Miracle-dz/UniFAR-FTUs huggingface dataset:
Schizophrenia-derived hiPSC brain microvascular endothelial cells show impairments in angiogenesis and blood-brain barrier function

Schizophrenia (SZ) is a complex neuropsychiatric disorder, affecting 1% of the world population. Long-standing clinical observations and molecular data have pointed out a possible vascular deficiency that could be acting synergistically with neuronal dysfunction in SZ. As SZ is a neurodevelopmental disease, the use of human induced pluripotent stem cells (hiPSC) allows disease biology modeling retaining the patient’s unique genetic signature. Previously, we reported a VEGF-A signaling impairment in SZ-hiPSC derived neural lineages leading to a decreased angiogenesis. Here, we present a functional characterization of SZ-derived brain microvascular endothelial-like cells (BEC), the counterpart of the neurovascular crosstalk, revealing an intrinsically defective Blood-Brain Barrier (BBB) phenotype. Transcriptomic assessment of genes related to endothelial function among three control (Ctrl BEC) and five schizophrenia patients derived BEC (SZP BEC), revealed that SZP BEC have a distinctive expression pattern of angiogenic and BBB-associated genes. Functionally, SZP BEC showed a decreased angiogenic response in vitro and higher transpermeability than Ctrl BEC. Immunofluorescence staining revealed less expression and altered distribution of tight junction proteins in SZP BEC. Moreover, SZP BEC’s secretome reduced barrier capacities in the brain microvascular endothelial cell line HCMEC/D3 and in an in vivo permeability assay in mice. Overall, our results describe an intrinsic failure of SZP BEC for proper barrier function. These findings are consistent with the hypothesis that traces schizophrenia origins to brain development and BBB dysfunction.
Stratospheric ClONO2 and HNO3 profiles inside the Arctic vortex from MIPAS-B limb emission spectra obtained during EASOE

Vertical profiles of ClONO2 and HNO3 inside the Arctic vortex have been retrieved from infrared limb emission spectra recorded during balloon flights on January 13 and in the night of March 14/15, 1992 from Esrange, Sweden (68°N) as part of the European Arctic Stratospheric Ozone Experiment (EASOE). The instrumentation used was the cryogenic Michelson Interferometer for Passive Atmospheric Sounding, Balloon-borne version (MIPAS-B). Low ClONO2 abundances in mid-January indicate that a significant portion of ClONO2 had already been converted at that time. An unexpectedly high ClONO2 amount (1.8 to 3.1 ppbv between 16.1 and 21.5 km altitude) has been inferred from the March flight data. This implies that obviously most of the total available chlorine (ClOy) in the lower stratosphere was then in this reservoir molecule. The measured HNO3 profiles give no hint of any significant layered removal of gaseous HNO3 by condensation on particles or/and sedimentation.
An effect of dissolved nutrient concentrations on alkenone‐based temperature estimates

The ratio of 37-carbon diunsaturated to diunsaturated and triunsaturated alkenones (UK′37) produced by some haptophytes is widely used as a proxy for past sea surface temperatures. However, our isothermal culturing experiments with Emiliania huxleyi clone CCMP372 show UK′37 values to also vary with nutrient availability and cell division rate. These results provide a reasonable explanation for large isothermal variation in UK′37 values of single coccolithophorid strains grown in culture. They also suggest that alkenone-based estimates of past sea surface temperatures may have been influenced by dissolved nutrient concentrations as well as by temperature.
In Vitro Metabolism of Slowly Cleared G Protein – Coupled Receptor 139 Agonist TAK-041 Using Rat, Dog, Monkey, and Human Hepatocyte Models (HepatoPac): Correlation with In Vivo Metabolism

