene expression is already observed in prediabetic individuals with impaired glucose tolerance. Our findings demonstrate a progressive, but disharmonic, remodelling of mature beta cells, challenging current hypotheses of linear trajectories toward precursor or transdifferentiation stages in T2D. Furthermore, through integration of islet transcriptomics with preoperative blood plasma lipidomics, we define the relative importance of gene coexpression modules and lipids that are positively or negatively associated with HbA1c levels, pointing to potential prognostic markers. Wigger, Barovic and Brunner et al. perform a multidimensional analysis of islets from metabolically characterized patients who had undergone pancreatectomy, observing remarkable heterogeneity between samples from individuals with type 2 diabetes, thus arguing against models of linear beta-cell dedifferentiation in diabetes.

Aims: Inflammation impacts several acute and chronic diseases causing localized stress and cell death, releasing tissue-specific lipids into the circulation from inflamed cells and tissues. The plasma lipidome may be expected to reflect the type of inflammation. However, deep lipid profiles of major chronic inflammatory diseases have not been compared. Methods and Results: We compared the plasma lipidomes of patients suffering from two etiologically distinct chronic inflammatory diseases, atherosclerosis-related cardiovascular disease (CVD) including ischemic stroke (IS), and systemic lupus erythematosus (SLE), to each other and to age-matched controls. The controls had never suffered from any of these diseases. Plasma lipidomes were screened by a top-down shotgun MS-based analysis without liquid chromatographic separation. Lipid profiling of 596 lipids based on MS was performed on a cohort of 427 individuals. Machine learning classifiers based on the plasma lipidomes of patients suffering from CVD and SLE allowed clear distinction of these two chronic inflammatory diseases from each other. We demonstrate convincing evidence for the capability of lipidomics to separate the studied chronic and inflammatory diseases from controls based on independent validation test set classification performance (CVD vs control - Sensitivity: 0.90, Specificity: 0.98; IS vs control - Sensitivity: 1.0, Specificity: 1.0; SLE vs control – Sensitivity: 1, Specificity: 0.88) and from each other (SLE vs CVD ‒ Sensitivity: 0.91, Specificity: 1). Preliminary linear discriminant analysis plots using all data clearly separated the clinical groups from each other and from the controls. In addition, CVD severities, as classified into five clinical groups, were partially separable by linear discriminant analysis. Conclusions: Dysregulation of the plasma lipidome is characteristic of chronic inflammatory diseases. Lipid profiling accurately identifies the diseases and in the case of CVD also identifies sub-classes. Dysregulated lipids are partially but not fully counterbalanced by statin treatment. Clinical Trial Registration Details: This study was registered with the Clinical Trials number NCT04786431 Funding Information: This work was supported by PTDC/MED-PAT/29395/2017 financially supported by Fundacao paraKS is CEO and shareholder of of Lipotype GmbH. CL and MG are KS is CEO and shareholder of of Lipotype GmbH. CL and MG are employees of Lipotype GmbH. All other authors declare that they do not have any competing interestsemployees of Lipotype GmbH. All other authors declare that they do not have any competing interests424 a Ciencia e a Tecnologia (FCT), through national funds and co-funded by FEDER under the PT2020 Partnership. ND was a holder of PhD fellowship from the FCT (Ref. N°:SFRH/BD/51877/2012), attributed 10 by Inter-University Doctoral Programme in Ageing and Chronic Disease (PhDOC). LA was a holder of a FCT PhD fellowship (PD/BD/114254/2016), attributed by the ProRegem Doctoral Programme in 2016. Declaration of Interests: KS is CEO and shareholder of of Lipotype GmbH. CL and MG are employees of Lipotype GmbH. All other authors declare that they do not have any competing interests. Ethics Approval Statement: The entire process was approved by the Ethical Review Board of the Faculty of Medicine of the New University of Lisbon and the Ethics Committee for Health of the Centro Hospitalar de Lisboa Ocidental, that includes the Hospital Santa Cruz, the Hospital Egas Moniz and Hospital Sao Francisco Xavier, and the Ethics Committee for Health of the Hospital Fernando Fonseca. All experiments were performed in accordance with the guidelines and regulations including, the Universal Declaration on Bioethics and Human Rights of UNESCO, 2005; The Charter of Fundamental rights of the EU, 2012; Ethical principles for medical research involving human subjects - Declaration of Helsinki, 2013; EU Regulation 2016/679 and Good Clinical Practice guidelines (Directive 2001/20/EC) and EU Clinical Trials Directive (2005/28/EC). Moreover, they complied with national legislations for the scientific use of human biological samples (Law No 12/2005 and No 131/2014).

