Gene Expression based Survival Prediction for Cancer Patients: A Topic Modeling Approach

Cancer is one of the leading cause of death, worldwide. Many believe that genomic data will enable us to better predict the survival time of these patients, which will lead to better, more personalized treatment options and patient care. As standard survival prediction models have a hard time coping with the high-dimensionality of such gene expression (GE) data, many projects use some dimensionality reduction techniques to overcome this hurdle. We introduce a novel methodology, inspired by topic modeling from the natural language domain, to derive expressive features from the high-dimensional GE data. There, a document is represented as a mixture over a relatively small number of topics, where each topic corresponds to a distribution over the words; here, to accommodate the heterogeneity of a patient's cancer, we represent each patient (~document) as a mixture over cancer-topics, where each cancer-topic is a mixture over GE values (~words). This required some extensions to the standard LDA model eg: to accommodate the "real-valued" expression values - leading to our novel "discretized" Latent Dirichlet Allocation (dLDA) procedure. We initially focus on the METABRIC dataset, which describes breast cancer patients using the r=49,576 GE values, from microarrays. Our results show that our approach provides survival estimates that are more accurate than standard models, in terms of the standard Concordance measure. We then validate this approach by running it on the Pan-kidney (KIPAN) dataset, over r=15,529 GE values - here using the mRNAseq modality - and find that it again achieves excellent results. In both cases, we also show that the resulting model is calibrated, using the recent "D-calibrated" measure. These successes, in two different cancer types and expression modalities, demonstrates the generality, and the effectiveness, of this approach

Mechanics-Based Modeling Approach for Rapid Prediction of Low Velocity Impact Damage in Composite Laminates

A mechanics-based modeling approach is developed to rapidly predict damage in polymer matrix composites resulting from a low velocity impact event. The approach is incorporated into a computer code that provides an efficient means to assess the damage resistance for a range of material systems, layup configurations, and impact scenarios. It is envisioned that the developed approach will aid in early design and analysis of composite structures where sizing and layup decisions must be made, and evaluating the feasibility of a large number of laminate configurations using numerical approaches such as finite element analysis (FEA) is prohibitively expensive. Therefore, the goal of the modeling approach is to predict the impact damage size given the laminate configuration and impact scenario. This information can then be used to determine the residual strength of the material. To be useful in such a context, the tool is designed to run quickly (<2 minutes) to allow a large number of design cases to be investigated. The results presented demonstrate that the model is capable of efficiently predicting low velocity impact damage size, shape, and location within an acceptable accuracy suitable for preliminary design and analysis of composite structures

Сучасний стан гончарства Гуцульщини та Покуття (за матеріалами керамологічної експедиції Інституту керамології – відділення Інституту народознавства НАН України та Національного музею-заповідника українського гончарства в Опішному)

6–17 червня 2007 року співробітниками Національного музею-заповідника українського гончарства в Опішному та науковцями Інституту керамології було проведено керамологічну експедицію до таких гончарних осередків Івано-Франківської області: Косів, Коломия, Кути, Пистинь

Inverse Method for Estimation of Composite Kink-Band Toughness from Open-Hole Compression Strength Data

Fiber-reinforced polymer matrix composite materials can fail by kink-band propagation mechanism when subjected to in-plane compressive loading. This mode of failure is especially prevalent in compressive loading of laminates with holes, cut-outs, or impact damage. Most of the successful models for predicting compressive strength of such laminates require fracture toughness associated with kink-band propagation under in-plane compression. However, this property is difficult to measure experimentally, limiting the use of such models in design practice. In this paper an inverse method is proposed to estimate the kink-band toughness of the laminate from its open-hole compression strength data, which is an easier property to measure experimentally. Furthermore, a scaling relationship is proposed to estimate kink-band toughness for other laminate configurations of the same material

Impact of climate events, pollution, and green spaces on mental health: an umbrella review of meta-analyses

Climate change may affect mental health. We conducted an umbrella review of meta-analyses examining the association between mental health and climate events related to climate change, pollution and green spaces. We searched major bibliographic databases and included meta-analyses with at least five primary studies. Results were summarized narratively. We included 24 meta-analyses on mental health and climate events (n = 13), pollution (n = 11), and green spaces (n = 2) (two meta-analyses provided data on two categories). The quality was suboptimal. According to AMSTAR-2, the overall confidence in the results was high for none of the studies, for three it was moderate, and for the other studies the confidence was low to critically low. The meta-analyses on climate events suggested an increased prevalence of symptoms of post-traumatic stress, depression, and anxiety associated with the exposure to various types of climate events, although the effect sizes differed considerably across study and not all were significant. The meta-analyses on pollution suggested that there may be a small but significant association between PM2.5, PM10, NO2, SO2, CO and mental health, especially depression and suicide, as well as autism spectrum disorders after exposure during pregnancy, but the resulting effect sizes varied considerably. Serious methodological flaws make it difficult to draw credible conclusions. We found reasonable evidence for an association between climate events and mental health and some evidence for an association between pollution and mental disorders. More high-quality research is needed to verify these associations

