Visual Data Mining

Occlusion is one of the major problems for interactive visual knowledge discovery and data mining in the process of finding patterns in multidimensional data.This project proposes a hybrid method that combines visual and analytical means to deal with occlusion in visual knowledge discovery called as GLC-S which uses visualization of n-D data in 2D in a set of Shifted Paired Coordinates (SPC). A set of Shifted Paired Coordinates for n-D data consists of n/2 pairs of common Cartesian coordinates that are shifted relative to each other to avoid their overlap. Each n-D point A is represented as a directed graph A* in SPC, where each node is the 2D projection of A in a respective pair of the Cartesian coordinates. The proposed GLC-S method significantly decrease cognitive load for analysis of n-D data and simplify pattern discovery in n-D data. The GLC-S method iteratively splits n-D data into non-overlapping clusters (hyper-rectangles) around local centers and visualizes only data within these clusters at each iteration. The requirements for these clusters are to contain cases of only one class and be the largest cluster with this property in SPC visualization. Such sequential splitting allows: (1) avoiding occlusion, (2) finding visually local classification patterns, rules, and (3) combine local sub-rules to a global rule that classifies all given data of two or more classes. The computational experiment with Wisconsin Breast Cancer data(9-D), User Knowledge Modeling data(6-D), and Letter Recognition data(17-D) from UCI Machine Learning Repository confirm this capability. At each iteration, these data have been split into training (70%) and validation (30%) data. It required 3 iterations in Wisconsin Breast Cancer data, 4 iterations in User Knowledge Modeling and 5 iterations in Letter Recognition data and respectively 3, 4, 5 local sub-rules that covered over 95% of all n-D data points with 100% accuracy at both training and validation experiments. After each iteration, the data that were used in this iteration are removed and remaining data are used in the next iteration. This removal process helps to decrease occlusion too. The GLC-S algorithm refuses to classify remaining cases that are not covered by these rules, i.e.,., do not belong to found hyper-rectangles. The interactive visualization process in SPC allows adjusting the sides of the hyper-rectangles to maximize the size of the hyper-rectangle without its overlap with the hyper-rectangles of the opposing classes. The GLC-S method splits data using the fixed split of n coordinates to pairs. This hybrid visual and analytical approach avoids throwing all data of several classes into a visualization plot that typically ends up in a messy highly occluded picture that hides useful patterns. This approach allows revealing these hidden patterns. The visualization process in SPC is reversible (lossless). i.e.,., all n-D information is visualized in 2D and can be restored from 2D visualization for each n-D case. This hybrid visual analytics method allowed classifying n-D data in a way that can be communicated to the user’s in the understandable and visual form

A LRRK2-Dependent EndophilinA Phosphoswitch Is Critical for Macroautophagy at Presynaptic Terminals.

Synapses are often far from the soma and independently cope with proteopathic stress induced by intense neuronal activity. However, how presynaptic compartments turn over proteins is poorly understood. We show that the synapse-enriched protein EndophilinA, thus far studied for its role in endocytosis, induces macroautophagy at presynaptic terminals. We find that EndophilinA executes this unexpected function at least partly independent of its role in synaptic vesicle endocytosis. EndophilinA-induced macroautophagy is activated when the kinase LRRK2 phosphorylates the EndophilinA-BAR domain and is blocked in animals where EndophilinA cannot be phosphorylated. EndophilinA-phosphorylation promotes the formation of highly curved membranes, and reconstitution experiments show these curved membranes serve as docking stations for autophagic factors, including Atg3. Functionally, deregulation of the EndophilinA phosphorylation state accelerates activity-induced neurodegeneration. Given that EndophilinA is connected to at least three Parkinson's disease genes (LRRK2, Parkin and Synaptojanin), dysfunction of EndophilinA-dependent synaptic macroautophagy may be common in this disorder

Interrogation of the Microenvironmental Landscape in Brain Tumors Reveals Disease-Specific Alterations of Immune Cells

Brain malignancies encompass a range of primary and metastatic cancers, including low-grade and high-grade gliomas and brain metastases (BrMs) originating from diverse extracranial tumors. Our understanding of the brain tumor microenvironment (TME) remains limited, and it is unknown whether it is sculpted differentially by primary versus metastatic disease. We therefore comprehensively analyzed the brain TME landscape via flow cytometry, RNA sequencing, protein arrays, culture assays, and spatial tissue characterization. This revealed disease-specific enrichment of immune cells with pronounced differences in proportional abundance of tissue-resident microglia, infiltrating monocyte-derived macrophages, neutrophils, and T cells. These integrated analyses also uncovered multifaceted immune cell activation within brain malignancies entailing converging transcriptional trajectories while maintaining disease- and cell-type-specific programs. Given the interest in developing TME-targeted therapies for brain malignancies, this comprehensive resource of the immune landscape offers insights into possible strategies to overcome tumor-supporting TME properties and instead harness the TME to fight cancer

Riluzole-Rasagiline Hybrids: Toward the Development of Multi-Target-Directed Ligands for Amyotrophic Lateral Sclerosis

Polypharmacology is a new trend in amyotrophic lateral sclerosis (ALS) therapy and an effective way of addressing a multifactorial etiology involving excitotoxicity, mitochondrial dysfunction, oxidative stress, and microglial activation. Inspired by a reported clinical trial, we converted a riluzole (1)-rasagiline (2) combination into single-molecule multi-target-directed ligands. By a ligand-based approach, the highly structurally integrated hybrids 3-8 were designed and synthesized. Through a target- and phenotypic-based screening pipeline, we identified hit compound 6. It showed monoamine oxidase A (MAO-A) inhibitory activity (IC50 = 6.9 mu M) rationalized by in silico studies as well as in vitro brain permeability. By using neuronal and non-neuronal cell models, including ALS-patient-derived cells, we disclosed for 6 a neuroprotective/neuroinflammatory profile similar to that of the parent compounds and their combination. Furthermore, the unexpected MAO inhibitory activity of 1 (IC50 = 8.7 mu M) might add a piece to the puzzle of its anti-ALS molecular profile