We studied the proton-rich T_{z}=-1 nucleus ^{70}Kr through inelastic scattering at intermediate energies in order to extract the reduced transition probability, B(E2;0^{+}→2^{+}). Comparison with the other members of the A=70 isospin triplet, ^{70}Br and ^{70}Se, studied in the same experiment, shows a 3σ deviation from the expected linearity of the electromagnetic matrix elements as a function of T_{z}. At present, no established nuclear structure theory can describe this observed deviation quantitatively. This is the first violation of isospin symmetry at this level observed in the transition matrix elements. A heuristic approach may explain the anomaly by a shape change between the mirror nuclei ^{70}Kr and ^{70}Se contrary to the model predictions.

We report on a study of the performance of the DEGAS-FATIMA Hybrid setup through GEANT4 simulations using accurate geometries of all detector components. We give details on the most compact detector configuration considered for this setup when maximizing efficiencies of both DEGAS (HpGe) and FATIMA (LaBr 3 (Ce)) systems with respect to a heavy-ion implantation and β -decay station. The possible configurations of the implantation system are discussed in terms of thickness variation and individual positioning of detector components. We provide guidelines for the Hybrid setup for the first NUSTAR/DESPEC experiments.

Summary After demyelinating injury of the central nervous system, resolution of the mounting acute inflammation is crucial for the initiation of a regenerative response. Here, we aim to identify fatty acids and lipid mediators that govern the balance of inflammatory reactions within demyelinating lesions. Using lipidomics, we identify bioactive lipids in the resolution phase of inflammation with markedly elevated levels of n-3 polyunsaturated fatty acids. Using fat-1 transgenic mice, which convert n-6 fatty acids to n-3 fatty acids, we find that reduction of the n-6/n-3 ratio decreases the phagocytic infiltrate. In addition, we observe accelerated decline of microglia/macrophages and enhanced generation of oligodendrocytes in aged mice when n-3 fatty acids are shuttled to the brain. Thus, n-3 fatty acids enhance lesion recovery and may, therefore, provide the basis for pro-regenerative medicines of demyelinating diseases in the central nervous system., Graphical abstract, Highlights • Lipid and fatty acid abundance is specifically altered during de- and remyelination • Reduction of pro- and anti-inflammatory lipid mediators impairs lesion recovery • DHA supplementation fosters phagocyte decline and oligodendrocyte generation • n-3 fatty acid supplementation may be a strategy to promote remyelination, Penkert et al. employ sequential proteomics and lipidomics to elucidate the role of lipid mediators in lesion recovery in a mouse model of focal, cerebral demyelination. Using genetic and pharmacologic interventions, they find n-3 fatty acid supplementation, specifically DHA, to enhance innate inflammation resolution and oligodendrocyte generation.

Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity, investigators of a previous study clustered people with diabetes according to five diabetes subtypes. The aim of the current study is to investigate the etiology of these clusters by comparing their molecular signatures. In three independent cohorts, in total 15,940 individuals were clustered based on five clinical characteristics. In a subset, genetic (N = 12,828), metabolomic (N = 2,945), lipidomic (N = 2,593), and proteomic (N = 1,170) data were obtained in plasma. For each data type, each cluster was compared with the other four clusters as the reference. The insulin-resistant cluster showed the most distinct molecular signature, with higher branched-chain amino acid, diacylglycerol, and triacylglycerol levels and aberrant protein levels in plasma were enriched for proteins in the intracellular PI3K/Akt pathway. The obese cluster showed higher levels of cytokines. The mild diabetes cluster with high HDL showed the most beneficial molecular profile with effects opposite of those seen in the insulin-resistant cluster. This study shows that clustering people with type 2 diabetes can identify underlying molecular mechanisms related to pancreatic islets, liver, and adipose tissue metabolism. This provides novel biological insights into the diverse aetiological processes that would not be evident when type 2 diabetes is viewed as a homogeneous disease.