Molecular docking of azole drugs and their analogs on CYP121 of Mycobacterium tuberculosis

The Mycobacterium tuberculosis genome codes for 20 different cytochromes. These cytochromes are involved in the breakdown of recalcitrant pollutants and the synthesis of polyketide antibiotics and other complex macromolecules. It has been demonstrated that CYP121 is essential for viability of the bacterium by gene knock-out and complementation studies. CYP121 could therefore be a probable target for the development of new drugs for TB. It has been widely reported that orthologs of CYP121 in fungi are inhibited by azole drugs. We evaluated whether these azole drugs or their structural analogs could bind to and inhibit CYP121 of M. tuberculosis using molecular docking. Six molecules with known anti-CYP121 activity were selected from literature and PubChem database was searched to identify structural analogs for these inhibitors. Three hundred and fifty seven molecules were identified as structural analogs and used in docking studies. Fifty three molecules were found to be scored better than the azole drugs and five of them were ranked among the top 12 molecules by two different scoring functions. These molecules may be further tested by in vitro experimentation for their activity against CYP121 of M. tuberculosis

Supramolecular architectures for neural prostheses

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (leaves 213-230).Neural prosthetic devices offer a means of restoring function that have been lost due to neural damage. The first part of this thesis investigates the design of a 15-channel, low-power, fully implantable stimulator chip. The chip is powered wirelessly and receives wireless commands. The chip features a CMOS only ASK detector, a single-differential converter based on a novel feedback loop, a low-power adaptive bandwidth DLL and 15 programmable current sources that can be controlled via four commands. Though it is feasible to build an implantable stimulator chip, the amount of power required to stimulate more than 16 channels is prohibitively large. Clearly, there is a need for a fundamentally different approach. The ultimate challenge is to design a self-sufficient neural interface. The ideal device will lend itself to seamless integration with the existing neural architecture. This necessitates that communication with the neural tissue should be performed via chemical rather than electrical messages. However, catastrophic destruction of neural tissue due to the release of large quantities of a neuroactive species, like neurotransmitters, precludes the storage of quantities large enough to suffice for the lifetime of the device. The ideal device then should actively sequester the chemical species from the body and release it upon receiving appropriate triggers in a power efficient manner. This thesis proposes the use of ionic gradients, specifically K+ ions as an alternative chemical stimulation method. The required ions can readily be sequestered from the background extracellular fluid. The parameters of using such a stimulation technique are first established by performing in-vitro experiments on rabbit retinas. The results show that modest increases (~~10mM) of K+ ions are sufficient to elicit a neural response.(cont.) The first building block of making such a stimulation technique possible is the development of a potassium selective membrane. To achieve low-power the membranes must be ultrathin to allow for efficient operation in the diffusive transport limited regime. One method of achieving this is to use lyotropic self-assembly; unfortunately, conventional lipid bilayers cannot be used since they are not robust enough. Furthermore, the membrane cannot be made potassium selective by simply incorporating ion carriers since they would eventually leach away from the membrane. A single solution that solves all the above issues was then investigated in this thesis. A novel facile synthesis of self-assembling receptor functionalized polymers was achieved. By combining the properties of hydrophobic and hydrophilic interactions of two polymers a triblock co-polymer was synthesized. The middle hydrophobic block was composed of biocompatible polysiloxanes and further derivatized to posses ion recognition capabilities via pendant crown ether chains. The hydrophilic blocks were composed of biocompatible polyoxazolines. The self-assembling properties of the membrane were then studied by electroforming them into vesicular structures. The ion responsive properties of these polymers were then examined. These polymers show emergent behavior such as, spontaneous fusion and shape transformation to ionic stimuli due to the synergy between form and function. The results from the thesis show that it is feasible to build a renewable chemically based neural prosthesis based on supramolecular architectures. However, there remains a lot of fundamental work that needs to be pursued in the future to bring the idea to complete fruition.by Luke Satish Kumar Theogarajan.Ph.D

Economics of Cormorant Predation on Catfish Farms

The Double-crested Cormorant is the primary avian predator on catfish farms causing significant economic losses primarily due to 1) on-farm expenditures related to bird-management activities and 2) value of the catfish lost to cormorants. This comprehensive economic study quantified these two economic effects by surveying catfish farms in the delta regions of Mississippi and Arkansas. On-farm expenditures for bird scaring were used to quantify bird-management costs. Economic losses from fish consumed by cormorants were quantified by evaluating data from field studies of the abundance, distribution, and diet of cormorants in the Mississippi delta. This study found that catfish farmers spent an average of $285 per acre on farms to scare birds, making bird-scaring costs one of the top five expenditures of raising catfish. Expenses for manpower (labor/manager) were the greatest cost, followed by vehicle expenses (fuel/depreciation/repairs/maintenance) used to run birds, and cost of levee upkeep to chase birds (Figure 1). Many of these costs were fixed in that effort was needed regardless of the volume of catfish produced. Increased fixed costs disproportionally harm small catfish farms because of their limited scale of production