Molecular modelling of the GIR1 branching ribozyme gives new insight into evolution of structurally related ribozymes

Twin-ribozyme introns contain a branching ribozyme (GIR1) followed by a homing endonuclease (HE) encoding sequence embedded in a peripheral domain of a group I splicing ribozyme (GIR2). GIR1 catalyses the formation of a lariat with 3 nt in the loop, which caps the HE mRNA. GIR1 is structurally related to group I ribozymes raising the question about how two closely related ribozymes can carry out very different reactions. Modelling of GIR1 based on new biochemical and mutational data shows an extended substrate domain containing a GoU pair distinct from the nucleophilic residue that dock onto a catalytic core showing a different topology from that of group I ribozymes. The differences include a core J8/7 region that has been reduced and is complemented by residues from the pre-lariat fold. These findings provide the basis for an evolutionary mechanism that accounts for the change from group I splicing ribozyme to the branching GIR1 architecture. Such an evolutionary mechanism can be applied to other large RNAs such as the ribonuclease P

Citizen science can improve conservation science, natural resource management, and environmental protection

Citizen science has advanced science for hundreds of years, contributed to many peer-reviewed articles, and informed land management decisions and policies across the United States. Over the last 10 years, citizen science has grown immensely in the United States and many other countries. Here, we show how citizen science is a powerful tool for tackling many of the challenges faced in the field of conservation biology. We describe the two interwoven paths bywhich citizen science can improve conservation efforts, natural resource management, and environmental protection. The first path includes building scientific knowledge, while the other path involves informing policy and encouraging public action. We explore how citizen science is currently used and describe the investments needed to create a citizen science program. We find that: 1. Citizen science already contributes substantially to many domains of science, including conservation, natural resource, and environmental science. Citizen science informs natural resource management, environmental protection, and policymaking and fosters public input and engagement. 2. Many types of projects can benefit fromcitizen science, but one must be careful tomatch the needs for science and public involvement with the right type of citizen science project and the right method of public participation. 3. Citizen science is a rigorous process of scientific discovery, indistinguishable from conventional science apart from the participation of volunteers.When properly designed, carried out, and evaluated, citizen science can provide sound science, efficiently generate high-quality data, and help solve problems

The First HET Planet: A Companion to HD 37605

We report the first detection of a planetary-mass companion to a star using the High Resolution Spectrograph (HRS) of the Hobby-Eberly Telescope (HET). The HET-HRS now gives routine radial velocity precision of 2-3 m/s for high SNR observations of quiescent stars. The planetary-mass companion to the metal-rich K0V star HD37605 has an orbital period of 54.23 days, an orbital eccentricity of 0.737, and a minimum mass of 2.84 Jupiter masses. The queue-scheduled operation of the Hobby-Eberly Telescope enabled us to discovery of this relatively short-period planet with a total observation time span of just two orbital periods. The ability of queue-scheduled large-aperture telescopes to respond quickly to interesting and important results demonstrates the power of this new approach in searching for extra-solar planets as well as in other ares of research requiring rapid response time critical observations.Comment: 4 Pages, 2 figures. Accepted in Astrophysical Journal Letters, http://austral.as.utexas.edu/planets/hd37605/hd37605.htm

Spring temperatures influence selection on breeding date and the potential for phenological mismatch in a migratory bird

Climate change has affected the seasonal phenology of a variety of taxa, including that of migratory birds and their critical food resources. However, whether climate-induced changes in breeding phenology affect individual fitness, and how these changes might, therefore, influence selection on breeding date remain unresolved. Here, we use a 36-year dataset from a long-term, individual-based study of House Wrens (Troglodytes aedon) to test whether the timing of avian breeding seasons is associated with annual changes in temperature, which have increased to a small but significant extent locally since the onset of the study in 1980. Increasing temperature was associated with an advancement of breeding date in the population, as the onset of breeding within years was closely associated with daily spring temperatures. Warmer springs were also associated with a reduced incubation period, but reduced incubation periods were associated with a prolonged duration of nestling provisioning. Nest productivity, in terms of fledgling production, was not associated with temperature, but wetter springs reduced fledging success. Most years were characterized by selection for earlier breeding, but cool and wet years resulted in stabilizing selection on breeding date. Our results indicate that climate change and increasing spring temperatures can affect suites of life-history traits, including selection on breeding date. Increasing temperatures may favor earlier breeding, but the extent to which the phenology of populations might advance may be constrained by reductions in fitness associated with early breeding during cool, wet years. Variability in climatic conditions will, therefore, shape the extent to which seasonal organisms can respond to changes in their environment.Peer reviewedIntegrative Biolog

Control of star formation by supersonic turbulence

Understanding the formation of stars in galaxies is central to much of modern astrophysics. For several decades it has been thought that stellar birth is primarily controlled by the interplay between gravity and magnetostatic support, modulated by ambipolar diffusion. Recently, however, both observational and numerical work has begun to suggest that support by supersonic turbulence rather than magnetic fields controls star formation. In this review we outline a new theory of star formation relying on the control by turbulence. We demonstrate that although supersonic turbulence can provide global support, it nevertheless produces density enhancements that allow local collapse. Inefficient, isolated star formation is a hallmark of turbulent support, while efficient, clustered star formation occurs in its absence. The consequences of this theory are then explored for both local star formation and galactic scale star formation. (ABSTRACT ABBREVIATED)Comment: Invited review for "Reviews of Modern Physics", 87 pages including 28 figures, in pres