Physics letters / B 816, 136183 (2021). doi:10.1016/j.physletb.2021.136183, Published by North-Holland Publ., Amsterdam

Aims/hypothesisFive clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes (T2D). In the current study we replicate and cross-validate these T2D clusters in three large cohorts using readily measured variables in the clinic.MethodsIn this cross-sectional study, 15,940 individuals were clustered based on age, BMI, HbA1c, random or fasting C-peptide and HDL in three independent cohorts. Clusters were cross-validated against the original clusters based on HOMA measures. In addition, between cohorts, clusters were cross-validated by re-assigning people based on each cohort’s cluster centres.ResultsFive distinct T2D clusters were identified and mapped back to the original four ANDIS clusters. Using C-peptide and HDL instead of HOMA-B and HOMA-S three of the clusters mapped with high sensitivity (80.6 – 90.7%) to the previously identified Severe Insulin Deficient (SIDD), Severe insulin resistant (SIRD) and Obese (MOD) clusters. The previously described ANDIS MARD cluster could be mapped to the two milder groups in our study – one characterised by high HDL, and the other having not any extreme characteristic (MDH cluster). When these two milder groups were combined they mapped well to the previously labelled MARD cluster (sensitivity 79.4%). In the cross-validation between cohorts, particularly the SIDD and MDH cluster cross-validated well with sensitivities ranging from 73.3% to 97.1%. SIRD and MD showed a lower sensitivity ranging from 36.1% to 92.3% where individuals shifted from SIRD to MD and vice versa.Conclusions/interpretationClusters based on C-peptide instead of HOMA measures result in clusters that resemble those based on HOMA measures, especially for SIDD, SIRD and MOD. By adding HDL, the MARD cluster based upon HOMA measures resulted in the current clustering in two clusters with one cluster having high HDL levels. Cross-validation between cohorts showed generally a good resemblance between cohorts. Together, our results show that the clustering based on clinical variables readily measured in the clinic (age, HbA1c, HDL, BMI and C-peptide) results in informative clusters that are representative of the original ANDIS clusters and stable across cohorts.

A Geant4 simulation has been carried out in order to determine the B-detection efficiency of a rare isotope beam implantation setup, for decay spectroscopy experiments, comprising a number of Double Sided Silicon Strip Detectors (DSSSDs) and two plastic scintillation detectors placed upstream and downstream. The absolute efficiency for the emitted B-particle detection from radioactive fragments implanted in the DSSSDs using fast-timing plastic-scintillator detector, is calculated. The detection efficiency of the setup has been studied with two different distances between the Si layers and plastics. The requirement for the thickness of the Si detector layers and its implication on the B-detection effciency has been investigated for 1 mm and 300 um thickness of Si layers. The combined efficiency of DSSSD and plastic detectors were also simulated for two different thicknesses of the DSSSD.

Objective Refeeding is the cornerstone of anorexia nervosa (AN) treatment, but little is known regarding the optimal pace and dietary composition or possible adverse effects of current clinical practices. Plasma lipids may be a moderating factor underlying unfavorable refeeding effects in AN, such as an abnormal central body fat distribution. The objective of this study was to analyze the plasma lipidome in the acutely underweight state of AN before and after refeeding. Method Using high-throughput quantitative mass spectrometry−based shotgun lipidomics, we measured 13 lipid classes and 204 lipid species or subspecies in the plasma of young female patients with acute AN, before (n = 39) and after (n = 23) short-term weight restoration during an intensive inpatient refeeding program (median body mass index [BMI] increase = 26.4%), in comparison to those in healthy control participants (n = 37). Results Before inpatient treatment, patients with AN exhibited increased concentrations of cholesterol and several other lipid classes. After refeeding, multiple lipid classes including cholesterol and ceramides, as well as certain ceramide species previously associated with obesity or overfeeding, showed increased concentrations, and a pattern of shorter and more saturated triacylgycerides emerged. A machine learning model trained to predict BMI based on the lipidomic profiles revealed a sizable overprediction in patients with AN after weight restoration. Conclusion The results point toward a profound lipid dysregulation with similarities to obesity and other features of the metabolic syndrome after short-term weight restoration. Thus, this study provides evidence for possible short-term adverse effects of current refeeding practices on the metabolic state and should inspire more research on nutritional interventions in AN.