Hepatic metabolism of low-clearance compound TAK-041 was studied in two different in vitro model systems using rat, dog, monkey, and human suspended cryopreserved hepatocytes and HepatoPac micropatterned coculture model primary hepatocytes. The aim of this work was to investigate the most appropriate system to assess the biotransformation of TAK-041, determine any notable species difference in the rate and in the extent of its metabolic pathways, and establish correlation with in vivo metabolism. TAK-041 exhibited very low turnover in suspended cryopreserved hepatocyte suspensions for all species, with no metabolites observed in human hepatocytes. However, incubations conducted for up to 14 days in the HepatoPac model resulted in more robust metabolic turnover. The major biotransformation pathways of TAK-041 proceed via hydroxylation on the benzene ring fused to the oxotriazine moiety and subsequent sulfate, glucuronide, and glutathione conjugation reactions. The glutathione conjugate of TAK-041 undergoes further downstream metabolism to produce the cysteine S-conjugate, which then undergoes N -acetylation to mercapturic acid and/or conversion to b -lyase – derived thiol metabolites. The minor biotransformation pathways include novel ring closure and hydrolysis, hydroxylation, oxidative N -dealkylation, and subsequent reduction. The HepatoPac model shows a notable species difference in the rate and in the extent of metabolic pathways of TAK-041, with dogs having the fastest metabolic clearance and humans the slowest. Furthermore, the model shows its suitability for establishing correlation with in vivo metabolism of low-turnover and extensively metabolized compounds such as TAK-041, displaying an extensive and unusual downstream sequential b -lyase – derived thiol metabolism in preclinical species and human.
The cognitive-emotional brain: Opportunities and challenges for understanding neuropsychiatric disorders

Many of the most common neuropsychiatric disorders are marked by prominent disturbances of cognition and emotion. Characterizing the complex neural circuitry underlying the interaction and integration of cognition and emotion is critically important, not just for clarifying the nature of the mind, but also for discovering the root causes of debilitating mental disorders, including anxiety, schizophrenia, and chronic pain. Until the 20th century, the study of cognition and emotion was largely a philosophical matter. But recent years have witnessed the emergence of powerful new tools for interrogating the brain and new areas of multidisciplinary research focused on identifying the neurobiological mechanisms underlying cognition, emotion, and their role in mental health and disease. In The Cognitive-Emotional Brain, Luiz Pessoa provides an authoritative perspective on this recent work and its implications for our understanding of the basic building blocks of the mind. Here, we highlight four of the book’s most important implications for understanding neuropsychiatric disorders, including anxiety, schizophrenia, substance abuse, chronic pain, and autism. These disorders cause enormous suffering for millions of patients and their families, outstripping the global burden of cancer or cardiovascular disease (Collins et al., 2011; Goldberg & McGee, 2011; Kessler, Petukhova, Sampson, Zaslavsky, & Wittchen, 2012; Whiteford et al., in press). Importantly, these disorders involve prominent alterations in both cognition and emotion (Millan et al., 2012), pointing to the need for a deeper understanding of the cognitive-emotional brain. Please address correspondence to: Alexander J. Shackman (shackman@umd.edu | 608.358.5025), Affective & Translational Neuroscience Laboratory, Department of Psychology | Neuroscience & Cognitive Science Program | Maryland Neuroimaging Center, University of Maryland, College Park, College Park, MD 20742 USA. HHS Public Access Author manuscript Behav Brain Sci. Author manuscript; available in PMC 2018 October 13. Published in final edited form as: Behav Brain Sci. 2015 ; 38: e86. doi:10.1017/S0140525X14001010. A uhor M anscript
MetricUNet: Synergistic Image- and Voxel-Level Learning for Precise CT Prostate Segmentation via Online Sampling

