PALEO-PGEM v1.0: a statistical emulator of Pliocene–Pleistocene climate

We describe the development of the “Paleoclimate PLASIM-GENIE (Planet Simulator–Grid-Enabled Integrated Earth system model) emulator” PALEO-PGEM and its application to derive a downscaled high-resolution spatio-temporal description of the climate of the last 5×106 years. The 5×106-year time frame is interesting for a range of paleo-environmental questions, not least because it encompasses the evolution of humans. However, the choice of time frame was primarily pragmatic; tectonic changes can be neglected to first order, so that it is reasonable to consider climate forcing restricted to the Earth's orbital configuration, ice-sheet state, and the concentration of atmosphere CO2. The approach uses the Gaussian process emulation of the singular value decomposition of ensembles of the intermediate-complexity atmosphere–ocean GCM (general circulation model) PLASIM-GENIE. Spatial fields of bioclimatic variables of surface air temperature (warmest and coolest seasons) and precipitation (wettest and driest seasons) are emulated at 1000-year intervals, driven by time series of scalar boundary-condition forcing (CO2, orbit, and ice volume) and assuming the climate is in quasi-equilibrium. Paleoclimate anomalies at climate model resolution are interpolated onto the observed modern climatology to produce a high-resolution spatio-temporal paleoclimate reconstruction of the Pliocene–Pleistocene

Clinical Characteristics of Patients with Severe Asthma by Different Elevated Biomarkers Classifications : patients from Spain in the ISAR Registry

Peer reviewe

Baseline disease burden in severe asthma patients treated with biologics, and eligible but not treated : Spanish patients in the ISAR Registry

Peer reviewe

Novel Metabolic Markers for the Risk of Diabetes Development in American Indians

OBJECTIVETo identify novel metabolic markers for diabetes development in American Indians.RESEARCH DESIGN AND METHODSUsing an untargeted high-resolution liquid chromatography–mass spectrometry, we conducted metabolomics analysis of study participants who developed incident diabetes (n = 133) and those who did not (n = 298) from 2,117 normoglycemic American Indians followed for an average of 5.5 years in the Strong Heart Family Study. Relative abundances of metabolites were quantified in baseline fasting plasma of all 431 participants. Prospective association of each metabolite with risk of developing type 2 diabetes (T2D) was examined using logistic regression adjusting for established diabetes risk factors.RESULTSSeven metabolites (five known and two unknown) significantly predict the risk of T2D. Notably, one metabolite matching 2-hydroxybiphenyl was significantly associated with an increased risk of diabetes, whereas four metabolites matching PC (22:6/20:4), (3S)-7-hydroxy-2′,3′,4′,5′,8-pentamethoxyisoflavan, or tetrapeptides were significantly associated with decreased risk of diabetes. A multimarker score comprising all seven metabolites significantly improved risk prediction beyond established diabetes risk factors including BMI, fasting glucose, and insulin resistance.CONCLUSIONSThe findings suggest that these newly detected metabolites may represent novel prognostic markers of T2D in American Indians, a group suffering from a disproportionately high rate of T2D

A CURE on the Evolution of Antibiotic Resistance in <i>Escherichia coli</i> Improves Student Conceptual Understanding

We developed labs on the evolution of antibiotic resistance to assess the costs and benefits of replacing traditional laboratory exercises in an introductory biology course for majors with a course-based undergraduate research experience (CURE). To assess whether participating in the CURE imposed a cost in terms of exam performance, we implemented a quasi-experiment in which four lab sections in the same term of the same course did the CURE labs, while all other students did traditional labs. To assess whether participating in the CURE impacted other aspects of student learning, we implemented a second quasi-experiment in which all students either did traditional labs over a two-quarter sequence or did CURE labs over a two-quarter sequence. Data from the first experiment showed minimal impact on CURE students' exam scores, while data from the second experiment showed that CURE students demonstrated a better understanding of the culture of scientific research and a more expert-like understanding of evolution by natural selection. We did not find disproportionate costs or benefits for CURE students from groups that are minoritized in science, technology, engineering, and mathematics