Here we present new information on the shape evolution of the very neutron-rich ^{92,94}Se nuclei from an isomer-decay spectroscopy experiment at the Radioactive Isotope Beam Factory at RIKEN. High-resolution germanium detectors were used to identify delayed γ rays emitted following the decay of their isomers. New transitions are reported extending the previously known level schemes. The isomeric levels are interpreted as originating from high-K quasineutron states with an oblate deformation of β∼0.25, with the high-K state in ^{94}Se being metastable and K hindered. Following this, ^{94}Se is the lowest-mass neutron-rich nucleus known to date with such a substantial K hindrance. Furthermore, it is the first observation of an oblate K isomer in a deformed nucleus. This opens up the possibility for a new region of K isomers at low Z and at oblate deformation, involving the same neutron orbitals as the prolate orbitals within the classic Z∼72 deformed hafnium region. From an interpretation of the level scheme guided by theoretical calculations, an oblate deformation is also suggested for the ^{94}Se_{60} ground-state band.

Here we present new information on the shape evolution of the very neutron-rich ^{92,94}Se nuclei from an isomer-decay spectroscopy experiment at the Radioactive Isotope Beam Factory at RIKEN. High-resolution germanium detectors were used to identify delayed γ rays emitted following the decay of their isomers. New transitions are reported extending the previously known level schemes. The isomeric levels are interpreted as originating from high-K quasineutron states with an oblate deformation of β∼0.25, with the high-K state in ^{94}Se being metastable and K hindered. Following this, ^{94}Se is the lowest-mass neutron-rich nucleus known to date with such a substantial K hindrance. Furthermore, it is the first observation of an oblate K isomer in a deformed nucleus. This opens up the possibility for a new region of K isomers at low Z and at oblate deformation, involving the same neutron orbitals as the prolate orbitals within the classic Z∼72 deformed hafnium region. From an interpretation of the level scheme guided by theoretical calculations, an oblate deformation is also suggested for the ^{94}Se_{60} ground-state band.

AGATA Collaboration, New physics opportunities are opening up by the Advanced Gamma Tracking Array, AGATA, as it evolves to the full 4π instrument. AGATA is a high-resolution γ-ray spectrometer, solely built from highly segmented high-purity Ge detectors, capable of measuring γ rays from a few tens of keV to beyond 10 MeV, with unprecedented efficiency, excellent position resolution for individual γ-ray interactions, and very high count-rate capability. As a travelling detector AGATA will be employed at all major current and near-future European research facilities delivering stable and radioactive ion beams., The AGATA project has been supported by the European Structural Funds FSE FEDER, the Academy of Finland FIRI program, Finland, the Direction de Recherches Fondamentales of CEA, France, the Institut National de Physique Nucléaire et de Physique des Particules (IN2P3) of CNRS, France, the Bundesministerium für Bildung und Forschung (BMBF), Germany, the Institute of Nuclear Research of the Hungarian Academy of Sciences (ATOMKI), Hungary, the IstitutoNazionale di Fisica Nucleare (INFN), Italy, theNational Science Center (NCN), Poland, the Knut and AliceWallenberg foundation (Sweden), the Swedish Research Council, the Conselleria d’Educació, Investigació, Cultura i Esport, Generalitat Valenciana and Ministerio de Ciencia, Innovación y Universidades, Spain, the Türkiye Bilimsel ve Teknolojik Ara¸stirma Kurumu (TÜBITAK), Turkey, and the United Kingdom Research and Innovation – Science and Technology Facilities Council (UKRI-STFC).