Fully convolutional networks (FCNs), including UNet and VNet, are widely-used network architectures for semantic segmentation in recent studies. However, conventional FCN is typically trained by the cross-entropy or Dice loss, which only calculates the error between predictions and ground-truth labels for pixels individually. This often results in non-smooth neighborhoods in the predicted segmentation. To address this problem, we propose a two-stage framework, with the first stage to quickly localize the prostate region, and the second stage to precisely segment the prostate by a multi-task UNet architecture. We introduce a novel online metric learning module through voxel-wise sampling in the multi-task network. Therefore, the proposed network has a dual-branch architecture that tackles two tasks: 1) a segmentation sub-network aiming to generate the prostate segmentation, and 2) a voxel-metric learning sub-network aiming to improve the quality of the learned feature space supervised by a combination of triplet and contrast loss function. Specifically, the voxel-metric learning sub-network sampled tuples (including triplets and pairs) in voxel-level through the intermediate feature maps. Unlike conventional deep metric learning methods that generate triplets or pairs in image-level before the training phase, our proposed voxel-wise tuples are sampled in an online manner and operated in an end-to-end fashion via multi-task learning. To evaluate the proposed method, we implement extensive experiments on a real CT image dataset consisting 339 patients. The ablation studies show that our method can effectively learn more representative voxel-level features compared with the conventional learning methods with cross-entropy or Dice loss. And the comparisons show that the proposed method outperforms the state-of-the-art methods by a reasonable margin.
Modeling Lapse Rates in the Maritime Uplands of Northern England: Implications for Climate Change

Recent high-resolution meteorological data from the Pennines of northern England are used to study temporal variation in surface temperature lapse rates. A regression approach uncovers significant relationships between lapse rates and solar input, mean temperature, vertical mixing (modeled through wind speed), and atmospheric moisture (specific and relative humidity). Prediction of lapse rates is successful, especially during spring, summer, and autumn, with mean r2 above 0.66 (66%). Lapse rates are shallower for higher mean temperatures and for a moister atmosphere, but steeper under increased daytime solar input. At night windy conditions increase lapse rate. In addition, synoptic influences upon lapse rate are investigated. The diurnal lapse rate cycle increases under anticyclonic influences and when flow strength is weak. Southerly airflows have shallower lapse rates. Application of the above to consider possible climate change suggests that lapse rates should be shallower in a warmer moister atmosphere, but that synoptic controls are equally influential.
K-Ar dating of illite fundamental particles separated from illite-smectite

Abstract Fundamental particles of illite-smectite from bentonites were separated into classes by high-speed centrifugation after infinite osmotic swelling of mixed-layer crystals, achieved by Naexchange and dispersion in distilled water. In samples free of detrital contamination, the thinnest fundamental particles yield older K-Ar ages than the thicker fundamental particles. This implies that they do not preferentially lose radiogenic 40Ar due to size, and that the illitization process is a crystal growth mechanism (not nucleation plus growth). As a result, any K-Ar age of fundamental illite particles from bentonites is an integral over longer or shorter periods of time, depending on the thermal history of the rocks. In thick bentonite beds, the measured age difference between the beginning of the illitization process at the contact with the host rocks and the end in the centre of the bed records extremely slow K diffusion in these well compacted rocks. These data explain why measured K-Ar ages of illite-smectite from bentonites are younger than the corresponding age of shale illitization, inferred from the burial history of the basin. The finest technically separable size-fractions of associated shales (<0.02 μm) yield K-Ar dates* greater than the stratigraphic age. This observation points to incomplete recrystallization of detrital illite during burial diagenesis.
No Difference in 2D:4D Ratio between Youth with Elevated Prenatal Androgen Exposure due to Congenital Adrenal Hyperplasia and Controls

The second-to-fourth digit ratio (2D:4D) has been associated with sexual dimorphism, with a lower 2D:4D in males. A large body of research has relied on the 2D:4D as a proxy for prenatal androgen exposure, and includes reports of relationships between 2D:4D and a wide range of human traits. Here, we examine the validity of the 2D:4D proxy by studying the association between 2D:4D and classical Congenital Adrenal Hyperplasia (CAH) due to 21-hydroxylase deficiency, a condition characterized by excessive prenatal exposure to androgens during most of the gestational period. To this end, we retrospectively examine serial radiographs of the left hand obtained clinically in 91 youth with classical CAH (49.5% female) and 70 control youth (44.3% female). Replicating previous reports, we observe associations of the 2D:4D with sex (lower 2D:4D in males), age (increase of 2D:4D through development) and ethnicity (lower 2D:4D in Hispanic individuals). However, we find no evidence for differences in 2D:4D between CAH and controls (full sample:
Scaling and persistence in observed and modeled surface temperature

