Scanning the visual world: a study of patients with homonymous hemianopia.

Published versio

Morphology-Controlled Aluminum-Doped Zinc Oxide Nanofibers for Highly Sensitive NO2 Sensors with Full Recovery at Room Temperature

Room-temperature (RT) gas sensitivity of morphology-controlled free-standing hollow aluminum-doped zinc oxide (AZO) nanofibers for NO2 gas sensors is presented. The free-standing hollow nanofibers are fabricated using a polyvinylpyrrolidone fiber template electrospun on a copper electrode frame followed by radio-frequency sputtering of an AZO thin overlayer and heat treatment at 400 degrees C to burn off the polymer template. The thickness of the AZO layer is controlled by the deposition time. The gas sensor based on the hollow nanofibers demonstrates fully recoverable n-type RT sensing of low concentrations of NO2 (0.5 ppm). A gas sensor fabricated with Al2O3-filled AZO nanofibers exhibits no gas sensitivity below 75 degrees C. The gas sensitivity of a sensor is determined by the density of molecules above the minimum energy for adsorption, collision frequency of gas molecules with the surface, and available adsorption sites. Based on finite-difference time-domain simulations, the RT sensitivity of hollow nanofiber sensors is ascribed to the ten times higher collision frequency of NO2 molecules confined inside the fiber compared to the outer surface, as well as twice the surface area of hollow nanofibers compared to the filled ones. This approach might lead to the realization of RT sensitive gas sensors with 1D nanostructures

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

Block of TREK and TRESK K2P channels by lamotrigine and two derivatives sipatrigine, and CEN-092

TREK and TRESK K2P channels are widely expressed in the nervous system, particularly in sensory neurons, where they regulate neuronal excitability. In this study, using whole-cell patch-clamp electrophysiology, we characterise the inhibitory effect of the anticonvulsant lamotrigine and two derivatives, sipatrigine and 3,5-diamino-6-(3,5-bistrifluoromethylphenyl)-1,2,4-triazine (CEN-092) on these channels. Sipatrigine was found to be a more effective inhibitor than lamotrigine of TREK-1, TREK-2 and TRESK channels. Sipatrigine was slightly more potent on TREK-1 channels (EC50 = 16 μM) than TRESK (EC50 = 34 μM) whereas lamotrigine was equally effective on TREK-1 and TRESK. Sipatrigine was less effective on a short isoform of TREK-2, suggesting the N terminus of the channel is important for both inhibition and subsequent over-recovery. Inhibition of TREK-1 and TREK-2 channels by sipatrigine was reduced by mutation of a leucine residue associated with the norfluoxetine binding site on these channels (L289A and L320A on TREK-1 and TREK-2, respectively) but these did not affect inhibition by lamotrigine. Inhibition of TRESK by sipatrigine and lamotrigine was attenuated by mutation of bulky phenylalanine residues (F145A and F352A) in the inner pore helix. However, phosphorylation mutations did not alter the effect of sipatrigine. CEN-092 was a more effective inhibitor of TRESK channels than TREK-1 channels. It is concluded that lamotrigine, sipatrigine and CEN-092 are all inhibitors of TREK and TRESK channels but do not greatly discriminate between them. The actions of these compounds may contribute to their current and potential use in the treatment of pain and depression

Influence of Aerosol Delivered BCG Vaccination on Immunological and Disease Parameters Following SARS-CoV-2 Challenge in Rhesus Macaques.

The tuberculosis vaccine, Bacille Calmette-Guerin (BCG), also affords protection against non-tuberculous diseases attributable to heterologous immune mechanisms such as trained innate immunity, activation of non-conventional T-cells, and cross-reactive adaptive immunity. Aerosol vaccine delivery can target immune responses toward the primary site of infection for a respiratory pathogen. Therefore, we hypothesised that aerosol delivery of BCG would enhance cross-protective action against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection and be a deployable intervention against coronavirus disease 2019 (COVID-19). Immune parameters were monitored in vaccinated and unvaccinated rhesus macaques for 28 days following aerosol BCG vaccination. High-dose SARS-CoV-2 challenge was applied by intranasal and intrabronchial instillation and animals culled 6-8 days later for assessment of viral, disease, and immunological parameters. Mycobacteria-specific cell-mediated immune responses were detected following aerosol BCG vaccination, but SARS-CoV-2-specific cellular- and antibody-mediated immunity was only measured following challenge. Early secretion of cytokine and chemokine markers associated with the innate cellular and adaptive antiviral immune response was detected following SARS-CoV-2 challenge in vaccinated animals, at concentrations that exceeded titres measured in unvaccinated macaques. Classical CD14+ monocytes and Vδ2 γδ T-cells quantified by whole-blood immunophenotyping increased rapidly in vaccinated animals following SARS-CoV-2 challenge, indicating a priming of innate immune cells and non-conventional T-cell populations. However, viral RNA quantified in nasal and pharyngeal swabs, bronchoalveolar lavage (BAL), and tissue samples collected at necropsy was equivalent in vaccinated and unvaccinated animals, and in-life CT imaging and histopathology scoring applied to pulmonary tissue sections indicated that the disease induced by SARS-CoV-2 challenge was comparable between vaccinated and unvaccinated groups. Hence, aerosol BCG vaccination did not induce, or enhance the induction of, SARS-CoV-2 cross-reactive adaptive cellular or humoral immunity, although an influence of BCG vaccination on the subsequent immune response to SARS-CoV-2 challenge was apparent in immune signatures indicative of trained innate immune mechanisms and primed unconventional T-cell populations. Nevertheless, aerosol BCG vaccination did not enhance the initial clearance of virus, nor reduce the occurrence of early disease pathology after high dose SARS-CoV-2 challenge. However, the heterologous immune mechanisms primed by BCG vaccination could contribute to the moderation of COVID-19 disease severity in more susceptible species following natural infection