6 pags., 4 figs., The γ-ray emission from the nuclei Fe following Coulomb excitation at bombarding energy of 400-440 AMeV was measured with special focus on E1 transitions in the energy region 4-8 MeV. The unstable neutron-rich nuclei Fe were produced at the FAIR-GSI laboratories and selected with the FRS spectrometer. The γ decay was detected with AGATA. From the measured γ-ray spectra the summed E1 strength is extracted and compared to microscopic quasi-particle phonon model calculations. The trend of the E1 strength with increasing neutron number is found to be fairly well reproduced with calculations that assume a rather complex structure of the 1 states (three-phonon states) inducing a strong fragmentation of the E1 nuclear response below the neutron binding energy., This work was partially supported by INFN (Italy) and STFC (UK), the Swedish Research Council (Vetenskapsrådet, VR 2010-147, 2011-5253, and 2016-3969), BMBF NuSTAR-AGATA 05P18RDFN9 and BMBF NuSTAR 05P18RDFN1. The project was co-funded by the European Commission under the 7th Framework Program for RTD (2007-2013) under the Capacities Program (Contract Number 262010, ENSAR). This work was par-tially supported by the Ministry of Science, and Generalitat Valenciana, Spain, under the Grants SEV-2014-0398, FPA2017-84756-C4, PROMETEO/2019/005 and by the EU FEDER funds.

International audience; A first performance test of the Coulomb excitation multipolarimetry (Coulex-multipolarimetry) method is presented. It is based on a $^{85}\hbox {Br}\,\pi p_{3/2}\rightarrow \pi p_{1/2}$ spin-flip experiment performed as part of the PreSPEC-AGATA campaign at the GSI Helmholtzzentrum für Schwerionenforschung (GSI). Via determination of background levels around the expected $^{85}\hbox {Br}$ excitations as well as measured $^{197}\hbox {Au}$ excitations, an upper limit for the M1 transition strength of the $1/2_1^-\rightarrow 3/2_\text {g.s.}^-$ transition in $^{85}\hbox {Br}$ and a lower beam time limit for upcoming experimental campaigns utilizing Coulex-multipolarimetry have been inferred. The impact of the use of AGATA in its anticipated $1\pi $ configuration on these estimates is deduced via Geant4 simulations.

12 pags., 11 figs., 2 tabs., The N= Z= 36 nucleus Kr has been studied by inelastic scattering at intermediate energies. Two targets, Be and Au, were used to extract the nuclear deformation length, δ, and the reduced E2 transition probability, B(E2). The previously unknown non-yrast 2 and 4 states as well as a new candidate for the octupole 3 state have been observed in the scattering on the Be target and placed in the level scheme based on γ- γ coincidences. The second 2 state was also observed in the scattering on the Au target and the B(E2;22+→01+) value could be determined for the first time. Analyzing the results in terms of a two-band mixing model shows clear evidence for a oblate-prolate shape coexistence and can be explained by a shape change from an oblate ground state to prolate deformed yrast band from the first 2 state. This interpretation is corroborated by beyond mean field calculations using the Gogny D1S interaction., We would like to thank the RIKEN accelerator and BigRIPS teams for providing the high intensity beams. We thank T. Furumoto for providing us with the optical potentials and A. Moro for giving access to an unpublished version of the FRESCO code. This work has been supported by UK STFC under Grant numbers ST/L005727/1 and ST/P003885/1, the Spanish Ministerio de Economía y Competitividad under Grants FPA2011-24553, FPA2014-52823-C2- 1-P, and PGC2018-094583-B-I00, the Program Severo Ochoa (SEV2014-0398), the European Research Council through the ERC Grant No. MINOS-258567, NKFIH (NN128072), and by the ÚNKP-19-4- DE-65 New National Excellence Program of the Ministry of Human Capacities of Hungary. G. K. acknowledges support from the János Bolyai research fellowship of the Hungarian Academy of Sciences. K. W. acknowledges the support from the Spanish Ministerio de Economía y Competitividad RYC-2017-22007.