We introduce a simple and effective method to test for temperature persistence on a range of time scales. Daily temperatures for three regions are examined: Central England, El‐Nino region and global. On time scales of less than a year, climate model simulations reproduce the observed high persistence in all regions. However, for longer time scales the climate model systematically underestimates the persistence of global mean temperatures. The anti‐persistence in the El‐Nino region is well simulated by the model. Scaling behaviour is seen for Central England temperatures but is not reproduced by the model. Some of these discrepancies may be accounted for by insufficient ocean‐atmosphere coupling.
Time-Dependent Shear Deformation Characteristics of Geomaterials and their Simulation

ABSTRACT The viscous aspects of the stress-strain behaviour of saturated and air-dried clean sands in drained plane strain compression (PSC) and saturated clean sand and soft clays in undrained triaxial compression (TC) are presented. Common as well as different viscous features among the different geomaterials are addressed. The general three-component model is used as the framework for constitutive modelling, in which the total strain rate e is decomposed into elastic and irreversible components ee and eir while the stress σ is decomposed into inviscid (non-viscous) and viscous components σf and σv. In the simplest model (called the new isotach model) among those described in the paper, σf is a nonlinear function of eir, while σv is a non-linear function of eir and always proportional to σf for primary loading. This model is relevant to kaolin for the full pre-peak range and a reconstituted low-plasticity clay (Fujinomori clay) at small strains, both in undrained TC. The model is modified to simulate the viscous effect that decays with eir, as observed with clean sands and a natural soft clay. It is shown that the second type of model (called the viscous evanescent model and the TESRA model) simulates well the above-mentioned behaviour, not only during primary loading, but also at unloaded conditions. The model is further modified to simulate the behaviour of Fujinomori clay whereby the rate at which the viscous effect decays gradually increases with eir (the general TESRA model). The viscous components σv of the three models can be represented by a set of common equations, and the other models are specifically simplified versions of the general TESRA model.
Plasmapause Equatorial Shape Determination via the Minimum L Algorithm: Description and Evaluation

[1] Algorithms for determination of the equatorial shape of the plasmapause using NASA IMAGE Extreme Ultraviolet (EUV) imagery are considered. Focus is on the Minimum L Algorithm, which operates without human intervention given a single EUV image in which the plasmasphere silhouette boundary has been identified. For each line of sight (LOS) through pixels on the plasmasphere silhouette boundary, the algorithm first finds all magnetic dipole field lines intersected by the LOS and then returns as the plasmasphere's boundary the field line with the minimum L value. An analysis of the reasonableness, applicability, and accuracy of the algorithm is presented, and it is contrasted with the well-known Edge Algorithm (Roelof and Skinner, 2000). A revised version of the Edge Algorithm is also introduced. Application of all three algorithms to real EUV imagery is demonstrated.
Permeability of a decollement zone: Results from a two-well experiment in the Barbados accretionary complex

Fault zones are hypothesized to play a major role in focusing fluid expulsion from accretionary complexes. A small number of previous investigations have examined the hydrogeologic properties of these fault zones using borehole packer or submersible-based slug and constant rate flow tests. While these single-well experiments yielded the first data on the permeability of active fault zones, they could only investigate a small area around the borehole and could not ensure reliable determination of formation storage properties. Recent data from an unplanned experiment in the decollement zone of the Barbados accretionary prism demonstrate the potential for multiple-well hydrogeologic tests. Pressure data from a sealed borehole show a clear signal of drilling activity ∼45 m away. Analysis of the pressure response suggests that decollement zone permeability lies between 1.0 and 1.2 x 10 -14 m 2 . This permeability is ∼2-4 orders of magnitude greater than overlying and underlying sediment and thus appears sufficient to focus fluid flow along the decollement zone. This inadvertent test evaluated fault zone hydrogeologic parameters over a larger radius and longer timescale and at pressures closer to in situ than previous single-well tests.
Upper Turonian–lower Campanian planktonic foraminifera from southern mid–high latitudes (Exmouth Plateau, NW Australia): biostratigraphy and taxonomic notes