The number of tree species on Earth

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness

Applications of yeast flocculation in biotechnological processes

A review on the main aspects associated with yeast flocculation and its application in biotechnological processes is presented. This subject is addressed following three main aspects – the basics of yeast flocculation, the development of “new” flocculating yeast strains and bioreactor development. In what concerns the basics of yeast flocculation, the state of the art on the most relevant aspects of mechanism, physiology and genetics of yeast flocculation is reported. The construction of flocculating yeast strains includes not only the recombinant constitutive flocculent brewer’s yeast, but also recombinant flocculent yeast for lactose metabolisation and ethanol production. Furthermore, recent work on the heterologous β-galactosidase production using a recombinant flocculent Saccharomyces cerevisiae is considered. As bioreactors using flocculating yeast cells have particular properties, mainly associated with a high solid phase hold-up, a section dedicated to its operation is presented. Aspects such as bioreactor productivity and culture stability as well as bioreactor hydrodynamics and mass transfer properties of flocculating cell cultures are considered. Finally, the paper concludes describing some of the applications of high cell density flocculation bioreactors and discussing potential new uses of these systems.Fundação para a Ciência e a Tecnologia (FCT) – PRAXIS XXI - BD11306/97

Climatic controls of decomposition drive the global biogeography of forest-tree symbioses

The identity of the dominant root-associated microbial symbionts in a forest determines the ability of trees to access limiting nutrients from atmospheric or soil pools1,2, sequester carbon3,4 and withstand the effects of climate change5,6. Characterizing the global distribution of these symbioses and identifying the factors that control this distribution are thus integral to understanding the present and future functioning of forest ecosystems. Here we generate a spatially explicit global map of the symbiotic status of forests, using a database of over 1.1 million forest inventory plots that collectively contain over 28,000 tree species. Our analyses indicate that climate variables—in particular, climatically controlled variation in the rate of decomposition—are the primary drivers of the global distribution of major symbioses. We estimate that ectomycorrhizal trees, which represent only 2% of all plant species7, constitute approximately 60% of tree stems on Earth. Ectomycorrhizal symbiosis dominates forests in which seasonally cold and dry climates inhibit decomposition, and is the predominant form of symbiosis at high latitudes and elevation. By contrast, arbuscular mycorrhizal trees dominate in aseasonal, warm tropical forests, and occur with ectomycorrhizal trees in temperate biomes in which seasonally warm-and-wet climates enhance decomposition. Continental transitions between forests dominated by ectomycorrhizal or arbuscular mycorrhizal trees occur relatively abruptly along climate-driven decomposition gradients; these transitions are probably caused by positive feedback effects between plants and microorganisms. Symbiotic nitrogen fixers—which are insensitive to climatic controls on decomposition (compared with mycorrhizal fungi)—are most abundant in arid biomes with alkaline soils and high maximum temperatures. The climatically driven global symbiosis gradient that we document provides a spatially explicit quantitative understanding of microbial symbioses at the global scale, and demonstrates the critical role of microbial mutualisms in shaping the distribution of plant species

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

The Distress Thermometer and Its Validity: A First Psychometric Study in Indonesian Women with Breast Cancer.

Purpose: This study aims to translate the Distress Thermometer (DT) into Indonesian, test its validity in Indonesian women with breast cancer and determine norm scores of the Indonesian DT for clinically relevant distress. Methods: First, the original version of the DT was translated using a forward and backward translation procedure according to the guidelines. Next, a group of 120 breast cancer patients who were treated at the Outpatient Surgical Oncology Clinic in Hasan Sadikin Hospital in Indonesia completed a standard socio-demographic form, the DT and the Problem List, the Hospital Anxiety and Depression Scale (HADS) and the WHO Quality of Life (WHOQOL-BREF). Results: Receiver operating characteristic (ROC) curve analyses identified an area under the curve = 0.81 when compared to the HADS cutoff score of 15. A cutoff score of 5 on the DT had the best sensitivity (0.81) and specificity (0.64). Patients who scored above this cutoff reported more problems in the practical, family, emotional, spiritual/religious and physical domains (30 out of 36 problems, p-value<0.05) than patients below the cutoff score. Patients at advanced stages of cancer experienced more emotional and physical problems. Patient's distress level was negatively correlated with overall quality of life, general health and all quality of life domains. Conclusions: The DT was found to be a valid tool for screening distress in Indonesian breas