Analysis of testbed airborne multispectral scanner data from Superflux II

A test bed aircraft multispectral scanner (TBAMS) was flown during the James Shelf, Plume Scan, and Chesapeake Bay missions as part of the Superflux 2 experiment. Excellent correlations were obtained between water sample measurements of chlorophyll and sediment and TBAMS radiance data. The three-band algorithms used were insensitive to aircraft altitude and varying atmospheric conditions. This was particularly fortunate due to the hazy conditions during most of the experiments. A contour map of sediment, and also chlorophyll, was derived for the Chesapeake Bay plume along the southern Virginia-Carolina coastline. A sediment maximum occurs about 5 nautical miles off the Virginia Beach coast with a chlorophyll maximum slightly shoreward of this. During the James Shelf mission, a thermal anomaly (or front) was encountered about 50 miles from the coast. There was a minor variation in chlorophyll and sediment across the boundary. During the Chesapeake Bay mission, the Sun elevation increased from 50 degrees to over 70 degrees, interfering with the generation of data products

Tissue eosinophilia and eosinophil degranulation in Riedel's invasive fibrous thyroiditis.

The etiology of Riedel's invasive fibrous thyroiditis (IFT) has remained obscure. This rare disorder has been confused in the past with the more common fibrous variant of Hashimoto's disease. The typical histological features of IFT, in particular the presence of an invasive fibrosclerotic process in conjunction with a prominent chronic inflammatory infiltrate, suggest that the release of fibrogenic cytokines and other factors from these cellular infiltrates may play an important role in the pathogenesis of this condition. Our observations in routinely processed tissue sections obtained from patients with documented IFT of striking tissue eosinophilia led us to hypothesize that eosinophils and their products may play a role in the evolution of this disease. Immunofluorescence staining with affinity-purified polyclonal rabbit antibody directed against human eosinophil granule major basic protein revealed marked tissue eosinophilia and abundant extracellular deposition of major basic protein in all specimens from 16 patients with IFT. By contrast, only occasional eosinophils and no extracellular major basic protein were detected in control thyroid tissues obtained from patients with multinodular goiter, Graves' disease, Hashimoto's disease, and normal thyroid tissue. The presence of marked eosinophil infiltration and extracellular major basic protein deposition in IFT and other associated fibrosclerotic conditions suggests a role for eosinophils and their products in propagating the fibrogenesis seen in IFT

Partly Occupied Wannier Functions

We introduce a scheme for constructing partly occupied, maximally localized Wannier functions (WFs) for both molecular and periodic systems. Compared to the traditional occupied WFs the partly occupied WFs posses improved symmetry and localization properties achieved through a bonding-antibonding closing procedure. We demonstrate the equivalence between bonding-antibonding closure and the minimization of the average spread of the WFs in the case of a benzene molecule and a linear chain of Pt atoms. The general applicability of the method is demonstrated through the calculation of WFs for a metallic system with an impurity: a Pt wire with a hydrogen molecular bridge.Comment: 5 pages, 4 figure

Using Matching Methods From Both Fisher\u27s Experimental Design and Rubin\u27s Causal Model to Compare Between Two Medical Facilities with Extremely Skewed Number of Subjects

The present study deals with the problem of comparison between a two medical facilities\u27 with extremely skewed sample sizes from non-experimental study. The data came from a study of rehabilitation interventions with patients diagnosed with cardiac and pulmonary issues who received treatment either in inpatient rehabilitation facilities (IRFs) or in skilled nursing facilities (SNFs). Due to inclusion and exclusion criteria, however, the study had failed to recruit sufficient number of participants between two comparison groups: 319 from IRFs and 27 from SNFs. As a result, the main hypothesis of the study was not tested due to the disparity of the participants between the two comparison groups, which could not be analyzed as a study with an unbalanced design because of lack of power in the analysis (Beacham, 2008). In medical research, this kind of problem occurs often not only because of inclusion and exclusion criteria in recruiting patients for a study but also because of dropout patients due to many reasons, such as technical changes (certain insurance and/or Medicare policies eliminate possible participants), medical changes, or personal circumstances change in the middle of the study. By extracting matching methods from both Fisher\u27s experimental design and Rubin\u27s Causal Model (RCM) the present study attempts to offer ways to draw the causal inference in a non-experimental study with sample size disparity between two comparison groups, especially when collected data disable a researcher to analyze. The matched datasets were analyzed in two ways: multivariate of covariance (MANCOVA) first and two analysis of covariance (ANCOVA) models when there was a significant main effect in the previous MANCOVA model. No significant different effectiveness was found between IRFs and SNFs in the 1:1 Matched Data, but IRFs took better care than SNFs in the Caliper Matched Data, rehabilitating the patients diagnosed with cardiac and pulmonary diseases on the functional independent measure (FIM). In comparison methodology, the results suggested that datasets created by both matching methods provided similar results, but that Fisher\u27s design fits better for small dataset while RCM, for larger dataset by using propensity scores to balance the matching sets

Proteomic systems evaluation of the molecular validity of preclinical psychosis models compared to schizophrenia brain pathology.