A planktonic foraminiferal zonal scheme is presented for subdivision of the Upper Cretaceous pelagic carbonate sequence from southern mid–high latitudes. Definition of the zones is based on first and last occurrences of planktonic foraminifera from Ocean Drilling Program Holes 762C and 763B (Leg 122; Exmouth Plateau, south Indian Ocean). During the Late Cretaceous the studied holes were located close to 50°S and for the first time a complete sedimentary record for the mid–high latitudes was obtained. A detailed biostratigraphic analysis has allowed recognition of two new zones (Falsotruncana maslakovae Zone and Marginotruncana marianosi Zone) for the interval extending from the last occurrence of Helvetoglobotruncana helvetica to the first occurrence of Dicarinella asymetrica (upper Turonian–lower Santonian). From this study it is apparent that some low latitude (Globotruncana ventricosa,Hedbergella flandrini , Marginotruncana marianosi) and high latitude (Globigerinelloides impensus andHedbergella sliteri ) marker taxa display a vertical distribution at mid–high latitudes which is different from that known from low latitudes; moreover, one species (Heterohelix papula), overlooked at low latitudes, exhibits a restricted range that seems to be useful for chrono-biostratigraphic correlations: its appearance is suggested to coincide with the Coniacian/Santonian boundary. The proposed biozonation, which is integrated with calcareous nannofossil and magnetostratigraphic data available for the sections studied, is compared with both the low-latitude standard zonation and the planktonic foraminiferal zonal scheme for the circum-Antarctic region, in order to define a bio-chronostratigraphic scale that is useful for mid–high latitudes of the southern oceans.
Cross flows in the Taiwan strait in winter

AbstractIn winter, a branch of the China Coastal Current can turn in the Taiwan Strait to join the poleward-flowing Taiwan Coastal Current. The associated cross-strait flows have been inferred from hydrographic and satellite data, from observed abundances off northwestern Taiwan of cold-water copepod species Calanus sinicus and, in late March of 2012, also from debris found along the northwestern shore of Taiwan of a ship that broke two weeks earlier off the coast of China. The dynamics related to such cross flows have not been previously explained and are the focus of this study using analytical and numerical models. It is shown that the strait’s currents can be classified into three regimes depending on the strength of the winter monsoon: equatorward (poleward) for northeasterly winds stronger (weaker) than an upper (lower) bound and cross-strait flows for relaxing northeasterly winds between the two bounds. These regimes are related to the formation of the stationary Rossby wave over the Changyun Ridge.
An Information-Efficient Bayesian Model for AMS Data Analysis

A Bayesian model for accelerator mass spectrometry (AMS) data analysis is presented. Instrumental drift is modeled with a continuous autoregressive (CAR) process, and measurement uncertainties are taken to be Gaussian. All samples have a parameter describing their true value. The model adapts itself to different instrumental parameters based on the data, and yields the most probable true values for the unknown samples. The model is able to use the information in the measurements more efficiently. First, all measurements tell something about the overall instrument performance and possible drift. The overall machine uncertainty can be used to obtain realistic uncertainties even when the number of measurements per sample is small. Second, even the measurements of the unknown samples can be used to estimate the variations in the standard level, provided that the samples have been measured more than once. Third, the uncertainty of the standard level is known to be smaller nearer a standard. Fourth, even though individual measurements follow a Gaussian distribution, the end result may not. For simulated data, the new Bayesian method gives more accurate results and more realistic uncertainties than the conventional mean-based (MB) method. In some cases, the latter gives unrealistically small uncertainties. This can be due to the non-Gaussian nature of the final result, which results from combining few samples from a Gaussian distribution without knowing the underlying variance and from the normalization with an uncertain standard level. In addition, in some cases the standard error of the mean does not represent well the true error due to correlations within the measurements resulting from, for example, a changing trend. While the conventional method fails in these cases, the CAR model gives representative uncertainties.