Nuclear instruments & methods in physics research / A Accelerators, spectrometers, detectors and associated equipment Section A 969, 163967 (2020). doi:10.1016/j.nima.2020.163967, Published by North-Holland Publ. Co., Amsterdam

Obesity is associated with changes in the plasma lipids. Although simple lipid quantification is routinely used, plasma lipids are rarely investigated at the level of individual molecules. We aimed at predicting different measures of obesity based on the plasma lipidome in a large population cohort using advanced machine learning modeling. A total of 1,061 participants of the FINRISK 2012 population cohort were randomly chosen, and the levels of 183 plasma lipid species were measured in a novel mass spectrometric shotgun approach. Multiple machine intelligence models were trained to predict obesity estimates, i.e., body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), and body fat percentage (BFP), and validated in 250 randomly chosen participants of the Malmö Diet and Cancer Cardiovascular Cohort (MDC-CC). Comparison of the different models revealed that the lipidome predicted BFP the best (R2 = 0.73), based on a Lasso model. In this model, the strongest positive and the strongest negative predictor were sphingomyelin molecules, which differ by only 1 double bond, implying the involvement of an unknown desaturase in obesity-related aberrations of lipid metabolism. Moreover, we used this regression to probe the clinically relevant information contained in the plasma lipidome and found that the plasma lipidome also contains information about body fat distribution, because WHR (R2 = 0.65) was predicted more accurately than BMI (R2 = 0.47). These modeling results required full resolution of the lipidome to lipid species level, and the predicting set of biomarkers had to be sufficiently large. The power of the lipidomics association was demonstrated by the finding that the addition of routine clinical laboratory variables, e.g., high-density lipoprotein (HDL)- or low-density lipoprotein (LDL)- cholesterol did not improve the model further. Correlation analyses of the individual lipid species, controlled for age and separated by sex, underscores the multiparametric and lipid species-specific nature of the correlation with the BFP. Lipidomic measurements in combination with machine intelligence modeling contain rich information about body fat amount and distribution beyond traditional clinical assays., Obesity is associated with changes in plasma lipids, but while simple lipid quantification is routinely used, plasma lipids are rarely investigated at the level of individual molecules. A machine learning study based on lipidomes of a total of 1,311 individuals reveals improved associations of plasma lipids with total body fat and fat distribution compared to routine clinical laboratory variables.

The performance of the novel HPGe-Cluster array DEGAS to be used at FAIR has been studied through GEANT4 simulations using accurate geometries of most of the detector components. The simulation framework has been tested by comparing experimental data of various detector setups. The study showed that the DEGAS system could provide a clear improvement of the photo-peak efficiency compared to the previous RISING array. In addition, the active BGO Back-catcher could greatly enhance the background suppression capability. The add-back analysis revealed that even at a γ multiplicity of six the sensitivity is improved by adding back the energy depositions of the neighboring Ge crystals.

Physics letters / B 820, 136591 (2021). doi:10.1016/j.physletb.2021.136591, Published by North-Holland Publ., Amsterdam

Context Meal timing affects metabolic homeostasis and body weight, but how composition and timing of meals affect plasma lipidomics in humans is not well studied. Objective We used high throughput shotgun plasma lipidomics to investigate effects of timing of carbohydrate and fat intake on lipid metabolism and its relation to glycemic control. Design 29 nondiabetic men consumed (1) a high-carb test meal (MTT-HC) at 09.00 and a high-fat meal (MTT-HF) at 15.40; or (2) MTT-HF at 09.00 and MTT-HC at 15.40. Blood was sampled before and 180 minutes after completion of each MTT. Subcutaneous adipose tissue (SAT) was collected after overnight fast and both MTTs. Prior to each investigation day, participants consumed a 4-week isocaloric diet of the same composition: (1) high-carb meals until 13.30 and high-fat meals between 16.30 and 22:00 or (2) the inverse order. Results 12 hour daily lipid patterns showed a complex regulation by both the time of day (67.8%) and meal composition (55.4%). A third of lipids showed a diurnal variation in postprandial responses to the same meal with mostly higher responses in the morning than in the afternoon. Triacylglycerols containing shorter and more saturated fatty acids were enriched in the morning. SAT transcripts involved in fatty acid synthesis and desaturation showed no diurnal variation. Diurnal changes of 7 lipid classes were negatively associated with insulin sensitivity, but not with glucose and insulin response or insulin secretion. Conclusions This study identified postprandial plasma lipid profiles as being strongly affected by meal timing and associated with insulin sensitivity.

A systematic study was performed of microsecond γ-decaying isomers around Sn100 produced in a fragmentation reaction of a Xe124 beam at 345 MeV/u at the Radioactive Ion Beam Factory of the RIKEN Nishina Center in Saitama, Japan. Half-lives of isomeric states in that region were remeasured allowing us to improve the currently available experimental information. Reduced transition probabilities were deduced and compared to shell-model calculations in various model spaces. The recently reported low-energy transitions in Rh92 and Ag96 were remeasured with improved precision. Additionally, experimental information on isomeric ratios, including five new ones, were extracted and compared to a previous experimental study and the sharp cutoff model of fragmentation reaction.

Background We asked whether, after excluding familial hypercholesterolemia, individuals with high low‐density lipoprotein cholesterol ( LDL ‐C) or triacylglyceride levels and a family history of the same hyperlipidemia have greater coronary artery disease risk or different lipidomic profiles compared with population‐based hyperlipidemias. Methods and Results We determined incident coronary artery disease risk for 755 members of 66 hyperlipidemic families (≥2 first‐degree relatives with similar hyperlipidemia) and 19 644 Finnish FINRISK population study participants. We quantified 151 circulating lipid species from 550 members of 73 hyperlipidemic families and 897 FINRISK participants using mass spectrometric shotgun lipidomics. Familial hypercholesterolemia was excluded using functional LDL receptor testing and genotyping. Hyperlipidemias ( LDL ‐C or triacylglycerides >90th population percentile) associated with increased coronary artery disease risk in meta‐analysis of the hyperlipidemic families and the population cohort (high LDL ‐C: hazard ratio, 1.74 [95% CI, 1.48–2.04]; high triacylglycerides: hazard ratio, 1.38 [95% CI, 1.09–1.74]). Risk estimates were similar in the family and population cohorts also after adjusting for lipid‐lowering medication. In lipidomic profiling, high LDL ‐C associated with 108 lipid species, and high triacylglycerides associated with 131 lipid species in either cohort (at 5% false discovery rate; P ‐value range 0.038–2.3×10 −56 ). Lipidomic profiles were highly similar for hyperlipidemic individuals in the families and the population ( LDL ‐C: r =0.80; triacylglycerides: r =0.96; no lipid species deviated between the cohorts). Conclusions Hyperlipidemias with family history conferred similar coronary artery disease risk as population‐based hyperlipidemias. We identified distinct lipidomic profiles associated with high LDL ‐C and triacylglycerides. Lipidomic profiles were similar between hyperlipidemias with family history and population‐ascertained hyperlipidemias, providing evidence of similar and overlapping underlying mechanisms.

The neutron-rich isotopes 211;213Tl, beyond the N = 126 shell-closure, have been studied for the first time in isomer γ-ray decay, exploiting the fragmentation of a primary uranium beam at the FRS-RISING (FRagment Separator-Rare ISotopes INvestigation at GSI) setup at GSI. The observed isomeric states in 211;213Tl show a deviation from the seniority-like scheme of 209Tl. The possible interpretation of the data is discussed on the basis of energy-level systematics and shell-model calculations.

The proton-rich isotope 68Br was discovered in secondary fragmentation reactions of fast radioactive beams. Proton-rich secondary beams of 70,71,72Kr and 70Br, produced at the RIKEN Nishina Center and identified by the BigRIPS fragment separator, impinged on a secondary 9Be target. Unambiguous particle identification behind the secondary target was achieved with the ZeroDegree spectrometer. Based on the expected direct production cross sections from neighboring isotopes, the lifetime of the ground or long-lived isomeric state of 68Br was estimated. The results suggest that secondary fragmentation reactions, where relatively few nucleons are removed from the projectile, offer an alternative way to search for new isotopes, as these reactions populate preferentially low-lying states., Comment: Phys. Lett. B accepted