Pharmacological and genetic rodent models of schizophrenia play an important role in the drug discovery pipeline, but quantifying the molecular similarity of such models with the underlying human pathophysiology has proved difficult. We developed a novel systems biology methodology for the direct comparison of anterior prefrontal cortex tissue from four established glutamatergic rodent models and schizophrenia patients, enabling the evaluation of which model displays the greatest similarity to schizophrenia across different pathophysiological characteristics of the disease. Liquid chromatography coupled tandem mass spectrometry (LC-MSE) proteomic profiling was applied comparing healthy and "disease state" in human post-mortem samples and rodent brain tissue samples derived from models based on acute and chronic phencyclidine (PCP) treatment, ketamine treatment or NMDA receptor knockdown. Protein-protein interaction networks were constructed from significant abundance changes and enrichment analyses enabled the identification of five functional domains of the disease such as "development and differentiation", which were represented across all four rodent models and were thus subsequently used for cross-species comparison. Kernel-based machine learning techniques quantified that the chronic PCP model represented schizophrenia brain changes most closely for four of these functional domains. This is the first study aiming to quantify which rodent model recapitulates the neuropathological features of schizophrenia most closely, providing an indication of face validity as well as potential guidance in the refinement of construct and predictive validity. The methodology and findings presented here support recent efforts to overcome translational hurdles of preclinical psychiatric research by associating functional dimensions of behaviour with distinct biological processes.This research was supported by the Stanley Medical Research Institute (SMRI) (R6123) and the NEWMEDS Innovative Medicines Initiative (FP7/2007-2013).This is the author accepted manuscript. The final version is available from Elsevier via https://doi.org/10.1016/j.schres.2016.06.01

Identification of proteomic signatures associated with depression and psychotic depression in post-mortem brains from major depression patients

Major depressive disorder (MDD) is a leading cause of disability worldwide and results tragically in the loss of almost one million lives in Western societies every year. This is due to poor understanding of the disease pathophysiology and lack of empirical medical tests for accurate diagnosis or for guiding antidepressant treatment strategies. Here, we have used shotgun proteomics in the analysis of post-mortem dorsolateral prefrontal cortex brain tissue from 24 MDD patients and 12 matched controls. Brain proteomes were pre-fractionated by gel electrophoresis and further analyzed by shotgun data-independent label-free liquid chromatography-mass spectrometry. This led to identification of distinct proteome fingerprints between MDD and control subjects. Some of these differences were validated by Western blot or selected reaction monitoring mass spectrometry. This included proteins associated with energy metabolism and synaptic function and we also found changes in the histidine triad nucleotide-binding protein 1 (HINT1), which has been implicated recently in regulation of mood and behavior. We also found differential proteome profiles in MDD with (n=11) and without (n=12) psychosis. Interestingly, the psychosis fingerprint showed a marked overlap to changes seen in the brain proteome of schizophrenia patients. These findings suggest that it may be possible to contribute to the disease understanding by distinguishing different subtypes of MDD based on distinct brain proteomic profiles

Hrk1 Plays Both Hog1-Dependent and -Independent Roles in Controlling Stress Response and Antifungal Drug Resistance in Cryptococcus neoformans

The HOG (High Osmolarity Glycerol response) pathway plays a central role in controlling stress response, ergosterol biosynthesis, virulence factor production, and differentiation of Cryptococcus neoformans, which causes fatal fungal meningoencephalitis. Recent transcriptome analysis of the HOG pathway discovered a Hog1-regulated gene (CNAG_00130.2), encoding a putative protein kinase orthologous to Rck1/2 in Saccharomyces cerevisiae and Srk1 in Schizosaccharomyces pombe. Its function is not known in C. neoformans. The present study functionally characterized the role of Hrk1 in C. neoformans. Northern blot analysis confirmed that HRK1 expression depends on the Hog1 MAPK. Similar to the hog1Δ mutant, the hrk1Δ mutant exhibited almost complete resistance to fludioxonil, which triggers glycerol biosynthesis via the HOG pathway. Supporting this, the hrk1Δ mutant showed reduced intracellular glycerol accumulation and swollen cell morphology in response to fludioxonil, further suggesting that Hrk1 works downstream of the HOG pathway. However, Hrk1 also appeared to have Hog1-independent functions. Mutation of HRK1 not only further increased osmosensitivity of the hog1Δ mutant, but also suppressed increased azole-resistance of the hog1Δ mutant in an Erg11-independent manner. Furthermore, unlike the hog1Δ mutant, Hrk1 was not involved in capsule biosynthesis. Hrk1 was slightly involved in melanin production but dispensable for virulence of C. neoformans. These findings suggest that Hrk1 plays both Hog1-dependent and –independent roles in stress and antifungal drug susceptibility and virulence factor production in C. neoformans. Particularly, the finding that inhibition of Hrk1 substantially increases azole drug susceptibility provides a novel strategy for combination antifungal therapy

Integrating proteomic, sociodemographic and clinical data to predict future depression diagnosis in subthreshold symptomatic individuals

Funder: Stanley Medical Research Institute (SMRI); doi: https://doi.org/10.13039/100007123Abstract: Individuals with subthreshold depression have an increased risk of developing major depressive disorder (MDD). The aim of this study was to develop a prediction model to predict the probability of MDD onset in subthreshold individuals, based on their proteomic, sociodemographic and clinical data. To this end, we analysed 198 features (146 peptides representing 77 serum proteins (measured using MRM-MS), 22 sociodemographic factors and 30 clinical features) in 86 first-episode MDD patients (training set patient group), 37 subthreshold individuals who developed MDD within two or four years (extrapolation test set patient group), and 86 subthreshold individuals who did not develop MDD within four years (shared reference group). To ensure the development of a robust and reproducible model, we applied feature extraction and model averaging across a set of 100 models obtained from repeated application of group LASSO regression with ten-fold cross-validation on the training set. This resulted in a 12-feature prediction model consisting of six serum proteins (AACT, APOE, APOH, FETUA, HBA and PHLD), three sociodemographic factors (body mass index, childhood trauma and education level) and three depressive symptoms (sadness, fatigue and leaden paralysis). Importantly, the model demonstrated a fair performance in predicting future MDD diagnosis of subthreshold individuals in the extrapolation test set (AUC = 0.75), which involved going beyond the scope of the model. These findings suggest that it may be possible to detect disease indications in subthreshold individuals up to four years prior to diagnosis, which has important clinical implications regarding the identification and treatment of high-risk individuals

Mathematical Model of Easter Island Society Collapse

In this paper we consider a mathematical model for the evolution and collapse of the Easter Island society, starting from the fifth century until the last period of the society collapse (fifteen century). Based on historical reports, the available primary sources consisted almost exclusively on the trees. We describe the inhabitants and the resources as an isolated system and both considered as dynamic variables. A mathematical analysis about why the structure of the Easter Island community collapse is performed. In particular, we analyze the critical values of the fundamental parameters driving the interaction humans-environment and consequently leading to the collapse. The technological parameter, quantifying the exploitation of the resources, is calculated and applied to the case of other extinguished civilization (Cop\'an Maya) confirming, with a sufficiently precise estimation, the consistency of the adopted model.Comment: 9 pages, 1 figure, final version published on EuroPhysics Letter

Carbon allocation and carbon isotope fluxes in the plant-soil-atmosphere continuum: a review

The terrestrial carbon (C) cycle has received increasing interest over the past few decades, however, there is still a lack of understanding of the fate of newly assimilated C allocated within plants and to the soil, stored within ecosystems and lost to the atmosphere. Stable carbon isotope studies can give novel insights into these issues. In this review we provide an overview of an emerging picture of plant-soil-atmosphere C fluxes, as based on C isotope studies, and identify processes determining related C isotope signatures. The first part of the review focuses on isotopic fractionation processes within plants during and after photosynthesis. The second major part elaborates on plant-internal and plant-rhizosphere C allocation patterns at different time scales (diel, seasonal, interannual), including the speed of C transfer and time lags in the coupling of assimilation and respiration, as well as the magnitude and controls of plant-soil C allocation and respiratory fluxes. Plant responses to changing environmental conditions, the functional relationship between the physiological and phenological status of plants and C transfer, and interactions between C, water and nutrient dynamics are discussed. The role of the C counterflow from the rhizosphere to the aboveground parts of the plants, e.g. via CO<sub>2</sub> dissolved in the xylem water or as xylem-transported sugars, is highlighted. The third part is centered around belowground C turnover, focusing especially on above- and belowground litter inputs, soil organic matter formation and turnover, production and loss of dissolved organic C, soil respiration and CO<sub>2</sub> fixation by soil microbes. Furthermore, plant controls on microbial communities and activity via exudates and litter production as well as microbial community effects on C mineralization are reviewed. A further part of the paper is dedicated to physical interactions between soil CO<sub>2</sub> and the soil matrix, such as CO<sub>2</sub> diffusion and dissolution processes within the soil profile. Finally, we highlight state-of-the-art stable isotope methodologies and their latest developments. From the presented evidence we conclude that there exists a tight coupling of physical, chemical and biological processes involved in C cycling and C isotope fluxes in the plant-soil-atmosphere system. Generally, research using information from C isotopes allows an integrated view of the different processes involved. However, complex interactions among the range of processes complicate or currently impede the interpretation of isotopic signals in CO<sub>2</sub> or organic compounds at the plant and ecosystem level. This review tries to identify present knowledge gaps in correctly interpreting carbon stable isotope signals in the plant-soil-atmosphere system and how future research approaches could contribute to closing these gaps