Metabolic Profiles of Obesity in American Indians: The Strong Heart Family Study

The authors would like to thank the Strong Heart Study participants, Indian Health Service facilities, and participating tribal communities for their extraordinary cooperation and involvement, which has contributed to the success of the Strong Heart Study. The views expressed in this article are those of the authors and do not necessarily reflect those of the Indian Health Service.Obesity is a typical metabolic disorder resulting from the imbalance between energy intake and expenditure. American Indians suffer disproportionately high rates of obesity and diabetes. The goal of this study is to identify metabolic profiles of obesity in 431 normoglycemic American Indians participating in the Strong Heart Family Study. Using an untargeted liquid chromatography–mass spectrometry, we detected 1,364 distinct m/z features matched to known compounds in the current metabolomics databases. We conducted multivariate analysis to identify metabolic profiles for obesity, adjusting for standard obesity indicators. After adjusting for covariates and multiple testing, five metabolites were associated with body mass index and seven were associated with waist circumference. Of them, three were associated with both. Majority of the obesity-related metabolites belongs to lipids, e.g., fatty amides, sphingolipids, prenol lipids, and steroid derivatives. Other identified metabolites are amino acids or peptides. Of the nine identified metabolites, five metabolites (oleoylethanolamide, mannosyl-diinositol-phosphorylceramide, pristanic acid, glutamate, and kynurenine) have been previously implicated in obesity or its related pathways. Future studies are warranted to replicate these findings in larger populations or other ethnic groups.Yeshttp://www.plosone.org/static/editorial#pee

Npn-1 Contributes to Axon-Axon Interactions That Differentially Control Sensory and Motor Innervation of the Limb

The initiation, execution, and completion of complex locomotor behaviors are depending on precisely integrated neural circuitries consisting of motor pathways that activate muscles in the extremities and sensory afferents that deliver feedback to motoneurons. These projections form in tight temporal and spatial vicinities during development, yet the molecular mechanisms and cues coordinating these processes are not well understood. Using cell-type specific ablation of the axon guidance receptor Neuropilin-1 (Npn-1) in spinal motoneurons or in sensory neurons in the dorsal root ganglia (DRG), we have explored the contribution of this signaling pathway to correct innervation of the limb. We show that Npn-1 controls the fasciculation of both projections and mediates inter-axonal communication. Removal of Npn-1 from sensory neurons results in defasciculation of sensory axons and, surprisingly, also of motor axons. In addition, the tight coupling between these two heterotypic axonal populations is lifted with sensory fibers now leading the spinal nerve projection. These findings are corroborated by partial genetic elimination of sensory neurons, which causes defasciculation of motor projections to the limb. Deletion of Npn-1 from motoneurons leads to severe defasciculation of motor axons in the distal limb and dorsal-ventral pathfinding errors, while outgrowth and fasciculation of sensory trajectories into the limb remain unaffected. Genetic elimination of motoneurons, however, revealed that sensory axons need only minimal scaffolding by motor axons to establish their projections in the distal limb. Thus, motor and sensory axons are mutually dependent on each other for the generation of their trajectories and interact in part through Npn-1-mediated fasciculation before and within the plexus region of the limbs

Location, location, location: Beneficial effects of autologous fat transplantation

Visceral adiposity is a risk factor for cardiovascular disorders, type 2 diabetes mellitus (T2D) and associated metabolic diseases. Sub-cutaneous fat is believed to be intrinsically different from visceral fat. To understand molecular mechanisms involved in metabolic advantages of fat transplantation, we studied a rat model of diet-induced adiposity. Adipokine genes (Adiponectin, Leptin, Resistin and Visfatin) were expressed at 10,000 to a million-fold lower in visceral fat depot as compared to peripheral (thigh/chest) fat depots. Interestingly, autologous transplantation of visceral fat to subcutaneous sites resulted in increased gene transcript abundance in the grafts by 3 weeks post-transplantation, indicating the impact of local (residence) factors influencing epigenetic memory. We show here that active transcriptional state of adipokine genes is linked with glucose mediated recruitment of enzymes that regulate histone methylation. Adipose depots have “residence memory” and autologous transplantation of visceral fat to sub-cutaneous sites offers metabolic advantage

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages